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Our research is focused on a better quantification of the variations in C02(sub) exchanges between the atmosphere and biosphere and the factors responsible for these exchanges. The principal approach is to infer the variations in the exchanges from variations in the atmospheric C02(sub) distribution.
Since H3+ was first spectroscopically detected on Jupiter, there has been considerable interest in using this simple molecular ion to probe conditions existing in the planet's auroral regions. Here we present a series of images of Jupiter recorded at wavelengths sensitive to emission by H3+, which reveal the spatial distribution of excited H3+ molecular ions in the jovian ionosphere, as seen from Earth. We believe that they provide high-spatial-resolution images of polar aurorae on Jupiter. They suggest that the intensity of the auroral emission can vary on a timescale of an hour, a shorter period than had previously been noted. We also find that the spatial distribution of H3+ emissions correlates only partially with the loci of auroral activity inferred from ultraviolet and longer-wavelength infrared observations. The H3+ emission may therefore be controlled by auroral processes that are different from those responsible for the ultraviolet and infrared emissions.
The building of the NASA Orbital Debris Engineering Model, whether ORDEM2000 or its recently updated version ORDEM2010, uses as its foundation a number of model debris populations, each truncated at a minimum object-size ranging from 10 micron to 1 m. This paper discusses the development of the ORDEM2010 model debris populations in LEO (low Earth orbit), focusing on centimeter (smaller than 10 cm) and millimeter size regimes. Primary data sets used in the statistical derivation of the cm- and mm-size model populations are from the Haystack radar operated in a staring mode. Unlike cataloged objects of sizes greater than approximately 10 cm, ground-based radars monitor smaller-size debris only in a statistical manner instead of tracking every piece. The mono-static Haystack radar can detect debris as small as approximately 5 mm at moderate LEO altitudes. Estimation of millimeter debris populations (for objects smaller than approximately 6 mm) rests largely on Goldstone radar measurements. The bi-static Goldstone radar can detect 2- to 3-mm objects. The modeling of the cm- and mm-debris populations follows the general approach to developing other ORDEM2010-required model populations for various components and types of debris. It relies on appropriate reference populations to provide necessary prior information on the orbital structures and other important characteristics of the debris objects. NASA's LEO-to-GEO Environment Debris (LEGEND) model is capable of furnishing such reference populations in the desired size range. A Bayesian statistical inference process, commonly adopted in ORDEM2010 model-population derivations, changes a priori distribution into a posteriori distribution and thus refines the reference populations in terms of data. This paper describes key elements and major steps in the statistical derivations of the cm- and mm-size debris populations and presents results. Due to lack of data for near 1-mm sizes, the model populations of 1- to 3.16-mm objects are an empirical extension from larger debris. The extension takes into account the results of micro-debris (from 10 micron to 1 mm) population modeling that is based on shuttle impact data, in the hope of making a smooth transition between micron and millimeter size regimes. This paper also includes a brief discussion on issues and potential future work concerning the analysis and interpretation of Goldstone radar data.
The Tagish Lake meteorite is a primitive C2 carbonaceous chondrite with a mineralogy, oxygen isotope, and bulk chemical. However, in contrast to many CI and CM carbonaceous chondrites, the Tagish Lake meteorite was reported to have only trace levels of indigenous amino acids, with evidence for terrestrial L-amino acid contamination from the Tagish Lake meltwater. The lack of indigenous amino acids in Tagish Lake suggested that they were either destroyed during parent body alteration processes and/or the Tagish Lake meteorite originated on a chemically distinct parent body from CI and CM meteorites where formation of amino acids was less favorable. We recently measured the amino acid composition of three different lithologies (11h, 5b, and 11i) of pristine Tagish Lake meteorite fragments that represent a range of progressive aqueous alteration in order 11h < 5b < 11i as inferred from the mineralogy, petrology, bulk isotopes, and insoluble organic matter structure. The distribution and enantiomeric abundances of the one- to six-carbon aliphatic amino acids found in hot-water extracts of the Tagish Lake fragments were determined by ultra performance liquid chromatography fluorescence detection and time of flight mass spectrometry coupled with OPA/NAC derivatization. Stable carbon isotope analyses of the most abundant amino acids in 11h were measured with gas chromatography coupled with quadrupole mass spectrometry and isotope ratio mass spectrometry.
The distribution of iron on the surface of the asteroid Vesta was investigated using Dawn's Gamma Ray and Neutron Detector (GRaND) [1,2]. Iron varies predictably with rock type for the howardite, eucrite, and diogenite (HED) meteorites, thought to be representative of Vesta. The abundance of Fe in howardites ranges from about 12 to 15 wt.%. Basaltic eucrites have the highest abundance, whereas, lower crustal and upper mantle materials (cumulate eucrites and diogenites) have the lowest, and howardites are intermediate [3]. We have completed a mapping study of 7.6 MeV gamma rays produced by neutron capture by Fe as measured by the bismuth germanate (BGO) detector of GRaND [1]. The procedures to determine Fe counting rates are presented in detail here, along with a preliminary distribution map, constituting the necessary initial step to quantification of Fe abundances. We find that the global distribution of Fe counting rates is generally consistent with independent mineralogical and compositional inferences obtained by other instruments on Dawn such as measurements of pyroxene absorption bands by the Visual and Infrared Spectrometer (VIR) [4] and Framing Camera (FC) [5] and neutron absorption measurements by GRaND [6].
We use high-quality data obtained by the High Resolution Coronal Imager (Hi-C) to examine bright dots (BDs) in a sunspot's penumbra. The sizes of these BDs are on the order of 1 arcsecond (1") and are therefore hard to identify using the Atmospheric Imaging Assembly's (AIA) 0.6" pixel(exp −1) resolution. These BD become readily apparent with Hi-C's 0.1" pixel(exp −1) resolution. Tian et al. (2014) found penumbral BDs in the transition region (TR) by using the Interface Region Imaging Spectrograph (IRIS). However, only a few of their dots could be associated with any enhanced brightness in AIA channels. In this work, we examine the characteristics of the penumbral BDs observed by Hi-C in a sunspot penumbra, including their sizes, lifetimes, speeds, and intensity. We also attempt to find any association of these BDs to the IRIS BDs. There are fewer Hi-C BDs in the penumbra than seen by IRIS, though different sunspots were studied. We use 193 Angstroms Hi-C data from July 11, 2012 which observed from approximately 18:52:00 UT- 18:56:00 UT and supplement it with data from AIA's 193 Angstrom passband to see the complete lifetime of the dots that were born before and/or lasted longer than Hi- C's 5-minute observation period. We use additional AIA passbands and compare the light curves of the BDs at different temperatures to test whether the Hi-C BDs are TR BDs. We find that most Hi-C BDs show clear movement, and of those that do, they move in a radial direction, toward or away from the sunspot umbra. Single BDs interact with other BDs, combining to fade away or brighten. The BDs that do not interact with other BDs tend to move less. Many of the properties of our BDs are similar to the extreme values of the IRIS BDs, e.g., they move slower on average and their sizes and lifetimes are on the higher end of the IRIS BDs. We infer that our penumbral BDs are the large-scale end of the distribution of BDs observed by IRIS.
This work presents a computationally-efficient inverse approach to probabilistic damage diagnosis. Given strain data at a limited number of measurement locations, Bayesian inference and Markov Chain Monte Carlo (MCMC) sampling are used to estimate probability distributions of the unknown location, size, and orientation of damage. Substantial computational speedup is obtained by replacing a three-dimensional finite element (FE) model with an efficient surrogate model. The approach is experimentally validated on cracked test specimens where full field strains are determined using digital image correlation (DIC). Access to full field DIC data allows for testing of different hypothetical sensor arrangements, facilitating the study of strain-based diagnosis effectiveness as the distance between damage and measurement locations increases. The ability of the framework to effectively perform both probabilistic damage localization and characterization in cracked plates is demonstrated and the impact of measurement location on uncertainty in the predictions is shown. Furthermore, the analysis time to produce these predictions is orders of magnitude less than a baseline Bayesian approach with the FE method by utilizing surrogate modeling and effective numerical sampling approaches.
Condensation clouds in substellar atmospheres have been widely inferred from spectra and photometric variability. Up until now, their horizontally averaged vertical distribution and mean particle size have been largely characterized using models, one of which is the eddy diffusion-sedimentation model from Ackerman and Marley that relies on a sedimentation efficiency parameter, f(sub sed), to determine the vertical extent of clouds in the atmosphere. However, the physical processes controlling the vertical structure of clouds in substellar atmospheres are not well understood. In this work, we derive trends in f(sub sed) across a large range of eddy diffusivities (K (sub zz) ), gravities, material properties, and cloud formation pathways by fitting cloud distributions calculated by a more detailed cloud microphysics model. We find that f(sub sed) is dependent on K (sub zz), but not gravity, when K (sub zz) is held constant. f(sub sed) is most sensitive to the nucleation rate of cloud particles, as determined by material properties like surface energy and molecular weight. High surface energy materials form fewer, larger cloud particles, leading to large f(sub sed) (>1), and vice versa for materials with low surface energy. For cloud formation via heterogeneous nucleation, f(sub sed) is sensitive to the condensation nuclei flux and radius, connecting cloud formation in substellar atmospheres to the objects' formation environments and other atmospheric aerosols. These insights could lead to improved cloud models that help us better understand substellar atmospheres. For example, we demonstrate that f(sub sed) could increase with increasing cloud base depth in an atmosphere, shedding light on the nature of the brown dwarf L/T transition.
This work demonstrates dual-arm lifting of bulky objects based on inferred object properties (center of mass (COM) location, weight, and shape) using proprioception (i.e. force torque measurements). Data-driven Bayesian models describe these quantities, which enables subsequent behaviors to depend on confidence of the learned models. Experiments were conducted using the NASA Jet Propulsion Laboratory’s (JPL) RoboSimian to lift a variety of cumbersome objects ranging in mass from 7kg to 25kg. The position of a supporting second manipulator was determined using a particle set and heuristics that were derived from inferred object properties. The supporting manipulator decreased the initial manipulator’s load and distributed the wrench load more equitably across each manipulator, for each bulky object. Knowledge of the objects came from pure proprioception (i.e. without reliance on vision or other exteroceptive sensors) throughout the experiments.
The sensitivity of the Deep Underground Neutrino Experiment (DUNE) to neutrino oscillation is evaluated using a Bayesian Markov Chain Monte Carlo (MCMC) approach. This analysis uses the same underlying sensitivity inputs as previous DUNE studies [Eur. Phys. J. C 80, 978 (2020)], and therefore does not present updated DUNE sensitivities, but instead explores the additional inferences accessible using a Bayesian approach. We present four-dimensional posterior probability distributions of the oscillation parameters, highlighting the breadth of correlation in the parameter space of interest, especially between $\sin^2 θ_{23}$ and $\sin^2 θ_{13}$. We exploit the flexibility of the Bayesian framework to incorporate parameter constraints post hoc and assess the impact of applying a reactor short-baseline $θ_{13}$ constraint. A significant increase in the sensitivity to the $θ_{23}$ octant is found when including the constraint. Posterior distributions of derived quantities can be easily constructed from MCMC results. This work presents the first study of DUNE's sensitivity to the Jarlskog invariant, $J$, a quantity that provides a parametrisation-independent measure of charge-parity violation in the leptonic sector.
A method for determining the location, size distribution, and composition of interstellar dust grains from the haloes of binary X-ray sources is described. The method is based on the time dependence of the halo X-ray emission during an eclipse of the point source. The distance of the dust cloud is inferred directly from observations of the growth of the dark circle around the eclipsed point source. Grain size distribution in the interstellar dust clouds is derived from the halo brightness profile at a given photon energy. The composition of the grains is obtained by observing the spectral features in the total optical depth due to X-ray scattering near the photoionization thresholds of the elements in the grains. The haloes become dim just below the ionization threshold, and sharply increase in function brightness as the photon energy increases beyond the absorption edge of the relevant atom. The method makes it possible to observe and analyze the halo emission during eclipse even without imaging the source. It is suggested that haloes probably account for the soft X-rays observed during eclipses and dips observed in sources including 4U1915-05 and X1755-338.
Global geologic maps are useful tools for efficient interpretation of a planetary body, and they provide global context for the diversity and evolution of the surface. We used data acquired by the OSIRIS-REx spacecraft to create the first global geologic map of the near-Earth asteroid (101955) Bennu. As this is the first geologic map of a small, non-spherical, rubble-pile asteroid, we discuss the distinctive mapping challenges and best practices that may be useful for future exploration of similar asteroids, such as those to be visited with the Hera and Janus missions. By mapping on two centimeter-scale global image mosaics (2D projected space) and a centimeter-scale global shape model (3D space), we generated three input maps respectively describing Bennu’s shape features, geologic features, and surface texture. Based on these input maps, we defined two geologic units: the Smooth Unit and the Rugged Unit. The units are differentiated primarily on the basis of surface texture, concentrations of boulders, and the distributions of lineaments, mass movement features, and craters. They are bounded by several scarps. The Rugged Unit contains abundant boulders and signs of recent mass movement. It also has fewer small(<20 m), putatively fresh craters than the Smooth Unit, suggesting that such craters have been erased in the former. Based on these geologic indicators, we infer that the Rugged Unit has the younger surface of the two. Differential crater size-frequency distributions and the distribution of the freshest craters suggest that both unit surfaces formed ~10–65 million years ago, when Bennu was located in the Main Asteroid Belt, and the Smooth Unit has not been significantly resurfaced in the past 2 million years. Meanwhile, the Rugged Unit has experienced resurfacing within the past ~500,000years during Bennu’s lifetime as a near-Earth asteroid. The geologic units are consistent with global diversity in slope, surface roughness, normal albedo, and thermal emission spectral characteristics. The site on Bennu where the OSIRIS-REx mission collected a regolith sample is located in the Smooth Unit, in a small crater nested within a larger one. So although the Smooth Unit is an older surface than the Rugged Unit, the impact-crater settingindicates that the material sampled was recently exposed. Several similarities are apparent between Bennu and asteroid (162173) Ryugu from a global geologic perspective, including two geologic units distinguishable by variations in the number density of boulders, as well as in other datasets such as brightness.
The Neutron Induced Fission Fragment Tracking Experiment (NIFFTE) collaboration has performed measurements with a fission time projection chamber (fissionTPC) to study the fission process by reconstructing full three-dimensional tracks of fission fragments and other ionizing radiation. The amount of linear momentum imparted to the fissioning nucleus by the incident neutron can be inferred by measuring the opening angle between the fission fragments. Using this measured linear momentum, fission fragment angular distributions can be converted to the center-of-mass frame for anisotropy measurements. Angular anisotropy is an important experimental observable for understanding the quantum mechanical state of the fissioning nucleus and vital to determining detection efficiency for cross section measurements. Neutron linear momentum transfer to fissioning 235 U, 238 U, and 239Pu and fission fragment angular anisotropy of 235 U and 238 U as a function of neutron energies in the range 130 keV–250 MeV are presented.
Abstract The demographic history of a population, and the distribution of fitness effects (DFE) of newly arising mutations in functional genomic regions, are fundamental factors dictating both genetic variation and evolutionary trajectories. Although both demographic and DFE inference has been performed extensively in humans, these approaches have generally either been limited to simple demographic models involving a single population, or, where a complex population history has been inferred, without accounting for the potentially confounding effects of selection at linked sites. Taking advantage of the coding-sparse nature of the genome, we propose a 2-step approach in which coalescent simulations are first used to infer a complex multi-population demographic model, utilizing large non-functional regions that are likely free from the effects of background selection. We then use forward-in-time simulations to perform DFE inference in functional regions, conditional on the complex demography inferred and utilizing expected background selection effects in the estimation procedure. Throughout, recombination and mutation rate maps were used to account for the underlying empirical rate heterogeneity across the human genome. Importantly, within this framework it is possible to utilize and fit multiple aspects of the data, and this inference scheme represents a generalized approach for such large-scale inference in species with coding-sparse genomes.
The projected density distribution of resolved stars near the center of M15 is shown to be consistent with either a power-law cusp N(r) approximately r(exp alpha), with alpha approximately -0.85 +/- 0.2, or with a King model with a core of radius approximately less than 2 sec. The inferred slope is in agreement with the theoretical value, alpha = -0.75, calculated by Bahcall and Wolf for the distribution of equal-mass stars surrounding a massive black hole and is also consistent with the radial profile expected from core collapse without a central black hole. The object AC 214 is a candidate for the central density cusp. Analysis of Monte Carlo simulations of the diffuse light indicates that, using current analysis techniques and available data, the residual light is not a reliable indicator of the true density distribution. This is contrary to earlier work. Photometric measurements in V and I of more than 5 x 10(exp 3) stars (and in U, V, and I of approximately greater than 1500 stars) are used to construct color-magnitude diagrams in the central 1 min of M15. Fourteen blue straggler candidates are identified in the inner 20 sec. The central color gradient noticed by previous researchers is caused by a central depletion of bright red giant stars rather than an excess of blue stragglers or blue horizontal branch stars.
The rapid expansion of artificial intelligence (AI) and machine learning is driving unprecedented electricity demand from data centers. It is predicted that by 2030, 90% of AI workloads will be inference-based, requiring interconnection of multiple low-latency edge data centers (<20 MW) sited closer to end users - often on already constrained distribution feeders. Although individually small, these loads can aggregate to large loads per feeder, straining infrastructure, creating multi-year interconnection delays, and driving up customer costs. This paper proposes a data center-focused grid-integration framework that combines feeder hosting capacity analysis with building energy efficiency, building load flexibility, and waste heat reuse to expand effective feeder and substation headroom. Such approaches can reduce interconnection delays, lower costs for ratepayers, and accelerate AI-ready infrastructure deployment.
The Nimbus-7 Total Ozone Mapping Spectrometer (TOMS) was used to map the distribution of total ozone in and around western Atlantic tropical cyclones from 1979 to 1982. It was found that the TOMS-observed total ozone distribution within the subtropics during the tropical cyclone season correlated well with the tropopause topography, similar to earlier middle-latitudinal observations. This relationship made it possible to use TOMS to monitor the propagation of upper-tropospheric subtropical transient waves and the mutual adjustment between the tropical cyclone and the upper-tropospheric waves during their interaction. These total ozone patterns reflected the three-dimensional upper-tropospheric transport processes that were conducive for storm intensification and weakening. It was also found from satellite observations and numerical model simulations that modification of the environmental distribution of total ozone by the tropical cyclones was primarily caused by the secondary circulation associated with the tropical cyclone's outflow jet and the intrusion of stratospheric air in the eyes of tropical cyclones.
Markov chain Monte Carlo (MCMC) methods have not been broadly adopted in Bayesian neural networks (BNNs). This paper initially reviews the main challenges in sampling from the parameter posterior of a neural network via MCMC. Such challenges culminate to lack of convergence to the parameter posterior. Nevertheless, this paper shows that a nonconverged Markov chain, generated via MCMC sampling from the parameter space of a neural network, can yield via Bayesian marginalization a valuable posterior predictive distribution of the output of the neural network. Further, classification examples based on multilayer perceptrons showcase highly accurate posterior predictive distributions. The postulate of limited scope for MCMC developments in BNNs is partially valid; an asymptotically exact parameter posterior seems less plausible, yet an accurate posterior predictive distribution is a tenable research avenue.