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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Long Duration Head Down Tilt Bed Rest and Spaceflight Effects on Neurocognitive Performance: Extent, Longevity and Neural Bases

We have recently completed a long duration head down tilt bed rest (HDBR) study in which we performed structural and functional magnetic resonance brain imaging to identify the relationships between changes in neurocognitive function and neural structural alterations in a spaceflight analog environment. We are also collecting the same measures in crewmembers prior to and following a six month International Space Station mission. We will present data demonstrating that bed rest resulted in functional mobility and balance deterioration with recovery post-HDBR. We observed numerous changes in brain structure, function, and connectivity relative to a control group which were associated with pre to post bed rest changes in sensorimotor function. For example, gray matter volume (GMv) increased in posterior parietal areas and decreased in frontal regions. GMv increases largely overlapped with fluid decreases and vice versa. Larger increases in precentral gyrus (M1)/ postcentral gyrus (S1+2) GMv and fluid decreases were associated with smaller balance decrements. Vestibular activation in the bilateral insular cortex increased with bed rest and subsequently recovered. Larger increases in vestibular activation in multiple brain regions were associated with greater decrements in balance and mobility. We found connectivity increases between left M1 with right S1+2 and the superior parietal lobule, and right vestibular cortex with the cerebellum. Decreases were observed between right Lobule VIII with right S1+2 and the supramarginal gyrus, right posterior parietal cortex (PPC) with occipital regions, and the right superior posterior fissure with right Crus I and II. Connectivity strength between left M1 and right S1+2/superior parietal lobule increased the most in individuals that exhibited the least balance impairments. In sum, we observed HDBR-related changes in measures of brain structure, function, and network connectivity, which correlated with indices of sensorimotor function. Recovery was observed post HDBR but remained incomplete at 12 days post-HDBR. Preliminary findings from our parallel ongoing flight study will be compared and contrasted with bed rest results during this presentation.

Seidler, R. D.↗
NASA NTRS2017

Spaceflight Effects on Neurocognitive Performance: Extent, Longevity and Neural Bases

We are conducting ongoing experiments in which we are performing structural and functional magnetic resonance brain imaging to identify the relationships between changes in neurocognitive function and neural structural alterations following a six month International Space Station mission. Our central hypothesis is that measures of brain structure, function, and network integrity will change from pre to post spaceflight. Moreover, we predict that these changes will correlate with indices of cognitive, sensory, and motor function in a neuroanatomically selective fashion. Our interdisciplinary approach utilizes cutting edge neuroimaging techniques and a broad ranging battery of sensory, motor, and cognitive assessments that are conducted pre flight, during flight, and post flight to investigate potential neuroplastic and maladaptive brain changes in crewmembers following long-duration spaceflight. Success in this endeavor would 1) result in identification of the underlying neural mechanisms and operational risks of spaceflight-induced changes in behavior, and 2) identify whether a return to normative behavioral function following re-adaptation to Earth's gravitational environment is associated with a restitution of brain structure and function or instead is supported by substitution with compensatory brain processes. We have collected data on several crewmembers and preliminary findings will be presented. Eventual comparison to results from our parallel bed rest study will enable us to parse out the multiple mechanisms contributing to any spaceflight-induced neural structural and behavioral changes that we observe.

Seidler, R. D.↗
NASA NTRS2017

Effects of One Year of Spaceflight on Neurocognitive Function

It is known that spaceflight adversely affects human sensorimotor function. With interests in longer duration deep space missions it is important to understand microgravity dose-response relationships. NASA's One Year Mission project allows for comparison of the effects of one year in space with those seen in more typical six month missions to the International Space Station. In the Neuromapping project we are performing structural and functional magnetic resonance brain imaging to identify the relationships between changes in neurocognitive function and neural structural alterations following a six month International Space Station mission. Our central hypothesis is that measures of brain structure, function, and network integrity will change from pre- to post-spaceflight. Moreover, we predict that these changes will correlate with indices of cognitive, sensory, and motor function in a neuroanatomically selective fashion. Our interdisciplinary approach utilizes cutting edge neuroimaging techniques and a broad-ranging battery of sensory, motor, and cognitive assessments that are conducted pre-flight, during flight, and post-flight to investigate potential neuroplastic and maladaptive brain changes in crewmembers following long-duration spaceflight. With the one year mission we had one crewmember participate in all of the same measures pre-, per- and post-flight as in our ongoing study. During this presentation we will provide an overview of the magnitude of changes observed with our brain and behavioral assessments for the one year crewmember in comparison to participants that have completed our six month study to date.

Seidler, R. D.↗
NASA NTRS1992

Wide-Angle, Reflective Strip-Imaging Camera

Proposed camera images thin, striplike portion of field of view of 180 degrees wide. Hemispherical concave reflector forms image onto optical fibers, which transfers it to strip of photodetectors or spectrograph. Advantages include little geometric distortion, achromatism, and ease of athermalization. Uses include surveillance of clouds, coarse mapping of terrain, measurements of bidirectional reflectance distribution functions of aerosols, imaging spectrometry, oceanography, and exploration of planets.

Vaughan, Arthur H.↗
NASA NTRS2011

Image Quality of the Helioseismic and Magnetic Imager (HMI) Onboard the Solar Dynamics Observatory (SDO)

We describe the imaging quality of the Helioseismic and Magnetic Imager (HMI) onboard the Solar Dynamics Observatory (SDO) as measured during the ground calibration of the instrument. We describe the calibration techniques and report our results for the final configuration of HMI. We present the distortion, modulation transfer function, stray light,image shifts introduced by moving parts of the instrument, best focus, field curvature, and the relative alignment of the two cameras. We investigate the gain and linearity of the cameras, and present the measured flat field.

Solar Dynamics Observatory↗
DOE OSTI2025

Mitigating imaging systematics for DESI 2024 emission Line Galaxies and beyond

Emission Line Galaxies (ELGs) are one of the main tracers that the Dark Energy Spectroscopic Instrument (DESI) uses to probe the universe. However, they are afflicted by strong spurious correlations between target density and observing conditions known as imaging systematics. In this paper, we present the imaging systematics mitigation applied to the DESI Data Release 1 (DR1) large-scale structure catalogs used in the DESI 2024 cosmological analyses. We also explore extensions of the fiducial treatment. This includes a combined approach, through forward image simulations (Obiwan) in conjunction with neural network-based regression, to obtain an angular selection function that mitigates the imaging systematics observed in the DESI DR1 ELGs target density. We further derive a line of sight selection function from the forward model that removes the strong redshift dependence between imaging systematics and low redshift ELGs. Combining both angular and redshift-dependent systematics, we construct a three-dimensional selection function and assess the impact of all selection functions on clustering statistics. We quantify differences between these extended treatments and the fiducial treatment in terms of the measured 2-point statistics. We find that the results are generally consistent with the fiducial treatment and conclude that the differences are far less than the imaging systematics uncertainty included in DESI 2024 full-shape measurements. We extend our investigation to the ELGs at 0.6 < z < 0.8, i.e., beyond the redshift range (0.8 < z < 1.6) adopted for the DESI clustering catalog, and demonstrate that determining the full three-dimensional selection function is necessary in this redshift range. Our tests showed that all changes are consistent with statistical noise for BAO analyses indicating they are robust to even severe imaging systematics. Specific tests for the full-shape analysis will be presented in a companion paper.

79 ASTRONOMY AND ASTROPHYSICS↗
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↗
NASA NTRS1990

Computerized tomographic imaging for space plasma physics

The measurement of plasma electron velocity distribution functions as a problem in imaging and image reconstruction is considered. A model instrument that measures the integral of the distribution function along lines in velocity space is presented. This allows the use of the powerful mathematical and numerical methods that have recently been so successful in other areas of imaging. It is found that this approach leads to classes of instruments that are qualitatively different from contemporary designs. An investigation of different methods of reconstruction of the distribution function from integral measurements reveals that the mathematical tools appropriate to one particular imaging problem may be very different from those required to deal with another.

Zhang, Yuhong↗
NASA NTRS1972

Optical to optical interface device

The development, fabrication, and testing of a preliminary model of an optical-to-optical (noncoherent-to-coherent) interface device for use in coherent optical parallel processing systems are described. The developed device demonstrates a capability for accepting as an input a scene illuminated by a noncoherent radiation source and providing as an output a coherent light beam spatially modulated to represent the original noncoherent scene. The converter device developed under this contract employs a Pockels readout optical modulator (PROM). This is a photosensitive electro-optic element which can sense and electrostatically store optical images. The stored images can be simultaneously or subsequently readout optically by utilizing the electrostatic storage pattern to control an electro-optic light modulating property of the PROM. The readout process is parallel as no scanning mechanism is required. The PROM provides the functions of optical image sensing, modulation, and storage in a single active material.

Oliver, D. S.↗
DOE OSTI2021

A glossary of plant cell structures: Current insights and future questions

Abstract In this glossary of plant cell structures, we asked experts to summarize a present-day view of plant organelles and structures, including a discussion of outstanding questions. In the following short reviews, the authors discuss the complexities of the plant cell endomembrane system, exciting connections between organelles, novel insights into peroxisome structure and function, dynamics of mitochondria, and the mysteries that need to be unlocked from the plant cell wall. These discussions are focused through a lens of new microscopy techniques. Advanced imaging has uncovered unexpected shapes, dynamics, and intricate membrane formations. With a continued focus in the next decade, these imaging modalities coupled with functional studies are sure to begin to unravel mysteries of the plant cell.

Biochemistry & Molecular Biology↗
NASA NTRS1977

Design and testing of the navigation model for three axis stabilized earth oriented satellites applied to the ATS-6 satellite image data base

An earth edge methodology has been developed to account for the relative attitude changes between successive ATS-6 images which allows reasonable high quality wind sets to be produced. The method consists of measuring the displacements of the right and left infrared earth edges between successive ATS-6 images as a function of scan line; from these measurements the attitude changes can be deduced and used to correct the apparent cloud displacement measurements. The wind data sets generated from ATS-6 using the earth-edge methodology were compared with those derived from the SMS-1 images (and model) covering the same time period. Quantitative comparisons for low level trade cumuli were made at interpolated uniformly spaced grid points and for selected individual comparison clouds. Selected individual comparison clouds, the root-mean-square differences for the U and V components were 1.0 and 1.2 meters per second with a maximum wind direction difference of 15 deg.

Kuhlow, W. W.↗
NASA NTRS1990

Characteristics of the GOES I-M Imager and Sounder

The design and the parameters of the improved thermal-imaging and sounding instruments (the Imager and the Sounder) that will be part of the instrument complements of the next-generation Geostationary Operational Environmental Satellite (GOES I-M) are discussed. The new design incorporates many features that enhance instrumental reliability over the previous GOES radiometric instruments, such as independently functioning Sounder and Imager, redundancy, and more reliable position sensors and lubrication methods. Tables are presented which list the instrument parameters of the GOES I-M Imager and Sounder and the performance characteristics of the two instruments.

Ernst, Thomas J.↗
NASA NTRS2011

GOATS Image Projection Component

When doing mission analysis and design of an imaging system in orbit around the Earth, answering the fundamental question of imaging performance requires an understanding of the image products that will be produced by the imaging system. GOATS software represents a series of MATLAB functions to provide for geometric image projections. Unique features of the software include function modularity, a standard MATLAB interface, easy-to-understand first-principles-based analysis, and the ability to perform geometric image projections of framing type imaging systems. The software modules are created for maximum analysis utility, and can all be used independently for many varied analysis tasks, or used in conjunction with other orbit analysis tools.

Haber, Benjamin M.↗
DOE OSTI2020

Deep learning approaches for neural decoding across architectures and recording modalities

Decoding behavior, perception or cognitive state directly from neural signals is critical for brain–computer interface research and an important tool for systems neuroscience. In the last decade, deep learning has become the state-of-the-art method in many machine learning tasks ranging from speech recognition to image segmentation. The success of deep networks in other domains has led to a new wave of applications in neuroscience. In this article, we review deep learning approaches to neural decoding. Here, we describe the architectures used for extracting useful features from neural recording modalities ranging from spikes to functional magnetic resonance imaging. Furthermore, we explore how deep learning has been leveraged to predict common outputs including movement, speech and vision, with a focus on how pretrained deep networks can be incorporated as priors for complex decoding targets like acoustic speech or images. Deep learning has been shown to be a useful tool for improving the accuracy and flexibility of neural decoding across a wide range of tasks, and we point out areas for future scientific development.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

The Impact of Pixel Size on the Characterization of Deep Convective Clouds for Calibration

The NASA CERES project provides the scientific community the observed TOA SW and LW fluxes for climate monitoring and climate model validation. CERES utilizes hourly geostationary imager derived broadband fluxes, which rely on the channel radiances and associated cloud retrievals, to estimate the broadband fluxes between CERES observations. This requires stable imager visible channel calibration, which the CERES project verifies by utilizing deep convective clouds (DCC) as an invariant Earth target. GSICS, which is an international collaboration, is also evaluating the DCC invariant target calibration methodology to provide consistent calibration coefficients across geostationary imagers anchored to the Aqua-MODIS calibration reference. Tropical DCC are the brightest, coldest, most Lambertian, top of the atmosphere Earth targets. The DCC invariant target calibration methodology relies on a large ensemble of tropical DCC-identified pixel-level reflectances, which are histogrammed to find the mode reflectance of the probability density function (PDF). The imager stability is monitored by tracking the monthly DCC PDF mode reflectance over time. Radiometric scaling is accomplished by ratioing the GEO and VIIRS DCC mode reflectance values. The PDF shape and mode dependency on sensor pixel resolution, which varies among sensors, is unknown. This study will characterize the impact of pixel resolution on the DCC PDFs by aggregating Landsat 30-m pixel reflectances into various coarser pixel resolutions ranging from 100-m to 4-km, and comparing the corresponding PDF statistics. This analysis will assist in improving the uncertainty in a DCC-based intercalibration between instruments with different pixel resolutions.

Conor Haney↗