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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Target of 1 Rapamycin kinase is a positive regulator of plant fatty acid 2 and lipid synthesis

In eukaryotes, Target of Rapamycin (TOR), a conserved protein sensor kinase, integrates a diverse set of environmental cues, including growth factor signals, energy availability, and nutritional status, to direct cell growth. In plants, TOR is activated by light and sugars and regulates a wide range of cellular processes, including protein synthesis and metabolism. Fatty acid synthesis is key to membrane biogenesis that in turn, is required for cell growth. To elucidate the primary regulatory role(s) of TOR in lipid metabolism, we followed fatty acid and lipid changes in plants with altered TOR protein levels or activity for short durations, using Nicotiana benthamiana leaves, Arabidopsis seedlings and Brassica napus cell suspension cultures. Transient expression of TOR significantly elevated the levels of total fatty acids in Nicotiana benthamiana leaves, while treatment of Arabidopsis seedlings with Torin 2, a TOR specific inhibitor, for one day, caused significant reductions in fatty acids and membrane lipids. Similarly, incubating oil-producing Brassica napus suspension culture cells with Torin 2 for eight hours led to significant decreases in the levels of TFA and TAG. Taken together the results from three independent systems presented here establishes that TOR positively regulates lipid synthesis in plants, consistent with its role in animals. Furthermore, RNA-seq analysis of Torin 2-treated Arabidopsis seedlings showed that TOR promotes the upregulation of a number of genes involved in de novo fatty acid synthesis while downregulating genes involved in lipid turnover, which we propose as a mechanistic explanation for its promotion of lipid synthesis and accumulation.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1970

Multipath signal model development

The development and use of mathematical models of signals received through the multipath environmental of a TDRS-to-user spacecraft link and vice versa are discussed. The TDRS (tracking and data relay satellite) will be in synchronous orbit. The user spacecraft will be in a low altitude orbit between 200 and 4000 km.

Ghais, A. F.↗
NASA NTRS1991

Optical fiber sensor for temperature measurement from 600 to 1900 C in gas turbine engines

A temperature sensor system has been fabricated specifically for the harsh environment encountered in temperature measurement on gas turbine engines. Four components comprised the system: a thermally emissive source, a high temperature lightguide, a flexible optical cable and an electro-optic signal processor. The emissive source was located inside a sapphire rod so that the sapphire serves as both a lightguide and as a protective shroud. As the probe was heated, the thermal radiation from the emissive source increased with increasing temperature. The flexible optical cable was constructed with 200 micron core fiber and ruggedized for turbine engine applications. The electro-optic signal processor used the ratio of intensity in two wavelength intervals to determine a digital value of the temperature. The probe tip was operated above 1900 C in a low velocity propane flame and above 1500 C at Mach .37. Probe housings, optical cables, and signal processors were constructed and environmentally tested for the temperature and vibration experienced by turbine engine sensors. This technology was used to build an optical exhaust gas sensor for a General Electric Aircraft Engines F404 turbine. The four optical probes and optical cable were a functional replacement for four thermocouple probes. The system was ground tested for 50 hours with an excess of 1000 thermal cycles. This optical temperature sensor system measured gas temperature up to the operational limit of the turbine engine.

Tregay, G. W.↗
NASA NTRS1995

AIAA spacecraft GN&C interface standards initiative: Overview

The American Institute of Aeronautics and Astronautics (AIAA) has undertaken an important standards initiative in the area of spacecraft guidance, navigation, and control (GN&C) subsystem interfaces. The objective of this effort is to establish standards that will promote interchangeability of major GN&C components, thus enabling substantially lower spacecraft development costs. Although initiated by developers of conventional spacecraft GN&C, it is anticipated that interface standards will also be of value in reducing the development costs of micro-engineered spacecraft. The standardization targets are specifically limited to interfaces only, including information (i.e. data and signal), power, mechanical, thermal, and environmental interfaces between various GN&C components and between GN&C subsystems and other subsystems. The current emphasis is on information interfaces between various hardware elements (e.g., between star trackers and flight computers). The poster presentation will briefly describe the program, including the mechanics and schedule, and will publicize the technical products as they exist at the time of the conference. In particular, the rationale for the adoption of the AS1773 fiber-optic serial data bus and the status of data interface standards at the application layer will be presented.

Challoner, A. Dorian↗
DOE OSTI2020

Development of a Convolutional Neural Network Classifier for Data Starved Spectra - 20199

The Institute for Clean Energy Technology (ICET) at Mississippi State University is exploring the utility of machine learning in augmenting its mobile radiation surveying platforms, which are currently being developed as means to survey depleted uranium contaminated areas in support of remediation and decommissioning efforts. Mobile survey platforms provide a means to efficiently scan large areas of interest while reducing human exposure to radiation and other hazards. The survey platforms can also be used for scanning for any gamma emitting isotope in addition to depleted uranium. The spectral data that the platforms collect may be data starved with relatively low counts and poorly defined spectral features depending on the speed of the platforms and scintillation detector selection. Such data-starved spectra are difficult to use for isotope identification, requiring advanced knowledge of the possible radionuclides that could be present and environmental factors that could attenuate signals or introduce background noise. These factors in combination with the volume of survey data increases the time it takes to perform analysis of survey data when the source type is unknown. There are a number of algorithms in the field of machine learning that can be used to classify data that would be challenging and time-consuming for a human to identify. Supervised machine learning algorithms train models based on extensive amounts of human-labeled training data. Once sufficiently trained, these models can be used to quickly make high-fidelity predictions on new data. Convolutional neural networks are machine learning algorithms that excel in learning representations of 'shapes'. They do this by taking numerical input data and convolving them with spatial feature detectors referred to as filters. These filters are incrementally adjusted to reduce the prediction error on the data during the backpropagation step of training. Discussed in this paper is the development of a convolutional neural network classifier (CNNC) that can utilize spectral survey data for source discrimination and isotope identification. Bench-top laboratory experiments data using LaBr{sub 3}(Ce) scintillation detectors were used to train and evaluate the performance of the developed CNNC. The CNNC is capable of discriminating a variety of gamma emitting source types, differentiating different forms of uranium (depleted vs. natural), and estimating the amount of uranium for a known geometry. The discussed CNNC may be useful in scenarios where survey systems are deployed in situations where hazardous radioactive material maybe present, but the type is unknown. When used in remediation applications the CNNC can be used to screen-out false positives, helping reduce remediation costs. (authors)

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2025

Electrical signaling in fungi: past and present challenges

Abstract Electrical signaling is a fundamental mechanism for integrating environmental stimuli and coordinating responses in living organisms. While extensively studied in animals and plants, the role of electrical signaling in fungi remains a largely underexplored field. Early studies suggested that filamentous fungi generate action potential-like signals and electrical currents at hyphal tips, yet their function in intracellular communication remained unclear. Renewed interest in fungal electrical activity has fueled developments such as the hypothesis that mycorrhizal networks facilitate electrical communication between plants and the emerging field of fungal-based electronic materials. Given their continuous plasma membrane, specialized septal pores, and insulating cell wall structures, filamentous fungi possess architectural features that could support electrical signaling over long distances. However, studying electrical phenomena in fungal networks presents unique challenges due to the microscopic dimensions of hyphae, the structural complexity of highly modular mycelial networks, and the limitations of traditional electrophysiological methods. This review synthesizes current evidence for electrical signaling in filamentous fungi, evaluates methodological approaches, and highlights experimental challenges. By addressing these challenges and identifying best practices, we aim to advance research in this field and provide a foundation for future studies exploring the role of electrical signaling in fungal biology.

Buffi, Matteo↗
NASA NTRS2003

Stabilized Fiber-Optic Distribution of Reference Frequency

An optoelectronic system distributes a reference signal of low noise and highly stabilized phase and frequency (100 MHz) from an atomic frequency standard to a remote facility at a distance up to tens of kilometers. The reference signal is transmitted to the remote station as amplitude modulation of an optical carrier signal propagating in an optical fiber. The stabilization scheme implemented in this system is intended particularly to suppress phase and frequency fluctuations caused by vibrations and by expansion and contraction of the optical fiber and other components in diurnal and seasonal heating and cooling cycles. The system (see figure) comprises several subsystems, the main one being (1) a hydrogen-maser or linear-ion-trap frequency standard in an environmentally controlled room in a signal-processing center (SPC), (2) a stabilized fiber-optic distribution assembly (SFODA), (3) a compensated sapphire oscillator (CSO) in an environmentally controlled room in the remote facility, (4) thermally stabilized distribution amplifiers and cabling from the environmentally controlled room to end users, and (5) performance- measuring equipment.

Calhoun, Malcolm↗
DOE OSTI2021

Preserved and variable spatial‐chemical changes of lipids across tomato leaves in response to central vein wounding reveals potential origin of linolenic acid in signal transduction cascade

Abstract Membrane lipids serve as substrates for the generation of numerous signaling lipids when plants are exposed to environmental stresses, and jasmonic acid, an oxidized product of 18‐carbon unsaturated fatty acids (e.g., linolenic acid), has been recognized as the essential signal in wound‐induced gene expression. Yet, the contribution of individual membrane lipids in linolenic acid generation is ill‐defined. In this work, we performed spatial lipidomic experiments to track lipid changes that occur locally at the sight of leaf injury to better understand the potential origin of linolenic and linoleic acids from individual membrane lipids. The central veins of tomato leaflets were crushed using surgical forceps, leaves were cryosectioned and analyzed by two orthogonal matrix‐assisted laser desorption/ionization mass spectrometry imaging platforms for insight into lipid spatial distribution. Significant changes in lipid composition are only observed 30 min after wounding, while after 60 min lipidome homeostasis has been re‐established. Phosphatidylcholines exhibit a variable pattern of spatial behavior in individual plants. Among lysolipids, lysophosphatidylcholines strongly co‐localize with the injured zone of wounded leaflets, while, for example, lysophosphatidylglycerol (LPG) (16:1) accumulated preferentially toward the apex in the injured zone of wounded leaflets. In contrast, two other LPGs (LPG [18:3] and LPG [18:2]) are depleted in the injured zone. Our high‐resolution co‐localization imaging analyses suggest that linolenic acids are predominantly released from PCs with 16_18 fatty acid composition along the entire leaf, while it seems that in the apex zone PG (16:1_18:3) significantly contributes to the linolenic acid pool. These results also indicate distinct localization and/or substrate preferences of phospholipase isoforms in leaf tissue.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2005

Lightning Detection Efficiency Analysis Process: Modeling Based on Empirical Data

A ground based lightning detection system employs a grid of sensors, which record and evaluate the electromagnetic signal produced by a lightning strike. Several detectors gather information on that signal s strength, time of arrival, and behavior over time. By coordinating the information from several detectors, an event solution can be generated. That solution includes the signal s point of origin, strength and polarity. Determination of the location of the lightning strike uses algorithms based on long used techniques of triangulation. Determination of the event s original signal strength relies on the behavior of the generated magnetic field over distance and time. In general the signal from the event undergoes geometric dispersion and environmental attenuation as it progresses. Our knowledge of that radial behavior together with the strength of the signal received by detecting sites permits an extrapolation and evaluation of the original strength of the lightning strike. It also limits the detection efficiency (DE) of the network. For expansive grids and with a sparse density of detectors, the DE varies widely over the area served. This limits the utility of the network in gathering information on regional lightning strike density and applying it to meteorological studies. A network of this type is a grid of four detectors in the Rondonian region of Brazil. The service area extends over a million square kilometers. Much of that area is covered by rain forests. Thus knowledge of lightning strike characteristics over the expanse is of particular value. I have been developing a process that determines the DE over the region [3]. In turn, this provides a way to produce lightning strike density maps, corrected for DE, over the entire region of interest. This report offers a survey of that development to date and a record of present activity.

Rompala, John T.↗
NASA NTRS2018

Uncertainty in Heart Rate Complexity Metrics Caused by R-Peak Perturbations

Heart rate complexity (HRC) is a proven metric for gaining insight into human stress and physiological deterioration. To calculate HRC, the detection of the exact instance of when the heart beats, the R-peak, is necessary. Electrocardiogram (ECG) signals can often be corrupted by environmental noise (e.g., from electromagnetic interference, movement artifacts), which can potentially alter the HRC measurement, producing erroneous inputs which feed into decision support models. Current literature has only investigated how HRC is affected by noise when R-peak detection errors occur (false positives and false negatives). However, the numerical methods used to calculate HRC are also sensitive to the specific location of the fiducial point of the R-peak. This raises many questions regarding how this fiducial point is altered by noise, the resulting impact on the measured HRC, and how we can account for noisy HRC measures as inputs into our decision models. This work uses Monte Carlo simulations to systematically add white and pink noise at different permutations of signal-to-noise ratios (SNRs), time segments, sampling rates, and HRC measurements to characterize the influence of noise on the HRC measure by altering the fiducial point of the R-peak. Using the generated information from these simulations provides improved decision processes for system design which address key concerns such as permutation entropy being a more precise, reliable, less biased, and more sensitive measurement for HRC than sample and approximate entropy.

Napoli, Nicholas J.↗
DOE OSTI2025

Improved guided-wave acoustic defect detection and localization in pipes under varying temperature conditions using deep learning

Early defect detection in pipelines is critical across industries, particularly in the oil and gas sector, where failures result in significant maintenance costs and operational disruptions. Acoustic guided-wave techniques are widely used for nondestructive evaluation of pipeline defects due to their long-distance propagation capability. However, environmental variations, sensitivity limitations, and complex signal interpretation challenges limit the effectiveness of traditional signal processing approaches with guided-wave signals. Recent advances in deep learning methods have demonstrated remarkable success in solving complex real-world problems in many fields. In particular, deep-learning-based signal processing holds substantial promise to overcome limitations and challenges of conventional signal processing. This study presents a deep learning framework for pipeline inspection using acoustic guided-wave signals under temperature varying environments. The proposed framework employs a dual-path one-dimensional convolutional autoencoder that combines defect detection, localization, and temperature prediction functions. The proposed system utilizes multi-mode and broadband acoustic waves with an optimized number of sensors that provide high accuracy while retaining practical simplicity. Experimental validation is performed on a carbon steel pipe. The results indicate exceptional defect detection accuracy and precise defect localization with a mean absolute error of 66 mm. The proposed technique also predicts the effective average temperature of the pipe with a mean absolute error of 0.2°C. Comparative analysis shows superior performance of the proposed method over a traditional method previously developed by the authors' team. These results highlight the potential of integrating deep learning methods into guided-wave pipeline inspection systems to improve reliability under varying environmental conditions.

42 ENGINEERING↗
NASA NTRS1990

Environmental sensitivities of quartz crystal oscillators

The frequency, amplitude, and noise of the output signal of a quartz crystal controlled oscillator is affected by a large number of environmental effects. The physical basis for the sensitivity of precision oscillators to temperature, humidity, pressure, vibration, magnetic field, electric field, load, and radiation is discussed. The sensitivity of crystal oscillators to radiation is a very complex topic and poorly understood. Therefore only a few general results are mentioned. The sensitivity to most external influences often varies significantly from one oscillator type to another and from one unit of given type to another. For a given unit, the sensitivity to one parameter often depends on the value of other parameters and history.

Walls, Fred L.↗
NASA NTRS1994

Fiber optic (flight quality) sensors for advanced aircraft propulsion

Development of flight prototype, fiber-optic sensing system components for measuring nine sensed parameters (three temperatures, two speeds, three positions, and one flame) on an F404-400 aircraft engine is described. Details of each sensor's design, functionality, and environmental testing, and the electro-optics architecture for sensor signal conditioning are presented. Eight different optical sensing techniques were utilized. Design, assembly, and environmental testing of an engine-mounted, electro-optics chassis unit (EOU), providing MIL-C-1553 data output, are related. Interconnection cables and connectors between the EOU and the sensors are identified. Results of sensor/cable/circuitry integrated testing, and installation and ground testing of the sensor system on an engine in October 1993 and April 1994 are given, including comparisons with the engine control system's electrical sensors. Lessons learned about the design, fabrication, testing, and integration of the sensor system components are included.

Poppel, Gary L.↗
DOE OSTI2025

Radiation portal monitor data file format for comprehensive background radiation monitoring

Radiation portal monitors (RPMs) are widely used at border security checkpoints to detect the presence of radioactive materials in people, vehicles, and cargo. Typically, RPM detection systems consist of two pillars equipped with gamma and neutron detectors. To improve detection efficiency, RPMs employ techniques such as a limited energy window, dynamic alarm thresholds, and lead shielding. However, without continuous monitoring of background radiation, signal interpretation can be compromised, because environmental factors and mechanical failures can cause fluctuations. Here, we introduce a daily file format that logs gamma background and neutron background radiation levels continuously over a 24 h period; this format is different from traditional formats that record data only when the RPM is active or occupied. The approach enables RPM operators and analysts to (1) identify and diagnose malfunctioning components, (2) adjust system settings to account for dynamic environmental factors, and (3) use the recorded data to characterize outer space phenomena. Continuous background reporting is essential for identifying issues such as faulty connections, voltage divider failures, and errors in background updates. Continuous background reporting also enables the detection of external influences, including nearby X-ray scanners, temperature fluctuations, rainfall, cosmic radiation, and lunar phase changes. These data files are designed to be easily evaluated and parsed using common tools, and a quick review by an expert is often sufficient for problem diagnosis. We anticipate that continuous background radiation monitoring and these new strategies will significantly improve the accuracy and reliability of RPM systems, reducing the rate of false alarms and enhancing overall system performance.

Background radiation monitoring↗
DOE OSTI2022

Sugar loading is not required for phloem sap flow in maize plants

We report phloem transport of photoassimilates from leaves to non-photosynthetic organs, such as the root and shoot apices and reproductive organs, is crucial to plant growth and yield. For nearly 90 years, evidence has been generally consistent with the theory of a pressure-flow mechanism of phloem transport. Central to this hypothesis is the loading of osmolytes, principally sugars, into the phloem to generate the osmotic pressure that propels bulk flow. Here we used genetic and light manipulations to test whether sugar import into the phloem is required as the driving force for phloem sap flow. Using carbon-11 radiotracer, we show that a maize sucrose transporter1 (sut1) loss-of-function mutant has severely reduced export of carbon from photosynthetic leaves (only ~4% of the wild type level). Yet, the mutant remarkably maintains phloem pressure at ~100% and sap flow speeds at ~50–75% of those of wild type. Potassium (K+) abundance in the phloem was elevated in sut1 mutant leaves. Fluid dynamic modelling supports the conclusion that increased K+ loading compensated for decreased sucrose loading to maintain phloem pressure, and thereby maintained phloem transport via the pressure-flow mechanism. Furthermore, these results suggest that sap flow and transport of other phloem-mobile nutrients and signalling molecules could be regulated independently of sugar loading into the phloem, potentially influencing carbon–nutrient homoeostasis and the distribution of signalling molecules in plants encountering different environmental conditions.

36 MATERIALS SCIENCE↗
NASA NTRS1977

Environmental synchronizers of squirrel monkey circadian rhythms

Various temporal signals in the environment were tested to determine if they could synchronize the circadian timing system of the squirrel monkey (Saimiri sciureus). The influence of cycles of light and dark, eating and fasting, water availability and deprivation, warm and cool temperature, sound and quiet, and social interaction and isolation on the drinking and activity rhythms of unrestrained monkeys was examined. In the absence of other time cues, 24-hr cycles of each of these potential synchronizers were applied for up to 3 wk, and the periods of the monkey's circadian rhythms were examined. Only light-dark cycles and cycles of food availability were shown to be entraining agents, since they were effective in determining the period and phase of the rhythmic variables. In the presence of each of the other environmental cycles, the monkey's circadian rhythms exhibited free-running periods which were significantly different from 24 hr with all possible phase relationships between the rhythms and the environmental cycles being examined.

Sulzman, F. M.↗
NASA NTRS1997

Plant responses to environmental stress: regulation and functions of the Arabidopsis TCH genes

Expression of the Arabidopsis TCH genes is markedly upregulated in response to a variety of environmental stimuli including the seemingly innocuous stimulus of touch. Understanding the mechanism(s) and factors that control TCH gene regulation will shed light on the signaling pathways that enable plants to respond to environmental conditions. The TCH proteins include calmodulin, calmodulin-related proteins and a xyloglucan endotransglycosylase. Expression analyses and localization of protein accumulation indicates that the potential sites of TCH protein function include expanding cells and tissues under mechanical strain. We hypothesize that at least a subset of the TCH proteins may collaborate in cell wall biogenesis.

Review, Tutorial↗
DOE OSTI2025

An elastin-like polymer targeting vascular endothelial growth factor receptor-1 reduces survival in serum-starved endothelial cells

Peptides often exhibit biological activity that depends on the context in which they are displayed and delivered. Understanding and controlling these contextual effects on peptide function is critical for designing targeted and responsive peptide-based biomaterials and therapeutics. Genetically engineered protein polymers such as elastin-like polypeptides (ELPs) can incorporate bioactive peptide motifs and are attractive candidates for biomaterials used in tissue engineering and targeted drug delivery. They also present an opportunity for investigating and modulating cell signaling pathways by presenting a peptide ligand in various defined chemical and physical environments. Vascular endothelial growth factor receptor-1 (VEGFR1) signaling plays important and complex roles in cell survival and angiogenesis, but polymeric materials that interact with this signaling axis are scarce. In this study, a novel genetically engineered elastin-like polymer that targets VEGFR1 is characterized. This polymer, termed R1B-ELP, binds to human endothelial cells in a manner dependent on its VEGFR1-targeting motif and, based on cell proliferation and cytotoxicity assays, demonstrates activity consistent with disrupting pro-survival signaling necessary for endothelial cell function under conditions of environmental stress. Notably, these findings indicate that ELP fusion alters the functional behavior of the targeting peptide. Modulators of VEGFR1 signaling have potential applications in basic studies of angiogenesis as well as in therapeutic applications targeting vascular or inflammatory diseases.

36 MATERIALS SCIENCE↗