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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Methods of combined bioprocessing and related microorganisms, thermophilic and/or acidophilic enzymes, and nucleic acids encoding said enzymes

A genetically modified organism comprising: at least one nucleic acid sequence and/or at least one recombinant nucleic acid isolated from Alicyclobacillus acidocaldarius and encoding a polypeptide involved in at least partially degrading, cleaving, transporting, metabolizing, or removing polysaccharides, cellulose, lignocellulose, hemicellulose, lignin, starch, sugars, sugar oligomers, carbohydrates, complex carbohydrates, chitin, heteroxylans, glycosides, xylan-, glucan-, galactan-, or mannan-decorating groups; and at least one nucleic acid sequence and/or at least one recombinant nucleic acid encoding a polypeptide involved in fermenting sugar molecules to a product. Additionally, enzymatic and/or proteinaceous extracts may be isolated from one or more genetically modified organisms. The extracts are utilized to convert biomass into a product. Further provided are methods of converting biomass into products comprising: placing the genetically modified organism and/or enzymatic extracts thereof in fluid contact with polysaccharides, cellulose, lignocellulose, hemicellulose, lignin, starch, sugars, sugar oligomers, carbohydrates, complex carbohydrates, chitin, heteroxylans, glycosides, and/or xylan-, glucan-, galactan-, or mannan-decorating groups.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Methods of combined bioprocessing and related microorganisms, thermophilic and/or acidophilic enzymes, and nucleic acids encoding said enzymes

A genetically modified organism comprising: at least one nucleic acid sequence and/or at least one recombinant nucleic acid isolated from Alicyclobacillus acidocaldarius and encoding a polypeptide involved in at least partially degrading, cleaving, transporting, metabolizing, or removing polysaccharides, cellulose, lignocellulose, hemicellulose, lignin, starch, sugars, sugar oligomers, carbohydrates, complex carbohydrates, chitin, heteroxylans, glycosides, xylan-, glucan-, galactan-, or mannan-decorating groups; and at least one nucleic acid sequence and/or at least one recombinant nucleic acid encoding a polypeptide involved in fermenting sugar molecules to a product. Additionally, enzymatic and/or proteinaceous extracts may be isolated from one or more genetically modified organisms. The extracts are utilized to convert biomass into a product. Further provided are methods of converting biomass into products comprising: placing the genetically modified organism and/or enzymatic extracts thereof in fluid contact with polysaccharides, cellulose, lignocellulose, hemicellulose, lignin, starch, sugars, sugar oligomers, carbohydrates, complex carbohydrates, chitin, heteroxylans, glycosides, and/or xylan-, glucan-, galactan-, or mannan-decorating groups.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Polypeptides having laccase activity and polynucleotides encoding same

The present invention relates to isolated polypeptides having laccase activity and polynucleotides encoding the polypeptides and polynucleotides encoding the polypeptides. The invention also relates to nucleic acid constructs, vectors, and host cells comprising the polynucleotides as well as methods of producing and using the polypeptides.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Spectrally encoded microbeads and methods and devices for making and using same

Spectrally encoded microbeads and methods and devices for making and using spectrally encoded microbeads are provided. The disclosed methods and devices facilitate the preparation and use of microbeads containing multiple lanthanide nanoparticles, which microbeads have uniquely identifiable spectral codes. The disclosed microbeads, and the methods and devices for making and using same, find use in multiplexing and high-throughput biomarker analysis.

Baxter, Brian Cullen↗
DOE OSTI2019

Polypeptides having cellulolytic enhancing activity and polynucleotides encoding same

The present invention provides isolated polypeptides having cellulolytic enhancing activity and polynucleotides encoding the polypeptides, catalytic domains, cellulose binding domains and polynucleotides encoding the polypeptides, catalytic domains or cellulose binding domains. The invention also provides nucleic acid constructs, vectors, and host cells comprising the polynucleotides as well as methods of producing and using the polypeptides, catalytic domains or cellulose binding domains.

Tang, Lan↗
DOE OSTI2019

Methods of combined bioprocessing and related microorganisms, thermophilic and/or acidophilic enzymes, and nucleic acids encoding said enzymes

A genetically modified organism comprising: at least one nucleic acid sequence and/or at least one recombinant nucleic acid isolated from Alicyclobacillus acidocaldarius and encoding a polypeptide involved in at least partially degrading, cleaving, transporting, metabolizing, or removing polysaccharides, cellulose, lignocellulose, hemicellulose, lignin, starch, sugars, sugar oligomers, carbohydrates, complex carbohydrates, chitin, heteroxylans, glycosides, xylan-, glucan-, galactan-, or mannan-decorating groups; and at least one nucleic acid sequence and/or at least one recombinant nucleic acid encoding a polypeptide involved in fermenting sugar molecules to a product. Additionally, enzymatic and/or proteinaceous extracts may be isolated from one or more genetically modified organisms. The extracts are utilized to convert biomass into a product. Further provided are methods of converting biomass into products comprising: placing the genetically modified organism and/or enzymatic extracts thereof in fluid contact with polysaccharides, cellulose, lignocellulose, hemicellulose, lignin, starch, sugars, sugar oligomers, carbohydrates, complex carbohydrates, chitin, heteroxylans, glycosides, and/or xylan-, glucan-, galactan-, or mannan-decorating groups.

09 BIOMASS FUELS↗
DOE OSTI2020

Methods of combined bioprocessing and related microorganisms, thermophilic and/or acidophilic enzymes, and nucleic acids encoding said enzymes

A genetically modified organism comprising: at least one nucleic acid sequence and/or at least one recombinant nucleic acid isolated from Alicyclobacillus acidocaldarius and encoding a polypeptide involved in at least partially degrading, cleaving, transporting, metabolizing, or removing polysaccharides, cellulose, lignocellulose, hemicellulose, lignin, starch, sugars, sugar oligomers, carbohydrates, complex carbohydrates, chitin, heteroxylans, glycosides, xylan-, glucan-, galactan-, or mannan-decorating groups; and at least one nucleic acid sequence and/or at least one recombinant nucleic acid encoding a polypeptide involved in fermenting sugar molecules to a product. Additionally, enzymatic and/or proteinaceous extracts may be isolated from one or more genetically modified organisms. The extracts are utilized to convert biomass into a product. Further provided are methods of converting biomass into products comprising: placing the genetically modified organism and/or enzymatic extracts thereof in fluid contact with polysaccharides, cellulose, lignocellulose, hemicellulose, lignin, starch, sugars, sugar oligomers, carbohydrates, complex carbohydrates, chitin, heteroxylans, glycosides, and/or xylan-, glucan-, galactan-, or mannan-decorating groups.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Late Breaking Results: COPPER: Computation Obfuscation by Producing Permutations for Encoding Randomly

Deployed embedded devices face security risks due to increased ease of physical access to the devices by unauthorized users. Capable adversaries can intercept a device to recover the data in memory, including results of performed sensitive computations. Device owners require data confidentiality on their physically insecure devices. To satisfy this goal we implement a novel method, COPPER (Computation Obfuscation by Producing Permutations for Encoding Randomly), to create data which never exists on the device digitally in plaintext format and which is subsequently used for computation. In this paper we utilize COPPER to calculate a moving average computation on encoded data.

embedded systems↗
DOE OSTI2025

SHF: Symmetrical Hierarchical Forest with Pretrained Vision Transformer Encoder for High-Resolution Medical Segmentation

This paper presents a novel approach to addressing the long-sequence problem in high-resolution medical images for Vision Transformers (ViTs). Using smaller patches as tokens can enhance ViT performance, but quadratically increases computation and memory requirements. Therefore, the common practice for applying ViTs to high-resolution images is either to: (a) employ complex sub-quadratic attention schemes or (b) use large to medium-sized patches and rely on additional mechanisms within the model to capture the spatial hierarchy of details. We propose Symmetrical Hierarchical Forest (SHF), a lightweight approach that adaptively patches the input image to increase token information density and encode hierarchical spatial structures into the input embedding. We then apply a reverse depatching scheme to the output embeddings of the transformer encoder, eliminating the need for convolution-based decoders. Unlike previous methods that modify attention mechanisms or use a complex hierarchy of interacting models, SHF can be retrofitted to any ViT model to allow it to learn the hierarchical structure of details in high-resolution images without requiring architectural changes. Experimental results demonstrate significant gains in computational efficiency and performance: on the PAIP WSI dataset, we achieved a 3∼32×speedup or a 2.95%∼7.03% increase in accuracy (measured by Dice score) at a 64K2 resolution with the same computational budget, compared to state-of-the-art production models. On the 3D medical datasets BTCV and KiTS, training was 6×faster, with accuracy gains of 6.93% and 5.9%, respectively, compared to models without SHF.

Zhang, Enzhi [Hokkaido University, Japan]↗
DOE OSTI2024

Generalization error guaranteed auto-encoder-based nonlinear model reduction for operator learning

Many physical processes in science and engineering are naturally represented by operators between infinite-dimensional function spaces. The problem of operator learning, in this context, seeks to extract these physical processes from empirical data, which is challenging due to the infinite or high dimensionality of data. An integral component in addressing this challenge is model reduction, which reduces both the data dimensionality and problem size. In this paper, we utilize low-dimensional nonlinear structures in model reduction by investigating Auto-Encoder-based Neural Network (AENet). AENet first learns the latent variables of the input data and then learns the transformation from these latent variables to corresponding output data. Our numerical experiments validate the ability of AENet to accurately learn the solution operator of nonlinear partial differential equations. Furthermore, we establish a mathematical and statistical estimation theory that analyzes the generalization error of AENet. Finally, our theoretical framework shows that the sample complexity of training AENet is intricately tied to the intrinsic dimension of the modeled process, while also demonstrating the robustness of AENet to noise.

Auto-encoder↗
DOE OSTI2022

Variational encoder geostatistical analysis (VEGAS) with an application to large scale riverine bathymetry

Estimation of riverbed profiles, also known as bathymetry, plays a vital role in many applications, such as safe and efficient inland navigation, prediction of bank erosion, land subsidence, and flood risk management. The high cost and complex logistics of direct bathymetry surveys, i.e, depth imaging, have encouraged the use of indirect measurements such as surface flow velocities. However, estimating high-resolution bathymetry from indirect measurements is an inverse problem that can be computationally challenging. Here, we propose a reduced-order model (ROM) based approach that utilizes a variational autoencoder (VAE), a type of deep neural network with a narrow layer in the middle, to compress bathymetry and flow velocity information and accelerate bathymetry inverse problems from flow velocity measurements. In our application, the shallow-water equations (SWE) with appropriate boundary conditions (BCs), e.g., the discharge and/or the free surface elevation, constitute the forward problem, to predict flow velocity. Then, ROMs of the SWEs are constructed on a nonlinear manifold of low dimensionality through a variational encoder and the bathymetry inversion problem is derived on the low-dimensional latent space in a Hierarchical Bayesian setting. Further, the reformulation allows variational inference with a small number (e.g., $\mathscr{O}$ (100) of ROM runs and efficient uncertainty quantification. We have tested our inversion approach on a one-mile reach of the Savannah River, GA, USA. Once the neural network is trained (offline stage), the proposed technique can perform the inversion operation orders of magnitude faster than traditional inversion methods that are commonly based on linear projections, such as principal component analysis (PCA), or the principal component geostatistical approach (PCGA). Furthermore, tests show that the algorithm can estimate the bathymetry with good accuracy even with sparse flow velocity measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Atlas of Transcription Factor Binding Sites from ENCODE DNase Hypersensitivity Data across 27 Tissue Types

Characterizing the tissue-specific binding sites of transcription factors (TFs) is essential to reconstruct gene regulatory networks and predict functions for non-coding genetic variation. DNase-seq footprinting enables the prediction of genome-wide binding sites for hundreds of TFs simultaneously. Despite the public availability of high-quality DNase-seq data from hundreds of samples, a comprehensive, up-to-date resource for the locations of genomic footprints is lacking. Here, we develop a scalable footprinting workflow using two state-of-the-art algorithms: Wellington and HINT. We apply our workflow to detect footprints in 192 ENCODE DNase-seq experiments and predict the genomic occupancy of 1,515 human TFs in 27 human tissues. We validate that these footprints overlap true-positive TF binding sites from ChIP-seq. We demonstrate that the locations, depth, and tissue specificity of footprints predict effects of genetic variants on gene expression and capture a substantial proportion of genetic risk for complex traits.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Demonstration of two-dimensional time-encoded imaging of fast neutrons

Here, we present a neutron detector system based on time-encoded imaging, and demonstrate its applicability toward the spatial mapping of special nuclear material. We also demonstrate that two-dimensional fast-neutron imaging with 2° resolution at 2 m stand-off is feasible with only two instrumented detectors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Source detection at 100 meter standoff with a time-encoded imaging system

Here, we present the design, characterization, and testing of a laboratory prototype radiological search and localization system. The system, based on time-encoded imaging, uses the attenuation signature of neutrons in time, induced by the geometrical layout and motion of the system. We have demonstrated the ability to detect a ~1 mCi 252 Cf radiological source at 100 m standoff with 90% detection efficiency and 10% false positives against background in 12 min. As a result, this same detection efficiency is met at 15 s for a 40 m standoff, and 1.2 s for a 20 m standoff.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

RanCompute: Computational Security in Embedded Devices via Random Input and Output Encodings

An embedded device in an insecure environment is subject to additional security risk through capture and reverse-engineering by a capable adversary. If this device contains a microchip performing sensitive computations, capture of the chip may leak functionality to an adversary. In this paper we propose a novel method in which we randomly encode the input operands and the outputs of a computation, thus not revealing the arithmetic operations being performed. The operations are sequenced in a graph representing the overall application. Once the initialization values are overwritten and lost, the results of these computations are indecipherable by the device performing the calculations as well as by any adversary. The result is transmitted back to a secure server which has stored the initialization values and so can decode the results which appear random to the adversary.

Embedded computing↗
DOE OSTI2021

Improved Localization Precision and Angular Resolution of a Cylindrical, Time-Encoded Imaging System From Adaptive Detector Movements

To the first order, the localization precision and angular resolution of a cylindrical, time-encoded imaging (c-TEI) system is governed by the geometry of the system. Improving either measure requires increasing the mask radius or decreasing the detector diameter, both of which are undesirable. Here, we propose an alternative option of repositioning the detector within the mask to increase the detector-to-mask distance in the direction of a source, thereby improving the localization precision and angular resolution in that direction. Since the detector-to-mask distance only increases for a small portion of the field of view (FOV), we propose implementing adaptive imaging where one leverages data collected during the measurement to optimize the system configuration. This article utilizes both simulations and experiments to set upper bounds on the potential gain from adaptive detector movements for one and two sources in the FOV. When only one source is present, adaptive detector movements can improve the localization precision and angular resolution by 20% for a source at 90 cm and by 32% for a far-field source. When two sources are present, adaptive detector movements can improve localization precision and angular resolution by up to 50% for sources that are ~10° apart (90 cm from the system). We experimentally verify these results through maximum likelihood estimation of the source position(s) and image reconstruction of point sources that are close together. As a demonstration of an adaptive imaging algorithm, we image a complex arrangement of special nuclear material at the Zero Power Physics Reactor facility at Idaho National Laboratory.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗