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At least 19 records

Hints on the Gradual Resizing of the Torus in AGNs through Decomposition of Spitzer/IRS Spectra

Several authors have claimed that less luminous active galactic nuclei (AGNs) are not capable of sustaining a dusty torus structure. Thus, a gradual resizing of the torus is expected when the AGN luminosity decreases. Our aim is to examine mid-infrared observations of local AGNs of different luminosities for the gradual resizing and disappearance of the torus. We applied the decomposition method described by Hernán-Caballero et al. to a sample of ∼100 Spitzer/IRS spectra of low-luminosity AGNs and powerful Seyferts in order to decontaminate the torus component from other contributors. We have also included Starburst objects to ensure secure decomposition of the Spitzer/IRS spectra. We have used the affinity propagation (AP) method to cluster the data into five groups within the sample according to torus contribution to the 5–15 μm range (C{sub torus}) and bolometric luminosity (L{sub bol}). The AP groups show a progressively higher torus contribution and an increase of the bolometric luminosity from Group 1 (C{sub torus}∼0% and log(L{sub bol})∼41) up to Group 5 (C{sub torus}∼80% and log(L{sub bol})∼44). We have fitted the average spectra of each of the AP groups to clumpy models. The torus is no longer present in Group 1, supporting its disappearance at low luminosities. We were able to fit the average spectra for the torus component in Groups 3 (C{sub torus}∼40% and log(L{sub bol})∼42.6), 4 (C{sub torus}∼60% and log(L{sub bol})∼43.7), and 5 to Clumpy torus models. We did not find a good fitting to Clumpy torus models for Group 2 (C{sub torus}∼18% and log(L{sub bol})∼42). This might suggest a different configuration and/or composition of the clouds for Group 2, which is consistent with the different gas content seen in Groups 1, 2, and 3, according to detections of H{sub 2} molecular lines. Groups 3, 4, and 5 show a trend of decreasing torus width (which leads to a likely decrease of the geometrical covering factor), although we cannot confirm it with the present data. Finally, Groups 3, 4, and 5 show an increase of the outer radius of the torus for higher luminosities, consistent with a resizing of the torus according to AGN luminosity.

79 ASTRONOMY AND ASTROPHYSICS↗

How fast can one resize a distributed file system?

Efficient resource utilization becomes a major concern as large-scale distributed computing infrastructures keep growing in size. Malleability, the possibility for resource managers to dynamically increase or decrease the amount of resources allocated to a job, is a promising way to save energy and costs. However, state-of-the-art parallel and distributed storage systems have not been designed with malleability in mind. The reason is mainly the supposedly high cost of data transfers required by resizing operations. Nevertheless, as network and storage technologies evolve, old assumptions about potential bottlenecks can be revisited. In this study, we evaluate the viability of malleability as a design principle for a distributed storage system. We specifically model the minimal duration of the commission and decommission operations. To show how our models can be used in practice, we evaluate the performance of these operations in HDFS, a relevant state-of-the-art distributed file system. We show that the existing decommission mechanism of HDFS is good when the network is the bottleneck, but can be accelerated by up to a factor 3 when storage is the limiting factor. We also show that the commission in HDFS can be substantially accelerated. With the highlights provided by our model, we suggest improvements to speed both operations in HDFS. We discuss how the proposed models can be generalized for distributed file systems with different assumptions and what perspectives are open for the design of efficient malleable distributed file systems.

97 MATHEMATICS AND COMPUTING↗

Mark-18A Cold Runs

The Savannah River National Laboratory (SRNL) is tasked by the National Nuclear Security Administration (NNSA) to recover highly valued isotopes from irradiated Mark-18A (Mk-18A) targets. The Savannah River Site (SRS) has sixty-five Mk-18A targets available for the recovery of the high valued materials. The sixty-five Mk-18A targets are currently stored in the L-Area Basin and will be removed one at a time and individually transported to SRNL. Upon receipt at SRNL, the Mk-18A target material will be removed from the confinement, dissolved, chemically separated, and calcined to a stable oxide. The flowsheet is designed to recover the plutonium as well as the trivalent actinides. The remaining unrecovered material will be discarded to the high activity drain (HAD) system in SRNL. A specially designed cask was procured for transport of the targets from L-Area to SRNL. Once received at SRNL, the targets will be loaded into the back of Cell 7 and resized as they enter the cell. The resized targets (1/4 lengths) will then be processed one at a time through the following processes: caustic dissolution and filtration; acidic dissolution and filtration, Reillex anion exchange, diglycolamide (DGA) cation exchange; and DGA calcination. This processing will result in two product streams. The first is an aqueous plutonium solution which will be removed from the shielded cells and taken to a glovebox for further purification and conversion to an oxide. The second is a calcined oxide containing the Am and Cm as well as other lanthanide fission products which will be removed from the shielded cells using a bagless transfer system. Both materials will be packaged for shipment to Oak Ridge National Laboratory (ORNL). All equipment to carry out this process was designed, procured or fabricated, and installed in a mock-up facility (716-4A) at SRS to allow for simulation testing in a non-radioactive area. This equipment was then dismantled and transferred from 716-4A to 773-A and installed in the SRNL Shielded Cells. After installation in the shielded cells facility testing was performed using water followed by surrogates and cold chemicals. Issues were identified during these evaluations, including equipment issues as well as technical challenges. Many of the issues were rectified during performance of the cold runs, and the remaining have a resolution identified. Table ES-1 provides a summary of all issues identified during the cold run operations, as well as the status and identified resolutions to outstanding issues.

07 ISOTOPE AND RADIATION SOURCES↗

Responsive Image Inline Filter

RIIF is a contributed module for the Drupal php web application framework (drupal.org). It is written as a helper or sub-module of other code which is part of version 8 "core Drupal" and is intended to extend its functionality. It allows Drupal to resize images uploaded through the user-facing text editor within the Drupal GUI (a.k.a. "inline images") for various browser widths. This resizing is already done foe other images through the parent "Responsive Image" core module. This code extends that functionality to inline images.

Freeman, Ian↗

Deep learning methods for event verification and image re-purposing detection

Systems and methods herein describe accessing an image, generating a resized image, generating an image feature vector by applying an image classification neural network to the resized image, generating analysis of the image by processing the image feature vector using a machine-learning classifier trained to analyze the image feature vector, and based on the analysis, determining an event that is attributed to the image.

Nataraj, Lakshmanan↗

Mark-18A Target Material Recovery Program: Initial Hot Startup

The Savannah River National Laboratory (SRNL) has been tasked by the National Nuclear Security Administration to recover highly valued isotopes from irradiated Mark-18A (Mk-18A) targets. The Savannah River Site (SRS) has sixty-five Mk-18A targets available for the recovery of the high valued materials. The Mk-18A targets were manufactured with Pu-242 then irradiated under high neutron flux in K-Reactor at the SRS from 1968 to 1978. The sixty-five Mk-18A targets are currently stored in the SRS L-Area Basin and will be removed one at a time and individually transported to SRNL. Upon receipt at SRNL, the Mk-18A target material will be removed from the confinement, dissolved, chemically separated, and calcined to a stable oxide. The flowsheet is designed to recover the plutonium as well as the trivalent actinides. The original targets were manufactured with varying quantities of Pu-242, ranging from 5.2 grams to 121.5 grams. Taking a graded approach to process start up, the lowest loaded target (FT-80-03) was selected as the first target to be received and processed at SRNL. As operational experience and knowledge is gained from processing targets, higher loaded targets will be selected for processing to increase the quantities of valuable isotopes recovered. Due to dose concerns, the receipt and processing of the Mk-18A targets is performed in the SRNL Shielded Cells Facility. The targets are stored in a double J-can confinement in the L-Area Basin. A specially designed cask was procured for transport of the targets from L-Area to SRNL. Once received at SRNL, the targets are loaded into the back of Cell 7 and resized as they enter the cell. The resized targets (1/4 length) are then processed one at a time through the following processes: caustic dissolution and filtration, acidic dissolution and filtration, elutable Reillex anion exchange, diglycolamide (DGA) resin extraction, and DGA calcination. This processing results in two product streams. The first is an aqueous plutonium solution which is removed from the shielded cells and taken to a glovebox for further purification and conversion to an oxide. The second is a calcined oxide product containing the Am and Cm as well as other lanthanide fission products which is removed from the shielded cells using a bagless transfer system. Both materials are packaged for shipment to Oak Ridge National Laboratory (ORNL). This paper will discuss the operating experience, lessons learned, and results from initial process hot startup.

Armstrong, Christopher [Savannah River National La↗

An Efficient Wait-Free Vector

The vector is a fundamental data structure, which provides constant-time access to a dynamically-resizable range of elements. Currently, there exist no wait-free vectors. The only non-blocking version supports only a subset of the sequential vector API and exhibits significant synchronization overhead caused by supporting opposing operations. Since many applications operate in phases of execution, wherein each phase only a subset of operations are used, this overhead is unnecessary for the majority of the application. To address the limitations of the non-blocking version, we present a new design that is wait-free, supports more of the operations provided by the sequential vector, and provides alternative implementations of key operations. These alternatives allow the developer to balance the performance and functionality of the vector as requirements change throughout execution. Compared to the known non-blocking version and the concurrent vector found in Intel’s TBB library, our design outperforms or provides comparable performance in the majority of tested scenarios. Over all tested scenarios, the presented design performs an average of 4.97 times more operations per second than the non-blocking vector and 1.54 more than the TBB vector. In a scenario designed to simulate the filling of a vector, performance improvement increases to 13.38 and 1.16 times. This work presents the first ABA-free non-blocking vector. Finally, unlike the other non-blocking approach, all operations are wait-free and bounds-checked and elements are stored contiguously in memory.

97 MATHEMATICS AND COMPUTING↗

Image Provenance Analysis

The literature of multimedia forensics is mainly dedicated to the analysis of single assets (such as sole image or video files), aiming at individually assessing their authenticity. Different from this, image provenance analysis is devoted to the joint examination of multiple assets, intending to ascertain their history of edits, by evaluating pairwise relationships. Each relationship, thus, expresses the probability of one asset giving rise to the other, through either global or local operations, such as data compression, resizing, color-space modifications, content blurring, and content splicing. The principled combination of these relationships unveils the provenance of the assets, also constituting an important forensic tool for authenticity verification. This chapter introduces the problem of provenance analysis, discussing its importance and delving into the state-of-the-art techniques to solve it.

Moreira, Daniel↗

Life Cycle Assessment of Vehicle Lightweighting: A Physics-Based Model To Estimate Use-Phase Fuel Consumption of Electrified Vehicles

Assessing the life-cycle benefits of vehicle lightweighting requires a quantitative description of mass-induced fuel consumption (MIF) and fuel reduction values (FRVs). We have extended our physics-based model of MIF and FRVs for internal combustion engine vehicles (ICEVs) to electrified vehicles (EVs) including hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), and battery electric vehicles (BEVs). We illustrate the utility of the model by calculating MIFs and FRVs for 37 EVs and 13 ICEVs. BEVs have much smaller MIF and FRVs, both in the range 0.04-0.07 L e /(100 km 100 kg), than those for ICEVs which are in the ranges 0.19-0.32 and 0.16-0.22 L/(100 km 100 kg), respectively. The MIF and FRVs for HEVs and PHEVs mostly lie between those for ICEVs and BEVs. Powertrain resizing increases the FRVs for ICEVs, HEVs and PHEVs. Lightweighting EVs is less effective in reducing greenhouse gas emissions than lightweighting ICEVs, however the benefits differ substantially for different vehicle models. The physics-based approach outlined here enables model specific assessments for ICEVs, HEVs, PHEVs, and BEVs required to determine the optimal strategy for maximizing the life-cycle benefits of lightweighting the light-duty vehicle fleet.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Quantum frequency resampling

In signal processing, resampling algorithms can modify the number of resources encoding a collection of data points. Downsampling reduces the cost of storage and communication, while upsampling interpolates new data from limited one, e.g., when resizing a digital image. We present a toolset of quantum algorithms to resample data encoded in the probabilities of a quantum register, using the quantum Fourier transform to adjust the number of high-frequency encoding qubits. We discuss advantage over classical resampling algorithms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Nanodisk fabrication by nanosphere lithography

Top-down fabrication of regular nanodisk arrays from an A{sub 3}B{sub 5} epitaxial heterostructure containing quantum well is demonstrated. Dry ion etching through the mask was emloyed. The spin-coated monolayer of polystyrene nanospheres served as a mask. Nanodisk diameter could be precisely controlled by oxygen plasma resizing of spheres after deposition. Nanodisks with diameters down to 200 nm were made.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Scalable pCT Image Reconstruction Delivered as a Cloud Service

We describe a cloud-based medical image reconstruction service designed to meet a real-time and daily demand to reconstruct thousands of images from proton cancer treatment facilities worldwide. Rapid reconstruction of a three-dimensional Proton Computed Tomography (pCT) image can require the transfer of 100 GB of data and use of approximately 120 GPU-enabled compute nodes. The nature of proton therapy means that demand for such a service is sporadic and comes from potentially hundreds of clients worldwide. We thus explore the use of a commercial cloud as a scalable and cost-efficient platform for pCT reconstruction. To address the high performance requirements of this application we leverage Amazon Web Services' GPU-enabled cluster resources that are provisioned with high performance networks between nodes. To support episodic demand, we develop an on-demand multi-user provisioning service that can dynamically provision and resize clusters based on image reconstruction requirements, priorities, and wait times. We compare the performance of our pCT reconstruction service running on commercial cloud resources with that of the same application on dedicated local high performance computing resources. We show that we can achieve scalable and on-demand reconstruction of large scale pCT images for simultaneous multi-client requests, processing images in less than 10 minutes for less than $10 per image.

Cloud computing↗

IRIS: A Performance-Portable Framework for Cross-Platform Heterogeneous Computing

From edge to exascale, computer architectures are becoming more heterogeneous and complex. The systems typically have fat nodes, with multicore CPUs and multiple hardware accelerators such as GPUs, FPGAs, and DSPs. This complexity is causing a crisis in programming systems and performance portability. Several programming systems are working to address these challenges, but the increasing architectural diversity is forcing software stacks and applications to be specialized for each architecture. As we show, all of these approaches critically depend on their software framework for discovery, execution, scheduling, and data orchestration. To address this challenge, we believe that a more agile and proactive software framework is essential to increase performance portability and improve user productivity. To this end, we have designed and implemented IRIS: a performance-portable framework for cross-platform heterogeneous computing. IRIS can discover available resources, manage multiple diverse programming platforms (e.g., CUDA, Hexagon, HIP, Level Zero, OpenCL, OpenMP) simultaneously in the same execution, respect data dependencies, orchestrate data movement proactively, and provide for user-configurable scheduling. To simplify data movement, IRIS introduces a shared virtual device memory with relaxed consistency among different heterogeneous devices. IRIS also adds an automatic kernel workload partitioning technique using the polyhedral model so that it can resize kernels for a wide range of devices. Our evaluation on three architectures, ranging from Qualcomm Snapdragon to a Summit supercomputer node, shows that IRIS improves portability across a wide range of diverse heterogeneous architectures with negligible overhead.

97 MATHEMATICS AND COMPUTING↗

Evaluation of Composite Structural Materials for Heliostat Cost Reduction

Structures manufactured from steel comprise up to 40% of a CSP heliostat's cost. Composite structures represent a potential opportunity to reduce this cost. A reference heliostat structural model has been created with a reflector area of 25m 2 . The design, constructed of low-carbon steel, pro-vides baseline deflection and stiffness under a 21 m/s operating wind speeds. Wind loads on the tracker structure are determined for both operating and stow conditions. An established roster of suitable metal alternative materials is considered including: glass, basalt, and carbon reinforced polymer (GFRP, BFRP, and CFRP respectively). Three heliostat components are investigated: the pylon, torque tube, and the purlin-strut assembly. Composite material properties are substituted for those of steel, and the beams are re-sized to match the original steel components' deflection under given wind loads. Weight and cost changes resulting from this resizing are evaluated. It is found that GFRP and BFRP represent a 3X–6X cost premium for the same operating deflection character-istics as steel across all three investigated component classes; with weight reduction only achieved for the purlin-strut assembly. While CFRP components can achieve approximately 25–75% weight savings depending on the application, this comes with a 9X–14X cost increase over the steel base-line for tube-type structures and roughly 5X cost increase when replacing c-channel structures. This work does not rule out the possibility of cost savings when the heliostat design and kinematics to take advantage of composites' specific properties.

14 SOLAR ENERGY↗

Evaluation of U-net-based Image Segmentation Model to Digital Mammography

Detecting suspicious lesions in medical imaging is the important first step in computer-aided detection (CAD) systems. However, detecting abnormalities in breast tissue is difficult due to the lesion's varying size, shape, margin, and contrast with the background tissue. We focused on mass segmentation, a method that provides notable morphological features by outlining contours of masses. Accurate segmentation is crucial for correct diagnosis. Recent advancements in deep learning have improved object detection and segmentation, and these techniques are also being applied to medical imaging studies. We focused on U-net, which is a recently developed mass segmentation algorithm based on a fully convolutional network. The U-net architecture consists of (1) a contracting path to increase the resolution of the output and (2) a symmetric expanding path to better locate the region of interest. The performance of a U-net model was tested with 63 digital mammograms from INbreast, a publicly available database. We trained the model with images resized to 40x40 pixels and conducted 10-fold cross-validation to prevent overfitting. The model's performance with respect to breast density and the lesion's BI-RADS rating was also investigated. Dice coefficients (DC) were used as a performance measure to compare the predicted segmentation of the model with the ground truth. Logistic regression and an analysis of variance were performed to determine the significance of the DCs with regards to breast density and lesion behavior and to calculate the 95% confidence interval. The average DC was 0.80. The difference between DCs for BI-RADS 2 and 4c and for BI-RADS 2 and 5 were significant, suggesting that the model has more difficulty in segmenting benign lesions.

Cho, Priscilla↗

SU-G-JeP1-10: Feasibility of CyberKnife Tracking Using the Previously-Implanted Permanent Brachytherapy Seed Cloud

Purpose: Robotic radiosurgery is a salvage treatment option for patients with recurrent prostate cancer. We explored the feasibility of tracking the bolus of permanent prostate implants (PPI) using image recognition software optimized to track spinal anatomy. Methods: Forty-five inert iodine seeds were implanted into a gelatin-based prostate phantom. Four superficial gold seeds were inserted to provide ground-truth alignment. A CT scan of the phantom (120 kVp, 1 mm slice thickness) was acquired and a single-energy iterative metal artifact reduction (MAR) algorithm was used to enhance the quality of the DRR used for tracking. CyberKnife treatment plans were generated from the MAR CT and regular CT (no-MAR) using spine tracking. The spine-tracking grid was centered on the bolus of seeds and resized to encompass the full seed cloud. A third plan was created from the regular CT scan, using fiducial tracking based on the 4 superficial gold seeds with identical align-center coordinates. The phantom was initially aligned using the fiducial-tracking plan. Then the MAR and no-MAR spine-tracking plans were loaded without moving the phantom. Differences in couch correction parameters were recorded in the case of perfect alignment and after the application of known rotations and translations (roll/pitch of 2 degrees; translations XYZ of 2 cm). Results: The spine tracking software was able to lock on to the bolus of seeds and provide couch corrections both in the MAR and no-MAR plans. In all cases, differences in the couch correction parameters from fiducial alignment were <0.5 mm in translations and <1 degree in rotations. Conclusion: We were able to successfully track the bolus of seeds with the spine-tracking grid in phantom experiments. For clinical applications, further investigation and developments to adapt the spine-tracking algorithm to optimize for PPI seed cloud tracking is needed to provide reliable tracking in patients. One of the authors (MD) has received research support and speaker honoraria from Accuray.

60 APPLIED LIFE SCIENCES↗

NETL RDE Image Classification Dataset 2025 - 14 Classes

Dataset including high-speed down-axis RDE images used for updated image classification study. This dataset includes 180,000 images with 14 classifications: 1CW, 1CCW, 2CW, 2CCW, 3CW, 3CCW, Deflagration, 4CW, 4CCW, 5CW, and 5CCW. Images are cropped to center annulus, and resized to 301x301 pixels. Images are filtered using the AFRL Beta correction factor.

Dataset↗