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NASA NTRS2023

Impacts of Marine Surface Pressure Observations From A Spaceborne Differential Absorption Radar Investigated With an Observing System Simulation Experiment

A new instrument has been proposed for measuring surface air pressure over the marine surface with a combined active/passive scanning multi-channel differential absorption radar (DAR) to provide an estimate of the total atmospheric column oxygen content. A demonstrator instrument, the Microwave Barometric Radar and Sounder (MBARS), has been funded by the National Aeronautics and Space Administration (NASA) for airborne test missions. Here, a proof-of-concept study to evaluate the potential impact of spaceborne surface pressure data on numerical weather prediction is performed using the Goddard Modeling and Assimilation Office global observing system simulation experiment (OSSE) framework. This OSSE framework employs the Goddard Earth Observing System model and the hybrid 4D ensemble variational Gridpoint Statistical Interpolation data assimilation system. Multiple flight and scanning configurations of potential spaceborne orbits are examined. Swath width and observation spacing for the surface pressure data are varied to explore a range of sampling strategies. For wider swaths, the addition of surface pressures reduces the root mean square surface pressure analysis error by as much as 20% over some ocean regions. The forecast sensitivity observation impact tool estimates impacts on the Pacific Ocean basin boundary layer 24-hour forecast temperatures for spaceborne surface pressures on par with rawinsondes and aircraft, and greater impacts than the current network of ships and buoys. The largest forecast impacts are found in the southern hemisphere extratropics.

N.C. Privé↗

DOE OSTI2022

CMB/kSZ and Compton-y Maps from 2500 deg 2 of SPT-SZ and Planck Survey Data

Abstract We present component-separated maps of the primary cosmic microwave background/kinematic Sunyaev–Zel’dovich (SZ) amplitude and the thermal SZ Compton- y parameter, created using data from the South Pole Telescope (SPT) and the Planck satellite. These maps, which cover the ∼2500 deg 2 of the southern sky imaged by the SPT-SZ survey, represent a significant improvement over previous such products available in this region by virtue of their higher angular resolution ( 1 .′ 25 for our highest-resolution Compton- y maps) and lower noise at small angular scales. In this work we detail the construction of these maps using linear combination techniques, including our method for limiting the correlation of our lowest-noise Compton- y map products with the cosmic infrared background. We perform a range of validation tests on these data products to test our sky modeling and combination algorithms, and we find good performance in all of these tests. Recognizing the potential utility of these data products for a wide range of astrophysical and cosmological analyses, including studies of the gas properties of galaxies, groups, and clusters, we make these products publicly available at http://pole.uchicago.edu/public/data/sptsz_ymap and on the NASA/LAMBDA website.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1954

Summary of Free-flight Performance of a Series of Ram-jet Engines at Mach Numbers from 0.80 to 2.20

Data obtained from the NACA air-launched ram-jet program are summarized with emphasis placed upon the transonic propulsive thrust potential of the engines. Data are presented for boosted and non-boosted engine configurations which incorporate a single-oblique-shock or double-oblique-shock diffuser designed for critical inlet operation at flight Mach numbers of 1.8 and 2.4, respectively. The engines are evaluated in terms of flight Mach number, mass-flow ratio, diffuser pressure recovery, combustion-chamber heat release, propulsive thrust, external drag, and specific impulse. From specific impulse considerations, it appears that for some air-launched missile applications the self-accelerating supersonic ram jet may have a lower gross weight than a rocket-boosted ram jet.

RESEARCH EQUIPMENT, FREE-FLIGHT↗

NASA NTRS2003

Water Ice Clouds in the Martian Atmosphere: A Comparison of Two Methods

To date, the only two data sets offer the potential to examine year-to-year changes in cloud features over an entire Martian year: the Viking Infrared Thermal Mapper (IRTM) data set and the Mars Global Surveyor (MGS) Thermal Emission Spectrometer (TES) data set. We have examined the TES data in the same way in which we examined the Viking IRTM data. This provides water-ice cloud information separated in time by 12 Martian years. Since the data are analyzed with the same method, we obtain a very accurate 'apples to apples' comparison, and can generate a historical record of the subtleties of this annual event. Consequently, it is desirable to compare their results to ours to see what differences exist.

Hale, A. S.↗

NASA NTRS2021

Application of Gaussian Mixture Regression for the Correction of Low Cost PM2.5 Monitoring Data in Accra, Ghana

Low-cost sensors (LCSs) for air quality monitoring have enormous potential to improve air quality data coverage in resource-limited parts of the world such as sub-Saharan Africa. LCSs, however, are affected by environment and source conditions. To establish high-quality data, LCSs must be collocated and calibrated with reference grade PM2.5 monitors. From March 2020, a low-cost PurpleAir PM2.5 monitor was collocated with a Met One Beta Attenuation Monitor 1020 in Accra, Ghana. While previous studies have shown that multiple linear regression (MLR) and random forest regression (RF) can improve accuracy and correlation between PurpleAir and reference data, MLR and RF yielded suboptimal improvement in the Accra collocation (R2 = 0.81 and R2 = 0.81, respectively). We present the first application of Gaussian mixture regression (GMR) to air quality data calibration and demonstrate improvement over traditional methods by increasing the collocated PM2.5 correlation and accuracy to R2 = 0.88 and MAE = 2.2 μg/cu. m. Gaussian mixture models (GMMs) are a probability density estimator and clustering method from which nonlinear regressions that tolerate missing inputs can be derived. We find that even when given missing inputs, GMR provides better correlation than MLR and RF performed with complete data. GMR also allows us to estimate calibration certainty. When evaluated, 95% confidence intervals agreed with reference PM2.5 data 96% of the time, suggesting that the model accurately assesses its own confidence. Additionally, clustering within the GMM is consistent with climate characteristics, providing confidence that the calibration approach can learn underlying relationships in data.

Sensors↗

DOE OSTI2017

Convolutional Neural Networks Applied to Neutrino Events in a Liquid Argon Time Projection Chamber

We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identifi-cation or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level.

Acciarri, R↗

DOE OSTI2015

Tungsten-induced carcinogenesis in human bronchial epithelial cells

Metals such as arsenic, cadmium, beryllium, and nickel are known human carcinogens; however, other transition metals, such as tungsten (W), remain relatively uninvestigated with regard to their potential carcinogenic activity. Tungsten production for industrial and military applications has almost doubled over the past decade and continues to increase. Here, for the first time, we demonstrate tungsten's ability to induce carcinogenic related endpoints including cell transformation, increased migration, xenograft growth in nude mice, and the activation of multiple cancer-related pathways in transformed clones as determined by RNA sequencing. Human bronchial epithelial cell line (Beas-2B) exposed to tungsten developed carcinogenic properties. In a soft agar assay, tungsten-treated cells formed more colonies than controls and the tungsten-transformed clones formed tumors in nude mice. RNA-sequencing data revealed that the tungsten-transformed clones altered the expression of many cancer-associated genes when compared to control clones. Genes involved in lung cancer, leukemia, and general cancer genes were deregulated by tungsten. Taken together, our data show the carcinogenic potential of tungsten. Further tests are needed, including in vivo and human studies, in order to validate tungsten as a carcinogen to humans. - Highlights: • Tungsten (W) induces cell transformation and increases migration in vitro. • W increases xenograft growth in nude mice. • W altered the expression of cancer-related genes such as those involved in leukemia. • Some of the dysregulated leukemia genes include, CD74, CTGF, MST4, and HOXB5. • For the first time, data is presented that demonstrates tungsten's carcinogenic potential.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

Size Dependence of the Melting Point of Silicon Nanoparticles: Molecular Dynamics and Thermodynamic Simulation

The size dependence of the melting point of Si nanoparticles is investigated using molecular dynamics and thermodynamic simulation based on the Thomson’s formula. The atomistic modeling data obtained using the Stillinger–Weber potential agree with the results reported by other authors and thermodynamic-simulation data and predict a decrease in the melting point T{sub m} of Si nanoparticles with an increase in their reciprocal radius R{sup –1} according to linear law. The available experimental data predict lower T{sub m} values, including the limiting value T{sub m}{sup (∞)}, which corresponds to the linear extrapolation of experimental points to R{sup –1} → 0 (to the radius R → ∞); the underestimation is 200–300 K as compared with the reference melting point of silicon (1688 K). It is concluded that the molecular-dynamics data on T{sub m}(R{sup –1}) obtained using the Stillinger–Weber potential are more adequate than the available experimental data.

74 ATOMIC AND MOLECULAR PHYSICS↗

NASA NTRS1980

Monthly and seasonal occurrences of potential flash flood-producing rains determined from Manually Digitized Radar data

An analysis is conducted of a small 4-year climatological data base of Manually Digitized Radar (MDR) data to infer the monthly and seasonal distributions of the relative frequency of occurrence of potential flash flood-producing rains over the Central and Eastern U.S. Some possible meteorological mechanisms for producing potential flash flooding rains are discussed in terms of the relative maxima and minima in the monthly and seasonal frequency distributions over the MDR network. Frequencies were found to be generally higher in more southern locations and lower farther north in all months and seasons. However, most locations experienced an annual cycle in the frequency of occurrence with maxima in summer and minima in winter. In given seasons and months, local areas of maximum and minimum occurrences may be related to quasi-stationary meteorological processes that trigger and organize intense convection over a common area.

Wilson, G. S.↗

DOE OSTI2016

Spectrum and Structure of Excited Baryons with CLAS*

In this contribution I discuss recent results in light quark baryon spectroscopy involving CLAS data and higher level analysis results from the partial wave analysis by the Bonn-Gatchina group. New baryon states were discovered largely based on the open strangeness production channels gamma p --> K^+Lambda and gamma p --> K^+Sigma^0. The data illustrate the great potential of the kaon-hyperon channel in the discovery of higher mass baryon resonances in s-channel production. Other channels with discovery potential, such as gamma p --> p omega and gamma p --> phi p are also discussed. In the second part I will demonstrate on data the sensitivity of meson electroproduction to expose the active degrees of freedom underlying resonance transitions as a function of the probed distance scale. For several of the prominent excited states in the lower mass range the short distance behavior is described by a core of three dressed-quarks with running quark mass, and meson-baryon contributions make up significant parts of the excitation strength at large distances. Finally, I give an outlook of baryon resonance physics at the 12 GeV CEBAF electron accelerator.

Burkert, Volker D.↗

DOE OSTI2022

Developing Novel Performance Measures for Traffic Congestion Management and Operational Planning Based on Connected Vehicle Data

In this study, the authors present their efforts in exploring a new type of traffic data, referred to as internet-connected vehicle (ICV) data, for traffic congestion management and operational planning. Most currently manufactured vehicles contain onboard GPS and cellular modules, and they constantly connect to automobile manufacturers' clouds via cellular networks and upload their status. Some automobile manufacturers have recently redistributed the nonpersonal part of such data, such as geolocation, to third-party organizations for innovative applications. Compared with the traditional vehicle GPS data, the ICV data contain high-resolution GPS waypoints accompanied with the vehicles' abnormal moving events (e.g., hard braking). The ICV data also have huge potential in congestion management and operational planning. They explore to identify and analyze traffic congestion on both freeways and arterials using the ICV data. The ICV data adopted for this research are redistributed by Wejo Data Service, representing 10%-15% of all moving vehicles in the Dallas-Fort Worth (DFW) area in Texas. Through one case study for a freeway segment and one for an arterial segment, new traffic performance metrics based on the characteristics of ICV data have been presented. The highlights of these efforts are as follows: (I) queue length and propagation at freeway bottlenecks can be directly measured based on where and when most internet-connected vehicles slow down and join the queue; (II) an internet-connected vehicle's actual delay time on arterials can be directly measured according to its slow movement percentage, without assuming the nondelay travel speed; and (III) the ICV data set are also combined with the high-resolution traffic signal events to generate a ground-truth time-space diagram (TSD) on arterials - a common visualization of arterial signal performance for transportation planning and operations.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2025

miss-SNF: a multimodal patient similarity network integration approach to handle completely missing data sources

Abstract Motivation Precision medicine leverages patient-specific multimodal data to improve prevention, diagnosis, prognosis, and treatment of diseases. Advancing precision medicine requires the non-trivial integration of complex, heterogeneous, and potentially high-dimensional data sources, such as multi-omics and clinical data. In the literature, several approaches have been proposed to manage missing data, but are usually limited to the recovery of subsets of features for a subset of patients. A largely overlooked problem is the integration of multiple sources of data when one or more of them are completely missing for a subset of patients, a relatively common condition in clinical practice. Results We propose miss-Similarity Network Fusion (miss-SNF), a novel general-purpose data integration approach designed to manage completely missing data in the context of patient similarity networks. miss-SNF integrates incomplete unimodal patient similarity networks by leveraging a non-linear message-passing strategy borrowed from the SNF algorithm. miss-SNF is able to recover missing patient similarities and is “task agnostic”, in the sense that can integrate partial data for both unsupervised and supervised prediction tasks. Experimental analyses on nine cancer datasets from The Cancer Genome Atlas (TCGA) demonstrate that miss-SNF achieves state-of-the-art results in recovering similarities and in identifying patients subgroups enriched in clinically relevant variables and having differential survival. Moreover, amputation experiments show that miss-SNF supervised prediction of cancer clinical outcomes and Alzheimer’s disease diagnosis with completely missing data achieves results comparable to those obtained when all the data are available. Availability and implementation miss-SNF code, implemented in R, is available at https://github.com/AnacletoLAB/missSNF.

Biochemistry & Molecular Biology↗

DOE OSTI2020

Understanding Impacts of Data Integrity Attacks on Transactive Control Systems

With the rapid growth of internet-connected smart devices capable of exchanging energy price information and adaptively controlling energy consumption of connected loads, the role of transactive control is expected to become more prominent in the modern grid. Transactive control systems integrate the wholesale and retail energy markets, and enable active participation of end users, thereby playing a key role in managing the rising number of distributed assets in the smart grid. The use of internet for the communication of data between the controllers at the building, distribution, and transmission levels makes the system susceptible to cyber-attacks. A skilled adversary can potentially manipulate the exchanged data with the intention of inflicting damage to the system. In this paper, four categories of metrics are put forth for evaluating the performance of the system when under data integrity attacks. A model for scaling-based data integrity attack has been described, and co-simulations have been performed on a 240 bus WECC transmission system model with detailed modeling of distribution systems at specific buses. Our results show that scaling-based data integrity attacks can have non-trivial impacts on the operational, financial, and comfort aspects of the transactive control system.

Smart grid, transactive control system, Buildings-↗

NASA NTRS1985

Early Results of Investigations of LANDSAT 4 Thematic Mapper and Multispectral Scanner Applications

The TM digital data were evaluated for their potential to provide improved land cover information. The analyses included: (1) testing for information that may be offered by the new TM spectral bands, and (2) comparing data characteristics for equivalent spectral bands of the TM and MSS sensors. The analyses were conducted on several large samples of pixels corresponding to five broad land cover classes. Some TM spectral data are presented and evaluated as single-band, black-and-white images, and in several three-band color-composite images. Some data transformations which can be used to present TM data in a manner that is potentially more useful for analysis or display are demonstrated. These transformations enable generating hue, intensity, and saturation data space from red, green, and blue color space, as well as perspective view images.

Sadowski, F. G.↗

DOE OSTI2023

RNAseq analysis of Cellvibrio japonicus during starch utilization differentiates between genes encoding carbohydrate active enzymes controlled by substrate detection or growth rate

ABSTRACT Bacterial utilization of starch is increasingly of interest as the importance and contributions of animal gut microbiomes become more defined. Consequently, identifying and characterizing the bacterial enzymes responsible for the degradation, transport, and metabolism of starch will enable developments in pharmaceutical, biotechnological, and culinary industries searching for novel prebiotics, carrier molecules, and low glycemic index sweeteners. The current challenge is that bacteria proficient at starch utilization often have hundreds of carbohydrate active enzymes, and it is unclear which are essential for starch utilization using only homology-based bioinformatics or computational methods. Complementary experimental data are also needed, especially to understand the regulation of bacterial starch utilization. We have completed an RNAseq analysis of the Gram-negative bacterium Cellvibrio japonicus and found that it has sophisticated regulation that includes substrate sensing and growth rate components for genes that encode starch-degrading enzymes. Among the 22 genes predicted to encode starch-active enzymes, C. japonicus has 10 alpha-amylases, 4 alpha-glucosidases, 2 pullulnases, and 2 cyclomaltodextrin glucanotransferases, 15 of which were up-regulated during exponential growth on starch and 8 up-regulated in stationary phase. Growth analyses with an enzyme secretion deficient mutant of C. japonicus suggested that secreted amylases are essential for this bacterium to degrade starch. Our approach of coupling a physiological growth assay with transcriptomic data provides a platform to identify targets for further genetic or biochemical analysis that can be broadly applied to other starch-utilizing bacteria. IMPORTANCE Understanding the bacterial metabolism of starch is important as this polysaccharide is a ubiquitous ingredient in foods, supplements, and medicines, all of which influence gut microbiome composition and health. Our RNAseq and growth data set provides a valuable resource to those who want to better understand the regulation of starch utilization in Gram-negative bacteria. These data are also useful as they provide an example of how to approach studying a starch-utilizing bacterium that has many putative amylases by coupling transcriptomic data with growth assays to overcome the potential challenges of functional redundancy. The RNAseq data can also be used as a part of larger meta-analyses to compare how C. japonicus regulates carbohydrate active enzymes, or how this bacterium compares to gut microbiome constituents in terms of starch utilization potential.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2003

In Situ Raman Microscopy of a Single Graphite Microflake Electrode in a Li(+)-containing Electrolyte

Highly detailed Raman spectra from a single KS-44 graphite microflake electrode as a function of the applied potential have been collected in situ using a Raman microscope and a sealed spectroelectrochemical cell isolated from the laboratory environment. Correlations were found between the Raman spectral features and the various Li(+) intercalation stages while recording in real time Raman spectra during a linear potential scan from 0.7 down ca. 0.0V vs Li/Li(+) at a rate of 0.1 mV/s in a 1M LiClO4 solution in a 1:l (by volume) ethylene carbonate (EC):diethyl carbonate (DEC) mixture. In particular, clearly defined isosbestic points were observed for data collected in the potential range where the transition between dilute phase 1 and phase 4 of lithiated graphite is known to occur, i.e. 0.157 < E < 0.215 vs Li/Li(+). Statistical analysis of the spectroscopic data within this region made it possible to determine independently the fraction of each of the two phases present as a function of potential without relying on coulometric information and then predict, based on the proposed stoichiometry for the transition, a spectrally-derived voltammetric feature.

Shi, Qing-Fang↗

NASA NTRS1991

An investigation of the distribution of eruptive products on the shield volcanoes of the western Galapagos Islands using remotely sensed data

Recent volcanic activity in the Galapagos Islands is concentrated on the two westernmost islands, Isla Isabela and Isla Fernandina. Difficult access has thus far prevented comprehensive geological field studies, so we examine the potential of remotely sensed data as a means of studying volcanic processes in the region. Volcan Wolf is used as an example of the analysis of SPOT HRV-1 data undertaken for each volcano. Landsat TM data are analyzed in an attempt to construct a relative age sequence for the recent eruptive activity on Isla Fernandina. No systematic variation in the surface reflectance of lava flows as a function of age could be detected with these data. Thus it was not possible to complete a study of the temporal distribution of volcanic activity.

Munro, Duncan C.↗

DOE OSTI2023

Uncertainty-driven dynamics for active learning of interatomic potentials

Machine learning (ML) models, if trained to data sets of high-fidelity quantum simulations, produce accurate and efficient interatomic potentials. Active learning (AL) is a powerful tool to iteratively generate diverse data sets. In this approach, the ML model provides an uncertainty estimate along with its prediction for each new atomic configuration. If the uncertainty estimate passes a certain threshold, then the configuration is included in the data set. Here we develop a strategy to more rapidly discover configurations that meaningfully augment the training data set. The approach, uncertainty-driven dynamics for active learning (UDD-AL), modifies the potential energy surface used in molecular dynamics simulations to favor regions of configuration space for which there is large model uncertainty. The performance of UDD-AL is demonstrated for two AL tasks: sampling the conformational space of glycine and sampling the promotion of proton transfer in acetylacetone. The method is shown to efficiently explore the chemically relevant configuration space, which may be inaccessible using regular dynamical sampling at target temperature conditions.

97 MATHEMATICS AND COMPUTING↗