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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

SU-F-R-17: Advancing Glioblastoma Multiforme (GBM) Recurrence Detection with MRI Image Texture Feature Extraction and Machine Learning

Purpose: To test the potential of early Glioblastoma Multiforme (GBM) recurrence detection utilizing image texture pattern analysis in serial MR images post primary treatment intervention. Methods: MR image-sets of six time points prior to the confirmed recurrence diagnosis of a GBM patient were included in this study, with each time point containing T1 pre-contrast, T1 post-contrast, T2-Flair, and T2-TSE images. Eight Gray-level co-occurrence matrix (GLCM) texture features including Contrast, Correlation, Dissimilarity, Energy, Entropy, Homogeneity, Sum-Average, and Variance were calculated from all images, resulting in a total of 32 features at each time point. A confirmed recurrent volume was contoured, along with an adjacent non-recurrent region-of-interest (ROI) and both volumes were propagated to all prior time points via deformable image registration. A support vector machine (SVM) with radial-basis-function kernels was trained on the latest time point prior to the confirmed recurrence to construct a model for recurrence classification. The SVM model was then applied to all prior time points and the volumes classified as recurrence were obtained. Results: An increase in classified volume was observed over time as expected. The size of classified recurrence maintained at a stable level of approximately 0.1 cm{sup 3} up to 272 days prior to confirmation. Noticeable volume increase to 0.44 cm{sup 3} was demonstrated at 96 days prior, followed by significant increase to 1.57 cm{sup 3} at 42 days prior. Visualization of the classified volume shows the merging of recurrence-susceptible region as the volume change became noticeable. Conclusion: Image texture pattern analysis in serial MR images appears to be sensitive to detecting the recurrent GBM a long time before the recurrence is confirmed by a radiologist. The early detection may improve the efficacy of targeted intervention including radiosurgery. More patient cases will be included to create a generalizable classification model applicable to a larger patient cohort. NIH R43CA183390 and R01CA188300.NSF Graduate Research Fellowship DGE-1144087.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1991

Geography of cretaceous extinctions: Data base development

Data bases built from the source literature are plagued by problems of data quality. Unless the data acquisition is done by experts, working slowly, the data base may contain so much garbage that true signals and patterns cannot be detected. On the other hand, high quality data bases develop so slowly that satisfactory statistical analysis may never be possible due to the small sample sizes. Results of a test are presented of the opposite strategy: rapid data acquisition by non-experts with minimal control on data quality. A published list of 186 species and genera of fossil invertibrates of the latest Cretaceous Age (Maestrichtian) were located through a random search of the paleobiological and geological literature. The geographic location for each faunal list was then transformed electronically to Maestrichtian latitude and longitude and the lists were further digested to identify the genera occurring in each ten-degree, latitude-longitude block. The geographical lists were clustered using the Otsuka similarity coefficient and a standard unweight-pair-group method. The resulting clusters are remarkably consistent geographically, indicating that a strong biogeographic signal is visible despite low-quality data. A further test evaluated the geographic pattern of end-Cretaceaous extinctions. All genera in the data base were compared with Sepkoski's compendium of time ranges of genera to determine which of the reported genera survived the Cretaceous mass extinction. In turn, extinction rates for the ten-degree, latitude-longitude blocks were mapped. The resulting distribution is readily interpretable as a robust pattern of the geography of the mass extinction. The study demonstrates that a low-quality data base, built rapidly, can provide a basis for meaningful analysis of past biotic events.

Raup, D. M.↗
DOE OSTI2022

Feature extraction for subtle anomaly detection using semi-supervised learning

The demand for automated and effective monitoring techniques has soared with the increased digitization of industrial monitoring systems. State-of-the-art machine learning methods are effectively detecting abrupt changes in system states. However, these methods lack comparable maturity in detecting subtle changes that may be signs of incipient faults. This manuscript argues that the current anomaly detection methods can be enhanced by exploring weak patterns to enable subtle variation detection. Specifically, the concept of semi-supervised learning is employed, with labels representing knowledge about some anomalous conditions of a system. The basic idea is to extract a candidate set of weak patterns discarded by state-of-the-art baselining algorithms. With few labeled anomalous data, the algorithm selects the weak patterns and allows for their possible fusion using the highest sensitivity to the labeled anomalies. Here, the method’s applicability is demonstrated using a representative pressurized water reactor (PWR) model simulated by Dymola.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Development of limited-view tomography for measurement of Spray G plume direction and liquid volume fraction

Abstract The method for direct injection of fuel in the cylinder of an IC engines is important to high-efficiency and low-emission performance. Optical spray diagnostics plays an important role in understanding plume movement and interaction for multi-hole injectors, and providing baseline understanding used for computational optimization of fuel delivery. Traditional planar or line-of-sight diagnostics fail to capture the liquid distribution because of optical thickness concerns. This work proposes a high-speed (67 kHz) extinction imaging technique at various injector rotations coupled to computed tomography (CT) for time-resolved reconstruction of liquid volume fraction in three dimensions. The number of views selected and processing were based on synthetic (modeled) liquid volume fraction data where extinction and CT adequately reconstructed each plume. The exercise showed that for an 8-hole, symmetric-design injector (ECN Spray G), only three different views are enough to reproduce the direction of each plume, and particularly the mean plume direction. Therefore, the number of views was minimized for experiments to save expense. Measurements applying this limited-view technique confirm plume–plume variations also detected with mechanical patternation, while providing better spatial and temporal resolution than achieved previously. Uncertainties due to the limited view within pressurized spray chambers, the droplet size, and optically thick regions are discussed. Graphic abstract

42 ENGINEERING↗
DOE OSTI2019

Can synthetic lethality approach be used with DNA repair genes for primary and secondary MDS?

Cancer-specific defects in DNA repair pathways create the opportunity to employ synthetic lethality approach. Recently, GEMA (gene expression and mutation analysis) approach detected insufficient expression of BRCA or NHEJ (non-homologous end joining) to predict PARP inhibitors response. We evaluated a possible role of DNA repair pathways using gene expression of single-strand break (XPA, XPC, XPG/ERCC5, CSA/ERCC8, and CSB/ERCC6) and double-strand break (ATM, BRCA1, BRCA2, RAD51, XRCC5, XRCC6, LIG4) in 92 patients with myelodysplastic syndrome (73 de novo, 9 therapy-related (t-MDS). Therapy-related MDS (t-MDS) demonstrated a significant downregulation of axis BRCA1-BRCA2-RAD51 comparing to normal controls (p = 0.048, p = 0.001, p = 0.001). XRCC6 showed significantly low expression in de novo MDS comparing to controls (p = 0.039) and for patients who presented chromosomal abnormalities (p = 0.047). Downregulation of LIG4 was consistently associated with poor prognostic markers in de novo MDS (hemoglobin < 8 g/dL (p = 0.040), neutrophils < 800/mm{sup 3} (p < 0.001), patients with excess of blasts (p = 0.001), very high (p = 0.002)/high IPSS-R (p = 0.043) and AML transformation (p < 0.001). We also performed an evaluation of GEPIA Database in 30 cancer types and detected a typical pattern of downregulation as here presented in primary or secondary MDS. All these results suggest synthetic lethality approach can be tested with DNA repair genes (beyond that of BRCA1/2 status) for de novo and therapy-related myelodysplastic syndrome and may encourage clinical trials evaluating the use of PARP1 inhibitors in MDS. Graphic Abstract: .

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Phonon-mediated lipid raft formation in biological membranes

Short-wavelength collective molecular motions, also known as phonons, have recently attracted much interest in revealing dynamic properties of biological membranes through the use of neutron and x-ray scattering, infrared and Raman spectroscopies, and molecular dynamics simulations. Experimentally detecting unique vibrational patterns such as, shear phonon excitations, viscoelastic crossovers, transverse acoustic phonon gaps, and continuous and truncated optical phonon modes in cellular membranes, to name a few, has proven non-trivial. Here, we review recent advances in liquid thermodynamics that have resulted in the development of the phonon theory of 1 liquids. The theory has important predictions regarding the shear vibrational spectra of fluids, namely the emergence of viscoelastic crossovers and transverse acoustic phonon gaps. Furthermore, we show that these vibrational patterns are common in soft (non-crystalline) materials, including, but not limited to liquids, colloids, liquid crystals (mesogens), block copolymers, and biological membranes. The existence of viscoelastic crossovers and acoustic phonon gaps define the self-diffusion properties of cellular membranes and provide a molecular picture of the transient nature of lipid rafts.1 Importantly, the timescales (picoseconds) for the formation and dissolution of transient lipid rafts match the lifetime of the formation and breakdown of interfacial water hydrogen bonds. Apart from acoustic propagating phonon modes, biological membranes can also support more energetic non-propagating optical phonon excitations, also known as standing waves or breathing modes. Importantly, optical phonons can be truncated due to the existence of finite size nanodomains made up of strongly correlated lipid-cholesterol molecular pairs. These strongly coupled molecular pairs can serve as nucleation centers for the formation of stable rafts at larger length scales, due to correlations of spontaneous fluctuations (Onsager’s regression hypothesis). Finally and importantly, molecular level viscoelastic crossovers, acoustic phonon gaps, and continuous and truncated optical phonon modes may offer insights as to how lipid-lipid and lipid-protein interactions enable biological function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Bacterial cGAS-like enzymes synthesize diverse nucleotide signals

Cyclic dinucleotides (CDNs) have central roles in bacterial homeostasis and virulence by acting as nucleotide second messengers. Bacterial CDNs also elicit immune responses during infection when they are detected by pattern-recognition receptors in animal cells. Here we perform a systematic biochemical screen for bacterial signalling nucleotides and discover a large family of cGAS/DncV-like nucleotidyltransferases (CD-NTases) that use both purine and pyrimidine nucleotides to synthesize a diverse range of CDNs. Here, a series of crystal structures establish CD-NTases as a structurally conserved family and reveal key contacts in the enzyme active-site lid that direct purine or pyrimidine selection. CD-NTase products are not restricted to CDNs and also include an unexpected class of cyclic trinucleotide compounds. Biochemical and cellular analyses of CD-NTase signalling nucleotides demonstrate that these cyclic di- and trinucleotides activate distinct host receptors and thus may modulate the interaction of both pathogens and commensal microbiota with their animal and plant hosts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Search for magnetically-induced signatures in the arrival directions of ultra-high-energy cosmic rays measured at the Pierre Auger Observatory

We search for signals of magnetically-induced effects in the arrival directions of ultra-high-energy cosmic rays detected at the Pierre Auger Observatory. We apply two different methods. One is a search for sets of events that show a correlation between their arrival direction and the inverse of their energy, which would be expected if they come from the same point-like source, they have the same electric charge and their deflection is relatively small and coherent. We refer to these sets of events as “multiplets”. The second method, called “thrust”, is a principal axis analysis aimed to detect the elongated patterns in a region of interest. We study the sensitivity of both methods using a benchmark simulation and we apply them to data in two different searches. The first search is done assuming as source candidates a list of nearby active galactic nuclei and starburst galaxies. The second is an all-sky blind search. We report the results and we find no statistically significant features. We discuss the compatibility of these results with the indications on the mass composition inferred from data of the Pierre Auger Observatory.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Shaping with water: linking moisture perception to development in plant roots

Water is the most limiting resource for plant growth and development. Heterogeneity in the environmental distribution of water requires plants to direct root growth toward water and to avoid investing resources in areas that lack water. Roots use hydrosignaling pathways—hydrotropism, hydropatterning, and xerobranching—to sense and respond to water availability. While molecular mechanisms of water perception remain unclear, recent studies suggest that organ-level processes using proxies like ethylene help detect spatial water patterns. This review summarizes advances in hydrosignaling and identifies key knowledge gaps to address how plants sense water. Understanding these processes will guide strategies to improve root water capture for sustainable agriculture.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

X-ray diffraction of dynamically compressed matter on Sandia's Z Pulsed Power Facility

Sandia's Z Pulsed Power Facility is able to dynamically compress matter to extreme states with exceptional uniformity, duration, and size, which are ideal for investigations of fundamental material properties of high energy density conditions. X-ray diffraction (XRD) is a key atomic scale probe since it provides direct observation of the compression and strain of the crystal lattice, and is used to detect, identify, and quantify phase transitions. Because of the destructive nature of Z-Dynamic Materials Properties (DMP) experiments and low signal vs background emission levels of XRD, it is very challenging to detect the XRD pattern close to the Z-DMP load and to recover the data. We developed a new Spherical Crystal Diffraction Imager (SCDI) diagnostic to relay and image the diffracted x-ray pattern away from the load debris field. The SCDI diagnostic utilizes the Z-Beamlet laser to generate 6.2-keV Mn-He c , x-rays to probe a shock-compressed sample on the Z-DMP load. A spherically bent crystal composed of highly oriented pyrolytic graphite is used to collect and focus the diffracted x-rays into a 1-inch thick tungsten housing, where an image plate is used to record the data. We performed experiments to implement the SCDI diagnostic on Z to measure the XRD pattern of shock compressed beryllium samples at pressures of 1.8-2.2 Mbar.

36 MATERIALS SCIENCE↗
DOE OSTI2023

“Shoulda, Coulda, Woulda”: Conceptualizing the Differences in Trust Between Human-Human Teaming and Human-Machine Teaming

Intelligent decision support systems (IDSSs) are machine teammates designed to facilitate better human decision-making in high-consequence domains such as health care, power grid operations, and fraud detection. IDSSs identify patterns in datasets and provide intelligent decision-making recommendations to human teammates. However, previous research indicates that humans often trust IDSS recommendations less than the recommendations from their human teammates, even when the machine teammate is more accurate. To conceptualize why trust differs, we review the literature surrounding trust, error, and predictability. Then, we compile and compare participant trust ratings and decision-making in an abridged systematic review of previous studies manipulating teammate type, error rate, and error type. Finally, we conduct a content analysis of participants’ qualitative responses to trust queries from a survey on generative language models. Results suggest that humans may trust IDSS teammates less than other human teammates because of differences in (1) interaction complexity, (2) blame attribution, and (3) swift trust. We conclude that human factors practitioners should collaborate with data scientists and domain experts to build and maintain trust in IDSSs by anthropomorphizing algorithms, matching mental models, and considering individual differences.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Poisson-response Tensor-on-Tensor Regression and Applications

We introduce Poisson-response tensor-on-tensor regression (PToTR), a novel regression framework designed to handle tensor responses composed element-wise of random Poisson-distributed counts. Tensors, or multi-dimensional arrays, composed of counts are common data in fields such as inter national relations, social networks, epidemiology, and medical imaging, where events occur across multiple dimensions like time, location, and dyads. PToTR accommodates such tensor responses alongside tensor covariates, providing a versatile tool for multi dimensional data analysis. We propose algorithms for maximum likelihood estimation under a canonical polyadic (CP) structure on the regression coefficient tensor that satisfy the positivity of Poisson parameters and then provide an initial theoretical error analysis for PToTR estimators. We also demonstrate the utility of PToTR through three concrete applications: longitudinal data analysis of the Integrated Crisis Early Warning System database, positron emission tomography (PET) image reconstruction, and change-point detection of communication patterns in longitudinal dyadic data. These applications highlight the versatility of PToTR in addressing complex, structured count data across various domains.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

IRAS 16253–2429: THE FIRST PROTO-BROWN DWARF BINARY CANDIDATE IDENTIFIED THROUGH THE DYNAMICS OF JETS

The formation mechanism of brown dwarfs (BDs) is one of the long-standing problems in star formation because the typical Jeans mass in molecular clouds is too large to form these substellar objects. To answer this question, it is crucial to study a BD in the embedded phase. IRAS 16253–2429 is classified as a very low-luminosity object (VeLLO) with an internal luminosity of <0.1 L {sub ⊙}. VeLLOs are believed to be very low-mass protostars or even proto-BDs. We observed the jet/outflow driven by IRAS 16253–2429 in CO (2–1), (6–5), and (7–6) using the IRAM 30 m and Atacama Pathfinder Experiment telescopes and the Submillimeter Array (SMA) in order to study its dynamical features and physical properties. Our SMA map reveals two protostellar jets, indicating the existence of a proto-binary system as implied by the precessing jet detected in H{sub 2} emission. We detect a wiggling pattern in the position–velocity diagrams along the jet axes, which is likely due to the binary orbital motion. Based on this information, we derive the current mass of the binary as ∼0.032 M{sub ⊙}. Given the low envelope mass, IRAS 16253–2429 will form a binary that probably consist of one or two BDs. Furthermore, we found that the outflow force as well as the mass accretion rate are very low based on the multi-transition CO observations, which suggests that the final masses of the binary components are at the stellar/substellar boundary. Since IRAS 16253 is located in an isolated environment, we suggest that BDs can form through fragmentation and collapse, similar to low-mass stars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

A Search for Rapidly Pulsating Hot Subdwarf Stars in the GALEX Survey

NASA’s Galaxy Evolution Explorer ( GALEX ) provided near- and far-UV observations for approximately 77% of the sky over a 10-year period; however, the data reduction pipeline initially only released single NUV and FUV images to the community. The recently released Python module gPhoton changes this, allowing calibrated time-series aperture photometry to be extracted easily from the raw GALEX data set. Here we use gPhoton to generate light curves for all hot subdwarf B (sdB) stars that were observed by GALEX , with the intention of identifying short-period, p-mode pulsations. We find that the spacecraft’s short visit durations, uneven gaps between visits, and dither pattern make the detection of hot subdwarf pulsations difficult. Nonetheless, we detect UV variations in four previously known pulsating targets and report their UV pulsation amplitudes and frequencies. Additionally, we find that several other sdB targets not previously known to vary show promising signals in their periodograms. Using optical follow-up photometry with the Skynet Robotic Telescope Network, we confirm p-mode pulsations in one of these targets, LAMOST J082517.99+113106.3, and report it as the most recent addition to the sdBV{sub r} class of variable stars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Soda Pop: A Time-Series Clustering, Alarming and Disease Forecasting Application

To introduce Soda Pop, an R/Shiny application designed to be a disease agnostic time-series clustering, alarming, and forecasting tool to assist in disease surveillance “triage, analysis and reporting” workflows within the Biosurveillance Ecosystem (BSVE). In this poster, we highlight the new capabilities that are brought to the BSVE by Soda Pop with an emphasis on the impact of methodological decisions. The Biosurveillance Ecosystem (BSVE) is a biological and chemical threat surveillance system sponsored by the Defense Threat Reduction Agency (DTRA). BSVE is intended to be user-friendly, multi-agency, cooperative, modular and threat agnostic platform for biosurveillance. In BSVE, a web-based workbench presents the analyst with applications (apps) developed by various DTRA funded researchers, which are deployed on-demand in the cloud(e.g., Amazon Web Services). These apps aim to address emerging needs and refine capabilities to enable early warning of chemical and biological threats for multiple users across local, state, and federal agencies. Soda Pop is an app developed by Pacific Northwest National Laboratory (PNNL) to meet the current needs of the BSVE for early warning and detection of disease outbreaks. Aimed for use bya diverse set of analysts, the application is agnostic to data source and spatial scale enabling it to be generalizable across many diseases and locations. To achieve this, we placed a particular emphasis on clustering and alerting of disease signals within Soda Pop without strong prior assumptions on the nature of observed diseased counts. Although designed to be agnostic to the data source, Soda Pop was initially developed and tested on data summarizing Influenza-Like Illness in military hospitals from collaboration with the Armed Forces Health Surveillance Branch. Currently, the data incorporated also includes the CDC’s National Notifiable Diseases Surveillance System(NNDSS) tables and the WHO’s Influenza A/B Influenza Data(Flunet). These data sources are now present in BSVE’s Postgres data storage for direct access. Soda Pop is designed to automate time-series tasks of data summarization, exploration, clustering, alarming and forecasting. Built as an R/Shiny application, Soda Pop is founded on the powerful statistical tool R.. Where applicable, Soda Pop facilitates nonparametric seasonal decomposition of time-series; hierarchical agglomerative clustering across reporting areas and between diseases within reporting areas; and a variety of alarming techniques including Exponential Weighted Moving Average alarms and Early Aberration Detection. Soda Pop embeds these techniques within a user-interface designed to enhance an analyst’s understanding of emerging trends in their data and enables the inclusion of its graphical elements into their dossier for further tracking and reporting. The ultimate goal of this software is to facilitate the discovery of unknown disease signals along with increasing the speed of detection of unusual patterns within these signals. Soda Pop organizes common statistical disease surveillance tasks in a manner integrated with BSVE data source inputs and outputs. The app analyzes time-series disease data and supports a robust set of clustering and alarming routines that avoid strong assumptions on the nature of observed disease counts. This attribute allows for flexibility in the data source, spatial scale, and disease types making it useful to a wide range of analysts.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1972

Land use mapping and modelling for the Phoenix quadrangle

The author has identified the following significant results. Experimentation with 70mm squares cut from ERTS-1 9.5 inch MSS positive transparencies in an I2S color additive viewer, a Richardson film production viewer at 10X magnification, and in a microfiche viewer at 12X and 18X magnification has indicated that band 5 photography provides the most useful interpretable data. In the I2S viewer high intensities of blue and red light in bands 4 and 6 respectively enhance faint vegetation patterns not easily detectable. Slides produced from 35mm color transparencies made by photographing the I2S viewing screen are suitable visual aids for use during presentation. Interpretation of MSS transparencies allowed compilation of a map of land use change in the Phoenix quadrangle.

Place, J. L.↗
NASA NTRS1972

Relevance of ERTS to the State of Ohio

The author has identified the following significant results. The ability to delineate and inventory strip mined areas using ERTS-1 imagery has been established. This gives Ohio a method to rapidly gain an up-to-date inventory of strip mined lands for state planning purposes, which has not been available previously. Smoke plume detection and sedimentation patterns in Sandusky Bay have also been determined from initial analysis of ERTS-1 data.

Sweet, D. C.↗