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The Isothermal Dendritic Growth Experiment (IDGE)

The Isothermal Dendritic Growth Experiment (IDGE) constituted a series of three NASA-supported microgravity experiments, all of which flew aboard the space shuttle, Columbia. This experimental space flight series was designed and operated to grow and record dendrite solidification in the absence of gravity-induced convective heat transfer, and thereby produce a wealth of benchmark-quality data for testing solidification scaling laws. The data and analysis performed on the dendritic growth speed and tip size in Succinontrie (SCN) demonstrates that although the theory yields predictions that are reasonably in agreement with experiment, there are significant discrepancies. However, some of these discrepancies can be explained by accurately describing the diffusion of heat. The key finding involves recognition that the actual three-dimensional shape of dendrites includes time-dependent side-branching and a tip region that is not a paraboloid of revolution. Thus, the role of heat transfer in dendritic growth is validated, with the caveat that a more realistic model of the dendrite then a paraboloid is needed to account for heat flow in an experimentally observed dendrite. We are currently conducting additional analysis to further confirm and demonstrate these conclusions. The data and analyses for the growth selection physics remain much less definitive. From the first flight, the data indicated that the selection parameter, sigma*, is not exactly a constant, but exhibits a slight dependence on the supercooling. Additional data from the second flight are being examined to investigate the selection of a unique dendrite speed, tip size and shape. The IDGE flight series is now complete. We are currently completing analyses and moving towards final data archiving. It is gratifying to see that the IDGE published results and archived data sets are being used actively by other scientists and engineers. In addition, we are also pleased to report that the techniques and IDGE hardware system that the authors developed with NASA, are being currently employed on both designated flight experiments, like EDSE, and on flight definition experiments, like TDSE.

Glicksman, Martin E.↗

Stimulus-response incompatibility activates cortex proximate to three eye fields

We used functional magnetic resonance imaging (fMRI) to investigate cortical activation during the performance of three oculomotor tasks that impose increasing levels of cognitive demand. (1) In a visually guided saccade (VGS) task, subjects made saccades to flashed targets. (2) In a compatible task, subjects made leftward and rightward saccades in response to foveal presentation of the uppercase words "LEFT" or "RIGHT." (3) In a mixed task, subjects made rightward saccades in response to the lowercase word "left" and leftward saccades in response to the lowercase word "right" on incompatible trials (60%). The remaining 40% of trials required compatible responses to uppercase words. The VGS and compatible tasks, when compared to fixation, activated the three cortical eye fields: the supplementary eye field (SEF), the frontal eye field (FEF), and the parietal eye field (PEF). The mixed task, when compared to the compatible task, activated three additional cortical regions proximate to the three eye fields: (1) rostral to the SEF in medial frontal cortex; (2) rostral to the FEF in dorsolateral prefrontal cortex (DLPFC); (3) rostral and lateral to the PEF in posterior parietal cortex. These areas may contribute to the suppression of prepotent responses and in holding novel visuomotor associations in working memory. Copyright 2001 Academic Press.

NASA Discipline Neuroscience↗

Laboratory Simulation of Impacts upon Aluminum Foils of the Stardust Spacecraft: Calibration of Dust Particle Size from Comet Wild 2

Metallic aluminium alloy foils exposed on the forward, comet-facing surface of the aerogel tray on the Stardust spacecraft are likely to have been impacted by the same cometary particle population as the dedicated impact sensors and the aerogel collector. The ability of soft aluminium alloy to record hypervelocity impacts as bowl-shaped craters offers an opportunistic substrate for recognition of impacts by particles of a wide potential size range. In contrast to impact surveys conducted on samples from low Earth orbit, the simple encounter geometry for Stardust and Wild 2, with a known and constant spacecraft-particle relative velocity and effective surface-perpendicular impact trajectories, permits closely comparable simulation in laboratory experiments. For a detailed calibration programme we have selected a suite of spherical glass projectiles of uniform density and hardness characteristics, with well-documented particle size range from 10 microns to nearly 100 microns. Light gas gun buckshot firings of these particles at approximately 6km s)exp -1) onto samples of the same foil as employed on Stardust have yielded large numbers of craters. Scanning electron microscopy of both projectiles and impact features has allowed construction of a calibration plot, showing a linear relationship between impacting particle size and impact crater diameter. The close match between our experimental conditions and the Stardust mission encounter parameters should provide another opportunity to measure particle size distributions and fluxes close to the nucleus of Wild 2, independent of the active impact detector instruments aboard the Stardust spacecraft.

Kearsley, A. T.↗

Climate Change Adaptation Activities at the NASA John F. Kennedy Space Center, FL., USA

In 2010, the Office of Strategic Infrastructure and Earth Sciences established the Climate Adaptation Science Investigators (CASI) program to integrate climate change forecasts and knowledge into sustainable management of infrastructure and operations needed for the NASA mission. NASA operates 10 field centers valued at $32 billion dollars, occupies 191,000 acres and employs 58,000 people. CASI climate change and sea-level rise forecasts focus on the 2050 and 2080 time periods. At the 140,000 acre Kennedy Space Center (KSC) data are used to simulate impacts on infrastructure, operations, and unique natural resources. KSC launch and processing facilities represent a valued national asset located in an area with high biodiversity including 33 species of special management concern. Numerical and advanced Bayesian and Monte Carlo statistical modeling is being conducted using LiDAR digital elevation models coupled with relevant GIS layers to assess potential future conditions. Results are provided to the Environmental Management Branch, Master Planning, Construction of Facilities, Engineering Construction Innovation Committee and our regional partners to support Spaceport development, management, and adaptation planning and design. Potential impacts to natural resources include conversion of 50% of the Center to open water, elevation of the surficial aquifer, alterations of rainfall and evapotranspiration patterns, conversion of salt marsh to mangrove forest, reductions in distribution and extent of upland habitats, overwash of the barrier island dune system, increases in heat stress days, and releases of chemicals from legacy contamination sites. CASI has proven successful in bringing climate change planning to KSC including recognition of the need to increase resiliency and development of a green managed shoreline retreat approach to maintain coastal ecosystem services while maximizing life expectancy of Center launch and payload processing resources.

plant communities↗

Direct writing of PVBVA/Ti 3 C 2 T x (MXene) triboelectric nanogenerators for energy harvesting and sensing applications

Triboelectric nanogenerators (TENGs) have gained recognition for their potential to convert mechanical energy into electrical energy, making them attractive for applications in healthcare, robotics, and human-device interfaces. However, many TENG devices rely on fluorinated polymers for high charge generation and involve complex fabrication processes, which limit their practicality and environmental sustainability. Here, we developed an eco-friendly composite of poly (vinyl butyral-co-vinyl alcohol-co-vinyl acetate) (PVBVA) and Ti 3 C 2 T x MXene for extrusion printing onto aluminum foil substrates, enabling the additive manufacturing of TENGs. Experimental results indicate that integrating 5.5 mg mL -1 of MXene (P-MX 5.5) into PVBVA resulted in a power density of 760 mW·m -2 , with simultaneous improvements in open-circuit voltage (129 %) and short-circuit current (250 %), demonstrating enhanced charge transfer efficiency. Beyond aluminum foil-based devices, we further explored the fully printed P-MX 5.5 TENG by utilizing silver ink electrodes, eliminating the need for aluminum foil. This fully printed, flexible TENG was successfully used for real-time human motion sensing, demonstrating its ability to detect activities such as walking, running, knee bending, and jumping. Collectively, our additively manufactured and sustainable PVBVA-MXene TENG composites, including both aluminum-based and fully printed versions, show promise for future energy harvesters, sensors, wearable electronics, healthcare, and robotic applications.

Additive manufacturing↗

Active Microwave Remote Sensing Observations of Weddell Sea Ice

Since July 1991, the European Space Agency's ERS-1 and ERS-2 satellites have acquired radar data of the Weddell Sea, Antarctica. The Active Microwave Instrument on board ERS has two modes; SAR and Scatterometer. Two receiving stations enable direct downlink and recording of high bit-rate, high resolution SAR image data of this region. When not in an imaging mode, when direct SAR downlink is not possible, or when a receiving station is inoperable, the latter mode allows normalized radar cross-section data to be acquired. These low bit-rate ERS scatterometer data are tape recorded, downlinked and processed off-line. Recent advances in image generation from Scatterometer backscatter measurements enable complementary medium-scale resolution images to be made during periods when SAR images cannot be acquired. Together, these combined C-band microwave image data have for the first time enabled uninterrupted night and day coverage of the Weddell Sea region at both high (25 m) and medium-scale (-20 km) resolutions. C-band ERS-1 radar data are analyzed in conjunction with field data from two simultaneous field experiments in 1992. Satellite radar signature data are compared with shipborne radar data to extract a regional and seasonal signature database for recognition of ice types in the images. Performance of automated sea-ice tracking algorithms is tested on Antarctic data to evaluate their success. Examples demonstrate that both winter and summer ice can be effectively tracked. The kinematics of the main ice zones within the Weddell Sea are illustrated, together with the complementary time-dependencies in their radar signatures. Time-series of satellite images are used to illustrate the development of the Weddell Sea ice cover from its austral summer minimum (February) to its winter maximum (September). The combination of time-dependent microwave signatures and ice dynamics tracking enable various drift regimes to be defined which relate closely to the circulation of the sea ice in response to current and wind forcing and iceberg barriers. These are closely related to continental-shelf or central basin regimes, in which tidal forcing or barotropic circulation patterns appear to influence the sea-ice motion, respectively. These regimes provide valuable information about the regions of most prolific ice growth and influence of ice conditions upon air-sea-ice exchange processes in the Weddell Sea.

Drinkwater, Mark R.↗

Structural and functional analyses of SARS-CoV-2 Nsp3 and its specific interactions with the 5’ UTR of the viral genome

ABSTRACT Non-structural protein 3 (Nsp3) is the largest open reading frame encoded in the SARS-CoV-2 genome, essential for the formation of double-membrane vesicles (DMV) wherein viral RNA replication occurs. We conducted an extensive structure-function analysis of Nsp3 and determined the crystal structures of the ubiquitin-like 1 (Ubl1), nucleic acid binding (NAB), β-coronavirus-specific marker (βSM) domains, and a sub-region of the Y domain of this protein. We show that the Ubl1, ADP-ribose phosphatase (ADRP), human SARS Unique (HSUD), NAB, and Y domains of Nsp3 bind the 5’ UTR of the viral genome and that the Ubl1 and Y domains possess affinity for recognition of this region, suggesting high specificity. The Ubl1-Nucleocapsid (N) protein complex binds the 5’ UTR with greater affinity than the individual proteins alone. Our results suggest that multiple domains of Nsp3, particularly Ubl1 and Y, shepherd the 5’ UTR of the viral genome during translocation through the DMV membrane, priming the Ubl1 domain to load the genome onto N protein. IMPORTANCE The largest protein encoded by the SARS-CoV-2 genome is Nsp3. In infected cells, this multi-domain protein forms a pore structure in the virus-induced double-membrane vesicles (DMV). We have incomplete data on Nsp3 molecular structure, and here, we describe crystal structures for multiple domains of Nsp3. It is thought that newly replicated viral RNA transits through the DMV pore; however, we possess incomplete data on which regions of Nsp3 actually interact with RNA. Here, we present data showing that five domains of Nsp3 interact with the 5’ UTR of the SARS-CoV-2 RNA, including the Y domain for which no function has ever been discovered. These data suggest that the pore structure plays an active role in recognizing the terminal end of the genome, transiting and loading the viral RNA onto the cytoplasmic nucleocapsid protein. These data help expand our knowledge of Nsp3 structure and function and the SARS-CoV-2 replication cycle.

Microbiology↗

Free-Flight Terrestrial Rocket Lander Demonstration for NASA's Autonomous Landing and Hazard Avoidance Technology (ALHAT) System

The Autonomous Landing Hazard Avoidance Technology (ALHAT) Project is chartered to develop and mature to a Technology Readiness Level (TRL) of six an autonomous system combining guidance, navigation and control with terrain sensing and recognition functions for crewed, cargo, and robotic planetary landing vehicles. The ALHAT System must be capable of identifying and avoiding surface hazards to enable a safe and accurate landing to within tens of meters of designated and certified landing sites anywhere on a planetary surface under any lighting conditions. Since its inception in 2006, the ALHAT Project has executed four field test campaigns to characterize and mature sensors and algorithms that support real-time hazard detection and global/local precision navigation for planetary landings. The driving objective for Government Fiscal Year 2012 (GFY2012) is to successfully demonstrate autonomous, real-time, closed loop operation of the ALHAT system in a realistic free flight scenario on Earth using the Morpheus lander developed at the Johnson Space Center (JSC). This goal represents an aggressive target consistent with a lean engineering culture of rapid prototyping and development. This culture is characterized by prioritizing early implementation to gain practical lessons learned and then building on this knowledge with subsequent prototyping design cycles of increasing complexity culminating in the implementation of the baseline design. This paper provides an overview of the ALHAT/Morpheus flight demonstration activities in GFY2012, including accomplishments, current status, results, and lessons learned. The ALHAT/Morpheus effort is also described in the context of a technology path in support of future crewed and robotic planetary exploration missions based upon the core sensing functions of the ALHAT system: Terrain Relative Navigation (TRN), Hazard Detection and Avoidance (HDA), and Hazard Relative Navigation (HRN).

Rutishauser, David K.↗

NASA's Biomedical Research Program

The biomedical research program has been established to investigate the major physiological and psychological problems encountered by man when he undertakes spaceflight. The program seeks to obtain a better definition of each problem, an understanding of its underlying mechanism, and ultimately a means of prevention. In pursuing these goals the program also includes a major effort to develop the research tools and procedures it needs where these are not being developed elsewhere. After almost twenty years of manned spaceflight activities and after a much longer period of space related ground-based research, the program now recognizes two characteristics of spaceflight which are truly unique to space. These are weightlessness and one specific form of radiation. In its present stage of maturity much of the research focuses on mechanisms underlying the basic responses of man and animals to weightlessness. The program consists of nine elements. Eight of these are referable to specific physiological problems that have either been encountered in previous manned spaceflight or which are anticipated to occur as spaceflights last longer, traverse steeper orbital inclinations, or are otherwise different from previous missions. The ninth addresses problems that have neither arisen nor can be reasonably predicted but are suspected on the basis of theoretical models, ground-based animal research, or for other reasons. The program's current emphasis is directed toward the motion sickness problem because of its relevance to Space Shuttle operations. Increased awareness and understanding of the radiation hazard has resulted in more emphasis being placed on the biological effects of high energy, high mass number particulate radiation and upon radiation protection . Cardiovascular and musculoskeleta1 studies are pursued in recognition of the considerable fundamental knowledge that must be acquired in these areas before effective countermeasures to the effects of repetitive or long-term flight can be devised. Major new avenues of research will deal with the psychological accompaniments of spaceflight and with mathematical modelling of physiological systems.

Ahn, Chung-Hae↗

High Resolution Spectroscopy to Support Atmospheric Measurements

The major research activities performed during the cooperative agreement enhanced our spectroscopic knowledge of molecules of atmospheric interest such as carbon dioxide, water vapor, ozone, methane, and carbon monoxide, to name a few. Measurements were made using the NASA Langley Tunable Diode Laser Spectrometer System (TDL) and several Fourier Transform Spectrometer Systems (FTS) around the globe. The results from these studies made remarkable improvements in the line positions and intensities for several molecules, particularly ozone and carbon dioxide in the 2 to 17-micrometer spectral region. Measurements of pressure broadening and pressure induced line shift coefficients and the temperature dependence of pressure broadening and pressure induced line shift coefficients for infrared transitions of ozone, methane, and water vapor were also performed. Results from these studies have been used for retrievals of stratospheric gas concentration profiles from data collected by several Upper Atmospheric Research satellite (UARS) infrared instruments as well as in the analysis of high resolution atmospheric spectra such as those acquired by space-based, ground-based, and various balloon- and aircraft-borne experiments. Our results made significant contributions in several updates of the HITRAN (HIgh resolution TRANsmission) spectral line parameters database. This database enjoys worldwide recognition in research involving diversified scientific fields.

Benner, D. Chris↗

GeoAI advances in specific landform mapping

Landform mapping (also referred to as geomorphology or geomorphometry) can be divided into two domains: general and specific (Evans 2012). Whereas general landform mapping categorizes all elements of the study area into landform classes, such as ridges, valleys, peaks, and depressions, the mapping of specific landforms requires the delineation (even if fuzzy) of individual landforms. The former is mainly driven by physical properties such as elevation, slope, and curvature. The latter, however, must consider the cognitive (human) reasoning that discriminates individual landforms in addition to these physical properties (Arundel and Sinha 2018). Both mapping forms are important. General geomorphometry is needed to understand geological and ecological processes and as boundary layer input to climate and environmental models. Specific geomorphometry supports such activities as disaster management and recovery, emergency response, transportation, and navigation. In the United States, individual landforms of interest are named in the U.S. Geological Survey (USGS) Geographic Names Information System, a point dataset captured specifically to digitize geographic names from the USGS Historical Topographic Map Collection (HTMC). Named landform extent is represented only by the name placement in the HTMC. Recent work has investigated CNN-based deep learning methods to capture these extents in machine-readable form. These studies first relied on physical properties (Arundel et al. 2020) and then included the HTMC as a band in RGB images in limited testing (Arundel et al. 2023). Results from the HTMC dataset surpassed those using just physical properties and using the HTMC alone performed best due to the hillshading and elevation (contour) data incorporated into the topographic maps. However, results fell short of an operational capacity to map all named landforms in the United States. Thus, our current work expands upon past research by focusing on the HTMC and physical information as inputs and the named landform label extents. Specifically, we propose to leverage pre-trained foundation models for segmentation and optical character recognition (OCR) models to jointly map landforms in the United States. Our approach aims to bridge the disparities among the independent information sources to facilitate informed decision-making. The modeling pipeline performs (1) segmentation using the physical information and (2) information extraction using OCR, in parallel. Then a computer vision approach merges the two branches into a labeled segmentation. References: Arundel, Samantha T., Wenwen Li, and Sizhe Wang. 2020. “GeoNat v1.0: A Dataset for Natural Feature Mapping with Artificial Intelligence and Supervised Learning.” Transactions in GIS 24 (3): 556–72. https://doi.org/10.1111/tgis.12633. Arundel, Samantha T, and Gaurav Sinha. 2018. “Validating GEOBIA Based Terrain Segmentation and Classification for Automated Delineation of Cognitively Salient Landforms BT - Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017).” In Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017), Lecture Notes in Geoinformation and Cartography, edited by Paolo Fogliaroni, Andrea Ballatore, and Eliseo Clementini, 9–14. Cham: Springer International Publishing. Arundel, Samantha T., Gaurav Sinha, Wenwen Li, David P. Martin, Kevin G. McKeehan, and Philip T. Thiem. 2023. “Historical Maps Inform Landform Cognition in Machine Learning.” Abstracts of the ICA 6 (August): 1–2. https://doi.org/10.5194/ica-abs-6-10-2023. Evans, Ian S. 2012. “Geomorphometry and Landform Mapping: What Is a Landform?” Geomorphology 137 (1): 94–106. https://doi.org/10.1016/j.geomorph.2010.09.029.

machine learning↗

GeoAI Advances in Specific Landform Mapping

Landform mapping (also referred to as geomorphology or geomorphometry) can be divided into two domains: general and specific (Evans 2012). Whereas general landform mapping categorizes all elements of the study area into landform classes, such as ridges, valleys, peaks, and depressions, the mapping of specific landforms requires the delineation (even if fuzzy) of individual landforms. The former is mainly driven by physical properties such as elevation, slope, and curvature. The latter, however, must consider the cognitive (human) reasoning that discriminates individual landforms in addition to these physical properties (Arundel and Sinha 2018). Both mapping forms are important. General geomorphometry is needed to understand geological and ecological processes and as boundary layer input to climate and environmental models. Specific geomorphometry supports such activities as disaster management and recovery, emergency response, transportation, and navigation. In the United States, individual landforms of interest are named in the U.S. Geological Survey (USGS) Geographic Names Information System, a point dataset captured specifically to digitize geographic names from the USGS Historical Topographic Map Collection (HTMC). Named landform extent is represented only by the name placement in the HTMC. Recent work has investigated CNN-based deep learning methods to capture these extents in machine-readable form. These studies first relied on physical properties (Arundel et al. 2020) and then included the HTMC as a band in RGB images in limited testing (Arundel et al. 2023). Results from the HTMC dataset surpassed those using just physical properties and using the HTMC alone performed best due to the hillshading and elevation (contour) data incorporated into the topographic maps. However, results fell short of an operational capacity to map all named landforms in the United States. Thus, our current work expands upon past research by focusing on the HTMC and physical information as inputs and the named landform label extents. Specifically, we propose to leverage pre-trained foundation models for segmentation and optical character recognition (OCR) models to jointly map landforms in the United States. Our approach aims to bridge the disparities among the independent information sources to facilitate informed decision-making. The modeling pipeline performs (1) segmentation using the physical information and (2) information extraction using OCR, in parallel. Then a computer vision approach merges the two branches into a labeled segmentation.

machine learning↗

High Resolution Spectroscopy to Support Atmospheric Measurements

The major research activities performed during the cooperative agreement enhanced our spectroscopic knowledge of molecules of atmospheric interest such as carbon dioxide, water vapor, ozone, methane, and carbon monoxide, to name a few. Measurements were made using the NASA Langley Tunable Diode Laser Spectrometer System (TDL) and several Fourier Transform Spectrometer Systems (FTS) around the globe. The results from these studies made remarkable improvements in the line positions and intensities for several molecules, particularly ozone and carbon dioxide in the 2 to 17-micrometer spectral region. Measurements of pressure broadening and pressure induced line shift coefficients and the temperature dependence of pressure broadening and pressure induced line shift coefficients for infrared transitions of ozone, methane, and water vapor were also performed. Results from these studies have been used for retrievals of stratospheric gas concentration profiles from data collected by several Upper Atmospheric Research satellite (UARS) infrared instruments as well as in the analysis of high resolution atmospheric spectra such as those acquired by space-based, ground-based, and various balloon-and aircraft-borne experiments. Our results made significant contributions in several updates of the HITRAN (HIgh resolution TRANsmission) spectral line parameters database. This database enjoys worldwide recognition in research involving diversified scientific fields.

Benner, D. Chris↗

Dynamic visual acuity using "far" and "near" targets

CONCLUSIONS: DVA may be useful for assessing the functional consequences of an impaired gaze stabilization mechanism or for testing the effectiveness of a rehabilitation paradigm. Because target distance influences the relative contributions of canal and otolith inputs, the ability to measure DVA at near and far viewing distances may also lead to tests that will independently assess canal and otolith function. OBJECTIVE: To present and test a methodology that uses dynamic visual acuity (DVA) to assess the efficacy of compensatory gaze mechanisms during a functionally relevant activity that differentially measures canal and otolith function. MATERIAL AND METHODS: The effect of treadmill walking at a velocity of 1.79 m/s on subjects' visual acuity was assessed at each of two viewing distances. A custom-written threshold determination program was used to display Landolt C optotypes on a laptop computer screen during a "far" (4 m) target condition and on a micro-display for a "near" (50 cm) target condition. The walking acuity scores for each target distance were normalized by subtracting a corresponding acuity measure obtained while standing still on the treadmill belt. RESULTS: As predicted by subjective reports of relative target motion, the decrease in visual acuity was significantly greater (p < 0.00001) for the near compared to the far condition.

Pattern Recognition, Visual/physiology↗

Wear and Tear - Mechanical

The focus of this chapter is on the long term wear and tear, or aging, of the mechanical subsystem of a spacecraft. The mechanical subsystem is herein considered to be the primary support structure (as in a skeleton or exoskeleton) upon which all other spacecraft systems rest, and the associated mechanisms. Mechanisms are devices which have some component that moves at least once, in response to some type of passive or active control system. For the structure, aging may proceed as a gradual degradation of mechanical properties and/or function, possibly leading to complete structural failure over an extended period of time. However, over the 50 years of the Space Age such failures appear to be unusual. In contrast, failures for mechanisms are much more frequent and may have a very serious effect on mission performance. Just as on Earth, all moving devices are subject to normal (and possibly accelerated) degradation from mechanical wear due to loss or breakdown of lubricant, misalignment, temperature cycling effects, improper design/selection of materials, fatigue, and a variety of other effects. In space, such environmental factors as severe temperature swings (possibly 100's of degrees C while going in and out of direct solar exposure), hard vacuum, micrometeoroids, wear from operation in a dusty or contaminated environment, and materials degradation from radiation can be much worse. In addition, there are some ground handling issues such as humidity, long term storage, and ground transport which may be of concern. This chapter addresses the elements of the mechanical subsystem subject to wear, and identifies possible causes. The potential impact of such degradation is addressed, albeit with the recognition that the impact of such wear often depends on when it occurs and on what specific components. Most structural elements of the mechanical system typically are conservatively designed (often to a safety factor of greater than approximately 1.25 on yield for unmanned spacecraft) but do not have backup structure due to the added mass this would impose, and also due to the fact that structural elements can be accurately modeled mathematically and in test. Critical mechanisms or devices may have backups, or alternate work-arounds, since characterization of these systems in a 1g environment is less accurate than structure, and repair in-space is often impossible.

Swanson, Theodore↗

Over-Expression, Purification and Crystallization of Human Dihydrolipoamide Dehydrogenase

Dehydrolipoamide dehydrogenase (E3; dihydrolipoan-tide:NAD+ oxidoreductase, EC 1.8.1.4) is a common catalytic component found in pyruvate dehydrogenase complex, alpha-ketoglutarate dehydrogenase complex, and branched-chain cc-keto acid dehydrogenase complex. E3 is also a component (referred to as L protein) of the glycine cleavage system in bacterial metabolism (2). Active E3 forms a homodimer with four distinctive subdomain structures (FAD binding, NAD+ binding, central and interface domains) with non-covalently but tightly bound FAD in the holoenzyme. Deduced amino acids from cloned full-length human E3 gene showed a total of 509 amino acids with a leader sequence (N-terminal 35 amino acids) that is excised (mature form) during transportation of expressed E3 into mitochondria membrane. So far, three-dimensional structure of human E3 has not been reported. Our effort to achieve the elucidation of the X-ray crystal structure of human E3 will be presented. Recombinant pPROEX-1 expression vector (from GIBCO BRL Life Technologies) having the human E3 gene without leader sequence was constructed by Polymerase Chain Reaction (PCR) and subsequent ligation, and cloned in E.coli XL1-Blue by transformation. Since pPROEX-1 vector has an internal His-tag (six histidine peptide) located at the upstream region of a multicloning site, one-step affinity purification of E3 using nickelnitriloacetic acid (Ni-NTA) agarose resin, which has a strong affinity to His-tag, was feasible. Also a seven-amino-acid spacer peptide and a recombinant tobacco etch virus protease recognition site (seven amino acids peptide) found between His-tag and first amino acid of expressed E3 facilitated the cleavage of His-tag from E3 after the affinity purification. By IPTG induction, ca. 15 mg of human E3 (mature form) was obtained from 1L LB culture with overnight incubation at 25C. Over 98% of purity of E3 from one-step Ni-NTA agarose affinity purification was confirmed by SDS-PAGE analysis. For crystallization, E3 samples were prepared with and without His-tag. To minimize the aggregation of E3, apo- and holo- forms of E3s were tested, as well as a mutated E3. Dynamic light scattering measurements revealed that the E3 preparations without His-tag and substrate are highly monodispersive with regard to homodimers. Consequent crystallization trials of this E3 preparation led to single crystals of E3 grown by the vapor diffusion method. Crystals were obtained within a few days from solution containing poly (ethylene glycol) monomethyl ether 5000 as a precipitant. Autoindexing and integration of the X-ray diffraction data showed that E3 crystals belong to an orthorhombic system with unit cell parameters a-- 123. 1, b= 165.3 and c=214.3A. Further optimization of protein preparation and crystallization experiments for the structural determination will be discussed.

Hong, Y. S.↗

A Rover Deployed Ground Penetrating Radar on Mars

Radar is a fundamental tool capable of addressing a variety of geological problems on Mars via collection of data suitable for interpreting variations in surface morphology and reflectivity. Surface-deployed ground penetrating radar (GPR) can help further constrain the geology and structure of the near surface of Mars by directly measuring the range and character of in situ radar properties. In recognition of this potential, a miniaturized, easily modified GPR is being developed for possible deployment on a future Mars rover and will enable definition of radar stratigraphy at high spatial resolution to depths of 10-20 meters. Ongoing development of a Mars impulse GPR with industry partners at Geophysical Survey Systems, Inc., focuses on design and testing of a prototype transducer array (with both high frequency bistatic and low frequency monostatic components) in parallel with fabrication of a low power, mass, and volume control unit. The operational depth of 10-20 meters is geared towards definition of stratigraphy, subsurface blocks, and structure at the decimeter to meter scale that is critical for establishing the geologic setting of the rover. GPR data can also be used to infer the degree of any post-depositional pedogenic alteration or weathering that has subsequently taken place, thereby enabling assessment of pristine versus secondary morphology at the landing site. As is the case for most remote sensing instruments, a GPR may not detect water unambiguously. Nevertheless, any local, near-surface occurrence of liquid water will lead to large, easily detected dielectric contrasts. Moreover, definition of stratigraphy and setting will help in evaluating the history of aqueous activity and where any water might occur and be accessible. Most importantly perhaps, GPR can provide critical context for other rover and orbital instruments/data sets. Hence, GPR deployment along well positioned transects in the vicinity of a lander should enable 3-D mapping of stratigraphy and could serve to guide direct subsurface sampling. Additional information is contained in the original extended abstract.

Grant, J. A.↗

Using Natural Language to Enhance Mission Effectiveness

The availability of highly capable, yet relatively cheap, unmanned aerial vehicles (UAVs) is opening up new areas of use for hobbyists and for professional-related activities. The driving function of this research is allowing a non-UAV pilot, an operator, to define and manage a mission. This paper describes the preliminary usability measures of an interface that allows an operator to define the mission using speech to make inputs. An experiment was conducted to begin to enumerate the efficacy and user acceptance of using voice commands to define a multi-UAV mission and to provide high-level vehicle control commands such as "takeoff." The primary independent variable was input type - voice or mouse. The primary dependent variables consisted of the correctness of the mission parameter inputs and the time needed to make all inputs. Other dependent variables included NASA-TLX workload ratings and subjective ratings on a final questionnaire. The experiment required each subject to fill in an online form that contained comparable required information that would be needed for a package dispatcher to deliver packages. For each run, subjects typed in a simple numeric code for the package code. They then defined the initial starting position, the delivery location, and the return location using either pull-down menus or voice input. Voice input was accomplished using CMU Sphinx4-5prealpha for speech recognition. They then inputted the length of the package. These were the option fields. The subject had the system "Calculate Trajectory" and then "Takeoff" once the trajectory was calculated. Later, the subject used "Land" to finish the run. After the voice and mouse input blocked runs, subjects completed a NASA-TLX. At the conclusion of all runs, subjects completed a questionnaire asking them about their experience in inputting the mission parameters, and starting and stopping the mission using mouse and voice input. In general, the usability of voice commands is acceptable. With a relatively well-defined and simple vocabulary, the operator can input the vast majority of the mission parameters using simple, intuitive voice commands. However, voice input may be more applicable to initial mission specification rather than for critical commands such as the need to land immediately due to time and feedback constraints. It would also be convenient to retrieve relevant mission information using voice input. Therefore, further on-going research is looking at using intent from operator utterances to provide the relevant mission information to the operator. The information displayed will be inferred from the operator's utterances just before key phrases are spoken. Linguistic analysis of the context of verbal communication provides insight into the intended meaning of commonly heard phrases such as "What's it doing now?" Analyzing the semantic sphere surrounding these common phrases enables us to predict the operator's intent and supply the operator's desired information to the interface. This paper also describes preliminary investigations into the generation of the semantic space of UAV operation and the success at providing information to the interface based on the operator's utterances.

Trujillo, Anna C.↗