66 resultados para Monte carlo simulation


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Little is known about the learning of the skills needed to perform ultrasound- or nerve stimulator-guided peripheral nerve blocks. The aim of this study was to compare the learning curves of residents trained in ultrasound guidance versus residents trained in nerve stimulation for axillary brachial plexus block. Ten residents with no previous experience with using ultrasound received ultrasound training and another ten residents with no previous experience with using nerve stimulation received nerve stimulation training. The novices' learning curves were generated by retrospective data analysis out of our electronic anaesthesia database. Individual success rates were pooled, and the institutional learning curve was calculated using a bootstrapping technique in combination with a Monte Carlo simulation procedure. The skills required to perform successful ultrasound-guided axillary brachial plexus block can be learnt faster and lead to a higher final success rate compared to nerve stimulator-guided axillary brachial plexus block.

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The present study was conducted to estimate the direct losses due to Neospora caninum in Swiss dairy cattle and to assess the costs and benefits of different potential control strategies. A Monte Carlo simulation spreadsheet module was developed to estimate the direct costs caused by N. caninum, with and without control strategies, and to estimate the costs of these control strategies in a financial analysis. The control strategies considered were "testing and culling of seropositive female cattle", "discontinued breeding with offspring from seropositive cows", "chemotherapeutical treatment of female offspring" and "vaccination of all female cattle". Each parameter in the module that was considered to be uncertain, was described using probability distributions. The simulations were run with 20,000 iterations over a time period of 25 years. The median annual losses due to N. caninum in the Swiss dairy cow population were estimated to be euro 9.7 million euros. All control strategies that required yearly serological testing of all cattle in the population produced high costs and thus were not financially profitable. Among the other control strategies, two showed benefit-cost ratios (BCR) >1 and positive net present values (NPV): "Discontinued breeding with offspring from seropositive cows" (BCR=1.29, NPV=25 million euros ) and "chemotherapeutical treatment of all female offspring" (BCR=2.95, NPV=59 million euros). In economic terms, the best control strategy currently available would therefore be "discontinued breeding with offspring from seropositive cows".

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Monte Carlo simulation was used to evaluate properties of a simple Bayesian MCMC analysis of the random effects model for single group Cormack-Jolly-Seber capture-recapture data. The MCMC method is applied to the model via a logit link, so parameters p, S are on a logit scale, where logit(S) is assumed to have, and is generated from, a normal distribution with mean μ and variance σ2 . Marginal prior distributions on logit(p) and μ were independent normal with mean zero and standard deviation 1.75 for logit(p) and 100 for μ ; hence minimally informative. Marginal prior distribution on σ2 was placed on τ2=1/σ2 as a gamma distribution with α=β=0.001 . The study design has 432 points spread over 5 factors: occasions (t) , new releases per occasion (u), p, μ , and σ . At each design point 100 independent trials were completed (hence 43,200 trials in total), each with sample size n=10,000 from the parameter posterior distribution. At 128 of these design points comparisons are made to previously reported results from a method of moments procedure. We looked at properties of point and interval inference on μ , and σ based on the posterior mean, median, and mode and equal-tailed 95% credibility interval. Bayesian inference did very well for the parameter μ , but under the conditions used here, MCMC inference performance for σ was mixed: poor for sparse data (i.e., only 7 occasions) or σ=0 , but good when there were sufficient data and not small σ .

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The aim of our study was to develop a modeling framework suitable to quantify the incidence, absolute number and economic impact of osteoporosis-attributable hip, vertebral and distal forearm fractures, with a particular focus on change over time, and with application to the situation in Switzerland from 2000 to 2020. A Markov process model was developed and analyzed by Monte Carlo simulation. A demographic scenario provided by the Swiss Federal Statistical Office and various Swiss and international data sources were used as model inputs. Demographic and epidemiologic input parameters were reproduced correctly, confirming the internal validity of the model. The proportion of the Swiss population aged 50 years or over will rise from 33.3% in 2000 to 41.3% in 2020. At the total population level, osteoporosis-attributable incidence will rise from 1.16 to 1.54 per 1,000 person-years in the case of hip fracture, from 3.28 to 4.18 per 1,000 person-years in the case of radiographic vertebral fracture, and from 0.59 to 0.70 per 1,000 person-years in the case of distal forearm fracture. Osteoporosis-attributable hip fracture numbers will rise from 8,375 to 11,353, vertebral fracture numbers will rise from 23,584 to 30,883, and distal forearm fracture numbers will rise from 4,209 to 5,186. Population-level osteoporosis-related direct medical inpatient costs per year will rise from 713.4 million Swiss francs (CHF) to CHF946.2 million. These figures correspond to 1.6% and 2.2% of Swiss health care expenditures in 2000. The modeling framework described can be applied to a wide variety of settings. It can be used to assess the impact of new prevention, diagnostic and treatment strategies. In Switzerland incidences of osteoporotic hip, vertebral and distal forearm fracture will rise by 33%, 27%, and 19%, respectively, between 2000 and 2020, if current prevention and treatment patterns are maintained. Corresponding absolute fracture numbers will rise by 36%, 31%, and 23%. Related direct medical inpatient costs are predicted to increase by 33%; however, this estimate is subject to uncertainty due to limited availability of input data.

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Background: Recently, Cipriani and colleagues examined the relative efficacy of 12 new-generation antidepressants on major depression using network meta-analytic methods. They found that some of these medications outperformed others in patient response to treatment. However, several methodological criticisms have been raised about network meta-analysis and Cipriani’s analysis in particular which creates the concern that the stated superiority of some antidepressants relative to others may be unwarranted. Materials and Methods: A Monte Carlo simulation was conducted which involved replicating Cipriani’s network metaanalysis under the null hypothesis (i.e., no true differences between antidepressants). The following simulation strategy was implemented: (1) 1000 simulations were generated under the null hypothesis (i.e., under the assumption that there were no differences among the 12 antidepressants), (2) each of the 1000 simulations were network meta-analyzed, and (3) the total number of false positive results from the network meta-analyses were calculated. Findings: Greater than 7 times out of 10, the network meta-analysis resulted in one or more comparisons that indicated the superiority of at least one antidepressant when no such true differences among them existed. Interpretation: Based on our simulation study, the results indicated that under identical conditions to those of the 117 RCTs with 236 treatment arms contained in Cipriani et al.’s meta-analysis, one or more false claims about the relative efficacy of antidepressants will be made over 70% of the time. As others have shown as well, there is little evidence in these trials that any antidepressant is more effective than another. The tendency of network meta-analyses to generate false positive results should be considered when conducting multiple comparison analyses.

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Oxygen-isotope variations were analyzed on bulk samples of shallow-water lake marl from Gerzensee, Switzerland, in order to evaluate major and minor climatic oscillations during the late-glacial. To highlight the overall signature of the Gerzensee δ18O record, δ18O records of four parallel sediment cores were first correlated by synchronizing major isotope shifts and pollen abundances. Then the records were stacked with a weighting depending on the differing sampling resolution. To develop a precise chronology, the δ18O-stack was then correlated with the NGRIP δ18O record applying a Monte Carlo simulation, relying on the assumption that the shifts in δ18O were climate-driven and synchronous in both archives. The established chronology on the GICC05 time scale is the basis for (1) comparing the δ18O changes recorded in Gerzensee with observed climatic and environmental fluctuations over the whole North Atlantic region, and (2) comparing sedimentological and biological changes during the rapid warming with smaller climatic variations during the Bølling/Allerød period. The δ18O record of Gerzensee is characterized by two major isotope shifts at the onset and at the termination of the Bølling/Allerød warm period, as well as four intervening negative shifts labeled GI-1e2, d, c2, and b, which show a shift of one third to one fourth of the major δ18O shifts at the beginning and end of the Bølling/Allerød. Despite some inconsistency in terminology, these oscillations can be observed in various climatic proxies over wide regions in the North Atlantic region, especially in reconstructed colder temperatures, and they seem to be caused by hemispheric climatic variations.

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The uncertainty on the calorimeter energy response to jets of particles is derived for the ATLAS experiment at the Large Hadron Collider (LHC). First, the calorimeter response to single isolated charged hadrons is measured and compared to the Monte Carlo simulation using proton-proton collisions at centre-of-mass energies of root s = 900 GeV and 7 TeV collected during 2009 and 2010. Then, using the decay of K-s and Lambda particles, the calorimeter response to specific types of particles (positively and negatively charged pions, protons, and anti-protons) is measured and compared to the Monte Carlo predictions. Finally, the jet energy scale uncertainty is determined by propagating the response uncertainty for single charged and neutral particles to jets. The response uncertainty is 2-5 % for central isolated hadrons and 1-3 % for the final calorimeter jet energy scale.

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The inclusive jet cross-section has been measured in proton-proton collisions at root s = 2.76 TeV in a dataset corresponding to an integrated luminosity of 0.20 pb(-1) collected with the ATLAS detector at the Large Hadron Collider in 2011. Jets are identified using the anti-k(t) algorithm with two radius parameters of 0.4 and 0.6. The inclusive jet double-differential cross-section is presented as a function of the jet transverse momentum p(T) and jet rapidity y, covering a range of 20 <= p(T) < 430 GeV and vertical bar y vertical bar < 4.4. The ratio of the cross-section to the inclusive jet cross-section measurement at root s = 7 TeV, published by the ATLAS Collaboration, is calculated as a function of both transverse momentum and the dimensionless quantity x(T) = 2p(T)/root s, in bins of jet rapidity. The systematic uncertainties on the ratios are significantly reduced due to the cancellation of correlated uncertainties in the two measurements. Results are compared to the prediction from next-to-leading order perturbative QCD calculations corrected for non-perturbative effects, and next-to-leading order Monte Carlo simulation. Furthermore, the ATLAS jet cross-section measurements at root s = 2.76 TeV and root s = 7 TeV are analysed within a framework of next-to-leading order perturbative QCD calculations to determine parton distribution functions of the proton, taking into account the correlations between the measurements.

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The measurement of the jet energy resolution is presented using data recorded with the ATLAS detector in proton-proton collisions at root s = 7 TeV. The sample corresponds to an integrated luminosity of 35 pb(-1). Jets are reconstructed from energy deposits measured by the calorimeters and calibrated using different jet calibration schemes. The jet energy resolution is measured with two different in situ methods which are found to be in agreement within uncertainties. The total uncertainties on these measurements range from 20 % to 10 % for jets within vertical bar y vertical bar < 2.8 and with transverse momenta increasing from 30 GeV to 500 GeV. Overall, the Monte Carlo simulation of the jet energy resolution agrees with the data within 10 %.

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Results from the nuclear recoil calibration of the XENON100 dark matter detector installed underground at the Laboratori Nazionali del Gran Sasso, Italy are presented. Data from measurements with an external AmB(241)e neutron source are compared with a detailed Monte Carlo simulation which is used to extract the energy-dependent charge-yield Q(y) and relative scintillation efficiency L-eff. A very good level of absolute spectral matching is achieved in both observable signal channels-scintillation S1 and ionization S2-along with agreement in the two-dimensional particle discrimination space. The results confirm the validity of the derived signal acceptance in earlier reported dark matter searches of the XENON100 experiment.

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Stochastische Modelle sind bei der Bewertung von Schadensbeträgen für Versicherungen von besonderer Bedeutung. Das Buch gibt eine Einführung in die dabei verwendeten Modelle für kleine und große Schadensbeträge wie auch in die stochastische Prozesse der aktuariellen Risikotheorie (Zählprozesse und Poisson-Prozess). Zentrales Thema ist die Analyse der Ruinwahrscheinlichkeit, wobei exakte Berechnungsmethoden, asymptotische Approximationen und numerische Algorithmen wie Monte Carlo-Simulation und schnelle Fourier-Transformation vorgestellt werden. Ein Appendix mit wichtigen Resultaten der Wahrscheinlichkeitstheorie erleichtert die Lektüre dieses Buches.

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We herein present a patient undergoing selective internal radiation therapy with an almost normal lung shunt fraction of 11.5 %, developing histologically proven radiation pneumonitis. Due to a predominance of pulmonary consolidations in the right lower lung and its proximity to a large liver metastases located in the dome of the right liver lobe a Monte Carlo simulation was performed to estimate the effect of direct irradiation of the lung parenchyma. According to our calculations direct irradiation seems negligible and RP is almost exclusively due to ectopic draining of radioactive spheres.

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Double-differential dijet cross-sections measured in pp collisions at the LHC with a 7TeV centre-of-mass energy are presented as functions of dijet mass and half the rapidity separation of the two highest-pT jets. These measurements are obtained using data corresponding to an integrated luminosity of 4.5 fb−1, recorded by the ATLAS detector in 2011. The data are corrected for detector effects so that cross-sections are presented at the particle level. Cross-sections are measured up to 5TeV dijet mass using jets reconstructed with the anti-kt algorithm for values of the jet radius parameter of 0.4 and 0.6. The cross-sections are compared with next-to-leading-order perturbative QCD calculations by NLOJet++ corrected to account for non-perturbative effects. Comparisons with POWHEG predictions, using a next-to-leading-order matrix element calculation interfaced to a partonshower Monte Carlo simulation, are also shown. Electroweak effects are accounted for in both cases. The quantitative comparison of data and theoretical predictions obtained using various parameterizations of the parton distribution functions is performed using a frequentist method. In general, good agreement with data is observed for the NLOJet++ theoretical predictions when using the CT10, NNPDF2.1 and MSTW 2008 PDF sets. Disagreement is observed when using the ABM11 and HERAPDF1.5 PDF sets for some ranges of dijet mass and half the rapidity separation. An example setting a lower limit on the compositeness scale for a model of contact interactions is presented, showing that the unfolded results can be used to constrain contributions to dijet production beyond that predicted by the Standard Model.

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Long-term electrocardiogram (ECG) often suffers from relevant noise. Baseline wander in particular is pronounced in ECG recordings using dry or esophageal electrodes, which are dedicated for prolonged registration. While analog high-pass filters introduce phase distortions, reliable offline filtering of the baseline wander implies a computational burden that has to be put in relation to the increase in signal-to-baseline ratio (SBR). Here we present a graphics processor unit (GPU) based parallelization method to speed up offline baseline wander filter algorithms, namely the wavelet, finite, and infinite impulse response, moving mean, and moving median filter. Individual filter parameters were optimized with respect to the SBR increase based on ECGs from the Physionet database superimposed to auto-regressive modeled, real baseline wander. A Monte-Carlo simulation showed that for low input SBR the moving median filter outperforms any other method but negatively affects ECG wave detection. In contrast, the infinite impulse response filter is preferred in case of high input SBR. However, the parallelized wavelet filter is processed 500 and 4 times faster than these two algorithms on the GPU, respectively, and offers superior baseline wander suppression in low SBR situations. Using a signal segment of 64 mega samples that is filtered as entire unit, wavelet filtering of a 7-day high-resolution ECG is computed within less than 3 seconds. Taking the high filtering speed into account, the GPU wavelet filter is the most efficient method to remove baseline wander present in long-term ECGs, with which computational burden can be strongly reduced.

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The decomposition technique introduced by Blinder (1973) and Oaxaca (1973) is widely used to study outcome differences between groups. For example, the technique is commonly applied to the analysis of the gender wage gap. However, despite the procedure's frequent use, very little attention has been paid to the issue of estimating the sampling variances of the decomposition components. We therefore suggest an approach that introduces consistent variance estimators for several variants of the decomposition. The accuracy of the new estimators under ideal conditions is illustrated with the results of a Monte Carlo simulation. As a second check, the estimators are compared to bootstrap results obtained using real data. In contrast to previously proposed statistics, the new method takes into account the extra variation imposed by stochastic regressors.