Gamma-ray Bursts, Classified Physically

From Galactic binary sources, to extragalactic magnetized neutron stars, to long-duration GRBs without associated supernovae, the types of sources we now believe capable of producing bursts of gamma-rays continues to grow apace. With this emergent diversity comes the recognition that the traditional (and newly formulated) high-energy observables used for identifying sub-classes does not provide an adequate one-to-one mapping to progenitors. The popular classification of some > 100 sec duration GRBs as ``short bursts'' is not only an unpalatable retronym and syntactically oxymoronic but highlights the difficultly of using what was once a purely phenomenological classification to encode our understanding of the physics that gives rise to the events. Here we propose a physically based classification scheme designed to coexist with the phenomenological system already in place and argue for its utility and necessity.Comment: 6 pages, 3 figures. Slightly expanded version of solicited paper to be published in the Proceedings of ''Gamma Ray Bursts 2007,'' Santa Fe, New Mexico, November 5-9. Edited by E. E. Fenimore, M. Galassi, D. Palme

Potential for Solar System Science with the ngVLA

Radio wavelength observations of solar system bodies are a powerful method of probing many characteristics of those bodies. From surface and subsurface, to atmospheres (including deep atmospheres of the giant planets), to rings, to the magnetosphere of Jupiter, these observations provide unique information on current state, and sometimes history, of the bodies. The ngVLA will enable the highest sensitivity and resolution observations of this kind, with the potential to revolutionize our understanding of some of these bodies. In this article, we present a review of state-of-the-art radio wavelength observations of a variety of bodies in our solar system, varying in size from ring particles and small near-Earth asteroids to the giant planets. Throughout the review we mention improvements for each body (or class of bodies) to be expected with the ngVLA. A simulation of a Neptune-sized object is presented in Section 6. Section 7 provides a brief summary for each type of object, together with the type of measurements needed for all objects throughout the Solar System

Model AI Assignments 2018

The Model AI Assignments session seeks to gather and disseminate the best assignment designs of the Artificial Intelligence (AI) Education community. Recognizing that assignments form the core of student learning experience, we here present abstracts of seven AI assignments from the 2018 session that are easily adoptable, playfully engaging, and flexible for a variety of instructor needs. Assignment specifications and supporting resources may be found at http://modelai.gettysburg.edu

Parameter Estimation from Time-Series Data with Correlated Errors: A Wavelet-Based Method and its Application to Transit Light Curves

We consider the problem of fitting a parametric model to time-series data that are afflicted by correlated noise. The noise is represented by a sum of two stationary Gaussian processes: one that is uncorrelated in time, and another that has a power spectral density varying as $1/f^\gamma$. We present an accurate and fast [O(N)] algorithm for parameter estimation based on computing the likelihood in a wavelet basis. The method is illustrated and tested using simulated time-series photometry of exoplanetary transits, with particular attention to estimating the midtransit time. We compare our method to two other methods that have been used in the literature, the time-averaging method and the residual-permutation method. For noise processes that obey our assumptions, the algorithm presented here gives more accurate results for midtransit times and truer estimates of their uncertainties.Comment: Accepted in ApJ. Illustrative code may be found at http://www.mit.edu/~carterja/code/ . 17 page

Development and validation of a Clostridium difficile infection risk prediction model

OBJECTIVE: The purpose of this study was to develop and validate a risk prediction model that could identify patients at high risk for Clostridium difficile infection (CDI) before they develop disease. DESIGN: Retrospective cohort. SETTING: Tertiary care medical center. PATIENTS: Patients admitted to the hospital for ≥48 hours from 1-1-2003 through 12-31-2003. METHODS: Data were collected electronically from the hospital’s Medical Informatics database and analyzed with logistic regression to determine variables that best predicted patients’ risk for development of CDI. Model discrimination and calibration were calculated. The model was bootstrapped 500 times to validate the predictive accuracy. A receiver operating characteristic (ROC) curve was calculated to evaluate potential risk cut-offs. RESULTS: 35,350 admissions with 329 CDI cases were included. Variables in the risk prediction model were age, CDI pressure, admissions in previous 60 days, modified Acute Physiology Score, days on high risk antibiotics, low albumin, admission to an ICU, and receipt of laxatives, gastric acid suppressors, or antimotility drugs. The calibration and discrimination of the model were very good to excellent (C index=0.88; Brier score 0.009). CONCLUSIONS: The CDI risk prediction model performed well. Further study is needed to determine if it could be used in a clinical setting to prevent CDI-associated outcomes and reduce costs

Reverse Shock Emission Revealed in Early Photometry in the Candidate Short GRB 180418A

We present observations of the possible short GRB 180418A in $\gamma$-rays, X-rays, and in the optical. Early optical photometry with the TAROT and RATIR instruments show a bright peak ($\approx$ 14.2 AB mag) between $T+28$ and $T+90$ seconds that we interpret as the signature of a reversal shock. Later observations can be modeled by a standard forward shock model and show no evidence of jet break, allowing us to constrain the jet collimation to $\theta_j> 7^\circ$. Using deep late-time optical observations we place an upper limit of $r>24$ AB mag on any underlying host galaxy. The detection of the afterglow in the \textit{Swift} UV filters constrains the GRB redshift to $z<1.3$ and places an upper bound on the $\gamma$-ray isotropic equivalent energy $E_{\rm{\gamma,iso}} < 3 \times 10^{51}$ erg. The properties of this GRB (e.g. duration, hardness ratio, energetic, and environment) lie at the intersection between short and long bursts, and we can not conclusively identify its type. We estimate that the probability that it is drawn from the population of short GRBs is 10\%-30\%.Comment: Accepted por publication in Ap

Electronic surveillance for healthcare-associated central line-associated bloodstream infections outside the intensive care unit

Background.Manual surveillance for central line-associated bloodstream infections (CLABSIs) by infection prevention practitioners is time-consuming and often limited to intensive care units (ICUs). An automated surveillance system using existing databases with patient-level variables and microbiology data was investigated.Methods.Patients with a positive blood culture in 4 non-ICU wards at Barnes-Jewish Hospital between July 1, 2005, and December 31, 2006, were evaluated. CLABSI determination for these patients was made via 2 sources; a manual chart review and an automated review from electronically available data. Agreement between these 2 sources was used to develop the best-fit electronic algorithm that used a set of rules to identify a CLABSI. Sensitivity, specificity, predictive values, and Pearson's correlation were calculated for the various rule sets, using manual chart review as the reference standard.Results.During the study period, 391 positive blood cultures from 331 patients were evaluated. Eighty-five (22%) of these were confirmed to be CLABSI by manual chart review. The best-fit model included presence of a catheter, blood culture positive for known pathogen or blood culture with a common skin contaminant confirmed by a second positive culture and the presence of fever, and no positive cultures with the same organism from another sterile site. The best-performing rule set had an overall sensitivity of 95.2%, specificity of 97.5%, positive predictive value of 90%, and negative predictive value of 99.2% compared with intensive manual surveillance.Conclusions.Although CLABSIs were slightly overpredicted by electronic surveillance compared with manual chart review, the method offers the possibility of performing acceptably good surveillance in areas where resources do not allow for traditional manual surveillance.</jats:sec