Finite Temperature and Density Effects in Planar Q.E.D

The behavior of finite temperature planar electrodynamics is investigated. We calculate the static as well as dynamic characteristic functions using real time formalism. The temperature and density dependence of dielectric and permeability functions, plasmon frequencies and their relation to the screening length is determined. The radiative correction to the fermion mass is also calculated. We also calculate the temperature dependence of the electron (anyon) magnetic moment. Our results for the gyromagnetic ratio go smoothly to the known result at zero temperature, $g=2$, in accordance with the general expectation.Comment: 24 pages, LaTe

Bulk and Edge excitations in a ν=1\nu =1 quantum Hall ferromagnet

In this article, we shall focus on the collective dynamics of the fermions in a $\nu = 1$ quantum Hall droplet. Specifically, we propose to look at the quantum Hall ferromagnet. In this system, the electron spins are ordered in the ground state due to the exchange part of the Coulomb interaction and the Pauli exclusion principle. The low energy excitations are ferromagnetic magnons. To provide a means for describing these magnons, we shall discuss a method of introducing collective coordinates in the Hilbert space of many-fermion systems. These collective coordinates are bosonic in nature. They map a part of the fermionic Hilbert space into a bosonic Hilbert space. Using this technique, we shall interpret the magnons as bosonic collective ex citations in the Hilbert space of the many-electron Hall system. By considering a Hall droplet of finite extent, we shall also obtain the effective Lagrangian governing the spin collective excitations at the edge of the sample.Comment: Plain TeX 18 Pages Proceedings for the Y2K conference on strongly c orrelated fermionic systems, Calcutta, Indi

Impacts of Biofuels on Water Supply: Proposed Cures May Worsen the Disease

water, conservation, biofuels, irrigation, Resource /Energy Economics and Policy, Q25, Q48,

Phase Space Reconstruction from Economic Time Series Data: Improving Models of Complex Real-World Dynamic Systems

Failure of economic models to anticipate the global financial crisis illustrates the need for modeling to better capture complex real-world dynamics. Conventional models—in which economic variables evolve toward equilibria or fluctuate about equilibria in response to exogenous random shocks—are ill-equipped to portray complex real-world dynamics in which economic variables may cycle aperiodically along low-dimensional ‘strange attractors’. We present a method developed in the physics literature—‘phase space reconstruction’—that reconstructs strange attractors present in real-world dynamical systems using time series data on a single variable. Phase space reconstruction provides pictures of real-world dynamics that can guide model specificationphase space reconstruction, time series data, economic dynamics, Agribusiness, Agricultural and Food Policy, Food Consumption/Nutrition/Food Safety, Food Security and Poverty, Production Economics, Risk and Uncertainty,

The topography of multivariate normal mixtures

Multivariate normal mixtures provide a flexible method of fitting high-dimensional data. It is shown that their topography, in the sense of their key features as a density, can be analyzed rigorously in lower dimensions by use of a ridgeline manifold that contains all critical points, as well as the ridges of the density. A plot of the elevations on the ridgeline shows the key features of the mixed density. In addition, by use of the ridgeline, we uncover a function that determines the number of modes of the mixed density when there are two components being mixed. A followup analysis then gives a curvature function that can be used to prove a set of modality theorems.Comment: Published at http://dx.doi.org/10.1214/009053605000000417 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Racism on Campus: An Exploratory Analysis of Black-White Perceptions in the South

Racism has been a persistent problem in American society. Sociologists refer to racism as unfair treatment of an individual or a group solely on the basis of race.[1] It may be covert or overt, and it may be expressed on an individual level when a person consciously or unconsciously discriminates against another person. Racism may also be expressed on an institutional level, when rules, policies and practices of organizations and/or institutions discriminate against an individual or a group.[2

Prediction of infectious disease epidemics via weighted density ensembles

Accurate and reliable predictions of infectious disease dynamics can be valuable to public health organizations that plan interventions to decrease or prevent disease transmission. A great variety of models have been developed for this task, using different model structures, covariates, and targets for prediction. Experience has shown that the performance of these models varies; some tend to do better or worse in different seasons or at different points within a season. Ensemble methods combine multiple models to obtain a single prediction that leverages the strengths of each model. We considered a range of ensemble methods that each form a predictive density for a target of interest as a weighted sum of the predictive densities from component models. In the simplest case, equal weight is assigned to each component model; in the most complex case, the weights vary with the region, prediction target, week of the season when the predictions are made, a measure of component model uncertainty, and recent observations of disease incidence. We applied these methods to predict measures of influenza season timing and severity in the United States, both at the national and regional levels, using three component models. We trained the models on retrospective predictions from 14 seasons (1997/1998 - 2010/2011) and evaluated each model's prospective, out-of-sample performance in the five subsequent influenza seasons. In this test phase, the ensemble methods showed overall performance that was similar to the best of the component models, but offered more consistent performance across seasons than the component models. Ensemble methods offer the potential to deliver more reliable predictions to public health decision makers.Comment: 20 pages, 6 figure