Economic study of New Hampshire poultry farms, Bulletin, no. 265

The Bulletin is a publication of the New Hampshire Agricultural Experiment Station, College of Life Sciences and Agriculture, University of New Hampshire, Durham, New Hampshire

The Higgs Sector and CoGeNT/DAMA-Like Dark Matter in Supersymmetric Models

Recent data from CoGeNT and DAMA are roughly consistent with a very light dark matter particle with m\sim 4-10\gev and spin-independent cross section of order \sigma_{SI} \sim (1-3)\times 10^{-4}\pb. An important question is whether these observations are compatible with supersymmetric models obeying $\Omega h^2\sim 0.11$ without violating existing collider constraints and precision measurements. In this talk, I review the fact the the Minimal Supersymmetric Model allows insufficient flexibility to achieve such compatibility, basically because of the highly constrained nature of the MSSM Higgs sector in relation to LEP limits on Higgs bosons. I then outline the manner in which the more flexible Higgs sectors of the Next-to-Minimal Supersymmetric Model and an Extended Next-to-Minimal Supersymmetric Model allow large $\sigma_{SI}$ and $\Omega h^2\sim 0.11$ at low LSP mass without violating LEP, Tevatron, BaBar and other experimental limits. The relationship of the required Higgs sectors to the NMSSM "ideal-Higgs" scenarios is discussed.Comment: 11 pages, 3 figures. To appear in Proceedings of PASCOS 2010. The paper is a compilation of talks given at: PASCOS 2010, ORSAY Workshop on "Higgs Hunting", and SLAC Workshop on "Topologies for Early LHC Searches

Variability of signal to noise ratio and the network analysis of gravitational wave burst signals

The detection and estimation of gravitational wave burst signals, with {\em a priori} unknown polarization waveforms, requires the use of data from a network of detectors. For determining how the data from such a network should be combined, approaches based on the maximum likelihood principle have proven to be useful. The most straightforward among these uses the global maximum of the likelihood over the space of all waveforms as both the detection statistic and signal estimator. However, in the case of burst signals, a physically counterintuitive situation results: for two aligned detectors the statistic includes the cross-correlation of the detector outputs, as expected, but this term disappears even for an infinitesimal misalignment. This {\em two detector paradox} arises from the inclusion of improbable waveforms in the solution space of maximization. Such waveforms produce widely different responses in detectors that are closely aligned. We show that by penalizing waveforms that exhibit large signal-to-noise ratio (snr) variability, as the corresponding source is moved on the sky, a physically motivated restriction is obtained that (i) resolves the two detector paradox and (ii) leads to a better performing statistic than the global maximum of the likelihood. Waveforms with high snr variability turn out to be precisely the ones that are improbable in the sense mentioned above. The coherent network analysis method thus obtained can be applied to any network, irrespective of the number or the mutual alignment of detectors.Comment: 13 pages, 6 figure

Pluto's global surface composition through pixel-by-pixel Hapke modeling of New Horizons Ralph/LEISA data

On July 14th 2015, NASA's New Horizons mission gave us an unprecedented detailed view of the Pluto system. The complex compositional diversity of Pluto's encounter hemisphere was revealed by the Ralph/LEISA infrared spectrometer on board of New Horizons. We present compositional maps of Pluto defining the spatial distribution of the abundance and textural properties of the volatiles methane and nitrogen ices and non-volatiles water ice and tholin. These results are obtained by applying a pixel-by-pixel Hapke radiative transfer model to the LEISA scans. Our analysis focuses mainly on the large scale latitudinal variations of methane and nitrogen ices and aims at setting observational constraints to volatile transport models. Specifically, we find three latitudinal bands: the first, enriched in methane, extends from the pole to 55deg N, the second dominated by nitrogen, continues south to 35deg N, and the third, composed again mainly of methane, reaches 20deg N. We demonstrate that the distribution of volatiles across these surface units can be explained by differences in insolation over the past few decades. The latitudinal pattern is broken by Sputnik Planitia, a large reservoir of volatiles, with nitrogen playing the most important role. The physical properties of methane and nitrogen in this region are suggestive of the presence of a cold trap or possible volatile stratification. Furthermore our modeling results point to a possible sublimation transport of nitrogen from the northwest edge of Sputnik Planitia toward the south.Comment: 43 pages, 7 figures; accepted for publication in Icaru

Possibilities for pedagogy in Further Education: Harnessing the abundance of literacy

In this report, it is argued that the most salient factor in the contemporary communicative landscape is the sheer abundance and diversity of possibilities for literacy, and that the extent and nature of students' communicative resources is a central issue in education. The text outlines the conceptual underpinnings of the Literacies for Learning in Further Education project in a social view of literacy, and the associated research design, methodology and analytical framework. It elaborates on the notion of the abundance of literacies in students' everyday lives, and on the potential for harnessing these as resources for the enhancement of learning. It provides case studies of changes in practice that have been undertaken by further education staff in order to draw upon students' everyday literacy practices on Travel and Tourism and Multimedia courses. It ends with some of the broad implications for conceptualising learning that arise from researching through the lens of literacy practices

Gravitational Waves from Axisymmetric, Rotational Stellar Core Collapse

We have carried out an extensive set of two-dimensional, axisymmetric, purely-hydrodynamic calculations of rotational stellar core collapse with a realistic, finite-temperature nuclear equation of state and realistic massive star progenitor models. For each of the total number of 72 different simulations we performed, the gravitational wave signature was extracted via the quadrupole formula in the slow-motion, weak-field approximation. We investigate the consequences of variation in the initial ratio of rotational kinetic energy to gravitational potential energy and in the initial degree of differential rotation. Furthermore, we include in our model suite progenitors from recent evolutionary calculations that take into account the effects of rotation and magnetic torques. For each model, we calculate gravitational radiation wave forms, characteristic wave strain spectra, energy spectra, final rotational profiles, and total radiated energy. In addition, we compare our model signals with the anticipated sensitivities of the 1st- and 2nd-generation LIGO detectors coming on line. We find that most of our models are detectable by LIGO from anywhere in the Milky Way.Comment: 13 pages, 22 figures, accepted for publication in ApJ (v600, Jan. 2004). Revised version: Corrected typos and minor mistakes in text and references. Minor additions to the text according to the referee's suggestions, conclusions unchange

Computational Relativistic Astrophysics With Adaptive Mesh Refinement: Testbeds

We have carried out numerical simulations of strongly gravitating systems based on the Einstein equations coupled to the relativistic hydrodynamic equations using adaptive mesh refinement (AMR) techniques. We show AMR simulations of NS binary inspiral and coalescence carried out on a workstation having an accuracy equivalent to that of a $1025^3$ regular unigrid simulation, which is, to the best of our knowledge, larger than all previous simulations of similar NS systems on supercomputers. We believe the capability opens new possibilities in general relativistic simulations.Comment: 7 pages, 16 figure

In silico evolution of diauxic growth

The glucose effect is a well known phenomenon whereby cells, when presented with two different nutrients, show a diauxic growth pattern, i.e. an episode of exponential growth followed by a lag phase of reduced growth followed by a second phase of exponential growth. Diauxic growth is usually thought of as a an adaptation to maximise biomass production in an environment offering two or more carbon sources. While diauxic growth has been studied widely both experimentally and theoretically, the hypothesis that diauxic growth is a strategy to increase overall growth has remained an unconfirmed conjecture. Here, we present a minimal mathematical model of a bacterial nutrient uptake system and metabolism. We subject this model to artificial evolution to test under which conditions diauxic growth evolves. As a result, we find that, indeed, sequential uptake of nutrients emerges if there is competition for nutrients and the metabolism/uptake system is capacity limited. However, we also find that diauxic growth is a secondary effect of this system and that the speed-up of nutrient uptake is a much larger effect. Notably, this speed-up of nutrient uptake coincides with an overall reduction of efficiency. Our two main conclusions are: (i) Cells competing for the same nutrients evolve rapid but inefficient growth dynamics. (ii) In the deterministic models we use here no substantial lag-phase evolves. This suggests that the lag-phase is a consequence of stochastic gene expression

Sometimes, Money Does Grow On Trees: Data-Driven Demand Response with DR-Advisor

Real-time electricity pricing and demand response has become a clean, reliable and cost-effective way of mitigating peak demand on the electricity grid. We consider the problem of end-user demand response (DR) for large commercial buildings which involves predicting the demand response baseline, evaluating fixed DR strategies and synthesizing DR control actions for load curtailment in return for a financial reward. Using historical data from the building, we build a family of regression trees and learn data-driven models for predicting the power consumption of the building in real-time. We present a method called DR-Advisor called DR-Advisor, which acts as a recommender system for the building\u27s facilities manager and provides suitable control actions to meet the desired load curtailment while maintaining operations and maximizing the economic reward. We evaluate the performance of DR-Advisor for demand response using data from a real office building and a virtual test-bed