Search NASA⌕ Search

SEARCH · Search NASA

Results for “Block encoding”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

PDF Entity Annotation Tool (PEAT)

While different text mining approaches – including the use of Artificial Intelligence (AI) and other machine based methods - continue to expand at a rapid pace, the tools used by researchers to create the labeled datasets required for training, modeling, and evaluation remain rudimentary. Labeled datasets contain the target attributes the machine is going to learn; for example, training an algorithm to delineate between images of a car or truck would generally require a set of images with a quantitative description of the underlying features of each vehicle type. Development of labeled textual data that can be used to build natural language machine learning models for scientific literature is not currently integrated into existing manual workflows used by domain experts. Published literature is rich with important information, such as different types of embedded text, plots, and tables that can all be used as inputs to train ML/natural language processing (NLP) models, when extracted and prepared in machine readable formats. Currently, both normalized data extraction of use to domain experts and extraction to support development of ML/NLP models are labor intensive and cumbersome manual processes. Automatic extraction of data and information from formats such as PDFs that are optimized for layout and human readability, not machine readability. The PDF (Portable Document Format) Entity Annotation Tool (PEAT) was developed with the goal of allowing users to annotate publications within their current print format, while also allowing those annotations to be captured in a machine-readable format. One of the main issues with traditional annotation tools is that they require transforming the PDF into plain text to facilitate the annotation process. While doing so lessens the technical challenges of annotating data, the user loses all structure and provenance that was inherent in the underlying PDF. Also, textual data extraction from PDFs can be an error prone process. Challenges include identifying sequential blocks of text and a multitude of document formats (multiple columns, font encodings, etc.). As a result of these challenges, using existing tools for development of NLP/ML models directly from PDFs is difficult because the generated outputs are not interoperable. We created a system that allows annotations to be completed on the original PDF document structure, with no plain text extraction. The result is an application that allows for easier and more accurate annotations. In addition, by including a feature that grants the user the ability to easily create a schema, we have developed a system that can be used to annotate text for different domain-centric schemas of relevance to subject matter experts. Different knowledge domains require distinct schemas and annotation tags to support machine learning.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1973

On the performance of block codes

It is important to define and evaluate measures which incorporate most, if not all, of the quantities affecting the overall system reliability. For the simple types of block codes normally employed in space communication systems, the complexity of the encoder and decoder is of little consequence, since the use of integrated circuit technology allows the construction of the basic components in an inexpensive fashion. The complexity is essentially independent of the particular code-decoder used. The processing speed is generally a function of the type of logic used and the technology in the construction of the integrated circuits.

Helgert, H. J.↗
NASA NTRS1993

Estimating the size of Huffman code preambles

Data compression via block-adaptive Huffman coding is considered. The compressor consecutively processes blocks of N data symbols, estimates source statistics by computing the relative frequencies of each source symbol in the block, and then synthesizes a Huffman code based on these estimates. In order to let the decompressor know which Huffman code is being used, the compressor must begin the transmission of each compressed block with a short preamble or header file. This file is an encoding of the list n = (n(sub 1), n(sub 2)....,n(sub m)), where n(sub i) is the length of the Hufffman codeword associated with the ith source symbol. A simple method of doing this encoding is to individually encode each n(sub i) into a fixed-length binary word of length log(sub 2)l, where l is an a priori upper bound on the codeword length. This method produces a maximum preamble length of mlog(sub 2)l bits. The object is to show that, in most cases, no substantially shorter header of any kind is possible.

Mceliece, R. J.↗
NASA NTRS1995

Weight distributions for turbo codes using random and nonrandom permutations

This article takes a preliminary look at the weight distributions achievable for turbo codes using random, nonrandom, and semirandom permutations. Due to the recursiveness of the encoders, it is important to distinguish between self-terminating and non-self-terminating input sequences. The non-self-terminating sequences have little effect on decoder performance, because they accumulate high encoded weight until they are artificially terminated at the end of the block. From probabilistic arguments based on selecting the permutations randomly, it is concluded that the self-terminating weight-2 data sequences are the most important consideration in the design of constituent codes; higher-weight self-terminating sequences have successively decreasing importance. Also, increasing the number of codes and, correspondingly, the number of permutations makes it more and more likely that the bad input sequences will be broken up by one or more of the permuters. It is possible to design nonrandom permutations that ensure that the minimum distance due to weight-2 input sequences grows roughly as the square root of (2N), where N is the block length. However, these nonrandom permutations amplify the bad effects of higher-weight inputs, and as a result they are inferior in performance to randomly selected permutations. But there are 'semirandom' permutations that perform nearly as well as the designed nonrandom permutations with respect to weight-2 input sequences and are not as susceptible to being foiled by higher-weight inputs.

Dolinar, S.↗
DOE OSTI2016

Building blocks for subleading helicity operators

On-shell helicity methods provide powerful tools for determining scattering amplitudes, which have a one-to-one correspondence with leading power helicity operators in the Soft-Collinear Effective Theory (SCET) away from singular regions of phase space. We show that helicity based operators are also useful for enumerating power suppressed SCET operators, which encode subleading amplitude information about singular limits. In particular, we present a complete set of scalar helicity building blocks that are valid for constructing operators at any order in the SCET power expansion. In conclusion, we also describe an interesting angular momentum selection rule that restricts how these building blocks can be assembled.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Hierarchical Materials from High Information Content Macromolecular Building Blocks: Construction, Dynamic Interventions, and Prediction

Hierarchical materials that exhibit order over multiple length scales are ubiquitous in nature. Because hierarchy gives rise to unique properties and functions, many have sought inspiration from nature when designing and fabricating hierarchical matter. More and more, however, nature’s own high-information content building blocks, proteins, peptides, and peptidomimetics, are being coopted to build hierarchy because the information that determines structure, function, and interfacial interactions can be readily encoded in these versatile macromolecules. Here, we take stock of recent progress in the rational design and characterization of hierarchical materials produced from high-information content blocks with a focus on stimuli-responsive and “smart” architectures. We also review advances in the use of computational simulations and data-driven predictions to shed light on how the side chain chemistry and conformational flexibility of macromolecular blocks drive the emergence of order and the acquisition of hierarchy and also on how ionic, solvent, and surface effects influence the outcomes of assembly. Furthermore, continued progress in the above areas will ultimately usher in an era where an understanding of designed interactions, surface effects, and solution conditions can be harnessed to achieve predictive materials synthesis across scale and drive emergent phenomena in the self-assembly and reconfiguration of high-information content building blocks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Generation of a chromosome-scale genome assembly of the insect-repellent terpenoid-producing Lamiaceae species, Callicarpa americana

Plants exhibit wide chemical diversity due to the production of specialized metabolites that function as pollinator attractants, defensive compounds, and signaling molecules. Lamiaceae (mints) are known for their chemodiversity and have been cultivated for use as culinary herbs, as well as sources of insect repellents, health-promoting compounds, and fragrance. We report the chromosome-scale genome assembly of Callicarpa americana L. (American beautyberry), a species within the early-diverging Callicarpoideae clade of Lamiaceae, known for its metallic purple fruits and use as an insect repellent due to its production of terpenoids. Using long-read sequencing and Hi-C scaffolding, we generated a 506.1-Mb assembly spanning 17 pseudomolecules with N50 contig and N50 scaffold sizes of 7.5 and 29.0 Mb, respectively. In all, 32,164 genes were annotated, including 53 candidate terpene synthases and 47 putative clusters of specialized metabolite biosynthetic pathways. Our analyses revealed 3 putative whole-genome duplication events, which, together with local tandem duplications, contributed to gene family expansion of terpene synthases. Kolavenyl diphosphate is a gateway to many of the bioactive terpenoids in C. americana; experimental validation confirmed that CamTPS2 encodes kolavenyl diphosphate synthase. Syntenic analyses with Tectona grandis L. f. (teak), a member of the Tectonoideae clade of Lamiaceae known for exceptionally strong wood resistant to insects, revealed 963 collinear blocks and 21,297 C. americana syntelogs. Access to the C. americana genome provides a road map for rapid discovery of genes encoding plant-derived agrichemicals and a key resource for understanding the evolution of chemical diversity in Lamiaceae.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Programming Function via Soft Materials (PFvSM) (Final Report)

The PFvSM cluster at the University of Illinois greatly deepened the science of soft materials and expanded the means for embedding within them unprecedented functionalities. We pioneered a mesoscopic approach to materials design that combined leading competencies in fundamental experimental and theoretical soft matter science and fabrication that powerfully establishes equilibrium and nonequilibrium assembly of novel and complex building blocks as a preeminent contributor to progress in materials chemistry. Our cluster’s vision was an integrated program of work centered on soft matter science with the ultimate goal of impacting important energy technologies. As elementary units we employed function-encoded colloids, nanoparticles, large mesh fibrillar gels, deterministically fabricated networks and hybrid objects. These materials were employed as building blocks for diverse model systems that allowed fundamental soft matter principles of wide relevance to be established. Their assembly into materials with useful functional behavior provided new approaches to challenging problems in basic energy science including energy harvesting, transport and storage. To achieve these goals the cluster brought together a team of recognized world-leaders in materials synthesis and processing, in-situ characterization, theory and modeling, and materials design, integration and fabrication

36 MATERIALS SCIENCE↗
DOE OSTI2017

Chromosome-level genome assembly and transcriptome of the green alga Chromochloris zofingiensis illuminates astaxanthin production

Microalgae have potential to help meet energy and food demands without exacerbating environmental problems. There is interest in the unicellular green alga Chromochloris zofingiensis, because it produces lipids for biofuels and a highly valuable carotenoid nutraceutical, astaxanthin. Here, to advance understanding of its biology and facilitate commercial development, we present a C. zofingiensis chromosome-level nuclear genome, organelle genomes, and transcriptome from diverse growth conditions. The assembly, derived from a combination of short- and long-read sequencing in conjunction with optical mapping, revealed a compact genome of ~58 Mbp distributed over 19 chromosomes containing 15,274 predicted protein-coding genes. The genome has uniform gene density over chromosomes, low repetitive sequence content (~6%), and a high fraction of protein-coding sequence (~39%) with relatively long coding exons and few coding introns. Functional annotation of gene models identified orthologous families for the majority (~73%) of genes. Synteny analysis uncovered localized but scrambled blocks of genes in putative orthologous relationships with other green algae. Two genes encoding beta-ketolase (BKT), the key enzyme synthesizing astaxanthin, were found in the genome, and both were up-regulated by high light. Isolation and molecular analysis of astaxanthin-deficient mutants showed that BKT1 is required for the production of astaxanthin. Moreover, the transcriptome under high light exposure revealed candidate genes that could be involved in critical yet missing steps of astaxanthin biosynthesis, including ABC transporters, cytochrome P450 enzymes, and an acyltransferase. Finally, the high-quality genome and transcriptome provide insight into the green algal lineage and carotenoid production.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Deletion of either the regulatory gene ara1 or metabolic gene xki1 in Trichoderma reesei leads to increased CAZyme gene expression on crude plant biomass

Background:Trichoderma reesei is one of the major producers of enzymes for the conversion of plant biomass to sustainable fuels and chemicals. Crude plant biomass can induce the production of CAZymes in T. reesei, but there is limited understanding of how the transcriptional response to crude plant biomass is regulated. In addition, it is unknown whether induction on untreated recalcitrant crude plant biomass (with a large diversity of inducers) can be sustained for longer. We investigated the transcriptomic response of T. reesei to the two industrial feedstocks, corn stover (CS) and soybean hulls (SBH), over time (4 h, 24 h and 48 h), and its regulatory basis using transcription factor deletion mutants (Δxyr1 and Δara1). We also investigated whether deletion of a xylulokinase gene (Δxki1) from the pentose catabolic pathway that converts potential inducers could lead to increased CAZyme gene expression. Results:By analyzing the transcriptomic responses using clustering as well as differential and cumulative expression of plant biomass degrading CAZymes, we found that corn stover induced a broader range and higher expression of CAZymes in T. reesei, while SBH induced more pectinolytic and mannanolytic transcripts. XYR1 was the major TF regulating CS utilization, likely due to the significant amount of d-xylose in this substrate. In contrast, ARA1 had a stronger effect on SBH utilization, which correlates with a higher abundance of l-arabinose in SBH that activates ARA1. Blocking pentose catabolism by deletion of xki1 led to higher expression of CAZyme encoding genes on both substrates at later time points. Surprisingly, this was also observed for Δara1 at later time points. Many of these genes were XYR1 regulated, suggesting that inducers for this regulator accumulated over time on both substrates. Conclusion:Our data demonstrates the complexity of the regulatory system related to plant biomass degradation in T. reesei and the effect the feedstock composition has on this. Furthermore, this dataset provides leads to improve the efficiency of a T. reesei enzyme cocktail, such as by the choice of substrate or by deleting xki1 to obtain higher production of plant biomass degrading CAZymes.

09 BIOMASS FUELS↗
NASA NTRS1976

Atmospheric temperature profiles derived through the inversion of a system of first order differential equations

Generation of vertical temperatures profiles from remotely sensed atmospheric radiance data is described as an analogous communications system. The radiative transport characteristics of the atmosphere encodes the continuous temperature profile into an 'n' element vector where 'n' is the number of channels in the satellite instrument. The temperature profile is a message transmitted from station A to station B and the link is the satellite instrument. At station B the decoder reproduces a continuous function which is the best estimate of the message encoded at station A. It is shown that the decoder must operate in a tuned mode where the parameters used in the encoder precisely determine the decoder parameters, and that the characteristics of the total message block must be given by a set of decoder constraints

Gatlin, J. A.↗
DOE OSTI2021

Automating Discovery of Physics-Informed Neural State Space Models via Learning and Evolution

Recent works exploring deep learning application to dynamical systems modeling have demonstrated that embedding physical priors into neural networks can yield more effective, physically-realistic, and data-efficient models. However, in the absence of complete prior knowledge of a dynamical system's physical characteristics, determining the optimal structure and optimization strategy for these models can be difficult. In this work, we explore methods for discovering neural state space dynamics models for system identification. Starting with a design space of block-oriented state space models and structured linear maps with strong physical priors, we encode these components into a model genome alongside network structure, penalty constraints, and optimization hyperparameters. Demonstrating the overall utility of the design space, we employ an asynchronous genetic search algorithm that alternates between model selection and optimization and obtains accurate physically consistent models of three physical systems: an aerodynamics body, a continuous stirred tank reactor, and a two tank interacting system.

genetic algorithms, neural architecture search, ne↗
DOE OSTI2012

Inorganic arsenic represses interleukin-17A expression in human activated Th17 lymphocytes

Trivalent inorganic arsenic [As(III)] is an efficient anticancer agent used to treat patients suffering from acute promyelocytic leukemia. Recently, experimental studies have clearly demonstrated that this metalloid can also cure lymphoproliferative and/or pro-inflammatory syndromes in different murine models of chronic immune-mediated diseases. T helper (Th) 1 and Th17 lymphocytes play a central role in development of these diseases, in mice and humans, especially by secreting the potent pro-inflammatory cytokine interferon-γ and IL-17A, respectively. As(III) impairs basic functions of human T cells but its ability to modulate secretion of pro-inflammatory cytokines by differentiated Th lymphocytes is unknown. In the present study, we demonstrate that As(III), used at concentrations clinically achievable in plasma of patients, has no effect on the secretion of interferon-γ from Th1 cells but almost totally blocks the expression and the release of IL-17A from human Th17 lymphocytes co-stimulated for five days with anti-CD3 and anti-CD28 antibodies, in the presence of differentiating cytokines. In addition, As(III) specifically reduces mRNA levels of the retinoic-related orphan receptor (ROR)C gene which encodes RORγt, a key transcription factor controlling optimal IL-17 expression in fully differentiated Th17 cells. The metalloid also blocks initial expression of IL-17 gene induced by the co-stimulation, probably in part by impairing activation of the JNK/c-Jun pathway. In conclusion, our results demonstrate that As(III) represses expression of the major pro-inflammatory cytokine IL-17A produced by human Th17 lymphocytes, thus strengthening the idea that As(III) may be useful to treat inflammatory immune-mediated diseases in humans. -- Highlights: ► Arsenic inhibits secretion of IL-17A from human naïve and memory Th17 lymphocytes. ► Arsenic represses early expression of IL-17A gene in human activated T lymphocytes. ► Arsenic interferes with activation of the JNK/c-Jun pathway in human T lymphocytes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Self-assembled elastomers with molecularly encoded tissue-like softness, strain-adaptive stiffening and coloration

The invention generally relates to linear-bottlebrush-linear copolymer blocks and methods of making and using same. The disclosed copolymer blocks can be useful in, for example, the formation of polymer networks that replicate biological stress-strain behavior. This abstract is intended as a scanning tool for purposes of searching in the particular art and is not intended to be limiting of the present invention.

Sheiko, Sergei↗
NASA NTRS1984

Cut-off rate calculations for the outer channel in a concatenated cooling system

Concatenated codes were long used as a practical means of achieving long block or constraint lengths for combating errors on very noisy channels. The inner and outer encoders are normally separated by an interleaver, so that decoded error bursts coming from the inner decoder are randomized before entering the outer decoder. The effectiveness of this interleaver is examined by calculating the cut-off rate of the outer channel seen by the outer decoder with and without interleaving. Interleaving never hurts the performance of a concatenated code, and when the inner code rate is near the cut-off rate of the inner channel, interleaving significantly improves code performance.

Herro, M. A.↗
NASA NTRS1993

Compression of spectral meteorological imagery

Data compression is essential to current low-earth-orbit spectral sensors with global coverage, e.g., meteorological sensors. Such sensors routinely produce in excess of 30 Gb of data per orbit (over 4 Mb/s for about 110 min) while typically limited to less than 10 Gb of downlink capacity per orbit (15 minutes at 10 Mb/s). Astro-Space Division develops spaceborne compression systems for compression ratios from as little as three to as much as twenty-to-one for high-fidelity reconstructions. Current hardware production and development at Astro-Space Division focuses on discrete cosine transform (DCT) systems implemented with the GE PFFT chip, a 32x32 2D-DCT engine. Spectral relations in the data are exploited through block mean extraction followed by orthonormal transformation. The transformation produces blocks with spatial correlation that are suitable for further compression with any block-oriented spatial compression system, e.g., Astro-Space Division's Laplacian modeler and analytic encoder of DCT coefficients.

Miettinen, Kristo↗
NASA NTRS2010

Performance Bounds on Two Concatenated, Interleaved Codes

A method has been developed of computing bounds on the performance of a code comprised of two linear binary codes generated by two encoders serially concatenated through an interleaver. Originally intended for use in evaluating the performances of some codes proposed for deep-space communication links, the method can also be used in evaluating the performances of short-block-length codes in other applications. The method applies, more specifically, to a communication system in which following processes take place: At the transmitter, the original binary information that one seeks to transmit is first processed by an encoder into an outer code (Co) characterized by, among other things, a pair of numbers (n,k), where n (n > k)is the total number of code bits associated with k information bits and n k bits are used for correcting or at least detecting errors. Next, the outer code is processed through either a block or a convolutional interleaver. In the block interleaver, the words of the outer code are processed in blocks of I words. In the convolutional interleaver, the interleaving operation is performed bit-wise in N rows with delays that are multiples of B bits. The output of the interleaver is processed through a second encoder to obtain an inner code (Ci) characterized by (ni,ki). The output of the inner code is transmitted over an additive-white-Gaussian- noise channel characterized by a symbol signal-to-noise ratio (SNR) Es/No and a bit SNR Eb/No. At the receiver, an inner decoder generates estimates of bits. Depending on whether a block or a convolutional interleaver is used at the transmitter, the sequence of estimated bits is processed through a block or a convolutional de-interleaver, respectively, to obtain estimates of code words. Then the estimates of the code words are processed through an outer decoder, which generates estimates of the original information along with flags indicating which estimates are presumed to be correct and which are found to be erroneous. From the perspective of the present method, the topic of major interest is the performance of the communication system as quantified in the word-error rate and the undetected-error rate as functions of the SNRs and the total latency of the interleaver and inner code. The method is embodied in equations that describe bounds on these functions. Throughout the derivation of the equations that embody the method, it is assumed that the decoder for the outer code corrects any error pattern of t or fewer errors, detects any error pattern of s or fewer errors, may detect some error patterns of more than s errors, and does not correct any patterns of more than t errors. Because a mathematically complete description of the equations that embody the method and of the derivation of the equations would greatly exceed the space available for this article, it must suffice to summarize by reporting that the derivation includes consideration of several complex issues, including relationships between latency and memory requirements for block and convolutional codes, burst error statistics, enumeration of error-event intersections, and effects of different interleaving depths. In a demonstration, the method was used to calculate bounds on the performances of several communication systems, each based on serial concatenation of a (63,56) expurgated Hamming code with a convolutional inner code through a convolutional interleaver. The bounds calculated by use of the method were compared with results of numerical simulations of performances of the systems to show the regions where the bounds are tight (see figure).

Moision, Bruce↗
DOE OSTI2018

DNA-Encoded Protein Janus Nanoparticles

Asymmetric functionality and directional interactions, which are characteristic of noncentrosymmetric particles, such as Janus particles, present an opportunity to encode particles with properties, but also a great synthetic challenge. Here, we exploit the chemical anisotropy of proteins, and the versatile chemistry of DNA to synthesize a protein-based Janus nanoparticle comprised of two proteins encoded with sequence-specific nucleic acid domains, tethered together by an interprotein “DNA bond”. We use these novel nanoparticles to realize a new class of three-dimensional superlattice, only possible when two sides of the particle are modified with orthogonal oligonucleotide sequences. The low symmetry, intrinsic to Janus particles, enables the realization of unprecedented multicomponent nanoparticle superlattices with unique, hexagonal layered architectures. In addition, the interprotein “DNA bond” can be modulated to selectively expand the lattice in a single direction. The results presented herein not only emphasize the power of rationally designing nanoscale building blocks to create highly engineered colloidal crystals, but also establish a precedent for applications of multidomain DNA-encoded nanoparticles, especially in the field of colloidal crystallization.

59 BASIC BIOLOGICAL SCIENCES↗