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At least 127 records · Page 7

All sources NASA NTRS DOE OSTI

DOE OSTI2018

Human N -acetylglucosaminyltransferase II substrate recognition uses a modular architecture that includes a convergent exosite

Asn-linked oligosaccharides are extensively modified during transit through the secretory pathway, first by trimming of the nascent glycan chains and subsequently by initiating and extending multiple oligosaccharide branches from the trimannosyl glycan core. Trimming and branching pathway steps are highly ordered and hierarchal based on the precise substrate specificities of the individual biosynthetic enzymes. A key committed step in the synthesis of complex-type glycans is catalyzed by N-acetylglucosaminyltransferase II (MGAT2), an enzyme that generates the second GlcNAcβ1,2- branch from the trimannosyl glycan core using UDP-GlcNAc as the sugar donor. We determined the structure of human MGAT2 as a Mn 2+ -UDP donor analog complex and as a GlcNAcMan 3 GlcNAc 2 -Asn acceptor complex to reveal the structural basis for substrate recognition and catalysis. The enzyme exhibits a GT-A Rossmann-like fold that employs conserved divalent cation-dependent substrate interactions with the UDP-GlcNAc donor. MGAT2 interactions with the extended glycan acceptor are distinct from other related glycosyltransferases. These interactions are composed of a catalytic subsite that binds the Man-α1,6- monosaccharide acceptor and a distal exosite pocket that binds the GlcNAc-β1,2Man-α1,3Manβ- substrate “recognition arm.” Recognition arm interactions are similar to the enzyme–substrate interactions for Golgi α-mannosidase II, a glycoside hydrolase that acts just before MGAT2 in the Asn-linked glycan biosynthetic pathway. Here, these data suggest that substrate binding by MGAT2 employs both conserved and convergent catalytic subsite modules to provide substrate selectivity and catalysis. More broadly, the MGAT2 active-site architecture demonstrates how glycosyltransferases create complementary modular templates for regiospecific extension of glycan structures in mammalian cells.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Wire-cell 3D pattern recognition techniques for neutrino event reconstruction in large LArTPCs: algorithm description and quantitative evaluation with MicroBooNE simulation

Wire-Cell is a 3D event reconstruction package for liquid argon time projection chambers. Through geometry, time, and drifted charge from multiple readout wire planes, 3D space points with associated charge are reconstructed prior to the pattern recognition stage. Pattern recognition techniques, including track trajectory and dQ/dx (ionization charge per unit length) fitting, 3D neutrino vertex fitting, track and shower separation, particle-level clustering, and particle identification are then applied on these 3D space points as well as the original 2D projection measurements. A deep neural network is developed to enhance the reconstruction of the neutrino interaction vertex. Compared to traditional algorithms, the deep neural network boosts the vertex efficiency by a relative 30% for charged-current ν e interactions. Therefore, this pattern recognition achieves 80–90% reconstruction efficiencies for primary leptons, after a 65.8% (72.9%) vertex efficiency for charged-current ν e (ν μ ) interactions. Based on the resulting reconstructed particles and their kinematics, we also achieve 15-20% energy reconstruction resolutions for charged-current neutrino interactions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Stereoselective recognition of morphine enantiomers by μ -opioid receptor

Stereospecific recognition of chiral molecules plays a crucial role in biological systems. The μ-opioid receptor (MOR) exhibits binding affinity towards (-)-morphine, a well-established gold standard in pain management, while it shows minimal binding affinity for the (+)-morphine enantiomer, resulting in a lack of analgesic activity. Understanding how MOR stereoselectively recognizes morphine enantiomers has remained a puzzle in neuroscience and pharmacology for over half-a-century due to the lack of direct observation techniques. To unravel this mystery, we constructed the binding and unbinding processes of morphine enantiomers with MOR via molecular dynamics simulations to investigate the thermodynamics and kinetics governing MOR's stereoselective recognition of morphine enantiomers. Our findings reveal that the binding of (-)-morphine stabilizes MOR in its activated state, exhibiting a deep energy well and a prolonged residence time. In contrast, (+)-morphine fails to sustain the activation state of MOR. Furthermore, the results suggest that specific residues, namely D114 2.50 and D147 3.32 , are deprotonated in the active state of MOR bound to (-)-morphine. This work highlights that the selectivity in molecular recognition goes beyond binding affinities, extending into the realm of residence time.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Cross-Domain Recognition by Identifying Joint Subspaces of Source Domain and Target Domain

This paper introduces here a new method to solve the cross-domain recognition problem. Different from the traditional domain adaption methods which rely on a global domain shift for all classes between the source and target domains, the proposed method is more flexible to capture individual class variations across domains. By adopting a natural and widely used assumption that the data samples from the same class should lay on an intrinsic low-dimensional subspace, even if they come from different domains, the proposed method circumvents the limitation of the global domain shift, and solves the cross-domain recognition by finding the joint subspaces of the source and target domains. Specifically, given labeled samples in the source domain, we construct a subspace for each of the classes. Then we construct subspaces in the target domain, called anchor subspaces, by collecting unlabeled samples that are close to each other and are highly likely to belong to the same class. The corresponding class label is then assigned by minimizing a cost function which reflects the overlap and topological structure consistency between subspaces across the source and target domains, and within the anchor subspaces, respectively. We further combine the anchor subspaces to the corresponding source subspaces to construct the joint subspaces. Subsequently, one-versus-rest support vector machine classifiers are trained using the data samples belonging to the same joint subspaces and applied to unlabeled data in the target domain. We evaluate the proposed method on two widely used datasets: 1) object recognition dataset for computer vision tasks and 2) sentiment classification dataset for natural language processing tasks. Comparison results demonstrate that the proposed method outperforms the comparison methods on both datasets.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

TU-C-17A-03: An Integrated Contour Evaluation Software Tool Using Supervised Pattern Recognition for Radiotherapy

Purpose: Radiotherapy (RT) contours delineated either manually or semiautomatically require verification before clinical usage. Manual evaluation is very time consuming. A new integrated software tool using supervised pattern contour recognition was thus developed to facilitate this process. Methods: The contouring tool was developed using an object-oriented programming language C# and application programming interfaces, e.g. visualization toolkit (VTK). The C# language served as the tool design basis. The Accord.Net scientific computing libraries were utilized for the required statistical data processing and pattern recognition, while the VTK was used to build and render 3-D mesh models from critical RT structures in real-time and 360° visualization. Principal component analysis (PCA) was used for system self-updating geometry variations of normal structures based on physician-approved RT contours as a training dataset. The inhouse design of supervised PCA-based contour recognition method was used for automatically evaluating contour normality/abnormality. The function for reporting the contour evaluation results was implemented by using C# and Windows Form Designer. Results: The software input was RT simulation images and RT structures from commercial clinical treatment planning systems. Several abilities were demonstrated: automatic assessment of RT contours, file loading/saving of various modality medical images and RT contours, and generation/visualization of 3-D images and anatomical models. Moreover, it supported the 360° rendering of the RT structures in a multi-slice view, which allows physicians to visually check and edit abnormally contoured structures. Conclusion: This new software integrates the supervised learning framework with image processing and graphical visualization modules for RT contour verification. This tool has great potential for facilitating treatment planning with the assistance of an automatic contour evaluation module in avoiding unnecessary manual verification for physicians/dosimetrists. In addition, its nature as a compact and stand-alone tool allows for future extensibility to include additional functions for physicians’ clinical needs.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2021

Transcranial Direct Current Stimulation (tDCS) Improves Empathy and Recognition of Facial Emotions Conveying Threat in Adults with Autism Spectrum Disorder (ASD): A Randomized Controlled Pilot Study

Introduction: Empathy is critical for human interactions to become shared and meaningful, and it is facilitated by the expression and processing of facial emotions. Deficits in empathy and facial emotion recognition are associated with individuals with autism spectrum disorder (ASD), with specific concerns over inaccurate recognition of facial emotion expressions conveying a threat. Yet, the number of evidenced interventions for facial emotion recognition and processing (FERP), emotion, and empathy remains limited, particularly for adults with ASD. Transcranial direct current stimulation (tDCS), a noninvasive brain stimulation, may be a promising treatment modality to safely accelerate and/or enhance treatment interventions to increase their efficacy. Methods: This study investigates the effectiveness of FERP, emotion, and empathy treatment interventions paired with tDCS for adults with ASD. Differences in scores on the Empathy Quotient (EQ) and on a FERP test were predicted for verum tDCS when compared to sham. Verum/sham tDCS was randomly assigned in a within-subjects, double-blinded design in adults with ASD without intellectual disability. Results: Verum tDCS significantly improved EQ scores and FERP scores for emotions that conveyed threat. Conclusions: These results suggest the potential for increasing the efficacy of treatment interventions by pairing them with tDCS for individuals with ASD.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2013

Non-Cooperative Facial Recognition Video Dataset Collection Plan

The Pacific Northwest National Laboratory (PNNL) will produce a non-cooperative (i.e. not posing for the camera) facial recognition video data set for research purposes to evaluate and enhance facial recognition systems technology. The aggregate data set consists of 1) videos capturing PNNL role players and public volunteers in three key operational settings, 2) photographs of the role players for enrolling in an evaluation database, and 3) ground truth data that documents when the role player is within various camera fields of view. PNNL will deliver the aggregate data set to DHS who may then choose to make it available to other government agencies interested in evaluating and enhancing facial recognition systems. The three operational settings that will be the focus of the video collection effort include: 1) unidirectional crowd flow 2) bi-directional crowd flow, and 3) linear and/or serpentine queues.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2023

LA100 Equity Strategies. Chapter 1: Justice as Recognition

The LA100 Equity Strategies project synthesizes community guidance with robust research, modeling, and analysis to identify strategy options that can increase equitable outcomes in Los Angeles' clean energy transition. Grounded in the analysis of past and ongoing energy inequities and engagement with underserved communities, the project presents community-guided and community-tailored strategies that aim to operationalize recognition and procedural justice. This chapter focuses on recognition justice, identifying and analyzing past and present social, cultural, and institutional barriers to affordable and clean energy for LA communities, as well as disparities in the distribution of energy system burdens and benefits. Acknowledging historical and structural factors behind current energy inequities is a first step in developing energy equity strategies for the Los Angeles Department of Water and Power (LADWP) to achieve distributional justice - the just and equitable distribution of energy benefits and burdens in LA's energy transition. Recognition, procedural, and distributional justice are the three tenets of energy justice around which the LA100 Equity Strategies project is organized. In the United States, theory and practice around justice have historically focused on unequal distribution of environmental benefits and burdens. The historical siting of hazardous infrastructure such as power plants and transportation corridors in communities of color and low-income communities has disproportionately concentrated negative environmental impacts in their neighborhoods. Those inequities are reproduced via programs, policies, and other efforts (e.g., zoning and regulations, rebates and incentives, lending, investment, and financing) that directly affect people's lives and livelihoods. In recent decades, energy justice scholars and activists broadened their analysis to examine how environmental inequities intersect with other forms of social difference in the distribution of energy benefits and burdens. This approach investigates how differences in class, race, gender, age, and abilities, among others, intersect to understand the social, cultural, and institutional processes that create and perpetuate energy inequities. The LA100 Equity Strategies project embraces this approach to developing a more just clean energy future for LA. Because recognizing and understanding past and existing inequities is vital to addressing them in ways that ensure an equitable energy transition for all Angelenos, this chapter focuses on identifying and analyzing the challenges and inequities of LA's past and existing energy system, including LADWP programs.

community↗

DOE OSTI2015

Conditional random fields for pattern recognition applied to structured data

Pattern recognition uses measurements from an input domain, X, to predict their labels from an output domain, Y. Image analysis is one setting where one might want to infer whether a pixel patch contains an object that is “manmade” (such as a building) or “natural” (such as a tree). Suppose the label for a pixel patch is “manmade”; if the label for a nearby pixel patch is then more likely to be “manmade” there is structure in the output domain that can be exploited to improve pattern recognition performance. Modeling P(X) is difficult because features between parts of the model are often correlated. Therefore, conditional random fields (CRFs) model structured data using the conditional distribution P(Y|X = x), without specifying a model for P(X), and are well suited for applications with dependent features. This paper has two parts. First, we overview CRFs and their application to pattern recognition in structured problems. Our primary examples are image analysis applications in which there is dependence among samples (pixel patches) in the output domain. Second, we identify research topics and present numerical examples.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2012

Composite Wavelet Filters for Enhanced Automated Target Recognition

Automated Target Recognition (ATR) systems aim to automate target detection, recognition, and tracking. The current project applies a JPL ATR system to low-resolution sonar and camera videos taken from unmanned vehicles. These sonar images are inherently noisy and difficult to interpret, and pictures taken underwater are unreliable due to murkiness and inconsistent lighting. The ATR system breaks target recognition into three stages: 1) Videos of both sonar and camera footage are broken into frames and preprocessed to enhance images and detect Regions of Interest (ROIs). 2) Features are extracted from these ROIs in preparation for classification. 3) ROIs are classified as true or false positives using a standard Neural Network based on the extracted features. Several preprocessing, feature extraction, and training methods are tested and discussed in this paper.

automated target recognition↗

NASA NTRS2011

Testing of a Composite Wavelet Filter to Enhance Automated Target Recognition in SONAR

Automated Target Recognition (ATR) systems aim to automate target detection, recognition, and tracking. The current project applies a JPL ATR system to low resolution SONAR and camera videos taken from Unmanned Underwater Vehicles (UUVs). These SONAR images are inherently noisy and difficult to interpret, and pictures taken underwater are unreliable due to murkiness and inconsistent lighting. The ATR system breaks target recognition into three stages: 1) Videos of both SONAR and camera footage are broken into frames and preprocessed to enhance images and detect Regions of Interest (ROIs). 2) Features are extracted from these ROIs in preparation for classification. 3) ROIs are classified as true or false positives using a standard Neural Network based on the extracted features. Several preprocessing, feature extraction, and training methods are tested and discussed in this report.

image processing↗

NASA NTRS2015

A Fast Goal Recognition Technique Based on Interaction Estimates

Goal Recognition is the task of inferring an actor's goals given some or all of the actor's observed actions. There is considerable interest in Goal Recognition for use in intelligent personal assistants, smart environments, intelligent tutoring systems, and monitoring user's needs. In much of this work, the actor's observed actions are compared against a generated library of plans. Recent work by Ramirez and Geffner makes use of AI planning to determine how closely a sequence of observed actions matches plans for each possible goal. For each goal, this is done by comparing the cost of a plan for that goal with the cost of a plan for that goal that includes the observed actions. This approach yields useful rankings, but is impractical for real-time goal recognition in large domains because of the computational expense of constructing plans for each possible goal. In this paper, we introduce an approach that propagates cost and interaction information in a plan graph, and uses this information to estimate goal probabilities. We show that this approach is much faster, but still yields high quality results.

gola recognition↗

NASA NTRSDate not supplied

Towards Understanding Data Requirements for Developing Automatic Speech Recognition Systems for Air Traffic Control

In recent years, the application of automatic speech recognition has gained popularity across diverse industries, including aviation. Given the many applications focusing on transcribing air traffic control and management communication, this paper explores the training of OpenAI's Whisper model across multiple existing public and private air traffic control voice datasets in an effort to improve robustness. Combining roughly 60+ hours of various air traffic datasets, our goal is to train a unified Whisper model and expect an average word error rate reduction across testing datasets. Furthermore, this work aims to understand the data quantity requirements for achieving state-of-the art results by comprehensively training Whisper on varying dataset sizes. This work has the potential to improve automatic speech recognition performance across the domain, improve understanding of the quantity of data required by an aviation speech recognition system, and lastly provide metrics to compare and improve upon in future research.

ATC↗

DOE OSTI2014

A role for carbohydrate recognition in mammalian sperm-egg binding

Highlights: • Mammalian sperm-egg binding as a carbohydrate dependent species recognition event. • The role of carbohydrate recognition in human, mouse and pig sperm-egg binding. • Historical perspective and future directions for research focused on gamete binding. - Abstract: Mammalian fertilization usually requires three sequential cell–cell interactions: (i) initial binding of sperm to the specialized extracellular matrix coating the egg known as the zona pellucida (ZP); (ii) binding of sperm to the ZP via the inner acrosomal membrane that is exposed following the induction of acrosomal exocytosis; and (iii) adhesion of acrosome-reacted sperm to the plasma membrane of the egg cell, enabling subsequent fusion of these gametes. The focus of this review is on the initial binding of intact sperm to the mammalian ZP. Evidence collected over the past fifty years has confirmed that this interaction relies primarily on the recognition of carbohydrate sequences presented on the ZP by lectin-like egg binding proteins located on the plasma membrane of sperm. There is also evidence that the same carbohydrate sequences that mediate binding also function as ligands for lectins on lymphocytes that can inactivate immune responses, likely protecting the egg and the developing embryo up to the stage of blastocyst hatching. The literature related to initial sperm-ZP binding in the three major mammalian models (human, mouse and pig) is discussed. Historical perspectives and future directions for research related to this aspect of gamete adhesion are also presented.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

Molecular basis for damage recognition and verification by XPC-RAD23B and TFIIH in nucleotide excision repair

Global genome nucleotide excision repair (GG-NER) is the main pathway for the removal of bulky lesions from DNA and is characterized by an extraordinarily wide substrate specificity. Remarkably, the efficiency of lesion removal varies dramatically and certain lesions escape repair altogether and are therefore associated with high levels of mutagenicity. Central to the multistep mechanism of damage recognition in NER is the sensing of lesion-induced thermodynamic and structural alterations of DNA by the XPC-RAD23B protein and the verification of the damage by the transcription/repair factor TFIIH. Additional factors contribute to the process: UV-DDB, for the recognition of certain UV-induced lesions in particular in the context of chromatin, while the XPA protein is believed to have a role in damage verification and NER complex assembly. In this paper, we consider the molecular mechanisms that determine repair efficiency in GG-NER based on recent structural, computational, biochemical, cellular and single molecule studies of XPC-RAD23B and its yeast ortholog Rad4. We discuss how the actions of XPC-RAD23B are integrated with those of other NER proteins and, based on recent high-resolution structures of TFIIH, present a structural model of how XPC-RAD23B and TFIIH cooperate in damage recognition and verification.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2013

Evolution of I-SceI Homing Endonucleases with Increased DNA Recognition Site Specificity

Elucidating how homing endonucleases undergo changes in recognition site specificity will facilitate efforts to engineer proteins for gene therapy applications. I-SceI is a monomeric homing endonuclease that recognizes and cleaves within an 18-bp target. It tolerates limited degeneracy in its target sequence, including substitution of a C:G{sub +4} base pair for the wild-type A:T{sub +4} base pair. Libraries encoding randomized amino acids at I-SceI residue positions that contact or are proximal to A:T{sub +4} were used in conjunction with a bacterial one-hybrid system to select I-SceI derivatives that bind to recognition sites containing either the A:T{sub +4} or the C:G{sub +4} base pairs. As expected, isolates encoding wild-type residues at the randomized positions were selected using either target sequence. All I-SceI proteins isolated using the C:G{sub +4} recognition site included small side-chain substitutions at G100 and either contained (K86R/G100T, K86R/G100S and K86R/G100C) or lacked (G100A, G100T) a K86R substitution. Interestingly, the binding affinities of the selected variants for the wild-type A:T{sub +4} target are 4- to 11-fold lower than that of wild-type I-SceI, whereas those for the C:G{sub +4} target are similar. The increased specificity of the mutant proteins is also evident in binding experiments in vivo. These differences in binding affinities account for the observed -36-fold difference in target preference between the K86R/G100T and wild-type proteins in DNA cleavage assays. An X-ray crystal structure of the K86R/G100T mutant protein bound to a DNA duplex containing the C:G{sub +4} substitution suggests how sequence specificity of a homing enzyme can increase. This biochemical and structural analysis defines one pathway by which site specificity is augmented for a homing endonuclease.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

Inhibition of Acinetobacter -Derived Cephalosporinase: Exploring the Carboxylate Recognition Site Using Novel β-Lactamase Inhibitors

Boronic acids are attracting a lot of attention as β-lactamase inhibitors, and in particular, compound S02030 (K i = 44 nM) proved to be a good lead compound against ADC-7 (Acinetobacter-derived cephalosporinase), one of the most significant resistance determinants in A. baumannii. The atomic structure of the ADC-7/S02030 complex highlighted the importance of critical structural determinants for recognition of the boronic acids. Herein, to elucidate the role in recognition of the R2-carboxylate, which mimics the C 3 /C 4 found in β-lactams, we designed, synthesized, and characterized six derivatives of S02030 (3a). Out of the six compounds, the best inhibitors proved to be those with an explicit negative charge (compounds 3a–c, 3h, and 3j, K i = 44–115 nM), which is in contrast to the derivatives where the negative charge is omitted, such as the amide derivative 3d (K i = 224 nM) and the hydroxyamide derivative 3e (K i = 155 nM). To develop a structural characterization of inhibitor binding in the active site, the X-ray crystal structures of ADC-7 in a complex with compounds 3c, SM23, and EC04 were determined. All three compounds share the same structural features as in S02030 but only differ in the carboxy-R2 side chain, thereby providing the opportunity of exploring the distinct binding mode of the negatively charged R2 side chain. This cephalosporinase demonstrates a high degree of versatility in recognition, employing different residues to directly interact with the carboxylate, thus suggesting the existence of a “carboxylate binding region” rather than a binding site in ADC enzymes. As a result, this class of compounds was tested against resistant clinical strains of A. baumannii and are effective at inhibiting bacterial growth in conjunction with a β-lactam antibiotic.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2013

DAXX envelops a histone H3.3-H4 dimer for H3.3-specific recognition

Histone chaperones represent a structurally and functionally diverse family of histone-binding proteins that prevent promiscuous interactions of histones before their assembly into chromatin. DAXX is a metazoan histone chaperone specific to the evolutionarily conserved histone variant H3.3. Here we report the crystal structures of the DAXX histone-binding domain with a histone H3.3–H4 dimer, including mutants within DAXX and H3.3, together with in vitro and in vivo functional studies that elucidate the principles underlying H3.3 recognition specificity. Occupying 40% of the histone surface-accessible area, DAXX wraps around the H3.3–H4 dimer, with complex formation accompanied by structural transitions in the H3.3–H4 histone fold. DAXX uses an extended α-helical conformation to compete with major inter-histone, DNA and ASF1 interaction sites. Our structural studies identify recognition elements that read out H3.3-specific residues, and functional studies address the contributions of Gly90 in H3.3 and Glu225 in DAXX to chaperone-mediated H3.3 variant recognition specificity.

Elsässer, Simon J↗