Rene\u27s Husband; The Shawl

Frederick Feirstein, a New Yorker, most recently published Manhattan Carnival: A Dramatic Monologue. The Shawl is from a new manuscript, Stubborn Spring; Renee\u27s Husband, from a book-length poem in progress, The Psychiatrist at the Cocktail Party

Development of a Groundwater Flow Model for the Colorado River Delta, Mexico

The Colorado River Delta (CRD) is a large sedimentary complex located in a structurally controlled basin in an active tectonic region. The CRD lies across the U.S. Mexico international boundary and is traversed by the Colorado River on it's way to the Gulf of California. Multidisciplinary research addressing the impact of the hydrologic change in the CRD has been increasing since the 1980' s. To help expand the base of this know ledge, a groundwater model for the CRD within Mexico was developed. A conceptual model was constructed and transformed within the Department of Defense Groundwater Modeling Software (GMS) into a numerical model using the MODFLOW code made available by the U.S. Geological Survey. Model results indicates that large scale flood events on the Colorado River act as a recharge to the aquifer and show that the relationship between groundwater withdrawals and capture are evident on an seasonal scale.Digitized from a paper copy provided by the Department of Hydrology & Atmospheric Sciences

Simulation of groundwater conditions in the Colorado River Delta, Mexico

The Colorado River Delta (CRD) is a large sedimentary complex within a tectonically active structurally controlled basin. The CRD lies across the U.S.-Mexico international boundary and is traversed by the Colorado River on is way to the Gulf of California. Multidisciplinary research addressing the impact of the hydrologic change in the CRD has been increasing since the 1980's. To help expand the base of this knowledge, a groundwater model for the CRD within Mexico was developed. A conceptual model was constructed and transformed within the Department of Defense Groundwater Modeling Software (GMS) into a numerical model using the MODFLOW 2005 code made available by the U.S. Geological Survey. Model results indicates that large scale flood events on the Colorado River act as a recharge to the aquifer and show that the relationship between groundwater withdrawals and capture are evident on an seasonal scale. The model will form the parent basis for further Delta studies using the Local Grid Refinement (LRG), a methodology inherent to MODFLOW 2005.Support for this work was provided by the David and Lucile Packard Foundation and the Thinker Foundation. We are also grateful to the National Water Commission office in Mexicali Baja California, in particular Ing. Francisco Tellez and Ing. Julio Navarro, for data provided for this work. Dr. Jorge Ramirez and Ing. Jose Trejo from Autonomous University of Baja California also provided insights and recommendations to build this model. This work was also supported by the United States Agency for International Development (USAID) funded Training, Exchanges, Internships, and Scholarships (TIES) partnership program "Partnership for Improved Management of Watershed Resources in the Lower Colorado River." Research and development for this model was also supported in part by the National Science Foundation Science and Technology Center for Sustainability of Semi-Arid Hydrology and Riparian Areas (SAHRA). We are grateful to the National Water Commission (CONAGUA) in Mexico - office in Mexicali Baja California, in particular Ing. Francisco Tellez and Ing. Julio Navarro, for data and input provided for this work. Dr. Jorge Ramírez- Hernandez and Ing. José Trejo Alvarado from Autonomous University of Baja California also provided insights and recommendations to build this model.This title from the Hydrology & Water Resources Technical Reports collection is made available by the Department of Hydrology & Atmospheric Sciences and the University Libraries, University of Arizona. If you have questions about titles in this collection, please contact [email protected]

Reinforcement learning of potential fields to achieve limit-cycle walking

Reinforcement learning is a powerful tool to derive controllers for systems where no models are available. Particularly policy search algorithms are suitable for complex systems, to keep learning time manageable and account for continuous state and action spaces. However, these algorithms demand more insight into the system to choose a suitable controller parameterization. This paper investigates a type of policy parameterization for impedance control that allows energy input to be implicitly bounded: Potential fields. In this work, a methodology for generating a potential field-constrained impedance controller via approximation of example trajectories, and subsequently improving the control policy using Reinforcement Learning, is presented. The potential field-const rained approximation is used as a policy parameterization for policy search reinforcement learning and is compared to its unconstrained counterpart. Simulations on a simple biped walking model show the learned controllers are able to surpass the potential field of gravity by generating a stable limit-cycle gait on flat ground for both parameterizations. The potential field-constrained controller provides safety with a known energy bound while performing equally well as the unconstrained policy.</p

Reinforcement learning of potential fields to achieve limit-cycle walking

Reinforcement learning is a powerful tool to derive controllers for systems where no models are available. Particularly policy search algorithms are suitable for complex systems, to keep learning time manageable and account for continuous state and action spaces. However, these algorithms demand more insight into the system to choose a suitable controller parameterization. This paper investigates a type of policy parameterization for impedance control that allows energy input to be implicitly bounded: Potential fields. In this work, a methodology for generating a potential field-constrained impedance controller via approximation of example trajectories, and subsequently improving the control policy using Reinforcement Learning, is presented. The potential field-const rained approximation is used as a policy parameterization for policy search reinforcement learning and is compared to its unconstrained counterpart. Simulations on a simple biped walking model show the learned controllers are able to surpass the potential field of gravity by generating a stable limit-cycle gait on flat ground for both parameterizations. The potential field-constrained controller provides safety with a known energy bound while performing equally well as the unconstrained policy.Biomechatronics & Human-Machine ControlOLD Intelligent Control & RoboticsBiorobotic

Effects of punishing elements of a simple instrumental-consummatory response chain

Rats were trained to press a lever, with every response reinforced with water. After responding was established, nine rats were administered a brief shock after each lever press, and nine others were shocked after drinking. The two procedures resulted in similar suppression of responding, and examination of the latency data when responding was partially suppressed indicated that under both conditions response suppression was due primarily to an increase in the latency of the instrumental response, rather than to pausing between the instrumental and consummatory responses. Thus, punishment following either the instrumental or consummatory component of the simple response sequence reduced the number of sequences initiated, rather than selectively suppressing the punished behavior