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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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170 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

High-dimensional multivariate autoregressive model estimation of human electrophysiological data using fMRI priors

Multivariate autoregressive (MVAR) model estimation enables assessment of causal interactions in brain networks. However, accurately estimating MVAR models for high-dimensional electrophysiological recordings is challenging due to the extensive data requirements. Hence, the applicability of MVAR models for study of brain behavior over hundreds of recording sites has been very limited. Prior work has focused on different strategies for selecting a subset of important MVAR coefficients in the model to reduce the data requirements of conventional least-squares estimation algorithms. Here we propose incorporating prior information, such as resting state functional connectivity derived from functional magnetic resonance imaging, into MVAR model estimation using a weighted group least absolute shrinkage and selection operator (LASSO) regularization strategy. The proposed approach is shown to reduce data requirements by a factor of two relative to the recently proposed group LASSO method of Endemann et al (Neuroimage 254:119057, 2022) while resulting in models that are both more parsimonious and more accurate. The effectiveness of the method is demonstrated using simulation studies of physiologically realistic MVAR models derived from intracranial electroencephalography (iEEG) data. The robustness of the approach to deviations between the conditions under which the prior information and iEEG data is obtained is illustrated using models from data collected in different sleep stages. This approach allows accurate effective connectivity analyses over short time scales, facilitating investigations of causal interactions in the brain underlying perception and cognition during rapid transitions in behavioral state.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

A review of non-cognitive applications for neuromorphic computing

Abstract Though neuromorphic computers have typically targeted applications in machine learning and neuroscience (‘cognitive’ applications), they have many computational characteristics that are attractive for a wide variety of computational problems. In this work, we review the current state-of-the-art for non-cognitive applications on neuromorphic computers, including simple computational kernels for composition, graph algorithms, constrained optimization, and signal processing. We discuss the advantages of using neuromorphic computers for these different applications, as well as the challenges that still remain. The ultimate goal of this work is to bring awareness to this class of problems for neuromorphic systems to the broader community, particularly to encourage further work in this area and to make sure that these applications are considered in the design of future neuromorphic systems.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1998

BioSIGHT: Interactive Visualization Modules for Science Education

Redefining science education to harness emerging integrated media technologies with innovative pedagogical goals represents a unique challenge. The Integrated Media Systems Center (IMSC) is the only engineering research center in the area of multimedia and creative technologies sponsored by the National Science Foundation. The research program at IMSC is focused on developing advanced technologies that address human-computer interfaces, database management, and high-speed network capabilities. The BioSIGHT project at is a demonstration technology project in the area of education that seeks to address how such emerging multimedia technologies can make an impact on science education. The scope of this project will help solidify NASA's commitment for the development of innovative educational resources that promotes science literacy for our students and the general population as well. These issues must be addressed as NASA marches toward the goal of enabling human space exploration that requires an understanding of life sciences in space. The IMSC BioSIGHT lab was established with the purpose of developing a novel methodology that will map a high school biology curriculum into a series of interactive visualization modules that can be easily incorporated into a space biology curriculum. Fundamental concepts in general biology must be mastered in order to allow a better understanding and application for space biology. Interactive visualization is a powerful component that can capture the students' imagination, facilitate their assimilation of complex ideas, and help them develop integrated views of biology. These modules will augment the role of the teacher and will establish the value of student-centered interactivity, both in an individual setting as well as in a collaborative learning environment. Students will be able to interact with the content material, explore new challenges, and perform virtual laboratory simulations. The BioSIGHT effort is truly cross-disciplinary in nature and requires expertise from many areas including Biology, Computer Science Electrical Engineering, Education, and the Cognitive Sciences. The BioSIGHT team includes a scientific illustrator, educational software designer, computer programmers as well as IMSC graduate and undergraduate students.

Wong, Wee Ling↗
NASA NTRS1998

BioSIGHT: Interactive Visualization Modules for Science Education

Redefining science education to harness emerging integrated media technologies with innovative pedagogical goals represents a unique challenge. The Integrated Media Systems Center (IMSC) is the only engineering research center in the area of multimedia and creative technologies sponsored by the National Science Foundation. The research program at IMSC is focused on developing advanced technologies that address human-computer interfaces, database management, and high- speed network capabilities. The BioSIGHT project at IMSC is a demonstration technology project in the area of education that seeks to address how such emerging multimedia technologies can make an impact on science education. The scope of this project will help solidify NASA's commitment for the development of innovative educational resources that promotes science literacy for our students and the general population as well. These issues must be addressed as NASA marches towards the goal of enabling human space exploration that requires an understanding of life sciences in space. The IMSC BioSIGHT lab was established with the purpose of developing a novel methodology that will map a high school biology curriculum into a series of interactive visualization modules that can be easily incorporated into a space biology curriculum. Fundamental concepts in general biology must be mastered in order to allow a better understanding and application for space biology. Interactive visualization is a powerful component that can capture the students' imagination, facilitate their assimilation of complex ideas, and help them develop integrated views of biology. These modules will augment the role of the teacher and will establish the value of student-centered interactivity, both in an individual setting as well as in a collaborative learning environment. Students will be able to interact with the content material, explore new challenges, and perform virtual laboratory simulations. The BioSIGHT effort is truly cross-disciplinary in nature and requires expertise from many areas including Biology, Computer Science, Electrical Engineering, Education, and the Cognitive Sciences. The BioSIGHT team includes a scientific illustrator, educational software designer, computer programmers as well as IMSC graduate and undergraduate students. Our collaborators include TERC, a research and education organization with extensive k-12 math and science curricula development from Cambridge, MA.; SRI International of Menlo Park, CA.; teachers and students from local area high schools (Newbury Park High School, USC's Family of Five schools, Chadwick School, and Pasadena Polytechnic High School).

Wong, Wee Ling↗
DOE OSTI2025

Direct effects of prolonged TNF-α and IL-6 exposure on neural activity in human iPSC-derived neuron-astrocyte co-cultures

Cognitive impairment is one of the many symptoms reported by individuals suffering from long-COVID and other post-viral infection disorders such as myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). A common factor among these conditions is a sustained immune response and increased levels of inflammatory cytokines. Tumor necrosis factor alpha (TNF-α) and interleukin-6 (IL-6) are two such cytokines that are elevated in patients diagnosed with long-COVID and ME/CFS. In this study, we characterized the changes in neural functionality, secreted cytokine profiles, and gene expression in co-cultures of human iPSC-derived neurons and primary astrocytes in response to prolonged exposure to TNF-α and IL-6. We found that exposure to TNF-α produced both a concentration-independent and concentration-dependent response in neural activity. Burst duration was significantly reduced within a few days of exposure regardless of concentration (1 pg/mL – 100 ng/mL) but returned to baseline after 7 days. Treatment with low concentrations of TNF-α (e.g., 1 and 25 pg/mL) did not lead to changes in the secreted cytokine profile or gene expression but still resulted in significant changes to electrophysiological features such as interspike interval and burst duration. Conversely, treatment with high concentrations of TNF-α (e.g., 10 and 100 ng/mL) led to reduced spiking activity, which may be correlated to changes in neural health, gene expression, and increases in inflammatory cytokine secretion (e.g., IL-1β, IL-4, and CXCL-10) that were observed at higher TNF-α concentrations. Prolonged exposure to IL-6 led to changes in bursting features, with significant reduction in the number of spikes in bursts across a wide range of treatment concentrations (i.e., 1 pg/mL–10 ng/mL). In combination, the addition of IL-6 appears to counteract the changes to neural function induced by low concentrations of TNF-α, while at high concentrations of TNF-α the addition of IL-6 had little to no effect. Conversely, the changes to electrophysiological features induced by IL-6 were lost when the cultures were co-stimulated with TNF-α regardless of the concentration, suggesting that TNF-α may play a more pronounced role in altering neural function. These results indicate that increased concentrations of key inflammatory cytokines associated with long-COVID can directly impact neural function and may be a component of the cognitive impairment associated with long-COVID and other post-viral infection disorders.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2015

Technology Alignment and Portfolio Prioritization (TAPP): Advanced Methods in Strategic Analysis, Technology Forecasting and Long Term Planning for Human Exploration and Operations, Advanced Exploration Systems and Advanced Concepts

The Advanced Concepts Office (ACO) at NASA, Marshall Space Flight Center is expanding its current technology assessment methodologies. ACO is developing a framework called TAPP that uses a variety of methods, such as association mining and rule learning from data mining, structure development using a Technological Innovation System (TIS), and social network modeling to measure structural relationships. The role of ACO is to 1) produce a broad spectrum of ideas and alternatives for a variety of NASA's missions, 2) determine mission architecture feasibility and appropriateness to NASA's strategic plans, and 3) define a project in enough detail to establish an initial baseline capable of meeting mission objectives ACO's role supports the decision­-making process associated with the maturation of concepts for traveling through, living in, and understanding space. ACO performs concept studies and technology assessments to determine the degree of alignment between mission objectives and new technologies. The first step in technology assessment is to identify the current technology maturity in terms of a technology readiness level (TRL). The second step is to determine the difficulty associated with advancing a technology from one state to the next state. NASA has used TRLs since 1970 and ACO formalized them in 1995. The DoD, ESA, Oil & Gas, and DoE have adopted TRLs as a means to assess technology maturity. However, "with the emergence of more complex systems and system of systems, it has been increasingly recognized that TRL assessments have limitations, especially when considering [the] integration of complex systems." When performing the second step in a technology assessment, NASA requires that an Advancement Degree of Difficulty (AD2) method be utilized. NASA has used and developed or used a variety of methods to perform this step: Expert Opinion or Delphi Approach, Value Engineering or Value Stream, Analytical Hierarchy Process (AHP), Technique for the Order of Prioritization by Similarity to Ideal Solution (TOPSIS), and other multi­‐criteria decision-making methods. These methods can be labor-intensive, often contain cognitive or parochial bias, and do not consider the competing prioritization between mission architectures. Strategic Decision-Making (SDM) processes cannot be properly understood unless the context of the technology is understood. This makes assessing technological change particularly challenging due to the relationships "between incumbent technology and the incumbent (innovation) system in relation to the emerging technology and the emerging innovation system." The central idea in technology dynamics is to consider all activities that contribute to the development, diffusion, and use of innovations as system functions. Bergek defines system functions within a TIS to address what is actually happening and has a direct influence on the ultimate performance of the system and technology development. ACO uses similar metrics and is expanding these metrics to account for the structure and context of the technology. At NASA technology and strategy is strongly interrelated. NASA's Strategic Space Technology Investment Plan (SSTIP) prioritizes those technologies essential to the pursuit of NASA's missions and national interests. The SSTIP is strongly coupled with NASA's Technology Roadmaps to provide investment guidance during the next four years, within a twenty-year horizon. This paper discusses the methods ACO is currently developing to better perform technology assessments while taking into consideration Strategic Alignment, Technology Forecasting, and Long Term Planning.

Funaro, Gregory V.↗
DOE OSTI2025

Simulating Atmospheric Processes in Earth System Models and Quantifying Uncertainties With Deep Learning Multi‐Member and Stochastic Parameterizations

Abstract Deep learning is a powerful tool to represent subgrid processes in climate models, but many application cases have so far used idealized settings and deterministic approaches. Here, we develop stochastic parameterizations with calibrated uncertainty quantification to learn subgrid convective and turbulent processes and surface radiative fluxes of a superparameterization embedded in an Earth System Model (ESM). We explore three methods to construct stochastic parameterizations: (a) a single Deep Neural Network (DNN) with Monte Carlo Dropout; (b) a multi‐member parameterization; and (c) a Variational Encoder Decoder with latent space perturbation. We show that the multi‐member parameterization improves the representation of convective processes, especially in the planetary boundary layer, compared to individual DNNs. The respective uncertainty quantification illustrates that methods (b) and (c) are advantageous compared to a dropout‐based DNN parameterization regarding the spread of convective processes. Hybrid simulations with our best‐performing multi‐member parameterizations remained challenging and crash within the first days. Therefore, we develop a pragmatic partial coupling strategy relying on the superparameterization for condensate emulation. Partial coupling reduces the computational efficiency of hybrid Earth‐like simulations but enables model stability over 5 months with our multi‐member parameterizations. However, our hybrid simulations exhibit biases in thermodynamic fields and differences in precipitation patterns. Despite this, the multi‐member parameterizations enable improvements in reproducing tropical extreme precipitation compared to a traditional convection parameterization. Despite these challenges, our results indicate the potential of a new generation of multi‐member machine learning parameterizations leveraging uncertainty quantification to improve the representation of stochasticity of subgrid effects.

Behrens, Gunnar [Deutsches Zentrum für Luft‐ und R↗
NASA NTRS2014

Use of Semi-Autonomous Tools for ISS Commanding and Monitoring

As the International Space Station (ISS) has moved into a utilization phase, operations have shifted to become more ground-based with fewer mission control personnel monitoring and commanding multiple ISS systems. This shift to fewer people monitoring more systems has prompted use of semi-autonomous console tools in the ISS Mission Control Center (MCC) to help flight controllers command and monitor the ISS. These console tools perform routine operational procedures while keeping the human operator "in the loop" to monitor and intervene when off-nominal events arise. Two such tools, the Pre-positioned Load (PPL) Loader and Automatic Operators Recorder Manager (AutoORM), are used by the ISS Communications RF Onboard Networks Utilization Specialist (CRONUS) flight control position. CRONUS is responsible for simultaneously commanding and monitoring the ISS Command & Data Handling (C&DH) and Communications and Tracking (C&T) systems. PPL Loader is used to uplink small pieces of frequently changed software data tables, called PPLs, to ISS computers to support different ISS operations. In order to uplink a PPL, a data load command must be built that contains multiple user-input fields. Next, a multiple step commanding and verification procedure must be performed to enable an onboard computer for software uplink, uplink the PPL, verify the PPL has incorporated correctly, and disable the computer for software uplink. PPL Loader provides different levels of automation in both building and uplinking these commands. In its manual mode, PPL Loader automatically builds the PPL data load commands but allows the flight controller to verify and save the commands for future uplink. In its auto mode, PPL Loader automatically builds the PPL data load commands for flight controller verification, but automatically performs the PPL uplink procedure by sending commands and performing verification checks while notifying CRONUS of procedure step completion. If an off-nominal condition occurs during procedure execution, PPL Loader notifies CRONUS through popup messages, allowing CRONUS to examine the situation and choose an option of how PPL loader should proceed with the procedure. The use of PPL Loader to perform frequent, routine PPL uplinks offloads CRONUS to better monitor two ISS systems. It also reduces procedure performance time and decreases risk of command errors. AutoORM identifies ISS communication outage periods and builds commands to lock, playback, and unlock ISS Operations Recorder files. Operation Recorder files are circular buffer files of continually recorded ISS telemetry data. Sections of these files can be locked from further writing, be played back to capture telemetry data that occurred during an ISS loss of signal (LOS) period, and then be unlocked for future recording use. Downlinked Operation Recorder files are used by mission support teams for data analysis, especially if failures occur during LOS. The commands to lock, playback, and unlock Operations Recorder files are encompassed in three different operational procedures and contain multiple user-input fields. AutoORM provides different levels of automation for building and uplinking the commands to lock, playback, and unlock Operations Recorder files. In its automatic mode, AutoORM automatically detects ISS LOS periods, then generates and uplinks the commands to lock, playback, and unlock Operations Recorder files when MCC regains signal with ISS. AutoORM also features semi-autonomous and manual modes which integrate CRONUS more into the command verification and uplink process. AutoORMs ability to automatically detect ISS LOS periods and build the necessary commands to preserve, playback, and release recorded telemetry data greatly offloads CRONUS to perform more high-level cognitive tasks, such as mission planning and anomaly troubleshooting. Additionally, since Operations Recorder commands contain numerical time input fields which are tedious for a human to manually build, AutoORM's ability to automatically build commands reduces operational command errors. PPL Loader and AutoORM demonstrate principles of semi-autonomous operational tools that will benefit future space mission operations. Both tools employ different levels of automation to perform simple and routine procedures, thereby offloading human operators to perform higher-level cognitive tasks. Because both tools provide procedure execution status and highlight off-nominal indications, the flight controller is able to intervene during procedure execution if needed. Semi-autonomous tools and systems that can perform routine procedures, yet keep human operators informed of execution, will be essential in future long-duration missions where the onboard crew will be solely responsible for spacecraft monitoring and control.

Brzezinski, Amy S.↗