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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.

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Hyaloscypha finlandica Metabolome Repository

This repository provides the curated data tables, manuscript figure and table exports, dependency records, and workflow scripts supporting an integrated comparative genomics and untargeted LC-MS/MS metabolomics analysis of Hyaloscypha finlandica strain PMI 746, a root-associated dark septate endophyte of poplar. The repository includes genome-mining summaries from antiSMASH, FunBGCeX, BGC-Prophet, and BiG-SCAPE; processed metabolomics inputs; metabolite annotation evidence; statistical outputs; and publication-facing figures and tables. Raw LC-MS/MS spectra, full genome/protein downloads, and large generated tool outputs are referenced through public archive/accession records and are not stored in Git.

59 BASIC BIOLOGICAL SCIENCES↗

Insight into a highly polymorphic endophyte isolated from the roots of the halophytic seepweed Suaeda salsa: Laburnicola rhizohalophila sp. nov. (Didymosphaeriaceae, Pleosporales)

In this work, we surveyed root endophytic fungi of the coastal halophyte Suaeda salsa and detected a population of a novel species that we described here as Laburnicola rhizohalophila sp. nov. No sexual sporulating structure was observed. Instead, it produced a large amount of thalloconidia, 0–1 transverse septa, hyaline to darkly pigmented, often peanut-shaped and sometimes dumbbell-shaped, both ends enlarged with numerous oil droplets inside the hyphal cells. Surprisingly, a high degree of phenotypic and physiological intraspecific variation (e.g., salinity tolerance, growth under different carbon:nitrogen ratios, and carbon utilization pattern) was recorded. The inoculation test indicated that the isolates could successfully infect host roots and form microsclerotia-like structures in cortical cells, a typical trait of dark septate endophytes (DSEs). Furthermore, most isolates were shown to promote host seedling growth. To evaluate conspecificity and infer its phylogenetic affinity, multiloci data including nuclear rRNA loci (ITS1 and 2, partial 28S), partial RNA Polymerase II second-largest subunit ( rpb2 ), and partial translation elongation factor-1α ( tef1 ) were characterized. Genealogical concordance phylogenetic species recognition (GCPSR) detected a genetically isolated clade of L. rhizohalophila within the Pleosporales in the Didymosphaeriaceae. Maximum likelihood phylogenetic reconstruction revealed that the endophytic fungus was genetically close to L aburnicola dactylidis but separated by a relatively long genetic distance. Our work highlights that the pleosporalean taxa might represent an underexplored reservoir of root DSEs.

59 BASIC BIOLOGICAL SCIENCES↗

Distinguishing Quarks and Gluons in Pion and Kaon PDFs

The leading-twist parton distribution functions of the pion and kwon are calculated for the first time using a rainbow-ladder truncation of QCD's Dyson-Schwinger equations (DSEs) that self-consistently sums all planar diagrams. The nonperturbative gluon dressing of the quarks is thereby correctly accounted for, which in practice means solving the inhomogeneous Bethe-Salpeter equation (BSE) for the quark operator that defines the spin-independent quark distribution functions. An immediate consequence of using this dressed vertex is that gluons carry 35% of the pion's and 30% of the kaon's light-cone momentum, with the remaining momentum carried by the quarks. The scale associated with these DSE results is μ 0 = 0.78 GeV. The gluon effects generated by the inhomogeneous BSE are inherently nonperturbative and cannot be mimicked by the perturbative QCD evolution equations. A key consequence of this gluon dressing is that the valence quarks have reduced support at low-to-intermediate x, where the gluons dominate, and increased support at large x. As a result, our DSE calculation of the pion's valence quark distribution is in excellent agreement with the Conway et al. pion-induced Drell-Yan data, but nevertheless exhibits the q π (x) similar or equal to (1 - x) 2 behavior as x -> 1 predicted by perturbative QCD.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A Hybrid Framework Combining Model-Based and Data-Driven Methods for Hierarchical Decentralized Robust Dynamic State Estimation

This paper combines model-based and data-driven methods to develop a hierarchical, decentralized, robust dynamic state estimator (DSE). A two-level hierarchy is proposed, where the lower level consists of robust, model-based, decentralized DSEs. The state estimates sent from the lower level are received at the upper level, where they are filtered by a robust data-driven DSE after a principled sparse selection. This selection allows us to shrink the dimension of the problem at the upper level and hence significantly speed up the computational time. The proposed hybrid framework does not depend on the centralized infrastructure of the control centers; thus it can be completely embedded into the wide-area measurement systems. This feature will ultimately facilitate the placement of hierarchical decentralized control schemes at the phasor data concentrator locations. Also, the network model is not necessary; thus, a topology processor is not required. Finally, there is no assumption on the dynamics of the electric loads. The proposed framework is tested on the 2,000-bus synthetic Texas system, and shown to be capable of reconstructing the dynamic states of the generators with high accuracy, and of forecasting in the advent of missing data.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Application of the Koopman Operator-Theoretic Framework to Power System Dynamic State Estimation

Model-based and data-driven methods are combined to develop a hierarchical decentralized, robust dynamic state estimator (DSE). A two-level hierarchy is proposed, where the lower level consists of robust, model-based, decentralized DSEs. The state estimates sent from the lower level are received at the upper level, where they are filtered by a robust data-driven DSE. The proposed hybrid framework does not depend on the centralized infrastructure of the control centers; thus it can be completely embedded into the wide-area measurement systems. This feature will ultimately facilitate the placement of hierarchical decentralized control schemes at the phasor data concentrator locations. Also, the network model is not necessary; thus, a topology processor is not required. Finally, there is no assumption on the dynamics of the electric loads. The proposed framework is tested on the 2,000-bus synthetic Texas system and shown to be capable of reconstructing the dynamic states of the generators with high accuracy, and of forecasting in the advent of missing data.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Hybrid Framework Combining Model-Based and Data-Driven Methods for Hierarchical Decentralized Robust Dynamic State Estimation: Preprint

This paper combines model-based and data-driven methods to develop a hierarchical decentralized robust dynamic state estimator (DSE). A two-level hierarchy is proposed, where the lower level is comprised of robust model-based decentralized DSEs. The state estimates sent from the lower level are received at the upper level, where they are filtered by a robust data- driven DSE, after a principled sparse selection. This selection allows us to shrink the dimension of the problem at the upper level, and hence to speed up the computational time significantly. The proposed hybrid framework does not depend upon the centralized infrastructure of the control centers, thus it can be completely embedded into the wide-area measurement systems. This feature will ultimately facilitate the placement of hierarchical decentralized control schemes at the phasor data concentrator (PDC) locations. Also, the network model is not necessary, thus a topology processor is not required. Finally, there is no assumption on the dynamics of the electric loads. The proposed framework is tested on a 2000-bus network.

24 POWER TRANSMISSION AND DISTRIBUTION↗