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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Structure and proposed mechanism of α-glycerophosphate oxidase from Mycoplasma pneumoniae

In this study, the formation of hydrogen peroxide (H₂O₂) by the FAD-dependent α-glycerophosphate oxidase (GlpO), is important for the pathogenesis of Streptococcus pneumoniae and Mycoplasma pneumoniae . The structurally known GlpO from Streptococcus sp. ( Ssp GlpO) is similar to the pneumococcal protein ( Sp GlpO) and provides a guide for drug design against that target. However, M. pneumoniae GlpO ( Mp GlpO), having <20% sequence identity with structurally known GlpOs, appears to represent a second type of GlpO we designate as Type II GlpOs. Here, the recombinant His-tagged Mp GlpO structure is described at ~2.5 Å resolution, solved by molecular replacement using as a search model the Bordetella pertussis protein 3253 (Bp3253) a protein of unknown function solved by structural genomics efforts. Recombinant Mp GlpO is an active oxidase with a turnover number of ~580 min⁻¹ while Bp3253 showed no GlpO activity. No substantial differences exist between the oxidized and dithionite-reduced Mp GlpO structures. Although, no liganded structures were determined, a comparison with the tartrate-bound Bp3253 structure and consideration of residue conservation patterns guided the construction of a model for α-glycerophosphate (Glp) recognition and turnover by Mp GlpO. The predicted binding mode also appears relevant for the type I GlpOs (such as Ssp GlpO) despite differences in substrate recognition residues, and it implicates a histidine conserved in type I and II Glp oxidases and dehydrogenases as the catalytic acid/base. This work provides a solid foundation for guiding further studies of the mitochondrial Glp dehydrogenases as well as for continued studies of M. pneumoniae and S. pneumoniae glycerol metabolism and the development of novel therapeutics targeting Mp GlpO and Sp GlpO.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Structural basis for LIN54 recognition of CHR elements in cell cycle-regulated promoters

The MuvB complex recruits transcription factors to activate or repress genes with cell cycle-dependent expression patterns. MuvB contains the DNA-binding protein LIN54, which directs the complex to promoter cell cycle genes homology region (CHR) elements. Here we characterize the DNA-binding properties of LIN54 and describe the structural basis for recognition of a CHR sequence. We biochemically define the CHR consensus as TTYRAA and determine that two tandem cysteine rich regions are required for high-affinity DNA association. A crystal structure of the LIN54 DNA-binding domain in complex with a CHR sequence reveals that sequence specificity is conferred by two tyrosine residues, which insert into the minor groove of the DNA duplex. We demonstrate that this unique tyrosine-mediated DNA binding is necessary for MuvB recruitment to target promoters. Our results suggest a model in which MuvB binds near transcription start sites and plays a role in positioning downstream nucleosomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

ChemNet: A Transferable and Generalizable Deep Neural Network for Small-Molecule Property Prediction

With access to large datasets, deep neural networks through representation learning have been able to identify patterns from raw data, achieving human-level accuracy in image and speech recognition tasks. However, in chemistry, availability of large standardized and labelled datasets is scarce, and with a multitude of chemical properties of interest, chemical data is inherently small and fragmented. In this work, we explore transfer learning techniques in conjunction with the existing Chemception CNN model, to create a transferable and generalizable deep neural network for small-molecule property prediction. Our latest model, ChemNet learns in a semi-supervised manner from inexpensive labels computed from the ChEMBL database. When fine-tuned to the Tox21, HIV and FreeSolv dataset, which are 3 separate chemical tasks that ChemNet was not originally trained on, we demonstrate that ChemNet exceeds the performance of existing Chemception models, contemporary MLP models that trains on molecular fingerprints, and it matches the performance of the ConvGraph algorithm, the current state-of-the-art. Furthermore, as ChemNet has been pre-trained on a large diverse chemical database, it can be used as a universal “plug-and-play” deep neural network, which accelerates the deployment of deep neural networks for the prediction of novel small-molecule chemical properties.

Artificial Intelligence↗
DOE OSTI2018

Structure of xyloglucan xylosyltransferase 1 reveals simple steric rules that define biological patterns of xyloglucan polymers

The plant cell wall is primarily a polysaccharide mesh of the most abundant biopolymers on earth. Although one of the richest sources of biorenewable materials, the biosynthesis of the plant polysaccharides is poorly understood. Structures of many essential plant glycosyltransferases are unknown and suitable substrates are often unavailable for in vitro analysis. The dearth of such information impedes the development of plants better suited for industrial applications. As such, presented here are structures of Arabidopsis xyloglucan xylosyltransferase 1 (XXT1) without ligands and in complexes with UDP and cellohexaose. XXT1 initiates side-chain extensions from a linear glucan polymer by transferring the xylosyl group from UDP-xylose during xyloglucan biosynthesis. XXT1, a homodimer and member of the GT-A fold family of glycosyltransferases, binds UDP analogously to other GT-A fold enzymes. Structures here and the properties of mutant XXT1s are consistent with a SN i -like catalytic mechanism. Distinct from other systems is the recognition of cellohexaose by way of an extended cleft. The XXT1 dimer alone cannot produce xylosylation patterns observed for native xyloglucans because of steric constraints imposed by the acceptor binding cleft. Homology modeling of XXT2 and XXT5, the other two xylosyltransferases involved in xyloglucan biosynthesis, reveals a structurally altered cleft in XXT5 that could accommodate a partially xylosylated glucan chain produced by XXT1 and/or XXT2. An assembly of the three XXTs can produce the xylosylation patterns of native xyloglucans, suggesting the involvement of an organized multienzyme complex in the xyloglucan biosynthesis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Anti-distortion bioinspired camera with an inhomogeneous photo-pixel array

The bioinspired camera, comprising a single lens and a curved image sensor—a photodiode array on a curved surface—, was born of flexible electronics. Its economical build lends itself well to space-constrained machine vision applications. The curved sensor, much akin to the retina, helps image focusing, but the curvature also creates a problem of image distortion, which can undermine machine vision tasks such as object recognition. Here we report an anti-distortion single-lens camera, where 4096 silicon photodiodes arrayed on a curved surface in a nonuniform pattern assimilated to the distorting optics are the key to anti-distortion engineering. That is, the photo-pixel distribution pattern itself is warped in the same manner as images are warped, which correctively reverses distortion. Acquired images feature no appreciable distortion across a 120° horizontal view, as confirmed by their neural-network recognition accuracies. This distortion correction via photo-pixel array reconfiguration is a form of in-sensor computing.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

Partnering with Artificial Intelligence

Machine learning is behind many of the surprising and technology advances in recent years – driverless cars, personal voice assistants, and facial recognition. But machine learning - an offshoot of artificial intelligence that encourages computers to learn hidden patterns and make novel predictions without being explicitly programmed – requires human partnership. Artificial intelligence is playing a significant role in defining new research methods that bring us to resolution or discovery more quickly than ever before. Argonne is using or developing many of these technologies as AI extends to new branches of science and technology.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Dissecting the cytochrome c2–reaction centre interaction in bacterial photosynthesis using single molecule force spectroscopy

The reversible docking of small, diffusible redox proteins onto a membrane protein complex is a common feature of bacterial, mitochondrial and photosynthetic electron transfer (ET) chains. Spectroscopic studies of ensembles of such redox partners have been used to determine ET rates and dissociation constants. Here, we report a single-molecule analysis of the forces that stabilise transient ET complexes. We examined the interaction of two components of bacterial photosynthesis, cytochrome c 2 and the reaction centre (RC) complex, using dynamic force spectroscopy and PeakForce quantitative nanomechanical imaging. RC–LH1–PufX complexes, attached to silicon nitride AFM probes and maintained in a photo-oxidised state, were lowered onto a silicon oxide substrate bearing dispersed, immobilised and reduced cytochrome c 2 molecules. Microscale patterns of cytochrome c 2 and the cyan fluorescent protein were used to validate the specificity of recognition between tip-attached RCs and surface-tethered cytochrome c 2 . Following the transient association of photo-oxidised RC and reduced cytochrome c 2 molecules, retraction of the RC-functionalised probe met with resistance, and forces between 112 and 887 pN were required to disrupt the post-ET RC– c 2 complex, depending on the retraction velocities used. If tip-attached RCs were reduced instead, the probability of interaction with reduced cytochrome c 2 molecules decreased 5-fold. Thus, the redox states of the cytochrome c 2 haem cofactor and RC ‘special pair’ bacteriochlorophyll dimer are important for establishing a productive ET complex. The millisecond persistence of the post-ET cytochrome c 2 [oxidised]–RC[reduced] ‘product’ state is compatible with rates of cyclic photosynthetic ET, at physiologically relevant light intensities.

Biochemistry & Molecular Biology↗
DOE OSTI2021

Variation in Gene Expression between Two Sorghum bicolor Lines Differing in Innate Immunity Response

Microbe associated molecular pattern (MAMPs) triggered immunity (MTI) is a key component of the plant innate immunity response to microbial recognition. However, most of our current knowledge of MTI comes from model plants (i.e., Arabidopsis thaliana) with comparatively less work done using crop plants. In this work, we studied the MAMP triggered oxidative burst (ROS) and the transcriptional response in two Sorghum bicolor genotypes, BTx623 and SC155-14E. SC155-14E is a line that shows high anthracnose resistance and the line BTx623 is susceptible to anthracnose. Our results revealed a clear variation in gene expression and ROS in response to either flagellin (flg22) or chitin elicitation between the two lines. While the transcriptional response to each MAMP and in each line was unique there was a considerable degree of overlap, and we were able to define a core set of genes associated with the sorghum MAMP transcriptional response. The GO term and KEGG pathway enrichment analysis discovered more immunity and pathogen resistance related DEGs in MAMP treated SC155-14E samples than in BTx623 with the same treatment. The results provide a baseline for future studies to investigate innate immunity pathways in sorghum, including efforts to enhance disease resistance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Early Alarm: Robust Event Analysis for Power Systems using 1-D Fully Convolutional Network

This work presents a novel deep learning model for early, accurate, and robust detection, recognition, and temporal localization of multi-type events in large-scale power systems. The proposed method develops a unified 1-D fully convolutional network (FCN) model that takes time series of raw frequency signals measured from a power system as input, extracts distinguishing features, and predicts at every temporal point in the time series if an event is happening and what the type of the event is. Compared to existing methods, the proposed model eliminates the necessity for hand-crafted feature extraction or complicated data pre-processing, can flexibly handle input signals of arbitrary length, and precisely infer the event occurrence time. Most importantly, the model is intentionally trained with incomplete patterns, such that it is more robust to partial features of an event which is common in real-world online recognition, resulting in early alarm for power system failures. Extensive experimental results demonstrate that the proposed method achieves superior performance to the state-of-the-art, and also shows strong robustness to noise and system oscillations.

Li, Chengcheng↗
DOE OSTI2015

A CLASSICAL MORPHOLOGICAL ANALYSIS OF GALAXIES IN THE SPITZER SURVEY OF STELLAR STRUCTURE IN GALAXIES (S{sup 4}G)

The Spitzer Survey of Stellar Structure in Galaxies (S{sup 4}G) is the largest available database of deep, homogeneous middle-infrared (mid-IR) images of galaxies of all types. The survey, which includes 2352 nearby galaxies, reveals galaxy morphology only minimally affected by interstellar extinction. This paper presents an atlas and classifications of S{sup 4}G galaxies in the Comprehensive de Vaucouleurs revised Hubble-Sandage (CVRHS) system. The CVRHS system follows the precepts of classical de Vaucouleurs morphology, modified to include recognition of other features such as inner, outer, and nuclear lenses, nuclear rings, bars, and disks, spheroidal galaxies, X patterns and box/peanut structures, OLR subclass outer rings and pseudorings, bar ansae and barlenses, parallel sequence late-types, thick disks, and embedded disks in 3D early-type systems. We show that our CVRHS classifications are internally consistent, and that nearly half of the S{sup 4}G sample consists of extreme late-type systems (mostly bulgeless, pure disk galaxies) in the range Scd-Im. The most common family classification for mid-IR types S0/a to Sc is SA while that for types Scd to Sm is SB. The bars in these two type domains are very different in mid-IR structure and morphology. This paper examines the bar, ring, and type classification fractions in the sample, and also includes several montages of images highlighting the various kinds of “stellar structures” seen in mid-IR galaxy morphology.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

FiberFlex: Real-time FPGA-based Intelligent and Distributed Fiber Sensor System for Pedestrian Recognition

In recent years, security monitoring of public places and critical infrastructure has heavily relied on the widespread use of cameras, raising concerns about personal privacy violations. To balance the need for effective security monitoring with the protection of personal privacy, we explore the potential of optical fiber sensors for this application. This article proposes FiberFlex, an intelligent and distributed fiber sensor system. Ultizing Field Programmable Gate Arrays (FPGA) high-level synthesis (HLS) acceleration, FiberFlex offers real-time pedestrian detection by co-designing the entire pipeline of optical signal acquisition, processing, and recognition networks based on the principles of optical fiber sensing. As a promising alternative to traditional camera-based monitoring systems, FiberFlex achieves pedestrian detection by analyzing the vibration patterns caused by pedestrian footsteps, enabling security monitoring while preserving individual privacy. FiberFlex comprises three modules: First , fiber-optic sensing system: A fiber-optic distributed acoustic sensing (DAS) system is built and used to measure the ground vibration waves generated by people walking. Second , algorithms: We first collect the training data by measuring the ground vibration waves, label the data, and use the data to train the neural network models to perform pedestrian recognition. Third , hardware accelerators: We use HLS tools to design hardware modules on FPGA for data collection and pre-processing and integrate them with the downstream neural network accelerators to perform in-line real-time pedestrian detection. The final detection results are sent back from FPGA to the host CPU. We implement our system FiberFlex with the in-house built DAS system and AMD/Xilinx Kintex7 FPGA KC705 board and verify the whole system using the real-world collected data. We conduct recognition tests on five test subjects of varying ages, heights, and weights in a fixed sensing area. Each subject experienced 20 real-time recognition tests using their daily walking habits, and the subjects were given adequate rest between tests. After 100 tests on five test subjects, the overall real-time recognition accuracy exceeded \(88.0\%\) . The whole system uses 55 W of power, 33 W in the optical DAS system and 22 W in the FPGA. Relying on its end-to-end interdisciplinary design, FiberFlex seamlessly combines fiber-optic sensors with FPGA accelerators to enable low-power real-time security monitoring without compromising privacy, making it a valuable addition to the existing security monitoring network. According to FiberFlex, more valuable research can be conducted in the future, such as fall monitoring for the elderly, migration of identification networks between different application scenarios, and improvement of anti-interference performance in more complex environments. In future perception networks, where the “eyes” are not feasible, let’s use fiber optic touch instead.

Distributed↗
DOE OSTI2016

Engineering Bioelectronic Signal Transduction Using the Bacterial Type III Secretion Apparatus

Engineering efficient methods for living systems to transfer electrical energy to non-living systems, at relevant size scales, continues to challenge our knowledge of materials and biology. Our goal was to enable signal transduction between cells and inorganic materials, using controlled electron transport as the energy transfer mechanism. We envision using the cell as a living battery, providing a set of environmental signals to trigger synthetic biological networks that divert intracellular electron transport pathways to inorganic extracellular structures. Conversely, changing electron influxes could guide cellular responses. It is challenging, however, to precisely engineer nanostructured materials to achieve controllable catalytic or electronic properties and connect them with biological energy sources. Our approach to this problem is to engineer protein scaffolds, taking advantage of the native recognition, selectivity and self-assembly properties of these nano-scale building blocks as well as their native intracellular localization patterns. We are using a type III secretion system (T3SS) needle protein from Salmonella enterica, PrgI, as a template for metal nanowire synthesis for biosensing and bioenergy applications. We demonstrate that purified PrgI monomers spontaneously self assemble into long filaments, and that high-affinity peptide tags specific for attachment to functionalized particles can be integrated into the N-terminal region of PrgI. The resulting filaments selectively bind to gold, whether the filaments are assembled in vitro, sheared from cells, or remain attached to live S. enterica cell membranes. Chemical reduction of the gold modified PrgI variants results in structures that are several microns in length and which incorporate a contiguous gold surface.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Heterothermic Migration Strategies in Flying Vertebrates

Migration is a widespread and highly variable trait among animals. Population-level patterns arise from individual-level decisions, including physiological and energetic constraints. Many aspects of migration are influenced by behaviors and strategies employed during periods of stopover, where migrants may encounter variable or unpredictable conditions. Thermoregulation can be a major cost for homeotherms which largely encounter ambient temperatures below the lower critical temperature during migration, especially during the rest phase of the daily cycle. In this review we describe the empirical evidence, theoretical models, and potential implications of bats and birds that use heterothermy to reduce thermoregulatory costs during migration. Torpor-assisted migration is a strategy described for migrating temperate insectivorous bats, whereby torpor can be used during periods of inactivity to drastically reduce thermoregulatory costs and increase net refueling rate, leading to shorter stopover duration, reduced fuel load requirement, and potential consequences for broad-scale movement patterns and survival. Hummingbirds can adopt a similar strategy, but most birds are not capable of torpor. However, there is an increasing recognition of the use of more shallow heterothermic strategies by diverse bird species during migration, with similarly important implications for migration energetics. A growing body of published literature and preliminary data from ongoing research indicate that heterothermic migration strategies in birds may be more common than traditionally appreciated. We further take a broad evolutionary perspective to consider heterothermy as an alternative to migration in some species, or as a conceptual link to consider alternatives to seasonal resource limitations. There is a growing body of evidence related to heterothermic migration strategies in bats and birds, but many important questions related to the broader implications of this strategy remain.

bats↗
DOE OSTI2024

Forecast of Wildfire Potential Across California USA Using a Transformer

Wildfires are a major issue facing the United States, a matter further exacerbated by an ever-changing climate. In California alone, wildfires are responsible for billions of dollars in damages and take lives each year. Accurately predicting fire danger conditions allows preparation awareness before wildfires start. Transformers are a class of deep learning models designed to identify patterns in sequential datasets. In recent years, transformers have gained popularity through their impressive performance in natural language processing and other applications of signal recognition. This analysis demonstrates the ability of a transformer with a residual connection to forecast fire danger potential over the state of California. Wildland fire potential index (WFPI) maps collected from the US Geological Survey database from January 1st 2020 to December 31st 2023 were used to tune, train and evaluate the transformer. Meteorological inputs (provided by Daymet daily weather and climatological summaries), the normalized difference vegetation index (NDVI) (calculated from the Moderate Resolution Imaging Spectroradiometer (MODIS)), and outputs from the Scott and Burgman fire behavior fuel models (to characterize maps of fuel types), were used as inputs. Our results show that a transformer can effectively emulate the US Forest Service modeled WFPI maps of California USA for four week long forecasts over the month of July, 2023, with correlations ranging from 0.85 – 0.98.

Limber, Russell [ORNL]↗
DOE OSTI2015

Porous silicon ring resonator for compact, high sensitivity biosensing applications

A ring resonator is patterned on a porous silicon slab waveguide to produce a compact, high quality factor biosensor with a large internal surface area available for enhanced recognition of biological and chemical molecules. The porous nature of the ring resonator allows molecules to directly interact with the guided mode. Quality factors near 10,000 were measured for porous silicon ring resonators with a radius of 25 μm. A bulk detection sensitivity of 380 nm/RIU was measured upon exposure to salt water solutions. Specific detection of nucleic acid molecules was demonstrated with a surface detection sensitivity of 4 pm/nM.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

GraphAide: Advanced Graph-Assisted Query and Reasoning System

Curating knowledge from multiple siloed sources that contain both structured and unstructured data is a major challenge in many real-world applications. Pattern matching and querying represent fundamental tasks in modern data analytics that leverage this curated knowledge. The development of such applications necessitates overcoming several research challenges, including data extraction, named entity recognition, data modeling, and designing query interfaces. Moreover, the explainability of these functionalities is critical for their broader adoption. The emergence of Large Language Models (LLMs) has accelerated the development lifecycle of new capabilities. Nonetheless, there is an ongoing need for domain-specific tools tailored to user activities. The creation of digital assistants has gained considerable traction in recent years, with LLMs offering a promising avenue to develop such assistants utilizing domain-specific knowledge and assumptions. In this context, we introduce an advanced query and reasoning system, GraphAide, which constructs a knowledge graph (KG) from diverse sources and allows to query and reason over the resulting KG. GraphAide harnesses both the KG and LLMs to rapidly develop domain-specific digital assistants. It integrates design patterns from retrieval augmented generation (RAG) and the semantic web to create an agentic LLM application. GraphAide underscores the potential for streamlined and efficient development of specialized digital assistants, thereby enhancing their applicability across various domains.

Purohit, Sumit [BATTELLE (PACIFIC NW LAB)] (ORCID:↗
DOE OSTI2016

Conserved patterns hidden within group A Streptococcus M protein hypervariability recognize human C4b-binding protein

No vaccine exists against group A Streptococcus (GAS), a leading cause of worldwide morbidity and mortality. A severe hurdle is the hypervariability of its major antigen, the M protein, with >200 different M types known. Neutralizing antibodies typically recognize M protein hypervariable regions (HVRs) and confer narrow protection. In stark contrast, human C4b-binding protein (C4BP), which is recruited to the GAS surface to block phagocytic killing, interacts with a remarkably large number of M protein HVRs (apparently ~90%). Such broad recognition is rare, and we discovered a unique mechanism for this through the structure determination of four sequence-diverse M proteins in complexes with C4BP. The structures revealed a uniform and tolerant ‘reading head’ in C4BP, which detected conserved sequence patterns hidden within hypervariability. Our results open up possibilities for rational therapies that target the M–C4BP interaction, and also inform a path towards vaccine design.

59 BASIC BIOLOGICAL SCIENCES↗