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Timeseries Photos of a Variably Inundated Stream: Umtanum Creek, Washington, United States

This dataset is associated with a broader study using game camera timeseries photos collected to evaluate stream variable inundation via changes in width (i.e. wet fraction). Four game cameras were deployed along Umtanum Creek (Washington, United States) to track changes in stream inundation over time. Drone imagery was collected at the same location on October 18, 2024 which was used to construct a digital elevation model (DEM) of the streambed topography. The associated paper and data can be found at https://doi.org/10.1016/j.envsoft.2025.106715 (Bao et al., 2025a)) and https://doi.org/10.15485/2589885 (Bao et al., 2025b), respectively. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to this readme, this data package also includes a file-level metadata (FLMD) files that describes each file and a data dictionaries (DD) that describe all column/row headers and variable definitions. This dataset is comprised of (1) file-level metadata; (2) data dictionary; (3) readme; (4) field metadata; (5) field protocol; and (5) folders containing game camera photos. Game camera photos are organized into folders for each camera (CDL, CUL, CDR, CUR; see readme for information on camera naming) by the month photos were collected. All files are .csv, .jpg, or .pdf.

AI image segmentation↗

NMIS with Imaging and Gamma Ray Spectrometry for Pu, HEU, HE and Other Materials

The Nuclear Material Identification System (NMIS) has been under development at ORNL and the National Nuclear Security Administration (NNSA) Y-12 National Security Complex since 1984. In the mid-1990s, what is now the US Department of Energy (DOE) Office of Nuclear Verification (ONV) realized that it was a useful technology for future arms control treaty applications and supported further development of the system. In 2004, fast-neutron imaging was incorporated into the system. In 2007, the ONV decided to develop a fieldable version of the system, designated as FNMIS, for potential use in future treaties. The FNMIS is being developed to be compatible with the eventual incorporation of gamma-ray spectrometry and an information barrier. This report addresses how and what attributes could be determined by the FNMIS system with gamma-ray spectrometry. The NMIS is a time-dependent coincidence system that incorporates tomographic imaging (including mapping of the fission sites) and gamma-ray spectrometry. It utilizes a small, lightweight (30 lb), portable deuterium-tritium (DT) neutron (14.1 MeV) generator (4 x 10 7 neutrons/second) for active interrogation and can also perform passive interrogation. A high-purity germanium (HPGe) gamma-ray detector with multichannel analysis can be utilized in conjunction with the source for active interrogation or passively. The system uses proton recoil scintillators: 32 small 2.5 x 2.5 x 10.2-cm-thick plastic scintillators for imaging and at least two 2 x 2 arrays of 27 x 27 x 10-cm-thick plastic scintillators that detect induced fission radiation. The DT generator contains an alpha detector that time and directionally tags a fan beam of some of the neutrons emitted and subdivides it into pixels. A fast (1 GHz) time correlation processor measures the time-dependent coincidence among all detectors in the system. A computer-controlled scanner moves the small detectors and the source appropriately for scanning a target object for imaging. The system is based on detection of transmitted 14.1 MeV neutrons, fission neutrons, and gamma rays from spontaneous, inherent source fission of the target, fission neutrons and gamma rays induced by the external DT source, gamma rays from natural emissions of uranium and plutonium, and induced gamma-ray emission by the interaction of the 14.1 MeV neutrons from the DT source. The NMIS can and has been used with a time-tagged californium spontaneous fission source. It has also been used with pulsed interrogation sources such as LINACs, DT, and deuterium-deuterium (DD) sources. This system is uniquely suited for detection of shielded highly enriched uranium (HEU), plutonium, and other special nuclear materials and detection of high explosives (HE) and chemical agents. The NMIS will be adapted to utilize a trusted processor that incorporates information barrier and authentication techniques using open software and then be useful in some international applications for materials whose characteristics may be classified. The proposed information barrier version of the NMIS system would consist of detectors and cables, the red (classified side) computer system, which processes the data, and the black (unclassified side) computer, which handles the computer interface. The system could use the 'IB wrapper' concept proposed by Los Alamos National Laboratory and the software integrity (digital signatures) system proposed by Sandia. Since it is based entirely on commercially available components, the entire system, including NMIS data acquisition boards, can be built with commercial off-the-shelf components. This system is being developed into a fieldable system (FNMIS) for potential arms control treaties by the ONV. The system will be modularly constructed with the RF shielded modules connected to the processor by appropriate control and signal cable in metal conduit. The FNMIS is presently being designed for eventual incorporation of gamma-ray spectrometry and an information barrier to protect classified information. The system hardware and software can be configured to obtain the following: plutonium presence, plutonium mass, Pu-240/239 ratio, plutonium geometry, plutonium metal vs non-metallic (absence of metal), time (age) since processing for plutonium (or last purification), uranium presence, uranium mass, uranium enrichment, uranium geometry, uranium metal vs non-metallic compound (absence of metal), beryllium presence and mass, tritium and deuterium gas bottle presence, HE, and chemical weapons. A matrix of the quantities determined, the method of determination, whether active (external neutron source) or passive, and the measurement equipment involved is given in the Tables 1-4. Some of these attributes can be obtained by multiple data analysis methods. The gamma-ray spectrometry methods for HEU, plutonium, and HE have been developed by other laboratories, are well known, and will be incorporated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Detailed Hydrographic Feature Extraction from High-Resolution LiDAR Data

Detailed hydrographic feature extraction from high-resolution light detection and ranging (LiDAR) data is investigated. Methods for quantitatively evaluating and comparing such extractions are presented, including the use of sinuosity and longitudinal root-mean-square-error (LRMSE). These metrics are then used to quantitatively compare stream networks in two studies. The first study examines the effect of raster cell size on watershed boundaries and stream networks delineated from LiDAR-derived digital elevation models (DEMs). The study confirmed that, with the greatly increased resolution of LiDAR data, smaller cell sizes generally yielded better stream network delineations, based on sinuosity and LRMSE. The second study demonstrates a new method of delineating a stream directly from LiDAR point clouds, without the intermediate step of deriving a DEM. Direct use of LiDAR point clouds could improve efficiency and accuracy of hydrographic feature extractions. The direct delineation method developed herein and termed “mDn”, is an extension of the D8 method that has been used for several decades with gridded raster data. The method divides the region around a starting point into sectors, using the LiDAR data points within each sector to determine an average slope, and selecting the sector with the greatest downward slope to determine the direction of flow. An mDn delineation was compared with a traditional grid-based delineation, using TauDEM, and other readily available, common stream data sets. Although, the TauDEM delineation yielded a sinuosity that more closely matches the reference, the mDn delineation yielded a sinuosity that was higher than either the TauDEM method or the existing published stream delineations. Furthermore, stream delineation using the mDn method yielded the smallest LRMSE.

58 GEOSCIENCES↗

High Energy Quasi - Differential Neutron Emission Measurements of 181 Ta and 19 F [Slides]

This presentation begins with the motivation for performing 181 Ta and 19 F high energy quasi-differential and neutron emission measurements. It then provides a discussion of significant pulse digitization upgrade. The Quasi-Differential methodology and importance for validating nuclear data are provided. Preliminary results from 181 Ta and 19 F are displayed. The presentation concludes with a discussion and future studies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A 32-Channel Cryo-CMOS ASIC for SNSPD Biasing and Readout with Picosecond Timing

Superconducting nanowire single-photon detectors (SNSPD) are a promising technology for particle detection. Although SNSPDs have demonstrated picosecond timing accuracy, scaling up large arrays has proved challenging. In this work, we introduce a 32-channel cryo-CMOS application-specifc integrated circuit (ASIC) that can be tightly integrated with SNSPD arrays. The ASIC is designed to operate at a temperature of 4K and can perform up to 32 simultaneous timing measurements with a root-mean-square (RMS) accuracy of 8.0ps. The ASIC includes on-chip circuitry for externally biasing superconducting devices, low-noise amplifers for reading superconducting devices, high-resolution time-to-digital converters (TDC) for time-tagging events, and serializers for transmitting data to room-temperature electronics. The ASIC is manufactured in a 22nm FDSOI process and occupies an area of 4.0mm x 1.0mm. The performance of the ASIC was verifed using custom cryogenic device models internally developed for the 22nm SOI process. Measurement results will be presented at the conference.

Fredenburg, Jeff↗

Estimating Vadose Zone Flow Properties at the 100 K-East Soil Flushing Site Using ERT Monitoring Data: 2023 Interim Report - 100 KE Soil Property Estimation

In situ soil flushing is being using at the Hanford 100 K-East (100 KE) area to transport mobile chromium contamination in the vadose zone to the water table, where it can be collected and treat through pump and treat operations. The efficacy of soil flushing is directly related to the volume of clean water that infiltrates through contaminated soils. In practice, it is infeasible to comprehensively monitor which regions of the vadose zone are being infiltrated through direct sampling of pore water. Consequently, there can be significant uncertainty about which regions of the subsurface have been treated, especially if hydrogeologic conditions are favorable for the development of unstable flows and preferred flow pathways through the vadose zone (Jarvis, Koestel, and Larsbo 2016). Current approaches for quantitative monitoring of soil flushing performance rely on contaminant concentration measurements collected from extractions wells. There is no quantitative information on the volume of flush water delivered to targeted regions of the vadose zone at the Hanford Site, leading to significant uncertainty regarding source term removal and long-term impacts to groundwater. If the subsurface hydrogeologic properties at the 100 KE Area were adequately known, qualitative metrics of soil flushing performance could be simulated, thereby negating expenses required to obtain quantitative performance information through borehole drilling/sampling. However, estimating in situ hydrogeologic properties has long proven elusive, due primarily to a lack of sufficient information to constrain heterogeneous property estimates to a useful degree of certainty. Estimating vadose zone hydrogeologic properties is particularly challenging due the dependence of hydraulic conductivity on saturation. This report describes progress toward a first-of-its-kind demonstration using surface time-lapse 3D electrical resistivity tomography (ERT) monitoring data to estimate the hydrogeologic properties that control flush water transport at the 100 KE soil flushing site. The ultimate objective is (1) to verify sufficient information exists in the ERT monitoring data to adequately resolve vadose zone hydraulic properties, and (2) generate a “digital twin” (i.e., a numerical simulator) that can be used to simulate the amount of flush water that has been delivered to each targeted region of the vadose zone, and thereby assess the efficacy of flush water delivery. Resulting performance estimates can be used in leu of comprehensive borehole drilling and direct sampling (or wellbore logging) that would otherwise be required to obtain the same information.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A New Infrared Criterion for Selecting Active Galactic Nuclei to Lower Luminosities

We present a spectroscopic and photometric analysis of a sample of 416,288 galaxies from the Sloan Digital Sky Survey (SDSS) matched to mid-infrared (mid-IR) data from the Wide-field Infrared Survey Explorer (WISE). By using a new spectroscopic fitting package, GELATO (Galaxy/AGN Emission Line Analysis TOol), we are able to retrieve emission line fluxes and uncertainties for SDSS spectra and robustly determine the presence of broad lines and outflowing components, enabling us to investigate WISE color space as a function of optical spectroscopic properties. In addition, we pursue spectral energy distribution template fitting to assess the relative active galactic nucleus (AGN) contribution and nuclear obscuration to compare to existing mid-IR selection criteria with WISE. We present a selection criterion in mid-IR color space to select AGNs with an ~80% accuracy and a completeness of ~16%. This is the first mid-IR color selection defined by solely using the distribution of Type I and Type II optical spectroscopic AGNs in WISE mid-IR color space. Our selection is an improvement of ~50% in the completeness of targeting spectroscopic AGNs with WISE down to an SDSS r < 17.77 mag. In addition, our new criterion targets a less-luminous population of AGNs, with on average lower [O ιιι] luminosities by~30% ( > 0.1 dex) compared to typical WISE color–color selections. With upcoming large photometric surveys without corresponding spectroscopy, our method presents a way to select larger populations of AGNs at lower AGN luminosities and higher nuclear obscuration levels than traditional mid-IR color selections.

79 ASTRONOMY AND ASTROPHYSICS↗

Transforming Energy through Computational Science: Computing for Clean Energy

This fact sheet discusses the opportunity space for NREL's computational science capabilities to address national clean energy objectives. Achieving a carbon-free power sector by 2035 as a step towards a decarbonized U.S. energy economy in 2050 will require major advances in power generation, autonomous energy systems, transportation, and buildings/communities. Development of integrated modeling approaches for complex energy systems will be essential for deployment. Success requires developments in optimization and control theory, complemented by machine learning (ML) and artificial intelligence (AI), all of which in turn need targeted investments in breadth and scale of computing. This document defines an opportunity space where: embracing computing can link established research and development (R&D) to a decarbonization agenda; pursuing emerging approaches can accelerate the pace of technology advancement across the portfolio; and leading by example could reduce the carbon footprint of computing worldwide.

advanced computing↗

Subsurface Characterization for Evaluating Geothermal Resource Potential from Existing Oil and Gas Wells in Tuttle, Oklahoma: Preprint

Oil and gas (O&G) wells often encounter co-produced hot water, possibly suitable for geothermal direct-use applications. The City of Tuttle is located on the eastern part of the Anadarko sedimentary basin in Oklahoma with high heat-in-place potential and recovery capability at depth. This study aims at demonstrating the potential of geothermal energy production for direct-use applications in two public schools and 250 nearby houses in Tuttle via repurposing existing O&G wells. In this scope, geochemistry, geology, and borehole log data were collected and incorporated into a 3D conceptual subsurface model. A digital elevation model (DEM) was used to represent the study area topography with four O&G wells. In addition, hydrogeochemical characteristics of the geothermal fluid and scaling potential were analyzed using ternary diagrams and chemical ratios to develop mixing models. The subsurface geology model indicated that the study area primarily consists of Permian to Mississippian Sandstone and Limestone formations, implying a porosity ranging between 12% and 22%, and a permeability up to 3.90E-14 m2 in certain reservoir levels. The reservoir temperature is expected to be ranging between 80 degrees C to 95 degrees C around 3 km depth with an average temperature gradient of 22.8 degrees C/km. Chemical geothermometers also estimated the reservoir temperature as 90 degrees C. Findings of the chemical model demonstrated that the geothermal fluid is Sodium-Potassium-Chloride-Sulfate type and possibly mixed with shallow groundwater resulting in higher Ca and Mg concentrations and lower Na/K ratio implying lower calcite scaling. These results comprehensively characterize the potential of geothermal resources in the study area and imply that geothermal energy production by repurposing existing O&G wells is suitable for low-temperature direct-use applications.

GEOTHERMAL ENERGY↗

Firmware development for the ATLAS TileCal sROD

TileCal is the central hadronic calorimeter of the ATLAS experiment at the Large Hadron Collider (LHC) at CERN. A main upgrade of the LHC (also called Phase-II) is planned in order to increase the instantaneous luminosity in 2022. At the TileCal level, the upgrade involves the redesign of the complete read-out architecture, affecting both the front-end and the back-end electronics. In the new read-out architecture, the front-end electronics will transmit digitized information of the full detector to the back-end system every single bunch crossing. Thus, the back-end system must provide digital calibrated information to the first level of trigger. Having all detector data per bunch crossing in the back-end will increase the precision and granularity of the trigger information, improving this way the trigger efficiencies. A reduced part of the detector, 1/256 of the total, will be equipped with the new electronics during 2014 to evaluate the proposed architecture in real conditions in the so-called 'demonstrator project'. The upgraded version of the Read-Out Driver (sROD) will be the core element of the back-end electronics in Phase-II. The sROD demonstrator is a prototype that is being developed to validate in the demonstrator project the future sROD for Phase-II. This module includes two Xilinx Series 7 Field Programmable Gate Arrays (FPGAs) for data receiving and processing and will be installed and working in an ATCA framework. A complete description of the sROD functionality in terms of firmware will be introduced. In addition, the status of the firmware development and a summary of the main milestones achieved and the future plans will be presented. (authors)

43 PARTICLE ACCELERATORS↗

Subsurface Characterization for Evaluating Geothermal Resource Potential from Existing Oil and Gas Wells in Tuttle, Oklahoma

Oil and gas (O&G) wells often encounter co-produced hot water, possibly suitable for geothermal direct-use applications. The City of Tuttle is located on the eastern part of the Anadarko sedimentary basin in Oklahoma with high heat-in-place potential and recovery capability at depth. This study aims at demonstrating the potential of geothermal energy production for direct-use applications in two public schools and 250 nearby houses in Tuttle via repurposing existing O&G wells. In this scope, geochemistry, geology, and borehole log data were collected and incorporated into a 3D conceptual subsurface model. A digital elevation model (DEM) was used to represent the study area topography with four O&G wells. In addition, hydrogeochemical characteristics of the geothermal fluid and scaling potential were analyzed using ternary diagrams and chemical ratios to develop mixing models. The subsurface geology model indicated that the study area primarily consists of Permian to Mississippian Sandstone and Limestone formations, implying a porosity ranging between 12% and 22%, and a permeability up to 3.90E-14 m2 in certain reservoir levels. The reservoir temperature is expected to be ranging between 80 degrees C to 95 degrees C around 3 km depth with an average temperature gradient of 22.8 degrees C/km. Chemical geothermometers also estimated the reservoir temperature as 90 degrees C. Findings of the chemical model demonstrated that the geothermal fluid is Sodium-Potassium-Chloride-Sulfate type and possibly mixed with shallow groundwater resulting in higher Ca and Mg concentrations and lower Na/K ratio implying lower calcite scaling. These results comprehensively characterize the potential of geothermal resources in the study area and imply that geothermal energy production by repurposing existing O&G wells is suitable for low-temperature direct-use applications.

gas wells↗

TH-EF-BRA-06: A Novel Retrospective 3D K-Space Sorting 4D-MRI Technique Using a Radial K-Space Acquisition MRI Sequence

Purpose: Current retrospective 4D-MRI provides superior tumor-to-tissue contrast and accurate respiratory motion information for radiotherapy motion management. The developed 4D-MRI techniques based on 2D-MRI image sorting require a high frame-rate of the MR sequences. However, several MRI sequences provide excellent image quality but have low frame-rate. This study aims at developing a novel retrospective 3D k-space sorting 4D-MRI technique using radial k-space acquisition MRI sequences to improve 4D-MRI image quality and temporal-resolution for imaging irregular organ/tumor respiratory motion. Methods: The method is based on a RF-spoiled, steady-state, gradient-recalled sequence with minimal echo time. A 3D radial k-space data acquisition trajectory was used for sampling the datasets. Each radial spoke readout data line starts from the 3D center of Field-of-View. Respiratory signal can be extracted from the k-space center data point of each spoke. The spoke data was sorted based on its self-synchronized respiratory signal using phase sorting. Subsequently, 3D reconstruction was conducted to generate the time-resolved 4D-MRI images. As a feasibility study, this technique was implemented on a digital human phantom XCAT. The respiratory motion was controlled by an irregular motion profile. To validate using k-space center data as a respiratory surrogate, we compared it with the XCAT input controlling breathing profile. Tumor motion trajectories measured on reconstructed 4D-MRI were compared to the average input trajectory. The mean absolute amplitude difference (D) was calculated. Results: The signal extracted from k-space center data matches well with the input controlling respiratory profile of XCAT. The relative amplitude error was 8.6% and the relative phase error was 3.5%. XCAT 4D-MRI demonstrated a clear motion pattern with little serrated artifacts. D of tumor trajectories was 0.21mm, 0.23mm and 0.23mm in SI, AP and ML directions, respectively. Conclusion: A novel retrospective 3D k-space sorting 4D-MRI technique has been developed and evaluated on human digital phantom. NIH (1R21CA165384-01A1)

60 APPLIED LIFE SCIENCES↗

Sloan Digital Sky Survey IV: Mapping the Milky Way, Nearby Galaxies, and the Distant Universe

We describe the Sloan Digital Sky Survey IV (SDSS-IV), a project encompassing three major spectroscopic programs. The Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) is observing hundreds of thousands of Milky Way stars at high resolution and high signal-to-noise ratios in the near-infrared. The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey is obtaining spatially resolved spectroscopy for thousands of nearby galaxies (median z∼0.03). The extended Baryon Oscillation Spectroscopic Survey (eBOSS) is mapping the galaxy, quasar, and neutral gas distributions between z∼0.6 and 3.5 to constrain cosmology using baryon acoustic oscillations, redshift space distortions, and the shape of the power spectrum. Within eBOSS, we are conducting two major subprograms: the SPectroscopic IDentification of eROSITA Sources (SPIDERS), investigating X-ray AGNs and galaxies in X-ray clusters, and the Time Domain Spectroscopic Survey (TDSS), obtaining spectra of variable sources. All programs use the 2.5 m Sloan Foundation Telescope at the Apache Point Observatory; observations there began in Summer 2014. APOGEE-2 also operates a second near-infrared spectrograph at the 2.5 m du Pont Telescope at Las Campanas Observatory, with observations beginning in early 2017. Observations at both facilities are scheduled to continue through 2020. In keeping with previous SDSS policy, SDSS-IV provides regularly scheduled public data releases; the first one, Data Release 13, was made available in 2016 July.

79 ASTRONOMY AND ASTROPHYSICS↗

Machine Learning Classification of Molten Salt Heat Exchanger Channel Plugging using Synthetic Data

This report addresses the requirements of Milestone M3.4 AI capability to identify and predict maintenance events. Development of digital twins (DT) for molten salt reactor (MSR) components is crucial for reducing operating and maintenance costs (O&M) and ensuring commercial viability of these reactors. Our focus is on development of DT for MSR primary system heat exchanger (HX), a critical component, the fault in which can reduce operating efficiency and force reactor shutdown. We are investigating the feasibility of a conceptual DT of HX consisting of internal distributed temperature sensing with fiber optics and machine learning (ML) algorithms to detect and localize faults. To determine the optimal approach to detection and localization of channel plugging, we benchmark seven different ML models: Logistic Regression, K-Nearest Neighbors (KNN), Gaussian Naïve Bayes, Support Vector Machines (SVM), Decision Tree Classifier, Random Forest Tree Classifier, and Feed-Forward Neural Network. ML algorithms are benchmarked using synthetic HX plugging data generated with computational fluid dynamics COMSOL software, with added brown noise to represent experimental noise. We show that the best performance is obtained with the Decision Tree classifier.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Active-Interrogation Measurements of Induced-Fission Neutrons from Low-Enriched Uranium

Protection and control of nuclear fuels is paramount for nuclear security and safeguards; therefore, it is important to develop fast and robust controlling mechanisms to ensure the safety of nuclear fuels. Through both passive- and active-interrogation methods we can use fast-neutron detection to perform real-time measurements of fission neutrons for process monitoring. Active interrogation allows us to use different ranges of incident neutron energy to probe for different isotopes of uranium. With fast-neutron detectors, such as organic liquid scintillation detectors, we can detect the induced-fission neutrons and photons and work towards quantifying a sample’s mass and enrichment. Using MCNPX-PoliMi, a system was designed to measure induced-fission neutrons from U-235 and U-238. Measurements were then performed in the summer of 2010 at the Joint Research Centre in Ispra, Italy. Fissions were induced with an associated particle D-T generator and an isotopic Am-Li source. The fission neutrons, as well as neutrons from (n, 2n) and (n, 3n) reactions, were measured with five 5” by 5” EJ-309 organic liquid scintillators. The D-T neutron generator was available as part of a measurement campaign in place by Padova University. The measurement and data-acquisition systems were developed at the University of Michigan utilizing a CAEN V1720 digitizer and pulse-shape discrimination algorithms to differentiate neutron and photon detections. Low-enriched uranium samples of varying mass and enrichment were interrogated. Acquired time-of-flight curves and cross-correlation curves are currently analyzed to draw relationships between detected neutrons and sample mass and enrichment. In the full paper, the promise of active-interrogation measurements and fast-neutron detection will be assessed through the example of this proof-of-concept measurement campaign. Additionally, MCNPX-PoliMi simulation results will be compared to the measured data to validate the MCNPX-PoliMi code when used for active-interrogation simulations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

THE DATA REDUCTION PIPELINE FOR THE SDSS-IV MaNGA IFU GALAXY SURVEY

Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) is an optical fiber-bundle integral-field unit (IFU) spectroscopic survey that is one of three core programs in the fourth-generation Sloan Digital Sky Survey (SDSS-IV). With a spectral coverage of 3622–10354 Å and an average footprint of ∼500 arcsec{sup 2} per IFU the scientific data products derived from MaNGA will permit exploration of the internal structure of a statistically large sample of 10,000 low-redshift galaxies in unprecedented detail. Comprising 174 individually pluggable science and calibration IFUs with a near-constant data stream, MaNGA is expected to obtain ∼100 million raw-frame spectra and ∼10 million reduced galaxy spectra over the six-year lifetime of the survey. In this contribution, we describe the MaNGA Data Reduction Pipeline algorithms and centralized metadata framework that produce sky-subtracted spectrophotometrically calibrated spectra and rectified three-dimensional data cubes that combine individual dithered observations. For the 1390 galaxy data cubes released in Summer 2016 as part of SDSS-IV Data Release 13, we demonstrate that the MaNGA data have nearly Poisson-limited sky subtraction shortward of ∼8500 Å and reach a typical 10 σ limiting continuum surface brightness μ = 23.5 AB arcsec{sup −2} in a five-arcsecond-diameter aperture in the g -band. The wavelength calibration of the MaNGA data is accurate to 5 km s{sup −1} rms, with a median spatial resolution of 2.54 arcsec FWHM (1.8 kpc at the median redshift of 0.037) and a median spectral resolution of σ = 72 km s{sup −1}.

79 ASTRONOMY AND ASTROPHYSICS↗

TH-E-BRF-11: Dynamic Treatment of Clinical Margins Beyond the PET-Avid Target in Emission Guided Radiation Therapy: A Retrospective Patient Study

Purpose: Emission guided radiation therapy (EGRT) is a new modality that uses PET emissions for direct real-time tumor tracking. Radiation beamlets are delivered along PET lines of response (LOR's) by a fast rotating PET-Linac closed ring gantry. In this work, we develop a scheme to treat clinical margins defined proximal to the moving PET-avid tumor, while maintaining EGRT's inherent real-time tracking ability. Methods: The principle of EGRT is to deliver radiation along PET emission paths to concentrate dose in the PET-avid gross tumor volume (GTV). To account for adjacent non- PET avid regions in the clinical volume (CTV) a method was developed that expands the set of radiation beamlet responses to include the effective margin extension from the GTV to the CTV. An LOR detection may now Result in multiple beamlet responses: one along the original LOR, and others that are adjacent to it in the direction of margin extension. Evaluation studies were performed on a 4D digital patient as well as a clinical breast cancer patient with moving lung tumors. Emission data were obtained using GATE and a commercial PET scanner. Dose delivery was simulated using VMC++. For the patient study, Philips Pinnacle was used for planning and Mirada RTx was used for deformable dose registration across multiple breathing phases. Results: Compared with IMRT, the EGRT margin extension method achieved a 25.3% and 9.0% relative increase in dose to 95% of the CTV for the digital and clinical patients, respectively. The corresponding CTV dose increases without margin extension were 9.7% and 1.4%. The organs at risk doses were kept similar or lower for EGRT in both cases, with tumor tracking preserved. Conclusions: With the capability of accurate treatment of the moving CTV, EGRT has the potential to enable a practical and effective implementation of 4D biologically guided radiation therapy. Authors SRM and AN are stockholders of RefleXion Medical.

60 APPLIED LIFE SCIENCES↗

SDSS-IV MaNGA IFS GALAXY SURVEY—SURVEY DESIGN, EXECUTION, AND INITIAL DATA QUALITY

The MaNGA Survey (Mapping Nearby Galaxies at Apache Point Observatory) is one of three core programs in the Sloan Digital Sky Survey IV. It is obtaining integral field spectroscopy for 10,000 nearby galaxies at a spectral resolution of R ∼ 2000 from 3622 to 10354 Å. The design of the survey is driven by a set of science requirements on the precision of estimates of the following properties: star formation rate surface density, gas metallicity, stellar population age, metallicity, and abundance ratio, and their gradients; stellar and gas kinematics; and enclosed gravitational mass as a function of radius. We describe how these science requirements set the depth of the observations and dictate sample selection. The majority of targeted galaxies are selected to ensure uniform spatial coverage in units of effective radius (R{sub e}) while maximizing spatial resolution. About two-thirds of the sample is covered out to 1.5 R{sub e} (Primary sample), and one-third of the sample is covered to 2.5 R{sub e} (Secondary sample). We describe the survey execution with details that would be useful in the design of similar future surveys. We also present statistics on the achieved data quality, specifically the point-spread function, sampling uniformity, spectral resolution, sky subtraction, and flux calibration. For our Primary sample, the median r -band signal-to-noise ratio is ∼70 per 1.4 Å pixel for spectra stacked between 1 R{sub e} and 1.5 R{sub e}. Measurements of various galaxy properties from the first-year data show that we are meeting or exceeding the defined requirements for the majority of our science goals.

79 ASTRONOMY AND ASTROPHYSICS↗

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