The three-dimensional (3D) revolution promised to transform archaeological practice. Of the technologies that contribute to the proliferation of 3D data, photogrammetry facilitates the rapid and inexpensive digitization of complex subjects in both field and lab settings. It finds additional use as a tool for public outreach, where it engages audiences ranging from source communities to artifact collectors. But what has photogrammetry's function been in advancing archaeological analysis? Drawing on our previous work, we review recent applications to understand the role of photogrammetry for contemporary archaeologists. Although photogrammetry is widely used as a visual aid, its analytical potential remains underdeveloped. Considering various scales of inquiry—graduating from objects to landscapes—we address how the technology fits within and expands existing documentation and data visualization routines, while evaluating the opportunity it presents for addressing archaeological questions and problems in innovative ways. We advance an agenda advocating that archaeologists move from proof-of-concept papers toward greater integration of photogrammetry with research.

This white paper identifies knowledge gaps and new challenges in healthcare epidemiology research, assesses the progress made toward addressing research priorities, provides the Society for Healthcare Epidemiology of America (SHEA) Research Committee's recommendations for high-priority research topics, and proposes a road map for making progress toward these goals. It updates the 2010 SHEA Research Committee document, “Charting the Course for the Future of Science in Healthcare Epidemiology: Results of a Survey of the Membership of SHEA,” which called for a national approach to healthcare-associated infections (HAIs) and a prioritized research agenda. This paper highlights recent studies that have advanced our understanding of HAIs, the establishment of the SHEA Research Network as a collaborative infrastructure to address research questions, prevention initiatives at state and national levels, changes in reporting and payment requirements, and new patterns in antimicrobial resistance.

We present the results of eighteen non-continuous nights of time series photometric observations of a 1.25 deg2 field in Cygnus centered on the NASA Kepler Mission field of view. Using the Case Western Burrell Schmidt telescope we gathered a dataset containing light curves of roughly 30,000 stars with 14 < r < 19. We have statistically examined each light curve to test for variability, periodicity, and unusual light curve trends, including exoplanet transits. We present a summary of our photometric project including a characterization of the level and content of stellar variability in this field. We will also discuss our potential exoplanet candidates.

Window functions describe, as a function of orbital period, the probability that an existing planetary transit is detectable in one's data for a given observing strategy. We show the dependence of this probability upon several strategy and astrophysical parameters, such as length of observing run, observing cadence, length of night, and transit duration. The ability to detect a transit is directly related to the intrinsic noise of the observations. In our simulations of the window function, we explicitly address non-correlated (white) noise and correlated (red) noise and discuss how these two different noise components affect window functions in different manners.