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At least 631 records · Page 35

MULTIPLE-PLANET SCATTERING AND THE ORIGIN OF HOT JUPITERS

Doppler and transit observations of exoplanets show a pile-up of Jupiter-size planets in orbits with a 3 day period. A fraction of these hot Jupiters have retrograde orbits with respect to the parent star's rotation, as evidenced by the measurements of the Rossiter-McLaughlin effect. To explain these observations we performed a series of numerical integrations of planet scattering followed by the tidal circularization and migration of planets that evolved into highly eccentric orbits. We considered planetary systems having three and four planets initially placed in successive mean-motion resonances, although the angles were taken randomly to ensure orbital instability in short timescales. The simulations included the tidal and relativistic effects, and precession due to stellar oblateness. Our results show the formation of two distinct populations of hot Jupiters. The inner population (Population I) is characterized by semimajor axis a < 0.03 AU and mainly formed in the systems where no planetary ejections occurred. Our follow-up integrations showed that this population was transient, with most planets falling inside the Roche radius of the star in <1 Gyr. The outer population of hot Jupiters (Population II) formed in systems where at least one planet was ejected into interstellar space. This population survives the effects of tides over >1 Gyr and fits nicely the observed 3 day pile-up. A comparison between our three-planet and four-planet runs shows that the formation of hot Jupiters is more likely in systems with more initial planets. Due to the large-scale chaoticity that dominates the evolution, high eccentricities and/or high inclinations are generated mainly by close encounters between the planets and not by secular perturbations (Kozai or otherwise). The relative proportion of retrograde planets seems of be dependent on the stellar age. Both the distribution of almost aligned systems and the simulated 3 day pile-up also fit observations better in our four-planet simulations. This may suggest that the planetary systems with observed hot Jupiters were originally rich in the number of planets, some of which were ejected. In a broad perspective, our work therefore hints on an unexpected link between the hot Jupiters and recently discovered free floating planets.

79 ASTRONOMY AND ASTROPHYSICS↗

Characterizing and mitigating coherent errors in a trapped ion quantum processor using hidden inverses

Quantum computing testbeds exhibit high-fidelity quantum control over small collections of qubits, enabling performance of precise, repeatable operations followed by measurements. Currently, these noisy intermediate-scale devices can support a sufficient number of sequential operations prior to decoherence such that near term algorithms can be performed with proximate accuracy (like chemical accuracy for quantum chemistry problems). While the results of these algorithms are imperfect, these imperfections can help bootstrap quantum computer testbed development. Demonstrations of these algorithms over the past few years, coupled with the idea that imperfect algorithm performance can be caused by several dominant noise sources in the quantum processor, which can be measured and calibrated during algorithm execution or in post-processing, has led to the use of noise mitigation to improve typical computational results. Conversely, benchmark algorithms coupled with noise mitigation can help diagnose the nature of the noise, whether systematic or purely random. Here, we outline the use of coherent noise mitigation techniques as a characterization tool in trapped-ion testbeds. We perform model-fitting of the noisy data to determine the noise source based on realistic physics focused noise models and demonstrate that systematic noise amplification coupled with error mitigation schemes provides useful data for noise model deduction. Further, in order to connect lower level noise model details with application specific performance of near term algorithms, we experimentally construct the loss landscape of a variational algorithm under various injected noise sources coupled with error mitigation techniques. This type of connection enables application-aware hardware codesign, in which the most important noise sources in specific applications, like quantum chemistry, become foci of improvement in subsequent hardware generations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Turbulent Compressible Convection with Rotation: Flow Structure and Evolution - Part 1

The effects of Coriolis forces on compressible convection are studied using three-dimensional numerical simulations carried out within a local modified f-plane model. The physics is simplified by considering a perfect gas occupying a rectilinear domain placed tangentially to a rotating sphere at various latitudes, through which a destabilizing heat flux is driven. The resulting convection is considered for a range of Rayleigh, Taylor, and Prandtl (and thus Rossby) numbers, evaluating conditions where the influence of rotation is both weak and strong. Given the computational demands of these high-resolution simulations, the parameter space is explored sparsely to ascertain the differences between laminar and turbulent rotating convection. The first paper in this series examines the effects of rotation on the flow structure within the convection, its evolution, and some consequences for mixing. Subsequent papers consider the large-scale mean shear flows that are generated by the convection, and the effects of rotation on the convective energetics and transport properties. It is found here that the structure of rotating turbulent convection is similar to earlier nonrotating studies, with a laminar, cellular surface network disguising a fully turbulent interior punctuated by vertically coherent structures. However, the temporal signature of the surface flows is modified by inertial motions to yield new cellular evolution patterns and an overall increase in the mobility of the network. The turbulent convection contains vortex tubes of many scales, including large-scale coherent structures spanning the full vertical extent of the domain involving multiple density scale heights. Remarkably, such structures align with the rotation vector via the influence of Coriolis forces on turbulent motions, in contrast with the zonal tilting of streamlines found in laminar flows. Such novel turbulent mechanisms alter the correlations which drive mean shearing flows and affect the convective transport properties. In contrast to this large-scale anisotropy, small-scale vortex tubes at greater depths are randomly orientated by the rotational mixing of momentum, leading to an increased degree of isotropy on the medium to small scales of motion there. Rotation also influences the thermodynamic mixing properties of the convection. In particular, interaction of the larger coherent vortices causes a loss of correlation between the vertical velocity and the temperature leaving a mean stratification which is not isentropic.

Brummell, Nicholas H.↗

Recurrence Rate and Magma Effusion Rate for the Latest Volcanism on Arsia Mons, Mars

Magmatism and volcanism have evolved the Martian lithosphere, surface, and climate throughout the history of Mars. Constraining the rates of magma generation and timing of volcanism on the surface clarifies the ways in which magma and volcanic activity have shaped these Martian systems. The ages of lava flows on other planets are often estimated using impact crater counts, assuming that the number and size-distribution of impact craters per unit area reflect the time the lava flow has been on the surface and exposed to potential impacts. Here we show that impact crater age model uncertainty is reduced by adding stratigraphic information observed at locations where neighboring lavas abut each other, and demonstrate the significance of this reduction in age uncertainty for understanding the history of a volcanic field comprising 29 vents in the 110-kilometer-diameter caldera of Arsia Mons, Mars. Each vent within this caldera produced lava flows several to tens of kilometers in length; these vents are likely among the youngest on Mars, since no impact craters in their lava flows are larger than 1 kilometer in diameter. First, we modeled the age of each vent with impact crater counts performed on their corresponding lava flows and found very large age uncertainties for the ages of individual vents, often spanning the estimated age for the entire volcanic field. The age model derived from impact crater counts alone is broad and unimodal, with estimated peak activity in the field around 130Ma (megaannum, 1 million years). Next we applied our volcano event age model (VEAM), which uses a directed graph of stratigraphic relationships and random sampling of the impact crater age determinations to create alternative age models. Monte Carlo simulation was used to create 10,000 possible vent age sets. The recurrence rate of volcanism is calculated for each possible age set, and these rates are combined to calculate the median recurrence rate of all simulations. Applying this approach to the 29 volcanic vents, volcanism likely began around 200-300Ma then first peaked around 150Ma, with an average production rate of 0.4 vents per Myr (million years). The recurrence rate estimated including stratigraphic data is distinctly bimodal, with a second, lower peak in activity around 100Ma. Volcanism then waned until the final vents were produced 10-90Ma. Based on this model, volume flux is also bimodal, reached a peak rate of 1-8 cubic kilometers per million years by 150Ma and remained above half this rate until about 90Ma, after which the volume flux diminished greatly. The onset of effusive volcanism from 200-150Ma might be due to a transition of volcanic style away from explosive volcanism that emplaced tephra on the western flank of Arsia Mons, while the waning of volcanism after the 150Ma peak might represent a larger-scale diminishing of volcanic activity at Arsia Mons related to the emplacement of flank apron lavas.

Richardson, Jacob A.↗

Interactive Visualization of Multi-Group Cross Sections on High-Fidelity Spatial Meshes

Core simulation tools utilizing Monte Carlo transport methods represent the 'Holy Grail' for nuclear reactor analysis. However, deterministic transport methods pose a number of advantages to Monte Carlo from a computational perspective, which seems likely to make these methods more viable in the near to intermediate term. Deterministic methods almost universally discretize the energy domain in a few to hundreds of energy groups. One of the key challenges for deterministic transport-based methods to be viable is accurate, reactor agnostic multi-group cross section generation. This paper describes tools for data processing and visualization of multigroup cross sections generated on high-fidelity spatial meshes from the OpenMC Monte Carlo code. Next generation deterministic transport reactor core modeling tools will require multi-group cross section (MGXS) generation on high-fidelity spatial meshes. High-fidelity MGXS are necessary for the accurate simulation of neutron physics in nuclear reactors with a high degree of spectral heterogeneity - e.g., large localized neutron flux gradients throughout a reactor core. Although many local (e.g., pin cell) approximations have been developed to model the scalar flux to compute spectral-averaged MGXS, these techniques cannot account for complex intra-pin and intra-assembly spatial self-shielding effects. Monte Carlo presents the most accurate method for reactor agnostic multi-group cross section generation since it does not require the use of local approximations to the flux. Monte Carlo has been proposed as a highly desirable framework for reactor agnostic cross section generation for many years. Monte Carlo methods can effectively embed all of the relevant spectral effects into the MGXS through the random particle tracking and interaction sampling processes. Previous work has applied MCNP and Serpent to compute few-group constants for diffusion calculations, and OpenMC to compute multi-group cross sections for transport-based methods. The primary difficulty with using Monte Carlo for MGXS generation is the tremendous computational resources required to adequately converge multi-group cross sections in each spatial region and energy group. Recent development of the OpenMC Monte Carlo code for high-performance computing platforms has made multigroup cross section generation from Monte Carlo more tractable in the foreseeable future. The recent release of OpenMC v0.7.1 includes a new Python-based module for MGXS generation. The MGXS generation module leverages many of the algorithms and features for 'big data' analysis of large tally datasets on complex spatial meshes. This paper describes the data management workflow and visualization tools which have been developed to explore the plethora of MGXS data generated with OpenMC. It is the authors' hope that the development of the visualization tool described in this paper will ultimately enable the design of machine learning algorithms to accelerate the convergence rate of high-fidelity multi-group cross section generated with Monte Carlo. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Neutron Scattering Studies of Vortex Matter in Type-II Superconductors

The proposed program is an experimental study of the fundamental properties of Abrikosov vortex matter in type-II superconductors. Most superconducting materials used in applications such as MRI are type II and their transport properties are determined by the interplay between random pinning, interaction and thermal fluctuation effects in the vortex state. Given the technological importance of these materials, a fundamental understanding of the vortex matter is necessary. The vortex lines in type-II superconductors also form a useful model system for fundamental studies of a number of important issues in condensed matter physics, such as the presence of a symmetry-breaking phase transition in the presence of random pinning. Recent advances in neutron scattering facilities such as the major upgrade of the NIST cold source and the Spallation Neutron Source are providing unprecedented opportunities in addressing some of the longstanding issues in vortex physics. The core component of the proposed program is to use small angle neutron scattering and Bitter decoration experiments to provide the most stringent test of the Bragg glass theory by measuring the structure factor in both the real and reciprocal spaces. The proposed experiments include a neutron reflectometry experiment to measure the precise Q-dependence of the structure factor of the vortex lattice in the Bragg glass state. A second set of SANS experiments will be on a shear-strained Nb single crystal for testing a recently proposed theory of the stability of Bragg glass. The objective is to artificially create a set of parallel grain boundaries into a Nb single crystal and use SANS to measure the vortex matter diffraction pattern as a function of the changing angle between the applied magnetic field to the grain boundaries. The intrinsic merits of the proposed work are a new fundamental understanding of type-II superconductors on which superconducting technology is based, and a firm understanding of phases and phase transitions in condensed matter systems with random pinning. The broader impact of the program includes the training of future generation of neutron scientists, and further development of neutron scattering and complementary techniques for studies of superconducting materials. The graduate and undergraduate students participating in this project will learn the state-of-the-art neutron scattering techniques, acquire a wide range of materials research experiences, and participate in the frontier research of superconductivity. This should best prepare the students for future careers in academia, industry, or government.

36 MATERIALS SCIENCE↗

Large-Eddy Simulation Code Developed for Propulsion Applications

A large-eddy simulation (LES) code was developed at the NASA Glenn Research Center to provide more accurate and detailed computational analyses of propulsion flow fields. The accuracy of current computational fluid dynamics (CFD) methods is limited primarily by their inability to properly account for the turbulent motion present in virtually all propulsion flows. Because the efficiency and performance of a propulsion system are highly dependent on the details of this turbulent motion, it is critical for CFD to accurately model it. The LES code promises to give new CFD simulations an advantage over older methods by directly computing the large turbulent eddies, to correctly predict their effect on a propulsion system. Turbulent motion is a random, unsteady process whose behavior is difficult to predict through computer simulations. Current methods are based on Reynolds-Averaged Navier- Stokes (RANS) analyses that rely on models to represent the effect of turbulence within a flow field. The quality of the results depends on the quality of the model and its applicability to the type of flow field being studied. LES promises to be more accurate because it drastically reduces the amount of modeling necessary. It is the logical step toward improving turbulent flow predictions. In LES, the large-scale dominant turbulent motion is computed directly, leaving only the less significant small turbulent scales to be modeled. As part of the prediction, the LES method generates detailed information on the turbulence itself, providing important information for other applications, such as aeroacoustics. The LES code developed at Glenn for propulsion flow fields is being used to both analyze propulsion system components and test improved LES algorithms (subgrid-scale models, filters, and numerical schemes). The code solves the compressible Favre-filtered Navier- Stokes equations using an explicit fourth-order accurate numerical scheme, it incorporates a compressible form of Smagorinsky s model for the subgrid-scale turbulence, and it uses generalized curvilinear coordinates to allow analysis of a wide range of geometries. The code runs in parallel on shared memory multiprocessor computers and is written in Fortran 90 with dynamic memory allocation. A sample result for a Mach-1.4 round jet is presented in the figure. Instantaneous Mach number contours in several cross-planes downstream of the nozzle exit are shown, illustrating how an LES captures the large unsteady three-dimensional turbulent structures present in the jet.

DeBonis, James R.↗

The Nature of Grand Minima and Maxima from Fully Nonlinear Flux Transport Dynamos

We aim to investigate the nature and occurrence characteristics of grand solar minimum and maximum periods, which are observed in the solar proxy records such as {sup 10}Be and {sup 14}C, using a fully nonlinear Babcock–Leighton type flux transport dynamo including momentum and entropy equations. The differential rotation and meridional circulation are generated from the effect of turbulent Reynolds stress and are subjected to back-reaction from the magnetic field. To generate grand minimum- and maximum-like periods in our simulations, we used random fluctuations in the angular momentum transport process, namely the Λ-mechanism, and in the Babcock–Leighton mechanism. To characterize the nature and occurrences of the identified grand minima and maxima in our simulations, we used the waiting time distribution analyses, which reflect whether the underlying distribution arises from a random or a memory-bearing process. The results show that, in the majority of the cases, the distributions of grand minima and maxima reveal that the nature of these events originates from memoryless processes. We also found that in our simulations the meridional circulation speed tends to be smaller during grand maximum, while it is faster during grand minimum periods. The radial differential rotation tends to be larger during grand maxima, while it is smaller during grand minima. The latitudinal differential rotation, on the other hand, is found to be larger during grand minima.

79 ASTRONOMY AND ASTROPHYSICS↗

Using Deep Learning to Automate Inference of Meteoroid Pre-Entry Properties

Properly assessing the asteroid threat depends on the knowledge of asteroid pre-entry parameters, such as size, velocity, mass, density, and strength. Although a vast number of possible bodies to study exist, such characterization of asteroid populations is currently limited by substantial costs associated with space rendezvous missions and rare meteorite findings. As asteroids fragment, ablate, and decelerate in the atmosphere, they emit light detectable by ground-based and space-borne instruments. Earth’s atmosphere, thus, becomes an accessible laboratory that enables impactor risk assessments by facilitating inference of the pre-entry parameters. These asteroid pre-entry conditions are typically deduced by modeling the entry and breakup physics that best reproduce the observed light or energy deposition curve. However, this process requires extensive manual trial-and-error of uncertain modeling parameters. Automating meteor modeling and inference would improve property distributions used in risk assessments and enable population characterization as more light curves become more readily available through the presence of space assets and ground-based camera networks. We previously developed a genetic algorithm to automate meteor modeling by using the fragment-cloud model (FCM) to search for the values of the FCM input parameters (e.g., diameter) that generate energy deposition profiles that match the observed one. Now, we apply deep learning to infer asteroid diameter, velocity, and density from observed energy deposition curves. We trained and tested our neural network models with synthetic energy deposition curves modeled using the FCM rubble pile implementation. We present an application of a 1D convolutional neural network and compare its performance to other attempted regressors and machine learning techniques, such as a fully connected neural network and Random Forest regression, to demonstrate its capabilities. We validate our model weights and approach using the Chelyabinsk, Tagish Lake, Benešov, Košice, and Lost City meteors.

Tarano, Ana Maria↗

SU-F-T-55: Reproducibility of Interstitial HDR Brachytherapy Plans

Purpose: Treating gynecological cancers with interstitial high-dose-rate (HDR) brachytherapy requires precise reconstruction of catheter positions to obtain accurate dosimetric plans. In this study, we investigated the degree of reproducibility of dosimetric plans for Syed HDR brachytherapy. Methods: We randomly selected five patients having cervix-vaginal cancer who were recently treated in our clinic with interstitial HDR brachytherapy with a prescription dose of 25–30 Gy in five fractions. Interstitial needles/catheters were placed under fluoroscopic guidance and intra-operative 3T MRI scan was performed to confirm the desired catheter placement for adequate target volume coverage. A CT scan was performed and fused with the MRI for delineating high-risk CTV (HR-CTV), intermediate-risk CTV (IR-CTV) and OARs. HDR treatment plans were generated using Oncentra planning software. A single plan was used for all five fractions of treatment for each patient. For this study, we took the original clinical plan and removed all the reconstructed catheters from the plan keeping the original contours unchanged. Then, we manually reconstructed all the catheters and entered the same dwell time from the first original clinical plan. The dosimetric parameters studied were: D90 for HR-CTV and IR-CV, and D2cc for bladder, rectum, sigmoid and bowel. Results: The mean of absolute differences in dosimetric coverage (D90) were (range): 1.3% (1.0–2.0%) and 2.0% (0.9–3.6%) for HR-CTV and IR-CTV, respectively. In case of OARs, the mean of absolute variations in D2cc were (range): 4.7% (0.7–8.9%) for bladder, 1.60% (0.3–3.2%) for rectum, 1.6% (0–3.9%) for sigmoid, and 1.8% (0–5.1%) for bowel. Conclusion: Overall, the reproducibility of interstitial HDR plans was within clinically acceptable limit. Observed maximum variation in D2cc for bladder. If number of catchers and dwell points were relatively low or any one catheter was heavily loaded, then reproducibility of the plan was more sensitive to the accuracy of catheter reconstruction.

60 APPLIED LIFE SCIENCES↗

Investigation of computational and spectral analysis methods for aeroacoustic wave propagation

Most computational fluid dynamics (CFD) schemes are not adequately accurate for solving aeroacoustics problems, which have wave amplitudes several orders of magnitude smaller yet with frequencies larger than the flow field variations generating the sound. Hence, a computational aeroacoustics (CAA) algorithm should have minimal dispersion and dissipation features. A dispersion relation preserving (DRP) scheme is, therefore, applied to solve the linearized Euler equations in order to simulate the propagation of three types of waves, namely: acoustic, vorticity, and entropy waves. The scheme is derived using an optimization procedure to ensure that the numerical derivatives preserve the wave number and angular frequency of the partial differential equations being discretized. Consequently, simulated waves propagate with the correct wave speeds and exhibit their appropriate properties. A set of radiation and outflow boundary conditions, compatible with the DRP scheme and derived from the asymptotic solutions of the governing equations, are also implemented. Numerical simulations are performed to test the effectiveness of the DRP scheme and its boundary conditions. The computed solutions are shown to agree favorably with the exact solutions. The major restriction appears to be that the dispersion relations can be preserved only for waves with wave lengths longer than four or five spacings. The boundary conditions are found to be transparent to the outgoing disturbances. However, when the disturbance source is placed closer to a boundary, small acoustic reflections start appearing. CAA generates enormous amounts of temporal data which needs to be reduced to understand the physical problem being simulated. Spectral analysis is one approach that helps us in extracting information which often can not be easily interpreted in the time domain. Thus, three different methods for the spectral analysis of numerically generated aeroacoustic data are studied. First, the capabilities of two traditional methods for spectral analysis, namely, the Blackman-Tukey method and periodogram method, are compared in estimating the spectra of a simple-periodic process. The periodogram is then applied to analyze transitory-deterministic processes. Finally, these two methods are compared with a more recent method, referred as the Weighted-Overlapped-Segment-Averaging (WOSA) method, in estimating the spectra of a chaotic (random-like) process. From the demonstrative case for the spectral analyses of data generated by simple-periodic process, the periodogram method is found to give a better estimate of the steep-sloped spectra than the Blackman-Tukey method. Also, for this problem, the Hanning window is found to perform better with the periodogram method than with the Blackman-Tukey method. Finally, for the spectral analysis of data generated by the chaotic process, the periodogram method does not perform well, whereas, the WOSA and Blackman-Tukey methods give equivalently good results.

Vanel, Florence O.↗

Toward Realistic Dynamics of Rotating Orbital Debris, and Implications for Lightcurve Interpretation

Optical observations of rotating space debris near GEO contain important information on size, shape, composition, and rotational states, but these aspects are difficult to extract due to data limitations and the high number of degrees of freedom in the modeling process. For tri-axial rigid debris objects created by satellite fragmentations, the most likely initial rotation state has a large component of initial angular velocity directed along the intermediate axis of inertia, leading to large angular reorientations of the body on the timescale of the rotation period. This lends some support to the simplest possible interpretation of light curves -- that they represent sets of random orientations of the objects of study. However, effects of internal friction and solar radiation are likely to cause significant modification of rotation states within a time as short as a few orbital periods. In order to examine the rotational dynamics of debris objects under the influences of these effects, a set of seven first-order coupled equations of motion were assembled in state form: three are Euler equations describing the rates of change of the components of angular velocity in the body frame, and four describe the rates of change of the components of the unit quaternion. Quaternions are a four-dimensional extension of complex numbers that form a seamless, singularity-free representation of body orientation on S3. The Euler equations contain explicit terms describing torque from solar radiation in terms of spherical harmonics, and terms representing effects of a prescribed rate of internal friction. Numerical integrations of these equations of motion are being performed, and results will be presented. Initial tests show that internal friction without solar radiation torque leads to rotation about the maximum principal axis of inertia, as required, and solar radiation torque is expected to lead to spin-up of objects. Because the axis of maximum rotational inertia tends to be roughly coincident with the normal to the largest projected cross-sectional area, internal friction is expected to lead to reduced variation of light curve amplitudes at a given phase angle, but a large dependence of the same on phase angle. At a given phase angle, databases are generated which contain reflected intensities for comprehensive sets of equally-likely orientations, represented as unit quaternions. When projected onto three dimensions (S2) and color-coded by intensity, the set is depicted as points within a solid, semi-transparent unit sphere, within which all possible reflected intensities for an object at a given phase angle may be inspected simultaneously. Rotational sequences are represented by trajectories through the sphere. Databases are generated for each of a set of phase angles separately, forming a comprehensive dataset of reflected intensities spanning all object orientations and solar phase angles. Symmetries in the problem suggest that preferred rotation states are likely, defined relative to the object-sun direction in inertial space and relative to the maximum principal axis of inertia in the body coordinate system. Such rotation states may greatly simplify the problem of light curve interpretation by reducing the number of degrees of freedom in the problem.

Ojakangas, Gregory W.↗

Artificial Neural Networks to Predict Cognitive Impairment of Rodents Subjected to Space Radiation

INTRODUCTION We use artificial neural networks (ANNs) as an example machine learning (ML) tool to predict the cognitive performance impairment of rats induced by irradiation. The experimental data in the analyses is attentional set-shifting (ATSET) test scores from a rodent model exposed to ≤15 cGy of individual galactic cosmic radiation (GCR) ions: 4He, 28Si, or 56Fe, expected for a Lunar or Mars mission [1]. This work investigates rats at a subject-based level and uses applied dose and performance scores taken before irradiation to predict whether a rat will be impaired when irradiated. The results of this study are significant to crewed space missions as they support the potential of predicting an astronaut’s impairment in a specific task before spaceflight through the implementation of appropriately trained ML tools. METHODS Data used in this work are scores from the ATSET, a multi-stage constrained cognitive flexibility test [2]. Our computational model utilizes the number of attempts to reach the criterion to pass a stage as a behavioral performance measure for rats. We use the post-irradiation scores, generate thresholds from cumulative distribution plots of non-irradiated rats, and calculate the percent of irradiated rats whose scores fall below the threshold to infer how each radiation type/dose affects a population. Rats scoring above the threshold are labeled impaired while the others are non-impaired. We then employ ANNs as a typical ML technique, and use each subject’s individual scores taken before radiation along with the applied dose, to predict their personal susceptibility to cognitive impairment due to space radiation exposure. RESULTS AND CONCLUSION A significant finding is the exhibition of a dose-dependent increasing probability of impairment for 1 to 10 cGy of 28Si or 56Fe in the simple discrimination (SD) stage of the ATSET, and for 1 to 10 cGy of 56Fe in the compound discrimination (CD) stage. On a subject-based level, implementing ML classifiers such as ANNs identifies rats that have a higher tendency for impairment after GCR exposure [1]. The receiver operating characteristic (ROC) and the precision-recall (PR) curves of the ML models show a better prediction of impairment when 56Fe is the ion in question in both SD (Figure 1) and CD stages. They, however, do not depict impairment due to 4He in SD (Figure 1) and 28Si in CD, suggesting no dose-dependent impairment response in these cases. In this work, “good” prediction pertains to “better-than-random-chance”, due to the limited sample size and the high inter- and intra-individual variabilities in response to brain stimulation paradigms, as applicable to both animals and humans. More behavioral tests and biomarkers should be investigated on the same subjects, to be fed to the ML models to capture the agents responsible for performance alterations of some individuals versus others.

machine learning↗

Machine Learning Models to Predict Cognitive Impairment of Rodents Subjected to Space Radiation

INTRODUCTION We use artificial neural networks (ANNs) as an example machine learning (ML) tool to predict the cognitive performance impairment of rats induced by irradiation. The experimental data in the analyses is attentional set-shifting (ATSET) test scores from a rodent model exposed to ≤15 cGy of individual galactic cosmic radiation (GCR) ions: 4He, 28Si, or 56Fe, expected for a Lunar or Mars mission [1]. This work investigates rats at a subject-based level and uses applied dose and performance scores taken before irradiation to predict whether a rat will be impaired when irradiated. The results of this study are significant to crewed space missions as they support the potential of predicting an astronaut’s impairment in a specific task before spaceflight through the implementation of appropriately trained ML tools. METHODS Data used in this work are scores from the ATSET, a multi-stage constrained cognitive flexibility test [2]. Our computational model utilizes the number of attempts to reach the criterion to pass a stage as a behavioral performance measure for rats. We use the post-irradiation scores, generate thresholds from cumulative distribution plots of non-irradiated rats, and calculate the percent of irradiated rats whose scores fall below the threshold to infer how each radiation type/dose affects a population. Rats scoring above the threshold are labeled impaired while the others are non-impaired. We then employ ANNs as a typical ML technique, and use each subject’s individual scores taken before radiation along with the applied dose, to predict their personal susceptibility to cognitive impairment due to space radiation exposure. RESULTS AND CONCLUSION A significant finding is the exhibition of a dose-dependent increasing probability of impairment for 1 to 10 cGy of 28Si or 56Fe in the simple discrimination (SD) stage of the ATSET, and for 1 to 10 cGy of 56Fe in the compound discrimination (CD) stage. On a subject-based level, implementing ML classifiers such as ANNs identifies rats that have a higher tendency for impairment after GCR exposure [1]. The receiver operating characteristic (ROC) and the precision-recall (PR) curves of the ML models show a better prediction of impairment when 56Fe is the ion in question in both SD (Figure 1) and CD stages. They, however, do not depict impairment due to 4He in SD (Figure 1) and 28Si in CD, suggesting no dose-dependent impairment response in these cases. In this work, “good” prediction pertains to “better-than-random-chance”, due to the limited sample size and the high inter- and intra-individual variabilities in response to brain stimulation paradigms, as applicable to both animals and humans. More behavioral tests and biomarkers should be investigated on the same subjects, to be fed to the ML models to capture the agents responsible for performance alterations of some individuals versus others.

machine learning↗

Genotyping by Sequencing of 393 Sorghum bicolor BTx623 × IS3620C Recombinant Inbred Lines Improves Sensitivity and Resolution of QTL Detection

We describe a genetic map with a total of 381 bins of 616 genotyping by sequencing (GBS)- based SNP markers in a F6-F8 recombinant inbred line (RIL) population of 393 individuals derived from crossing S. bicolor BTx623 to S. bicolor IS3620C, a guinea line substantially diverged from BTx623. Five segregation distorted regions were found with four showing enrichment for S. bicolor alleles, suggesting possible selection during formation of this RIL population. A quantitative trait locus (QTL) study with this number of individuals, tripled relative to prior studies of this cross, provided resources, validated previous findings, and demonstrated improved power to detect plant height and flowering time related QTL relative to other published studies. An unexpected low correlation between flowering time and plant height permitted us to separate QTL for each trait and provide evidence against pleiotropy. Ten non- random syntenic regions conferring QTL for the same trait suggest that those QTL may represent alleles at genes functioning in the same manner since the 96 million year ago genome duplication that created these syntenic relationships, while syntenic regions conferring QTL for different trait may suggest sub-functionalization after duplication. Collectively, this study provides resources for marker-assisted breeding, as well as a framework for fine mapping and subsequent cloning of major genes for important traits such as plant height and flowering time in sorghum.

54 ENVIRONMENTAL SCIENCES↗

Objective models of compressed breast shapes undergoing mammography

Purpose: To develop models of compressed breasts undergoing mammography based on objective analysis, that are capable of accurately representing breast shapes in acquired clinical images and generating new, clinically realistic shapes. Methods: An automated edge detection algorithm was used to catalogue the breast shapes of clinically acquired cranio-caudal (CC) and medio-lateral oblique (MLO) view mammograms from a large database of digital mammography images. Principal component analysis (PCA) was performed on these shapes to reduce the information contained within the shapes to a small number of linearly independent variables. The breast shape models, one of each view, were developed from the identified principal components, and their ability to reproduce the shape of breasts from an independent set of mammograms not used in the PCA, was assessed both visually and quantitatively by calculating the average distance error (ADE). Results: The PCA breast shape models of the CC and MLO mammographic views based on six principal components, in which 99.2% and 98.0%, respectively, of the total variance of the dataset is contained, were found to be able to reproduce breast shapes with strong fidelity (CC view mean ADE = 0.90 mm, MLO view mean ADE = 1.43 mm) and to generate new clinically realistic shapes. The PCA models based on fewer principal components were also successful, but to a lesser degree, as the two-component model exhibited a mean ADE = 2.99 mm for the CC view, and a mean ADE = 4.63 mm for the MLO view. The four-component models exhibited a mean ADE = 1.47 mm for the CC view and a mean ADE = 2.14 mm for the MLO view. Paired t-tests of the ADE values of each image between models showed that these differences were statistically significant (max p-value = 0.0247). Visual examination of modeled breast shapes confirmed these results. Histograms of the PCA parameters associated with the six principal components were fitted with Gaussian distributions. The six-component model was also used to generate CC and MLO view mammogram breast shapes, using the mean PCA parameter values of these distributions and randomly generated values based on the fitted Gaussian distributions, which resemble clinically encountered breasts. A spreadsheet with the data necessary to apply this model is provided as the supplementary material. Conclusions: Our PCA models of breast shapes in both mammographic views successfully reproduce analyzed breast shapes and generate new clinically relevant shapes. This work can aid in research applications which incorporate breast shape modeling, such as x-ray scatter correction, dosimetry, and image registration.

60 APPLIED LIFE SCIENCES↗

A Critical Examination of Wind-Wave Spectral Functional Form

Traditionally, data from random ocean waves are presented in spectral functions. The spectra are the result of Fourier analysis. Fourier spectral analysis has dominated data analysis for, at least, the last hundred years. It has been the standard method for is examining the global amplitude-frequency distributions. Although Fourier transform valid under extremely general conditions, there are some crucial restrictions for the Fourier spectral analysis. The system must be linear, and the data must be stationary- otherwise, the resulting spectrum will make little physical sense. The stationarity requirement is also a common required criterion for most of other available data analysis methods. Nevertheless, few, if any, natural phenomena are linear and stationary. To compound these complications is the imperfection of our probes or numerical schemes the interactions of the imperfect probes even with a perfect linear system can make the final data nonlinear. Furthermore, all the available data are usually of finite duration. Under these conditions, Fourier analysis is of limited use, For lack of alternatives, however, Fourier analysis is still used to process such data. The loose application of Fourier analysis and the insouciant adoption of the stationary and linear assumptions may lead to misleading conclusions. Ocean waves are know to be nonlinear, and the wind system generating the wave field are seldom stationary- As a result, the traditional examination of the spectral form hardly made physical sense. A new method for analyzing nonlinear and nonstationary data has been developed. The key part is the Empirical Mode Decomposition (EMD) method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF) that serve as the basis of the representation of the data, This decomposition method is adaptive, and, therefore, highly efficient. The IMFs admit well-behaved Hilbert transforms, and yield instantaneous energy and frequency as functions of time that give sharp identifications of imbedded structures. The final presentation of the results is an energy-frequency-time distribution, designated as the Hilbert Spectrum. Among the main conceptual innovations is the introduction of the instantaneous frequencies for complicated data sets, which eliminate the need of spurious harmonics to represent nonlinear and nonstationary signals. The spectral forms of the ocean waves are very different. This new method offers the first physical meaningful view of the wave spectrum. Data from laboratory and field will be presented to illustrate the differences.

Huang, Norden E.↗

Wireless and chip-less passive radiation sensors for high dose monitoring

The safety of nuclear infrastructures may involve the monitoring of many parameters in harsh environments (high radiation level, high temperature, high pressure,..). If technological solutions exist for transducers part in such environments, the electronic part used in reader is not appropriate and still a challenging task. Well-known solutions to remove the electronic part from the harsh environment consist of connecting the transducer and the reader by long electrical wires or performing ex situ remote sensing. However wires may practically be difficult to implement while ex situ measurements are not compatible with on line monitoring. Wireless and passive sensors working in harsh environments could be an appropriate solution for the remote sensing of critical parameters. Passive sensors without electronics in the sensing unit are available (e.g., SAW sensors) but they suffer from short reading range (typically lower than 10 meters). In order to overcome this range limitation a new class of electromagnetic transducers was developed in the mid-2000's. The operating principle is based on the modification of the properties of high-frequency (>> 1 GHz) passive electromagnetic devices by the quantity to be measured. Based on this principle a wide range of sensing properties can be addressed and a large number of materials can be chosen. Moreover the use of high frequency allows reducing the size of the sensor elements (antenna, transducer) and enhancing the immunity to multi-path. Several principles of RF transducers have been already validated by LAAS-CNRS (e;g; pressure, temperature, stress) as well as radar-based solution for the wireless long-range sensors interrogation. The sensor dosimeter exploit here the known property of Hydrogen-Pressure Dosimeters (HPD) for which the polymer material dehydrogenates under nuclear irradiation. The transducer principle is described. The irradiation will generate the out-gazing (hydrogen) of the polymer inside a micro-chamber. The resulting overpressure leads to the deflection of a silicon membrane which modifies the resonant frequency of the RF resonator. Tests structures have been designed in order to quantify the HDPE out-gazing inside a micro-cavity by measuring the deflection of a boss silicon membrane with a mechanical profiler. A specific set up using interferometry method has been also developed to evaluate the pressure generated inside the micro-cavity. The procedure consists in applying a pressure that pushes the membrane to recover a flat membrane. This condition is monitored thanks to the extinction of the Newton rings. Irradiations have been performed up to 30 kGy using 6 MeV focused e-beam providing by electron accelerator. Membrane deflection and generated pressure around 0.2 μm/mg{sub HDPE}/kGy and 70 mbar/mg{sub HDPE}/kGy has been obtained for a 70 μm thick membrane. In order to characterize the hermetic sealing of the micro-chamber under hydrogen over-pressure, membrane deflection after irradiation has been recorded during 50 days. The variations of membrane deflection are randomly distributed and generally lower than ±5%, showing a good hermeticity during this period. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗