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At least 1,117 records · Page 62

Cryo-EM visualization of viruses from partially irrigated soils

Viruses are numerically the most abundant forms on Earth, and most are present in soil. Even though viruses are highly abundant in soil and critical to rhizosphere function, visualizing the diverse morphotypes within soil has been challenging. The difficulty is primarily due to the heterogenous nature of isolated suspensions that typically contain nanometer to micron scale debris which renders protein crystallography for structural studies unfeasible and hinders cryo-electron microscopy due to ice thickness and contrast issues. Here we employed and compared a simple spin filtration method to cleanup solutions of extracted viruses for direct observation with cryo-electron microscopy. The method employs common physical biochemical separation steps to remove large and small debris which dramatically improves image quality and preservation of structural features to permit visualizing morphotypes not typically seen with conventional negative stain approaches. In addition to tailed and non-tailed polyhedral phages, several under reported or novel morphotypes of soil viruses are directly visualized as a particle library with both 2D and 3D information.

cryo-EM↗

Solid carbon monoxide in the Serpens dark cloud

The 4.67 micrometer absorption feature of solid CO is an important signature of grain mantles in molecular clouds. This paper presents new observations of solid CO absorption in the spectra of four infrared sources in and behind the Serpens dark cloud. We also present supplementary 2.0-2.5 micrometer spectra which clarify the nature of selected sources. Solid CO profiles are compared with models based on laboratory data. In common with previous studies of other clouds, we find that the observed profiles are consistent with the presence of two distinct phases of CO-bearing ice, one dominated either by CO itself or by CO mixed with absorption relative to that of the water-ice feature at 3.1 micrometers is unusually high in Serpens: we deduce column densities for CO and H2O in solid form and conclude that the mean CO abundance in dust is 40% of the H2O abundance, compared with values in the range 0%-30% typical of other molecular clouds. On the basis of its 2.0-2.5 micrometer spectrum and near-infrared colors, we deduce the infrared source CK 2 to be a K5-M0 III field star situated behind the Serpens cloud and suffering 40-50 mag of visual extinction. Assuming empirical correlations between extinction and total (gas + dust) CO column density, we estimate the CO depletion (i.e., the fraction of interstellar CO in the line of sight tied up in grains) to be approximately 40% in the intracloud medium of the Serpens cloud, comparable with previous estimates for the Taurus dark cloud, and much higher than that found in the environments of protostellar objects.

Chiar, J. E.↗

Toward a Visualization-Supported Workflow for Cyber Alert Management using Threat Models and Human-Centered Design

Cyber network analysts follow complex processes in their investigations of potential threats to their network. Much research is dedicated to providing automated tool support in the effort to make their tasks more efficient, accurate, and timely. This tool support comes in a variety of implementations from machine learning algorithms that monitor streams of data to visual analytic environments for exploring rich and noisy data sets. Cyber analysts, however, often speak of a need for tools which help them merge the data they already have and help them establish appropriate baselines against which to compare potential anomalies. Furthermore, existing threat models that cyber analysts regularly use to structure their investigation are not often leveraged in support tools. We report on our work with cyber analysts to understand they analytic process and how one such model, the MITRE ATT&CK Matrix [32], is used to structure their analytic thinking. We present our efforts to map specific data needed by analysts into the threat model to inform our eventual visualization designs. We examine data mapping for gaps where the threat model is under-supported by either data or tools. We discuss these gaps as potential design spaces for future research efforts. We also discuss the design of a prototype tool that combines machine-learning and visualization components to support cyber analysts working with this threat model.

Cyber Security↗

Impact of dissolved salts on two-phase flow and boiling heat transfer in a natural circulation loop

Two-phase natural circulation and boiling experiments are conducted in this study with artificial seawater as a heat transfer fluid or process coolant. This experimental work is focused on understanding the role of dissolved salts in water on the steady state two-phase natural circulation flow rates. Mass flow rates were measured at different heat flux levels with artificial seawater, deionized water and tap water in the experimental loop. It was found that the average quasi-steady state mass flow rates were the same at any particular heat flux level regardless of the fluid being used. Artificial seawater coolant exhibited more stable natural circulation at higher heat flux as compared to the other two coolants. Mass flow measurements recorded at 2 s intervals show that magnitude of flow oscillations are much higher in case of tap water and deionized water. Also, high speed camera images revealed that the bubble departure diameters are smaller in seawater compared to tap or deionized water. This can be attributed to the increased local wettability due to the presence of dissolved salts in the fluid. Visual observations of the riser section showed that bubble coalescence and formation of slugs is inhibited in the seawater. These observations also explain the reduced pressure drop across test section when seawater was used as a coolant.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Resolution Versus Error for Computational Electron Microscopy

Images that are collected via scanning transmission electron microscopy (STEM) can be undersampled to avoid damage to the specimen while maintaining resolution [1, 2]. We have used BPFA to impute missing data and reduce noise [3]. The reconstruction is typically evaluated using the peak signal-to-noise ratio (PSNR). This measure is too conservative for STEM images and we propose that the Fourier ring correlation (FRC) is used instead to evaluate the reconstruction. We are not concerned with exact reconstruction of the truth image, and therefore PSNR is a conservative estimation of the quality of the reconstruction. Instead, we are concerned with the visual resolution of the image and whether atoms can be distinguished. We have evaluated the reconstruction of a simulated STEM image using the FRC and compared the results with the PSNR measurements. The FRC captures the resolution of the image and is not affected by a large MSE if the atom peaks are still distinguishable. The noisy and reconstructed images are shown in Figure 1. The simulated STEM image was sampled at 100%, 80%, 40%, and 20% of the original pixels to simulate an undersampled scan. The reconstruction was done using BPFA with a patch size of 10 x 10 and no overlapping patches. Not having overlapping patches produces inferior results but they are still acceptable. The dictionary size is 64 and 30 iterations were completed during each reconstruction. The 100% image was denoised instead of reconstructed. Poisson noise was applied to the simulated image with λ values of 500, 50, and 5 to simulate lower imaging dose. The original simulated STEM image was also included in our calculations and was generated using a dose of 1000. The simulated STEM image is 100 by 100 pixels and has essentially no high frequency components. The image reconstruction tends to smooth the data, also resulting in no high frequency components. This causes the FRC of the two images to be large at higher resolutions and may be misleading. For this reason, the BPFA has no overlap to avoid excessive smoothing. Moreover, the resolution of the simulated image is approximately 9.2 (1/nm), so we only look that far in the frequency domain when performing FRC. If the FRC curve does not crossover the threshold, a resolution value of 9.2 is used. We emphasize that our reported results are conservative. The FRC and PSNR values using the ground truth and the reconstructed images are shown in Tables 1 and 2. The left side show the metrics without using BPFA (missing pixels) and the right side show the metrics after using BPFA. When we did not use BPFA, the Fourier transform was estimated [4]. Some threshold curves have been studied [5], but they are derived for additive noise models. Since we have a Poisson noise model, we have used the more conservative threshold of 0.5 for our calculations. Ten images were used to construct each cell of tables in the form of the mean of the metric plus or minus its standard deviation. As expected, the PSNR dies off much quicker than the FRC values for the same image. For the 100% and 80% sampled versions of the truth image, the resolution only dies off when the dose is 5. However, the PSNR dies off rapidly as the dose is reduced. For the 1000, 500, and 50 dose images, the FRC is the maximum, or close, until we undersample at 20%. The PSNR for these values tapers down as we get into the bottom right hand corner of the table, even though the resolution remains high. Overall, we find that undersampled images can be reconstructed to acceptable resolution even when the dose per pixel is also reduced[6]. References: [1]A Stevens, H Yang, L Carin et al. Microscopy 63(1), (2014), pp. 41. [2]A Stevens, L Kovarik, P Abellan et al. Advanced Structural and Chemical Imaging 1(1), (2015), pp. 1. [3]M Zhou, H Chen, J Paisley et al. Image Processing, IEEE Transactions on 21(1), (2012), pp. 130. [4]V. Y. Liepin’sh. Automatic control and computer sciences 30(3), (1996), pp. 20.

Luzi, Lorenzo↗

Application of a Chemical Index to Aerosol Mass Spectrometry: Delta Plots and Functional Group Distributions

A better understanding of the chemical properties of organic aerosol (OA) particles will improve our ability to characterize their sources and predict their lifetime. The high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) is widely used to measure OA in real time using thermal vaporization followed by electron ionization (EI). EI creates fragment ions that can be assigned to functional groups using delta analysis, a method of classifying mass spectra according to the presence of different chemically related ion series. In this study, we demonstrate the application of delta analysis to characterize molecular structures using a new visualization method. We also use delta analysis to quantify the functional group distribution with an average absolute error of ∼5–6% for individual standard molecules, comparable to the error observed for OA mixtures from biomass and coal combustion fit with Fourier transform infrared spectroscopy. Finally, we apply delta functional group analysis to AMS positive matrix factorization (PMF) factors across seven different field campaigns and find a similar composition across the more oxidized factors with about 55% acid and 26% alcohol groups. The analysis method described here can be applied to any HR-ToF-AMS data set to provide quantitative relative functional group distributions for OA mixtures.

aerosol↗

Beyond the hubble sequence – exploring galaxy morphology with unsupervised machine learning

We explore unsupervised machine learning for galaxy morphology analyses using a combination of feature extraction with a vector-quantized variational autoencoder (VQ-VAE) and hierarchical clustering (HC). We propose a new methodology that includes: (1) consideration of the clustering performance simultaneously when learning features from images; (2) allowing for various distance thresholds within the HC algorithm; (3) using the galaxy orientation to determine the number of clusters. This set-up provides 27 clusters created with this unsupervised learning that we show are well separated based on galaxy shape and structure (e.g. Sérsic index, concentration, asymmetry, Gini coefficient). These resulting clusters also correlate well with physical properties such as the colour–magnitude diagram, and span the range of scaling relations such as mass versus size amongst the different machine-defined clusters. When we merge these multiple clusters into two large preliminary clusters to provide a binary classification, an accuracy of $\sim 87{{\ \rm per\ cent}}$ is reached using an imbalanced data set, matching real galaxy distributions, which includes 22.7 per cent early-type galaxies and 77.3 per cent late-type galaxies. Comparing the given clusters with classic Hubble types (ellipticals, lenticulars, early spirals, late spirals, and irregulars), we show that there is an intrinsic vagueness in visual classification systems, in particular galaxies with transitional features such as lenticulars and early spirals. Based on this, the main result in this work is not how well our unsupervised method matches visual classifications and physical properties, but that the method provides an independent classification that may be more physically meaningful than any visually based ones.

79 ASTRONOMY AND ASTROPHYSICS↗

Discovering faint and high apparent motion rate near-Earth asteroids using a deep learning program

ABSTRACT Although many near-Earth objects have been found by ground-based telescopes, some fast-moving ones, especially those near detection limits, have been missed by observatories. We developed a convolutional neural network for detecting faint fast-moving near-Earth objects. It was trained with artificial streaks generated from simulations and was able to find these asteroid streaks with an accuracy of 98.7 per cent and a false positive rate of 0.02 per cent on simulated data. This program was used to search image data from the Zwicky Transient Facility (ZTF) in four nights in 2019, and it identified six previously undiscovered asteroids. The visual magnitudes of our detections range from ∼19.0 to 20.3 and motion rates range from ∼6.8 to 24 deg d−1, which is very faint compared to other ZTF detections moving at similar motion rates. Our asteroids are also ∼1–51 m diameter in size and ∼5–60 lunar distances away at close approach, assuming their albedo values follow the albedo distribution function of known asteroids. The use of a purely simulated data set to train our model enables the program to gain sensitivity in detecting faint and fast-moving objects while still being able to recover nearly all discoveries made by previously designed neural networks which used real detections to train neural networks. Our approach can be adopted by any observatory for detecting fast-moving asteroid streaks.

Wang, Franklin (ORCID:0000000344887355)↗

Indirect detection constraints on the model space of dark matter effective theories

Using limits on photon flux from Dwarf Spheroidal galaxies, we place bounds on the parameter space of models in which Dark Matter annihilates into multiple final state particle pair channels. We derive constraints on effective operator models with Dark Matter couplings to third generation fermions and to pairs of Standard Model vector bosons. We present limits in various slices of model parameter space along with estimations of the region of maximal validity of the effective operator approach for indirect detection. Finally, we visualize our bounds for models with multiple final state annihilations by projecting parameter space constraints onto triangles, a technique familiar from collider physics; and we compare our bounds to collider limits on equivalent models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A digitally reconstructed radiograph algorithm calculated from first principles

Purpose: To develop an algorithm for computing realistic digitally reconstructed radiographs (DRRs) that match real cone-beam CT (CBCT) projections with no artificial adjustments. Methods: The authors used measured attenuation data from cone-beam CT projection radiographs of different materials to obtain a function to convert CT number to linear attenuation coefficient (LAC). The effects of scatter, beam hardening, and veiling glare were first removed from the attenuation data. Using this conversion function the authors calculated the line integral of LAC through a CT along rays connecting the radiation source and detector pixels with a ray-tracing algorithm, producing raw DRRs. The effects of scatter, beam hardening, and veiling glare were then included in the DRRs through postprocessing. Results: The authors compared actual CBCT projections to DRRs produced with all corrections (scatter, beam hardening, and veiling glare) and to uncorrected DRRs. Algorithm accuracy was assessed through visual comparison of projections and DRRs, pixel intensity comparisons, intensity histogram comparisons, and correlation plots of DRR-to-projection pixel intensities. In general, the fully corrected algorithm provided a small but nontrivial improvement in accuracy over the uncorrected algorithm. The authors also investigated both measurement- and computation-based methods for determining the beam hardening correction, and found the computation-based method to be superior, as it accounted for nonuniform bowtie filter thickness. The authors benchmarked the algorithm for speed and found that it produced DRRs in about 0.35 s for full detector and CT resolution at a ray step-size of 0.5 mm. Conclusions: The authors have demonstrated a DRR algorithm calculated from first principles that accounts for scatter, beam hardening, and veiling glare in order to produce accurate DRRs. The algorithm is computationally efficient, making it a good candidate for iterative CT reconstruction techniques that require a data fidelity term based on the matching of DRRs and projections.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

SU-C-9A-07: Fabrication and Calibration of a Novel High-Sensitivity Collimator for Brain SPECT Imaging

Purpose: We have designed a novel collimator for brain SPECT imaging that yields greatly increased sensitivity near the center of the brain without loss of resolution. The collimator was manufactured and initial evaluation has been completed. Methods: The collimator was time-consuming and challenging to build. Because our desired hole pattern required substantial variations in hole angle, we designed two supporting plates to securely position about 34,000 hexagonal, slightly tapered, 75-mm long steel pins. The holes in the plates were modeled to yield the desired focal length, hole length and septal thickness. Molten lead was poured in between the plates, and all pins were removed after cooling. The sensitivity gain compared to a fan-beam collimator was measured using a point source placed along the central ray at several distances from the collimator face. Visual inspection of the holes was not possible as the collimator was sealed so it could be safely mounted on a SPECT system. Therefore, we prepared a 2D array of 768, ∼48μCi Tc-99m point sources, separated by 1.6 cm. The array was imaged for 10 minutes at 4 shifted locations to reduce sampling distance to 8 mm. Results: The sensitivity of the novel cone-beam collimator varied with distance from the detector face; it was higher than that of the fan-beam collimator by factors ranging from 3 to 176. Examination of the projections of the 4×768 point sources revealed that fewer than 2% of the holes were fully or partially blocked, which indicates that the intensive manual fabrication process was very successful. Conclusion: We have designed and manufactured a novel collimator for brain SPECT imaging. As expected, the sensitivity is much higher than that of a fan-beam collimator. Because of differences between the manufactured collimator and its design, reconstruction of the data will require a measured system function.

60 APPLIED LIFE SCIENCES↗

SU-F-I-57: Evaluate and Optimize PET Acquisition Overlap in 18F-FDG Oncology Wholebody PET/CT: Can We Scan PET Faster?

Purpose: The longer patient has to remain on the table during PET imaging, the higher the likelihood of motion artifacts due to patient discomfort. This study was to investigate and optimize PET acquisition overlap in 18F-FDG oncology wholebody PET/CT to speed up PET acquisition and improve patient comfort. Methods: Wholebody 18F-FDG PET/CT of phantoms, 8 pre-clinical patients (beagles) and 5 clinical oncology patients were performed in 90s/bed on a time-of-flight Gemini TF 64 system. Imaging of phantoms and beagles was acquired with reduced PET overlaps (40%, 33%, 27%, 20%, 13% and no overlap) in addition to the system default (53%). In human studies, 1 or 2 reduced overlaps from the listed options were used to acquire PET/CT sweeps right after the default standard of care imaging. Image quality was blindly reviewed using visual scoring criteria and quantitative SUV assessment. NEMA PET sensitivity was performed under different overlaps. Results: All PET exams demonstrated no significant impact on the visual grades for overlaps >20%. Blinded reviews assigned the best visual scores to PET using overlaps 53%–27%. Reducing overlap to 27% for oncology patients (12-bed) saved an average of ∼40% acquisition time (11min) compared to using the default overlap (18min). No significant SUV variances were found when reducing overlap to half of default for cerebellum, lung, heart, aorta, liver, fat, muscle, bone marrow, thighs and target lesions (p>0.05), except expected variability in urinary system. Conclusion: This study demonstrated by combined phantom, pre-clinical and clinical PET/CT scans that PET acquisition overlap in axial of today’s systems can be reduced and optimized. It showed that a reduction of PET acquisition overlap to 27% (half of system default) can be implemented to reduce table time by ∼40% to improve patient comfort and minimize potential motion artifacts, without prominently degrading image quality or compromising PET quantification.

60 APPLIED LIFE SCIENCES↗

Hydrogen Crossover Flux through Two-Dimensional Nanomaterials

Energy storage and conversion devices require an ion-exchange membrane with high transmission of charge-balancing ions and separation of anode and cathode electrolytes/gases. This ensures optimum device performance. Most conventional membranes suffer huge cross-permeation resulting in low energy efficiency and material degradation. This work investigated hydrogen permeability and proton transmission through membrane electrode assemblies (MEAs) containing a monolayer of hexagonal boron nitride and single-layer and bi-layer graphene in a gas-phase small-scale cell and a liquid cell. Here we found that the hydrogen crossover flux through MEAs with 2D materials was inhibited by at least a factor of 5 compared to the one without. Single-layer graphene and boron nitride enabled high proton transmission, but bi-layer graphene inhibited proton conduction. Defect visualization of 2D materials revealed few atomic-scale defects in graphene. These findings suggest that a monolayer of 2D material may provide good selectivity for energy conversion and storage devices by blocking species crossover while allowing high proton transmission.

2D materials↗

Real-time X-ray phase-contrast imaging using SPINNet—a speckle-based phase-contrast imaging neural network

X-ray phase-contrast imaging has become indispensable for visualizing samples with low absorption contrast. In this regard, speckle-based techniques have shown significant advantages in spatial resolution, phase sensitivity, and implementation flexibility compared with traditional methods. However, the computational cost associated with data inversion has hindered their wider adoption. By exploiting the power of deep learning, we developed a speckle-based phase-contrast imaging neural network (SPINNet) that significantly improves the imaging quality and boosts the phase retrieval speed by at least 2 orders of magnitude compared to existing methods. To achieve this performance, we combined SPINNet with a coded-mask-based technique, an enhanced version of the speckle-based method. Using this scheme, we demonstrate the simultaneous reconstruction of absorption and phase images on the order of 100 ms, where a traditional correlation-based analysis would take several minutes even with a cluster. In addition to significant improvement in speed, our experimental results show that the imaging and phase retrieval quality of SPINNet outperform existing single-shot speckle-based methods. Furthermore, we successfully demonstrate SPINNet application in x-ray optics metrology and 3D x-ray phase-contrast tomography. Our result shows that SPINNet could enable many applications requiring high-resolution and fast data acquisition and processing, such as in situ and in operando 2D and 3D phase-contrast imaging and real-time at-wavelength metrology and wavefront sensing.

36 MATERIALS SCIENCE↗

Oxidation Resistant Graphite Studies

The Very High Temperature Reactor (VHTR) Graphite Research and Development Program is investigating doped nuclear graphite grades exhibiting oxidation resistance. During a oxygen ingress accident the oxidation rates of the high temperature graphite core region would be extremely high resulting in significant structural damage to the core. Reducing the oxidation rate of the graphite core material would reduce the structural effects and keep the core integrity intact during any air-ingress accident. Oxidation testing of graphite doped with oxidation resistant material is being conducted to determine the extent of oxidation rate reduction. Nuclear grade graphite doped with varying levels of Boron-Carbide (B4C) was oxidized in air at nominal 740°C at 10/90% (air/He) and 100% air. The oxidation rates of the boronated and unboronated graphite grade were compared. With increasing boron-carbide content (up to 6 vol%) the oxidation rate was observed to have a 20 fold reduction from unboronated graphite. Visual inspection and uniformity of oxidation across the surface of the specimens were conducted. Future work to determine the remaining mechanical strength as well as graphite grades with SiC doped material are discussed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Automated scanning of plastic nuclear track detectors using the Minnesota star scanner

The problems found in an attempt to adapt an automated scanner of astronomical plates, the Minnesota Automated Dual Plate Scanner (APS), to locating and measuring the etch pits produced by ionizing particles in plastic nuclear track detectors (CR-39) are described. A visual study of these pits was made to determine the errors introduced in determining positions and shapes. Measurements made under a low power microscope were compared with those from the APS.

Fink, P. J.↗

The interstellar light echoes around SN 1987A

The observed light echoes around SN 1987A are modeled by dust in planar clouds roughly 120 and 330 pc in front of the supernova. The expected echo profiles depend on the observed light curve and on the cloud thicknesses. The surface brightness and colors of the echoes are modeled using a mix of silicate and graphite grains appropriate to the Large Magellanic Cloud (LMC). The model colors approximately agree with the observed ones. The observed surface brightness suggests that the dust column density in the echo clouds is comparable to the total dust column density in the LMC toward SN 1987A. The model predicts the presence of a narrow ultraviolet echo outside the visual echo; it should be detectable with future ultraviolet observatories and will give information on the supernova near the phase of shock breakout.

Chevalier, Roger A.↗

Summary of work on shock wave feature extraction in 3-D datasets

A method for extracting and visualizing shock waves from three dimensional data-sets is discussed. Issues concerning computation time, robustness to numerical perturbations, and noise introduction are considered and compared with other methods. Finally, results using this method are discussed.

Hesselink, Lambertus↗