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At least 19 records

Science and Science-Enabling Activities of the SHERLOC and WATSON Imaging Systems in Jezero Crater, Mars

During its first year of operation, the Perseverance rover explored the cratered and fractured floor of Jezero crater on Mars. Here, we report the use of the Scanning Habitability Environments with Raman and Luminescence for Organics and Chemicals (SHERLOC) imaging system that includes two high-resolution cameras, the Autofocus and Contextual Imager (ACI) and Wide Angle Topographic Sensor for Operations and eNgineering (WATSON). ACI is a fixed focus gray scale imager with a resolution of 10.1 μm/pixel whereas WATSON is a variable field of view, variable focus imager capable of resolution down to 14 μm/pixel. WATSON is a reflight of the MArs Hand Lens Imager (MAHLI) imager and has similar capabilities. During first-time activities, WATSON was used to support both science and engineering operations related to sample and abrasion patch assessment and sample collection and caching. WATSON also documented the deployment of the Ingenuity helicopter. The Crater Floor Campaign identified two primary rock units, the Máaz formation and the Séítah formation, which have been interpreted as lava flows and an olivine cumulate, respectively. Interpretation of rock textures with WATSON and ACI images was limited to abraded surfaces because unmodified outcrop surfaces (herein termed “natural surfaces”) show high degrees of dust covering, wind abrasion, and coating by secondary mineral products. WATSON and ACI images support the hypothesis that the material of both the Máaz and Séítah formations consists of largely aqueously altered mafic materials with varying igneous origins.

WATSON↗

NASA Pilot-Engaged Expert Response Using IBM Watson Technology: Prototype Evaluation of Knowledge Retrieval System

NASA Langley Research Center and IBM have been investigating the use of IBM Watson technology in aerospace research and development. One application of Watson technology is the Pilot-Engaged Expert Response (PEER) use case. The PEER system is envisioned as an in-cockpit advisor that will act as a source of situationally-relevant information for pilots and other flight crew members to assist in decision making about real-time events and situations that arise in the course of aircraft operations. PEER will make available vast stores of knowledge and information quickly and directly, putting important informational resources where they are needed most. IBM has worked with NASA to develop an architecture and articulate a roadmap for the development of the PEER system. That vision is built around Watson Discovery Advisor (WDA) software solution, derived from IBM's Jeopardy!-winning automatic question answering system. PEER makes use of WDA's sophisticated question-answering capabilities as its core, adding important User Interface components and other customizations for the cockpit environment, including communication with flight systems and other external data sources. The development plan for PEER includes four development stages, with the current project constituting the first phase. In this project, a prototype instance of PEER was successfully adapted to the aviation domain, enabling users to ask questions about aviation topics and receive useful and accurate answers to these questions. Major tasks accomplished include the development of procedures for domain adaptation through automatic lexicon extraction from domain glossaries; generation of question-answer training data which was used to train the system; and assessment of the effectiveness of domain adaptation, which showed a dramatic improvement in the ability of the PEER system to answer domain-relevant questions. In addition, the vision for the PEER system was pushed forward by the articulation of a plan for the automatic enhancement of question-answering with contextual information. This initial phase focused on two main goals: 1) the targeted domain adaptation of the underlying WDA system to the aviation domain; and, 2) the design of the software systems needed to leverage flight-contextual data. Domain adaptation of the WDA system proceeds via three main activities: Domain data ingestion, lexical customization and model training. A textual corpus consisting of 1,147 individual documents with more than 7.5 million words of text was ingested into the system and this served as the basis of all further development. A domain lexicon of over 3,500 aviation-domain terms was semi-automatically generated from domain documents and used to train the system. In addition, a set of over 500 question-answer (QA) pairs relevant to the PEER use case was developed; these were used to train and assess the system. These important first steps established the basis for the PEER system. In addition, steps were taken towards the integration of the PEER system into the cockpit environment with the development of a functional design for the Contextual Data Augmentation (CDA) subsystem. This subsystem brings to bear contextual data to improve system responses. It has three main submodules: the Contextual Data Collection module, the Contextual Data Selection module, and the Contextual QA Augmentation module. These modules form a processing pipeline that addresses the problems associated with automatically integrating information from external resources into the knowledge-retrieval mechanism.

Machine learning↗

Watson: A new link in the IIE iron chain

Watson, which was found in 1972 in South Australia, contains the largest single silicate rock mass seen in any known iron meteorite. A comprehensive study has been completed on this unusual meteorite: petrography, metallography, analyses of the silicate inclusion (whole rock chemical analysis, INAA, RNAA, noble gases, and oxygen isotope analysis) and mineral compositions (by electron microprobe and ion microprobe). The whole rock has a composition of an H-chondrite minus the normal H-group metal and troilite content. The oxygen isotope composition is that of the silicates in the IIE iron meteorites and lies along an oxygen isotope fractionation line with the H-group chondrites. Trace elements in the metal confirm Watson is a new IIE iron. Whole rock Watson silicate shows an enrichment in K and P (each approximately 2X H-chondrites). The silicate inclusion has a highly equilibrated igneous (peridotite-like) texture with olivine largely poikilitic within low-Ca pyroxene: olivine (Fa20), opx (Fs17Wo3), capx (Fs9Wo14)(with very fine exsolution lamellae), antiperthite feldspar (An1-3Or5) with less than 1 micron exsolution lamellae (An1-3Or greater than 40), shocked feldspar with altered stoichiometry, minor whitlockite (also a poorly characterized interstitial phosphate-rich phase) and chromite, and only traces of metal and troilite. The individual silicate minerals have normal chondritic REE patterns, but whitlockite has a remarkable REE pattern. It is very enriched in light REE (La is 720X C1, and Lu is 90X C1, as opposed to usual chonditic values of approximately 300X and 100-150X, respectively) with a negative Eu anomaly. The enrichment of whole rock K is expressed both in an unusually high mean modal Or content of the feldspar, Or13, and in the presence of antiperthite.

Olsen, Edward↗

The Mars 2020 Watson Imaging Subsystem of the Sherloc Investigation and Anticpated Early Results

In February 2021, the Mars 2020 Perseverance rover is anticipated to touch down in Jezero crater, Mars. Perseverance is unique in that it will conduct in situ science as well as cache samples for eventual return to Earth for analysis in terrestrial laboratories. It will explore the geologic setting within Jezero over a range of scales in order to address fundamental questions about the evolution of Mars and assess whether there is evidence of past or present Martian life. The Wide Angle Topographic Sensor for Operations and eNgineering (WATSON), one of two imaging subsystems within the Scanning Habitable Environments with Raman and Luminescence for Organics and Chemicals (SHERLOC) instrument[1,2], acquires images that support scientific study of Jezero crater and sample acquisition, as well as rover and instrument operations(Fig. 1).WATSON serves a number of roles; it 1) provides color context imaging of SHERLOC and Planetary Instrument for X-Ray Litho chemistry (PIXL)analysis locations, placing the spatial distribution of organics and mineralogy detected by SHERLOC and the elemental maps generated by PIXL within the context of rock texture and structure; 2)acquires stand-alone observations of rock structures and textures from the outcrop to the grain scale; and 3)images rover components and other instruments to monitor their health and condition. We plan to present images acquired within the first ~30 sols of operations.

M E Minitti↗

Robonaut 2 and Watson: Cognitive Dexterity for Future Exploration

Future exploration missions will dictate a level of autonomy never before experienced in human spaceflight. Mission plans involving the uncrewed phases of complex human spacecraft in deep space will require a coordinated autonomous capability to be able to maintain the spacecraft when ground control is not available. One promising direction involves embedding intelligence into the system design both through the employment of state-of-the-art system engineering principles as well as through the creation of a cognitive network between a smart spacecraft or habitat and embodiments of cognitive agents. The work described here details efforts to integrate IBM's Watson and other cognitive computing services into NASA Johnson Space Center (JSC)'s Robonaut 2 (R2) anthropomorphic robot. This paper also discusses future directions this work will take. A cognitive spacecraft management system that is able to seamlessly collect data from subsystems, determine corrective actions, and provide commands to enable those actions is the end goal. These commands could be to embedded spacecraft systems or to a set of robotic assets that are tied into the cognitive system. An exciting collaboration with Woodside provides a promising Earth-bound testing analog, as controlling and maintaining not normally manned off-shore platforms have similar constraints to the space missions described.

Badger, Julia M.↗

IBM Watson Supporting Space Radiation

The NASA Human Research Program (HRP) Space Radiation (SR) Program Element has been working with IBM Watson Explorer (WEX) to create a tool that allows researchers to search the NASA SR-funded research corpus to help streamline research and maximize efficiency. The entire corpus of publications from research funded by the NASA SR Program Element has been ingested into WEX to allow for examination of: synergies across funded research areas, gaps in research, and collaboration opportunities. This information will be valuable to both scientists and managers as it will allow analysis related to specific scientific questions, inform key decisions and support cross validation of study results. NASA will also evaluate the potential to make WEX publicly available in order to facilitate proposal generation and to enhance collaborations within and across disciplines.

Scott Carnell, Lisa A.↗

Observations of Thermospheric Horizontal Winds at Watson Lake, Yukon Territory (lambda=65 Deg N)

Fabry-Perot interferometer observations of the thermospheric O I (6300 A) emission have been conducted from an airglow observatory at a dark field site in the southeastern Yukon Territory, Canada, for the period November 1991 to April 1993. The experiment operated in unattended, remote fashion, has resulted in a substantial data set from which mean neutral winds have been determined. Dependent upon geomagnetic activity, the nocturnal location of the site is either equatorward of the auroral oval or within oval boundaries. The data set is rich enough to permit hourly binning of neutral winds based upon the K(sub p) geomagnetic disturbance index as well as the season. For cases of low geomagnetic activity the averaged vector horizontal neutral wind exhibits the characteristics of a midlatitude site displaying antisunward pressure-gradient-driven winds. As the geomagnetic activity rises in the late afternoon and evening winds slowly rotate sunward in an anticlockwise direction, initially remaining near 100 m/s in speed but eventually increasing to 300 m/s for K(sub p) greater than 5. For the higher levels of activity the observed neutral wind flow pattern resembles a higher-latitude polar cap pattern characterized by ion drag forcing of thermospheric neutral gases. In addition, rotational Coriolis forcing on the dusk side enhances the ion drag forcing, resulting in dusk winds which trace out the clockwise dusk cell plasma flow. On the dawn side the neutral winds also rotate in an anticlockwise direction as the strength of geomagnetic disturbances increase. Since the site is located at a transition latitude between the midlatitude and the polar cap the data set provides a sensitive test for general circulation models which attempt to parameterize the contribution of magnetospheric processes. A comparison with the Vector Spherical Harmonic (VSH) model indicates several regions of poor correspondence for December solstice conditions but reasonable agreement for the vernal equinox.

Niciejewski, R. J.↗

Base pairing and base mis-pairing in nucleic acids

In recent years we have learned that DNA is conformationally active. It can exist in a number of different stable conformations including both right-handed and left-handed forms. Using single crystal X-ray diffraction analysis we are able to discover not only additional conformations of the nucleic acids but also different types of hydrogen bonded base-base interactions. Although Watson-Crick base pairings are the predominant type of interaction in double helical DNA, they are not the only types. Recently, we have been able to examine mismatching of guanine-thymine base pairs in left-handed Z-DNA at atomic resolution (1A). A minimum amount of distortion of the sugar phosphate backbone is found in the G x T pairing in which the bases are held together by two hydrogen bonds in the wobble pairing interaction. Because of the high resolution of the analysis we can visualize water molecules which fill in to accommodate the other hydrogen bonding positions in the bases which are not used in the base-base interactions. Studies on other DNA oligomers have revealed that other types of non-Watson-Crick hydrogen bonding interactions can occur. In the structure of a DNA octamer with the sequence d(GCGTACGC) complexed to an antibiotic triostin A, it was found that the two central AT base pairs are held together by Hoogsteen rather than Watson-Crick base pairs. Similarly, the G x C base pairs at the ends are also Hoogsteen rather than Watson-Crick pairing. Hoogsteen base pairs make a modified helix which is distinct from the Watson-Crick double helix.

Wang, A. H. J.↗

Chronology and Petrology of Silicates From IIE Iron Meteorites: Evidence of a Complex Parent Body Evolution

IIE iron meteorites contain silicate inclusions whose characteristics suggest a parent body similar to that of H-chondrites. However, these silicates show a wide range of alteration, ranging from Netschadvo and Techado, whose inclusions are little altered. to highly differentiated silicates like-those in Kodaikanal, Weekeroo Station and Colomera, which have lost metal and sulfur and are enriched in feldspar. We find these inclusions to show varying degrees of shock alteration. Because only a limited amount of data on - isotopic ages of HE silicates were available, we made Ar-39 - Ar-40 age determinations of Watson, Techado, miles Colomera, and Sombrerete. Watson has an Ar-Ar age of 3.653 +/- 0.012 Gyr, similar to previously reported ages for Kodaikanal and Netschadvo. We suggest that the various determined radiometric ages of these three meteorites were probably reset by a common impact event. The space exposure ages for these three meteorites are also similar to each other and are considerably younger than exposure ages of other IIEs. Ar-39 - Ar-40 ages inferred for the other four meteorites analyzed are considerably older than Watson and are: Techado =4.49 +/- 0.01 Gyr, Miles =4.412 +/- 0.016 Gyr, Colomera =4.469 +/- 0.012 Gyr, and Sombrerete =4.535 +/- 0.005 Gyr. These ages are in fair agreement with previously reported Rb-Sr isochron ages for Colomera and Weekeroo Station. Although several mechanisms to form HE meteorites previously were suggested, it is not obvious that a single mechanism could produce a suite of meteorites with very different degrees of silicate differentiation and with isotopic ages that differ by >0.8 Gyr. We suggest that those IIEs with older isotopic ages are a product of partial melting and differentiation within the parent body, followed by mixing of silicate and metal while both were relatively hot. Netschadvo and Watson may have formed by this same process or by impact mixing about 4.5 Gyr ago, but their isotopic ages were subsequently reset by shock heating. Kodaikanal apparently is required to have formed more recently, in which case impact melting and differentiation seems the only viable process. We see no compelling reasons to believe that IIE silicate and metal derived from different parent bodies or that the parent body of IIEs was the same as that of H-chondrites.

Bogard, Donald D.↗

Diffusion in Melts and Magmas

Diffusion results from random motion of particles and entities. Diffusion in melts and magmas is due to thermally excited random motion of atoms, ions, and clusters, and plays a critical role in magmatic and volcanic processes. In melts and magmas, diffusion is one of the two mechanisms of mass transfer; the other being bulk flow (referred to as convection or advection). When both are present, diffusion refers to the dispersive motion relative to the mean bulk flow in a given reference frame (Richter et al. 1998). Diffusion plays critical roles in controlling magma mixing (Watson 1982; Koyaguchi 1985, 1989; Lesher 1994; Huber et al. 2009; Guo and Zhang 2020), mineral growth and dissolution rates in magmas (e.g., Watson 1982; Harrison and Watson 1983; Zhang et al. 1989; Newcombe et al. 2014; Macris et al. 2018), bubble growth and dissolution rate in magmas (Sparks 1978; Proussevitch and Sahagian 1998; Liu and Zhang 2000; Zhang 2013), and elemental and isotope fractionation during mineral 2 growth and dissolution (Jambon 1980; Richter et al. 1999, 2003; Watson and Muller 2009; Chopra et al. 2012; Watkins et al. 2014, 2017; Holycross et al. 2016, 2018). As a result, diffusion also plays an essential role in explosive volcanic eruptions and magma crystallization. Furthermore, diffusion has important applications in geospeedometry (Lasaga 1983, 1998; Zhang 1994, 2008; Trail et al. 2016; Zhang and Xu 2016). Experimental investigation of diffusion in geologically relevant silicate melts began to flourish in the 1970’s when micro-analytical measurements of diffusion profiles became available. In addition to the vast number of papers published since then, numerous books and reviews are available for diffusion in silicate melts. Hofmann et al. (1974) edited a book titled “Geochemical Transport and Kinetics” published by Carnegie Institution of Washington. This was the first landmark book summarizing the field. Lasaga and Kirkpatrick (1981) edited a book “Kinetics of Geochemical Processes” as volume 8 of the Reviews in Mineralogy (later becoming Reviews in Mineralogy and Geochemistry) series. Zhang and Cherniak (2010) edited “Diffusion in Minerals and Melts” as volume 72 of Reviews of Mineralogy and Geochemistry series, in which one chapter focused on diffusion theory, five chapters on diffusion in silicate melts (Behrens 2010; Lesher 2010; Liang 2010; Zhang and Ni 2010; Zhang et al. 2010), and other chapters were on experimental, analytical, and computational methods, and diffusion in minerals. Several textbooks covered the principles and applications of diffusion theories (Kirkaldy and Young 1987; Shewmon 1989; Cussler 1997; Lasaga 1998; Zhang 2008; Vrentas and Vrentas 2016), and two classic books covered the mathematics of diffusion (Carslaw and Jaeger 1959; Crank 1975). In preparing for this review chapter, we thought carefully about what to cover for this vast field, and decided to briefly go through the fundamentals of diffusion (more complete review can be found in Chakraborty 1995; Zhang 2008, 2010) and solutions to often-encountered 3 diffusion problems, and then focus on post-2010 diffusion studies on silicate melts and magmas. Here, melts refer to (mostly natural) silicate liquid, and magmas refer to crystal-bearing and/or bubble-bearing melts in which the continuous phase is the melt. There is a large body of work on diffusion in glasses, especially in the materials science literature, which is not covered in this review.

Youxue Zhang↗

How do we get robots to take self-portraits on Mars? – Perseverance-Ingenuity and Curiosity selfies

The Perseverance rover landed in Jezero crater,Mars, on 18 February 2021. It carried with it a technologydemonstration, the Ingenuity helicopter, which hasdemonstrated the first controlled, powered flight on anotherplanet. This paper describes how an iconic, April 2021 imageof the Perseverance rover with the Ingenuity helicopter wasdesigned and executed as the rover was getting ready todeploy the helicopter. WATSON is a camera mounted at theend of the rover’s robotic arm and was used to acquire theself-portrait. WATSON is designed to take close up picturesof rocks and regolith on Mars but can also provide views ofthe terrain. A single image covers a small portion of thescene. In order to a create a mosaic covering the full roverand helicopter, 62 WATSON images were acquired. To allowthe images to be mosaicked together, the camera needs to bekept in the same spot. The robotic arm has five degrees offreedom for motion; small changes in orientation can requiresignificant repositioning of the robotic arm joints. Todocument this, a movie of the arm motion was acquired bythe rover’s mast-mounted left navigation camera pointed atthe WATSON and robotic arm while it was simultaneouslymoving to acquire the selfie. For the first time, we alsocaptured the sound of the arm motion as it was acquiring theselfie. In the case of the Perseverance selfie with the Ingenuity helicopter, we also had to think about how toposition the rover with respect to the helicopter and fit theselfie acquisition into the helicopter prime mission timeline.This paper also describes the history of NASA Mars roverselfies.

Beegle, Luther↗

Calibration and Validation of the SHERLOC Instrument Operating in Jezero Crater, Mars

The Scanning Habitable Environments with Raman and Luminescence for Organics and Chemistry (SHERLOC) is an instrument onboard the Mars 2020 Perseverance rover. It consists of a spectrometer that measures deep ultraviolet (DUV) resonance Raman and native fluorescence photons generated through surface interactions with a 248.6 nm pulsed laser. Two microscopic imagers, the Autofocus Context Imager (ACI) and the Wide-Angle Topographic Sensor for Operations and eNgineering (WATSON), provide high-resolution context images of SHERLOC targets. The ACI is co-boresighted with the spectrometer. To ensure proper calibration, the SHERLOC calibration target (SCT) is mounted on the front of the rover and consists of ten different materials. The SCT was designed, fabricated, assembled, and tested by Jacobs Technology, Inc., and NASA Johnson Space Center. The dimensions of the calibration target housing are 150 x 89 x 33 mm and it weighs ~437 g. The ten targets are arranged in two rows; the first six are hard targets (AlGaN for Raman and fluorescence, diffuse transmission target, a slice of the SaU008 Mars meteorite, an intensity maze, and polycarbonate over geocache coin) and the remaining four are soft-goods targets (Vectran, Ortho-Fabric, Teflon, and nGimat-coated Teflon). The hard targets calibrate the spectrometer’s Raman and fluorescence spectral accuracy, ambient light reflection, and Raman response curve, while the soft-goods targets are spacesuit materials that function as human exploration targets, some of which are also used for spectral calibration. SHERLOC also has an internal calibration target consisting of AlGaN on sapphire (275 nm) located inside the ACI opaque dust cover to ensure proper instrument functioning between calibration target analyses. Initial SHERLOC, ACI, and WATSON calibration and validation on Mars was performed using the internal calibration target on sols 59, 83, 98, and 141; WATSON imaging of the SCT on sols 26 and 62, and SHERLOC spectroscopy and ACI imaging of the SCT on sol 59. These early data provide initial insights into instrument performance and the stability and degradation of the calibration target materials relative to the Martian surface and dust environment. Early observations also have implications for future astronaut spacesuit materials.

Trevor G Graff↗

Reduction of display artifacts by random sampling

The application of random-sampling techniques to remove visible artifacts (such as flicker, moire patterns, and paradoxical motion) introduced in TV-type displays by discrete sequential scanning is discussed and demonstrated. Sequential-scanning artifacts are described; the window of visibility defined in spatiotemporal frequency space by Watson and Ahumada (1982 and 1983) and Watson et al. (1983) is explained; the basic principles of random sampling are reviewed and illustrated by the case of the human retina; and it is proposed that the sampling artifacts can be replaced by random noise, which can then be shifted to frequency-space regions outside the window of visibility. Vertical sequential, single-random-sequence, and continuously renewed random-sequence plotting displays generating 128 points at update rates up to 130 Hz are applied to images of stationary and moving lines, and best results are obtained with the single random sequence for the stationary lines and with the renewed random sequence for the moving lines.

Ahumada, A. J., Jr.↗

Updating the Standard Spatial Observer for Contrast Detection

Watson and Ahmuada (2005) constructed a Standard Spatial Observer (SSO) model for foveal luminance contrast signal detection based on the Medelfest data (Watson, 1999). Here we propose two changes to the model, dropping the oblique effect from the CSF and using the cone density data of Curcio et al. (1990) to estimate the variation of sensitivity with eccentricity. Dropping the complex images, and using medians to exclude outlier data points, the SSO model now accounts for essentially all the predictable variance in the data, with an RMS prediction error of only 0.67 dB.

Ahumada, Albert J.↗