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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Structure and in vivo psoralen DNA crosslink repair activity of mycobacterial Nei2

Mycobacterium smegmatis Nei2 is a monomeric enzyme with AP β-lyase activity on single-stranded DNA. Expression of Nei2, and its operonic neighbor Lhr (a tetrameric 3'-to-5' helicase), is induced in mycobacteria exposed to DNA damaging agents. Here, we find that nei2 deletion sensitizes M. smegmatis to killing by DNA inter-strand crosslinker trimethylpsoralen but not to crosslinkers mitomycin C and cisplatin. By contrast, deletion of lhr sensitizes to killing by all three crosslinking agents. We report a 1.45 Å crystal structure of recombinant Nei2, which is composed of N and C terminal lobes flanking a central groove suitable for DNA binding. The C lobe includes a tetracysteine zinc complex. Mutational analysis identifies the N-terminal proline residue (Pro2 of the ORF) and Lys51, but not Glu3, as essential for AP lyase activity. We find that Nei2 has 5-hydroxyuracil glycosylase activity on single-stranded DNA that is effaced by alanine mutations of Glu3 and Lys51 but not Pro2. Testing complementation of psoralen sensitivity by expression of wild-type and mutant nei2 alleles in Δnei2 cells established that AP lyase activity is neither sufficient nor essential for crosslink repair. By contrast, complementation of psoralen sensitivity of Δlhr cells by mutant lhr alleles depended on Lhr’s ATPase/helicase activities and its tetrameric quaternary structure. The lhr–nei2 operon comprises a unique bacterial system to rectify inter-strand crosslinks.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

SARS-CoV-2 Diverges from Other Betacoronaviruses in Only Partially Activating the IRE1α/XBP1 Endoplasmic Reticulum Stress Pathway in Human Lung-Derived Cells

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has killed over 6 million individuals worldwide and continues to spread in countries where vaccines are not yet widely available or its citizens are hesitant to become vaccinated. Therefore, it is critical to unravel the molecular mechanisms that allow SARS-CoV-2 and other coronaviruses to infect and overtake the host machinery of human cells. Coronavirus replication triggers endoplasmic reticulum (ER) stress and activation of the unfolded protein response (UPR), a key host cell pathway widely believed to be essential for viral replication. We examined the master UPR sensor IRE1α kinase/RNase and its downstream transcription factor effector XBP1s, which is processed through an IRE1α-mediated mRNA splicing event, in human lung-derived cells infected with betacoronaviruses. We found that human respiratory coronavirus OC43 (HCoV-OC43), Middle East respiratory syndrome coronavirus (MERS-CoV), and murine coronavirus (MHV) all induce ER stress and strongly trigger the kinase and RNase activities of IRE1α as well as XBP1 splicing. In contrast, SARS-CoV-2 only partially activates IRE1α through autophosphorylation, but its RNase activity fails to splice XBP1. Moreover, while IRE1α was dispensable for replication in human cells for all coronaviruses tested, it was required for maximal expression of genes associated with several key cellular functions, including the interferon signaling pathway, during SARS-CoV-2 infection. Our data suggest that SARS-CoV-2 actively inhibits the RNase of autophosphorylated IRE1α, perhaps as a strategy to eliminate detection by the host immune system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Review—Development of Highly Active and Durable Hybrid Compressive Platinum Lattice Catalysts for Polymer Electrolyte Membrane Fuel Cells: Mathematical Modeling and Experimental Work

This review provides a comprehensive overview on the development of highly active and durable platinum catalysts with ultra-low Pt loadings for polymer electrolyte membrane fuel cells (PEMFCs) through a combined mathematical modeling and experimental work. First, simulation techniques were applied to evaluate the validity of the Tafel approximation for the calculation of the mass activity (MA) and specific activity (SA). A one-dimensional agglomeration model was developed and solved to understand the effects of exchange current density, porosity, agglomerate size, Nafion ® film thickness, and Pt loading on the MA and SA. High porosity (> 60%) and agglomerations at high Pt loadings cause the loss of the Tafel approximation and consequently the decrease in MA and SA. A new structure parameter was introduced to estimate the real porous structure using the fractal theory. The volumetric catalyst density was corrected by the fractal dimension (measured by Hg porosimetry), which gave a good agreement with the experimental values. The loading-dependent Tafel equation was then derived, which contains both the utilization and the non-linear scaling factor. Second, activated carbon composite support (ACCS) with optimized surface area, porosity, pore size, and pore size distribution was developed. The hydrophilic/hydrophobic ratio, structural properties (amorphous/crystalline ratio), and the number of active sites were optimized through metal-catalyzed pyrolysis. Stability of ACCS and Pt/ACCS were evaluated using an accelerated stress test (AST). The results indicated that Pt/ACCS showed no significant loss of MA and power density after 5,000 cycles at 1.0–1.5 V, while the commercial Pt/C catalysts showed drastic losses of MA and power density. Finally, monolayers of compressed Pt (core–shell-type Pt 3 Co 1 ) catalysts were structured by diffusing Co atoms (previously embedded in ACCS) into Pt. Compressive Pt lattice (Pt * ) catalysts were synthesized through an annealing procedure developed at the University of South Carolina (USC). The Pt * /ACCS catalyst showed high initial power density (rated) of 0.174 g Pt kW −1 and high stability (24 mV loss) at 0.8 A cm −2 after 30,000 cycles (0.6–1.0 V). The outstanding performance of Pt * /ACCS is due to the synergistic effect of ACCS and compressive Pt * lattice.

25 ENERGY STORAGE↗
DOE OSTI2020

DFT-Based Calculation of Dissolution Activation Energy and Kinetics of Ni–Cr Alloys

A density functional theory investigation of the process of dissolution of Ni and Cr adatoms from model Ni–Cr(111) alloy surfaces is presented, both in vacuum and with explicit water molecules. The goal is to understand how the electronic structures solved using DFT can provide insights as to changes in valence, energy and coordination of the adatoms in the process of dissolving from the alloy surface. It is found that nearby Cr solute atoms increase the dissolution activation energy of Ni. Cr adatoms have a similar dissolution activation energy as Ni adatoms, except for one particular surface configuration that has a much smaller dissolution activation energy, which might promote selective dissolution of Cr in Ni–Cr alloys. To interpret the first-principles modeling results for the potential energy trajectory along the dissolution reaction coordinate, we provide a thermodynamic breakdown of the various terms that contribute to the dissolution activation and total reaction energy. The role of addition of Cr is explored on the dissolution kinetics of a Ni–Cr alloys of varying composition by constructing a model for the corrosion current density with DFT-based activation energies. Lastly, dissolution resistance index is proposed as a quantifiable descriptor of the dissolution resistance of corrosion resistant alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Multiple Reaction Pathways for the Oxygen Evolution Reaction May Contribute to IrO 2 (110)’s High Activity

Density functional theory calculations in conjunction with statistical mechanical arguments are performed on the rutile IrO 2 (110) facet in order to characterize multiple reaction pathways on the surface at the highest active limit (the stoichiometric surface with all metal sites available) and at the lowest active limit (the oxygen-terminated surface). Alternative pathways to the oxygen evolution reaction (OER) are found, with multiple pathways determined at each step of the four proton-coupled electron transfer reaction. Of particular interest is the detailed characterization of a co-adsorption pathway utilizing neighboring, adsorbed O, OH species in order to evolve oxygen; activation energies of this pathway are <0.5 eV and therefore easily surmountable at the high operating potentials of OER. We also determined that surface Ir atoms can potentially participate in deprotonating an OOH* intermediate; the activation energy to this is 0.67 eV on the oxygen-terminated surface. These theoretical findings explain in part the high activity present in iridium oxide catalysts and also provide insight into the mechanistic pathways available on metal oxide catalysts, which may require the concerted interaction of nearest neighbor co-adsorbates to produce chemicals of interest.

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

Do Melamine and Melamine-Formaldehyde Surface Modifiers Improve Fuel Cell Activity and Durability?

Precious group metal-based catalysts based on Pt- and Pt-alloys are currently used as catalysts for the kinetically sluggish Oxygen Reduction Reaction (ORR) on the cathode of fuel cells. The activity of Pt or Pt-alloy catalysts towards ORR is severely compromised by the adsorption of spectator-species such as sulfonate anions from perfluorosulfonic acid (PFSA) ionomer or Pt-O(H) ad via water activation. Considering recent evidence pointing to the improvement in ORR activity via the use of melamine organic molecule or melamine-formaldehyde copolymeric additives as surface blocking agents for the prevention of sulfonate or Pt-OH ad adsorption, we evaluated these additives in fuel cells. The catalysts were modified with either of these additives and characterized using ex situ and in situ methods to verify successful adsorption and eventual performance in fuel cells. These surface modifying agents were found to suppress Pt-OH ad formation as well as suppress ORR activity. There was no evidence to point out that these additives improved ORR activity and H 2 /air polarization performance in a fuel cell MEA on supported, polycrystalline Pt catalyst.

08 HYDROGEN↗
DOE OSTI2023

Active Learning Framework

Machine learning (ML) of interatomic potentials show great promise to accelerate scientific simulation, e.g., by emulating expensive computations at a high accuracy but much reduced computational cost. Training datasets are calculated from computationally expensive ab initio quantum mechanics methods, density functional theory (DFT). Trained on this data, an ML model can be very successful in predicting energy and forces for new atomic configurations. A critical factor is the quality and diversity of the training dataset. Thus, a highly automated approach to dataset construction based on active learning framework is designed suitable for material physics. The active learning scheme begins with fully randomized atomic configurations. Then, many Molecular Dynamics (MD) trajectories are simulated using current ML potentials, where each MD trajectory is initialized to a random disordered configuration. The temperature is varied in order to diversify the sampled configuration during these simulations. The variance of predictions for eight neural networks within an ensemble is analyzed to determine whether the model is operating as expected. This helps in determining whether collecting more data would be helpful to the model by checking the ensemble variance is greater than the threshold. In this case, the MD trajectory is terminated and the final atomic configuration is placed on a queue (SQL database) for DFT calculations and added to training dataset. Periodically, ML model is retrained to the updated training model. This Active Learning loop is iterated until the cost of MD simulations becomes prohibitively expensive. The MD simulations will hopefully be sufficiently robust to support nucleation after many active learning iterations. In this sense, active learning scheme must automatically discover the important low energy and nonequilibrium physics.

Nebgen, Benjamin↗
DOE OSTI2023

Logical Activation Functions v.1.1

SAND2024-01501O Logical Activation Functions software is a PyTorch implementation from the paper, "Logical Activation Functions for Training Arbitrary Probabilistic Boolean Logic." The activation functions approximate logit-space marginalization of probabilistic truth tables from probabilistic interpretations of inputs. They also provide a general methodology to approximate logical relationships between abstract antecedents and consequents for machine learning architectures. They do not target any specific application or use-case. By training probabilistic truth tables, these activation functions can capture more expressive relationships in a neural network than typical elementwise activation functions. This code is only designed for a single compute node with a GPU and is limited to machine learning architectures than can fit within the memory of a single GPU. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Duersch, Jed↗
DOE OSTI2025

Global Precipitation Experiment—A New World Climate Research Programme Lighthouse Activity

The future state of the global water cycle and the prediction of freshwater availability for humans around the world remain among the challenges of climate research and are relevant to several United Nations Sustainable Development Goals. The Global Precipitation Experiment (GPEX) takes on the challenge of improving the prediction of precipitation quantity, phase, timing, and intensity, characteristics that are products of a complex integrated system. It will achieve this by leveraging existing World Climate Research Programme (WCRP) activities and community capabilities in satellite, surface-based, and airborne observations, modeling, and experimental research and by conducting new and focused activities. It was launched in October 2023 as a WCRP Lighthouse Activity. Here, we present an overview of the GPEX Science Plan that articulates the primary science questions related to precipitation measurements, process understanding, model performance and improvements, and plans for capacity development. The central phase of GPEX is the WCRP Years of Precipitation for 2–3 years with coordinated global field campaigns focusing on different storm types (atmospheric rivers, mesoscale convective systems, monsoons, and tropical cyclones, among others) over different regions and seasons. Activities are planned over the three phases (before, during, and after the Years of Precipitation) spanning a decade. These include gridded data evaluation and development, advanced modeling, enhanced understanding of processes critical to precipitation, multiscale prediction of precipitation events across scales, and capacity development. These activities will be further developed as part of the GPEX Implementation Plan.

Climate change↗
DOE OSTI2023

Effects from Time Dependence of Ice Nucleus Activity for Contrasting Cloud Types

Abstract The role of time-dependent freezing of ice nucleating particles (INPs) is evaluated with the “Aerosol–Cloud” (AC) model in 1) deep convection observed over Oklahoma during the Midlatitude Continental Convective Cloud Experiment (MC3E), 2) orographic clouds observed over North California during the Atmospheric Radiation Measurement (ARM) Cloud Aerosol Precipitation Experiment (ACAPEX), and 3) supercooled, stratiform clouds over the United Kingdom, observed during the Aerosol Properties, Processes And Influences on the Earth’s climate (APPRAISE) campaign. AC uses the dynamical core of the WRF Model and has hybrid bin–bulk microphysics and a 3D mesoscale domain. AC is validated against coincident aircraft, ground-based, and satellite observations for all three cases. Filtered concentrations of ice (>0.1–0.2 mm) agree with those observed at all sampled levels. AC predicts the INP activity of various types of aerosol particles with an empirical parameterization (EP), which follows a singular approach (no time dependence). Here, the EP is modified to represent time-dependent INP activity by a purely empirical approach, using our published laboratory observations of time-dependent INP activity. In all simulated clouds, the inclusion of time dependence increases the predicted INP activity of mineral dust particles by 0.5–1 order of magnitude. However, there is little impact on the cloud glaciation because the total ice is mostly (80%–90%) from secondary ice production (SIP) at levels warmer than about −36°C. The Hallett–Mossop process and fragmentation in ice–ice collisions together initiate about 70% of the total ice, whereas fragmentation during both raindrop freezing and sublimation contributes <10%. Overall, total ice concentrations and SIP are unaffected by time-dependent INP activity. In the simulated APPRAISE case, the main causes of persistence of long-lived clouds and precipitation are predicted to be SIP in weak embedded convection and reactivation following recirculation of dust particles in supercooled layer cloud.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Method for quantification of porcine type I interferon activity using luminescence, by direct and indirect means

Abstract Background Type I interferons are widely used in research applications and as biotherapeutics. Current assays used to measure interferon concentrations, such as plaque reduction assays and ELISA, are expensive, technically challenging, and may take days to provide results. We sought to develop a robust and rapid assay to determine interferon concentrations produced from transiently transfected cell cultures. Method Indirect quantification of recombinant interferon was evaluated using a novel bi-cistronic construct encoding the Foot-and-mouth disease virus 2A translational interrupter sequence to yield equimolar expression of Gaussia princeps luciferase and porcine interferon α. Direct quantification was evaluated by expression of a novel fusion protein comprised of Gaussia princeps luciferase and porcine type I interferon. Plasmids encoding constructs are transiently transfected into cell cultures and supernatant harvested for testing of luminescence, ELISA determined concentration, and anti-viral activity against vesicular stomatitis virus. Results Bi-cistronic constructs, utilized for indirect quantification, demonstrate both luciferase activity and anti-viral activity. Fusion proteins, utilized for direct quantification, retained secretion and luminescence however only the interferon α fusion protein had antiviral activity comparable to wildtype porcine interferon α. A strong linear correlation was observed between dilution and luminescence for all compounds over a dynamic range of concentrations. Conclusion The correlation of antiviral and luciferase activities demonstrated the utility of this approach, both direct and indirect, to rapidly determine recombinant interferon concentrations. Concentration can be determined over a more dynamic concentration range than available ELISA based assays using this methodology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Ultra-sensitive isotope probing to quantify activity and substrate assimilation in microbiomes

Abstract Background Stable isotope probing (SIP) approaches are a critical tool in microbiome research to determine associations between species and substrates, as well as the activity of species. The application of these approaches ranges from studying microbial communities important for global biogeochemical cycling to host-microbiota interactions in the intestinal tract. Current SIP approaches, such as DNA-SIP or nanoSIMS allow to analyze incorporation of stable isotopes with high coverage of taxa in a community and at the single cell level, respectively, however they are limited in terms of sensitivity, resolution or throughput. Results Here, we present an ultra-sensitive, high-throughput protein-based stable isotope probing approach (Protein-SIP), which cuts cost for labeled substrates by 50–99% as compared to other SIP and Protein-SIP approaches and thus enables isotope labeling experiments on much larger scales and with higher replication. The approach allows for the determination of isotope incorporation into microbiome members with species level resolution using standard metaproteomics liquid chromatography-tandem mass spectrometry (LC–MS/MS) measurements. At the core of the approach are new algorithms to analyze the data, which have been implemented in an open-source software ( https://sourceforge.net/projects/calis-p/ ). We demonstrate sensitivity, precision and accuracy using bacterial cultures and mock communities with different labeling schemes. Furthermore, we benchmark our approach against two existing Protein-SIP approaches and show that in the low labeling range used our approach is the most sensitive and accurate. Finally, we measure translational activity using 18 O heavy water labeling in a 63-species community derived from human fecal samples grown on media simulating two different diets. Activity could be quantified on average for 27 species per sample, with 9 species showing significantly higher activity on a high protein diet, as compared to a high fiber diet. Surprisingly, among the species with increased activity on high protein were several Bacteroides species known as fiber consumers. Apparently, protein supply is a critical consideration when assessing growth of intestinal microbes on fiber, including fiber-based prebiotics. Conclusions We demonstrate that our Protein-SIP approach allows for the ultra-sensitive (0.01 to 10% label) detection of stable isotopes of elements found in proteins, using standard metaproteomics data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Pattern formation and transport for externally driven active matter on periodic substrates (a)

Abstract We investigate the transport of interacting active run-and-tumble particles moving under an external drift force through a periodic array of obstacles for increasing drive amplitudes. For high activity where the system forms a motility-induced phase-separated state, there are several distinct dynamic phases including a low drive pinned cluster phase, an intermediate uniform fluid, and a higher drive stripe crystal state. The transitions between the phases are correlated with signatures in the transport curves, differential mobility, and power spectra of the velocity fluctuations. In contrast, in the low activity regime the transport curves and power spectra undergo little change as a function of drive. We argue that in the high activity limit, the behavior is similar to that of driven solids on periodic substrates, while in the low activity limit the system behaves like a driven fluid.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Demonstrating the importance of porcine reproductive and respiratory syndrome virus papain-like protease 2 deubiquitinating activity in viral replication by structure-guided mutagenesis

Deubiquitination of cellular substrates by viral proteases is a mechanism used to interfere with host cellular signaling processes, shared between members of the coronavirus- and arterivirus families. In the case of Arteriviruses, deubiquitinating and polyprotein processing activities are accomplished by the virus-encoded papain-like protease 2 (PLP2). Several studies have implicated the deubiquitinating activity of the porcine reproductive and respiratory syndrome virus (PRRSV) PLP2 in the downregulation of cellular interferon production, however to date, the only arterivirus PLP2 structure described is that of equine arteritis virus (EAV), a distantly related virus. Here we describe the first crystal structure of the PRRSV PLP2 domain both in the presence and absence of its ubiquitin substrate, which reveals unique structural differences in this viral domain compared to PLP2 from EAV. To probe the role of PRRSV PLP2 deubiquitinating activity in host immune evasion, we selectively removed this activity from the domain by mutagenesis and found that the viral domain could no longer downregulate cellular interferon production. Interestingly, unlike EAV, and also unlike the situation for MERS-CoV, we found that recombinant PRRSV carrying PLP2 DUB-specific mutations faces significant selective pressure to revert to wild-type virus in MARC-145 cells, suggesting that the PLP2 DUB activity, which in PRRSV is present as three different versions of viral protein nsp2 expressed during infection, is critically important for PRRSV replication.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Comprehensive Physical Activity Assessment During U.S. Army Basic Combat Training

Abstract Alemany, JA, Pierce, JR, Bornstein, DB, Grier, TL, Jones, BH, and Glover, SH. Comprehensive physical activity assessment during U.S. Army Basic Combat Training. J Strength Cond Res 36(12): 3505–3512, 2022—Physical activity (PA) volume, intensity, and qualitative contextual information regarding activity type and loads carried are limited during U.S. Army Basic Combat Training (BCT). The purpose of this study was to characterize daily (05:00–20:00 hours) PA during BCT using a comprehensive approach. During 2 10-week BCT cycles ( n = 40 trainees per cycle), pedometers, accelerometers, and direct observation were used to estimate daily step count, PA volume, and intensity. Physical activity intensity was categorized by metabolic equivalents (METs) such as “sedentary” (1–2 METs), “light” (2–3 METs), “moderate” (3–6 METs), or “vigorous” (≥6 METs). Daily PA data were analyzed longitudinally using linear mixed models, with significance set at p ≤ 0.05. The mean daily step count was 13,459 ± 4,376 steps, and the mean daily accelerometer-assessed PA volume and intensity were as follows: sedentary: 505 ± 98 minutes, light: 190 ± 78 minutes, moderate: 168 ± 51 minutes, and vigorous: 14 ± 14 minutes, with no differences between cycles for all measures ( p > 0.50). Cumulative time on feet (∼50%) and sitting (20–25%) accounted for most daily activity types during both cycles. Trainees, on average, carried between 3 and 9 kg, and ≥9 kg, for 60% and 10% of the monitored day, respectively. Basic Combat Training's physical demands are high, where trainees achieved 1.7 to 2.7 times greater daily ambulation and 6 times the recommended weekly moderate-to-vigorous PA compared with civilian counterparts and performed weight-bearing load carriage for nearly half of the day. Basic Combat Training-associated PA may increase injury risk among trainees unaccustomed to arduous PA and exercise. Implementing national PA policies to improve physical fitness and facilitate acclimatization to BCT's high physical demands could reduce public health burdens and military nonreadiness.

Sport Sciences↗
DOE OSTI2022

Microbial extracellular enzyme activity with simulated climate change

It is critical to understand the consequences of environmental change for the microbial regulation of carbon and nutrient cycling. Specifically, understanding microbial community traits, such as extracellular enzyme activity, can help inform nutrient cycling models and address knowledge gaps. We analyzed data on extracellular enzyme activities and litter decomposition from an 18-month experiment in which microbial communities were reciprocally transplanted along a climate gradient in Southern California. Communities were from desert, scrubland, grassland, pine–oak, and subalpine ecosystems. We aimed to test how enzyme activities responded to climate change following transplantation and how those responses related to decomposition rates. We hypothesized that microbial communities would specialize on their native climate conditions, resulting in higher enzyme activities when transplanted back into their native climate. We investigated the relationship between extracellular enzyme Vmax values, substrate mass loss, and microbial biomass as well as variation in these variables across the climate gradient. We found little evidence for climate specialization, and there was rarely a reduction in enzyme functioning after microbial communities were transplanted into new climate conditions. Moreover, observed differences in decomposition were not related to changes in extracellular enzyme potential, although there were significant differences in enzyme activities and decomposition rates across sites. These results suggest that direct, physiological impacts of climate are likely to be important for enzyme-mediated decomposition, but climate specialization will not constrain the microbial response to climate change in our system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Machine-Learning-Based High-Resolution Earthquake Catalog Reveals How Complex Fault Structures Were Activated during the 2016–2017 Central Italy Sequence

The 2016–2017 central Italy seismic sequence occurred on an 80 km long normal-fault system. The sequence initiated with the Mw 6.0 Amatrice event on 24 August 2016, followed by the Mw 5.9 Visso event on 26 October and the Mw 6.5 Norcia event on 30 October. We analyze continuous data from a dense network of 139 seismic stations to build a high-precision catalog of ~900,000 earthquakes spanning a 1 yr period, based on arrival times derived using a deep-neural-network-based picker. Our catalog contains an order of magnitude more events than the catalog routinely produced by the local earthquake monitoring agency. Aftershock activity reveals the geometry of complex fault structures activated during the earthquake sequence and provides additional insights into the potential factors controlling the development of the largest events. Activated fault structures in the northern and southern regions appear complementary to faults activated during the 1997 Colfiorito and 2009 L’Aquila sequences, suggesting that earthquake triggering primarily occurs on critically stressed faults. Delineated major fault zones are relatively thick compared to estimated earthquake location uncertainties, and a large number of kilometer-long faults and diffuse seismicity were activated during the sequence. These properties might be related to fault age, roughness, and the complexity of inherited structures. The rich details resolvable in this catalog will facilitate continued investigation of this energetic and well-recorded earthquake sequence.

58 GEOSCIENCES↗
DOE OSTI2020

ESGF project plan for ramping down development activities and transition the project and data to a new team

This document summarizes the current software development activities carried by the ESGF team with planned delivery dates before the transition of the project to a new team. The work we started on the publishing, search and retrieval, and the backend for indexing and data management that can be deployed using Kubernetes are planned to be delivered within the next three months; however, this assumes that the current team members will continue to work on the project. The activities are listed in Table 1 by priority and in case we lose team members, development of lower priority tasks can be paused and passed to the new team with its current status. Team members can be re-assigned based on their availability and transition work needed. Table 2 below describe activities necessary to help project transition to the new team. Deadlines for these activities are before October 1 st of 2022 or the completion of a successful transition. Support during the transition period assumes that we will have 3 key ESGF members and the ESGF PI supported at the 50% level or less for the duration of the transition. The level of support is an estimate, and it depends on several factors that cannot be decided at this time. The total cost of the proposed work and support activities for fiscal year 2021 is $1,270K with $230K carry over to fiscal year 2022. The cost for the support work listed in Table 2 is the sum of the two rows “HW support” and “project support, maintenance, and transition efforts”, colored blue, in Table1 which adds up to $720K. This cost is included in the $1,270K cost in table 1.

97 MATHEMATICS AND COMPUTING↗