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At least 163 records · Page 9

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↗

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↗

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↗

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↗

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↗

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↗

A new concept of vertically integrated pattern recognition associative memory

Hardware-based pattern recognition for fast triggering on particle tracks has been successfully used in high-energy physics experiments for some time. The CDF Silicon Vertex Trigger (SVT) at the Fermilab Tevatron is an excellent example. The method used there, developed in the 1990's, is based on algorithms that use a massively parallel associative memory architecture to identify patterns efficiently at high speed. However, due to much higher occupancy and event rates at the LHC, and the fact that the LHC detectors have a much larger number of channels in their tracking detectors, there is an enormous challenge in implementing fast pattern recognition for a track trigger, requiring about three orders of magnitude more associative memory patterns than what was used in the original CDF SVT. Scaling of current technologies is unlikely to satisfy the scientific needs of the future, and investments in transformational new technologies need to be made. In this paper, we will discuss a new concept of using the emerging 3D vertical integration technology to significantly advance the state-of-the-art for fast pattern recognition within and outside HEP. A generic R and D proposal based on this new concept, with a few institutions involved, has recently been submitted to DOE with the goal to design and perform the ASIC engineering necessary to realize a prototype device. The progress of this R and D project will be reported in the future. Here we will only focus on the concept of this new approach.

43 PARTICLE ACCELERATORS↗

Structural insights into the regulation and the recognition of histone marks by the SET domain of NSD1

Highlights: {yields} NSD1, NSD2/MMSET/WHSC1, and NSD3/WHSC1L1 are histone methyltransferases linked to numerous cancers. {yields} Little is known about the NSD pathways and HMTase inhibitors are sorely needed in the epigenetic therapy of cancers. {yields} We investigate the regulation and the recognition of histone marks by the SET domain of NSD1. {yields} A unique and key mechanism is driven by a loop at the interface of the SET and postSET region. {yields} Implications for developing specific and selective HMTase inhibitors are presented. -- Abstract: The development of epigenetic therapies fuels cancer hope. DNA-methylation inhibitors, histone-deacetylase and histone-methyltransferase (HMTase) inhibitors are being developed as the utilization of epigenetic targets is emerging as an effective and valuable approach to chemotherapy as well as chemoprevention of cancer. The nuclear receptor binding SET domain (NSD) protein is a family of three HMTases, NSD1, NSD2/MMSET/WHSC1, and NSD3/WHSC1L1 that are critical in maintaining the chromatin integrity. A growing number of studies have reported alterations or amplifications of NSD1, NSD2, or NSD3 in numerous carcinogenic events. Reducing NSDs activity through specific lysine-HMTase inhibitors appears promising to help suppressing cancer growth. However, little is known about the NSD pathways and our understanding of the histone lysine-HMTase mechanism is partial. To shed some light on both the recognition and the regulation of epigenetic marks by the SET domain of the NSD family, we investigate the structural mechanisms of the docking of the histone-H4 tail on the SET domain of NSD1. Our finding exposes a key regulatory and recognition mechanism driven by the flexibility of a loop at the interface of the SET and postSET region. Finally, we prospect the special value of this regulatory region for developing specific and selective NSD inhibitors for the epigenetic therapy of cancers.

60 APPLIED LIFE SCIENCES↗

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↗

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↗

Recognition of Nucleoside Monophosphate Substrates by Haemophilus influenzae Class C Acid Phosphatase

The e (P4) phosphatase from Haemophilus influenzae functions in a vestigial NAD{sup +} utilization pathway by dephosphorylating nicotinamide mononucleotide to nicotinamide riboside. P4 is also the prototype of class C acid phosphatases (CCAPs), which are nonspecific 5{prime},3{prime}-nucleotidases localized to the bacterial outer membrane. To understand substrate recognition by P4 and other class C phosphatases, we have determined the crystal structures of a substrate-trapping mutant P4 enzyme complexed with nicotinamide mononucleotide, 5{prime}-AMP, 3{prime}-AMP, and 2{prime}-AMP. The structures reveal an anchor-shaped substrate-binding cavity comprising a conserved hydrophobic box that clamps the nucleotide base, a buried phosphoryl binding site, and three solvent-filled pockets that contact the ribose and the hydrogen-bonding edge of the base. The span between the hydrophobic box and the phosphoryl site is optimal for recognizing nucleoside monophosphates, explaining the general preference for this class of substrate. The base makes no hydrogen bonds with the enzyme, consistent with an observed lack of base specificity. Two solvent-filled pockets flanking the ribose are key to the dual recognition of 5{prime}-nucleotides and 3{prime}-nucleotides. These pockets minimize the enzyme's direct interactions with the ribose and provide sufficient space to accommodate 5{prime} substrates in an anti conformation and 3{prime} substrates in a syn conformation. Finally, the structures suggest that class B acid phosphatases and CCAPs share a common strategy for nucleotide recognition.

08 HYDROGEN↗

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↗

Novel object recognition ability in female mice following exposure to nanoparticle-rich diesel exhaust

Recently, our laboratory reported that exposure to nanoparticle-rich diesel exhaust (NRDE) for 3 months impaired hippocampus-dependent spatial learning ability and up-regulated the expressions of memory function-related genes in the hippocampus of female mice. However, whether NRDE affects the hippocampus-dependent non-spatial learning ability and the mechanism of NRDE-induced neurotoxicity was unknown. Female BALB/c mice were exposed to clean air, middle-dose NRDE (M-NRDE, 47 μg/m{sup 3}), high-dose NRDE (H-NRDE, 129 μg/m{sup 3}), or filtered H-NRDE (F-DE) for 3 months. We then investigated the effect of NRDE exposure on non-spatial learning ability and the expression of genes related to glutamate neurotransmission using a novel object recognition test and a real-time RT-PCR analysis, respectively. We also examined microglia marker Iba1 immunoreactivity in the hippocampus using immunohistochemical analyses. Mice exposed to H-NRDE or F-DE could not discriminate between familiar and novel objects. The control and M-NRDE-exposed groups showed a significantly increased discrimination index, compared to the H-NRDE-exposed group. Although no significant changes in the expression levels of the NMDA receptor subunits were observed, the expression of glutamate transporter EAAT4 was decreased and that of glutamic acid decarboxylase GAD65 was increased in the hippocampus of H-NRDE-exposed mice, compared with the expression levels in control mice. We also found that microglia activation was prominent in the hippocampal area of the H-NRDE-exposed mice, compared with the other groups. These results indicated that exposure to NRDE for 3 months impaired the novel object recognition ability. The present study suggests that genes related to glutamate metabolism may be involved in the NRDE-induced neurotoxicity observed in the present mouse model. -- Highlights: ► The effects of nanoparticle-induced neurotoxicity remain unclear. ► We investigated the effect of exposure to nanoparticles on learning behavior. ► We found that exposure to nanoparticles impaired novel object recognition ability.

60 APPLIED LIFE SCIENCES↗

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↗

Stability and Sugar Recognition Ability of Ricin-Like Carbohydrate Binding Domains

Lectins are a class of proteins known for their novel binding to saccharides. Understanding this sugar recognition process can be crucial in creating structure-based designs of proteins with various biological roles. We focus on the sugar binding of a particular lectin, ricin, which has two -trefoil carbohydrate-binding domains (CRDs) found in several plant protein toxins. The binding ability of possible sites of ricin-like CRD has been puzzling. The apo and various (multiple) ligand-bound forms of the sugar-binding domains of ricin were studied by molecular dynamics simulations. By evaluating structural stability, hydrogen bond dynamics, flexibility, and binding energy, we obtained a detailed picture of the sugar recognition of the ricin-like CRD. Unlike what was previously believed, we found that the binding abilities of the two known sites are not independent of each other. The binding ability of one site is positively affected by the other site. While the mean positions of different binding scenarios are not altered significantly, the flexibility of the binding pockets visibly decreases upon multiple ligand binding. This change in flexibility seems to be the origin of the binding cooperativity. All the hydrogen bonds that are strong in the monoligand state are also strong in the double-ligand complex, although the stability is much higher in the latter form due to cooperativity. These strong hydrogen bonds in a monoligand state are deemed to be the essential hydrogen bonds. Furthermore, by examining the structural correlation matrix, the two domains are structurally one entity. Galactose hydroxyl groups, OH4 and OH3, are the most critical parts in both site 1 and site 2 recognition.

08 HYDROGEN↗

Molecular Recognition of Insulin by a Synthetic Receptor

The discovery of molecules that bind tightly and selectively to desired proteins continues to drive innovation at the interface of chemistry and biology. This paper describes the binding of human insulin by the synthetic receptor cucurbit[7]uril (Q7) in vitro. Isothermal titration calorimetry and fluorescence spectroscopy experiments show that Q7 binds to insulin with an equilibrium association constant of 1.5 x 10{sup 6} M{sup -1} and with 50-100-fold selectivity versus proteins that are much larger but lack an N-terminal aromatic residue, and with >1000-fold selectivity versus an insulin variant lacking the N-terminal phenylalanine (Phe) residue. The crystal structure of the Q7{center_dot}insulin complex shows that binding occurs at the N-terminal Phe residue and that the N-terminus unfolds to enable binding. These findings suggest that site-selective recognition is based on the properties inherent to a protein terminus, including the unique chemical epitope presented by the terminal residue and the greater freedom of the terminus to unfold, like the end of a ball of string, to accommodate binding. Insulin recognition was predicted accurately from studies on short peptides and exemplifies an approach to protein recognition by targeting the terminus.

59 BASIC BIOLOGICAL SCIENCES↗

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↗

Chiral recognition and selection during the self-assembly process of protein-mimic macroanions

The research on chiral recognition and chiral selection is not only fundamental in resolving the puzzle of homochirality, but also instructive in chiral separation and stereoselective catalysis. Here we report the chiral recognition and chiral selection during the self-assembly process of two enantiomeric wheel-shaped macroanions, [Fe28(μ3-O)8(Tart)16(HCOO)24]20- (Tart=D- or L-tartaric acid tetra-anion). The enantiomers are observed to remain self-sorted and self-assemble into their individual assemblies in their racemic mixture solution. The addition of chiral co-anions can selectively suppress the self-assembly process of the enantiomeric macroanions, which is further used to separate the two enantiomers from their mixtures on the basis of the size difference between the monomers and the assemblies. We believe that delicate long-range electrostatic interactions could be responsible for such high-level chiral recognition and selection.

Yin, Panchao↗