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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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Timeseries data from the experimental testing of the OPI's prototype hydraulic drivetrain. The data is provided in .mat file format. The units for the data can be found in the ReadMe included in the submission resources.
The program for the DC 8-D3 flight planning was slightly modified for the three dimensional flight planning for DC 10 aircrafts. Several test runs of the modified program over the North Atlantic and North America were made for verifying the program. While geopotential height and temperature were used in a previous program as meteorological data, the modified program uses wind direction and speed and temperature received from the National Weather Service. A scanning program was written to collect required weather information from the raw data received in a packed decimal format. Two sets of weather data, the 12-hour forecast and 24-hour forecast based on 0000 GMT, are used for dynamic processes in testruns. In order to save computing time only the weather data of the North Atlantic and North America is previously stored in a PCF file and then scanned one by one.
The Cockpit Oriented Display of Aircraft Configurations (CODAC) package is an interactive FORTRAN 77 graphics program which produces high quality publication grade hidden line images of three dimensional wireframe objects. The term, Cockpit Oriented, is used because CODAC rotates objects relative to the changing aircraft axis system (rather than about a fixed global axis system) and uses the more familiar directions of yaw, roll, and pitch. In addition, CODAC accepts geometry data in a variety of formats (LaWGS, Craidon, Hess, and FVS data check), and automatically selects the appropriate panel driver. Finally, CODAC makes full use of the Precision Visuals' DI-3000 metafile option, allowing users to save, edit, and print images for group presentations or research publications.
A summary of the surface data collected by Colorado State University (CSU) on San Nicolas Island during the First ISCCP Regional Experiment (FIRE) from 30 June (Julian Day 181) through 19 July (Julian Day 200) is given. The data are available in two formats: hard copy graphs, and processed data on floppy disk.
The Intergovernmental Oceanographic Commission (IOC) wishes to develop an integrated software package for oceanographic data entry and access in developing countries. The software, called 'OCEAN-PC', would run on low cost PC microcomputers and would encourage and standardize: (1) entry of local ocean observations; (2) quality control of the local data; (3) merging local data with historical data; (4) improved display and analysis of the merged data; and (5) international data exchange. OCEAN-PC will link existing MS-DOS oceanographic programs and data sets with table-driven format conversions. Since many ocean data sets are now being distributed on optical discs (Compact Discs - Read Only Memory, CD-ROM, Mass et al. 1987), OCEAN-PC will emphasize access to CD-ROMs.
The Boreal Ecosystem-Atmosphere Study (BOREAS) Remote Sensing Science (RSS)-17 team acquired and analyzed imaging radar data from the European Space Agency's (ESA's) European Remote Sensing Satellite (ERS)-1 over a complete annual cycle at the BOREAS sites in Canada in 1994 to detect shifts in radar backscatter related to varying environmental conditions. Two independent transitions corresponding to soil thaw and possible canopy thaw were revealed by the data. The results demonstrated that radar provides an ability to observe thaw transitions at the beginning of the growing season, which in turn helps constrain the length of the growing season. The data set presented here includes change maps derived from radar backscatter images that were mosaicked together to cover the southern BOREAS sites. The image values used for calculating the changes are given relative to the reference mosaic image. The data are stored in binary image format files. The imaging radar data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).
The Instrument Remote Control (IRC) architecture is a flexible, platform-independent application framework that is well suited for the control and monitoring of remote devices and sensors. IRC enables significant savings in development costs by utilizing extensible Markup Language (XML) descriptions to configure the framework for a specific application. The Instrument Markup Language (IML) is used to describe the commands used by an instrument, the data streams produced, the rules for formatting commands and parsing the data, and the method of communication. Often no custom code is needed to communicate with a new instrument or device. An IRC instance can advertise and publish a description about a device or subscribe to another device's description on a network. This simple capability of dynamically publishing and subscribing to interfaces enables a very flexible, self-adapting architecture for monitoring and control of complex instruments in diverse environments.
This paper presents the work of the Navigation Working Group of the Consultative Committee for Space Data Systems (CCSDS) on development of standards addressing the transfer of orbit, attitude and tracking data for space objects. Much progress has been made since the initial presentation of the standards in 2004, including the progression of the orbit data standard to an accepted standard, and the near completion of the attitude and tracking data standards. The orbit, attitude and tracking standards attempt to address predominant parameterizations for their respective data, and create a message format that enables communication of the data across space agencies and other entities. The messages detailed in each standard are built upon a keyword = value paradigm, where a fixed list of keywords is provided in the standard where users specify information about their data, and also use keywords to encapsulate their data. The paper presents a primer on the CCSDS standardization process to put in context the state of the message standards, and the parameterizations supported in each standard, then shows examples of these standards for orbit, attitude and tracking data. Finalization of the standards is expected by the end of calendar year 2007.
Proton CT (pCT) is a promising new imaging technique that can reconstruct relative stopping power (RSP) more accurately than x-ray CT in each cubic millimeter voxel of the patient. This, in turn, will result in better proton range accuracy and, therefore, smaller planned tumor volumes (PTV). The hardware description and some reconstructed images have previously been reported. In a series of two contributions, we focus on presenting the software algorithms that convert pCT detector data to the final reconstructed pCT images for application in proton treatment planning. There were several options on how to accomplish this, and we will describe our solutions at each stage of the data processing chain. In the first paper of this series, we present the data acquisition with the pCT tracking and energy-range detectors and how the data are preprocessed, including the conversion to the well-formatted track information from tracking data and water-equivalent path length from the data of a calibrated multi-stage energy-range detector. These preprocessed data are then used for the initial image formation with an FDK cone-beam CT algorithm. The output of data acquisition, preprocessing, and FDK reconstruction is presented along with illustrative imaging results for two phantoms, including a pediatric head phantom. The second paper in this series will demonstrate the use of iterative solvers in conjunction with the superiorization methodology to further improve the images resulting from the upfront FDK image reconstruction and the implementation of these algorithms on a hybrid CPU/GPU computer cluster.
This repository features an Arduino-based GPS logger, called LLUDA, which uses the Adafruit Ultimate GPS FeatherWing with the Adafruit Feather M0 Adalogger, designed to capture and log GPS data in CSV format onto an SD card (embedded inside the Feather M0 Adalogger). The FeatherWing is powered through the vehicle's auxiliary power (from cigarette lighter) socket via a micro USB cable. The data it collects can be used to analyze vehicle operations and support vehicle modeling applications, helping to assess the potential for electrification.
Data-processor-and-buffer electronic system receives audio signals digitized in first standard format at relatively low data rate, rearranges data for transmission in bursts in second standard format at relatively high rate, stores second-format bursts, and releases them at higher rate upon request. Conceived for asynchronous, one-way transmission of digitized speech in outer-space communications, concept of system applied in other digital communication systems in which data transmitted from low-rate sources to high-rate sinks not synchronized with sources.
The author has identified the following significant results. Identification and mapping of three major kinds of coal refuse targets based on spectral signatures in channels four through seven of the ERTS-1 MSS were conducted. Correlation of the placement of the coal refuse targets with an existing map of their location was accomplished. Digital processing of ERTS-1 data permitted identification of stripped areas including ones that are not discernible by visual analysis of ERTS imagery. Combined visual and digital techniques of analyzing ERTS-1 data for geologic formations have been tried on selected areas of Pennsylvania. Mapping of two major agriculture counties to show land forms, drainage patterns, water, and urban areas were made using positive transparencies of MSS data. Two frames of the same central Pennsylvania area were brought into registration by translation and then merged even though the frames were obtained 71 days apart.
The harvesting of behavioral data and their analysis through evidence-based reasoning enable the detection of sociocultural signatures in their context to support situation awareness and decision making. Harvested data are used as training materials from which to infer computational models of sociocultural behaviors or calibrate parameters for such models. Harvested data also serve as evidence input that the models use to provide insights about observed and future behaviors for targets of interest. The harvested data is often the result of assembling diverse data types and aggregating them into a form suitable for analysis. Data need to be analyzed to bring out the categories of content that are relevant to the domain being addressed in order to train or run a model. If, for example, we are modeling the intent of a group to engage in violent behavior using messages that the group has broadcasted, then these messages need to be processed to extract and measure indicators of violent intent. The extracted indicators and the associated measurements (e.g. rates or counts of occurrence) can then be used to train/calibrate and run computational models that assess the propensity for violence expressed in the source message. Ubiquitous access to the Internet, mobile telephony and technologies such as digital photography and digital video have enabled social media application platforms such as Facebook, YouTube, and Twitter that are altering the nature of human social interaction. The fast increasing pace of online social interaction introduces new challenges and opportunities for gathering sociocultural data. Challenges include the development of harvesting and processing techniques tailored to new data environments and formats (e.g. Twitter, Facebook), the integration of social media content with traditional media content, and the protection of personal privacy. As these and other challenges are addressed, a new wealth of behavioral data and data analysis methods becomes available that are shaping social computing as a strongly data-driven experimental discipline with an increasingly stronger impact on the decision-making process of groups and individuals alike. In this chapter, we review current advances and trends in the detection of sociocultural signatures. Specific embodiments of the issues discussed are provided with respect to the assessment of violent intent and sociopolitical contention. We begin by reviewing current approaches to the detection of sociocultural signatures in these domains. Next, we turn to the review of novel data harvesting methods for social media content. Finally, we discuss the application of sociocultural models to social media content, and conclude by commenting on current challenges and future developments.
The Watershed Function Science Focus Area (WF SFA) at Lawrence Berkeley National Lab is working to build a mechanistic understanding of the distribution and dynamics of biogeochemical processes in mountainous watersheds and their response to perturbation. In June 2018, the NEON (National Ecological Observatory Network) Airborne Observatory Platform (AOP) performed a taskable airborne imaging campaign to collect visible to shortwave infrared (VSWIR) imaging spectroscopy and LiDAR data across 330 km2 in the Upper East River at Crested Butte, CO. We conducted a parallel ground sampling campaign to sample vegetation traits, as well as soil physical, chemical, and microbiological characteristics. We collected these samples from 438 sites across 12 locations spanning much of the elevation, topographic, and geologic variability across the study area. A subset of 250 samples were used for soil metagenomics which is presented here. In addition, at each site, vegetation samples were collected to measure species-specific leaf water content and leaf mass area, foliar elemental composition and foliar CN stable isotope ratios. Soil samples were collected to measure soil physical properties which include bulk density and soil texture analysis. A suite of soil chemical properties was measured from the samples collected at each site, including pH, organic matter, concentrations exchangeable cations, total elemental composition, and the concentrations of extractable N pools (e.g. total free amino acids, ammonium, nitrate, dissolved organic N, and total dissolved N). Additionally, we have measured soil microbial biomass CN stoichiometry. Here, we present 1982 metagenome-assembled genomes (MAGs) for the bacterial and archaeal community from topsoil collected from during NEON 2018 campaign. All metagenomes were sequenced at JGI (Joint Genome Institute) (GOLD Study ID: Gs0149986). Metagenomes were assembled using JGI Metagenome Workflow (10.1128/mSystems.00804-20). The dataset includes (1) zip files for 1982 MAG fasta files (neon_genomes1-5.tar.gz, split into 5 tarballs to keep tarballs under 0.5 GB), (2) neon_Gs0149986_samples_soilproperties_metagenomes.csv: the sample information together with the accession numbers for the underlying metagenomes and the associated soil physical and chemical measurements in NMDC (National Microbiome Data Collaborative) compliant format, (3) neon_Gs0149986.kml: location bounding box file for the sampled locations, (4) samples.csv: sample metadata file used to register Internationall Generic Sample Numbers (IGSNs), (5) flmd.csv: file level metadata file, and (6) dd.csv: data dictionary file. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.
We present new data on the globular cluster system of the elliptical galaxy NGC 3923 which show that it has the most globular clusters per unit luminosity of any noncluster elliptical yet observed, with S(sub N) = 6.4 +/- 1.4. NGC 3923 is also among the brightest ellipticals outside of a galaxy cluster for which the number of globular clusters has been determined. Our observation of a large number of clusters per unit luminosity (high S(sub N)-value) for a bright elliptical in a sparse environment is consistent with the suggestion of Djorgovski and Santiago that the number of globular clusters is a power-law function of the luminosity with an exponent greater than 1. We relate this higher specific frequency of globular clusters in more luminous galaxies to other observations which indicate that the physical conditions within elliptical galaxies at the time of their formation were dependent on galaxy mass.
Copper-catalyzed aerobic oxidative coupling of diaryl imines provides a route for conversion of ammonia to hydrazine. Here the present study uses experimental and density functional theory computational methods to investigate the mechanism of N–N bond formation, and the data support a mechanism involving bimolecular coupling of Cu-coordinated iminyl radicals. Computational analysis is extended to Cu II -mediated C–C, N–N, and O–O coupling reactions involved in the formation of cyanogen (NC–CN) from HCN, 1,3-butadiyne from ethyne (i.e., Glaser coupling), hydrazine from ammonia, and hydrogen peroxide from water. The results reveal two different mechanistic pathways. Heteroatom ligands with an uncoordinated lone pair (iminyl, NH 2 , OH) undergo charge transfer to Cu II , generating ligand-centered radicals that undergo facile bimolecular radical–radical coupling. Ligands lacking a lone pair (CN and CCH) form bridged binuclear diamond-core structures that undergo C–C coupling. This mechanistic bifurcation is rationalized by analysis of spin densities in key intermediates and transition states, as well as multiconfigurational calculations. Radical–radical coupling is especially favorable for N–N coupling owing to energetically favorable charge transfer in the intermediate and thermodynamically favorable product formation.
Synthesizing monolayers and heterostructures is an enabling approach to extract new physical phenomena from bulk materials. Among the structures amenable to this approach is stanene, which is a monolayer of tin, similar to graphene, and has been predicted to host one-dimensional topological states at its edges. Stanene can be tuned by decorating with different adatoms, which makes it a promising platform on which to engineer topological devices. Here, we deposit Sn on Bi 2 Te 3 and characterize the growth using anomalous synchrotron x-ray scattering and x-ray photoelectron spectroscopy (XPS). X-ray diffraction data reveal the formation of epitaxial Sn-based structures, along with penetration of Sn into the Bi 2 Te 3 , with Sn intercalating between the upper 10 Bi 2 Te 3 quintuple layers. Additionally, XPS data show deposited Sn reacting to form SnTe and Bi at the Bi 2 Te 3 surface. The calculated heat of reaction for Sn and Bi2Te3 is consistent with an exothermic reaction to SnTe and Bi. Using thermodynamic calculations as a guide, we identify several candidate substrates that can stabilize the stanene phase.
The Space Physics Archive Search and Extract (SPASE) project is an international collaboration among Heliophysics (solar and space physics) groups concerned with data acquisition and archiving. Within this community there are a variety of old and new data centers, resident archives, "virtual observatories", etc. acquiring, holding, and distributing data. The main product of the SPASE group is an XML-based SPASE Data Model now in operational use to enable searches for and ultimate acquisition of data of interest to a researcher. The SPASE Data Model defines the content of resource descriptions (metadata). The intent is to describe all SCientifically usable Heliophysics data sets using the Data Model. Another product of the SPASE group, in collaboration with NASA's Virtual Observatories, is a set of tools and services which work with SPASE meta data. This includes Registry Services which can retrieve and render metadata using resource identifiers and facilitate the downloading of the data referenced by the meta data. The SPASE Data Model has also been used as a vocabulary in specialized data models. One example is the Heliophysics Event List Manager (HELM) model. The SPASE Data Model is also being expanded to provide the means for more detailed description of data sets with the aim of enabling more automated ingestion and use of the data through detailed format descriptions. The evolution is based on a number of lessons learned and feedback from our community. Some of the lessons learned are unique to Heliophysics, and some are common to the various data diSCiplines. We will discuss the present state of SPASE usage, the role the SPASE Data Model can play in speCialized data models and how we foresee the development direction in the future.
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