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At least 397 records · Page 22

2018 Industrial Energy Data Book

The Industrial Energy Data Book (IEDB) aggregates and synthesizes information on the trends in industrial energy use, energy prices, economic activity, and water use. The IEDB also estimates county-level industrial energy use and combustion energy use of large energy-using facilities (i.e., facilities required to report greenhouse gas emissions under the EPA's Greenhouse Gas Reporting Program). These estimates are derived from publicly available sources from EPA, Energy Information Administration, Census Bureau, USDA, and USGS. The estimation methodology is meant to be improved over time with input from the energy analysis and developer communities. Please refer to https://github.com/NREL/Industry-energy-data-book.

agriculture↗

An adaptive adversarial domain adaptation approach for corn yield prediction

Recently, statistical machine learning and deep learning methods have been widely explored for corn yield prediction. Though successful, machine learning models generated within a specific spatial domain often lose their validity when directly applied to new regions. To address this issue, we designed an unsupervised adaptive domain adversarial neural network (ADANN). Specifically, through domain adversarial training, the ADANN model reduced the impact of domain shift by projecting data from different domains into the same subspace. Also, the ADANN model was designed to be trained in an adaptive way, which guaranteed the model can learn the domain-invariant features and perform accurate yield prediction simultaneously. Informative variables including time-series vegetation indices and sequential weather observations were first collected from multiple data sources and aggregated to the county level. Then, we trained the ADANN model with the extracted features and corresponding reported county-level corn yield from the U.S. Department of Agriculture (USDA). Finally, the trained model was evaluated in four testing years 2016–2019. The U.S. corn belt was used as the study area and counties under study were grouped into two diverse ecological regions. Overall, the experimental results showed that the developed ADANN model had better performance than three other state-of-the-art machine learning models in both local experiments (train and test in the same region) and transfer experiments (train and test in different regions). As the first study using adversarial learning for crop yield prediction, this research demonstrates a novel solution for improving model transferability on crop yield prediction.

59 BASIC BIOLOGICAL SCIENCES↗

Hybrid phosphazene anodes for energy storage applications

The use of hybrid cyclic phosphazene polymer/graphite anodes, where the phosphazene serves as distributed loci for Li deposition, has been investigated. Capacity within the hybrid system was found to occur reversibly in distinct regions. At the most positive voltages, above 0.06 V vs Li/Li+, the capacity was associated mostly with Li+ intercalation into graphite. In the most negative region, deposition of Li within the polymer was the predominate mechanism. A transitional region is inferred by the data whereby bulk aggregation or clustering of Li atoms occurs in proximity to the phosphazene sites that then serve as a template for more widespread population of Li within the anode at higher voltages, akin to a nucleation process. In full cells with a mixed oxide cathode, controlling the extent of Li deposition by limiting the charging voltage to 4.45 V enabled repeated cycling with no loss in capacity. Capacities as high as 183 mAh g-1 have been achieved for systems containing as little as 10% graphite while retaining coulombic efficiencies of 98% over 50 cycles. This level of cycling equates to the deposition of 7.4 Li per cyclic phosphazene.

25 ENERGY STORAGE↗

Confronting the water potential information gap

Water potential directly controls the function of leaves, roots and microbes, and gradients in water potential drive water flows throughout the soil–plant–atmosphere continuum. Notwithstanding its clear relevance for many ecosystem processes, soil water potential is rarely measured in situ, and plant water potential observations are generally discrete, sparse, and not yet aggregated into accessible databases. These gaps limit our conceptual understanding of biophysical responses to moisture stress and inject large uncertainty into hydrologic and land-surface models. Here, we outline the conceptual and predictive gains that could be made with more continuous and discoverable observations of water potential in soils and plants. We discuss improvements to sensor technologies that facilitate in situ characterization of water potential, as well as strategies for building new networks that aggregate water potential data across sites. Here, we end by highlighting novel opportunities for linking more representative site-level observations of water potential to remotely sensed proxies. Together, these considerations offer a road map for clearer links between ecohydrological processes and the water potential gradients that have the ‘potential’ to substantially reduce conceptual and modelling uncertainties.

58 GEOSCIENCES↗

Spatial and Temporal Characterization of Activity in Public Space, 2019–2020

The data reported here characterize spatial and temporal variation in the ratio of short-to-long-duration visits in public places (i.e., points of interest) in the United States for each week between January 2019 and December 2020. The underlying data on anonymized and aggregated foot traffic to public places is curated by SafeGraph, a geospatial data provider. In this work, we report the estimated number and duration of “short” (i.e., <4 hours) and “long” (i.e., >4 hours) visits to public places at the US census block group level. Long visits are shown to be a good proxy for workers based on formal economic data. We propose that short visits are more likely to represent nonobligate activities: people visiting a public place for leisure, shopping, entertainment, or civic or cultural engagement. Our work constructs a ratio of short to long visits, which can be used to inform population estimates for nonworker use of public space. These data may be useful for understanding how people’s use of public space has changed during the COVID-19 pandemic and, more generally, for understanding activity patterns in public.

99 GENERAL AND MISCELLANEOUS↗

A STACKED ANALYSIS OF 115 PULSARS OBSERVED BY THE FERMI LAT

Due to the low gamma-ray fluxes from pulsars above 50 GeV and the small collecting area of space-based telescopes, the gamma-ray emission discovered by the Fermi Large Area Telescope (LAT) in ∼150 pulsars is largely unexplored at these energies. In this regime, the uncertainties on the spectral data points and/or the constraints from upper limits are not sufficient to provide robust tests of competing emission models in individual pulsars. The discovery of power-law-type emission from the Crab pulsar at energies exceeding 100 GeV provides a compelling justification for exploration of other pulsars at these energies. We applied the method of aperture photometry to measure pulsar emission spectra from Fermi-LAT data and present a stacked analysis of 115 pulsars selected from the Second Fermi-LAT catalog of gamma-ray pulsars. This analysis, which uses an average of ∼4.2 yr of data per pulsar, aggregates low-level emission which cannot be resolved in individual objects but can be detected in an ensemble. We find no significant stacked excess at energies above 50 GeV. An upper limit of 30% of the Crab pulsar level is found for the average flux from 115 pulsars in the 100–177 GeV energy range at the 95% confidence level. Stacked searches exclusive to the young pulsar sample, the millisecond pulsar sample, and several other promising sub-samples also return no significant excesses above 50 GeV.

79 ASTRONOMY AND ASTROPHYSICS↗

MARIAH PCAP data for Validation Demonstration

This dataset holds simulated PCAP (packet capture) data from the SCEPTRE validation demonstration model as a set of pairwise communications between devices via specific protocols. All connections should be assumed to be symmetric, as this data is an aggregation of the true PCAP. A mapping is also provided associating each IP address with its true device type.

cyber-physical system↗

Biogeophysical Effects of Land-Use and Land-Cover Change Not Detectable in Warmest Month

Land-use and land-cover changes (hereafter simply “land use”) alter climates biogeophysically by affecting surface fluxes of energy and water. Yet, near-surface temperature responses to land use across observational versus model-based studies and spatial-temporal scales can be inconsistent. Here we assess the prevalence of the historical land use signal of daily maximum temperatures averaged over the warmest month of the year (t LU ) using regularized optimal fingerprinting for detection and attribution. We use observations from the Climatic Research Unit and Berkeley Earth alongside historical simulations with and without land use from phase 6 of the Coupled Model Intercomparison Project to reconstruct an experiment representing the effects of land use on climate. To assess the signal of land use at spatially resolved continental and global scales, we aggregate all input data across reference regions and continents, respectively. At both scales, land use does not comprise a significantly detectable set of forcings for two of four Earth system models and their multimodel mean. Furthermore, using a principal component analysis, we find that t LU is mostly composed of the nonlocal effects of land use rather than its local effects. These findings show that, at scales relevant for climate attribution, uncertainties in Earth system model representations of land use are too high relative to the effects of internal variability to confidently assess land use.

54 ENVIRONMENTAL SCIENCES↗

Adoption of AI in the Utility T&D Sector: Use Cases, Consequence, Assessment and Benefits

Digital transformation and utilization of artificial intelligence (AI) in the electric grid are fundamentally changing the industry’s approach to common problems and enabling a broader paradigm shift in grid planning and operations. The change in approach is circularly both enabling and driving modernization, with load growth and reliable management of data center and AI infrastructure shifting away from planning approaches with relatively predictable behaviors and toward a mix of consumer and industrial choices that surpass human cognitive abilities to process. This movement has potential to condition humans to not understand the system on which the AI depends, while requiring it for development of the necessary infrastructure. Approaches which would address most likely grid conditions and events, such as faults, aging of equipment, and weather, now must also account for large loads which shift not based upon weather or time of day, but the computational load. Quantifying computational load is independent of the traditional grid forecasting variables, where a data center’s aggregate load is determined by user and AI system behavior and decoupled from normal grid planning and operations. AI is both the cause and solution for these challenges, with new grid planning tools integrating massive amounts of decisions into frameworks.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Comparison of Radiosonde Datasets: SondeHub and Integrated Global Radiosonde Archive

SondeHub aggregates radiosonde telemetry data uploaded from community-run radiosonde receiver stations. This radiosonde telemetry dataset is open-source, available to anyone through Amazon S3. There are also other public radiosonde datasets such as National Centers for Environmental Information (NCEI)’s Integrated Global Radiosonde Archive (IGRA). While there are many similarities between the two datasets, there are many differences as well due to the nature of the two datasets: one is community-run, while the other is managed by a government agency. This report presents the result of analyzing and comparing the two datasets.

54 ENVIRONMENTAL SCIENCES↗

3D reconstruction identifies loci linked to variation in angle of individual sorghum leaves

Selection for yield at high planting density has reshaped the leaf canopy of maize, improving photosynthetic productivity in high density settings. Further optimization of canopy architecture may be possible. However, measuring leaf angles, the widely studied component trait of leaf canopy architecture, by hand is a labor and time intensive process. Here, we use multiple, calibrated, 2D images to reconstruct the 3D geometry of individual sorghum plants using a voxel carving based algorithm. Automatic skeletonization and segmentation of these 3D geometries enable quantification of the angle of each leaf for each plant. The resulting measurements are both heritable and correlated with manually collected leaf angles. This automated and scaleable reconstruction approach was employed to measure leaf-by-leaf angles for a population of 366 sorghum plants at multiple time points, resulting in 971 successful reconstructions and 3,376 leaf angle measurements from individual leaves. A genome wide association study conducted using aggregated leaf angle data identified a known large effect leaf angle gene, several previously identified leaf angle QTL from a sorghum NAM population, and novel signals. Genome wide association studies conducted separately for three individual sorghum leaves identified a number of the same signals, a previously unreported signal shared across multiple leaves, and signals near the sorghum orthologs of two maize genes known to influence leaf angle. Automated measurement of individual leaves and mapping variants associated with leaf angle reduce the barriers to engineering ideal canopy architectures in sorghum and other grain crops.

3D reconstruction↗

Current QSO statistics - Implications for the intergalactic medium

The results of numerous QSO surveys have been compiled and analyzed to form a single spatially averaged QSO ionizing function that is independent of evolution mode (number density or luminosity). An intergalactic medium (IGM) that satisfies the observational constraints may now have a density with respect to closure of approximately 0.1, which is substantially less than hitherto modeled. The aggregate of QSO data also indicate that if evolution is due to number density, then, when split into luminosity classes, an exponential in look-back time fits the data better than a power law, and the evolution rates increase roughly with absolute luminosity if analyzed by the exponential.

Sherman, R. D.↗

Using 100G Network Technology in Support of Petascale Science

NASA in collaboration with a number of partners conducted a set of individual experiments and demonstrations during SC 10 that collectively were titled "Using 100G Network Technology in Support of Petascale Science". The partners included the iCAIR, Internet2, LAC, MAX, National LambdaRail (NLR), NOAA and SCinet Research Sandbox (SRS) as well as the vendors Ciena, Cisco, ColorChip, cPacket, Extreme Networks, Fusion-io, HP and Panduit who most generously allowed some of their leading edge 40G/100G optical transport, Ethernet switch and Internet Protocol router equipment and file server technologies to be involved. The experiments and demonstrations featured different vendor-provided 40G/100G network technology solutions for full-duplex 40G and 100G LAN data flows across SRS-deployed single-node fiber-pairs among the Exhibit Booths of NASA, the National Center for Data lining, NOAA and the SCinet Network Operations Center, as well as between the NASA Exhibit Booth in New Orleans and the Starlight Communications Exchange facility in Chicago across special SC 10- only 80- and 100-Gbps wide area network links provisioned respectively by the NLR and Internet2, then on to GSFC across a 40-Gbps link. provisioned by the Mid-Atlantic Crossroads. The networks and vendor equipment were load-stressed by sets of NASA/GSFC High End Computer Network Team-built, relatively inexpensive, net-test-workstations that are capable of demonstrating greater than 100Gbps uni-directional nuttcp-enabled memory-to-memory data transfers, greater than 80-Gbps aggregate--bidirectional memory-to-memory data transfers, and near 40-Gbps uni-directional disk-to-disk file copying. This paper will summarize the background context, key accomplishments and some significances of these experiments and demonstrations.

Gary, James P.↗

Exploratory Analysis of Carbon Dioxide Levels, Ultrasound and Optical Coherence Tomography Measures of the Eye During ISS Missions

Enhanced screening for the Visual Impairment/Intracranial Pressure (VIIP) syndrome has been implemented to better characterize the ocular and vision changes observed in some long-duration crewmembers. This includes implementation of in-flight ultrasound in 2010 and optical coherence tomography (OCT) in 2013. Potential risk factors for VIIP include cardiovascular health, diet, anatomical and genetic factors, and environmental conditions. Carbon dioxide (CO2), a potent vasodilator, is chronically elevated on the International Space Station (ISS) relative to ambient levels on Earth, and is a plausible risk factor for VIIP. In an effort to understand the possible associations between CO2 and VIIP, this study explores the relationship of ambient CO2 levels on ISS compared to inflight ultrasound and OCT measures of the eye obtained from ISS crewmembers. CO2 measurements were aggregated from Operational Data Reduction Complex and Node 3 major constituent analyzers (MCAs) on ISS or from sensors located in the European Columbus module, as available. CO2 levels in the periods between each ultrasound and OCT session are summarized using timeseries metrics, including time-weighted means and variances. Partial least squares regression analyses are used to quantify the complex relationship between specific ultrasound and OCT measures and the CO2 metrics simulataneously. These analyses will enhance our understanding of the possible associations between CO2 levels and structural changes to the eye which will in turn inform future analysis of inflight VIIP data.

Schaefer, C.↗

NASA's Next Generation Optical Communications Relay

NASA's Space Communications and Navigation (SCaN) program is creating an operational optical communications network to complement its current radio frequency (RF) networks. NASA is currently planning for a new optical communications relay node in geostationary (GEO) orbit to be commissioned in 2025, developed by NASA's Goddard Space Flight Center (GSFC), as evolved from Goddard's Laser Communications Relay Demonstration (LCRD) GEO relay payload that will launch in 2019. The Next Generation optical relay node will serve as an initial element in a larger optical networking constellation that will consist of Government and commercial, and international relays. NASA's nodes will aggregate traffic at data rates of up to 10 Gigabits per second (Gbps) from users on the Earth's surface and up through suborbital, LEO, MEO, GEO, cislunar and even out to Earth-Sun Lagrange (1.25 Mkm) distances. Users that require low-latency will be serviced with an onboard complementary Ka-band downlink service. The next generation network will deploy > 100 Gbps space-to-ground links and also optical crosslinks between nodes to allow for user traffic backhaul to minimize ground station location constraints.

Israel, David↗

NASA's Next Generation ≥100 Gbps Optical Communications Relay

NASA’s Space Communications and Navigation (SCaN) program is creating an operational optical communications network to complement its current radio frequency (RF) networks. NASA is currently planning for a new optical communications relay node in geostationary (GEO) orbit to be commissioned in 2025, developed by NASA’s Goddard Space Flight Center (GSFC), as evolved from Goddard’s Laser Communications Relay Demonstration (LCRD) GEO relay payload that will launch in 2019. The Next Generation optical relay node will serve as an initial element in a larger optical networking constellation that will consist of Government and commercial, and international relays. NASA’s nodes will aggregate traffic at data rates of up to 10 Gigabits per second (Gbps) from users on the Earth’s surface and up through suborbital, LEO, MEO, GEO, cislunar and even out to Earth-Sun Lagrange (1.25 Mkm) distances. Users that require low-latency will be serviced with an onboard complementary Ka-band downlink service. The next generation network will deploy ≥ 100 Gbps space-to-ground links and also optical crosslinks between nodes to allow for user traffic backhaul to minimize ground station location constraints.

Park, Elizabeth A.↗

Evidence for Primordial Alignment: Insights from Stellar Obliquity Measurements for Compact Sub-Saturn Systems

Despite decades of effort, the mechanisms by which the spin axis of a star and the orbital axes of its planets become misaligned remain elusive. In particular, it is of great interest whether the large spin–orbit misalignments observed are driven primarily by high-eccentricity migration—expected to have occurred for short-period, isolated planets—or reflect a more universal process that operates across systems with a variety of present-day architectures. Compact multiplanet systems offer a unique opportunity to differentiate between these competing hypotheses, as their tightly packed configurations preclude violent dynamical histories, including high-eccentricity migration, allowing them to trace the primordial disk plane. In this context, we report measurements of the sky-projected stellar obliquity (λ) via the Rossiter–McLaughlin effect for two sub-Saturns in multiple-transiting systems: TOI-5126 b (λ = 1 ± 48°) and TOI-5398 b (λ = -8.1 +5.3 −6.3 ). Both are spin–orbit aligned, joining a fast-growing group of just three other compact sub-Saturn systems, all of which exhibit spin–orbit alignment. In aggregate with archival data, our results strongly suggest that sub-Saturn systems are primordially aligned and become misaligned largely in the postdisk phase, as appears to be the case increasingly for other exoplanet populations.

Brandon T Radzom↗