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At least 1,747 records · Page 97

Batch Effect Correction Methods for NASA GeneLab Transcriptomic Datasets

RNA sequencing (RNA-seq) data from space biology experiments promise to yield invaluable insights into the effects of spaceflight on terrestrial biology. However, sample numbers from each study are low due to limited crew availability, hardware, and space. To increase statistical power, spaceflight RNA-seq datasets from different missions are often aggregated together. However, this can introduce technical variation or "batch effects", often due to differences in sample handling, sample processing, and sequencing platforms. Several computational methods have been developed to correct for technical batch effects, thereby reducing their impact on true biological signals. In this study, we combined 7 mouse liver RNA-seq datasets from NASA GeneLab (part of the NASA Open Science Data Repository) to evaluate several common batch effect correction methods (ComBat and ComBat-seq from the sva R package, and Median Polish, Empirical Bayes, and ANOVA from the MBatch R package). We quantitatively evaluated the ability of these methods to correct for technical batch variables in space biology RNA-seq data using the following criteria: BatchQC, principal component analysis, dispersion separability criterion, log fold change correlation, and differential gene expression analysis. Each batch variable / correction method combination was then assessed using a custom scoring approach to identify the optimal correction method for the combined dataset, by geometrically probing the space of all allowable scoring functions to yield an aggregate volume-based scoring measure. Finally, we describe the way in which the GeneLab multi-study analysis and visualization portal will allow users to examine the presence or absence of batch effects using multiple metrics. If the user chooses to perform batch effect correction, the scoring approach described here can be implemented to identify the optimal correction method to use for their specific combined dataset prior to analysis.

Lauren M. Sanders↗

Ceci N'est Pas a globular cluster: the metallicity distribution of the stellar system Terzan 5

We present new determinations of the iron abundance for 220 stars belonging to the stellar system Terzan 5 in the Galactic bulge. The spectra have been acquired with FLAMES at the Very Large Telescope of the European Southern Observatory and DEIMOS at the Keck II Telescope. This is by far the largest spectroscopic sample of stars ever observed in this stellar system. From this data set, a subsample of targets with spectra unaffected by TiO bands was extracted and statistically decontaminated from field stars. Once combined with 34 additional stars previously published by our group, a total sample of 135 member stars covering the entire radial extent of the system has been used to determine the metallicity distribution function of Terzan 5. The iron distribution clearly shows three peaks: a super-solar component at [Fe/H] ≅ 0.25 dex, accounting for ∼29% of the sample, a dominant sub-solar population at [Fe/H] ≅ –0.30 dex, corresponding to ∼62% of the total, and a minor (6%) metal-poor component at [Fe/H] ≅ –0.8 dex. Such a broad, multi-modal metallicity distribution demonstrates that Terzan 5 is not a genuine globular cluster but the remnant of a much more complex stellar system.

79 ASTRONOMY AND ASTROPHYSICS↗

Event-by-Event Evaluation of the Prompt Fission Neutron Spectrum From 239 Pu(n,f)

We have developed an improved evaluation method for the spectrum of neutrons emitted in fission of 239 Pu induced by incident neutrons with energies up to 20 MeV. The <v> covariance data, including incident energy correlations introduced by the <v> evaluation method, were used to fix the input parameters in our event-by-event model of fission, FREYA, by applying formal statistical methods. Formal estimates of uncertainties in the evaluation were developed by randomly sampling model inputs and calculating likelihood functions based on agreement with the evaluated <v>. Our approach is able to employ a greater variety of fission measurements than the relatively coarse spectral data alone. It also allows the study of numerous fission observables for more accurate model validation. The combination of an event-by-event Monte Carlo fission model with a statistical-likelihood analysis is thus a powerful tool for evaluation of fission-neutron data. Our empirical model FREYA follows the complete fission event from birth of the excited fragments through their decay via neutron emission until the fragment excitation energy is below the neutron separation energy when neutron emission can no longer occur. The most recent version of FREYA incorporates pre-equilibrium neutron emission, the emission of the first neutron before equilibrium is reached in the compound nucleus, and multi-chance fission, neutron evaporation prior to fission when the incident neutron energy is above the neutron separation energy. Energy, momentum, charge and mass number are conserved throughout the fission process. The best available values of fragment masses and total kinetic energies are used as inputs to FREYA. We fit three parameters that are not well under control from previous measurements: the shift in the total fragment kinetic energy; the energy scale of the asymptotic level density parameter, controlling the fragment 'temperature' for neutron evaporation; and the relative excitation of the light and heavy fragments, governing the number and energy of neutrons emitted from each fragment. The latter two parameters are assumed to be independent of the incident neutron energy while the first varies with incident energy. We describe our method and the subsequent spectral evaluation and present the results of several standard validation calculations that test our new evaluation. These benchmarks include critical assemblies, sensitive to criticality in fast systems; pulsed sphere measurements testing the spectra at incident neutron energies of 14 MeV; and other tests.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A REFINED ESTIMATE OF THE IONIZING EMISSIVITY FROM GALAXIES AT z {approx_equal} 3: SPECTROSCOPIC FOLLOW-UP IN THE SSA22a FIELD

We investigate the contribution of star-forming galaxies to the ionizing background at z {approx} 3, building on previous work based on narrowband (NB3640) imaging in the SSA22a field. We use new Keck/LRIS spectra of Lyman break galaxies (LBGs) and narrowband-selected Ly{alpha} emitters (LAEs) to measure redshifts for 16 LBGs and 87 LAEs at z > 3.055, such that our NB3640 imaging probes the Lyman-continuum (LyC) region. When we include the existing set of spectroscopically confirmed LBGs, our total sample with z > 3.055 consists of 41 LBGs and 91 LAEs, of which 9 LBGs and 20 LAEs are detected in our NB3640 image. With our combined imaging and spectroscopic data sets, we critically investigate the origin of NB3640 emission for detected LBGs and LAEs. We remove from our samples three LBGs and three LAEs with spectroscopic evidence of contamination of their NB3640 flux by foreground galaxies and statistically model the effects of additional, unidentified foreground contaminants. The resulting contamination and LyC-detection rates, respectively, are 62% {+-} 13% and 8% {+-} 3% for our LBG sample, and 47% {+-} 10% and 12% {+-} 2% for our LAE sample. The corresponding ratios of non-ionizing UV to LyC flux density, corrected for intergalactic medium (IGM) attenuation, are 18.0{sup +34.8} {sub -7.4} for LBGs and 3.7{sup +2.5} {sub -1.1} for LAEs. We use these ratios to estimate the total contribution of star-forming galaxies to the ionizing background and the hydrogen photoionization rate in the IGM, finding values larger than, but consistent with, those measured in the Ly{alpha} forest. Finally, the measured UV to LyC flux-density ratios imply model-dependent LyC escape fractions of f {sup LyC} {sub esc} {approx} 5%-7% for our LBG sample and f {sup LyC} {sub esc} {approx} 10%-30% for our fainter LAE sample.

79 ASTRONOMY AND ASTROPHYSICS↗

Statistical fracture behavior of doped UO 2 using a ball-on-ring equibiaxial flexure test method

Metal oxide dopants, such as titanium and chromium oxides, have garnered considerable attention for their potential to increase grain size (≥ 30 µm) in UO 2 fuel, purportedly enhancing fission gas retention during reactor operation. Fuel performance is significantly impacted by fuel fracture behavior, so it is important to understand the effects of enhanced grain size and dopant content on UO 2 fuel fracture. UO 2 pellets were doped with 0.1 wt% TiO 2 and 0.3 wt% Cr 2 O 3 to alter density and grain size. Inductively coupled plasma mass spectroscopy measured dopant levels pre- and post-sintering. X-ray diffraction revealed lattice changes and microstrain via Rietveld refinement. Field emission scanning electron microscopy determined grain sizes of approximately 30 µm for TiO 2 doping and 7 µm for Cr 2 O 3 doping. Transverse rupture strength tests were performed on over 30 samples per dataset to obtain characteristic strength and Weibull modulus. Results indicate no statistical difference in fracture strength between 0.1 wt% TiO 2 doped UO 2 and undoped UO 2 , while 0.3 wt% Cr 2 O 3 doped UO 2 exhibited a 20% decrease in fracture strength. Doped UO 2 samples also showed reduced Weibull modulus compared to undoped UO 2 , suggesting increased scatter in fracture strength. This study's findings suggest that titanium and chromium oxide doping in UO 2 , regardless of grain size, induce residual stresses, decreasing fracture strength and increasing variability in fracture behavior.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

THE LBT BOOeTES FIELD SURVEY. I. THE REST-FRAME ULTRAVIOLET AND NEAR-INFRARED LUMINOSITY FUNCTIONS AND CLUSTERING OF BRIGHT LYMAN BREAK GALAXIES AT Z {approx} 3

We present a deep LBT/LBC U{sub spec}-band imaging survey (9 deg{sup 2}) covering the NOAO Booetes field. A total of 14,485 Lyman break galaxies (LBGs) at z {approx} 3 are selected, which are used to measure the rest-frame UV luminosity function (LF). The large sample size and survey area reduce the LF uncertainties due to Poisson statistics and cosmic variance by {>=}3 compared to previous studies. At the bright end, the LF shows excess power compared to the best-fit Schechter function, which can be attributed to the contribution of z {approx} 3 quasars. We compute the rest-frame near-infrared LF and stellar mass function (SMF) of z {approx} 3 LBGs based on the R-band and [4.5 {mu}m]-band flux relation. We investigate the evolution of the UV LFs and SMFs between z {approx} 7 and z {approx} 3, which supports a rising star formation history in the LBGs. We study the spatial correlation function of two bright LBG samples and estimate their average host halo mass. We find a tight relation between the host halo mass and the galaxy star formation rate (SFR), which follows the trend predicted by the baryonic accretion rate onto the halo, suggesting that the star formation in LBGs is fueled by baryonic accretion through the cosmic web. By comparing the SFRs with the total baryonic accretion rates, we find that cosmic star formation efficiency is about 5%-20% and it does not evolve significantly with redshift, halo mass, or galaxy luminosity.

79 ASTRONOMY AND ASTROPHYSICS↗

Arm structure in normal spiral galaxies, 1: Multivariate data for 492 galaxies

Multivariate data have been collected as part of an effort to develop a new classification system for spiral galaxies, one which is not necessarily based on subjective morphological properties. A sample of 492 moderately bright northern Sa and Sc spirals was chosen for future statistical analysis. New observations were made at 20 and 21 cm; the latter data are described in detail here. Infrared Astronomy Satellite (IRAS) fluxes were obtained from archival data. Finally, new estimates of arm pattern radomness and of local environmental harshness were compiled for most sample objects.

Magri, Christopher↗

Evaluating Optical Classification for Fermi Blazar Candidates with a Statistical Method Using Broadband Spectral Indices

We aim to test whether a blazar candidate of uncertain type (BCU) in the third Fermi catalog of active galactic nuclei (3LAC) can be potentially classified as a BL Lac object or a flat-spectrum radio quasar (FSRQ) by performing a statistical analysis of its broadband spectral properties. We find that 34% of the radio-selected BCUs (583 BCUs) are BL Lac-like and 20% are FSRQ-like, at a 90% level of confidence. Similarly, 77.3% of the X-ray-selected BCUs (176 BCUs) are evaluated as BL Lac-like and 6.8% may be FSRQ-like sources. And 88.7% of the BL Lac-like BCUs that have synchrotron peak frequencies available are high synchrotron peaked BL Lacs in the X-ray-selected BCUs. The percentages are accordingly 62% and 7.3% in the sample of 124 optically selected BCUs. The high ratio of the number of BL Lac-like sources to the number of FSRQ-like BCUs in the X-ray-selected and optically selected BCU samples is due to selection effects. Examining the consistency between our evaluation and spectroscopic identification case by case with a sample of 78 radio-selected BCUs, it is found that the statistical analysis and its resulting classifications agree with the results of the optical follow-up spectroscopic observations. Our observation campaign for high-|ρ{sub s}| BCUs selected with our method, i.e., |ρ{sub s}|>0.8, is ongoing.

79 ASTRONOMY AND ASTROPHYSICS↗

Determining the tensile strength of fuel surrogate TRISO-coated particle buffer, IPyC, and buffer-IPyC interlayer regions

A novel micro tensile sample fabrication technique for determining the tensile strength of the buffer, IPyC, and buffer -IPyC interlayer regions of surrogate (ZrO2) TRISO fuel particle layers was refined and implemented. Copper micro tensile samples served as baseline materials to verify the methods used. Tensile tests performed in this study, while limited in number, were analyzed using standard and Weibull statistics. As expected, the buffer layer was weakest, with an average ultimate tensile strength of 138.70 MPa, and the IPyC layer samples, were strongest, with an average ultimate tensile strength of 189.74 MPa. In the buffer -IPyC interface samples, all breaks occurred in the buffer region, though the average ultimate tensile strength of the samples, 159.80 MPa, was between the pure buffer and IPyC samples. These results suggest the interlayer region has unique properties, perhaps associated with pyrocarbon infiltration into the buffer layer during particle coating. All interlayer samples fractured within the buffer side; however, the stress strain behavior of some of these samples resembled the behavior of the IPyC layer samples. Here, the buffer and IPyC layer strengths had a normal distribution under Weibull analysis, while the interlayer region had a Rayleigh distribution. Further testing is needed to clarify both the standard and Weibull statistical results

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Inspection error and its adverse effects - A model with implications for practitioners

Inspection error has clearly been shown to have adverse effects upon the results desired from a quality assurance sampling plan. These effects upon performance measures have been well documented from a statistical point of view. However, little work has been presented to convince the QC manager of the unfavorable cost consequences resulting from inspection error. This paper develops a very general, yet easily used, mathematical cost model. The basic format of the well-known Guthrie-Johns model is used. However, it is modified as required to assess the effects of attributes sampling errors of the first and second kind. The economic results, under different yet realistic conditions, will no doubt be of interest to QC practitioners who face similar problems daily. Sampling inspection plans are optimized to minimize economic losses due to inspection error. Unfortunately, any error at all results in some economic loss which cannot be compensated for by sampling plan design; however, improvements over plans which neglect the presence of inspection error are possible. Implications for human performance betterment programs are apparent, as are trade-offs between sampling plan modification and inspection and training improvements economics.

Collins, R. D., Jr.↗

BATSE Observations of the Large-Scale Isotropy of Gamma-Ray Bursts

We use dipole and quadrupole statistics to test the large-scale isotropy of the first 1005 gamma-ray bursts observed by the Burst and Transient Source Experiment (BATSE). In addition to the entire sample of 1005 gamma-ray bursts, many subsets are examined. We use a variety of dipole and quadrupole statistics to search for Galactic and other predicted anisotropies and for anisotropies in a coordinate-system independent manner. We find the gamma-ray burst locations to be consistent with isotropy, e.g., for the total sample the observed Galactic dipole moment (cos theta) differs from the value predicted for isotropy by 0.9 sigma and the observed Galactic quadrupole moment (sin(exp 2) b - 1/3) by 0.3 sigma. We estimate for various models the anisotropies that could have been detected. If one-half of the locations were within 86 deg of the Galactic center, or within 28 deg of the Galactic plane, the ensuing dipole or quadrupole moment would have typically been detected at the 99% confidence level. We compare the observations with the dipole and quadrupole moments of various Galactic models. Several Galactic gamma-ray bursts models have moments within 2 sigma of the observations; most of the Galactic models proposed to date are no longer in acceptable agreement with the data. Although a spherical dark matter halo distribution could be consistent with the data, the required core radius is larger than the core radius of the dark matter halo used to explain the Galaxy's rotation curve. Gamma-ray bursts are much more isotropic than any observed Galactic population, strongly favoring but not requiring an origin at cosmological distances.

Briggs, Michael S.↗

Singular spectrum analysis in nonlinear dynamics, with applications to paleoclimatic time series

Two dimensions of a dynamical system given by experimental time series are distinguished. Statistical dimension gives a theoretical upper bound for the minimal number of degrees of freedom required to describe the attractor up to the accuracy of the data, taking into account sampling and noise problems. The dynamical dimension is the intrinsic dimension of the attractor and does not depend on the quality of the data. Singular Spectrum Analysis (SSA) provides estimates of the statistical dimension. SSA also describes the main physical phenomena reflected by the data. It gives adaptive spectral filters associated with the dominant oscillations of the system and clarifies the noise characteristics of the data. SSA is applied to four paleoclimatic records. The principal climatic oscillations and the regime changes in their amplitude are detected. About 10 degrees of freedom are statistically significant in the data. Large noise and insufficient sample length do not allow reliable estimates of the dynamical dimension.

Vautard, R.↗

The Containment Assurance Risk Framework of the Mars Sample Return Program

The Mars Sample Return campaign aims at bringing rock and atmospheric samples from Mars to Earth through a series of robotic missions. These missions would collect the samples being cached and deposited on Martian soil by the Perseverance rover, place them in a container, and launch them into Martian orbit for subsequent capture by an orbiter that would bring them back. Given there exists a non-zero probability that the samples contain biological material, precautions are being taken to design systems that would break the chain of contact between Mars and Earth. These include techniques such as sterilization of Martian particles, redundant containment vessels, and a robust reentry capsule capable of accurate landings without a parachute. Requirements exist that the probability of containment not assured of Martian-contaminated material into Earth’s biosphere be less than one in a million. To demonstrate compliance with this strict requirement, a statistical framework was developed to assess the likelihood of containment loss during each sample return phase and make a statement about the total combined mission probability of containment not assured. The work presented here describes this framework, which considers failure modes or fault conditions that can initiate failure sequences ultimately leading to containment not assured. Reliability estimates are generated from databases, design heritage, component specifications, or expert opinion in the form of probability density functions or point estimates and provided as inputs to the mathematical models that simulate the different failure sequences. The probabilistic outputs are then combined following the logic of several fault trees to compute the ultimate probability of containment not assured. Given the multidisciplinary nature of the problem and the different types of mathematical models used, the statistical tools needed for analysis are required to be computationally efficient. While standard Monte Carlo approaches are used for fast models, a multi-fidelity approach to rare event probabilities is proposed for expensive models. In this paradigm, inexpensive low-fidelity models are developed for computational acceleration purposes while the expensive high-fidelity model is kept in the loop to retain accuracy in the results. This work presents an example of end-to-end application of this framework highlighting the computational benefits of a multi-fidelity approach.

Giuseppe Cataldo↗

Statistical summaries of fatigue data for design purposes

Two methods are discussed for constructing a design curve on the safe side of fatigue data. Both the tolerance interval and equivalent prediction interval (EPI) concepts provide such a curve while accounting for both the distribution of the estimators in small samples and the data scatter. The EPI is also useful as a mechanism for providing necessary statistics on S-N data for a full reliability analysis which includes uncertainty in all fatigue design factors. Examples of statistical analyses of the general strain life relationship are presented. The tolerance limit and EPI techniques for defining a design curve are demonstrated. Examples usng WASPALOY B and RQC-100 data demonstrate that a reliability model could be constructed by considering the fatigue strength and fatigue ductility coefficients as two independent random variables. A technique given for establishing the fatigue strength for high cycle lives relies on an extrapolation technique and also accounts for "runners." A reliability model or design value can be specified.

Wirsching, P. H.↗

Instrument for precision long-term β-decay rate measurements

We describe an experimental setup for making precision measurements of relative β-decay rates of {sup 22}Na, {sup 36}Cl, {sup 54}Mn, {sup 60}Co, {sup 90}Sr, {sup 133}Ba, {sup 137}Cs, {sup 152}Eu, and {sup 154}Eu. The radioactive samples are mounted in two automated sample changers that sequentially position the samples with high spatial precision in front of sets of detectors. The set of detectors for one sample changer consists of four Geiger-Müller (GM) tubes and the other set of detectors consists of two NaI scintillators. The statistical uncertainty in the count rate is few times 0.01% per day for the GM detectors and about 0.01% per hour on the NaI detectors. The sample changers, detectors, and associated electronics are housed in a sealed chamber held at constant absolute pressure, humidity, and temperature to isolate the experiment from environmental variations. The apparatus is designed to accumulate statistics over many years in a regulated environment to test recent claims of small annual variations in the decay rates. We demonstrate that absent this environmental regulation, uncontrolled natural atmospheric pressure variations at our location would imprint an annual signal of 0.1% on the Geiger-Müller count rate. However, neither natural pressure variations nor plausible indoor room temperature variations cause a discernible influence on our NaI scintillator detector count rate.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Enabling probabilistic learning on manifolds through double diffusion maps

Here, we present a generative learning framework for probabilistic sampling that extends Probabilistic Learning on Manifolds (PLoM), which is designed to generate statistically consistent realizations of a random vector in a finite-dimensional Euclidean space, informed by a (representative) set of observations. In its original form, PLoM constructs a reduced-order probabilistic model by combining three main components: (a) kernel density estimation to approximate the underlying probability measure, (b) Diffusion Maps to characterize the manifold of the data, and (c) a reduced-order Itô Stochastic Differential Equation (ISDE) to sample from the learned distribution. However, its sampling dynamics are posed in the ambient space and the retained number of reduced coordinates is chosen by projection-reconstruction error. In practice, this often (i) requires more coordinates than the data’s intrinsic dimension to achieve stable sampling and (ii) lacks a smooth, basis-independent lifting back to the data domain; moreover, standard Diffusion Maps emphasize harmonic eigenfunctions and can miss non-harmonic latent structure. We address these limitations by decoupling geometry learning from sampling: a first Diffusion Maps pass identifies non-harmonic coordinates on which we formulate a full-order ISDE directly in the latent space, while Double Diffusion Maps captures multiscale geometric features and Geometric Harmonics (GH) learns a smooth lifting map to the ambient variables that is independent of the particular diffusion basis. This hybrid design preserves the system’s dynamical richness with a compact geometric representation and enables principled out-of-sample inference. The effectiveness and robustness of the proposed method are illustrated through two numerical studies: one based on data generated from two-dimensional Hermite polynomial functions and another based on high-fidelity simulations of a detonation wave in a reactive flow.

Double diffusion maps↗

Bayesian calibration of thermodynamic parameters for geochemical speciation modeling of cementitious materials

Chemical equilibrium modeling of cementitious materials requires aqueous-solid equilibrium constants of the controlling mineral phases (K{sub sp}) and the available concentrations of primary components. Inherent randomness of the input and model parameters, experimental measurement error, the assumptions and approximations required for numerical simulation, and inadequate knowledge of the chemical process contribute to uncertainty in model prediction. A numerical simulation framework is developed in this paper to assess uncertainty in K{sub sp} values used in geochemical speciation models. A Bayesian statistical method is used in combination with an efficient, adaptive Metropolis sampling technique to develop probability density functions for K{sub sp} values. One set of leaching experimental observations is used for calibration and another set is used for comparison to evaluate the applicability of the approach. The estimated probability distributions of K{sub sp} values can be used in Monte Carlo simulation to assess uncertainty in the behavior of aqueous-solid partitioning of constituents in cement-based materials.

36 MATERIALS SCIENCE↗