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NASA NTRSDate not supplied

The NASA Biological Institutional Scientific Collection (NBISC): Tissue and Microbe Biospecimens to Advance Space Research

The NASA Biological Institutional Scientific Collection (NBISC) is a biorepository of non-human biospecimens from NASA-funded spaceflight investigations and correlative ground studies. The collection has its roots in the 1960s through collaborations by NASA Ames Research Center with other NASA centers, universities, and international space agencies by sharing non-human biospecimens from spaceflight and space-relevant ground experiments. These collaborations have advanced the field of space exploration by helping to maximize the data gained from spaceflight and other NASA-funded experiments. NBISC coordinates closely with the Biospecimen Sharing Program (BSP) which is responsible for organized sample collection from spaceflight and ground rodent experiments. In 2022 NBISC partnered with HRP’s Biospecimen and Tissue Sharing Collection (BTSC) Program to also archive samples from HRP’s Space Radiation Element-funded studies which primarily involve rodents exposed to various radiation protocols at the NASA Space Radiation Laboratory (NSRL) and other analog facilities. To date, more than fifty thousand biospecimens from BTSC have been transferred to NBISC for distribution to the community. In 2023, NBISC embarked on a new Space Biology funded endeavor to create the Space Microbial Culture Collection (SMCC) which will serve as a central repository for microbial isolates associated with space flight, gravitational, and space radiation research. This presentation will highlight several success stories of analyses carried out using archived NBISC samples received by researchers in recent years and will detail the process for proposing and receiving samples from NBISC, BTSC and SMCC. Making available these 150,000+ unique biospecimens to the scientific research community, NBISC not only serves as a repository for storing and distributing non-human biospecimens, but also acts as a resource to enable new discoveries that will benefit NASA and humankind.

Biospecimen↗

NASA NTRS1993

Technology for national asset storage systems

An industry-led collaborative project, called the National Storage Laboratory, was organized to investigate technology for storage systems that will be the future repositories for our national information assets. Industry participants are IBM Federal Systems Company, Ampex Recording Systems Corporation, General Atomics DISCOS Division, IBM ADSTAR, Maximum Strategy Corporation, Network Systems Corporation, and Zitel Corporation. Industry members of the collaborative project are funding their own participation. Lawrence Livermore National Laboratory through its National Energy Research Supercomputer Center (NERSC) will participate in the project as the operational site and the provider of applications. The expected result is an evaluation of a high performance storage architecture assembled from commercially available hardware and software, with some software enhancements to meet the project's goals. It is anticipated that the integrated testbed system will represent a significant advance in the technology for distributed storage systems capable of handling gigabyte class files at gigabit-per-second data rates. The National Storage Laboratory was officially launched on 27 May 1992.

Coyne, Robert A.↗

NASA NTRS2009

Software Tools Streamline Project Management

Three innovative software inventions from Ames Research Center (NETMARK, Program Management Tool, and Query-Based Document Management) are finding their way into NASA missions as well as industry applications. The first, NETMARK, is a program that enables integrated searching of data stored in a variety of databases and documents, meaning that users no longer have to look in several places for related information. NETMARK allows users to search and query information across all of these sources in one step. This cross-cutting capability in information analysis has exponentially reduced the amount of time needed to mine data from days or weeks to mere seconds. NETMARK has been used widely throughout NASA, enabling this automatic integration of information across many documents and databases. NASA projects that use NETMARK include the internal reporting system and project performance dashboard, Erasmus, NASA s enterprise management tool, which enhances organizational collaboration and information sharing through document routing and review; the Integrated Financial Management Program; International Space Station Knowledge Management; Mishap and Anomaly Information Reporting System; and management of the Mars Exploration Rovers. Approximately $1 billion worth of NASA s projects are currently managed using Program Management Tool (PMT), which is based on NETMARK. PMT is a comprehensive, Web-enabled application tool used to assist program and project managers within NASA enterprises in monitoring, disseminating, and tracking the progress of program and project milestones and other relevant resources. The PMT consists of an integrated knowledge repository built upon advanced enterprise-wide database integration techniques and the latest Web-enabled technologies. The current system is in a pilot operational mode allowing users to automatically manage, track, define, update, and view customizable milestone objectives and goals. The third software invention, Query-Based Document Management (QBDM) is a tool that enables content or context searches, either simple or hierarchical, across a variety of databases. The system enables users to specify notification subscriptions where they associate "contexts of interest" and "events of interest" to one or more documents or collection(s) of documents. Based on these subscriptions, users receive notification when the events of interest occur within the contexts of interest for associated document or collection(s) of documents. Users can also associate at least one notification time as part of the notification subscription, with at least one option for the time period of notifications.

Source record↗

NASA NTRS2015

Software Development: 3D Animations and Creating User Interfaces for Realistic Simulations

My fall 2015 semester was spent at the Lyndon B. Johnson Space Center working in the Integrated Graphics, Operations, and Analysis Laboratory (IGOAL). My first project was to create a video animation that could tell the story of OMICS. OMICS is a term being used in the field of biomedical science to describe the collective technologies that study biological systems, such as what makes up a cell and how it functions with other systems. In the IGOAL I used a large 23 inch Wacom monitor to draw storyboards, graphics, and line art animations. I used Blender as the 3D environment to sculpt, shape, cut or modify the several scenes and models for the video. A challenge creating this video was to take a term used in biomedical science and describe it in such a way that an 8th grade student can understand. I used a line art style because it would visually set the tone for what we thought was an educational style. In order to get a handle on the perspective and overall feel for the animation without overloading my workspace, I split up the 2 minute animation into several scenes. I used Blender's python scripting capabilities which allowed for the addition of plugins to add or modify tools. The scripts can also directly interact with the objects to create naturalistic patterns or movements. After collecting the rendered scenes, I used Blender's built-in video editing workspace to output the animation. My second project was to write software that emulates a physical system's interface. The interface was to simulate a boat, ROV, and winch system. Simulations are a time and cost effective way to test complicated data and provide training for operators without having to use expensive hardware. We created the virtual controls with 3-D Blender models and 2-D graphics, and then add functionality in C# using the Unity game engine. The Unity engine provides several essential behaviors of a simulator, such as the start and update functions. A framework for Unity, which was developed in the lab, provided a way to place the different widgets on the virtual console dock and have them resize correctly based on the window dimensions.. My task in this project was to create the controls and visualizations for the data coming in from the simulator for the boat portion of the project. I wrote a class for each control window to handle the functionality of that widget. I implemented 11 widgets that make up the ship portion of the simulator. The members of the lab were each masters of their craft and I'm glad I had the opportunity to learn from them. I learned to plan strategically so I could finish this project on time. I allotted time for storyboarding, development, and refinement. In regards to animating I learned to use modifiers like lattice, boolean and build deformers. I also learned how to animate with drivers, how to use the dope sheet, and how to use the graph editor. In coding I learned to limit the chances for bugs by privatizing functions that should be exclusive to their class. I learned how to use the GIT repository to commit, stash and pull the latest build. I learned a bit of everything because I had the chance to see the entire application development process from the artwork, to the implementation.

Gordillo, Orlando Enrique↗

NASA NTRS2002

The Exobiological Role of Interstellar Polycyclic Aromatic Hydrocarbons and Ices

Tremendous strides have been made in our understanding of interstellar material over the past twenty years thanks to significant, parallel developments in observational astronomy and laboratory astrophysics. Before this time, the composition of interstellar dust was largely guessed-at, the presence of ices in interstellar clouds ignored, and the notion that large, gas phase, carbon rich molecules might be abundant and widespread throughout the interstellar medium (ISM) considered impossible. Today, the composition of dust in the ISM is reasonably well constrained to micron-sized cold refractory materials comprised of amorphous and crystalline silicates mixed with an amorphous carbonaceous material containing aromatic structural units and short, branched aliphatic chains. Shrouded within the protective confines of cold, opaque molecular clouds--the birthplace of stars and planets--these cold dust particles secrete mantles of mixed molecular ices whose compositions are also well constrained. Finally, amidst the molecular inventory of these ice mantles are likely to be found polycyclic aromatic hydrocarbons (PAHs), shockingly large molecules by the standards of interstellar chemistry, the telltale infrared spectral signature of which is now recognized throughout the Universe. In the first part of this talk, we will review the spectroscopic evidence that forms the basis for the currently accepted abundance and ubiquity of PANs in the ISM. We will then look at a few specific examples which illustrate how experimental and theoretical data can be applied to interpret the interstellar spectra and track how the PAN population evolves as it passes from its formation site in the circumstellar outflows of dying stars, through the various phases of the ISM, and into forn~iing planetary systems. Nevertheless, despite the fact that PANs likely represent the single largest molecular reservoir of organic carbon in evolving planetary systems, they are not what would be considered "biogenic" molecules. Although interesting from a chemical and astrophysical standpoint, in the absence of a mechanism by which this population can be dislodged from the precipitous thermodynamic well afforded by their extensive aromatic networks, they are of little Astrobiological significance. Consequently, for the remainder of the talk, we will consider the photochemical evolution of PANS under conditions similar to those found in the ISM and in proto-planetary systems with an eye toward means by which this rich repository of pre-biotic organic "ore" might be converted into materials of greater importance to Astrobiology.

Hudgins, Douglas M.↗

NASA NTRS2020

Medics: Medical Decision Support System for Long-Duration Space Exploration

The Autonomous Medical Operations (AMO) group at NASA Ames is developing a “medical decision support system” to enable astronauts on long-duration exploration missions to operate autonomously. The system will support clinical actions by providing medical interpretation advice and procedural recommendations during emergent care and clinical work performed by crew. The current state of development of the system, called MedICS (Medical Interpretation Classification and Segmentation) includes two separate aspects: a set of machine learning diagnostic models trained to analyze organ images and patient health records, and an interface to ultrasound diagnostic hardware and to medical repositories. Three sets of images of different organs and medical records were utilized for training machine learning models for various analyses, as follows: 1. Pneumothorax condition (collapsed lung). The trained model provides a positive or negative diagnosis of the condition. 2. Carotid artery occlusion. The trained model produces a diagnosis of 5 different occlusion levels (including “normal”). 3. Ocular retinal images. The model extracts optic disc pixels (image segmentation). This is a precursor step for advanced autonomous fundus clinical evaluation algorithms to be implemented in FY20. 4. Medical health records. The model produces a differential diagnosis for any particular individual, based on symptoms and other health and demographic information. A probability is calculated for each of 25 most common conditions. The same model provides the likelihood of survival. All results are provided with a confidence level. Item 1 images were provided by the US Army and were part of a data set for the clinical treatment of injured battlefield soldiers. This condition is relevant to possible space mishaps, due to pressure management issues. Item 2 images were provided by Houston Methodist Hospital, and item 3 health records were acquired from the MIT laboratory of computational physiology. The machine learning technology utilized is deep multilayer networks (Deep Learning), and new models will continue to be produced, as relevant data is made available and specific health needs of astronaut crews are identified. The interfacing aspects of the system include a GUI for running the different models, and retrieving and storing data, as well as support for integration with an augmented reality (AR) system deployed at JSC by Tietronix Software Inc. (HoloLens). The AR system provides guidance for the placement of an ultrasound transducer that captures images to be sent to the MedICS system for diagnosis. The image captured and the associated diagnosis appear in the technician’s AR visual display.

Colombano, Silvano↗

NASA NTRSDate not supplied

Transcriptomic Analysis of Irradiated Mouse Retina Following Readaptation

Rodent models are used as analogs for studying the effects of spaceflight. NASA GeneLab provides access to relevant omics datasets generated from spaceflight and ground-based experiments allowing for additional retrospective analysis. In this study, we used GeneLab’s GLDS-203, a dataset generated by researchers at Loma Linda University to study the impact of prolonged unloading and/or low-dose radiation on mouse retina. We analyzed transcriptomics data from retina of mice irradiated with gamma-rays for 21 days followed by 7 days, 1 month, or 4 months of readaptation. We obtained raw gene counts from GeneLab and performed differential gene expression analysis after data normalization. For each of the three timepoints, we performed differential expression analysis to compare transcriptional profiles for retina from irradiated vs. non-irradiated (controls) mice, all exposed to gravity. We observed the highest number of differentially expressed genes at 7 days, followed by 1 month and 4 months. Enrichment analysis showed top pathways (adjusted p-value < 0.05) were related to transport along microtubule and photoreceptor cell development in the 7-day readaptation group. Fewer significantly enriched pathways were observed for the 1-month group and included mRNA metabolic processes and neuron differentiation. No significantly enriched pathways were found in the 4-month group. The Gene Ontology biological processes common between the 7 days and 1-month groups include visual perception, synapse organization, and perception of light stimulus. This analysis is part of a larger effort to characterize the molecular mechanisms involved in retinal readaptation following radiation exposure. Future analyses will include other related retina datasets in GeneLab repository to assess whether gene expression patterns are consistent across different study cohorts.

Prachi Kothiyal↗

NASA NTRSDate not supplied

Open-source Numerical Modeling of Solidification Cracking Susceptibility: Application to Refractory Alloy Systems

Introduction. Alloys such as aluminum, nickel-base, and austenitic stainless steels are susceptible to solidification cracking during welding and 3D printing. Compositional optimization is one method used to effectively mitigate solidification cracking of those alloy systems. With the surge in hypersonic and in-space propulsion activities, refractory metals (Nb, Mo, Ta, W, and Re) and their alloy derivatives are increasing in importance due to their extreme high melting point and retention of high-temperature strength; however, their chemistry was most typically optimized to promote ductility during mechanical operations such as drawing and forming. Welding of such alloys has been a challenge due to a number of issues including solidification cracking, atmospheric contamination (O, C, and N), as well as a shift in ductile-to-brittle transition to higher temperature following grain growth induced by welding. Compositional optimization of refractory alloys for solidification cracking resistance in particular is desirable as their usage increases with the advent of advanced manufacturing methods such as 3D printing. This work evaluates the effect of compositional variation in refractory metal systems on the solidification cracking susceptibility with the goals of optimizing existing alloys and joining process techniques, and formulating new alloys with increased solidification cracking resistance. Experimental Procedures. A python code was developed in a Jupyter notebook environment (Michael and Sowards, 2023) to facilitate the calculation of crack susceptibility index proposed by Kou (2015). Composition is entered as a single point, or as a 1-D or 2-D array. The notebook calls pycalphad (Otis and Liu, 2017 and Bocklund et al, 2020) to calculate the evolution of fraction solid as a function of temperature (under either Scheil or equilibrium assumptions) and then evaluates steepness of the fraction solid curve near the terminal stage of solidification to predict solidification cracking resistance. Open source thermodynamic databases available at online repositories are used (van de Walle). The process is setup in an automated fashion to generate plots that show variation in solidification cracking susceptibility according to composition on 1-D line plots or 2-D contour plots. The Jupyter notebook and crack susceptibility algorithm was also integrated with a widely used commercial CALPHAD code for validation and alloy exploration. Results and Discussion. The crack susceptibility model was first validated against a series of refractory alloy compositions evaluated in past work which utilized a specialized Varestraint test built inside a vacuum chamber environment (Lessman and Gold, 1971). The alloys tested in the Varestraint apparatus included T-111 (Ta-8W-2Hf), ASTAR-811C (Ta-8W-1Re-0.7Hf-0.025C), FS-85 (Nb-27Ta-10W-1Zr), T-222 (Ta-9.6W-2.4Hf-0.01C), Ta-10W, B-66 (Nb-5Mo-5V-1Zr), and SCb-291 (Nb-10W-10Ta). The initial test of the model showed a strong correlation with empirical Varestraint data, i.e., a Spearman rank correlation between model predictions and hot cracking measurements was observed to be greater than 0.8. Following the validation, a set of refractory metal binary mixtures was investigated to evaluate sensitivity of Nb, Mo, W, and Ta to C, N, and O content. A series of plots were produced that suggest ppmw ranges of C, N, and O where solidification cracking increases significantly and reaches a maximum. Also comparative ranking of each primary refractory metal to each interstitial was produced. For example C produces greater cracking response in Mo whereas O produces greater cracking response in Ta and Nb. Such compositional values have utility in setting limits on pickup of these interstitial elements during welding and printing rather than using a one-size-fits-all approach. Furthermore, the results have use in determining additive powder recycling requirements, which is especially pertinent for refractory metal powders due to their high cost compared to conventional alloys. Another application created thousands of hypothetical alloys within the nominal specified composition range of two widely used refractory alloys C103 (Nb-10Hf-1Ti) and TZM (Mo-0.5Ti-0.1Zr). The cracking index was calculated for the alloys and results were fed into machine learning regression techniques including Multiple Linear Regression, Ridge Regression, and Lasso Regression to determine relative potency each alloying element had on computed solidification cracking index. A series of linear equations were produced that relate composition of C103 and TZM to solidification cracking index. The crack susceptibility of C103 for example is described by an equation of the form: cracking index ~ O + 0.667*C + 0.635*N + 0.00037*Ta – 0.0008*Hf (in wt.%) From that equation, it is clear that O has strong propensity to induce solidification cracking. Interestingly, Hf is shown to reduce calculated cracking response. Finally, realizing the potential of this method to discover new refractory alloy formulations across the period table that have low solidification cracking sensitivity, the code was applied to new untested alloy systems including W-Zr-C, W-Ta-C, and others. Conclusions. In summary, an open source numerical method has been developed using Python code to calculate Kou’s crack susceptibility index. The method was applied to refractory metals which are inherently difficult to study from a weldability testing standpoint since inert shielding gas is not sufficient and welding is typically done in vacuum, especially in light of findings presented here where oxygen has profound influence on solidification cracking. This work revealed the effect of compositional variations on a series of refractory metals and showed the framework defined here will be useful in 1) the development of new alloys that have improved weldability and 3D printability, 2) placing compositional limits on existing alloys, and 3) ensuring adequate controls of manufacturing processes such as 3D printing where powder reuse is critical. Keywords. pycalphad; Python; refractory metals; solidification cracking. References. B. Bocklund et. al. (2020) http://doi.org/10.5281/zenodo.3630657. S. Kou. (2015) https://doi.org/10.1016/j.actamat.2015.01.034. G.G. Lessmann and R.E. Gold. Welding Journal, issue 1, pp. 1-s – 8-s (1971). F.N. Michael and J.W. Sowards. NASA/TM-20230002218 (2023). R. Otis and Z.-K. Liu. (2017) http://doi.org/10.5334/jors.140. A. Van de Wallle et. al. (2018) https://doi.org/10.1016/j.calphad.2018.04.003.

pycalphad↗

NASA NTRS2023

SafeAeroBERT: Towards a Safety-Informed Aerospace-Specific Language Model

As aviation systems continue to operate with high traffic, large amounts of documents containing safety-relevant data continue to be generated via reporting systems such as the ASRS. Advanced natural language processing techniques, specifically pre-trained language models, have shown great success in domain-specific applications; however, the text in aviation safety reports is inundated with jargon and thus not fully utilized by general pre-trained models. In this research, we work towards developing a safety-informed aerospace-specific language model by pre-training a Bidirectional Encoder Representations from Transformer (BERT) model on reports from the Aviation Safety Reporting System and the National Transportation Safety Board. The resulting model, called SafeAeroBERT, is fine-tuned for the specific task of document classification, and can be further tuned for named-entity recognition, relation detection, information retrieval, and summarization. Results from the classification task are compared between SafeAeroBERT, the base BERT, and SciBERT models and show SafeAeroBERT outperforms the general BERT and SciBERT on classifying reports about human factors, aircraft, and procedure. SafeAeroBERT can be used on custom tasks, not limited to document classification, and is intended to aid an intelligent knowledge manager for safety report repositories.

Aviation↗

NASA NTRS2018

New Metadata Capabilities within NASA's Common Metadata Repository (CMR)

This talk will convey the new capabilities and features of the UMM-Variables and the UMM-Services metadata model within the Common Metadata Repository (CMR) and how community engagement through the ESDIS Standards Office (ESO) review shaped the new versions of the models. The Unified Metadata Model (UMM) provides a common metadata model to unify legacy systems (i.e. GCMD (Global Change Master Directory), ECHO (Earth Observing System (EOS) Clearinghouse)) with new systems (i.e. CMR). The rationale and migration process of the Service Entry Resource Format (SERF) to the UMM-S will also be conveyed. The talk will conclude with discussing issues and lessons learned from the review process and how future reviews will be conducted to ensure a more targeted, meaningful review with a faster turn-around time for triage and implementation.

Earth Observing System↗

NASA NTRSDate not supplied

SafeAeroBERT: Towards a Safety-Informed Aerospace-Specific Language Model

As aviation systems continue to operate with high traffic, large amounts of documents containing safety-relevant data continue to be generated via reporting systems such as the Aviation Safety Reporting System (ASRS). Advanced natural language processing techniques, specifically pre-trained language models, have shown great success in domain-specific applications; however, the text in aviation safety reports is inundated with jargon and thus not fully utilized by general pre-trained models. In this research, we work towards developing a safety-informed aerospace-specific language model by pre-training a Bidirectional Encoder Representations from Transformer (BERT) model on reports from the Aviation Safety Reporting System and the National Transportation Safety Board. The resulting model, called SafeAeroBERT, is fine-tuned for the specific task of document classification, and can be further tuned for named-entity recognition, relation detection, information retrieval, and summarization. Results from the classification task are compared between SafeAeroBERT, the base BERT, and SciBERT models and show SafeAeroBERT outperforms the general BERT and SciBERT on classifying reports about weather and procedure. SafeAeroBERT can be used on custom tasks, not limited to document classification, and is intended to aid an intelligent knowledge manager for safety report repositories.

Aviation↗

NASA NTRS1997

Issues in Defining Software Architectures in a GIS Environment

The primary mission of the Pan-American Center for Earth and Environmental Studies (PACES) is to advance the research areas that are relevant to NASA's Mission to Planet Earth program. One of the activities at PACES is the establishment of a repository for geographical, geological and environmental information that covers various regions of Mexico and the southwest region of the U.S. and that is acquired from NASA and other sources through remote sensing, ground studies or paper-based maps. The center will be providing access of this information to other government entities in the U.S. and Mexico, and research groups from universities, national laboratories and industry. Geographical Information Systems(GIS) provide the means to manage, manipulate, analyze and display geographically referenced information that will be managed by PACES. Excellent off-the-shelf software exists for a complete GIS as well as software for storing and managing spatial databases, processing images, networking and viewing maps with layered information. This allows the user flexibility in combining systems to create a GIS or to mix these software packages with custom-built application programs. Software architectural languages provide the ability to specify the computational components and interactions among these components, an important topic in the domain of GIS because of the need to integrate numerous software packages. This paper discusses the characteristics that architectural languages address with respect to the issues relating to the data that must be communicated between software systems and components when systems interact. The paper presents a background on GIS in section 2. Section 3 gives an overview of software architecture and architectural languages. Section 4 suggests issues that may be of concern when defining the software architecture of a GIS. The last section discusses the future research effort and finishes with a summary.

Acosta, Jesus↗

NASA NTRS1993

The Advanced Technology Operations System: ATOS

Mission control systems supporting new space missions face ever-increasing requirements in terms of functionality, performance, reliability and efficiency. Modern data processing technology is providing the means to meet these requirements in new systems under development. During the past few years the European Space Operations Centre (ESOC) of the European Space Agency (ESA) has carried out a number of projects to demonstrate the feasibility of using advanced software technology, in particular, knowledge based systems, to support mission operations. A number of advances must be achieved before these techniques can be moved towards operational use in future missions, namely, integration of the applications into a single system framework and generalization of the applications so that they are mission independent. In order to achieve this goal, ESA initiated the Advanced Technology Operations System (ATOS) program, which will develop the infrastructure to support advanced software technology in mission operations, and provide applications modules to initially support: Mission Preparation, Mission Planning, Computer Assisted Operations, and Advanced Training. The first phase of the ATOS program is tasked with the goal of designing and prototyping the necessary system infrastructure to support the rest of the program. The major components of the ATOS architecture is presented. This architecture relies on the concept of a Mission Information Base (MIB) as the repository for all information and knowledge which will be used by the advanced application modules in future mission control systems. The MIB is being designed to exploit the latest in database and knowledge representation technology in an open and distributed system. In conclusion the technological and implementation challenges expected to be encountered, as well as the future plans and time scale of the project, are presented.

Kaufeler, J.-F.↗

NASA NTRS2003

Principles for Integrating Mars Analog Science, Operations, and Technology Research

During the Apollo program, the scientific community and NASA used terrestrial analog sites for understanding planetary features and for training astronauts to be scientists. Human factors studies (Harrison, Clearwater, & McKay 1991; Stuster 1996) have focused on the effects of isolation in extreme environments. More recently, with the advent of wireless computing, we have prototyped advanced EVA technologies for navigation, scheduling, and science data logging (Clancey 2002b; Clancey et al., in press). Combining these interests in a single expedition enables tremendous synergy and authenticity, as pioneered by Pascal Lee's Haughton-Mars Project (Lee 2001; Clancey 2000a) and the Mars Society s research stations on a crater rim on Devon Island in the High Canadian Arctic (Clancey 2000b; 2001b) and the Morrison Formation of southeast Utah (Clancey 2002a). Based on this experience, the following principles are proposed for conducting an integrated science, operations, and technology research program at analog sites: 1) Authentic work; 2) PI-based projects; 3) Unencumbered baseline studies; 4) Closed simulations; and 5) Observation and documentation. Following these principles, we have been integrating field science, operations research, and technology development at analog sites on Devon Island and in Utah over the past five years. Analytic methods include work practice simulation (Clancey 2002c; Sierhuis et a]., 2000a;b), by which the interaction of human behavior, facilities, geography, tools, and procedures are formalized in computer models. These models are then converted into the runtime EVA system we call mobile agents (Clancey 2002b; Clancey et al., in press). Furthermore, we have found that the Apollo Lunar Surface Journal (Jones, 1999) provides a vast repository or understanding astronaut and CapCom interactions, serving as a baseline for Mars operations and quickly highlighting opportunities for computer automation (Clancey, in press).

Clancey, William J.↗

NASA NTRSDate not supplied

Application of ML/AI for Identifying Earth Science Datasets in Research Publications

NASA Data Active Archive Centers, or DAACs, ingest, store and distribute data acquired from satellites, ground systems as well as modelling data. These data are organized by the datasets, each presenting collection of files usually associated with the certain mission, instrument, processing level, parameter(s), algorithm and/or model. The number of datasets offered by a single DAAC to the public varies. GES DISC, for example, currently offers for public use approximately ~1,300 datasets. While each publicly offered dataset comes with supporting documentation, it is challenging for novice and even experienced scientists to navigate among the datasets that offer similar parameters to find the datasets for their particular research application. Supplying dataset documentation with the scientific paper citations that refer to that dataset provides means for the dataset users to educate themselves with the application research that dataset is being used in. Collecting citations of the papers that use the datasets for their research yield valuable insights into application areas of those datasets, information about usage of the dataset groups for specific applications and those application topics. It also gives insights into the “deep metrics” of the dataset usage, as opposed to the common metrics of the dataset usage such as number of users who downloaded the dataset files and volumes of downloaded data. Association of a certain scientific paper with the dataset(s) presents a challenge because most of the paper authors do not properly cite the datasets, datasets usually have cryptic names and Digital Object Identifiers (DOIs) that are used for dataset identification were assigned to the datasets only few years ago. Simple Google or online library search do not provide even meaningful fraction of the results when performed by the dataset name or DOI, however they provide too many results when the search is done by more broader terms such as mission and instrument names. Attempts to create an AI system capable to identify dataset in the scientific papers have already been made using neural networks classifiers on the basis of the dataset mission, instrument and variable name. This method was applied to NASA SEDAC, which has 41 datasets in total. In GES DISC there can be as many as ~100 datasets per mission/instrument with some of the datasets consisting of multiple variables so there is a need for more differentiating parameters for dataset identification in the paper. The approach we are currently investigating is creating AI classifiers that are based on multiple dataset features, or keywords, extracted from the NASA Earthdata Common Dataset Repository (CMR). The features are weighted based on how precisely they can identify a dataset. The classifier uses preprocessed paper text as input and searches for the CMR datasets whose feature sets are the closest to the feature sets contained in the paper. The challenges of dataset identification include variety of ways the paper authors describe the datasets in their papers and incomplete tagging of the CMR dataset description (DIFs).

Irina Gerasimov↗

NASA NTRS2014

Humic Acid Complexation of Th, Hf and Zr in Ligand Competition Experiments: Metal Loading and Ph Effects

The mobility of metals in soils and subsurface aquifers is strongly affected by sorption and complexation with dissolved organic matter, oxyhydroxides, clay minerals, and inorganic ligands. Humic substances (HS) are organic macromolecules with functional groups that have a strong affinity for binding metals, such as actinides. Thorium, often studied as an analog for tetravalent actinides, has also been shown to strongly associate with dissolved and colloidal HS in natural waters. The effects of HS on the mobilization dynamics of actinides are of particular interest in risk assessment of nuclear waste repositories. Here, we present conditional equilibrium binding constants (Kc, MHA) of thorium, hafnium, and zirconium-humic acid complexes from ligand competition experiments using capillary electrophoresis coupled with ICP-MS (CE- ICP-MS). Equilibrium dialysis ligand exchange (EDLE) experiments using size exclusion via a 1000 Damembrane were also performed to validate the CE-ICP-MS analysis. Experiments were performed at pH 3.5-7 with solutions containing one tetravalent metal (Th, Hf, or Zr), Elliot soil humic acid (EHA) or Pahokee peat humic acid (PHA), and EDTA. CE-ICP-MS and EDLE experiments yielded nearly identical binding constants for the metal- humic acid complexes, indicating that both methods are appropriate for examining metal speciation at conditions lower than neutral pH. We find that tetravalent metals form strong complexes with humic acids, with Kc, MHA several orders of magnitude above REE-humic complexes. Experiments were conducted at a range of dissolved HA concentrations to examine the effect of [HA]/[Th] molar ratio on Kc, MHA. At low metal loading conditions (i.e. elevated [HA]/[Th] ratios) the ThHA binding constant reached values that were not affected by the relative abundance of humic acid and thorium. The importance of [HA]/[Th] molar ratios on constraining the equilibrium of MHA complexation is apparent when our estimated Kc, MHA values attained at very low metal loading conditions are compared to existing literature data. Overall, experimental data suggest that the tetravalent transition metal/-actinide-humic acid complexation is important over a wide range of pH values, including mildly acidic conditions, and thus, these complexes should be included in speciation models.

humic acid↗

NASA NTRS1997

Risk Management of NASA Projects

Various NASA Langley Research Center and other center projects were attempted for analysis to obtain historical data comparing pre-phase A study and the final outcome for each project. This attempt, however, was abandoned once it became clear that very little documentation was available. Next, extensive literature search was conducted on the role of risk and reliability concepts in project management. Probabilistic risk assessment (PRA) techniques are being used with increasing regularity both in and outside of NASA. The value and the usage of PRA techniques were reviewed for large projects. It was found that both civilian and military branches of the space industry have traditionally refrained from using PRA, which was developed and expanded by nuclear industry. Although much has changed with the end of the cold war and the Challenger disaster, it was found that ingrained anti-PRA culture is hard to stop. Examples of skepticism against the use of risk management and assessment techniques were found both in the literature and in conversations with some technical staff. Program and project managers need to be convinced that the applicability and use of risk management and risk assessment techniques is much broader than just in the traditional safety-related areas of application. The time has come to begin to uniformly apply these techniques. The whole idea of risk-based system can maximize the 'return on investment' that the public demands. Also, it would be very useful if all project documents of NASA Langley Research Center, pre-phase A through final report, are carefully stored in a central repository preferably in electronic format.

Sarper, Hueseyin↗

NASA NTRSDate not supplied

Discovery Through Biospecimen Sharing: The Nasa Biological Institutional Scientific Collection (NBISC)

NASA Ames Research Center has fostered collaborations with other NASA centers, universities, and international space agencies by sharing non-human biospecimens from spaceflight and space-relevant ground experiments since the 1960s. These collaborations have advanced the field of space exploration by helping to maximize the data gained from spaceflight experiments. Non-human tissues archived from experiments funded by NASA’s Space Biology and Human Research Programs (HRP) are available for request through the NASA Life Sciences Portal (NLSP) and distributed by the NASA Biological Institutional Scientific Collection (NBISC). NBISC coordinates closely with the Ames Biospecimen Sharing Program (BSP) which is responsible for sample collection from spaceflight and ground experiments. NBISC currently houses more than 90,000 biospecimens in its facility at NASA Ames. Until recently, NBISC primarily distributed samples from Space Biology funded research. In 2022 NBISC partnered with HRP Space Radiation Element to also archive samples from studies which primarily involve rodents exposed to galactic cosmic radiation simulations at the NASA Space Radiation Laboratory (NSRL) and other analog facilities. In this presentation we will highlight several success stories of analyses carried out using archived NBISC samples received by researchers in recent years and will detail the process for proposing and receiving samples from NBISC. Making available these 90,000+ unique biospecimens to the scientific research community, NBISC not only functions as a resource for storing and distributing non-human biospecimens, but as a warehouse for future discoveries for the benefit of NASA and humankind.

NBISC↗