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At least 1,387 records · Page 77

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DOE OSTI2022

Dimension-adaptive machine learning-based quantum state reconstruction

Here, we introduce an approach for performing quantum state reconstruction on systems of n qubits using a machine learning-based reconstruction system trained exclusively on m qubits, where m ≥ n. This approach removes the necessity of exactly matching the dimensionality of a system under consideration with the dimension of a model used for training. We demonstrate our technique by performing quantum state reconstruction on randomly sampled systems of one, two, and three qubits using machine learning-based methods trained exclusively on systems containing at least one additional qubit. The reconstruction time required for machine learning-based methods scales significantly more favorably than the training time; hence this technique can offer an overall saving of resources by leveraging a single neural network for dimension-variable state reconstruction, obviating the need to train dedicated machine learning systems for each Hilbert space.

42 ENGINEERING↗

DOE OSTI2014

An efficient Bayesian inversion of a geothermal prospect using a multivariate adaptive regression spline method

In this study, an efficient Bayesian framework equipped with a multivariate adaptive regression spline (MARS) technique is developed to alleviate computational burdens encountered in a conventional Bayesian inversion of a geothermal prospect. Fast MARS models are developed from training dataset generated by CPU-intensive hydrothermal models and used as surrogate of high-fidelity physical models in Markov Chain Monte Carlo (MCMC) sampling. This Bayesian inference with MARS-enabled MCMC method is used to reduce prior estimates of uncertainty in structural or characteristic hydrothermal flow parameters of the model to posterior distributions. A geothermal prospect near Superstition Mountain in Imperial County of California in USA is used to illustrate the proposed framework and demonstrate the computational efficiency of MARS-based Bayesian inversion. The developed MARS models are also used to efficiently drive calculation of Sobol’ total sensitivity indices. Furthermore, only top sensitive parameters are included in Bayesian inference to further improve the computational efficiency of inversion. Sensitivity analysis also confirms that water circulation through high permeable structures, rather than heat conduction through impermeable granite, is the primary heat transfer method. The presented framework is demonstrated an efficient tool to update knowledge of geothermal prospects by inversing field data. Although only thermal data is used in this study, other type of data, such as flow and transport observations, can be jointly used in this method for underground hydrocarbon reservoirs.

15 GEOTHERMAL ENERGY↗

DOE OSTI2020

Sequential ensemble transform for Bayesian inverse problems

In this work, we present the Sequential Ensemble Transform (SET) method, an approach for generating approximate samples from a Bayesian posterior distribution. The method explores the posterior distribution by solving a sequence of discrete optimal transport problems to produce a series of transport plans which map prior samples to posterior samples. We prove that the sequence of Dirac mixture distributions produced by the SET method converges weakly to the true posterior as the sample size approaches infinity. Furthermore, our numerical results indicate that, when compared to standard Sequential Monte Carlo (SMC) methods, the SET approach is more robust to the choice of Markov mutation kernels and requires less computational efforts to reach a similar accuracy when used to explore complex posterior distributions. Finally, we describe adaptive schemes that allow to completely automate the use of the SET method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Wavefront Preservation in Soft X-Ray Beamlines for the Advanced Light Source Upgrade

In the 4th generation of X-ray light sources, including Free-Electron Lasers (FEL) and Diffraction-Limited Storage Rings (DLSR), the emittance of the electron beam is small or negligible compared to the emittance of the photon beam produced by insertion devices, thus generating coherent beams of light. Over the next few years, several lightsource facilities will be built or upgraded to produce X-ray beams of unprecedented coherent flux. Delivering these exceptional beams to the sample chambers requires beamline optical systems that are designed to preserve the wavefront properties. Our goal in the Advanced Light Source upgrade project (ALS-U) is to create a new class of beamlines that reach diffraction-limited X-ray optical quality through tightly integrated, efficient optical systems, diagnostics, and adaptive mirrors, thus providing users with new scientific capabilities offered by coherent X-ray light interactions with matter. Herein we describe aspects of the beamlines’ design as they enter the project’s final design phase.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2015

Luminous red galaxies: selection and classification by combining optical and infrared photometry

We describe a new method of combining optical and infrared photometry to select luminous red galaxies (LRGs) at redshifts z>0.6. We explore this technique using a combination of optical photometry from CFHTLS and Hubble Space Telescope, infrared photometry from the Wide-Field Infrared Survey Explorer satellite, and spectroscopic or photometric redshifts from the DEEP2 Galaxy Redshift Survey or COSMOS. We present a variety of methods for testing the success of our selection and present methods for optimization given a set of rest-frame color and redshift requirements. We have tested this selection in two different regions of the sky, the COSMOS and Extended Groth Strip (EGS) fields, to reduce the effect of cosmic/sample variance. We have used these methods to assemble large samples of LRGs for two different ancillary programs as a part of the Sloan Digital Sky Survey (SDSS)-III/Baryon Oscillation Spectroscopic Survey. This technique is now being used to select ∼600,000 LRG targets for SDSS-IV/Extended Baryon Oscillation Spectroscopic Survey, which began observations in Fall 2014, and will be adapted for the proposed Dark Energy Spectroscopic Instrument survey. We have found that these methods can select high-redshift LRGs efficiently with minimal stellar contamination; this is extremely difficult to achieve with selections that rely on optical photometry alone.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Complete genome sequence of Desulfurivibrio alkaliphilus strain AHT2 T , a haloalkaliphilic sulfidogen from Egyptian hypersaline alkaline lakes

Desulfurivibrio alkaliphilus strain AHT2 T is a strictly anaerobic sulfidogenic haloalkaliphile isolated from a composite sediment sample of eight hypersaline alkaline lakes in the Wadi al Natrun valley in the Egyptian Libyan Desert. D. alkaliphilus AHT2 T is Gram-negative and belongs to the family Desulfobulbaceae within the Deltaproteobacteria . Here we report its genome sequence, which contains a 3.10 Mbp chromosome. Here, D. alkaliphilus AHT2 T is adapted to survive under highly alkaline and moderately saline conditions and therefore, is relevant to the biotechnology industry and life under extreme conditions. For these reasons, D. alkaliphilus AHT2 T was sequenced by the DOE Joint Genome Institute as part of the Community Science Program.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Acute Exposure to Aerosolized Nanoplastics Modulates Redox-Linked Immune Responses in Human Airway Epithelium

Micro- and nanoplastics (MPs and NPs) are pervasive environmental pollutants detected in aquatic ecosystems, with emerging evidence suggesting their presence in airborne particles generated by water body motion. Inhalation exposure to airborne MPs and NPs remains understudied despite documented links between occupational exposure to these particles and adverse respiratory outcomes, including airway inflammation, oxidative stress, and chronic respiratory diseases. This study explored the effects of acute NP exposure on a fully differentiated 3D human airway epithelial model derived from 14 healthy donors. Airway epithelium was exposed to aerosolized 50 nm polystyrene NPs at concentrations ranging from 2.5 to 2500 µg/mL for three minutes per day over three days. Functional assays revealed no significant alterations in tissue integrity, cell survival, mucociliary clearance, or cilia beat frequency, suggesting intact epithelial function post-exposure. However, cytokine and chemokine profiling identified a significant five-fold increase in CCL3 (MIP-1α), a neutrophilic chemoattractant, in NP-exposed samples compared to controls. This was corroborated by increased neutrophil chemotaxis in response to conditioned media from NP-exposed tissues, indicating a pro-inflammatory neutrophilic response. Conversely, levels of interleukins (IL-21, IL-2, IL-15), CXCL10, and TGF-β were significantly reduced, suggesting immunomodulatory effects that may impair adaptive immune responses and tissue repair mechanisms. These findings demonstrate that short-term exposure to NP-containing aerosols induces a distinct pro-inflammatory response in airway epithelium, characterized by enhanced neutrophil recruitment and reduced secretion of key immune modulators. These findings underscore the potential for aerosolized NPs to induce oxidative and inflammatory stress, raising concerns about their long-term impact on respiratory health and redox regulation.

Biochemistry & Molecular Biology↗

NASA NTRS1989

Neuromorphic learning of continuous-valued mappings in the presence of noise: Application to real-time adaptive control

The ability of feed-forward neural net architectures to learn continuous-valued mappings in the presence of noise is demonstrated in relation to parameter identification and real-time adaptive control applications. Factors and parameters influencing the learning performance of such nets in the presence of noise are identified. Their effects are discussed through a computer simulation of the Back-Error-Propagation algorithm by taking the example of the cart-pole system controlled by a nonlinear control law. Adequate sampling of the state space is found to be essential for canceling the effect of the statistical fluctuations and allowing learning to take place.

Troudet, Terry↗

NASA NTRS1994

Massively Parallel Algorithms for Real-Time Wavefront Control of a Dense Adaptive Optics System

In this paper massively parallel algorithms and architectures for real-time wavefront control of a dense adaptive optic system (SELENE) are presented. We have already shown that the computation of a near optimal control algorithm for SELENE can be reduced to the solution of a discrete Poisson equation on a regular domain. Although this represents an optimal computation, due the large size of the system and the high sampling rate requirement, the implementation of this control algorithm poses a computationally challenging problem since it demands a sustained computational throughput of the order of 10 GFlops. We develop a novel algorithm, designated as Fast Invariant Imbedding algorithm, which offers a massive degree of parallelism with simple communication and synchronization requirements. Due to these features, our algorithm is significantly more efficient than other Fast Poisson Solvers for implementation on massively parallel architectures.

massively↗

DOE OSTI2020

Safeguards Technical Objectives for Thorium Molten Salt Reactor Fuel Cycles

China, Denmark, France, India, Indonesia, the United Kingdom, and the United States, among others, are exploring commercial thorium fuel cycles for domestic power production and/or international export. For any thorium fuel cycle facilities built and/or operated in a non-nuclear weapon State with a comprehensive safeguards agreement, those facilities and any associated nuclear material would be subject to international nuclear safeguards by the International Atomic Energy Agency (IAEA). Thorium fuel cycle facilities offered for the application of safeguards under a voluntary offer agreement by a nuclear weapon State would also be subject to safeguards, if selected by the IAEA. Compared to uranium/plutonium fuel cycle facilities, thorium fuel cycle facilities are comparatively diverse from an inspection and accounting perspective, differing greatly in material type, form, and design from uranium/plutonium fuel cycle facilities and also from each other. Of these, the most complex thorium fuel cycles – and therefore likely the most challenging to the implementation of international nuclear safeguards – are those that include thorium molten salt reactors. With thorium fuel cycles approaching near-term commercial deployment timelines, it is imperative that the international nuclear safeguards community begins to think about how to adapt existing international nuclear safeguards concepts and approaches to thorium fuel cycles, as well as mitigate any gaps that may exist. This paper focuses on the development of recommended safeguards technical objectives for efficient and effective application of international nuclear safeguards measures (e.g., containment / surveillance, non-destructive assay, destructive assay, environmental sampling) to thorium molten salt reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

DeepAstroUDA: semi-supervised universal domain adaptation for cross-survey galaxy morphology classification and anomaly detection

Abstract Artificial intelligence methods show great promise in increasing the quality and speed of work with large astronomical datasets, but the high complexity of these methods leads to the extraction of dataset-specific, non-robust features. Therefore, such methods do not generalize well across multiple datasets. We present a universal domain adaptation method, DeepAstroUDA , as an approach to overcome this challenge. This algorithm performs semi-supervised domain adaptation (DA) and can be applied to datasets with different data distributions and class overlaps. Non-overlapping classes can be present in any of the two datasets (the labeled source domain, or the unlabeled target domain), and the method can even be used in the presence of unknown classes. We apply our method to three examples of galaxy morphology classification tasks of different complexities (three-class and ten-class problems), with anomaly detection: (1) datasets created after different numbers of observing years from a single survey (Legacy Survey of Space and Time mock data of one and ten years of observations); (2) data from different surveys (Sloan Digital Sky Survey (SDSS) and DECaLS); and (3) data from observing fields with different depths within one survey (wide field and Stripe 82 deep field of SDSS). For the first time, we demonstrate the successful use of DA between very discrepant observational datasets. DeepAstroUDA is capable of bridging the gap between two astronomical surveys, increasing classification accuracy in both domains (up to 40 % on the unlabeled data), and making model performance consistent across datasets. Furthermore, our method also performs well as an anomaly detection algorithm and successfully clusters unknown class samples even in the unlabeled target dataset.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Effect of Water Vapor, Temperature, and Rapid Annealing on Formamidinium Lead Triiodide Perovskite Crystallization

Perovskite-based solar cells are one of the emerging candidates for radically lower cost photovoltaics. Herein, we report on the synthesis and crystallization of organic-inorganic formamidinium lead triiodide perovskite films under controlled atmospheric and environmental conditions. Using in situ (scanning) transmission electron microscopy, we make observations of the crystallization process of these materials in nitrogen and oxygen gas with and without the presence of water vapor. Complementary planar samples were also fabricated in the presence of water vapor and characterized by in situ X-ray diffraction. Direct observations of the material structure and final morphology indicate that the exposure to water vapor results in a porous film that is metastable, regardless of the presence of argon, nitrogen, or oxygen. However, the optimal crystallization temperature of 175 °C is unperturbed across conditions. Rapid modulation about the annealing temperature of 175 °C in ±25 °C steps (150-200 °C) promotes crystallization and significantly improves the film morphology by overcoming the presence of impregnated water trapped in the material. Following this processing protocol, we demonstrate substantial growth to micron-size grains via observation inside of an environmentally controlled transmission electron microscope. Adapting this insight from our in situ microscopy, we are able to provide an informed materials protocol to control the structure and morphology of these organic-inorganic semiconductors, which is readily applicable to benchtop device growth strategies.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Using Skyline to Analyze Data-Containing Liquid Chromatography, Ion Mobility Spectrometry, and Mass Spectrometry Dimensions

Recent advances in ion mobility spectrometry (IMS) have illustrated its power in determining the structural characteristics of a molecule, especially when coupled with other separations dimensions such as liquid chromatography (LC) and mass spectrometry (MS). However, these three separation techniques together greatly complicate data analyses, making better informatics tools essential for assessing the resulting data. In this manuscript, Skyline was adapted to analyze LC-IMS-CID-MS data from numerous instrument vendor datasets and determine the effect of adding the IMS dimension into the normal LC-MS molecular pipeline. For the initial evaluation, a tryptic digest of bovine serum albumin (BSA) was spiked into a yeast protein digest at seven different concentrations, and Skyline was able to rapidly analyze the MS and CID-MS data for 38 of the BSA peptides. Calibration curves for the precursor and fragment ions were assessed with and without the IMS dimension. In all cases, addition of the IMS dimension removed noise from co-eluting peptides with close m/z values, resulting in calibration curves with greater linearity and lower detection limits. This study presents an important informatics development since to date LC-IMS-CID-MS data from the different instrument vendors is often assessed manually and cannot be analyzed quickly. Because these evaluations require days for the analysis of only a few target molecules in a limited number of samples, it is unfeasible to evaluate hundreds of targets in numerous samples. Thus, this study showcases Skyline’s ability to work with the multidimensional LC-IMS-CID-MS data and provide biological and environmental insights rapidly. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Block Design with Common Reference Samples Enables Robust Large-Scale Label-Free Quantitative Proteome Profiling

Label-free quantitative proteomics has become an increasingly popular tool for profiling global protein abundances. However, one major weakness is the potential performance drift of the LC-MS platform over time, which in turn limits its utility for analyzing large-scale sample sets. To address this, in this work we introduce an experimental and data analysis scheme based on a block-design with common controls within each block for enabling LC-MS-based large-scale label-free quantification. In this scheme, a large number of samples (e.g., >100 samples) are analyzed in smaller, and more manageable blocks, minimizing instrument drift and variability within a block. Furthermore, each designated block also contains common controls (or reference) samples for normalization within and across blocks. We demonstrated the effectiveness of this method by profiling the proteome response of human macrophage THP-1 cells to 11 engineered nanomaterials (ENMs) at two different doses. A total of 116 samples were analyzed in six blocks, yielding an average coverage of 4500 proteins per sample. The data revealed consistent quantification of proteins across all six blocks, as shown by highly stable quantification of house-keeping proteins in all samples and high levels of quantification correlation among samples from different blocks. The data also demonstrated that label-free quantification is robust and accurate enough to quantify even very subtle abundance changes as well as large fold-changes without potential ratio compression as often encountered with isobaric labeling. Our streamlined workflow is easy to implement and can be readily adapted to other large cohort studies for reproducible label-free proteome quantification.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2014

Note: Versatile sample stick for neutron scattering experiments in high electric fields

We present a versatile high voltage sample stick that fits into all cryomagnets and standard cryostats at the Swiss Spallation Neutron Source, Paul Scherrer Institut, and which provides a low effort route to neutron scattering experiments that combine electric field with low temperature and magnetic field. The stick allows for voltages up to 5 kV and can be easily adapted for different scattering geometries. We discuss the design consideration and thermal behavior of the stick, and give one example to showcase the abilities of the device.

07 ISOTOPE AND RADIATION SOURCES↗

NASA NTRS1996

Microstructural Preparation and Examination of Polymer-Matrix Composites

Adapting procedures widely used in the metallographic characterization of metals and alloys, the microstructural preparation and examination of three polymer-matrix composites (PMC's) is described. The materials investigated contained either hollow ceramic filler particles or woven, continuous carbon/graphite fibers. Since the two particulate composites were considered to be isotropic, only one sample orientation was prepared. For the fiber composite, both longitudinal and planar orientations were studied. Once prepared, the samples were examined using reflected light microscopy. A number of microstructural features were evaluated qualitatively, including porosity and cracks, filler-matrix interfacial bonding, filler particle characteristics (shape, size, size distribution, and loading variation) and fiber characteristics (orientation, packing variation, and discontinuities).

Elban, Wayne L.↗

NASA NTRS2002

Development and Flight Testing of an Adaptive Vehicle Health-Monitoring Architecture

On going development and testing of an adaptable vehicle health-monitoring architecture is presented. The architecture is being developed for a fleet of vehicles. It has three operational levels: one or more remote data acquisition units located throughout the vehicle; a command and control unit located within the vehicle, and, a terminal collection unit to collect analysis results from all vehicles. Each level is capable of performing autonomous analysis with a trained expert system. The expert system is parameterized, which makes it adaptable to be trained to both a user's subject reasoning and existing quantitative analytic tools. Communication between all levels is done with wireless radio frequency interfaces. The remote data acquisition unit has an eight channel programmable digital interface that allows the user discretion for choosing type of sensors; number of sensors, sensor sampling rate and sampling duration for each sensor. The architecture provides framework for a tributary analysis. All measurements at the lowest operational level are reduced to provide analysis results necessary to gauge changes from established baselines. These are then collected at the next level to identify any global trends or common features from the prior level. This process is repeated until the results are reduced at the highest operational level. In the framework, only analysis results are forwarded to the next level to reduce telemetry congestion. The system's remote data acquisition hardware and non-analysis software have been flight tested on the NASA Langley B757's main landing gear. The flight tests were performed to validate the following: the wireless radio frequency communication capabilities of the system, the hardware design, command and control; software operation and, data acquisition, storage and retrieval.

Woodard, Stanley E.↗

NASA NTRS2013

Plasma Cytokine Concentrations Indicate In-vivo Hormonal Regulation of Immunity is Altered During Long-Duration Spaceflight

Background: Aspects of immune system dysregulation associated with long‐duration spaceflight have yet to be fully characterized, and may represent a clinical risk to crewmembers during deep space missions. Plasma cytokine concentration may serve as an indicator of in vivo physiological changes or immune system mobilization. Methods: The plasma concentrations of 22 cytokines were monitored in 28 astronauts during long‐duration spaceflight onboard the International Space Station. Blood samples were collected three times before flight, 3‐5 times during flight (depending on mission duration), at landing and 30 days post‐landing. Analysis was performed by bead array immunoassay. Results: With few exceptions, minimal detectable mean plasma levels (<10 pg/ml) were observed at baseline (launch minus 180) for innate inflammatory cytokines or adaptive regulatory cytokines, however IL‐1ra and several chemokines were constitutively present. An increase in the plasma concentration IL‐8, IL‐1ra, Tpo, CCL4, CXCL5, TNF(alpha), GM‐CSF and VEGF was observed associated with spaceflight. Significant post‐flight increases were observed for IL‐6 and CCL2. No significant alterations were observed during or following spaceflight for adaptive/T‐regulatory cytokines (IL‐2, IFN(gamma), IL‐17, IL4, IL‐5, IL‐10). Conclusions: This pattern of cytokine dysregulation suggests multiple physiological adaptations persist during flight, including inflammation, leukocyte recruitment, angiogenesis and thrombocyte regulation.

Crician, Brian E.↗