The GIFT of Signature Work

The September 25, 2015 Center for Faculty Enrichment program was a GIFT session (Great Ideas For Teaching) focused on the theme of fostering Signature Work (SW). As defined by the AAC&U, Signature Work represents a culminating production by students that reflects each student\u27s personal interests, builds on a student\u27s unique experiences, integrates multiple components of a student\u27s educational journey, and projects toward each student\u27s personal goals. Presenters will share teaching strategies that can help prepare novice students to produce a future piece of SW or that can help experienced students identify a meaningful SW project and integrate prior learning into the project. Presenters include Anne Earel & Connie Ghinazzi (library support for SW), Mike Egan (service-learning and SW), Stephanie Fuhr (senior inquiry and SW), and Shara Stough (course projects and SW)

Immersive 4D Interactive Visualization of Large-Scale Simulations

In dense clusters a bewildering variety of interactions between stars can be observed, ranging from simple encounters to collisions and other mass-transfer encounters. With faster and special-purpose computers like GRAPE, the amount of data per simulation is now exceeding 1TB. Visualization of such data has now become a complex 4D data-mining problem, combining space and time, and finding interesting events in these large datasets. We have recently starting using the virtual reality simulator, installed in the Hayden Planetarium in the American Museum for Natural History, to tackle some of these problem. This work (http://www.astro.umd.edu/nemo/amnh/) reports on our first ``observations'', modifications needed for our specific experiments, and perhaps field ideas for other fields in science which can benefit from such immersion. We also discuss how our normal analysis programs can be interfaced with this kind of visualization.Comment: 4 pages, 1 figure, ADASS-X conference proceeding

Swift X-Ray Observations of Classical Novae. II. The Super Soft Source sample

The Swift GRB satellite is an excellent facility for studying novae. Its rapid response time and sensitive X-ray detector provides an unparalleled opportunity to investigate the previously poorly sampled evolution of novae in the X-ray regime. This paper presents Swift observations of 52 Galactic/Magellanic Cloud novae. We included the XRT (0.3-10 keV) X-ray instrument count rates and the UVOT (1700-8000 Angstroms) filter photometry. Also included in the analysis are the publicly available pointed observations of 10 additional novae the X-ray archives. This is the largest X-ray sample of Galactic/Magellanic Cloud novae yet assembled and consists of 26 novae with super soft X-ray emission, 19 from Swift observations. The data set shows that the faster novae have an early hard X-ray phase that is usually missing in slower novae. The Super Soft X-ray phase occurs earlier and does not last as long in fast novae compared to slower novae. All the Swift novae with sufficient observations show that novae are highly variable with rapid variability and different periodicities. In the majority of cases, nuclear burning ceases less than 3 years after the outburst begins. Previous relationships, such as the nuclear burning duration vs. t_2 or the expansion velocity of the eject and nuclear burning duration vs. the orbital period, are shown to be poorly correlated with the full sample indicating that additional factors beyond the white dwarf mass and binary separation play important roles in the evolution of a nova outburst. Finally, we confirm two optical phenomena that are correlated with strong, soft X-ray emission which can be used to further increase the efficiency of X-ray campaigns.Comment: Accepted to ApJ Supplements. Full data for Table 2 and Figure 17 available in the electronic edition. New version of the previously posted paper since the earlier version was all set in landscape mod

Equalization of four cardiovascular risk algorithms after systematic recalibration: individual-participant meta-analysis of 86 prospective studies

Aims: There is debate about the optimum algorithm for cardiovascular disease (CVD) risk estimation. We conducted head-to-head comparisons of four algorithms recommended by primary prevention guidelines, before and after ‘recalibration’, a method that adapts risk algorithms to take account of differences in the risk characteristics of the populations being studied. Methods & Results: Using individual-participant data on 360737 participants without CVD at baseline in 86 prospective studies from 22 countries, we compared the Framingham risk score (FRS), Systematic COronary Risk Evaluation (SCORE), pooled cohort equations (PCE), and Reynolds risk score (RRS). We calculated measures of risk discrimination and calibration, and modelled clinical implications of initiating statin therapy in people judged to be at ‘high’ 10 year CVD risk. Original risk algorithms were recalibrated using the risk factor profile and CVD incidence of target populations. The four algorithms had similar risk discrimination. Before recalibration, FRS, SCORE, and PCE overpredicted CVD risk on average by 10%, 52%, and 41%, respectively, whereas RRS under-predicted by 10%. Original versions of algorithms classified 29–39% of individuals aged \u3e_40years as high risk. By contrast, recalibration reduced this proportion to 22–24% for every algorithm. We estimated that to prevent one CVD event, it would be necessary to initiate statin therapy in 44–51 such individuals using original algorithms, in contrast to 37–39 individuals with recalibrated algorithms. Conclusions: Before recalibration, the clinical performance of four widely used CVD risk algorithms varied substantially. By contrast, simple recalibration nearly equalized their performance and improved modelled targeting of preventive action to clinical need

Stellar Exotica in 47 Tucanae

We have used far-ultraviolet spectroscopy and broad-band photometry to identify and study dynamically-formed stellar exotica in the core of 47 Tucanane. Here, we present a subset of our main results, including: (i) the spectroscopic confirmation of three cataclysmic variables; (ii) the discovery of stripped sub-giant core in a binary system with a dark primary; (iii) the discovery of a Helium white dwarf; (iv) the discovery of a blue straggler with a white dwarf companio

Equalization of four cardiovascular risk algorithms after systematic recalibration: individual-participant meta-analysis of 86 prospective studies.

There is debate about the optimum algorithm for cardiovascular disease (CVD) risk estimation. We conducted head-to-head comparisons of four algorithms recommended by primary prevention guidelines, before and after 'recalibration', a method that adapts risk algorithms to take account of differences in the risk characteristics of the populations being studied. Using individual-participant data on 360 737 participants without CVD at baseline in 86 prospective studies from 22 countries, we compared the Framingham risk score (FRS), Systematic COronary Risk Evaluation (SCORE), pooled cohort equations (PCE), and Reynolds risk score (RRS). We calculated measures of risk discrimination and calibration, and modelled clinical implications of initiating statin therapy in people judged to be at 'high' 10 year CVD risk. Original risk algorithms were recalibrated using the risk factor profile and CVD incidence of target populations. The four algorithms had similar risk discrimination. Before recalibration, FRS, SCORE, and PCE over-predicted CVD risk on average by 10%, 52%, and 41%, respectively, whereas RRS under-predicted by 10%. Original versions of algorithms classified 29-39% of individuals aged ≥40 years as high risk. By contrast, recalibration reduced this proportion to 22-24% for every algorithm. We estimated that to prevent one CVD event, it would be necessary to initiate statin therapy in 44-51 such individuals using original algorithms, in contrast to 37-39 individuals with recalibrated algorithms. Before recalibration, the clinical performance of four widely used CVD risk algorithms varied substantially. By contrast, simple recalibration nearly equalized their performance and improved modelled targeting of preventive action to clinical need