Probing the Inner Regions of Protoplanetary Disks with CO Absorption Line Spectroscopy

Carbon monoxide (CO) is the most commonly used tracer of molecular gas in the inner regions of protoplanetary disks. CO can be used to constrain the excitation and structure of the circumstellar environment. Absorption line spectroscopy provides an accurate assessment of a single line-of-sight through the protoplanetary disk system, giving more straightforward estimates of column densities and temperatures than CO and molecular hydrogen emission line studies. We analyze new observations of ultraviolet CO absorption from the Hubble Space Telescope along the sightlines to six classical T Tauri stars. Gas velocities consistent with the stellar velocities, combined with the moderate-to-high disk inclinations, argue against the absorbing CO gas originating in a fast-moving disk wind. We conclude that the far-ultraviolet observations provide a direct measure of the disk atmosphere or possibly a slow disk wind. The CO absorption lines are reproduced by model spectra with column densities in the range N(^{12}CO) ~ 10^{16} - 10^{18} cm^{-2} and N(^{13}CO) ~ 10^{15} - 10^{17} cm^{-2}, rotational temperatures T_{rot}(CO) ~ 300 - 700 K, and Doppler b-values, b ~ 0.5 - 1.5 km s^{-1}. We use these results to constrain the line-of-sight density of the warm molecular gas (n_{CO} ~ 70 - 4000 cm^{-3}) and put these observations in context with protoplanetary disk models.Comment: 12 pages, 14 figures, ApJ - accepte

Stable Frank-Kasper phases of self-assembled, soft matter spheres

Single molecular species can self-assemble into Frank Kasper (FK) phases, finite approximants of dodecagonal quasicrystals, defying intuitive notions that thermodynamic ground states are maximally symmetric. FK phases are speculated to emerge as the minimal-distortional packings of space-filling spherical domains, but a precise quantitation of this distortion and how it affects assembly thermodynamics remains ambiguous. We use two complementary approaches to demonstrate that the principles driving FK lattice formation in diblock copolymers emerge directly from the strong-stretching theory of spherical domains, in which minimal inter-block area competes with minimal stretching of space-filling chains. The relative stability of FK lattices is studied first using a diblock foam model with unconstrained particle volumes and shapes, which correctly predicts not only the equilibrium {\sigma} lattice, but also the unequal volumes of the equilibrium domains. We then provide a molecular interpretation for these results via self-consistent field theory, illuminating how molecular stiffness regulates the coupling between intra-domain chain configurations and the asymmetry of local packing. These findings shed new light on the role of volume exchange on the formation of distinct FK phases in copolymers, and suggest a paradigm for formation of FK phases in soft matter systems in which unequal domain volumes are selected by the thermodynamic competition between distinct measures of shape asymmetry.Comment: 40 pages, 22 figure

Strategic Flexibility and SMEs: The Role of Information Technology for Managing Internal and External Relations

The purpose of the current study was to assess the impact of information technology on strategic flexibility for small- and medium-sized enterprises (SMEs). Results of the study show that under conditions of low environmental dynamism, IT capabilities are associated with greater reactive strategic flexibility. Specifically, IT capabilities enabling the management of internal activities was significant. Under conditions of high environmental dynamism, IT capabilities are associated with greater proactive strategic flexibility. Specifically, IT capabilities enabling the management of competitor information was significant. Managerial as well as future research implications are discussed

Small Business Internet Use and Strategic Flexibility

Research on SME Internet use has focused almost exclusively on factors leading to the adoption of Internet technologies. In this study, we focus on the potentially valuable connection between Internet use and strategic flexibility. Specifically, we propose that Internet use for communications will promote greater strategic flexibility for the small firm, but only in a dynamic environment. The results, based on a sample of 160 small Midwest companies, largely support this hypothesis. Environmental dynamism was found to moderate the relationship between Internet use for communications and strategic flexibility. Use of the Internet for communications was found to be positively and significantly related to strategic flexibility in a dynamic environment. As expected, dynamism did not moderate the relationship between Internet use for transactions and strategic flexibility. These findings hold implications for future research and for managers of small firms attempting to effectively leverage the Internet for competitive advantage

A Summary Of: Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments

Sleep loss and circadian misalignment contribute to a meaningful proportion of operational accidents and incidents. Countermeasures and work scheduling designs aimed at mitigating fatigue are typically evaluated in controlled laboratory environments, but the effectiveness of translating such strategies to operational environments can be challenging to assess. This manuscript summarizes an approach for collecting sleep, circadian, fatigue, and performance data in a complex operational environment. We studied 44 airline pilots over 34 days while they flew a fixed schedule, which included a baseline data collection with 5 days of mid-morning flights, four early flights, four high-workload mid-day flights, and four late flights that landed after midnight. Each work block was separated by 3-4 days of rest. To assess sleep, participants wore a wrist-worn research-validated activity monitor continuously and completed daily sleep diaries. To assess the circadian phase, pilots were asked to collect all urine produced in four or eight hourly bins during the 24 h after each duty block for the assessment of 6-sulfatoxymelatonin (aMT6s), which is a biomarker of the circadian rhythm. To assess subjective fatigue and objective performance, participants were provided with a touchscreen device used to complete the Samn-Perelli Fatigue Scale and Psychomotor Vigilance Task (PVT) during and after each flight, and at wake-time, mid-day, and bedtime. Using these methods, it was found that sleep duration was reduced during early starts and late finishes relative to baseline. Circadian phase shifted according to duty schedule, but there was a wide range in the aMT6s peak between individuals on each schedule. PVT performance was worse on the early, high-workload, and late schedules relative to baseline. Overall, the combination of these methods was practical and effective for assessing the influence of sleep loss and circadian phase on fatigue and performance in a complex operational environment

A Search for Water in the Atmosphere of HAT-P-26b Using LDSS-3C

The characterization of a physically-diverse set of transiting exoplanets is an important and necessary step towards establishing the physical properties linked to the production of obscuring clouds or hazes. It is those planets with identifiable spectroscopic features that can most effectively enhance our understanding of atmospheric chemistry and metallicity. The newly-commissioned LDSS-3C instrument on Magellan provides enhanced sensitivity and suppressed fringing in the red optical, thus advancing the search for the spectroscopic signature of water in exoplanetary atmospheres from the ground. Using data acquired by LDSS-3C and the Spitzer Space Telescope, we search for evidence of water vapor in the transmission spectrum of the Neptune-mass planet HAT-P-26b. Our measured spectrum is best explained by the presence of water vapor, a lack of potassium, and either a high-metallicity, cloud-free atmosphere or a solar-metallicity atmosphere with a cloud deck at ~10 mbar. The emergence of multi-scale-height spectral features in our data suggests that future observations at higher precision could break this degeneracy and reveal the planet's atmospheric chemical abundances. We also update HAT-P-26b's transit ephemeris, t_0 = 2455304.65218(25) BJD_TDB, and orbital period, p = 4.2345023(7) days.Comment: 9 pages, 8 figures, Accepted for publication in Ap

Background Adaptive Faster R-CNN for Semi-Supervised Convolutional Object Detection of Threats in X-Ray Images

Recently, progress has been made in the supervised training of Convolutional Object Detectors (e.g. Faster R-CNN) for threat recognition in carry-on luggage using X-ray images. This is part of the Transportation Security Administration's (TSA's) mission to protect air travelers in the United States. While more training data with threats may reliably improve performance for this class of deep algorithm, it is expensive to stage in realistic contexts. By contrast, data from the real world can be collected quickly with minimal cost. In this paper, we present a semi-supervised approach for threat recognition which we call Background Adaptive Faster R-CNN. This approach is a training method for two-stage object detectors which uses Domain Adaptation methods from the field of deep learning. The data sources described earlier make two "domains": a hand-collected data domain of images with threats, and a real-world domain of images assumed without threats. Two domain discriminators, one for discriminating object proposals and one for image features, are adversarially trained to prevent encoding domain-specific information. Without this penalty a Convolutional Neural Network (CNN) can learn to identify domains based on superficial characteristics, and minimize a supervised loss function without improving its ability to recognize objects. For the hand-collected data, only object proposals and image features from backgrounds are used. The losses for these domain-adaptive discriminators are added to the Faster R-CNN losses of images from both domains. This can reduce threat detection false alarm rates by matching the statistics of extracted features from hand-collected backgrounds to real world data. Performance improvements are demonstrated on two independently-collected datasets of labeled threats