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At least 775 records · Page 43

An implantable instrument for studying the long-term flight biology of migratory birds

The design of an instrument deployed in a project studying the high altitude Himalayan migrations of bar-headed geese (Anser indicus) is described. The electronics of this archival datalogger measured 22 × 14 × 6.5 mm, weighed 3 g, was powered by a ½AA-sized battery weighing 10 g and housed in a transparent biocompatible tube sealed with titanium electrodes for electrocardiography (ECG). The combined weight of 32 g represented less than 2% of the typical bodyweight of the geese. The primary tasks of the instrument were to continuously record a digitised ECG signal for heart-rate determination and store 12-bit triaxial accelerations sampled at 100 Hz with 15% coverage over each 2 min period. Measurement of atmospheric pressure provided an indication of altitude and rate of ascent or descent during flight. Geomagnetic field readings allowed for latitude estimation. These parameters were logged twice per minute along with body temperature. Data were stored to a memory card of 8 GB capacity. Instruments were implanted in geese captured on Mongolian lakes during the breeding season when the birds are temporarily flightless due to moulting. The goal was to collect data over a ten month period, covering both southward and northward migrations. This imposed extreme constraints on the design's power consumption. Raw ECG can be post-processed to obtain heart-rate, allowing improved rejection of signal interference due to strenuous activity of locomotory muscles during flight. Accelerometry can be used to monitor wing-beat frequency and body kinematics, and since the geese continued to flap their wings continuously even during rather steep descents, act as a proxy for biomechanical power. The instrument enables detailed investigation of the challenges faced by the geese during these arduous migrations which typically involve flying at extreme altitudes through cold, low density air where oxygen availability is significantly reduced compared to sea level.

60 APPLIED LIFE SCIENCES↗

Performance Analysis of Large Scale HPC Workflows for Earth System Models

Climate assessment reports, such as the Intergovernmental Panel on Climate Change’s 5th assesment report [IPCC AR5; IPCC et al., 2014] or the United States National Climate Assessment [U.S. Global Change Research Program, 2014], increasingly rely on many-ensemble climate projections from fully-coupled Earth system models (ESM) to asses possible future climate states. ESM participate in a large set of Coupled Model Intercomparson Projects (CMIP) to better understand their models and the climate system, so that they may provide credible climate projections. However, fully participating in these intercomparison exercises represents an extremely large computational personnel burden for modeling centers [Eyring et al., 2016, Williams et al., 2016a]. However, there has been little attention within the climate modeling community paid to the in situ performance of ESMs up until now. Recently a computational performance model intercomparison project (CPMIP) for CMIP6 has begun [Balaji et al., 2017], but there has not yet been an effort to gather, process, and analyze the historical performance data that has been saved within archived log files from previous modeling efforts, nor the development of performance analysis system capable of providing detailed statistical analyses or visualizations of this performance data. Therefore, we’ve begun a joint effort to analyze the historical and current performance data on both GFDL and OLCF modeling systems. Here, we have developed a preliminary performance analysis system to captue, analyize, and visualize end-to-end in situ performance data and applied it to NOAA/GFDL’s post-processing system. Through the course of the project a number of performance improvements have been made, with the steps necessary to handle the expected volume of data (Big Data) likely to come out of the CMIP6 exercises (TB to PB) provided. We have also begun developing a statistical workload model that will allow modeling centers to determined their expected scientific throughput in the context of expected resource (computational and personnel) availability and accounting for typical workflow disruptions. This will allow them to develop a CMIP participation strategy and maximize their level of participation in the exercises. We expect this infrastructure, and the data it produces, to ultimately allow us to identify performance issues and workflow errors that exist across Earth system modeling centers, and possibly HPC modeling centers in general. Center-independent solutions to workflow or performance issues would help alleviate the computational burden for CMIP6+ modeling projects and should realize both labor and cost savings benefits throughout the CMIP community.

54 ENVIRONMENTAL SCIENCES↗

NSTX-U Advances in Real-Time C++11 on Linux

Programming languages like C and Ada combined with proprietary embedded operating systems have dominated the real-time application space for decades. The new C++11standard includes native, language-level support for concurrency, a required feature for any nontrivial event-oriented real-time software. Threads, Locks, and Atomics now exist to provide the necessary tools to build the structures that make up the foundation of a complex real-time system. The National Spherical Torus Experiment Upgrade (NSTX-U) at the Princeton Plasma Physics Laboratory (PPPL) is breaking new ground with the language as applied to the needs of fusion devices. A new Digital Coil Protection System (DCPS) will serve as the main protection mechanism for the magnetic coils, and it is written entirely in C++11 running on Concurrent Computer Corporation's real-time operating system, RedHawk Linux. It runs over 600 algorithms in a 5 kHz control loop that determine whether or not to shut down operations before physical damage occurs. To accomplish this, NSTX-U engineers developed software tools that do not currently exist elsewhere, including real-time atomic synchronization, real-time containers, and a real-time logging framework. Together with a recent (and carefully configured) version of the GCC compiler, these tools enable data acquisition, processing, and output using a conventional operating system to meet a hard real-time deadline (that is, missing one periodic is a failure) of 200 microseconds.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

RE-EXAMINING HIGH ABUNDANCE SLOAN DIGITAL SKY SURVEY MASS-METALLICITY OUTLIERS: HIGH N/O, EVOLVED WOLF-RAYET GALAXIES?

We present new MMT spectroscopic observations of four dwarf galaxies representative of a larger sample observed by the Sloan Digital Sky Survey and identified by Peeples et al. as low-mass, high oxygen abundance outliers from the mass-metallicity relation. Peeples showed that these four objects (with metallicity estimates of 8.5 {<=} 12 + log(O/H) {<=} 8.8) have oxygen abundance offsets of 0.4-0.6 dex from the M{sub B} luminosity-metallicity relation. Our new observations extend the wavelength coverage to include the [O II] {lambda}{lambda}3726, 3729 doublet, which adds leverage in oxygen abundance estimates and allows measurements of N/O ratios. All four spectra are low excitation, with relatively high N/O ratios (N/O {approx}> 0.10), each of which tend to bias estimates based on strong emission lines toward high oxygen abundances. These spectra all fall in a regime where the 'standard' strong-line methods for metallicity determinations are not well calibrated either empirically or by photoionization modeling. By comparing our spectra directly to photoionization models, we estimate oxygen abundances in the range of 7.9 {<=} 12 + log (O/H) {<=} 8.4, consistent with the scatter of the mass-metallicity relation. We discuss the physical nature of these galaxies that leads to their unusual spectra (and previous classification as outliers), finding their low excitation, elevated N/O, and strong Balmer absorption are consistent with the properties expected from galaxies evolving past the 'Wolf-Rayet galaxy' phase. We compare our results to the 'main' sample of Peeples and conclude that they are outliers primarily due to enrichment of nitrogen relative to oxygen and not due to unusually high oxygen abundances for their masses or luminosities.

79 ASTRONOMY AND ASTROPHYSICS↗

COSMIC EVOLUTION OF DUST IN GALAXIES: METHODS AND PRELIMINARY RESULTS

We investigate the redshift (z) evolution of dust mass and abundance, their dependences on initial conditions of galaxy formation, and physical correlations between dust, gas, and stellar contents at different z based on our original chemodynamical simulations of galaxy formation with dust growth and destruction. In this preliminary investigation, we first determine the reasonable ranges of the most important two parameters for dust evolution, i.e., the timescales of dust growth and destruction, by comparing the observed and simulated dust mass and abundances and molecular hydrogen (H{sub 2}) content of the Galaxy. We then investigate the z-evolution of dust-to-gas ratios (D), H{sub 2} gas fraction (f{sub H{sub 2}}), and gas-phase chemical abundances (e.g., A {sub O} = 12 + log (O/H)) in the simulated disk and dwarf galaxies. The principal results are as follows. Both D and f{sub H{sub 2}} can rapidly increase during the early dissipative formation of galactic disks (z ∼ 2-3), and the z-evolution of these depends on initial mass densities, spin parameters, and masses of galaxies. The observed A {sub O}-D relation can be qualitatively reproduced, but the simulated dispersion of D at a given A {sub O} is smaller. The simulated galaxies with larger total dust masses show larger H{sub 2} and stellar masses and higher f{sub H{sub 2}}. Disk galaxies show negative radial gradients of D and the gradients are steeper for more massive galaxies. The observed evolution of dust masses and dust-to-stellar-mass ratios between z = 0 and 0.4 cannot be reproduced so well by the simulated disks. Very extended dusty gaseous halos can be formed during hierarchical buildup of disk galaxies. Dust-to-metal ratios (i.e., dust-depletion levels) are different within a single galaxy and between different galaxies at different z.

79 ASTRONOMY AND ASTROPHYSICS↗

BATSE Observations of the Piccinotti Sample of AGN II: Variability and Spectral Analysis

The Piccinotti sample is the hard x-ray-selected sample of active galactic nuclei (AGNs) best studied at energies below approximately 10 keV. It represents the only unbiased and complete high-energy survey of the sky down to a limiting flux of 3.1 x 10(exp -11) per square erg per second. As such, it has been used to study AGN properties such as X-ray spectral characteristics, log N-log S relation, and luminosity function. The BATSE data provide, for the first time, a systematic coverage of the whole sample at high energies. BATSE data from nearly four years of observations (1993 November - 1997 September) were analyzed using standard BATSE occultation analysis software to extract a signal from sources in the Piccinotti sample. Although the BATSE sensitivity for individual source measurements is relatively poor on short time scales, the near all-sky coverage and long CGRO lifetime allows us to improve our sensitivity considerably by sumrr~ng data over many years. This significantly reduces our statistical errors at the expense of loss of temporal information. However, the systematic errors associated with the summation of data over such a long period are not negligible, and the study of systematic effects was a major part of our effort. We evaluated two types of systematic error: those affecting the overall normalization (which are important for comparison with other instruments) and those affecting the size of the fluctuations (which are relevant for estimating the confidence level of a detection). The former was studied by comparison of BATSE data with other instruments, primarily CGRO/OSSE. The results indicate that our absolute flux values maybe overestimated by as much as 35% for some sources. However, since this does not affect our estimation of the detection confidence, we made no corrections to our flux estimates.

Paciesas, William S.↗

Towards Probablistic Assessment of Hypobaric Decompression Sickness Treatment

INTRODUCTION: Pressure, oxygen (O2), and time are the pillars to effective treatment of decompression sickness (DCS). The NASA DCS Treatment Model links a decrease in computed bubble volume to the resolution of a symptom. The decrease in volume is realized in two stages: a) during the Boyle's Law compression and b) during subsequent dissolution of the gas phase by the O2 window. METHODS: The cumulative distribution of 154 symptoms that resolved during repressurization was described with a log-logistic density function of pressure difference (deltaP as psid) associated with symptom resolution and two other explanatory variables. The 154 symptoms originated from 119 cases of DCS during 969 exposures in 47 different altitude tests. RESULTS: The probability of symptom resolution [P(symptom resolution)] = 1 / (1+exp(- (ln(deltaP) - 1.682 + 1.089×AMB - 0.00395×SYMPTOM TIME) / 0.633)), where AMB is 1 when the subject ambulated as part of the altitude exposure or else 0 and SYMPTOM TIME is the elapsed time in min from start of the altitude exposure to recognition of a DCS symptom. The P(symptom resolution) was estimated from computed deltaP from the Tissue Bubble Dynamics Model based on the "effective" Boyle's Law change: P2 - P1 (deltaP, psid) = P1×V1/V2 - P1, where V1 is the computed volume of a spherical bubble in a unit volume of tissue at low pressure P1 and V2 is computed volume after a change to a higher pressure P2. V2 continues to decrease through time at P2, at a faster rate if 100% ground level O2 was breathed. The computed deltaP is the effective treatment pressure at any point in time as if the entire deltaP was just from Boyle's Law compression. DISCUSSION: Given the low probability of DCS during extravehicular activity and the prompt treatment of a symptom with options through the model it is likely that the symptom and gas phase will resolve with minimum resources and minimal impact on astronaut health, safety, and productivity.

Conkin, J.↗

THE FIRST X-SHOOTER OBSERVATIONS OF JETS FROM YOUNG STARS

We present the first pilot study of jets from young stars conducted with X-shooter, on the ESO/Very Large Telescope. As it offers simultaneous, high-quality spectra in the range 300-2500 nm, X-shooter is uniquely important for spectral diagnostics in jet studies. We chose to probe the accretion/ejection mechanisms at low stellar masses examining two targets with well-resolved continuous jets lying on the plane of the sky: ESO-HA 574 in Chameleon I and Par-Lup3-4 in Lupus III. The mass of the latter is close to the sub-stellar boundary (M{sub *} = 0.13 M{sub sun}). A large number of emission lines probing regions of different excitation are identified, position-velocity diagrams are presented, and mass outflow/accretion rates are estimated. Comparison between the two objects is striking. ESO-HA 574 is a weakly accreting star for which we estimate a mass accretion rate of log ( M-dot{sub acc}) = -10.8{+-}0.5 (in M{sub sun} yr{sup -1}), yet it drives a powerful jet with M-dot{sub out} {approx} 1.5-2.7 x 10{sup -9} M{sub sun} yr{sup -1}. These values can be reconciled with a magneto-centrifugal jet acceleration mechanism assuming that the presence of the edge-on disk severely depresses the luminosity of the accretion tracers. In comparison, Par-Lup3-4, with stronger mass accretion ( log ( M-dot{sub acc}) = -9.1{+-}0.4 M{sub sun} yr{sup -1}), drives a low-excitation jet with about M-dot{sub out} {approx} 3.2 x 10{sup -10} M{sub sun} yr{sup -1} in both lobes. Despite the low stellar mass, M-dot{sub out}/ M-dot{sub acc} for Par-Lup3-4 is at the upper limit of the range usually measured for young objects, but still compatible with a steady magneto-centrifugal wind scenario if all uncertainties are considered.

79 ASTRONOMY AND ASTROPHYSICS↗

COMPASS-FME Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) Experiment Level 1 Sensor Data v2-1

This is the version 2-1 Level 1 (L1) data release for COMPASS-FME environmental sensors located at our Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experimental site. This manipulative, ecosystem-scale TEMPEST experiment addresses the potential for freshwater and estuarine-water disturbance events to alter tree function, species composition, and ecosystem processes in a deciduous coastal forest in MD, USA. The experiment uses a large-unit (2000 m2), un-replicated experimental design, with three 50 m × 40 m plots serving as control, freshwater, and estuarine-water treatments. L1 data are close to raw, but are units-transformed and have out-of-instrument-bounds, out-of-service, and outlier flags added. Duplicates and missing data are removed but otherwise these data are not filtered, and have not been subject to any additional algorithmic or human QA/QC. Any scientific analyses of L1 data should be performed with care. **This dataset will be updated quarterly with new data for the duration of the project** This dataset includes: - An overall dataset README file that describes the current version, gives citation and contact information, etc. - Site- and year-specific folders, each holding variable-specific CSV (comma separated value) data files for each site and plot in that year. - Metadata files within each site-year folder provide full information on data units, expected ranges, contact information, detailed flood times, as well as a general description of the site. - Environmental sensor types that appear in the data files include weather (ClimaVUE50, CS, RM Young, and LI instruments in the graphs below); soil conditions (TEROS12); soil redox state (Redox); groundwater variables (AquaTROLL200 and AquaTROLL600); open water sondes (Exo); tree sap velocity (Sapflow); and system voltage and state (Datalogger). Data are normally logged every 15 minutes. Please see v2-1 TEMPEST L1 Sensor Package Quick Start.pdf for detailed information on data package structure, temporal coverage, and versioning. The TEMPEST flood events occurred on the following dates. They lasted for ~10 hours each day and delivered ~80,000 gallons to each plot; many data streams are available at 1 or 5 minute frequency during these periods. * Tests: Aug 25 (fresh plot) and Sep 9 (salt plot), 2021 * TEMPEST 1: June 22, 2022 * TEMPEST 2: June 6-7, 2023 * TEMPEST 3: June 11-13, 2024 This dataset was updated 2026-03-12: (i) data now go through 2025-12-31 (previous end was 2025-06-30) and (ii) dataset and file names updated to “…v2-1” (previously was “v2-0”).

54 ENVIRONMENTAL SCIENCES↗

COMPASS-FME Synoptic Sites Level 1 Sensor Data v2-1

This is the version 2-1 Level 1 (L1) data release for COMPASS-FME environmental sensors located at our synoptic field sites. COMPASS-FME is studying sites in two distinct regions, the Chesapeake Bay and the Western Lake Erie Basin. We established the network at seven "synoptic" (observational) sites along the Chesapeake Bay and Lake Erie coastlines, collectively generating over three million observations per month, to track and comprehend environmental changes where land and water intersect. Additionally, the two regions provide an interesting contrast of saltwater and freshwater coasts that allow us to differentiate the impacts of inundation and coastal water chemistries in two nationally important coastal systems. L1 data are close to raw, but are units-transformed and have out-of-instrument-bounds, out-of-service, and outlier flags added. Duplicates and missing data are removed but otherwise these data are not filtered, and have not been subject to any additional algorithmic or human QA/QC. Any scientific analyses of L1 data should be performed with care. **This dataset will be updated quarterly with new data for the duration of the project** This dataset includes: - An overall dataset README file that describes the current version, gives citation and contact information, etc. - Site- and year-specific folders, each holding up to 12 CSV (comma separated value) data files for each site and plot in that year. - Metadata files within each site-year folder provide full information on data units, expected ranges, contact information, as well as a general description of the site. - Environmental sensor types that appear in the data files include weather (ClimaVUE50, CS, RM Young, and LI instruments in the graphs below); soil conditions (TEROS12); soil redox state (Redox); groundwater variables (AquaTROLL200 and AquaTROLL600); open water sondes (Exo); tree sap velocity (Sapflow); and system voltage and state (Datalogger). Data are normally logged every 15 minutes. Please see v2-0 Synoptic L1 Sensor Package Quick Start.pdf for detailed information on data package structure, temporal coverage, and versioning. This dataset was updated 2026-03-12: (i) data now go through 2025-12-31 (previous end was 2025-06-30) and (ii) dataset and file names updated to “…v2-1” (previously was “v2-0”).

54 ENVIRONMENTAL SCIENCES↗

Infiltration Data Package for the E-Area Low-Level Waste Facility Performance Assessment

The infiltration data package contains the input parameters, the cap design and material properties assumptions, and the modeling results for the Hydrologic Evaluation of Landfill Performance (HELP) infiltration model simulations performed in support of the E-Area Low-Level Waste Facility Performance Assessment (PA). The infiltration estimates establish the upper boundary condition for the PORFLOW vadose-zone model and GoldSim model simulations for the following E-Area disposal unit types: Slit and Engineered Trenches, Low-Activity Waste Vault (LAWV), Intermediate-Level Vault (ILV), Componentin- Grout (CIG) special waste form trench segments, and the Naval Reactor Component Disposal Areas (NRCDAs). The infiltration data package builds upon relevant, foundational PA technical reports and memoranda from the past 15 years and is supported by three important components: the HELP model input parameter datasheets, HELP model input and output filenames and directory structure, and infiltration rates as a function of time for each scenario for each disposal unit type. For Slit and Engineered Trenches, a single best-estimate Bahia-grass case of two-percent slope and 585- foot slope length represents an upper bound on intact closure-cap infiltration rates over a 10,000-year period. Building upon the single, bounding, and intact case, two different approaches were considered for incorporating the effect of localized cap subsidence on infiltration rates in the PORFLOW flow and transport model simulations. In the first approach, a Monte Carlo probabilistic model was developed to calculate infiltration rates for 0.54%, 2%, 3.6%, and 4.9% subsidence scenariosa reflecting historical and future non-crushable content for the Slit and Engineered Trenches. The resulting blended (spatially and slope-length averaged) infiltration rates become an inflow upper boundary condition for the PORFLOW vadose zone model simulations. In the second and preferred approach, a Monte Carlo rectangle packing algorithm (Danielson, 2019) and a simplified equation for the total mass flux of water draining into a subsided compartment (Equation 1) will be employed to implement a weighted blending of radionuclide fluxes to the water table using the results of deterministic PORFLOW vadose zone simulations representative of specific subsidence cases. Finally, HELP-model results from sensitivity studies of the intact infiltration case were fit to a log-logistic function to generate infiltration profiles over a 10,000-year period for most-optimistic, more-optimistic, best-estimate, more-pessimistic, and most-pessimistic cases, for both the intact and four subsidence scenarios. For the LAWV and IL vaults, infiltration rate profiles for a 10,000-year period were developed for both an on-vault (above the concrete/metal vault roof) and an off-vault (10-foot soil zone adjacent to vault walls) scenario. The purpose of the off-vault simulations was to confirm that subsurface runoff from the concrete vault roof will adequately drain through the lowermost backfill layers adjacent to the vault walls. The LAWV and ILV infiltration profiles assume collapse of the concrete roof at relative Years 2,905 and 7,100, respectively. The identical Bahia-grass case with two-percent slope and 585-foot slope length assumed for the Slit and Engineered Trenches will represent an upper bound on intact infiltration rates for the NRCDAs and CIG special waste form as well. While the NRCDA casks are assumed to remain structurally intact (i.e., non-assumed to collapse 300 years after the end of operations. Because both rows of the existing CIG trench segments in ST23 (formerly CIG01) extend across the planned cap crest, the subsided CIG trench segments are treated conservatively in the HELP model as a 100%-subsidence case with zero subsurface run-on. The CIG special waste form trench segment infiltration profile, therefore, consists of an intact-cap period from relative Year 100 to Year 300, followed by a 100%-subsidence period from relative Year 300 to Year 10,100.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

The 4 Ms CHANDRA Deep Field-South Number Counts Apportioned by Source Class: Pervasive Active Galactic Nuclei and the Ascent of Normal Galaxies

We present 0.5-2 keV, 2-8 keV, 4-8 keV, and 0.5-8 keV (hereafter soft, hard, ultra-hard, and full bands, respectively) cumulative and differential number-count (log N-log S ) measurements for the recently completed approx. equal to 4 Ms Chandra Deep Field-South (CDF-S) survey, the deepest X-ray survey to date. We implement a new Bayesian approach, which allows reliable calculation of number counts down to flux limits that are factors of approx. equal to 1.9-4.3 times fainter than the previously deepest number-count investigations. In the soft band (SB), the most sensitive bandpass in our analysis, the approx. equal to 4 Ms CDF-S reaches a maximum source density of approx. equal to 27,800 deg(sup -2). By virtue of the exquisite X-ray and multiwavelength data available in the CDF-S, we are able to measure the number counts from a variety of source populations (active galactic nuclei (AGNs), normal galaxies, and Galactic stars) and subpopulations (as a function of redshift, AGN absorption, luminosity, and galaxy morphology) and test models that describe their evolution. We find that AGNs still dominate the X-ray number counts down to the faintest flux levels for all bands and reach a limiting SB source density of approx. equal to 14,900 deg(sup -2), the highest reliable AGN source density measured at any wavelength. We find that the normal-galaxy counts rise rapidly near the flux limits and, at the limiting SB flux, reach source densities of approx. equal to 12,700 deg(sup -2) and make up 46% plus or minus 5% of the total number counts. The rapid rise of the galaxy counts toward faint fluxes, as well as significant normal-galaxy contributions to the overall number counts, indicates that normal galaxies will overtake AGNs just below the approx. equal to 4 Ms SB flux limit and will provide a numerically significant new X-ray source population in future surveys that reach below the approx. equal to 4 Ms sensitivity limit. We show that a future approx. equal to 10 Ms CDF-S would allow for a significant increase in X-ray-detected sources, with many of the new sources being cosmologically distant (z greater than or approx. equal to 0.6) normal galaxies.

Field-South↗

THE 4 Ms CHANDRA DEEP FIELD-SOUTH NUMBER COUNTS APPORTIONED BY SOURCE CLASS: PERVASIVE ACTIVE GALACTIC NUCLEI AND THE ASCENT OF NORMAL GALAXIES

We present 0.5-2 keV, 2-8 keV, 4-8 keV, and 0.5-8 keV (hereafter soft, hard, ultra-hard, and full bands, respectively) cumulative and differential number-count (log N-log S) measurements for the recently completed Almost-Equal-To 4 Ms Chandra Deep Field-South (CDF-S) survey, the deepest X-ray survey to date. We implement a new Bayesian approach, which allows reliable calculation of number counts down to flux limits that are factors of Almost-Equal-To 1.9-4.3 times fainter than the previously deepest number-count investigations. In the soft band (SB), the most sensitive bandpass in our analysis, the Almost-Equal-To 4 Ms CDF-S reaches a maximum source density of Almost-Equal-To 27,800 deg{sup -2}. By virtue of the exquisite X-ray and multiwavelength data available in the CDF-S, we are able to measure the number counts from a variety of source populations (active galactic nuclei (AGNs), normal galaxies, and Galactic stars) and subpopulations (as a function of redshift, AGN absorption, luminosity, and galaxy morphology) and test models that describe their evolution. We find that AGNs still dominate the X-ray number counts down to the faintest flux levels for all bands and reach a limiting SB source density of Almost-Equal-To 14,900 deg{sup -2}, the highest reliable AGN source density measured at any wavelength. We find that the normal-galaxy counts rise rapidly near the flux limits and, at the limiting SB flux, reach source densities of Almost-Equal-To 12,700 deg{sup -2} and make up 46% {+-} 5% of the total number counts. The rapid rise of the galaxy counts toward faint fluxes, as well as significant normal-galaxy contributions to the overall number counts, indicates that normal galaxies will overtake AGNs just below the Almost-Equal-To 4 Ms SB flux limit and will provide a numerically significant new X-ray source population in future surveys that reach below the Almost-Equal-To 4 Ms sensitivity limit. We show that a future Almost-Equal-To 10 Ms CDF-S would allow for a significant increase in X-ray-detected sources, with many of the new sources being cosmologically distant (z {approx}> 0.6) normal galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

Radiation testing of 2.4 micron wavelength extended InGaAs photodiodes for 100 MeV/n carbon ions

We have successfully tested simultaneously 2.4 Micron Wavelength, Extended InGaAs Photodiodes having diameters of 20, 30, 40, 50, 100, 150, 200, 250, and 290 Micron, coupled with a Single Mode Fiber using 100 MeV/n Carbon (C) Ions up to a cumulative dose of ~40 krad. During irradiation, the devices were maintained at dry ice temperature, reverse biased at 100 mV, and their leakage current was continuously monitored in-situ during the run. After the exposure was completed, all nine devices were monitored for any change in their leakage current at 100 mV and room temperature for several weeks to monitor any annealing effects that may occur. Nine Photodiodes with the above varying diameters were radiated with 100 MeV/n Carbon Ions with a fluence of 10 6 , 10 7 , 10 8 , 10 9 , and 10 10 ions/cm 2 at each fluence level. At 100 MeV/n the Linear Energy Transfer (LET) of Carbon Ion is ~0.156 MeV-cm 2 /mg in Extended InGaAs, which is an order magnitude more than Proton (H) and Helium (He) Ions of 100 MeV/n energy. Thus, significant displacement damage is anticipated in the Extended InGaAs Photodiode with 100 MeV/n Carbon Ions with a total fluence of 1 × 1010 ions/cm 2 . Pre- and Post- radiation results were also measured for: (1) Leakage Current Vs. Voltage for the Extended InGaAs Photodiodes; (2) Responsivity (Quantum Efficiency) in A/W for Photodiodes; and (3) Bandwidth of the Photodiodes. All devices were found to be fully functional at the normal operating conditions and at both dry ice and room temperature. The leakage current increased up to a factor of ~2X at lower bias of 100 mV at the highest fluence of 10 10 ions/cm 2 , but not significantly at higher bias of 2 V. Finally, we did not observe any post radiation annealing effect for leakage current at room temperature and 100 mV bias for any of the devices after several weeks of data logging.

2.4 micron wavelength↗

The relationship between anatomic noise and volumetric breast density for digital mammography

Purpose: The appearance of parenchymal/stromal patterns in mammography have been characterized as having a Wiener power spectrum with an inverse power-law shape described by the exponential parameter, {beta}. The amount of fibroglandular tissue, which can be quantified in terms of volumetric breast density (VBD), influences the texture and appearance of the patterns formed in a mammogram. Here, a large study is performed to investigate the variations in {beta} in a clinical population and to indicate the relationship between {beta} and breast density. Methods: From a set of 2686 cranio-caudal normal screening mammograms, the parameter {beta} was extracted from log-log fits to the Wiener spectrum over the range 0.15-1 mm{sup -1}. The Wiener spectrum was calculated from regions of interest in the compression paddle contact region of the breast. An in-house computer program, Cumulus V, was used to extract the volumetric breast density and identify the compression paddle contact regions of the breast. The Wiener spectra were calculated with and without modulation transfer function (MTF) correction to determine the impact of VBD on the intrinsic anatomic noise. Results: The mean volumetric breast density was 25.5% ({+-}12.6%) over all images. The mean {beta} following a MTF correction which decreased the {beta} slightly ( Almost-Equal-To -0.08) was found to be 2.87. Varying the maximum of the spatial frequency range of the fits from 0.7 to 1.0, 1.25 or 1.5 mm{sup -1} showing small decreases in the result, although the effect of the quantum noise power component on reducing {beta} was clearly observed at 1.5 mm{sup -1}. Conclusions: The texture parameter, {beta}, was found to increase with VBD at low volumetric breast densities with an apparent leveling off at higher densities. The relationship between {beta} and VBD measured here can be used to create probabilistic models for computer simulations of detectability. As breast density is a known risk predictor for breast cancer, the correlation between {beta} and VBD suggests that {beta} may provide predictive information and this will be investigated in the future.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

A semi–automatic analytical methodology for characterizing the energy consumption of MRI systems using load duration curves

Background and purpose: Magnetic resonance imaging (MRI) scanners are a major contributor to greenhouse gas emissions from the healthcare sector, and efforts to improve energy efficiency and reduce energy consumption rely on quantification of the characteristics of energy consumption. The purpose of this work was to develop a semi-automatic analytical methodology for the characterization of the energy consumption of MRI systems using only the load duration curve (LDC). LDCs are a fundamental tool used across various fields to analyze and understand the behavior of loads over time. Methods: An electric current transformer sensor and data logger were installed on two 3T MRI scanners from two vendors, termed M1 (outpatient scanner) and M2 (inpatient/emergency scanner). Data was collected for 1 month (7/11/2023 to 8/11/2023). Active power was calculated, assuming a balanced three-phase system, using the average current measured across all three phases, a 480 V reference voltage for both machines, and vendor-provided power factors. An LDC was constructed for each system by sorting the active power values in descending order and computing the cumulative time (in units of percentage) for each data point. The first derivative of the LDC was then computed (LDC’), smoothed by convolution with a window function (sLDC’), and used to detect transitions between different system modes including (in descending power levels): scan, prepared-to-scan, idle, low-power, and off. The final, segmented LDC was used to measure time (% total time), total energy (kWh), and mean power (kW) for each system mode on both scanners. The method was validated by comparing mean power values, computed using the segmented 1-month LDC, for each nonproductive system mode (i.e., prepared-to-scan, idle, lower-power, and off) against power levels measured after a deliberate system shutdown was performed for each scanner (1 day worth of data). Results: The validation revealed differences in mean power values <1.4% for all nonproductive modes and both scanners. In the scan system mode, the mean power values ranged from 29.8 to 37.2 kW and the total energy consumed for 1 month ranged from 11 106 to 14 466 kWh depending on the scanner. Over the course of 1 month, the portion of time the scanners were in nonproductive modes ranged from 76% to 80% across scanners and the nonproductive energy consumption ranged from 8010 to 6722 kWh depending on the scanner. The M1 (outpatient) scanner consumed 99.9 and 183.9 kWh/day in idle mode for weekdays and weekends, respectively, because the scanner spent 23% more time proportionally in idle mode on the weekends. Conclusions: A semi-automatic method for quantifying energy consumption characteristics of MRI scanners was introduced and validated. This method is relatively simple to implement as it requires only power data from the scanners and avoids the technical challenges associated with extracting and processing scanner log files. Finally, the methodology enables quantitative evaluation of the power, time, and energy characteristics of MRI scanners in scan and nonproductive system modes, providing baseline data and the capability of identifying potential opportunities for enhancing the energy efficiency of MRI scanners.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Hybrid Reynolds-Averaged/Large Eddy Simulation of the Flow in a Model SCRamjet Cavity Flameholder

Steady-state and scale-resolving simulations have been performed for flow in and around a model scramjet combustor flameholder. Experimental data available for this configuration include velocity statistics obtained from particle image velocimetry. Several turbulence models were used for the steady-state Reynolds-averaged simulations which included both linear and non-linear eddy viscosity models. The scale-resolving simulations used a hybrid Reynolds-averaged/large eddy simulation strategy that is designed to be a large eddy simulation everywhere except in the inner portion (log layer and below) of the boundary layer. Hence, this formulation can be regarded as a wall-modeled large eddy simulation. This e ort was undertaken to not only assess the performance of the hybrid Reynolds-averaged / large eddy simulation modeling approach in a flowfield of interest to the scramjet research community, but to also begin to understand how this capability can best be used to augment standard Reynolds-averaged simulations. The numerical errors were quantified for the steady-state simulations, and at least qualitatively assessed for the scale-resolving simulations prior to making any claims of predictive accuracy relative to the measurements. The steady-state Reynolds-averaged results displayed a high degree of variability when comparing the flameholder fuel distributions obtained from each turbulence model. This prompted the consideration of applying the higher-fidelity scale-resolving simulations as a surrogate "truth" model to calibrate the Reynolds-averaged closures in a non-reacting setting prior to their use for the combusting simulations. In general, the Reynolds-averaged velocity profile predictions at the lowest fueling level matched the particle imaging measurements almost as well as was observed for the non-reacting condition. However, the velocity field predictions proved to be more sensitive to the flameholder fueling rate than was indicated in the measurements.

Baurle, R. A.↗

MSL Telecom Automated Anomaly Detection

The Mars Science Laboratory (MSL) Telecom Operations Team at the Jet Propulsion Laboratory (JPL) has implemented a machine learning system in order to automate the anomaly detection process as a part of daily operations. Machine learning enables reliable detection of anomalies in Telecom-related telemetry and automated reporting of Telecom subsystem status, resulting in an 90% reduction in team workload and improved anomaly detection reliability. At present, machine learning methods are used to detect: 1. Anomalous long-term trends in telemetry data 2. Anomalous time-domain evolution of telemetry values Both types of anomalies pose their own unique challenges that are addressed in different ways. In the first case, long term trending of daily minima, maximum, and mean telemetry values in temperatures, currents, voltages, and radio frequency (RF) power levels is used in addition to hard threshold safety checks to look for changes in long-term equipment health and performance. Long-term trending methods allow for ordinary seasonal variations in these quantities caused by temperature changes over the course of the Martian year while allowing operators to determine whether current performance remains in line with historical values from previous years. Changes in long-term trends can provide important insights into the health and status of the rover's on-board systems as well as valuable early warning if subtle degradation begins to take hold. But while trending of daily statistics is valuable, it does not detect anomalies in the short-term time evolution of data over the course of minutes or hours during a day, and this task is handled with short-term shape analysis. Principal components analysis (PCA) has been found to provide robust detection of short-term anomalies, and several examples of the use of PCA to detect actual anomalous events will be provided here. In using PCA, we use both the percentage of explained variance and also a log likelihood test on the PCA expansion coefficients to flag telemetry data for human review. Previous work in the field of spacecraft anomaly detection includes [1] for MSL and [2] for some other JPL missions.

Mukai, Ryan↗