Effects of variable eccentricity on the climate of an Earth-like world

The Kepler era of exoplanetary discovery has presented the Astronomical community with a cornucopia of planetary systems very different from the one which we inhabit. It has long been known that Jupiter plays a major role in the orbital parameters of Mars and it's climate, but there is also a long-standing belief that Jupiter would play a similar role for Earth if not for its large moon. Using a three dimensional general circulation model (3-D GCM) with a fully-coupled ocean we simulate what would happen to the climate of an Earth-like world if Mars did not exist, but a Jupiter-like planet was much closer to Earth's orbit. We investigate two scenarios that involve evolution of the Earth-like planet's orbital eccentricity from 0--0.283 over 6500 years, and from 0--0.066 on a time scale of 4500 years. In both cases we discover that they would maintain relatively temperate climates over the time-scales simulated. More Earth-like planets in multi-planet systems will be discovered as we continue to survey the skies and the results herein show that the proximity of large gas giant planets may play an important role in the habitability of these worlds. These are the first such 3-D GCM simulations using a fully-coupled ocean with a planetary orbit that evolves over time due to the presence of a giant planet.Comment: 11 pages, 4 figures, 1 table, submitted to ApJ Letters. Updated figures and discussion at referee reques

Proceedings of the 2011 New York Workshop on Computer, Earth and Space Science

The purpose of the New York Workshop on Computer, Earth and Space Sciences is to bring together the New York area's finest Astronomers, Statisticians, Computer Scientists, Space and Earth Scientists to explore potential synergies between their respective fields. The 2011 edition (CESS2011) was a great success, and we would like to thank all of the presenters and participants for attending. This year was also special as it included authors from the upcoming book titled "Advances in Machine Learning and Data Mining for Astronomy". Over two days, the latest advanced techniques used to analyze the vast amounts of information now available for the understanding of our universe and our planet were presented. These proceedings attempt to provide a small window into what the current state of research is in this vast interdisciplinary field and we'd like to thank the speakers who spent the time to contribute to this volume.Comment: Author lists modified. 82 pages. Workshop Proceedings from CESS 2011 in New York City, Goddard Institute for Space Studie

Long term evolution of planetary systems with a terrestrial planet and a giant planet

We study the long term orbital evolution of a terrestrial planet under the gravitational perturbations of a giant planet. In particular, we are interested in situations where the two planets are in the same plane and are relatively close. We examine both possible configurations: the giant planet orbit being either outside or inside the orbit of the smaller planet. The perturbing potential is expanded to high orders and an analytical solution of the terrestrial planetary orbit is derived. The analytical estimates are then compared against results from the numerical integration of the full equations of motion and we find that the analytical solution works reasonably well. An interesting finding is that the new analytical estimates improve greatly the predictions for the timescales of the orbital evolution of the terrestrial planet compared to an octupole order expansion. Finally, we briefly discuss possible applications of the analytical estimates in astrophysical problems.Comment: Accepted for publication in MNRA

Evaluating automatically acquired f-structures against PropBank

An automatic method for annotating the Penn-II Treebank (Marcus et al., 1994) with high-level Lexical Functional Grammar (Kaplan and Bresnan, 1982; Bresnan, 2001; Dalrymple, 2001) f-structure representations is presented by Burke et al. (2004b). The annotation algorithm is the basis for the automatic acquisition of wide-coverage and robust probabilistic approximations of LFG grammars (Cahill et al., 2004) and for the induction of subcategorisation frames (O’Donovan et al., 2004; O’Donovan et al., 2005). Annotation quality is, therefore, extremely important and to date has been measured against the DCU 105 and the PARC 700 Dependency Bank (King et al., 2003). The annotation algorithm achieves f-scores of 96.73% for complete f-structures and 94.28% for preds-only f-structures against the DCU 105 and 87.07% against the PARC 700 using the feature set of Kaplan et al. (2004). Burke et al. (2004a) provides detailed analysis of these results. This paper presents an evaluation of the annotation algorithm against PropBank (Kingsbury and Palmer, 2002). PropBank identifies the semantic arguments of each predicate in the Penn-II treebank and annotates their semantic roles. As PropBank was developed independently of any grammar formalism it provides a platform for making more meaningful comparisons between parsing technologies than was previously possible. PropBank also allows a much larger scale evaluation than the smaller DCU 105 and PARC 700 gold standards. In order to perform the evaluation, first, we automatically converted the PropBank annotations into a dependency format. Second, we developed conversion software to produce PropBank-style semantic annotations in dependency format from the f-structures automatically acquired by the annotation algorithm from Penn-II. The evaluation was performed using the evaluation software of Crouch et al. (2002) and Riezler et al. (2002). Using the Penn-II Wall Street Journal Section 24 as the development set, currently we achieve an f-score of 76.58% against PropBank for the Section 23 test set

Beef, Mutton, Pork, and a Taste of Turtle: Zooarchaeology and Nineteenth-Century African American Foodways at the Boston-Higginbotham House, Nantucket, Massachusetts

In 1774, nearly ten years before slavery was abolished in Massachusetts, an emancipated African American weaver named Seneca Boston purchased a tract of land in the Newtown section of Nantucket, Massachusetts. It is here that over the next thirty years Seneca Boston and his Wampanoag wife, Thankful Micah, would build a house, now known as the Boston-Higginbotham House, and raise six children. The Boston-Higginbotham House was home to the descendents of Seneca Boston and Thankful Micah for over one hundred years. Throughout the 19th century a vibrant and active African American community was developing in Newtown, and several generations of the Boston family played an integral role in this community\u27s development. This thesis utilizes foodways as an entrée into the lives of these individuals through a zooarchaeological analysis of faunal remains deposited as trash from the meals they consumed. Focusing specifically on the animal components of their diets, this thesis considers the role that the foods they consumed may have played in constructing, reconstructing, and negotiating social and economic statuses and ethnicity and in challenging racist stereotypes and ideologies

Evaluation of an automatic f-structure annotation algorithm against the PARC 700 dependency bank

An automatic method for annotating the Penn-II Treebank (Marcus et al., 1994) with high-level Lexical Functional Grammar (Kaplan and Bresnan, 1982; Bresnan, 2001; Dalrymple, 2001) f-structure representations is described in (Cahill et al., 2002; Cahill et al., 2004a; Cahill et al., 2004b; O’Donovan et al., 2004). The annotation algorithm and the automatically-generated f-structures are the basis for the automatic acquisition of wide-coverage and robust probabilistic approximations of LFG grammars (Cahill et al., 2002; Cahill et al., 2004a) and for the induction of LFG semantic forms (O’Donovan et al., 2004). The quality of the annotation algorithm and the f-structures it generates is, therefore, extremely important. To date, annotation quality has been measured in terms of precision and recall against the DCU 105. The annotation algorithm currently achieves an f-score of 96.57% for complete f-structures and 94.3% for preds-only f-structures. There are a number of problems with evaluating against a gold standard of this size, most notably that of overfitting. There is a risk of assuming that the gold standard is a complete and balanced representation of the linguistic phenomena in a language and basing design decisions on this. It is, therefore, preferable to evaluate against a more extensive, external standard. Although the DCU 105 is publicly available, 1 a larger well-established external standard can provide a more widely-recognised benchmark against which the quality of the f-structure annotation algorithm can be evaluated. For these reasons, we present an evaluation of the f-structure annotation algorithm of (Cahill et al., 2002; Cahill et al., 2004a; Cahill et al., 2004b; O’Donovan et al., 2004) against the PARC 700 Dependency Bank (King et al., 2003). Evaluation against an external gold standard is a non-trivial task as linguistic analyses may differ systematically between the gold standard and the output to be evaluated as regards feature geometry and nomenclature. We present conversion software to automatically account for many (but not all) of the systematic differences. Currently, we achieve an f-score of 87.31% for the f-structures generated from the original Penn-II trees and an f-score of 81.79% for f-structures from parse trees produced by Charniak’s (2000) parser in our pipeline parsing architecture against the PARC 700