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At least 883 records · Page 49

The Dark Energy Survey Year 3 high-redshift sample: selection, characterization, and analysis of galaxy clustering

ABSTRACT The fiducial cosmological analyses of imaging surveys like DES typically probe the Universe at redshifts z < 1. We present the selection and characterization of high-redshift galaxy samples using DES Year 3 data, and the analysis of their galaxy clustering measurements. In particular, we use galaxies that are fainter than those used in the previous DES Year 3 analyses and a Bayesian redshift scheme to define three tomographic bins with mean redshifts around z ∼ 0.9, 1.2, and 1.5, which extend the redshift coverage of the fiducial DES Year 3 analysis. These samples contain a total of about 9 million galaxies, and their galaxy density is more than 2 times higher than those in the DES Year 3 fiducial case. We characterize the redshift uncertainties of the samples, including the usage of various spectroscopic and high-quality redshift samples, and we develop a machine-learning method to correct for correlations between galaxy density and survey observing conditions. The analysis of galaxy clustering measurements, with a total signal to noise S/N ∼ 70 after scale cuts, yields robust cosmological constraints on a combination of the fraction of matter in the Universe Ωm and the Hubble parameter h, $\Omega _m h = 0.195^{+0.023}_{-0.018}$, and 2–3 per cent measurements of the amplitude of the galaxy clustering signals, probing galaxy bias and the amplitude of matter fluctuations, bσ8. A companion paper (in preparation) will present the cross-correlations of these high-z samples with cosmic microwave background lensing from Planck and South Pole Telescope, and the cosmological analysis of those measurements in combination with the galaxy clustering presented in this work.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Ion irradiation effects on Cr-coated zircaloy-4 surface wettability and pool boiling critical heat flux.

The concept of coating the currently used nuclear fuel cladding (zirconium-based alloy, typically Zircaloy-4 or Zirc-4) with an oxidation preventive layer is a progressing Accident tolerant Fuel (ATF) candidate alloys. The coated Zirc-4-based alloys could be a solution to suppress undesirable fast reaction kinetics with high-temperature steam. Zirc-4 has been the most preferred cladding material in pressurized water reactors (PWRs). Chromium (Cr) based alloys as a coating material provides excellent corrosion protection and good strength and wear resistance. In this paper, we present the surface wettability measurements and pool boiling Critical Heat Flux (CHF) for Cr-coated Zirc-4 claddings pre- and post-exposure to an ion irradiation environment. The wettability measurements, including static contact angle (contact angle, θ) and average surface roughness (surface roughness, Ra), are introduced for samples of different coating thicknesses (5–30 μm thick). The coatings fabricated by the cold spray of Cr-Al particles to 10 mm × 10 mm × 1.95 mm Zirc-4 substrates. Post fabrication, a Pilgering (cold rolling) process, was applied to finalize the coating thickness and resulted in a significant reduction in surface roughness of initially fabricated rough surfaces. The process produced three distinguished samples 5-μm unpolished (as machined), 5-μm, and 30-μm polished (cold rolled). The measurements are presented for the three surfaces and bare Zirc-4 as a baseline surface. The contact angle analyses were implemented in theoretical models from the literature to predict pool boiling CHF. Pool boiling experiments were conducted to measure the pool boiling CHF values and compare them to the predicted values. Scanning Electron Microscope (SEM) images and Energy Dispersive X-ray Spectroscopy (EDS) analysis was performed to characterize the surfaces for better understanding and interpreting the results. The SEM images showed localized surface damage due to ion irradiation. No recognized change in the measured surface roughness due to ion irradiation. The contact angles of irradiated Cr-coated surfaces are consistently higher (10°) than pre-irradiated surfaces. Decreasing the Cr-coating layer thickness resulted in lower contact angle pre- and post- ion irradiation. The predicted pool boiling CHF using the Kandlikar model is in good agreement with the experimentally measured CHF values within ±12% for all samples.

36 MATERIALS SCIENCE↗

Real-time kinematic (RTK) Drone-collected Data and Processed Models of Port Arthur Coastal Neighborhood and Pleasure Island Golf Course, June 2024

The Southeast Texas Urban Integrated field lab’s Co-design team captured aerial photos in the Port Arthur Coastal Neighborhood Community and the Golf Course on Pleasure Island, Texas, in June 2024. Aerial photos taken were through autonomous flight, and models were processed through the DroneDeploy engine. All aerial photos are in .JPG format and contained in zipped files for each area. The processed data package includes 3D models, geospatial data, mappings, and point clouds. Please be aware that DTM, Elevation toolbox, Point Cloud, and Orthomosaic use EPSG: 6588. And 3D Model uses EPSG: 3857.For using these data:- The Adobe Suite gives you great software to open .Tif files.- You can use LASUtility (Windows), ESRI ArcGIS Pro (Windows), or Blaze3D (Windows, Linux) to open a LAS file and view the data it contains.- Open an .OBJ file with a large number of free and commercial applications. Some examples include Microsoft 3D Builder, Apple Preview, Blender, and Autodesk.- You may use ArcGIS, Merkaartor, Blender (with the Google Earth Importer plug-in), Global Mapper, and Marble to open .KML files.- The .tfw world file is a text file used to georeference the GeoTIFF raster images, like the orthomosaic and the DSM. You need suitable software like ArcView to open a .TFW file.This dataset provides researchers with sufficient geometric data and the status quo of the land surface at the locations mentioned above. This dataset will support researchers' decision-making processes under uncertainties.

2D mapping↗

Uranium Oxide Synthetic Pathway Discernment through Unsupervised Morphological Analysis

We present a novel unsupervised machine learning method for quantitative representation of scanning electron micrographs and its applications and performance for nuclear forensic analysis of uranium ore concentrates. The method uses a vector quantizing variational autoencoder followed by a histogram operation to encode a micrograph into a single dimensional representation, called the latent vector. The method requires no extant labeling of the data and can be applied over large datasets of micrographs with minimal human interaction. The representations generated are broadly descriptive of each micrograph and the microstructure of the material imaged. In the case of uranium ore concentrate analysis, the representations were amenable to processing reagent and ore concentrate species classification with accuracy of 81:8%, which is competitive with state-of-the-art supervised networks. The representations were also used to classify previously unseen processing routes, were able to classify imaging parameters such as magnification (to 76:0% accuracy), were able to classify fine grained process parameters such as calcining temperature (to 74:4% accuracy), and their informatic properties indicate that they are generally descriptive of the image represented. This method can be applied across microstructure analysis fields to perform quantitative analysis without the need for labor intensive and possibly biased human analysis.

Scanning Electron Microscopy, Vector Quantizing Va↗

Aerial Data and Processed Models of Port Arthur Coastal Neighborhood and Pleasure Island Golf Course, June 2024

Our Co-design team is from the University of Texas, working on a Department of Energy-funded project focused on the Beaumont-Port Arthur area. As part of this project, we will be developing climate-resilient design solutions for areas of the region. More on www.caee.utexas.edu.We captured aerial photos in the Port Arthur Coastal Neighborhood Community and the Golf Course on Pleasure Island, Texas, in June 2024.Aerial photos taken were through DroneDeploy autonomous flight, and models were processed through the DroneDeploy engine as well. All aerial photos are in .JPG format and contained in zipped files for each area.The processed data package includes 3D models, geospatial data, mappings, and point clouds. Please be aware that DTM, Elevation toolbox, Point cloud, and Orthomosaic use EPSG: 6588. And 3D Model uses EPSG: 3857.For using these data:- The Adobe Suite gives you great software to open .Tif files.- You can use LASUtility (Windows), ESRI ArcGIS Pro (Windows), or Blaze3D (Windows, Linux) to open a LAS file and view the data it contains.- Open an .OBJ file with a large number of free and commercial applications. Some examples include Microsoft 3D Builder, Apple Preview, Blender, and Autodesk.- You may use ArcGIS, Merkaartor, Blender (with the Google Earth Importer plug-in), Global Mapper, and Marble to open .KML files.- The .tfw world file is a text file used to georeference the GeoTIFF raster images, like the orthomosaic and the DSM. You need suitable software like ArcView to open a .TFW file.This dataset provides researchers with sufficient geometric data and the status quo of the land surface at the locations mentioned above. This dataset could streamline researchers' decision-making processes and enhance the design as well.

2D mapping↗

Detecting optical transients using artificial neural networks and reference images from different surveys

ABSTRACT We present a technique to detect optical transients based on an artificial neural networks method. We describe the architecture of two networks capable of comparing images of the same part of the sky taken by different telescopes. One image corresponds to the epoch in which a potential transient could exist; the other is a reference image of an earlier epoch. We use data obtained by the Dr. Cristina V. Torres Memorial Astronomical Observatory and archival reference images from the Sloan Digital Sky Survey. We trained a convolutional neural network and a dense layer network on simulated source samples and then tested the trained networks on samples created from real image data. Autonomous detection methods replace the standard process of detecting transients, which is normally achieved by source extraction of a difference image followed by human inspection of the detected candidates. Replacing the human inspection component with an entirely autonomous method would allow for a rapid and automatic follow-up of interesting targets of opportunity. The toy-model pipeline that we present here is not yet able to replace human inspection, but it might provide useful hints to identify potential candidates. The method will be further expanded and tested on telescopes participating in the Transient Optical Robotic Observatory of the South Collaboration.

79 ASTRONOMY AND ASTROPHYSICS↗

Energy Flow in Thin Shell Implosions and Explosions

Energy flow and balance in convergent systems beyond petapascal energy densities controls the fate of late-stage stars and the potential for controlling thermonuclear inertial fusion ignition. Time-resolved x-ray self-emission imaging combined with a Bayesian inference analysis is used to describe the energy flow and the potential information stored in the rebounding spherical shock at 0.22 PPa (2.2 Gbar or billions of atmospheres pressure). This analysis, together with a simple mechanical model, describes the trajectory of the shell and the time history of the pressure at the fuel-shell interface, ablation pressure, and energy partitioning including kinetic energy of the shell and internal energy of the fuel. Here, the techniques used here provide a fully self-consistent uncertainty analysis of integrated implosion data, a thermodynamic-path independent measurement of pressure in the petapascal range, and can be used to deduce the energy ow in a wide variety of implosion systems to petapascal energy densities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Quantifying Properties for a Mechanistic, Predictive Understanding of Aqueous Impact on Aging of Medium and Low Voltage AC and DC Cabling in Nuclear Power Plants

To address the gap in knowledge in understanding degradation in relevant service conditions, this project aimed to develop a mechanistic, predictive model of medium and low voltage cable failure based on the primary environmental degradation parameters of aqueous immersion time, temperature, and the oxidation extent. To do so, we took a two-fold approach toward evaluating degradation as related to the aqueous condition. First, we evaluated the chemical, mechanical, and electrical properties of polymers that comprise the cabling insulation under varied aqueous conditions at different temperatures. Secondly, we evaluated the performance of insulation materials under similar accelerated aging conditions in addition to the dielectric breakdown of the cabling under submersion conditions. Thermal oxidation and immersion of LDPE thin films were done using a Parr vessel and the extent of oxidation was monitored using the carbonyl index from ATR-FTIR spectrum, a ratio quantifying the carbonyl functionality produced on the LDPE film surface. Increasing the temperature, oxidation time, and oxygen pressure increased the water-vapor permeability and the carbonyl content. Thermogravimetric analysis of the films confirmed that there is indeed an initial weight loss of the smaller molecular weight molecules and volatiles. At higher temperatures, there is a secondary mass loss. Up to 70°C, the mass loss curves were similar until 80°C, when the aged films decreased at a much greater rate with respect to increasing temperature. This was seen in the 10, 50, 90% weight loss temperatures. The mechanical properties of sheet PP and HDPE as well as injection molded LDPE, HDPE, HDPP dog bones were plotted with respect to the time spent in the Parr vessel during thermal oxidation. For the sheet PP and HDPE, the UTS and the modulus of elasticity decreased while the elongation increased. The injection-molded LDPE, HDPE, and HDPP dog bones experienced a similar trend where the changes in the properties were within experimental uncertainty. This analysis of LDPE in dry and immersive oxygen-rich environments is an important baseline for future experiments looking at other degradation mechanisms. A predictive aging model for low-density polyethylene insulative cable housings was developed. This model revealed a combination of physical and chemical processes which lead to an increase in permeability and a decrease in strength of the insulator. In creating this predictive model, a gap of knowledge in the literature was revealed in two areas: understanding how the crystallinity of a polymer changes with time and visualizing the predicted pores formed through the insulator which leads to failure. Developing and using an adapted ATR-FTIR method, crystallinity was monitored and compared to bulk crystallinity found via DSC. Inhomogeneity in crystallinity changes were observed but the FTIR method but was found to be less reliable. Pore visualization was found utilizing electrical impedance spectroscopy saturated aged polyethylene films with synthesized citrate-capped gold nanoparticles, and chloroauric acid precursor. results indicate a decreasing impedance of the polyethylene films caused by the transport of ions through the film. SEM imaging was then performed for elemental analysis of the films and counter electrodes for the presence of ions. Chloride and gold ions were detected; however, no nanoparticles were found. This gives an estimated pore size of at least 0.3 nm through the aged film. Cyclic submergence of polyethylene and polypropylene in aqueous solutions of copper sulfate and Harrison’s solution were examined. It was discovered that aging in these mixed conditions and at 90°C did cause a small, yet significant increase to tensile strength for both unaged polyethylene and polypropylene. The PE and PP in cycled and submerged conditions did not have tensile strengths significantly different from dry-aged after 16 weeks. For both solutions, it was determined that capacitance increases with both water tree depth and cable temperature and is relatively independent of changing water tree AR. As for resistance, there is no apparent change between depth percentages of 10 and 80 for both solutions. This is because the water tree has not yet entered the conductor and thus there is no shorting current flowing through the tree yet. Between 80 and 100% water tree depth, it is observed that for both solutions there is a rapid decrease in resistance because the tree is now impacting the conductor shield and allowing shorting current to flow through it. The relationship between resistance and temperature was found to be inversed. As temperature increases, resistance decreases for both water tree solutions with distilled water having the most apparent difference across the range of temperatures simulated. With regards to water tree AR, resistance was found to be relatively independent at depth percentages of 10, 50, and 70, but there was some relationship at 100% depth for both solutions. At this depth, as water tree AR increased, resistance was found to also increase. Through the examination of voltage and electric field distribution plots, it was confirmed for EPR cables that increasing water tree depth leads to increasing distortion. The increase in shorting current at 100% depth for aqueous copper sulfate compared to distilled water was also visualized. Lastly, the relationship between shorting current and temperature for narrow water trees was visualized and validated using the distribution plots. This study has led to a better understanding of the effect of cable temperature, water tree solution, and geometry of the tree region on cable degradation. Furthermore, this study has documented simulation results of water tree degradation in EPR MV cables, which had been previously lacking in information. Future work in this area will add frequency into the mix and examine what effect it has on the rate of cable degradation as a result of water treeing. To compliment the work being carried by UMD on different polymer chemistries, harvested medium voltage (MV) cables were selected for accelerated aging study at ORNL. These medium voltage cables are representative of the vintages and materials that are currently in use at existing nuclear power plants (NPPs). These cables were immersed in water at 90°C and energized for a period of two years at elevated voltage. Partial discharge was measured during this period of time to track potential degradation. Unfortunately, due to the absence of failure, the extent of integration between the UMD techniques and the harvested MV insulation was limited. However, based on the findings and from the UMD research in the previous sections on polyethylene and polypropylene, follow-on characterization for harvested MV cable insulation should focus on sample preparation to take advantage of the UMD techniques to better understand mechanistic degradation in MV cable insulations. This would include: 1.) Utilization of solutions and impedance measurement insulation to track permeability in harvested and accelerated aging insulation samples, 2.) Adaptation of gold nanoparticle synthesis for electrical impedance spectroscopy with supporting SEM characterization to study pore formation in harvested and accelerated aged insulation samples, & 3.) ATR-FTIR crystallinity with multiple temperature dependent harvested MV cable insulation under different air and submerged accelerated aging. In addition, low voltage dielectric spectroscopy and high voltage dissipation factor, tan δ, could be implemented as a condition monitoring tool for harvested MV cable insulation in submerged environments.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Aerial Captured Data and Processed Models in Beaumont-Port Arthur Region in Feb and Oct, 2023

Our Co-design team is from the University of Texas, working on a Department of Energy-funded project focused on the Beaumont-Port Arthur area. As part of this project, we will be developing climate-resilient design solutions for areas of the region. More on www.caee.utexas.edu.We used a DJI Mavic 2 Pro to capture aerial photos in Beaumont-Port Arthur, TX, in February 2023, including:I. Beaumont Soccer ClubII. Corps’ Port Arthur Resident OfficeIII. Halbouty Pump Station comprises its vicinityIV. Lamar University (Including Exxon Power Plants close to Lamar Univ.)V. MLK Boulevard for aerial images of the industry and the ship channelVI. Salt Water Barrier (include some aerial images about the Big Thicket)Aerial photos taken were through DroneDeploy autonomous flight, and models were processed through the DroneDeploy engine as well. All aerial photos are in .JPG format and contained in zipped files for each location.The processed data package including 3D models, geospatial data, mappings, point clouds, and the animation video of Halbouty Pump Station has various file types:- The Adobe Suite gives you great software to open .Tif files.- You can use LASUtility (Windows), ESRI ArcGIS Pro (Windows), or Blaze3D (Windows, Linux) to open a LAS file and view the data it contains.- Open an .OBJ file with a large number of free and commercial applications. Some examples include Microsoft 3D Builder, Apple Preview, Blender, and Autodesk.- You may use ArcGIS, Merkaartor, Blender (with the Google Earth Importer plug-in), Global Mapper, and Marble to open .KML files.- The .tfw world file is a text file used to georeference the GeoTIFF raster images, like the orthomosaic and the DSM. You need suitable software like ArcView to open a .TFW file.This dataset provides researchers with sufficient geometric data and the status quo of the land surface at the locations mentioned above. This dataset could streamline researchers' decision-making processes and enhance the design as well.In October 2023, we had our follow-up data collection, including:I. Beaumont Soccer ClubII. Shipping and Receiving Center at Lamar UniversityAfter the aerial collection, we obtained aerial photos of those two locations mentioned above, as well as processed data (such as point clouds and models).

2D mapping↗

Seeking regularity from irregularity: unveiling the synthesis–nanomorphology relationships of heterogeneous nanomaterials using unsupervised machine learning

Nanoscale morphology of functional materials determines their chemical and physical properties. However, despite increasing use of transmission electron microscopy (TEM) to directly image nanomorphology, it remains challenging to quantify the information embedded in TEM data sets, and to use nanomorphology to link synthesis and processing conditions to properties. We develop an automated, descriptor-free analysis workflow for TEM data that utilizes convolutional neural networks and unsupervised learning to quantify and classify nanomorphology, and thereby reveal synthesis–nanomorphology relationships in three different systems. While TEM records nanomorphology readily in two-dimensional (2D) images or three-dimensional (3D) tomograms, we advance the analysis of these images by identifying and applying a universal shape fingerprint function to characterize nanomorphology. After dimensionality reduction through principal component analysis, this function then serves as the input for morphology grouping through unsupervised learning. We demonstrate the wide applicability of our workflow to both 2D and 3D TEM data sets, and to both inorganic and organic nanomaterials, including tetrahedral gold nanoparticles mixed with irregularly shaped impurities, hybrid polymer-patched gold nanoprisms, and polyamide membranes with irregular and heterogeneous 3D crumple structures. In each of these systems, unsupervised nanomorphology grouping identifies both the diversity and the similarity of the nanomaterial across different synthesis conditions, revealing how synthetic parameters guide nanomorphology development. Our work opens possibilities for enhancing synthesis of nanomaterials through artificial intelligence and for understanding and controlling complex nanomorphology, both for 2D systems and in the far less explored case of 3D structures, such as those with embedded voids or hidden interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Cytogenetic follow-up studies on humans with internal and external exposure to ionizing radiation

Cells exposed to ionizing radiation have a wide spectrum of DNA lesions that include DNA single-strand breaks, DNA double-strand breaks (DSBs), oxidative base damage and DNA-protein crosslinks. Among them, DSB is the most critical lesion, which when mis-repaired leads to unstable and stable chromosome aberrations. Currently, chromosome aberration analysis is the preferred method for biological monitoring of radiation-exposed humans. Here, stable chromosome aberrations, such as inversions and balanced translocations, persist in the peripheral blood lymphocytes of radiation-exposed humans for several years and, therefore, are potentially useful tools to prognosticate the health risks of radiation exposure, particularly in the hematopoietic system. In this review, we summarize the cytogenetic follow-up studies performed by REAC/TS (Radiation Emergency Assistance Center/Training site, Oak Ridge, USA) on humans exposed to internal and external radiation. In the light of our observations as well as the data existing in the literature, this review attempts to highlight the importance of follow-up studies for predicting the extent of genomic instability and its impact on delayed health risks in radiation-exposed victims.

61 RADIATION PROTECTION AND DOSIMETRY↗

U Metal Oxidation with Steam (U)

The Savannah Rive National Laboratory 9SRNL) is evaluating a method to produce uranium oxide (UO 2 ) from uranium metal using steam. The typical methods for making UO 2 yield powders with particle-size ranges of 1 to 50 micron. The goal of the steam oxidation is to produce a depleted uranium (DU) product with a larger particle size that can be used as a surrogate for testing physical and mechanical process techniques to refine uranium and/or plutonium bearing residues. Several studies in the literature indicated that reactions between uranium metal and steam will yield UO 2 as fine powders in the 160 to 500 °C range, but granular materials form above 500°C. Above 880 °C, a hard compact scale forms on the U metal. Furthermore, sintering of UO 2 occurs at about 1300 °C, but it has been stated that the presence of steam enhances the sintering characteristics of UO 2 . Initial studies into the oxidation of DU metal in an atmosphere of argon and steam have been completed. Oxidation of depleted uranium metal in Ar/steam at 600, 710, 700, and 830 °C yielded at UO 2 product with little or no impurity at each temperature. Although not enough sample was available to perform sieve analysis for particle size distribution, SEM images reveal that a significant volume fraction of the products at 710, 770, and 830 °C exceeds 100 microns. The material produced at 600 °C was too fine for programmatic needs. Questions associated with the UO 2 include morphology of product, mechanical strength of the particles, and performance in milling operations. The size of the samples produced in these tests did not allow for quantitative assessment of particle size of mechanical strength. A qualitative assessment of the particles formed at 710, 770, and 830 °C was that the samples produced at 710 and 770 °C were friable, and the sample produced 830 °C had more mechanical strength. Sintering of the samples in Ar/steam at 970 °C appeared to increase the strength of the particles without changing their general particle size characteristics. Due to the small sample sizes, the increase in strength could not be quantified. If the sintering at 970 °C is inadequate, higher sintering temperatures in Ar/steam can be evaluated. Future work will increase scale of the steam oxidation conditions which yield the most-favorable particle-size distributions with sufficient mechanical strength for programming usage. Further consideration will be given to oxidation temperature, steam addition to the reaction vessel, U metal pretreatment, and sintering conditions after oxidation. The UO 2 production could involve a two-step process where particles are formed in steam at lower temperatures (700-850 °C) and then sintered in Ar/steam at elevated temperatures (950-1200 °C). Larger samples (50-100 g each) will provide sufficient UO 2 product for sieve analysis and assessment of mechanical strength relatives to subsequent milling operations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Characterization of Field-Exposed Photovoltaic Modules Featuring Signs of Contact Degradation

Here, this work investigates several photovoltaic (PV) modules that have shown signs of metal contact corrosion due to field exposure in a hot and humid climate. This includes two multicrystalline silicon aluminum back surface field systems with 10 and 14 years of exposure and one monocrystalline silicon passivated emitter and rear cell system with four years of exposure. A comprehensive, multiscale characterization process is used to evaluate these PV modules in great detail. Current–voltage (I−V), Suns-V OC measurements, electroluminescence imaging, infrared imaging, and ultraviolet fluorescence imaging were performed, and locations of interest were cored and analyzed using cross-sectional scanning electron microscopy (SEM). A rigorous, quantitative analysis procedure for the cross-sectional SEM images is proposed and implemented. Careful characterization does reveal that some of these PV modules do indeed exhibit the same classic signs of acetic-acid-based corrosion of the glass frit that is present at the silver/silicon interface, which have been observed previously in PV modules exposed to damp heat in an environmental chamber.

14 SOLAR ENERGY↗

FSVPy: A python-based package for fluorescent streak velocimetry (FSV)

Predictive constitutive equations that connect easy-to-measure transport properties (e.g., viscosity and conductivity) with system performance variables (e.g., power consumption and efficiency) are needed to design advanced thermal and electrical systems. In this work, we explore the use of fluorescent particle-streak analysis to directly measure the local velocity field of a pressure-driven flow, introducing a new Python package (FSVPy) to perform the analysis. Fluorescent streak velocimetry combines high-speed imaging with highly fluorescent particles to produce images that contain fluorescent streaks, whose length and intensity can be related to the local flow velocity. By capturing images throughout the sample volume, the three-dimensional velocity field can be quantified and reconstructed. We demonstrate this technique by characterizing the channel flow profiles of several non-Newtonian fluids: micellar Cetylpyridinium Chloride solution, Carbopol 940, and Polyethylene Glycol. We then explore more complex flows, where significant acceleration is created due to microscale features encountered within the flow. We demonstrate the ability of FSVPy to process streaks of various shapes and use the variable intensity along the streak to extract position-specific velocity measurements from individual images. Thus, we demonstrate that FSVPy is a flexible tool that can be used to extract local velocimetry measurements from a wide variety of fluids and flow conditions.

Mechanics↗

Estimating cluster masses from SDSS multiband images with transfer learning

ABSTRACT The total masses of galaxy clusters characterize many aspects of astrophysics and the underlying cosmology. It is crucial to obtain reliable and accurate mass estimates for numerous galaxy clusters over a wide range of redshifts and mass scales. We present a transfer-learning approach to estimate cluster masses using the ugriz-band images in the SDSS Data Release 12. The target masses are derived from X-ray or SZ measurements that are only available for a small subset of the clusters. We designed a semisupervised deep learning model consisting of two convolutional neural networks. In the first network, a feature extractor is trained to classify the SDSS photometric bands. The second network takes the previously trained features as inputs to estimate their total masses. The training and testing processes in this work depend purely on real observational data. Our algorithm reaches a mean absolute error (MAE) of 0.232 dex on average and 0.214 dex for the best fold. The performance is comparable to that given by redMaPPer, 0.192 dex. We have further applied a joint integrated gradient and class activation mapping method to interpret such a two-step neural network. The performance of our algorithm is likely to improve as the size of training data set increases. This proof-of-concept experiment demonstrates the potential of deep learning in maximizing the scientific return of the current and future large cluster surveys.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Mass Spectrometry Imaging of Bio‐oligomer Polydispersity in Plant Tissues by Laser Desorption Ionization from Silicon Nanopost Arrays

Abstract Mass spectrometry imaging (MSI) enables simultaneous spatial mapping for diverse molecules in biological tissues. Matrix‐assisted laser desorption ionization (MALDI) mass spectrometry (MS) has been a mainstream MSI method for a wide range of biomolecules. However, MALDI‐MSI of biological homopolymers used for energy storage and molecular feedstock is limited by, e.g., preferential ionization for certain molecular classes. Matrix‐free nanophotonic ionization from silicon nanopost arrays (NAPAs) is an emerging laser desorption ionization (LDI) platform with ultra‐trace sensitivity and molecular imaging capabilities. Here, we show complementary analysis and MSI of polyhydroxybutyric acid (PHB), polyglutamic acid (PGA), and polysaccharide oligomers in soybean root nodule sections by NAPA‐LDI and MALDI. For PHB, number and weight average molar mass, polydispersity, and oligomer size distributions across the tissue section and in regions of interest were characterized by NAPA‐LDI‐MSI.

Samarah, Laith Z.↗

Global functional connectivity density alterations in patients with bipolar disorder with auditory verbal hallucinations and modest short‐term effects of transcranial direct current stimulation augmentation treatment—Baseline and follow‐up study

Abstract Objectives To investigate the neuroimaging characteristics of auditory verbal hallucinations (AVHs) in patients with bipolar disorder (BP) experiencing depressive episodes with and without AVHs, and alterations in those characteristics after transcranial direct current stimulation (tDCS). Methods For a baseline pilot study, we recruited 80 patients with BP and depressive status (40 with and 40 without AVHs), and 40 healthy controls (HCs). Their global functional connectivity density (gFCD) was screened by functional magnetic resonance imaging (fMRI). Voxel‐wise one‐way analysis of covariance (ANCOVA) was conducted to detect intergroup differences in gFCD. In a follow‐up study, the effects of 5 weeks of tDCS augmentation treatment on clinical symptoms and gFCD were assessed in the 40 BP patients with AVHs. Results Compared to HCs, BP patients with and without AVHs exhibited increased gFCD in the central parietal lobe, insular lobe, and middle cingulate cortex, with decreased gFCD in the posterior parietal cortex, lateral prefrontal cortex, and occipital lobe (all bilateral). Only patients with AVHs showed increased gFCD in the Broca and Wernicke regions, and decreased gFCD in the hippocampus (all bilateral). After 5 weeks of tDCS, AVHs were slightly alleviated and gFCD abnormalities in the hippocampus were mildly attenuated. Conclusions Patients with BP and AVHs showed disturbances in the brain's communication capacity mainly in the left frontoparietal network, control network, and memory circuitry. Five weeks of tDCS alleviated AVHs slightly, without improving depressive symptoms, and attenuated hippocampal gFCD alterations in these patients.

Zhuo, Chuanjun↗