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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Neurochemical phenotype of corticocortical connections in the macaque monkey: quantitative analysis of a subset of neurofilament protein-immunoreactive projection neurons in frontal, parietal, temporal, and cingulate cortices

The neurochemical characteristics of the neuronal subsets that furnish different types of corticocortical connections have been only partially determined. In recent years, several cytoskeletal proteins have emerged as reliable markers to distinguish subsets of pyramidal neurons in the cerebral cortex of primates. In particular, previous studies using an antibody to nonphosphorylated neurofilament protein (SMI-32) have revealed a consistent degree of regional and laminar specificity in the distribution of a subpopulation of pyramidal cells in the primate cerebral cortex. The density of neurofilament protein-immunoreactive neurons was shown to vary across corticocortical pathways in macaque monkeys. In the present study, we have used the antibody SMI-32 to examine further and to quantify the distribution of a subset of corticocortically projecting neurons in a series of long ipsilateral corticocortical pathways in comparison to short corticocortical, commissural, and limbic connections. The results demonstrate that the long association pathways interconnecting the frontal, parietal, and temporal neocortex have a high representation of neurofilament protein-enriched pyramidal neurons (45-90%), whereas short corticocortical, callosal, and limbic pathways are characterized by much lower numbers of such neurons (4-35%). These data suggest that different types of corticocortical connections have differential representation of highly specific neuronal subsets that share common neurochemical characteristics, thereby determining regional and laminar cortical patterns of morphological and molecular heterogeneity. These differences in neuronal neurochemical phenotype among corticocortical circuits may have considerable influence on cortical processing and may be directly related to the type of integrative function subserved by each cortical pathway. Finally, it is worth noting that neurofilament protein-immunoreactive neurons are dramatically affected in the course of Alzheimer's disease. The present results support the hypothesis that neurofilament protein may be crucially linked to the development of selective neuronal vulnerability and subsequent disruption of corticocortical pathways that lead to the severe impairment of cognitive function commonly observed in age-related dementing disorders.

Non-NASA Center↗
NASA NTRSDate not supplied

A Climate and History Case Study of 18th- and 19th-Century Multidecadal Droughts in East Africa Using a new Tree-Ring Drought Atlas

Historians and paleoclimatologists have both identified the decades spanning the late-18th and early-19th centuries in many East African regions as a period of prolonged and severe drought. A challenge that emerges from both the historical evidence and the paleolimnological data that have been primarily used to characterize this drought period, however, concerns the dating of events and the characterization of their spatial character; both oral traditions and lake-core proxies cannot typically offer hydroclimate estimates with seasonal or annual resolution, nor can they provide gridded reconstructions on the order of 1° latitude and longitude. The new East African Drought Atlas (EADA) incorporates far-field dendroclimatic records and several local East African tree-ring chronologies to provide estimates of the self-calibrating Palmer Drought Severity Index (scPDSI) on a 0.5° latitude-longitude grid. We present the Point-by-Point Regression technique that was used to create the EADA, the rationale for the employed input data network, and the calibration and validation skill of the derived hydroclimatic field reconstruction. We use the EADA to characterize the timing of two decadal-scale droughts, centered over the Uganda and Kenya regions, which occurred in the late 18th century and early in the 19th century and were separated by a shorter, but pronounced wet period. We characterize the spatial patterns of the associated events and the dynamical causes that that the patterns imply. The reconstructed droughts are also compared to historical and paleolimnological data to evaluate the robustness of the reconstruction and the degree of agreement across the different sources of information.

Droughts↗
NASA NTRSDate not supplied

A Climate and History Case Study of 18th- and 19th-Century Multidecadal Droughts in East Africa Using a new Tree-Ring Drought Atlas

Historians and paleoclimatologists have both identified the decades spanning the late-18th and early-19th centuries in many East African regions as a period of prolonged and severe drought. A challenge that emerges from both the historical evidence and the paleolimnological data that have been primarily used to characterize this drought period, however, concerns the dating of events and the characterization of their spatial character; both oral traditions and lake-core proxies cannot typically offer hydroclimate estimates with seasonal or annual resolution, nor can they provide gridded reconstructions on the order of 1° latitude and longitude. The new East African Drought Atlas (EADA) incorporates far-field dendroclimatic records and several local East African tree-ring chronologies to provide estimates of the self-calibrating Palmer Drought Severity Index (scPDSI) on a 0.5° latitude-longitude grid. We present the Point-by-Point Regression technique that was used to create the EADA, the rationale for the employed input data network, and the calibration and validation skill of the derived hydroclimatic field reconstruction. We use the EADA to characterize the timing of two decadal-scale droughts, centered over the Uganda and Kenya regions, which occurred in the late 18th century and early in the 19th century and were separated by a shorter, but pronounced wet period. We characterize the spatial patterns of the associated events and the dynamical causes that that the patterns imply. The reconstructed droughts are also compared to historical and paleolimnological data to evaluate the robustness of the reconstruction and the degree of agreement across the different sources of information.

Droughts↗
NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth independence and autonomy of mission operations. Here we present an overview of AI/ML architecture to support deep space mission goals, developed with leaders in the field. First, we focus on the fundamental biological research that supports our understanding of physiological responses to spaceflight, and we describe current efforts to support AI/ML research including data standardization and data engineering through maximally open and FAIR (findable, accessible, interoperable, reusable) databases and the generation of AI-ready datasets for reuse and analysis. We also discuss remote data management frameworks for research data as well as environmental and health data that are generated during deep space missions. We highlight several research projects that leverage data standardization and management for fundamental biological discovery to uncover the complex effects of space travel on living systems. Next, we provide an overview of cutting-edge AI/ML approaches that can be integrated to support remote monitoring and analysis during deep space missions, including generative models and large language models to learn the underlying biomedical patterns and predict outcomes or answer questions during off world medical scenarios. We also describe current AI/ML methods to support this research and monitoring through automated cloud-based labs which enable limited human intervention and closed-loop experimentation in remote settings. These labs could support mission autonomy by analyzing environmental data streams, and would be facilitated through in situ analytics capabilities to avoid sending large raw data files through low bandwidth communications. Finally, in the context of deep space missions with limited communications or access to medical advice from Earth, we describe a solution for integrated, real-time mission biomonitoring across hierarchical levels from continuous environmental monitoring, to wearables and point-of-care devices, to molecular and physiological monitoring. We introduce a precision space health system that will ensure that the future of space health is predictive, preventative, participatory and personalized.

artificial intelligence↗
NASA NTRS1990

The vestibular nerve of the chinchilla. III. Peripheral innervation patterns in the utricular macula

1. Nerve fibers supplying the utricular macula of the chinchilla were labeled by extracellular injection of horseradish peroxidase into the vestibular nerve. The peripheral terminations of individual fibers were reconstructed and related to the regions of the end organ they innervated and to the sizes of their parent axons. 2. The macula is divided into medial and lateral parts by the striola, a narrow zone that runs for almost the entire length of the sensory epithelium. The striola can be distinguished from the extrastriolar regions to either side of it by the wider spacing of its hair cells. Calyx endings in the striola have especially thick walls, and, unlike similar endings in the extrastriola, many of them innervate more than one hair cell. The striola occupies 10% of the sensory epithelium; the lateral extrastriola, 50%; and the medial extrastriola, 40%. 3. The utricular nerve penetrates the bony labyrinth anterior to the end organ. Axons reaching the anterior part of the sensory epithelium run directly through the connective tissue stroma. Those supplying more posterior regions first enter a fiber layer located at the bottom of the stroma. Approximately one-third of the axons bifurcate below the epithelium, usually within 5-20 microns of the basement membrane. Bifurcations are more common in fibers destined for the extrastriola than for the striola. 4. Both calyx and bouton endings were labeled. Calyces can be simple or complex. Simple calyces innervate individual hair cells, whereas complex calyces supply 2-4 adjacent hair cells. Complex endings are more heavily concentrated in the striola than in the extrastriola. Simple calyces and boutons are found in all parts of the epithelium. Calyces emerge from the parent axon or one of its thick branches. Boutons, whether en passant or terminal, are located on thin collaterals. 5. Fibers can be classified into calyx, bouton, or dimorphic categories. The first type only has calyx endings; the second, only bouton endings; and the third, both kinds of endings. Calyx units make up 6% of the labeled fibers, bouton units less than 2%, and dimorphic units greater than 92%. The three fiber types differ in the macular zones they supply and in the diameters of their parent axons. Calyx units were restricted to the striola. The few bouton units were found in the extrastriola.(ABSTRACT TRUNCATED AT 400 WORDS).

NASA Discipline Neuroscience↗
NASA NTRS2019

Predictive Modeling for Differential Diagnosis and Mortality Risk Assessment

The prevalence of electronic health record (EHR) systems has brought prodigious biomedical informatics opportunity. Automated machine learning methods can effectively utilize such data and have become common tools for healthcare predictive modeling. Researches in medical informatics have explored the potential of deep learning and classical models in emergent care scenarios. In particular, predicting differential diagnoses for admissions have proven useful in decreasing unnecessary lab tests and improving inpatient triage decision-making. Moreover, identification of high-risk patients for in-hospital mortality is vitally important to maximize allocation of medical resources.The Medical Information Mart for Intensive Care (MIMIC-III) database, containing de-identified critical care inpatient was used in our study. This data set captures hospital patient laboratory measurements, pharmacologic prescriptions, diagnostic data and procedure event recordings. When considering adult patients and discounting admissions with ICU length of stay less than 24 hours, there were 37,787 unique admissions and 30,414 total patients. We examined the top 25 most prevalent ICD-9 group-level disease specificities in MIMIC-III using a multi-label classification model. In-hospital mortality was modeled as binary classification with 4,155 (13%) adult patients that expired, of which 3,138 (75.5%) were in the ICU setting. The metrics AUC, F1 score, sensitivity and specificity values calculated for each disease label measured prediction performance.The usage of ICD-9 group codes reduced feature dimension from 14,567 to 942 and greatly improved distribution of patient diagnostic categories. Disease temporal patterns were captured by considering the most frequently sampled 6 vital signs and 13 laboratory values. Missing data were imputed at each time-stamp. Time-series raw hourly average values were converted into 5 summary features (mean, standard deviation, number of observations, min & max values). Patient demographic variables such as age, gender, marital status and ethnicity were also factored into the modeling. Choi et al showed that contextual embedding of medical data, diagnostic and procedural codes alone can predict future diagnoses with sensitivity as high as 0.79. We utilized an embedding technique called word2vec which allowed sparse representations of medical history to be transformed into dense word vectors. The mappings captured contextual information by treating each admission as a sentence and learning the most likely neighboring words in a sliding window fashion. Binary and multi-label classification was achieved via collapse models, which do not consider temporal information, as well as recurrent neural networks with regularization, Softmax output layer activation together with categorical cross-entropy as the loss function.

US Army collaboration↗
NASA NTRS2008

Application of Ruze Equation for Inflatable Aperture Antennas

Inflatable aperture reflector antennas are an emerging technology that NASA is investigating for potential uses in science and exploration missions. As inflatable aperture antennas have not been proven fully qualified for space missions, they must be characterized properly so that the behavior of the antennas can be known in advance. To properly characterize the inflatable aperture antenna, testing must be performed in a relevant environment, such as a vacuum chamber. Since the capability of having a radiofrequency (RF) test facility inside a vacuum chamber did not exist at NASA Glenn Research Center, a different methodology had to be utilized. The proposal to test an inflatable aperture antenna in a vacuum chamber entailed performing a photogrammetry study of the antenna surface by using laser ranging measurements. A root-mean-square (rms) error term was derived from the photogrammetry study to calculate the antenna surface loss as described by the Ruze equation. However, initial testing showed that problems existed in using the Ruze equation to calculate the loss due to errors on the antenna surface. This study utilized RF measurements obtained in a near-field antenna range and photogrammetry data taken from a laser range scanner to compare the expected performance of the test antenna (via the Ruze equation) with the actual RF patterns and directivity measurements. Results showed that the Ruze equation overstated the degradation in the directivity calculation. Therefore, when the photogrammetry study is performed on the test antennas in the vacuum chamber, a more complex equation must be used in light of the fact that the Ruze theory overstates the loss in directivity for inflatable aperture reflector antennas.

Welch, Bryan W.↗
NASA NTRS2019

Supporting Crew Autonomy in Deep Space Exploration: Preliminary Onboard Capability Requirements and Proposed Research Questions. Technical Report of the Autonomous Crew Operations Technical Interchange Meeting

Communication delays are a critical challenge posed by long duration deep space exploration. Space missions historically have relied on an ever-present Mission Control Center (MCC) to direct operations in near real-time. As unanticipated anomalies that defeat fault detection and resolution systems do arise, the lack of real-time communication will significantly weaken what the MCC support represents: a reliable safety net for the flight crew through its deep and diverse areas of expertise and investigative resources. As a consequence, future space vehicles and habitats need to be equipped with capabilities to support the flight crew to operate with little or no ground support. Considerations must be given to vehicle and mission designs that will fortify the traditionally ground-centered safety net and forge new support systems, when communication delays exist. In August 2018, NASA’s Human Research Program, through its Human Factors and Behavioral Performance Element, convened a Technical Interchange Meeting (TIM) on Autonomous Crew Operations at NASA Ames Research Center. The goal of the meeting was to gather input from NASA centers, industry, academia, and branches of the Department of Defense (DoD) to address how intelligent technologies can be applied to augment onboard capabilities to support crew anomaly response. The TIM featured 24 presentations by 29 speakers and hosted a total of 59 attendees, including 43 from 5 NASA centers (Ames, Johnson, Langley, Marshall, and Jet Propulsion Lab) and 4 from the DoD (3 from Army Research Lab and 1 from Naval Postgraduate School), with remaining attendees from academia (e.g., UC Davis, CMU) and industry (e.g., IBM, Siemens). Discussions were centered around three themes: standards and guidelines, lessons learned in analog environments, and technologies. To help provide a framework for discussion, a concept matrix describing anomaly response processes was created prior to the TIM (Figure 1, page 6). The matrix captures the steps involved (monitoring and detection, diagnosis, solution development and evaluation, solution implementation and verification, resolution documentation) as well as the resources and capabilities required to support these steps (data, knowledge, analysis, synthesis, resource management). A wallpaper size printout of the matrix was utilized at the TIM to solicit attendee inputs along the three themes; the activity garnered 108 submissions of ideas. Overall, what emerged from TIM discussions was a picture of mismatch between crew anomaly response needs and support that can be provided by existing intelligent technologies. The needs are broad, spanning multiple steps and processes/resources, with many of which lacking support from existing technologies, such as knowledge management throughout the steps of problem solving (especially in resolution documentation) and manpower management. The solutions provided by existing intelligent technologies are specific to the steps/processes that they are designed to support and constrained to solving only problems similar to those that have occurred before. What is lacking from technologies is typically made up by humans, specifically their complex critical thinking, creative problem solving, and domain expertise. In the end, the TIM highlighted the pressing need to support responses to onboard anomalies during autonomous crew operations, particularly those that have eluded the system tests, inspection, and other assurance processes. Such anomalies can potentially threaten crew and vehicle safety, as well as significantly impact overall operations with additional workload. These fairly rare events are difficult to anticipate and prepare for, given the state-of-the-art in intelligent technologies. This is true even for anomalies that stem from “unknown knowns”—cases in which there is sufficient external information to characterize the problem but the overall pattern fails to be recognized by the problem solver, or in which the internal knowledge needed to solve a problem is held tacitly and potentially accessible by the problem solver but not articulated. It follows that the ability to tackle anomalies lies not only with the availability of relevant information and knowledge but also their accessibility in times of need. To that end, we propose research questions along the following three broad themes: • How intelligent technologies can help make relevant knowledge and information available? • How intelligent technologies can help make relevant knowledge and information accessible? • How intelligent technologies can help support the crew operating as a team in anomaly response processes?

autonomous crew operations↗
NASA NTRS2010

Adaptive Data-based Predictive Control for Short Take-off and Landing (STOL) Aircraft

Data-based Predictive Control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. The characteristics of adaptive data-based predictive control are particularly appropriate for the control of nonlinear and time-varying systems, such as Short Take-off and Landing (STOL) aircraft. STOL is a capability of interest to NASA because conceptual Cruise Efficient Short Take-off and Landing (CESTOL) transport aircraft offer the ability to reduce congestion in the terminal area by utilizing existing shorter runways at airports, as well as to lower community noise by flying steep approach and climb-out patterns that reduce the noise footprint of the aircraft. In this study, adaptive data-based predictive control is implemented as an integrated flight-propulsion controller for the outer-loop control of a CESTOL-type aircraft. Results show that the controller successfully tracks velocity while attempting to maintain a constant flight path angle, using longitudinal command, thrust and flap setting as the control inputs.

Barlow, Jonathan Spencer↗
NASA NTRS1991

Cyclic variations in nitrogen uptake rate of soybean plants: effects of pH and mixed nitrogen sources

To determine if the daily pattern of NO3- and NH4+ uptake is affected by acidity or NO3- : NH4+ ratio of the nutrient solution, non-nodulated soybean plants (Glycine max) were exposed for 21 days to replenished, complete nutrient solutions at pH 6.0, 5.5, 5.0, and 4.5 which contained either 1.0 mM NH4+, 1.0 mM NO3- [correction of NO3+], 0.67 mM NH4+ plus 0.33 mM NO3- (2:1 NH4+ : NO3-) [correction of (2:1 NH3+ : NO4-)], or 0.33 mM NH4+ plus 0.67 mM NO3- (1:2 NH4+ : NO3-). Net uptake rates of NH4+ and NO3- were measured daily by ion chromatography as depletion from the replenished solutions. When NH4+ and NO3- were supplied together, cumulative uptake of total nitrogen was not affected by pH or solution NH4+ : NO3- ratio. The cumulative proportion of nitrogen absorbed as NH4+ decreased with increasing acidity; however, the proportional uptake of NH4+ and NO3- was not constant, but varied day-to-day. This day-to-day variation in relative proportions of NH4+ and NO3- absorbed when NH4+ : NO3- ratio and pH of solution were constant indicates that the regulatory mechanism is not directly competitive. Regardless of the effect of pH on cumulative uptake of NH4+, the specific nitrogen uptake rates from mixed and from individual NH4+ and NO3- sources oscillated between maxima and minima at each pH with average periodicities similar to the expected interval of leaf emergence.

Non-NASA Center↗
NASA NTRS2012

Best Practices for the Application of Functional Near Infrared Spectroscopy to Operator State Sensing

Functional Near Infrared Spectroscopy (fNIRS) is an emerging neuronal measurement technique with many advantages for application in operational and training contexts. Instrumentation and protocol improvements, however, are required to obtain useful signals and produce expeditiously self-applicable, comfortable and unobtrusive headgear. Approaches for improving the validity and reliability of fNIRS data for the purpose of sensing the mental state of commercial aircraft operators are identified, and an exemplary system design for attentional state monitoring is outlined. Intelligent flight decks of the future can be responsive to state changes to optimally support human performance. Thus, the identification of cognitive performance decrement, such as lapses in operator attention, may be used to predict and avoid error-prone states. We propose that attentional performance may be monitored with fNIRS through the quantification of hemodynamic activations in cortical regions which are part of functionally-connected attention and resting state networks. Activations in these regions have been shown to correlate with behavioral performance and task engagement. These regions lie beneath superficial tissue in head regions beyond the forehead. Headgear development is key to reliably and robustly accessing locations beyond the hair line to measure functionally-connected networks across the whole head. Human subject trials using both fNIRS and functional Magnetic Resonance Imaging (fMRI) will be used to test this system. Data processing employs Support Vector Machines for state classification based on the fNIRS signals. If accurate state classification is achieved based on sensed activation patterns, fNIRS will be shown to be useful for monitoring attentional performance.

Harrivel, Angela R.↗
NASA NTRS2016

Meeting the Grand Challenge of Protecting Astronauts Health: Electrostatic Active Space Radiation Shielding for Deep Space Missions

This report describes the research completed during 2011 for the NASA Innovative Advanced Concepts (NIAC) project. The research is motivated by the desire to safely send humans in deep space missions and to keep radiation exposures within permitted limits. To this end current material shielding, developed for low earth orbit missions, is not a viable option due to payload and cost penalties. The active radiation shielding is the path forward for such missions. To achieve active space radiation shielding innovative large lightweight gossamer space structures are used. The goal is to deflect enough positive ions without attracting negatively charged plasma and to investigate if a charged Gossamer structure can perform charge deflections without significant structural instabilities occurring. In this study different innovative configurations are explored to design an optimum active shielding. In addition, to establish technological feasibility experiments are performed with up to 10kV of membrane charging, and an electron flux source with up to 5keV of energy and 5mA of current. While these charge flux energy levels are much less than those encountered in space, the fundamental coupled interaction of charged Gossamer structures with the ambient charge flux can be experimentally investigated. Of interest are, will the EIMS remain inflated during the charge deflections, and are there visible charge flux interactions. Aluminum coated Mylar membrane prototype structures are created to test their inflation capability using electrostatic charging. To simulate the charge flux, a 5keV electron emitter is utilized. The remaining charge flux at the end of the test chamber is measured with a Faraday cup mounted on a movable boom. A range of experiments with this electron emitter and detector were performed within a 30x60cm vacuum chamber with vacuum environment capability of 10-7 Torr. Experiments are performed with the charge flux aimed at the electrostatically inflated membrane structure (EIMS) in both charged and uncharged configurations. The amount of charge shielding behind and around the EIMS was studied for different combinations of membrane structure voltages and electron energies. Both passive and active shielding were observed, with active shielding capable of deflecting nearly all incoming electrons. The pattern of charge distribution around the structure was studied as well as the stability of the structures in the charge flow. The charge deflection experiments illustrate that the EIMS remain inflated during charge deflection, but will experience small amplitude oscillations. Investigations were performed to determine a potential cause of the vibrations. It is postulated these vibrations are due to the charge flux causing local membrane charge distribution changes. As the membrane structure inflation pressure is changed, the shape responds, and causes the observed sustained vibration. Having identified this phenomenon is important when considering electrostatically inflated membrane structures (EIMS) in a space environment. Additionally, this project included a study of membrane material impacts, specifically the impact of membrane thickness. Extremely thin materials presented new challenges with vacuum preparation techniques and rapid charging. The thinner and lighter membrane materials were successfully inflated using electrostatic forces in a vacuum chamber. However, care must be taken when varying the potentials of such lighter structures as the currents can cause local heating and melting of the very thin membranes. Lastly, a preliminary analysis is performed to study rough order of magnitude power requirements for using EIMS for radiation shielding. The EIMS power requirement becomes increasingly more challenging as the spacecraft voltage is increased. As a result, the emphasis is on the deflection of charges away from the spacecraft rather than totally stopping them. This significantly alleviates the initial power requirements. With modest technological development(s) active shielding is emerging to be a viable option.

Radiation↗
NASA NTRS1988

The effect of exhaust plume/afterbody interaction on installed Scramjet performance

Newly emerging aerospace technology points to the feasibility of sustained hypersonic flight. Designing a propulsion system capable of generating the necessary thrust is now the major obstacle. First-generation vehicles will be driven by air-breathing scramjet (supersonic combustion ramjet) engines. Because of engine size limitations, the exhaust gas leaving the nozzle will be highly underexpanded. Consequently, a significant amount of thrust and lift can be extracted by allowing the exhaust gases to expand along the underbody of the vehicle. Predicting how these forces influence overall vehicle thrust, lift, and moment is essential to a successful design. This work represents an important first step toward that objective. The UWIN code, an upwind, implicit Navier-Stokes computer program, has been applied to hypersonic exhaust plume/afterbody flow fields. The capability to solve entire vehicle geometries at hypersonic speeds, including an interacting exhaust plume, has been demonstrated for the first time. Comparison of the numerical results with available experimental data shows good agreement in all cases investigated. For moderately underexpanded jets, afterbody forces were found to vary linearly with the nozzle exit pressure, and increasing the exit pressure produced additional nose-down pitching moment. Coupling a species continuity equation to the UWIN code enabled calculations indicating that exhaust gases with low isentropic exponents (gamma) contribute larger afterbody forces than high-gamma exhaust gases. Moderately underexpanded jets, which remain attached to unswept afterbodies, underwent streamwise separation on upswept afterbodies. Highly underexpanded jets produced altogether different flow patterns, however. The highly underexpanded jet creates a strong plume shock, and the interaction of this shock with the afterbody was found to produce complicated patterns of crossflow separation. Finally, the effect of thrust vectoring on vehicle balance has been shown to alter dramatically the vehicle pitching moment.

Edwards, Thomas Alan↗
NASA NTRS2016

Translational Cellular Research on the International Space Station

The emerging field of Translational Research aims to coalesce interdisciplinary findings from basic science for biomedical applications. To complement spaceflight research using human subjects, translational studies can be designed to address aspects of space-related human health risks and help develop countermeasures to prevent or mitigate them, with therapeutical benefits for analogous conditions experienced on Earth. Translational research with cells and model organisms is being conducted onboard the International Space Station (ISS) in connection with various human systems impacted by spaceflight, such as the cardiovascular, musculoskeletal, and immune systems. Examples of recent cell-based translational investigations on the ISS include the following. The JAXA investigation Cell Mechanosensing seeks to identify gravity sensors in skeletal muscle cells to develop muscle atrophy countermeasures by analyzing tension fluctuations in the plasma membrane, which changes the expression of key proteins and genes. Earth applications of this study include therapeutic approaches for some forms of muscular dystrophy, which appear to parallel aspects of muscle wasting in space. Spheroids is an ESA investigation examining the system of endothelial cells lining the inner surface of all blood vessels in terms of vessel formation, cellular proliferation, and programmed cell death, because injury to the endothelium has been implicated as underpinning various cardiovascular and musculoskeletal problems arising during spaceflight. Since endothelial cells are involved in the functional integrity of the vascular wall, this research has applications to Earth diseases such as atherosclerosis, diabetes, and hypertension. The goal of the T-Cell Activation in Aging NASA investigation is to understand human immune system depression in microgravity by identifying gene expression patterns of candidate molecular regulators, which will provide further insight into factors that may play a critical role in immune function loss during aging. In addition, Omics investigations with cells have synergistic applications ranging from the evaluation of pharmacological countermeasures to drug discovery. Thus, cell-based translational research onboard the ISS is bidirectionally bridging cutting-edge cellular and molecular approaches with space bioastronautics and human health methodologies on Earth.

Love, John↗
NASA NTRS1990

Experiment K-6-21. Effect of microgravity on 1) metabolic enzymes of type 1 and type 2 muscle fibers and on 2) metabolic enzymes, neutransmitter amino acids, and neurotransmitter associated enzymes in motor and somatosensory cerebral cortex. Part 1: Metabolic enzymes of individual muscle fibers; part 2: metabolic enzymes of hippocampus and spinal cord

The individual fibers of any individual muscle vary greatly in enzyme composition, a fact which is obscured when enzyme levels of a whole muscle are measured. The purpose of this study was therefore to assess the changes due to weightless on the enzyme patterns composed by the individual fibers within the flight muscles. In spite of the limitation in numbers of muscles examined, it is apparent that: (1) that the size of individual fibers (i.e., their dry weight) was reduced about a third, (2) that this loss in dry mass was accompanied by changes in the eight enzymes studied, and (3) that these changes were different for the two muscles, and different for the two enzyme groups. In the soleus muscle the absolute amounts of the three enzymes of oxidative metabolism decreased about in proportion to the dry weight loss, so that their concentration in the atrophic fibers was almost unchanged. In contrast, there was little loss among the four enzymes of glycogenolysis - glycolysis so that their concentrations were substantially increased in the atrophic fibers. In the TA muscle, these seven enzymes were affected in just the opposite direction. There appeared to be no absolute loss among the oxidative enzymes, whereas the glycogenolytic enzymes were reduced by nearly half, so that the concentrations of the first metabolic group were increased within the atrophic fibers and the concentrations of the second group were only marginally decreased. The behavior of hexokinase was exceptional in that it did not decrease in absolute terms in either type of muscle and probably increased as much as 50 percent in soleus. Thus, their was a large increase in concentration of this enzyme in the atrophied fibers of both muscles. Another clear-cut finding was the large increase in the range of activities of the glycolytic enzymes among individual fibers of TA muscles. This was due to the emergence of TA fibers with activities for enzymes of this group extending down to levels as low as those found in control soleus muscles. It would be interesting to know if this represents a transition stage, and whether with prolonged weightlessness most of the fibers would be transformed into a low glycogenolytic type.

Lowry, O.↗
NASA NTRS2015

Sensitivity of Water Scarcity Events to ENSO-Driven Climate Variability at the Global Scale

Globally, freshwater shortage is one of the most dangerous risks for society. Changing hydro-climatic and socioeconomic conditions have aggravated water scarcity over the past decades. A wide range of studies show that water scarcity will intensify in the future, as a result of both increased consumptive water use and, in some regions, climate change. Although it is well-known that El Niño- Southern Oscillation (ENSO) affects patterns of precipitation and drought at global and regional scales, little attention has yet been paid to the impacts of climate variability on water scarcity conditions, despite its importance for adaptation planning. Therefore, we present the first global-scale sensitivity assessment of water scarcity to ENSO, the most dominant signal of climate variability. We show that over the time period 1961-2010, both water availability and water scarcity conditions are significantly correlated with ENSO-driven climate variability over a large proportion of the global land area (> 28.1 %); an area inhabited by more than 31.4% of the global population. We also found, however, that climate variability alone is often not enough to trigger the actual incidence of water scarcity events. The sensitivity of a region to water scarcity events, expressed in terms of land area or population exposed, is determined by both hydro-climatic and socioeconomic conditions. Currently, the population actually impacted by water scarcity events consists of 39.6% (CTA: consumption-to-availability ratio) and 41.1% (WCI: water crowding index) of the global population, whilst only 11.4% (CTA) and 15.9% (WCI) of the global population is at the same time living in areas sensitive to ENSO-driven climate variability. These results are contrasted, however, by differences in growth rates found under changing socioeconomic conditions, which are relatively high in regions exposed to water scarcity events. Given the correlations found between ENSO and water availability and scarcity conditions, and the relative developments of water scarcity impacts under changing socioeconomic conditions, we suggest that there is potential for ENSO-based adaptation and risk reduction that could be facilitated by more research on this emerging topic.

risk↗
NASA NTRS2019

Software Tool for Tracking & Mapping the NASA Orion AA-2 Test Flight Ejectable Data Recorders in Real Time

On 2 July 2019, the NASA Ascent Abort 2 flight took place off the Florida coast to test the emergency systems to separate the Orion Crew Module (CM) from the future Space Launch System rocket in the event of a malfunction. During this high-altitude test, instrumentation data was recorded on twelve customized buoyant Ejectable Data Recorders (EDRs) and subsequently jettisoned from the CM in mid-air. Upon release, the EDRs activated their GPS-Iridium beacon systems and began transmitting Short Burst Data (SBD) messages via the Iridium satellite network to relay their individual location and system health information. To locate, track and retrieve each EDR from the ocean surface in real-time, multiple open-source programming tools (Python and Linux shells) were developed for parsing the incoming Iridium binary SBD messages. For this, a Linux laptop was used to receive the Iridium-generated emails containing the SBD messages and autonomously execute the parsing tools. The received SBD data contained location, timestamp and health status information that was translated, saved, and subsequently used for simultaneously generating a continuously updated color-coded tabular display summary and unique KML files used with Google Earth to track their locations. Once their locations were known, dedicated recovery vessels retrieved all EDRs from the ocean. An additional tool was also developed in order to generate 5- and 10-minute geolocation predictions for each EDR by deriving the displacement distance, elapsed time, displacement heading and velocity based on the latest known information available. The recovery vessels were also tracked with the use of a separate commercial GPS beacon system. After jettison, 67% of the EDRs transmitted valid data by the time they were retrieved from the ocean. However, the real-time information presented by the plotting tool allowed for the ready depiction of EDR dispersal patterns and reference drift trajectories, which contributed to the recovery of all twelve EDRs and the AA-2 flight data. Lastly, the available data showed that the distance between the software’s reported drift/predicted locations and the recovery locations did not exceed 38 meters, therefore demonstrating the advantages of this software tool for supporting real-time tracking and recovery efforts of beacon devices.

Moxey, Lucas↗
NASA NTRS2014

Ecological Impacts of the Space Shuttle Program at John F. Kennedy Space Center, Florida

The Space Shuttle Program was one of NASAs first major undertakings to fall under the environmental impact analysis and documentation requirements of the National Environmental Policy Act of 1969 (NEPA). Space Shuttle Program activities at John F. Kennedy Space Center (KSC) and the associated Merritt Island National Wildlife Refuge (MINWR) contributed directly and indirectly to both negative and positive ecological trends in the region through the long-term, stable expenditure of resources over the 40 year program life cycle. These expenditures provided support to regional growth and development in conjunction with other sources that altered land use patterns, eliminated and modified habitats, and contributed to cultural eutrophication of the Indian River Lagoon. At KSC, most Space Shuttle Program related actions were conducted in previously developed facilities and industrial areas with the exception of the construction of the shuttle landing facility (SLF) and the space station processing facility (SSPF). Launch and operations impacts were minimal as a result of the low annual launch rate. The majority of concerns identified during the NEPA process such as potential weather modification, acid rain off site, and local climate change did not occur. Launch impacts from deposition of HCl and particulates were assimilated as a result of the high buffering capacity of the system and low launch and loading rates. Metals deposition from exhaust deposition did not display acute impacts. Sub-lethal effects are being investigated as part of the Resource Conservation and Recovery Act (RCRA) regulatory process. Major positive Space Shuttle Program effects were derived from the adequate resources available at the Center to implement the numerous environmental laws and regulations designed to enhance the quality of the environment and minimize impacts from human activities. This included reduced discharges of domestic and industrial wastewater, creation of stormwater management systems, remediation of past contamination sites, implementation of hazardous waste management systems, and creation of a culture of sustainability. Working with partners such as the USFWS and the St Johns River Water Management District (SJRWMD), wetlands and scrub restoration and management initiatives were implemented to enhance fish and wildlife populations at the Center. KSC remains the single largest preserve on the east coast of Florida in part due to NASAs commitment to stewardship. Ongoing Ecological Program projects are directed at development of information and knowledge to address future KSC management questions including the transition to a joint government and commercial launch facility, enhanced habitat management requirements for wetlands and scrub, potential impacts of emerging contaminants, and adaptation to climate change including projected sea level rise over the next 50-75 years.

Space Shuttle Program↗