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NSDS is the adept coordination of Los Alamos National Laboratory's nuclear science data, including the collection, integration, storage and access. The poster highlights historical milestones.
The typical patterns of spectral development (profiles) for corn and soybeans are presented, based on field-collected reflectance data transformed to correspond to LANDSAT-MSS Tasseled Cap coordinates. Reasonable variations in field conditions and cultural practices are shown to significantly influence profile features. The separability of the two crops is determined to be primarily related to the maximum value of the reflectance equivalent of Greenness, and to the plateau effect seen in corn Greenness profiles. The impact of changes in conditions on separability is described. In addition, association is made between profile features and stages of development for corn and soybeans. Corn is shown to peak at a stage well before tasseling or maximum LAI, while the characteristics of the soybean profile are shown to be unrelated to any particular stage of development.
The typical patterns of spectral development (profiles) for corn and soybeans are presented, based on field-collected reflectance data transformed to correspond to Landsat-MSS Tasseled Cap coordinates. Reasonable variations in field conditions and cultural practices are shown to significantly influence profile features. The separability of the two crops is determined to be primarily related to the maximum value of the reflectance equivalent of Greenness, and to the plateau effect seen in corn Greenness profiles. The impact of changes in conditions on separability is described. In addition, association is made between profile features and stages of development for corn and soybeans. Corn is shown to peak at a stage well before tasseling or maximum LAI, while the characteristics of the soybean profile are shown to be unrelated to any particular stage of development.
Spectroscopic observations of Comets P/Crommelin, P/Giacobini-Zinner and P/Halley are coordinated, preliminary results are delivered to the astronomical community and the data collected from observers throughout the world are archived. The ASU IHW Center has the additional responsibility of maintaining the IHW Electronic Bulletin Board which reports real-time information on the status of Comet P/Halley. Access to this electronic bulletin board via telephone modem connection is available to any astronomer upon request.
Nickel in the extraterrestrial world is commonly found in both Fe-Ni sulfide and Fe-Ni met-al forms [1] and in the pure metal state in the interior of iron meteorites where it is not easily oxidized. Ni is also found in olivine, pyroxene and glasses and in some melts the partitioning of Ni between the olivines and glass is controlled by the amount of S in the melt [2]. Its most common valence state is Ni(2+) but Ni also occurs as Ni(0), Ni(+), and Ni(3+) and rarely as Ni(2-), Ni(1-) and Ni(4+) [3]. It's valence state in olivines is Ni(2+) in octa-hedral coordination on the M1 site and rarely on the M2 site.[4]. The chemical sensitivity of X-ray absorp-tion near-edge structure (XANES) spectroscopy is well established and can be used to determine not only va-lence states but also coordination sites [5]. We report here Ni XANES spectroscopy and elemental maps collected from 2 carbonaceous chondrites, 2 large clus-ter IDPs, 1 ureilite and 1 LL3 orginary chondrite.Using XANES it may be possible to find a common trait in the large cluster IDPs that will also be found in mete-orite samples.
United States forestland is an important ecosystem type, land cover, land use, and economic resource that is facing several drivers of change including climatic. Because of its significance, forestland was identified through the National Climate Assessment(NCA) as a key sector and system of concern to be included in a system of climate indicators as part of a sustained assessment effort. Here, we describe 11 informative core indicators of forests and climate change impacts with metrics available or nearly available for use in the NCA efforts. The recommended indicators are based on a comprehensive conceptual model which recognizes forests as a land use, an ecosystem, and an economic sector. The indicators cover major forest attributes such as extent, structural components such as biomass, functions such as growth and productivity, and ecosystem services such as biodiversity and outdoor recreation. Interactions between humans and forests are represented through indicators focused on the wildland-urban interface, cost to mitigate wildfire risk, and energy produced from forest-based biomass. Selected indicators also include drought and disturbance from both wildfires and biotic agents. The forest indicators presented are an initial set that will need further refinement in coordination with other NCA indicator teams. Our effort ideally will initiate the collection of critical measurements and observations and lead to additional research on forest-climate indicators.
Suborbital (e.g., airborne) campaigns that carry advanced remote sensing and in situ payloads provide detailed observations of atmospheric processes, but can be challenging to use when it is necessary to geographically collocate data from multiple platforms that make repeated observations of a given geographic location at different altitudes. This study reports on a data collocation algorithm that maximizes the volume of collocated data from two coordinated suborbital platforms and demonstrates its value using data from the NASA Aerosol Cloud Meteorology Interactions Over the western Atlantic Experiment (ACTIVATE) suborbital mission. A robust data collocation algorithm is critical for the success of the ACTIVATE mission goal to develop new and improved remote sensing algorithms, and quantify their performance. We demonstrate the value of these collocated data to quantify the performance of a recently developed vertically resolved lidar + polarimeter–derived aerosol particle number concentration (Na ) product, resulting in a range-normalized mean absolute deviation (NMAD) of 9% compared to in situ measurements. We also show that this collocation algorithm increases the volume of collocated ACTIVATE data by 21% compared to using only nearest-neighbor finding algorithms alone. Additional to the benefits demonstrated within this study, the data files and routines produced by this algorithm have solved both the critical collocation and the collocation application steps for researchers who require collocated data for their own studies. This freely available and open-source collocation algorithm can be applied to future suborbital campaigns that, like ACTIVATE, use multiple platforms to conduct coordinated observations, e.g., a remote sensing aircraft together with in situ data collected from suborbital platforms.
NASA’s Small Spacecraft & Distributed Systems (SSDS) within the Research and Technology Mission Directorate (RTMD) expands U.S. capability to execute unique missions through targeted investment, rapid development, and flight demonstration of small spacecraft technologies applicable to exploration, science and the commercial space sector. SSDS strategically invests in technology development and on-orbit demonstrations executed across NASA, other government agencies, industry, and academia. The program’s University SmallSat Technology Partnerships initiative awards academic researchers with the opportunity to collaborate with NASA to mature innovative technology. Capabilities aligned with RTMD’s technology shortfalls and interests - power, processing, propulsion, sensors, communications, autonomous navigation, architectures, and advanced applications like artificial intelligence (AI), machine learning, and edge computing - are prioritized in SSDS investments. These investments enable distributed, autonomous, and cooperative small spacecraft systems that support swarm missions extending beyond low Earth orbit into cislunar and deep space. This paper highlights representative SSDS flight demonstrations that mature these capabilities to enable a future operational infrastructure needed to support sustained exploration of the Moon and beyond. SSDS’s investment strategy emphasizes rapid development and on-orbit demonstration to validate spacecraft technologies required for swarms and distributed mission architectures. The Starling swarm technology demonstration mission exemplifies this approach by advancing distributed spacecraft autonomy, cooperative operations, and space situational awareness. Extended flight testing and ongoing studies of next generation swarm configurations and on-orbit space traffic monitoring and management continue to inform future swarm designs. DiskSat’s four-spacecraft demonstration mission represents SSDS’s strategic vision to expand the design space for future small spacecraft through its commitment to advance novel platform concepts that can impact how science is performed on orbit. Continuing to invest in future platforms, the notional PY12 concept is a 12-spacecraft swarm hosting neuromorphic processors and is envisioned as an on-orbit testbed for AI, edge computing, and positioning, navigation and timing technologies. SSDS also invests in single-spacecraft technology demonstrations that underpin the success of future swarm missions and accelerate the availability of validated technologies across the small spacecraft ecosystem. Examples of such demonstrations include Pathfinder Technology Demonstrator-3 (PTD-3), which performed high-rate optical communications; PTD-R, which demonstrated a camera capable of simultaneous ultraviolet and short-wave infrared optical sensing; and CAPSTONE, the Cislunar Autonomous Positioning System Technology and Operations Navigation Experiment, which validated autonomous navigation in cislunar space. Collectively, SSDS-funded demonstrations advance capabilities across swarms and illustrate a coordinated investment strategy to mature high-impact technologies required for autonomous, distributed, and cooperative small spacecraft systems for low Earth orbit, cislunar, and deep space applications. Technology demonstrations strengthen SSDS partnerships with industry, academia, and other government agencies, and promote small spacecraft community adoption of capabilities required to close technical gaps for swarm missions.
NASA’s Small Spacecraft & Distributed Systems (SSDS) within the Research and Technology Mission Directorate (RTMD) expands U.S. capability to execute unique missions through targeted investment, rapid development, and flight demonstration of small spacecraft technologies applicable to exploration, science and the commercial space sector. SSDS strategically invests in technology development and on-orbit demonstrations executed across NASA, other government agencies, industry, and academia. The program’s University SmallSat Technology Partnerships initiative awards academic researchers with the opportunity to collaborate with NASA to mature innovative technology. Capabilities aligned with RTMD’s technology shortfalls and interests - power, processing, propulsion, sensors, communications, autonomous navigation, architectures, and advanced applications like artificial intelligence (AI), machine learning, and edge computing - are prioritized in SSDS investments. These investments enable distributed, autonomous, and cooperative small spacecraft systems that support swarm missions extending beyond low Earth orbit into cislunar and deep space. This paper highlights representative SSDS flight demonstrations that mature these capabilities to enable a future operational infrastructure needed to support sustained exploration of the Moon and beyond. SSDS’s investment strategy emphasizes rapid development and on-orbit demonstration to validate spacecraft technologies required for swarms and distributed mission architectures. The Starling swarm technology demonstration mission exemplifies this approach by advancing distributed spacecraft autonomy, cooperative operations, and space situational awareness. Extended flight testing and ongoing studies of next generation swarm configurations and on-orbit space traffic monitoring and management continue to inform future swarm designs. DiskSat’s four-spacecraft demonstration mission represents SSDS’s strategic vision to expand the design space for future small spacecraft through its commitment to advance novel platform concepts that can impact how science is performed on orbit. Continuing to invest in future platforms, the notional PY12 concept is a 12-spacecraft swarm hosting neuromorphic processors and is envisioned as an on-orbit testbed for AI, edge computing, and positioning, navigation and timing technologies. SSDS also invests in single-spacecraft technology demonstrations that underpin the success of future swarm missions and accelerate the availability of validated technologies across the small spacecraft ecosystem. Examples of such demonstrations include Pathfinder Technology Demonstrator-3 (PTD-3), which performed high-rate optical communications; PTD-R, which demonstrated a camera capable of simultaneous ultraviolet and short-wave infrared optical sensing; and CAPSTONE, the Cislunar Autonomous Positioning System Technology and Operations Navigation Experiment, which validated autonomous navigation in cislunar space. Collectively, SSDS-funded demonstrations advance capabilities across swarms and illustrate a coordinated investment strategy to mature high-impact technologies required for autonomous, distributed, and cooperative small spacecraft systems for low Earth orbit, cislunar, and deep space applications. Technology demonstrations strengthen SSDS partnerships with industry, academia, and other government agencies, and promote small spacecraft community adoption of capabilities required to close technical gaps for swarm missions.
Stardust, a NASA Discovery-class mission, was the first sample-return mission to return solid samples from beyond the Moon. Stardust was effectively two missions in one spacecraft: it returned the first materials from a known primitive solar system body, the Jupiter-family comet Wild 2; Stardust also returned a collector that was exposed to the contemporary interstellar dust stream for 200 days during the interplanetary cruise. Both collections present severe technical challenges in sample preparation and in analysis. By far the largest collection is the cometary one: approximately 300 micro g of material was returned from Wild 2, mostly consisting of approx. 1 ng particles embedded in aerogel or captured as residues in craters on aluminum foils. Because of their relatively large size, identification of the impacts of cometary particles in the collection media is straightforward. Reliable techniques have been developed for the extraction of these particles from aerogel. Coordinated analyses are also relatively straightforward, often beginning with synchrotron-based x-ray fluorescence (S-XRF), X-ray Absorption Near-Edge Spectoscopy (XANES) and x-ray diffraction (S-XRD) analyses of particles while still embedded in small extracted wedges of aerogel called ``keystones'', followed by ultramicrotomy and TEM, Scanning Transmission X-ray Microscopy (STXM) and ion microprobe analyses (e.g., Ogliore et al., 2010). Impacts in foils can be readily analyzed by SEM-EDX, and TEM analysis after FIB liftout sample preparation. In contrast, the interstellar dust collection is vastly more challenging. The sample size is approximately six orders of magnitude smaller in total mass. The largest particles are only a few pg in mass, of which there may be only approx.10 in the entire collection. The technical challenges, however, are matched by the scientific importance of the collection. We formed a consortium carry out the Stardust Interstellar Preliminary Examination (ISPE) to carry out an assessment of this collection, partly in order to characterize the collection in sufficient detail so that future investigators could make well-informed sample requests. The ISPE is the sixth PE on extraterrestrial collections carried out with NASA support. Some of the basic questions that we asked were: how many impacts are there in the collector, and what fraction of them have characteristics consistent with extraterrestrial materials? What is the elemental composition of the rock-forming elements? Is there crystalline material? Are there organics? Here we present coordinated microanalyses of particles captured in aerogel, using S-FTIR, S-XRF, STXM, S-XRD; and coordinated microanalyses of residues in aluminum foil, using SEMEDX, Auger spectroscopy, STEM, and ion microprobe. We discuss a novel approach that we employed for identification of tracks in aerogel, and new sample preparation techniques developed during the ISPE. We have identified seven particles - three in aerogel and four in foils - that are most consistent with an interstellar origin. The seven particles exhibit a large diversity in elemental composition. Dynamical evidence, supported supported by laboratory simulations of interstellar dust impacts in aerogel and foils, and numerical modeling of interstellar dust propagation in the heliosphere, suggests that at least some of the particles have high optical cross-section, perhaps due to an aggregate structure. However, the observations are most consistent with a variety of morphologies
Working with Hamiltonians from chiral effective field theory, we develop a novel framework for describing arbitrary deformed medium-mass nuclei by combining the in-medium similarity renormalization group with the generator coordinate method. The approach leverages the ability of the first method to capture dynamic correlations and the second to include collective correlations without violating symmetries. In this work, we use our scheme to compute the matrix element that governs the neutrinoless double beta decay of 48 Ca to 48 Ti, and find it to have the value 0.61, near or below the predictions of most phenomenological methods. The result opens the door to ab initio calculations of the matrix elements for the decay of heavier nuclei such as 76 Ge, 130 Te, and 136 Xe.
Background Individuals with respiratory conditions, such as asthma, are particularly susceptible to adverse health effects associated with higher levels of ambient air pollution and temperature. This study evaluates whether hourly levels of fine particulate matter (PM 2.5 ) and dry bulb globe temperature (DBGT) are associated with the lung function of adult participants with asthma. Methods and findings Global positioning system (GPS) location, respiratory function (measured as forced expiratory volume at 1 second (FEV 1 )), and self-reports of asthma medication usage and symptoms were collected as part of the Exposure, Location, and Lung Function (ELF) study. Hourly ambient PM 2.5 and DBGT exposures were estimated by integrating air quality and temperature public records with time-activity patterns using GPS coordinates for each participant (n = 35). The relationships between acute PM 2.5 , DBGT, rescue bronchodilator use, and lung function collected in one week periods and over two seasons (summer/winter) were analyzed by multivariate regression, using different exposure time frames. In separate models, increasing levels in PM 2.5 , but not DBGT, were associated with rescue bronchodilator use. Conversely DBGT, but not PM 2.5 , had a significant association with FEV 1 . When DBGT and PM 2.5 exposures were placed in the same model, the strongest association between cumulative PM 2.5 exposures and the use of rescue bronchodilator was identified at the 0–24 hours (OR = 1.030; 95% CI = 1.012–1.049; p-value = 0.001) and 0–48 hours (OR = 1.030; 95% CI = 1.013–1.057; p-value = 0.001) prior to lung function measure. Conversely, DBGT exposure at 0 hours (β = 3.257; SE = 0.879; p-value>0.001) and 0–6 hours (β = 2.885; SE = 0.903; p-value = 0.001) hours before a reading were associated with FEV 1 . No significant interactions between DBGT and PM 2.5 were observed for rescue bronchodilator use or FEV 1 . Conclusions Short-term increases in PM 2.5 were associated with increased rescue bronchodilator use, while DBGT was associated with higher lung function (i.e. FEV 1 ). Further studies are needed to continue to elucidate the mechanisms of acute exposure to PM 2.5 and DBGT on lung function in asthmatics.
This dataset contains uncorrected sap velocity measurements using the heat ratio method (HRM) collected using ICT International SFM1x sensors at five urban sites in Chicago, Illinois, as part of the DOE CROCUS project. The data includes continuous monitoring of sap velocity from various tree species, including Maples (Acer spp.): Sugar Maple (Acer saccharum), Silver Maple (Acer saccharinum), and Red Maple (Acer rubrum); Oaks (Quercus spp.): Swamp White Oak (Quercus bicolor); American Elm (Ulmus americana); Honey Locust (Gleditsia triacanthos); Cottonwood (Populus deltoides); and Tree of Heaven (Ailanthus altissima) across Chicago State University (CSU), Northeastern Illinois University (NEIU), Northwestern University (NU), University of Illinois Chicago (UIC), and West Woodlawn "Blacks in Green" (BIG). These include both street trees and those in urban park locations. Measurements were collected at 15-20 minute intervals, depending on the sensor, and transmitted via Long Range Wide Area Network (LoRaWAN) protocols. The wireless data was collected by Sage Network (https://sagecontinuum.org/) nodes. The dataset includes sensor ID, Global Positioning System (GPS) coordinates, tree species (common and scientific names), tree identification number, diameter at breast height (DBH in cm), uncorrected sap velocity measurements (cm/hr) from both inner and outer probes, and Sage Node identifiers so the data can be mapped to related variables such as air quality and wind speed that were collected on the Sage nodes. All timestamps are in local Chicago time (CDT/CST). Quality control flags are provided using a 3-bit binary system indicating physical range violations (< -10 or > 60 cm/hr), step spikes (absolute difference > 36 cm/hr), and stuck sensor conditions (> 10 consecutive identical values). These are raw data, not corrected for wood anatomy or species-specific characteristics. Data is provided in comma separated (CSV) format. This dataset is part of a larger collection of CROCUS environmental monitoring data, including linked datasets from Air Quality Transmitter (AQT) sensors, Weather Transmitter (WXT) sensors, and Multi-Function Research LoRaWAN (MFR) Nodes. DOIs for the supporting data are provided as part of this data package.
Non-destructive measurements of longitudinal beam profile in non-relativistic hadron accelerators are usually performed with Bunch Shape Monitors that utilize secondary electron emission to reproduce the shape of a primary ion beam. The existing devices, however, have poor electron collection efficiency from the wire and are limited to one dimensional measurements of the phase coordinate. Here, we present the development of a bunch shape monitor with improved performance for proton beams to be used in the Spallation Neutron Source accelerator. This improvement was achieved by adding focusing optics between the wire and the entrance slit, which will also allow measurements over a much higher dynamic range. Here we present the design, simulation and experimental test results of the developed new electron beam guidance system for the existing SNS bunch shape monitor that allowed significant improvement in the collection efficiency.
The rapid expansion of large electric loads is reshaping the operational and regulatory landscape of the U.S. electric grid. These facilities are reaching new scales of expansion, now exceeding a gigawatt per site, and their highly sensitive, digitally driven behaviors introduce new reliability risks. Recent grid events, including large load losses following routine transmission disturbances, highlight the consequences of limited ride-through capability, inconsistent protection settings, inadequate modeling, and lack of behind-the-meter visibility. Parallels to earlier integration challenges of new grid technologies suggest that the grid’s existing processes, standards, and interconnection frameworks are no longer adequate for emerging large loads. This brief synthesizes lessons from the evolution of inverter-based resource regulation and applies them to large-load integration. It identifies critical gaps in modeling accuracy, interconnection processes, performance standards, and compliance mechanisms. Technical recommendations emphasize advanced monitoring, improved modeling, coordinated communication protocols, modernized substations, and structured behind-the-meter control schemes. Collectively, these measures provide a roadmap to maintain bulk power system reliability while enabling the continued growth of large, electrified digital infrastructure.
We survey how AI/ML is being deployed across Jefferson Lab's experimental and accelerator programs. In EPSCI, Hydra applies computer vision to automate real-time data-quality monitoring across all four experimental halls, replacing manual inspection of hundreds to thousands of histograms per shift. AIEC (AI Experiment Controls) uses ML to stabilize drift chamber gains and is now part of standard CEBAF production running, while AI Optimized Polarization (AIOP) targets autonomous control of polarized targets and photon beam angular alignment. In CASA, cavity fault classification models identify faulted cavities and trip types from waveform data with ~85% and ~78% agreement to labeled data, respectively, and are deployed in production; a separate effort applies LLMs and hybrid search to make the CEBAF operations logbook AI-ready. QCD-focused work includes transformer- and GAN-based generative models for particle-level event simulation, with distributed GAN training scaling studies on Polaris. Additional efforts span ML-on-FPGA for the EIC and a new Data Science Department coordinating anomaly detection, uncertainty quantification, and HPC-scalable ML lab-wide. Collectively, these projects illustrate AI's growing role in improving efficiency across JLab's nuclear physics mission.
An extensive analytical and experimental study SEU in an advanced silicon bipolar process was made. The modeling used process and device parameters to model the SEU charge, collection, and circuit response derived from a special version of PISCES in cylindrical coordinates and SPICE, respectively. Data are reported for test cells of various sizes.
The C130 Earth Resources Aircraft provides a platform for a variety of sensors that collect data in support of terrestrial and atmospheric projects sponsored by NASA in coordination with Federal, state, university, and industry investigators. This data is applied to research in the areas of forestry, agriculture, land use and land cover analysis, hydrology, geology, photogrammetry, oceanography, meteorology, and other earth science disciplines. The C130 is a platform aircraft flying up to 25,000 feet above sea level at speeds between 150 and 330 knots True Air Speed. The aircraft is capable of precise flight line navigation by means of an optical borescope from which line guidance is provided to the pilots.