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At least 1,711 records · Page 95

Super-Resolution Approaches in Three-Dimensions for Classification and Screening of Commercial-Off-The-Shelf Components

X-ray computed tomography is generally a primary step in characterization of defective electronic components, but is generally too slow to screen large lots of components. Super-resolution imaging approaches, in which higher-resolution data is inferred from lower-resolution images, have the potential to substantially reduce collection times for data volumes accessible via x-ray computed tomography. Here we seek to advance existing two-dimensional super-resolution approaches directly to three-dimensional computed tomography data. Multiple scan resolutions over a half order of magnitude of resolution were collected for four classes of commercial electronic components to serve as training data for a deep-learning, super-resolution network. A modular python framework for three-dimensional super-resolution of computed tomography data has been developed and trained over multiple classes of electronic components. Initial training and testing demonstrate the vast promise for these approaches, which have the potential for more than an order of magnitude reduction in collection time for electronic component screening.

47 OTHER INSTRUMENTATION↗

DeePKS + ABACUS as a Bridge between Expensive Quantum Mechanical Models and Machine Learning Potentials

Recently, the development of machine learning (ML) potentials has made it possible to perform large-scale and long-time molecular simulations with the accuracy of quantum mechanical (QM) models. However, for different levels of QM methods, such as density functional theory (DFT) at the meta-GGA level and/or with exact exchange, quantum Monte Carlo, etc., generating a sufficient amount of data for training an ML potential has remained computationally challenging due to their high cost. In this work, we demonstrate that this issue can be largely alleviated with Deep Kohn–Sham (DeePKS), an ML-based DFT model. DeePKS employs a computationally efficient neural network-based functional model to construct a correction term added upon a cheap DFT model. Upon training, DeePKS offers closely matched energies and forces compared with high-level QM method, but the number of training data required is orders of magnitude less than that required for training a reliable ML potential. As such, DeePKS can serve as a bridge between expensive QM models and ML potentials: one can generate a decent amount of high-accuracy QM data to train a DeePKS model and then use the DeePKS model to label a much larger amount of configurations to train an ML potential. Further, this scheme for periodic systems is implemented in a DFT package ABACUS, which is open source and ready for use in various applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Accelerating Nuclear-Integrated Data Centers in the USA: SWOT Analysis, Power-Thermal Management Strategies, and Industrial-Scale Demonstration and Potential Deployment

Driven by the growth in digital services, cloud computing, AI, and manufacturing, data centers face rising energy demands that challenge traditional power sources and cooling efficiency. This study explores using nuclear power to meet these demands, focusing on accelerated reactor technology deployment and highlighting needs such as N+1/N+2 power supplies and integrated power-thermal management. A SWOT analysis addresses grid connectivity, reactors, and site selection, particularly DOE sites. Reactor technology demonstration and deployment could be accelerated by leveraging test facilities such as MARVEL, MAGNET, TED, FAS, DOME, LOTUS, ATR, Energy System Proving Grounds, and upcoming Energy Launch Pads, along with modeling and simulation tools such as RELAP5, MOOSE, VERA, RAVEN, and FORCE. The potential power and thermal management options, including various cooling technologies, waste-heat utilization, and an industrial-scale demonstration plan, aim to accelerate the integration of nuclear power and data centers in the USA, while emphasizing community and stakeholder engagement and synergistic efforts.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Application of IRTAM to Support ISS Program Safety

The International Space Station (ISS) orbits near the F-peak of the ionosphere (approximately 400 km altitude). Generally, satellites orbiting at this altitude would have a floating potential (FP) of approximately -1 V due to the electron temperature (Te). However, the ISS has 8 large negatively grounded 160 V solar array wings (SAW) that collect a significant electron current from the ionosphere. This current drives the ISS FP much more negative during insolation and is highly dependent on the electron density (Ne). Also, due to the size of the ISS, magnetic inductance caused by the geomagnetic field produces a delta potential up to 40 V across the truss, possibly producing positive potentials. During Extravehicular Activity (EVA) the negative FP can lead to an arcing hazard when it exceeds -45.5 V, and the positive FP can produce a DC current high enough to stimulate the astronaut's muscles and also cause a hazard. Data collected from the Floating Potential Monitoring Unit (FPMU) have shown that the probability of either of these hazards occurring during times with quiet to moderately disturbed geomagnetic activity is low enough to no longer be considered a risk. However, a study of the ionosphere Ne during severe geomagnetic storm activity has shown that the Ne can be enhanced by a factor of 6 in the ISS orbit. As a result, the ISS Safety Review Panel (SRP) requires that ionospheric conditions be monitored using the FPMU in conjunction with the ISS Plasma Interaction Model (PIM) to determine if a severe geomagnetic storm could result in a plasma environment that could produce a hazard. A 'Real-Time' plasma hazard assessment process was developed to support ISS Program real-time decision making providing constraint relief information for EVAs planning and operations. This process incorporates 'real time' ionospheric conditions, ISS solar arrays' orientation, ISS flight attitude, and where the EVA will be performed on the ISS. This assessment requires real time data that is presently provided by the FPMU including ISS floating potential, along with ionospheric Ne and Te, in order to determine the present environment. Once the present environment conditions are known to be either above, below, or near the current IRI values, the IRI is used to forecast what the environment could become in the event of a severe geomagnetic storm. If the FPMU should fail, the Space Environments team needs another source of data which is utilized to support a short-term forecast for EVAs. The IRI Real-Time Assimilative Mapping (IRTAM) model is an ionospheric model that uses real time measurements from approximately 70 digisondes to produce foF2 and hmF2 global maps in 15 minute cadence. The Boeing Space Environments team has used the IRI coefficients produced in IRTAM to calculate the Ne along the ISS orbital track. The results of the IRTAM model have been compared to FPMU measurements and show excellent agreement (figure 1). IRTAM has been identified as a potential FPMU back-up system will be used as a backup for the FPMU to support the ISS Program following completion of an FPMU/IRTAM validation campaign.

Hartman, William A.↗

Physical Parameters of Space Mission Asteroid Targets

Ground-based characterization of asteroids that are planned or potential targets of space missions provides important data on their physical parameters and properties. Knowledge of the properties of mission targets is important especially during mission preparation and planning, as it serves to select best or suitable targets for specific purpose of a given mission, to prepare mission plans, to constrain possible mission scenarios, and to design mission experiments. Such characterization efforts may be particularly critical for flyby missions that take only limited data during the high-speed flybys of their target asteroids, but they also provide very crucial data for targets of rendezvous missions. Moreover, long-term observations taken from Earth also allows the modelling of, or constraining, processes acting on the asteroids over extended time scales. Over the past years and decades we have obtained rich data on physical parameters of 82 asteroids that are planned or potential targets of space missions. Our primary observing technique is time-resolved (lightcurve) photometry, but we use also data obtained with other techniques, such as spectroscopy, thermal or radar observations. 15 of the 82 characterized asteroids are planned or possible targets of several space missions that are in flight or preparation, such as ESA’s Hera, RAMSES and PRIAMOS, NASA’s OSIRIS-APEX, JAXA’s Hayabusa2#, DESTINY+ and Next Generation Sample Return (NGSR), the Emirates Mission to Asteroids (EMA), and Karman+’s High Frontier, but we have also characterized 67 asteroids that are potential targets of space missions for their low delta-V’s and were announced as being “of interest to NASA” in the Small-Bodies-Observations- NASA mailing list or listed on the NHATS page of “Accessible NEAs”. The sample of asteroid targets span 3 orders of magnitude in size, with absolute magnitudes H from 12.57 to 26.8, corresponding to diameters from about 10 m to about 10 km. The sample contains a variety of taxonomic types and physically or dynamically interesting objects. Among them, we have identified 5 binary asteroids and 20 tumblers (i.e., asteroids in excited, non-principal axis rotation states). Rotation periods of the characterized asteroids range from 1.45 min to 280 h, reflecting diversity of their properties and formation/evolution paths. We will present an overview of the data set and highlight several representative cases.

Petr Pravec↗

Forecasting influenza-like illness dynamics for military populations using neural networks and social media

This work is the first to take advantage of recurrent neural networks to predict influenza-like-illness (ILI) dynamics from various linguistic signals extracted from social media data. Unlike other approaches that rely on timeseries analysis of historical ILI data [1, 2] and the state-of-the-art machine learning models [3, 4], we build and evaluate the predictive power of Long Short Term Memory (LSTMs) architectures capable of nowcasting (predicting in \real-time") and forecasting (predicting the future) ILI dynamics in the 2011 { 2014 influenza seasons. To build our models we integrate information people post in social media e.g., topics, stylistic and syntactic patterns, emotions and opinions, and communication behavior. We then quantitatively evaluate the predictive power of different social media signals and contrast the performance of the-state-of-the-art regression models with neural networks. Finally, we combine ILI and social media signals to build joint neural network models for ILI dynamics prediction. Unlike the majority of the existing work, we specifically focus on developing models for local rather than national ILI surveillance [1], specifically for military rather than general populations [3] in 26 U.S. and six international locations. Our approach demonstrates several advantages: (a) Neural network models learned from social media data yield the best performance compared to previously used regression models. (b) Previously under-explored language and communication behavior features are more predictive of ILI dynamics than syntactic and stylistic signals expressed in social media. (c) Neural network models learned exclusively from social media signals yield comparable or better performance to the models learned from ILI historical data, thus, signals from social media can be potentially used to accurately forecast ILI dynamics for the regions where ILI historical data is not available. (d) Neural network models learned from combined ILI and social media signals significantly outperform models that rely solely on ILI historical data, which adds to a great potential of alternative public sources for ILI dynamics prediction. (e) Location-specific models outperform previously used location-independent models e.g., U.S. only. (f) Prediction results significantly vary across geolocations depending on the amount of social media data available and ILI activity patterns.

60 APPLIED LIFE SCIENCES↗

Measurement of aerodynamic roughness using radar backscatter over vegetated surfaces

The importance of the measurement of wind fields is discussed. Wind regime data can be used to infer the amount and type of wind induced (aerolian) transport of sand and dust, or to establish global circulation models, for example on other planets. Since local measurements are costly and often impossible, it is desired to infer such data from remotely sensed information. A potential mechanism for remotely inferring the wind regime by using synthetic aperture radar data to describe the roughness of the surface is described. A project to estimate the practicality of using such a mechanism is described. An experiment that extends the mechanism to vegetated sites, where the goal is to measure potential for erosion, is reported.

Wall, S. D.↗

Uncertainty Quantification and Global Sensitivity Analysis of Subsurface Flow Parameters to Gravimetric Variations During Pumping Tests in Unconfined Aquifers

We study the contribution of typically uncertain subsurface flow parameters to gravity changes that can be recorded during pumping tests in unconfined aquifers. We do so in the framework of a Global Sensitivity Analysis and quantify the effects of uncertainty of such parameters on the first four statistical moments of the probability distribution of gravimetric variations induced by the operation of the well. System parameters are grouped into two main categories, respectively, governing groundwater flow in the unsaturated and saturated portions of the domain. We ground our work on the three-dimensional analytical model proposed by Mishra and Neuman (2011), which fully takes into account the richness of the physical process taking place across the unsaturated and saturated zones and storage effects in a finite radius pumping well. The relative influence of model parameter uncertainties on drawdown, moisture content, and gravity changes are quantified through (a) the Sobol' indices, derived from a classical decomposition of variance and (b) recently developed indices quantifying the relative contribution of each uncertain model parameter to the (ensemble) mean, skewness, and kurtosis of the model output. Our results document (i) the importance of the effects of the parameters governing the unsaturated flow dynamics on the mean and variance of local drawdown and gravity changes; (ii) the marked sensitivity (as expressed in terms of the statistical moments analyzed) of gravity changes to the employed water retention curve model parameter, specific yield, and storage, and (iii) the influential role of hydraulic conductivity of the unsaturated and saturated zones to the skewness and kurtosis of gravimetric variation distributions. The observed temporal dynamics of the strength of the relative contribution of system parameters to gravimetric variations suggest that gravity data have a clear potential to provide useful information for estimating the key hydraulic parameters of the system.

54 ENVIRONMENTAL SCIENCES↗

Ambipolar Electrochemistry of Pre‐Intercalated Ti 3 C 2 T x MXene in Ionic Liquid Electrolyte

Abstract Cation intercalation with or without redox remains the dominant charge storage mechanism for two‐dimensional (2D) Ti 3 C 2 T x MXene. Anion‐based charge storage remains unexplored due to intrinsic negative surface charge of MXenes preventing spontaneous intercalation of anions and irreversible oxidation of Ti at anodic potentials in aqueous electrolytes. In this work, we report on the ambipolar electrochemical behavior of the Ti 3 C 2 T x in ionic liquid electrolyte over a 2.5 V electrochemically stable window. The experiments are conducted on a thin Ti 3 C 2 T x film current collector coated with an electroactive layer of small flakes (∼150 nm) of Ti 3 C 2 T x pre‐intercalated with 1‐ethyl‐3‐methylimidazolium bis‐(trifluoromethylsulfonyl)‐imide (EMIM‐TFSI) ionic liquid. Couples of redox peaks with a very small potential separation during the voltage sweep are observed at high negative (−0.75 V vs. Ag wire) and high positive (+0.75 V vs. Ag wire) potentials. Our experimental electrochemical data combined with density functional theory (DFT) calculations suggest feasibility of pseudo‐intercalation of TFSI anions between Ti 3 C 2 T x flakes. This study provides a pathway for elucidating anion intercalation for different MXene chemistries in solvent‐free electrolytes, which can lead to development of MXene based energy storage devices with improved performance.

Electrochemistry↗

From Grain to Floodplain: Evaluating heterogeneity of floodplain hydrostatigraphy using sedimentology, geophysics, and remote sensing

Stratigraphy is a fundamental component of floodplain heterogeneity and hydraulic conductivity and connectivity of alluvial aquifers, which affect hydrologic processes such as groundwater flow and hyporheic exchange. Watershed–scale hydrological models commonly simplify the sedimentology and stratigraphy of floodplains, neglecting natural floodplain heterogeneity and anisotropy. This study, conducted in the upper reach of the East River in the East River Basin, Colorado, USA, combines point–, meander–, and floodplain–scale data to determine key features of alluvial aquifers important for estimating hydrologic processes. We compare stratigraphy of two meanders with disparate geometries to explore floodplain heterogeneity and connectivity controls on flow and transport. Meander shape, orientation, and internal stratigraphy affected residence time estimates of laterally exchanged hyporheic water. Although the two meanders share a sediment source, vegetation, and climate, their divergent river migration histories resulted in contrasting meander hydrofacies. In turn, the extent and orientation of these elements controlled the effective hydraulic conductivity and, ultimately, estimates of groundwater transport and hyporheic residence times. Additionally, the meanders’ orientation relative to the valley gradient impacted the hydraulic gradient across the meanders—a key control of groundwater velocity. In conclusion, we combine our field data with remotely sensed data and introduce a potential approach to estimate key hydrostratigraphic packages across floodplains. Prospective applications include contaminant transport studies, hyporheic models, and watershed models.

58 GEOSCIENCES↗

Novel Segregated Solid Propulsion System with Separately Stored Fuel and Oxidizer

Abstract The development and experimentation of a solid propulsion concept consisting of separate hydrogen‐rich solid propellant and solid oxidizer grains is presented. This system consists of an extremely fuel‐rich solid propellant, which, once ignited, undergoes a self‐sustaining decomposition to release fuel‐rich product gases, which are particularly rich in hydrogen gas. These relatively high‐temperature gases subsequently react with a solid oxidizer grain stored downstream. Progress in high‐nitrogen materials has allowed for the synthesis of fuel‐rich compounds that can store significant amounts of hydrogen, with little or no bound oxygen. With these new developments in propellant chemistry, a unique segregated propulsion system has been developed, creating an all‐solid propulsion system that combusts analogously to a reverse hybrid rocket system. Because of the physical separation of fuel and oxidizer, a higher level of safety is achieved which concurrently allows for the utilization of higher energy ingredients without the penalty of higher sensitivity. Theoretical performance calculations and experimental data have shown the potential for this system to compete with existing composite rocket propellants while having significant benefits in terms of safety, toxicity, and mission space. This paper presents a detailed overview of the conception, development, and testing of this propulsion system.

42 ENGINEERING↗

Phase transitions from the fifth dimension

We study the cosmological transition of 5D warped compactifications, from the high-temperature black-brane phase to the low-temperature Randall-Sundrum I phase. The transition proceeds via percolation of bubbles of IR-brane nucleating from the black-brane horizon. The violent bubble dynamics can be a powerful source of observable stochastic gravitational waves. While bubble nucleation is non-perturbative in 5D gravity, it is amenable to semiclassical treatment in terms of a “bounce” configuration interpolating between the two phases. We demonstrate how such a bounce configuration can be smooth enough to maintain 5D effective field theory control, and how a simple ansatz for it places a rigorous lower-bound on the transition rate in the thin-wall regime, and gives plausible estimates more generally. When applied to the Hierarchy Problem, the minimal Goldberger-Wise stabilization of the warped throat leads to a slow transition with significant supercooling. We demonstrate that a simple generalization of the Goldberger-Wise potential modifies the IR-brane dynamics so that the transition completes more promptly. Supercooling determines the dilution of any (dark) matter abundances generated before the transition, potentially at odds with data, while the prompter transition resolves such tensions. We discuss the impact of the different possibilities on the strength of the gravitational wave signals. Via AdS/CFT duality the warped transition gives a theoretically tractable holographic description of the 4D Composite Higgs (de)confinement transition. Our generalization of the Goldberger-Wise mechanism is dual to, and concretely models, our earlier proposal in which the composite dynamics is governed by separate UV and IR RG fixed points. The smooth 5D bounce configuration we introduce complements the 4D dilaton/radion dominance derivation presented in our earlier work.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Bayesian merging of numerical modeling and remote sensing for saltwater intrusion quantification in the Vietnamese Mekong Delta

Saltwater intrusion has become one of the most concerning issues in the Vietnamese Mekong Delta (VMD) due to its increasing impacts on agriculture and food security of Vietnam. Reliable estimation of salinity plays a crucial role to mitigate the impacts of saltwater intrusion. Here, this study developed a hybrid technique that merges satellite imagery with numerical simulations to improve the estimation of salinity in the VMD. The salinity derived from Landsat images and by numerical simulations was fused using the Bayesian inference technique. The results indicate that our technique significantly reduces the uncertainties and improves the accuracy of salinity estimates. The Nash–Sutcliffe coefficient is 0.74, which is much higher than that of numerical simulation (0.63) and Landsat estimation (0.6). The correlation coefficient between the ensemble and measured salinity is relatively high (0.88). The variance of the ensemble salinity errors (5.0 ppt 2 ) is lower than that of Landsat estimation (10.4 ppt 2 ) and numerical simulations (9.6 ppt 2 ). The proposed approach shows a great potential to combine multiple data sources of a variable of interest to improve its accuracy and reliability wherever these data are available.

54 ENVIRONMENTAL SCIENCES↗

Exploring the use of thorium isotope compositions and concentrations as nuclear forensic signatures for uranium ore concentrates

This interlaboratory study measured thorium concentrations and isotope compositions in uranium ore concentrates from different geographical locations to examine whether thorium impurities may be useful forensic signatures for uranium ore concentrates found out of regulatory control. Measured 230 Th/ 232 Th in fifteen uranium ore concentrates record over three orders of magnitude of compositional variation. Results demonstrate that 230 Th/ 232 Th used in combination with U/Th ratios resulted in a unique signature for individual uranium ore concentrates from different processing locations. Data presented here suggest potential for 230 Th/ 232 Th and U/Th to be used as comparative signatures to investigate the provenance of seized uranium ore concentrates.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Quantifying metal-binding specificity of Cc NikZ-II from Clostridium carboxidivorans in the presence of competing metal ions

Many proteins bind transition metal ions as cofactors to carry out their biological functions. Despite binding affinities for divalent transition metal ions being predominantly dictated by the Irving-Williams series for wild-type proteins, in vivo metal ion binding specificity is ensured by intracellular mechanisms that regulate free metal ion concentrations. However, a growing area of biotechnology research considers the use of metal-binding proteins in vitro to purify specific metal ions from wastewater, where specificity is dictated by the protein's metal binding affinities. A goal of metalloprotein engineering is to modulate these affinities to improve a protein's specificity towards a particular metal; however, the quantitative relationship between the affinities and the equilibrium metal-bound protein fractions depends on the underlying binding mechanisms. Here we demonstrate a high-throughput intrinsic tryptophan fluorescence quenching method to validate binding models in multi-metal solutions for CcNikZ-II, a nickel-binding protein from Clostridium carboxidivorans. Using our validated models, we quantify the relationship between binding affinity and specificity in different classes of metal-binding models for CcNikZ-II. In conclusion, we further illustrate the potential relevance of data-informed models to predicting engineering targets for improved specificity.

59 BASIC BIOLOGICAL SCIENCES↗

Atmospheric pion, kaon, and muon fluxes for sub-orbital experiments

Cosmic rays interacting with the Earth's atmosphere generate extensive air showers, which produce Cherenkov, fluorescence and radio emissions. These emissions are key signatures for detection by ground-based, sub-orbital, and satellite-based telescopes aiming to study high energy cosmic ray and neutrino events. However, detectors operating at ground and balloon altitudes are also exposed to a background of atmospheric charged particles, primarily pions, kaons, and muons, that can mimic or obscure the signals from astrophysical sources. In this work, we use coupled cascade equations to calculate the atmospheric pion, kaon and muon fluxes reaching detectors at various altitudes. Our analysis focuses on energies above 10 GeV, where the influence of the Earth's magnetic field on particle trajectories is minimal. We provide angular and energy-resolved flux estimates and discuss their relevance as background for extensive air shower detection. Furthermore, our results are potentially relevant for interpreting data from current and future balloon-borne experiments such as EUSO-SPB2 and for refining trigger and veto strategies in Cherenkov and fluorescence telescopes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Pyruvate dehydrogenase kinase 4 mediates lipogenesis and contributes to the pathogenesis of nonalcoholic steatohepatitis

Highlights: • The expression of PDK4 is increased in both NAFLD human and mice. • Pdk4 deficiency results in impaired glucose and lipid metabolism in the liver. • Pdk4 deficiency ameliorated hepatic steatosis in NASH mice. • Multiple hepatic signaling pathways are altered by Pdk4 deficiency. Nonalcoholic steatohepatitis (NASH) is a progressive disease and poses a high risk of severe liver damage. However, the pathogenesis of NASH is still unclear. Accumulation of lipid droplets and insulin resistance is the hallmark of NASH. Pyruvate dehydrogenase kinase isoenzyme 4 (PDK4) plays key role in glucose metabolism via regulating the activity of pyruvate dehydrogenase complex (PDC). Here, we demonstrated a novel of PDK4 in NASH by regulating hepatic steatosis and insulin signaling pathway in methionine and choline deficient (MCD) diet induced NASH model. Hepatic PDK4 levels were highly induced in human patients with NASH and MCD diet fed mice, as well as in hepatocytes treated with oleic acid. The glucose and lipid metabolism were impaired in Pdk4{sup −/−} mice. Pdk4 deficiency ameliorated the hepatic steatosis significantly in NASH mice. Pdk4{sup −/−}-MCD mice had reduced liver weights and triglyceride (TG) levels. And Pdk4 deficiency dramatically reduced the expression of genes related to fatty acid uptake, synthesis and gluconeogenesis. In addition, elevated phosphorylated AMPK (p-AMPK), p-SAPK/JNK and diminished p-ERK, p-P38, p-Akt and p-mTOR/p-4EBP1 proteins were observed. In conclusion, our data indicated that PDK4 potentially contributes to the hepatic steatosis in NASH via regulating several signaling pathway and PDK4 may be a new therapeutic strategy against NAFLD.

60 APPLIED LIFE SCIENCES↗