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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Gene network analysis of poplar root transcriptome in response to drought stress identifies a PtaJAZ3PtaRAP2.6-centered hierarchical network

Using time-series transcriptomic data from poplar roots undergoing polyethylene glycol (PEG)-induced drought stress, we built a genetic network model of the involved putative molecular responses. We found that the network resembled a hierarchical structure. The highest hierarchical level in this structure is occupied by 9 genes, which we called superhubs because they were primarily connected to 18 hub genes, which are then connected to 2,934 terminal genes. We were only able to regenerate transgenic plants overexpressing two of the superhubs, suggesting that the majority of the superhubs might interfere with the regeneration process and did not allow recovery of transgenic plants. The two superhubs encode proteins with closest homology to JAZ3 and RAP2.6 genes of Arabidopsis and were consequently named PtaJAZ3 and PtaRAP2.6. PtaJAZ3 and PtaRAP2.6 overexpressing transgenic lines showed a significant increase in both root elongation and lateral root proliferation and these responses were specific for the drought stress conditions and were highly correlated with the levels of overexpression of the transgenes. Several lines of evidence suggest of regulatory interactions between the two superhubs. Both superhubs were significantly induced by methyl jasmonate (MeJA). Because jasmonate signaling involves ubiquitin-mediated proteasome degradation, treatment with proteasome inhibitor abolished the MeJA induction for both genes. PtaRAP2.6 was upregulated in PtaJAZ3 transgenics but PtaJAZ3 expression was not affected in the PtaRAP2.6 overexpressors. The discovery of the two genes and further future insights into the associated mechanisms can lead to improved understanding and novel approaches to regulate root architecture in relation to drought stress.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Topological network analysis of patient similarity for precision management of acute blood pressure in spinal cord injury

Background: Predicting neurological recovery after spinal cord injury (SCI) is challenging. Using topological data analysis, we have previously shown that mean arterial pressure (MAP) during SCI surgery predicts long-term functional recovery in rodent models, motivating the present multicenter study in patients. Methods: Intra-operative monitoring records and neurological outcome data were extracted (n = 118 patients). We built a similarity network of patients from a low-dimensional space embedded using a non-linear algorithm, Isomap, and ensured topological extraction using persistent homology metrics. Confirmatory analysis was conducted through regression methods. Results: Network analysis suggested that time outside of an optimum MAP range (hypotension or hypertension) during surgery was associated with lower likelihood of neurological recovery at hospital discharge. Logistic and LASSO (least absolute shrinkage and selection operator) regression confirmed these findings, revealing an optimal MAP range of 76–[104-117] mmHg associated with neurological recovery. Conclusions: We show that deviation from this optimal MAP range during SCI surgery predicts lower probability of neurological recovery and suggest new targets for therapeutic intervention. Funding: NIH/NINDS: R01NS088475 (ARF); R01NS122888 (ARF); UH3NS106899 (ARF); Department of Veterans Affairs: 1I01RX002245 (ARF), I01RX002787 (ARF); Wings for Life Foundation (ATE, ARF); Craig H. Neilsen Foundation (ARF); and DOD: SC150198 (MSB); SC190233 (MSB); DOE: DE-AC02-05CH11231 (DM).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Generalization Across Experimental Parameters in Neural Network Analysis of High-Resolution Transmission Electron Microscopy Datasets

Neural networks are promising tools for high-throughput and accurate transmission electron microscopy (TEM) analysis of nanomaterials, but are known to generalize poorly on data that is “out-of-distribution” from their training data. Given the limited set of image features typically seen in high-resolution TEM imaging, it is unclear which images are considered out-of-distribution from others. Here, we investigate how the choice of metadata features in the training dataset influences neural network performance, focusing on the example task of nanoparticle segmentation. We train and validate neural networks across curated, experimentally collected high-resolution TEM image datasets of nanoparticles under various imaging and material parameters, including magnification, dosage, nanoparticle diameter, and nanoparticle material. Overall, we find that our neural networks are not robust across microscope parameters, but do generalize across certain sample parameters. Additionally, data preprocessing can have unintended consequences on neural network generalization. Our results highlight the need to understand how dataset features affect deployment of data-driven algorithms.

42 ENGINEERING↗
DOE OSTI2021

Gene co-expression network analysis in zebrafish reveals chemical class specific modules

Zebrafish is a popular animal model used for high-throughput screening of chemical hazards, however, investigations of transcriptomic mechanisms of toxicity are still needed. Here, our goal was to identify genes and biological pathways that Aryl Hydrocarbon Receptor 2 (AHR2) Activators and flame retardant chemicals (FRCs) alter in developing zebrafish. Taking advantage of a compendium of phenotypically-anchored RNA sequencing data collected from 48-h post fertilization (hpf) zebrafish, we inferred a co-expression network that grouped genes based on their transcriptional response. Genes responding to the FRCs and AHR2 Activators localized to distinct regions of the network, with FRCs inducing a broader response related to neurobehavior. AHR2 Activators centered in one region related to chemical stress responses. We also discovered several highly co-expressed genes in this module, including cyp1a, and we subsequently show that these genes are definitively within the AHR2 signaling pathway. Systematic removal of the two chemical types from the data, and analysis of network changes identified neurogenesis associated with FRCs, and regulation of vascular development associated with both chemical classes. We also identified highly connected genes responding specifically to each class that are potential biomarkers of exposure. Overall, we created the first zebrafish chemical-specific gene co-expression network illuminating how chemicals alter the transcriptome relative to each other. In addition to our conclusions regarding FRCs and AHR2 Activators, our network can be leveraged by other studies investigating chemical mechanisms of toxicity.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2022

S-band Network Analysis and Strategies for LEO Multi-CubeSat Science Missions

This paper presents the network architecture utilized at NASA’s Goddard Space Flight Center (GSFC) to support a mission set of five 6U CubeSats. These five CubeSats employ a multi-waveform Software Defined Radio (SDR) platform developed by Vulcan Wireless for use with NASA’s Space Relay (SR) and Direct to Earth (DTE) networks. The performance testing of the SDR is discussed via a comprehensive S-band and communication link analysis. The tested capabilities of the SDR and antenna components are reviewed in terms of the mission requirements for each CubeSat. Size Weight and Power (SWaP), required availability, and access times are discussed. The measured data from experimental compatibility testing is incorporated into detailed simulations of the CubeSat mission set to verify desired performance over the mission lifetime. The model is also used to investigate the impact of potential adverse effects on the communication links such as interference and weather conditions. This paper also reviews potential improvements from future technological advances and commercial partnerships. A collaborative investigation between GSFC and Oklahoma State University is presented in which a qualitative analysis of Hybrid RF/Optical communication strategies is performed. The data rate improvements of optical communication techniques are weighed against attitude control and science mission requirements for CubeSats, and network architectures/switching strategies are discussed. A separate analysis reviews the potential benefits of ground station partnerships, which aligns with NASA’s future goal to include commercial partners in its Earth and space network architectures, e.g. LunaNet.

Space networks↗
NASA NTRS2020

Exploring Carbon Mineral Systems: Recent Advances in C Mineral Evolution, Mineral Ecology, and Network Analysis

Large and growing data resources on the spatial and temporal diversity and distribution of the more than 400 carbon-bearing mineral species reveal patterns of mineral evolution and ecology. Recent advances in analytical and visualization techniques leverage these data and are propelling mineralogy from a largely descriptive field into one of prediction within complex, integrated, multidimensional systems. These discoveries include: (1) systematic changes in the character of carbon minerals and their networks of coexisting species through deep time; (2) improved statistical predictions of the number and types of carbon minerals that occur on Earth but are yet to be discovered and described; and (3) a range of proposed and ongoing studies related to the quantification of network structures and trends, relation of mineral “natural kinds” to their genetic environments, prediction of the location of mineral species across the globe, examination of the tectonic drivers of mineralization through deep time, quantification of preservational and sampling bias in the mineralogical record, and characterization of feedback relationships between minerals and geochemical environments with microbial populations. These aspects of Earth’s carbon mineralogy underscore the complex coevolution of the geosphere and biosphere and highlight the possibility for scientific discovery in Earth and planetary systems.

Carbon↗
NASA NTRS1992

Advanced Solid Rocket Motor (ASRM) communications network analysis

This paper describes the simulation of a proposed campus-wide network for a new manufacturing facility. The proposed network consists of five carrier sense multiple access with collision detection (CSMA/CD) networks connected to five ports of a VAX cluster. In Section 1 the system configuration, the projected traffic pattern, and the proposed protocols are presented. Section 2 describes the models used in constructing the network simulation, while Section 3 contains the results and an analysis of the simulations. The simulations are compared to a mathematical model in Section 4. Some conclusions are drawn in Section 5.

Thompson, Dale R.↗
DOE OSTI2019

Is There a Negative Thermal Expansion in Supported Metal Nanoparticles? An in Situ X-ray Absorption Study Coupled with Neural Network Analysis

Interactions with their support, adsorbates, and unique structural motifs are responsible for many intriguing properties and potential applications of supported metal nanoparticles (NPs). At the same time, they complicate the interpretation of experimental data. In fact, the methods and approaches that work well for the ex situ analysis of bulk materials may be inaccurate or introduce artifacts in the in situ analysis of nanomaterials. Here, we revisit the controversial topic of negative thermal expansion and anomalies in the Debye temperature reported for oxide-supported metal NPs. In situ X-ray absorption experimental data collected for Pt NPs in ultrahigh vacuum and an advanced data analysis approach based on an artificial neural network demonstrate that Pt NPs do not exhibit intrinsic negative thermal expansion. Similarly, as for bulk materials, in the absence of adsorbates and strong particle-support interaction, the bond lengths in metal NPs increase with temperature. Lastly, the previously reported anomalies in particle-size-dependent Debye temperatures can also be linked to the artifacts in the interpretation of conventional X-ray absorption data of disordered materials such as NPs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1994

Switched-beam radiometer front-end network analysis

The noise figure performance of various delay-line networks fabricated from microstrip lines with varying number of elements was investigated using a computer simulation. The effects of resistive losses in both the transmission lines and power combiners were considered. In general, it is found that an optimum number of elements exists, depending upon the resistive losses present in the network. Small resistive losses are found to have a significant degrading effect upon the noise figure performance of the array. Extreme stability in switching characteristics is necessary to minimize the nondeterministic noise of the array. For example, it is found that a 6 percent tolerance on the delay-line lengths will produce a 0.2 db uncertainty in the noise figure which translates into a 13.67 K temperature uncertainty generated by the network. If the tolerance can be held to 2 percent, the uncertainty in noise figure and noise temperature will be 0.025 db and 1.67 K, respectively. Three phase shift networks fabricated using a commercially available PIN diode switch were investigated. Loaded-line phase shifters are found to have desirable RF and noise characteristics and are attractive components for use in phased-array networks.

Trew, R. J.↗
NASA NTRS2020

Striped Mullet Migration Patterns in the Indian River Lagoon: A Network Analysis Approach to Spatial Fisheries Management

Striped mullet (Mugil cephalus) are numerically abundant forage fish, highly valuable as prey and commercially valuable to humans. From September to December, mullet in the Indian River Lagoon (IRL), Florida undergo an annual migration from inshore foraging habitats to oceanic spawning sites. However, their migratory pathways, in particular their intra-estuarine movement pathways, remain unknown. To address this knowledge gap, we utilized passive acoustic telemetry to assess the movement patterns of M. cephalus within the IRL. Thirty-two fish were tagged, generating usable tracks from 18 individuals. The mean (±s.d.) time that fish were detected in the array was ~38 ± 90 days, with the longest at 444 days. We also document the first evidence of skipped spawning in M. cephalus inhabiting waters of the southeastern United States. These data suggest impoundments around the Merritt Island National Wildlife Refuge appear to serve as important refugia for striped mullet while the Banana and Indian Rivers act as corridors during their inshore migratory movements. Through spatial fisheries management, high value habitat and connective elements utilized by mullet and other vital forage fish may be identified, to benefit both natural and human dynamics in estuarine systems.

Acoustic telemetry↗
NASA NTRS1973

Computer program for compressible flow network analysis

Program solves problem of an arbitrarily connected one dimensional compressible flow network with pumping in the channels and momentum balancing at flow junctions. Program includes pressure drop calculations for impingement flow and flow through pin fin arrangements, as currently found in many air cooled turbine bucket and vane cooling configurations.

Wilton, M. E.↗
DOE OSTI2014

Gene co-expression network analysis in Rhodobacter capsulatus and application to comparative expression analysis of Rhodobacter sphaeroides

The genus Rhodobacter contains purple nonsulfur bacteria found mostly in freshwater environments. Representative strains of two Rhodobacter species, R. capsulatus and R. sphaeroides, have had their genomes fully sequenced and both have been the subject of transcriptional profiling studies. Gene co-expression networks can be used to identify modules of genes with similar expression profiles. Functional analysis of gene modules can then associate co-expressed genes with biological pathways, and network statistics can determine the degree of module preservation in related networks. In this paper, we constructed an R. capsulatus gene co-expression network, performed functional analysis of identified gene modules, and investigated preservation of these modules in R. capsulatus proteomics data and in R. sphaeroides transcriptomics data. Results: The analysis identified 40 gene co-expression modules in R. capsulatus. Investigation of the module gene contents and expression profiles revealed patterns that were validated based on previous studies supporting the biological relevance of these modules. We identified two R. capsulatus gene modules preserved in the protein abundance data. We also identified several gene modules preserved between both Rhodobacter species, which indicate that these cellular processes are conserved between the species and are candidates for functional information transfer between species. Many gene modules were non-preserved, providing insight into processes that differentiate the two species. In addition, using Local Network Similarity (LNS), a recently proposed metric for expression divergence, we assessed the expression conservation of between-species pairs of orthologs, and within-species gene-protein expression profiles. Conclusions: Our analyses provide new sources of information for functional annotation in R. capsulatus because uncharacterized genes in modules are now connected with groups of genes that constitute a joint functional annotation. We identified R. capsulatus modules enriched with genes for ribosomal proteins, porphyrin and bacteriochlorophyll anabolism, and biosynthesis of secondary metabolites to be preserved in R. sphaeroides whereas modules related to RcGTA production and signalling showed lack of preservation in R. sphaeroides. In addition, we demonstrated that network statistics may also be applied within-species to identify congruence between mRNA expression and protein abundance data for which simple correlation measurements have previously had mixed results.

Comparative transcriptomics, Module preservation, ↗
DOE OSTI2019

Social-ecological network analysis for sustainability sciences: a systematic review and innovative research agenda for the future

Social-ecological network (SEN) concepts and tools are increasingly used in human-environment and sustainability sciences. We take stock of this budding research area to further show the strength of SEN analysis for complex human-environment settings, identify future synergies between SEN and wider human-environment research, and provide guidance about when to use different kinds of SEN approaches and models. We characterize SEN research along a spectrum specifying the degree of explicit network representation of system components and dynamics. We then systematically review one end of this spectrum, what we term ‘fully articulated SEN’ studies, which specifically model unique social and ecological units and relationships. Results show a larger number of papers focus on methodological advancement and applied ends. While there has been some development and testing of theories, this remains an area for future work and would help develop SENs as a unique field of research, not just a method. Authors have studied diverse systems, while mainly focusing on the problem of social-ecological fit alongside a scattering of other topics. There is strong potential, however, to engage other issues central to human-environment studies. Analyzing the simultaneous effects of multiple social, environmental, and coupled processes, change over time, and linking network structures to outcomes are also areas for future advancement. This review provides a comprehensive assessment of (fully articulated) SEN research, a necessary step that can help scholars develop comparable cases and fill research gaps.

environmental governance↗
DOE OSTI2023

Transcriptomic Network Analysis of Cyanobacterial-Methylotroph Interactions in Coculture and Axenic Conditions

A previous study demonstrated the potential for Cyanobacterial-Methylotroph cocultures to facilitate biogas processing as well as to be used in other biotechnological applications. To advance this technology, we investigated potential interactions between Cyanobacterium stanieri HL-69 (HL69) and Methylotuvimicrobium alkaliphilum 20Z (20Z) by inferring and analyzing gene co-expression networks under co-culture and axenic conditions. Five different co-expression networks were examined. These networks were inferred using gene expression profiles for 20Z axenic condition, HL-69 axenic, HL-69, 20Z coculture, HL-69 coculture, and cross-species HL-69-20Z coculture. Through the analysis of node (gene) betweenness and node normalized degree values in all five network cases, we compared adjustments in gene expression between growth conditions (axenic vs co-culture) as well as identify biological functions relevant to interspecies interactions. This analysis was done to distinguish between gene interactions within an organism and gene interactions between two organisms. Moreover, for all five cases we investigated two different network cutoff levels of 3,000 and 10,000. By shedding light on inter- and intra- species interactions, we hope to gain a better understanding of how these two organisms interact. This research will allow the investigation of further biotechnological applications of coculture systems and optimization of such applications for biotechnological purposes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Cyber-Power Co-Simulation for End-to-End Synchrophasor Network Analysis and Applications

The resiliency, reliability and security of the next generation cyber-power smart grid depend upon efficiently leveraging advanced communication and computing technologies. Also, developing real-time data-driven applications is critical to enable wide-area monitoring and control of the cyber-power grid given high-resolution data from Phasor Measurement Units (PMUs). North American Synchrophasor Initiative Network (NASPlnet) provides guidance for PMU data exchanges. With the advancement in networking and grid operation, it is necessary to evaluate the performance of different data flow architectures suggested by NASPInet and analyze the impact on applications. Therefore, we need a cyber-power co-simulation framework that supports very large-scale co-simulation capable of running in parallel, high-performance computing platforms and capturing real-life network behavior. This work presents an end-to-end automated and user-driven cyber-power co-simulation using NS3 to model communication networks, GridPACK to model the power grid, and HELICS as a co-simulation engine. Comparative analysis of latency in synchrophasor networks and a performance evaluation of a power system stabilizer application utilizing PMU data in an IEEE 39 bus test system is presented using this cosimulation testbed.

Mustafa, Hussain M.↗