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NASA NTRS1986

Test and evaluation of a multifunction keyboard and a dedicated keyboard for control of a flight management computer

A flight management computer (FMC) control display unit (CDU) test was conducted to compare two types of input devices: a fixed legend (dedicated) keyboard and a programmable legend (multifunction) keyboard. The task used for comparison was operation of the flight management computer for the Boeing 737-300. The same tasks were performed by twelve pilots on the FMC control display unit configured with a programmable legend keyboard and with the currently used B737-300 dedicated keyboard. Flight simulator work activity levels and input task complexity were varied during each pilot session. Half of the points tested were previously familiar with the B737-300 dedicated keyboard CDU and half had no prior experience with it. The data collected included simulator flight parameters, keystroke time and sequences, and pilot questionnaire responses. A timeline analysis was also used for evaluation of the two keyboard concepts.

Crane, J. M.↗

NASA NTRS1987

Numerical simulations and the problem of periodicity in the cratering record

Ages of craters in the record of impacts on earth may be uniformly periodic, totally random, or a mixture of the two. These alternatives are studied through numerical simulation wherein time-series analysis is performed on real and simulated sequences to which random noise has been added to represent age-dating uncertainty. It is concluded that the real record is most likely to have been generated by a mixture of random and periodic impacts, with the random events constituting the majority.

Trefil, J. S.↗

NASA NTRS1987

Expert systems tools for Hubble Space Telescope observation scheduling

This paper discusses the utility of expert systems techniques for Hubble Space Telescope (HST) planning and scheduling and describes a plan for development of expert system tools which will augment the existing ground system. Additional capabilities provided by these tools will include graphics-oriented plan evaluation, long-range analysis of the observation pool, analysis of optimal scheduling time intervals, constructing sequences of spacecraft activities which minimize operational overhead, and optimization of linkages between observations. Initial prototyping of a scheduler used the Automated Reasoning Tool running on a LISP workstation.

Miller, Glenn↗

NASA NTRS1987

Expert systems tools for Hubble Space Telescope observation scheduling

The utility of expert systems techniques for the Hubble Space Telescope (HST) planning and scheduling is discussed and a plan for development of expert system tools which will augment the existing ground system is described. Additional capabilities provided by these tools will include graphics-oriented plan evaluation, long-range analysis of the observation pool, analysis of optimal scheduling time intervals, constructing sequences of spacecraft activities which minimize operational overhead, and optimization of linkages between observations. Initial prototyping of a scheduler used the Automated Reasoning Tool running on a LISP workstation.

Miller, Glenn↗

NASA NTRS1991

Vision-based optimal obstacle-avoidance guidance for rotorcraft

An optimal guidance scheme for vision-based obstacle avoidance is developed. The proposed approach is useful for automating low-altitude rotorcraft flight. It explicitly accounts for the discrete nature of range information available from vision-based sensors and uses a linear combination of flight time, square of the vehicle acceleration and the square of the distance to various sensed obstacles as the performance index. A sixth-order, three-degree-of-freedom nonlinear point-mass vehicle model is included in the analysis. Numerical results using a sample image sequence is given.

Menon, P. K. A.↗

NASA NTRS1993

Connecting science and operations: The operations coordinator

For a current space mission under development at the Applied Physics Laboratory, the Mission Operations staff includes a team of 'Operations Coordinators' who have been working with the Mission Science and Spacecraft Development teams since completion of mission conceptual design. The Operations Coordinators are responsible for bringing knowledge of the spacecraft to the Mission Science team and bringing knowledge of the experiment requirements to the Spacecraft Development and Mission Operations teams. Once on-orbit operations begin, the Operations Coordinators will be responsible for implementation of specific science experiments from analysis through scheduling, generation of spacecraft command sequences, delivery of science data to the end user, and operations assessment. The Operations Coordinator concept is proving very effective during the development phase of the current mission.

Marshall, Madeleine H.↗

NASA NTRS1997

A Model for Space Shuttle Orbiter Tire Side Forces Based on NASA Landing Systems Research Aircraft Test Results

Forces generated by the Space Shuttle orbiter tire under varying vertical load, slip angle, speed, and surface conditions were measured using the Landing System Research Aircraft (LSRA). Resulting data were used to calculate a mathematical model for predicting tire forces in orbiter simulations. Tire side and drag forces experienced by an orbiter tire are cataloged as a function of vertical load and slip angle. The mathematical model is compared to existing tire force models for the Space Shuttle orbiter. This report describes the LSRA and a typical test sequence. Testing methods, data reduction, and error analysis are presented. The LSRA testing was conducted on concrete and lakebed runways at the Edwards Air Force Flight Test Center and on concrete runways at the Kennedy Space Center (KSC). Wet runway tire force tests were performed on test strips made at the KSC using different surfacing techniques. Data were corrected for ply steer forces and conicity.

Carter, John F.↗

NASA NTRS2004

A Fast-Time Simulation Tool for Analysis of Airport Arrival Traffic

The basic objective of arrival sequencing in air traffic control automation is to match traffic demand and airport capacity while minimizing delays. The performance of an automated arrival scheduling system, such as the Traffic Management Advisor developed by NASA for the FAA, can be studied by a fast-time simulation that does not involve running expensive and time-consuming real-time simulations. The fast-time simulation models runway configurations, the characteristics of arrival traffic, deviations from predicted arrival times, as well as the arrival sequencing and scheduling algorithm. This report reviews the development of the fast-time simulation method used originally by NASA in the design of the sequencing and scheduling algorithm for the Traffic Management Advisor. The utility of this method of simulation is demonstrated by examining the effect on delays of altering arrival schedules at a hub airport.

Erzberger, Heinz↗

NASA NTRS2011

Sptrace

Sptrace is a general-purpose space utilization tracing system that is conceptually similar to the commercial Purify product used to detect leaks and other memory usage errors. It is designed to monitor space utilization in any sort of heap, i.e., a region of data storage on some device (nominally memory; possibly shared and possibly persistent) with a flat address space. This software can trace usage of shared and/or non-volatile storage in addition to private RAM (random access memory). Sptrace is implemented as a set of C function calls that are invoked from within the software that is being examined. The function calls fall into two broad classes: (1) functions that are embedded within the heap management software [e.g., JPL's SDR (Simple Data Recorder) and PSM (Personal Space Management) systems] to enable heap usage analysis by populating a virtual time-sequenced log of usage activity, and (2) reporting functions that are embedded within the application program whose behavior is suspect. For ease of use, these functions may be wrapped privately inside public functions offered by the heap management software. Sptrace can be used for VxWorks or RTEMS realtime systems as easily as for Linux or OS/X systems.

Burleigh, Scott C.↗

NASA NTRS2015

Numerical Calibration of Mass Flow Plug for Inlet Testing

A simple control volume model has been developed to calculate the discharge coefficient through a mass flow plug (MFP) and validated with a calibration experiment. The maximum error of the model within the operating region of the MFP is 0.54%. The control volume analysis developed work is comprised of a sequence of flow calculations through the MFP. The model uses the MFP geometry and operating pressure and temperature to couple continuity, momentum, energy, an equation of state, and wall shear. The discharge coefficient calculation also includes the effects of boundary layer growth, including the reduction in cross-sectional flow area as characterized by the boundary layer displacement thickness. The last calculation in the sequence uses an integral method to calculate the growth of the boundary layer, from which the displacement thickness is then determined. The result of these successive calculations is an accurate one-dimension model of the velocity, pressure, and temperature through the MFP. For comparison, a computational fluid dynamic (CFD) calibration is shown, which when compared to the presented numerical model, had a lower accuracy with a maximum error of 1.35% in addition to being slower by a factor of 100."

Flow Measurement↗

NASA NTRS2019

A Lab with a View: Findings from NASA's Aircraft Bioaerosol Collector

Airborne microorganisms in the upper troposphere and lower stratosphere remain elusive due to a lack of reliable sample collection systems. To address this problem, we designed, installed, and flight-validated a novel Aircraft Bioaerosol Collector (ABC) for NASA's C-20A that can make collections for microbiological research investigations up to altitudes of 13.7 km. Herein we report results from the first set of science flights-four consecutive missions flown over the United States (US) from 30 October to 2 November, 2017. To ascertain how the concentration of airborne bacteria changed across the tropopause, we collected air during aircraft Ascent/Descent (0.3 to 11 km), as well as sustained Cruise altitudes in the lower stratosphere (~12 km). Bioaerosols were captured on DNA-treated gelatinous filters inside a cascade air sampler, then analyzed with molecular and culture-based characterization. Several viable bacterial isolates were recovered from flight altitudes, including Bacillus sp., Micrococcus sp., Arthrobacter sp., and Staphylococcus sp. from Cruise samples and Brachybacterium sp. from Ascent/Descent samples. Using 16S V4 sequencing methods for a culture-independent analysis of bacteria, the average number of total OTUs was 305 for Cruise samples and 276 for Ascent/Descent samples. Surprisingly, our results revealed a homogeneous distribution of bacteria in the atmosphere up to 12 km. The observation could be due to atmospheric conditions producing similar background aerosols across the western US, as suggested by modeled back trajectories and satellite measurements. However, the influence of aircraft-associated bacterial contaminants could not be fully eliminated and that background signal was reported throughout our dataset. Considering the tremendous engineering challenge of collecting biomass at extreme altitudes where contamination from flight hardware remains an ever-present issue, we note the utility of using the stratosphere as a proving ground for planned life detection missions across the solar system.

bioaerosols↗

DOE OSTI2025

Exploring the Potential of ASHRAE Guideline 36 in District Cooling Systems: Preprint

ASHRAE Guideline 36-2021 (G36) provides high-performance control sequences for all-air and hydronic HVAC systems, and it has proven effective at reducing energy use for single building all-air equipment. The most recent version of G36 included control sequences for water-cooled chiller plants, which can be used in district cooling systems (DCSs). Despite not being a traditional application of G36 controls, DCSs could benefit from energy savings that G36 control sequences have demonstrated in single building systems. We therefore investigate the possibility to extend G36 chiller plant control from a single building to district cooling using a real-world district cooling system in Boulder, Colorado as a case study. Four timeframes representing low to peak loads are simulated and analyzed to compare energy use of the district cooling system for three control sequences. Results show that although G36 chiller plant sequences can be applied to DCSs, further analysis and potentially control optimization is needed to ensure energy savings compared to default controls.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2018

Distorted antibody repertoire developed in the absence of pre-B cell receptor formation

Highlights: • Leaky B cells in SLC-deficient mice circumvent the pre-BCR checkpoint. • Antibody repertoires differing in VDJ-usage exist in leaky B cells in λ5{sup −}/{sup −} mice. • Leaky B cells do not originate from B1 or particular B2 cells. • The CDR-H3 middle loop in λ5{sup −}/{sup −} bone marrow B cells is enriched in arginines. The pre-B cell receptor (pre-BCR), consisting of the μ heavy chain (μHC) and the surrogate light chain (SLC, Vpre-B and λ5), plays important roles during B cell development. The formation of the pre-BCR, which enables the nascent immunoglobulin HC to associate with the SLC, is considered a prerequisite for B cell development. However, a significant number of peripheral mature (leaky) B cells exist in SLC-deficient mice. These leaky B cells develop in the absence of pre-BCR and do not undergo the pre-BCR checkpoint. The antibody repertoires of leaky B cells thus reflect the absence of pre-BCR function. To investigate how the absence of the pre-BCR is circumvented by these leaky-B cells and examine the effect of the pre-BCR checkpoint on the antibody system, we analyzed the antibody repertoires of λ5-deficient (λ5{sup −/−}) mice using next-generation sequencing. In λ5{sup −/−} mice, spleen B cells displayed different patterns of VDJ-usage, relative to those in wild-type (WT) mice. Moreover, leaky B cells were neither derived from unusual B2 cells, characterized by particular LC gene rearrangements in the absence of pre-BCR signaling, nor from B1 cells, originating from different B cell progenitors. Analysis of the CDR-H3 amino acid sequences of μ-chain repertoires revealed that certain bone marrow B cells with particular CDR-H3 profiles undergo clonal expansion in λ5{sup −/−} mice. Part of these CDR-H3s contain arginine(s) in the middle of the CDR-H3 loop in λ5{sup −/−} mice, whereas few arginine(s) exist in this middle loop in WT CDR-H3s in the absence of clonal expansion. This CDR-H3 feature in λ5{sup −/−} mice presumably reflects the role of the pre-BCR in autoantibody regulation, since arginine(s) are often found in the antigen-binding site of autoantibodies. Here, we present a unique viewpoint on the role of pre-BCR, by assessing the whole antibody repertoire formed in SLC-deficient mice.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

Single-Genome Sequencing of Hepatitis C Virus in Donor-Recipient Pairs Distinguishes Modes and Models of Virus Transmission and Early Diversification

Despite the recent development of highly effective anti-hepatitis C virus (HCV) drugs, the global burden of this pathogen remains immense. Control or eradication of HCV will likely require the broad application of antiviral drugs and development of an effective vaccine. A precise molecular identification of transmitted/founder (T/F) HCV genomes that lead to productive clinical infection could play a critical role in vaccine research, as it has for HIV-1. However, the replication schema of these two RNA viruses differ substantially, as do viral responses to innate and adaptive host defenses. These differences raise questions as to the certainty of T/F HCV genome inferences, particularly in cases where multiple closely related sequence lineages have been observed. To clarify these issues and distinguish between competing models of early HCV diversification, we examined seven cases of acute HCV infection in humans and chimpanzees, including three examples of virus transmission between linked donors and recipients. Using single-genome sequencing (SGS) of plasma vRNA, we found that inferred T/F sequences in recipients were identical to viral sequences in their respective donors. Early in infection, HCV genomes generally evolved according to a simple model of random evolution where the coalescent corresponded to the T/F sequence. Closely related sequence lineages could be explained by high multiplicity infection from a donor whose viral sequences had undergone a pretransmission bottleneck due to treatment, immune selection, or recent infection. These findings validate SGS, together with mathematical modeling and phylogenetic analysis, as a novel strategy to infer T/F HCV genome sequences.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Towards resolving protein structures at the atomic scale using atom probe tomography

In the field of Structural Biology, Atom Probe Tomography (APT) is in the nascent stages of development wherein coarse-grained visuals of proteins have been captured. The characterization of organic samples or biomolecules through the technique is currently limited to the detection of a few dominant signatures. The problem of indecipherable characterization can inherently be traced back to multiple forms of technique-specific responses to organic samples and consequent triggers leading to organic-sample and sample-medium interactions. While it is possible for captured manifestations of protein reconstructions to seemingly appear intact from a basic visual purview, the parameter-protein associative responses throughout the structure as a direct consequence of the inherent workings of the technique (until harmonized with organic sample complexity and behavior) and field evaporation-based factors make non-aberrative atomic associations infeasible. The work focused on identifying and theorizing the (above stated and other) fundamental mechanisms that stronghold the study of intricate atomic to higher order associations in proteins through APT. Attempts at structure elucidation of the cryogenic sample under study, through indirect associations (and methods) based on other imaging techniques, further revealed the distinct and highly distortive nature at the atomic scale deterring structural tunability and thus characterization of APT based cryogenic samples under analysis. As a direct counter to the atomic scale characterization problem, by taking the experiment-specific uncertainties, and probable APT-centric organic sample-based variabilities into account, a basic result is extracted and presented. Through mass-spectrometric and computational analysis, specific individual amino acids (Sulfur-containing protein-bound amino acids) in proteins and aspects of protein structure (probable backbone fragments, partial sequence - partial backbone portions) have been identified and characterized. Under analysis considerations, a few of the simplest known and easily inferable segments that favor structural deteriorations in the reconstructions are stated. Additionally, to overcome technique-specific deterrents to the characterization of biomolecules in cryogenic sample medium, the development of a protein-labeling strategy tailored to APT is suggested.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Effects of error, chimera, bias, and GC content on the accuracy of amplicon sequencing

ABSTRACT Targeted amplicon sequencing is widely used in microbial ecology studies. However, sequencing artifacts and amplification biases are of great concern. To identify sources of these artifacts, a systematic analysis was performed using mock communities comprised of 16S rRNA genes from 33 bacterial strains. Our results indicated that while sequencing errors were generally isolated to low-abundance operational taxonomic units, chimeric sequences were a major source of artifacts. Singleton and doubleton sequences were primarily chimeras. Formation of chimeric sequences was significantly correlated with the GC content of the targeted sequences. Low-GC-content mock community members exhibited lower rates of chimeric sequence formation. GC content also had a large impact on sequence recovery. The quantitative capacity was notably limited, with substantial recovery variations and weak correlation between anticipated and observed strain abundances. The mock community strains with higher GC content had higher recovery rates than strains with lower GC content. Amplification bias was also observed due to the differences in primer affinity. A two-step PCR strategy reduced the number of chimeric sequences by half. In addition, comparative analyses based on the mock communities showed that several widely used sequence processing pipelines/methods, including DADA2, Deblur, UCLUST, UNOISE, and UPARSE, had different advantages and disadvantages in artifact removal and rare species detection. These results are important for improving sequencing quality and reliability and developing new algorithms to process targeted amplicon sequences. IMPORTANCE Amplicon sequencing of targeted genes is the predominant approach to estimate the membership and structure of microbial communities. However, accurate reconstruction of community composition is difficult due to sequencing errors, and other methodological biases and effective approaches to overcome these challenges are essential. Using a mock community of 33 phylogenetically diverse strains, this study evaluated the effect of GC content on sequencing results and tested different approaches to improve overall sequencing accuracy while characterizing the pros and cons of popular amplicon sequence data processing approaches. The sequencing results from this study can serve as a benchmarking data set for future algorithmic improvements. Furthermore, the new insights on sequencing error, chimera formation, and GC bias from this study will help enhance the quality of amplicon sequencing studies and support the development of new data analysis approaches.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

A standardized quantitative analysis strategy for stable isotope probing metagenomics

ABSTRACT Stable isotope probing (SIP) facilitates culture-independent identification of active microbial populations within complex ecosystems through isotopic enrichment of nucleic acids. Many DNA-SIP studies rely on 16S rRNA gene sequences to identify active taxa, but connecting these sequences to specific bacterial genomes is often challenging. Here, we describe a standardized laboratory and analysis framework to quantify isotopic enrichment on a per-genome basis using shotgun metagenomics instead of 16S rRNA gene sequencing. To develop this framework, we explored various sample processing and analysis approaches using a designed microbiome where the identity of labeled genomes and their level of isotopic enrichment were experimentally controlled. With this ground truth dataset, we empirically assessed the accuracy of different analytical models for identifying active taxa and examined how sequencing depth impacts the detection of isotopically labeled genomes. We also demonstrate that using synthetic DNA internal standards to measure absolute genome abundances in SIP density fractions improves estimates of isotopic enrichment. In addition, our study illustrates the utility of internal standards to reveal anomalies in sample handling that could negatively impact SIP metagenomic analyses if left undetected. Finally, we present SIPmg , an R package to facilitate the estimation of absolute abundances and perform statistical analyses for identifying labeled genomes within SIP metagenomic data. This experimentally validated analysis framework strengthens the foundation of DNA-SIP metagenomics as a tool for accurately measuring the in situ activity of environmental microbial populations and assessing their genomic potential. IMPORTANCE Answering the questions, “who is eating what?” and “who is active?” within complex microbial communities is paramount for our ability to model, predict, and modulate microbiomes for improved human and planetary health. These questions can be pursued using stable isotope probing to track the incorporation of labeled compounds into cellular DNA during microbial growth. However, with traditional stable isotope methods, it is challenging to establish links between an active microorganism’s taxonomic identity and genome composition while providing quantitative estimates of the microorganism’s isotope incorporation rate. Here, we report an experimental and analytical workflow that lays the foundation for improved detection of metabolically active microorganisms and better quantitative estimates of genome-resolved isotope incorporation, which can be used to further refine ecosystem-scale models for carbon and nutrient fluxes within microbiomes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Efficient DNA sequence compression with neural networks

Abstract Background The increasing production of genomic data has led to an intensified need for models that can cope efficiently with the lossless compression of DNA sequences. Important applications include long-term storage and compression-based data analysis. In the literature, only a few recent articles propose the use of neural networks for DNA sequence compression. However, they fall short when compared with specific DNA compression tools, such as GeCo2. This limitation is due to the absence of models specifically designed for DNA sequences. In this work, we combine the power of neural networks with specific DNA models. For this purpose, we created GeCo3, a new genomic sequence compressor that uses neural networks for mixing multiple context and substitution-tolerant context models. Findings We benchmark GeCo3 as a reference-free DNA compressor in 5 datasets, including a balanced and comprehensive dataset of DNA sequences, the Y-chromosome and human mitogenome, 2 compilations of archaeal and virus genomes, 4 whole genomes, and 2 collections of FASTQ data of a human virome and ancient DNA. GeCo3 achieves a solid improvement in compression over the previous version (GeCo2) of $2.4\%$, $7.1\%$, $6.1\%$, $5.8\%$, and $6.0\%$, respectively. To test its performance as a reference-based DNA compressor, we benchmark GeCo3 in 4 datasets constituted by the pairwise compression of the chromosomes of the genomes of several primates. GeCo3 improves the compression in $12.4\%$, $11.7\%$, $10.8\%$, and $10.1\%$ over the state of the art. The cost of this compression improvement is some additional computational time (1.7–3 times slower than GeCo2). The RAM use is constant, and the tool scales efficiently, independently of the sequence size. Overall, these values outperform the state of the art. Conclusions GeCo3 is a genomic sequence compressor with a neural network mixing approach that provides additional gains over top specific genomic compressors. The proposed mixing method is portable, requiring only the probabilities of the models as inputs, providing easy adaptation to other data compressors or compression-based data analysis tools. GeCo3 is released under GPLv3 and is available for free download at https://github.com/cobilab/geco3.

Silva, Milton↗