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At least 1,081 records · Page 60

PNNL Soil Microbiome SFA

PNNL's Soil Microbiome Science Focus Area (SFA) is focused on understanding the basic biology underpinning how interactions among various soil microbial community members, across trophic levels, lead to the emergence of community functions. Moisture, in particular, drives microbial interactions and influences everything from cell function to substrate fate within soils. The group predicts this results in repeatable, predictable phenotypes. The sum of these phenotypes comprises the “soil metaphenome”. Understanding how the soil metaphenome shifts in response to moisture will provide a basis for modeling and predicting these shifts in reaction network responses. PNNL’s Soil Microbiome SFA project repository on DataHub allows for exploring and downloading integrated experimental omics data, experimental metadata, pre- and post-processed data files, and other associated materials directly related to experimental project publication data. Visit the PNNL Soil Microbiome Science Focus Area Program homepage for more information.

54 ENVIRONMENTAL SCIENCES↗

KBase partners with community developers from several Department of Energy Science Focus Areas to increase functionality of tools and analysis

Several SFAs were selected for training on the KBase Software Development Kit (SDK) to integrate tools and data into the KBase platform. Overall, the collaborative effort was viewed as highly successful. Every SFA project was able to achieve their proposed targets for training and functionality, while also gaining an appreciation for the role KBase plays/could play in their future science plans. Both the SFA and KBase teams felt that continued collaboration would be beneficial, especially if the programs were able to jointly prioritize scope and readiness of future projects. This poster will outline the scope of functionality added by SFA community developers, and highlight points of intersection across these efforts.

59 BASIC BIOLOGICAL SCIENCES↗

Genome Extraction from Shotgun Metagenome Sequence Data

Uncultivated Bacteria and Archaea comprise the vast majority of species on Earth, but obtaining their genomes directly from the environment, using shotgun sequencing, has only recently become possible. To realize the hope of capturing Earth’s microbial genetic complement, technologies that accelerate recovery of high-quality genomes are necessary. We present a series of analysis steps and data products for the extraction of high quality metagenome-assembled genomes (MAGs) from microbiomes using the U.S. Department of Energy Systems Biology Knowledgebase (KBase) platform (http://www.kbase.us/). In KBase, the process is end-to-end, allowing a user to go from the initial sequencing reads all the way through to MAG genomes, which can then be analyzed with other KBase capabilities such as phylogenetic placement, functional assignment, metabolic modeling, pangenome functional profiling, RNA-Seq, and others. While portions of such capabilities are individually available from other resources, the combination of the intuitive usability, data interoperability, and integration of tools in a freely available compute resource makes KBase a uniquely powerful platform for obtaining MAGs from microbiomes. While this workflow offers tools for each of the key steps in the genome extraction process, it also provides a scaffold that can be easily extended, with additional MAG recovery and analysis tools, via the KBase SDK (Software Development Kit).

Chivian, Dylan↗

Moab Desert Crust - Sample 4E

Uncultivated Bacteria and Archaea comprise the vast majority of species on Earth, but obtaining their genomes directly from the environment, using shotgun sequencing, has only recently become possible. To realize the hope of capturing Earth’s microbial genetic complement, technologies that accelerate recovery of high-quality genomes are necessary. We present a series of analysis steps and data products for the extraction of high quality metagenome-assembled genomes (MAGs) from microbiomes using the U.S. Department of Energy Systems Biology Knowledgebase (KBase) platform (http://www.kbase.us/). In KBase, the process is end-to-end, allowing a user to go from the initial sequencing reads all the way through to MAG genomes, which can then be analyzed with other KBase capabilities such as phylogenetic placement, functional assignment, metabolic modeling, pangenome functional profiling, RNA-Seq, and others. While portions of such capabilities are individually available from other resources, the combination of the intuitive usability, data interoperability, and integration of tools in a freely available compute resource makes KBase a uniquely powerful platform for obtaining MAGs from microbiomes. While this workflow offers tools for each of the key steps in the genome extraction process, it also provides a scaffold that can be easily extended, with additional MAG recovery and analysis tools, via the KBase SDK (Software Development Kit).

Chivian, Dylan↗

Total Power Factor Smart Contract with Cyber Grid Guard Using Distributed Ledger Technology for Electrical Utility Grid with Customer-Owned Wind Farm

In modern electrical grids, the numbers of customer-owned distributed energy resources (DERs) have increased, and consequently, so have the numbers of points of common coupling (PCC) between the electrical grid and customer-owned DERs. The disruptive operation of and out-of-tolerance outputs from DERs, especially owned DERs, present a risk to power system operations. A common protective measure is to use relays located at the PCC to isolate poorly behaving or out-of-tolerance DERs from the grid. Ensuring the integrity of the data from these relays at the PCC is vital, and blockchain technology could enhance the security of modern electrical grids by providing an accurate means to translate operational constraints into actions/commands for relays. This study demonstrates an advanced power system application solution using distributed ledger technology (DLT) with smart contracts to manage the relay operation at the PCC. The smart contract defines the allowable total power factor (TPF) of the DER output, and the terms of the smart contract are implemented using DLT with a Cyber Grid Guard (CGG) system for a customer-owned DER (wind farm). This article presents flowcharts for the TPF smart contract implemented by the CGG using DLT. The test scenarios were implemented using a real-time simulator containing a CGG system and relay in-the-loop. The data collected from the CGG system were used to execute the TPF smart contract. The desired TPF limits on the grid-side were between +0.9 and +1.0, and the operation of the breakers in the electrical grid and DER sides was controlled by the relay consistent with the provisions of the smart contract. The events from the real-time simulator, CGG, and relay showed a successful implementation of the TPF smart contract with CGG using DLT, proving the efficacy of this approach in general for implementing electrical grid applications for utilities with connections to customer-owned DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

High-contrast Thermal Infrared Spectroscopy with ALES: The 3–4 μm Spectrum of κ Andromedae b

We present the first L-band (2.8–4.1 μm) spectroscopy of κ Andromedae b, a ~20 M Jup companion orbiting at 1" projected separation from its B9-type stellar host. We combine our Large Binocular Telescope (LBT) Arizona Lenslets for Exoplanet Spectroscopy (ALES) integral field spectrograph data with measurements from other instruments to analyze the atmosphere and physical characteristics of κ And b. We report a discrepancy of ~20% (2σ) in the L' flux of κ And b when comparing to previously published values. We add an additional L' constraint using an unpublished imaging data set collected in 2013 using the LBT Interferometer/LMIRCam, the instrument in which the ALES module has been built. The LMIRCam measurement is consistent with the ALES measurement, both suggesting a fainter L-band scaling than previous studies. The data, assuming the flux scaling measured by ALES and LMIRCam imaging, are well fit by an L3-type brown dwarf. Atmospheric model fits to measurements spanning 0.9–4.8 μm reveal some tension with the predictions of evolutionary models, but the proper choice of cloud parameters can provide some relief. In particular, models with clouds extending to very low pressures composed of grains ≤1 μm appear to be necessary. If the brighter L' photometry is accurate, there is a hint that subsolar metallicity may be required.

79 ASTRONOMY AND ASTROPHYSICS↗

The Young Massive Star Cluster Westerlund 2 Observed with MUSE. III. A Cluster in Motion—The Complex Internal Dynamics

Analyzing the dynamical state of nearby young massive star clusters is essential for understanding star cluster formation and evolution during their earliest stages. In this work we analyze the stellar and gas kinematics of the young massive star cluster Westerlund 2 (Wd2) using data from the integral field unit Multi Unit Spectroscopic Explorer (MUSE) and complement them with proper motions from the Gaia DR2. The mean gas radial velocity of 15.9 km s{sup −1} agrees with the assumption that Wd2 is the result of a cloud–cloud collision. The gas motions show the expansion of the H ii region, driven by the radiation from the many OB stars in the cluster center. The velocity profile of the cluster member stars reveals an increasing velocity dispersion with decreasing stellar mass and that the low-mass stars show five distinct velocity groups. Based on their spatial correlation with the cluster’s two clumps, we concluded that this is the imprint of the initial cloud collapse that formed Wd2. A thorough analysis of the dynamical state of Wd2, which determines a dynamical mass range of M {sub dyn,Wd2} = (7.5 ± 1.9) × 10{sup 4} − (4.4 ± 1.1) × 10{sup 5} M {sub ⊙} and exceeds the photometric mass by at least a factor of two, leads to the conclusion that Wd2 is not massive enough to remain gravitationally bound. Additionally we also identify 22 runaway candidates with peculiar velocities between 30 and 546 km s{sup −1}.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Subgalactic Scaling Relations with T e -based Metallicities of Low-metallicity Regions in Galaxies: Metal-poor Gas Inflow May Have Important Effects?

The scaling relationship is a fundamental probe of the evolution of galaxies. Using the integral field spectroscopic data from the Mapping Nearby Galaxies at Apache Point Observatory survey, we select 1698 spaxels with a significant detection of the auroral emission line [O ιιι]λ4363 from 52 galaxies to investigate the scaling relationships at the low-metallicity end. We find that our sample’s star formation rate is higher and its metallicity is lower in the scaling relationship than the star-forming sequence after removing the contribution of the Fundamental Metallicity Relation. We also find that the stellar ages of our sample are younger (<1 Gyr) and the stellar metallicities are also lower. Morphological parameters from the Deep Learning catalog indicate that our galaxies are more likely to be mergers. These results suggest that their low-metallicity regions may be related to interaction; the inflow of metal-poor gas may dilute the interstellar medium and form new metal-poor stars in these galaxies during interactions.

79 ASTRONOMY AND ASTROPHYSICS↗

SDSS-IV MaNGA: Cannibalism Caught in the Act—On the Frequency of Occurrence of Multiple Cores in Brightest Cluster Galaxies

Although it is generally accepted that massive galaxies form in a two-phased fashion, beginning with a rapid mass buildup through intense starburst activities followed by primarily dry mergers that mainly deposit stellar mass at outskirts, the late time stellar mass growth of brightest cluster galaxies (BCGs), the most massive galaxies in the universe, is still not well understood. Several independent measurements have indicated a slower mass growth rate than predictions from theoretical models. We attempt to resolve the discrepancy by measuring the frequency of BCGs with multiple cores, which serve as a proxy of the merger rates in the central region and facilitate a more direct comparison with theoretical predictions. Using 79 BCGs at z = 0.06–0.15 with integral field spectroscopic data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) project, we obtain a multiple-core fraction of 0.11 ± 0.04 at z ≈ 0.1 within an 18 kpc radius from the center, which is comparable to the value of 0.08 ± 0.04 derived from mock observations of 218 simulated BCGs from the cosmological hydrodynamical simulation IllustrisTNG. We find that most cores that appear close to the BCGs from imaging data turn out to be physically associated systems. Anchoring on the similarity in the multiple-core frequency between the MaNGA and IllustrisTNG, we discuss the mass growth rate of BCGs over the past 4.5 Gyr.

79 ASTRONOMY AND ASTROPHYSICS↗

Different Formation Scenarios for Counterrotating Stellar Disks in Nearby Galaxies

Using the integral field unit data from the Mapping Nearby Galaxies at Apache Point Observatory survey, we select a sample of 101 galaxies with counterrotating stellar disks and regularly rotating ionized gas disks. We classify the 101 galaxies into four types based on the features of their stellar velocity fields. The relative fractions and stellar population age radial gradients of the four types are different in the blue cloud, green valley, and red sequence populations. We suggest different formation scenarios for counterrotating stellar disks; the key factors in the formation of counterrotating stellar disks include (1) the abundance of preexisting gas in the progenitor and (2) the efficiency in angular momentum consumption.

79 ASTRONOMY AND ASTROPHYSICS↗

Watershed zonation through hillslope clustering for tractably quantifying above- and below-ground watershed heterogeneity and functions

Abstract. In this study, we develop a watershed zonation approach for characterizing watershed organization and functions in a tractable manner by integrating multiple spatial data layers. We hypothesize that (1) a hillslope is an appropriate unit for capturing the watershed-scale heterogeneity of key bedrock-through-canopy properties and for quantifying the co-variability of these properties representing coupled ecohydrological and biogeochemical interactions, (2) remote sensing data layers and clustering methods can be used to identify watershed hillslope zones having the unique distributions of these properties relative to neighboring parcels, and (3) property suites associated with the identified zones can be used to understand zone-based functions, such as response to early snowmelt or drought and solute exports to the river. We demonstrate this concept using unsupervised clustering methods that synthesize airborne remote sensing data (lidar, hyperspectral, and electromagnetic surveys) along with satellite and streamflow data collected in the East River Watershed, Crested Butte, Colorado, USA. Results show that (1) we can define the scale of hillslopes at which the hillslope-averaged metrics can capture the majority of the overall variability in key properties (such as elevation, net potential annual radiation, and peak snow-water equivalent – SWE), (2) elevation and aspect are independent controls on plant and snow signatures, (3) near-surface bedrock electrical resistivity (top 20 m) and geological structures are significantly correlated with surface topography and plan species distribution, and (4) K-means, hierarchical clustering, and Gaussian mixture clustering methods generate similar zonation patterns across the watershed. Using independently collected data, we show that the identified zones provide information about zone-based watershed functions, including foresummer drought sensitivity and river nitrogen exports. The approach is expected to be applicable to other sites and generally useful for guiding the selection of hillslope-experiment locations and informing model parameterization.

58 GEOSCIENCES↗

Sensors with Intelligent Measurement Platform for Monitoring and Control in Distribution Circuits

This paper presents a medium-voltage intelligent measurement platform that provides post-processing of raw measurements received from commercially-available voltage/current sensors to enhance accuracy and bandwidth of the monitoring system. Furthermore, this platform integrates into a Data Distribution Service (DDS) messaging bus for distributed control and interoperability. The authors present the design, specifications, and major components included in the platform, and argue for applications and use cases that most benefit from this new approach. A laboratory testbed has been created to demonstrate the functionality, for which test results are presented for selected test cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Gas-mapping 3D imager measurement techniques and method of data processing

Measurement approaches and data analysis methods are disclosed for combining 3D topographic data with spatially-registered gas concentration data to increase the efficiency of gas monitoring and leak detection tasks. Here, the metric for efficiency is defined as reducing the measurement time required to achieve the detection, or non-detection, of a gas leak with a desired confidence level. Methods are presented for localizing and quantifying detected gas leaks. Particular attention is paid to the combination of 3D spatial data with path-integrated gas concentration measurements acquired using remote gas sensing technologies, as this data can be used to determine the path-averaged gas concentration between the sensor and points in the measurement scene. Path-averaged gas concentration data is useful for finding and quantifying localized regions of elevated (or anomalous) gas concentration making it ideal for a variety of applications including: oil and gas pipeline monitoring, facility leak and emissions monitoring, and environmental monitoring.

Thorpe, Michael↗

Evolution of Energy Efficiency Programs Over Time: The Case of Standby Power

Issued in 2001, Presidential Executive Order 13221 directed federal agencies to purchase products with low standby power, with the goal of 1) reducing energy consumption in federal facilities, and 2) drawing attention to the problem of high standby power consumption, with guidance provided by the Federal Energy Management Program (FEMP). At that time, standby power was newly recognized as an increasing building energy load. Since then, procurement of products with low standby power have been set in place in acquisition processes, and the purchasing power of the federal government continues to influence manufacturers’ design decisions related to standby power. In recent years, FEMP has shifted effort from direct manufacturer outreach for data collection, to integrating low standby requirement into broader acquisition programs including Energy Star and Electronic Product Environmental Assessment Tool (EPEAT). Another milestone has been the labeling of low standby products on the GSA Advantage website to simplify and enhance compliance. Looking forward into the program’s future, this question arises “How do we design programs over time to reflect market and technology changes, by adjusting programmatic requirements while maintaining effectiveness?” This paper discusses that question for the case of standby power, which transitioned from covering a single to multiple environmental attributes, both in the context of the program’s past and future.

Payne, CT↗

Characterization of fluid inside pipe using multi frequency electrical signal

A multi-frequency signal may be used to induce voltage difference across a portion of a pipe. The voltage difference may be induced to take multi-frequency measurement of impedance characteristics of fluid inside the pipe. The multi-frequency measurement of the impedance characteristic of the fluid inside the pipe may be used to determine a characteristic of the fluid inside the pipe. This may be achieved by active integration of experimental data with high-resolution multi-frequency electrical impedance tomography (MFEIT) modeling.

Chillara, Vamshi Krishna↗

Component Failure R&D

This presentation is to establish a scientific basis for risk and reliability analysis through integrated work with data collection, model development, and stakeholder engagement.

availability↗

Integrated SOAs enable energy-efficient intra-data center coherent links

Coherent optical links are becoming increasingly attractive for intra-data center applications as data rates scale. Realizing the era of high-volume short-reach coherent links will require substantial improvements in transceiver cost and power efficiency, necessitating a reassessment of conventional architectures best-suited for longer-reach links and a review of assumptions for shorter-reach implementations. In this work, we analyze the impact of integrated semiconductor optical amplifiers (SOAs) on link performance and power consumption, and describe the optimal design spaces for low-cost and energy-efficient coherent links. Placing SOAs after the modulator provide the most energy-efficient link budget improvement, up to 6 pJ/bit for large link budgets, despite any penalties from nonlinear impairments. Increased robustness to SOA nonlinearities makes QPSK-based coherent links especially attractive, and larger supported link budgets enable the inclusion of optical switches, which could revolutionize data center networks and improve overall energy efficiency.

Maharry, Aaron (ORCID:0000000273732697)↗

PS3: The Pheno-Synthesis software suite for integration and analysis of multi-scale, multi-platform phenological data

Phenology is the study of recurring plant and animal life-cycle stages which can be observed across spatial and temporal scales that span orders of magnitude (e.g., organisms to landscapes). The variety of scales at which phenological processes operate is reflected in the range of methods for collecting phenologically relevant data, and the programs focused on these collections. Consideration of the scale at which phenological observations are made, and the platform used for observation, is critical for the interpretation of phenological data and the application of these data to both research questions and land management objectives. However, there is currently little capacity to facilitate access, integration and analysis of cross-scale, multi-platform phenological data. This paper reports on a new suite of software and analysis tools – the “Pheno-Synthesis Software Suite,” or PS3 – to facilitate integration and analysis of phenological and ancillary data, enabling investigation and interpretation of phenological processes at scales ranging from organisms to landscapes and from days to decades. We use PS3 to investigate phenological processes in a semi-aride, mixed shrub-grass ecosystem, and find that the apparent importance of seasonal precipitation to vegetation activity (i.e., “greenness”) is affected by the scale and platform of observation. We end by describing potential applications of PS3 to phenological modeling and forecasting, understanding patterns and drivers of phenological activity in real-world ecosystems, and supporting agricultural and natural resource management and decision-making.

54 ENVIRONMENTAL SCIENCES↗