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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS1977

Volatile metal deposits on lunar soils: Relation to volcanism

Parallel leaching and volatilization experiments conducted on lunar samples and similar experiments on sphalerite do not supply the information needed to resolve the question of the chemical nature of pb 204, Zn, Bi and Tl deposits on lunar soil surfaces. It is proposed that in Apollo 17 mare and terra soils and fractions of pb 204, Zn and Tl that are insoluble under mild, hot pH 5HNO3, leaching conditions and involatile at 600 C were originally surface deposits which became immobilized by migration into the silicate substrate or by chemisorption. Only Bi is predominantly indigenous. The implication is also that the soils over their respective times of evolution were exposed to heavy metal vapors or that an episodic exposure occurred after they had evolved. A sequence of events is proposed to account for orange 74220 and black 74001 glasses by lava fountaining and for soil 74241 as tephra from an explosive volcanic eruption.

Reed, G. W., Jr.↗
NASA NTRS2000

Laboratory Study of Water Surface Roughness Generation by Wave-Current Interaction

Within the framework of this project, the blocking of waves by inhomogeneous currents was studied. A laboratory experiment was conducted in collaboration with Steven R. Long at the linear wave tank of the NASA Air-Sea Interaction Facility, Wallops Island, VA during May 1999. Mechanically-generated waves were blocked approximately 3m upstream from the wave paddle by an opposing current. A false bottom was used to obtain a spatially varying flow field in the measurement section of the wave tank. We used an imaging slope gauge, which was mounted directly underneath the sloping section of the false tank bottom to observe the wave field. For a given current speed, the amplitude and the frequency of the waves was adjusted so that the blocking occurred within the observed footprint. Image sequences of up to 600 images at up 100 Hz sampling rate were recorded for an area of approximately 25cm x 25cm. Unlike previous measurements with wave wire gauges, the captured image sequences show the generation of the capillary waves at the blocking point and give detailed insight into the spatial and temporal evolution of the blocking process. The image data were used to study the wave-current interaction for currents from 5 to 25 cm/s and waves with frequencies between 1 and 3 Hz. First the images were calibrated with regard to size and slope. Then standard Fourier techniques as well the empirical mode decomposition method developed by Dr. Norden Huang and Dr. Steven R. Long were employed to quantify the wave number downshift from the gravity to the capillary regime.

Klinke, Jochen↗
NASA NTRS2002

Bounding the Risk of Crew Loss Following Orbital Debris Penetration of the International Space Station at Assembly Stages 1J and 1E

Orbital debris impacts on the International Space Station occur frequently. To date, none of the impacting particles has been sufficiently large to penetrate manned pressurized volumes. We used the Manned Spacecraft Crew Survivability code to evaluate the risk to crew of penetrations of pressurized modules at two assembly stages: after Flight lJ, when the pressurized elements of Kibo, the Japanese Experiment Module, are present, and after Flight lE, when the European Columbus Module is present. Our code is a Monte Carlo simulation of impacts on the Station that considers several potential event types that could lead to crew loss. Among the statistics tabulated by the program is the probability of death of one or more crew members, expressed as the risk factor, R. This risk factor is dependent on details of crew operations during both ordinary circumstances and decompression emergencies, as well as on details of internal module configurations. We conducted trade studies considering these procedure and configuration details to determine the bounds on R at the 1J and 1E stages in the assembly sequence. Here we compare the R-factor bounds, and procedures and configurations that reduce R at these stages.

Evans, S.↗
NASA NTRS2007

Effect Of Spaceflight On Microbial Gene Expression And Virulence: Preliminary Results From Microbe Payload Flown On-Board STS-115

Human presence in space, whether permanent or temporary, is accompanied by the presence of microbes. However, the extent of microbial changes in response to spaceflight conditions and the corresponding changes to infectious disease risk is unclear. Previous studies have indicated that spaceflight weakens the immune system in humans and animals. In addition, preflight and in-flight monitoring of the International Space Station (ISS) and other spacecraft indicates the presence of opportunistic pathogens and the potential of obligate pathogens. Altered antibiotic resistance of microbes in flight has also been shown. As astronauts and cosmonauts live for longer periods in a closed environment, especially one using recycled water and air, there is an increased risk to crewmembers of infectious disease events occurring in-flight. Therefore, understanding how the space environment affects microorganisms and their disease potential is critically important for spaceflight missions and requires further study. The goal of this flight experiment, operationally called MICROBE, is to utilize three model microbial pathogens, Salmonella typhimurium, Pseudomonas aeruginosa, and Candida albicans to examine the global effects of spaceflight on microbial gene expression and virulence attributes. Specifically, the aims are (1) to perform microarray-mediated gene expression profiling of S. typhimurium, P. aeruginosa, and C. albicans, in response to spaceflight in comparison to ground controls and (2) to determine the effect of spaceflight on the virulence potential of these microorganisms immediately following their return from spaceflight using murine models. The model microorganisms were selected as they have been isolated from preflight or in-flight monitoring, represent different degrees of pathogenic behavior, are well characterized, and have sequenced genomes with available microarrays. In particular, extensive studies of S. typhimurium by the Principal Investigator, Dr. Nickerson, using ground-based analog systems demonstrate important changes in the genotypic, phenotypic, and virulence characteristics of this pathogen resulting from exposure to a flight-like environment (i.e. modeled microgravity).

Wilson, J. W.↗
NASA NTRS2009

ARTEMIS: The First Mission to the Lunar Libration Orbits

The ARTEMIS mission will be the first to navigate to and perform stationkeeping operations around the Earth-Moon L1 and L2 Lagrangian points. The NASA Goddard Space Flight Center (GSFC) has previous mission experience flying in the Sun-Earth L1 (SOHO, ACE, WIND, ISEE-3) and L2 regimes (WMAP) and have maintained these spacecraft in libration point orbits by performing regular orbit stationkeeping maneuvers. The ARTEMIS mission will build on these experiences, but stationkeeping in Earth-Moon libration orbits presents new challenges since the libration point orbit period is on the order of two weeks rather than six months. As a result, stationkeeping maneuvers to maintain the Lissajous orbit will need to be performed frequently, and the orbit determination solutions between maneuvers will need to be quite accurate. The ARTEMIS mission is a collaborative effort between NASA GSFC, the University of California at Berkeley (UCB), and the Jet Propulsion Laboratory (JPL). The ARTEMIS mission is part of the THEMIS extended mission. ARTEMIS comprises two of the five THEMIS spacecraft that will be maneuvered from near-Earth orbits into lunar libration orbits using a sequence of designed orbital maneuvers and Moon & Earth gravity assists. In July 2009, a series of orbit-raising maneuvers began the proper orbit phasing of the two spacecraft for the first lunar flybys. Over subsequent months, additional propulsive maneuvers and gravity assists will be performed to move each spacecraft though the Sun-Earth weak stability regions and eventually into Earth-Moon libration point orbits. We will present the overall orbit designs for the two ARTEMIS spacecraft and provide analysis results of the 3/4-body dynamics, and the sensitivities of the trajectory design to both · maneuver errors and orbit determination errors. We will present results from the. initial orbit-raising maneuvers.

Woodward, Mark↗
NASA NTRSDate not supplied

Developing Open-Source Training Materials for AI/ML and Space Biological Sciences Using NASA Cloud-Based Data

Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields, in part due to a culture of open data sharing and reuse. AI/ML methodology is well-suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Inexperienced researchers can produce models that perform poorly outside of the training dataset. Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.

James Casaletto↗
DOE OSTI2021

Enabling discovery data science through cross-facility workflows

Experimental and observational instruments for scientific research (such as light sources, genome sequencers, accelerators, telescopes and electron microscopes) increasingly require High Performance Computing (HPC) scale capabilities for data analysis and workflow processing. Next-generation instruments are being deployed with higher resolutions and faster data capture rates, creating a big data crunch that cannot be handled by modest institutional computing resources. Often these big data analysis pipelines also require near real-time computing and have higher resilience requirements than the simulation and modeling workloads more traditionally seen at HPC centers. While some facilities have enabled workflows to run at a single HPC facility, there is a growing need to integrate capabilities across HPC facilities to enable cross-facility workflows, either to provide resilience to an experiment, increase analysis throughput capabilities, or to better match a workflow to a particular architecture. In this paper we describe the barriers to executing complex data analysis workflows across HPC facilities and propose an architectural design pattern for enabling scientific discovery using cross-facility workflows that includes orchestration services, application programming interfaces (APIs), data access and co-scheduling.

Antypas, Katerina B.↗
DOE OSTI2024

Projective Integral Updates for High-Dimensional Variational Inference

Variational inference is an approximation framework for Bayesian inference that seeks to improve quantified uncertainty in predictions by optimizing a simplified distribution over parameters to stand in for the full posterior. Capturing model variations that remain consistent with training data enables more robust predictions by reducing parameter sensitivity. This work introduces a fixed-point optimization for variational inference that is applicable when every feasible log density can be expressed as a linear combination of functions from a given basis. In such cases, the optimizer becomes a fixed-point of projective integral updates. When the basis spans univariate quadratics in each parameter, the feasible distributions are Gaussian mean-fields and the projective integral updates yield quasi-Newton variational Bayes (QNVB). Other bases and updates are also possible. Since these updates require high-dimensional integration, this work begins by proposing an efficient quasirandom sequence of quadratures for mean-field distributions. Each iterate of the sequence contains two evaluation points that combine to correctly integrate all univariate quadratic functions and, if the mean-field factors are symmetric, all univariate cubics. More importantly, averaging results over short subsequences achieves periodic exactness on a much larger space of multivariate polynomials of quadratic total degree. The corresponding variational updates require four loss evaluations with standard (not second-order) backpropagation to eliminate error terms from over half of all multivariate quadratic basis functions. Furthermore, this integration technique is motivated by first proposing stochastic blocked mean-field quadratures, which may be useful in other contexts. A PyTorch implementation of QNVB allows for better control over model uncertainty during training than competing methods. Experiments demonstrate superior generalizability for multiple learning problems and architectures.

Gaussian mean-field↗
NASA NTRS1991

LDEF Interplanetary Dust Experiment - Techniques for identification and study of long-lived orbital debris clouds

The Long Duration Exposure Facility (LDEF) is a 12-sided, 4.3-m-diameter, 9.1-m-long cylinder designed and built by NASA Langley to carry experiments for extended periods in space. The LDEF was first placed in orbit by the Shuttle Challenger on 7 April 1984 and recovered by the Shuttle Columbia in January 1990, only days before it was expected to burn up in the earth's atmosphere. The Interplanetary Dust Experiment (IDE) was designed to detect impacts of extra-terrestrial particles and orbital debris. The IDE detectors (which covered about 1 sq m of the surface of LDEF) were sensitive to particles ranging in size from about 0.2 to 100 microns. Data were recorded for 11.5 months before the supply of magnetic tape was exhausted. Examination of the LDEF IDE dataset shows that impacts often occurred in 'bursts', during which numerous impacts occurred in a short time (typically 3-5 min) at a rate much greater than the average impact rate. In several cases, such events reoccurred each time the LDEF returned to the same point in its orbit. Such multi-orbit event sequences were found to extend for as many as 25 or more orbits.

Singer, S. F.↗
NASA NTRS2019

Mapping the Zonal Structure of Titan’s Northern Polar Vortex

Saturn exhibits an obliquity of 26.7° such that the largest moon, Titan, experiences seasonal variations including the formation of a polar vortex in the winter hemisphere. Titan’s polar vortex is characterised by cold stratospheric temperatures due to the lack of insolation over the winter pole, and an increase in trace gas abundance as a result of complex organic chemistry in the upper atmosphere combined with polar subsidence. Meridional variations in temperature and gas abundance across the vortex have previously been investigated, but there has not yet been any in-depth study of the zonal variations in the temperature or composition of the northern vortex. Here we present the first comprehensive two-dimensional seasonal mapping of Titan’s northern winter vortex. Using 18 nadir mapping sequences observed by the Composite InfraRed Spectrometer (CIRS) instrument on-board Cassini, we investigate the evolution of the vortex over almost half a Titan year, from late winter through to mid summer (L(sub s) = 326 - 86°, 2007-2017). We find the stratospheric symmetry axis to be tilted from the solid body rotation axis by around 3.5°, although our results for the azimuthal orientation of the tilt are inconclusive. We find that the northern vortex appears to remain zonally uniform in both temperature and composition at all times. A comparison with vortices observed on Earth, Mars, and Venus shows that large-scale wave mechanisms that are important on other terrestrial planets are not as significant in Titan’s atmosphere. This allows the northern vortex to be more symmetrical and persist longer throughout the annual cycle compared to other terrestrial planets.

Jason Sharkey↗
DOE OSTI2026

Development of a pattern recognition algorithm for reconstructing multi-particle events in the Mu2e detector

Mu2e is an upcoming experiment at Fermilab and its main goal is to search for the Charged Lepton Flavor Violation (CLFV) in the coherent transition of a muon into an electron on an Al target. In Mu2e, multi-particle events can occur simultaneously within the same time region and it is crucial to accurately identify each particle track, including signals, to improve the robustness of track finding methods and enhance reconstruction efficiency. ¯p annihilation is one of the background events and produces multiple particles that can mimic signal events. Additionally, photons from radiative pion captures can produce a γ → $e+e−$ pair, which can be used to calibrate the Mu2e momentum scale and the resolution. The Mu2e track reconstruction sequence begins by grouping hits produced in the tracker based on time and z coordinate information, called TimeCluster, and selected hits are processed to reconstruct helices and determine their momentum. The current pattern recognition algorithms identify a single helix per TimeCluster for single track events. A new pattern recognition algorithm is being developed to reconstruct multi-particle events and its features for finding multiple tracks and the current evaluation results are reported.

Kitagawa, H. [Pisa U.]↗
NASA NTRS1981

Human factors in equipment development for the Space Shuttle - A study of the general purpose work station

The results of a human factors test to assay the suitability of a prototype general purpose work station (GPWS) for biosciences experiments on the fourth Spacelab mission are reported. The evaluation was performed to verify that users of the GPWS would optimally interact with the GPWS configuration and instrumentation. Six male subjects sat on stools positioned to allow assimilation of the zero-g body posture. Trials were run concerning the operator viewing angles facing the console, the console color, procedures for injecting rates with dye, a rat blood cell count, mouse dissection, squirrel monkey transfer, and plant fixation. The trials were run for several days in order to gage improvement or poor performance conditions. Better access to the work surface was found necessary, together with more distinct and better located LEDs, better access window latches, clearer sequences on control buttons, color-coded sequential buttons, and provisions made for an intercom system when operators of the GPWS work in tandem.

Junge, M. K.↗
NASA NTRS2013

MESSENGER at Mercury: Early Orbital Operations

The MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) spacecraft, launched in August 2004 under NASA's Discovery Program, was inserted into orbit about the planet Mercury in March 2011. MESSENGER's three flybys of Mercury in 2008-2009 marked the first spacecraft visits to the innermost planet since the Mariner 10 flybys in 1974-1975. The unprecedented orbital operations are yielding new insights into the nature and evolution of Mercury. The scientific questions that frame the MESSENGER mission led to the mission measurement objectives to be achieved by the seven payload instruments and the radio science experiment. Interweaving the full set of required orbital observations in a manner that maximizes the opportunity to satisfy all mission objectives and yet meet stringent spacecraft pointing and thermal constraints was a complex optimization problem that was solved with a software tool that simulates science observations and tracks progress toward meeting each objective. The final orbital observation plan, the outcome of that optimization process, meets all mission objectives. MESSENGER's Mercury Dual Imaging System is acquiring a global monochromatic image mosaic at better than 90% coverage and at least 250 m average resolution, a global color image mosaic at better than 90% coverage and at least 1 km average resolution, and global stereo imaging at better than 80% coverage and at least 250 m average resolution. Higher-resolution images are also being acquired of targeted areas. The elemental remote sensing instruments, including the Gamma-Ray and Neutron Spectrometer and the X-Ray Spectrometer, are being operated nearly continuously and will establish the average surface abundances of most major elements. The Visible and Infrared Spectrograph channel of MESSENGER's Mercury Atmospheric and Surface Composition Spectrometer is acquiring a global map of spectral reflectance from 300 to 1450 nm wavelength at a range of incidence and emission angles. Targeted areas have been selected for spectral coverage into the ultraviolet with the Ultraviolet and Visible Spectrometer (UVVS). MESSENGER's Mercury Laser Altimeter is acquiring topographic profiles when the slant range to Mercury's surface is less than 1800 km, encompassing latitudes from 20 deg. S to the north pole. Topography over the remainder of the southern hemisphere will be derived from stereo imaging, radio occultations, and limb profiles. MESSENGER's radio science experiment is determining Mercury's gravity field from Doppler signals acquired during frequent downlinks. MESSENGER's Magnetometer is measuring the vector magnetic field both within Mercury's magnetosphere and in Mercury's solar wind environment at an instrument sampling rate of up to 20 samples/s. The UVVS is determining the three-dimensional, time-dependent distribution of Mercury's exospheric neutral and ionic species via their emission lines. During each spacecraft orbit, the Energetic Particle Spectrometer measures energetic electrons and ions, and the Fast Imaging Plasma Spectrometer measures the energies and mass per charge of thermal plasma components, both within Mercury's magnetosphere and in Mercury's solar-wind environment. The primary mission observation sequence will continue for one Earth year, until March 2012. An extended mission, currently under discussion with NASA, would add a second year of orbital observations targeting a set of focused follow-on questions that build on observations to date and take advantage of the more active Sun expected during 2012-2013. MESSENGER's total primary mission cost, projected at $446 M in real-year dollars, is comparable to that of Mariner 10 after adjustment for inflation.

mercury↗
NASA NTRS2012

MESSENGER at Mercury: Early Orbital Operations

The MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) spacecraft, launched in August 2004 under NASA's Discovery Program, was inserted into orbit about the planet Mercury in March 2011. MESSENGER's three flybys of Mercury in 2008-2009 marked the first spacecraft visits to the innermost planet since the Mariner 10 flybys in 1974-1975. The unprecedented orbital operations are yielding new insights into the nature and evolution of Mercury. The scientific questions that frame the MESSENGER mission led to the mission measurement objectives to be achieved by the seven payload instruments and the radio science experiment. Interweaving the full set of required orbital observations in a manner that maximizes the opportunity to satisfy all mission objectives and yet meet stringent spacecraft pointing and thermal constraints was a complex optimization problem that was solved with a software tool that simulates science observations and tracks progress toward meeting each objective. The final orbital observation plan, the outcome of that optimization process, meets all mission objectives. MESSENGER's Mercury Dual Imaging System is acquiring a global monochromatic image mosaic at better than 90%coverage and at least 250 m average resolution, a global color image mosaic at better than 90%coverage and at least 1 km average resolution, and global stereo imaging at better than 80%coverage and at least 250 m average resolution. Higher-resolution images are also being acquired of targeted areas. The elemental remote sensing instruments, including the Gamma-Ray and Neutron Spectrometer and the X-Ray Spectrometer, are being operated nearly continuously and will establish the average surface abundances of most major elements. The Visible and Infrared Spectrograph channel of MESSENGER's Mercury Atmospheric and Surface Composition Spectrometer is acquiring a global map of spectral reflectance from 300 to 1450 nm wavelength at a range of incidence and emission angles. Targeted areas have been selected for spectral coverage into the ultraviolet with the Ultraviolet and Visible Spectrometer (UVVS). MESSENGER's Mercury Laser Altimeter is acquiring topographic profiles when the slant range to Mercury's surface is less than 1800 km, encompassing latitudes from 201S to the north pole. Topography over the remainder of the southern hemisphere will be derived from stereo imaging, radio occultations, and limb profiles. MESSENGER's radio science experiment is determining Mercury's gravity field from Doppler signals acquired during frequent downlinks. MESSENGER's Magnetometer is measuring the vector magnetic field both within Mercury's magnetosphere and in Mercury's solar wind environment at an instrument sampling rate of up to 20 samples/s. The UVVS is determining the three-dimensional, time-dependent distribution of Mercury's exospheric neutral and ionic species via their emission lines. During each spacecraft orbit, the Energetic Particle Spectrometer measures energetic electrons and ions, and the Fast Imaging Plasma Spectrometer measures the energies and mass per charge of thermal plasma components, both within Mercury's magnetosphere and in Mercury's solar-wind environment. The primary mission observation sequence will continue for one Earth year, until March 2012. An extended mission, currently under discussion with NASA, would add a second year of orbital observations targeting a set of focused follow-on questions that build on observations to date and take advantage of the more active Sun expected during 2012-2013. MESSENGER's total primary mission cost, projected at $446 M in real-year dollars, is comparable to that of Mariner 10 after adjustment for inflation.

Planetary Science↗
DOE OSTI2022

The Arabidopsis T‐DNA mutant SALK_008491 carries a 14‐kb deletion on chromosome 3 that provides rare insights into the plant response to dynamic light stress

Abstract In nature, plants experience rapid changes in light intensity and quality throughout the day. To maximize growth, they have established molecular mechanisms to optimize photosynthetic output while protecting components of the light‐dependent reaction and CO 2 fixation pathways. Plant phenotyping of mutant collections has become a powerful tool to unveil the genetic loci involved in environmental acclimation. Here, we describe the phenotyping of the transfer‐DNA (T‐DNA) insertion mutant line SALK_008491, previously known as nhd1‐1 . Growth in a fluctuating light regime caused a loss in growth rate accompanied by a spike in photosystem (PS) II damage and increased non‐photochemical quenching (NPQ). Interestingly, an independent nhd1 null allele did not recapitulate the NPQ phenotype. Through bulk sequencing of a backcrossed segregating F 2 pool, we identified an ~14‐kb large deletion on chromosome 3 (Chr3) in SALK_008491 affecting five genes upstream of NHD1 . Besides NHD1 , which encodes for a putative plastid Na + /H + antiporter, the stromal NAD‐dependent D‐3‐phosphoglycerate dehydrogenase 3 ( PGDH3 ) locus was eradicated. Although some changes in the SALK_008491 mutant's photosynthesis can be assigned to the loss of PGDH3, our follow‐up studies employing respective single mutants and complementation with overlapping transformation‐competent artificial chromosome (TAC) vectors reveal that the exacerbated fluctuating light sensitivity in SALK_008491 mutants result from the simultaneous loss of PGDH3 and NHD1. Altogether, the data obtained from this large deletion‐carrying mutant provide new and unintuitive insights into the molecular mechanisms that function to protect the photosynthetic machinery. Moreover, our study renews calls for caution when setting up reverse genetic studies using T‐DNA lines. Although second‐site insertions, indels, and SNPs have been reported before, large deletion surrounding the insertion site causes yet another problem. Nevertheless, as shown through this research, such unpredictable genetic events following T‐DNA mutagenesis can provide unintuitive insights that allow for understanding complex phenomena such as the plant acclimation to dynamic high light stress.

Lopez, Laura S.↗
DOE OSTI2017

Enhancement of Environmental Hazard Degradation in the Presence of Lignin: a Proteomics Study

Proteomics studies of fungal systems have progressed dramatically based on the availability of more fungal genome sequences in recent years. Different proteomics strategies have been applied toward characterization of fungal proteome and revealed important gene functions and proteome dynamics. Presented here is the application of shot-gun proteomic technology to study the bio-remediation of environmental hazards by white-rot fungus. Lignin, a naturally abundant component of the plant biomass, is discovered to promote the degradation of Azo dye by white-rot fungus Irpex lacteus CD2 in the lignin/dye/fungus system. Shotgun proteomics technique was used to understand degradation mechanism at the protein level for the lignin/dye/fungus system. Our proteomics study can identify about two thousand proteins (one third of the predicted white-rot fungal proteome) in a single experiment, as one of the most powerful proteomics platforms to study the fungal system to date. The study shows a significant enrichment of oxidoreduction functional category under the dye/lignin combined treatment. An in vitro validation is performed and supports our hypothesis that the synergy of Fenton reaction and manganese peroxidase might play an important role in DR5B dye degradation. The results could guide the development of effective bioremediation strategies and efficient lignocellulosic biomass conversion.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Improved annotation of the insect vector of citrus greening disease: biocuration by a diverse genomics community

The Asian citrus psyllid ( Diaphorina citri Kuwayama) is the insect vector of the bacterium Candidatus Liberibacter asiaticus (CLas), the pathogen associated with citrus Huanglongbing (HLB, citrus greening). HLB threatens citrus production worldwide. Suppression or reduction of the insect vector using chemical insecticides has been the primary method to inhibit the spread of citrus greening disease. Accurate structural and functional annotation of the Asian citrus psyllid genome, as well as a clear understanding of the interactions between the insect and CLas, are required for development of new molecular-based HLB control methods. A draft assembly of the D. citri genome has been generated and annotated with automated pipelines. However, knowledge transfer from well-curated reference genomes such as that of Drosophila melanogaster to newly sequenced ones is challenging due to the complexity and diversity of insect genomes. To identify and improve gene models as potential targets for pest control, we manually curated several gene families with a focus on genes that have key functional roles in D. citri biology and CLas interactions. This community effort produced 530 manually curated gene models across developmental, physiological, RNAi regulatory and immunity-related pathways. As previously shown in the pea aphid, RNAi machinery genes putatively involved in the microRNA pathway have been specifically duplicated. A comprehensive transcriptome enabled us to identify a number of gene families that are either missing or misassembled in the draft genome. In order to develop biocuration as a training experience, we included undergraduate and graduate students from multiple institutions, as well as experienced annotators from the insect genomics research community. The resulting gene set (OGS v1.0) combines both automatically predicted and manually curated gene models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Hardware-Based Emulator with Deep Learning Model for Building Energy Control and Prediction Based on Occupancy Sensors’ Data

Heating, ventilation, and air conditioning (HVAC) is the largest source of residential energy consumption. Occupancy sensors’ data can be used for HVAC control since it indicates the number of people in the building. HVAC and sensors form a typical cyber-physical system (CPS). In this paper, we aim to build a hardware-based emulation platform to study the occupancy data’s features, which can be further extracted by using machine learning models. In particular, we propose two hardware-based emulators to investigate the use of wired/wireless communication interfaces for occupancy sensor-based building CPS control, and the use of deep learning to predict the building energy consumption with the sensor data. We hypothesize is that the building energy consumption may be predicted by using the occupancy data collected by the sensors, and question what type of prediction model should be used to accurately predict the energy load. Another hypothesis is that an in-lab hardware/software platform could be built to emulate the occupancy sensing process. The machine learning algorithms can then be used to analyze the energy load based on the sensing data. To test the emulator, the occupancy data from the sensors is used to predict energy consumption. The synchronization scheme between sensors and the HVAC server will be discussed. We have built two hardware/software emulation platforms to investigate the sensor/HVAC integration strategies, and used an enhanced deep learning model—which has sequence-to-sequence long short-term memory (Seq2Seq LSTM)—with an attention model to predict the building energy consumption with the preservation of the intrinsic patterns. Because the long-range temporal dependencies are captured, the Seq2Seq models may provide a higher accuracy by using LSTM architectures with encoder and decoder. Meanwhile, LSTMs can capture the temporal and spatial patterns of time series data. The attention model can highlight the most relevant input information in the energy prediction by allocating the attention weights. The communication overhead between the sensors and the HVAC control server can also be alleviated via the attention mechanism, which can automatically ignore the irrelevant information and amplify the relevant information during CNN training. Our experiments and performance analysis show that, compared with the traditional LSTM neural network, the performance of the proposed method has a 30% higher prediction accuracy.

Ye, Zhijing↗