2,317 research outputs found

    Auction Design and the Market for Sulfur Dioxide Emissions

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    Title IV of the Clean Air Act Amendments of 1990 created a market for electric utility emissions of sulfur dioxide (SO2). Recent papers have argued that flaws in the design of the auctions that are part of this market have adversely affected its performance. These papers incorrectly assume that trade can only occur at auctions, however. Our empirical analysis of the SO2 emissions market shows that the auctions have become a small part of a relatively efficient market and that the auction design problems that have attracted the most attention have had no effect on actual market prices

    Generalized Integer Partitions, Tilings of Zonotopes and Lattices

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    In this paper, we study two kinds of combinatorial objects, generalized integer partitions and tilings of two dimensional zonotopes, using dynamical systems and order theory. We show that the sets of partitions ordered with a simple dynamics, have the distributive lattice structure. Likewise, we show that the set of tilings of zonotopes, ordered with a simple and classical dynamics, is the disjoint union of distributive lattices which we describe. We also discuss the special case of linear integer partitions, for which other dynamical systems exist. These results give a better understanding of the behaviour of tilings of zonotopes with flips and dynamical systems involving partitions.Comment: See http://www.liafa.jussieu.fr/~latapy

    Auction design and the market for sulfur dioxide emissions

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    Title IV of the Clean Air Act Amendments of 1990 created a market for electric utility emissions of sulfur dioxide (SO2). Recent papers have argued that flaws in the design of the auctions that are part of this market have adversely affected its performance. These papers incorrectly assume that trade can only occur at auctions, however. Our empirical analysis of the SO2 emissions market shows that the auctions have become a small part of a relatively efficient market and that the auction design problems that have attracted the most attention have had no effect on actual market prices.Supported by the MIT Center for Energy and Environmental Policy Research and the Acid Rain Division of the U.S. Environmental Protection Agency

    Volitional Control of Neural Activity Relies on the Natural Motor Repertoire

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    Background: The results from recent brain-machine interface (BMI) studies suggest that it may be more efficient to use simple arbitrary relationships between individual neuron activity and BMI movements than the complex relationship observed between neuron activity and natural movements. This idea is based on the assumption that individual neurons can be conditioned independently regardless of their natural movement association. Results: We tested this assumption in the parietal reach region (PRR), an important candidate area for BMIs in which neurons encode the target location for reaching movements. Monkeys could learn to elicit arbitrarily assigned activity patterns, but the seemingly arbitrary patterns always belonged to the response set for natural reaching movements. Moreover, neurons that are free from conditioning showed correlated responses with the conditioned neurons as if they encoded common reach targets. Thus, learning was accomplished by finding reach targets (intrinsic variable of PRR neurons) for which the natural response of reach planning could approximate the arbitrary patterns. Conclusions: Our results suggest that animals learn to volitionally control single-neuron activity in PRR by preferentially exploring and exploiting their natural movement repertoire. Thus, for optimal performance, BMIs utilizing neural signals in PRR should harness, not disregard, the activity patterns in the natural sensorimotor repertoire

    Native Fauna on Exotic Trees: Phylogenetic Conservatism and Geographic Contingency in Two Lineages of Phytophages on Two Lineages of Trees

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    International audienceThe relative roles of evolutionary history and geographical and ecological contingency for community assembly remain unknown. Plant species, for instance, share more phytophages with closer relatives (phylogenetic conservatism), but for exotic plants introduced to another continent, this may be overlaid by geographically contingent evolution or immigration from locally abundant plant species (mass effects). We assessed within local forests to what extent exotic trees (Douglas-fir, red oak) recruit phytophages (Coleoptera, Heteroptera) from more closely or more distantly related native plants. We found that exotics shared more phytophages with natives from the same major plant lineage (angiosperms vs. gymnosperms) than with natives from the other lineage. This was particularly true for Heteroptera, and it emphasizes the role of host specialization in phylogenetic conservatism of host use. However, for Coleoptera on Douglas-fir, mass effects were important: immigration from beech increased with increasing beech abundance. Within a plant phylum, phylogenetic proximity of exotics and natives increased phytophage similarity, primarily in younger Coleoptera clades on angiosperms, emphasizing a role of past codiversification of hosts and phytophages. Overall, phylogenetic conservatism can shape the assembly of local phytophage communities on exotic trees. Whether it outweighs geographic contingency and mass effects depends on the interplay of phylogenetic scale, local abundance of native tree species, and the biology and evolutionary history of the phytophage taxon

    Body temperature patterns as a predictor of hospital-acquired sepsis in afebrile adult intensive care unit patients: A case-control study

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    INTRODUCTION: Early treatment of sepsis improves survival, but early diagnosis of hospital-acquired sepsis, especially in critically ill patients, is challenging. Evidence suggests that subtle changes in body temperature patterns may be an early indicator of sepsis, but data is limited. The aim of this study was to examine whether abnormal body temperature patterns, as identified by visual examination, could predict the subsequent diagnosis of sepsis in afebrile critically ill patients. METHODS: Retrospective case-control study of 32 septic and 29 non-septic patients in an adult medical and surgical ICU. Temperature curves for the period starting 72 hours and ending 8 hours prior to the clinical suspicion of sepsis (for septic patients) and for the 72-hour period prior to discharge from the ICU (for non-septic patients) were rated as normal or abnormal by seven blinded physicians. Multivariable logistic regression was used to compare groups in regard to maximum temperature, minimum temperature, greatest change in temperature in any 24-hour period, and whether the majority of evaluators rated the curve to be abnormal. RESULTS: Baseline characteristics of the groups were similar except the septic group had more trauma patients (31.3% vs. 6.9%, p = .02) and more patients requiring mechanical ventilation (75.0% vs. 41.4%, p = .008). Multivariable logistic regression to control for baseline differences demonstrated that septic patients had significantly larger temperature deviations in any 24-hour period compared to control patients (1.5°C vs. 1.1°C, p = .02). An abnormal temperature pattern was noted by a majority of the evaluators in 22 (68.8%) septic patients and 7 (24.1%) control patients (adjusted OR 4.43, p = .017). This resulted in a sensitivity of 0.69 (95% CI [confidence interval] 0.50, 0.83) and specificity of 0.76 (95% CI 0.56, 0.89) of abnormal temperature curves to predict sepsis. The median time from the temperature plot to the first culture was 9.40 hours (IQR [inter-quartile range] 8.00, 18.20) and to the first dose of antibiotics was 16.90 hours (IQR 8.35, 34.20). CONCLUSIONS: Abnormal body temperature curves were predictive of the diagnosis of sepsis in afebrile critically ill patients. Analysis of temperature patterns, rather than absolute values, may facilitate decreased time to antimicrobial therapy

    Summary of Almost 20 Years of Storm Overflight Electric Field, Conductivity, Flash Rate, and Current Statistics

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    We present total conduction (Wilson) currents for more than 1000 high-altitude aircraft overflights of electrified clouds acquired over nearly two decades. The overflights include a wide geographical sample of storms over land and ocean, with and without lightning, and with positive (i.e., upward-directed) and negative current. Peak electric field, with lightning transients removed, ranged from -1.0 kV/m to 16. kV/m, with mean (median) of 0.9 kV/m (0.29 kV/m). Total conductivity at flight altitude ranged from 0.6 pS/m to 3.6 pS/m, with mean and median of 2.2 pS/m. Peak current densities ranged from -2.0 nA m(exp -2) to 33.0 nA m(exp -2) with mean (median) of 1.9 nA m(exp -2) (0.6 nA m(exp -2)). Total upward current flow from storms in our dataset ranged from -1.3 to 9.4 A. The mean current for storms with lightning is 1.7 A over ocean and 1.0 A over land. The mean current for electrified shower clouds (i.e. electrified storms without lightning) is 0.41 A for ocean and 0.13 A for land. About 78% (43%) of the land (ocean) storms have detectable lightning. Land storms have 2.8 times the mean flash rate as ocean storms (2.2 versus 0.8 flashes min-1, respectively). Approximately 7% of the overflights had negative current. The mean and median currents for positive (negative) polarity storms are 1.0 and 0.35 A (-0.30 and -0.26 A). We found no regional or latitudinal-based patterns in our storm currents, nor support for simple scaling laws between cloud top height and lightning flash rate

    On Evidence Weighted Mixture Classification

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    2005 Joint Annual Meeting of the Interface and the Classification Society of North America, St. Louis, Missouri, 8-12 June 2005Calculation of the marginal likelihood or evidence is a problem central to model selection and model averaging in a Bayesian framework. Many sampling methods, especially (Reversible Jump) Markov chain Monte Carlo techniques, have been devised to avoid explicit calculation of the evidence, but they are limited to models with a common parameterisation. It is desirable to extend model averaging to models with disparate architectures and parameterisations. In this paper we present a straightforward general computational scheme for calculating the evidence, applicable to any model for which samples can be drawn from the posterior distribution of parameters conditioned on the data. The scheme is demonstrated on a simple feature subset selection example

    Summary of Almost 20 Years of Storm Overflight Electric Field, Conductivity, Flash Rates, and Electric Current Statistics

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    We determined total conduction currents and flash rates for around 900 high-altitude aircraft overflights of electrified clouds over 17 years. The overflights include a wide geographical sample of storms over land and ocean, with and without lightning, and with positive (i.e., upward-directed) and negative current. Peak electric field, with lightning transients removed, ranged from -1.0 kV m(sup -1) to 16. kV m(sup -1), with mean (median) of 0.9 kV m(sup -1) (0.29 kV m(sup -1)). Total conductivity at flight altitude ranged from 0.6 pS m(sup -1) to 3.6 pS m(sup -1), with mean and median of 2.2 pS m(sup -1). Peak current densities ranged from -2.0 nA m(sup -2) to 33.0 nA m(sup -2) with mean (median) of 1.9 nA m(sup -2) (0.6 nA m(sup -2)). Total upward current flow from storms in our dataset ranged from -1.3 to 9.4 A. The mean current for storms with lightning is 1.6 A over ocean and 1.0 A over land. The mean current for electrified shower clouds (i.e. electrified storms without lightning) is 0.39 A for ocean and 0.13 A for land. About 78% (43%) of the land (ocean) storms have detectable lightning. Land storms have 2.8 times the mean flash rate as ocean storms (2.2 versus 0.8 flashes min(sup -1), respectively). Approximately 7% of the overflights had negative current. The mean and median currents for positive (negative) polarity storms are 1.0 and 0.35 A (-0.30 and -0.26 A). We found no regional or latitudinal-based patterns in our storm currents, nor support for simple scaling laws between cloud top height and lightning flash rate
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