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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Diagnosing Intermittent and Persistent Faults using Static Bayesian Networks

Both intermittent and persistent faults may occur in a wide range of systems. We present in this paper the introduction of intermittent fault handling techniques into ProDiagnose, an algorithm that previously only handled persistent faults. We discuss novel algorithmic techniques as well as how our static Bayesian networks help diagnose, in an integrated manner, a range of intermittent and persistent faults. Through experiments with data from the ADAPT electrical power system test bed, generated as part of the Second International Diagnostic Competition (DXC-10), we show that this novel variant of ProDiagnose diagnoses intermittent faults accurately and quickly, while maintaining strong performance on persistent faults.

Megshoel, Ole Jakob↗
DOE OSTI2022

Local Versus Global Distances for Zigzag and Multi-Parameter Persistence Modules

In this paper, we establish explicit and broadly applicable relationships between persistence-based distances computed locally and globally. In particular, we show that the bottleneck distance and the Wasserstein distance between two zigzag persistence modules restricted to an interval is always bounded above by the distance between the unrestricted versions. While this result is not surprising, it could have potential practical implications. We give two related applications for metric graph distances, as well as an extension for the matching distance between multi-parameter persistence modules.

persistent homology, metric graph, inequality↗
DOE OSTI2022

Metall: A persistent memory allocator for data-centric analytics

Data analytics applications transform raw input data into analytics-specific data structures before performing analytics. Unfortunately, such data ingestion steps are often more expensive than analytics. In addition, various types of NVRAM devices are already used in many HPC systems today. Such devices will be useful for storing and reusing data structures beyond a single process life cycle. We developed Metall, a persistent memory allocator built on top of the memory-mapped file mechanism. Metall enables applications to transparently allocate custom C++ data structures into various types of persistent memories. Metall incorporates a concise and high-performance memory management algorithm inspired by Supermalloc and the rich C++ interface developed by Boost.Interprocess library. On a dynamic graph construction workload, Metall achieved up to 11.7x and 48.3x performance improvements over Boost.Interprocess and memkind (PMEM kind), respectively. We also demonstrate Metall’s high adaptability by integrating Metall into a graph processing framework, GraphBLAS Template Library. Here this study’s outcomes indicate that Metall will be a strong tool for accelerating future large-scale data analytics by allowing applications to leverage persistent memory efficiently.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Vaccination with mycobacterial lipid loaded nanoparticle leads to lipid antigen persistence and memory differentiation of antigen-specific T cells

Mycobacterium tuberculosis (Mtb) infection elicits both protein and lipid antigen-specific T cell responses. However, the incorporation of lipid antigens into subunit vaccine strategies and formulations has been underexplored, and the characteristics of vaccine-induced Mtb lipid-specific memory T cells have remained elusive. Mycolic acid (MA), a major lipid component of the Mtb cell wall, is presented by human CD1b molecules to unconventional T cell subsets. These MA-specific CD1b-restricted T cells have been detected in the blood and disease sites of Mtb-infected individuals, suggesting that MA is a promising lipid antigen for incorporation into multicomponent subunit vaccines. In this study, we utilized the enhanced stability of bicontinuous nanospheres (BCN) to efficiently encapsulate MA for in vivo delivery to MA-specific T cells, both alone and in combination with an immunodominant Mtb protein antigen (Ag85B). Pulmonary administration of MA-loaded BCN (MA-BCN) elicited MA-specific T cell responses in humanized CD1 transgenic mice. Simultaneous delivery of MA and Ag85B within BCN activated both MA- and Ag85B-specific T cells. Notably, pulmonary vaccination with MA-Ag85B-BCN resulted in the persistence of MA, but not Ag85B, within alveolar macrophages in the lung. Vaccination of MA-BCN through intravenous or subcutaneous route, or with attenuated Mtb likewise reproduced MA persistence. Moreover, MA-specific T cells in MA-BCN-vaccinated mice differentiated into a T follicular helper-like phenotype. Overall, the BCN platform allows for the dual encapsulation and in vivo activation of lipid and protein antigen-specific T cells and leads to persistent lipid depots that could offer long-lasting immune responses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

The persistence and conversion of coastal foredune and swale vegetation community distributions 63 years later

Vegetation shifts can directly alter habitat dynamics and indirectly impact habitat stability relative to disturbance response. Barrier island dune habitats exhibit spatiotemporally dynamic topography that is affected by vegetation. However, vegetation distribution data can be rare and vegetation persistence is largely unknown such that species turnover over in communities can occur unnoticed. This is true despite concerns and documented cases of woody encroachment related to climate change in these ecogeomorphic habitats where physical stability to resist storm erosion varies with vegetation distribution and density. In 1956 and 1957, the vegetation of Island Beach State Park, NJ, was mapped as a permanent record for subsequent ecological study. In June 2020, we remapped the vegetation of 5.4 of 17 km north to south, seaward of the thicket community boundary. We maintained the same classification system as the historic record, physically mapping vegetation patches via GPS. We quantified changes in thicket, heather, and grass community distribution between the two time periods. Habitat persistence and conversion varied in the 63 years. Heath communities saw 80%–97% habitat loss in conversion to woody thicket. Conversely, thicket community distribution drastically increased, replacing heath where it was previously prevalent. This represents the first known documented instances of woody encroachment for Morella pensylvanica. When they did not expand, thicket communities receded landward or underwent turnover to an invasive species. Woody species of interest for dune stabilization occupied areas of similar habitat characteristics. Dune vegetation distribution persistence from 1957 to 2020 was relatively consistent and stable with the exception of heath habitat conversion. Barrier island stability is directly related to vegetation stability such that understanding where community shifts might occur over time can aid in managing and modeling efforts surrounding these dynamic ecogeomorphic habitats.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Persistent Classification: Understanding Adversarial Attacks by Studying Decision Boundary Dynamics

ABSTRACT There are a number of hypotheses underlying the existence of adversarial examples for classification problems. These include the high‐dimensionality of the data, the high codimension in the ambient space of the data manifolds of interest, and that the structure of machine learning models may encourage classifiers to develop decision boundaries close to data points. This article proposes a new framework for studying adversarial examples that does not depend directly on the distance to the decision boundary. Similarly to the smoothed classifier literature, we define a (natural or adversarial) data point to be ( γ , σ)‐stable if the probability of the same classification is at least for points sampled in a Gaussian neighborhood of the point with a given standard deviation . We focus on studying the differences between persistence metrics along interpolants of natural and adversarial points. We show that adversarial examples have significantly lower persistence than natural examples for large neural networks in the context of the MNIST and ImageNet datasets. We connect this lack of persistence with decision boundary geometry by measuring angles of interpolants with respect to decision boundaries. Finally, we connect this approach with robustness by developing a manifold alignment gradient metric and demonstrating the increase in robustness that can be achieved when training with the addition of this metric.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Persistent Sampling: Enhancing the Efficiency of Sequential Monte Carlo

Sequential Monte Carlo (SMC) samplers are powerful tools for Bayesian inference but suffer from high computational costs due to their reliance on large particle ensembles for accurate estimates. We introduce persistent sampling (PS), an extension of SMC that systematically retains and reuses particles from all prior iterations to construct a growing, weighted ensemble. By leveraging multiple importance sampling and resampling from a mixture of historical distributions, PS mitigates the need for excessively large particle counts, directly addressing key limitations of SMC such as particle impoverishment and mode collapse. Crucially, PS achieves this without additional likelihood evaluations-weights for persistent particles are computed using cached likelihood values. This framework not only yields more accurate posterior approximations but also produces marginal likelihood estimates with significantly lower variance, enhancing reliability in model comparison. Furthermore, the persistent ensemble enables efficient adaptation of transition kernels by leveraging a larger, decorrelated particle pool. Experiments on high-dimensional Gaussian mixtures, hierarchical models, and non-convex targets demonstrate that PS consistently outperforms standard SMC and related variants, including recycled and waste-free SMC, achieving substantial reductions in mean squared error for posterior expectations and evidence estimates, all at reduced computational cost. PS thus establishes itself as a robust, scalable, and efficient alternative for complex Bayesian inference tasks.

Karamanis, Minas↗
DOE OSTI2025

Persistence of bacterial-mediated anti-rotifer protection in preliminary outdoor cultivation trial for Microchloropsis salina

Outdoor algal cultivation systems are susceptible to a wide variety of deleterious species. In previously published studies, we observed protection using microbial consortia at laboratory scale cultures; Microchloropsis salina in the presence of microbial consortia were protected from grazing from the marine rotifer, Brachionus plicatilis. Our objective for the present work was to determine if this protection conferred by microbial consortia in controlled laboratory experiments would persist in an open, outdoor multi-liter cultivation system. We found that algal protection did persist as evidenced by the presence of fewer motile rotifers and decreased rotifer-associated egg counts for the consortia-treated outdoor cultures. Due to the low temperature and light conditions that reduced growth of the algae outdoors, we performed an indoor laboratory assay which also confirmed the persistence of algal protection. Lastly, the lower numbers of motile rotifers and fewer rotifer-associated eggs in the consortia-treated algal cultures suggests a possible protective mechanism by the consortia through interfering with the rotifer lifecycle or reproduction. Finally, these initial results support the possibility that low cost, prophylactic treatments with microbial consortia can protect algae from deleterious species in outdoor cultivation systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Persistent urinary metabolic signatures in children with type 1 diabetes

There are an estimated 3.7 million people with undiagnosed type 1 diabetes (T1D), living primarily in poor areas of the globe. Therefore, there is a need for non-invasive, affordable tests to provide accurate diagnosis despite the time post-disease onset and fasting state. Here, we studied persistent urinary T1D biomarkers that can be used to develop such tests. Here, we analyzed the urine metabolomes of three independent cohorts of samples collected within 48 h (from Indiana University), and 1 year (from University of Colorado) and 1–10 years (6 years in average) (from Children’s National Medical Center) post-diagnosis. Samples were submitted to gas chromatography-mass spectrometry and machine learning an0alyses to determine diagnostic metabolite panels. The data were also mapped into a metabolic pathway to understand persistently regulated processes in T1D. Seven metabolites showed consistent increases in all three cohorts: d-glucose, d-mannose, myo-inositol, 3-hydroxyisobutyric acid, gluconolactone, d-gluconic acid, and d-glucuronic acid. A combination of machine learning analysis and metabolite ratios as biomarker candidates diagnosed T1D with high sensitivity and specificity across different cohorts and times. Mapping the regulated metabolites into a pathway showed impairment in glycolysis and overflow of glucose towards other pathways in subjects with T1D that was persistent over time. We identified and cross-validated highly specific and sensitive urinary biomarkers. This opens opportunities to develop affordable, robust, and non-invasive tests. The results also show that most of the biomarkers were signatures of dysregulated glucose metabolism.

Type 1 diabetes↗
DOE OSTI2021

Chronic arsenic increases cell migration in BEAS-2B cells by increasing cell speed, cell persistence, and cell protrusion length

Highlights: • Chronic arsenic exposure primes lung epithelial cells for enhanced cell migration. • Chronic arsenic increases cell motility in an EGFR-dependent manner. • Chronic arsenic increases cell persistence in an EGFR-independent manner. • EGFR is sufficient, but not necessary for increasing cell protrusion length in chronic arsenic treated cells. There is a strong association between arsenic exposure and lung cancer development, however, the mechanism by which arsenic exposure leads to carcinogenesis is not clear. In our previous study, we observed that when BEAS-2B cells are chronically exposed to arsenic, there is an increase in secreted TGFα, as well as an increase in EGFR expression and activity. Further, these changes were broadly accompanied with an increase in cell migration. The overarching goal of this study was to acquire finer resolution of the arsenic-dependent changes in cell migration, as well as to understand the role of increased EGFR expression and activity levels in the underlying mechanisms of cell migration. To do this, we used a combination of biochemical and single cell assays, and observed chronic arsenic treatment enhancing cell migration by increasing cell speed, cell persistence and cell protrusion length. All three parameters were further increased by the addition of TGFα, indicating EGFR activity is sufficient to enhance those aspects of cell migration. In contrast, EGFR activity was necessary for the increase in cell speed, as it was reversed with an EGFR inhibitor, AG1478, but was not necessary to enhance persistence and protrusion length. From these data, we were able to isolate both EGFR-dependent and –independent features of cell migration that were enhanced by chronic arsenic exposure.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Ultranano Titania: Selectively Ridding Water of Persistent Organic Pollutants

Persistent organic pollutants, including the EPA's “dirty dozen”, are difficult to remove from water supplies due to their chemical stability. Here, we report a stable oxide photocatalyst, ultranano titania (d < 2 nm) doped with iron, Fe•TiUNP, that efficiently mineralizes multiple persistent pollutants including aromatic compounds plus common troublesome, difficult-to-oxidize intermediates such as formaldehyde and acetone, netting mineralization of persistent pollutants. Efficiency stems from a direct charge-transfer pathway. The key role of iron doping is to lower the reduction potential of the photogenerated electron so that it is insufficient to reduce water, thus eliminating competition from the hydrogen evolution reaction. The reduction potential of the localized electron is similarly insufficient to reduce quinone, enabling breaking aromaticity. Specific results for degrading acetone, phenol, benzoic acid, and 1,4-benzoquinone are reported.

alcohols↗
DOE OSTI2023

Photocarrier-induced persistent structural polarization in soft-lattice lead halide perovskites

The success of the lead halide perovskites in diverse optoelectronics has motivated considerable interest in their fundamental photocarrier dynamics. Here, in this work, we report the discovery of photocarrier-induced persistent structural polarization and local ferroelectricity in lead halide perovskites. Photoconductance studies of thin-film single-crystal CsPbBr 3 at 10 K reveal long-lasting persistent photoconductance with an ultralong photocarrier lifetime beyond 10 6 s. X-ray diffraction studies reveal that photocarrier-induced structural polarization is present up to a critical freezing temperature. Photocapacitance studies at cryogenic temperatures further demonstrate a systematic local phase transition from linear dielectric to paraelectric and relaxor ferroelectric under increasing illumination. Our theoretical investigations highlight the critical role of photocarrier–phonon coupling and large polaron formation in driving the local relaxor ferroelectric phase transition. Our findings show that this photocarrier-induced persistent structural polarization enables the formation of ferroelectric nanodomains at low temperature, which suppress carrier recombination and offer the possibility of exploring intriguing carrier–phonon interplay and the rich polaron photophysics.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Effect of proton irradiation temperature on persistent photoconductivity in zinc oxide metal-semiconductor-metal ultraviolet photodetectors

The electrical and structural characteristics of 50-nm-thick zinc oxide (ZnO) metal-semiconductor-metal ultraviolet (UV) photodetectors subjected to proton irradiation at different temperatures are reported and compared. The devices were irradiated with 200 keV protons to a fluence of 1016 cm−2. Examination of the x-ray diffraction (XRD) rocking curves indicates a preferred (100) orientation prior to irradiation, with decrease in crystal quality afterward. Additionally, peak shifts in XRD and Raman spectra of the control sample relative to well-known theoretical positions are indicative of tensile strain in the as-deposited ZnO films. Shifts toward theoretical unstrained positions are observed in the irradiated films, which indicates partial relaxation. Raman spectra also indicate increase in oxygen vacancies (VO) and zinc interstitial defects (Zni) compared to the control sample. Additionally, transient photocurrent measurements performed on each sample at different temperatures showed up to 2× increase in photocurrent decay time constants for irradiated samples vs the control. This persistent photoconductive behavior is linked to the activation of electron and hole traps near the surface, and to the desorption and reabsorption of O2 molecules on the ZnO surface under the influence of UV light. Using an Arrhenius model, trap activation energies were extracted and, by comparing with known energies from the literature, the dominant defects contributing to persistent photoconductivity for each irradiation condition were identified. The persistence of differences in photocurrent transients between different samples months after irradiation indicates that the defects introduced by the suppression of thermally activated dynamic annealing processes have a long-term deleterious effect on device performance.

Heuser, Thomas A. (ORCID:0000000225642400)↗
DOE OSTI2023

Dominant heterocyclic composition of dissolved organic nitrogen in the ocean: A new paradigm for cycling and persistence

Marine dissolved organic nitrogen (DON) is one of the planet’s largest reservoirs of fixed N, which persists even in the N-limited oligotrophic surface ocean. The vast majority of the ocean’s total DON reservoir is refractory (RDON), primarily composed of low molecular weight (LMW) compounds in the subsurface and deep sea. However, the composition of this major N pool, as well as the reasons for its accumulation and persistence, are not understood. Past characterization of the analytically more tractable, but quantitatively minor, high molecular weight (HMW) DON fraction revealed a functionally simple amide-dominated composition. While extensive work in the past two decades has revealed enormous complexity and structural diversity in LMW dissolved organic carbon, no efforts have specifically targeted LMW nitrogenous molecules. Here, we report the first coupled isotopic and solid-state NMR structural analysis of LMW DON isolated throughout the water column in two ocean basins. Together these results provide a first view into the composition, potential sources, and cycling of this dominant portion of marine DON. Our data indicate that RDON is dominated by 15N-depleted heterocyclic-N structures, entirely distinct from previously characterized HMW material. This fundamentally new view of marine DON composition suggests an important structural control for RDON accumulation and persistence in the ocean. The mechanisms of production, cycling, and removal of these heterocyclic-N-containing compounds now represents a central challenge in our understanding of the ocean’s DON reservoir.

58 GEOSCIENCES↗
DOE OSTI2024

Cosmology with persistent homology: a Fisher forecast

Abstract Persistent homology naturally addresses the multi-scale topological characteristics of the large-scale structure as a distribution of clusters, loops, and voids. We apply this tool to the dark matter halo catalogs from theQuijotesimulations, and build a summary statistic for comparison with the joint power spectrum and bispectrum statistic regarding their information content on cosmological parameters and primordial non-Gaussianity. Through a Fisher analysis, we find that constraints from persistent homology are tighter for 8 out of the 10 parameters by margins of 13–50%. The complementarity of the two statistics breaks parameter degeneracies, allowing for a further gain in constraining power when combined. We run a series of consistency checks to consolidate our results, and conclude that our findings motivate incorporating persistent homology into inference pipelines for cosmological survey data.

Astronomy & Astrophysics↗
DOE OSTI2021

Quantitative and interpretable order parameters for phase transitions from persistent homology

Here, we apply modern methods in computational topology to the task of discovering and characterizing phase transitions. As illustrations, we apply our method to four two-dimensional lattice spin models: the Ising, square ice, XY, and fully frustrated XY models. In particular, we use persistent homology, which computes the births and deaths of individual topological features as a coarse-graining scale or sublevel threshold is increased, to summarize multiscale and high-point correlations in a spin configuration. We employ vector representations of this information called persistence images to formulate and perform the statistical task of distinguishing phases. For the models we consider, a simple logistic regression on these images is sufficient to identify the phase transition. Interpretable order parameters are then read from the weights of the regression. This method suffices to identify magnetization, frustration, and vortex-antivortex structure as relevant features for phase transitions in our models. We also define “persistence” critical exponents and study how they are related to those critical exponents usually considered.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Strain engineering a persistent spin helix with infinite spin lifetime

Persistent spin textures (PSTs) in solid-state materials arise from a unidirectional spin-orbit field in momentum space and offer a route to deliver long carrier spin lifetimes sought for future quantum microelectronic devices. Nonetheless, few three-dimensional materials are known to host PSTs owing to crystal symmetry and chemical requirements. There are even fewer examples demonstrated experimentally. Here we report that high-quality persistent spin textures can be obtained in the polar point groups containing an odd number of mirror operations. We use representation theory analysis and electronic structure calculations to formulate general discovery principles to identify PSTs hidden in known complex ternary layered and perovskite structures with large electric polarizations. We then show some of these materials exhibit PSTs without requiring any special crystalline symmetries. This finding removes the limitation imposed by mirror-symmetry protected PSTs that has limited compound discovery. Our general design approach enables the pursuit of persistent spin helices in materials exhibiting the C 3 v crystal class adopted by many quantum materials exhibiting large Rashba coefficients.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Applications of persistent homology in nuclear collisions

Here, we introduce a novel set of observables associated to the rapidly developing field of persistent homology for the quantitative characterization of nuclear collisions and their evolution. Persistent homology allows for the identification of topological and homological characteristics of distributions in multidimensional spaces. We demonstrate here how to apply the tool kit of persistent homology to the extraction of novel clustering signatures and the identification of long-range flow correlations in the particle production process of nuclear collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗