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DOE OSTI2023

Discovering useful genetic variation in the seed parent gene pool for sorghum improvement

Multi-parent populations contain valuable genetic material for dissecting complex, quantitative traits and provide a unique opportunity to capture multi-allelic variation compared to the biparental populations. A multi-parent advanced generation inter-cross (MAGIC) B-line (MBL) population composed of 708 F 6 recombinant inbred lines (RILs), was recently developed from four diverse founders. These selected founders strategically represented the four most prevalent botanical races (kafir, guinea, durra, and caudatum) to capture a significant source of genetic variation to study the quantitative traits in grain sorghum [Sorghum bicolor (L.) Moench]. MBL was phenotyped at two field locations for seven yield-influencing traits: panicle type (PT), days to anthesis (DTA), plant height (PH), grain yield (GY), 1000-grain weight (TGW), tiller number per meter (TN) and yield per panicle (YPP). High phenotypic variation was observed for all the quantitative traits, with broad-sense heritabilities ranging from 0.34 (TN) to 0.84 (PH). The entire population was genotyped using Diversity Arrays Technology (DArTseq), and 8,800 single nucleotide polymorphisms (SNPs) were generated. A set of polymorphic, quality-filtered markers (3,751 SNPs) and phenotypic data were used for genome-wide association studies (GWAS). We identified 52 marker-trait associations (MTAs) for the seven traits using BLUPs generated from replicated plots in two locations. We also identified desirable allelic combinations based on the plant height loci (Dw1, Dw2, and Dw3), which influences yield related traits. Additionally, two novel MTAs were identified each on Chr1 and Chr7 for yield traits independent of dwarfing genes. We further performed a multi-variate adaptive shrinkage analysis and 15 MTAs with pleiotropic effect were identified. The five best performing MBL progenies were selected carrying desirable allelic combinations. Since the MBL population was designed to capture significant diversity for maintainer line (B-line) accessions, these progenies can serve as valuable resources to develop superior sorghum hybrids after validation of their general combining abilities via crossing with elite pollinators. Further, newly identified desirable allelic combinations can be used to enrich the maintainer germplasm lines through marker-assisted backcross breeding.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Shotgun Immunoproteomic Approach for the Discovery of Linear B-Cell Epitopes in Biothreat Agents Francisella tularensis and Burkholderia pseudomallei

Peptide-based subunit vaccines are coming to the forefront of current vaccine approaches, with safety and cost-effective production among their top advantages. Peptide vaccine formulations consist of multiple synthetic linear epitopes that together trigger desired immune responses that can result in robust immune memory. The advantages of linear compared to conformational epitopes are their simple structure, ease of synthesis, and ability to stimulate immune responses by means that do not require complex 3D conformation. Prediction of linear epitopes through use of computational tools is fast and cost-effective, but typically of low accuracy, necessitating extensive experimentation to verify results. On the other hand, identification of linear epitopes through experimental screening has been an inefficient process that requires thorough characterization of previously identified full-length protein antigens, or laborious techniques involving genetic manipulation of organisms. In this study, we apply a newly developed generalizable screening method that enables efficient identification of B-cell epitopes in the proteomes of pathogenic bacteria. As a test case, we used this method to identify epitopes in the proteome of Francisella tularensis (Ft), a Select Agent with a well-characterized immunoproteome. Our screen identified many peptides that map to known antigens, including verified and predicted outer membrane proteins and extracellular proteins, validating the utility of this approach. We then used the method to identify seroreactive peptides in the less characterized immunoproteome of Select Agent Burkholderia pseudomallei (Bp). This screen revealed known Bp antigens as well as proteins that have not been previously identified as antigens. Although B-cell epitope prediction tools Bepipred 2.0 and iBCE-EL classified many of our seroreactive peptides as epitopes, they did not score them significantly higher than the non-reactive tryptic peptides in our study, nor did they assign higher scores to seroreactive peptides from known Ft or Bp antigens, highlighting the need for experimental data instead of relying on computational epitope predictions alone. The present workflow is easily adaptable to detecting peptide targets relevant to the immune systems of other mammalian species, including humans (depending upon the availability of convalescent sera from patients), and could aid in accelerating the discovery of B-cell epitopes and development of vaccines to counter emerging biological threats.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Multiplex detection and identification of viral, bacterial, and protozoan pathogens in human blood and plasma using an expanded high-density resequencing microarray platform

Introduction: Nucleic acid tests for blood donor screening have improved the safety of the blood supply; however, increasing numbers of emerging pathogen tests are burdensome. Multiplex testing platforms are a potential solution. Methods: The Blood Borne Pathogen Resequencing Microarray Expanded (BBP-RMAv.2) can perform multiplex detection and identification of 80 viruses, bacteria and parasites. This study evaluated pathogen detection in human blood or plasma. Samples spiked with selected pathogens, each with one of 6 viruses, 2 bacteria and 5 protozoans were tested on this platform. The nucleic acids were extracted, amplified using multiplexed sets of primers, and hybridized to a microarray. The reported sequences were aligned to a database to identify the pathogen. To directly compare the microarray to an emerging molecular approach, the amplified nucleic acids were also submitted to nanopore next generation sequencing (NGS). Results: The BBP-RMAv.2 detected viral pathogens at a concentration as low as 100 copies/ml and a range of concentrations from 1,000 to 100,000 copies/ml for all the spiked pathogens. Coded specimens were identified correctly demonstrating the effectiveness of the platform. The nanopore sequencing correctly identified most samples and the results of the two platforms were compared. Discussion: These results indicated that the BBP-RMAv.2 could be employed for multiplex detection with potential for use in blood safety or disease diagnosis. The NGS was nearly as effective at identifying pathogens in blood and performed better than BBP-RMAv.2 at identifying pathogen-negative samples.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Longitudinal genome-wide association study reveals early QTL that predict biomass accumulation under cold stress in sorghum

Sorghum bicolor is a promising cellulosic feedstock crop for bioenergy due to its high biomass yields. However, early growth phases of sorghum are sensitive to cold stress, limiting its planting in temperate environments. Cold adaptability is crucial for cultivating bioenergy and grain sorghum at higher latitudes and elevations, or for extending the growing season. Identifying genes and alleles that enhance biomass accumulation under early cold stress can lead to improved sorghum varieties through breeding or genetic engineering. We conducted image-based phenotyping on 369 accessions from the sorghum Bioenergy Association Panel (BAP) in a controlled environment with early cold treatment. The BAP includes diverse accessions with dense genotyping and varied racial, geographical, and phenotypic backgrounds. Daily, non-destructive imaging allowed temporal analysis of growth-related traits and water use efficiency (WUE). A genome-wide association study (GWAS) was performed to identify genomic intervals and genes associated with cold stress response. The GWAS identified transient quantitative trait loci (QTL) strongly associated with growth-related traits, enabling an exploration of the genetic basis of cold stress response at different developmental stages. This analysis of daily growth traits, rather than endpoint traits, revealed early transient QTL predictive of final phenotypes. The study identified both known and novel candidate genes associated with growth-related traits and temporal responses to cold stress. The identified QTL and candidate genes contribute to understanding the genetic mechanisms underlying sorghum's response to cold stress. These findings can inform breeding and genetic engineering strategies to develop sorghum varieties with improved biomass yields and resilience to cold, facilitating earlier planting, extended growing seasons, and cultivation at higher latitudes and elevations.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Investigation and Expression Analysis of R2R3-MYBs and Anthocyanin Biosynthesis-Related Genes during Seed Color Development of Common Bean ( Phaseolus vulgaris )

Anthocyanins are responsible for the coloration of common bean seeds, and their accumulation is positively correlated with the expression level of anthocyanin biosynthetic genes. The MBW (MYB-bHLH-WD40) complex is thought to regulate the expression of these genes, and MYB proteins, which are a key factor in activating anthocyanin pathway genes, have been identified in several plants. This study demonstrated gene structures, chromosomal placements, gene duplications of R2R3-MYBs, miRNAs associated with R2R3-MYBs, and the interaction of these genes with other flavonoid regulatory genes. qRT-PCR was used to investigate the role of specific R2R3-MYBs and flavonoid genes in common bean seed color development. As a result of a comprehensive analysis with the help of in silico tools, we identified 160 R2R3-MYB genes in the common bean genome. We divided these genes into 16 classes on the basis of their intron-exon and motif structures. Except for three, the rest of the common bean R2R3-MYB members were distributed to all chromosomes with different densities, primarily located on chromosomes 3 and 8. We identified a total of 44 duplicated gene pairs dispersed across 11 chromosomes and evolved under purifying selection (Ka/Ks < 1), 19 of which were derived from a whole-genome duplication. Our research uncovered 25 putative repressor PvMYB proteins that contain the EAR motif. Additionally, fifty different cis-regulatory elements regulated by light, stress, and hormone were identified. Within the genome of the common bean, we discovered a total of 36 microRNAs that target a total of 72 R2R3-MYB transcripts. The effect of 16 R2R3-MYB genes and 16 phenylpropanoid pathway genes, selected on the basis of their interaction in the protein-protein interaction map, playing role in the regulation of seed coat color development was evaluated using qRT-PCR in 5 different tissues at different developmental stages. The results revealed that these specific genes have different expression levels during different developmental periods, with higher levels in the pod filling and early pod stages than in the rest of the developmental periods. Furthermore, it was shown that PvTT8 (bHLH), PvTT2 (PvMYB42), PvMYB113, PvTTG1, and PvWD68 genes have effects on the regulation of seed coat color. The findings of this study, which is the first to use whole-genome analysis to identify and characterize the R2R3-MYB genes in common bean, may serve as a reference for future functional research in the legume.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Unlocking Manufacturing Sustainability: Energy Efficiency Opportunities through the US Department of Energy’s Better Plants Program Energy Treasure Hunts (2023–2024)

The US manufacturing sector faces critical challenges: improving sustainability, reducing energy consumption, and reducing greenhouse gas emissions. Energy Treasure Hunt (ETH) training, a service provided by the US Department of Energy’s Better Plants program, offers a compelling solution. Although ETHs have traditionally focused on energy and cost savings, data indicate that ETHs can be used to identify opportunities to reduce emissions and water use and to support a sustainable and circular operation. These 3-day on-site events engage employees in a collaborative search for operational and maintenance efficiency improvement opportunities. The success of ETHs lies in a comprehensive methodology. Each phase in an ETH uses various tools and resources to empower employees to identify practical solutions. This study presents data from 13 ETHs conducted between 2023 and 2024 across diverse manufacturing subsectors in the United States and demonstrates that the events can help create a pragmatic decarbonization pathway. Through the events, a total of 234 energy and emissions reduction opportunities were identified, and the potential impact is significant. Implementing the recommendations could translate to annual savings of 497,299 MMBtu of energy, 64,374 kgal of water, and 4.85 million tCO 2 e of emissions. The fiscal savings from the proposed recommendations translate into nearly $\$$5 million annually. This study identifies the opportunities by energy system type and by the specific actions recommended, while also analyzing the identified opportunities, presenting the most established sustainability recommendations. Case studies from participating partners are presented to further demonstrate that ETHs provide a practical and impactful approach to reducing energy consumption, emissions, and operating costs and promote a more sustainable future for the industrial sector.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

A Census of Star Formation in the Outer Galaxy. II. The GLIMPSE360 Field

We have conducted a study of star formation in the outer Galaxy from 65°< l < 265° in the region observed by the GLIMPSE360 program. This Spitzer warm mission program mapped the plane of the outer Milky Way with IRAC at 3.6 and 4.5 μm. We combine the IRAC, Wide-field Infrared Survey Explorer (WISE), and Two Micron All Sky Survey catalogs and our previous results from another outer Galaxy survey and identify a total of 47,338 young stellar objects (YSOs) across the field spanning >180° in Galactic longitude. Using the DBSCAN method on the combined catalog, we identify 618 clusters or aggregations of YSOs having five or more members. We identify 10,476 class I, 29,604 class II, and 7325 anemic class II/class III YSOs. The ratio of YSOs identified as members of clusters was 25,528/47,338, or 54%. We found that 100 of the clusters identified have previously measured distances in the WISE H ii survey. We used these distances in our spectral energy distribution (SED) fitting of the YSOs in these clusters, of which 96 had YSOs with <3σ fits. We used the derived masses from the SED model fits to estimate the initial mass function (IMF) in the inner and outer Galaxy clusters; dividing the clusters by galactocentric distances, the slopes were Γ = 1.87 ± 0.31 above 3 M {sub ⊙} for R {sub Gal} < 11.5 kpc and Γ = 1.15 ± 0.24 above 3 M {sub ⊙} for R {sub Gal} > 11.5 kpc. The slope of the combined IMF was found to be Γ = 1.92 ± 0.42 above 3 M {sub ⊙}. These values are consistent with each other within the uncertainties and with literature values in the inner Galaxy high-mass star formation regions. The slopes are likely also consistent with a universal Salpeter IMF.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Variable Active Galactic Nuclei in the Galaxy Evolution Explorer Time Domain Survey

We searched the northern hemisphere fields of the Galaxy Evolution Explorer Time Domain Survey for galaxies with UV variability indicative of active galactic nuclei (AGNs). We identified 48 high-probability candidate AGNs from a parent sample of 1819 galaxies in the NASA Sloan Atlas catalog. We further characterized these systems using optical spectroscopic diagnostics, Wide-field Infrared Survey Explorer IR color selection criteria, and spectral energy distribution modeling. Of the 48 candidates, eight were identified as AGNs from optical emission lines, two were identified by their IR colors, and 28 were identified through spectral energy decomposition. Observational biases of each selection method are discussed in connecting these AGN subsamples to another. By selecting AGNs based on UV variability, we also identified six low-mass AGN candidates, all of which would have been missed by spectroscopic selection.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

A Multiwavelength Study of Active Galactic Nuclei in Post-merger Remnants

Here, we investigate the role of galaxy mergers in triggering active galactic nuclei (AGN) in the nearby universe. Our analysis is based on a sample of 79 post-merger remnant galaxies with deep X-ray observations from Chandra/XMM-Newton capable of detecting a low-luminosity AGN of ≥10 40.5 erg s -1 . This sample is derived from a visually classified, volume-limited sample of 807 post-mergers identified in the Sloan Digital Sky Survey Data Release 14 with log M * /M ⊙ ≥ 10.5 and 0.02 ≤ z ≤ 0.06. We find that the X-ray AGN fraction in this sample is 55.7% ± 5.6% compared to 23.6% ± 2.8% for a mass- and redshift-matched noninteracting control sample. The multiwavelength AGN fraction (identified as an AGN in one of X-ray, IR, radio or optical diagnostics) for post-mergers is 76.6% ± 4.8% compared to 39.1% ± 3.2% for controls. Thus post-mergers exhibit a high overall AGN fraction with an excess between 2 and 4 depending on the AGN diagnostics used. In addition, we find most optical, IR, and radio AGN are also identified as X-ray AGN while a large fraction of X-ray AGN are not identified in any other diagnostic. This highlights the importance of deep X-ray imaging to identify AGN. We find that the X-ray AGN fraction of post-mergers is independent of the stellar mass above log M * /M ⊙ ≥ 10.5 unlike the trend seen in control galaxies. Overall, our results show that post-merger galaxies are a good tracer of the merger–AGN connection and strongly support the theoretical expectations that mergers trigger AGN.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Ch3MS-RF: a random forest model for chemical characterization and improved quantification of unidentified atmospheric organics detected by chromatography–mass spectrometry techniques

Abstract. The chemical composition of ambient organic aerosols plays a critical role in driving their climate and health-relevant properties and holds important clues to the sources and formation mechanisms of secondary aerosol material. In most ambient atmospheric environments, this composition remains incompletely characterized, with the number of identifiable species consistently outnumbered by those that have no mass spectral matches in the literature or the National Institute of Standards and Technology/National Institutes of Health/Environmental Protection Agency (NIST/NIH/EPA) mass spectral databases, making them nearly impossible to definitively identify. This creates significant challenges in utilizing the full analytical capabilities of techniques which separate and generate spectra for complex environmental samples. In this work, we develop the use of machine learning techniques to quantify and characterize novel, or unidentifiable, organic material. This work introduces Ch3MS-RF (Chemical Characterization by Chromatography–Mass Spectrometry Random Forest Modeling), an open-source, R-based software tool, for efficient machine-learning-enabled characterization of compounds separated in chromatography–mass spectrometry applications but not identifiable by comparison to mass spectral databases. A random forest model is trained and tested on a known 130 component representative external standard to predict the response factors of novel environmental organics based on position in volatility–polarity space and mass spectrum, enabling the reproducible, efficient, and optimized quantification of novel environmental species. Quantification accuracy on a reserved 20 % test set randomly split from the external standard compound list indicates that random forest modeling significantly outperforms the commonly used methods in both precision and accuracy, with a median response factor percent error of −2 %, for modeled response factors, compared to > 15 %, for typically used proxy assignment-based methods. Chemical properties modeling, evaluated on the same reserved 20 % test set and an extrapolation set of species identified in ambient organic aerosol samples collected in the Amazon rainforest, also demonstrate robust performance. Extrapolation set property prediction mean absolute errors for carbon number, oxygen to carbon ratio (O : C), average carbon oxidation state (OSc‾), and vapor pressure are 1.8, 0.15, 0.25, and 1.0 (log(atm)), respectively. Extrapolation set out-of-sample R2 for all properties modeled are above 0.75, with the exception of vapor pressure. While predictive performance for vapor pressure is less robust compared to the other chemical properties modeled, random-forest-based modeling was significantly more accurate than other commonly used methods of vapor pressure prediction, decreasing the mean vapor pressure prediction error to 0.24 (log(atm)) from 0.55 (log(atm)) (chromatography-based vapor pressure prediction) and 1.2 (log(atm)) (chemical formula-based vapor pressure prediction). The random forest model significantly advances an untargeted analysis of the full scope of chemical speciation yielded by two-dimensional gas chromatography (GCxGC-MS) techniques and can be applied to gas chromatography coupled with electron ionization mass spectrometry (GC-MS) as well. It enables the accurate estimation of key chemical properties commonly utilized in the atmospheric chemistry community, which may be used to more efficiently identify important tracers for further individual analysis and to characterize compound populations uniquely formed under specific ambient conditions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

HarDWR - Cumulative Water Rights Curves

For a detailed description of the database of which this record is only one part, please see the HarDWR meta-record. This product is the dataset used as input to the WBM model (Grogan et al., in review; Grogan et al. 2022), and is the result of the step creating cumulative water rights curves described in Lisk et al. (submission pending). This database contains 1,744 individual .csv files, two for each Water Management Area (WMA; see here) in the 11-state region. File naming convention: WMA_[###]_[X]W.csv, where [###] is the unique identifier for each WMA, and [X] is either S for surface water rights, or G for groundwater rights. Column headers in each file: Year: the priority date year CUML: the total cumulative water rights allocated up to this priority date year (ft3s-1) Irrigation: The percent of cumulative water rights allocated to the Irrigation category up to this priority date year (%) Domestic: The percent of cumulative water rights allocated to the Domestic category up to this priority date year (%) Livestock: The percent of cumulative water rights allocated to the Livestock category up to this priority date year (%) Fish: The percent of cumulative water rights allocated to the Fish category up to this priority date year (%) Industrial: The percent of cumulative water rights allocated to the Industrial category up to this priority date year (%) Environmental: The percent of cumulative water rights allocated to the Environmental category up to this priority date year (%) Other: The percent of cumulative water rights allocated to the Other category up to this priority date year (%) In addition to the database files, there is a companion .csv file, called stateWMAs_ID.csv. The main purpose of this file is to provide the means of translating between the ### unique identifier and the various other id of the WMA the file is attached to. This translation file has five columns, which are: basinNum: The official state given alpha-numeric identifier of the WMA basinName: the state provided English name of the area, where applicable state: the state name uniID: a unique identifier we created by concatenating the state name, and underscore, and the state numerical ID ID: a unique numeric identifier we created as a requirement for the files to be used within WBM (Grogan et al., in review)

Economics↗

DOE OSTI2024

HarDWR - Cumulative Water Rights Curves

Economics↗

DOE OSTI2020

HarDWR - Cumulative Water Rights Curves

A dataset within the Harmonized Database of Western U.S. Water Rights (HarDWR). For a detailed description of the database, please see the meta-record v2.0. Changelog v2.0 - Recalculated based on Harmonized Water Rights Records v2.0 sourced from WestDAAT - Added "Unspecified" was a water source category, and files associated with this category v1.01 - Updated the names of each file with an ID number less than 3 digits to include leading 0s v1.0 - Initial public release Description This product an updated version of the database used as input to the WBM model (Grogan et al. in review; Grogan et al. 2022), and is the result of the step creating cumulative water rights curves described in Lisk et al. (2024). This database contains 2,667 individual .csv files, three for each Water Management Area (WMA) in the 11-state region. File Naming WMA_[###]_[X]W.csv, where [###] is the unique identifier for each WMA, and [X] is either "S" for surface water rights, "G" for groundwater rights, or "U" for unspecified. Column headers in each file: Year: the priority date year CUML: the total cumulative water rights allocated up to this priority date year (ft3s-1) Irrigation: The percent of cumulative water rights allocated to the Irrigation category up to this priority date year (%) Domestic: The percent of cumulative water rights allocated to the Domestic category up to this priority date year (%) Livestock: The percent of cumulative water rights allocated to the Livestock category up to this priority date year (%) Fish: The percent of cumulative water rights allocated to the Fish category up to this priority date year (%) Industrial: The percent of cumulative water rights allocated to the Industrial category up to this priority date year (%) Environmental: The percent of cumulative water rights allocated to the Environmental category up to this priority date year (%) Other: The percent of cumulative water rights allocated to the Other category up to this priority date year (%) In addition to the database files, there is a companion .csv file, called stateWMAs_ID.csv. The main purpose of this file is to provide the means of translating between the [###] unique identifier and the various other id of the WMA the file is attached to. This translation file has five columns, which are: basinNum: The official state given alpha-numeric identifier of the WMA basinName: the state provided English name of the area, where applicable state: the state name uniID: a unique identifier we created by concatenating the state name, and underscore, and the state numerical ID ID: a unique numeric identifier we created as a requirement for the files to be used within WBM (Grogan et al. in review) For those whom may be interested in exploring our code more in depth, we are also making available an internal data file for convenience. The file is in .RData format and contains everything described above as well as some minor additional objects used within the code calculating the cumulative curves. For completeness, here is a detailed description of the various objects which can be found within the .RData file: states: A character vector containing the state names for those states in the study region. More importantly, the index of the state name is also the index in which that state's data can be found in the various following list objects. For example, if California is the second index in this object, the data for California will also be in the second index for each accompanying list. wmasRightsPersGrd: A list of nested lists of data frames. Each state has one entry in the top level list and consist of a list with one data frame per WMA. The data frames in this object are the same as the above described .csv files, specifically for groundwater. wmasRightsPersSur: A list of nested lists of data frames. Each state has one entry in the top level list and consist of a list with one data frame per WMA. The data frames in this object are the same as the above described .csv files, specifically for surface water. wmasRightsPersUnsp: A list of nested lists of data frames. Each state has one entry in the top level list and consist of a list with one data frame per WMA. The data frames in this object are the same as the above described .csv files, specifically for water from an unspecified source. wmasRightsTotsGrd: A list of nested lists of data frames. Each state has one entry in the top level list and consist of a list with one data frame per WMA. The values in the data frames of this object would be the equivalent to multiplying the CUML column by the sector percentage columns to create the sector total ft3s-1, specifically for groundwater. This object is provided for convenience to check out original total values, if desired. wmasRightsTotsSur: A list of nested lists of data frames. Each state has one entry in the top level list and consist of a list with one data frame per WMA. The values in the data frames of this object would be the equivalent to multiplying the CUML column by the sector percentage columns to create the sector total ft3s-1, specifically for surface water. This object is provided for convenience to check out original total values, if desired. wmasRightsTotsUnsp: A list of nested lists of data frames. Each state has one entry in the top level list and consist of a list with one data frame per WMA. The values in the data frames of this object would be the equivalent to multiplying the CUML column by the sector percentage columns to create the sector total ft3s-1, specifically for water from an unspecified source. This object is provided for convenience to check out original total values, if desired. wmaIDByState: A list of data frames which contain the by state allocation by WMA matrix. There is a matrix for each state in a different data frame within the object.

Economics↗

NASA NTRS1973

Urban and regional land use analysis: CARETS and Census Cities experiment package

The author has identified the following significant results. Areas of post 1970 and 1972 land use changes were identified solely from the Skylab imagery from comparisons with 1970 land use maps. Most land use changes identified involved transition from agriculture to single family residential land use. The second most prominent changes identified from the Skylab imagery were areas presently under construction. Post 1970 changes from Skylab were compared with the 1972 changes noted from the high altitude photographs. A good correlation existed between the change polygons mapped from Skylab and those mapped from the 1972 high altitude aerial photos. In addition, there were a number of instances where additional built-up land use not noted in the 1972 aerial photo as being developed were identified on the Skylab imagery. While these cases have not been documented by field observation, by correlating these areas with the appearance of similar land use areas whose identity has been determined, we can safely say that we have been able to map further occurrences of land use change beyond existing high altitude photo coverage from the Skylab imagery. It was concluded that Skylab data can be used to detect areas of land use change within an urban setting.

Alexander, R. H.↗

NASA NTRS1974

Helicopter derivative identification from analytic models and flight test data

Recent results of stability derivative identification from helicopter analytic models and flight test data are presented. Six and nine degree-of-freedom (DOF) linear models are identified from an analytic nonlinear helicopter simulation using a least square technique. The identified models are compared with the convectional partial differentiation method for obtaining derivatives to form the basis for interpretation of derivatives identified from flight data. Six degree-of-freedom models are identified from CH-53A and CH-54B flight data, using an extended Kalman filter modified to process several maneuvers simultaneously. The a priori derivative estimate is obtained by optimal filtering of the data and then using a least square method. The results demonstrate that a six DOF identified model is sufficient to determine the low frequency modes of motion, but a nine DOF rotor/body model is necessary for proper representation of short-term response.

Molusis, J. H.↗

NASA NTRS1974

Land use mapping in Erie County, Pennsylvania: A pilot study

The author has identified the following significant results. A pilot study was conducted to determine the feasibility of mapping land use in the Great Lakes Basin area utilizing ERTS-1 data. Small streams were clearly defined by the presence of trees along their length in predominantly agricultural country. Field patterns were easily differentiated from forested areas; dairy and beef farms were differentiated from other farmlands, but no attempt was made to identify crops. Large railroad lines and major highway systems were identified. The city of Erie and several smaller towns were identified, as well as residential areas between these towns, and docks along the shoreline in Erie. Marshes, forests, and beaches within Presque Isle State Park were correctly identified, using the DCLUS program. Bay water was differentiated from lake water, with a small amount of misclassification.

Mcmurtry, G. J.↗

NASA NTRS1978

26.3 MHz radio source survey. III - Correlation with extragalactic X-ray sources

The correlation between extragalactic X-ray sources and radio sources in a 26.3-MHz catalog is studied. A list of reliably identified sources is developed by examining X-ray, optical, and radio data for those candidate objects that are in or near the X-ray error boxes. The source 3UR 0432+05 is identified with 3C 120, 3UR 1555+27 (identified with A2142) is shown to be a steep-spectrum radio source, and it is found that 86% of the high-galactic-latitude sources can be reliably identified when the X-ray source error areas are no more than 1 sq deg. The results also indicate that: (1) X-ray sources identified with clusters of galaxies as a whole, with individual galaxies in clusters, and with separate isolated galaxies have similar decametric properties in that their spectral indices and radio luminosities fall in the same range; (2) there is a Bautz-Morgan dependence of both the X-ray and the decametric luminosities of clusters and of individual objects in clusters; and (3) the X-ray luminosity of all except compact sources appears to be approximately proportional to the decametric luminosity.

Erickson, W. C.↗

NASA NTRS1980

First Scientific Working Group Meeting of Airborne Doppler Lidar Wind Velocity Measurement Program

The purpose of the first scientific working group meeting was fourfold: (1) to identify flight test options for engineering verification of the MSFC Doppler Lidar; (2) to identify flight test options for gathering data for scientific/technology applications; (3) to identify additional support equipment needed on the CV 990 aircraft for the flight tests; and (4) to identify postflight data processing and data sets requirements. The working group identified approximately ten flight options for gathering data on atmospheric dynamics processes, including turbulence, valley breezes, and thunderstorm cloud anvil and cold air outflow dynamics. These test options will be used as a basis for planning the fiscal year 1981 tests of the Doppler Lidar system.

Kaufman, J. W.↗