Estimates of Stellar Weak Interaction Rates for Nuclei in the Mass Range A=65-80

We estimate lepton capture and emission rates, as well as neutrino energy loss rates, for nuclei in the mass range A=65-80. These rates are calculated on a temperature/density grid appropriate for a wide range of astrophysical applications including simulations of late time stellar evolution and x-ray bursts. The basic inputs in our single particle and empirically inspired model are i) experimentally measured level and weak decay information, ii) estimates of matrix elements for allowed experimentally-unmeasured transitions based on the systematics of experimentally observed allowed transitions, and iii) estimates of the centroids of the GT resonances motivated by shell model calculations in the fp shell as well as by (n,p) and (p,n) experiments. Transitions involving Fermi resonances (isobaric analog states) are also included and dominate the rates for many interesting proton rich nuclei for which an experimentally-determined ground state lifetime is unavailable. To compare our results with more detailed shell model based calculations we also calculate weak rates for nuclei in the mass range A=60-65 for which Langanke and Martinez-Pinedo have provided rates. The typical deviation in the electron capture and B- decay rates for these ~30 nuclei is less than a factor of two or three for a wide range of temperature and density appropriate for pre-supernova stellar evolution. We also discuss some subtleties associated with the partition functions used in calculations of stellar weak rates and show that the proper treatment of the partition functions is essential for estimating high temperature beta decay rates. Partition functions based on un-converged Lanczos calculations can result in estimates of high temperature beta decay rates that are systematically low.Comment: Tables of rates for nuclei in the mass range A=66-110 are available from J. Prue

Interactive Correspondence Analysis in a Dynamic Object-Oriented Environment

A highly interactive, user-friendly object-oriented software package written in LispStat is introduced that performs simple and multiple correspondence analysis, and profile analysis. These three techniques are integrated into a single environment driven by a user-friendly graphical interface that takes advantage of Lisp-Stat's advanced graphical capabilities. Techniques that assess the stability of the solution are also introduced. Some of the features of the package include colored graphics, incremental graph zooming capabilities, manual point separation to determine identities of overlapping points, and stability and fit measures. The features of the package are used to show some interesting trends in a large educational dataset.

Pesticide Use and IPM Adoption: Does IPM Reduce Pesticide Use in the United States?

In 2001, the United States General Accounting Office issued a report entitled “Management Improvements Needed to Further Promote Integrated Pest Management.” This report documents that overall agricultural pesticide usage increased from 1992 to 2000 while the use of the most toxic levels of pesticides have decreased. The USDA suggests that these changes in pesticide use could have been caused by integrated pest management (IPM) adoption. However, the GAO maintains that there is not enough evidence to support this claim. This paper contributes to this debate by estimating the relationship between pesticide use and IPM practices adopted for number of commodities across the nation from 1996 to 2005. The paper exploits an aggregated data set that combines surveys from different crops and different years, but it also examines specific surveys conducted on cotton and corn crops to better control for other factors that could affect pesticide use. The paper applies multiple definitions of IPM and uses different spatial variables to control for environmental effects that affect pesticide use. Although some specific strategies such as GM adoption decreased the amount of active ingredients sprayed on cotton and corn, the results suggest that on average the adoption of IPM strategies lead to slightly increased pesticide spending and pounds of active ingredient sprayed per acre. This result is confirmed in both the analysis on the aggregated data as well as the analysis of the cotton and corn data. The results also suggest that fixed environmental factors explain a significant amount of chemical spending and pesticide use in the United States. The significance of these factors demonstrates the importance of research and programs that aid farmers in making intelligent pesticide use decisions at the local level.Pesticide Use, Integrated Pest Management, Corn Production, Cotton Production, Agricultural and Food Policy, Environmental Economics and Policy,

Harnessing resilience: biased voltage overscaling for probabilistic signal processing

A central component of modern computing is the idea that computation requires determinism. Contrary to this belief, the primary contribution of this work shows that useful computation can be accomplished in an error-prone fashion. Focusing on low-power computing and the increasing push toward energy conservation, the work seeks to sacrifice accuracy in exchange for energy savings. Probabilistic computing forms the basis for this error-prone computation by diverging from the requirement of determinism and allowing for randomness within computing. Implemented as probabilistic CMOS (PCMOS), the approach realizes enormous energy sav- ings in applications that require probability at an algorithmic level. Extending probabilistic computing to applications that are inherently deterministic, the biased voltage overscaling (BIVOS) technique presented here constrains the randomness introduced through PCMOS. Doing so, BIVOS is able to limit the magnitude of any resulting deviations and realizes energy savings with minimal impact to application quality. Implemented for a ripple-carry adder, array multiplier, and finite-impulse-response (FIR) filter; a BIVOS solution substantially reduces energy consumption and does so with im- proved error rates compared to an energy equivalent reduced-precision solution. When applied to H.264 video decoding, a BIVOS solution is able to achieve a 33.9% reduction in energy consumption while maintaining a peak-signal-to-noise ratio of 35.0dB (compared to 14.3dB for a comparable reduced-precision solution). While the work presented here focuses on a specific technology, the technique realized through BIVOS has far broader implications. It is the departure from the conventional mindset that useful computation requires determinism that represents the primary innovation of this work. With applicability to emerging and yet to be discovered technologies, BIVOS has the potential to contribute to computing in a variety of fashions.PhDCommittee Chair: Anderson, David; Committee Member: Conte, Thomas; Committee Member: Ferri, Bonnie; Committee Member: Hasler, Paul; Committee Member: Mooney, Vincen

Sensor Management for Tracking in Sensor Networks

We study the problem of tracking an object moving through a network of wireless sensors. In order to conserve energy, the sensors may be put into a sleep mode with a timer that determines their sleep duration. It is assumed that an asleep sensor cannot be communicated with or woken up, and hence the sleep duration needs to be determined at the time the sensor goes to sleep based on all the information available to the sensor. Having sleeping sensors in the network could result in degraded tracking performance, therefore, there is a tradeoff between energy usage and tracking performance. We design sleeping policies that attempt to optimize this tradeoff and characterize their performance. As an extension to our previous work in this area [1], we consider generalized models for object movement, object sensing, and tracking cost. For discrete state spaces and continuous Gaussian observations, we derive a lower bound on the optimal energy-tracking tradeoff. It is shown that in the low tracking error regime, the generated policies approach the derived lower bound

Sensor Scheduling for Energy-Efficient Target Tracking in Sensor Networks

In this paper we study the problem of tracking an object moving randomly through a network of wireless sensors. Our objective is to devise strategies for scheduling the sensors to optimize the tradeoff between tracking performance and energy consumption. We cast the scheduling problem as a Partially Observable Markov Decision Process (POMDP), where the control actions correspond to the set of sensors to activate at each time step. Using a bottom-up approach, we consider different sensing, motion and cost models with increasing levels of difficulty. At the first level, the sensing regions of the different sensors do not overlap and the target is only observed within the sensing range of an active sensor. Then, we consider sensors with overlapping sensing range such that the tracking error, and hence the actions of the different sensors, are tightly coupled. Finally, we consider scenarios wherein the target locations and sensors' observations assume values on continuous spaces. Exact solutions are generally intractable even for the simplest models due to the dimensionality of the information and action spaces. Hence, we devise approximate solution techniques, and in some cases derive lower bounds on the optimal tradeoff curves. The generated scheduling policies, albeit suboptimal, often provide close-to-optimal energy-tracking tradeoffs

Competing Narratives: Choosing the Tiger in Ang Lee's Life of Pi

Life of Pi’s global resonance, international production team, and cos- mopolitan director are mainstream Hollywood’s answer to the de- mands of a “world cinema” marketplace. Having grossed over $600 million at the box office, with$482 million coming from theaters outside North America, Life of Pi earned more in mainland China than the United States and was Hollywood’s highest earning release in India for 2012. Ignoring these notable facts, reviewers often focus upon the film’s spiritual themes and impressive visual effects, but Lee’s interpretation clearly resonates in the global political climate. Though his films speak to an international audience, for whom does Ang Lee speak? Scholars such as Rey Chow, Emilie Yeh, Darrell Da- vis, Shu-mei Shih, and Gina Marchetti examine Lee’s work through a transnational lens, though much of this work remains framed within a regional discourse. By reviewing this scholarship, this paper dis- cusses the critical connections between these interpretations and my own reading of Life of Pi as a cosmopolitan allegory of migration and survival.published_or_final_versio

Light Element Synthesis in High Entropy Relativistic Flows Associated with Gamma Ray Bursts

We calculate and discuss the light element freeze-out nucleosynthesis in high entropy winds and fireballs for broad ranges of entropy-per-baryon, dynamic timescales characterizing relativistic expansion, and neutron-to-proton ratios. With conditions characteristic of Gamma Ray Bursts (GRBs) we find that deuterium production can be prodigious, with final abundance values 2H/H approximately 2%, depending on the fireball isospin, late time dynamics, and the effects of neutron decoupling- induced high energy non-thermal nuclear reactions. This implies that there potentially could be detectable local enhancements in the deuterium abundance associated with GRB events.Comment: 14 pages 3 figure