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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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At least 37 records · Page 2

Combinatorial transcription factor binding encodes cis -regulatory wiring of mouse forebrain GABAergic neurogenesis

Transcription factors (TFs) bind combinatorially to cis-regulatory elements, orchestrating transcriptional programs. Although studies of chromatin state and chromosomal interactions have demonstrated dynamic neurodevelopmental cis-regulatory landscapes, parallel understanding of TF interactions lags. To elucidate combinatorial TF binding driving mouse basal ganglia development, we integrated chromatin immunoprecipitation sequencing (ChIP-seq) for twelve TFs, H3K4me3-associated enhancer-promoter interactions, chromatin and gene expression data, and functional enhancer assays. We identified sets of putative regulatory elements with shared TF binding (TF-pRE modules) that orchestrate distinct processes of GABAergic neurogenesis and suppress other cell fates. The majority of pREs were bound by one or two TFs; however, a small proportion were extensively bound. These sequences had exceptional evolutionary conservation and motif density, complex chromosomal interactions, and activity as in vivo enhancers. Our results provide insights into the combinatorial TF-pRE interactions that activate and repress expression programs during telencephalon neurogenesis and demonstrate the value of TF binding toward modeling developmental transcriptional wiring.

59 BASIC BIOLOGICAL SCIENCES

SetBERT: the deep learning platform for contextualized embeddings and explainable predictions from high-throughput sequencing

MOTIVATION: High-throughput sequencing (HTS) is a modern sequencing technology used to profile microbiomes by sequencing thousands of short genomic fragments from the microorganisms within a given sample. This technology presents a unique opportunity for artificial intelligence to comprehend the underlying functional relationships of microbial communities. However, due to the unstructured nature of HTS data, nearly all computational models are limited to processing DNA sequences individually. This limitation causes them to miss out on key interactions between microorganisms, significantly hindering our understanding of how these interactions influence the microbial communities as a whole. Furthermore, most computational methods rely on post-processing of samples which could inadvertently introduce unintentional protocol-specific bias. RESULTS: Addressing these concerns, we present SetBERT, a robust pre-training methodology for creating generalized deep learning models for processing HTS data to produce contextualized embeddings and be fine-tuned for downstream tasks with explainable predictions. By leveraging sequence interactions, we show that SetBERT significantly outperforms other models in taxonomic classification with genus-level classification accuracy of 95%. Furthermore, we demonstrate that SetBERT is able to accurately explain its predictions autonomously by confirming the biological-relevance of taxa identified by the model. AVAILABILITY AND IMPLEMENTATION: All source code is available at https://github.com/DLii-Research/setbert. SetBERT may be used through the q2-deepdna QIIME 2 plugin whose source code is available at https://github.com/DLii-Research/q2-deepdna.

Ludwig, David W

LRIR observations of diurnal ozone variation in the mesosphere

The Limb Radiance Inversion Radiometer (LRIR) on the Nimbus 6 spacecraft obtained measurements of atmospheric infrared emission from which vertical profiles of temperature and ozone mixing ratio can be deduced. A three day sequence of data on either side of the evening terminator has been analyzed as a function of solar zenith angle (35 deg to 105 deg) and pressure level (2 mb to .1 mb). The response of the ozone field to solar flux extinction, temperature variability, and nighttime recombination are readily detected.

Anderson, G. P.

Software simulator for multiple computer simulation system

A description is given of the structure and use of a computer program that simulates the operation of a parallel processor simulation system. The program is part of an investigation to determine algorithms that are suitable for simulating continous systems on a parallel processor configuration. The simulator is designed to accurately simulate the problem-solving phase of a simulation study. Care has been taken to ensure the integrity and correctness of data exchanges and to correctly sequence periods of computation and periods of data exchange. It is pointed out that the functions performed during a problem-setup phase or a reset phase are not simulated. In particular, there is no attempt to simulate the downloading process that loads object code into the local, transfer, and mapping memories of processing elements or the memories of the run control processor and the system control processor. The main program of the simulator carries out some problem-setup functions of the system control processor in that it requests the user to enter values for simulation system parameters and problem parameters. The method by which these values are transferred to the other processors, however, is not simulated.

Ogrady, E. P.

Estimation of a remote sensing system point-spread function from measured imagery

A general approach to identifying the point spread function (PSF) of a remotely sensed scene is demonstrated in terms of a step function for an abrupt change in the gray level along the row or column of the image data. The estimate of the PSF is made in terms of a finite sum of basis functions, employing a sequence of rectangular pulses covering the spatial extent of the PSF. The approximation, if narrow impulses are employed, provides accurate fidelity to the PSF. The method becomes practical when the geometrical structure of the scene elements producing the measured response is known. The field boundary is obtained through consideration of the differing intensities on each side of the boundary, which is a step discontinuity. The mathematical procedure for the technique is provided, together with a sample problem from Landsat-4 Thematic Mapper data. Atmospheric blurring and electronic effects on the overall PSF and the cubic convolution resampling effects are noted.

Mcgillem, C. D.

Tetranucleotide frequencies differentiate genomic boundaries and metabolic strategies across environmental microbiomes

Microbiomes are constrained by physicochemical conditions, nutrient regimes, and community interactions across diverse environments, yet genomic signatures of this adaptation remain unclear. Metagenome sequencing is a powerful technique to analyze genomic content in the context of natural environments, establishing concepts of microbial ecological trends. Here, we developed a data discovery tool-a tetranucleotide-informed metagenome stability diagram-that is publicly available in the integrated microbial genomes and microbiomes (IMG/M) platform for metagenome ecosystem analyses. We analyzed the tetranucleotide frequencies from quality-filtered and unassembled sequence data of over 12,000 metagenomes to assess ecosystem-specific microbial community composition and function. We found that tetranucleotide frequencies can differentiate communities across various natural environments and that specific functional and metabolic trends can be observed in this structuring. Our tool places metagenomes sampled from diverse environments into clusters and along gradients of tetranucleotide frequency similarity, suggesting microbiome community compositions specific to gradient conditions. Within the resulting metagenome clusters, we identify protein-coding gene identifiers that are most differentiated between ecosystem classifications. We plan for annual updates to the metagenome stability diagram in IMG/M with new data, allowing for refinement of the ecosystem classifications delineated here. This framework has the potential to inform future studies on microbiome engineering, bioremediation, and the prediction of microbial community responses to environmental change. IMPORTANCE: Microbes adapt to diverse environments influenced by factors like temperature, acidity, and nutrient availability. We developed a new tool to analyze and visualize the genetic makeup of over 12,000 microbial communities, revealing patterns linked to specific functions and metabolic processes. This tool groups similar microbial communities and identifies characteristic genes within environments. By continually updating this tool, we aim to advance our understanding of microbial ecology, enabling applications like microbial engineering, bioremediation, and predicting responses to environmental change.

Kellom, Matthew

AMPS data management concepts

Five typical AMPS experiments were formulated to allow simulation studies to verify data management concepts. Design studies were conducted to analyze these experiments in terms of the applicable procedures, data processing and displaying functions. Design concepts for AMPS data management system are presented which permit both automatic repetitive measurement sequences and experimenter-controlled step-by-step procedures. Extensive use is made of a cathode ray tube display, the experimenters' alphanumeric keyboard, and the computer. The types of computer software required by the system and the possible choices of control and display procedures available to the experimenter are described for several examples. An electromagnetic wave transmission experiment illustrates the methods used to analyze data processing requirements.

Metzelaar, P. N.

A scheme for handling arrays in data-flow systems

An examination of the effects of atomicity (higher resolution) on the performance of array processors (data-flow computers) is presented. Data-flow principles are reviewed, noting the reliance on parallel processing using functional languages to specify sequencing of the operations. Techniques are described for eliminating the necessity of copying whole arrays between processing steps, thereby reducing the number of store cycles. The method involves setting whole columns to specific values rather than individual elements. The individual column values can be processed in parallel, i.e., a locally optimized condition exists. A drawback of the system is the need for more low level arguments, to identify the appropriate processing sequences, and high system complexity.

Gaudiot, J.-L.

MicroFisher: Fungal taxonomic classification for metatranscriptomic and metagenomic data using multiple short hypervariable markers

AbstractProfiling the taxonomic and functional composition of microbes using metagenomic (MG) and metatranscriptomic (MT) sequencing is advancing our understanding of microbial functions. However, the sensitivity and accuracy of microbial classification using genome– or core protein-based approaches, especially the classification of eukaryotic organisms, is limited by the availability of genomes and the resolution of sequence databases. To address this, we propose the MicroFisher, a novel approach that applies multiple hypervariable marker genes to profile fungal communities from MGs and MTs. This approach utilizes the hypervariable regions of ITS and large subunit (LSU) rRNA genes for fungal identification with high sensitivity and resolution. Simultaneously, we propose a computational pipeline (MicroFisher) to optimize and integrate the results from classifications using multiple hypervariable markers. To test the performance of our method, we applied MicroFisher to the synthetic community profiling and found high performance in fungal prediction and abundance estimation. In addition, we also used MGs from forest soil and MTs of root eukaryotic microbes to test our method and the results showed that MicroFisher provided more accurate profiling of environmental microbiomes compared to other classification tools. Overall, MicroFisher serves as a novel pipeline for classification of fungal communities from MGs and MTs.

Wang, Haihua

A genomic view of Earth’s biomes

Microorganisms are essential to all life on Earth through critical roles in key biological processes and diverse interactions with other organisms that shape ecosystems, drive biogeochemical cycles and influence both human health and environmental health. High-throughput sequencing from environmental samples has revolutionized the understanding of microbial diversity and functions. With vast amounts of genomes now available across Earth’s biomes, these data provide a blueprint of microbial life that can be harnessed for a more holistic understanding of microbiome structure and function across the various ecosystems on Earth. Here we review the application of genome-centric approaches, including recent advances in single-cell sequencing and functional profiling, to survey microbial and viral diversity. Furthermore, we highlight some of the most impactful evolutionary and functional discoveries, explore the spatial diversity and temporal dynamics of microorganisms across diverse environments, and discuss genome-enabled insights into host-associated microorganisms.

Ecology

Studies in astronomical time series analysis: Modeling random processes in the time domain

Random process models phased in the time domain are used to analyze astrophysical time series data produced by random processes. A moving average (MA) model represents the data as a sequence of pulses occurring randomly in time, with random amplitudes. An autoregressive (AR) model represents the correlations in the process in terms of a linear function of past values. The best AR model is determined from sampled data and transformed to an MA for interpretation. The randomness of the pulse amplitudes is maximized by a FORTRAN algorithm which is relatively stable numerically. Results of test cases are given to study the effects of adding noise and of different distributions for the pulse amplitudes. A preliminary analysis of the optical light curve of the quasar 3C 273 is given.

Scargle, J. D.

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

Development of the Coastal Zone Color Scanner for NIMBUS 7. Volume 2: Test and performance data, revision A

The results of the Coastal Zone Color Scanner protoflight tests are examined in detail while some of the test results are evaluated with respect to expected performance. Performance characteristics examined include spectral response, signal to noise ratio as a function of radiance input, radiance response, the modulation transfer function, and the field of view and coregistration. The results of orbital sequence tests are also included. The in orbit performance or return of radiometric data in the six spectral bands is evaluated along with the data processing sequence necessary to derive the final data products. Examples of the raw data are given and the housekeeping or diagnostic data which provides information on the day to day health or status of the instrument are discussed.

Source record

ATS-6 flight accelerometers

Five accelerometers mounted near the adapter base of the Titan 3-C launch vehicle and three on the hub of the ATS-F spacecraft provided (1) data for verifying basic spacecraft mode shapes and frequencies during powered flight while attached to the launch vehicle; (2) failure mode detection and diagnostic information on in-flight anomalies; and (3) data to be used in the design of future spacecraft to be flown on the Titan 3-C. Because data from the instruments mounted on the spacecraft hub passed through an in-flight disconnect at the separation plane between the transtage and ATS-F, the moment this connector was broken, the signal to the telemetry system showed a step function change. By monitoring these telemetry traces on the ground at appropriate times during flight sequences, a positive indication of spacecraft separation was obtained. Flight data showing dynamic response at spacecraft launch vehicle interface and at the top of ATS spacecraft during significant launch events are presented in tables.

Mattson, R.

Mariner 9 data storage subsystem flight performance summary

The performance is summarized of the Mariner 9 Data Storage Subsystem (DSS) throughout the primary and extended missions. Information presented is limited to reporting of anomalies which occurred during the playback sequences. Tables and figures describe the anomalies (dropouts, missing and added bits, in the imaging data) as a function of time (accumulated tape passes). The data results indicate that the performance of the DSS was satisfactory and within specification throughout the mission. The data presented is taken from the Spacecraft Team Incident/Surprise Anomaly Log recorded during the mission. Pertinent statistics concerning the tape transport performance are given. Also presented is a brief description of DSS operation, particularly that related to the recorded anomalies. This covers the video data encoding and how it is interpreted/decoded by ground data processing and the functional operation of the DSS in abnormal conditions such as loss of lock to the playback signal.

Thomas, N. E.

The NASTRAN user's manual

All information directly associated with problem solving using the NASTRAN program is presented. This structural analysis program uses the finite element approach to structural modeling wherein the distributed finite properties of a structure are represented by a finite element of structural elements which are interconnected at a finite number of grid points, to which loads are applied and for which displacements are calculated. Procedures are described for defining and loading a structural model. Functional references for every card used for structural modeling, the NASTRAN data deck and control cards, problem solution sequences (rigid formats), using the plotting capability, writing a direct matrix abstraction program, and diagnostic messages are explained. A dictionary of mnemonics, acronyms, phrases, and other commonly used NASTRAN terms is included.

Source record

Programs for analysis and resizing of complex structures

The paper describes the PARS (Programs for Analysis and Resizing of Structures) system. PARS is a user oriented system of programs for the minimum weight design of structures modeled by finite elements and subject to stress, displacement, flutter and thermal constraints. The system is built around SPAR - an efficient and modular general purpose finite element program, and consists of a series of processors that communicate through the use of a data base. An efficient optimizer based on the Sequence of Unconstrained Minimization Technique (SUMT) with an extended interior penalty function and Newton's method is used. Several problems are presented for demonstration of the system capabilities.

Haftka, R. T.