Teacher-stress and present day grading practices

Includes bibliographical references

Introduction: Archaeological and Forensic Investigations of an Abolitionist Church in New York City

While excavating the foundations for a planned condominium hotel complex in Manhattan, construction crews discovered human remains. The construction staff subsequently ceased excavation and notified the New York City Police Department and the Medical Examiner’s office. Project officials also notified the New York City Department of Buildings and the New York City Landmarks Preservation Commission who requested all excavation be stopped in the vicinity of the remains. Ultimately, the Department of Buildings, the construction permitting agency, determined that all further construction activities be suspended pending the receipt and approval of an integrated work plan for the recovery, documentation and analysis of any human remains. This volume presents the results of the historical background research, archaeological investigation and forensic analysis

Experiments with and Implementation of a Context Sensitive Text Summarizer

Automatic text summarization is the ability to obtain key ideas from a text passage using as few words as possible. With the increase in data on the web, manual summarization of web pages has become unfeasible, and the need for automatic text summarization has become ever greater. This project explored and implemented various parts of the automatic text summarization process for an open source search engine, Yioop. These parts included stemming, text segmentation, term frequency weighting, automatic sentence compression, and content management system detection. In addition, experiments were conducted on different pre-existing Yioop summarizers. These results served as a baseline for comparison with results obtained from two new ways to generate summaries which we implemented: A graph based approach and an average sentence approach. Summaries were evaluated using Recall-Oriented Understudy for Gisting Evaluation (ROUGE). Analyzing the ROUGE results of each summarizer showed that the new summarizers did not produce better summaries than Yioop’s pre-existing summarizers. During the course of conducting these experiments, it was noted that the location of useful information on a web page could often be obtained if one could determine the content management system that created the web page. An extensible detector for the content management system was written for the Yioop search engine. ROUGE results using this system were recomputed for the various summarizers. Using the content management system detector resulted in a ten to twenty percent increase in ROUGE scores across various page experiments

Compliance: Data Management Plans and Public Access to Data

Three years ago, the Office of Science and Technology Policy released the memo “Increasing Public Access to the Results of Federally Funded Research.” So far, 16 agencies have released plans. These new requirements relate to information access so librarians are well placed to help researchers and grants administrators comply. Many librarians have previous experience with NIH Public Access Policy and/or NSF data management plan requirements, so the transition to the new mandates should be easy. This breakout session will help you focus your efforts on the most important aspects of public access and data management plans when helping researchers with compliance. Margaret Henderson is Director of Research Data Services and Hillary Miller is Scholarly Communications Outreach Librarian, Virginia Commonwealth University Libraries

Song sparrows (Melospiza melodia; Emberizidae) reliably broadcast information about perceived threats using alarm calls

Expanding our understanding of signal complexity in animals could start with thevery smallest songbirds. Black-capped Chickadees (Poecile atricapillus) can encodevery specific details about a threat in their acoustically simple alarm calls. Can othersmall songbird species, such as the Song sparrow (Melospiza melodia), encode thatsame level of detail in their even simpler alarms? Furthermore, is it possible for them tointerpret those details, and are those details reliable? I measured the response of Songsparrows to the suggestion of a threat (two recordings of Song sparrow alarms, one inwhich the call elements were played much faster than a normal call and one in whichthey were played much slower) then, separately, to the threat itself (a taxadermic mountof an Eastern screech owl, Megascops asio), and then to a non-threating control (aNorthern bobwhite, Colinus virginianus). The Song sparrows consistently approachedthe speaker more closely when they heard a faster alarm call and also produced afaster alarm call in response to the more threatening screech owl mount. This suggeststhat there is specific data encoded in the alarms and that they will produce a differentalarm according to the perceived threat level of what they are encountering