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At least 505 records · Page 28

Robot Acquisition of Active Maps Through Teleoperation and Vector Space Analysis

The work performed under this contract was in the area of intelligent robotics. The problem being studied was the acquisition of intelligent behaviors by a robot. The method was to acquire action maps that describe tasks as sequences of reflexive behaviors. Action maps (a.k.a. topological maps) are graphs whose nodes represent sensorimotor states and whose edges represent the motor actions that cause the robot to proceed from one state to the next. The maps were acquired by the robot after being teleoperated or otherwise guided by a person through a task several times. During a guided task, the robot records all its sensorimotor signals. The signals from several task trials are partitioned into episodes of static behavior. The corresponding episodes from each trial are averaged to produce a task description as a sequence of characteristic episodes. The sensorimotor states that indicate episode boundaries become the nodes, and the static behaviors, the edges. It was demonstrated that if compound maps are constructed from a set of tasks then the robot can perform new tasks in which it was never explicitly trained.

Peters, Richard Alan, II↗

Bleach Rescues Nannochloropsis from an Obligate Parasite and Alters Microbial and Metabolite Signatures of Outdoor Cultures

Chemical agents are commonly used to protect algal crops. Yet, few studies have characterized the effects of these agents on associated microbial communities to understand effects on microbial functions relevant to algal crop production and protection. Here, we used shotgun metagenomic sequencing and untargeted exometabolite profiling to link the application of bleach, a -cidal agent used to protect algae from pests, to changes in community composition, metabolic pathways, and exometabolies - at a whole community level. Bleach protected the algal crop from crashing but altered bacterial diversity. Analysis of metagenome-assembled genomes (MAGs) revealed a classic predator-prey cycle between Oligoflexus and our target alga Nannochloropsis. Olifoflexus genomes from our study were notably similar to a previously identified BALO (Bdellovibrio and like organism), FD111, known to kill Nannochloropsis cultures, providing strong evidence that an FD111-like organism was responsible for the crash. Metabolic pathway composition differed between bleached and unbleached ponds, with abundance of twelve pathways related to stress tolerance, including the superpathway of methylglyoxal degradation, lipid IVA biosynthesis, and ectoine biosynthesis, greater in bleached ponds compared to unbleached ponds. Virulence factors related to adherence, biofilm formation, motility, and pathogenicity increased dramatically in bleached ponds with time, although this increase was not coupled with an increase in pathogens - algal or otherwise - or a decline in algal health. Our study highlights the importance of coupling 16S rRNA gene sequencing with whole genome data and other -omics tools to sketch a larger picture of community structure and function in crop systems. Moreover, our results highlight that continued long-term bleaching may lead to negative effects to crop health or downstream adverse health effects to humans or animals, depending on the algal product (i.e. human supplements or animal feedstocks). Future work on alternative treatment methods that would reduce resistance is necessary in the field.

09 BIOMASS FUELS↗

Automated mesoscale winds derived from GOES multispectral imagery

An automated technique for extracting mesoscale winds from sequences of GOES visible infrared spin scan radiatiometer (VISSR) image pairs has been developed, tested extensively, and configured for quasi-real time research applications on the Atmospheric Sciences Division's research computing sytem. The entire system of computer codes was successfully vectorized for execution on an array processor resulting in job turnaround in less than 1 hour. An objective quality control system provides much greater than 99 percent accuracy in eliminating questionable wind estimates. Dynamical analysis of cloud wind divergence has revealed temporally consistent convergence centers on the meso-beta scale that are highly correlated with ongoing and future developing convective storms.

Wilson, G. S.↗

The Role of Rotation in the Evolution of Massive Stars

Recent evolutionary models of massive stars predict important effects of rotation including: increasing the rate of mass-loss; lowering the effective gravity; altering the evolutionary track on the HRD; extending the main-sequence phase (both on the HR diagram and in time); and mixing of CNO-processed elements up to the stellar surface. Observations suggest that rotation is a more important factor at lower metallicities because of higher initial rotational velocities and weaker winds. This makes the SMC, a low-metallicity galaxy (Z= 0.2 solar Z), an excellent environment for discerning the role of rotation in massive stars. We report on a FUSE + STIS + optical spectral analysis of 17 O-type stars in the SMC, where we found an enormous range in N abundances. Three stars in the sample have the same (low) CN abundances as the nebular material out of which they formed, namely C = 0.085 solar C and N = 0.034 solar N. However, more than half show N approx. solar N, an enrichment factor of 30X! Such unexpectedly high levels of N have ramifications for the evolution of massive stars including precursors to supernovae. They also raise questions about the sources of nitrogen in the early universe.

Heap, Sara R.↗

Deep-Learning-Derived Evaluation Metrics Enable Effective Benchmarking of Computational Tools for Phosphopeptide Identification

Tandem mass spectrometry (MS/MS)-based phosphoproteomics is a powerful technology for global phosphorylation analysis. However, applying four computational pipelines to a typical mass spectrometry (MS)-based phosphoproteomic dataset from a human cancer study, we observed a large discrepancy among the reported phosphopeptide identification and phosphosite localization results, underscoring a critical need for benchmarking. While efforts have been made to compare performance of computational pipelines using data from synthetic phosphopeptides, evaluations involving real application data have been largely limited to comparing the numbers of phosphopeptide identifications due to the lack of appropriate evaluation metrics. We investigated three deep learning-derived features as potential evaluation metrics: phosphosite probability, Delta RT and spectral similarity. Predicted phosphosite probability is computed by MusiteDeep, which provides high accuracy as previously reported; Delta RT is defined as the absolute retention time (RT) difference between RTs observed and predicted by AutoRT; and spectral similarity is defined as the Pearson’s correlation coefficient between spectra observed and predicted by pDeep2. Using a synthetic peptide dataset, we found that both Delta RT and spectral similarity provided excellent discrimination between correct and incorrect peptide-spectrum matches (PSMs) both when incorrect PSMs involved wrong peptide sequences and even when incorrect PSMs were caused by only incorrect phosphosite localization. Based on these results, we used all the three deep learning-derived features as evaluation metrics to compare different computational pipelines on diverse set of phosphoproteomic datasets and showed their utility in benchmarking performance of the pipelines. The benchmark metrics demonstrated in this study will enable users to select computational pipelines and parameters for routine analysis of phosphoproteomics data and will offer guidance for developers to improve computational methods.

59 BASIC BIOLOGICAL SCIENCES↗

RSM 1.0 user's guide: A resupply scheduler using integer optimization

The Resupply Scheduling Model (RSM) is a PC based, fully menu-driven computer program. It uses integer programming techniques to determine an optimum schedule to replace components on or before a fixed replacement period, subject to user defined constraints such as transportation mass and volume limits or available repair crew time. Principal input for RSJ includes properties such as mass and volume and an assembly sequence. Resource constraints are entered for each period corresponding to the component properties. Though written to analyze the electrical power system on the Space Station Freedom, RSM is quite general and can be used to model the resupply of almost any system subject to user defined resource constraints. Presented here is a step by step procedure for preparing the input, performing the analysis, and interpreting the results. Instructions for installing the program and information on the algorithms are given.

Viterna, Larry A.↗

Principal modes of variation of rain-rate probability distributions

Radar or satellite observations of an area generate sequences of rain-rate maps. From a gridded map a histogram of rain rates can be obtained representing the relative areas occupied by rain rates of various strengths. The histograms vary with time as precipitating systems in the area evolve and decay and amounts of convective and stratiform rain in the area change. A method of decomposing the histograms into linear combinations of a few empirical distributions with time-dependent coefficients is developed, using principal component analysis as a starting point. When applied to a tropical Atlantic dataset (GATE), two distributions emerge naturally from the analysis, resembling stratiform and convective rain-rate distributions in that they peak at low and high rain rates, respectively. The two 'modes' have different timescales and only the high-rain-rate mode has a statistically significant diurnal cycle. The ability of just two modes to describe rain variabiltiy over an area can explain why methods of estimating area-averaged rain rate from the area covered by rain rates above a certain threshold are so successful.

Bell, Thomas L.↗

Evaluation of genetic diversity, agronomic traits, and anthracnose resistance in the NPGS Sudan Sorghum Core collection

The United States Department of Agriculture (USDA) National Plant Germplasm System (NPGS) sorghum core collection contains 3011 accessions randomly selected from 77 countries. Genomic and phenotypic characterization of this core collection is necessary to encourage and facilitate its utilization in breeding programs and to improve conservation efforts. In this study, we examined the genome sequences of 318 accessions belonging to the NPGS Sudan sorghum core set, and characterized their agronomic traits and anthracnose resistance response. We identified 183,144 single nucleotide polymorphisms (SNPs) located within or in proximity of 25,124 annotated genes using the genotyping-by-sequencing (GBS) approach. The core collection was genetically highly diverse, with an average pairwise genetic distance of 0.76 among accessions. Population structure and cluster analysis revealed five ancestral populations within the Sudan core set, with moderate to high level of genetic differentiation. In total, 171 accessions (54%) were assigned to one of these populations, which covered 96% of the total genomic variation. Genome scan based on Tajima’s D values revealed two populations under balancing selection. Phenotypic analysis showed differences in agronomic traits among the populations, suggesting that these populations belong to different ecogeographical regions. A total of 55 accessions were resistant to anthracnose; these accessions could represent multiple resistance sources. Genome-wide association study based on fixed and random model Circulating Probability (farmCPU) identified genomic regions associated with plant height, flowering time, panicle length and diameter, and anthracnose resistance response. Integrated analysis of the Sudan core set and sorghum association panel indicated that a large portion of the genetic variation in the Sudan core set might be present in breeding programs but remains unexploited within some clusters of accessions. The NPGS Sudan core collection comprises genetically and phenotypically diverse germplasm with multiple anthracnose resistance sources. Population genomic analysis could be used to improve screening efforts and identify the most valuable germplasm for breeding programs. The new GBS data set generated in this study represents a novel genomic resource for plant breeders interested in mining the genetic diversity of the NPGS sorghum collection.

59 BASIC BIOLOGICAL SCIENCES↗

Genomic dissection of anthracnose resistance response in sorghum [Sorghum bicolor (L.) Moench]

Sorghum [Sorghum bicolor (L.) Moench] is the fifth most important grain crop behind maize, wheat, rice, and barley. Today, it is of interest as a source of fermentable sugars for the production of renewable fuels and chemicals, and as a source of biomass for co-firing. The productivity and profitability of sorghum are limited by several biotic constraints, most notably anthracnose caused by the fungal pathogen Colletotrichum sublineolum. The most cost-effective and environmentally benign strategy to control anthracnose is through the incorporation of resistance genes. Over the last three years, our research efforts have been directed to identify new sources of resistance in temperate adapted and tropical germplasm, and to delimited genomic regions associated with the observe anthracnose resistant response. Three biparental mapping populations derived from the resistant lines SC112-14, QL3 and IS18760 were evaluated for anthracnose resistance response in Texas, Georgia, Florida and Puerto Rico. In parallel, three high density recombination maps were constructed and used to identify resistant loci. Anthracnose resistant response in line SC112-14 is controlled by a major locus on chromosome 5. Segregation analysis of 1,500 progenies delimited the resistance locus on chromosome 5 to a 23-kb region harboring three candidate genes, including Sobic.005G17230 identified by GWAS of the sorghum association panel (SAP). The latter gene belongs to a family of genes encoding F-box proteins indicating that this resistance response involved in signaling cascades and transcriptional reprograming, rather than recognition of pathotype-associated molecular patterns. In contrast, anthracnose resistant response in lines QL3 and IS18760 is controlled by multiple small-effect genes. Greenhouse evaluation of a representative subset of the three mapping populations against nine pathotypes found that lines susceptible in the field could be resistant to a single pathotype in the greenhouse. Thus, the activation of a resistance response system by a single pathotype could not provide a broader resistance response against multiple pathotypes. The screening of 1,801 sweet sorghum accessions from the National Plant Germplasm System identified 654 accessions with Brix value larger than 10, which in turn was used to select a subset of 233 accessions for evaluation of anthracnose resistant response. Even though most of the accessions were not completely infected by anthracnose, 28 accessions were completely resistant against pathotypes from Texas, Georgia, Florida and Puerto Rico. Genotyping-by-sequencing analysis of this subset identified 157,843 single nucleotide polymorphisms. Population structure analysis of the subset based on a subset of 2,345 unlinked SNPs found that the genetic diversity could be divided into four populations. The genetic relatedness among accessions within populations suggests most of the resistant germplasm may contain few different resistance sources. These resistance sources present in sweet sorghum germplasm could expedite the development of new resistant sweet sorghum cultivars and hybrids by avoiding time-consuming introgression breeding approaches with non-sweet sorghums serving as donor of the resistance alleles.

59 BASIC BIOLOGICAL SCIENCES↗

Simulation-Based Recovery Action Analysis Using the EMRALD Dynamic Risk Assessment Tool

A recovery action is defined as the action that prevents deviant conditions from producing unwanted effects. It generally indicates a kind of countermeasure performed in response to a failure of human action. The recovery actions especially play an important role in complex systems like nuclear power plants (NPPs), which consist of highly sophisticated controllers to ensure that desired performance and safety must be achieved and maintained. This is because a combination of human error and its recovery failure may be able to cause a catastrophic effect on a system. Analyzing recovery actions has been a critical part of HRA, which is a technique to evaluate human errors and provide human error probabilities (HEPs) for application in probabilistic safety assessment (PSA). If recovery actions are not adequately analyzed and applied to PSA models, the PSA results may be under-estimated or be not able to reasonably account for the failure of human actions in the context of PSA. For this reason, some regulatory documents such as ASME/ANS RA-Sb-2013 by the American Society for Mechanical Engineers and the American Nuclear Society and NUREG-1792 by U.S. Nuclear Regulatory Commission have emphasized the importance of recovery analysis within the HRA. A couple of existing HRA methods, such as the Technique for Human Error-Rate Prediction (THERP), the Cause-Based Decision Tree (CBDT), and the Korean Standard HRA (K-HRA), have respectively suggested their own approaches to the HRA recovery analysis. However, there are a couple of limitations to treating recovery actions using only the current HRA methods available. The biggest limitation is that the existing recovery analysis does not explicitly consider a variety of recovery action types and recovery sequences as they occur in actual NPPs. To handle the limitations of existing recovery analysis, this study proposes a simulation-based recovery analysis method using the Event Modeling Risk Assessment Using Linked Diagram (EMRALD) software. The EMRALD software is a dynamic simulation tool for PSA. It supports realistic and dynamic modeling of human actions as they would be performed at NPPs. It is also favorable to simultaneously model the specific moment at which an action is performed, the time it takes to perform the action, and the failure probability of that action. In this paper, a detailed methodology for modeling recovery actions in the simulation platform is proposed with a couple of examples. Then, outputs from the simulation are discussed as reviewing if this novel approach can complement the challenges of existing recovery analyses.

99 GENERAL AND MISCELLANEOUS↗

Short-interval SMS wind vector determinations for a severe local storms area

Short-interval SMS-2 visible digital image data are used to derive wind vectors from cloud tracking on time-lapsed sequences of geosynchronous satellite images. The cloud tracking areas are located in the Central Plains, where on May 6, 1975 hail-producing thunderstorms occurred ahead of a well defined dry line. Cloud tracking is performed on the Goddard Space Flight Center Atmospheric and Oceanographic Information Processing System. Lower tropospheric cumulus tracers are selected with the assistance of a cloud-top height algorithm. Divergence is derived from the cloud motions using a modified Cressman (1959) objective analysis technique which is designed to organize irregularly spaced wind vectors into uniformly gridded wind fields. The results demonstrate the feasibility of using satellite-derived wind vectors and their associated divergence fields in describing the conditions preceding severe local storm development. For this case, an area of convergence appeared ahead of the dry line and coincided with the developing area of severe weather. The magnitude of the maximum convergence varied between -10 to the -5th and -10 to the -14th per sec. The number of satellite-derived wind vectors which were required to describe conditions of the low-level atmosphere was adequate before numerous cumulonimbus cells formed. This technique is limited in areas of advanced convection.

Peslen, C. A.↗

The Role of Rotation in the Evolution of Massive Stars

Recent evolutionary models of massive stars predict important effects of rotation including: increasing the rate of mass loss; lowering the effective gravity; altering the evolutionary track on the Hertzsprung-Russel Diagram (HRD); extending the main-sequence phase (both on the HR diagram and in time); and mixing of CNO-processed elements up to the stellar surface. Observations suggest that rotation is a more important factor at lower metallicities because of higher initial rotational velocities and weaker winds. This makes the Small Magellanic Cloud (SMC), a low-metallicity galaxy (Z=0.2 solar Z), an excellent environment for discerning the role of rotation in massive stars. We report on a FUSE+STIS+optical spectral analysis of 17 O-type stars in the SMC, where we found an enormous range in N abundances. Three stars in the sample have the same (low) CN abundances as the nebular material out of which they formed, namely C=0.085 solar C and N=0.034 solar N. However, more than half show N approx. solar N, an enrichment factor of 30X! Such unexpectedly high levels of N have ramifications for the evolution of massive stars including precursors to supernovae. They also raise questions about the sources of nitrogen in the early universe. This study was supported in part by grants from NASA's ADP, HST GO-7437, and FUSE B134.

Heap, Sara R.↗

Systems Maintenance Automated Repair Tasks (SMART)

SMART is an interactive decision analysis and refinement software system that uses evaluation criteria for discrepant conditions to automatically provide and populate a document/procedure with predefined steps necessary to repair a discrepancy safely, effectively, and efficiently. SMART can store the tacit (corporate) knowledge merging the hardware specification requirements with the actual "how to" repair methods, sequences, and required equipment, all within a user-friendly interface. Besides helping organizations retain repair knowledge in streamlined procedures and sequences, SMART can also help them in saving processing time and expense, increasing productivity, improving quality, and adhering more closely to safety and other guidelines. Though SMART was developed for Space Shuttle applications, its interface is easily adaptable to any hardware that can be broken down by component, subcomponent, discrepancy, and repair.

Source record↗

Disc dichotomy signature in the vertical distribution of [Mg/Fe] and the delayed gas infall scenario

Context. Analysis of the Apache Point Observatory Galactic Evolution Experiment project (APOGEE) data suggests the existence of a clear distinction between two sequences of disc stars in the [α/Fe] versus [Fe/H] abundance ratio space, known as the high- and low-α sequence, respectively. This dichotomy also emerges from an analysis of the vertical distribution of the [α/Fe] abundance ratio. Aims. We aim to test whether the revised two-infall chemical evolution models designed to reproduce the low- and high-α sequences in the [α/Fe] versus [Fe/H] ratios in the solar neighbourhood are also capable of predicting the disc bimodality observed in the vertical distribution of [Mg/Fe] in APOGEE DR16 data. Methods. Along with the chemical composition of the simple stellar populations born at different Galactic times predicted by our reference chemical evolution models in the solar vicinity, we provide their maximum vertical height above the Galactic plane |zmax| computed assuming the relation between the vertical action and stellar age in APOGEE thin-disc stars. Result. The vertical distribution of the [Mg/Fe] abundance ratio predicted by the reference chemical evolution models is in agreement with that observed when combining the APOGEE DR16 data (chemical abundances) with the astroNN catalogue (stellar ages, orbital parameters) for stars younger than 8 Gyr (only low-α sequence stars). Including the high-α disc component, the dichotomy in the vertical [Mg/Fe] abundance distribution is reproduced considering the observational cut in the Galactic height of |z|< 2 kpc. However, our model predicts an overly flat (almost constant) growth of the maximum vertical height |zmax| quantity as a function of [Mg/Fe] for high-α objects in contrast with the median values from APOGEE data. Possible explanations for such a tension are that: (i) the APOGEE sample with |z|< 2 kpc is more likely than ours to be contaminated by halo stars, causing the median values to be kinematically hotter, and (ii) external perturbations – such as minor mergers – that the Milky Way experienced in the past could have heated up the disc, and the heating of the orbits cannot be modeled by only scattering processes. Assuming a disc dissection based on chemistry for APOGEE-DR16 stars (|z|< 2 kpc), the observed |zmax| distributions for high-α and low-α sequences are in good agreement with our model predictions if we consider the errors in the vertical action estimates in the calculation. Moreover, a better agreement between predicted and observed stellar distributions at different Galactic vertical heights is achieved if asteroseismic ages are included as a constraint in the best-fit model calculations. Conclusions. The signature of a delayed gas infall episode, which gives rise to a hiatus in the star formation history of the Galaxy, are imprinted both in the [Mg/Fe] versus [Fe/H] relation and in vertical distribution of [Mg/Fe] abundances in the solar vicinity.

79 ASTRONOMY AND ASTROPHYSICS↗

Eye movements - On-line measurement, analysis, and control

The paper outlines the plans and progress related to the development of a Programmed Eye-track Recording System and Eye-coupled Ubiquitous Scene-generator known by the acronym PERSEUS. Particular attention is given to the design and implementation of a computer-based real-time eye-tracking system with associated digital scenic display capability. The accurate eye-tracker developed by Cornsweet and Crane (1973) is selected for this purpose. The discussion covers automatic detection of fixations and saccades, automatic scanpath analysis, fixation-conditional stimulation, and digital scene generation. The all-digital approach to scenic simulation not only eliminates the camera optics and electromechanical servomechanisms of TV-model systems of simulation but also opens the way to the virtually unlimited sequencing of data-base contents and perspectives thereof.

Anliker, J.↗

ATLAS, an integrated structural analysis and design system. Volume 3: User's manual, input and execution data

The input data and execution control statements for the ATLAS integrated structural analysis and design system are described. It is operational on the Control Data Corporation (CDC) 6600/CYBER computers in a batch mode or in a time-shared mode via interactive graphic or text terminals. ATLAS is a modular system of computer codes with common executive and data base management components. The system provides an extensive set of general-purpose technical programs with analytical capabilities including stiffness, stress, loads, mass, substructuring, strength design, unsteady aerodynamics, vibration, and flutter analyses. The sequence and mode of execution of selected program modules are controlled via a common user-oriented language.

Dreisbach, R. L.↗

Rapid, low-level X-ray variability in active late-type dwarfs

A sensitive new statistical analysis method was used to establish certain properties of quiescent X-ray variability in a sample of 19 late-type dwarfs. Sixteen stars proved to be significantly variable. The typical amplitude of the fluctuations was about 30 percent. Variability time scales ranged from about 150 s for 40 Eri C to lower limits as large as 2000 s. Neither the amplitudes nor the time scales of the X-ray variability appeared to depend on position along the main sequence.

Ambruster, Carol W.↗

An assessment of nominal and contingency altitude reboost scenarios during Space Station assembly

The results of an analysis of several reboost scenarios for nominal and contingency SS operations during the Phase I assembly sequence are presented. Space Station program requirements on assembly and operational altitudes are outlined, and essential features of the SS reaction control system are described. A nominal reboost strategy designed to meet the current program requirements is presented. In addition, reboost strategies are developed for several contingency scenarios, including one missed STS mission, and an extended STS outage. It is shown that the time-averaged propellant 'cost' of maintaining altitude is greatest for equivalent continuous-thrusting altitude maintenance; it decreases with increasing reboost/rendezvous time interval to an asymptotic minimum value.

Bilardo, Vincent J., Jr.↗