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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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Models for synthetic data generation

The software includes a suite of probabilistic statistical/machine learning models that can generate discrete synthetic data. Each model is trained on a set of real (private) data and then it can be used to generate synthetic but statistically similar data. Once ready, the model can generate as many samples as we want. Finally, in addition to the actual models, the software includes code to process data, evaluate results (based on cross validation), and produce reports.

De Oliveira Sales, Ana Paula↗

Data and scripts associated with “Riverine dissolved organic matter transformations increase with watershed area, water residence time, and Damköhler numbers in nested watersheds” (v2)

This data package is associated with the publication “Riverine dissolved organic matter transformations increase with watershed area, water residence time, and Damköhler numbers in nested watersheds” submitted to Biogeochemistry by Ryan et al., 2024 (DOI: https://doi.org/10.1007/s10533-024-01169-5). This study aims to investigate fundamental and transferable drivers of dissolved organic matter (DOM) diversity across five nested watersheds within the contiguous United States. DOM diversity was explored using ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). The samples and the unprocessed FTICR-MS data used in this study are publicly available on the Environmental System Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) data repository (see DOIs below). The data for the Willamette, Gunnison, Connecticut, and Deschutes basins were collected as part of a collaboration between the Watershed Rules of Life (WROL) project and Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS). The data for the Yakima River basin (YRB) was collected by the PNNL River Corridor SFA. The raw, unprocessed FTICR-MS data with additional (meta)data can be found at doi:10.15485/1895159 for WROL samples and doi:10.15485/1898912 for YRB samples. This data package contains the processed data used in the associated manuscript. This package also contains ancillary geospatial, hydrological, and geochemical information that supports the interpretation of the FTICR-MS data within Ryan et al., 2024. This data package is associated with the GitHub repository found at https://github.com/WHONDRS-Hub/rcsfa-RC4-WROL-YRB_DOM_Diversity. This data package was originally published August 2024. It was updated January 2025 (modified files). See the change history in the readme more details. At the directory level, the data package is comprised of three folders: (1) data, (2) output, and (3) src; and five additional files including the data dictionary (file ending in "_dd.csv”) and file-level metadata (file ending in “_flmd.csv”). The “src” folder contains the scripts used to process the FTICR data, conduct the analyses, and produce the manuscript figures. The inputs for these scripts are in the “data” folder and the returned outputs in the “output” folder. Inputs include temporal and spatial metadata associated with the sampling efforts, processed FTICR data, and total and normalized putative biochemical transformations per sample. Outputs include cleaned and combined data presented as tables, descriptive statistics, and plots. The file-level metadata file lists all files contained in this data package and descriptions for each. The data dictionary describes the units and definitions for each tabular data column or row header.

54 ENVIRONMENTAL SCIENCES↗

Hierarchical Linear Regression (Rev. 1)

We describe an algorithm for making inferences in a hierarchical linear model. The model allows different slopes and intercepts for different groups, and ties together the different slopes by representing them as samples from a higher level distribution. (The intercepts are treated as statistically independent.) Our model and code permit many options for the variance of this hierarchical distribution for the slopes, including gamma distributions on the precision, t-distributions on the standard error, pooled slopes (all equal), and independent slopes. The algorithm is described in the paper; an implementation of the algorithm in R is available on request.

97 MATHEMATICS AND COMPUTING↗

Escaping Events at the NOvA Far Detector

aThe NuMI Off-axis $\nu_e$ Appearance (NOvA) experiment studies neutrino oscillations in the NuMI (Neutrinos at the Main Injector) beam. The goal of the experiment is to determine the mass hierarchy and measure $\delta_{CP}$, however it is also sensitive to $\sin\theta_{23}$, and $\Delta m^2_{32}$. The present work tries to improve experimental sensitivity to the oscillation parameters by considering neutrino events which are discarded by the previous analysis - escaping events. The biggest issues with the escaping sample are significant cosmic background and correct energy estimation. Both issues were addressed and inclusion of escaping sample to the final fit led to an effective increase of statistics by 4% with best- fit measurements of $\sin\theta^2_{23} = 0.504$ and $\Delta m^2_{32} = 2.45 \times 10^{-3}$ eV$^2$.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Bayesian Optimal Sensor Augmentation Via Estimated Mutual Information

We consider the problem of designing a sensor network to most efficiently locate the source of a seismic event. The left panel of Figure 1 shows 982 possible sensor locations in a region of interest. The objective is to infer the unknown location of an earthquake, indicated by the gold dot for illustration purposes. Assume that three sensors have already been placed for data collection. Travel times of the P-wave from the source to the three sensors are observed and used to infer the unknown source location via a Bayesian statistical model described subsequently. The right panel of Figure 1 shows samples from the resulting posterior distribution for source location along with a posterior estimate of this location.

47 OTHER INSTRUMENTATION↗

Galaxy Clustering with LSST: Effects of Number Count Bias from Blending

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will survey the southern sky to create the largest galaxy catalog to date, and its statistical power demands an improved understanding of systematic effects such as source overlaps, also known as blending. In this work we study how blending introduces a bias in the number counts of galaxies (instead of the flux and colors), and how it propagates into galaxy clustering statistics. We use the 300 deg 2 DC2 image simulation and its resulting galaxy catalog (LSST Dark Energy Science Collaboration et al. 2021) to carry out this study. We find that, for a LSST Year 1 (Y1)-like cosmological analyses, the number count bias due to blending leads to small but statistically significant differences in mean redshift measurements when comparing an observed sample to an unblended calibration sample. In the two-point correlation function, blending causes differences greater than 3σ on scales below approximately 10', but large scales are unaffected. We fit Ω m and linear galaxy bias in a Bayesian cosmological analysis and find that the recovered parameters from this limited area sample, with the LSST Y1 scale cuts, are largely unaffected by blending. Our main results hold when considering photometric redshift and a LSST Year 5 (Y5)-like sample.

79 ASTRONOMY AND ASTROPHYSICS↗

Quantification of hydraulic trait control on plant hydrodynamics and risk of hydraulic failure within a demographic structured vegetation model in a tropical forest (FATES–HYDRO V1.0)

Abstract. Vegetation plays a key role in the global carbon cycle and thus is an important component within Earth system models (ESMs) that project future climate. Many ESMs are adopting methods to resolve plant size and ecosystem disturbance history, using vegetation demographic models. These models make it feasible to conduct more realistic simulation of processes that control vegetation dynamics. Meanwhile, increasing understanding of the processes governing plant water use, and ecosystem responses to drought in particular, has led to the adoption of dynamic plant water transport (i.e., hydrodynamic) schemes within ESMs. However, the extent to which variations in plant hydraulic traits affect both plant water stress and the risk of mortality in trait-diverse tropical forests is understudied. In this study, we report on a sensitivity analysis of an existing hydrodynamic scheme (HYDRO) model that is updated and incorporated into the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) (FATES–HYDRO V1.0). The size- and canopy-structured representation within FATES is able to simulate how plant size and hydraulic traits affect vegetation dynamics and carbon–water fluxes. To better understand this new model system, and its functionality in tropical forest systems in particular, we conducted a global parameter sensitivity analysis at Barro Colorado Island, Panama. We assembled 942 observations of plant hydraulic traits on 306 tropical plant species for stomata, leaves, stems, and roots and determined the best-fit statistical distribution for each trait, which was used in model parameter sampling to assess the parametric sensitivity. We showed that, for simulated leaf water potential and loss of hydraulic conductivity across different plant organs, the four most important traits were associated with xylem conduit taper (buffers increasing hydraulic resistance with tree height), stomatal sensitivity to leaf water potential, maximum stem hydraulic conductivity, and the partitioning of total hydraulic resistance above vs. belowground. Our analysis of individual ensemble members revealed that trees at a high risk of hydraulic failure and potential tree mortality generally have a lower conduit taper, lower maximum xylem conductivity, lower stomatal sensitivity to leaf water potential, and lower resistance to xylem embolism for stem and transporting roots. We expect that our results will provide guidance on future modeling studies using plant hydrodynamic models to predict the forest responses to droughts and future field campaigns that aim to better parameterize plant hydrodynamic models.

54 ENVIRONMENTAL SCIENCES↗

Computer simulation of Saturn 5 response to pre-launch wind loads

A digital computer program is described which was developed to estimate Saturn 5 response to prelaunch wind conditions at Cape Kennedy. The program computes displacement and bending moment statistics as a function of parameters defining the atmospheric environment. A sample problem is provided to illustrate utilization of the program.

Coffin, T.↗

The luminosity function of galactic X-ray sources - A cutoff and a 'standard candle'

Analysis of the 2- to 10-kev luminosity distribution of 36 X-ray sources in the Local Group having known or estimated distances, showing that there exists a luminosity cutoff of approximately 10 to the 37.7th ergs/sec in agreement with the theoretical (Eddington) limit for the luminosity of an approximately 1 solar mass star. Furthermore, among the complete sample of high-luminosity sources, there appears to be a statistically significant group of X-ray 'standard candles' at (within less than 0.8 mag) the critical luminosity. This finding (which is in agreement with the self-consistent mass flow accretion models) presents the possibility that X-ray sources may be used as extragalactic distance indicators in the next generation of X-ray astronomy experiments.

Margon, B.↗

The Apollo 16 microbial response to space environment experiment

The effect was evaluated of a particular space flight on the survival rate of nine different species. Although a reasonable variety of organisms (viruses, yeasts, filamentous fungi, bacteria, and an invertebrate) were tested under several different conditions, no statistically valid differences could be detected in the survival of flight samples when compared to corresponding ground-based controls. In general, these evaluations were based on multiple observations of from ten to thirty replicates of up to one million cells each. While the results conflict with those of certain other space flight investigations, it is observed that the conditions of a particular space flight cannot be exactly duplicated, and therefore results from different flights are not directly comparable.

Gerald R. Taylor↗

Crop identification and area estimation by computer-aided analysis of Landsat data

This report describes the results of a study involving the use of computer-aided analysis techniques applied to Landsat MSS data for identification and area estimation of winter wheat in Kansas and corn and soybeans in Indiana. Key elements of the approach included use of aerial photography for classifier training, stratification of Landsat data and extension of training statistics to areas without training data, and classification of a systematic sample of pixels from each county. Major results and conclusions are: (1) Landsat data was adequate for accurate identification and area estimation of winter wheat in Kansas, but corn and soybean estimates for Indiana were less accurate; (2) computer-aided analysis techniques can be effectively used to extract crop identification information from Landsat MSS data, and (3) systematic sampling of entire counties made possible by computer classification methods resulted in very precise area estimates at county as well as district and state levels.

Bauer, M. E.↗

The crop assessment subsystem: System implementation and approaches used for the generation of crop production reports

The primary responsibility of the crop assessment subsystem (CAS) during the three phases of LACIE was to produce crop reports that included estimates of wheat area, yield, and production, as well as a specified set of associated statistical descriptors. The operations of CAS are described with emphasis on sampling strategy, input/output data, evolution of aggregation/reporting system capabilities, and CAS aggregation procedures.

Mcallum, W. E.↗

A search for long-term periodicities in large earthquakes of southern and coastal central California

It has been occasionally suggested that large earthquakes may follow the 8.85-year and 18.6-year lunar-solar tidal cycles and possibly the approximately 11-year solar activity cycle. From a new study of earthquakes with magnitudes greater than 5.5 in southern and coastal central California during the years 1855-1983, it is concluded that, at least in this selected area of the world, no statistically significant long-term periodicities in earthquake frequency occur. The sample size used is about twice that used in comparable earlier studies of this region, which concentrated on large earthquakes.

Stothers, Richard B.↗

A radio continuum survey of edge-on spiral galaxies at 90 cm

Accurate spectral indices of the radio emission from both the thin disk and thick disk or halo components are critical to understanding the propagation mechanisms of electrons within spiral galaxies. The spectral indices give information of relative importance of diffusion and synchrotron energy loss in the propagation of electrons in the disk. Our goal of this survey is to locate a larger sample of spiral galaxies that exhibit halo phenomena so that a statistical analysis will be possible.

Heikkila, B.↗

Bias Reduction in Short Records of Satellite Soil Moisture

Although surface soil moisture data from different sources (satellite retrievals, ground measurements, and land model integrations of observed meteorological forcing data) have been shown to contain consistent and useful information in their seasonal cycle and anomaly signals, they typically exhibit very different mean values and variability. These biases pose a severe obstacle to exploiting the useful information contained in satellite retrievals through data assimilation. A simple method of bias removal is to match the cumulative distribution functions (cdf) of the satellite and model data. However, accurate cdf estimation typically requires a long record of satellite data. We demonstrate here that by wing spatial sampling with a 2 degree moving window we can obtain local statistics based on a one-year satellite record that are a good approximation to those that would be derived from a much longer time series. This result should increase the usefulness of relatively short satellite data records.

Reichle, Rolf H.↗

Bayesian Approach to the Joint Inversion of Gravity and Magnetic Data, with Application to the Ismenius Area of Mars

This viewgraph presentation reviews a Bayesian approach to the inversion of gravity and magnetic data with specific application to the Ismenius Area of Mars. Many inverse problems encountered in geophysics and planetary science are well known to be non-unique (i.e. inversion of gravity the density structure of a body). In hopes of reducing the non-uniqueness of solutions, there has been interest in the joint analysis of data. An example is the joint inversion of gravity and magnetic data, with the assumption that the same physical anomalies generate both the observed magnetic and gravitational anomalies. In this talk, we formulate the joint analysis of different types of data in a Bayesian framework and apply the formalism to the inference of the density and remanent magnetization structure for a local region in the Ismenius area of Mars. The Bayesian approach allows prior information or constraints in the solutions to be incorporated in the inversion, with the "best" solutions those whose forward predictions most closely match the data while remaining consistent with assumed constraints. The application of this framework to the inversion of gravity and magnetic data on Mars reveals two typical challenges - the forward predictions of the data have a linear dependence on some of the quantities of interest, and non-linear dependence on others (termed the "linear" and "non-linear" variables, respectively). For observations with Gaussian noise, a Bayesian approach to inversion for "linear" variables reduces to a linear filtering problem, with an explicitly computable "error" matrix. However, for models whose forward predictions have non-linear dependencies, inference is no longer given by such a simple linear problem, and moreover, the uncertainty in the solution is no longer completely specified by a computable "error matrix". It is therefore important to develop methods for sampling from the full Bayesian posterior to provide a complete and statistically consistent picture of model uncertainty, and what has been learned from observations. We will discuss advanced numerical techniques, including Monte Carlo Markov

data analysis↗

Parametric Cost Models for Space Telescopes

A study is in-process to develop a multivariable parametric cost model for space telescopes. Cost and engineering parametric data has been collected on 30 different space telescopes. Statistical correlations have been developed between 19 variables of 59 variables sampled. Single Variable and Multi-Variable Cost Estimating Relationships have been developed. Results are being published.

Stahl, H. Philip↗

Effects of Ionizing Radiation on Murine Gene Expression in Skin and Bone

Long duration spaceflight causes a negative calcium balance and reduces bone density in astronauts. The potential for exposure to space radiation to contribute to lasting decrements in bone mass is not yet understood. Sustained changes to bone mass have a relatively long latency for development, however skin is a radiation sensitive organ and changes in skin gene expression may serve as an early radiation biomarker of exposures and may correlate with adverse effects on skeletal tissue. Previous studies have shown that FGF18 gene expression levels of hair follicles collected from astronauts on the ISS rose over time. In the hair follicle, FGF18 signaling mediates radioresistance in the telogen by arresting the cell cycle, and FGF18 has the potential to function as a radioprotector. In bone, FGF18 appears to regulate cell proliferation and differentiation positively during osteogenesis and negatively during chondrogenesis. Cellular defense responses to radiation are shared by a variety of organs, hence in this study, we examined whether radiation induced gene expression changes in skin may be predictive of the responses of skeletal tissue to radiation exposure. We have examined oxidative stress and growth arrest pathways in mouse skin and long bones by measuring gene expression levels via quantitative polymerase chain reaction (qPCR) after exposure to total body irradiation (TBI). To investigate the effects of irradiation on gene expression, we used skin and femora (cortical shaft) from the following treatment groups: control (normally loaded, sham-irradiated), and TBI (0.5 Gy Fe-56 600 MeV/n and 0.5 Gy H-1 150 MeV/n). Animals were euthanized one and 11 days post-IR. Statistical analysis was performed via a Student's ttest. In skin samples one day after IR, skin expression of FGF18 was significantly greater (3.8X) than sham-irradiated controls (3.8X), but did not differ 11 days post TBI. Expression levels of other radiation related genes (Nfe2l2, Trp53, Cdkn1a, FoxO3, Gadd45g, SOD1), was not different due to TBI at either time point. In bone (femora) TBI significantly increased (3.8X) expression of the pro-bone resorption cytokine, MCP-1, one day after TBI. FGF18 expression in skin and MCP- 1 expression in bone were found to be positively correlated (P less than 0.002, r=0.8779). Further, microcomputed tomography analysis of tibae from these animals showed reduced fractional cancellous bone volume (-21.7%) at 11 days post exposure. These results suggest that early radiation induced changes in FGF18 gene expression in skin may have value for predicting subsequent loss of cancellous bone mass.

space radiation↗