120 resultados para Bayesian probing
Resumo:
We propose a scheme to probe quantum coherence in the state of a nanocantilever based on its magnetic coupling (mediated by a magnetic tip) with a spinor Bose Einstein condensate (BEC). By mapping the BEC into a rotor, its coupling with the cantilever results in a gyroscopic motion whose properties depend on the state of the cantilever: the dynamics of one of the components of the rotor angular momentum turns out to be strictly related to the presence of quantum coherence in the state of the cantilever. We also suggest a detection scheme relying on Faraday rotation, which produces only a very small back-action on the BEC and is thus suitable for a continuous detection of the cantilever's dynamics.
Resumo:
The paper introduces a new modeling approach that represents the waiting times in an accident and emergency (A&E) department in a UK based national health service (NHS) hospital. The technique uses Bayesian networks to capture the heterogeneity of arriving patients by representing how patient covariates interact to influence their waiting times in the department. Such waiting times have been reviewed by the NHS as a means of investigating the efficiency of A&E departments (emergency rooms) and how they operate. As a result activity targets are now established based on the patient total waiting times with much emphasis on trolley waits.
Resumo:
We propose a complete application capable of tracking multiple objects in an environment monitored by multiple cameras. The system has been specially developed to be applied to sport games, and it has been evaluated in a real association-football stadium. Each target is tracked using a local importance-sampling particle filter in each camera, but the final estimation is made by combining information from the other cameras using a modified unscented Kalman filter algorithm. Multicamera integration enables us to compensate for bad measurements or occlusions in some cameras thanks to the other views it offers. The final algorithm results in a more accurate system with a lower failure rate. (C) 2009 Society of Photo-Optical Instrumentation Engineers. [DOI: 10.1117/1.3114605]
Resumo:
In this paper, we present a Bayesian approach to estimate a chromosome and a disorder network from the Online Mendelian Inheritance in Man (OMIM) database. In contrast to other approaches, we obtain statistic rather than deterministic networks enabling a parametric control in the uncertainty of the underlying disorder-disease gene associations contained in the OMIM, on which the networks are based. From a structural investigation of the chromosome network, we identify three chromosome subgroups that reflect architectural differences in chromosome-disorder associations that are predictively exploitable for a functional analysis of diseases.
Resumo:
A benefit function transfer obtains estimates of willingness-to-pay (WTP) for the evaluation of a given policy at a site by combining existing information from different study sites. This has the advantage that more efficient estimates are obtained, but it relies on the assumption that the heterogeneity between sites is appropriately captured in the benefit transfer model. A more expensive alternative to estimate WTP is to analyze only data from the policy site in question while ignoring information from other sites. We make use of the fact that these two choices can be viewed as a model selection problem and extend the set of models to allow for the hypothesis that the benefit function is only applicable to a subset of sites. We show how Bayesian model averaging (BMA) techniques can be used to optimally combine information from all models. The Bayesian algorithm searches for the set of sites that can form the basis for estimating a benefit function and reveals whether such information can be transferred to new sites for which only a small data set is available. We illustrate the method with a sample of 42 forests from U.K. and Ireland. We find that BMA benefit function transfer produces reliable estimates and can increase about 8 times the information content of a small sample when the forest is 'poolable'. © 2008 Elsevier Inc. All rights reserved.
Resumo:
The relationships among organisms and their surroundings can be of immense complexity. To describe and understand an ecosystem as a tangled bank, multiple ways of interaction and their effects have to be considered, such as predation, competition, mutualism and facilitation. Understanding the resulting interaction networks is a challenge in changing environments, e.g. to predict knock-on effects of invasive species and to understand how climate change impacts biodiversity. The elucidation of complex ecological systems with their interactions will benefit enormously from the development of new machine learning tools that aim to infer the structure of interaction networks from field data. In the present study, we propose a novel Bayesian regression and multiple changepoint model (BRAM) for reconstructing species interaction networks from observed species distributions. The model has been devised to allow robust inference in the presence of spatial autocorrelation and distributional heterogeneity. We have evaluated the model on simulated data that combines a trophic niche model with a stochastic population model on a 2-dimensional lattice, and we have compared the performance of our model with L1-penalized sparse regression (LASSO) and non-linear Bayesian networks with the BDe scoring scheme. In addition, we have applied our method to plant ground coverage data from the western shore of the Outer Hebrides with the objective to infer the ecological interactions. (C) 2012 Elsevier B.V. All rights reserved.
Resumo:
Rhizosphere microorganisms play an important role in soil carbon flow, through turnover of root exudates, but there is little information on which organisms are actively involved or on the influence of environmental conditions on active communities. In this study, a (CO2)-C-13 pulse labelling field experiment was performed in an upland grassland soil, followed by RNA-stable isotope probing (SIP) analysis, to determine the effect of liming on the structure of the rhizosphere microbial community metabolizing root exudates. The lower limit of detection for SIP was determined in soil samples inoculated with a range of concentrations of C-13-labelled Pseudomonas fluorescens and was found to lie between 10(5) and 10(6) cells per gram of soil. The technique was capable of detecting microbial communities actively assimilating root exudates derived from recent photo-assimilate in the field. Denaturing gradient gel electrophoresis (DGGE) profiles of bacteria, archaea and fungi derived from fractions obtained from caesium trifluoroacetate (CsTFA) density gradient ultracentrifugation indicated that active communities in limed soils were more complex than those in unlimed soils and were more active in utilization of recently exuded C-13 compounds. In limed soils, the majority of the community detected by standard RNA-DGGE analysis appeared to be utilizing root exudates. In unlimed soils, DGGE profiles from C-12 and C-13 RNA fractions differed, suggesting that a proportion of the active community was utilizing other sources of organic carbon. These differences may reflect differences in the amount of root exudation under the different conditions.
Resumo:
Recently, Bayesian statistical software has been developed for age-depth modeling (wiggle-match dating) of sequences of densely spaced radiocarbon dates from peat cores. The method is described in non-statistical terms, and is compared with an alternative method of chronological ordering of 14C dates. Case studies include the dating of the start of agriculture in the northeastern part of the Netherlands, and of a possible Hekla-3 tephra layer in the same country. We discuss future enhancements in Bayesian age modeling.
Resumo:
In order to assess qualitatively the ejecta geometry of stripped-envelope core-collapse supernovae (SNe), we investigate 98 late-time spectra of 39 objects, many of them previously unpublished. We perform a Gauss-fitting of the [O ] ??6300, 6364 feature in all spectra, with the position, full width at half maximum and intensity of the ?6300 Gaussian as free parameters, and the ?6364 Gaussian added appropriately to account for the doublet nature of the [O ] feature. On the basis of the best-fitting parameters, the objects are organized into morphological classes, and we conclude that at least half of all Type Ib/c SNe must be aspherical. Bipolar jet models do not seem to be universally applicable, as we find too few symmetric double-peaked [O ] profiles. In some objects, the [O ] line exhibits a variety of shifted secondary peaks or shoulders, interpreted as blobs of matter ejected at high velocity and possibly accompanied by neutron-star kicks to assure momentum conservation. At phases earlier than ~200 d, a systematic blueshift of the [O ] ??6300, 6364 line centroids can be discerned. Residual opacity provides the most convincing explanation of this phenomenon, photons emitted on the rear side of the SN being scattered or absorbed on their way through the ejecta. Once modified to account for the doublet nature of the oxygen feature, the profile of Mg i] ?4571 at sufficiently late phases generally resembles that of [O ] ??6300, 6364, suggesting negligible contamination from other lines and confirming that O and Mg are similarly distributed within the ejecta. © 2009 RAS.