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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
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NASA NTRS2020

WISE 2150-7520AB: A Very Low-mass, Wide Comoving Brown Dwarf System Discovered through the Citizen Science Project Backyard Worlds: Planet 9

We report the discovery of WISE 2150-7520AB (W2150AB): a widely separated (∼341 au) very low-mass L1 + T8 co-moving system. The system consists of the previously known L1 primary 2MASS J21501592-7520367 and a newly discovered T8 secondary found at position 21:50:18.99–75:20:54.6 (MJD = 57947) using Wide-field Infrared Survey Explorer data via the Backyard Worlds: Planet 9 citizen science project. We present Spitzer ch1 and ch2 photometry (ch1–ch2 = 1.41 ± 0.04 mag) of the secondary and Folded-port InfraRed Echellette prism spectra of both components. The sources show no peculiar spectral or photometric signatures, indicating that each component is likely field age. Using all observed data and the Gaia DR2 parallax of 41.3593 ± 0.2799 mas for W2150A we deduce fundamental parameters of log(L(bol)/L(☉)) = −3.69 ± 0.01, T(eff) = 2118 ± 62 K, and an estimated mass = 72 ± 12 M(Jup) for the L1 and log(L(bol)/L(☉)) = −5.64 ± 0.02, T(eff) = 719 ± 61 K, and an estimated mass = 34 ± 22 M(Jup) for the T8. At a physical separation of ∼341 au this system has E(bin) = 1041 erg, making it the lowest binding energy system of any pair with M(tot) < 0.1 M(Sun) not associated with a young cluster. It is equivalent in estimated mass ratio, E(bin), and physical separation to the ∼2 Myr M7.25 + M8.25 binary brown dwarf 2MASS J11011926-7732383AB (2M1101AB) found in the Chameleon star-forming region. W2150AB is the widest companion system yet observed in the field where the primary is an L dwarf or later.

Jacqueline Faherty↗
NASA NTRS2021

K2-138 g: Spitzer Spots a Sixth Planet for the Citizen Science System

K2 greatly extended Kepler's ability to find new planets, but it was typically limited to identifying transiting planets with orbital periods below 40 days. While analyzing K2 data through the Exoplanet Explorers project, citizen scientists helped discover one super-Earth and four sub-Neptune sized planets in the relatively bright (V = 12.21, K = 10.3) K2-138 system, all which orbit near 3:2 mean-motion resonances. The K2 light curve showed two additional transit events consistent with a sixth planet. Using Spitzer photometry, we validate the sixth planet's orbital period of 41.966 ± 0.006 days and measure a radius of 3.44 (+0.32,-.031)Rꚛ, solidifying K2-138 as the K2 system with the most currently known planets. There is a sizeable gap between the outer two planets, since the fifth planet in the system, K2-138 f, orbits at 12.76 days. We explore the possibility of additional nontransiting planets in the gap between f and g. Due to the relative brightness of the K2-138 host star, and the near resonance of the inner planets, K2-138 could be a key benchmark system for both radial velocity and transit-timing variation mass measurements, and indeed radial velocity masses for the inner four planets have already been obtained. With its five sub-Neptunes and one super-Earth, the K2-138 system provides a unique test bed for comparative atmospheric studies of warm to temperate planets of similar size, dynamical studies of near-resonant planets, and models of planet formation and migration.

Kevin K. Hardegree-Ullman↗
NASA NTRS2021

New Candidate Extreme T Subdwarfs from the Backyard Worlds: Planet 9 Citizen Science Project

Schneider et al. presented the discovery of WISEA J041451.67−585456.7 and WISEA J181006.18−101000.5, which appear to be the first examples of extreme T-type subdwarfs (esdTs; metallicity ≤−1 dex, T(eff) ≲ 1400 K). Here, we present new discoveries and follow-up of three T-type subdwarf candidates, with an eye toward expanding the sample of such objects with very low metallicity and extraordinarily high kinematics, properties that suggest membership in the Galactic halo. Keck/NIRES near-infrared spectroscopy of WISEA J155349.96+693355.2, a fast-moving object discovered by the Backyard Worlds: Planet 9 citizen science project, confirms that it is a mid-T subdwarf. With H(W2) = 22.3 mag, WISEA J155349.96+693355.2 has the largest W2 reduced proper motion among all spectroscopically confirmed L and T subdwarfs, suggesting that it may be kinematically extreme. Nevertheless, our modeling of the WISEA J155349.96+693355.2 near-infrared spectrum indicates that its metallicity is only mildly subsolar. In analyzing the J155349.96+693355.2 spectrum, we present a new grid of low-temperature, low-metallicity model atmosphere spectra. We also present the discoveries of two new esdT candidates, CWISE J073844.52−664334.6 and CWISE J221706.28−145437.6, based on their large motions and colors similar to those of the two known esdT objects. Finding more esdT examples is a critical step toward mapping out the spectral sequence and observational properties of this newly identified population.

Aaron M. Meisner↗
NASA NTRS2021

Ross 19B: An Extremely Cold Companion Discovered via the Backyard Worlds: Planet 9 Citizen Science Project

Through the Backyard Worlds: Planet 9 citizen science project, we have identified a wide-separation (∼10', ∼9900 au projected) substellar companion to the nearby (∼17.5 pc), mid-M dwarf Ross 19. We have developed a new formalism for determining chance alignment probabilities based on the BANYAN Σ tool, and find a 100% probability that this is a physically associated pair. Through a detailed examination of Ross 19A, we find that the system is metal-poor ([Fe/H] = −0.40 ± 0.12) with an age of 7.2 (+3.8, -3.6) Gyr. Combining new and existing photometry and astrometry, we find that Ross 19B is one of the coldest known wide-separation companions, with a spectral type on the T/Y boundary, an effective temperature of 500 (+115, -100) K, and a mass in the range 15–40 M(Jup). This new, extremely cold benchmark companion is a compelling target for detailed characterization with future spectroscopic observations using facilities such as the Hubble Space Telescope or James Webb Space Telescope.

Adam C. Schneider↗
NASA NTRSDate not supplied

Hot on the Trail: Mapping Wildland Fires With Citizen Science and Live Image Processing

Heightened fire activity is straining existing firefighting resources and budgets across the nation and worldwide. For this reason, the 2021 NASA Academy at Langley Research Center has the challenge of applying NASA technology to the challenges faced by wild-land firefighting professionals. The approach is three-fold: Data Acquisition, Communications, and Equipment Development. The Communications Team focused on improving data latency for fire mapping and advancing communications between civilians and incident dispatch. The team developed two main concepts to address these areas: First, they tried to identify, map, and transmit fire perimeter data via an Uncrewed Aerial System (UAS), and second, they suggest a fully functioning web-app for early fire detection and fire monitoring using citizen science. This report outlines the materials and methods of these concepts, as well as future work necessary to bring the proposed technology into the field.

UAS data transfer ground stations↗
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↗
NASA NTRS2018

A 3D Citizen Science Video Game for NeMO-Net, the NASA Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

NeMO-Net, the NASA neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network aimed at accurately assessing the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. We present here the active learning component of the project, which consists of an interactive video game prototype for tablet and mobile devices where players are able to intuitively label morphology classifications over mm-scale 3D coral reef imagery. Active learning applications present a novel methodology for engaging the public while efficiently providing large-scale training and test data for increasingly complex and data-intensive machine learning algorithms. NeMO-Net trains players on domain-specific knowledge through interactive tutorials and periodically checks players' input against pre-classified coral imagery to gauge their accuracy and utilize in-game mechanics to provide personalized classification training. Players can rate the classifications of other players, unlock rewards and join a global community as they explore and classify coral reefs and other shallow marine environments.

Citizen Science↗
NASA NTRS2021

GLOBE Observer and the GO on a Trail Data Challenge: A Citizen Science Approach to Generating a Global Land Cover Land Use Reference Dataset

Land cover and land use are highly visible indicators of climate change and human disruption to natural processes. While land cover is frequently monitored over a large area using satellite data, ground-based reference data is valuable as a comparison point. The NASA-funded GLOBE Observer (GO) program provides volunteer-collected land cover photos tagged with location, date and time, and, in some cases, land cover type. When making a full land cover observation, volunteers take six photos of the site, one facing north, south, east, and west (N-S-E-W) respectively, one pointing straight up to capture canopy and sky, and one pointing down to document ground cover. Together, the photos document a 100 meter square of land. Volunteers may then optionally tag each N-S-E-W photo with the land cover types present. Volunteers collect the data through a smartphone app, also called GLOBE Observer, resulting in consistent data. While land cover data collected through GLOBE Observer is ongoing, this paper presents the results of a data challenge held between June 1 and October 15, 2019. Called “GO on a Trail,” the challenge focused on collecting land cover observations at designated points along the Lewis and Clark National Historic Trail (LCNHT), which transects approximately 7,900 kilometers of the United States from east to west. The challenge also included an international component in which participants were recognized for the most data collected during the period. The challenge resulted in more than 2800 land cover data points from around the world with just over 900 land cover data points along the LCNHT. The data collected along the LCNHT is largely within a 1,000 meter corridor along the historic route. Internationally, the challenge had strong participation in Australia, where a Scouts Australia team-based competition was conducted in conjunction with GO on a Trail. GLOBE Observer collections can serve as reference data, ground truthing satellite imagery for the improvement and verification of broad land cover maps. Continued collection using this protocol will build a database documenting climate-related land cover and land use change into the future.

land cover↗
NASA NTRSDate not supplied

Citizen Science Approach for Searching and Curating Literature of the Effects of Spaceflight on Cardiovascular Outcomes in Rodents and Humans

The spaceflight environment causes significant changes to the structure and function of the cardiovascular system, including fluid redistribution, alterations in blood pressure, and changes in cardiac output. The goal of this project is to quantitatively summarize the data on the effects of actual or simulated microgravity and radiation exposure resulting from spaceflight on the cardiovascular system. As the first step, a group of investigators approached through a collaboration of the Ames Life Science Data Archive (ALSDA) Analysis Working Group developed a list of relevant cardiovascular search terms. Based on these, medical librarians generated and executed the search strategy in Medline, CINAHL, Embase and NASA repositories. In parallel, we recruited students and young professionals from various space industry-affiliated organizations, resulting in ~100 individuals joining. With this program we aimed to reach students and young people underrepresented in STEM, including first-generation, female, minorities, disadvantaged backgrounds, fostered individuals, etc. These individuals completed a virtual training course on the nature and methodologies of the project. Following this, the participants were structured into teams with more senior/experienced individuals designated as team leaders. Currently, the teams are screening approximately 15,000 studies using the systematic review tool, Covidence. Teams will be extracting and curating data for meta-analysis of the cardiovascular spaceflight literature, but also extracting, submitting, and curating appropriate datasets into the new ALSDA submission portal and repository. This effort will result in collaborative publications based upon the literature meta-analyses, and a number of publicly accessible datasets for reuse, modeling, machine learning, and knowledge graph-type approaches. This approach reduces the length of time to complete title/abstract screening time from 1-2 years needed for this volume of studies, to 3-4 months, while also providing a unique, open-access educational experience to space research and training in knowledge synthesis tools to interested individuals.

space biology↗
NASA NTRS1973

Satellites for the citizen

Applications Technology Satellite ATS-F scheduled for launch in 1974 will be the last of its type sponsored by NASA. In the years that these satellites have served the practical needs of prototype development programs for space technology, immense benefits have accrued to the general public in the fields of communications, navigation, meteorology, and a host of related areas. If the public is to continue to benefit from this extremely successful series of launchings, private enterprise will have to assume the cost of future ATS experiments when NASA withdraws from the field.

Metzger, E.↗
NASA NTRS2004

Making NASA Earth Observing System Satellite Data Accessible to the K-12 and Citizen Scientist Communities

The Atmospheric Sciences Data Center (ASDC) at NASA s Langley Research Center houses over 700 data sets related to Earth s radiation budget, clouds, aerosols and tropospheric chemistry. These data sets are produced to increase academic understanding of the natural and anthropogenic perturbations that influence global climate change. The Mentoring and inquirY using NASA Data on Atmospheric and earth science for Teachers and Amateurs (MY NASA DATA) project has been established to systematically support educational activities at all levels of formal and informal education by reducing these large data holdings to microsets that will be easily explored and understood by the K-12 and the amateur scientist communities

Moore, Susan W.↗