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The BOREAS TGB-1 team made several chamber and tower measurements of trace gases at sites in the BOREAS NSA. This data set contains sulfur hexafluoride (SF6) dark chamber flux measurements at the NSA-OJP and NSA-YJP sites from 16-May through 13-Sep-1994. Gas samples were extracted approximately every 7 days from dark chambers and analyzed at the NSA lab facility. The data are provided in tabular ASCII files.
The task of managing the GLOBE Online Teacher s Guide during this time period focused on transforming the technology behind the delivery system of this document. The web application transformed from a flat file retrieval system to a dynamic database access approach. The new methodology utilizes Java Server Pages (JSP) on the front-end and an Oracle relational database on the backend. This new approach allows users of the web site, mainly teachers, to access content efficiently by grade level and/or by investigation or educational concept area. Moreover, teachers can gain easier access to data sheets and lab and field guides. The new online guide also included updated content for all GLOBE protocols. The GLOBE web management team was given documentation for maintaining the new application. Instructions for modifying the JSP templates and managing database content were included in this document. It was delivered to the team by the end of October, 2003. The National Geophysical Data Center (NGDC) continued to manage the school study site photos on the GLOBE website. 333 study site photo images were added to the GLOBE database and posted on the web during this same time period for 64 schools. Documentation for processing study site photos was also delivered to the new GLOBE web management team. Lastly, assistance was provided in transferring reference applications such as the Cloud and LandSat quizzes and Earth Systems Online Poster from NGDC servers to GLOBE servers along with documentation for maintaining these applications.
The JPL Channel Simulator lab was modified to allow full duplex links and to allow the use of field propagation data for link fading. This capability will be used to test equipment for the joint AUSSAT/NASA mobile satellite experiment in July 1989.
The LaRC Smart Lab applications are a series of software tools to greatly enhance researcher efficiency by streamlining and automating workflows. Python scripts and applications are increasingly being used in scientific workflows, including for instrument control and data processing. Interactive Python scripting environments such as Jupyter Lab provide powerful tools for using Python. In some use cases, the development of standalone applications with dedicated graphical user interfaces (GUIs) can enhance the utility of the code and open it up to more users, including non-programmers. Here, we describe a GUI based optical micrometer data visualization application developed as part of the LaRC SmartLab project. We highlight its use in visualizing experimental data and briefly discuss its implementation to give pointers to programmers who wish develop work based on this application's or similar co de.
Based on solar irradiance data published by Neckel and Labs (1984) and Iqbal (1983), the solar exoatmospheric irradiances for Thematic Mapper (TM) bands 1, 2, 3, and 4 have been calculated. Results vary by up to 1 percent from previous published values, which were based on the earlier data of Neckel and Labs. For TM bands 5 and 7, integrated solar exoatmospheric irradiances have also been recalculated using solar irradiance data published by Labs and Neckel (1968), Arvesen et al. (1969), and Iqbal (1983). These irradiances vary by up to 6 percent from previously published results, which were based on data published by Thekaekara (1972).
NASA grant NAG9-329 was in effect from 3/1/89 to 8/31/94, the last 18 months being a no-cost extension. While the grant was in effect, the P.I., coworkers, and students gave 22 talks and poster sessions at professional meetings, published 12 articles in referred journals (one more is in press, and another is in review), and edited 2 workshop reports relevant to this project. Copies of all the publications are appended to this report. The major accomplishments during the grant period have derived from three quarters: 1) the application of quantitative models of fractional crystallization and partial melting to various problems in planetary science, such as the petrogenesis of picritic glasses and mare basalts and the implications of the SNC meteorites for martian evolution; 2) an experimental study of silicate liquid immiscibility relevant to early lunar differentiation and the petrogenesis of evolved highlands rocks; and 3) experimental studies of massif anorthosites and related rocks that provide terrestrial analogs for the proposed origin of lunar anorthosites by multistage processes. The low-pressure aspects of the quantitative models were developed by the P.I. in the 1980s with NASA support and culminated with a paper comparing the crystallization of terrestrial and lunar lavas. The basis for the high-pressure modifications to the quantitative models is a data set gleaned from high pressure melting experiments done at Lamont and is supplemented by published data from other labs that constrain the baric and compositional dependences of various liquidus phase boundaries such as olivine/orthopyroxene, relevant to the melting of the mantles of the terrestrial planets. With these models it is possible to predict not only the thermal and compositional evolution of magmatic liquids ranging in composition from lumar mare basalt to terrestrial calc-alkaline basalts, but also the small increments of fractional melting that are produced when mantle rises adiabatically. Copies of the crystallization/melting programs have been given to several colleagues in planetary science. Additionally, a series of computer graphics programs, based on the algorithms in the crystallization programs have been developed that display liquidus diagrams appropriate to input compositions.
Under an SBIR contract with Dryden Flight Research Center, Creare Inc. developed a data collection tool called the Ring Buffered Network Bus. The technology has now been released under an open source license and is hosted by the Open Source DataTurbine Initiative. DataTurbine allows anyone to stream live data from sensors, labs, cameras, ocean buoys, cell phones, and more.
We report on our study of the design of a neutrino detector, shielding and veto array needed to operate a neutrino detector in space close to the Sun. This study also took into account the expected rates of Galactic gamma and cosmic rays in addition to the particles from the Sun.These preliminary studies show that we can devise a detector such that a small signal of neutrino interactions can be extracted from a large random number of events from the background sources using a double timing method from the conversion electron produced in the neutrino interaction and a secondary delayed signal from the nuclear excited state produced from the initial neutrino interaction; in our case the conversion of Ga 69 or 71 into Ge 69 or 71, but this method could apply to other nuclei with large neutrino cross sections such as Ir 115. Although these types of events need to be above 0.405 megaelectronvolt (MeV) neutrino energy and are only 66 percent of all conversion neutrino interactions on Gallium, this is a small price to pay for an increase of 10,000 by going close to the Sun to enhance the neutrino rate over the background combatorical fake-signal events. The conclusion of this Phase-1 study is very positive in that we can get the backgrounds less than 20 percent fake signals, and in addition to this we have devised another shielding method that makes the Galactic gamma-ray rate a hundred fold less which will make further improvements over these initial estimates. Although these studies are very encouraging it suggests that the next step is a NIAC Phase-II to actually build a test device,measuring basic principles such as light attention within the scintillator with high dopants and to take data in the lab with a cosmic-ray test stand and triggered X-ray source for comparison with simulated expected performance of the detector. This would be the perfect lead into a future proposal beyond a NIAC (NASA Innovative Advanced Concepts) Phase-II for a test flight of a small one-pint detector in orbit of the detector concept beyond Earth outside of the radiation belts.
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 computer science 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. We present a decadal view of AI/ML architecture to support deep space mission goals, developed in concert with leaders in the field. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing hardware, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated real-time mission biomonitoring, and 8) a Precision Space Health system. Cutting-edge AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics data to phenotypic data using an ensemble model to infer causality of spaceflight rodent liver health disruption, 2) usage of explainable ML to interrogate the muscular underpinnings of spaceflight muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human space health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interaction networks, and 5) a suite of benchmarked open science datasets (spaceflight mouse liver; radiation DNA damage) enabling programmers to identify the best ML algorithms to answer space biological science questions.
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 and support human space missions. Through artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in space biosciences and engineered astronaut health systems, to enable Earth-independence and mission operations autonomy. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated mission biomonitoring, and 8) a Precision Space Health system. AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the space biology field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics to phenotypic data using an ensemble model to infer causality of rodent liver health disruption, 2) usage of explainable ML to interrogate muscular underpinnings of muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interactions, and 5) a suite of benchmarked open science datasets enabling programmers to identify best algorithms to answer space biology questions.
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 computer science 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. We present a decadal view of AI/ML architecture to support deep space mission goals, developed in concert with leaders in the field. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing hardware, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated real-time mission biomonitoring, and 8) a Precision Space Health system. Cutting-edge AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics data to phenotypic data using an ensemble model to infer causality of spaceflight rodent liver health disruption, 2) usage of explainable ML to interrogate the muscular underpinnings of spaceflight muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human space health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interaction networks, and 5) a suite of benchmarked open science datasets (spaceflight mouse liver; radiation DNA damage) enabling programmers to identify the best ML algorithms to answer space biological science questions.
The NASA PAIR program incorporated the NASA-Sponsored research into the undergraduate environment at North Carolina Agricultural and Technical State University. This program is designed to significantly improve undergraduate education in the areas of mathematics, science, engineering, and technology (MSET) by directly benefiting from the experiences of NASA field centers, affiliated industrial partners and academic institutions. The three basic goals of the program were enhancing core courses in MSET curriculum, upgrading core-engineering laboratories to compliment upgraded MSET curriculum, and conduct research training for undergraduates in MSET disciplines through a sophomore shadow program and through Research Experience for Undergraduates (REU) programs. Since the inception of the program nine courses have been modified to include NASA related topics and research. These courses have impacted over 900 students in the first three years of the program. The Electrical Engineering circuit's lab is completely re-equipped to include Computer controlled and data acquisition equipment. The Physics lab is upgraded to implement better sensory data acquisition to enhance students understanding of course concepts. In addition a new instrumentation laboratory in the department of Mechanical Engineering is developed. Research training for A&T students was conducted through four different programs: Apprentice program, Developers program, Sophomore Shadow program and Independent Research program. These programs provided opportunities for an average of forty students per semester.
The excellent microwave properties of the High-Temperature-Superconductors (HTS) have been amply demonstrated in the laboratory by techniques such as resonant cavity, power transmission and microstrip resonator measurements. The low loss and high Q passive structures made possible with HTS, present attractive options for applications in commercial, military and spacebased systems. However, to readily insert HTS into these systems improvement is needed in such areas as repeatability in the deposition and processing of the HTS films, metal-contact formation, wire bonding, and overall film endurance to fabrication and assembly procedures. In this paper we present data compiled in our lab which illustrate many of the problems associated with these issues. Much of this data were obtained in the production of a space qualified hybrid receiver-downconverter module for the Naval Research Laboratory's High Temperature Superconductivity Space Experiment 2 (HTSSE-2). Examples of variations observed in starting films and finished circuits will be presented. It is shown that under identical processing the properties of the HTS films can degrade to varying extents. Finally, we present data on ohmic contacts and factors affecting their adhesion to HTS films, strength of wire bonds made to such contacts, and aging effects.
The excellent microwave properties of the High-Temperature-Superconductors (HTS) have been amply demonstrated in the laboratory by techniques such as resonant cavity, power transmission and microstrip resonator measurements. The low loss and high Q passive structures made possible with HTS, present attractive options for applications in commercial, military and space-based systems. However, to readily insert HTS into these systems, improvement is needed in such areas as repeatability in the deposition and processing of the HTS films, metal-contact formation, wire bonding, and overall film endurance to fabrication and assembly procedures. In this paper, we present data compiled in our lab which illustrate many of the problems associated with these issues. Much of this data were obtained in the production of a space qualified hybrid receiver-downconverter module for the Naval Research Laboratory's High Temperature Superconductivity Space Experiment II (HTSSE-II). Examples of variations observed in starting films and finished circuits will be presented. It is shown that under identical processing the properties of the HTS films can degrade to varying extents. Finally, we present data on ohmic contacts and factors affecting their adhesion to HTS films, strength of wire bonds made to such contacts, and aging effects.
Cold Atom Laboratory (CAL) is a facility that will enable scientists to study ultra-cold quantum gases in a microgravity environment on the International Space Station (ISS) beginning in 2016. The primary science data for each experiment consists of two images taken in quick succession. The first image is of the trapped cold atoms and the second image is of the background. The two images are subtracted to obtain optical density. These raw Level 0 atom and background images are processed into the Level 1 optical density data product, and then into the Level 2 data products: atom number, Magneto-Optical Trap (MOT) lifetime, magnetic chip-trap atom lifetime, and condensate fraction. These products can also be used as diagnostics of the instrument health. With experiments being conducted for 8 hours every day, the amount of data being generated poses many technical challenges, such as downlinking and managing the required data volume. A parallel processing design is described, implemented, and benchmarked. In addition to optimizing the data pipeline, accuracy and speed in producing the Level 1 and 2 data products is key. Algorithms for feature recognition are explored, facilitating image cropping and accurate atom number calculations.
Stability derivatives affecting lateral behavior of aircraft and missiles
Spectral sensitivity of the chromophores to their immediate chemical environment establishes some of the chemical constituents of the grains in which they reside. These are: (1) Paraffins, such as, octane, nonane, decane, and others...(needed for Shpolskii matrices and producing quasilines); and (2) Pyridine. The presence of pyridine is required not only to produce the spectral DIB matching, but also to produce the 36 cm(sup -1) crystal field splitting of the S(sub 1) electronic state. The presence of pyridine in the grains can be confirmed spectroscopically. Pyridine produces a transmission window at 2175 A, matching exactly the well known UV hump. On grain reflection, some of the incoming UV radiation is absorbed into the grain's outer layers. Spikes in the lab and in the astronomical data are due to vibronic transitions in pyridine. The lab spectroscopy reported here clearly establishes the presence of MgTBP, H2TPB, and pyridine in the interstellar grains. The high fluorescence efficiency of MgTBP (being optically pumped in the visible) apparently accounts for all the observed UIR emissions.
The session "Mars: Remote Sensing and Terrestrial Analogs" included the following:Physical Meaning of the Hapke Parameter for Macroscopic Roughness: Experimental Determination for Planetary Regolith Surface Analogs and Numerical Approach; Near-Infrared Spectra of Martian Pyroxene Separates: First Results from Mars Spectroscopy Consortium; Anomalous Spectra of High-Ca Pyroxenes: Correlation Between Ir and M ssbauer Patterns; THEMIS-IR Emissivity Spectrum of a Large Dark Streak near Olympus Mons; Geomorphologic/Thermophysical Mapping of the Athabasca Region, Mars, Using THEMIS Infrared Imaging; Mars Thermal Inertia from THEMIS Data; Multispectral Analysis Methods for Mapping Aqueous Mineral Depostis in Proposed Paleolake Basins on Mars Using THEMIS Data; Joint Analysis of Mars Odyssey THEMIS Visible and Infrared Images: A Magic Airbrush for Qualitative and Quantitative Morphology; Analysis of Mars Thermal Emission Spectrometer Data Using Large Mineral Reference Libraries ; Negative Abundance : A Problem in Compositional Modeling of Hyperspectral Images; Mars-LAB: First Remote Sensing Data of Mineralogy Exposed at Small Mars-Analog Craters, Nevada Test Site; A Tool for the 2003 Rover Mini-TES: Downwelling Radiance Compensation Using Integrated Line-Sight Sky Measurements; Learning About Mars Geology Using Thermal Infrared Spectral Imaging: Orbiter and Rover Perspectives; Classifying Terrestrial Volcanic Alteration Processes and Defining Alteration Processes they Represent on Mars; Cemented Volcanic Soils, Martian Spectra and Implications for the Martian Climate; Palagonitic Mars: A Basalt Centric View of Surface Composition and Aqueous Alteration; Combining a Non Linear Unmixing Model and the Tetracorder Algorithm: Application to the ISM Dataset; Spectral Reflectance Properties of Some Basaltic Weathering Products; Morphometric LIDAR Analysis of Amboy Crater, California: Application to MOLA Analysis of Analog Features on Mars; Airborne Radar Study of Soil Moisture at a Mars Analog Site: Tohachi Wash/Little Colorado River; and Antarctic Dry Valleys: Modification of Rocks and Soils and Implications for Mars The Arkaroola Mars Analogue Region, South Australia.