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At least 433 records · Page 24

On the possibility to detect multipolar order in URu 2 Si 2 by the electric quadrupolar transition of resonant elastic x-ray scattering

Resonant elastic x-ray scattering is a powerful technique for measuring multipolar order parameters. In this paper, we theoretically and experimentally study the possibility of using this technique to detect the proposed multipolar order parameters in URu 2 Si 2 at the U- L 3 edge with the electric quadrupolar transition. Based on an atomic model, we calculate the azimuthal dependence of the quadrupolar transition at the U- L 3 edge. Our results illustrate the potential of this technique for distinguishing different multipolar order parameters. We then perform experiments on ultraclean single crystals of URu 2 Si 2 at the U- L 3 edge to search for the predicted signal, but do not detect any indications of multipolar moments within the experimental uncertainty. We also theoretically estimate the orders of magnitude of the cross section and the expected count rate of the quadrupolar transition and compare them to the dipolar transitions at the U- M 4 and U- L 3 edges, clarifying the difficulty in detecting higher order multipolar order parameters in URu 2 Si 2 in the current experimental setup.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Long Duration Exposure Facility experiment M0003 deintegration observation data base

The four trays (2 leading edge and 2 trailing edge) of the M0003 materials experiment on the Long Duration Exposure Facility (LDEF) contained 1274 samples from 20 subexperiments. The complete sample complement represented a broad range of materials, including thin film optical coatings, paints, polymer sheets and tapes, adhesives, and composites, for use in various spacecraft applications, including thermal control, structures, optics, and solar power. Most subexperiments contained sets of samples exposed on both the leading and trailing edge trays of LDEF. Each individual sample was examined by high resolution optical microscope during the deintegration of the subexperiments from the M0003 trays. Observations of the post-flight condition of the samples made during this examination were recorded in a computer data base. The deintegration observation data base is available to requesters on floppy disk in 4th Dimension for the Macintosh format. Over 3,000 color macrographs and photomicrographs were shot to complement the observation records and to document the condition of the individual samples and of the M0003 trays. The photographs provide a visual comparison of the response of materials in leading and trailing edge LDEF environments. The Aerospace Corporate Archives is distributing photographs of the samples and hard copies of the database records to the general public upon request. Information on obtaining copies of the data base disks and for ordering photographs and records of specific samples or materials are given.

Gyetvay, S. R.↗

Blade and airfoil damping configurations

The present embodiments set forth a blade including an airfoil, the airfoil including a tip cap, a pressure sidewall and a suction sidewall extending axially between corresponding leading and trailing edges and radially between the base and the tip cap. The blade, including the airfoil and base, being formed in at least two airfoil parts, each of the two airfoil parts including contacting edges engaging each other respective contacting edges, the contacting edges defining a joint for preloading each of the at least two parts with each other and with the base. The at least two airfoil parts forming the airfoil being retained to each other by an interference fit at the joint. The interference fit providing frictional damping of vibrations in the blade during blade operation.

Hart, Andrew Clifford↗

A coupled ice-ocean model of upwelling in the marginal ice zone

A dynamical coupled ice-ocean numerical model for the marginal ice zone (MIZ) is suggested and used to study upwelling dynamics in the MIZ. The nonlinear sea ice model has a variable ice concentration and includes internal ice stress. The model is forced by stresses on the air/ocean and air/ice surfaces. The main coupling between the ice and the ocean is in the form of an interfacial stress on the ice/ocean interface. The ocean model is a linear reduced gravity model. The wind stress exerted by the atmosphere on the ocean is proportional to the fraction of open water, while the interfacial stress ice/ocean is proportional to the concentration of ice. A new mechanism for ice edge upwelling is suggested based on a geostrophic equilibrium solution for the sea ice medium. The upwelling reported in previous models invoking a stationary ice cover is shown to be replaced by a weak downwelling due to the ice motion. Most of the upwelling dynamics can be understood by analysis of the divergence of the across ice edge upper ocean transport. On the basis of numerical model, an analytical model is suggested that reproduces most of the upwelling dynamics of the more complex numerical model.

Roed, L. P.↗

Vacuum sealing flange

Flange technologies are described for a flange comprising a first and second side. Each side may include a knife edge surface disposed circumferentially around a base surface and a periphery section disposed around the knife edge surface. The knife edge surface and the periphery section are effective to define grooves therebetween. The flange may include an alloy with a relatively high thermal conductivity and yield strength. The flange may include water channels to remove heat.

Sharma, Sushil Kumar↗

Localizing resonant magnetic perturbations for edge localized mode control in KSTAR

An external 3D magnetic perturbation typically drives a resonant response at the rational surfaces from the core to the edge of tokamak plasmas, due to strong mode coupling and amplification. In this paper, we present a method to isolate the edge from core resonant fields using the ideal perturbed equilibrium code and to design an edge-localized resonant magnetic perturbation (RMP) for effective edge localized mode (ELM) control. A robust feature of the edge-localized RMP is the curtailed response to the field at the low-field-side (LFS) midplane, as opposed to typical RMPs which strongly resonate with the LFS fields. This emphasizes the importance of off-midplane coils to improve ELM control without provoking a large core response that could lead to devastating instabilities. The conceptual design of new ELM control coils based on the edge-localized RMP in KSTAR shows how this new insight can be utilized to enhance the efficiency of our ELM suppression capabilities. Simple window-pane coils matching the edge-localized resonant mode structure substantially expand in the ELM suppression window beyond the existing coil. Further optimization using the flexible optimized coils using space-curves code leads to additional enhancement in the edge-localized control.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Wind tunnel test of the 0.015-scale Rockwell International space shuttle vehicle orbiter in the Ames 6 by 6 foot supersonic wind tunnel

Experimental investigations were performed in a 6- by 6-Foot Supersonic wind tunnel on a 0.015-scale model of the Rockwell International space shuttle vehicle (SSV) 2A orbiter. The purpose of the test was to investigate the longitudinal and lateral-directional characteristics of the vehicle. In addition, hinge moments were measured on the rudder and elevons. Buffet onset was investigated using wing trailing edge pressures and a strain gauge instrumented panel mounted in the wing. The model was tested through a Mach range from 0.6 to 2.0 at a constant unit Reynolds number of 2.5 million. Pitch runs were made at angles of attack from minus 2 deg to +26 deg with beta = 0 deg and 5 deg; yaw runs were made in the range from minus 5 deg to 10 deg of sideslip at angles of attack of 0 deg and 10 deg. Static pressures were measured at the fuselage base and the trailing edges of the wing and rudder. Boundary layer transition was fixed for some runs using distributed roughness strips.

Milam, M. D.↗

First Astronomical Use Of Multiplexed Transition Edge Bolometers

We present performance results based on the first astronomical use of multiplexed superconducting bolometers. The Fabry-Perot Interferometer Bolometer Research Experiment (FIBRE) is a broadband submillimeter spectrometer that achieved first light in June 2001 at the Caltech Submillimeter Observatory (CSO). FIBRE's detectors are superconducting transition edge sensor (TES) bolometers read out by a SQUID multiplexer. The Fabry-Perot uses a low resolution grating to order sort the incoming light. A linear bolometer array consisting of 16 elements detects this dispersed light, capturing five orders simultaneously from one position on the sky. With tuning of the Fabry-Perot over one free spectral range, a spectrum covering delta-lamda/lamda = 1/7 at a resolution of delta-lamda/lamda = 1/1200 can be acquired. This spectral resolution is sufficient to resolve doppler broadened line emission from external galaxies. FIBRE operates in the 350 micrometer and 450 micrometer bands. These bands cover line emission from the important PDR tracers neutral carbon [CI] and carbon monoxide (CO). We have verified that the multiplexed bolometers are photon noise limited even with the low power present in moderate resolution spectrometry.

Benford, D. J.↗

Node-degree aware edge sampling mitigates inflated classification performance in biomedical random walk-based graph representation learning

Motivation: Graph representation learning is a family of related approaches that learn low-dimensional vector representations of nodes and other graph elements called embeddings. Embeddings approximate characteristics of the graph and can be used for a variety of machine-learning tasks such as novel edge prediction. For many biomedical applications, partial knowledge exists about positive edges that represent relationships between pairs of entities, but little to no knowledge is available about negative edges that represent the explicit lack of a relationship between two nodes. For this reason, classification procedures are forced to assume that the vast majority of unlabeled edges are negative. Existing approaches to sampling negative edges for training and evaluating classifiers do so by uniformly sampling pairs of nodes. Results: We show here that this sampling strategy typically leads to sets of positive and negative examples with imbalanced node degree distributions. Using representative heterogeneous biomedical knowledge graph and random walk-based graph machine learning, we show that this strategy substantially impacts classification performance. If users of graph machine-learning models apply the models to prioritize examples that are drawn from approximately the same distribution as the positive examples are, then performance of models as estimated in the validation phase may be artificially inflated. We present a degree-aware node sampling approach that mitigates this effect and is simple to implement. Availability and implementation: Our code and data are publicly available at https://github.com/monarch-initiative/negativeExampleSelection.

59 BASIC BIOLOGICAL SCIENCES↗

Relationships between water and paddlefish Polyodon spathula dentary elemental and stable-isotopic signatures: potential application for reconstructing environmental history

The objectives of this study were to characterize relationships between water and paddlefish Polyodon spathula dentary Sr:Ca, δ 18 O and stable hydrogen isotope ratio (δD) to determine the accuracy with which individual P. spathula could be assigned to their collection locations using dentary-edge Sr:Ca, δD and δ 18 O. A laboratory experiment was also conducted to determine whether dentary Sr:Ca in age 0 year P. spathula would reflect shifts in water Sr:Ca to which fish were exposed. Significant linear relationships between water and dentary Sr:Ca, δD and δ 18 O were observed, although the relationship between water and dentary δ 18 O was weaker than those for Sr:Ca and δD. Classification success for individual fish to collection locations that differed in water Sr:Ca, δD and δ 18 O ranged from 86 to 100% based on dentary-edge Sr:Ca, δD and δ18O. Dentary Sr:Ca increased significantly in laboratory-reared age 0 year P. spathula following 4 weeks of exposure to elevated water Sr:Ca; dentary Sr:Ca of fish held in water with elevated Sr:Ca was also significantly higher than that of control fish reared in ambient laboratory water. Results indicated that P. spathula dentaries reflect water signatures for commonly-applied natural chemical markers and strongly suggest that dentary microchemistry and stable-isotopic compositions will be applicable for reconstructing P. spathula environmental history in locations where sufficient spatial differences in water chemistry occur.

07 ISOTOPE AND RADIATION SOURCES↗

Feature Selection and Inferential Procedures for Video Data [Slides]

With the rise of electronic and high-dimensional data, new and innovative feature detection and statistical methods are required to perform accurate and meaningful statistical analysis of these datasets that provide unique statistical challenges. In the area of feature detection, much of the recent feature detection research in the computer vision community has focused on deep learning methods, which require large amounts of labeled training data. However, in many application areas, training data is very limited and often difficult to obtain. We develop methods for fast, unsupervised, precise feature detection for video data based on optical flows, edge detection, and clustering methods. We also use pretrained neural networks and interpretable linear models to extract features using very limited training data. In the area of statistics, while high-dimensional data analysis has been a main focus of recent statistical methodological research, much focus has been on populations of high-dimensional vectors, rather than populations of high-dimensional tensors, which are three-dimensional arrays that can be used to model dependent images, such as images taken of the same person or ripped video frames. Our feature detection method is a non-model-based method that fusses information from dense optical flow, raw image pixels, and frame differences to generate detections. Our hypothesis testing methods are based on the assumption that dependent images are concatenated into a tensor that follows a tensor normal distribution, and from this assumption, we derive likelihood-ratio, score, and regression-based tests for one- and multiple-sample testing problems. Our methods will be illustrated on simulated and real datasets. We conclude this report with comments on the relationship between feature detection and hypothesis testing methods.

97 MATHEMATICS AND COMPUTING↗

Investigation of the multiplet features of SrTiO 3 in X-ray absorption spectra based on configuration interaction calculations

Synchrotron-based L 2,3 -edge absorption spectra show strong sensitivities to the local electronic structure and chemical environment. However, detailed physical information cannot be extracted easily without computational aids. Here in this study using the experimental Ti L 2,3 -edges absorption spectrum of SrTiO 3 as a fingerprint and considering full multiplet effects, calculations yield different energy parameters characterizing local ground state properties. The peak splitting and intensity ratios of the L 3 and L 2 set of peaks are carefully analyzed quantitatively, giving rise to a small hybridization energy around 1.2 eV, and the different hybridization energy values reported in the literature are further addressed. Finally, absorption spectra with different linearly polarized photons under various tetragonal crystal fields are investigated, revealing a non-linear orbital–lattice interaction, and a theoretical guidance for material engineering of SrTiO 3 -based thin films and heterostructures is offered. Finally, detailed analysis of spectrum shifts with different tetragonal crystal fields suggests that the e g crystal field splitting is a necessary parameter for a thorough analysis of the spectra, even though it is not relevant for the ground state properties.

3 d transition metal oxide↗

Development and evaluation of aperture-based complexity metrics using film and EPID measurements of static MLC openings

Purpose: Complexity metrics have been suggested as a complement to measurement-based quality assurance for intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT). However, these metrics have not yet been sufficiently validated. This study develops and evaluates new aperture-based complexity metrics in the context of static multileaf collimator (MLC) openings and compares them to previously published metrics. Methods: This study develops the converted aperture metric and the edge area metric. The converted aperture metric is based on small and irregular parts within the MLC opening that are quantified as measured distances between MLC leaves. The edge area metric is based on the relative size of the region around the edges defined by the MLC. Another metric suggested in this study is the circumference/area ratio. Earlier defined aperture-based complexity metrics—the modulation complexity score, the edge metric, the ratio monitor units (MU)/Gy, the aperture area, and the aperture irregularity—are compared to the newly proposed metrics. A set of small and irregular static MLC openings are created which simulate individual IMRT/VMAT control points of various complexities. These are measured with both an amorphous silicon electronic portal imaging device and EBT3 film. The differences between calculated and measured dose distributions are evaluated using a pixel-by-pixel comparison with two global dose difference criteria of 3% and 5%. The extent of the dose differences, expressed in terms of pass rate, is used as a measure of the complexity of the MLC openings and used for the evaluation of the metrics compared in this study. The different complexity scores are calculated for each created static MLC opening. The correlation between the calculated complexity scores and the extent of the dose differences (pass rate) are analyzed in scatter plots and using Pearson’s r-values. Results: The complexity scores calculated by the edge area metric, converted aperture metric, circumference/area ratio, edge metric, and MU/Gy ratio show good linear correlation to the complexity of the MLC openings, expressed as the 5% dose difference pass rate, with Pearson’s r-values of −0.94, −0.88, −0.84, −0.89, and −0.82, respectively. The overall trends for the 3% and 5% dose difference evaluations are similar. Conclusions: New complexity metrics are developed. The calculated scores correlate to the complexity of the created static MLC openings. The complexity of the MLC opening is dependent on the penumbra region relative to the area of the opening. The aperture-based complexity metrics that combined either the distances between the MLC leaves or the MLC opening circumference with the aperture area show the best correlation with the complexity of the static MLC openings.

60 APPLIED LIFE SCIENCES↗

Liquid lithium divertor analysis using coupled plasma material interaction model

A liquid lithium divertor can improve performance of future fusion devices by creating efficient power exhaust and improving the energy confinement via pumping of the hydrogen isotopes. In addition, significantly higher heat fluxes can be handled if controlled vapor shielding is used to redistribute the divertor heat flux over a wider area. Design and optimization of such a system calls for an analysis model which includes a strong two-way coupling between the plasma and divertor material. The incoming plasma heat and particle flux will affect the divertor surface temperature, which is a defining factor of the lithium evaporative and sputtered flux going into the plasma. Results of the coupled model based on the plasma edge code SOLPS-ITER and the computational fluid dynamics (CFD) code ANSYS-CFX will be presented for different configurations. An analytical slab flow model is used as a heat transfer boundary condition for SOLPS, defining particle flux from the wall via calculation of the surface temperature. At the final step, results of the SOLPS analysis are verified using a 3D CFD magnetohydrodynamics (MHD) analysis which uses heat and particle flux from SOLPS as a boundary condition. In addition to plasma heat flux, both analytical and CFD temperature models include several plasma material interaction effects, such as lithium evaporation, condensation and sputtering based on deuterium target flux. New adatom sputtering model based on the available experimental data is presented. Analytical model is expanded to include free surface axisymmetric configurations. Results of parametric studies of the divertor configurations with different lithium inlet temperature and velocity will be presented leading to the optimal design resulting in the lowest possible lithium contamination in the core.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The Double Edge Aerosol and Molecular Techniques for Doppler Lidar Wind Measurement

We have developed the theory for aerosol- and molecular-based lidar measurements of the wind using double edge versions of the edge technique. Aerosol-based wind measurements have been made at Goddard Space Flight Center and molecular-based wind measurements at the University of Geneva. We have demonstrated atmospheric measurements using these techniques for altitudes from 1 to more than 10 km. Measurement accuracies of better than 1.25 m/s have been obtained with integration times from 5 to 30 seconds. The measurements can be scaled to space and agree, within a factor of two, with satellite-based simulations of performance based on Poisson statistics.

Korb, C. Laurence↗

Review of Graph Databases for Big Data Dynamic Entity Scoring

Modeling data as a graph enables users to quickly analyze networked phenomenon, such as social network-based marketing data (e.g., linking entities in social media based on their friends and their "likes", their friend-of-a-friend's "likes", etc.) and scientific data, such as in biology to assess a gene's proximity in a graph to particular disease phenotype. Numerous purpose-built graph databases (DBs) called “NoSQL” or “Not Only SQL” DBs are emerging to support this type of graph analysis. These DBs differ from traditional relational DBs in that they are optimized to improve storage and query performance across large, complex graphs. This document reviews the state of the art in graph DBs and identifies potential DBs that show promise for dynamic entity-scoring algorithms. Dynamic entity scoring is a new area of research that allows analysis of data within graphs using undirected methods to weigh the edges of the graph based on the proximity or ambient influence of near-by nodes. The EntityScore (eScore) methodology developed at Lawrence Livermore National Laboratory (LLNL) is one application of these emerging graph-analysis algorithms to help analysts identify and prioritize entities, based on complex, analyst-defined weighting criteria. Our review examines a wide range of different, well-known graph DBs in use since at least 2010 and identifies unique advantages and disadvantages that may impact eScore-specific requirements. Specifically, we review data structures employed, query features employed, load times, query calculation times, memory usage and several other important attributes reported in the literature. We limited our considerations for eScore to Blueprints-compliant graph DBs (https://github.com/tinkerpop/blueprints/) because they provide a standard, java application programming interface (API) based on the property graph model.

42 ENGINEERING↗

SU-E-J-249: Characterization of Gynecological Tumor Heterogeneity Using Texture Analysis in the Context of An 18F-FDG PET Adaptive Protocol

Purpose: We propose a method to examine gynecological tumor heterogeneity using texture analysis in the context of an adaptive PET protocol in order to establish if texture metrics from baseline PET-CT predict tumor response better than SUV metrics alone as well as determine texture features correlating with tumor response during radiation therapy. Methods: This IRB approved protocol included 29 women with node positive gynecological cancers visible on FDG-PET treated with EBRT to the PET positive nodes. A baseline and intra-treatment PET-CT was obtained. Tumor outcome was determined based on RECIST on posttreatment PET-CT. Primary GTVs were segmented using 40% threshold and a semi-automatic gradient-based contouring tool, PET Edge (MIM Software Inc., Cleveland, OH). SUV histogram features, Metabolic Volume (MV), and Total Lesion Glycolysis (TLG) were calculated. Four 3D texture matrices describing local and regional relationships between voxel intensities in the GTV were generated: co-occurrence, run length, size zone, and neighborhood difference. From these, 39 texture features were calculated. Prognostic power of baseline features derived from gradientbased and threshold GTVs were determined using the Wilcoxon rank-sum test. Receiver Operating Characteristics and logistic regression was performed using JMP (SAS Institute Inc., Cary, NC) to find probabilities of predicting response. Changes in features during treatment were determined using the Wilcoxon signed-rank test. Results: Of the 29 patients, there were 16 complete responders, 7 partial responders, and 6 non-responders. Comparing CR/PR vs. NR for gradient-based GTVs, 7 texture values, TLG, and SUV kurtosis had a p < 0.05. Threshold GTVs yielded 4 texture features and TLG with p < 0.05. From baseline to intra-treatment, 14 texture features, SUVmean, SUVmax, MV, and TLG changed with p < 0.05. Conclusion: Texture analysis of PET imaged gynecological tumors is an effective method for early prognosis and should be used complimentary to SUV metrics, especially when using gradient based segmentation.

60 APPLIED LIFE SCIENCES↗

Cognitive IoT and Edge Computing for Intrusion Detection with Federated TinyML

Internet of Things (IoT) and Edge Computing (EC) are rapidly becoming an integral part of the modern society. By 2030, there is estimated to be over 40 billion active and connected IoT devices [1]. This rapid progress also comes with a significant implication on cybersecurity. Back-end infrastructure and systems have a much broader attack than they did previously due to vulnerable IoT/EC devices being connected to wireless networks. This expanding attack surface is a growing concern because IoT/EC are increasingly being used in critical systems such as power grids, health care, and smart homes. To effectively address a problem of this scale, cognitive cyber methods—which can autonomously detect and react to cyber attacks as they develop—are needed. To address this, we bring Artificial Intelligence (AI) and Machine Learning (ML) to IoT/EC devices, using tinyML to monitor voluminous IoT data against cyber threats, and using Federated Learning (FL) to share local detection knowledge across the system while preserving privacy. We propose a novel three-layer architecture: (1) an IoT layer for tinyML-based inference, (2) an edge layer for ML model training, and (3) a cloud layer for FL operations. Using the publicly available 11-class N-BaIoT dataset [2], we demonstrate that this architecture mitigates resource constraints at the IoT layer while improving detection accuracy over standard two-layer designs. An outlier-resistant scaler, feature reduction, and quantization enable the tinyML model to maintain detection accuracy with a reduced model size. Additionally, federated learning that only utilizes the intersection (across heterogenous devices) of the reduced feature set achieves superior detection accuracy compared to locally trained models.

Li, Mingyan [ORNL] (ORCID:0009000569532640)↗