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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Star formation characteristics of CNN-identified post-mergers in the Ultraviolet Near Infrared Optical Northern Survey (UNIONS)

ABSTRACT The importance of the post-merger epoch in galaxy evolution has been well documented, but post-mergers are notoriously difficult to identify. While the features induced by mergers can sometimes be distinctive, they are frequently missed by visual inspection. In addition, visual classification efforts are highly inefficient because of the inherent rarity of post-mergers (~1 per cent in the low-redshift Universe), and non-parametric statistical merger selection methods do not account for the diversity of post-mergers or the environments in which they appear. To address these issues, we deploy a convolutional neural network (CNN) that has been trained and evaluated on realistic mock observations of simulated galaxies from the IllustrisTNG simulations, to galaxy images from the Canada France Imaging Survey, which is part of the Ultraviolet Near Infrared Optical Northern Survey. We present the characteristics of the galaxies with the highest CNN-predicted post-merger certainties, as well as a visually confirmed subset of 699 post-mergers. We find that post-mergers with high CNN merger probabilities [p(x) > 0.8] have an average star formation rate that is 0.1 dex higher than a mass- and redshift-matched control sample. The SFR enhancement is even greater in the visually confirmed post-merger sample, a factor of 2 higher than the control sample.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Predicting rare events using neural networks and short-trajectory data

Estimating the likelihood, timing, and nature of events is a major goal of modeling stochastic dynamical systems. When the event is rare in comparison with the timescales of simulation and/or measurement needed to resolve the elemental dynamics, accurate prediction from direct observations becomes challenging. In such cases a more effective approach is to cast statistics of interest as solutions to Feynman-Kac equations (partial differential equations). Here, we develop an approach to solve Feynman-Kac equations by training neural networks on short-trajectory data. Our approach is based on a Markov approximation but otherwise avoids assumptions about the underlying model and dynamics. This makes it applicable to treating complex computational models and observational data. Additionally, we illustrate the advantages of our method using a low-dimensional model that facilitates visualization, and this analysis motivates an adaptive sampling strategy that allows on-the-fly identification of and addition of data to regions important for predicting the statistics of interest. Finally, we demonstrate that we can compute accurate statistics for a 75-dimensional model of sudden stratospheric warming. This system provides a stringent test bed for our method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Three-dimensional imaging of grain boundaries via quantitative fluorescence X-ray tomography analysis

Abstract Three-dimensional visualization of material composition within multiple grains and across complex networks of grain boundaries at nanoscales can provide new insight into the structure evolution and emerging functional properties of the material for diverse applications. Here, using nanoscale scanning X-ray fluorescence tomography, coupled with an advanced self-absorption correction algorithm developed in this work, we analyze the three-dimensional gain distributions and compositions in a Ce 0.8 Gd 0.2 O 2-δ -CoFe 2 O 4 mixed ionic-electronic conductor system with high accuracy and statistical significance. Our systematic investigation reveals an additional emergent phase and uncovers highly intriguing composition stability ranges for the multiple material phases within this system. The presented visualization of composition variations across complex interfaces, supported by our quantitative composition analysis, discloses mechanistic pathways of the diverse phase transformations occurring in the material synthesis, providing insights for the optimization of transport properties in the mixed ionic-electronic conductor system.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Large-eddy simulation of helical- and straight-bladed vertical-axis wind turbines in boundary layer turbulence

Here, turbulent wake flows behind helical- and straight-bladed vertical axis wind turbines (VAWTs) in boundary layer turbulence are numerically studied using the large-eddy simulation (LES) method combined with the actuator line model. Based on the LES data, systematic statistical analyses are performed to explore the effects of blade geometry on the characteristics of the turbine wake. The time-averaged velocity fields show that the helical-bladed VAWT generates a mean vertical velocity along the center of the turbine wake, which causes a vertical inclination of the turbine wake and alters the vertical gradient of the mean streamwise velocity. Consequently, the intensities of the turbulent fluctuations and Reynolds shear stresses are also affected by the helical-shaped blades when compared with those in the straight-bladed VAWT case. The LES results also show that reversing the twist direction of the helical-bladed VAWT causes the spatial patterns of the turbulent wake flow statistics to be reversed in the vertical direction. Moreover, the mass and kinetic energy transports in the turbine wakes are directly visualized using the transport tube method, and the comparison between the helical- and straight-bladed VAWT cases show significant differences in the downstream evolution of the transport tubes.

17 WIND ENERGY↗
DOE OSTI2016

Development of a mobile toolmark characterization/comparison system [Development of a mobile, automated toolmark characterization/comparison system]

Since the development of the striagraph, various attempts have been made to enhance forensic investigation through the use of measuring and imaging equipment. This study describes the development of a prototype system employing an easy-to-use software interface designed to provide forensic examiners with the ability to measure topography of a toolmarked surface and then conduct various comparisons using a statistical algorithm. Acquisition of the data is carried out using a portable 3D optical profilometer, and comparison of the resulting data files is made using software named “MANTIS” (Mark and Tool Inspection Suite). The system has been tested on laboratory-produced markings that include fully striated marks (e.g., screwdriver markings), quasistriated markings produced by shear-cut pliers, impression marks left by chisels, rifling marks on bullets, and cut marks produced by knives. Using the system, an examiner has the potential to (i) visually compare two toolmarked surfaces in a manner similar to a comparison microscope and (ii) use the quantitative information embedded within the acquired data to obtain an objective statistical comparison of the data files. Finally, this study shows that, based on the results from laboratory samples, the system has great potential for aiding examiners in conducting comparisons of toolmarks.

47 OTHER INSTRUMENTATION↗
NASA NTRS1984

LANDSAT 4 investigations of Thematic Mapper and multispectral scanner applications

The optimum index factor package was used to choose TM band for color compositing. Processing techniques were also used on TM data over several sites to: (1) reduce the amount of data that needs to be processed and analyzed by using statistical methods or by combining full-resolution products with spatially compressed products; (2) digitally process small subareas to improve the visual appearance of large-scale products or to merge different-resolution image data; and (3) evaluate and compare the information content of the different three-band combinations that can be made using the TM data. Results indicate that for some applications the added spectral information over MSS is even more important than the TM's increased spatial resolution.

Lauer, D. T.↗
NASA NTRS2020

Airborne Weather Radar Observations & Analysis Results from the 2014/2015 HAIC Flight Campaigns

This document presents a summary of the airborne weather radar observations made during joint EU/US flight campaigns to study High Altitude Ice Crystal (HAIC) atmospheric conditions. These flight campaigns were conducted near Darwin, Australia and Cayenne, French Guiana in 2014 and 2015, respectively. A variety of analyses were conducted resulting in statistical descriptions of the radar reflectivities of HAIC encountered during storm penetrations. These results are presented along with a set of visualization tools that aided flight operations and post-flight assessments. A summary of HAIC radar reflectivities observed during these flight campaigns corroborates reports by commercial pilots during HAIC encounters.

Radar↗
DOE OSTI2023

Reevaluating Contour Visualizations for Power Systems Data

Effective visual analytics tools are needed now more than ever as emerging energy systems data and models are rapidly growing in scale and complexity. Here we examined the suitability of colored contour maps to visually represent bus values in two different power system models: a dense 24k-bus distribution system and a 240-bus transmission system. In a quantitative analysis, we found that contour maps misrepresent power systems data, changing the statistical dispersion of the bus values, including the loss of extreme values. In a controlled empirical study with thirty professional power system research engineers, we found that these distortions significantly impact excursion identification tasks. Additionally, the engineers were less confident in their assessments using contour-based visualizations than glyph-based visualizations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1984

Reaction times to weak test lights

Maloney and Wandell (1984) describe a model of the response of a single visual channel to weak test lights. The initial channel response is a linearly filtered version of the stimulus. The filter output is randomly sampled over time. Each time a sample occurs there is some probability increasing with the magnitude of the sampled response - that a discrete detection event is generated. Maloney and Wandell derive the statistics of the detection events. In this paper a test is conducted of the hypothesis that the reaction time responses to the presence of a weak test light are initiated at the first detection event. This makes it possible to extend the application of the model to lights that are slightly above threshold, but still within the linear operating range of the visual system. A parameter-free prediction of the model proposed by Maloney and Wandell for lights detected by this statistic is tested. The data are in agreement with the prediction.

Wandell, B. A.↗
NASA NTRS2015

Informal Statistics Help Desk

Back by popular demand, the JSC Biostatistics Lab is offering an opportunity for informal conversation about challenges you may have encountered with issues of experimental design, analysis, data visualization or related topics. Get answers to common questions about sample size, repeated measures, violation of distributional assumptions, missing data, multiple testing, time-to-event data, when to trust the results of your analyses (reproducibility issues) and more.

Ploutz-Snyder, R. J.↗
DOE OSTI2018

A Visual Atlas on Strategic Trade

Strategic trade concerns global trade flows of items with strategic military value. Items include goods with exclusive military use, but also dual-use items that can have both military and civil uses. Many countries require licenses for trade in strategic items as a measure of non-proliferation. For example, items listed for trade control by multilateral export control arrangements, such as the Nuclear Suppliers Group (NSG), typically are considered strategic goods. Analysts and officials involved in strategic trade control often lack quantitative global understanding of relevant trade patterns that would help them focus control and enforcement efforts, select companies for outreach and audit, target transactions for verification and inspection, and assess the potential economic impact of trade control policies. Many are unaware of available open source data on international trade that can inform these issues. Many do not know how to make use of such data or lack the tools necessary to do so. A book of charts dubbed a ‘Strategic Trade Atlas’ was developed to illustrate global trade flows of strategic goods and raise awareness of the availability and utility of open source trade data. The Atlas was prepared for the World Customs Organization (WCO) and its Member States to support their planning and execution of Strategic Trade Control Enforcement (STCE) operations. It offers macroscopic graphical representations of global trade flows classified under Harmonized System (HS) codes associated by the WCO with commodities described in its STCE Implementation Guide. While these HS codes are understood to also encompass many non-strategic items, they nevertheless provide a good overview of potentially strategic trade flows. These include HS codes covering nuclear and nuclear-related commodities listed by the NSG, such as uranium, heavy water, graphite, carbon fiber, nickel powder, beryllium, aluminum tubes, vacuum pumps, valves, machine tools, cameras, and many others. The Atlas uses trade data from the Base pour l’Analyse du Commerce International (BACI), a statistical elaboration of public UN Comtrade data. BACI data reconciles trade flows, taking into account asymmetries in import and export trade valuation. The data visualization approach facilitates rapid sense making, pattern recognition, and anomaly detection. Country-based profiles summarize vast amounts of data into readily understandable graphical representations of each country’s primary strategic imports and exports and their main trading partners. Commodity-based profiles provide a global view of major exporters, importers, and trade patterns for each commodity. These insights can inform the risk management approach employed by customs to allocate enforcement and compliance efforts.

customs controls↗
DOE OSTI2023

Alternatives to Contour Visualizations for Power Systems Data

Electrical grids are geographical and topological structures whose voltage states are challenging to represent accurately and efficiently for visual analysis. The current common practice is to use colored contour maps, yet these can misrepresent the data. We examine the suitability of four alternative visualization methods for depicting voltage data in a geographically dense distribution system-Voronoi polygons, H3 tessellations, S2 tessellations, and a network-weighted contour map. We find that Voronoi tessellations and network-weighted contour maps more accurately represent the statistical distribution of the data than regular contour maps.

MATHEMATICS AND COMPUTING↗
DOE OSTI2014

A statistical approach for detection of anatomical change - Paper 115

The purpose of this study was to develop a novel statistics-based method for automated detection of anatomical changes using cone-beam CT (CBCT) images of head and neck (H and N) patients. Vendor supplied CBCT software provides the user with the basic tools that allow for the visual assessment of the co-registration of the reference CT data and daily CBCT images. Currently there is no commercially available CBCT software that is capable of detecting anatomical changes and giving the clinician an early alert for the treatment plan adaptation. An algorithm was developed that can detect statistically significant changes at a given confidence level for H and N patients. This tool provides a reliable and automated early warning system that enables a 'just-in-time' adaptation of the treatment plan. A method was developed for automated detection of anatomical changes in H and N patients under radiation therapy treatment. The method utilized imaging CT data along with daily CBCT images to quantitatively compare the patient anatomy against the reference CT imaging data. The comparison algorithm was developed using a statistics-based approach as opposed to threshold-based methods. The algorithm allows for reliable detection of statistically significant changes in the observed patient anatomy at a given level of confidence. The method can be employed as an integral part of the adaptive radiotherapy framework. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2018

Application of multiplexed ion mobility spectrometry towards the identification of host protein signatures of treatment effect in pulmonary tuberculosis

Rationale: The monitoring of TB treatments in clinical practice and clinical trials relies on traditional sputum-based culture status indicators at specific time points. Accurate, predictive, blood-based protein markers would provide a simpler and more informative view of patient health and response to treatment. Objective: We utilized sensitive, high throughput multiplexed ion mobility-mass spectrometry (IM-MS) to characterize the serum proteome of TB patients at the start of and at 8 weeks of rifamycin-based treatment. We sought to identify treatment specific signatures within patients as well as correlate the proteome signatures to various clinical markers of treatment efficacy. Methods: Serum samples were collected from 289 subjects enrolled in CDC TB Trials Consortium Study 29 at time of enrollment and at the end of the intensive phase (after 40 doses of TB treatment). Serum proteins were immunoafinity-depleted of high abundant components, digested to peptides and analyzed for data acquisition utilizing a unique liquid chromatography IM-MS platform (LC-IM-MS). Linear mixed models were utilized to identify serum protein changes in the host response to antibiotic treatment as well as correlations with culture status end points. Results: A total of 10,137 peptides corresponding to 872 proteins were identified, quantified, and used for statistical analysis across the longitudinal patient cohort. In response to TB treatment, 244 proteins were sig- ni?cantly altered. Pathway/network comparisons helped visualize the interconnected proteins, identifying up regulated (lipid transport, coagulation cascade, endopeptidase activity) and down regulated (acute phase) processes and pathways in addition to other cross regulated networks (inflammation, cell adhesion, extracellular matrix). Detection of possible lung injury serum proteins such as HPSE, significantly downregulated upon treatment. Analyses of microbiologic data over time identified a core set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2) which change in response to treatment and also strongly correlate with culture status. A similar set of proteins at baseline were found to be predictive of week 6 and 8 culture status. Conclusion: A comprehensive host serum protein dataset reflective of TB treatment effect is defined. A repeating set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2, among others) were found to change significantly in response to treatment, to strongly correlate with culture status, and at baseline to be predictive of future culture conversion. If validated in cohorts with long term follow-up to capture failure and relapse of TB, these protein markers could be developed for monitoring of treatment in clinical trials and in patient care.

Kedia, Komal↗
DOE OSTI2017

Scaling up to address data science challenges

Statistics and Data Science provide a variety of perspectives and technical approaches for exploring and understanding Big Data. Partnerships between scientists from different fields such as statistics, machine learning, computer science, and applied mathematics can lead to innovative approaches for addressing problems involving increasingly large amounts of data in a rigorous and effective manner that takes advantage of advances in computing. Here, this article will explore various challenges in Data Science and will highlight statistical approaches that can facilitate analysis of large-scale data including sampling and data reduction methods, techniques for effective analysis and visualization of large-scale simulations, and algorithms and procedures for efficient processing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

The edge-on Galaxies in the Pan-STARRS survey (EGIPS)

ABSTRACT We present a catalogue of 16 551 edge-on galaxies created using the public DR2 data of the Pan-STARRS survey. The catalogue covers the three quarters of the sky above Dec. = −30°. The galaxies were selected using a convolutional neural network, trained on a sample of edge-on galaxies identified earlier in the SDSS survey. This approach allows us to dramatically improve the quality of the candidate selection and perform a thorough visual inspection in a reasonable amount of time. The catalogue provides homogeneous information on astrometry, SExtractor photometry, and non-parametric morphological statistics of the galaxies. The photometry is reliably for objects in the 13.8–17.4 r-band magnitude range. According to the HyperLeda data base, redshifts are known for about 63 per cent of the galaxies in the catalogue. Our sample is well separated into the red sequence and blue cloud galaxy populations. The edge-on galaxies of the red sequence are systematically Δ(g − i) ≈ 0.1 mag redder than galaxies oriented at an arbitrary angle to the observer. We found a variation of the galaxy thickness with the galaxy colour. The red sequence galaxies are thicker than the galaxies of the blue cloud. In the blue cloud, on average, thinner galaxies turn out to be bluer. In the future, based on this catalogue it is intended to explore the three-dimensional structure of galaxies of different morphologies, as well as to study the scaling relations for discs and bulges.

Makarov, D. (ORCID:0000000191103221)↗
DOE OSTI2015

An affinity-structure database of helix-turn-helix: DNA complexes with a universal coordinate system

Molecular interactions between proteins and DNA molecules underlie many cellular processes, including transcriptional regulation, chromosome replication, and nucleosome positioning. Computational analyses of protein-DNA interactions rely on experimental data characterizing known protein-DNA interactions structurally and biochemically. While many databases exist that contain either structural or biochemical data, few integrate these two data sources in a unified fashion. Such integration is becoming increasingly critical with the rapid growth of structural and biochemical data, and the emergence of algorithms that rely on the synthesis of multiple data types to derive computational models of molecular interactions. We have developed an integrated affinity-structure database in which the experimental and quantitative DNA binding affinities of helix-turn-helix proteins are mapped onto the crystal structures of the corresponding protein-DNA complexes. This database provides access to: (i) protein-DNA structures, (ii) quantitative summaries of protein-DNA binding affinities using position weight matrices, and (iii) raw experimental data of protein-DNA binding instances. Critically, this database establishes a correspondence between experimental structural data and quantitative binding affinity data at the single basepair level. Furthermore, we present a novel alignment algorithm that structurally aligns the protein-DNA complexes in the database and creates a unified residue-level coordinate system for comparing the physico-chemical environments at the interface between complexes. Using this unified coordinate system, we compute the statistics of atomic interactions at the protein-DNA interface of helix-turn-helix proteins. We provide an interactive website for visualization, querying, and analyzing this database, and a downloadable version to facilitate programmatic analysis. Lastly, this database will facilitate the analysis of protein-DNA interactions and the development of programmatic computational methods that capitalize on integration of structural and biochemical datasets. The database can be accessed at http://ProteinDNA.hms.harvard.edu.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

BioSig3D: High Content Screening of Three-Dimensional Cell Culture Models

BioSig3D is a computational platform for high-content screening of three-dimensional (3D) cell culture models that are imaged in full 3D volume. It provides an end-to-end solution for designing high content screening assays, based on colony organization that is derived from segmentation of nuclei in each colony. BioSig3D also enables visualization of raw and processed 3D volumetric data for quality control, and integrates advanced bioinformatics analysis. The system consists of multiple computational and annotation modules that are coupled together with a strong use of controlled vocabularies to reduce ambiguities between different users. It is a web-based system that allows users to: design an experiment by defining experimental variables, upload a large set of volumetric images into the system, analyze and visualize the dataset, and either display computed indices as a heatmap, or phenotypic subtypes for heterogeneity analysis, or download computed indices for statistical analysis or integrative biology. BioSig3D has been used to profile baseline colony formations with two experiments: (i) morphogenesis of a panel of human mammary epithelial cell lines (HMEC), and (ii) heterogeneity in colony formation using an immortalized non-transformed cell line. These experiments reveal intrinsic growth properties of well-characterized cell lines that are routinely used for biological studies. BioSig3D is being released with seed datasets and video-based documentation.

Science & Technology - Other Topics↗