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At least 73 records · Page 4

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NASA NTRS1991

Changing environments of pre-main-sequence stars and their effect on the 3 microns ice feature

Three micron spectra of three premain-sequence stellar objects are presented. The heavily embedded infrared source HH100-IR, and two optically visible stars that apparently power the Herbig-Haro objects HH52, 53, 54, and HH57, are likely to represent different stages during early stellar evolution. The medium-resolution spectra of HH100-IR confirm the existence of a very strong ice band absorption (optical depth 0.8-1.2 at 3.07 microns) discovered by Whittet & Blades MNRAS, 191, 309 (1980) with lower resolution. Each of the visible stars shows a weaker (optical depth 0.2-0.4) water-ice feature but with a relatively prominent absorption dip at 2.97 microns which it is believed is due to ammonia ice. A detailed inspection of the line profiles suggests that the environment around the optically visible stars is significantly warmer (about 100 K) than that around HH100-IR (about 10-20 K) and that processing of remnant circumstellar dust is already underway.

Graham, J. A.↗

DOE OSTI2018

Contradictory Feature Size Effects in the Tensile Yield Strength of Cu Sheets Produced Using Different Sequences Involving Annealing, Rolling, and Grinding

The feature size effect is significant research interest in the field of microforming. It is assumed that the size effect is influenced by the material preparation process. To verify this, the feature size effects associated with the tensile yield strength of Cu sheets with thicknesses ranging from 100 to 200 μm, produced using different sequences involving annealing, rolling, and grinding, were studied. Differing feature size effects were observed in the Cu specimens, and it was confirmed that the size effect was indeed influenced by the specimen preparation sequence. The tensile yield strengths of the annealed–ground–rolled and annealed–rolled specimens increased as the specimen thicknesses decreased. However, an opposing size effect was observed in the case of the annealed–rolled–annealed, annealed–ground, and annealed–rolled–ground specimens. The reduction ratio did not alter the trend associated with the size effect, but influenced the intensity of the size effect. It is believed that the reinforcement and erosion of the surface-hardened layer introduced during rolling resulted in the contradictory results.

36 MATERIALS SCIENCE↗

NASA NTRS1995

Statistical properties of DNA sequences

We review evidence supporting the idea that the DNA sequence in genes containing non-coding regions is correlated, and that the correlation is remarkably long range--indeed, nucleotides thousands of base pairs distant are correlated. We do not find such a long-range correlation in the coding regions of the gene. We resolve the problem of the "non-stationarity" feature of the sequence of base pairs by applying a new algorithm called detrended fluctuation analysis (DFA). We address the claim of Voss that there is no difference in the statistical properties of coding and non-coding regions of DNA by systematically applying the DFA algorithm, as well as standard FFT analysis, to every DNA sequence (33301 coding and 29453 non-coding) in the entire GenBank database. Finally, we describe briefly some recent work showing that the non-coding sequences have certain statistical features in common with natural and artificial languages. Specifically, we adapt to DNA the Zipf approach to analyzing linguistic texts. These statistical properties of non-coding sequences support the possibility that non-coding regions of DNA may carry biological information.

Non-NASA Center↗

NASA NTRS1977

Cluster compression algorithm: A joint clustering/data compression concept

The Cluster Compression Algorithm (CCA), which was developed to reduce costs associated with transmitting, storing, distributing, and interpreting LANDSAT multispectral image data is described. The CCA is a preprocessing algorithm that uses feature extraction and data compression to more efficiently represent the information in the image data. The format of the preprocessed data enables simply a look-up table decoding and direct use of the extracted features to reduce user computation for either image reconstruction, or computer interpretation of the image data. Basically, the CCA uses spatially local clustering to extract features from the image data to describe spectral characteristics of the data set. In addition, the features may be used to form a sequence of scalar numbers that define each picture element in terms of the cluster features. This sequence, called the feature map, is then efficiently represented by using source encoding concepts. Various forms of the CCA are defined and experimental results are presented to show trade-offs and characteristics of the various implementations. Examples are provided that demonstrate the application of the cluster compression concept to multi-spectral images from LANDSAT and other sources.

Hilbert, E. E.↗

DOE OSTI2025

Uncovering Sequence and Structural Characteristics of Fungal Expansin‐Related Proteins With Potential to Drive Substrate Targeting

Expansins loosen plant cell wall networks through disrupting non-covalent bonds between cellulose microfibrils and matrix polysaccharides. Whereas expansins were first discovered in plants, expansin-related proteins have since been identified in bacteria and fungi. The biological function of microbial expansins remains unclear; however, several studies have shown distinct binding preferences toward different structural polysaccharides. Earlier studies of bacterial expansin-related proteins uncovered sequence and structural features that correlate to substrate binding. Herein, 20 fungal expansin-related sequences were recombinantly produced in Komagataella phaffii, and the purified proteins were compared in terms of substrate binding to cellulosic and chitinous substrates. The impact of pH on the zeta potential of prioritized substrates was also measured, and Principal Component Analysis was performed to uncover correlations between protein characteristics (e.g., pI, hydrophobicity, surface charge distribution) and measured substrate binding preferences. Whereas acidic proteins with a predicted pI less than 5.0 preferentially bound to chitin, basic proteins with pI greater than 8.0 preferentially bound to xylan and xylan-containing fiber. Similar to many cellulases, binding to cellulose was correlated to relatively high aromatic amino acid content in the protein sequence and presence of a carbohydrate binding module (CBM), which in the case of expansins is a C-terminal CBM63. Whereas overall sequence characteristics could be correlated to substrate binding preference, the identity of amino acids occupying conserved positions that impact protein activity was better correlated with loosenin versus expansin classifications.

chitin↗

DOE OSTI2020

Uncovering DNA-PKcs ancient phylogeny, unique sequence motifs and insights for human disease

DNA-dependent protein kinase catalytic subunit (DNA-PKcs) is a key member of the phosphatidylinositol-3 kinase-like (PIKK) family of protein kinases with critical roles in DNA-double strand break repair, transcription, metastasis, mitosis, RNA processing, and innate and adaptive immunity. The absence of DNA-PKcs from many model organisms has led to the assumption that DNA-PKcs is a vertebrate-specific PIKK. Here, we find that DNA-PKcs is widely distributed in invertebrates, fungi, plants, and protists, and that threonines 2609, 2638, and 2647 of the ABCDE cluster of phosphorylation sites are highly conserved amongst most Eukaryotes. Furthermore, we identify highly conserved amino acid sequence motifs and domains that are characteristic of DNA-PKcs relative to other PIKKs. These include residues in the Forehead domain and a novel motif we have termed YRPD, located in an α helix C-terminal to the ABCDE phosphorylation site loop. Combining sequence with biochemistry plus structural data on human DNA-PKcs unveils conserved sequence and conformational features with functional insights and implications. The defined generally progressive DNA-PKcs sequence diversification uncovers conserved functionality supported by Evolutionary Trace analysis, suggesting that for many organisms both functional sites and evolutionary pressures remain identical due to fundamental cell biology. The mining of cancer genomic data and germline mutations causing human inherited disease reveal that robust DNA-PKcs activity in tumors is detrimental to patient survival, whereas germline mutations compromising function are linked to severe immunodeficiency and neuronal degeneration. We anticipate that these collective results will enable ongoing DNA-PKcs functional analyses with biological and medical implications.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1992

Amazonis and Utopia Planitiae: Martian Lacustrine basins

Amazonis and Utopia Planitiae are two large (greater than 10(exp 6) sq. km) basins on Mars having morphological features commonly associated with former lakes. The investigation of these areas is an extension of our previous paleolake studies in the Elysium basin. Using Viking images, we are searching for familiar geologic forms commonly associated with standing bodies of water on Earth. Like Elysium, the two basins exhibit terraces and lineations resembling shorelines, etched and infilled floors with channel-like sinuous markings in places, inflow channels along their borders, and other geomorphic indicators believed to be related to the presence of water and ice. In some areas these features are better displayed than in others where they may be very tenuous; their value as indicators can be justified only by their association with related features. Even though these postulated paleolakes are very young in the Martian stratigraphic sequence, their shoreline features are poorly preserved and they are probably much older than large Pleistocene lakes on Earth.

Scott, David H.↗

NASA NTRS1980

Central peaks in Mercurian craters - Comparisons to the moon

A key question in cratering studies continues to be the mode of formation of central structures. Studies of central peaks, the smallest and simplest central features found in impact structures, could provide clues to the formational mechanisms of the entire morphologic sequence of central features. The present investigation is concerned with a systematic examination of central peaks in fresh Mercurian craters, and a comparison of Mercurian and lunar central peak morphometry and morphology. It is found that the central peak diameter/rim diameter relation on Mercury is indistinguishable from the lunar case. The gravitational field strength of the planet, therefore, does not appear to be the dominant force controlling central peak formation. Of the presently proposed processes for central peak formation, dynamic rebound best fits current observations.

Hale, W.↗

NASA NTRS1984

Io's sodium directional features - Evidence for a magnetospheric-wind-driven gas escape mechanism

Elongated features in Io's sodium cloud, directed away from Jupiter and inclined both to the north and to the south of the satellite's orbital plane, have been observed. The north/south directions of the features are correlated with Io's magnetic longitude, suggesting a formation mechanism involving the oscillating plasma torus. It is shown by means of a model analysis that the features can result from a source of high-velocity (about 20 km/s) sodium combined with the oscillating neutral sodium sink provided by the plasma. The phase relationship between the features' directions and Io's magnetic longitude can be understood if escaping sodium is initially directed at near right angles to Io's orbital motion. The directionality of the features requires that the sodium flux from equatorial regions be higher than that from the poles. The initial directions and speeds of sodium atoms escaping Io to form the directional features can be understood in terms of a magnetospheric-wind-driven escape mechanism. The one sequence of directional feature observations that has been analyzed in detail implies a high-speed sodium source rate of about 10 to the 26th atoms/s.

Pilcher, C. B.↗

NASA NTRS2010

Real-Time Feature Tracking Using Homography

This software finds feature point correspondences in sequences of images. It is designed for feature matching in aerial imagery. Feature matching is a fundamental step in a number of important image processing operations: calibrating the cameras in a camera array, stabilizing images in aerial movies, geo-registration of images, and generating high-fidelity surface maps from aerial movies. The method uses a Shi-Tomasi corner detector and normalized cross-correlation. This process is likely to result in the production of some mismatches. The feature set is cleaned up using the assumption that there is a large planar patch visible in both images. At high altitude, this assumption is often reasonable. A mathematical transformation, called an homography, is developed that allows us to predict the position in image 2 of any point on the plane in image 1. Any feature pair that is inconsistent with the homography is thrown out. The output of the process is a set of feature pairs, and the homography. The algorithms in this innovation are well known, but the new implementation improves the process in several ways. It runs in real-time at 2 Hz on 64-megapixel imagery. The new Shi-Tomasi corner detector tries to produce the requested number of features by automatically adjusting the minimum distance between found features. The homography-finding code now uses an implementation of the RANSAC algorithm that adjusts the number of iterations automatically to achieve a pre-set probability of missing a set of inliers. The new interface allows the caller to pass in a set of predetermined points in one of the images. This allows the ability to track the same set of points through multiple frames.

Clouse, Daniel S.↗

DOE OSTI2025

Machine learning guided selection of broad-spectrum epitope-specific functional antibodies for "Disease X"

Our project established and demonstrated a transfer learning framework that enables prediction of antibody–antigen interactions across related viruses. The approach focused on three major activities: 1. Conserved region and epitope identification – We compared viral protein structures and sequences to identify shared receptor-binding domains and neutralizing epitope regions across variants and related viruses. These conserved features formed the foundation for discovering broadly functional antibodies. 2. Machine learning model development – We built neural network–based models that integrate epitope features with antibody sequence information. Instead of relying solely on structural or physical properties, the models learned transferable patterns that describe antibody binding potential across different viral families. 3. Transfer learning and validation – Using SARS-CoV-2 and Ebola as source systems, we successfully transferred learned epitope features to predict antibody interactions for SARS CoV-1 and Marburg virus. Iterative cycles of dataset generation, retraining, and evaluation improved generalization and predictive power, ensuring the framework can adapt to new threats.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Hardware In the Loop for Demand Flexibility (HIL4DF) v1.0

The software package in question is a collection of simulation models in the Modelica language, representing a variety of mechanical system designs and envelope conditions related to LBL's FLEXLAB facility. The collection of models also features multiple controls sequences that can be simulated with the FLEXLAB model to simulate different demand flexibility scenarios. Additionally, this package will feature datasets from 3 experimental tests, used for calibration, validation and comparison against the Modelica models, this includes weather data that can be used to replicate different scenarios in simulation across the same weather conditions experienced in real experiments. Given FLEXLAB high level of instrumentation and available data, the models are calibrated across multiple measurement points, and thus results from the extension of this model to other climate zones or control sequences, would provide high level of confidence.

Huang, Weiping↗

NASA NTRS2020

Shedding Light on Microbial Dark Matter with A Universal Language of Life

The majority of microbial genomes have yet to be cultured, and most proteins predicted from microbial genomes or sequenced from the environment cannot be functionally annotated. As a result, current computational approaches to describe microbial systems rely on incomplete reference databases that cannot adequately capture the full functional diversity of the microbial tree of life, limiting our ability to model high-level features of biological sequences. The scientific community needs a means to capture the functionally and evolutionarily relevant features underlying biology, independent of our incomplete reference databases. Such a model can form the basis for transfer learning tasks, enabling downstream applications in environmental microbiology, medicine, and bioengineering. Here we present LookingGlass, a deep learning model capturing a “universal language of life”. LookingGlass encodes contextually-aware, functionally and evolutionarily relevant representations of short DNA reads, distinguishing reads of disparate function, homology, and environmental origin. We demonstrate the ability of LookingGlass to be fine-tuned to perform a range of diverse tasks: to identify novel oxidoreductases, to predict enzyme optimal temperature, and to recognize the reading frames of DNA sequence fragments. LookingGlass is the first contextually-aware, general purpose pre-trained “biological language” representation model for short-read DNA sequences. LookingGlass enables functionally relevant representations of otherwise unknown and unannotated sequences, shedding light on the microbial dark matter that dominates life on Earth.

A Hoarfrost↗

NASA NTRS1982

Identification of the emission features near 3.5 microns in the pre main sequence star HD 97048

The spectrum of HD97048 was measured with a resolving power of 450 between 3.37 and 3.64 microns. The prominent feature near 3.5 microns is well resolved, with a peak at 3.53 microns and a wing extending to a shorter wavelength. The weaker feature near 3.4 microns is found to peak at 3.43 microns, in contrast to the 3.40 micron feature seen in other astronomical objects. The observed spectrum strongly resembles laboratory spectra of mixtures of monomeric and dimeric formaldehyde embedded in low temperature solids. Of various possible excitation mechanisms, ultraviolet pumped infrared fluorescence of formaldehyde in interstellar grains provides the best explanation for the observed spectrum of HD 97048.

Baas, F.↗

NASA NTRS2007

Robotic Vision-Based Localization in an Urban Environment

A system of electronic hardware and software, now undergoing development, automatically estimates the location of a robotic land vehicle in an urban environment using a somewhat imprecise map, which has been generated in advance from aerial imagery. This system does not utilize the Global Positioning System and does not include any odometry, inertial measurement units, or any other sensors except a stereoscopic pair of black-and-white digital video cameras mounted on the vehicle. Of course, the system also includes a computer running software that processes the video image data. The software consists mostly of three components corresponding to the three major image-data-processing functions: Visual Odometry This component automatically tracks point features in the imagery and computes the relative motion of the cameras between sequential image frames. This component incorporates a modified version of a visual-odometry algorithm originally published in 1989. The algorithm selects point features, performs multiresolution area-correlation computations to match the features in stereoscopic images, tracks the features through the sequence of images, and uses the tracking results to estimate the six-degree-of-freedom motion of the camera between consecutive stereoscopic pairs of images (see figure). Urban Feature Detection and Ranging Using the same data as those processed by the visual-odometry component, this component strives to determine the three-dimensional (3D) coordinates of vertical and horizontal lines that are likely to be parts of, or close to, the exterior surfaces of buildings. The basic sequence of processes performed by this component is the following: 1. An edge-detection algorithm is applied, yielding a set of linked lists of edge pixels, a horizontal-gradient image, and a vertical-gradient image. 2. Straight-line segments of edges are extracted from the linked lists generated in step 1. Any straight-line segments longer than an arbitrary threshold (e.g., 30 pixels) are assumed to belong to buildings or other artificial objects. 3. A gradient-filter algorithm is used to test straight-line segments longer than the threshold to determine whether they represent edges of natural or artificial objects. In somewhat oversimplified terms, the test is based on the assumption that the gradient of image intensity varies little along a segment that represents the edge of an artificial object.

Mchenry, Michael↗

DOE OSTI2017

Foldamer hypothesis for the growth and sequence differentiation of prebiotic polymers

It is not known how life originated. It is thought that prebiotic processes were able to synthesize short random polymers. However, then, how do short-chain molecules spontaneously grow longer? Also, how would random chains grow more informational and become autocatalytic (i.e., increasing their own concentrations)? We study the folding and binding of random sequences of hydrophobic ( H ) and polar ( P ) monomers in a computational model. We find that even short hydrophobic polar ( HP ) chains can collapse into relatively compact structures, exposing hydrophobic surfaces. In this way, they act as primitive versions of today’s protein catalysts, elongating other such HP polymers as ribosomes would now do. Such foldamer catalysts are shown to form an autocatalytic set, through which short chains grow into longer chains that have particular sequences. An attractive feature of this model is that it does not overconverge to a single solution; it gives ensembles that could further evolve under selection. This mechanism describes how specific sequences and conformations could contribute to the chemistry-to-biology (CTB) transition.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Seismic Features Predict Ground Motions During Repeating Caldera Collapse Sequence

Abstract Applying machine learning to continuous acoustic emissions, signals previously deemed noise, from laboratory faults and slowly slipping subduction‐zone faults, demonstrates hidden signatures are emitted that describe physical details, including fault displacement and friction. However, no evidence currently exists to demonstrate that similar hidden signals occur during seismogenic stick‐slip on earthquake faults—the damaging earthquakes of most societal interest. We show that continuous seismic emissions emitted during the 2018 multi‐month caldera collapse sequence at the Kı̄lauea volcano in Hawai'i contain hidden signatures characterizing the earthquake cycle. Multi‐spectral data features extracted from 30 s intervals of the continuous seismic emission are used to train a gradient boosted tree regression model to predict the GNSS‐derived contemporaneous surface displacement and time‐to‐failure of the upcoming collapse event. This striking result suggests that at least some faults emit such signals and provide a potential path to characterizing the instantaneous and future behavior of earthquake faults.

58 GEOSCIENCES↗

DOE OSTI2021

Hierarchical Nanomaterials Assembled from Peptoids and Other Sequence-Defined Synthetic Polymers

In nature, the self-assembly of sequence-specific biopolymers into hierarchical structures plays an essential role in the construction of functional biomaterials. To develop synthetic materials that can mimic and surpass the function of these natural counterparts, various sequence-defined bio- and biomimetic polymers have been developed and exploited as building blocks for hierarchical self-assembly. This review summarizes the recent advances in the molecular self-assembly of hierarchical nanomaterials based on peptoids (or poly-N-substituted glycines) and other sequence-defined synthetic polymers. Modern techniques to monitor the assembly mechanisms and characterize the physicochemical properties of these self-assembly systems are highlighted. In addition, discussions about their potential applications in biomedical sciences and renewable energy are also included. Furthermore, this review aims to highlight essential features of sequence-defined synthetic polymers (e.g., high stability and protein-like high-information content) and how these unique features enable the construction of robust biomimetic functional materials with high programmability and predictability, with an emphasis on peptoids and their self-assembled nanomaterials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗