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NASA NTRS1987

Optimization of the tungsten oxide technique for measurement of atmospheric ammonia

Hollow tubes coated with tungstic acid have been shown to be of value in the determination of ammonia and nitric acid in ambient air. Practical application of this technique was demonstrated utilizing an automated sampling system for in-flight collection and analysis of atmospheric samples. Due to time constraints these previous measurements were performed on tubes that had not been well characterized in the laboratory. As a result the experimental precision could not be accurately estimated. Since the technique was being compared to other techniques for measuring these compounds, it became necessary to perform laboratory tests which would establish the reliability of the technique. This report is a summary of these laboratory experiments as they are applied to the determination of ambient ammonia concentration.

Brown, Kenneth G.↗

NASA NTRS1998

RIACS

The Research Institute for Advanced Computer Science (RIACS) was established by the Universities Space Research Association (USRA) at the NASA Ames Research Center (ARC) on June 6, 1983. RIACS is privately operated by USRA, a consortium of universities that serves as a bridge between NASA and the academic community. Under a five-year co-operative agreement with NASA, research at RIACS is focused on areas that are strategically enabling to the Ames Research Center's role as NASA's Center of Excellence for Information Technology. Research is carried out by a staff of full-time scientist,augmented by visitors, students, post doctoral candidates and visiting university faculty. The primary mission of RIACS is charted to carry out research and development in computer science. This work is devoted in the main to tasks that are strategically enabling with respect to NASA's bold mission in space exploration and aeronautics. There are three foci for this work: Automated Reasoning. Human-Centered Computing. and High Performance Computing and Networking. RIACS has the additional goal of broadening the base of researcher in these areas of importance to the nation's space and aeronautics enterprises. Through its visiting scientist program, RIACS facilitates the participation of university-based researchers, including both faculty and students, in the research activities of NASA and RIACS. RIACS researchers work in close collaboration with NASA computer scientists on projects such as the Remote Agent Experiment on Deep Space One mission, and Super-Resolution Surface Modeling.

Moore, Robert C.↗

NASA NTRS1999

Transition to Glass: Pilot Training for High-Technology Transport Aircraft

This report examines the activities of a major commercial air carrier between 1993 and late 1996 as it acquired an advanced fleet of high-technology aircraft (Boeing 757). Previously, the airline's fleet consisted of traditional (non-glass) aircraft, and this report examines the transition from a traditional fleet to a glass one. A total of 150 pilots who were entering the B-757 transition training volunteered for the study, which consisted of three query phases: (1) first day of transition training, (2) 3 to 4 months after transition training, and (3) 12 to 14 months after initial operating experience. Of these initial 150 pilots, 99 completed all three phases of the study, with each phase consisting of probes on attitudes and experiences associated with their training and eventual transition to flying the line. In addition to the three questionnaires, 20 in-depth interviews were conducted. Although the primary focus of this study was on the flight training program, additional factors such as technical support, documentation, and training aids were investigated as well. The findings generally indicate that the pilot volunteers were highly motivated and very enthusiastic about their training program. In addition, the group had low levels of apprehension toward automation and expressed a high degree of satisfaction toward their training. However, there were some concerns expressed regarding the deficiencies in some of the training aids and lack of a free-play flight management system training device.

Wiener, Earl L.↗

NASA NTRS2002

Vertex Movement for Mission Status Graphics: A Polar-Star Display

Humans are traditionally bad monitors, especially over long periods of time on reliable systems, and they are being called upon to do this more and more as systems become further automated. Because of this, there is a need to find a way to display the monitoring information to the human operator in such a way that he can notice pertinent deviations in a timely manner. One possible solution is to use polar-star displays that will show deviations from normal in a more salient manner. A polar-star display uses a polygon's vertices to report values. An important question arises, though, of how the vertices should move. This experiment investigated two particular issues of how the vertices should move: (1) whether the movement of the vertices should be continuous or discrete and (2) whether the parameters that made up each vertex should always move in one direction regardless of parameter sign or move in both directions indicating parameter sign. The results indicate that relative movement direction is best. Subjects performed better with this movement type and they subjectively preferred it to the absolute movement direction. As for movement type, no strong preferences were shown.

Trujillo, Anna↗

NASA NTRS2009

Estimation of Separation Buffers for Wind-Prediction Error in an Airborne Separation Assistance System

Wind prediction errors are known to affect the performance of automated air traffic management tools that rely on aircraft trajectory predictions. In particular, automated separation assurance tools, planned as part of the NextGen concept of operations, must be designed to account and compensate for the impact of wind prediction errors and other system uncertainties. In this paper we describe a high fidelity batch simulation study designed to estimate the separation distance required to compensate for the effects of wind-prediction errors throughout increasing traffic density on an airborne separation assistance system. These experimental runs are part of the Safety Performance of Airborne Separation experiment suite that examines the safety implications of prediction errors and system uncertainties on airborne separation assurance systems. In this experiment, wind-prediction errors were varied between zero and forty knots while traffic density was increased several times current traffic levels. In order to accurately measure the full unmitigated impact of wind-prediction errors, no uncertainty buffers were added to the separation minima. The goal of the study was to measure the impact of wind-prediction errors in order to estimate the additional separation buffers necessary to preserve separation and to provide a baseline for future analyses. Buffer estimations from this study will be used and verified in upcoming safety evaluation experiments under similar simulation conditions. Results suggest that the strategic airborne separation functions exercised in this experiment can sustain wind prediction errors up to 40kts at current day air traffic density with no additional separation distance buffer and at eight times the current day with no more than a 60% increase in separation distance buffer.

Consiglio, Maria C.↗

NASA NTRS2013

High Speed Mobility Through On-Demand Aviation

Game changing advances come about by the introduction of new technologies at a time when societal needs create the opportunity for new market solutions. A unique opportunity exists for NASA to bring about such a mobility revolution in General Aviation, extendable to other aviation markets, to maintain leadership in aviation by the United States. This report outlines the research carried out so far under NASA's leadership towards developing a new mobility choice, called Zip Aviation1,2,3. The feasibility, technology and system gaps that need to be addressed, and pathways for successful implementation have been investigated to guide future investment. The past decade indicates exciting trends in transportation technologies, which are quickly evolving. Automobiles are embracing automation to ease driver tasks as well as to completely control the vehicle with added safety (Figure 1). Electric propulsion is providing zero tail-pipe emission vehicles with dramatically lower energy and maintenance costs. These technologies have not yet been applied to aviation, yet offer compelling potential benefits across all aviation markets, and in particular to General Aviation (GA) as an early adopter market. The benefits of such an adoption are applicable in the following areas: 􀁸 Safety: The GA market experiences accident rates that are substantially higher than automobiles or commercial airlines, with 7.5 fatal accidents per 100 million vehicle miles compared to 1.3 for automobiles and.068 for airlines. Approximately 80% of these accidents are caused by some form of pilot error, with another 13% caused by single point propulsion system failure. 􀁸 Emissions: Environmental constraints are pushing for the elimination of 100Low Lead (LL) fuel used in most GA aircraft, with aviation fuel the #1 source of lead emissions into the environment. Aircraft also have no emission control systems (i.e. no catalytic converters etc.), so they are gross hydrocarbon polluters compared to automobiles. 􀁸 Community Noise: Hub and smaller GA airports are facing increasing noise restrictions, and while commercial airliners have dramatically decreased their community noise footprint over the past 30 years, GA aircraft noise has essentially remained same, and moreover, is located in closer proximity to neighborhoods and businesses. 􀁸 Operating Costs: GA operating costs have risen dramatically due to average fuel costs of over $6 per gallon, which has constrained the market over the past decade and resulted in more than 50% lower sales and 35% less yearly operations. Infusion of autonomy and electric propulsion technologies can accomplish not only a transformation of the GA market, but also provide a technology enablement bridge for both larger aircraft and the emerging civil Unmanned Aerial Systems (UAS) markets. The NASA Advanced General Aviation Transport Experiments (AGATE) project successfully used a similar approach to enable the introduction of primary composite structures and flat panel displays in the 1990s, establishing both the technology and certification standardization to permit quick adoption through partnerships with industry, academia, and the Federal Aviation Administration (FAA). Regional and airliner markets are experiencing constant pressure to achieve decreasing levels of community emissions and noise, while lowering operating costs and improving safety. But to what degree can these new technology frontiers impact aircraft safety, the environment, operations, cost, and performance? Are the benefits transformational enough to fundamentally alter aircraft competiveness and productivity to permit much greater aviation use for high speed and On-Demand Mobility (ODM)? These questions were asked in a Zip aviation system study named after the Zip Car, an emerging car-sharing business model. Zip Aviation investigates the potential to enable new emergent markets for aviation that offer "more flexibility than the existing transportation solutions." These studies indicate that autonomy and electric propulsion technology infusions offer a unique opportunity to provide breakthrough capabilities for new high speed, on-demand travel alternatives that can leapfrog the need for future expensive ground-based infrastructure investment. At the same time, such investments offer a method of laying the foundation for these technologies to be incubated for commercial aviation at lower cost, and with lower initial certification thresholds due to the relatively poor capabilities of GA aircraft to permit early adoption and private market capitalization by rapid technology accelerations, as depicted in Figure 2.

Moore, Mark D.↗

NASA NTRSDate not supplied

Automated Tracking of Shallow Maritime Clouds on Geostationary Imagery to Extract Lifecycle Characteristics

Shallow moist convection is ubiquitous throughout the tropics and represents a key player in boundary layer processes. Satellites have provided many statistics on shallow clouds, such as size, structure, and geographical coverage, from static views of recurring cloud fields. But determining why certain cloud features appear and persist for different periods requires a time-evolving view of their behaviors. Geostationary satellites provide a unique opportunity to follow the time evolution of individual convective features, given their enhanced spatial and temporal sampling. A cloud-tracking tool was developed to identify properties of cloud lifecycle from the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2EX) field campaign of 2019. The mission conducted intensive sampling of shallow cumulus in the West Pacific Ocean, in tandem with Rapid Scan imagery from the Advanced Himawari Imager (AHI) on the Japan Meteorological Agency’s (JMA) Himawari-8 satellite. Shallow cumulus was segmented according to thresholds in 0.5-km visible reflectance and with blurring techniques. Despite being limited to daytime hours, the segmentations yielded the best resolution possible for capturing cloud initiation and decay. The tracking procedure is based on a computer vision package that includes Kalman filters for motion prediction, object overlap search, and the Hungarian (or Kuhn-Munkres) matching algorithm for track designation. AHI radiances available within the tracked cloud boundaries are assembled to form individual spectral histories. The resulting catalog provides thousands of cloud histories for domains measuring only a few degrees in latitude and longitude. We present an overview of the cloud-tracking tool, strategies to identify development stages from cloud tracks, and preliminary results that document cumulus lifecycle properties from satellite. The application of AHI 0.5-km reflectance has both strengths and limitations when attempting to track lifecycles of the smallest resolvable clouds. We show that by aggregating cloud tracks from a few case studies of CAMP2EX, we can discern differences in cloud lifetime and development according to ensembles selected from areas of interest. The results demonstrate an ability to quantify lifetimes and assess rates of change in cloud characteristics that are likely controlled by the surrounding environment and meteorology.

Cloud Tracking↗

NASA NTRSDate not supplied

Automated Tracking of Shallow Maritime Clouds on Geostationary Imagery to Extract Lifecycle Characteristics

Shallow moist convection is ubiquitous throughout the tropics and represents a key player in boundary layer processes. Satellites have provided valuable insight on shallow clouds, such as size, structure, and geographical coverage, from static views of recurring cloud fields. But determining why certain cloud features appear and persist for different periods requires a time-evolving view of their behaviors. Geostationary satellites provide a unique opportunity to follow the time evolution of individual convective features, given their enhanced spatial and temporal sampling. A cloud-tracking tool was developed to identify properties of cloud lifecycle from the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2EX) field campaign of 2019. The mission conducted intensive sampling of shallow cumulus in the West Pacific Ocean, in tandem with Rapid Scan imagery from the Advanced Himawari Imager (AHI) on the Japan Meteorological Agency’s (JMA) Himawari-8 satellite. Shallow cumulus were segmented according to thresholds in 0.5-km visible reflectance and with blurring techniques. Despite being limited to daytime hours, the segmentations yielded the best resolution available for capturing cloud initiation, growth, and decay. The tracking procedure is based on a computer vision package that includes Kalman filters for motion prediction, object overlap search, and the Hungarian (or Kuhn-Munkres) matching algorithm for track designation. AHI radiances available within the tracked cloud boundaries are assembled to form individual spectral histories. The resulting catalog provides thousands of cloud histories for domains measuring only a few degrees in latitude and longitude. We present an overview of the cloud-tracking tool and its results for cloud fields sampled throughout CAMP2EX by the airborne P-3. Cloud tracks were selected from about 10 flights to form ensembles, specific groups of tracks occurring in a region with airborne sampling. Cloud lifecycle properties, including duration and maximum area, are calculated for all ensemble members, and analyzed for cloud behavior and P-3 coincidences. By following this strategy, we quantitatively assess the degree of airborne sampling for specific cloud classes defined by the lifecycle calculations. We can summarize which cloud classes had more sampling, the stage of development during sampling, and general differences in character (e.g., isolated congestus vs. cold-pool producer).

Cloud Tracking↗

NASA NTRS1973

Space science plans for the shuttle era.

Three separate and distinct modes of using the space shuttle system have been identified. These modes include the boost of a spacecraft plus one or more propulsion stages into earth orbit or parking orbit, the establishment and maintenance of automated observatories in space, and the support of exploratory research and instrument development. Studies show that approximately 60% of all planned NASA missions require a shuttle third stage. Illustrations are presented to show how the largest spacecraft, Viking, and its propulsion system, Centaur, and a communications satellite, with an Agena stage to place it into a geostationary orbit, would fit into the shuttle. Results of the NASA Shuttle Sortie Workshop studies are discussed together with prospects of European cooperation in future workshop experiments.

Naugle, J. E.↗

NASA NTRS1998

RIACS

The Research Institute for Advanced Computer Science (RIACS) was established by the Universities Space Research Association (USRA) at the NASA Ames Research Center (ARC) on June 6, 1983. RIACS is privately operated by USRA, a consortium of universities that serves as a bridge between NASA and the academic community. Under a five-year co-operative agreement with NASA, research at RIACS is focused on areas that are strategically enabling to the Ames Research Center's role as NASA's Center of Excellence for Information Technology. The primary mission of RIACS is charted to carry out research and development in computer science. This work is devoted in the main to tasks that are strategically enabling with respect to NASA's bold mission in space exploration and aeronautics. There are three foci for this work: (1) Automated Reasoning. (2) Human-Centered Computing. and (3) High Performance Computing and Networking. RIACS has the additional goal of broadening the base of researcher in these areas of importance to the nation's space and aeronautics enterprises. Through its visiting scientist program, RIACS facilitates the participation of university-based researchers, including both faculty and students, in the research activities of NASA and RIACS. RIACS researchers work in close collaboration with NASA computer scientists on projects such as the Remote Agent Experiment on Deep Space One mission, and Super-Resolution Surface Modeling.

Moore, Robert C.↗

NASA NTRS2004

Using Generative Representations to Evolve Robots

Recent research has demonstrated the ability of evolutionary algorithms to automatically design both the physical structure and software controller of real physical robots. One of the challenges for these automated design systems is to improve their ability to scale to the high complexities found in real-world problems. Here we claim that for automated design systems to scale in complexity they must use a representation which allows for the hierarchical creation and reuse of modules, which we call a generative representation. Not only is the ability to reuse modules necessary for functional scalability, but it is also valuable for improving efficiency in testing and construction. We then describe an evolutionary design system with a generative representation capable of hierarchical modularity and demonstrate it for the design of locomoting robots in simulation. Finally, results from our experiments show that evolution with our generative representation produces better robots than those evolved with a non-generative representation.

Hornby, Gregory S.↗

NASA NTRS2014

Lightning Jump Algorithm Development for the GOES·R Geostationary Lightning Mapper

Current work on the lightning jump algorithm to be used in GOES‐R Geostationary Lightning Mapper (GLM)'s data stream is multifaceted due to the intricate interplay between the storm tracking, GLM proxy data, and the performance of the lightning jump itself. This work outlines the progress of the last year, where analysis and performance of the lightning jump algorithm with automated storm tracking and GLM proxy data were assessed using over 700 storms from North Alabama. The cases analyzed coincide with previous semi‐objective work performed using total lightning mapping array (LMA) measurements in Schultz et al. (2011). Analysis shows that key components of the algorithm (flash rate and sigma thresholds) have the greatest influence on the performance of the algorithm when validating using severe storm reports. Automated objective analysis using the GLM proxy data has shown probability of detection (POD) values around 60% with false alarm rates (FAR) around 73% using similar methodology to Schultz et al. (2011). However, when applying verification methods similar to those employed by the National Weather Service, POD values increase slightly (69%) and FAR values decrease (63%). The relationship between storm tracking and lightning jump has also been tested in a real‐time framework at NSSL. This system includes fully automated tracking by radar alone, real‐time LMA and radar observations and the lightning jump. Results indicate that the POD is strong at 65%. However, the FAR is significantly higher than in Schultz et al. (2011) (50‐80% depending on various tracking/lightning jump parameters) when using storm reports for verification. Given known issues with Storm Data, the performance of the real‐time jump algorithm is also being tested with high density radar and surface observations from the NSSL Severe Hazards Analysis & Verification Experiment (SHAVE).

Schultz. E.↗

NASA NTRS1994

Toward Integrated Operator Interface for Advanced Teleoperation under Time-Delay

This paper briefly describes an Advanced Teleoperator (ATOP) system and its control station where a variety of computer-based operator interface devices and techniques are integrated into a functional setting, accommodating a primary operator and secondary operators. Computer graphics is a key operator interface component in the control station where new types of manual interface devices also are employed. The results of some generic and applications task experiments are summarized, including the performance of a simulated remote satellite servicing task, carried out under four to eight seconds communications time delay, using satellite TV and Internet computer communication links. In conclusion, the paper highlights the lessons learned so far,.

remote control communications delay automation↗

NASA NTRS1991

Decision blocks: A tool for automating decision making in CLIPS

The human capability of making complex decision is one of the most fascinating facets of human intelligence, especially if vague, judgemental, default or uncertain knowledge is involved. Unfortunately, most existing rule based forward chaining languages are not very suitable to simulate this aspect of human intelligence, because of their lack of support for approximate reasoning techniques needed for this task, and due to the lack of specific constructs to facilitate the coding of frequently reoccurring decision block to provide better support for the design and implementation of rule based decision support systems. A language called BIRBAL, which is defined on the top of CLIPS, for the specification of decision blocks, is introduced. Empirical experiments involving the comparison of the length of CLIPS program with the corresponding BIRBAL program for three different applications are surveyed. The results of these experiments suggest that for decision making intensive applications, a CLIPS program tends to be about three times longer than the corresponding BIRBAL program.

Eick, Christoph F.↗

NASA NTRS1980

An integrative approach to space-flight physiology using systems analysis and mathematical simulation

An approach was developed to aid in the integration of many of the biomedical findings of space flight, using systems analysis. The mathematical tools used in accomplishing this task include an automated data base, a biostatistical and data analysis system, and a wide variety of mathematical simulation models of physiological systems. A keystone of this effort was the evaluation of physiological hypotheses using the simulation models and the prediction of the consequences of these hypotheses on many physiological quantities, some of which were not amenable to direct measurement. This approach led to improvements in the model, refinements of the hypotheses, a tentative integrated hypothesis for adaptation to weightlessness, and specific recommendations for new flight experiments.

Leonard, J. I.↗

NASA NTRS1992

The Language Research Center's Computerized Test System for environmental enrichment and psychological assessment

In the spring of 1987, we undertook to provide environmental enrichment to nonhuman primate subjects in ways that would complement and even contribute to the bio-behaviorial science that justified the monkeys' captivity. Of course, the psychological well-being of captive primates--and indeed all research species-- has been an area of intense research activity since the 1985 amendment of the Animal Welfare Act. This mandate for researchers to ensure the psychological, as well as physical, fitness of experimental animals catalyzed the humane and scientific interests of the research community. The contemporary literature is replete with proposed means both of assaying and of providing enrichment and well-being. Notwithstanding, consensus on either assessment or intervention has yet to be reached. The paradigm we employed was modelled after successful efforts with chimpanzees. An automated test system was constructed in which subjects responded to computer tasks by manipulating a joystick. The tasks, interactive game-like versions of many of the classic testing paradigms of cognitive and comparative psychology, permitted the controlled presentation of stimuli and demands without the required presence of a human experimenter. Despite significant barriers to the success, rhesus monkeys (Macaca mulatta) and a variety of other primate species (including, of course, humans) have mastered the skills necessary for testing in this paradigm. Previous experiments have illustrated the utility of the test system for addressing questions of learning, memory, attention, perception, and motivation. Additional data have been reported to support the contention that the Language Research Center's Computerized Test System (LRC-CTS) serves its other raison d'etre--providing environmental enrichment and assessing psychological well-being. This paper is designed to augment previous descriptions of the technology and the paradigm for scientists and caretakers interested in environmental enrichment and performance assessment with primates.

Non-NASA Center↗

NASA NTRS2016

Piloted Well Clear Performance Evaluation of Detect and Avoid Systems with Suggestive Guidance

Regulations to establish operational and performance requirements for unmanned aircraft systems (UAS) are being developed by a consortium of government, industry and academic institutions (RTCA, 2013). Those requirements will apply to the new detect-and-avoid (DAA) systems and other equipment necessary to integrate UAS with the United States (U.S) National Airspace System (NAS) and will be determined according to their contribution to the overall safety case. That safety case requires demonstration that DAA-equipped UAS collectively operating in the NAS meet an airspace safety threshold (AST). Several key gaps must be closed in order to link equipment requirements to an airspace safety case. Foremost among these is calculation of the systems risk ratio, the degree to which a particular system mitigates violation of an aircraft separation standard (FAA, 2013). The risk ratio of a DAA system, in combination with risk ratios of other collision mitigation mechanisms, will determine the overall safety of the airspace measured in terms of the number of collisions per flight hour. It is not known what the effectiveness is of a pilot-in-the-loop DAA system or even what parameters of the DAA system most improve the pilots ability to maintain separation. The relationship between the DAA system design and the overall effectiveness of the DAA system that includes the pilot, expressed as a risk ratio, must be determined before DAA operational and performance requirements can be finalized. Much research has been devoted to integrating UAS into non-segregated airspace (Dalamagkidis, 2009, Ostwald, 2007, Gillian, 2012, Hesselink, 2011, Santiago, 2015, Rorie 2015 and 2016). Several traffic displays intended for use as part of a DAA system have gone through human-in-the-loop simulation and flight-testing. Most of these evaluations were part of development programs to produce a deployable system, so it is unclear how to generalize particular aspects of those designs to general requirements for future traffic displays (Calhoun, 2014). Other displays have undergone testing to collect data that may generalize to new displays, but have not been evaluated in the context of the development of an overall safety case for UAS equipped with DAA systems in the NAS (Bell, 2012). Other research efforts focus on DAA surveillance performance and separation standards. Together with this work, they are expected to facilitate validation of the airspace safety case (Park, 2014 and Johnson, 2015). The contribution of the present work is to quantify the effectiveness of the pilot-automation system to remain well clear as a function of display features and surveillance sensor error. This quantification will help enable selection of a minimum set of DAA design features that meets the AST, a set that may not be unique for all UAS platforms. A second objective is to collect and analyze pilot performance parameters that will improve the modeling of overall DAA system performance in non-human-in-the-loop simulations. Simulating the DAA-equipped UAS in such batch experiments will allow investigation of a much larger number of encounters than is possible in human simulations. This capability is necessary to demonstrate that a particular set of DAA requirements meets the AST under all foreseeable operational conditions.

detect and avoid↗

NASA NTRSDate not supplied

High School Citizen Scientists Use AI/ML to Predict Intra-Ocular Pressure From Gene Expression Data for Spaceflown Mice

Artificial Intelligence (AI) and Machine Learning (ML) have increasingly become pivotal in biological and biomedical research, largely due to the culture of open data sharing and its associated benefits. The methodologies inherent in AI/ML are particularly adept at identifying and forecasting biological phenotypes from the vast amounts of data generated by next-generation sequencing technologies. These techniques offer substantial promise for advancing research in space biosciences and for the development of automated systems for monitoring space health. Nevertheless, there are crucial aspects to consider when training, validating, and testing machine learning models in both biological research and clinical contexts. It is essential that Open Science principles, including data sharing and the availability of open-source code, are complemented by high-quality, publicly accessible training resources. These resources should focus on best practices and include modules based on real-world scientific cases and data to ensure that future AI/ML practitioners gain practical experience with genuine problems. Addressing this knowledge gap, we have designed, developed, and delivered both interactive and self-paced training programs for citizen scientists worldwide, enabling them to utilize AI/ML for space biology research. This initiative was made possible through generous funding from a Transformation to Open Science Training grant. The interactive training sessions, conducted this summer, utilized AI/ML techniques to analyze data from the Open Science Data Repository, specifically targeting the effects of spaceflight on ocular structure and function. The dataset OSD-583, from the Rodent Research 9 mission, provides experimental data detailing the ocular responses of mice subjected to a 35-day spaceflight, compared with ground control counterparts. Using OSD-583 as observational data, our summer training participants applied AI/ML methods to predict intraocular pressure from RNA-seq data and identify the genes most predictive of the observed responses. Further analysis through pathway enrichment and gene set enrichment revealed that these genes are involved in molecular and cellular processes contributing to retinal degeneration.

James Casaletto↗