Internationalizing the Study Abroad Classroom: An Intensive English Program at the American Graduate School in Paris

The American Graduate School in Paris (AGS) is a not-for-profit institution founded in 1994 to provide U.S. higher education in France to students from around the world pursuing graduate degrees in International Relations, Diplomacy, and Business. Since 2008, AGS has partnered with Arcadia University located in Glenside, Pennsylvania, USA, to provide summer, semester, and academic year undergraduate study abroad programs in these fields. While current study abroad participants are undergraduate students pursuing degrees at U.S. institutions, AGS has recently received permission to internationalize the study abroad classroom by recruiting students from around the world. Because AGS courses are delivered exclusively in English, and maintaining the academic rigor of its study abroad program is of utmost importance to the institution, it has been deemed necessary to not only set appropriate English language requirements for prospective international students in this initial phase of recruitment, but to develop a future Intensive English Program (IEP) that would serve as a precursor or complementary course to enrollment in the undergraduate study abroad program. This Course-Linked Capstone provides a comprehensive plan for designing, delivering, and evaluating an IEP at AGS. Best practices in the fields of International Education, English as a Foreign Language, administration of Intensive English Programs, international student recruitment, and cultural learning have been reviewed and incorporated into the program design. This program seeks to diversify program offerings at AGS, increase accessibility of the current undergraduate study abroad program to a greater number of international participants, and foster a more global study abroad experience in which diverse backgrounds, cultures, and perspectives are represented. Keywords: Intensive English Program, France, study abroad, orientation, cultural learnin

Plasticity of Noddy Parents and Offspring to Sea-Surface Temperature Anomalies

Behavioral and/or developmental plasticity is crucial for resisting the impacts of environmental stressors. We investigated the plasticity of adult foraging behavior and chick development in an offshore foraging seabird, the black noddy (Anous minutus), during two breeding seasons. The first season had anomalously high sea-surface temperatures and ‘low’ prey availability, while the second was a season of below average sea-surface temperatures and ‘normal’ food availability. During the second season, supplementary feeding of chicks was used to manipulate offspring nutritional status in order to mimic conditions of high prey availability. When sea-surface temperatures were hotter than average, provisioning rates were significantly and negatively impacted at the day-to-day scale. Adults fed chicks during this low-food season smaller meals but at the same rate as chicks in the unfed treatment the following season. Supplementary feeding of chicks during the second season also resulted in delivery of smaller meals by adults, but did not influence feeding rate. Chick begging and parental responses to cessation of food supplementation suggested smaller meals fed to artificially supplemented chicks resulted from a decrease in chick demands associated with satiation, rather than adult behavioral responses to chick condition. During periods of low prey abundance, chicks maintained structural growth while sacrificing body condition and were unable to take advantage of periods of high prey abundance by increasing growth rates. These results suggest that this species expresses limited plasticity in provisioning behavior and offspring development. Consequently, responses to future changes in sea-surface temperature and other environmental variation may be limited

Murine startle mutant Nmf11 affects the structural stability of the glycine receptor and increases deactivation

Dysfunctional glycinergic inhibitory transmission underlies the debilitating neurological condition, hyperekplexia, which is characterised by exaggerated startle reflexes, muscle hypertonia and apnoea. Here we investigated the N46K missense mutation in the GlyR α1 subunit gene found in the ethylnitrosourea (ENU) murine mutant, Nmf11, which causes reduced body size, evoked tremor, seizures, muscle stiffness, and morbidity by postnatal day 21. Introducing the N46K mutation into recombinant GlyR α1 homomeric receptors, expressed in HEK cells, reduced the potencies of glycine, β-alanine and taurine by 9-, 6- and 3-fold respectively, and that of the competitive antagonist strychnine by 15-fold. Replacing N46 with hydrophobic, charged or polar residues revealed that the amide moiety of asparagine was crucial for GlyR activation. Co-mutating N61, located on a neighbouring β loop to N46, rescued the wild-type phenotype depending on the amino acid charge. Single-channel recording identified that burst length for the N46K mutant was reduced and fast agonist application revealed faster glycine deactivation times for the N46K mutant compared with the WT receptor. Overall, these data are consistent with N46 ensuring correct alignment of the α1 subunit interface by interaction with juxtaposed residues to preserve the structural integrity of the glycine binding site. This represents a new mechanism by which GlyR dysfunction induces startle disease

Deep learning for robotic exploration

Emerging applications for robotic data collection include ocean monitoring, emergency response and urban search and rescue. At the core of these applications is a robot's ability to make informed decisions on incomplete data. This dissertation addresses this problem by developing novel techniques for modeling and estimating structured environments using deep learning. The proposed methods improve the eciency of robotics systems across a wide array of applications and scenarios. A challenging problem in robotics is to predict future observations based on previously-recorded data. Robots often operate in built environments that tend to contain some underlying structure, such that newly-visited locations may appear broadly similar to previously visited locations but dier in individual details. The proposed technique exploits the inherent structure of the environment to train a convolutional neural network that is leveraged to facilitate robotic search. We start by investigating environments where the full environmental structure is known, and then we extend the work to unknown environments. Experimental results show the proposed framework provides a reliable method for decreasing the area searched to nd a point of interest. We demonstrate the proposed framework increases the search eciency of a mobile robot in a real-world oce environment. To utilize uncertainty in our decision making and account for dynamic environments, we propose a convolutional LSTM network with bootstrapped condence bounds as a method for modeling spatio-temporal data. By providing estimates with condence bounds that are accurate far into the future, multi-step planners can be utilized to improve performance on information gathering missions. This technique is compared to existing environment modeling techniques. We demonstrate that our proposed approach constructs long-horizon estimates with greater accuracy. We also achieve more accurate and more conservative condence bounds. Validation through simulation shows our technique increases path planning performance in environmental information gathering missions. Robots often require a model of their environment to make informed decisions. In unknown environments, the ability to infer the value of a data eld from a limited number of samples is essential to many robotics applications. In this dissertation, we propose a neural network architecture to model these spatially correlated data elds based on a limited number of spatially continuous samples. Additionally, we provide a method based on biased loss functions to suggest future areas of exploration to minimize reconstruction error. We run simulated robotic information gathering trials on both the MNIST hand written digits dataset and a Regional Ocean Modeling System (ROMS) ocean dataset for ocean monitoring. Our method outperforms Gaussian process regression in both environments for modeling the data eld and action selection

30 Days in the life: daily nutrient balancing in a wild chacma baboon

For most animals, the ability to regulate intake of specific nutrients is vital to fitness. Recent studies have demonstrated nutrient regulation in nonhuman primates over periods of one observation day, though studies of humans indicate that such regulation extends to longer time frames. Little is known about longer-term regulation in nonhuman primates, however, due to the challenges of multiple-day focal follows. Here we present the first detailed study of nutrient intake across multiple days in a wild nonhuman primate. We conducted 30 consecutive all day follows on one female chacma baboon ( Papio hamadryas ursinus ) in the Cape Peninsula of South Africa. We documented dietary composition, compared the nutritional contribution of natural and human-derived foods to the diet, and quantified nutrient intake using the geometric framework of nutrition. Our focus on a single subject over consecutive days allowed us to examine daily dietary regulation within an individual over time. While the amounts varied daily, our subject maintained a strikingly consistent balance of protein to non-protein (fat and carbohydrate) energy across the month. Human-derived foods, while contributing a minority of the diet, were higher in fat and lower in fiber than naturally-derived foods. Our results demonstrate nutrient regulation on a daily basis in our subject, and demonstrate that she was able to maintain a diet with a constant proportional protein content despite wide variation in the composition of component foods. From a methodological perspective, the results of this study suggest that nutrient intake is best estimated over at least an entire day, with longer-term regulatory patterns (e.g., during development and reproduction) possibly requiring even longer sampling. From a management and conservation perspective, it is notable that nearly half the subject's daily energy intake derived from exotic foods, including those currently being eradicated from the study area for replacement by indigenous vegetation

Three-tangle for mixtures of generalized GHZ and generalized W states

We give a complete solution for the three-tangle of mixed three-qubit states composed of a generalized GHZ state, a|000>+b|111>, and a generalized W state, c|001>+d|010>+f|100>. Using the methods introduced by Lohmayer et al. we provide explicit expressions for the mixed-state three-tangle and the corresponding optimal decompositions for this more general case. Moreover, as a special case we obtain a general solution for a family of states consisting of a generalized GHZ state and an orthogonal product state

Relaxation rate of the reverse biased asymmetric exclusion process

We compute the exact relaxation rate of the partially asymmetric exclusion process with open boundaries, with boundary rates opposing the preferred direction of flow in the bulk. This reverse bias introduces a length scale in the system, at which we find a crossover between exponential and algebraic relaxation on the coexistence line. Our results follow from a careful analysis of the Bethe ansatz root structure.Comment: 22 pages, 12 figure

Summary of tank information relating salt well pumping to flammable gas safety issues

The Hanford Site has 149 single-shell tanks (SSTs) containing radioactive wastes that are complex mixes of radioactive and chemical products. Active use of these SSTs was phased out completely by November 1980, and the first step toward final disposal of the waste in the SSTs is interim stabilization, which involves removing essentially all of the drainable liquid from the tank. Stabilization can be achieved administratively, by jet pumping to remove drainable interstitial liquid, or by supernatant pumping. To date, 116 tanks have been declared interim stabilized; 44 SSTs have had drainable liquid removed by salt well jet pumping. Of the 149 SSTs, 19 are on the Flammable Gas Watch List (FGWL) because the waste in these tanks is known or suspected, in all but one case, to generate and retain mixtures of flammable gases, including; hydrogen, nitrous oxide, and ammonia. Salt well pumping to remove the drainable interstitial liquid from these SSTs is expected to cause the release of much of the retained gas, posing a number of safety concerns. The scope of this work is to collect and summarize information, primarily tank data and observations, that relate salt well pumping to flammable gas safety issues. While the waste within FGWL SSTs is suspected offering flammable gases, the effect of salt well pumping on the waste behavior is not well understood. This study is being conducted for the Westinghouse Hanford Company as part of the Flammable Gas Project at the Pacific Northwest National Laboratory (PNNL). Understanding the historical tank behavior during and following salt well pumping will help to resolve the associated safety issues