The nonlinear diocotron mode in a pure electron plasma

The nonlinear diocotron mode, discussed by Fine, Driscoll, and Malmberg [Phys. Rev. Lett. 63, 2232 (1989)] is characterized by two equations, one describing the frequency of orbiting, the other giving the quadrupole moment, as functions of size and offset. A new analysis, based on the method of moments, which yields equations more general in their content, is presented here. For example, the new equations describe columns whose shapes are not elliptical and whose densities are not constant

Linear response of the two-dimensional pure electron plasma: Quasimodes for some model profiles

After examining the initial value problem for the linear, diocotron response of a long cylinder of pure-electron plasma, the "quasimodes" associated with convex, power-law density profiles are studied. For these profiles, exact, analytic results are available. The "quasimodes," which are damped by phase mixing, may be characterized by their angular variation, flatness, and the magnitude of the gap separating the plasma from the containing wall

USDA'S ASSESSMENT OF THE COSTS OF MANAGING MANURE NUTRIENTS WITH LAND APPLICATION

Livestock Production/Industries,

Utilizing Deep Neural Networks for Brain–Computer Interface-Based Prosthesis Control

Limb amputations affect a significant portion of the world’s population every year. The necessity for these operations can be associated with related health conditions or a traumatic event. Currently, prosthetic devices intended to alleviate the burden of amputation lack many of the premier features possessed by their biological counterparts. The foremost of these features are agility and tactile function. In an effort to address the former, researchers here investigate the fundamental connection between agile finger movement and brain signaling. In this study each subject was asked to move his or her right index finger in sync with a time-aligned finger movement demonstration while each movement was labeled and the subject’s brain waves were recorded via a single-channel electroencephalograph. This data was subsequently used to train and test a deep neural network in an effort to classify each subject’s intention to rest and intention to extend his or her right index finger. On average, the employed model yielded an accuracy of 63.3%, where the most predictable subject’s movements were classified with an accuracy of 70.5%

ESTIMATING THE VARIANCE OF FOOD PRICE INFLATION

Stochastic index theory views each commodity price change as an independent observation on the rate of inflation that can be estimated by averaging over all prices. Our methodology estimates both the overall rate of inflation and relative price changes along with standard errors.Food prices, Index numbers, Inflation, Demand and Price Analysis,

A spatial analysis of multivariate output from regional climate models

Climate models have become an important tool in the study of climate and climate change, and ensemble experiments consisting of multiple climate-model runs are used in studying and quantifying the uncertainty in climate-model output. However, there are often only a limited number of model runs available for a particular experiment, and one of the statistical challenges is to characterize the distribution of the model output. To that end, we have developed a multivariate hierarchical approach, at the heart of which is a new representation of a multivariate Markov random field. This approach allows for flexible modeling of the multivariate spatial dependencies, including the cross-dependencies between variables. We demonstrate this statistical model on an ensemble arising from a regional-climate-model experiment over the western United States, and we focus on the projected change in seasonal temperature and precipitation over the next 50 years.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS369 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Advanced content-based semantic scene analysis and information retrieval: the SCHEMA project

The aim of the SCHEMA Network of Excellence is to bring together a critical mass of universities, research centers, industrial partners and end users, in order to design a reference system for content-based semantic scene analysis, interpretation and understanding. Relevant research areas include: content-based multimedia analysis and automatic annotation of semantic multimedia content, combined textual and multimedia information retrieval, semantic -web, MPEG-7 and MPEG-21 standards, user interfaces and human factors. In this paper, recent advances in content-based analysis, indexing and retrieval of digital media within the SCHEMA Network are presented. These advances will be integrated in the SCHEMA module-based, expandable reference system

ASCIE: An integrated experiment to study CSI in large segmented optical systems

A description of the advanced structures/control integrated experiment (ASCIE) experimental setup, a generic test bed for several essential technologies was presented. In particular its multi-input, multi-output, non-collocated control system and its complex structural dynamics, characteristic of large segmented systems make it an ideal test bed for Control-Structure Interaction (CSI) experiments. The high accuracy of its measurement system will make it possible to investigate the dynamics of microvibrations and its implication for the CSI phenomenon

Beyond Water-Quality Regulations for CAFOs? Manure Management Costs to Meet Air-Quality Objectives

Federal policy on manure management has focused on water-quality protection. However, animal agriculture is an important source of ammonia-nitrogen and other air emissions, increasing attention on air-quality concerns. Policies to address air emissions would influence both the costs of meeting water-quality objectives and environmental tradeoffs. We consider hypothetical policies at a regional level.manure management, confined animals, water quality, air quality, regional optimization, Chesapeake Bay, Environmental Economics and Policy,

ESTIMATING PRODUCER'S SURPLUS WITH THE CENSORED REGRESSION MODEL: AN APPLICATION TO PRODUCERS AFFECTED BY COLUMBIA RIVER BASIN SALMON RECOVERY

Application of the tobit model to estimate economic welfare is transferred from the consumer side to the producer side. Supply functions are estimated for multioutput irrigators in the Pacific Northwest. Empirical procedures are then developed for computing expected producer's surplus from the output supply functions. Confidence intervals for the surplus measures are generated using the Krinsky-Robb method. An experiment predicts decreases in surplus given increases in water pumping cost. The experiment replicates possible increases in hydroelectric prices due to the salmon recovery program in the Columbia-Snake River Basin. Output substitution explains producers' ability to mitigate the effect of the price increases on producer's surplus.Resource /Energy Economics and Policy,