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NASA NTRS1977

Capabilities of operational infrared sounding systems from satellite altitude

Initial attempts at using satellite radiances resulted in the production of temperature profiles similar to those produced by radiosondes. While increases in accuracy were made and additional increases are expected to result from increased instrument capabilities, it was recognized that the production of level temperatures is not consistent with the average temperature that is represented by the radiances.

Mcmillin, L.↗
NASA NTRS1992

Registration of interferometric SAR images

Interferometric synthetic aperture radar (INSAR) is a new way of performing topography mapping. Among the factors critical to mapping accuracy is the registration of the complex SAR images from repeated orbits. A new algorithm for registering interferometric SAR images is presented. A new figure of merit, the average fluctuation function of the phase difference image, is proposed to evaluate the fringe pattern quality. The process of adjusting the registration parameters according to the fringe pattern quality is optimized through a downhill simplex minimization algorithm. The results of applying the proposed algorithm to register two pairs of Seasat SAR images with a short baseline (75 m) and a long baseline (500 m) are shown. It is found that the average fluctuation function is a very stable measure of fringe pattern quality allowing very accurate registration.

Lin, Qian↗
NASA NTRS1996

The JPL Hg(sup +) Extended Linear Ion Trap Frequency Standard: Status, Stability, and Accuracy Prospects

Microwave frequency standards based on room temperature (sup 199)Hg(sup +) ions in a Linear Ion Trap (LITS) presently achieve a Signal to Noise and line Q inferred short frequency stability. Long term stability has been measured for averaging intervals up to 5 months with apparent sensitivity to variations in ion number/temperature limiting the flicker floor.

Hg+ linear ion trap frequency LITE LITS microwave ↗
NASA NTRS2007

New and Improved T-wave Morphology Parameters to Differentiate Healthy Individuals from those with Cardiomyopathy and Coronary Artery Disease

We investigated the ability of several known as well as new ECG repolarization parameters to differentiate healthy individuals from patients with obstructive coronary artery disease (CAD) and cardiomyopathy (CM). Advanced high-fidelity 12-lead ECG tests (approx. 5-min supine) were first performed on a "training set" of 99 individuals: 33 with ischemic or dilated CM and low ejection fraction (EF less than 40%); 33 with catheterization-proven obstructive CAD but normal EF; and 33 age-/gender-matched healthy controls. The following multiple parameters of T-wave morphology (TWM) were derived via signal averaging and singular value decomposition (SVD, which yields 8 eigenvalues, rho(sub 1) greater than rho(sub 2)...greater than rho(sub 8) and studied for their retrospective accuracy in detecting underlying disease: 1) Principal component analysis ratio of the T wave (T-PCA) = 100*rho(sub 2)/rho(sub 1); 2) Relative T-wave residuum (rTWR) = 100* SIGMA (rho(sub 4)(sup 2) +...+ rho(sub 8)(sup 2)); 3) Modified complexity ratio of the T wave (T-mCR) = 100*SIGMA(rho(sub 3)(sup 2) +...+rho(sb 8) (sup 2)); and 4) Normalized 3-dimensional volume of the T wave (nTV) = 100*(rho(sub 2)*rho(sub 3)/rho(sub 1)(sup 2). All TWM parameters significantly differentiated CAD from controls (p less than 0.0001), and also CM from controls (p less than 0.0001). Retrospective areas under the ROC curve were 0.77, 0.81, 0.82, and 0.83 (CAD vs. controls) and 0.93, 0.89, 0.95 and 0.96 (CM vs. controls) for T-PCA, rTWR, T-mCR and nTV respectively. The newer TWM parameters (T-mCR and nTV) thus outperformed the more established parameters (T-PCA and rTWR), presumably by putting a greater emphasis on the third T-wave eigenvalue, which in most healthy subjects has little energy compared to the first two eigenvalues. Subsequent prospective analyses have also yielded similar results, such that we conclude that diagnostic differentiation of pathology from non-pathology may be especially aided by detecting the transference of energy from the first and second T-wave eigenvalues into the third T-wave eigenvalue.

Greco, E. C.↗
NASA NTRS2007

Gravity Probe B Timing System and Roll Phase Determination

An oven-controlled crystal oscillator at 16.368 MHz provides clock signals to all GP-B components and synchronizes the data collection, transmission and processing. The sampled science data signals are stamped with the vehicle time, a counter of the 10Hz data strobe divided down from the clock. The GPS receiver supplies an external reference for time transfer between the vehicle time and coordinated universal time. Ground and space flight tests show the time transfer error is within 1 microsecond. The time latency between the effective sample time of science signals and the stamped vehicle time is verified to 1 ms in the ground tests. The GP-B satellite is controlled to roll with a period of 77.5 sec about an axis along the direction to the guide star to average out the disturbance torques fixed to the body of the satellite and reduce the gyroscope readout noise. The roll phase is determined on the ground to high accuracy with the telemetry data from two star trackers and used in the data analysis to separate the drifts of gyroscope spin axes in the orbital plane and perpendicular to the orbital plane. The flight data shows that the roll phase is controlled to within 40 arcsec with a measurement uncertainty of 7 arcsec.

Jie, Li↗
NASA NTRS2012

Carnegie Hubble Program: A Mid-Infrared Calibration of the Hubble Constant

Using a mid-infrared calibration of the Cepheid distance scale based on recent observations at 3.6 micrometers with the Spitzer Space Telescope, we have obtained a new, high-accuracy calibration of the Hubble constant. We have established the mid-IR zero point of the Leavitt law (the Cepheid period-luminosity relation) using time-averaged 3.6 micrometers data for 10 high-metallicity, MilkyWay Cepheids having independently measured trigonometric parallaxes. We have adopted the slope of the PL relation using time-averaged 3.6micrometers data for 80 long-period Large Magellanic Cloud (LMC) Cepheids falling in the period range 0.8 < log(P) < 1.8.We find a new reddening-corrected distance to the LMC of 18.477 +/- 0.033 (systematic) mag. We re-examine the systematic uncertainties in H(sub 0), also taking into account new data over the past decade. In combination with the new Spitzer calibration, the systematic uncertainty in H(sub 0) over that obtained by the Hubble Space Telescope Key Project has decreased by over a factor of three. Applying the Spitzer calibration to the Key Project sample, we find a value of H(sub 0) = 74.3 with a systematic uncertainty of +/-2.1 (systematic) kilometers per second Mpc(sup −1), corresponding to a 2.8% systematic uncertainty in the Hubble constant. This result, in combination with WMAP7measurements of the cosmic microwave background anisotropies and assuming a flat universe, yields a value of the equation of state for dark energy, w(sub 0) = −1.09 +/- 0.10. Alternatively, relaxing the constraints on flatness and the numbers of relativistic species, and combining our results with those of WMAP7, Type Ia supernovae and baryon acoustic oscillations yield w(sub 0) = −1.08 +/- 0.10 and a value of N(sub eff) = 4.13 +/- 0.67, mildly consistent with the existence of a fourth neutrino species.

Program↗
NASA NTRS2017

Evaluating a Priori Ozone Profile Information Used in TEMPO (Tropospheric Emissions: Monitoring of Pollution) Tropospheric Ozone Retrievals

A primary objective for TOLNet is the evaluation and validation of space-based tropospheric O3 retrievals from future systems such as the Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite. This study is designed to evaluate the tropopause-based O3 climatology (TB-Clim) dataset which will be used as the a priori profile information in TEMPO O3 retrievals. This study also evaluates model simulated O3 profiles, which could potentially serve as a priori O3 profile information in TEMPO retrievals, from near-real-time (NRT) data assimilation model products (NASA Global Modeling and Assimilation Office (GMAO) Goddard Earth Observing System (GEOS-5) Forward Processing (FP) and Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA2)) and full chemical transport model (CTM), GEOS-Chem, simulations. The TB-Clim dataset and model products are evaluated with surface (0-2 km) and tropospheric (0-10 km) TOLNet observations to demonstrate the accuracy of the suggested a priori dataset and information which could potentially be used in TEMPO O3 algorithms. This study also presents the impact of individual a priori profile sources on the accuracy of theoretical TEMPO O3 retrievals in the troposphere and at the surface. Preliminary results indicate that while the TB-Clim climatological dataset can replicate seasonally-averaged tropospheric O3 profiles observed by TOLNet, model-simulated profiles from a full CTM (GEOS-Chem is used as a proxy for CTM O3 predictions) resulted in more accurate tropospheric and surface-level O3 retrievals from TEMPO when compared to hourly (diurnal cycle evaluation) and daily-averaged (daily variability evaluation) TOLNet observations. Furthermore, it was determined that when large daily-averaged surface O3 mixing ratios are observed (65 ppb), which are important for air quality purposes, TEMPO retrieval values at the surface display higher correlations and less bias when applying CTM a priori profile information compared to all other data products. The primary reason for this is that CTM predictions better capture the spatio-temporal variability of the vertical profiles of observed tropospheric O3 compared to the TB-Clim dataset and other NRT data assimilation models evaluated during this study.

Pollution↗
NASA NTRS2017

Importance of a Priori Vertical Ozone Profiles for TEMPO Air Quality Retrievals

Ozone (O3) is a toxic pollutant which plays a major role in air quality. Typically, monitoring of surface air quality and O3 mixing ratios is conducted using in situ measurement networks. This is partially due to high-quality information related to air quality being limited from space-borne platforms due to coarse spatial resolution, limited temporal frequency, and minimal sensitivity to lower tropospheric and surface-level O3. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite is designed to address the limitations of current space-based platforms and to improve our ability to monitor North American air quality. TEMPO will provide hourly data of total column and vertical profiles of O3 with high spatial resolution to be used as a near-real-time air quality product. TEMPO O3 retrievals will apply the Smithsonian Astrophysical Observatory profile algorithm developed based on work from GOME (Global Ozone Monitoring Experiment), GOME-2, and OMI (Ozone Monitoring Instrument). This algorithm is suggested to use a priori O3 profile information from a climatological data-base developed from long-term ozone-sonde measurements (tropopause-based (TB-Clim) O3 climatology). This study evaluates the TB-Clim dataset and model simulated O3 profiles, which could potentially serve as a priori O3 profile information in TEMPO retrievals, from near-real-time data assimilation model products (NASA GMAO's (Global Modeling and Assimilation Office) operational GEOS-5 (Goddard Earth Observing System, Version 5) FP (Forecast Products) model and reanalysis data from MERRA2 (Modern-Era Retrospective analysis for Research and Applications, Version 2)) and a full chemical transport model (CTM), GEOS-Chem. In this study, vertical profile products are evaluated with surface (0-2 kilometers) and tropospheric (0-10 kilometers) TOLNet (Tropospheric Ozone Lidar Network) observations and the theoretical impact of individual a priori profile sources on the accuracy of TEMPO O3 retrievals in the troposphere and at the surface are presented. Results indicate that while the TB-Clim climatological dataset can replicate seasonally-averaged tropospheric O3 profiles, model-simulated profiles from a full CTM resulted in more accurate tropospheric and surface-level O3 retrievals from TEMPO when compared to hourly and daily-averaged TOLNet observations. Furthermore, it is shown that when large surface O3 mixing ratios are observed, TEMPO retrieval values at the surface are most accurate when applying CTM a priori profile information compared to all other data products.

Priori↗
NASA NTRS2020

Automated Cardiovascular Pathology Assessment using Semantic Segmentation and Ensemble Learning

Cardiac magnetic resonance imaging provides high spatial resolution, enabling improved extraction of important functional and morphological features for cardiovascular disease staging. Segmentation of ventricular cavities and myocardium in cardiac cine sequencing provides a basis to quantify cardiac measures such as ejection fraction. A method is presented that curtails the expense and observer bias of manual cardiac evaluation by combining semantic segmentation and disease classification into a fully automatic processing pipeline. The initial processing element consists of a robust dilated convolutional neural network architecture for voxel-wise segmentation of the myocardium and ventricular cavities. The resulting comprehensive volumetric feature matrix captures diagnostic clinical procedure data and is utilized by the final processing element to model a cardiac pathology classifier. Our approach evaluated anonymized cardiac images from a training data set of 100 patients (4 pathology groups, 1 healthy group, 20 patients per group) examined at the University Hospital of Dijon. The top average Dice index scores achieved were 0.940, 0.886, 0.849 for structure segmentation of the left ventricle (LV), myocardium and right ventricle (RV) respectively. A 5-ary pathology classification accuracy of 90% was recorded on an independent test set using the trained model. Performance results demonstrate potential for advanced machine learning methods to deliver accurate, efficient and reproducible cardiac pathological assessment.

Semantic Segmentation↗
NASA NTRS2022

Assimilation of SMAP Products for Improving Streamflow Simulations over Tropical Climate Region—Is Spatial Information More Important Than Temporal Information?

Streamflow is one of the key variables in the hydrological cycle. Simulation and forecasting of streamflow are challenging tasks for hydrologists, especially in sparsely gauged areas. Coarse spatial resolution remote sensing soil moisture products (equal to or larger than 9 km) are often assimilated into hydrological models to improve streamflow simulation in large catchments. This study uses the Ensemble Kalman Filter (EnKF) technique to assimilate SMAP soil moisture products at the coarse spatial resolution of 9 km (SMAP 9 km), and downscaled SMAP soil moisture product at the higher spatial resolution of 1 km (SMAP 1 km), into the Soil and Water Assessment Tool (SWAT) to investigate the usefulness of different spatial and temporal resolutions of remotely sensed soil moisture products in streamflow simulation and forecasting. The experiment was set up for eight catchments across the tropical climate of Vietnam, with varying catchment areas from 267 to 6430 km^2 during the period 2017–2019. We comprehensively evaluated the EnKF-based SWAT model in simulating streamflow at low, average, and high flow. Our results indicated that high-spatial resolution of downscaled SMAP 1 km is more beneficial in the data assimilation framework in aiding the accuracy of streamflow simulation, as compared to that of SMAP 9 km, especially for the small catchments. Our analysis on the impact of observation resolution also indicates that the improvement in the streamflow simulation with data assimilation is more significant at catchments where downscaled SMAP 1 km has fewer missing observations. This study is helpful for adding more understanding of performances of soil moisture data assimilation based hydrological modelling over the tropical climate region, and exhibits the potential use of remote sensing data assimilation in hydrology.

soil moisture↗
NASA NTRSDate not supplied

Initial On-Orbit Spectral Calibration of the PACE Ocean Color Instrument

The NASA Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission Project Science Team has used Ocean Color Instrument (OCI) measurements of Fraunhofer lines in spectra of sunlight reflected by the solar diffuser and measurements of atmospheric absorption bands in cloudtop and ocean spectra to characterize the spectral calibration of OCI on orbit. Multiple lines have been analyzed for both the ultraviolet to visible (UVVIS, 340−607 nm) and visible to near-infrared (VISNIR, 597−897 nm) grating spectrographs. The spectrographs yield hyperspectral observations with 5 nm bandwidths and 0.625 nm sampling intervals. The on-orbit observations have been compared with the prelaunch spectral calibration of OCI performed by the Goddard Laser for Absolute Measurement of Radiance (GLAMR) during thermal vacuum testing to track any changes in the calibration since launch. The calibration analyzed the line positions and strengths for the Fraunhofer lines for each spectrograph by comparing the solar spectra measured by OCI with predicted solar spectra derived from the solar reference spectrum and the BRDF of the solar diffuser, convolved with the OCI relative spectral responses. The calibration also compared the line positions of the atmospheric absorption bands with the model transmissions used by the PACE Project. The line position comparisons show that the root mean square (RMS) spectral difference between the measured and predicted spectra is 0.15 nm, the average spectral shift is 0.062 nm, and the residual spectral dispersion over the wavelength range of the Fraunhofer lines is 0.17 nm. All three estimates of the spectral accuracy of OCI meet the instrument functional requirement of a spectral accuracy of 0.5 nm and are well within the 0.625 nm sampling interval of the data. The line strength comparisons between measured and predicted spectra are essentially the same. These results show that the spectral calibration of OCI on orbit has not drifted since the prelaunch calibration of OCI by GLAMR and that the on-orbit spectral calibration of OCI is stable over time. These results also provide a baseline for monitoring the future spectral performance of OCI on orbit.

Radiometric Calibration↗
DOE OSTI2025

Mapping tree height in complex terrain of northern China using ultra-high-resolution images

Tree height is a key parameter for estimating forest biomass and carbon sequestration. In recent years, notable progress has been made in mapping tree height using satellite imagery. However, existing tree height products show low accuracy in mountainous and complex terrains, and few studies typically addressed tree height estimations in mountain areas. This study examines the Mentougou district of Beijing, China, characterized by complex terrain and mountainous landscapes. We analyzed two methods for estimating tree height: one using only spectral features and another combining spectral features with topographic factors (elevation, slope, aspect). We used 3-m resolution PlanetScope 8-band multispectral imagery, with 710 field-measured individual tree heights averaged to obtain 471 pixel-level tree height values as ground-truth, to develop tree height prediction models using eXtreme Gradient Boosting (XGBoost), Random Forest (RF), and Gradient Boosting Machine (GBM) models. The results show that the XGBoost model consistently presented the highest accuracy for both methods evaluated. Specifically, the XGBoost model that combined spectral data with elevation and slope variables with an R² of 0.75 and an RMSE of 2.69 m. Using the XGBoost model, we generated the tree height map for the Mentougou area at 3 m resolution, showing tree heights ranging from 0.5 to 30.4 m, and the model’s prediction error standard deviations ranged from 2.50 to 4.71 m, indicating reliable performance across varied terrain. Additionally, we compared and evaluated the global tree height products, identifying limitations in the accuracy within complex terrains. This study demonstrates the potential for accurately predicting tree heights by combining high-resolution multispectral satellites with a terrain factor modeling approach.

Complex terrain↗
DOE OSTI2026

Data for Clumping Index Estimation With 30°-tilted Cameras in Row Crops: Evaluation of Methods and Segment Size Effects

The clumping index (CI) quantifies the spatial distribution of foliage elements and is essential for accurately estimating the plant area index (PAI), canopy radiative transfer, and photosynthesis. Traditionally, the finite-length averaging method (LX), the gap size distribution method (CC), and a combined approach of CC and LX (CLX) have been applied to instruments like TRAC and digital hemispherical photography to estimate CI. However, a comprehensive evaluation of these methods in row crops remains limited, especially regarding the influence of segment size on CI. Meanwhile, digital cameras offer a cost-effective and user-friendly solution for canopy measurements in row crops, yet their application in this context remains underexplored. In this study, we employed a new approach using a 30°-tilted digital camera to estimate CI in corn and soybean fields, applying the LX, CC, and CLX methods. We systematically assessed the performance of these three methods by combining field measurements in real-world fields with simulations using the LESS 3D radiative transfer model. Our results showed that CLX applied to the whole image and 45° segment offered accurate estimation of CI (bias within ±0.1, RMSE < 0.2) and PAI (bias within ±0.4, RMSE < 1) in real-world fields and LESS simulations. The accuracy of the LX method was highly sensitive to segment size, with the best performance observed at the 15° segment (PAI bias within ±0.4). In contrast, the CC method remained stable across different segment sizes, and its performance was generally comparable to that of LX, except at the 15° segment. Across view zenith angles, CI derived from CC generally showed a continuous increase, while those from LX and CLX followed a rising trend at small zenith angles but began to decline at 68°, likely due to an increasing proportion of no-gap segments. Seasonally, LX tended to show decreasing CI during early growth stages but increased as the canopy matured, whereas CC and CLX showed gradually increasing CI before plateauing at peak PAI. The 30°-tilted camera effectively captured CI variations across different angles and growth stages, making it a practical and robust instrument for row crop canopy structure analysis. Applying these CI methods to digital cameras offers a low-cost and accessible CI estimation alternative, improving canopy structure monitoring accuracy in row crops.

Modeling↗
NASA NTRS2006

Comanche Helmet-Mounted Display Symbology Simulation

The Aeroflightdynamics Directorate (AMRDEC) conducted a simulation to examine the performance of the Comanche Contact Analog world-referenced symbology displayed on the Comanche HIDSS when compared with a compressed symbology design similar to that specified by the former MIL-STD 1295. Six experimental test pilots flew one modified ADS-33 maneuver (hover turn, bob-up), an unusual attitude recovery, and two terrain flight tactical tasks in the NASA Vertical Motion Simulator (VMS). Analysis of the pilot objective performance data and subjective data showed the following results. Objective test results showed that 1295 symbology yielded more rapid maneuvering in the hover turn bob-up than Contact Analog symbology. The average margin of difference in the time to complete the maneuver was approximately two seconds, which was statistically significant. There were no significant differences measured between symbology sets with respect to altitude or position performance measures for all other maneuvers. The NOE target ID task data showed improved accuracy in determining heading to target when using Contact Analog over MIL-STD-1295. Subjective test results, including handling qualities ratings (HQRs) and NASA-TLX workload ratings, showed small but consistent advantages of 1295 symbology over Contact Analog for most parameters. For the bob-up maneuver, 1295 symbology handling qualities were rated Desired for lateral position error and time to complete whereas Contact Analog was rated adequate. The average HQRs for all other maneuvers were rated the same for both symbology sets. Pilot comments and the results of an online questionnaire more strongly favored 1295 over Contact Analog. Repeated comments from all six pilots led to a focus on design issues with six Contact Analog symbols. Those symbols were the heading tape, horizon line, radar altitude six-second predictor, the position of the torque symbol, the absence of a hover position cue, and the widespread positioning of the symbology to the outer edges of the display field-of-view. Pilots rated the present design of three of the six symbols as having safety-of-flight implications. Those symbols were the heading tape, horizon line, and six-second predictor. To summarize, test results showed no objective data that would warrant restricting experimental test pilots from flying constrained tasks. Small but consistent advantages were recorded for the MILSTD-1295 symbology design when executing ADS-33 constrained tasks. No general performance differences were recorded for the operational maneuvers (NOE, contour flight modes) except for the azimuth-to-target task, which favored the Contact Analog heading tape design. There were consistent and strong pilot comments supporting the MIL-STD-1295 design over Contact Analog in both this current simulation and in Comanche Sim I. Three Contact Analog symbols warrant modification and further evaluation to mitigate safety-of-flight implications noted by participating test pilots. A plan for symbology redesign and testing was developed. However, the Comanche program was cancelled by Department of Army in February 2004.

Turpin, Terry S.↗
DOE OSTI2023

Prediction of chronic kidney disease progression using recurrent neural network and electronic health records

Chronic kidney disease (CKD) is a progressive loss in kidney function. Early detection of patients who will progress to late-stage CKD is of paramount importance for patient care. To address this, we develop a pipeline to process longitudinal electronic heath records (EHRs) and construct recurrent neural network (RNN) models to predict CKD progression from stages II/III to stages IV/V. The RNN model generates predictions based on time-series records of patients, including repeated lab tests and other clinical variables. Our investigation reveals that using a single variable, the recorded estimated glomerular filtration rate (eGFR) over time, the RNN model achieves an average area under the receiver operating characteristic curve (AUROC) of 0.957 for predicting future CKD progression. When additional clinical variables, such as demographics, vital information, lab test results, and health behaviors, are incorporated, the average AUROC increases to 0.967. In both scenarios, the standard deviation of the AUROC across cross-validation trials is less than 0.01, indicating a stable and high prediction accuracy. Our analysis results demonstrate the proposed RNN model outperforms existing standard approaches, including static and dynamic Cox proportional hazards models, random forest, and LightGBM. The utilization of the RNN model and the time-series data of previous eGFR measurements underscores its potential as a straightforward and effective tool for assessing the clinical risk of CKD patients concerning their disease progression.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Single particle – MC-ICP-MS for isotopic analysis of uranium particles

Single particle – multi-collector – inductively coupled plasma – mass spectrometry (SP-MC-ICP-MS) was employed to measure a suspension of 1 µm U3O8 particles (∼1.3 pg total U/particle) to determine their individual isotopic compositions of 234U/238U, 235U/238U, and 236U/238U. The effects of different detector combinations for 235U and 238U, including secondary electron multipliers (SEM) and Faraday detectors (1011 and 1013 Ω amplifiers), were explored for accuracy and precision optimization on the observed 235U/238U. The minor isotopic ratios (i.e., 234U/238U and 236U/238U) were analyzed such that the 234U and 236U were monitored on SEM detectors and the 238U was monitored on a Faraday (1011 Ω) detector. Various integration times (5, 10, 25, and 50 ms) were investigated in all detector configurations to gain a better understanding of their impact on sensitivity, accuracy, and precision. For 235U/238U ratios of 1 µm U3O8 particles, a dual Faraday detector measurement with 1011 Ω was the optimal choice; measurement of 1021 particles yielded an average 235U/238U ratio of 0.00170 (14), a −1.8% relative difference (% RD) from the reference value. The minor isotopic compositions were determined to be 0.0000070 (14) and 0.0000758 (48) for the 234U/238U and 236U/238U, respectively. These measurements correspond to <8% and <1% RD from their reference value for the 234U/238U and 236U/238U, respectively. SP-MC-ICP-MS was also able to provide insight into measurement sensitivity. In these individual particles, merely 15 and 165 atto-grams (ag) of 234U and 236U were present (calculated). Initial limits of detection for SP-MC-ICP-MS were determined to be ∼1.0 ag (when measured via SEM detectors). This valuable approach is applicable to areas including nuclear forensics, nuclear safeguards, and geochemical analysis, which require high-precision measurements of uranium within micron-sized particles.

Manard, Benjamin [ORNL] (ORCID:0000000207400627)↗
DOE OSTI2022

Multi-head attention-based U-Nets for predicting protein domain boundaries using 1D sequence features and 2D distance maps

Abstract The information about the domain architecture of proteins is useful for studying protein structure and function. However, accurate prediction of protein domain boundaries (i.e., sequence regions separating two domains) from sequence remains a significant challenge. In this work, we develop a deep learning method based on multi-head U-Nets (called DistDom) to predict protein domain boundaries utilizing 1D sequence features and predicted 2D inter-residue distance map as input. The 1D features contain the evolutionary and physicochemical information of protein sequences, whereas the 2D distance map includes the structural information of proteins that was rarely used in domain boundary prediction before. The 1D and 2D features are processed by the 1D and 2D U-Nets respectively to generate hidden features. The hidden features are then used by the multi-head attention to predict the probability of each residue of a protein being in a domain boundary, leveraging both local and global information in the features. The residue-level domain boundary predictions can be used to classify proteins as single-domain or multi-domain proteins. It classifies the CASP14 single-domain and multi-domain targets at the accuracy of 75.9%, 13.28% more accurate than the state-of-the-art method. Tested on the CASP14 multi-domain protein targets with expert annotated domain boundaries, the average per-target F1 measure score of the domain boundary prediction by DistDom is 0.263, 29.56% higher than the state-of-the-art method.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1977

Lowest-order average effect of turbulence on atmospheric profiles derived from radio occultation

Turbulence in planetary atmospheres and ionospheres causes changes in angles of refraction of radio waves used in occultation experiments. Atmospheric temperature and pressure profiles, and ionospheric electron concentration profiles, derived from radio occultation measurements of Doppler frequency contain errors due to such angular offsets. The lowest-order average errors are derived from a geometrical-optics treatment of the radio-wave phase advance caused by the addition of uniform turbulence to an initially homogeneous medium. It is concluded that the average profile errors are small and that precise Doppler frequency measurements at two or more wavelengths could be used to help determine characteristics of the turbulence, as well as accuracy limits and possible correction terms for the profiles. However, a more detailed study of both frequency and intensity characteristics in radio and optical occultation measurements of turbulent planetary atmospheres and ionospheres is required to realize the full potential of such measurements.

Eshleman, V. R.↗