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Robust Predictions (robust + prediction)
Selected AbstractsRobust Predictions for Bilateral Contracting with ExternalitiesECONOMETRICA, Issue 3 2003Ilya Segal The paper studies bilateral contracting between one principal and N agents when each agent's utility depends on the principal's unobservable contracts with other agents. We show that allowing deviations to menu contracts from which the principal chooses bounds equilibrium outcomes in a wide class of bilateral contracting games without imposing ad hoc restrictions on the agents' beliefs. This bound yields, for example, competitive convergence as N ,, in environments in which an appropriately-defined notion of competitive equilibrium exists. We also examine the additional restrictions arising in two common bilateral contracting games: the "offer game" in which the principal makes simultaneous offers to the agents, and the "bidding game" in which the agents make simultaneous offers to the principal. [source] Design of a high-efficiency hydrofoil through the use of computational fluid dynamics and multiobjective optimizationAICHE JOURNAL, Issue 7 2009N. Spogis Abstract A computational fluid dynamics (CFD) model is proposed, based on ANSYS-CFX tools coupled to optimization models inside the commercial optimization software modeFRONTIER in order to obtain an optimal design of a high-efficiency impeller for solids suspension. The analysis of impeller shape performance was carried out using the shear-stress transport (SST) turbulence model with streamline curvature correction. This turbulence model combined the advantages of the ,,, and ,,, models, ensuring a proper relation between turbulent stress and turbulent kinetic energy, allowing an accurate and robust prediction of the impeller blade flow separation. The multiple frames of reference and the frozen rotor frame change models were used for the rotor/stator interaction inside the mixing vessel. The optimization procedure used seven design variables, two nonlinear constraints and two objective functions. The objective functions chosen (among many other possible options) to evaluate the impeller performance were the maximum solid distribution throughout the vessel (homogeneous suspension) reflected by a low variance between local solid concentration and average solid concentration inside the vessel and the higher pumping effectiveness, which was defined as the quotient of the flow and power numbers. The first objective function searches for impeller configurations able to provide good solid suspension, since it aims to achieve homogeneous suspension. The second objective function aims to reduce power consumption for a high-pumping capacity of the impeller. These criteria were considered enough to characterize the optimized impeller. Results indicated that the optimized impeller presented an increase of the pumping impeller capacity and homogeneous solid suspension with low-power consumption, especially when compared with the PBT 45° impeller. © 2009 American Institute of Chemical Engineers AIChE J, 2009 [source] The dust-eliminated shape of quasar spectra in the near-infrared: a hidden part of the big blue bumpMONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, Issue 2 2005Makoto Kishimoto ABSTRACT The near-infrared shape of the big blue bump component in quasar spectra has till now been essentially unknown. It usually cannot be observed directly, due to the strong hot dust emission that dominates quasar spectra longward of ,1 ,m. However, this is quite an important part of the spectrum theoretically. At least bare-disc models provide quite a robust prediction for the overall continuum shape in the near-infrared. Self-gravity should become important in the outer, near-infrared-emitting regions of the putative disc, possibly leaving a signature of disc truncation in the near-infrared. We propose here that this important part of the spectrum can be revealed for the first time by observing polarized flux from normal quasars. At least in some polarized quasars, the emission lines are all unpolarized and so the polarized flux should originate interior to the broad-line region, and therefore also interior to the dust-emitting region. This can then be used to eliminate the dust emission. We present the results of near-infrared polarimetry for three such quasars (Ton202, 4C 37.43 and B2 1208+32). The data for Ton202 have the highest signal-to-noise ratio, and the near-infrared polarized flux in this case is measured to have quite a blue shape, F,,,+0.42±0.29, intriguingly consistent with the simple multitemperature blackbody, bare-disc prediction of ,+1/3. All these data, although still with quite low signal-to-noise ratio for the other two objects, demonstrate the unique potential of the technique with future better data. We also present similar data for other quasars and radio galaxies, and briefly discuss the nature of the polarization. [source] How does the knowledge about the spatial distribution of Iberian dung beetle species accumulate over time?DIVERSITY AND DISTRIBUTIONS, Issue 6 2007Jorge M. Lobo ABSTRACT Different distribution maps can be obtained for the same species if localities where species are present are mapped at different times. We analysed the accumulation of information over time for a group of dung beetle species in the Iberian Peninsula. To do this, we used all available information about the distribution of the group as well as data on selected species to examine if the process of discovery of species distribution has occurred in a climatically or spatially structured fashion. Our results show the existence of a well-defined pattern of temporal growth in distributional information; due to this, the date of capture of each specimen can be explained by the environmental and spatial variables associated to the collection sites. We hypothesize that such temporal biases could be the rule rather than the exception in most distributional data. These biases could affect the weighting of environmental factors that influence species distributions, as well as the accuracy of predictive distribution models. Systematic surveys should be a priority for the description of species geographical ranges in order to make robust predictions about the consequences of habitat and climate change for their persistence and conservation. [source] Integrating physiology, population dynamics and climate to make multi-scale predictions for the spread of an invasive insect: the Argentine ant at Haleakala National Park, HawaiiECOGRAPHY, Issue 1 2010Stephen Hartley Mechanistic models for predicting species' distribution patterns present particular advantages and challenges relative to models developed from statistical correlations between distribution and climate. They can be especially useful for predicting the range of invasive species whose distribution has not yet reached equilibrium. Here, we illustrate how a physiological model of development for the invasive Argentine ant can be connected to differences in micro-site suitability, population dynamics and climatic gradients; processes operating at quite different spatial scales. Our study is located in the subalpine shrubland of Haleakala National Park, Hawaii, where the spread of Argentine ants Linepithema humile has been documented for the past twenty-five years. We report four main results. First, at a microsite level, the accumulation of degree-days recorded in potential ant nest sites under bare ground or rocks was significantly greater than under a groundcover of grassy vegetation. Second, annual degree-days measured where population boundaries have not expanded (456,521,degree-days), were just above the developmental requirements identified from earlier laboratory studies (445,degree-days above 15.9°C). Third, rates of population expansion showed a strong linear relationship with annual degree-days. Finally, an empirical relationship between soil degree-days and climate variables mapped at a broader scale predicts the potential for future range expansion of Argentine ants at Haleakala, particularly to the west of the lower colony and the east of the upper colony. Variation in the availability of suitable microsites, driven by changes in vegetation cover and ultimately climate, provide a hierarchical understanding of the distribution of Argentine ants close to their cold-wet limit of climatic tolerances. We conclude that the integration of physiology, population dynamics and climate mapping holds much promise for making more robust predictions about the potential spread of invasive species. [source] Characterization of marine isoprene-degrading communitiesENVIRONMENTAL MICROBIOLOGY, Issue 12 2009Laura Acuña Alvarez Summary Isoprene is a volatile and climate-altering hydrocarbon with an atmospheric concentration similar to that of methane. It is well established that marine algae produce isoprene; however, until now there was no specific information about marine isoprene sinks. Here we demonstrate isoprene consumption in samples from temperate and tropical marine and coastal environments, and furthermore show that the most rapid degradation of isoprene coincides with the highest rates of isoprene production in estuarine sediments. Isoprene-degrading enrichment cultures, analysed by denaturing gradient gel electrophoresis and 454 pyrosequencing of the 16S rRNA gene and by culturing, were generally dominated by Actinobacteria, but included other groups such as Alphaproteobacteria and Bacteroidetes, previously not known to degrade isoprene. In contrast to specialist methane-oxidizing bacteria, cultivated isoprene degraders were nutritionally versatile, and nearly all of them were able to use n -alkanes as a source of carbon and energy. We therefore tested and showed that the ubiquitous marine hydrocarbon-degrader, Alcanivorax borkumensis, could also degrade isoprene. A mixture of the isolates consumed isoprene emitted from algal cultures, confirming that isoprene can be metabolized at low, environmentally relevant concentrations, and suggesting that, in the absence of spilled petroleum hydrocarbons, algal production of isoprene could maintain viable populations of hydrocarbon-degrading microbes. This discovery of a missing marine sink for isoprene is the first step in obtaining more robust predictions of its flux, and suggests that algal-derived isoprene provides an additional source of carbon for diverse microbes in the oceans. [source] Multivariate calibration of hyperspectral ,-ray energy spectra for proximal soil sensingEUROPEAN JOURNAL OF SOIL SCIENCE, Issue 1 2007R. A. Viscarra Rossel Summary The development of proximal soil sensors to collect fine-scale soil information for environmental monitoring, modelling and precision agriculture is vital. Conventional soil sampling and laboratory analyses are time-consuming and expensive. In this paper we look at the possibility of calibrating hyperspectral ,-ray energy spectra to predict various surface and subsurface soil properties. The spectra were collected with a proximal, on-the-go ,-ray spectrometer. We surveyed two geographically and physiographically different fields in New South Wales, Australia, and collected hyperspectral ,-ray data consisting of 256 energy bands at more than 20 000 sites in each field. Bootstrap aggregation with partial least squares regression (or bagging-PLSR) was used to calibrate the ,-ray spectra of each field for predictions of selected soil properties. However, significant amounts of pre-processing were necessary to expose the correlations between the ,-ray spectra and the soil data. We first filtered the spectra spatially using local kriging, then further de-noised, normalized and detrended them. The resulting bagging-PLSR models of each field were tested using leave-one-out cross-validation. Bagging-PLSR provided robust predictions of clay, coarse sand and Fe contents in the 0,15 cm soil layer and pH and coarse sand contents in the 15,50 cm soil layer. Furthermore, bagging-PLSR provided us with a measure of the uncertainty of predictions. This study is apparently the first to use a multivariate calibration technique with on-the-go proximal ,-ray spectrometry. Proximally sensed ,-ray spectrometry proved to be a useful tool for predicting soil properties in different soil landscapes. [source] The continuous smooth hockey stick: a newly proposed spawner-recruitment modelJOURNAL OF APPLIED ICHTHYOLOGY, Issue 6 2008R. Froese Summary Spawner-recruit relationships are important components of fisheries management. The two most widely used models have been criticized for unsatisfactory fits and biologically unreasonable extrapolations. A simple hockey stick model has been shown to provide more robust predictions, however, this model is not widely used, possibly because the abrupt change from density-dependence to density-independence is unrealistic and the piecewise model is difficult to fit. Here I present a continuous two-parameter model that resembles a smoothed hockey stick and provides parameter estimates similar to the piecewise hockey stick. The new model is easily parameterized with regular curve-fitting routines. [source] Genomic-scale comparison of sequence- and structure-based methods of function prediction: Does structure provide additional insight?PROTEIN SCIENCE, Issue 5 2001Jacquelyn S. Fetrow Abstract A function annotation method using the sequence-to-structure-to-function paradigm is applied to the identification of all disulfide oxidoreductases in the Saccharomyces cerevisiae genome. The method identifies 27 sequences as potential disulfide oxidoreductases. All previously known thioredoxins, glutaredoxins, and disulfide isomerases are correctly identified. Three of the 27 predictions are probable false-positives. Three novel predictions, which subsequently have been experimentally validated, are presented. Two additional novel predictions suggest a disulfide oxidoreductase regulatory mechanism for two subunits (OST3 and OST6) of the yeast oligosaccharyltransferase complex. Based on homology, this prediction can be extended to a potential tumor suppressor gene, N33, in humans, whose biochemical function was not previously known. Attempts to obtain a folded, active N33 construct to test the prediction were unsuccessful. The results show that structure prediction coupled with biochemically relevant structural motifs is a powerful method for the function annotation of genome sequences and can provide more detailed, robust predictions than function prediction methods that rely on sequence comparison alone. [source] | ||||||||||||||||