IMPACT OF ALTERNATIVE GRID PRICING STRUCTURES ON CATTLE MARKETING DECISIONS

Quality grade, yield grade, and other feedlot performance factors explain much of the variation in profit under grid pricing. Thus, feedlot owners can change profits by adjusting time on feed to influence these performance factors. This research uses growth models, logistic regression, and an optimization process to determine how the optimal number of days on feed changes under different grid pricing structures. It was found that large quality or small yield discounts increases the optimal number of days on feed and small quality or large yield discounts result in fewer days on feed. Losses associated with a grid having large quality discounts are minimized as cattle fed for more days are able to obtain Choice premiums despite the discounts for more Yield Grade 4 and 5 carcasses. Given small quality discounts, cattle fed for a shorter length of time can obtain the Yield Grade 1 and 2 premiums without a large loss in revenue due to grading Select or Standard. Under cash pricing, cattle are fed for very long periods because there are no discounts applied to the carcasses and, therefore, the more weight they gain, the more revenue they generate. During periods of low feed prices, cattle can be fed longer so more cattle grade Prime but also have more Yield Grade 4 and 5 cattle.grid pricing, profits, animal growth, logistic regression, days on feed, Livestock Production/Industries, Marketing,

A Flexible Analytic Model of Cosmic Variance in the First Billion Years

Cosmic variance is the intrinsic scatter in the number density of galaxies due to fluctuations in the large-scale dark matter density field. In this work, we present a simple analytic model of cosmic variance in the high redshift Universe ($z\sim5-15$). We assume that galaxies grow according to the evolution of the halo mass function, which we allow to vary with large-scale environment. Our model produces a reasonable match to the observed ultraviolet luminosity functions in this era by regulating star formation through stellar feedback and assuming that the UV luminosity function is dominated by recent star formation. We find that cosmic variance in the UVLF is dominated by the variance in the underlying dark matter halo population, and not by differences in halo accretion or the specifics of our stellar feedback model. We also find that cosmic variance dominates over Poisson noise for future high-$z$ surveys except for the brightest sources or at very high redshifts ($z \gtrsim 12$). We provide a linear approximation of cosmic variance for a variety of redshifts, magnitudes, and survey areas through the public Python package galcv. Finally, we introduce a new method for incorporating priors on cosmic variance into estimates of the galaxy luminosity function and demonstrate that it significantly improves constraints on that important observable

Reconstructing 3D x-ray CT images of polymer gel dosimeters using the zero-scan method

In this study x-ray CT has been used to produce a 3D image of an irradiated PAGAT gel sample, with noise-reduction achieved using the ‘zero-scan’ method. The gel was repeatedly CT scanned and a linear fit to the varying Hounsfield unit of each pixel in the 3D volume was evaluated across the repeated scans, allowing a zero-scan extrapolation of the image to be obtained. To minimise heating of the CT scanner’s x-ray tube, this study used a large slice thickness (1 cm), to provide image slices across the irradiated region of the gel, and a relatively small number of CT scans (63), to extrapolate the zero-scan image. The resulting set of transverse images shows reduced noise compared to images from the initial CT scan of the gel, without being degraded by the additional radiation dose delivered to the gel during the repeated scanning. The full, 3D image of the gel has a low spatial resolution in the longitudinal direction, due to the selected scan parameters. Nonetheless, important features of the dose distribution are apparent in the 3D x-ray CT scan of the gel. The results of this study demonstrate that the zero-scan extrapolation method can be applied to the reconstruction of multiple x-ray CT slices, to provide useful 2D and 3D images of irradiated dosimetry gels

Linearly independent pure-state decomposition and quantum state discrimination

We put the pure-state decomposition mathematical property of a mixed state to a physical test. We begin by characterizing all the possible decompositions of a rank-two mixed state by means of the complex overlap between two involved states. The physical test proposes a scheme of quantum state recognition of one of the two linearly independent states which arise from the decomposition. We find that the two states associated with the balanced pure-state decomposition have the smaller overlap modulus and therefore the smallest probability of being discriminated conclusively, while in the nonconclusive scheme they have the highest probability of having an error. In addition, we design an experimental scheme which allows to discriminate conclusively and optimally two nonorthogonal states prepared with different a priori probabilities. Thus, we propose a physical implementation for this linearly independent pure-state decomposition and state discrimination test by using twin photons generated in the process of spontaneous parametric down conversion. The information-state is encoded in one photon polarization state whereas the second single-photon is used for heralded detection.Comment: 6 pages, 5 figures, Submitted to Phys. Rev.

DiversiTree: Computing Diverse Sets of Near-Optimal Solutions to Mixed-Integer Optimization Problems

While most methods for solving mixed-integer optimization problems seek a single optimal solution, finding a diverse set of near-optimal solutions can often be more useful. State of the art methods for generating diverse near-optimal solutions usually take a two-phase approach, first finding a set of near-optimal solutions and then finding a diverse subset. In contrast, we present a method of finding a set of diverse solutions by emphasizing diversity within the search for near-optimal solutions. Specifically, within a branch-and-bound framework, we investigate parameterized node selection rules that explicitly consider diversity. Our results indicate that our approach significantly increases diversity of the final solution set. When compared with existing methods for finding diverse near-optimal sets, our method runs with similar run-time as regular node selection methods and gives a diversity improvement of up to 140%. In contrast, popular node selection rules such as best-first search gives an improvement of no more than 40%. Further, we find that our method is most effective when diversity is emphasized more in node selection when deeper in the tree and when the solution set has grown large enough.Comment: 30 pages, 11 figures, submitted to INFORMS Journal on Computin

Quantitative evaluation of polymer gel dosimeters by broadband ultrasound attenuation

Ultrasound has been examined previously as an alternative readout method for irradiated polymer gel dosimeters, with authors reporting varying dose response to ultrasound transmission measurements. In this current work we extend previous work to measure the broadband ultrasound attenuation (BUA) response of irradiated PAGAT gel dosimeters, using a novel ultrasound computed tomography system

The infrared imaging spectrograph (IRIS) for TMT: electronics-cable architecture

The InfraRed Imaging Spectrograph (IRIS) is a first-light instrument for the Thirty Meter Telescope (TMT). It combines a diffraction limited imager and an integral field spectrograph. This paper focuses on the electrical system of IRIS. With an instrument of the size and complexity of IRIS we face several electrical challenges. Many of the major controllers must be located directly on the cryostat to reduce cable lengths, and others require multiple bulkheads and must pass through a large cable wrap. Cooling and vibration due to the rotation of the instrument are also major challenges. We will present our selection of cables and connectors for both room temperature and cryogenic environments, packaging in the various cabinets and enclosures, and techniques for complex bulkheads including for large detectors at the cryostat wall

Overcoming Human Trafficking via Operations Research and Analytics: Opportunities for Methods, Models, and Applications

Human trafficking is a transnational complex societal and economic issue. While human trafficking has been studied in a variety of contexts, including criminology, sociological, and clinical domains, to date there has been very little coverage in the operations research (OR) and analytics community. This paper highlights how operations research and analytics techniques can be used to address the growing issue of human trafficking. It is intended to give insight to operations research and analytics professionals into the unique concerns, problems, and challenges in human trafficking; the relevance of OR and analytics to key pillars of human trafficking including prevention, protection, and prosecution; and to discuss opportunities for OR and analytics to make a difference in the human trafficking domain. We maintain that a profound need exists to explore how operations research and analytics can be effectively leveraged to combat human trafficking, and set forth this call to action to inhibit its pervasiveness