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Neutral sodium (Na I) is an alkali metal with a favorable absorption cross section such that tenuous gases are easily illuminated at select transiting exoplanet systems. We examine both the time-averaged and time-series alkali spectral flux individually, over 4 nights at a hot Saturn system on a $\sim$ 2.8 day orbit about a Sun-like star WASP-49 A. Very Large Telescope/ESPRESSO observations are analyzed, providing new constraints. We recover the previously confirmed residual sodium flux uniquely when averaged, whereas night-to-night Na I varies by more than an order of magnitude. On HARPS/3.6-m Epoch II, we report a Doppler redshift at $v_{ \Gamma, \mathrm{NaD}} =$ +9.7 $\pm$ 1.6 km/s with respect to the planet's rest frame. Upon examining the lightcurves, we confirm night-to-night variability, on the order of $\sim$ 1-4 % in NaD rarely coinciding with exoplanet transit, not readily explained by stellar activity, starspots, tellurics, or the interstellar medium. Coincident with the $\sim$+10 km/s Doppler redshift, we detect a transient sodium absorption event dF$_{\mathrm{NaD}}$/F$_{\star}$ = 3.6 $\pm$ 1 % at a relative difference of $\Delta F_{\mathrm{NaD}} (t) \sim$ 4.4 $\pm$ 1 %, enduring $\Delta t_{\mathrm{NaD}} \gtrsim$ 40 minutes. Since exoplanetary alkali signatures are blueshifted due to the natural vector of radiation pressure, estimated here at roughly $\sim$ -5.7 km/s, the radial velocity is rather at +15.4 km/s, far larger than any known exoplanet system. Given that the redshift magnitude v$_{\Gamma}$ is in between the Roche limit and dynamically stable satellite orbits, the transient sodium may be a putative indication of a natural satellite orbiting WASP-49 A b., Comment: Accepted to ApJ Letters (2024 August 2)

Asteroseismology of dwarf stars cooler than the Sun is very challenging due to the low amplitudes and rapid timescales of oscillations. Here, we present the asteroseismic detection of solar-like oscillations at 4-minute timescales ($\nu_{\mathrm{max}}\sim4300\mu$Hz) in the nearby K-dwarf $\sigma$ Draconis using extreme precision Doppler velocity observations from the Keck Planet Finder and 20-second cadence photometry from NASA's Transiting Exoplanet Survey Satellite. The star is the coolest dwarf star to date with both velocity and luminosity observations of solar-like oscillations, having amplitudes of $5.9\pm0.8\,$cm$\,\text{s}^{-1}$ and $0.8\pm0.2$ ppm, respectively. These measured values are in excellent agreement with established luminosity-velocity amplitude relations for oscillations and provide further evidence that mode amplitudes for stars with $T_{\mathrm{eff}}<\,5500\,$K diminish in scale following a $(L/M)^{1.5}$ relation. By modeling the star's oscillation frequencies from photometric data, we measure an asteroseismic age of $4.5\pm0.9\,\rm{(ran)} \pm 1.2\,\rm{(sys)}$ Gyr. The observations demonstrate the capability of next-generation spectrographs and precise space-based photometry to extend observational asteroseismology to nearby cool dwarfs, which are benchmarks for stellar astrophysics and prime targets for directly imaging planets using future space-based telescopes., Comment: Accepted for publication in The Astrophysical Journal

HISPEC is a new, high-resolution near-infrared spectrograph being designed for the W.M. Keck II telescope. By offering single-shot, R=100,000 between 0.98 - 2.5 um, HISPEC will enable spectroscopy of transiting and non-transiting exoplanets in close orbits, direct high-contrast detection and spectroscopy of spatially separated substellar companions, and exoplanet dynamical mass and orbit measurements using precision radial velocity monitoring calibrated with a suite of state-of-the-art absolute and relative wavelength references. MODHIS is the counterpart to HISPEC for the Thirty Meter Telescope and is being developed in parallel with similar scientific goals. In this proceeding, we provide a brief overview of the current design of both instruments, and the requirements for the two spectrographs as guided by the scientific goals for each. We then outline the current science case for HISPEC and MODHIS, with focuses on the science enabled for exoplanet discovery and characterization. We also provide updated sensitivity curves for both instruments, in terms of both signal-to-noise ratio and predicted radial velocity precision., Comment: 25 pages, 9 figures. To appear in the Proceedings of SPIE: Techniques and Instrumentation for Detection of Exoplanets XI, vol. 12680 (2023)

Adaptive planning is ideally suited for the deep uncertainties presented by climate change. While there is a robust scholarship on the theory and methods of adaptive planning, this has largely neglected how adaptive planning is affected by existing planning institutions and how to move forward within the constraints of traditional planning organizations. This study asks: How do existing traditional planning institutions support adaptive planning? We explore this for flood planning in the Lower Rio Grande Valley of Texas, United States. We draw on county hazard plan and regional flood plan documents as well as transcripts of regional flood planning meetings to explore the emergent topics of these institutional outputs. Using Natural Language Processing to analyze this large amount of text, we find that hazard plans and discussions developing these plans are largely lacking an adaptive approach.

In this paper, we introduce a novel form of value function, $Q(s, s')$, that expresses the utility of transitioning from a state $s$ to a neighboring state $s'$ and then acting optimally thereafter. In order to derive an optimal policy, we develop a forward dynamics model that learns to make next-state predictions that maximize this value. This formulation decouples actions from values while still learning off-policy. We highlight the benefits of this approach in terms of value function transfer, learning within redundant action spaces, and learning off-policy from state observations generated by sub-optimal or completely random policies. Code and videos are available at http://sites.google.com/view/qss-paper., Comment: Accepted into ICML 2020

Observations of the Sun as a star have been key to guiding models of stellar atmospheres and additionally provide useful insights on the effects of granulation and stellar activity on radial velocity measurements. Most high resolution solar atlases contain telluric lines that span the optical and limit the spectral regions useful for analysis. We present here a telluric-corrected solar atlas covering 0.5-1.0 micron derived from solar spectra taken with a Fourier Transform Spectrograph (FTS) at the Institut f\"ur Astrophysik, G\"ottingen. This atlas is the highest resolution spectrum with a wavelength calibration precise to +/-10 m/s across this 500 nm spectral window. We find that the atlas matches to within 3% of the telluric-corrected Kitt Peak atlas in regions containing telluric absorption weaker than 50% in transmission. The telluric component of the spectral data is fit with a semi-empirical model composed of Lorentz profiles initialized to the HITRAN parameters for each absorption feature. Comparisons between the best-fit telluric parameters describing the Lorentz profile for each absorption feature to the original HITRAN values in general show excellent agreement considering the effects atmospheric pressure and temperature have on our final parameters. However, we identify a small subset of absorption features with larger offsets relative to the catalogued line parameters. We make our final solar atlas available online. We additionally make available the telluric spectra extracted from the data that, given the high resolution of the spectrum, would be useful for studying the time evolution of telluric line shapes and their impact on Doppler measurements., Comment: 20 pages, 12 figures

Imitation by observation is an approach for learning from expert demonstrations that lack action information, such as videos. Recent approaches to this problem can be placed into two broad categories: training dynamics models that aim to predict the actions taken between states, and learning rewards or features for computing them for Reinforcement Learning (RL). In this paper, we introduce a novel approach that learns values, rather than rewards, directly from observations. We show that by using values, we can significantly speed up RL by removing the need to bootstrap action-values, as compared to sparse-reward specifications., Comment: Accepted into the Workshop on Self-Supervised Learning at ICML 2019

The MINiature Exoplanet Radial Velocity Array (MINERVA) is a dedicated observatory of four 0.7m robotic telescopes fiber-fed to a KiwiSpec spectrograph. The MINERVA mission is to discover super-Earths in the habitable zones of nearby stars. This can be accomplished with MINERVA's unique combination of high precision and high cadence over long time periods. In this work, we detail changes to the MINERVA facility that have occurred since our previous paper. We then describe MINERVA's robotic control software, the process by which we perform 1D spectral extraction, and our forward modeling Doppler pipeline. In the process of improving our forward modeling procedure, we found that our spectrograph's intrinsic instrumental profile is stable for at least nine months. Because of that, we characterized our instrumental profile with a time-independent, cubic spline function based on the profile in the cross dispersion direction, with which we achieved a radial velocity precision similar to using a conventional "sum-of-Gaussians" instrumental profile: 1.8 m s$^{-1}$ over 1.5 months on the RV standard star HD 122064. Therefore, we conclude that the instrumental profile need not be perfectly accurate as long as it is stable. In addition, we observed 51 Peg and our results are consistent with the literature, confirming our spectrograph and Doppler pipeline are producing accurate and precise radial velocities., Comment: 22 pages, 9 figures, submitted to PASP, Peer-Reviewed and Accepted

With TESS and ground-based surveys searching for rocky exoplanets around cooler, nearby stars, the number of Earth-sized exoplanets that are well-suited for atmospheric follow-up studies will increase significantly. For atmospheric characterization, the James Webb Space Telescope will only be able to target a small fraction of the most interesting systems, and the usefulness of ground-based observatories will remain limited by a range of effects related to Earth's atmosphere. Here, we explore a new method for ground-based exoplanet atmospheric characterization that relies on simultaneous, differential, ultra-narrow-band photometry. The instrument uses a narrow-band interference filter and an optical design that enables simultaneous observing over two 0.3 nm wide bands spaced 1 nm apart. We consider the capabilities of this instrument in the case where one band is centered on an oxygen-free continuum region while the other band overlaps the 760 nm oxygen band head in the transmission spectrum of the exoplanet, which can be accessible from Earth in systems with large negative line-of-sight velocities. We find that M9 and M4 dwarfs that meet this radial velocity requirement will be the easiest targets but must be nearby (<8 pc) and will require the largest upcoming Extremely Large Telescopes. The oxyometer instrument design is simple and versatile and could be adapted to enable the study of a wide range of atmospheric species. We demonstrate this by building a prototype oxyometer and present its design and a detection of a 50 ppm simulated transit signal in the laboratory. We also present data from an on-sky test of a prototype oxyometer, demonstrating the ease of use of the compact instrument design., Comment: 27 pages, 13 figures

In this paper, we describe a novel approach to imitation learning that infers latent policies directly from state observations. We introduce a method that characterizes the causal effects of latent actions on observations while simultaneously predicting their likelihood. We then outline an action alignment procedure that leverages a small amount of environment interactions to determine a mapping between the latent and real-world actions. We show that this corrected labeling can be used for imitating the observed behavior, even though no expert actions are given. We evaluate our approach within classic control environments and a platform game and demonstrate that it performs better than standard approaches. Code for this work is available at https://github.com/ashedwards/ILPO., Comment: Accepted to ICML 2019

Goals for reinforcement learning problems are typically defined through hand-specified rewards. To design such problems, developers of learning algorithms must inherently be aware of what the task goals are, yet we often require agents to discover them on their own without any supervision beyond these sparse rewards. While much of the power of reinforcement learning derives from the concept that agents can learn with little guidance, this requirement greatly burdens the training process. If we relax this one restriction and endow the agent with knowledge of the reward function, and in particular of the goal, we can leverage backwards induction to accelerate training. To achieve this, we propose training a model to learn to take imagined reversal steps from known goal states. Rather than training an agent exclusively to determine how to reach a goal while moving forwards in time, our approach travels backwards to jointly predict how we got there. We evaluate our work in Gridworld and Towers of Hanoi and empirically demonstrate that it yields better performance than standard DDQN.

A major bottleneck for developing general reinforcement learning agents is determining rewards that will yield desirable behaviors under various circumstances. We introduce a general mechanism for automatically specifying meaningful behaviors from raw pixels. In particular, we train a generative adversarial network to produce short sub-goals represented through motion templates. We demonstrate that this approach generates visually meaningful behaviors in unknown environments with novel agents and describe how these motions can be used to train reinforcement learning agents., Comment: Deep Reinforcement Learning Symposium, NIPS 2017

We examine the z = 0 group-integrated stellar and cold baryonic (stars + cold atomic gas) mass functions (group SMF and CBMF) and the baryonic collapse efficiency (group cold baryonic to dark matter halo mass ratio) using the RESOLVE and ECO survey galaxy group catalogs and a galform semi-analytic model (SAM) mock catalog. The group SMF and CBMF fall off more steeply at high masses and rise with a shallower low-mass slope than the theoretical halo mass function (HMF). The transition occurs at group-integrated cold baryonic mass M_coldbary ~ 10^11 Msun. The SAM, however, has significantly fewer groups at the transition mass ~ 10^11 Msun and a steeper low-mass slope than the data, suggesting that feedback is too weak in low-mass halos and conversely too strong near the transition mass. Using literature prescriptions to include hot halo gas and potential unobservable galaxy gas produces a group BMF with slope similar to the HMF even below the transition mass. Its normalization is lower by a factor of ~2, in agreement with estimates of warm-hot gas making up the remaining difference. We compute baryonic collapse efficiency with the halo mass calculated two ways, via halo abundance matching (HAM) and via dynamics (extended all the way to three-galaxy groups using stacking). Using HAM, we find that baryonic collapse efficiencies reach a flat maximum for groups across the halo mass range of M_halo ~ 10^11.4-12 Msun, which we label "nascent groups." Using dynamics, however, we find greater scatter in baryonic collapse efficiencies, likely indicating variation in group hot-to-cold baryon ratios. Similarly, we see higher scatter in baryonic collapse efficiencies in the SAM when using its true groups and their group halo masses as opposed to friends-of-friends groups and HAM masses., Comment: 23 pages, 16 figures, accepted for publication in ApJ

Ground-based astronomical observations may be limited by telluric water vapor absorption, which is highly variable in time and significantly complicates both spectroscopy and photometry in the near-infrared (NIR). To achieve the sensitivity required to detect Earth-sized exoplanets in the NIR, simultaneous monitoring of precipitable water vapor (PWV) becomes necessary to mitigate the impact of variable telluric lines on radial velocity measurements and transit light curves. To address this issue, we present the Camera for the Automatic Monitoring of Atmospheric Lines (CAMAL), a stand-alone, inexpensive six-inch aperture telescope dedicated to measuring PWV at the Fred Lawrence Whipple Observatory on Mount Hopkins. CAMAL utilizes three narrowband NIR filters to trace the amount of atmospheric water vapor affecting simultaneous observations with the MINiature Exoplanet Radial Velocity Array (MINERVA) and MINERVA-Red telescopes. Here we present the current design of CAMAL, discuss our data analysis methods, and show results from 11 nights of PWV measurements taken with CAMAL. For seven nights of data, we have independent PWV measurements extracted from high-resolution stellar spectra taken with the Tillinghast Reflector Echelle Spectrometer (TRES) also located on Mount Hopkins. We use the TRES spectra to calibrate the CAMAL absolute PWV scale. Comparisons between CAMAL and TRES PWV estimates show excellent agreement, matching to within 1 mm over a 10 mm range in PWV. Analysis of CAMAL's photometric precision propagates to PWV measurements precise to better than 0.5 mm in dry (PWV < 4 mm) conditions. We also find that CAMAL-derived PWVs are highly correlated with those from a GPS-based water vapor monitor located approximately 90 km away at Kitt Peak National Observatory, with a root mean square PWV difference of 0.8 mm., Comment: 17 pages, 14 figures, Accepted for publication in PASP

In reinforcement learning, we often define goals by specifying rewards within desirable states. One problem with this approach is that we typically need to redefine the rewards each time the goal changes, which often requires some understanding of the solution in the agents environment. When humans are learning to complete tasks, we regularly utilize alternative sources that guide our understanding of the problem. Such task representations allow one to specify goals on their own terms, thus providing specifications that can be appropriately interpreted across various environments. This motivates our own work, in which we represent goals in environments that are different from the agents. We introduce Cross-Domain Perceptual Reward (CDPR) functions, learned rewards that represent the visual similarity between an agents state and a cross-domain goal image. We report results for learning the CDPRs with a deep neural network and using them to solve two tasks with deep reinforcement learning., Comment: A shorter version of this paper was accepted to RLDM (http://rldm.org/rldm2017/)

We present the HI mass inventory for the RESOLVE survey, a volume-limited, multi-wavelength census of >1500 z=0 galaxies spanning diverse environments and complete in baryonic mass down to dwarfs of 10^9 Msun. This first 21cm data release provides robust detections or strong upper limits (1.4M_HI < 5 to 10% of stellar mass M_stars) for 94% of RESOLVE. We examine global atomic gas-to-stellar mass ratios (G/S) in relation to galaxy environment using several metrics: group dark matter halo mass M_h , central/satellite designation, relative mass density of the cosmic web, and distance to nearest massive group. We find that at fixed M_stars, satellites have decreasing G/S with increasing M_h starting clearly at M_h = 10^12 Msun, suggesting the presence of starvation and/or stripping mechanisms associated with halo gas heating in intermediate-mass groups. The analogous relationship for centrals is uncertain because halo abundance matching builds in relationships between central G/S, stellar mass, and halo mass, which depend on the integrated group property used as a proxy for halo mass (stellar or baryonic mass). On larger scales G/S trends are less sensitive to the abundance matching method. At fixed M_h < 10^12 Msun, the fraction of gas-poor centrals increases with large-scale structure density. In overdense regions, we identify a rare population of gas-poor centrals in low-mass (M_h < 10^11.4 Msun) halos primarily located within 1.5 times the virial radius of more massive (M_h > 10^12 Msun) halos, suggesting that gas stripping and/or starvation may be induced by interactions with larger halos or the surrounding cosmic web. We find that the detailed relationship between G/S and environment varies when we examine different subvolumes of RESOLVE independently, which we suggest may be a signature of assembly bias., Comment: 24 pages, 13 figures, accepted for publication in ApJ, data tables available at http://resolve.astro.unc.edu/pages/database.php

Atomic force microscope (AFM) users often calibrate the spring constants of cantilevers using functionality built into individual instruments. This is performed without reference to a global standard, which hinders robust comparison of force measurements reported by different laboratories. In this article, we describe a virtual instrument (an internet-based initiative) whereby users from all laboratories can instantly and quantitatively compare their calibration measurements to those of others - standardising AFM force measurements - and simultaneously enabling non-invasive calibration of AFM cantilevers of any geometry. This global calibration initiative requires no additional instrumentation or data processing on the part of the user. It utilises a single website where users upload currently available data. A proof-of-principle demonstration of this initiative is presented using measured data from five independent laboratories across three countries, which also allows for an assessment of current calibration., Comment: 34 pages, 14 figures

We continue the investigation of how to use the divergence-free condition to resolve the azimuthal ambiguity present in vector magnetogram data. In previous articles, by Crouch, Barnes, and Leka (Solar Physics, 260, 271, 2009) and Crouch (Solar Physics, 282, 107, 2013), all methods used an expression for the divergence of the magnetic field that involves differentiation of quantities that depend on the choice of azimuthal angle. As a result, all heights used to approximate line-of-sight derivatives should generally be disambiguated simultaneously. In this article, we investigate a set of methods that use an expression for the divergence that involves differentiation of quantities that do not depend on the choice of azimuthal angle. This results in an expression for the divergence that can be used to disambiguate each height independently. We test two methods using synthetic and find that the two-step, hybrid method, adapted to disambiguate each height independently, generally produces reasonable results. Moreover, the time required to compute solutions is substantially decreased in comparison to the corresponding method that disambiguates all relevant heights simultaneously., Comment: Accepted for publication in Solar Physics. arXiv admin note: text overlap with arXiv:1210.3351

Motivated by the idea that a subset of HVCs trace dark matter substructure in the Local Group, we search for signs of star formation in the Smith Cloud, a nearby ~2x10^6 Msun HVC currently falling into the Milky Way. Using GALEX NUV and WISE/2MASS NIR photometry, we apply a series of color and apparent magnitude cuts to isolate candidate O and B stars that are plausibly associated with the Smith Cloud. We find an excess of stars along the line of sight to the cloud, but not at a statistically significant level relative to a control region. The number of stars found in projection on the cloud after removing an estimate of the contamination by the Milky Way implies an average star formation rate surface density of 10^(-4.8 +/- 0.3) Msun yr^(-1) kpc^(-2), assuming the cloud has been forming stars at a constant rate since its first passage through the Milky Way ~70 Myr ago. This value is consistent with the star formation rate expected based on the average gas density of the cloud. We also discuss how the newly discovered star forming galaxy Leo P has very similar properties to the Smith Cloud, but its young stellar population would not have been detected at a statistically significant level using our method. Thus, we cannot yet rule out the idea that the Smith Cloud is really a dwarf galaxy., Comment: 9 pages, 7 figures, accepted for publication in MNRAS

We investigate how the azimuthal ambiguity in solar vector magnetogram data can be resolved by using the divergence-free property of magnetic fields. In a previous article, by Crouch, Barnes, and Leka (Solar Phys. 260, 271, 2009), error-free synthetic data were used to test several methods that each make a different assumption about how the divergence-free property can be used to resolve the ambiguity. In this paper this testing is continued with an examination of the effects of Poisson photon noise and limited instrumental spatial resolution. We find that all currently available methods based on the divergence-free property can produce undesirable results when photon noise or unresolved structure are present in the data. We perform a series of experiments aimed at improving the performance of the global minimisation method, which is the most promising of the methods. We present a two-step approach that produces reasonable results in tests using synthetic data. The first step of this approach involves the global minimisation of a combination of the absolute value of the approximation for the divergence and a smoothness constraint, which is designed to minimise the difference between the magnetic field in neighbouring pixels. In the second step, pixels with measurements known to be strongly affected by photon noise are revisited with a smoothing algorithm that also seeks to minimise the difference between the magnetic field in neighbouring pixels., Comment: Accepted for publication in Solar Physics

We investigate least-squares fitting methods for estimating the winding rate of field lines about the axis of twisted magnetic-flux tubes. These methods estimate the winding rate by finding the values for a set of parameters that correspond to the minimum of the discrepancy between magnetic-field measurements and predictions from a twisted flux-tube model. For the flux-tube model used in the fitting, we assume that the magnetic field is static, axisymmetric, and does not vary in the vertical direction. Using error-free, synthetic vector magnetic-field data constructed with models for twisted magnetic-flux tubes, we test the efficacy of fitting methods at recovering the true winding rate. Furthermore, we demonstrate how assumptions built into the flux-tube models used for the fitting influence the accuracy of the winding-rate estimates. We identify the radial variation of the winding rate within the flux tube as one assumption that can have a significant impact on the winding-rate estimates. We show that the errors caused by making a fixed, incorrect assumption about the radial variation of the winding rate can be largely avoided by fitting directly for the radial variation of the winding rate. Other assumptions that we investigate include the lack of variation of the field in the azimuthal and vertical directions in the flux tube model used for the fitting, and the inclination, curvature, and location of the flux-tube axis. When the observed field deviates substantially from the flux-tube model used for the fitting, we find that the winding-rate estimates can be unreliable. We conclude that the magnetic-flux tube models used in this investigation are probably too simple to yield reliable estimates for the winding rate of the field lines in solar magnetic structures in general, unless additional information is available to justify the choice of flux-tube model used for the fitting., Comment: Accepted for publication in Solar Physics

In 2015, the U.S. Department of Agriculture, Forest Service, Forest Inventory and Analysis program collected forest and tree measurements from 37 plots among three forest communities on the islands of Rota, Saipan, and Tinian in the Commonwealth of the Northern Mariana Islands (CNMI). A total of 36 tree species and 132 dominant vascular plant species were recorded, including 28 invasive species. Invasive plant species covered most of the forest area, and 9 of the top 20 most dominant nontree plant species were invasive. The small tree Leucaena leucocephala (tångantångan), comprising by far the largest invasive component in CNMI, made up a substantial percentage of damaged trees and was the only tree species removed by people between inventories (2004-2015). Tree damages from coconut rhinoceros beetles and forest disturbance from wild pigs were not observed. Rota had the least disturbed forests among inventoried islands, with the most native forest--about two-thirds of the total forest area was undisturbed. About 60 percent of the forest area on Saipan and 100 percent of the forest area on Tinian were disturbed. Tree disease was the most prevalent disturbance and damage type in 2015. Vegetation suppression due to vines occurred in about one-third of the total forest area. Disturbance from livestock affected about 10 percent of the total forest area (mostly on Tinian). This was roughly the same situation as in the 2004 inventory. In both inventories, tree stem density was about 1,400 stems per acre, and forests were dominated by small trees less than 3 inches in diameter at breast height (DBH). About 11 percent of these trees grew into the 3.0-4.9-inch DBH size class between inventories, and although the mean DBH, tree height, and stem density did not change significantly between 2004 and 2015 in CNMI forests, there was a significant increase in mean basal area per acre. [ABSTRACT FROM AUTHOR]

We investigate how the divergence-free property of magnetic fields can be exploited to resolve the azimuthal ambiguity present in solar vector magnetogram data, by using line-of-sight and horizontal heliographic derivative information as approximated from discrete measurements. Using synthetic data we test several methods that each make different assumptions about how the divergence-free property can be used to resolve the ambiguity. We find that the most robust algorithm involves the minimisation of the absolute value of the divergence summed over the entire field of view. Away from disk centre this method requires the sign and magnitude of the line-of-sight derivatives of all three components of the magnetic field vector., Comment: Solar Physics, in press, 20 pages, 11 figures

In 2014, the U.S. Department of Agriculture Forest Service Forest Inventory and Analysis program collected forest and tree measurements from 56 forest plots among three forest communities (lowland forest, mangrove, and strand forest) in the Republic of Palau, across Babeldaob, Koror, Peleliu, Angaur, and the Rock Islands. A total of 125 tree species and 196 dominant vascular plants were recorded, most in lowland tropical rainforest. Strand forest had the lowest stem density and highest basal area and volume per acre among forest communities. The Rock Islands had the highest basal area, volume per acre, and percentage of trees >10 inches diameter at breast height, but also the highest stem density among island groups (Babeldaob, Peleliu/Angaur, or the Rock Islands). Palau had a high percentage of forest canopy cover in 2014, with some missing canopy cover associated with wind or fire disturbance. Little evidence of damages from feral pigs or tree cutting were recorded, and no specific human disturbance was observed except for fire. About 40 percent of observed Cocos nucifera L. (lius) trees had Oryctes rhinoceros beetle damage. Less than 1 percent of total forest area was covered with nonnative invasive plants, and the mean percentage of cover of the native/invasive vine Merremia peltata (L.) Merr. (kebeas) decreased by 17 percent compared to 2003. Between 2003 and 2014, the average height of all trees in Palau increased by 2 feet, and the forest grew about 100,000 tons of tree biomass per year (50,000 tons of carbon). The estimates for mean diameter and stem density per acre did not change significantly, but mean basal area per acre significantly increased between inventories. Disturbed forest area increased from 1 to 25 percent, and tree damage increased by 10 percent. [ABSTRACT FROM AUTHOR]

We present a study analyzing relativistic and ultra relativistic electron energization and the evolution of pitch angle distributions using data from the Van Allen Probes. We study the connection between energization and isotropization to determine if there18is a coherence across storms and across energies. Pitch angle distributions are fit with a J(sub 0) sin(sup n)θ function, and the variable ’n’ is characterized as the pitch angle index and tracked over time. Our results show that, consistently across all storms with ultra relativistic electron energization, electron distributions are most anisotropic within around a day of Dst(sub min) and become more isotropic in the following week. Also, each consecutively higher energy channel is associated with higher anisotropy after storm main phase. Changes in the pitch angle index are reflected in each energy channel; when 1.8 MeV electron pitch angle distributions increase (or decrease) in pitch angle index, so do the other energy channels. We show that the peak anisotropies differ between CME- and CIR- driven storms and measure the relaxation rate as the anisotropy falls after the storm. The isotropization rate in pitch angle index for CME-driven storms is -0.15±0.02 day(sup −1) at 1.8 MeV, -0.30±0.01 day(sup −1) at 3.4 MeV, and -0.39±0.02 day(sup −1) at 5.2 MeV. For CIR-driven storms, the isotropization rates are -0.10±0.01 day(sup −1) for 1.8 MeV, -0.13±0.02 day(sup −1) for 3.4 MeV, and -0.11±0.0231 day(sup −1) for 5.2 MeV. This study shows that there is a global coherence across energies and that storm type may play a role in the evolution of electron pitch angle distributions. Plain Language Summary Using Van Allen Probes data, we measure pitch angle distributions of relativistic and ultra relativistic electrons. Anisotropic pitch angle distributions are sharply peaked around 90 degrees. More evenly distributed pitch angles are isotropic. Our results show that, consistently across all storms with ultra relativistic electron enhancements, electrons are most anistropic within around a day of storm onset and slowly isotropize in the following week. In addition, each consecutively higher energy channel is also associated with higher anisotropy after the main phase of geomagnetic storms, a characteristic which holds through the storm and recovery. Changes in the pitch angle index are reflected in each energy channel; when 1.8 MeV electrons increase (or decrease) in pitch angle index, so do all the other energy channels. In a superposed epoch study, we show that the peak anisotropies differ between different storm drivers (namely, coronal mass ejections and corotating interaction regions) and measure the isotropization rate as the anisotropy falls after the storm. This study shows that there is a global coherence across energies and that storm type may play a role in the evolution of electron pitch angle distributions.

Terrorist acts and the fear of terrorism have become a part of everyday life in the early 21st century. Among the threats most feared is bioterrorism, including the intentional release of smallpox. With the invasion of Iraq and toppling of the Saddam Hussein regime, acute bioterrorism fears have abated; however, an ongoing threat remains. This article addresses the need for knowledge and rational policies in dealing with potential bioterrorism attacks. It presents information on four of the most likely bioterrorism agents: smallpox, anthrax, botulism, and plague. It illustrates the importance of accurate knowledge and rational decision making in addressing the threat of terrorism through the intentional release of biological weapons such as smallpox. Finally, it provides information essential for social workers to make informed practice decisions, to educate clients and the public, and to advocate for sound public policy.

Dayside interplanetary (IP) shock-induced injections are known to be a source of highly relativistic electrons in Earth's outer radiation belt, and are possibly the only source of greater than 1 megaelectronvolt electrons in the inner belt. The associated electron energization process is well understood and modeled. Recently, relativistic electron depletion echoes have also been associated with IP shocks, but the processes driving the depletions are less well understood. In this study, we investigate in detail two shock induced greater than 1 megaelectronvolt electron depletion events observed by the Van Allen Probes, March 17, 2015 and May 24, 2013, and draw similarities to night-side substorm related enhancements and depletions. Both events exhibit shock induced enhancements on one of the Van Allen Probes and depletions on the other in greater than 1 megaelectronvolt channels, such observations have not previously been reported. The depletion of greater than 1 megaelectronvolt electrons during the March 17, 2015 event is associated with enhancements in 10 second - 100 second kiloelectronvolt electrons on the same spacecraft. The depletion is consistent with the effects of a lack of seed electrons at larger radial distances combined with inward motion due to asymmetric compression by the shock impact. The immediate enhancements and depletions of 75 kiloelectronvolt - 2.6 greater than 1 megaelectronvolt electrons are explained by the local phase space density radial profile. Observations of electron flux dynamics during the May 24, 2013 event can also be explained by a lack of a seed population at larger radial distances, supported by butterfly distributions observed during the event. The electron's inward radial motion can be attributed to the inward propagating impulse also associated with the greater than 1 megaelectronvolt electron enhancements observed on the complementary probe, rather than global asymmetric compression. This causal mechanism has parallels to substorm related depletions. Alternatively, evidence is provided to attribute the sudden depletions to losses due to a sudden but brief inward motion of the magnetopause.

Long-term forest monitoring is vital to understand how Hawaiian forests change over time and to manage and conserve natural resources. Forest inventories are assessed about every 10 years in Hawai'i by the U.S. Department of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) program, in collaboration with state and federal partners. This report summarizes key findings from 246 forested plots in Hawai'i, inventoried from 2010 to 2015. Estimates were provided for forest area, tree species composition, size distribution, volume, biomass, carbon, understory vegetation, damage to trees, damaging agents, and invasive plant species across all management or owner groups (federal, state and county, and private). Forested FIA plots were located on five of the eight major Hawaiian Islands: Hawai'i, Maui, Lāna'i, O'ahu, and Kaua'i. An estimated 1.5 million ac of forested lands were present statewide, containing many high-value resources, such as clean water, wood products, and carbon sequestration, and delivering a range of cultural ecosystem services. Hawai'i's forest inventory consisted of an estimated 1.8 billion live trees and 112 distinct tree species, including species that were native (indigenous), introduced (either by early Polynesians or more recently via European and Asian contact with Hawai'i), and invasive (those that cause economic, environmental, or ecological harm). Montane rainforests were the most common forest community type, accounting for 30 percent of Hawai'i's forested lands. 'Ōhi'a lehua (Metrosideros polymorpha Gaudich.), an endemic, keystone tree species, was the most common and dominant tree species =5 inches diameter at breast height (d.b.h.) within Hawai'i's forests, followed by hāpu'u 'i'i (Cibotium menziesii Hook.), hāpu'u pulu (Cibotium glaucum (Sm.) Hook. & Arn.), and koa (Acacia koa A. Gray). Strawberry guava (Psidium cattleianum Sabine) was the most abundant tree species =1 inch d.b.h., followed by 'ōhi'a lehua, invasive haole koa (Leucaena leucocephala (Lam.) de Wit), and Christmas berry (Schinus terebinthifolius Raddi). Strawberry guava is invasive and degrades Hawai'i's native forests, adversely affecting ecosystem composition, structure, function, and ecosystem services. Hawai'i's live trees represented 51 million U.S. tons of dry mass (46.3 Tg) carbon. A total of 47 percent of Hawai'i's forests were located on reserved land, primarily ceded lands managed by Hawai'i's state and county governments. This report also serves as a baseline for assessing the extent and health of 'ōhi'a prior to the manifestation of rapid 'ōhi'a death, a disease that began causing widespread mortality of 'ōhi'a lehua trees in 2014. This is the first FIA report for Hawai'i using the nationally standardized plot design developed by FIA, and it provides the baseline for future forest assessments and estimates of change in forest composition, structure, and health. Detailed tables and graphical highlights are included to inform resource managers, policymakers, and the public about the status and trends of their local forest ecosystems and resources. [ABSTRACT FROM AUTHOR]

Launch vehicle ascent is a time of high risk for an onboard crew. There is a large fraction of possible failures for which time is of the essence and a successful abort is possible if the detection and action happens quickly enough. This paper focuses on abort determination based on data already available from the Guidance, Navigation, and Control system. This work is the result of failure analysis efforts performed during the Ares I launch vehicle development program. The two primary areas of focus are the derivation of abort triggers to ensure that abort occurs as quickly as possible when needed, but that false aborts are avoided, and evaluation of success in aborting off the failing launch vehicle.

A surrogate model methodology is described for predicting in real time the residual strength of flight structures with discrete-source damage. Starting with design of experiment, an artificial neural network is developed that takes as input discrete-source damage parameters and outputs a prediction of the structural residual strength. Target residual strength values used to train the artificial neural network are derived from 3D finite element-based fracture simulations. A residual strength test of a metallic, integrally-stiffened panel is simulated to show that crack growth and residual strength are determined more accurately in discrete-source damage cases by using an elastic-plastic fracture framework rather than a linear-elastic fracture mechanics-based method. Improving accuracy of the residual strength training data would, in turn, improve accuracy of the surrogate model. When combined, the surrogate model methodology and high-fidelity fracture simulation framework provide useful tools for adaptive flight technology.

A simplified ascent trajectory optimization procedure has been developed with application to NASA's proposed Ares I launch vehicle. In the interest of minimizing bending loads and ensuring safe separation of the first-stage solid rocket motor, the vehicle is con- strained to follow a gravity-turn trajectory. This reduces the design space to just two free parameters, the pitch rate after a short vertical rise phase to clear the launch pad, and initial launch azimuth. The pitch rate primarily controls the in-plane parameters (altitude, speed, flight path angle) of the trajectory whereas the launch azimuth primarily controls the out-of-plane portion (velocity heading.) Thus, the optimization can be mechanized as two one-dimensional searches that converge quickly and reliably. The method is compared with POST-optimized trajectories to verify its optimality.