SEARCH · Search NASA

Results for “sequencing test”

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.

SourceResearch connectionFrom yearThrough year

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

At least 631 records · Page 35

All sources NASA NTRS DOE OSTI

DOE OSTI2020

Silicon photonic chip for 16-channel wavelength division (de-)multiplexing in the O-band

We experimentally demonstrate a silicon photonic chip-scale 16-channel wavelength division multiplexer (WDM) operating in the O-band. The silicon photonic chip consists of a common-input bus waveguide integrated with a sequence of 16 spectral add-drop filters implemented by 4-port contra-directional Bragg couplers and resonant cladding modulated perturbations. The combination of these features reduces the spectral bandwidth of the filters and improves the crosstalk. An apodization of the cladding modulated perturbations between the bus and the add/drop waveguides is used to optimize the strength of the coupling coefficient in the propagation direction to reduce the intra-channel crosstalk on adjacent channels. The fabricated chip was validated experimentally with a measured intra-channel crosstalk of ∼−18.9 dB for a channel spacing of 2.6 nm. The multiplexer/demultiplexer chip was also experimentally tested with a 10 Gbps data waveform. The resulting eye-pattern indicates that this approach is suitable for datacenter WDM-based interconnects in the O-band with large aggregate bandwidths.

Davis, Jordan A. (ORCID:0000000343483295)↗

DOE OSTI2024

HERO CarbonSAFE Phase 2 Project in the Columbia River Basalt Group

The Hermiston, Oregon Basalt CarbonSAFE Phase II project (HERO CarbonSAFE) seeks to accelerate the deployment of commercial carbon dioxide (CO2) storage projects in basaltic rocks. Basalt CO2 storage has several advantages to conventional saline storage reservoirs including 1. The potential for rapid mineralization of CO2, 2. Associated decreases in pressure and CO2 migration risks, 3. Reduced long-term monitoring requirements with respect to plume tracking, 4. Widespread geographic distribution and, 5. Large storage potential due to thickness, porosity, and CO2 interactions with basalt. And for locations such as the Pacific Northwest, Hawaii, Iceland, India and Japan, basalts may offer the only economically feasible option for local CO2 storage. However, there are limited field-scale assessments of CO2 storage in basalt, and current carbon capture utilization and storage (CCUS) permitting and regulatory frameworks were developed for conventional saline reservoirs. HERO CarbonSAFE is designed to address research gaps and uncertainties associated with basalt storage. Specifically, the project will assess the feasibility of CO2 injection in the deep layered basalts, long-term storage (mineralization), practical approaches for large-scale implementation (50+ million metric tons of CO2 over 30 years), lithology-specific risks, and the technoeconomic potential for CO2 storage in basalts. The HERO CarbonSAFE project will assess feasibility of developing a commercial-scale (50+ million metric tons of CO2) geological storage complex within the Columbia River Basalt Group (CRBG), a layered continental flood basalt complex that underlies Calpine’s natural gas-fired Hermiston Power Project (HPP) in Hermiston, OR (Figure 1). Under this 2-year CarbonSAFE Phase II project, the HERO team will conduct a data acquisition campaign that includes drilling a stratigraphic well to a total depth of ~1,500 m into the thick layered basalts proximal to HPP. A comprehensive well logging and hydrologic testing program will be augmented with new core collected from flow zones and sealing units, and comprehensive laboratory testing to help refine the kinetic rates of mineralization. The newly acquired information will be integrated with existing data from regional wells to correlate basalt injection zone properties to develop storage hub/commercial-scale models. Using these models, the project team will evaluate injection scenarios to define the technical and economic potential for storing a minimum of 50 million metric tons of CO2 over a 30-year period, along with a robust sensitivity analysis on key parameters governing reservoir viability for sustainable injection over a commercial project lifetime. Specific technical objectives of HERO are: (1) assessing the reservoir response of a series of stacked layered reservoir flowtop sequences occurring in this area of the CRBG to commercial-scale injection volumes; (2) extending prior efforts by the project team to characterize the deep layered basalts encountered in regional studies, to leverage prior investments by U.S. Department of Energy’s (DOE) Carbon Storage program; (3) leveraging DOE’s mineralization characterization efforts to advance model parametrization for commercial scale injection of CO2 in basalts; (4) conducting risk assessments associated with scaling up to commercial storage hub injection goals, while validating DOE’s National Risk Assessment Partnership (NRAP) tools, to identify potential constraints that would prevent the CRBG from serving as a commercial-scale storage complex; (5) developing mitigation plans to address identified risks; (6) developing a commercial-scale injection and monitoring, verification and accounting (MVA) strategy; (7) utilizing computational models to define and minimize, if possible, the Area of Review (AoR) under Class VI regulations; and (8) developing a robust CO2 management strategy for CRBG that also considers a regional source/sink approach that is responsive to stakeholder needs and industrial demand. Specific institutional objectives are: (1) identifying and developing plans to mitigate the nontechnical challenges associated with the build-out of a commercial-scale storage complex within the CRBG with integrated CO2 sources; (2) implementing the community outreach plan; (3) conducting regulatory research, including a survey of issues related to pore space ownership, MVA and long-term assurance of mineralization-based storage, to support an eventual application for a UIC Class VI permit; (4) advancing the project’s plan for CO2 liability management; and (5) continuing to refine and update the project’s economic model. The final objective is the preparation of a comprehensive Site Characterization Plan that draws upon the technical and institutional feasibility assessments to prepare the project for future commercialization efforts.

58 GEOSCIENCES↗

DOE OSTI2025

Replace Human Intelligence with Fast and Smart Geometric Reasoning and Graph Neural Network to Accelerate Next Gen ModSim Workflows

We present an agent-guided approach to CAD geometry decomposition that automates hex/hybrid meshing with graph neural networks (GNNs) to accelerate next-generation ModSim workflows. Our end-to-end pipeline (i) reduces 3D boundary-representation (B-Rep) models to a 2D chordal axis skeleton (CAT) and then to a 1D bipartite graph of surface and curve nodes, (ii) assigns per node labels as Cubit® WebCut actions, (iii) trains a multi-action GNN under supervised learning, and (iv) predicts five surface-node and three curve-node actions on out-of-distribution test geometries. Each graph node carries geometric, topological, and meshing attributes drawn from the B-Rep “skin” and CAT “skeleton,” with two-way mappings across 3D↔2D↔1D representations to maintain traceability back to 3D CAD. The supervised learning model exhibits stable convergence of the binary cross-entropy loss and achieves 98.7% accuracy on unseen lattice models. To operationalize decision-making, we rank predicted commands by geometric significance and prototyped the agent-guided workflow through the Cubit® Meshing PowerTool GUI. As a stretch goal, we explore reinforcement learning (RL) to reduce or remove label requirements and to learn policies for action sequences that maximize total reward (e.g., size of hex-meshable regions and resulting hex mesh quality). When all-hex meshing is not feasible, the agent assists in producing hybrid meshes—prioritizing hex in critical regions and transitioning to tetrahedral elements (tets) elsewhere—maintaining fidelity while ensuring robustness. The overarching objective is to replace manual, heuristics-based decomposition with data-driven, reproducible automation, cutting meshing turnaround time by orders of magnitude. We anticipate direct impact on simulation workflows through intelligent, scalable decomposition of complex CAD models into hex-meshable subdomains.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Closing the Loop between In Situ Stress Complexity and EGS Fracture Complexity

42 ENGINEERING↗

DOE OSTI2026

Cold Trap Replacement Project Report

This report documents the replacement of the Mechanisms Engineering Test Loop (METL) cold trap. The work involved preparation of the facility to replace the cold trap, removal of the existing welded cold trap from the sodium purification circuit, installation of a new replacement cold trap, completion of associated welds and examinations, restoration of instrumentation and heaters, and controlled return of the cold trap circuit to service. The replacement represented a significant maintenance evolution because the cold trap is an integral welded component of the sodium system. As a result, the work required coordinated control of sodium chemistry, deliberate formation of freeze plugs, inert gas management, precision cutting and welding, and a staged reheating and refill sequence. The activity was executed using procedural controls intended to protect personnel, preserve system cleanliness, and maintain the integrity of the sodium boundary throughout the work. This report provides a narrative summary of the milestone, including the purpose of the work, the pre-job system condition, the major field activities performed, observations made during execution, and the resulting post-work condition of the METL cold trap circuit.

42 ENGINEERING↗

DOE OSTI2024

Alkaloids are associated with increased microbial diversity and metabolic function in poison frogs

Shifts in host-associated microbiomes can impact both host and microbes. It is of interest to understand how perturbations, like the introduction of exogenous chemicals, impact microbiomes. In poison frogs (family Dendrobatidae), the skin microbiome is exposed to alkaloids that the frogs sequester for defense. These alkaloids are antimicrobial; however, their effect on the frogs’ skin microbiome is unknown. To test this, we characterized microbial communities from field-collected dendrobatid frogs. Then, we conducted a laboratory experiment to monitor the effect of the alkaloid decahydroquinoline (DHQ) on the microbiome of two frog species with contrasting alkaloid loads in nature. In both datasets, we found that alkaloid-exposed microbiomes were more phylogenetically diverse, with an increase in diversity among rare taxa. Further, to better understand the isolate-specific response to alkaloids, we cultured microbial isolates from poison frog skin and found that many isolates exhibited enhanced growth or were not impacted by the addition of DHQ. To further explore the microbial response to alkaloids, we sequenced the metagenomes from high- and low-alkaloid frogs and observed a greater diversity of genes associated with nitrogen and carbon metabolism in high-alkaloid frogs. From these data, we hypothesized that some strains may metabolize the alkaloids. We used stable isotope tracing coupled to nanoSIMS (nanoscale secondary ion mass spectrometry), which supported the idea that some of these isolates are able to metabolize DHQ. Together, these data suggest that poison frog alkaloids open new niches for skin-associated microbes with specific adaptations, such as alkaloid metabolism, that enable survival in this environment.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Experimental and theoretical study of the restrained shrinkage cracking of early age well cement

The shrinkage cracking occurring in oil & gas well cement material is a major factor that reduces the cement sheath integrity and impairs the durability of an underground well. Shrinkage mainly takes place in the early hydration period of the cement, and the resulting restrained shrinkage cracking can form a leaking network for oil & gas or carbon dioxide stored in an underground reservoir. It is thus important to understand the early age behavior of well cement and the leaking pathway formation in the well. This study describes the application of the digital image correlation (DIC) method as a tool to measure the strain development and crack distributions of well cement in the lab during early phase changes. A theoretical model is presented to calculate the stress distribution built up in the cement sheath during early ages of well cement hydration, which helps to interpret the experimental observations and determine the major factors influencing the cracking sequences. This study presents the whole hydration – drying shrinkage – and cracking mechanism of early age well cement under restrained ring conditions experimentally and theoretically. Finally, the results offer useful insights on the key material and geometric parameters which control the fracture of a well cementing structure.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Automating the Analysis of Large Language Models Responses through Zero-Shot Question Answering

Recent advancements in Large Language Models (LLMs) have shown significant potential in various applications, yet their evaluation, particularly in zero-shot question answering scenarios, remains a challenging task. In this study, our objective was to explore precision metrics for Large Language Models (LLM) and design and implement a software pipeline to automatically evaluate LLMs' outputs under zero-shot question answering. Zero-shot question answering involves a model providing answers to questions about topics it hasn't seen during training. It leverages the principles of zero-shot learning by relying on semantic understanding and generalization from related knowledge. The data used was metadata from medical databases on congenital heart disease. We explored eleven LLM metrics and selected three for our evaluation: BLEU, BERTScore, and MoverScore. BLEU calculates a score based on the overlap of n-grams (contiguous sequences of n items, typically words) between the machine-generated translation and the reference translations. Higher BLEU scores indicate better correspondence between the machine-generated and human-generated translations. BERTScore is a metric used to evaluate the quality of machine-generated text by measuring the similarity of token embeddings produced by BERT (Bidirectional Encoder Representations from Transformers) between the generated text and reference text. MoverScore is a metric that quantifies the dissimilarity between the distributions of word embeddings from machine-generated text and reference text, emphasizing semantic similarity over exact token overlap. We also introduced HBKI, a composite metric summarizing these approaches. We tested five models —GPT-3, Llama-2, Gemini 1.5 Pro, Solar 10.7B, and Mixtral-8x7b. Our software pipeline, designed and implemented using Object-Oriented Programming principles, allows users to customize the selection and extraction of features for topics of interest in their own research. Our results show that MoverScore delivered the most precise evaluation of the LLM's outputs, while Mixtral-8x7b achieved the best overall performance in extracting metadata from the databases.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Star-spots and magnetism: testing the activity paradigm in the Pleiades and M67

We measure star-spot filling fractions for 240 stars in the Pleiades and M67 open star clusters using APOGEE high-resolution H-band spectra. For this work, we developed a modified spectroscopic pipeline which solves for star-spot filling fraction and star-spot temperature contrast. We exclude binary stars, finding that the large majority of binaries in these clusters (80 per cent) can be identified from Gaia DR3 and APOGEE criteria – important for field star applications. Our data agree well with independent activity proxies, indicating that this technique recovers real star-spot signals. In the Pleiades, filling fractions saturate at a mean level of 0.248 ± 0.005 for active stars with a decline at slower rotation; we present fitting functions as a function of Rossby number. In M67, we recover low mean filling fractions of 0.030 ± 0.008 and 0.003 ± 0.002 for main sequence GK stars and evolved red giants, respectively, confirming that the technique does not produce spurious spot signals in inactive stars. Star-spots also modify the derived spectroscopic effective temperatures and convective overturn time-scales. Effective temperatures for active stars are offset from inactive ones by −109 ± 11 K, in agreement with the Pecaut & Mamajek empirical scale. Star-spot filling fractions at the level measured in active stars changes their inferred overturn time-scale, which biases the derived threshold for saturation. Finally, we identify a population of stars statistically discrepant from mean activity–Rossby relations and present evidence that these are genuine departures from a Rossby scaling. Our technique is applicable to the full APOGEE catalogue, with broad applications to stellar, galactic, and exoplanetary astrophysics.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Population Genomics of Pseudocercospora griseola Reveals New Groups in the Middle American Clade and the Presence of the Endophytic Bacterium Achromobacter xylosoxidans

Angular leaf spot (ALS), caused by Pseudocercospora griseola is an important disease of common beans. P. griseola, is highly variable and has co-evolved with its host. In this study, 48 isolates of P. griseola from Puerto Rico, Guatemala, Honduras and Tanzania were sequenced (3RADseq), resulting in the de novo assembly of 42,214 contigs. Phylogenomic, population genetic structure and principal component analyses using 1,260 SNPs divided these isolates into two populations, Andean and Middle American, while the Middle American population was further divided into three sub-populations. There were moderate to high levels of differentiation between P. griseola populations, with pairwise Fst values ranging from 0.11 to 0.95. The Andean population was composed of isolates from Tanzania, and was separated from the Middle American population (Fst = 0.95). The Middle American population was separated into 3 subpopulations including isolates from: 1. Guatemala and Honduras, 2. Tanzania, and 3. Puerto Rico. Pathogenicity testing of 27 isolates from Puerto Rico, using 12 common bean differential lines, identified ten races, but these races were not associated with SNPs found in virulence genes. DNA of an endophytic bacterium (Achromobacter xylosoxidans) was found in seven mildly virulent isolates suggesting a possible role of the bacterium in the observed virulence patterns. To understand the evolution and diversity of P. griseola, further study of the virulence genes and the interactions among the endophytic bacterium, the fungus, and the host plant is required. Such information is critical to inform breeding strategies for the development of resistant germplasm and cultivars.

Serrato-Diaz, Luz M. [U.S. Department of Agricultu↗

DOE OSTI2020

A CRISPRi-dCas9 System for Archaea and Its Use To Examine Gene Function during Nitrogen Fixation by Methanosarcina acetivorans

CRISPR-based systems are emerging as the premier method to manipulate many cellular processes. In this study, a simple and efficient CRISPR interference (CRISPRi) system for targeted gene repression in archaea was developed. The Methanosarcina acetivorans CRISPR-Cas9 system was repurposed by replacing Cas9 with the catalytically dead Cas9 (dCas9) to generate a CRISPRi-dCas9 system for targeted gene repression. To test the utility of the system, genes involved in nitrogen (N2) fixation were targeted for dCas9-mediated repression. First, the nif operon (nifHI 1 I 2 DKEN) that encodes molybdenum nitrogenase was targeted by separate guide RNAs (gRNAs), one targeting the promoter and the other targeting nifD. Remarkably, growth of M. acetivorans with N 2 was abolished by dCas9-mediated repression of the nif operon with each gRNA. The abundance of nif transcripts was >90% reduced in both strains expressing the gRNAs, and NifD was not detected in cell lysate. Next, we targeted NifB, which is required for nitrogenase cofactor biogenesis. Expression of a gRNA targeting the coding sequence of NifB decreased nifB transcript abundance >85% and impaired but did not abolish growth of M. acetivorans with N2. Finally, to ascertain the ability to study gene regulation using CRISPRi-dCas9, nrpR1, encoding a subunit of the repressor of the nif operon, was targeted. The nrpR1 repression strain grew normally with N2 but had increased nif operon transcript abundance, consistent with NrpR1 acting as a repressor. Furthermore, these results highlight the utility of the system, whereby a single gRNA when expressed with dCas9 can block transcription of targeted genes and operons in M. acetivorans.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Machine learning predicts new anti-CRISPR proteins

The increasing use of CRISPR–Cas9 in medicine, agriculture, and synthetic biology has accelerated the drive to discover new CRISPR–Cas inhibitors as potential mechanisms of control for gene editing applications. Many anti-CRISPRs have been found that inhibit the CRISPR–Cas adaptive immune system. However, comparing all currently known anti-CRISPRs does not reveal a shared set of properties for facile bioinformatic identification of new anti-CRISPR families. Here, we describe AcRanker, a machine learning based method to aid direct identification of new potential anti-CRISPRs using only protein sequence information. Using a training set of known anti-CRISPRs, we built a model based on XGBoost ranking. We then applied AcRanker to predict candidate anti-CRISPRs from predicted prophage regions within self-targeting bacterial genomes and discovered two previously unknown anti-CRISPRs: AcrllA20 (ML1) and AcrIIA21 (ML8). We show that AcrIIA20 strongly inhibits Streptococcus iniae Cas9 (SinCas9) and weakly inhibits Streptococcus pyogenes Cas9 (SpyCas9). We also show that AcrIIA21 inhibits SpyCas9, Streptococcus aureus Cas9 (SauCas9) and SinCas9 with low potency. The addition of AcRanker to the anti-CRISPR discovery toolkit allows researchers to directly rank potential anti-CRISPR candidate genes for increased speed in testing and validation of new anti-CRISPRs. A web server implementation for AcRanker is available online at http://acranker.pythonanywhere.com/.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Implicit-Explicit Multirate Infinitesimal GARK Methods

This work focuses on the development of a new class of high-order accurate methods for multirate time integration of systems of ordinary differential equations. Unlike other recent work in this area, the proposed methods support mixed implicit-explicit (IMEX) treatment of the slow time scale. In addition to allowing this slow time scale flexibility, the proposed methods utilize a so-called infinitesimal formulation for the fast time scale through definition of a sequence of modified “fast" initial-value problems that may be solved using any viable algorithm. We name the proposed class as implicit-explicit multirate infinitesimal generalized-structure additive Runge--Kutta (IMEX-MRI-GARK) methods. In addition to defining these methods, we prove that they may be viewed as specific instances of GARK methods and derive a set of order conditions on the IMEX-MRI-GARK coefficients to guarantee both third and fourth order accuracy for the overall multirate method. Additionally, we provide three specific IMEX-MRI-GARK methods, two of order three and one of order four. We conclude with numerical simulations on two multirate test problems, demonstrating the methods' predicted convergence rates and comparing their efficiency against both legacy IMEX multirate schemes and recent third and fourth order implicit MRI-GARK methods.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Big Data Synchrophasor Monitoring and Analytics for Resiliency Tracking (BDSMART)

This report contains key findings from a project titled Big Data Synchrophasor Monitoring and Analytics for Resiliency Tracking (BDSMART), which was carried out through a collaborative effort of a team of researchers from Texas A&M Engineering Experiment Station, Temple University, and Quanta Technology, LLC. The in-kind support came from OSIsoft (acquired by AVEVA), which provided their PI Historian software to demonstrate the use case of streaming PMU data. The first section of the report describes the project goals and objectives related to the development of Machine Learning (ML) models capable of detecting and classifying events by processing phasor measurements captured in the field by Phasor Measurement Units (PMUs). The data for this study was contributed by the utilities/ISOs from the Western and Eastern interconnects and ERCOT, further referred to as Interconnect B (IC B), Interconnect A (IC A), and Interconnect C (IC C), respectively. The approach that the BDSMART Research Team proposed and the key research tasks defined by the team are outlined in this section. The next section describes the technical approach. We first discuss the data constraints related to the PMU measurements and data interpretation constraints imposed by the data contributors. They provided neither the topological information of the grid nor PMU placement locations and captured recorded data at very few locations in the system with the reporting rate of either 30 or 60 fps. The recordings are mostly positive sequence voltage, frequency, and ROCOF, and in some limited cases, three-phase voltages and currents. We then reflect on the bad data issues that stem from poor recording practices and vague definitions of the PMU status bits to supposedly be used for bad data identification. Finally, the data discovery points to imprecise time stamps with incomplete event start/end time, as well as inconsistent and incomplete event labeling, which combined make the implementation of the data models using supervising learning quite challenging. Following the data discovery study, we hypothesize that because the IC B data has the most complete labels, we should focus our model development on that data and then test it on data from other interconnects. We also define the common metrics used to evaluate the results from the ML algorithm tests. We concluded this section by summarizing the common ML models we used and explaining how we implemented and tested them. The issues from this section are expanded in the Training Dataset Report from this project. The final section of this report deals with the accomplishments and conclusions. As the accomplishments, we formulate the problem we are solving and what is achieved by solving the problem. We then reflect on each of the analytics tools we developed and point out the performance of each tool when applied to solving the mentioned problems. We reference this work for further details to the papers we published on each tool. In the conclusions, we give recommendations on how to improve future PMU recording practices to facilitate the ML algorithm implementation and guidance for the future standardization work aimed at clarifying the ambiguities associated with the PMU status bits. We finally list future tasks that can bring about further improvements in the proposed algorithms. The issues from this section are expanded in the Training, and Test Dataset Report filed at the project completion date.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Assessment of the Phase-to-Ground Fault Apparent Admittance Method with Phase/Ground Boundaries to Detect Types of Electrical Faults for Protective Relays Using Signature Library and Simulated Events

Protective relays in electric power grids recognize the types of electrical faults in a few seconds. The most common detection method to detect the types of electrical faults is based on measuring the angle between the zero and negative sequence currents. However, it is not completely accurate because the phase-to-phase-ground and phase-to-ground electrical faults could have the same detection conditions. Therefore, engineers need to plot the events after an electrical fault to observe the nature of the incidents in detail. In this study, the phase-to-ground fault apparent (PGFA) admittance method with phase/ground boundaries identified the types of electrical faults located in distribution power lines and feeders. This method was based on measuring the PGFA admittance magnitudes for the faulted and nonfaulted phases, resulting in greater than zero and near zero, respectively. The PGFA admittance algorithm was built with MATLAB/Simulink software and tested with signature library and grid simulation events. The PGFA method with phase/ground boundaries was evaluated with the confusion matrix. The measured and predicted values matched in more than 90% of the tests, and the PGFA admittance method with phase/ground boundaries presented an accuracy of 94.3% and a precision of 100%.

42 ENGINEERING↗

DOE OSTI2023

Assessment of the Phase-to-Ground Fault Apparent Admittance Method with Phase/Ground Boundaries to Detect Types of Electrical Faults for Protective Relays Using Signature Library and Simulated Events

Protective relays in electric power grids recognize the types of electrical faults in a few seconds. The most common detection method to detect the types of electrical faults is based on measuring the angle between the zero and negative sequence currents. However, it is not completely accurate because the phase to phase ground and phase to ground electrical faults could have the same detection conditions. Therefore, engineers need to plot the events after an electrical fault to observe the nature of the incidents in detail. In this study, the phase to ground fault apparent (PGFA) admittance method with phase/ground boundaries identified the types of electrical faults located in distribution power lines and feeders. This method was based on measuring the PGFA admittance magnitudes for the faulted and non-faulted phases, resulting in greater than zero and near zero, respectively. The PGFA admittance algorithm was built with MATLAB/ Simulink software and tested with signature library and grid simulation events. The PGFA method with phase/ground boundaries was evaluated with the confusion matrix. The measured and predicted values matched in more than 90% of the tests, and the PGFA admittance method with phase/ground boundaries presented an accuracy of 94.3% and a precision of 100%.

Piesciorovsky, Emilio↗

DOE OSTI2020

Neurosensory and Sinus Evolution as Tyrannosauroid Dinosaurs Developed Giant Size: Insight from the Endocranial Anatomy of Bistahieversor sealeyi

Tyrannosaurus rex and other tyrannosaurid dinosaurs were apex predators during the latest Cretaceous, which combined giant size and advanced neurosensory systems. Computed tomography (CT) data have shown that tyrannosaurids had a trademark system of a large brain, large olfactory bulbs, elongate cochlear ducts, and expansive endocranial sinuses surrounding the brain and sense organs. Older, smaller tyrannosauroid relatives of tyrannosaurids developed some, but not all, of these features, raising the hypothesis that tyrannosaurid-style brains evolved before the enlarged tyrannosaurid-style sinuses, which might have developed only with large body size. This has been difficult to test, however, because little is known about the brains and sinuses of the first large-bodied tyrannosauroids, which evolved prior to Tyrannosauridae. Here we present the first CT data for one of these species, Bistahieversor sealeyi from New Mexico. Bistahieversor had a nearly identical brain and sinus system as tyrannosaurids like Tyrannosaurus, including a large brain, large olfactory bulbs, reduced cerebral hemispheres, and optic lobes, a small tab-like flocculus, long and straight cochlear ducts, and voluminous sinuses that include a supraocciptal recess, subcondyar sinus, and an anterior tympanic recess that exits the braincase via a prootic fossa. When characters are plotted onto tyrannosauroid phylogeny, there is a two-stage sequence in which features of the tyrannosaurid-style brain evolved first (in smaller, nontyrannosaurid species like Timurlengia), followed by features of the tyrannosaurid-style sinuses (in the first large-bodied nontyrannosaurid tyrannosauroids like Bistahieversor). This suggests that the signature tyrannosaurid sinus system evolved in concert with large size, whereas the brain did not.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Characterization of a Novel CD4 Mimetic Compound YIR-821 against HIV-1 Clinical Isolates

Small CD4-mimetic compound (CD4mc), which inhibits the interaction between gp120 with CD4, acts as an entry inhibitor and induces structural changes in the HIV-1 envelope glycoprotein trimer (Env) through its insertion within the Phe43 cavity of gp120. Here, we recently developed YIR-821, a novel CD4mc, that has potent antiviral activity and lower toxicity than the prototype NBD-556. To assess the possibility of clinical application of YIR-821, we tested its antiviral activity using a panel of HIV-1 pseudoviruses from different subtypes. YIR-821 displayed entry inhibitor activity against 53.5% (21/40) of the pseudoviruses tested and enhanced neutralization mediated by coreceptor binding site (CoRBS) antibodies in 50% (16/32) of these. Furthermore, when we assessed the antiviral effects using a panel of pseudoviruses and autologous plasma IgG, enhancement of antibody-mediated neutralization activity was observed for 48% (15/31) of subtype B strains and 51% (28/55) of non-B strains. The direct antiviral activity of YIR-821 as an entry inhibitor was observed in 53% of both subtype B (27/51) and non-B subtype (40/75) pseudoviruses. Enhancement of antibody-dependent cellular cytotoxicity was also observed with YIR-821 for all six selected clinical isolates, as well as for the transmitted/founder (T/F) CH58 virus-infected cells. The sequence diversity in the CD4 binding site as well as other regions, such as the gp120 inner domain layers or gp41, may be involved in the multiple mechanisms related to the sensitive/resistant phenotype of the virus to YIR-821. Our findings may facilitate the clinical application of YIR-821.

60 APPLIED LIFE SCIENCES↗