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NASA NTRSDate not supplied

How Eye Drift Adapts to the History of Eye Positions

Oculomotor behavior is a powerful tool to probe brain function and disease. Previous studies have shown how fixational drift velocities depend on eccentricity (Bertolini et al., 2013; Romano et al., 2017) and how fixational drift can adapt after prolonged eccentric fixation (Otero-Millan et al., 2019). Here, eighteen subjects completed two experiments where we measured drift velocity while fixating a briefly flashed target, to remove retinal slip cues. In the first experiment, we measured their baseline relationship between fixational drift velocity and eye position. In the second experiment, we investigated the adaptation of that relationship after prolonged fixation at a very eccentric position. This adaptation usually manifests by the presence of rebound nystagmus (RN) upon returning to central gaze. Our results replicate the finding that drift increases at central fixation in the direction consistent with rebound nystagmus, that is, towards the previously held eccentric position, highlighting that drift velocity depends on the history of eye positions. When examining the entire relationship between drift velocity and eye position we find a mostly linear relationship but with increased slope relative to the baseline condition. However, the adaptation of the integrator cannot be modeled by a simple change in leakiness, as that would not result in increased drift at central gaze. Other mechanisms of adaptation such as shifts in the position or velocity set-points for gaze holding could be present but are indistinguishable with the current data.

eye movement↗
DOE OSTI2026

The solubility of ErPO 4 and Er speciation in hydrothermal fluids at varying pH and salinity between 350 and 450 °C

The rare earth elements (REE) are important for the green-energy transition and can be incorporated into the REE phosphates, such as xenotime-(Y), which also hosts heavy REE (Tb– Lu). Xenotime-(Y) is a common accessory mineral in metamorphic rocks and a range of mineral deposits where it controls the mobility of heavy REE, however, the impact of high temperature aqueous fluids on the behavior of heavy REE is largely unknown. Thermodynamic modeling can be utilized as a tool to predict the mobility of REE in hydrothermal aqueous fluids, but must be supported by accurate experimental data. Here, we measured the solubility of endmember synthetic xenotime-structured ErPO4 in NaCl-HCl-NaOH-bearing aqueous solutions at 350 °C and water vapor saturation pressure, at 400 and at 450 °C and 500 bar using batch-type Inconel reactors. Erbium speciation was investigated as a function of pH from 2.8 to 8, where Er chloride species are predominant at acidic conditions (pH <3) and Er hydroxyl complexes are predominant at near- neutral to alkaline conditions (pH >3). At pH 7–9, the measured ErPO 4 solubility (-9.8 to -7.5 log m Er ) is up to 2.5 orders of magnitude lower than thermodynamic predictions (-9.4 to -6.7 log m Er ) using existing thermodynamic databases. At pH 2–3, the predicted ErPO 4 solubility is ~0.5 orders of magnitude higher at 350 °C and ~1 order of magnitude lower at 450 °C compared to experimentally measured Er concentrations. The thermodynamic properties of aqueous Er species were therefore revised in this study. The partial molal Gibbs energy of formation (Δ f G 0 T,P ) for aqueous Er hydroxyl and chloride species are optimized using GEMSFITS and the logarithmic formation constants (logβ n ( Cl,OH) ) were derived at each experimental temperature and pressure. The updated thermodynamic properties for Er hydroxyl species (Er(OH) +2 , Er(OH) 2 + , and Er(OH) 3 0 ) show that their stability shifts to more acidic conditions at and below 400 °C. The Er chloride species (ErCl +2 and ErCl 2 + ) show increased stability compared to Er hydroxyl species at temperatures of 450 °C and 0.01 mol/kg NaCl. The updated thermodynamic properties are implemented into the GEM-Selektor modeling package to investigate the mobility of Er in saline hydrothermal fluids in equilibrium with alkaline rocks. Importantly, the updated properties for Er hydroxyl species result in low Er solubility at rock equilibrated pH conditions due to an expanded hydroxyl predominance zone, but lower aqueous complex stability overall, whereas previous models suggest greater stability for aqueous Er species. Furthermore, ErPO 4 solubility increases with decreasing temperature due to the deprotonation of HCl, which increases the acidity of hydrothermal fluids and the availability of Cl - to complex with the REE. These simulations highlight how fluid-rock reaction and temperature affect the mobility of REE in hydrothermal ore-forming systems.

58 GEOSCIENCES↗
DOE OSTI2022

Hot and dense matter equation of state probability distributions for astrophysical simulations

We add an ensemble of nuclei to the equation of state for homogeneous nucleonic matter to generate a new set of models suitable for astrophysical simulations of core-collapse supernovae and neutron star mergers. We implement empirical constraints from (i) nuclear mass measurements, (ii) proton-proton scattering phase shifts, and (iii) neutron star observations. Our model is also guided by microscopic many-body theory calculations based on realistic nuclear forces, including the zero-temperature neutron matter equation of state from quantum Monte Carlo simulations and thermal contributions to the free energy from finite-temperature many-body perturbation theory. We ensure that the parameters of our model can be varied while preserving thermodynamic consistency and the connection to experimental or observational data, thus providing a probability distribution of the astrophysical hot and dense matter equation of state. Furthermore, we compare our results with those obtained from other available equations of state. While our probability distributions indeed represent a large number of possible equations of state, we cannot yet claim to have fully explored all of the uncertainties, especially with regard to the structure of nuclei in the hot and dense medium.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2000

Role of hypoxia-inducible factor-1 in transcriptional activation of ceruloplasmin by iron deficiency

A role of the copper protein ceruloplasmin (Cp) in iron metabolism is suggested by its ferroxidase activity and by the tissue iron overload in hereditary Cp deficiency patients. In addition, plasma Cp increases markedly in several conditions of anemia, e.g. iron deficiency, hemorrhage, renal failure, sickle cell disease, pregnancy, and inflammation. However, little is known about the cellular and molecular mechanism(s) involved. We have reported that iron chelators increase Cp mRNA expression and protein synthesis in human hepatocarcinoma HepG2 cells. Furthermore, we have shown that the increase in Cp mRNA is due to increased rate of transcription. We here report the results of new studies designed to elucidate the molecular mechanism underlying transcriptional activation of Cp by iron deficiency. The 5'-flanking region of the Cp gene was cloned from a human genomic library. A 4774-base pair segment of the Cp promoter/enhancer driving a luciferase reporter was transfected into HepG2 or Hep3B cells. Iron deficiency or hypoxia increased luciferase activity by 5-10-fold compared with untreated cells. Examination of the sequence showed three pairs of consensus hypoxia-responsive elements (HREs). Deletion and mutation analysis showed that a single HRE was necessary and sufficient for gene activation. The involvement of hypoxia-inducible factor-1 (HIF-1) was shown by gel-shift and supershift experiments that showed HIF-1alpha and HIF-1beta binding to a radiolabeled oligonucleotide containing the Cp promoter HRE. Furthermore, iron deficiency (and hypoxia) did not activate Cp gene expression in Hepa c4 hepatoma cells deficient in HIF-1beta, as shown functionally by the inactivity of a transfected Cp promoter-luciferase construct and by the failure of HIF-1 to bind the Cp HRE in nuclear extracts from these cells. These results are consistent with in vivo findings that iron deficiency increases plasma Cp and provides a molecular mechanism that may help to understand these observations.

NASA Discipline Cardiopulmonary↗
DOE OSTI2022

Synechocystis sp. PCC 6803 Requires the Bidirectional Hydrogenase to Metabolize Glucose and Arginine Under Oxic Conditions

The cyanobacterium Synechocystis sp.PCC 6803 possesses a bidirectional NiFe-hydrogenase, HoxEFUYH. It functions to produce hydrogen under dark, fermentative conditions and photoproduces hydrogen when dark-adapted cells are illuminated. Unexpectedly, we found that the deletion of the large subunit of the hydrogenase (HoxH) in Synechocystis leads to an inability to grow on arginine and glucose under continuous light in the presence of oxygen. This is surprising, as the hydrogenase is an oxygen-sensitive enzyme. In wild-type (WT) cells, thylakoid membranes largely disappeared, cyanophycin accumulated, and the plastoquinone (PQ) pool was highly reduced, whereas ΔhoxH cells entered a dormant-like state and neither consumed glucose nor arginine at comparable rates to the WT. Hydrogen production was not traceable in the WT under these conditions. We tested and could show that the hydrogenase does not work as an oxidase on arginine and glucose but has an impact on the redox states of photosynthetic complexes in the presence of oxygen. It acts as an electron valve as an immediate response to the supply of arginine and glucose but supports the input of electrons from arginine and glucose oxidation into the photosynthetic electron chain in the long run, possibly via the NDH-1 complex. Despite the data presented in this study, the latter scenario requires further proof. The exact role of the hydrogenase in the presence of arginine and glucose remains unresolved. In addition, a unique feature of the hydrogenase is its ability to shift electrons between NAD(H), NADP(H), ferredoxin, and flavodoxin, which was recently shown in vitro and might be required for fine-tuning. Taken together, our data show that Synechocystis> depends on the hydrogenase to metabolize organic carbon and nitrogen in the presence of oxygen, which might be an explanation for its prevalence in aerobic cyanobacteria.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1996

Single residue substitutions that change the gating properties of a mechanosensitive channel in Escherichia coli

MscL is a channel that opens a large pore in the Escherichia coli cytoplasmic membrane in response to mechanical stress. Previously, we highly enriched the MscL protein by using patch clamp as a functional assay and cloned the corresponding gene. The predicted protein contains a largely hydrophobic core spanning two-thirds of the molecule and a more hydrophilic carboxyl terminal tail. Because MscL had no homology to characterized proteins, it was impossible to predict functional regions of the protein by simple inspection. Here, by mutagenesis, we have searched for functionally important regions of this molecule. We show that a short deletion from the amino terminus (3 amino acids), and a larger deletion of 27 amino acids from the carboxyl terminus of this protein, had little if any effect in channel properties. We have thus narrowed the search of the core mechanosensitive mechanism to 106 residues of this 136-amino acid protein. In contrast, single residue substitutions of a lysine in the putative first transmembrane domain or a glutamine in the periplasmic loop caused pronounced shifts in the mechano-sensitivity curves and/or large changes in the kinetics of channel gating, suggesting that the conformational structure in these regions is critical for normal mechanosensitive channel gating.

Non-NASA Center↗
NASA NTRS2016

Preparations for Integrating Space-Based Total Lightning Observations into Forecast Operations

NASA's Short-term Prediction Research and Transition (SPoRT) Center has been a leader in collaborating with the United States National Weather Service (NWS) offices to integrate ground-based total lightning (intra-cloud and cloud-to-ground) observations into the real-time operational environment. For much of these collaborations, the emphasis has been on training, dissemination of data to the NWS AWIPS system, and focusing on the utility of these data in the warning decision support process. A shift away from this paradigm has occurred more recently for several reasons. For one, SPoRT's collaborations have expanded to new partners, including emergency managers and the aviation community. Additionally, and most importantly, is the impending launch of the GOES-R Geostationary Lightning Mapper (GLM). This has led to collaborative efforts to focus on additional forecast needs, new data displays, develop training for GLM uses based on the lessons learned from ground-based lightning mapping arrays, and ways to better relate total lightning data to other meteorological parameters. This presentation will focus on these efforts to prepare the operational end user community for GLM with an eye towards sharing lessons learned as EUMETSAT prepares for the Meteosat Third Generation Lightning Imager. This will focus on both software and training needs. In particular, SPoRT has worked closely with the Meteorological Development Laboratory to create the total lightning tracking tool. This software allows for NWS forecasters to manually track storms of interest and display a time series trend of observations. This tool also has been expanded to work on any gridded data set allowing for easy visual comparisons of multiple parameters in addition to total lightning. A new web display has been developed for the ground-based observations that can be easily extended to satellite observations. This paves the way for new collaborations outside of the NWS, both domestically and internationally, as the web display will be functional on PCs and mobile devices. Furthermore, SPoRT has helped developed the software plug-in to visualize GLM data. Examples using the official GLM proxy product will be used to provide a glimpse as to what real-time GLM and likely MTG-LI data will be in the near future.

GLM↗
DOE OSTI2022

Molecular basis of force-pCa relation in MYL2 cardiomyopathy mice: Role of the super-relaxed state of myosin

Here, in this study, we investigated the role of the super-relaxed (SRX) state of myosin in the structure–function relationship of sarcomeres in the hearts of mouse models of cardiomyopathy-bearing mutations in the human ventricular regulatory light chain (RLC, MYL2 gene). Skinned papillary muscles from hypertrophic (HCM–D166V) and dilated (DCM–D94A) cardiomyopathy models were subjected to small-angle X-ray diffraction simultaneously with isometric force measurements to obtain the interfilament lattice spacing and equatorial intensity ratios (I 11 /I 10 ) together with the force-pCa relationship over a full range of [Ca 2+ ] and at a sarcomere length of 2.1 μm. In parallel, we studied the effect of mutations on the ATP-dependent myosin energetic states. Compared with wild-type (WT) and DCM–D94A mice, HCM–D166V significantly increased the Ca 2+ sensitivity of force and left shifted the I 11 /I 10 -pCa relationship, indicating an apparent movement of HCM–D166V cross-bridges closer to actin-containing thin filaments, thereby allowing for their premature Ca 2+ activation. The HCM–D166V model also disrupted the SRX state and promoted an SRX-to-DRX (super-relaxed to disordered relaxed) transition that correlated with an HCM-linked phenotype of hypercontractility. While this dysregulation of SRX ↔ DRX equilibrium was consistent with repositioning of myosin motors closer to the thin filaments and with increased force-pCa dependence for HCM–D166V, the DCM–D94A model favored the energy-conserving SRX state, but the structure/function–pCa data were similar to WT. Our results suggest that the mutation-induced redistribution of myosin energetic states is one of the key mechanisms contributing to the development of complex clinical phenotypes associated with human HCM–D166V and DCM–D94A mutations.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2016

Enabling the Direct Detection of Earth-Sized Exoplanets with the LBTI HOSTS Project: A Progress Report

NASA has funded a project called the Hunt for Observable Signatures of Terrestrial Systems (HOSTS) to survey nearby solar type stars to determine the amount of warm zodiacal dust in their habitable zones. The goal is not only to determine the luminosity distribution function but also to know which individual stars have the least amount of zodiacal dust. It is important to have this information for future missions that directly image exoplanets as this dust is the main source of astrophysical noise for them. The HOSTS project utilizes the Large Binocular Telescope Interferometer (LBTI), which consists of two 8.4-m apertures separated by a 14.4-m baseline on Mt. Graham, Arizona. The LBTI operates in a nulling mode in the mid-infrared spectral window (8-13 micrometers), in which light from the two telescopes is coherently combined with a 180 degree phase shift between them, producing a dark fringe at the location of the target star. In doing so the starlight is greatly reduced, increasing the contrast, analogous to a coronagraph operating at shorter wavelengths. The LBTI is a unique instrument, having only three warm reflections before the starlight reaches cold mirrors, giving it the best photometric sensitivity of any interferometer operating in the mid-infrared. It also has a superb Adaptive Optics (AO) system giving it Strehl ratios greater than 98% at 10 micrometers. In 2014 into early 2015 LBTI was undergoing commissioning. The HOSTS. project team passed its Operational Readiness Review (ORR) in April 2015. The team recently published papers on the target sample, modeling of the nulled disk images, and initial results such as the detection of warm dust around eta Corvi. Recently a paper was published on the data pipeline and on-sky performance. An additional paper is in preparation on Beta Leo. We will discuss the scientific and programmatic context for the LBTI project, and we will report recent progress, new results, and plans for the science verification phase that started in February 2016, and for the survey.

Hunt for Observable Signatures of Terrestrial Syst↗
DOE OSTI2023

Grid-Integrated Production of Fischer-Tropsch Synfuels from Nuclear Power

Idaho National Laboratory (INL) investigates the relative economic profitability of an integrated energy system (IES) coupling an NPP with a synfuel production process at selected case study locations across the United States. In the synfuel IES, a high-temperature steam electrolysis (HTSE) plant is thermally and electrically coupled with an NPP to produce zero-carbon hydrogen. The synthetic fuel is produced from this H 2 combined with a CO 2 supply using the reverse water gas shift process followed by the Fischer-Tropsch (FT) reaction. This analysis considers a system in which the CO 2 is sourced from regional CO 2 emitters via the construction and operation of pipeline-based CO 2 supply networks. Locating the FT plant at the same site as the NPP and HTSE plants enables the NPP to provide zero-carbon heat and power to the HTSE plant and zero-carbon power to the FT plant as well as avoid the requirement for long-distance H 2 product transport from the HTSE plant to the FT plant. Hydrogen storage is used to enable the NPP to dispatch power to the electrical grid (instead of the HTSE plant) when grid demand increases, thus enabling the FT plant to continue to operate in a steady-state production mode. The ability to cease hydrogen production for several hours within each day enables the NPP to provide power to the grid to balance the electricity market during peak periods and maximize revenues for the nuclear synfuel IES. The FT process design considered has a 99% carbon conversion efficiency. The use of nuclear energy and nuclear energy-derived hydrogen enables synfuel production to achieve this high level of carbon utilization. Additionally, the life-cycle carbon emissions of the nuclear-based synfuel production process are very low, with WTW emissions of approximately 25 gCO 2 e/MJ, including steam credits (generated from FT process excess heat), and approximately 7 gCO 2 e/MJ, if steam credits are excluded. This compares favorably with the WTW emissions of 90.5 gCO 2 e/MJ for a compression-ignition, direct injection (CIDI) vehicle with a fuel economy of 31.6 miles per gallon gasoline equivalent (MPGGE), using low-sulfur diesel produced using conventional petroleum production and refining processes. Several NPPs in various regions of the U.S. are considered as case study analyses. Supply locations and transportation via pipeline of the CO 2 feedstock to the NPP site are analyzed through the National Energy Technology Laboratory (NETL) CO 2 Transport Cost model. The team finds that the amount of CO 2 generated by different sectors is sufficient for the synfuel production process at all locations considered. The CO 2 transportation costs are functions of the distance of the source to the NPP location, the CO 2 capture cost at the source, and the quantity of CO 2 transported. Historical electricity prices for the NPP case study locations are collected and analyzed. Monthly average prices, price range, and duration of negative-price periods vary among these locations. For each location, an auto-regressive moving average (ARMA) model is trained on historical electricity price data. ARMA validation is done to ensure the synthetic price distributions represent one of historical prices with high fidelity. Synthetic time series from these ARMA models are used in a coupled dispatch and system optimization in the Holistic Energy Resource Optimization Network (HERON) to compute the differential net present value (NPV) of the IES. The team finds that this econometric is positive, ranging from $14M–1.3bn (2020) depending on the location. The optimal synfuel IES configuration to obtain this increase in NPV often maximizes the size of the synfuel production process with regards to the size of the NPP. However, the team shows that the NPP still plays a stabilizing role for the grid: In periods of high prices and high loads, more electricity from the NPP is sent to the grid. A high variability of electricity prices and extreme maximum prices tend to drive up electricity production. While it requires significant investment, the synfuel IES could increase the economic profitability for the existing fleet of LWRs across the country while still maintaining the grid stabilizer role of NPPs. During its lifetime, the main costs for the nuclear synfuel IES are the carbon feedstock transportation costs, followed by the capital expenses (CAPEX) and operation and maintenance (O&M) costs while the revenue comes first from the IRA H 2 production tax credit (PTC) and then from the sales of synfuel products. The profitability of the synfuel IES is most sensitive to the value of the hydrogen PTC and the synfuel products as well as the cost of the carbon feedstock, highlighting the importance of governmental incentives regarding hydrogen, carbon emissions, and synfuel in driving the deployment of future nuclear synfuel IESs.

08 HYDROGEN↗
NASA NTRSDate not supplied

OpenNEX: An open collaboration platform for the earth science community

Satellite data from the past several decades provide the most consistent record of land-surface processes that form the basis for scientific assessments of the impacts of climate variations and changes on the environment and human social-economical activities. During this time, scientific research on the characterization and assessment of environmental changes had tended to focus on large-scale land-surface changes with significant social-economic impacts. Increasingly, attention is shifting toward changes that occur more locally and that most directly relate to the everyday life of the majority of the population. In addition, there has been needs to develop management and policy decision support systems that are based on local environmental information. Almost at the same time, the advancement in sensor technology has allowed us to collect an unprecedented volume of environmental data. These data must be curated and analyzed to extract useful information for research and decision support purposes. Established in 2013 and funded by NASA, the Open NASA Earth eXchange (OpenNEX; https://opennex.org/ , Jia et al., 2019 ) project partnered with Amazon Web Services (AWS) to make available a large amount of Earth observing data, modeling results, and analysis tools on the AWS. OpenNEX provides researchers, developers, educators, and ordinary users with easy access to an integrated Earth science computational and data platform, enabling citizen scientists and application developers to realize the full value of NASA data assets and software tools. To encourage the public's engagement in this project, NASA ran virtual workshops and prize competitions. The virtual workshops provided online lectures and tutorials about how prominent scientists used the data in their research and the tutorials gave examples how to use the tools to interrogate the data in the Amazon cloud. Finally, the prize competitions allowed much wider participation in the OpenNEX project and enable testing the non-traditional projects and out-of-box ideas. OpenNEX has continued to evolve and mature. Here, we highlight new features and functionalities available to the community.

Jian Zhang↗
NASA NTRS1995

High Accuracy In-Flight Wavelength Calibration of Imaging Spectrometry Data

Accurate wavelength calibration of imaging spectrometer data is essential if proper atmospheric transmission corrections are to be made to obtain apparent surface reflectance. Accuracies of 0.1 nm are necessary for a 10 nm-sampling instrument in order to match the slopes of the deep atmospheric water vapor features that dominate the 0.7-2.3 micrometer regions. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) is calibrated in the laboratory to determine the wavelength position and full-width-half-maximum (FWHM) response for each of the 224 channels. The accuracies are limited by the quality of the monochromator used as a source. The accuracies vary from plus or minus to plus or minus 1.5 nm depending on the wavelength region, in general decreasing with increasing wavelength. Green et al. make corrections to the wavelength calibrations by using the known positions of 14 atmospheric absorption features throughout the 0.4-2.5 micrometer wavelength region. These features, having varying width and intensity, were matched to the MODTRAN model with a non-linear least squares fitting algorithm. A complete calibration was developed for all 224 channels by interpolation. Instrument calibration cannot be assumed to be stable to 0.1 nm over a flight season given the rigors of thermal cycling and launch and landing loads. The upcoming sensor HYDICE will require a means for in-flight spectral calibration of each scene because the calibration is both temperature and pressure sensitive. In addition, any sensor using a two-dimensional array has the potential for systematic wavelength shifts as a function of cross-track position, commonly called 'smile'. Therefore, a rapid means for calibrating complete images will be required. The following describes a method for determining instrument wavelength calibration using atmospheric absorption features that is efficient enough to be used for entire images on workstations. This study shows the effect of the surface reflectance on the calibration accuracy and the calibration history for the AVIRIS B spectrometer over the 1992 flight season.

Goetz, Alexander F. H.↗
NASA NTRS2022

Quantifying urban, industrial, and background changes in NO2 during the COVID-19 lockdown period based on TROPOMI satellite observations

The COVID-19 lockdown had a large impact on anthropogenic emissions of air pollutants and particularly on nitrogen dioxide (NO 2 ). While the overall NO 2 decline over some large cities is well-established, understanding the details remains a challenge since multiple source categories contribute. In this study, a new method of isolation of three components (background NO 2 , NO 2 from urban sources, and NO 2 from industrial point sources) is applied to estimate the impact of the COVID-19 lockdown on each of them. The approach is based on fitting satellite data by a statistical model with empirical plume dispersion functions driven by a meteorological reanalysis. Population density and surface elevation data as well as coordinates of industrial sources were used in the analysis. The tropospheric NO 2 vertical column density (VCD) values measured by the Tropospheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor over 261 urban areas for the period from 16 March to 15 June 2020 were compared with the average VCD values for the same period in 2018 and 2019. While the background NO 2 component remained almost unchanged, the urban NO 2 component declined by −18 % to −28 % over most regions. India, South America, and a part of Europe (particularly, Italy, France, and Spain) demonstrated a −40 % to −50 % urban emission decline. In contrast, the decline over urban areas in China, where the lockdown was over during the analysed period, was, on average, only -4.4± 8 %. Emissions from large industrial sources in the analysed urban areas varied greatly from region to region from -4.8 ± 6 % for China to -40 ± 10 % for India. Estimated changes in urban emissions are correlated with changes in Google mobility data (the correlation coefficient is 0.62) confirming that changes in traffic were one of the key elements in the decline in urban NO2 emissions. No correlation was found between changes in background NO2 and Google mobility data. On the global scale, the background and urban components were remarkably stable in 2018, 2019, and 2021, with averages of all analysed areas all being within ±2.5 % and suggesting that there were no substantial drifts or shifts in TROPOMI data. The 2020 data are clearly an outlier: in 2020, the mean background component for all analysed areas (without China) was -6.0 % ± 1.2 % and the mean urban component was -26.7 ± 2.6 % or 20σ below the baseline level from the other years.

COVID-19↗
NASA NTRS1999

Cloning the promoter for transforming growth factor-beta type III receptor. Basal and conditional expression in fetal rat osteoblasts

Transforming growth factor-beta binds to three high affinity cell surface molecules that directly or indirectly regulate its biological effects. The type III receptor (TRIII) is a proteoglycan that lacks significant intracellular signaling or enzymatic motifs but may facilitate transforming growth factor-beta binding to other receptors, stabilize multimeric receptor complexes, or segregate growth factor from activating receptors. Because various agents or events that regulate osteoblast function rapidly modulate TRIII expression, we cloned the 5' region of the rat TRIII gene to assess possible control elements. DNA fragments from this region directed high reporter gene expression in osteoblasts. Sequencing showed no consensus TATA or CCAAT boxes, whereas several nuclear factors binding sequences within the 3' region of the promoter co-mapped with multiple transcription initiation sites, DNase I footprints, gel mobility shift analysis, or loss of activity by deletion or mutation. An upstream enhancer was evident 5' proximal to nucleotide -979, and a silencer region occurred between nucleotides -2014 and -2194. Glucocorticoid sensitivity mapped between nucleotides -687 and -253, whereas bone morphogenetic protein 2 sensitivity co-mapped within the silencer region. Thus, the TRIII promoter contains cooperative basal elements and dispersed growth factor- and hormone-sensitive regulatory regions that can control TRIII expression by osteoblasts.

Non-NASA Center↗
NASA NTRS1999

Cloud 3D Effects Evidenced in Landsat Power Spectra and Autocorrelation Functions

An analysis of nadir reflectivity Fourier spatial power spectra and autocorrelation functions at solar wavelengths and for cloudy conditions has been carried out. The data come from Landsat Thematic Mapper (TM) observations, while Monte Carlo (MC) simulations are used to aid the interpretation of the Landsat results. We show that radiative processes produce consistent signatures on power spectra and autocorrelation functions. The former take a variety of forms not shown or explained in previous observational studies. We demonstrate that the TM spectra can potentially be affected by both radiative "roughening" at intermediate scales (approx. 1 -5 km), being more prevalent at large solar zenith angles, and the already documented radiative "smoothing" at small scales (less than 1 km). These processes are wavelength dependent, as shown by systematic differences between conservative (for cloud droplets) TM band 4 (approx. 0.8 microns) and absorbing band 7 (approx. 2.2 microns): band 7 exhibits more roughening and less smoothing. This is confirmed quantitatively by comparing least-squared fitted power spectral slopes for the two bands. It is also corroborated by a slower decrease with distance of autocorrelation function values for band 4 compared to band 7. The appearance of roughening at large solar zenith angles is a result of side illumination and shadowing and adds an additional complexity to the power spectra. MC spectra are useful in illustrating that scale invariant optical depth fields can produce complex power spectra that take a variety of shapes under different conditions. We show that radiative roughening increases with the decrease of single scattering albedo and with the increase of solar zenith angle (as in the observations). For high Sun there is also a clear shift of the radiative smoothing scale to smaller values as droplet absorption increases. The shape of the power spectrum is sensitive to the magnitude and type of cloud top height variability, with the spectral signatures of decorrelation between reflectance and optical depth at large scales becoming stronger as the magnitude of cloud top variations increase. Finally, the usefulness of power spectral analysis in evaluating the skill of novel optical depth retrieval techniques in removing 3D radiative effects is demonstrated. New techniques using inverse Non-local Independent Pixel Approximation (NIPA) and Normalized Difference of Nadir Reflectivity (NDNR) yield optical depth fields which better match the scale-by-scale variability of the true optical depth field.

Oreopoulos, Lazaros↗
NASA NTRS2007

Roller Bearing Health Monitoring Using CPLE Frequency Analysis Method

This paper describes a unique vibration signature analysis technique Coherence Phase Line Enhancer (CPLE) Frequency Analysis - for roller bearing health monitoring. Defects of roller bearing (e.g. wear, foreign debris, crack in bearing supporting structure, etc.) can cause small bearing characteristic frequency shifts due to minor changes in bearing geometry. Such frequency shifts are often too small to detect by the conventional Power Spectral Density (PSD) due to its frequency bandwidth limitation. This Coherent Phase Line Enhancer technology has been evolving over the last few years and has culminated in the introduction of a new and novel frequency spectrum which is fully described in this paper. This CPLE technology uses a "key phasor" or speed probe as a preprocessor for this analysis. With the aid of this key phasor, this CPLE technology can develop a two dimensional frequency spectrum that preserves both amplitude and phase that is not normally obtained using conventional frequency analysis. This two-dimensional frequency transformation results in several newly defined spectral functions; i. e. CPLE-PSD, CPLE-Coherence and the CPLE-Frequency. This paper uses this CPLE frequency analysis to detect subtle, low level bearing related signals in the High Pressure Fuel Pump (HPFP) of the Space Shuttle Main Engine (SSME). For many rotating machinery applications, a key phasor is an essential measurement that is used in the detection of bearing related signatures. There are times however, when a key phasor is not available; i. e. during flight of any of the SSME turbopumps or on the SSME High Pressure Oxygen Turbopump (HPOTP) where no speed probe is present. In this case, the CPLE analysis approach can still be achieved using a novel Pseudo Key Phasor (PKP) technique to reconstruct a 1/Rev PKP signal directly from external vibration measurements. This paper develops this Pseudo Key Phasor technique and applies it to the SSME vibration data.

Jong, Jen-Yi↗
NASA NTRS2006

Less-Complex Method of Classifying MPSK

An alternative to an optimal method of automated classification of signals modulated with M-ary phase-shift-keying (M-ary PSK or MPSK) has been derived. The alternative method is approximate, but it offers nearly optimal performance and entails much less complexity, which translates to much less computation time. Modulation classification is becoming increasingly important in radio-communication systems that utilize multiple data modulation schemes and include software-defined or software-controlled receivers. Such a receiver may "know" little a priori about an incoming signal but may be required to correctly classify its data rate, modulation type, and forward error-correction code before properly configuring itself to acquire and track the symbol timing, carrier frequency, and phase, and ultimately produce decoded bits. Modulation classification has long been an important component of military interception of initially unknown radio signals transmitted by adversaries. Modulation classification may also be useful for enabling cellular telephones to automatically recognize different signal types and configure themselves accordingly. The concept of modulation classification as outlined in the preceding paragraph is quite general. However, at the present early stage of development, and for the purpose of describing the present alternative method, the term "modulation classification" or simply "classification" signifies, more specifically, a distinction between M-ary and M'-ary PSK, where M and M' represent two different integer multiples of 2. Both the prior optimal method and the present alternative method require the acquisition of magnitude and phase values of a number (N) of consecutive baseband samples of the incoming signal + noise. The prior optimal method is based on a maximum- likelihood (ML) classification rule that requires a calculation of likelihood functions for the M and M' hypotheses: Each likelihood function is an integral, over a full cycle of carrier phase, of a complicated sum of functions of the baseband sample values, the carrier phase, the carrier-signal and noise magnitudes, and M or M'. Then the likelihood ratio, defined as the ratio between the likelihood functions, is computed, leading to the choice of whichever hypothesis - M or M'- is more likely. In the alternative method, the integral in each likelihood function is approximated by a sum over values of the integrand sampled at a number, 1, of equally spaced values of carrier phase. Used in this way, 1 is a parameter that can be adjusted to trade computational complexity against the probability of misclassification. In the limit as 1 approaches infinity, one obtains the integral form of the likelihood function and thus recovers the ML classification. The present approximate method has been tested in comparison with the ML method by means of computational simulations. The results of the simulations have shown that the performance (as quantified by probability of misclassification) of the approximate method is nearly indistinguishable from that of the ML method (see figure).

Hamkins, Jon↗
NASA NTRSDate not supplied

A Science-Focused Artificial Intelligence (AI) Responding in Real-Time to New Information: Capability Demonstration for Ocean World Missions

Introduction: Artificial intelligence (AI) has long been considered a potential mechanism to explore increasingly challenging environments, including those with extreme temperatures and pressures, limited communication capabilities, or those with demanding terrain. We posit that missions in extreme environments could deploy an onboard AI focused on science observations and goals in order to augment a traditional concept(s) of operations (ConOps). An onboard AI capability could perform functions such as data analysis in order to make high-level decisions, including prioritized data transmission for analysis by ground-based teams or autonomously-guided follow-on analyses that maximize science return. Such a capability would empower missions to respond to scientific data of interest in real-time; a mission could make observations and perform a preliminary analysis to alert ground-based scientists to an observation of interest, enabling an informed, rapid response from Earth-based teams. Enceladus Case Study for Onboard AI: We are developing an onboard AI capability for real-time telemetry response that formulates and carries-out informed decisions in service to established mission goals, enabling increased science return of a mission. We focus our AI development for use on a constellation of SmallSats orbiting Enceladus. Our Enceladus case study tests autonomous decision-making capabilities in scenarios with complex orbital dynamics, plume ejecta, extreme cold environments, power restrictions, and a requirement to maximize science return for a potential positive detection of life, while critically evaluating the potential for false positives. Telemetry includes simulated scientific data, spacecraft onboard operational data (e.g., position, velocity, and rotation), and engineering hardware performance data. Enceladus SmallSat Constellation. Our constellation includes eight SmallSat spacecraft in an 8:35 resonant orbit-based formation, leveraging Saturn’s gravitational forces to maintain stable orbits with global coverage around Enceladus. To our knowledge, we simulate the first stable configuration of multiple spacecraft in closed orbits around Enceladus, using a full ephemeris force model (Russell and Lara, 2009). Each spacecraft’s orbit will precess, causing an eastward ground track shift (from an orbiter’s perspective) of each spacecraft for each orbit. However, all spacecraft return to their original positions relative to Enceladus after eight Enceladus revolutions around Saturn. We model communication pathways between SmallSats to understand how information would need to be transmitted across the constellation to enable AI-driven decision-making and resource allocation across the fleet. Capability Demonstration. Our simulated capability demonstration inputs position, velocity, and rotation telemetry from our Enceladus-focused constellation simulations, and mass spectrometry data collected from abiotic and biotic laboratory-analog ocean world experiments (Theiling et al., 2018; Theiling, 2021; Da Poian et al., 2023). Data from these experiments are used to simulate MS measurements and different scenarios of science observations for onboard analysis performed on each of the eight spacecraft. For these demonstrations, we integrate 24 machine learning (ML) algorithms into an onboard intelligence as a ‘knowledge base’, including algorithms evaluating data quality and those predicting (with % confidence) gas composition, ocean aqueous chemistry, and whether the sample was influenced by microbial life. The onboard AI capability is designed to use the knowledge base to come to a consensus-based decision in the interpretation of the observed data in order to request additional action outside of a pre-defined ConOps. Requested actions could include e.g., prioritized downlink to Earth (for analysis by ground-based teams) or follow-on analyses performed across the constellation. The spacecraft’s intelligent onboard planner must then determine whether sufficient resources (e.g., time, power, etc.) are available and weigh the request with mission priorities. In our simulation, the constellation is able to identify potential biosignatures using onboard ML algorithms, evaluate the confidence of that prediction, and perform follow-on analyses across the fleet to confirm the detection, in order to best prepare a transmission of these data to Earth-based teams.

astrobiology↗