27,582 research outputs found
Transitions in non-conserving models of Self-Organized Criticality
We investigate a random--neighbours version of the two dimensional
non-conserving earthquake model of Olami, Feder and Christensen [Phys. Rev.
Lett. {\bf 68}, 1244 (1992)]. We show both analytically and numerically that
criticality can be expected even in the presence of dissipation. As the
critical level of conservation, , is approached, the cut--off of the
avalanche size distribution scales as . The
transition from non-SOC to SOC behaviour is controlled by the average branching
ratio of an avalanche, which can thus be regarded as an order
parameter of the system. The relevance of the results are discussed in
connection to the nearest-neighbours OFC model (in particular we analyse the
relevance of synchronization in the latter).Comment: 8 pages in latex format; 5 figures available upon reques
The Devil is in the Detail: Hints for Practical Optimisation
Finding the minimum of an objective function, such as a least squares or negative log-likelihood function, with respect to the unknown model parameters is a problem often encountered in econometrics. Consequently, students of econometrics and applied econometricians are usually well-grounded in the broad differences between the numerical procedures employed to solve these problems. Often, however, relatively little time is given to understanding the practical subtleties of implementing these schemes when faced with illbehaved problems. This paper addresses some of the details involved in practical optimisation, such as dealing with constraints on the parameters, specifying starting values, termination criteria and analytical gradients, and illustrates some of the general ideas with several instructive examples.gradient algorithms, unconstrained optimisation, generalised method of moments.
On Self-Organized Criticality and Synchronization in Lattice Models of Coupled Dynamical Systems
Lattice models of coupled dynamical systems lead to a variety of complex
behaviors. Between the individual motion of independent units and the
collective behavior of members of a population evolving synchronously, there
exist more complicated attractors. In some cases, these states are identified
with self-organized critical phenomena. In other situations, with
clusterization or phase-locking. The conditions leading to such different
behaviors in models of integrate-and-fire oscillators and stick-slip processes
are reviewed.Comment: 41 pages. Plain LaTeX. Style included in main file. To appear as an
invited review in Int. J. Modern Physics B. Needs eps
Discrete time-series models when counts are unobservable
Count data in economics have traditionally been modeled by means of integer-valued autoregressive models. Consequently, the estimation of the parameters of these models and their asymptotic properties have been well documented in the literature. The models comprise a description of the survival of counts generally in terms of a binomial thinning process and an independent arrivals process usually specified in terms of a Poisson distribution. This paper extends the existing class of models to encompass situations in which counts are latent and all that is observed is the presence or absence of counts. This is a potentially important modification as many interesting economic phenomena may have a natural interpretation as a series of 'events' that are driven by an underlying count process which is unobserved. Arrivals of the latent counts are modeled either in terms of the Poisson distribution, where multiple counts may arrive in the sampling interval, or in terms of the Bernoulli distribution, where only one new arrival is allowed in the same sampling interval. The models with latent counts are then applied in two practical illustrations, namely, modeling volatility in financial markets as a function of unobservable 'news' and abnormal price spikes in electricity markets being driven by latent 'stress'.Integer-valued autoregression, Poisson distribution, Bernoulli distribution, latent factors, maximum likelihood estimation
An assessment of two decades of contaminant monitoring in the Nation’s Coastal Zone.
Executive Summary:
Information found in this report covers the years 1986 through 2005. Mussel Watch began monitoring a suite of trace metals and organic contaminants such as DDT, PCBs and PAHs. Through time additional chemicals were added, and today approximately 140 analytes are monitored. The Mussel Watch Program is the longest running estuarine and coastal pollutant monitoring effort conducted in the United States that is national in scope each year. Hundreds of scientific journal articles and technical reports based on Mussel Watch data have been written; however, this report is the first that presents local, regional and national findings
across all years in a Quick Reference format, suitable for use by policy makers, scientists, resource managers and the general public.
Pollution often starts at the local scale where high concentrations point to a specific source of contamination, yet some contaminants such as PCBs are atmospherically transported across regional and national scales, resulting in contamination far from their origin. Findings presented here showed few national trends for trace metals and decreasing trends for most organic contaminants; however, a wide variety of trends, both increasing and decreasing, emerge at regional and local levels. For most organic contaminants, trends have resulted from state and
federal regulation. The highest concentrations for both metal and organic contaminants are found near urban and industrial areas.
In addition to monitoring throughout the nation’s coastal shores and Great Lakes, Mussel Watch samples are stored in a specimen bank so that trends can be determined retrospectively for new and emerging contaminants of
concern. For example, there is heightened awareness of a group of flame retardants that are finding their way into the marine environment. These compounds, known as polybrominated diphenyl ethers (PBDEs), are now being studied using historic samples from the specimen bank and current samples to determine their spatial distribution. We will continue to use this kind of investigation to assess new contaminant threats.
We hope you find this document to be valuable, and that
you continue to look towards the Mussel Watch Program
for information on the condition of your coastal waters. (PDF contains 118 pages
Ground Beetles (Coleoptera: Carabidae) Inhabiting Stands of Reed Canary Grass Phalaris Arundinacea on Islands in the Lower Chippewa River, Wisconsin
We used pitfall traps to assess ground beetle diversity (Coleoptera:Carabidae) on two islands in the lower Chippewa River, Eau Claire County, Wisconsin, with rapidly expanding populations of reed canary grass, Phalaris arundinaceae. We collected 233 individuals belonging to 17 species over four, 3-9 day sampling periods, May-August 1994. All species have been documented in Wisconsin and most are considered habitat generalists. Agonum fidele, A. extensicolle, Anisodactylus harrisii and Bembidion quadrimaculatum oppositum comprised 70% of all species collected. Seven species were common to both islands, with 13 species collected on Canarygrass Island and 11 species on Ski Jump Island. Carabid species diversity (Shannon’s H=2.01) was greatest on Canarygrass Island
Influence of temperature probe sheathing materials during ultrasonic heating
Journal ArticleThe influence of sheathing materials upon temperature probes used during the monitoring of ultrasonic heating was measured. The measurements show that the sheathing can be heated in a manner not representative of the temperature rise occurring in the surrounding material, altering the probe readings
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