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DOE OSTI2025

Toward scalable bound-to-resonance extrapolations for few- and many-body systems

In open quantum many-body systems, the theoretical description of resonant states of many particles strongly coupled to the continuum can be challenging. Such states are commonplace in, for example, exotic nuclei and hadrons, and can reveal important information about the underlying forces at play in these systems. In this work, we demonstrate that the complex-augmented eigenvector continuation (CA-EC) method, originally formulated for the two-body problem with uniform complex scaling, can reliably perform bound-to-resonance extrapolations for genuine three-body resonances having no bound subsystems. Here, we first establish that three-body bound-to-resonance extrapolations are possible by benchmarking different few-body approaches, and we provide arguments to explain how the extrapolation works in the many-body case. We furthermore pave the way towards scalable resonance extrapolations in many-body systems by showing that the CA-EC method also works in the Berggren basis, studying a realistic application using the Gamow shell model.

Ab initio calculations↗

DOE OSTI2020

Nonlinear self-focusing in strongly magnetized pair plasma

An intense radiation field can modify plasma properties and the corresponding refractive index and lead to nonlinear propagation effects such as self-focusing. In this work, we estimate the corresponding effects in pair plasmas for circularly polarized waves, in both unmagnetized and strongly magnetically dominated cases. First, in the unmagnetized pair plasma the ponderomotive force does not lead to charge separation but to density depletion. Second, for astrophysically relevant plasmas of pulsar magnetospheres [and possible loci of fast radio bursts (FRBs)], where the cyclotron frequency $ω_B$ dominates over the plasma frequency $ω_p$ and the frequency of the electromagnetic wave $ω_B \gg ω_p, ω$, we show that (i) there is virtually no nonlinearity due to changing effective mass in the field of the wave; (ii) the ponderomotive force is $F^{(B)}_p = –m_ec^2/4B^2_0∇E^2$, which is reduced by a factor $(ω/ω_B)^2$ if compared to the unmagnetized case ($B_0$ is the external magnetic field and $\textit{E}$ is the electric field of the wave); and (iii) for a radiation beam propagating along a constant magnetic field in the pair plasma with density $n_±$, the ponderomotive force leads to the appearance of circular currents that lead to a decrease of the field within the beam by a factor $ΔB/B_0 = 2πn_±m_ec^2E^2 /B^4_0$. Applications to the physics of FRBs are discussed; we conclude that for the parameters of FRBs, the dominant magnetic field completely suppresses nonlinear self-focusing or filamentation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2014

Structural evidence for the partially oxidized dipyrromethene and dipyrromethanone forms of the cofactor of porphobilinogen deaminase: structures of the Bacillus megaterium enzyme at near-atomic resolution

The enzyme porphobilinogen deaminase (PBGD; hydroxymethylbilane synthase; EC 2.5.1.61) catalyses a key early step in the biosynthesis of tetrapyrroles in which four molecules of the monopyrrole porphobilinogen are condensed to form a linear tetrapyrrole. Two near-atomic resolution structures of PBGD from B. megaterium are reported that demonstrate the time-dependent accumulation of partially oxidized forms of the cofactor, including one that possesses a tetrahedral C atom in the terminal pyrrole ring. The enzyme porphobilinogen deaminase (PBGD; hydroxymethylbilane synthase; EC 2.5.1.61) catalyses an early step of the tetrapyrrole-biosynthesis pathway in which four molecules of the monopyrrole porphobilinogen are condensed to form a linear tetrapyrrole. The enzyme possesses a dipyrromethane cofactor, which is covalently linked by a thioether bridge to an invariant cysteine residue (Cys241 in the Bacillus megaterium enzyme). The cofactor is extended during the reaction by the sequential addition of the four substrate molecules, which are released as a linear tetrapyrrole product. Expression in Escherichia coli of a His-tagged form of B. megaterium PBGD has permitted the X-ray analysis of the enzyme from this species at high resolution, showing that the cofactor becomes progressively oxidized to the dipyrromethene and dipyrromethanone forms. In previously solved PBGD structures, the oxidized cofactor is in the dipyromethenone form, in which both pyrrole rings are approximately coplanar. In contrast, the oxidized cofactor in the B. megaterium enzyme appears to be in the dipyrromethanone form, in which the C atom at the bridging α-position of the outer pyrrole ring is very clearly in a tetrahedral configuration. It is suggested that the pink colour of the freshly purified protein is owing to the presence of the dipyrromethene form of the cofactor which, in the structure reported here, adopts the same conformation as the fully reduced dipyrromethane form.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2016

Crystallization and X-ray diffraction analysis of an l-arabinonate dehydratase from Rhizobium leguminosarum bv. trifolii and a d-xylonate dehydratase from Caulobacter crescentus

l-Arabinonate dehydratase and d-xylonate dehydratase from the IlvD/EDD family were crystallized by the vapour-diffusion method. Diffraction data sets were collected to resolutions of 2.40 and 2.66 Å from crystals of l-arabinonate dehydratase and d-xylonate dehydratase, respectively. l-Arabinonate dehydratase (EC 4.2.1.25) and d-xylonate dehydratase (EC 4.2.1.82) are two enzymes that are involved in a nonphosphorylative oxidation pathway of pentose sugars. l-Arabinonate dehydratase converts l-arabinonate into 2-dehydro-3-deoxy-l-arabinonate, and d-xylonate dehydratase catalyzes the dehydration of d-xylonate to 2-dehydro-3-deoxy-d-xylonate. l-Arabinonate and d-xylonate dehydratases belong to the IlvD/EDD family, together with 6-phosphogluconate dehydratases and dihydroxyacid dehydratases. No crystal structure of any l-arabinonate or d-xylonate dehydratase is available in the PDB. In this study, recombinant l-arabinonate dehydratase from Rhizobium leguminosarum bv. trifolii (RlArDHT) and d-xylonate dehydratase from Caulobacter crescentus (CcXyDHT) were heterologously expressed in Escherichia coli and purified by the use of affinity chromatography followed by gel-filtration chromatography. The purified proteins were crystallized using the hanging-drop vapour-diffusion method at 293 K. Crystals of RlArDHT that diffracted to 2.40 Å resolution were obtained using sodium formate as a precipitating agent. They belonged to space group P2{sub 1}, with unit-cell parameters a = 106.07, b = 208.61, c = 147.09 Å, β = 90.43°. Eight RlArDHT molecules (two tetramers) in the asymmetric unit give a V{sub M} value of 3.2 Å{sup 3} Da{sup −1} and a solvent content of 62%. Crystals of CcXyDHT that diffracted to 2.66 Å resolution were obtained using sodium formate and polyethylene glycol 3350. They belonged to space group C2, with unit-cell parameters a = 270.42, b = 236.13, c = 65.17 Å, β = 97.38°. Four CcXyDHT molecules (a tetramer) in the asymmetric unit give a V{sub M} value of 4.0 Å{sup 3} Da{sup −1} and a solvent content of 69%.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2015

Characterization of melted fuel by neutron resonance spectroscopy

Neutrons can be used as a tool to study properties of materials and objects. An evolving activity in this field focusses on neutron induced reaction cross sections. The probability that a neutron interacts with nuclei strongly depends on the energy of the neutron. The cross sections reveal the presence of resonance structures, the energy and width of which are isotope specific. As such, these resonance structures can be used as fingerprints to determine the elemental and isotopic composition of materials and objects. They are the basis of two analytical methods which have been developed at Institute for Reference Materials and Measurements of the European Commission's Joint Research Centre (EC-JRC-IRMM): Neutron Resonance Capture Analysis (NRCA) and Neutron Resonance Transmission Analysis (NRTA). The first technique is based on the detection of gamma rays emitted during a neutron capture reaction in the sample being studied; the latter determines the fraction of neutrons transmitted through a sample positioned in a neutron beam. In the past both techniques have been applied to determine the composition of archaeological objects and to characterize nuclear reference materials. More recently a combination of NRTA and NRCA is being studied as a non-destructive method to determine the heavy metal content of particle-like debris of melted fuel that is formed in severe nuclear accidents such as the one which occurred at the Fukushima Daiichi nuclear power plant in Japan. This study is part of a collaboration between the Japan Atomic Energy Agency (JAEA) and ECJRC- IRMM and is a spin-off from the core activity of IRMM, i.e. the production of nuclear data for nuclear technology applications. This contribution focusses on a newly developed NRTA measurement station that has been set up recently at one of the flight paths of the neutron time-of-flight facility GELINA at the EC-JRC-IRMM. The basic principles of NRTA and first results of measurements at the new set up will be discussed. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2016

Emitter Choice for Epitaxial CdTe Solar Cells

High-quality epitaxial CdTe layers with low defect density and high carrier concentration have been demonstrated by several research groups. Nevertheless, one primary challenge for high-performance epitaxial CdTe solar cells is how to choose a suitable emitter partner for the junction formation. The numerical simulations show that a type I heterojunction with small conduction band offset (0.1 eV = ..delta..Ec = 0.3 eV) is necessary to maintain a good cell efficiency even with large interface recombination. Otherwise, a small 'cliff' can assist interface recombination causing smaller Voc, and a large 'spike' (..delta..Ec = 0.4 eV) can impede the photo current and lead to a reduction of JSC and FF. Among the three possible emitters, CdS, CdMgTe, and MgZnO, CdMgTe (with ~30% Mg) and MgZnO (with ~ 20% Mg) are likely to be a better choice since their type-I junction can tolerate a larger density of interface defects.

14 SOLAR ENERGY↗

DOE OSTI2026

Neural-Network-Enhanced COTSIM: Advancing Predictive Capabilities for Fast DIII-D Simulations

Sustaining fusion reactions in tokamaks requires heating plasma to thermonuclear temperatures while maintaining confinement and stability. Neutral beam injection (NBI) provides heating, current drive, torque, and fueling, while electron cyclotron (EC) waves are widely used for heating and current drive; together, these actuators shape the plasma current, temperature, and density profiles. The control-oriented tokamak simulator (COTSIM), a predictive, control-oriented code, has been enhanced with neural-network surrogates for transport and sources. Turbulent transport is predicted by MMMnet—a neural-network version of the updated multimode model (MMM 9.0.10)—with significantly reduced computation time relative to MMM; neoclassical transport follows the Chang–Hinton model. NUBEAMnet, a surrogate of the Monte Carlo NUBEAM module, predicts beam-driven heating, current, and torque. EC heating and current drive use a control-oriented, empirically scaled source model; plasma resistivity follows the Spitzer formulation; bootstrap current uses the Sauter model. Equilibrium is computed using both prescribed and fixed-boundary solvers (FBSs), and the pedestal structure is modeled with an empirical pedestal model. For a representative DIII-D discharge, COTSIM predicts electron and ion temperature and safety-factor profiles in close agreement with TRANSP predictive and interpretive simulations while extending predictions through the pedestal region to the plasma edge (versus 80% of the minor radius in TRANSP). Furthermore, the equivalent COTSIM simulation runs in under 3 min compared to about 2 h for TRANSP, enabling rapid scenario planning, optimization of tokamak operation, and between-pulse control design.

Control-oriented tokamak simulator (COTSIM)↗

DOE OSTI2022

Quantitative Metrics for Grid Resilience Evaluation and Optimization

Power system resilience has become a critical topic in recent years because of the increasing trend of extreme events and the growing integration of intermittent renewable energy sources. To enhance grid resilience against high-impact, low-frequency events, two questions should be answered: how to quantify the resilience of a given grid and how to incorporate the quantification into power system planning, operation, and restoration. Here this paper develops a new set of quantitative metrics with clear physical interpretation to comprehensively evaluate power system resilience. Using microgrids as an example, an event-based corrective scheduling (ECS) model and an online model predictive control (OMPC) model are developed to integrate the proposed quantitative resilience metrics into power system optimization models for resilience enhancement. The ECS model employs extreme event data to investigate the optimal restoration solution and to help microgrid operators prepare to respond to similar events. The OMPC model provides online decision-making support for operators to handle ongoing outages in the most resilient fashion. The effectiveness and superiority of the proposed quantitative resilience metrics and the resilience enhancement models are demonstrated through simulations and comparative studies on an IEEE test feeder and a real distribution feeder in Southern California.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2016

Rubis CO selection using the vigorously aerobic and metabolically versatile bacterium Ralstonia eutropha

Recapturing atmospheric CO 2 is key to reducing global warming and increasing biological carbon availability. Ralstonia eutropha is a biotechnologically useful aerobic bacterium that uses the Calvin–Benson–Bassham ( CBB ) cycle and the enzyme ribulose 1,5‐bisphosphate carboxylase/oxygenase (Rubis CO ) for CO 2 utilization, suggesting that it may be a useful host to bioselect Rubis CO molecules with improved CO 2 ‐capture capabilities. A host strain of R. eutropha was constructed for this purpose after deleting endogenous genes encoding two related Rubis CO s. This strain could be complemented for CO 2 ‐dependent growth by introducing native or heterologous Rubis CO genes. Mutagenesis and suppressor selection identified amino acid substitutions in a hydrophobic region that specifically influences Rubis CO 's interaction with its substrates, particularly O 2 , which competes with CO 2 at the active site. Unlike most Rubis CO s, the R. eutropha enzyme has evolved to retain optimal CO 2 ‐fixation rates in a fast‐growing host, despite the presence of high levels of competing O 2 . Yet its structure‐function properties resemble those of several commonly found Rubis CO s, including the higher plant enzymes, allowing strategies to engineer analogous enzymes. Because R. eutropha can be cultured rapidly under harsh environmental conditions (e.g., with toxic industrial flue gas), in the presence of near saturation levels of oxygen, artificial selection and directed evolution studies in this organism could potentially impact efforts toward improving Rubis CO ‐dependent biological CO 2 utilization in aerobic environments. Enzymes d ‐ribulose 1,5‐bisphosphate carboxylase/oxygenase, EC 4.1.1.39 ; phosphoribulokinase, EC 2.7.1.19

Satagopan, Sriram↗

DOE OSTI2024

Recent increases in annual, seasonal, and extreme methane fluxes driven by changes in climate and vegetation in boreal and temperate wetland ecosystems

Climate warming is expected to increase global methane (CH 4 ) emissions from wetland ecosystems. Although in situ eddy covariance (EC) measurements at ecosystem scales can potentially detect CH 4 flux changes, most EC systems have only a few years of data collected, so temporal trends in CH 4 remain uncertain. Here, we use established drivers to hindcast changes in CH 4 fluxes (FCH 4 ) since the early 1980s. We trained a machine learning (ML) model on CH 4 flux measurements from 22 [methane-producing sites] in wetland, upland, and lake sites of the FLUXNET-CH 4 database with at least two full years of measurements across temperate and boreal biomes. The gradient boosting decision tree ML model then hindcasted daily FCH 4 over 1981-2018 using meteorological reanalysis data. We found that, mainly driven by rising temperature, half of the sites (n = 11) showed significant increases in annual, seasonal, and extreme FCH 4 , with increases in FCH 4 of ca. 10% or higher found in the fall from 1981–1989 to 2010–2018. The annual trends were driven by increases during summer and fall, particularly at high-CH 4 -emitting fen sites dominated by aerenchymatous plants. We also found that the distribution of days of extremely high FCH 4 (defined according to the 95th percentile of the daily FCH 4 values over a reference period) have become more frequent during the last four decades and currently account for 10–40% of the total seasonal fluxes. The share of extreme FCH 4 days in the total seasonal fluxes was greatest in winter for boreal/taiga sites and in spring for temperate sites, which highlights the increasing importance of the non-growing seasons in annual budgets. Our results shed light on the effects of climate warming on wetlands, which appears to be extending the CH 4 emission seasons and boosting extreme emissions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Methane fluxes in tidal marshes of the conterminous United States

Abstract Methane (CH 4 ) is a potent greenhouse gas (GHG) with atmospheric concentrations that have nearly tripled since pre‐industrial times. Wetlands account for a large share of global CH 4 emissions, yet the magnitude and factors controlling CH 4 fluxes in tidal wetlands remain uncertain. We synthesized CH 4 flux data from 100 chamber and 9 eddy covariance (EC) sites across tidal marshes in the conterminous United States to assess controlling factors and improve predictions of CH 4 emissions. This effort included creating an open‐source database of chamber‐based GHG fluxes ( https://doi.org/10.25573/serc.14227085 ). Annual fluxes across chamber and EC sites averaged 26 ± 53 g CH 4 m −2 year −1 , with a median of 3.9 g CH 4 m −2 year −1 , and only 25% of sites exceeding 18 g CH 4 m −2 year −1 . The highest fluxes were observed at fresh‐oligohaline sites with daily maximum temperature normals (MATmax) above 25.6°C. These were followed by frequently inundated low and mid‐fresh‐oligohaline marshes with MATmax ≤25.6°C, and mesohaline sites with MATmax >19°C. Quantile regressions of paired chamber CH 4 flux and porewater biogeochemistry revealed that the 90th percentile of fluxes fell below 5 ± 3 nmol m −2 s −1 at sulfate concentrations >4.7 ± 0.6 mM, porewater salinity >21 ± 2 psu, or surface water salinity >15 ± 3 psu. Across sites, salinity was the dominant predictor of annual CH 4 fluxes, while within sites, temperature, gross primary productivity (GPP), and tidal height controlled variability at diel and seasonal scales. At the diel scale, GPP preceded temperature in importance for predicting CH 4 flux changes, while the opposite was observed at the seasonal scale. Water levels influenced the timing and pathway of diel CH 4 fluxes, with pulsed releases of stored CH 4 at low to rising tide. This study provides data and methods to improve tidal marsh CH 4 emission estimates, support blue carbon assessments, and refine national and global GHG inventories.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Multi‐Decadal Dynamics of Wetland Methane Emissions Revealed by Knowledge‐Guided Machine Learning

Measurement of methane fluxes (FCH 4 ) from natural systems, such as wetlands, has lagged far behind carbon dioxide fluxes. Short and fragmented wetland FCH 4 data limit our ability to assess its long-term dynamics and potential climate feedbacks. Extrapolating short-term FCH 4 records to recent decades remains challenging for both process-based models and data-driven machine learning (ML) approaches. Here, we develop a knowledge-guided ML framework that integrates eddy covariance (EC) FCH 4 observations, field warming experiments, and biogeochemical knowledge to reconstruct the long-term FCH 4 budgets and trends. Focusing on the 11 longest EC monitoring sites in the AmeriFlux network, we found considerable variability in multi-decadal trends of wetland FCH 4 , with increases up to 14% per decade from 2000 to 2024. We also found that the strength of these increasing trends declines from high to low latitudes, highlighting the vulnerability of northern wetlands. This work presents novel and robust reconstructions of long-term wetland FCH 4 , offering critical benchmark datasets for bottom-up ecosystem models and advancing fundamental understanding of wetland biogeochemistry.

AmeriFlux site↗

DOE OSTI2017

Real‐time monitoring of crystal accumulation in the high‐level waste glass melters using an electrical conductivity method

Abstract During the vitrification of high‐level radioactive waste ( HLW ) in HLW melters in the Waste Treatment and Immobilization Plant located in Washington State, spinel crystals may precipitate from glass and accumulate in the melter riser, preventing the discharge of molten glass into canisters. Therefore, an effort is being made to develop an electrical conductivity method to monitor crystal buildup in the melter riser. A vertically configured electrical conductivity ( EC ) probe with an alumina shaft and Pt‐10%Rh‐electrodes was designed and tested in standard conductivity solutions and glass melts both with and without spinel crystals. The EC probe measured conductivity in conductivity solutions within 10% of their certified values and showed a linear relationship with increased spinel layer thicknesses. Testing in silicate glass containing spinel crystals allowed for the determination of spinel conductivity as a function of temperature. The conductivities of spinel crystals of 20‐24 S/m at 800°C were in excellent agreement with the conductivity of trevorite (NiFe 2 O 4 ) crystals at 800°C reported in the literature. The conductivities of spinel crystals and measured changes in the conductivity across the accumulated layer allowed for a successful measurement of spinel crystal accumulation in simulated HLW glass.

Edwards, Matthew↗

DOE OSTI2018

Evolutionary and demographic correlates of Pleistocene coastline changes in the Sicilian wall lizard Podarcis wagleriana

Abstract Aim Emergence of coastal lowlands during Pleistocene ice ages might have provided conditions for glacial expansions (demographic and spatial), rather than contraction, of coastal populations of temperate species. Here, we tested these predictions in the insular endemic Sicilian wall lizard Podarcis wagleriana . Location Sicily and neighbouring islands. Methods We sampled 179 individuals from 45 localities across the whole range of P. wagleriana . We investigated demographic and spatial variations through time using Bayesian coalescent models (Bayesian phylogeographic reconstruction, Extended Bayesian Skyline plots, Isolation‐with‐migration models) based on multilocus DNA sequence data. We used species distribution modelling to reconstruct present and past habitat suitability. Results We found two main lineages distributed in the east and west portions of the current species range and a third lineage restricted to a small area in the north of Sicily. Multiple lines of evidence from palaeogeographic (shorelines), palaeoclimatic (species distribution models), and multilocus genetic data (demographic and spatial Bayesian reconstructions) indicate that these lineages originated in distinct refugia, located in the north‐western and south‐eastern coastal lowlands, during Middle Pleistocene interglacial phases, and came into secondary contact following demographic and spatial expansions during the last glacial phase. Main conclusions This scenario of interglacial contraction and glacial expansion is in sharp contrast with patterns commonly observed in temperate species on the continent but parallels recent findings on other Mediterranean island endemics. Such a reverse expansion–contraction ( EC ) dynamic has been likely associated with glacial increases of climatically suitable coastal lowlands, suggesting this might be a general pattern in Mediterranean island species and also in other coastal regions strongly affected by glacial marine regressions during glacial episodes. This study provides explicit predictions and some methodological recommendations for testing the reverse EC model in other region and taxa.

Senczuk, Gabriele↗

DOE OSTI2018

The Effect of Solvent on the Capacity Retention in a Germanium Anode for Lithium Ion Batteries

A thin and mechanically stable solid electrolyte interphase (SEI) is desirable for a stable cyclic performance in a lithium ion battery. For the electrodes that undergo a large volume expansion such as Si, Ge and Sn, the presence of a robust SEI layer can improve the capacity retention. In this work, the role of solvent choice on the electrochemical performance of Ge electrode is presented by a systematic comparison of the SEI layers in EC-based and FEC-based electrolytes. The results show that the presence of FEC as a co-solvent in a binary or ternary solvent electrolyte results in an excellent capacity retention of ~ 85% after 200 cycles at the current density of 500 mA·g-1; while EC-based electrode suffers a rapid capacity degradation with a capacity retention of just 17% at the end of 200 cycles. Post analysis by an extensive use of x-ray photoelectron spectroscopy was carried out, which showed that the presence of Li2O in FEC-based SEIs was the origin for the improved electrochemical performance.

Mishra, Kuber↗

DOE OSTI2015

SU-E-T-811: Volumetric Modulated Arc Therapy Vs. C-IMRT for the Treatment of Upper Thoracic Esophageal Cancer

Purpose: To compare plans using volumetric-modulated arc therapy (VMAT) with conventional sliding window intensity-modulated radiation therapy (c-IMRT) to treat upper thoracic esophageal cancer (EC). Methods: CT datasets of 11 patients with upper thoracic EC were identified. Four plans were generated for each patient: c-IMRT with 5 fields (5F) and VMAT with a single arc (1A), two arcs (2A), or three arcs (3A). The prescribed doses were 64 Gy/32 F for the primary tumor (planning target volume 64, PTV64). The dose-volume histogram data, the number of monitoring units (MUs) and the treatment time (TT) for the different plans were compared. Results: All of the plans generated similar dose distributions for PTVs and organs at risk (OARs), except that the 2A- and 3A-VMAT plans yielded a significantly higher conformity index (CI) than the c-IMRT plan. The CI of the PTV64 was improved by increasing the number of arcs in the VMAT plans. The maximum spinal cord dose and the planning risk volume of the spinal cord dose for the two techniques were similar. The 2A- and 3A-VMAT plans yielded lower mean lung doses and heart V50 than the c-IMRT. The V20 and V30 for the lungs in all of the VMAT plans were lower than those in the c-IMRT plan, at the expense of increasing V5, V10 and V13. The VMAT plan resulted in significant reductions in MUs and TT. Conclusion: The 2A-VMAT plan appeared to spare the lungs from moderate-dose irradiation most effectively of all plans, at the expense of increasing the low-dose irradiation volume, and also significantly reduced the number of required MUs and the TT. The CI of the PTVs and the OARs was improved by increasing the arc-number from 1 to 2. however, no significant improvement was observed using the 3A-VMAT, except for an increase in the TT. This work was sponsored by Shantou University Medical College Clinical Research Enhancement Initiative(NO.201424)

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

A Modified P1 Moiety Enhances in vitro Antiviral Activity against Various Multi-Drug-Resistant HIV-1 Variants and in vitro CNS Penetration Properties of a Novel Nonpeptidic Protease Inhibitor, GRL-10413

We here report that GRL-10413, a novel non-peptidic HIV-1 protease inhibitor (PI) containing a modified P1 moiety and a sulfonamide isostere, is highly active against laboratory HIV-1 strains and primary clinical isolates (EC 50 : 0.00035 - 0.0018 μM) with minimal cytotoxicity (CC 50 : 35.7 μM). GRL-10413 blocked the infectivity and replication of HIV-1 NL4-3 variants selected by up to 5 μM concentrations of atazanavir, lopinavir, or amprenavir (EC 50 : 0.0021 - 0.0023 μM). GRL-10413 also maintained its strong antiviral activity against multi-drug-resistant clinical HIV-1 variants isolated from patients, who no longer responded to various antiviral regimens after long-term antiretroviral therapy. The development of resistance against GRL-10413 was significantly delayed compared to that of APV. In addition, GRL-10413 showed a favorable central nervous system (CNS) penetration property as assessed with an in vitro blood brain barrier (BBB) reconstruction system. Analysis of the crystal structure of HIV-1 protease in complex with GRL-10413 demonstrated that the modified P1 moiety of GRL-10413 has a greater hydrophobic surface area and makes greater van der Waals contacts with active-site amino acids of protease than in the case of darunavir. Moreover, the chlorine substituent in the P1 moiety interacts with protease in two distinct configurations. The present data demonstrate that GRL-10413 has desirable features for treating patients infected with wild-type and/or multi-drug-resistant HIV-1 variants with favorable CNS-penetration capability and that the newly modified P1-moiety may confer desirable features in designing novel anti-HIV-1 PIs.

Amano, Masayuki↗

DOE OSTI2023

RAPIDS: Reconciling Availability, Accuracy, and Performance in Managing Geo-Distributed Scientific Data

In modern science, big data plays an increasingly important role. Many scientific applications, such as running simulations on supercomputers or conducting experiments on advanced instruments, produce huge amount of data at unprecedented speed. Analyzing and understanding such big data is the key for scientists to make scientific breakthroughs. However, data might become unavailable for scientists to access when outages or maintenance of the storage system occur, which severely hinders scientific discovery. To improve the data availability, data duplication and erasure coding (EC) are often used. But as the scientific data gets larger, using these two methods can cause considerable storage and network overhead.In this paper, we propose RAPIDS, a hybrid approach that combines the multigrid-based error-bounded lossy compression with erasure coding, to significantly reduce the storage and network overhead required for maintaining high data availability. Our experiments show that RAPIDS reduces the storage overhead by up to 7.5x and network overhead by up to 3x to achieve the same level of availability compared to the regular EC method. We improve RAPIDS by building two models to optimize the fault tolerance configurations and data gathering strategy. We demonstrate that RAPIDS significantly improves performance when running on many CPU cores in parallel or on GPUs.

Wan, Lipeng↗