NONCONSTANT PRICE EXPECTATIONS AND ACREAGE RESPONSE: THE CASE OF COTTON PRODUCTION IN GEORGIA

An adaptive regression model is used to examine the relative importance of cash and government support prices in determining cotton production over time. The results show that the cash price is more important as a source of price information for cotton producers than the government program price. The cash price was shown to have a greater influence on acreage response in every year, including periods thought to be dominated by government commodity programs.Adaptive regression, Cotton acreage response, Price expectations, Crop Production/Industries,

Cost effectiveness of ward based non-invasive ventilation for acute exacerbations of chronic obstructive pulmonary disease: economic analysis of randomised controlled trial

OBJECTIVE: To evaluate the cost effectiveness of standard treatment with and without the addition of ward based non-invasive ventilation in patients admitted to hospital with an acute exacerbation of chronic obstructive pulmonary disease. DESIGN: Incremental cost effectiveness analysis of a randomised controlled trial. SETTING: Medical wards in 14 hospitals in the United Kingdom. PARTICIPANTS: The trial comprised 236 patients admitted to hospital with an acute exacerbation of chronic obstructive pulmonary disease and mild to moderate acidosis (pH 7.25-7.35) secondary to respiratory failure. The economic analysis compared the costs of treatment that these patients received after randomisation. MAIN OUTCOME MEASURE: Incremental cost per in-hospital death. RESULTS: 24/118 died in the group receiving standard treatment and 12/118 in the group receiving non-invasive ventilation (P=0.05). Allocation to the group receiving non-invasive ventilation was associated with a reduction in costs of £49 362 ($78 741; 73 109), mainly through reduced use of intensive care units. The incremental cost effectiveness ratio was £645 per death avoided (95% confidence interval £2310 to £386), indicating a dominant (more effective and less costly) strategy. Modelling of these data indicates that a typical UK hospital providing a non-invasive ventilation service will avoid six deaths and three to nine admissions to intensive care units per year, with an associated cost reduction of £12 000-53 000 per year. CONCLUSIONS: Non-invasive ventilation is a highly cost effective treatment that both reduced total costs and improved mortality in hospital

Radiation from a Charge Uniformly Accelerated for All Time

A recent paper of Singal [Gen. Rel. Grav. 27 (1995), 953-967] argues that a uniformly accelerated particle does not radiate, in contradiction to the consensus of the research literature over the past 30 years. This note points out some questionable aspects of Singal's argument and shows how similar calculations can lead to the opposite conclusion.Comment: LaTeX, 9 pages, to appear in General Relativity and Gravitatio

Genetic algorithms with elitism-based immigrants for changing optimization problems

Copyright @ Springer-Verlag Berlin Heidelberg 2007.Addressing dynamic optimization problems has been a challenging task for the genetic algorithm community. Over the years, several approaches have been developed into genetic algorithms to enhance their performance in dynamic environments. One major approach is to maintain the diversity of the population, e.g., via random immigrants. This paper proposes an elitism-based immigrants scheme for genetic algorithms in dynamic environments. In the scheme, the elite from previous generation is used as the base to create immigrants via mutation to replace the worst individuals in the current population. This way, the introduced immigrants are more adapted to the changing environment. This paper also proposes a hybrid scheme that combines the elitism-based immigrants scheme with traditional random immigrants scheme to deal with significant changes. The experimental results show that the proposed elitism-based and hybrid immigrants schemes efficiently improve the performance of genetic algorithms in dynamic environments

Applications of graphics to support a testbed for autonomous space vehicle operations

Researchers describe their experience using graphics tools and utilities while building an application, AUTOPS, that uses a graphical Machintosh (TM)-like interface for the input and display of data, and animation graphics to enhance the presentation of results of autonomous space vehicle operations simulations. AUTOPS is a test bed for evaluating decisions for intelligent control systems for autonomous vehicles. Decisions made by an intelligent control system, e.g., a revised mission plan, might be displayed to the user in textual format or he can witness the effects of those decisions via out of window graphics animations. Although a textual description conveys essentials, a graphics animation conveys the replanning results in a more convincing way. Similarily, iconic and menu-driven screen interfaces provide the user with more meaningful options and displays. Presented here are experiences with the SunView and TAE Plus graphics tools used for interface design, and the Johnson Space Center Interactive Graphics Laboratory animation graphics tools used for generating out out of the window graphics

Triggered memory-based swarm optimization in dynamic environments

This is a post-print version of this article - Copyright @ 2007 Springer-VerlagIn recent years, there has been an increasing concern from the evolutionary computation community on dynamic optimization problems since many real-world optimization problems are time-varying. In this paper, a triggered memory scheme is introduced into the particle swarm optimization to deal with dynamic environments. The triggered memory scheme enhances traditional memory scheme with a triggered memory generator. Experimental study over a benchmark dynamic problem shows that the triggered memory-based particle swarm optimization algorithm has stronger robustness and adaptability than traditional particle swarm optimization algorithms, both with and without traditional memory scheme, for dynamic optimization problems

A particle swarm optimization based memetic algorithm for dynamic optimization problems

Copyright @ Springer Science + Business Media B.V. 2010.Recently, there has been an increasing concern from the evolutionary computation community on dynamic optimization problems since many real-world optimization problems are dynamic. This paper investigates a particle swarm optimization (PSO) based memetic algorithm that hybridizes PSO with a local search technique for dynamic optimization problems. Within the framework of the proposed algorithm, a local version of PSO with a ring-shape topology structure is used as the global search operator and a fuzzy cognition local search method is proposed as the local search technique. In addition, a self-organized random immigrants scheme is extended into our proposed algorithm in order to further enhance its exploration capacity for new peaks in the search space. Experimental study over the moving peaks benchmark problem shows that the proposed PSO-based memetic algorithm is robust and adaptable in dynamic environments.This work was supported by the National Nature Science Foundation of China (NSFC) under Grant No. 70431003 and Grant No. 70671020, the National Innovation Research Community Science Foundation of China under Grant No. 60521003, the National Support Plan of China under Grant No. 2006BAH02A09 and the Ministry of Education, science, and Technology in Korea through the Second-Phase of Brain Korea 21 Project in 2009, the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/01 and the Hong Kong Polytechnic University Research Grants under Grant G-YH60

Homeless population

The aim was to derive and analyze a model for numbers of homeless and non-homeless people in a borough, in particular to see how these figures might be affected by different policies regarding housing various categories of people. Most attention was focused on steady populations although the stability of these and possible timescales of dynamic problems were also discussed. The main outcome of this brief study is the identification of the key role played by the constant k_1 - the constant which fixes the speed at which the homeless are rehoused in permanent council property. Reducing this constant, i.e. making the system "fairer" with less priority to accommodating homeless families, appears to have little effect on the sizes of other categories on the waiting list but there is a marked increase in the number of households in temporary accommodation. The model, indicated by the size of its longest time-scale, should be modified to allow for births etc. It could be varied by allowing people to remove themselves from the register or by allowing the rates at which registered and unregistered people become homeless to differ, but these modifications are unlikely to substantially change the main result. The inclusion of movement from the homeless to the general population would have the effect of limiting the numbers in temporary accommodation. However, it is thought this effect is very small so a great reduction in k_1 would be needed for this flow to become significant

Bridging Time Scales in Cellular Decision Making with a Stochastic Bistable Switch

Cellular transformations which involve a significant phenotypical change of the cell's state use bistable biochemical switches as underlying decision systems. In this work, we aim at linking cellular decisions taking place on a time scale of years to decades with the biochemical dynamics in signal transduction and gene regulation, occuring on a time scale of minutes to hours. We show that a stochastic bistable switch forms a viable biochemical mechanism to implement decision processes on long time scales. As a case study, the mechanism is applied to model the initiation of follicle growth in mammalian ovaries, where the physiological time scale of follicle pool depletion is on the order of the organism's lifespan. We construct a simple mathematical model for this process based on experimental evidence for the involved genetic mechanisms. Despite the underlying stochasticity, the proposed mechanism turns out to yield reliable behavior in large populations of cells subject to the considered decision process. Our model explains how the physiological time constant may emerge from the intrinsic stochasticity of the underlying gene regulatory network. Apart from ovarian follicles, the proposed mechanism may also be of relevance for other physiological systems where cells take binary decisions over a long time scale.Comment: 14 pages, 4 figure