Series:

Brett Graham

Abstract

This paper explains how recent advances in NLP technology can be harnessed to search for allusions and influences. The algorithms that have been used in several recent projects in the Digital Humanities are briefly analyzed with the aim of determining how effective these algorithms are in detecting the variety of reference forms that were used in ancient literature. Using the lessons learned from this analysis, a generic NLP algorithm is presented, including a set of syntax rules for textual references. The algorithm is designed to be generic so that it can be used to detect any type of textual reference in any type of text (or even an oral allusion to an oral speech). Finally, the benefits of this approach are highlighted using the results from testing the algorithm on the Pastoral Epistles.

Adrienne R. McLean, Sherry N.N. Du, Jasmine A. Choi, Brett M. Culbert, Erin S. McCallum, Graham R. Scott and Sigal Balshine

Abstract

Wastewater from municipal, agricultural and industrial sources is a pervasive contaminant of aquatic environments worldwide. Most studies that have investigated the negative impacts of wastewater on organisms have taken place in a laboratory. Here, we tested whether fish behaviour is altered by exposure to environmentally relevant concentrations of wastewater effluent in the field. We caged bluegill sunfish (Lepomis macrochirus) for 28 days at two sites downstream (adjacent to and 870 m) from a wastewater treatment plant and at a reference site without wastewater inputs. We found that exposed fish had a dampened response to simulated predation compared to unexposed fish, suggesting that fish may be at greater risk of predation after exposure to wastewater effluent. Fish held at the different sites did not differ in activity and exploration. Our results suggest that predator avoidance may be impaired in fish exposed to wastewater effluent, which could have detrimental implications for aquatic communities.