Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Recognition”

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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Structural basis for recognition of the central conserved region of RSV G by neutralizing human antibodies

Respiratory syncytial virus (RSV) is a major cause of severe lower respiratory tract infections in infants and the elderly, and yet there remains no effective treatment or vaccine. The surface of the virion is decorated with the fusion glycoprotein (RSV F) and the attachment glycoprotein (RSV G), which binds to CX3CR1 on human airway epithelial cells to mediate viral attachment and subsequent infection. RSV G is a major target of the humoral immune response, and antibodies that target the central conserved region of G have been shown to neutralize both subtypes of RSV and to protect against severe RSV disease in animal models. However, the molecular underpinnings for antibody recognition of this region have remained unknown. Therefore, we isolated two human antibodies directed against the central conserved region of RSV G and demonstrated that they neutralize RSV infection of human bronchial epithelial cell cultures in the absence of complement. Moreover, the antibodies protected cotton rats from severe RSV disease. Both antibodies bound with high affinity to a secreted form of RSV G as well as to a peptide corresponding to the unglycosylated central conserved region. High-resolution crystal structures of each antibody in complex with the G peptide revealed two distinct conformational epitopes that require proper folding of the cystine noose located in the C-terminal part of the central conserved region. Comparison of these structures with the structure of fractalkine (CX3CL1) alone or in complex with a viral homolog of CX3CR1 (US28) suggests that RSV G would bind to CX3CR1 in a mode that is distinct from that of fractalkine. Collectively, these results build on recent studies demonstrating the importance of RSV G in antibody-mediated protection from severe RSV disease, and the structural information presented here should guide the development of new vaccines and antibody-based therapies for RSV.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Cooperation between somatic mutation and germline-encoded residues enables antibody recognition of HIV-1 envelope glycans

Viral glycoproteins are a primary target for host antibody responses. However, glycans on viral glycoproteins can hinder antibody recognition since they are self glycans derived from the host biosynthesis pathway. During natural HIV-1 infection, neutralizing antibodies are made against glycans on HIV-1 envelope glycoprotein (Env). However, such antibodies are rarely elicited with vaccination. Previously, the vaccine-induced, macaque antibody DH501 was isolated and shown to bind to high mannose glycans on HIV-1 Env. Understanding how DH501 underwent affinity maturation to recognize glycans could inform vaccine induction of HIV-1 glycan antibodies. Here, we show that DH501 Env glycan reactivity is mediated by both germline-encoded residues that contact glycans, and somatic mutations that increase antibody paratope flexibility. Only somatic mutations in the heavy chain were required for glycan reactivity. The paratope conformation was fragile as single mutations within the immunoglobulin fold or complementarity determining regions were sufficient for eliminating antibody function. Taken together, the initial germline V H DJ H rearrangement generated contact residues capable of binding glycans, and somatic mutations were required to form a flexible paratope with a cavity conducive to HIV-1 envelope glycan binding. The requirement for the presence of most somatic mutations across the heavy chain variable region provides one explanation for the difficulty in inducing anti-Env glycan antibodies with HIV-1 Env vaccination.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Antibody recognition of the Pneumovirus fusion protein trimer interface

Human metapneumovirus (hMPV) is a leading cause of viral respiratory infection in children, and can cause severe lower respiratory tract infection in infants, the elderly, and immunocompromised patients. However, there remain no licensed vaccines or specific treatments for hMPV infection. Although the hMPV fusion (F) protein is the sole target of neutralizing antibodies, the immunological properties of hMPV F remain poorly understood. To further define the humoral immune response to the hMPV F protein, we isolated two new human monoclonal antibodies (mAbs), MPV458 and MPV465. Both mAbs are neutralizing in vitro and were determined to target a unique antigenic site using competitive biolayer interferometry. We determined both MPV458 and MPV465 have higher affinity for monomeric hMPV F than trimeric hMPV F. MPV458 was co-crystallized with hMPV F, and the mAb primarily interacts with an alpha helix on the F2 region of the hMPV F protein. Surprisingly, the major epitope for MPV458 lies within the trimeric interface of the hMPV F protein, suggesting significant breathing of the hMPV F protein must occur for host immune recognition of the novel epitope. In addition, significant glycan interactions were observed with a somatically mutated light chain framework residue. The data presented identifies a novel epitope on the hMPV F protein for epitope-based vaccine design, and illustrates a new mechanism for human antibody neutralization of viral glycoproteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Structure-function studies of Vibrio cholerae quorum-sensing receptor CqsR signal recognition

Ethanolamine signaling through the transmembrane quorum-sensing receptor CqsR influencesVibrio choleraeniche recognition and host colonization. In this study, we present a comprehensive structure-function analysis of CqsR. Specifically, we have determined X-ray crystal structures of the CqsR periplasmic domain bound to the signaling agonist ethanolamine and its analogs, serinol and L-alaninol, as well as the ligand-free (apo) form of CqsR. The periplasmic ligand-binding domain of CqsR is a Cache domain, the most prevalent extracellular sensory module in prokaryotes. Our findings provide a rare structural comparison of ligand-bound and unbound states of a Cache domain receptor. Coupled with thermodynamic binding assays and genetic analyses, these structures elucidate the molecular basis of CqsR ligand specificity. This study not only advances the understanding of Cache domain function but also informs the identification of ligands for orphan Cache receptors and the rational design of signaling agonists and antagonists. Lastly, we discuss ligand-induced conformational changes in the CqsR Cache domains and explore the potential for the existence of additional regulatory ligands.

Microbiology↗
DOE OSTI2014

COE Task Order 4. Final Report: Automated Threat Recognition

Lawrence Livermore National Laboratory (LLNL) was tasked by the Department of Homeland Security (DHS) Science and Technology Directorate (S&T) with developing an automated target recognition algorithm for finding objects of interest in checked baggage at airports. The project used x-ray computed tomography (CT) data collected on a medical scanner of various simulated checked bags. Target objects of interest include clay, rubber, and saline in various concentrations. The final results are 93.9% probability of detection (P D ) with 11.9% probability of false alarm (PFA) on all targets and 100% detection for pseudo target sheets. This result is achieved by using a three-stage algorithm made up of segmentation, post-processing, and feature extraction and object classification. The segmentation proved to be the most important stage and it involves merging two distinct segmentation results followed by a set of algorithms for cleaning up the merged segmentations. The first segmentation algorithm operates on planar 10x10 voxel slabs (two- dimensional segments) in the three spatial planes. The segmenter calculates a probability that each slab in the image is a part of a target, determines if the probability was above a threshold, and then merges all connected slabs together. The second segmentation algorithm is an ensemble segmenter, which generates a set of possible segmentations through random permutations and computes an average behavior. The distinct properties of these segmenters results in a merged segmentation with superior results than either segmenter alone. The merged segmentation is “cleaned up” using post processing techniques to achieve the final labeled images. The final classification stage made use of a random forest classifier algorithm to discriminate targets from non-targets based on a set of features of the segmented objects partially from the voxel slabs and partially from the individual voxels. Features include standard statistics such as mean, median, and standard deviations of the density, features capturing some aspects of texture, and some features about the surrounding bag structure. In addition to the detection and false alarm results above, we show how the algorithms can be trained to “overfit” to the limited data set provided and achieve near perfect results (P D =100% and P FA =0%). This over-training is not recommended for long-term operation, but instead is meant to demonstrate how test design is an important factor in aviation security. Possible improvements to the algorithm and the testing methodology (including blind testing) are also presented.

42 ENGINEERING↗
DOE OSTI2018

Seismic Phase Identification with Speech Recognition Algorithms

Seismic signals are composed of the seismic waves (phases) that reach a sensor, similar to the way speech signals are composed of phonemes that reach a listener's ear. Large/small seismic events near/far from a sensor are similar to loud/quiet speakers with high/low-pitched voices. We leverage ideas from speech recognition for the classification of seismic phases at a seismic sensor. Seismic Phase ID is challenging due to the varying paths and distances an event takes to reach a sensor, but there is consistent structure of the makeup (e.g. ordering) of the different phases arriving at the sensor.

58 GEOSCIENCES↗
DOE OSTI2018

An FPGA-based Pattern Recognition Associative Memory

Pattern recognition associative memory (PRAM) devices are parallel processing engines which are used to tackle the complex combinatorics of track nding algorithms, particularly for silicon based tracking triggers. PRAM development has been mostly limited to the realm of ASICs, which often leads to lengthy and expensive design cycles. FPGAs allow for quick iterations, making them an ideal hardware platform for designing and evaluating new PRAM features before committing to silicon. In this paper we present our FPGA-based PRAM designs and discuss how logic blocks which were originally developed for ASICs have been redesigned to take advantage of modern FPGA architectures.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Automated Threat Recognition For Aviation Security Applications

We have developed a framework for automated threat recognition (ATR) of explosive threat materials for both single-energy and dual-energy X-ray CT systems. Under this framework, two different types of ATR have been developed. The first type of ATR employs supervised machine learning with statistical characterization of target materials for threat identification training. The reliance only on statistical characterization information for threat training uniquely enables this style of ATR to adapt quickly to evolving threats. The second type of ATR employs deep learning through convolutional neural networks. Convolutional neural networks are attractive due to their human-like capacity for learning and strong ability to identify trends and patterns. Although this method is more powerful than the first type, it requires large amounts of training data and therefore is less agile. Each ATR performs threat characterization at the voxel neighborhood level. This approach avoids the use of threat shape as a detection criterion, which is prohibited by DHS and TSA guidelines.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Simulation, Challenge Testing & Validation of Occupancy Recognition & CO 2 Technologies (Final Project Report)

This final report covers the results of the development of testing methods of occupancy sensor systems connected to HVAC controls. This project focused on the development of test methods to evaluate the performance of HVAC-connected occupancy sensor systems, including occupancy presence, occupancy counting, and CO 2 sensor systems in commercial and residential buildings. This included evaluation of the reliability, ease of commissioning, and energy savings potential of these sensor systems. The results of this work help to standardize the methods used to evaluate performance, to enable the ability to compare sensor system performance following the same methods, to understand which sensor systems perform better or worse compared to others. The U.S. building stock’s energy usage can benefit substantially from having building system operations informed by reliable occupancy recognition and CO 2 measurements, however to date, standard methods have not been in place to ensure that sensor systems’ reported performance is uniformly evaluated. The results of this work support the development of a standard or guideline that outlines the developed methods of testing. This project also included the testing of both off-the-shelf and novel SENSOR team-developed low-cost occupancy sensor systems, using the developed methods of testing. The results of this testing helped to inform further development and improvement of new low-cost sensor systems that will benefit from being used in residential and commercial buildings throughout the country.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

De Novo Design of Molecular Recognition for Sequence Defined Polymers

The proposed research aims at developing a computational framework that allows the de novo design of sequence defined polymers for molecular recognition. This framework will include the prediction of the 1) accessible backbone conformational space in solution environments for small to medium polymer length and 2) how side chains of different size and functionality can be used to design convergent or divergent receptor configurations. A structural database inspired by the protein database will be build that can be used to construct larger scaffolds based on smaller sequences

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

Confidence Assessment for Automatic Target Recognition

Confidence assessment is critical for effective automatic target recognition (ATR). Productive use and interpretation of ATR results by analysts or downstream algorithms requires not only algorithmic declarations of target presence and identity, but also algorithmic assessment of the certainty of those declarations in comparison to the certainties of alternative target-identity possibilities. Unfortunately, despite its importance, confidence assessment is an understudied, underdeveloped, and often-neglected function of ATR systems. This lack of regard stems not only from the difficulty of accurate algorithmic determination of target-identity certainty, but also from a general lack of understanding and careful consideration about what confidence should actually represent. We present a framework for confidence assessment that establishes a clear definition of confidence and provides a straightforward theoretical basis for its calculation. This framework is grounded in a hypothesis-theoretic consideration of ATR and it springs from from a handful of axiomatic principles concerning the nature and meaning of confidence in this context. This framework establishes a rigorous mathematical definition of confidence and it provides equations relating confidence to other information that is almost always provided by ATRs. We present an approach for computing confidence within this framework, using an advance process of ATR characterization followed by a simple computation at the time of ATR execution. We discuss practical difficulties with our approach, and we suggest methods for effective mitigation of these difficulties in implemented systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Facial Named Entity Recognition by Attention-Based Graph Convolutional Neural Network

In the realm of facial recognition and analysis, the ability to accurately cluster large datasets of facial images stands as a cornerstone for various applications, ranging from security surveillance to user biometric identification. This project evolves a novel approach to facial data clustering by embedding facial images into a high-dimensional vector space using an advanced embedding model trained on separate data and assumes a graph-like structure on the high-dimensional vectors. We find our method works significantly better than common shallow methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

De novo synthesis and near atomic resolution imaging of host immune receptors critical for pathogen recognition (Abbreviated Final Report)

The innate immune system serves as the body’s first line of defense against invading pathogens, responding rapidly through the deployment of immune cells at common sites of infection, such as the skin and airways. These immune-cell sentinels express a range of highly conserved receptors, including Toll-like receptors (TLRs), which recognize and bind to pathogen-derived components. This recognition event triggers intracellular signaling cascades that initiate and coordinate immune responses. Despite their significance, the complete structural characterization of full-length TLRs, including their extracellular domain (ECD), transmembrane domain (TMD), and Toll/interleukin-1 receptor (TIR) domain, remains incomplete. In this study, we examined the expression and isolation of human TLR4 incorporated into nanodiscs using two approaches: a cell-free synthesis system and a cell-based transfection strategy employing Expi293F cells derived from the human embryonic kidney lineage. Our findings demonstrate that NLP-bound human TLR4 produced via the cell-based method yielded functional protein suitable for time-resolved single-particle cryo-electron microscopy (cryo-EM). This advancement enables structural characterization of full-length TLR4, maintaining the integrity of its extracellular domain, transmembrane domain, and Toll/Interleukin-1 receptor (TIR) domain.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Assessing Local Structure Motifs Using Order Parameters for Motif Recognition, Interstitial Identification, and Diffusion Path Characterization

Structure–property relationships form the basis of many design rules in materials science, including synthesizability and long-term stability of catalysts, control of electrical and optoelectronic behavior in semiconductors, as well as the capacity of and transport properties in cathode materials for rechargeable batteries. The immediate atomic environments (i.e., the first coordination shells) of a few atomic sites are often a key factor in achieving a desired property. Some of the most frequently encountered coordination patterns are tetrahedra, octahedra, body and face-centered cubic as well as hexagonal close packed-like environments. Here, we showcase the usefulness of local order parameters to identify these basic structural motifs in inorganic solid materials by developing classification criteria. We introduce a systematic testing framework, the Einstein crystal test rig, that probes the response of order parameters to distortions in perfect motifs to validate our approach. Subsequently, we highlight three important application cases. First, we map basic crystal structure information of a large materials database in an intuitive manner by screening the Materials Project (MP) database (61,422 compounds) for element-specific motif distributions. Second, we use the structure-motif recognition capabilities to automatically find interstitials in metals, semiconductor, and insulator materials. Our Interstitialcy Finding Tool (InFiT) facilitates high-throughput screenings of defect properties. Third, the order parameters are reliable and compact quantitative structure descriptors for characterizing diffusion hops of intercalants as our example of magnesium in MnO 2 -spinel indicates. Finally, the tools developed in our work are readily and freely available as software implementations in the pymatgen library, and we expect them to be further applied to machine-learning approaches for emerging applications in materials science.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Creating molecular macrocycles for anion recognition

The creation and functionality of new classes of macrocycles that are shape persistent and can bind anions is described. The genesis of triazolophane macrocycles emerges out of activity surrounding 1,2,3-triazoles made using click chemistry; and the same triazoles are responsible for anion capture. Mistakes made and lessons learnt in anion recognition provide deeper understanding that, together with theory, now provides for computer-aided receptor design. The lessons are acted upon in the creation of two new macrocycles. First, cyanostars are larger and like to capture large anions. Second is tricarb, which also favors large anions but shows a propensity to self-assemble in an orderly and stable manner, laying a foundation for future designs of hierarchical nanostructures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

Conformational Melding Permits a Conserved Binding Geometry in TCR Recognition of Foreign and Self Molecular Mimics

Molecular mimicry between foreign and self Ags is a mechanism of TCR cross-reactivity and is thought to contribute to the development of autoimmunity. The {alpha}{beta} TCR A6 recognizes the foreign Ag Tax from the human T cell leukemia virus-1 when presented by the class I MHC HLA-A2. In a possible link with the autoimmune disease human T cell leukemia virus-1-associated myelopathy/tropical spastic paraparesis, A6 also recognizes a self peptide from the neuronal protein HuD in the context of HLA-A2. We found in our study that the complexes of the HuD and Tax epitopes with HLA-A2 are close but imperfect structural mimics and that in contrast with other recent structures of TCRs with self Ags, A6 engages the HuD Ag with the same traditional binding mode used to engage Tax. Although peptide and MHC conformational changes are needed for recognition of HuD but not Tax and the difference of a single hydroxyl triggers an altered TCR loop conformation, TCR affinity toward HuD is still within the range believed to result in negative selection. Probing further, we found that the HuD-HLA-A2 complex is only weakly stable. Overall, these findings help clarify how molecular mimicry can drive self/nonself cross-reactivity and illustrate how low peptide-MHC stability can permit the survival of T cells expressing self-reactive TCRs that nonetheless bind with a traditional binding mode.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Immunodominance of Antibody Recognition of the HIV Envelope V2 Region in Ig-Humanized Mice

In the RV144 gp120 HIV vaccine trial, decreased transmission risk was correlated with Abs that reacted with a linear epitope at a lysine residue at position 169 (K169) in the HIV-1 envelope (Env) V2 region. The K169 V2 response was restricted to Abs bearing Vλ rearrangements that expressed aspartic acid/glutamic acid in CDR L2. The AE.A244 gp120 in AIDSVAX B/E also bound to the unmutated ancestor of a V2-glycan broadly neutralizing Ab, but this Ab type was not induced in the RV144 trial. In this study, we sought to determine whether immunodominance of the V2 linear epitope could be overcome in the absence of human Vλ rearrangements. We immunized IgH- and Igκ-humanized mice with the AE.A244 gp120 Env. In these mice, the V2 Ab response was focused on a linear epitope that did not include K169. V2 Abs were isolated that used the same human VH gene segment as an RV144 V2 Ab but paired with a mouse λ L chain. Structural characterization of one of these V2 Abs revealed how the linear V2 epitope could be engaged, despite the lack of aspartic acid/glutamic acid encoded in the mouse repertoire. Furthermore, despite the absence of the human Vλ locus in these humanized mice, the dominance of Vλ pairing with human VH for HIV-1 Env V2 recognition resulted in human VH pairing with mouse λ L chains instead of allowing otherwise subdominant V2-glycan broadly neutralizing Abs to develop.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

A Meier-Gorlin syndrome mutation in a conserved C-terminal helix of Orc6 impedes origin recognition complex formation

In eukaryotes, DNA replication requires the origin recognition complex (ORC), a six-subunit assembly that promotes replisome formation on chromosomal origins. Despite extant homology between certain subunits, the degree of structural and organizational overlap between budding yeast and metazoan ORC has been unclear. Using 3D electron microscopy, we determined the subunit organization of metazoan ORC, revealing that it adopts a global architecture very similar to the budding yeast complex. Bioinformatic analysis extends this conservation to Orc6, a subunit of somewhat enigmatic function. Unexpectedly, a mutation in the Orc6 C-terminus linked to Meier-Gorlin syndrome, a dwarfism disorder, impedes proper recruitment of Orc6 into ORC; biochemical studies reveal that this region of Orc6 associates with a previously uncharacterized domain of Orc3 and is required for ORC function and MCM2–7 loading in vivo. Together, our results suggest that Meier-Gorlin syndrome mutations in Orc6 impair the formation of ORC hexamers, interfering with appropriate ORC functions.

59 BASIC BIOLOGICAL SCIENCES↗