Posterior distributions for likelihood ratios in forensic science.

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van den Hout, Ardo; Alberink, Ivo

2016-09-01

Evaluation of evidence in forensic science is discussed using posterior distributions for likelihood ratios. Instead of eliminating the uncertainty by integrating (Bayes factor) or by conditioning on parameter values, uncertainty in the likelihood ratio is retained by parameter uncertainty derived from posterior distributions. A posterior distribution for a likelihood ratio can be summarised by the median and credible intervals. Using the posterior mean of the distribution is not recommended. An analysis of forensic data for body height estimation is undertaken. The posterior likelihood approach has been criticised both theoretically and with respect to applicability. This paper addresses the latter and illustrates an interesting application area. Copyright © 2016 The Chartered Society of Forensic Sciences. Published by Elsevier Ireland Ltd. All rights reserved.

Modeling of mouse eye and errors in ocular parameters affecting refractive state

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Bawa, Gurinder

Rodents eye are particularly used to study refractive error state of an eye and development of refractive eye. Genetic organization of rodents is similar to that of humans, which makes them interesting candidates to be researched upon. From rodents family mice models are encouraged over rats because of availability of genetically engineered models. Despite of extensive work that has been performed on mice and rat models, still no one is able to quantify an optical model, due to variability in the reported ocular parameters. In this Dissertation, we have extracted ocular parameters and generated schematics of eye from the raw data from School of Medicine, Detroit. In order to see how the rays would travel through an eye and the defects associated with an eye; ray tracing has been performed using ocular parameters. Finally we have systematically evaluated the contribution of various ocular parameters, such as radii of curvature of ocular surfaces, thicknesses of ocular components, and refractive indices of ocular refractive media, using variational analysis and a computational model of the rodent eye. Variational analysis revealed that variation in all the ocular parameters does affect the refractive status of the eye, but depending upon the magnitude of the impact those parameters are listed as critical or non critical. Variation in the depth of the vitreous chamber, thickness of the lens, radius of the anterior surface of the cornea, radius of the anterior surface of the lens, as well as refractive indices for the lens and vitreous, appears to have the largest impact on the refractive error and thus are categorized as critical ocular parameters. The radii of the posterior surfaces of the cornea and lens have much smaller contributions to the refractive state, while the radii of the anterior and posterior surfaces of the retina have no effect on the refractive error. These data provide the framework for further refinement of the optical models of the rat and mouse

Back to Normal! Gaussianizing posterior distributions for cosmological probes

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Schuhmann, Robert L.; Joachimi, Benjamin; Peiris, Hiranya V.

2014-05-01

We present a method to map multivariate non-Gaussian posterior probability densities into Gaussian ones via nonlinear Box-Cox transformations, and generalizations thereof. This is analogous to the search for normal parameters in the CMB, but can in principle be applied to any probability density that is continuous and unimodal. The search for the optimally Gaussianizing transformation amongst the Box-Cox family is performed via a maximum likelihood formalism. We can judge the quality of the found transformation a posteriori: qualitatively via statistical tests of Gaussianity, and more illustratively by how well it reproduces the credible regions. The method permits an analytical reconstruction of the posterior from a sample, e.g. a Markov chain, and simplifies the subsequent joint analysis with other experiments. Furthermore, it permits the characterization of a non-Gaussian posterior in a compact and efficient way. The expression for the non-Gaussian posterior can be employed to find analytic formulae for the Bayesian evidence, and consequently be used for model comparison.

Patient-specific parameter estimation in single-ventricle lumped circulation models under uncertainty

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Schiavazzi, Daniele E.; Baretta, Alessia; Pennati, Giancarlo; Hsia, Tain-Yen; Marsden, Alison L.

2017-01-01

Summary Computational models of cardiovascular physiology can inform clinical decision-making, providing a physically consistent framework to assess vascular pressures and flow distributions, and aiding in treatment planning. In particular, lumped parameter network (LPN) models that make an analogy to electrical circuits offer a fast and surprisingly realistic method to reproduce the circulatory physiology. The complexity of LPN models can vary significantly to account, for example, for cardiac and valve function, respiration, autoregulation, and time-dependent hemodynamics. More complex models provide insight into detailed physiological mechanisms, but their utility is maximized if one can quickly identify patient specific parameters. The clinical utility of LPN models with many parameters will be greatly enhanced by automated parameter identification, particularly if parameter tuning can match non-invasively obtained clinical data. We present a framework for automated tuning of 0D lumped model parameters to match clinical data. We demonstrate the utility of this framework through application to single ventricle pediatric patients with Norwood physiology. Through a combination of local identifiability, Bayesian estimation and maximum a posteriori simplex optimization, we show the ability to automatically determine physiologically consistent point estimates of the parameters and to quantify uncertainty induced by errors and assumptions in the collected clinical data. We show that multi-level estimation, that is, updating the parameter prior information through sub-model analysis, can lead to a significant reduction in the parameter marginal posterior variance. We first consider virtual patient conditions, with clinical targets generated through model solutions, and second application to a cohort of four single-ventricle patients with Norwood physiology. PMID:27155892

Bayesian Inference on the Memory Parameter for Gamma-Modulated Regression Models

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Plinio Andrade

2015-09-01

Full Text Available In this work, we propose a Bayesian methodology to make inferences for the memory parameter and other characteristics under non-standard assumptions for a class of stochastic processes. This class generalizes the Gamma-modulated process, with trajectories that exhibit long memory behavior, as well as decreasing variability as time increases. Different values of the memory parameter influence the speed of this decrease, making this heteroscedastic model very flexible. Its properties are used to implement an approximate Bayesian computation and MCMC scheme to obtain posterior estimates. We test and validate our method through simulations and real data from the big earthquake that occurred in 2010 in Chile.

HIV Model Parameter Estimates from Interruption Trial Data including Drug Efficacy and Reservoir Dynamics

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Luo, Rutao; Piovoso, Michael J.; Martinez-Picado, Javier; Zurakowski, Ryan

2012-01-01

Mathematical models based on ordinary differential equations (ODE) have had significant impact on understanding HIV disease dynamics and optimizing patient treatment. A model that characterizes the essential disease dynamics can be used for prediction only if the model parameters are identifiable from clinical data. Most previous parameter identification studies for HIV have used sparsely sampled data from the decay phase following the introduction of therapy. In this paper, model parameters are identified from frequently sampled viral-load data taken from ten patients enrolled in the previously published AutoVac HAART interruption study, providing between 69 and 114 viral load measurements from 3–5 phases of viral decay and rebound for each patient. This dataset is considerably larger than those used in previously published parameter estimation studies. Furthermore, the measurements come from two separate experimental conditions, which allows for the direct estimation of drug efficacy and reservoir contribution rates, two parameters that cannot be identified from decay-phase data alone. A Markov-Chain Monte-Carlo method is used to estimate the model parameter values, with initial estimates obtained using nonlinear least-squares methods. The posterior distributions of the parameter estimates are reported and compared for all patients. PMID:22815727

Comparison of sampling techniques for Bayesian parameter estimation

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Allison, Rupert; Dunkley, Joanna

2014-02-01

The posterior probability distribution for a set of model parameters encodes all that the data have to tell us in the context of a given model; it is the fundamental quantity for Bayesian parameter estimation. In order to infer the posterior probability distribution we have to decide how to explore parameter space. Here we compare three prescriptions for how parameter space is navigated, discussing their relative merits. We consider Metropolis-Hasting sampling, nested sampling and affine-invariant ensemble Markov chain Monte Carlo (MCMC) sampling. We focus on their performance on toy-model Gaussian likelihoods and on a real-world cosmological data set. We outline the sampling algorithms themselves and elaborate on performance diagnostics such as convergence time, scope for parallelization, dimensional scaling, requisite tunings and suitability for non-Gaussian distributions. We find that nested sampling delivers high-fidelity estimates for posterior statistics at low computational cost, and should be adopted in favour of Metropolis-Hastings in many cases. Affine-invariant MCMC is competitive when computing clusters can be utilized for massive parallelization. Affine-invariant MCMC and existing extensions to nested sampling naturally probe multimodal and curving distributions.

On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: an application of flexible sampling methods using neural networks

NARCIS (Netherlands)

L.F. Hoogerheide (Lennart); J.F. Kaashoek (Johan); H.K. van Dijk (Herman)

2005-01-01

textabstractLikelihoods and posteriors of instrumental variable regression models with strong endogeneity and/or weak instruments may exhibit rather non-elliptical contours in the parameter space. This may seriously affect inference based on Bayesian credible sets. When approximating such contours

Uncertainty in dual permeability model parameters for structured soils

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Arora, B.; Mohanty, B. P.; McGuire, J. T.

2012-01-01

Successful application of dual permeability models (DPM) to predict contaminant transport is contingent upon measured or inversely estimated soil hydraulic and solute transport parameters. The difficulty in unique identification of parameters for the additional macropore- and matrix-macropore interface regions, and knowledge about requisite experimental data for DPM has not been resolved to date. Therefore, this study quantifies uncertainty in dual permeability model parameters of experimental soil columns with different macropore distributions (single macropore, and low- and high-density multiple macropores). Uncertainty evaluation is conducted using adaptive Markov chain Monte Carlo (AMCMC) and conventional Metropolis-Hastings (MH) algorithms while assuming 10 out of 17 parameters to be uncertain or random. Results indicate that AMCMC resolves parameter correlations and exhibits fast convergence for all DPM parameters while MH displays large posterior correlations for various parameters. This study demonstrates that the choice of parameter sampling algorithms is paramount in obtaining unique DPM parameters when information on covariance structure is lacking, or else additional information on parameter correlations must be supplied to resolve the problem of equifinality of DPM parameters. This study also highlights the placement and significance of matrix-macropore interface in flow experiments of soil columns with different macropore densities. Histograms for certain soil hydraulic parameters display tri-modal characteristics implying that macropores are drained first followed by the interface region and then by pores of the matrix domain in drainage experiments. Results indicate that hydraulic properties and behavior of the matrix-macropore interface is not only a function of saturated hydraulic conductivity of the macroporematrix interface (Ksa) and macropore tortuosity (lf) but also of other parameters of the matrix and macropore domains.

NIMROD: a program for inference via a normal approximation of the posterior in models with random effects based on ordinary differential equations.

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Prague, Mélanie; Commenges, Daniel; Guedj, Jérémie; Drylewicz, Julia; Thiébaut, Rodolphe

2013-08-01

Models based on ordinary differential equations (ODE) are widespread tools for describing dynamical systems. In biomedical sciences, data from each subject can be sparse making difficult to precisely estimate individual parameters by standard non-linear regression but information can often be gained from between-subjects variability. This makes natural the use of mixed-effects models to estimate population parameters. Although the maximum likelihood approach is a valuable option, identifiability issues favour Bayesian approaches which can incorporate prior knowledge in a flexible way. However, the combination of difficulties coming from the ODE system and from the presence of random effects raises a major numerical challenge. Computations can be simplified by making a normal approximation of the posterior to find the maximum of the posterior distribution (MAP). Here we present the NIMROD program (normal approximation inference in models with random effects based on ordinary differential equations) devoted to the MAP estimation in ODE models. We describe the specific implemented features such as convergence criteria and an approximation of the leave-one-out cross-validation to assess the model quality of fit. In pharmacokinetics models, first, we evaluate the properties of this algorithm and compare it with FOCE and MCMC algorithms in simulations. Then, we illustrate NIMROD use on Amprenavir pharmacokinetics data from the PUZZLE clinical trial in HIV infected patients. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Can the human lumbar posterior columns be stimulated by transcutaneous spinal cord stimulation? A modeling study.

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Danner, Simon M; Hofstoetter, Ursula S; Ladenbauer, Josef; Rattay, Frank; Minassian, Karen

2011-03-01

Stimulation of different spinal cord segments in humans is a widely developed clinical practice for modification of pain, altered sensation, and movement. The human lumbar cord has become a target for modification of motor control by epidural and, more recently, by transcutaneous spinal cord stimulation. Posterior columns of the lumbar spinal cord represent a vertical system of axons and when activated can add other inputs to the motor control of the spinal cord than stimulated posterior roots. We used a detailed three-dimensional volume conductor model of the torso and the McIntyre-Richard-Grill axon model to calculate the thresholds of axons within the posterior columns in response to transcutaneous lumbar spinal cord stimulation. Superficially located large-diameter posterior column fibers with multiple collaterals have a threshold of 45.4 V, three times higher than posterior root fibers (14.1 V). With the stimulation strength needed to activate posterior column axons, posterior root fibers of large and small diameters as well as anterior root fibers are coactivated. The reported results inform on these threshold differences, when stimulation is applied to the posterior structures of the lumbar cord at intensities above the threshold of large-diameter posterior root fibers. © 2011, Copyright the Authors. Artificial Organs © 2011, International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Efficient Bayesian parameter estimation with implicit sampling and surrogate modeling for a vadose zone hydrological problem

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Liu, Y.; Pau, G. S. H.; Finsterle, S.

2015-12-01

Parameter inversion involves inferring the model parameter values based on sparse observations of some observables. To infer the posterior probability distributions of the parameters, Markov chain Monte Carlo (MCMC) methods are typically used. However, the large number of forward simulations needed and limited computational resources limit the complexity of the hydrological model we can use in these methods. In view of this, we studied the implicit sampling (IS) method, an efficient importance sampling technique that generates samples in the high-probability region of the posterior distribution and thus reduces the number of forward simulations that we need to run. For a pilot-point inversion of a heterogeneous permeability field based on a synthetic ponded infiltration experiment simu­lated with TOUGH2 (a subsurface modeling code), we showed that IS with linear map provides an accurate Bayesian description of the parameterized permeability field at the pilot points with just approximately 500 forward simulations. We further studied the use of surrogate models to improve the computational efficiency of parameter inversion. We implemented two reduced-order models (ROMs) for the TOUGH2 forward model. One is based on polynomial chaos expansion (PCE), of which the coefficients are obtained using the sparse Bayesian learning technique to mitigate the "curse of dimensionality" of the PCE terms. The other model is Gaussian process regression (GPR) for which different covariance, likelihood and inference models are considered. Preliminary results indicate that ROMs constructed based on the prior parameter space perform poorly. It is thus impractical to replace this hydrological model by a ROM directly in a MCMC method. However, the IS method can work with a ROM constructed for parameters in the close vicinity of the maximum a posteriori probability (MAP) estimate. We will discuss the accuracy and computational efficiency of using ROMs in the implicit sampling procedure

Posterior Probability Matching and Human Perceptual Decision Making.

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Richard F Murray

2015-06-01

Full Text Available Probability matching is a classic theory of decision making that was first developed in models of cognition. Posterior probability matching, a variant in which observers match their response probabilities to the posterior probability of each response being correct, is being used increasingly often in models of perception. However, little is known about whether posterior probability matching is consistent with the vast literature on vision and hearing that has developed within signal detection theory. Here we test posterior probability matching models using two tools from detection theory. First, we examine the models' performance in a two-pass experiment, where each block of trials is presented twice, and we measure the proportion of times that the model gives the same response twice to repeated stimuli. We show that at low performance levels, posterior probability matching models give highly inconsistent responses across repeated presentations of identical trials. We find that practised human observers are more consistent across repeated trials than these models predict, and we find some evidence that less practised observers more consistent as well. Second, we compare the performance of posterior probability matching models on a discrimination task to the performance of a theoretical ideal observer that achieves the best possible performance. We find that posterior probability matching is very inefficient at low-to-moderate performance levels, and that human observers can be more efficient than is ever possible according to posterior probability matching models. These findings support classic signal detection models, and rule out a broad class of posterior probability matching models for expert performance on perceptual tasks that range in complexity from contrast discrimination to symmetry detection. However, our findings leave open the possibility that inexperienced observers may show posterior probability matching behaviour, and our methods

Morphological parameters for implantation of the screwless spring loop dynamic posterior spinous process stabilizing system.

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Song, Geun Soo; Lee, Yeon Soo

2015-07-01

This study aimed to quantify morphological characteristics of the posterior lumbar spinous process, which may affect stable implantation of screwless wire spring loops. Virtual implantations of a screwless wire spring loop onto pairs of lumbar spinous processes were performed for computed tomography (CT)-derived three-dimensional vertebral models of 40 Korean subjects. Morphological parameters of lumbar vertebrae 1 through 5 (L1-L5) were measured with regard to bone-implant interference. In males, the transspinous process fixation lengths decreased from 57.8±3.0mm to 48.8±3.2mm as the lumbar joints descend from L1-L2 to L4-L5, with those in females about 4.1±0.4mm shorter (pprocess and the greatest (8.1±2.2mm) for the L4 upper spinous process; this was 1.0±10.3mm less than that for males at corresponding levels (p>0.05). The ratio of the spinous process clenched thickness to the transspinous fixation length increased from 0.133±0.016 to 0.196±0.076 for the upper spinous processes as the lumbar joints descend. The ratio of the spinous process clenched thickness to the transspinous fixation length varies, depending on gender and whether the clenched level is the upper or lower spinous process. These parameters related to the clenching fixation stability should be considered in development and implantations of the screwless wire spring loop. Copyright © 2015 Elsevier GmbH. All rights reserved.

Forecasts of non-Gaussian parameter spaces using Box-Cox transformations

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Joachimi, B.; Taylor, A. N.

2011-09-01

Forecasts of statistical constraints on model parameters using the Fisher matrix abound in many fields of astrophysics. The Fisher matrix formalism involves the assumption of Gaussianity in parameter space and hence fails to predict complex features of posterior probability distributions. Combining the standard Fisher matrix with Box-Cox transformations, we propose a novel method that accurately predicts arbitrary posterior shapes. The Box-Cox transformations are applied to parameter space to render it approximately multivariate Gaussian, performing the Fisher matrix calculation on the transformed parameters. We demonstrate that, after the Box-Cox parameters have been determined from an initial likelihood evaluation, the method correctly predicts changes in the posterior when varying various parameters of the experimental setup and the data analysis, with marginally higher computational cost than a standard Fisher matrix calculation. We apply the Box-Cox-Fisher formalism to forecast cosmological parameter constraints by future weak gravitational lensing surveys. The characteristic non-linear degeneracy between matter density parameter and normalization of matter density fluctuations is reproduced for several cases, and the capabilities of breaking this degeneracy by weak-lensing three-point statistics is investigated. Possible applications of Box-Cox transformations of posterior distributions are discussed, including the prospects for performing statistical data analysis steps in the transformed Gaussianized parameter space.

Assessment of structural model and parameter uncertainty with a multi-model system for soil water balance models

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Michalik, Thomas; Multsch, Sebastian; Frede, Hans-Georg; Breuer, Lutz

2016-04-01

Water for agriculture is strongly limited in arid and semi-arid regions and often of low quality in terms of salinity. The application of saline waters for irrigation increases the salt load in the rooting zone and has to be managed by leaching to maintain a healthy soil, i.e. to wash out salts by additional irrigation. Dynamic simulation models are helpful tools to calculate the root zone water fluxes and soil salinity content in order to investigate best management practices. However, there is little information on structural and parameter uncertainty for simulations regarding the water and salt balance of saline irrigation. Hence, we established a multi-model system with four different models (AquaCrop, RZWQM, SWAP, Hydrus1D/UNSATCHEM) to analyze the structural and parameter uncertainty by using the Global Likelihood and Uncertainty Estimation (GLUE) method. Hydrus1D/UNSATCHEM and SWAP were set up with multiple sets of different implemented functions (e.g. matric and osmotic stress for root water uptake) which results in a broad range of different model structures. The simulations were evaluated against soil water and salinity content observations. The posterior distribution of the GLUE analysis gives behavioral parameters sets and reveals uncertainty intervals for parameter uncertainty. Throughout all of the model sets, most parameters accounting for the soil water balance show a low uncertainty, only one or two out of five to six parameters in each model set displays a high uncertainty (e.g. pore-size distribution index in SWAP and Hydrus1D/UNSATCHEM). The differences between the models and model setups reveal the structural uncertainty. The highest structural uncertainty is observed for deep percolation fluxes between the model sets of Hydrus1D/UNSATCHEM (~200 mm) and RZWQM (~500 mm) that are more than twice as high for the latter. The model sets show a high variation in uncertainty intervals for deep percolation as well, with an interquartile range (IQR) of

Computation of posterior distribution in Bayesian analysis – application in an intermittently used reliability system

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V. S.S. Yadavalli

2002-09-01

Full Text Available Bayesian estimation is presented for the stationary rate of disappointments, D∞, for two models (with different specifications of intermittently used systems. The random variables in the system are considered to be independently exponentially distributed. Jeffreys’ prior is assumed for the unknown parameters in the system. Inference about D∞ is being restrained in both models by the complex and non-linear definition of D∞. Monte Carlo simulation is used to derive the posterior distribution of D∞ and subsequently the highest posterior density (HPD intervals. A numerical example where Bayes estimates and the HPD intervals are determined illustrates these results. This illustration is extended to determine the frequentistical properties of this Bayes procedure, by calculating covering proportions for each of these HPD intervals, assuming fixed values for the parameters.

A Novel Rodent Model of Posterior Ischemic Optic Neuropathy

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Wang, Yan; Brown, Dale P.; Duan, Yuanli; Kong, Wei; Watson, Brant D.; Goldberg, Jeffrey L.

2014-01-01

Objectives To develop a reliable, reproducible rat model of posterior ischemic optic neuropathy (PION) and study the cellular responses in the optic nerve and retina. Methods Posterior ischemic optic neuropathy was induced in adult rats by photochemically induced ischemia. Retinal and optic nerve vasculature was examined by fluorescein isothiocyanate–dextran extravasation. Tissue sectioning and immunohistochemistry were used to investigate the pathologic changes. Retinal ganglion cell survival at different times after PION induction, with or without neurotrophic application, was quantified by fluorogold retrograde labeling. Results Optic nerve injury was confirmed after PION induction, including local vascular leakage, optic nerve edema, and cavernous degeneration. Immunostaining data revealed microglial activation and focal loss of astrocytes, with adjacent astrocytic hypertrophy. Up to 23%, 50%, and 70% retinal ganglion cell loss was observed at 1 week, 2 weeks, and 3 weeks, respectively, after injury compared with a sham control group. Experimental treatment by brain-derived neurotrophic factor and ciliary neurotrophic factor remarkably prevented retinal ganglion cell loss in PION rats. At 3 weeks after injury, more than 40% of retinal ganglion cells were saved by the application of neurotrophic factors. Conclusions Rat PION created by photochemically induced ischemia is a reproducible and reliable animal model for mimicking the key features of human PION. Clinical Relevance The correspondence between the features of this rat PION model to those of human PION makes it an ideal model to study the pathophysiologic course of the disease, most of which remains to be elucidated. Furthermore, it provides an optimal model for testing therapeutic approaches for optic neuropathies. PMID:23544206

Lumped-parameter models

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Ibsen, Lars Bo; Liingaard, M.

2006-12-15

A lumped-parameter model represents the frequency dependent soil-structure interaction of a massless foundation placed on or embedded into an unbounded soil domain. In this technical report the steps of establishing a lumped-parameter model are presented. Following sections are included in this report: Static and dynamic formulation, Simple lumped-parameter models and Advanced lumped-parameter models. (au)

Femoral Component External Rotation Affects Knee Biomechanics: A Computational Model of Posterior-stabilized TKA.

Science.gov (United States)

Kia, Mohammad; Wright, Timothy M; Cross, Michael B; Mayman, David J; Pearle, Andrew D; Sculco, Peter K; Westrich, Geoffrey H; Imhauser, Carl W

2018-01-01

The correct amount of external rotation of the femoral component during TKA is controversial because the resulting changes in biomechanical knee function associated with varying degrees of femoral component rotation are not well understood. We addressed this question using a computational model, which allowed us to isolate the biomechanical impact of geometric factors including bony shapes, location of ligament insertions, and implant size across three different knees after posterior-stabilized (PS) TKA. Using a computational model of the tibiofemoral joint, we asked: (1) Does external rotation unload the medial collateral ligament (MCL) and what is the effect on lateral collateral ligament tension? (2) How does external rotation alter tibiofemoral contact loads and kinematics? (3) Does 3° external rotation relative to the posterior condylar axis align the component to the surgical transepicondylar axis (sTEA) and what anatomic factors of the femoral condyle explain variations in maximum MCL tension among knees? We incorporated a PS TKA into a previously developed computational knee model applied to three neutrally aligned, nonarthritic, male cadaveric knees. The computational knee model was previously shown to corroborate coupled motions and ligament loading patterns of the native knee through a range of flexion. Implant geometries were virtually installed using hip-to-ankle CT scans through measured resection and anterior referencing surgical techniques. Collateral ligament properties were standardized across each knee model by defining stiffness and slack lengths based on the healthy population. The femoral component was externally rotated from 0° to 9° relative to the posterior condylar axis in 3° increments. At each increment, the knee was flexed under 500 N compression from 0° to 90° simulating an intraoperative examination. The computational model predicted collateral ligament forces, compartmental contact forces, and tibiofemoral internal/external and

Effect of posterior crown margin placement on gingival health.

Science.gov (United States)

Reitemeier, Bernd; Hänsel, Kristina; Walter, Michael H; Kastner, Christian; Toutenburg, Helge

2002-02-01

The clinical impact of posterior crown margin placement on gingival health has not been thoroughly quantified. This study evaluated the effect of posterior crown margin placement with multivariate analysis. Ten general dentists reviewed 240 patients with 480 metal-ceramic crowns in a prospective clinical trial. The alloy was randomly selected from 2 high gold, 1 low gold, and 1 palladium alloy. Variables were the alloy used, oral hygiene index score before treatment, location of crown margins at baseline, and plaque index and sulcus bleeding index scores recorded for restored and control teeth after 1 year. The effect of crown margin placement on sulcular bleeding and plaque accumulation was analyzed with regression models (Prisk of bleeding at intrasulcular posterior crown margins was approximately twice that at supragingival margins. Poor oral hygiene before treatment and plaque also were associated with sulcular bleeding. Facial sites exhibited a lower probability of sulcular bleeding than lingual surfaces. Type of alloy did not influence sulcular bleeding. In this study, placement of crown margins was one of several parameters that affected gingival health.

Biomechanical Effects of Posterior Condylar Offset and Posterior Tibial Slope on Quadriceps Force and Joint Contact Forces in Posterior-Stabilized Total Knee Arthroplasty

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Kyoung-Tak Kang

2017-01-01

Full Text Available This study aimed to determine the biomechanical effect of the posterior condylar offset (PCO and posterior tibial slope (PTS in posterior-stabilized (PS fixed-bearing total knee arthroplasty (TKA. We developed ±1, ±2, and ±3 mm PCO models in the posterior direction and −3°, 0°, 3°, and 6° PTS models using a previously validated FE model. The influence of changes in the PCO and PTS on the biomechanical effects under deep-knee-bend loading was investigated. The contact stress on the PE insert increased by 14% and decreased by 7% on average as the PCO increased and decreased, respectively, compared to the neutral position. In addition, the contact stress on post in PE insert increased by 18% on average as PTS increased from −3° to 6°. However, the contact stress on the patellar button decreased by 11% on average as PTS increased from −3° to 6° in all different PCO cases. The quadriceps force decreased by 14% as PTS increased from −3° to 6° in all PCO models. The same trend was found in patellar tendon force. Changes in PCO had adverse biomechanical effects whereas PTS increase had positive biomechanical effects. However, excessive PTS should be avoided to prevent knee instability and subsequent failure.

Convergence monitoring of Markov chains generated for inverse tracking of unknown model parameters in atmospheric dispersion

International Nuclear Information System (INIS)

Kim, Joo Yeon; Ryu, Hyung Joon; Jung, Gyu Hwan; Lee, Jai Ki

2011-01-01

The dependency within the sequential realizations in the generated Markov chains and their reliabilities are monitored by introducing the autocorrelation and the potential scale reduction factor (PSRF) by model parameters in the atmospheric dispersion. These two diagnostics have been applied for the posterior quantities of the release point and the release rate inferred through the inverse tracking of unknown model parameters for the Yonggwang atmospheric tracer experiment in Korea. The autocorrelations of model parameters are decreasing to low values approaching to zero with increase of lag, resulted in decrease of the dependencies within the two sequential realizations. Their PSRFs are reduced to within 1.2 and the adequate simulation number recognized from these results. From these two convergence diagnostics, the validation of Markov chains generated have been ensured and PSRF then is especially suggested as the efficient tool for convergence monitoring for the source reconstruction in atmospheric dispersion. (author)

Finite Element Modeling of the Posterior Eye in Microgravity

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Feola, Andrew; Raykin, Julia; Mulugeta, Lealem; Gleason, Rudolph; Myers, Jerry G.; Nelson, Emily S.; Samuels, Brian; Ethier, C. Ross

2015-01-01

Microgravity experienced during spaceflight affects astronauts in various ways, including weakened muscles and loss of bone density. Recently, visual impairment and intracranial pressure (VIIP) syndrome has become a major concern for space missions lasting longer than 30 days. Astronauts suffering from VIIP syndrome have changes in ocular anatomical and visual impairment that persist after returning to earth. It is hypothesized that a cephalad fluid shift in microgravity may increase the intracranial pressure (ICP), which leads to an altered biomechanical environment of the posterior globe and optic nerve sheath (ONS).Currently, there is a lack of knowledge of how elevated ICP may lead to vision impairment and connective tissue changes in VIIP. Our goal was to develop a finite element model to simulate the acute effects of elevated ICP on the posterior eye and optic nerve sheath. We used a finite element (FE) analysis approach to understand the response of the lamina cribrosa and optic nerve to the elevations in ICP thought to occur in microgravity and to identify which tissue components have the greatest impact on strain experienced by optic nerve head tissues.

Sensitivity of tumor motion simulation accuracy to lung biomechanical modeling approaches and parameters.

Science.gov (United States)

Tehrani, Joubin Nasehi; Yang, Yin; Werner, Rene; Lu, Wei; Low, Daniel; Guo, Xiaohu; Wang, Jing

2015-11-21

Finite element analysis (FEA)-based biomechanical modeling can be used to predict lung respiratory motion. In this technique, elastic models and biomechanical parameters are two important factors that determine modeling accuracy. We systematically evaluated the effects of lung and lung tumor biomechanical modeling approaches and related parameters to improve the accuracy of motion simulation of lung tumor center of mass (TCM) displacements. Experiments were conducted with four-dimensional computed tomography (4D-CT). A Quasi-Newton FEA was performed to simulate lung and related tumor displacements between end-expiration (phase 50%) and other respiration phases (0%, 10%, 20%, 30%, and 40%). Both linear isotropic and non-linear hyperelastic materials, including the neo-Hookean compressible and uncoupled Mooney-Rivlin models, were used to create a finite element model (FEM) of lung and tumors. Lung surface displacement vector fields (SDVFs) were obtained by registering the 50% phase CT to other respiration phases, using the non-rigid demons registration algorithm. The obtained SDVFs were used as lung surface displacement boundary conditions in FEM. The sensitivity of TCM displacement to lung and tumor biomechanical parameters was assessed in eight patients for all three models. Patient-specific optimal parameters were estimated by minimizing the TCM motion simulation errors between phase 50% and phase 0%. The uncoupled Mooney-Rivlin material model showed the highest TCM motion simulation accuracy. The average TCM motion simulation absolute errors for the Mooney-Rivlin material model along left-right, anterior-posterior, and superior-inferior directions were 0.80 mm, 0.86 mm, and 1.51 mm, respectively. The proposed strategy provides a reliable method to estimate patient-specific biomechanical parameters in FEM for lung tumor motion simulation.

A Bayesian posterior predictive framework for weighting ensemble regional climate models

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Y. Fan

2017-06-01

Full Text Available We present a novel Bayesian statistical approach to computing model weights in climate change projection ensembles in order to create probabilistic projections. The weight of each climate model is obtained by weighting the current day observed data under the posterior distribution admitted under competing climate models. We use a linear model to describe the model output and observations. The approach accounts for uncertainty in model bias, trend and internal variability, including error in the observations used. Our framework is general, requires very little problem-specific input, and works well with default priors. We carry out cross-validation checks that confirm that the method produces the correct coverage.

Parameter sensitivity analysis of a 1-D cold region lake model for land-surface schemes

Science.gov (United States)

Guerrero, José-Luis; Pernica, Patricia; Wheater, Howard; Mackay, Murray; Spence, Chris

2017-12-01

Lakes might be sentinels of climate change, but the uncertainty in their main feedback to the atmosphere - heat-exchange fluxes - is often not considered within climate models. Additionally, these fluxes are seldom measured, hindering critical evaluation of model output. Analysis of the Canadian Small Lake Model (CSLM), a one-dimensional integral lake model, was performed to assess its ability to reproduce diurnal and seasonal variations in heat fluxes and the sensitivity of simulated fluxes to changes in model parameters, i.e., turbulent transport parameters and the light extinction coefficient (Kd). A C++ open-source software package, Problem Solving environment for Uncertainty Analysis and Design Exploration (PSUADE), was used to perform sensitivity analysis (SA) and identify the parameters that dominate model behavior. The generalized likelihood uncertainty estimation (GLUE) was applied to quantify the fluxes' uncertainty, comparing daily-averaged eddy-covariance observations to the output of CSLM. Seven qualitative and two quantitative SA methods were tested, and the posterior likelihoods of the modeled parameters, obtained from the GLUE analysis, were used to determine the dominant parameters and the uncertainty in the modeled fluxes. Despite the ubiquity of the equifinality issue - different parameter-value combinations yielding equivalent results - the answer to the question was unequivocal: Kd, a measure of how much light penetrates the lake, dominates sensible and latent heat fluxes, and the uncertainty in their estimates is strongly related to the accuracy with which Kd is determined. This is important since accurate and continuous measurements of Kd could reduce modeling uncertainty.

A 3D finite element model to investigate prosthetic interface stresses of different posterior tibial slope.

Science.gov (United States)

Shen, Yi; Li, Xiaomiao; Fu, Xiaodong; Wang, Weili

2015-11-01

Posterior tibial slope that is created during proximal tibial resection in total knee arthroplasty has emerged as an important factor in the mechanics of the knee joint and the surgical outcome. But the ideal degree of posterior tibial slope for recovery of the knee joint function and preventions of complications remains controversial and should vary in different racial groups. The objective of this paper is to investigate the effects of posterior tibial slope on contact stresses in the tibial polyethylene component of total knee prostheses. Three-dimensional finite element analysis was used to calculate contact stresses in tibial polyethylene component of total knee prostheses subjected to a compressive load. The 3D finite element model of total knee prosthesis was constructed from the images produced by 3D scanning technology. Stresses in tibial polyethylene component were calculated with four different posterior tibial slopes (0°, 3°, 6° and 9°). The 3D finite element model of total knee prosthesis we presented was well validated. We found that the stress distribution in the polythene as evaluated by the distributions of the von Mises stress, the maximum principle stress, the minimum principle stress and the Cpress were more uniform with 3° and 6° posterior tibial slopes than with 0° and 9° posterior tibial slopes. Moreover, the peaks of the above stresses and trends of changes with increasing degree of knee flexion were more ideal with 3° and 6° posterior slopes. The results suggested that the tibial component inclination might be favourable to 7°-10° so far as the stress distribution is concerned. The range of the tibial component inclination also can decrease the wear of polyethylene. Chinese posterior tibial slope is bigger than in the West, and the current domestic use of prostheses is imported from the West, so their demands to tilt back bone cutting can lead to shorten the service life of prostheses; this experiment result is of important

Fourier analysis algorithm for the posterior corneal keratometric data: clinical usefulness in keratoconus.

Science.gov (United States)

Sideroudi, Haris; Labiris, Georgios; Georgantzoglou, Kimon; Ntonti, Panagiota; Siganos, Charalambos; Kozobolis, Vassilios

2017-07-01

To develop an algorithm for the Fourier analysis of posterior corneal videokeratographic data and to evaluate the derived parameters in the diagnosis of Subclinical Keratoconus (SKC) and Keratoconus (KC). This was a cross-sectional, observational study that took place in the Eye Institute of Thrace, Democritus University, Greece. Eighty eyes formed the KC group, 55 eyes formed the SKC group while 50 normal eyes populated the control group. A self-developed algorithm in visual basic for Microsoft Excel performed a Fourier series harmonic analysis for the posterior corneal sagittal curvature data. The algorithm decomposed the obtained curvatures into a spherical component, regular astigmatism, asymmetry and higher order irregularities for averaged central 4 mm and for each individual ring separately (1, 2, 3 and 4 mm). The obtained values were evaluated for their diagnostic capacity using receiver operating curves (ROC). Logistic regression was attempted for the identification of a combined diagnostic model. Significant differences were detected in regular astigmatism, asymmetry and higher order irregularities among groups. For the SKC group, the parameters with high diagnostic ability (AUC > 90%) were the higher order irregularities, the asymmetry and the regular astigmatism, mainly in the corneal periphery. Higher predictive accuracy was identified using diagnostic models that combined the asymmetry, regular astigmatism and higher order irregularities in averaged 3and 4 mm area (AUC: 98.4%, Sensitivity: 91.7% and Specificity:100%). Fourier decomposition of posterior Keratometric data provides parameters with high accuracy in differentiating SKC from normal corneas and should be included in the prompt diagnosis of KC. © 2017 The Authors Ophthalmic & Physiological Optics © 2017 The College of Optometrists.

Sensitivity of tumor motion simulation accuracy to lung biomechanical modeling approaches and parameters

International Nuclear Information System (INIS)

Tehrani, Joubin Nasehi; Wang, Jing; Yang, Yin; Werner, Rene; Lu, Wei; Low, Daniel; Guo, Xiaohu

2015-01-01

Finite element analysis (FEA)-based biomechanical modeling can be used to predict lung respiratory motion. In this technique, elastic models and biomechanical parameters are two important factors that determine modeling accuracy. We systematically evaluated the effects of lung and lung tumor biomechanical modeling approaches and related parameters to improve the accuracy of motion simulation of lung tumor center of mass (TCM) displacements. Experiments were conducted with four-dimensional computed tomography (4D-CT). A Quasi-Newton FEA was performed to simulate lung and related tumor displacements between end-expiration (phase 50%) and other respiration phases (0%, 10%, 20%, 30%, and 40%). Both linear isotropic and non-linear hyperelastic materials, including the neo-Hookean compressible and uncoupled Mooney–Rivlin models, were used to create a finite element model (FEM) of lung and tumors. Lung surface displacement vector fields (SDVFs) were obtained by registering the 50% phase CT to other respiration phases, using the non-rigid demons registration algorithm. The obtained SDVFs were used as lung surface displacement boundary conditions in FEM. The sensitivity of TCM displacement to lung and tumor biomechanical parameters was assessed in eight patients for all three models. Patient-specific optimal parameters were estimated by minimizing the TCM motion simulation errors between phase 50% and phase 0%. The uncoupled Mooney–Rivlin material model showed the highest TCM motion simulation accuracy. The average TCM motion simulation absolute errors for the Mooney–Rivlin material model along left-right, anterior–posterior, and superior–inferior directions were 0.80 mm, 0.86 mm, and 1.51 mm, respectively. The proposed strategy provides a reliable method to estimate patient-specific biomechanical parameters in FEM for lung tumor motion simulation. (paper)

Oracle convergence rate of posterior under projection prior and Bayesian model selection

NARCIS (Netherlands)

Babenko, A.; Belitser, E.N.

2010-01-01

We apply the Bayes approach to the problem of projection estimation of a signal observed in the Gaussian white noise model and we study the rate at which the posterior distribution concentrates about the true signal from the space ℓ2 as the information in observations tends to infinity. A benchmark

Oracle convergence rate of posterior under projection prior and Bayesian model selection

NARCIS (Netherlands)

Babenko, A.; Belitser, E.

2010-01-01

We apply the Bayes approach to the problem of projection estimation of a signal observed in the Gaussian white noise model and we study the rate at which the posterior distribution concentrates about the true signal from the space l2 as the information in observations tends to infinity. A benchmark

Late-onset Alzheimer disease genetic variants in posterior cortical atrophy and posterior AD.

Science.gov (United States)

Carrasquillo, Minerva M; Khan, Qurat ul Ain; Murray, Melissa E; Krishnan, Siddharth; Aakre, Jeremiah; Pankratz, V Shane; Nguyen, Thuy; Ma, Li; Bisceglio, Gina; Petersen, Ronald C; Younkin, Steven G; Dickson, Dennis W; Boeve, Bradley F; Graff-Radford, Neill R; Ertekin-Taner, Nilüfer

2014-04-22

To investigate association of genetic risk factors for late-onset Alzheimer disease (LOAD) with risk of posterior cortical atrophy (PCA), a syndrome of visual impairment with predominant Alzheimer disease (AD) pathology in posterior cortical regions, and with risk of "posterior AD" neuropathology. We assessed 81 participants with PCA diagnosed clinically and 54 with neuropathologic diagnosis of posterior AD vs 2,523 controls for association with 11 significant single nucleotide polymorphisms (SNPs) from published LOAD risk genome-wide association studies. There was highly significant association with APOE ε4 and increased risk of PCA (p = 0.0003, odds ratio [OR] = 3.17) and posterior AD (p = 1.11 × 10(-17), OR = 6.43). No other locus was significant after corrections for multiple testing, although rs11136000 near CLU (p = 0.019, OR = 0.60) and rs744373 near BIN1 (p = 0.025, OR = 1. 63) associated nominally significantly with posterior AD, and rs3851179 at the PICALM locus had significant association with PCA (p = 0.0003, OR = 2.84). ABCA7 locus SNP rs3764650, which was also tested under the recessive model because of Hardy-Weinberg disequilibrium, also had nominally significant association with PCA risk. The direction of association at APOE, CLU, and BIN1 loci was the same for participants with PCA and posterior AD. The effects for all SNPs, except rs3851179, were consistent with those for LOAD risk. We identified a significant effect for APOE and nominate CLU, BIN1, and ABCA7 as additional risk loci for PCA and posterior AD. Our findings suggest that at least some of the genetic risk factors for LOAD are shared with these atypical conditions and provide effect-size estimates for their future genetic studies.

A new training model for robot-assisted urethrovesical anastomosis and posterior muscle-fascial reconstruction: the Verona training technique.

Science.gov (United States)

Cacciamani, G; De Marco, V; Siracusano, S; De Marchi, D; Bizzotto, L; Cerruto, M A; Motton, G; Porcaro, A B; Artibani, W

2017-06-01

A training model is usually needed to teach robotic surgical technique successfully. In this way, an ideal training model should mimic as much as possible the "in vivo" procedure and allow several consecutive surgical simulations. The goal of this study was to create a "wet lab" model suitable for RARP training programs, providing the simulation of the posterior fascial reconstruction. The second aim was to compare the original "Venezuelan" chicken model described by Sotelo to our training model. Our training model consists of performing an anastomosis, reproducing the surgical procedure in "vivo" as in RARP, between proventriculus and the proximal portion of the esophagus. A posterior fascial reconstruction simulating Rocco's stitch is performed between the tissues located under the posterior surface of the esophagus and the tissue represented by the serosa of the proventriculus. From 2014 to 2015, during 6 different full-immersion training courses, thirty-four surgeons performed the urethrovesical anastomosis using our model and the Sotelo's one. After the training period, each surgeon was asked to fill out a non-validated questionnaire to perform an evaluation of the differences between the two training models. Our model was judged the best model, in terms of similarity with urethral tissue and similarity with the anatomic unit urethra-pelvic wall. Our training model as reported by all trainees is easily reproducible and anatomically comparable with the urethrovesical anastomosis as performed during radical prostatectomy in humans. It is suitable for performing posterior fascial reconstruction reported by Rocco. In this context, our surgical training model could be routinely proposed in all robotic training courses to develop specific expertise in urethrovesical anastomosis with the reproducibility of the Rocco stitch.

A new moving strategy for the sequential Monte Carlo approach in optimizing the hydrological model parameters

Science.gov (United States)

Zhu, Gaofeng; Li, Xin; Ma, Jinzhu; Wang, Yunquan; Liu, Shaomin; Huang, Chunlin; Zhang, Kun; Hu, Xiaoli

2018-04-01

Sequential Monte Carlo (SMC) samplers have become increasing popular for estimating the posterior parameter distribution with the non-linear dependency structures and multiple modes often present in hydrological models. However, the explorative capabilities and efficiency of the sampler depends strongly on the efficiency in the move step of SMC sampler. In this paper we presented a new SMC sampler entitled the Particle Evolution Metropolis Sequential Monte Carlo (PEM-SMC) algorithm, which is well suited to handle unknown static parameters of hydrologic model. The PEM-SMC sampler is inspired by the works of Liang and Wong (2001) and operates by incorporating the strengths of the genetic algorithm, differential evolution algorithm and Metropolis-Hasting algorithm into the framework of SMC. We also prove that the sampler admits the target distribution to be a stationary distribution. Two case studies including a multi-dimensional bimodal normal distribution and a conceptual rainfall-runoff hydrologic model by only considering parameter uncertainty and simultaneously considering parameter and input uncertainty show that PEM-SMC sampler is generally superior to other popular SMC algorithms in handling the high dimensional problems. The study also indicated that it may be important to account for model structural uncertainty by using multiplier different hydrological models in the SMC framework in future study.

Eliciting hyperparameters of prior distributions for the parameters of paired comparison models

Directory of Open Access Journals (Sweden)

Nasir Abbas

2013-02-01

Full Text Available Normal 0 false false false EN-US X-NONE AR-SA In the study of paired comparisons (PC, items may be ranked or issues may be prioritized through subjective assessment of certain judges. PC models are developed and then used to serve the purpose of ranking. The PC models may be studied through classical or Bayesian approach. Bayesian inference is a modern statistical technique used to draw conclusions about the population parameters. Its beauty lies in incorporating prior information about the parameters into the analysis in addition to current information (i.e. data. The prior and current information are formally combined to yield a posterior distribution about the population parameters, which is the work bench of the Bayesian statisticians. However, the problems the Bayesians face correspond to the selection and formal utilization of prior distribution. Once the type of prior distribution is decided to be used, the problem of estimating the parameters of the prior distribution (i.e. elicitation still persists. Different methods are devised to serve the purpose. In this study an attempt is made to use Minimum Chi-square (hence forth MCS for the elicitation purpose. Though it is a classical estimation technique, but is used here for the election purpose. The entire elicitation procedure is illustrated through a numerical data set.

Harnessing the theoretical foundations of the exponential and beta-Poisson dose-response models to quantify parameter uncertainty using Markov Chain Monte Carlo.

Science.gov (United States)

Schmidt, Philip J; Pintar, Katarina D M; Fazil, Aamir M; Topp, Edward

2013-09-01

Dose-response models are the essential link between exposure assessment and computed risk values in quantitative microbial risk assessment, yet the uncertainty that is inherent to computed risks because the dose-response model parameters are estimated using limited epidemiological data is rarely quantified. Second-order risk characterization approaches incorporating uncertainty in dose-response model parameters can provide more complete information to decisionmakers by separating variability and uncertainty to quantify the uncertainty in computed risks. Therefore, the objective of this work is to develop procedures to sample from posterior distributions describing uncertainty in the parameters of exponential and beta-Poisson dose-response models using Bayes's theorem and Markov Chain Monte Carlo (in OpenBUGS). The theoretical origins of the beta-Poisson dose-response model are used to identify a decomposed version of the model that enables Bayesian analysis without the need to evaluate Kummer confluent hypergeometric functions. Herein, it is also established that the beta distribution in the beta-Poisson dose-response model cannot address variation among individual pathogens, criteria to validate use of the conventional approximation to the beta-Poisson model are proposed, and simple algorithms to evaluate actual beta-Poisson probabilities of infection are investigated. The developed MCMC procedures are applied to analysis of a case study data set, and it is demonstrated that an important region of the posterior distribution of the beta-Poisson dose-response model parameters is attributable to the absence of low-dose data. This region includes beta-Poisson models for which the conventional approximation is especially invalid and in which many beta distributions have an extreme shape with questionable plausibility. © Her Majesty the Queen in Right of Canada 2013. Reproduced with the permission of the Minister of the Public Health Agency of Canada.

Quantifying Key Climate Parameter Uncertainties Using an Earth System Model with a Dynamic 3D Ocean

Science.gov (United States)

Olson, R.; Sriver, R. L.; Goes, M. P.; Urban, N.; Matthews, D.; Haran, M.; Keller, K.

2011-12-01

Climate projections hinge critically on uncertain climate model parameters such as climate sensitivity, vertical ocean diffusivity and anthropogenic sulfate aerosol forcings. Climate sensitivity is defined as the equilibrium global mean temperature response to a doubling of atmospheric CO2 concentrations. Vertical ocean diffusivity parameterizes sub-grid scale ocean vertical mixing processes. These parameters are typically estimated using Intermediate Complexity Earth System Models (EMICs) that lack a full 3D representation of the oceans, thereby neglecting the effects of mixing on ocean dynamics and meridional overturning. We improve on these studies by employing an EMIC with a dynamic 3D ocean model to estimate these parameters. We carry out historical climate simulations with the University of Victoria Earth System Climate Model (UVic ESCM) varying parameters that affect climate sensitivity, vertical ocean mixing, and effects of anthropogenic sulfate aerosols. We use a Bayesian approach whereby the likelihood of each parameter combination depends on how well the model simulates surface air temperature and upper ocean heat content. We use a Gaussian process emulator to interpolate the model output to an arbitrary parameter setting. We use Markov Chain Monte Carlo method to estimate the posterior probability distribution function (pdf) of these parameters. We explore the sensitivity of the results to prior assumptions about the parameters. In addition, we estimate the relative skill of different observations to constrain the parameters. We quantify the uncertainty in parameter estimates stemming from climate variability, model and observational errors. We explore the sensitivity of key decision-relevant climate projections to these parameters. We find that climate sensitivity and vertical ocean diffusivity estimates are consistent with previously published results. The climate sensitivity pdf is strongly affected by the prior assumptions, and by the scaling

Visual attention in posterior stroke

DEFF Research Database (Denmark)

Fabricius, Charlotte; Petersen, Anders; Iversen, Helle K

Objective: Impaired visual attention is common following strokes in the territory of the middle cerebral artery, particularly in the right hemisphere. However, attentional effects of more posterior lesions are less clear. The aim of this study was to characterize visual processing speed...... and apprehension span following posterior cerebral artery (PCA) stroke. We also relate these attentional parameters to visual word recognition, as previous studies have suggested that reduced visual speed and span may explain pure alexia. Methods: Nine patients with MR-verified focal lesions in the PCA......-territory (four left PCA; four right PCA; one bilateral, all >1 year post stroke) were compared to 25 controls using single case statistics. Visual attention was characterized by a whole report paradigm allowing for hemifield-specific speed and span measurements. We also characterized visual field defects...

Surgical revascularization of posterior coronary arteries without cardiopulomonary bypass

Directory of Open Access Journals (Sweden)

Lobo Filho J. Glauco

1999-01-01

Full Text Available OBJECTIVE: To assess the results observed during the early postoperative period in patients who had the posterior coronary arteries revascularized without cardiopulmonary bypass (CPB, in regard to the following parameters: age, sex,bypass grafts types, morbidity and mortality. METHODS: From January 1995 to June 1998, 673 patients underwent myocardial revascularization (MR. Of this total, 607 (90.20% MR procedures were performed without CPB. The posterior coronary arteries (PCA were revascularized in 298 (44.27% patients, 280 (93.95% without CPB. The age of the patients ranged from 37 to 88 years (mean, 61 years. The male gender predominated, with 198 men (70.7%. The revascularization of the posterior coronary arteries had the following distribution: diagonalis artery (31 patients, 10%; marginal branches of the circumflex artery (243 patients, 78.7%; posterior ventricular artery (4 patients, 1.3%; and posterior descending artery (31 patients, 10%. RESULTS: Procedure-related complications without death occurred in 7 cases, giving a morbidity of 2.5%. There were 11 deaths in the early postoperative period (mortality of 3.9%. CONCLUSION: Similarly to the anterior coronary arteries, the posterior coronary arteries may benefit from myocardial revascularization without CPB.

The mechanical consequence of failure of ossified union in attempted posterior spinal fusion. A canine model.

Science.gov (United States)

Stonecipher, T K; Vanderby, R; Sciammarella, C A; Lei, S S; Fisk, J R

1983-01-01

The mechanical behavior of pseudarthrosis in posterior spinal fusion was investigated. A canine model was developed in which an incompletely ossified posterior fusion mass was consistently produced. The spines were excised, and the motion segments were mechanically tested using a specially developed loading apparatus. Tests were performed to evaluate stiffness of the segments to loading with compression, torsion, and anterioposterior and lateral bending shear stiffness. Changes in other modes of loading were less consistent. The motion characteristics of the pseudarthrosis could not be predicted from the extent of the osseous defect noted on roentgenograms. These findings correlate clinically with the progression of curvature seen with pseudarthrosis in scoliosis surgery and the unpredictable results of pseudarthrosis in posterior fusion performed in treatment of degenerative disc disease.

Iterative importance sampling algorithms for parameter estimation

OpenAIRE

Morzfeld, Matthias; Day, Marcus S.; Grout, Ray W.; Pau, George Shu Heng; Finsterle, Stefan A.; Bell, John B.

2016-01-01

In parameter estimation problems one computes a posterior distribution over uncertain parameters defined jointly by a prior distribution, a model, and noisy data. Markov Chain Monte Carlo (MCMC) is often used for the numerical solution of such problems. An alternative to MCMC is importance sampling, which can exhibit near perfect scaling with the number of cores on high performance computing systems because samples are drawn independently. However, finding a suitable proposal distribution is ...

Posterior glenoid rim deficiency in recurrent (atraumatic) posterior shoulder instability

International Nuclear Information System (INIS)

Weishaupt, D.; Zanetti, M.; Hodler, J.; Nyffeler, R.W.; Gerber, C.

2000-01-01

Objective. To assess the shape of the posterior glenoid rim in patients with recurrent (atraumatic) posterior instability.Design and patients. CT examinations of 15 shoulders with recurrent (atraumatic) posterior instability were reviewed in masked fashion with regard to abnormalities of the glenoid shape, specifically of its posterior rim. The glenoid version was also assessed. The findings were compared with the findings in 15 shoulders with recurrent anterior shoulder instability and 15 shoulders without instability. For all patients, surgical correlation was available.Results. Fourteen of the 15 (93%) shoulders with recurrent (atraumatic) posterior shoulder instability had a deficiency of the posteroinferior glenoid rim. In patients with recurrent anterior instability or stable shoulders such deficiencies were less common (60% and 73%, respectively). The craniocaudal length of the deficiencies was largest in patients with posterior instability. When a posteroinferior deficiency with a craniocaudal length of 12 mm or more was defined as abnormal, sensitivity and specificity for diagnosing recurrent (atraumatic) posterior instability were 86.7% and 83.3%, respectively. There was a statistically significant difference in glenoid version between shoulders with posterior instability and stable shoulders (P=0.01).Conclusion. Recurrent (atraumatic) posterior shoulder instability should be considered in patients with a bony deficiency of the posteroinferior glenoid rim with a craniocaudal length of more than 12 mm. (orig.)

Magnetic resonance imaging textural evaluation of posterior cranial fossa tumors in childhood; Avaliacao textural por ressonancia magnetica dos tumores da fossa posterior em criancas

Energy Technology Data Exchange (ETDEWEB)

Santos, Joelson Alves dos; Costa, Maria Olivia Rodrigues da; Otaduy, Maria Concepcion Garcia; Lacerda, Maria Teresa Carvalho de; Leite, Claudia da Costa [Sao Paulo Univ., SP (Brazil). Faculdade de Medicina. Dept. de Radiologia]. E-mail: joelson_alves@ig.com.br; Matsushita, Hamilton [Sao Paulo Univ., SP (Brazil). Faculdade de Medicina. Dept. de Neurologia

2004-08-01

Objective: To distinguish healthy from pathological tissues in pediatric patients with posterior cranial fossa tumors using calculated textural parameters from magnetic resonance images. Materials And Methods: We evaluated 14 pediatric patients with posterior cranial fossa tumors using the software MaZda to define the texture parameters in selected regions of interest representing healthy and pathological tissues based on T2-weighted magnetic resonance images. Results: There was a statistically significant difference between normal and tumoral tissues as well as between supposedly normal tissues adjacent and distant from the tumoral lesion. Conclusion: Magnetic resonance textural evaluation is an useful tool for determining differences among various tissues, including tissues that appear apparently normal on visual analysis. (author)

Learn-as-you-go acceleration of cosmological parameter estimates

International Nuclear Information System (INIS)

Aslanyan, Grigor; Easther, Richard; Price, Layne C.

2015-01-01

Cosmological analyses can be accelerated by approximating slow calculations using a training set, which is either precomputed or generated dynamically. However, this approach is only safe if the approximations are well understood and controlled. This paper surveys issues associated with the use of machine-learning based emulation strategies for accelerating cosmological parameter estimation. We describe a learn-as-you-go algorithm that is implemented in the Cosmo++ code and (1) trains the emulator while simultaneously estimating posterior probabilities; (2) identifies unreliable estimates, computing the exact numerical likelihoods if necessary; and (3) progressively learns and updates the error model as the calculation progresses. We explicitly describe and model the emulation error and show how this can be propagated into the posterior probabilities. We apply these techniques to the Planck likelihood and the calculation of ΛCDM posterior probabilities. The computation is significantly accelerated without a pre-defined training set and uncertainties in the posterior probabilities are subdominant to statistical fluctuations. We have obtained a speedup factor of 6.5 for Metropolis-Hastings and 3.5 for nested sampling. Finally, we discuss the general requirements for a credible error model and show how to update them on-the-fly

Hip morphology predicts posterior hip impingement in a cadaveric model.

Science.gov (United States)

Morris, William Z; Fowers, Cody A; Weinberg, Douglas S; Millis, Michael B; Tu, Leigh-Anne; Liu, Raymond W

2018-05-01

Posterior hip impingement is a recently-identified cause of hip pain. The purpose of this study is to characterise posterior femoroacetabular and ischiofemoral impingement and identify its predisposing morphologic traits. Two hundred and six cadaveric hips were randomly selected and taken through controlled motion in two pure axes associated with posterior hip impingement: external rotation (through the mechanical axis) and adduction (coronal plane). The range of motion and location of impingement was noted for each specimen. Morphologic traits including femoral/acetabular version, and true neck-shaft angle (TNSA) were also measured. External rotation impingement occurred between the femoral neck and acetabulum in 83.0% of hips, and between the lesser trochanter and ischial tuberosity in 17.0%. Adduction impingement occurred between the lesser trochanter and ischial tuberosity in 78.6% of hips, and between the femoral neck and acetabulum in 21.4%. Multiple regression revealed that increased femoral/acetabular version predicted earlier external rotation and adduction impingement. Unstandardised betas ranging from -0.39 to -0.64 reflect that each degree of increased femoral/acetabular version individually accounts for a loss of external rotation or adduction of approximately half a degree before impingement ( p < 0.001 for each). Increased TNSA was associated with earlier adduction impingement only (unstandardised beta -0.35, p = 0.005). Relative femoral/acetabular anteversion was associated with earlier posterior hip impingement. Coxa valga was associated with earlier adduction impingement, but protective against external rotation impingement. These findings highlight the importance of monitoring correction during femoral/acetabular osteotomies, as overcorrection of retroversion may predispose to earlier posterior impingement.

Combined Estimation of Hydrogeologic Conceptual Model, Parameter, and Scenario Uncertainty with Application to Uranium Transport at the Hanford Site 300 Area

Energy Technology Data Exchange (ETDEWEB)

Meyer, Philip D.; Ye, Ming; Rockhold, Mark L.; Neuman, Shlomo P.; Cantrell, Kirk J.

2007-07-30

This report to the Nuclear Regulatory Commission (NRC) describes the development and application of a methodology to systematically and quantitatively assess predictive uncertainty in groundwater flow and transport modeling that considers the combined impact of hydrogeologic uncertainties associated with the conceptual-mathematical basis of a model, model parameters, and the scenario to which the model is applied. The methodology is based on a n extension of a Maximum Likelihood implementation of Bayesian Model Averaging. Model uncertainty is represented by postulating a discrete set of alternative conceptual models for a site with associated prior model probabilities that reflect a belief about the relative plausibility of each model based on its apparent consistency with available knowledge and data. Posterior model probabilities are computed and parameter uncertainty is estimated by calibrating each model to observed system behavior; prior parameter estimates are optionally included. Scenario uncertainty is represented as a discrete set of alternative future conditions affecting boundary conditions, source/sink terms, or other aspects of the models, with associated prior scenario probabilities. A joint assessment of uncertainty results from combining model predictions computed under each scenario using as weight the posterior model and prior scenario probabilities. The uncertainty methodology was applied to modeling of groundwater flow and uranium transport at the Hanford Site 300 Area. Eight alternative models representing uncertainty in the hydrogeologic and geochemical properties as well as the temporal variability were considered. Two scenarios represent alternative future behavior of the Columbia River adjacent to the site were considered. The scenario alternatives were implemented in the models through the boundary conditions. Results demonstrate the feasibility of applying a comprehensive uncertainty assessment to large-scale, detailed groundwater flow

Bayesian selection of misspecified models is overconfident and may cause spurious posterior probabilities for phylogenetic trees.

Science.gov (United States)

Yang, Ziheng; Zhu, Tianqi

2018-02-20

The Bayesian method is noted to produce spuriously high posterior probabilities for phylogenetic trees in analysis of large datasets, but the precise reasons for this overconfidence are unknown. In general, the performance of Bayesian selection of misspecified models is poorly understood, even though this is of great scientific interest since models are never true in real data analysis. Here we characterize the asymptotic behavior of Bayesian model selection and show that when the competing models are equally wrong, Bayesian model selection exhibits surprising and polarized behaviors in large datasets, supporting one model with full force while rejecting the others. If one model is slightly less wrong than the other, the less wrong model will eventually win when the amount of data increases, but the method may become overconfident before it becomes reliable. We suggest that this extreme behavior may be a major factor for the spuriously high posterior probabilities for evolutionary trees. The philosophical implications of our results to the application of Bayesian model selection to evaluate opposing scientific hypotheses are yet to be explored, as are the behaviors of non-Bayesian methods in similar situations.

Polarization and migration in the zebrafish posterior lateral line system.

Directory of Open Access Journals (Sweden)

Hildur Knutsdottir

2017-04-01

Full Text Available Collective cell migration plays an important role in development. Here, we study the posterior lateral line primordium (PLLP a group of about 100 cells, destined to form sensory structures, that migrates from head to tail in the zebrafish embryo. We model mutually inhibitory FGF-Wnt signalling network in the PLLP and link tissue subdivision (Wnt receptor and FGF receptor activity domains to receptor-ligand parameters. We then use a 3D cell-based simulation with realistic cell-cell adhesion, interaction forces, and chemotaxis. Our model is able to reproduce experimentally observed motility with leading cells migrating up a gradient of CXCL12a, and trailing (FGF receptor active cells moving actively by chemotaxis towards FGF ligand secreted by the leading cells. The 3D simulation framework, combined with experiments, allows an investigation of the role of cell division, chemotaxis, adhesion, and other parameters on the shape and speed of the PLLP. The 3D model demonstrates reasonable behaviour of control as well as mutant phenotypes.

Microanatomical bases for intraoperative division of the posterior communicating artery.

Science.gov (United States)

Gabrovsky, N

2002-11-01

Micro-anatomical parameters of the hypoplastic posterior communicating artery (PCoA) are assessed and compared with the micro-anatomical parameters of the adult type PCoA. Based on the results obtained, the safest place is proposed for PCoA division during basilar tip aneurysm surgery via the pterional route. In 35 human cadaver brains, red coloured latex was injected and micro-anatomical dissection was performed. Seventy PCoA were found. Adult type PCoA was found in 29 cases (41.43%) with mean length 12.58 mm. Reduction of the PCoA diameter from its anterior to its posterior third by up to 20% was found in 27% and by more than 20% in 10% of the cases. The mean perforating vessel number was 8.17, distributed in each third: 3.48, 2.90 and 1.79, respectively. A hypoplastic PCoA was found in 33 cases (47.14%) with mean length 16.09 mm. The PCoA's diameter reduction by up to 20% was found in 24% and by more in 27% of the cases. In 6% of the cases an extreme reduction by up to 70% was observed. The mean perforating vessel (PV) number was 8.82, distributed in each third: 3.18, 3.36 and 2.27, respectively. Hypoplastic PCoA tends to be longer and with a more distinct diameter reduction from the anterior to the posterior third than the adult type PCoA. The PV anatomical parameters are similar for both groups. The posterior third of the PCoA seems to be the area where the risk of perforating vessel damage is the least when performing intra-operative PCoA division.

Outcomes of Surgery for Posterior Polar Cataract Using Torsional Ultrasound

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Selçuk Sızmaz

2013-10-01

Full Text Available Purpose: The aim of this study is to report outcomes of surgery for posterior polar cataract using torsional ultrasound. Material and Method: Medical records of 26 eyes of 21 consecutive patients with posterior polar cataract who had cataract surgery using the torsional phacoemulsification were evaluated retrospectively. The surgical procedure used, phacoemulsification parameters, intraoperative complications, and postoperative visual outcome were recorded. Results: Of the 26 eyes, 24 (92.3% had small to medium posterior polar opacity. Two eyes had large opacity. All surgeries were performed using the torsional handpiece. Posterior capsule rupture occurred in 4 (15.3% eyes. The mean visual acuity improved significantly after surgery (p<0.001. The postoperative visual acuity was worse than 20/20 in 5 eyes. The cause of the low acuity was amblyopia. Discussion: Successful surgical results and good visual outcome can be achieved with phacoemulsification using the torsional handpiece. (Turk J Ophthalmol 2013; 43: 345-7

Prior and posterior probabilistic models of uncertainties in a model for producing voice

International Nuclear Information System (INIS)

Cataldo, Edson; Sampaio, Rubens; Soize, Christian

2010-01-01

The aim of this paper is to use Bayesian statistics to update a probability density function related to the tension parameter, which is one of the main parameters responsible for the changing of the fundamental frequency of a voice signal, generated by a mechanical/mathematical model for producing voiced sounds. We follow a parametric approach for stochastic modeling, which requires the adoption of random variables to represent the uncertain parameters present in the cited model. For each random variable, a probability density function is constructed using the Maximum Entropy Principle and the Monte Carlo method is used to generate voice signals as the output of the model. Then, a probability density function of the voice fundamental frequency is constructed. The random variables are fit to experimental data so that the probability density function of the fundamental frequency obtained by the model can be as near as possible of a probability density function obtained from experimental data. New values are obtained experimentally for the fundamental frequency and they are used to update the probability density function of the tension parameter, via Bayes's Theorem.

Oracle posterior rates in the White Noise Model

NARCIS (Netherlands)

Babenko, A.

2010-01-01

All the results about posterior rates obtained until now are related to the optimal (minimax) rates for the estimation problem over the corresponding nonparametric smoothness classes, i.e. of a global nature. In the meantime, a new local approach to optimality has been developed within the

Model parameter updating using Bayesian networks

International Nuclear Information System (INIS)

Treml, C.A.; Ross, Timothy J.

2004-01-01

This paper outlines a model parameter updating technique for a new method of model validation using a modified model reference adaptive control (MRAC) framework with Bayesian Networks (BNs). The model parameter updating within this method is generic in the sense that the model/simulation to be validated is treated as a black box. It must have updateable parameters to which its outputs are sensitive, and those outputs must have metrics that can be compared to that of the model reference, i.e., experimental data. Furthermore, no assumptions are made about the statistics of the model parameter uncertainty, only upper and lower bounds need to be specified. This method is designed for situations where a model is not intended to predict a complete point-by-point time domain description of the item/system behavior; rather, there are specific points, features, or events of interest that need to be predicted. These specific points are compared to the model reference derived from actual experimental data. The logic for updating the model parameters to match the model reference is formed via a BN. The nodes of this BN consist of updateable model input parameters and the specific output values or features of interest. Each time the model is executed, the input/output pairs are used to adapt the conditional probabilities of the BN. Each iteration further refines the inferred model parameters to produce the desired model output. After parameter updating is complete and model inputs are inferred, reliabilities for the model output are supplied. Finally, this method is applied to a simulation of a resonance control cooling system for a prototype coupled cavity linac. The results are compared to experimental data.

A three-step Maximum-A-Posterior probability method for InSAR data inversion of coseismic rupture with application to four recent large earthquakes in Asia

Science.gov (United States)

Sun, J.; Shen, Z.; Burgmann, R.; Liang, F.

2012-12-01

We develop a three-step Maximum-A-Posterior probability (MAP) method for coseismic rupture inversion, which aims at maximizing the a posterior probability density function (PDF) of elastic solutions of earthquake rupture. The method originates from the Fully Bayesian Inversion (FBI) and the Mixed linear-nonlinear Bayesian inversion (MBI) methods , shares the same a posterior PDF with them and keeps most of their merits, while overcoming its convergence difficulty when large numbers of low quality data are used and improving the convergence rate greatly using optimization procedures. A highly efficient global optimization algorithm, Adaptive Simulated Annealing (ASA), is used to search for the maximum posterior probability in the first step. The non-slip parameters are determined by the global optimization method, and the slip parameters are inverted for using the least squares method without positivity constraint initially, and then damped to physically reasonable range. This step MAP inversion brings the inversion close to 'true' solution quickly and jumps over local maximum regions in high-dimensional parameter space. The second step inversion approaches the 'true' solution further with positivity constraints subsequently applied on slip parameters using the Monte Carlo Inversion (MCI) technique, with all parameters obtained from step one as the initial solution. Then the slip artifacts are eliminated from slip models in the third step MAP inversion with fault geometry parameters fixed. We first used a designed model with 45 degree dipping angle and oblique slip, and corresponding synthetic InSAR data sets to validate the efficiency and accuracy of method. We then applied the method on four recent large earthquakes in Asia, namely the 2010 Yushu, China earthquake, the 2011 Burma earthquake, the 2011 New Zealand earthquake and the 2008 Qinghai, China earthquake, and compared our results with those results from other groups. Our results show the effectiveness of

Magnetic resonance imaging textural evaluation of posterior cranial fossa tumors in childhood

International Nuclear Information System (INIS)

Santos, Joelson Alves dos; Costa, Maria Olivia Rodrigues da; Otaduy, Maria Concepcion Garcia; Lacerda, Maria Teresa Carvalho de; Leite, Claudia da Costa; Matsushita, Hamilton

2004-01-01

Objective: To distinguish healthy from pathological tissues in pediatric patients with posterior cranial fossa tumors using calculated textural parameters from magnetic resonance images. Materials And Methods: We evaluated 14 pediatric patients with posterior cranial fossa tumors using the software MaZda to define the texture parameters in selected regions of interest representing healthy and pathological tissues based on T2-weighted magnetic resonance images. Results: There was a statistically significant difference between normal and tumoral tissues as well as between supposedly normal tissues adjacent and distant from the tumoral lesion. Conclusion: Magnetic resonance textural evaluation is an useful tool for determining differences among various tissues, including tissues that appear apparently normal on visual analysis. (author)

Comparison of different morphological parameters with duration of obstruction created experimentally in unilateral upper ureters: an animal model.

Science.gov (United States)

Panda, Shasanka Shekhar; Bajpai, Minu; Mallick, Saumyaranjan; Sharma, Mehar C

2014-01-01

The objective of the following study is to determine and to compare the different morphological parameters with duration of obstruction created experimentally in unilateral upper ureters of rats. Unilateral upper ureteric obstruction was created in 60 adult Wistar rats that were reversed after predetermined intervals. Rats were sacrificed and ipsilateral kidneys were subjected for analysis of morphological parameters such as renal height, cranio-caudal diameter, antero-posterior diameter, lateral diameter, volume of the pelvis and average cortical thickness: Renal height. Renal height and cranio-caudal diameter of renal pelvis after ipsilateral upper ureteric obstruction started rising as early as 7 days of creating obstruction and were affected earlier than antero-posterior and lateral diameter and also were reversed earlier than other parameters after reversal of obstruction. Renal cortical thickness and volume of the pelvis were affected after prolonged obstruction (> 3 weeks) and were the late parameters to be reversed after reversal of obstruction. Cranio-caudal diameter and renal height were the early morphological parameters to be affected and reversed after reversal of obstruction in experimentally created ipsilateral upper ureteric obstruction.

PARAMETER ESTIMATION IN BREAD BAKING MODEL

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Hadiyanto Hadiyanto

2012-05-01

Full Text Available Bread product quality is highly dependent to the baking process. A model for the development of product quality, which was obtained by using quantitative and qualitative relationships, was calibrated by experiments at a fixed baking temperature of 200°C alone and in combination with 100 W microwave powers. The model parameters were estimated in a stepwise procedure i.e. first, heat and mass transfer related parameters, then the parameters related to product transformations and finally product quality parameters. There was a fair agreement between the calibrated model results and the experimental data. The results showed that the applied simple qualitative relationships for quality performed above expectation. Furthermore, it was confirmed that the microwave input is most meaningful for the internal product properties and not for the surface properties as crispness and color. The model with adjusted parameters was applied in a quality driven food process design procedure to derive a dynamic operation pattern, which was subsequently tested experimentally to calibrate the model. Despite the limited calibration with fixed operation settings, the model predicted well on the behavior under dynamic convective operation and on combined convective and microwave operation. It was expected that the suitability between model and baking system could be improved further by performing calibration experiments at higher temperature and various microwave power levels.  Abstrak  PERKIRAAN PARAMETER DALAM MODEL UNTUK PROSES BAKING ROTI. Kualitas produk roti sangat tergantung pada proses baking yang digunakan. Suatu model yang telah dikembangkan dengan metode kualitatif dan kuantitaif telah dikalibrasi dengan percobaan pada temperatur 200oC dan dengan kombinasi dengan mikrowave pada 100 Watt. Parameter-parameter model diestimasi dengan prosedur bertahap yaitu pertama, parameter pada model perpindahan masa dan panas, parameter pada model transformasi, dan

Modelling of glucose-insulin-glucagon pharmacodynamics in man

DEFF Research Database (Denmark)

Wendt, Sabrina Lyngbye; Møller, Jan Kloppenborg; Haidar, A.

The purpose is to build a simulation model of the glucoregulatory system in man. We estimate individual human parameters of a physiological glucose-insulin-glucagon model. We report posterior probability distributions and correlations of model parameters....

Posterior consistency for Bayesian inverse problems through stability and regression results

International Nuclear Information System (INIS)

Vollmer, Sebastian J

2013-01-01

In the Bayesian approach, the a priori knowledge about the input of a mathematical model is described via a probability measure. The joint distribution of the unknown input and the data is then conditioned, using Bayes’ formula, giving rise to the posterior distribution on the unknown input. In this setting we prove posterior consistency for nonlinear inverse problems: a sequence of data is considered, with diminishing fluctuations around a single truth and it is then of interest to show that the resulting sequence of posterior measures arising from this sequence of data concentrates around the truth used to generate the data. Posterior consistency justifies the use of the Bayesian approach very much in the same way as error bounds and convergence results for regularization techniques do. As a guiding example, we consider the inverse problem of reconstructing the diffusion coefficient from noisy observations of the solution to an elliptic PDE in divergence form. This problem is approached by splitting the forward operator into the underlying continuum model and a simpler observation operator based on the output of the model. In general, these splittings allow us to conclude posterior consistency provided a deterministic stability result for the underlying inverse problem and a posterior consistency result for the Bayesian regression problem with the push-forward prior. Moreover, we prove posterior consistency for the Bayesian regression problem based on the regularity, the tail behaviour and the small ball probabilities of the prior. (paper)

Posterior microphthalmos pigmentary retinopathy syndrome.

Science.gov (United States)

Pehere, Niranjan; Jalali, Subhadra; Deshmukh, Himanshu; Kannabiran, Chitra

2011-04-01

Posterior Microphthalmos Pigmentary Retinopathy Syndrome (PMPRS). Posterior microphthalmos (PM) is a relatively infrequent type of microphthalmos where posterior segment is predominantly affected with normal anterior segment measurements. Herein, we report two siblings with posterior microphthalmos retinopathy syndrome with postulated autosomal recessive mode of inheritance. A 13-year-old child had PM and retinitis pigmentosa (RP) and his 7-year-old sister had PM, RP, and foveoschisis. The genetics of this syndrome and variable phenotype is discussed. Importance of being aware of posterior microphthalmos and its posterior segment associations is highlighted.

Posterior instrumentation, anterior column reconstruction with single posterior approach for treatment of pyogenic osteomyelitis of thoracic and lumbar spine.

Science.gov (United States)

Gorensek, M; Kosak, R; Travnik, L; Vengust, R

2013-03-01

Surgical treatment of thoracolumbar osteomyelitis consists of radical debridement, reconstruction of anterior column either with or without posterior stabilization. The objective of present study is to evaluate a case series of patients with osteomyelitis of thoracic and lumbar spine treated by single, posterior approach with posterior instrumentation and anterior column reconstruction. Seventeen patients underwent clinical and radiological evaluation pre and postoperatively with latest follow-up at 19 months (8-56 months) after surgery. Parameters assessed were site of infection, causative organism, angle of deformity, blood loss, duration of surgery, ICU stay, deformity correction, time to solid bony fusion, ambulatory status, neurologic status (ASIA impairment scale), and functional outcome (Kirkaldy-Willis criteria). Mean operating time was 207 min and average blood loss 1,150 ml. Patients spent 2 (1-4) days in ICU and were able to walk unaided 1.6 (1-2) days after surgery. Infection receded in all 17 patients postoperatively. Solid bony fusion occurred in 15 out of 17 patients (88 %) on average 6.3 months after surgery. Functional outcome was assessed as excellent or good in 82 % of cases. Average deformity correction was 8 (1-18) degrees, with loss of correction of 4 (0-19) degrees at final follow-up. Single, posterior approach addressing both columns poses safe alternative in treatment of pyogenic vertebral osteomyelitis of thoracic and lumbar spine. It proved to be less invasive resulting in faster postoperative recovery.

Robust estimation of hydrological model parameters

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A. Bárdossy

2008-11-01

Full Text Available The estimation of hydrological model parameters is a challenging task. With increasing capacity of computational power several complex optimization algorithms have emerged, but none of the algorithms gives a unique and very best parameter vector. The parameters of fitted hydrological models depend upon the input data. The quality of input data cannot be assured as there may be measurement errors for both input and state variables. In this study a methodology has been developed to find a set of robust parameter vectors for a hydrological model. To see the effect of observational error on parameters, stochastically generated synthetic measurement errors were applied to observed discharge and temperature data. With this modified data, the model was calibrated and the effect of measurement errors on parameters was analysed. It was found that the measurement errors have a significant effect on the best performing parameter vector. The erroneous data led to very different optimal parameter vectors. To overcome this problem and to find a set of robust parameter vectors, a geometrical approach based on Tukey's half space depth was used. The depth of the set of N randomly generated parameters was calculated with respect to the set with the best model performance (Nash-Sutclife efficiency was used for this study for each parameter vector. Based on the depth of parameter vectors, one can find a set of robust parameter vectors. The results show that the parameters chosen according to the above criteria have low sensitivity and perform well when transfered to a different time period. The method is demonstrated on the upper Neckar catchment in Germany. The conceptual HBV model was used for this study.

Echocardiographic Wall Motion Abnormality in Posterior Myocardial Infarction: The Diagnostic Value of Posterior Leads

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A Darehzereshki

2008-06-01

Full Text Available Background: For the purpose of ascertaining myocardial infarction (MI and ischemia, the sensitivity of the initial 12-lead ECG is inadequate. It is risky to diagnose posterior MI using only precordial reciprocal changes, since the other leads may be more optimally positioned for the identification of electrocardiographic changes. In this study, we evaluated the relationship between electrocardiography changes and wall motion abnormalities in patients with posterior MI for earlier and better diagnosis of posterior MI.Methods: In this prospective cross-sectional study, we enrolled patients with posterior MI who had come to the Emergency Department of Shariati Hospital with their first episode of chest pain. A 12-lead surface electrocardiogram using posterior leads (V7-V9 was performed for all participants. Patients with ST elevation >0.05 mV or pathologic Q wave in the posterior leads, as well as those with specific changes indicating posterior MI in V1-V2, were evaluated by echocardiography in terms of wall motion abnormalities. All data were analyzed using SPSS and p<0.05 were considered statistically significant.Results: Of a total 79 patients enrolled, 48 (60.8% were men, and the mean age was 57.35±8.22 years. Smoking (54.4% and diabetes (48% were the most prevalent risk factors. In the echocardiographic evaluation, all patients had wall motion abnormalities in the left ventricle and 19 patients (24.1% had wall motion abnormalities in the right ventricle. The most frequent segment with motion abnormality among the all patients was the mid-posterior. The posterior leads showed better positive predictive value than the anterior leads for posterior wall motion abnormality.Conclusion: Electrocardiography of the posterior leads in patients with acute chest pain can help in earlier diagnosis and in time treatment of posterior MI.

Photovoltaic module parameters acquisition model

Energy Technology Data Exchange (ETDEWEB)

Cibira, Gabriel, E-mail: cibira@lm.uniza.sk; Koščová, Marcela, E-mail: mkoscova@lm.uniza.sk

2014-09-01

Highlights: • Photovoltaic five-parameter model is proposed using Matlab{sup ®} and Simulink. • The model acquisits input sparse data matrix from stigmatic measurement. • Computer simulations lead to continuous I–V and P–V characteristics. • Extrapolated I–V and P–V characteristics are in hand. • The model allows us to predict photovoltaics exploitation in different conditions. - Abstract: This paper presents basic procedures for photovoltaic (PV) module parameters acquisition using MATLAB and Simulink modelling. In first step, MATLAB and Simulink theoretical model are set to calculate I–V and P–V characteristics for PV module based on equivalent electrical circuit. Then, limited I–V data string is obtained from examined PV module using standard measurement equipment at standard irradiation and temperature conditions and stated into MATLAB data matrix as a reference model. Next, the theoretical model is optimized to keep-up with the reference model and to learn its basic parameters relations, over sparse data matrix. Finally, PV module parameters are deliverable for acquisition at different realistic irradiation, temperature conditions as well as series resistance. Besides of output power characteristics and efficiency calculation for PV module or system, proposed model validates computing statistical deviation compared to reference model.

Photovoltaic module parameters acquisition model

International Nuclear Information System (INIS)

Cibira, Gabriel; Koščová, Marcela

2014-01-01

Highlights: • Photovoltaic five-parameter model is proposed using Matlab ® and Simulink. • The model acquisits input sparse data matrix from stigmatic measurement. • Computer simulations lead to continuous I–V and P–V characteristics. • Extrapolated I–V and P–V characteristics are in hand. • The model allows us to predict photovoltaics exploitation in different conditions. - Abstract: This paper presents basic procedures for photovoltaic (PV) module parameters acquisition using MATLAB and Simulink modelling. In first step, MATLAB and Simulink theoretical model are set to calculate I–V and P–V characteristics for PV module based on equivalent electrical circuit. Then, limited I–V data string is obtained from examined PV module using standard measurement equipment at standard irradiation and temperature conditions and stated into MATLAB data matrix as a reference model. Next, the theoretical model is optimized to keep-up with the reference model and to learn its basic parameters relations, over sparse data matrix. Finally, PV module parameters are deliverable for acquisition at different realistic irradiation, temperature conditions as well as series resistance. Besides of output power characteristics and efficiency calculation for PV module or system, proposed model validates computing statistical deviation compared to reference model

A practical method to assess model sensitivity and parameter uncertainty in C cycle models

Science.gov (United States)

Delahaies, Sylvain; Roulstone, Ian; Nichols, Nancy

2015-04-01

data streams or by considering longer observation windows no systematic analysis has been carried out so far to explain the large differences among results. We consider adjoint based methods to investigate inverse problems using DALEC and various data streams. Using resolution matrices we study the nature of the inverse problems (solution existence, uniqueness and stability) and show how standard regularization techniques affect resolution and stability properties. Instead of using standard prior information as a penalty term in the cost function to regularize the problems we constraint the parameter space using ecological balance conditions and inequality constraints. The efficiency and rapidity of this approach allows us to compute ensembles of solutions to the inverse problems from which we can establish the robustness of the variational method and obtain non Gaussian posterior distributions for the model parameters and initial carbon stocks.

Posterior urethral injuries associated with motorcycle accidents and pelvic trauma in adolescents: analysis of urethral lesions occurring prior to a bony fracture using a computerized finite-element model.

Science.gov (United States)

Bréaud, J; Montoro, J; Lecompte, J F; Valla, J S; Loeffler, J; Baqué, P; Brunet, C; Thollon, L

2013-02-01

Adolescent males involved in motorcycle accidents are particularly at risk for pelvic injury, which may provoke a posterior urethral injury. The aim of this study was to develop a model to analyze the association between injuries and fractures of the pelvic ring and the risk of posterior urethral injury. Based on experience with traffic accident modeling, a computerized finite-element model was extrapolated from a computerized tomography scan of a 15-year-old boy. The anatomic structures concerned in urethral and pelvic ring trauma were isolated, rendered in 3D and given biomechanical properties. The model was verified according to available experiments on pelvic ring trauma. To apply the model, we recreated three impact mechanisms on the pelvic ring: lateral impact, antero-posterior impact and a real car‒motorcycle accident situation (postero-lateral impact). In all three situations, stretching of the posterior urethra was identified prior to bony fracture visualization. Application of this model allowed us to analyze precisely the link between trauma of the pelvic ring and lesions of the posterior urethra. The results should help to establish guidelines for urethral catheterization in male adolescents in cases of pelvic trauma, even when no bony fracture is present, in order to prevent iatrogenic worsening of a misdiagnosed posterior urethral trauma. Copyright © 2011 Journal of Pediatric Urology Company. Published by Elsevier Ltd. All rights reserved.

Development of uncertainty-based work injury model using Bayesian structural equation modelling.

Science.gov (United States)

Chatterjee, Snehamoy

2014-01-01

This paper proposed a Bayesian method-based structural equation model (SEM) of miners' work injury for an underground coal mine in India. The environmental and behavioural variables for work injury were identified and causal relationships were developed. For Bayesian modelling, prior distributions of SEM parameters are necessary to develop the model. In this paper, two approaches were adopted to obtain prior distribution for factor loading parameters and structural parameters of SEM. In the first approach, the prior distributions were considered as a fixed distribution function with specific parameter values, whereas, in the second approach, prior distributions of the parameters were generated from experts' opinions. The posterior distributions of these parameters were obtained by applying Bayesian rule. The Markov Chain Monte Carlo sampling in the form Gibbs sampling was applied for sampling from the posterior distribution. The results revealed that all coefficients of structural and measurement model parameters are statistically significant in experts' opinion-based priors, whereas, two coefficients are not statistically significant when fixed prior-based distributions are applied. The error statistics reveals that Bayesian structural model provides reasonably good fit of work injury with high coefficient of determination (0.91) and less mean squared error as compared to traditional SEM.

Posterior fossa epidural hematoma

International Nuclear Information System (INIS)

Kushner, M.J.; Luken, M.G. III

1983-01-01

CT demonstrated posterior fossa epidural hematoma in three patients with head trauma in whom this diagnosis was not clinically apparent. No patient was in stupor or coma and no patient experienced a lucid interval. Only one patient had signs referable to the posterior fossa. Two patients had occipital skull fracture disclosed by plain radiographs. CT revealed a unilateral biconvex hematoma in two cases, and a bilateral hematoma with supratentorial extension in the third. All patients underwent suboccipital craniectomy and recovered. Therapeutic success in these cases was facilitated by early CT and the rapid disclosure of the unsuspected posterior fossa lesions. CT showing contiguous hematoma below and above the tentorium cerebelli after posterior head trauma is highly suggestive of epidural hematoma arising from the posterior fossa. (orig.)

Posterior leukoencephalopathy following repair of an ileocecal anastomosis breakdown: a case report and review of the literature

Directory of Open Access Journals (Sweden)

Kasper Ekkehard M

2011-01-01

Full Text Available Abstract Introduction Posterior reversible leukoencephalopathy syndrome refers to a constellation of neurologic symptoms related to temporary white matter changes. The disease typically presents in the context of an abrupt and drastic elevation in blood pressure (>180/110 mmHg. We report an unusual case of posterior reversible leukoencephalopathy syndrome in a post-operative setting, with a blood pressure parameter generally tolerated by most patients. Case presentation We report the case of a 22-year-old Caucasian man who suffered acute onset visual acuity loss four days after an ileocecal anastomosis. A head magnetic resonance imaging scan revealed findings typically associated with posterior reversible leukoencephalopathy syndrome. His symptoms developed in the context of blood pressure parameters that are typically well tolerated in a post-operative setting (150-160/80-90 mmHg. He did not have a history of renal failure or immunosuppression. His symptoms resolved with aggressive blood pressure management. Conclusions Posterior reversible leukoencephalopathy syndrome can occur in a post-operative setting with blood pressure parameters typically well-tolerated in most post-surgical patients. Timely diagnosis and treatment will minimize the risk of permanent neurologic injury.

Irreducible Traumatic Posterior Shoulder Dislocation

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Blake Collier

2017-01-01

Full Text Available History of present illness: A 22-year-old male presented to the Emergency Department complaining of right shoulder pain after a motocross accident. He was traveling at approximately 10 mph around a turn when he lost control and was thrown over the handlebars, landing directly on his right shoulder. On arrival, he was holding his arm in adduction and internal rotation. An area of swelling was noted over his anterior shoulder. He was unable to abduct his shoulder. No humeral gapping was noted. He had normal neuro-vascular status distal to the injury. Significant findings: Radiographs demonstrated posterior displacement of the humeral head on the “Y” view (see white arrow and widening of the glenohumeral joint space on anterior-posterior view (see red arrow. The findings were consistent with posterior dislocation and a Hill-Sachs type deformity. Sedation was performed and reduction was attempted using external rotation, traction counter-traction. An immediate “pop” was felt during the procedure. Post-procedure radiographs revealed a persistent posterior subluxation with interlocking at posterior glenoid. CT revealed posterior dislocation with acute depressed impaction deformity medial to the biceps groove with the humeral head perched on the posterior glenoid, interlocked at reverse Hill-Sachs deformity (see blue arrow. Discussion: Posterior shoulder dislocations are rare and represent only 2% of all shoulder dislocations. Posterior shoulder dislocations are missed on initial diagnosis in more than 60% of cases.1 Posterior shoulder dislocations result from axial loading of the adducted and internally rotated shoulder, violent muscle contractions (resulting from seizures or electrocution, a direct posterior force applied to the anterior shoulder.1 Physical findings include decreased anterior prominence of the humeral head, increased palpable posterior prominence of the humeral head below the acromion, increased palpable prominence of the

A study to compare the efficacy of polyether ether ketone rod device with titanium devices in posterior spinal fusion in a canine model.

Science.gov (United States)

Wang, Nanxiang; Xie, Huanxin; Xi, Chunyang; Zhang, Han; Yan, Jinglong

2017-03-09

The benefits of posterior lumbar fusion surgery with orthotopic paraspinal muscle-pediculated bone flaps are well established. However, the problem of non-union due to mechanical support is not completely resolved. The aim of the study was to compare the efficacy of polyether ether ketone (PEEK) rod device with conventional titanium devices in the posterior lumbar fusion surgery with orthotopic paraspinal muscle-pediculated bone flaps. This was a randomized controlled study with an experimental animal model. Thirty-two mongrel dogs were randomly divided into two groups-control group (n = 16), which received the titanium device and the treatment group (n = 16), which received PEEK rods. The animals were sacrificed 8 or 16 weeks after surgery. Lumbar spines of dogs in both groups were removed, harvested, and assessed for radiographic, biomechanical, and histological changes. Results in the current study indicated that there was no significant difference in the lumbar spine of the control and treatment groups in terms of radiographic, manual palpation, and gross examination. However, certain parameters of biomechanical testing showed significant differences (p < 0.05) in stiffness and displacement, revealing a better fusion (treatment group showed decreased stiffness with decreased displacement) of the bone graft. Similarly, the histological analysis also revealed a significant fusion mass in both treatment and control groups (p < 0.05). These findings revealed that fixation using PEEK connecting rod could improve the union of the bone graft in the posterior lumbar spine fusion surgery compared with that of the titanium rod fixation.

The estimation of soil parameters using observations on crop biophysical variables and the crop model STICS improve the predictions of agro environmental variables.

Science.gov (United States)

Varella, H.-V.

2009-04-01

Dynamic crop models are very useful to predict the behavior of crops in their environment and are widely used in a lot of agro-environmental work. These models have many parameters and their spatial application require a good knowledge of these parameters, especially of the soil parameters. These parameters can be estimated from soil analysis at different points but this is very costly and requires a lot of experimental work. Nevertheless, observations on crops provided by new techniques like remote sensing or yield monitoring, is a possibility for estimating soil parameters through the inversion of crop models. In this work, the STICS crop model is studied for the wheat and the sugar beet and it includes more than 200 parameters. After a previous work based on a large experimental database for calibrate parameters related to the characteristics of the crop, a global sensitivity analysis of the observed variables (leaf area index LAI and absorbed nitrogen QN provided by remote sensing data, and yield at harvest provided by yield monitoring) to the soil parameters is made, in order to determine which of them have to be estimated. This study was made in different climatic and agronomic conditions and it reveals that 7 soil parameters (4 related to the water and 3 related to the nitrogen) have a clearly influence on the variance of the observed variables and have to be therefore estimated. For estimating these 7 soil parameters, a Bayesian data assimilation method is chosen (because of available prior information on these parameters) named Importance Sampling by using observations, on wheat and sugar beet crop, of LAI and QN at various dates and yield at harvest acquired on different climatic and agronomic conditions. The quality of parameter estimation is then determined by comparing the result of parameter estimation with only prior information and the result with the posterior information provided by the Bayesian data assimilation method. The result of the

Comparison of different morphological parameters with duration of obstruction created experimentally in unilateral upper ureters: An animal model

Directory of Open Access Journals (Sweden)

Shasanka Shekhar Panda

2014-01-01

Full Text Available Background: The objective of the following study is to determine and to compare the different morphological parameters with duration of obstruction created experimentally in unilateral upper ureters of rats. Materials and Methods: Unilateral upper ureteric obstruction was created in 60 adult Wistar rats that were reversed after predetermined intervals. Rats were sacrificed and ipsilateral kidneys were subjected for analysis of morphological parameters such as renal height, cranio-caudal diameter, antero-posterior diameter, lateral diameter, volume of the pelvis and average cortical thickness: Renal height. Results: Renal height and cranio-caudal diameter of renal pelvis after ipsilateral upper ureteric obstruction started rising as early as 7 days of creating obstruction and were affected earlier than antero-posterior and lateral diameter and also were reversed earlier than other parameters after reversal of obstruction. Renal cortical thickness and volume of the pelvis were affected after prolonged obstruction (> 3 weeks and were the late parameters to be reversed after reversal of obstruction. Conclusions: Cranio-caudal diameter and renal height were the early morphological parameters to be affected and reversed after reversal of obstruction in experimentally created ipsilateral upper ureteric obstruction.

Modeling the Effects of Spaceflight on the Posterior Eye in VIIP

Science.gov (United States)

Ethier, C. R.; Feola, A. J.; Raykin, J.; Mulugeta, L.; Gleason, R.; Myers, J. G.; Nelson, E. S.; Samuels, B.

2015-01-01

Purpose: Visual Impairment and Intracranial Pressure (VIIP) syndrome is a new and significant health concern for long-duration space missions. Its etiology is unknown, but is thought to involve elevated intracranial pressure (ICP)that induces connective tissue changes and remodeling in the posterior eye (Alexander et al. 2012). Here we study the acute biomechanical response of the lamina cribrosa (LC) and optic nerve to elevations in ICP utilizing finite element (FE) modeling. Methods: Using the geometry of the posterior eye from previous axisymmetric FE models (Sigal et al. 2004), we added an elongated optic nerve and optic nerve sheath, including the pia and dura. Tissues were modeled as linear elastic solids. Intraocular pressure and central retinal vessel pressures were set at 15 mmHg and 55 mmHg, respectively. ICP varied from 0 mmHg (suitable for standing on earth) to 30 mmHg (representing severe intracranial hypertension, thought to occur in space flight). We focused on strains and deformations in the LC and optic nerve (within 1 mm of the LC) since we hypothesize that they may contribute to vision loss in VIIP. Results: Elevating ICP from 0 to 30 mmHg significantly altered the strain distributions in both the LC and optic nerve (Figure), notably leading to more extreme strain values in both tension and compression. Specifically, the extreme (95th percentile) tensile strains in the LC and optic nerve increased by 2.7- and 3.8-fold, respectively. Similarly, elevation of ICP led to a 2.5- and 3.3-fold increase in extreme (5th percentile) compressive strains in the LC and optic nerve, respectively. Conclusions: The elevated ICP thought to occur during spaceflight leads to large acute changes in the biomechanical environment of the LC and optic nerve, and we hypothesize that such changes can activate mechanosensitive cells and invoke tissue remodeling. These simulations provide a foundation for more comprehensive studies of microgravity effects on human vision, e

Probabilistic estimation of the constitutive parameters of polymers

Directory of Open Access Journals (Sweden)

Siviour C.R.

2012-08-01

Full Text Available The Mulliken-Boyce constitutive model predicts the dynamic response of crystalline polymers as a function of strain rate and temperature. This paper describes the Mulliken-Boyce model-based estimation of the constitutive parameters in a Bayesian probabilistic framework. Experimental data from dynamic mechanical analysis and dynamic compression of PVC samples over a wide range of strain rates are analyzed. Both experimental uncertainty and natural variations in the material properties are simultaneously considered as independent and joint distributions; the posterior probability distributions are shown and compared with prior estimates of the material constitutive parameters. Additionally, particular statistical distributions are shown to be effective at capturing the rate and temperature dependence of internal phase transitions in DMA data.

MCMC for parameters estimation by bayesian approach

International Nuclear Information System (INIS)

Ait Saadi, H.; Ykhlef, F.; Guessoum, A.

2011-01-01

This article discusses the parameter estimation for dynamic system by a Bayesian approach associated with Markov Chain Monte Carlo methods (MCMC). The MCMC methods are powerful for approximating complex integrals, simulating joint distributions, and the estimation of marginal posterior distributions, or posterior means. The MetropolisHastings algorithm has been widely used in Bayesian inference to approximate posterior densities. Calibrating the proposal distribution is one of the main issues of MCMC simulation in order to accelerate the convergence.

Cranial CT with 64-, 16-, 4- and single-slice CT systems-comparison of image quality and posterior fossa artifacts in routine brain imaging with standard protocols

Energy Technology Data Exchange (ETDEWEB)

Ertl-Wagner, Birgit; Eftimov, Lara; Becker, Christoph; Reiser, Maximilian [University of Munich, Grosshadern (Germany). Institute of Clinical Radiology; Blume, Jeffrey; Cormack, Jean [Brown University, Center for Statistical Sciences, Providence, RI (United States); Bruening, Roland; Brueckmann, Hartmut [University of Munich, Grosshadern (Germany). Department of Neuroradiology

2008-08-15

Posterior fossa artifacts constitute a characteristic limitation of cranial CT. To identify practical benefits and drawbacks of newer CT systems with reduced collimation in routine cranial imaging, we aimed to investigate image quality, posterior fossa artifacts and parenchymal delineation in non-enhanced CT (NECT) with 1-, 4-, 16- and 64-slice scanners using standard scan protocols. We prospectively enrolled 25 consecutive patients undergoing NECT on a 64-slice CT. Three groups with 25 patients having undergone NECT on 1-, 4- and 16-slice CT machines were matched regarding age and sex. Standard routine CT parameters were used on each CT system with helical acquisition in the posterior fossa; the parameters varied regarding collimation and radiation dose. Three blinded readers independently assessed the cases regarding image quality, infra- and supratentorial artifacts and delineation of brain parenchymal structures on a five-point ordinal scale. Reading orders were randomized. A proportional odds model that accounted for the correlated nature of the data was fit using generalized estimating equations. Posterior fossa artifacts were significantly reduced, and the delineation of infratentorial brain structures was significantly improved with the thinner collimation used for the newer CT systems (p<0.001). No significant differences were observed for midbrain structures (p>0.5). The thinner collimation available on modern CT systems leads to reduced posterior fossa artifacts and to a better delineation of brain parenchyma in the posterior fossa. (orig.)

[Efficacy of retained rectal posterior mucosa in procedure for prolapse and hemorrhoids].

Science.gov (United States)

Zheng, Chenguo; Jin, Chun; Lian, Shaoxiong; Jin, Dingguo

2014-12-01

To evaluate the efficacy and necessity of retained rectal posterior mucosa in procedure for prolapse and hemorrhoids (PPH). Clinical data of 260 cases with severe hemorrhoids in our hospital from January 2010 to May 2012 were analyzed retrospectively. A total of 132 cases with severe hemorrhoids excluding in rectal posterior wall were enrolled in retained rectal posterior mucosa in PPH (improvement group), other 128 cases of severe hemorrhoids were assigned to PPH (conventional group). Operative parameters, efficacy and complication after operation were compared. Two groups of patients received successful operations. Postoperative pain duration, frequency of analgesic drugs and postoperative hospital stay in improvement group were significantly reduced [(1.3 ± 0.5) d vs. (4.8 ± 0.7) d, 1.1 ± 0.3 vs. 5.9 ± 0.6, (5.2 ± 0.8) d vs. (5.8 ± 0.5) d, all Phemorrhoids excluding in rectal posterior wall can significantly reduce postoperative complications. But long-term efficacy needs further observation.

A general approach to posterior contraction in nonparametric inverse problems

NARCIS (Netherlands)

Knapik, Bartek; Salomond, Jean Bernard

In this paper, we propose a general method to derive an upper bound for the contraction rate of the posterior distribution for nonparametric inverse problems. We present a general theorem that allows us to derive contraction rates for the parameter of interest from contraction rates of the related

Association Between Vascular Anatomy and Posterior Communicating Artery Aneurysms.

Science.gov (United States)

Can, Anil; Ho, Allen L; Emmer, Bart J; Dammers, Ruben; Dirven, Clemens M F; Du, Rose

2015-11-01

Hemodynamic stress, conditioned by the geometry and morphology of the vessel trees, plays an important role in the formation of intracranial aneurysms. The aim of this study was to identify image-based location-specific morphologic parameters that are associated with posterior communicating artery (PCoA) aneurysms. Morphologic parameters obtained from computed tomography angiography of 56 patients with PCoA aneurysms and 23 control patients were evaluated with 3D Slicer, an open-source image analysis software, to generate 3-dimensional models of the aneurysms and surrounding vasculature. Segment lengths, diameters, and vessel-to-vessel angles were examined. To control for genetic and clinical risk factors, the unaffected contralateral side of patients with unilateral PCoA aneurysms was used as a control group for internal carotid artery (ICA)-related parameters. A separate control group with visible PCoAs and aneurysms elsewhere was used as a control group for PCoA-related parameters. Internal carotid artery-related parameters were not statistically different between the PCoA aneurysm and control groups. Univariate and multivariate subgroup analysis for patients with visualized PCoAs demonstrated that a larger PCoA diameter was significantly associated with the presence of a PCoA aneurysm (odds ratio = 12.1, 95% confidence interval = 1.3-17.1, P = 0.04) after adjusting for other morphologic parameters. Larger PCoA diameters are associated with the presence of PCoA aneurysms. These parameters may provide objective metrics to assess aneurysm formation and growth risk stratification in high-risk patients. Copyright © 2015 Elsevier Inc. All rights reserved.

Quality assessment for radiological model parameters

International Nuclear Information System (INIS)

Funtowicz, S.O.

1989-01-01

A prototype framework for representing uncertainties in radiological model parameters is introduced. This follows earlier development in this journal of a corresponding framework for representing uncertainties in radiological data. Refinements and extensions to the earlier framework are needed in order to take account of the additional contextual factors consequent on using data entries to quantify model parameters. The parameter coding can in turn feed in to methods for evaluating uncertainties in calculated model outputs. (author)

A hierarchical method for Bayesian inference of rate parameters from shock tube data: Application to the study of the reaction of hydroxyl with 2-methylfuran

KAUST Repository

Kim, Daesang

2017-06-22

We developed a novel two-step hierarchical method for the Bayesian inference of the rate parameters of a target reaction from time-resolved concentration measurements in shock tubes. The method was applied to the calibration of the parameters of the reaction of hydroxyl with 2-methylfuran, which is studied experimentally via absorption measurements of the OH radical\\'s concentration following shock-heating. In the first step of the approach, each shock tube experiment is treated independently to infer the posterior distribution of the rate constant and error hyper-parameter that best explains the OH signal. In the second step, these posterior distributions are sampled to calibrate the parameters appearing in the Arrhenius reaction model for the rate constant. Furthermore, the second step is modified and repeated in order to explore alternative rate constant models and to assess the effect of uncertainties in the reflected shock\\'s temperature. Comparisons of the estimates obtained via the proposed methodology against the common least squares approach are presented. The relative merits of the novel Bayesian framework are highlighted, especially with respect to the opportunity to utilize the posterior distributions of the parameters in future uncertainty quantification studies.

Improvising a Posterior Nasal Pack with Equipment in a Basic First Aid Kit.

Science.gov (United States)

Royer, Allison K; Royer, Mark C

2016-09-01

Posterior epistaxis is a serious condition that can be difficult to treat in a wilderness setting. The initial standard of care involves packing the affected nostril with a 7 to 9 cm nasal pack to tamponade the bleed. These packs are often unavailable outside of the emergency or operating room. This study set out to determine whether a posterior nasal pack could be constructed from the supplies present in a basic first aid kit in order to control massive nasal hemorrhage in a wilderness setting. A basic first aid kit was utilized to construct a posterior nasal pack that was inserted into an anatomical model and visibly compared with the Rapid Rhino (Posterior, 7.5 cm; Smith & Nephew, Austin, TX) nasal packing. The shape, size, and anatomical areas of compression (ie, into nasopharynx and posterior aspect of inferior turbinate) of this pack was similar to the commercially available posterior nasal pack. Placement in an anatomical model appears to provide similar compression as the commercially available posterior pack. This technique may provide short-term hemorrhage control in cases of serious posterior nasal hemorrhage where standard treatment options are not available. Copyright © 2016 Wilderness Medical Society. Published by Elsevier Inc. All rights reserved.

Classification of posterior vitreous detachment

Science.gov (United States)

Kakehashi, Akihiro; Takezawa, Mikiko; Akiba, Jun

2014-01-01

Diagnosing a posterior vitreous detachment (PVD) is important for predicting the prognosis and determining the indication for vitreoretinal surgery in many vitreoretinal diseases. This article presents both classifications of a PVD by slit-lamp biomicroscopy and of a shallow PVD by optical coherence tomography (OCT). By biomicroscopy, the vitreous condition is determined based on the presence or absence of a PVD. The PVD then is classified as either a complete posterior vitreous detachment (C-PVD) or a partial posterior vitreous detachment (P-PVD). A C-PVD is further divided into a C-PVD with collapse and a C-PVD without collapse, while a P-PVD is divided into a P-PVD with shrinkage of the posterior hyaloid membrane (P-PVD with shrinkage) and a P-PVD without shrinkage of the posterior hyaloid membrane (P-PVD without shrinkage). A P-PVD without shrinkage has a subtype characterized by vitreous gel attachment through the premacular hole in a posterior hyaloid membrane to the macula (P-PVD without shrinkage [M]). By OCT, a shallow PVD is classified as the absence of a shallow PVD or as a shallow PVD. A shallow PVD is then subclassified as a shallow PVD without shrinkage of the posterior vitreous cortex, a shallow PVD with shrinkage of the posterior vitreous cortex, and a peripheral shallow PVD. A shallow PVD without shrinkage of the posterior vitreous cortex has two subtypes: an age-related shallow PVD and a perifoveal PVD associated with a macular hole. PMID:24376338

Overlapping sphincteroplasty and posterior repair.

Science.gov (United States)

Crane, Andrea K; Myers, Erinn M; Lippmann, Quinn K; Matthews, Catherine A

2014-12-01

Knowledge of how to anatomically reconstruct extensive posterior-compartment defects is variable among gynecologists. The objective of this video is to demonstrate an effective technique of overlapping sphincteroplasty and posterior repair. In this video, a scripted storyboard was constructed that outlines the key surgical steps of a comprehensive posterior compartment repair: (1) surgical incision that permits access to posterior compartment and perineal body, (2) dissection of the rectovaginal space up to the level of the cervix, (3) plication of the rectovaginal muscularis, (4) repair of internal and external anal sphincters, and (5) reconstruction of the perineal body. Using a combination of graphic illustrations and live video footage, tips on repair are highlighted. The goals at the end of repair are to: (1) have improved vaginal caliber, (2) increase rectal tone along the entire posterior vaginal wall, (3) have the posterior vaginal wall at a perpendicular plane to the perineal body, (4) reform the hymenal ring, and (5) not have an overly elongated perineal body. This video provides a step-by-step guide on how to perform an overlapping sphincteroplasty and posterior repair.

Parameter Estimation for Thurstone Choice Models

Energy Technology Data Exchange (ETDEWEB)

Vojnovic, Milan [London School of Economics (United Kingdom); Yun, Seyoung [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-04-24

We consider the estimation accuracy of individual strength parameters of a Thurstone choice model when each input observation consists of a choice of one item from a set of two or more items (so called top-1 lists). This model accommodates the well-known choice models such as the Luce choice model for comparison sets of two or more items and the Bradley-Terry model for pair comparisons. We provide a tight characterization of the mean squared error of the maximum likelihood parameter estimator. We also provide similar characterizations for parameter estimators defined by a rank-breaking method, which amounts to deducing one or more pair comparisons from a comparison of two or more items, assuming independence of these pair comparisons, and maximizing a likelihood function derived under these assumptions. We also consider a related binary classification problem where each individual parameter takes value from a set of two possible values and the goal is to correctly classify all items within a prescribed classification error. The results of this paper shed light on how the parameter estimation accuracy depends on given Thurstone choice model and the structure of comparison sets. In particular, we found that for unbiased input comparison sets of a given cardinality, when in expectation each comparison set of given cardinality occurs the same number of times, for a broad class of Thurstone choice models, the mean squared error decreases with the cardinality of comparison sets, but only marginally according to a diminishing returns relation. On the other hand, we found that there exist Thurstone choice models for which the mean squared error of the maximum likelihood parameter estimator can decrease much faster with the cardinality of comparison sets. We report empirical evaluation of some claims and key parameters revealed by theory using both synthetic and real-world input data from some popular sport competitions and online labor platforms.

Posterior urethral injuries associated with pelvic injuries in young adults: computerized finite element model creation and application to improve knowledge and prevention of these lesions.

Science.gov (United States)

Bréaud, J; Baqué, P; Loeffler, J; Colomb, F; Brunet, C; Thollon, L

2012-05-01

Young adult males involved in motorcycle accidents are particularly at risk for posterior urethral injury whenever pelvic injury occurs. Posterior urethral injuries remain problematic because their diagnosis may be missed, and during the initial treatment response the urethral injury can be aggravated by urethral catheterization. Few anatomical and clinical tools exist that establish a correlation between injuries and fractures of the pelvic ring and the risk of posterior urethral injury. Based on experience with traffic accident modeling, a computerized finite element model was conceived integrating the specific anatomic structures concerned. This model was extrapolated from a CAT scan of a young adult. The anatomic structures concerned in urethral and pelvic ring trauma (PRT) were isolated, placed in 3D and given biomechanical properties. The model was verified according to available experiments on PRT. To apply the model, we recreated a lateral impact mechanism on the pelvic ring. Stretching between the prostatic and membranous portions of the urethra (before and after visualization of a pelvic fracture) as well as timing of injury was studied. The model's application permitted us to analyze precisely the link between lateral impact trauma of the pelvic ring and lesions of the posterior urethra and to identify an urethra stretching prior to visualization of a pelvic fracture. Utilization of the model with other mechanisms of injury should allow for better comprehension of this associated trauma, improved prevention, iatrogenic aggravation of, and care for, these serious injuries. © Springer-Verlag 2011

International comparative evaluation of fixed-bearing non-posterior-stabilized and posterior-stabilized total knee replacements.

Science.gov (United States)

Comfort, Thomas; Baste, Valborg; Froufe, Miquel Angel; Namba, Robert; Bordini, Barbara; Robertsson, Otto; Cafri, Guy; Paxton, Elizabeth; Sedrakyan, Art; Graves, Stephen

2014-12-17

Differences in survivorship of non-posterior-stabilized compared with posterior-stabilized knee designs carry substantial economic consequences, especially with limited health-care resources. However, these comparisons have often been made between relatively small groups of patients, often with short-term follow-up, with only small differences demonstrated between the groups. The goal of this study is to compare the outcomes of non-posterior-stabilized and posterior-stabilized total knee arthroplasties with use of a unique collaboration of multiple established knee arthroplasty registries. A distributed health data network was developed by the International Consortium of Orthopaedic Registries and was used in this study to reduce barriers to participation (such as security, propriety, legal, and privacy issues) compared with a centralized data warehouse approach. The study included only replacements in osteoarthritis patients who underwent total knee procedures involving fixed-bearing devices from 2001 to 2010. The outcome of interest was time to first revision. On average, not resurfacing showed a more harmful effect than resurfacing did when posterior-stabilized and non-posterior-stabilized knee replacements were compared, while the risk of revision for posterior-stabilized compared with non-posterior-stabilized knees was highest in year zero to one, followed by year one to two, years eight through ten, and years two through eight. Posterior-stabilized knees did significantly worse than non-posterior-stabilized knees did when the patella was not resurfaced. This difference was most pronounced in the first two years (year zero to one: hazard ratio [HR] = 2.15, 95% confidence interval [CI] = 1.56 to 2.95, p < 0.001; year one to two: HR = 1.61, 95% CI = 1.48 to 1.75, p < 0.001). When the patella was resurfaced, posterior-stabilized knees did significantly worse than non-posterior-stabilized knees did. This was again most pronounced in the first two years (year zero

Automated parameter estimation for biological models using Bayesian statistical model checking.

Science.gov (United States)

Hussain, Faraz; Langmead, Christopher J; Mi, Qi; Dutta-Moscato, Joyeeta; Vodovotz, Yoram; Jha, Sumit K

2015-01-01

Probabilistic models have gained widespread acceptance in the systems biology community as a useful way to represent complex biological systems. Such models are developed using existing knowledge of the structure and dynamics of the system, experimental observations, and inferences drawn from statistical analysis of empirical data. A key bottleneck in building such models is that some system variables cannot be measured experimentally. These variables are incorporated into the model as numerical parameters. Determining values of these parameters that justify existing experiments and provide reliable predictions when model simulations are performed is a key research problem. Using an agent-based model of the dynamics of acute inflammation, we demonstrate a novel parameter estimation algorithm by discovering the amount and schedule of doses of bacterial lipopolysaccharide that guarantee a set of observed clinical outcomes with high probability. We synthesized values of twenty-eight unknown parameters such that the parameterized model instantiated with these parameter values satisfies four specifications describing the dynamic behavior of the model. We have developed a new algorithmic technique for discovering parameters in complex stochastic models of biological systems given behavioral specifications written in a formal mathematical logic. Our algorithm uses Bayesian model checking, sequential hypothesis testing, and stochastic optimization to automatically synthesize parameters of probabilistic biological models.

Posterior capsule opacification.

Science.gov (United States)

Wormstone, I Michael; Wang, Lixin; Liu, Christopher S C

2009-02-01

Posterior Capsule Opacification (PCO) is the most common complication of cataract surgery. At present the only means of treating cataract is by surgical intervention, and this initially restores high visual quality. Unfortunately, PCO develops in a significant proportion of patients to such an extent that a secondary loss of vision occurs. A modern cataract operation generates a capsular bag, which comprises a proportion of the anterior and the entire posterior capsule. The bag remains in situ, partitions the aqueous and vitreous humours, and in the majority of cases, houses an intraocular lens. The production of a capsular bag following surgery permits a free passage of light along the visual axis through the transparent intraocular lens and thin acellular posterior capsule. However, on the remaining anterior capsule, lens epithelial cells stubbornly reside despite enduring the rigours of surgical trauma. This resilient group of cells then begin to re-colonise the denuded regions of the anterior capsule, encroach onto the intraocular lens surface, occupy regions of the outer anterior capsule and most importantly of all begin to colonise the previously cell-free posterior capsule. Cells continue to divide, begin to cover the posterior capsule and can ultimately encroach on the visual axis resulting in changes to the matrix and cell organization that can give rise to light scatter. This review will describe the biological mechanisms driving PCO progression and discuss the influence of IOL design, surgical techniques and putative drug therapies in regulating the rate and severity of PCO.

Visual Attention in Posterior Stroke and Relations to Alexia

DEFF Research Database (Denmark)

Petersen, Anders; Vangkilde, Signe; Fabricius, Charlotte

2016-01-01

that reduced visual speed and span may explain pure alexia. Eight patients with unilateral PCA strokes (four left hemisphere, four right hemisphere) were selected on the basis of lesion location, rather than the presence of any visual symptoms. Visual attention was characterized by a whole report paradigm......Impaired visual attention is common following strokes in the territory of the middle cerebral artery, particularly in the right hemisphere, while attentional effects of more posterior lesions are less clear. Commonly, such deficits are investigated in relation to specific syndromes like visual...... agnosia or pure alexia. The aim of this study was to characterize visual processing speed and apprehension span following posterior cerebral artery (PCA) stroke. In addition, the relationship between these attentional parameters and single word reading is investigated, as previous studies have suggested...

Bayesian calibration of the Community Land Model using surrogates

Energy Technology Data Exchange (ETDEWEB)

Ray, Jaideep; Hou, Zhangshuan; Huang, Maoyi; Swiler, Laura Painton

2014-02-01

We present results from the Bayesian calibration of hydrological parameters of the Community Land Model (CLM), which is often used in climate simulations and Earth system models. A statistical inverse problem is formulated for three hydrological parameters, conditional on observations of latent heat surface fluxes over 48 months. Our calibration method uses polynomial and Gaussian process surrogates of the CLM, and solves the parameter estimation problem using a Markov chain Monte Carlo sampler. Posterior probability densities for the parameters are developed for two sites with different soil and vegetation covers. Our method also allows us to examine the structural error in CLM under two error models. We find that surrogate models can be created for CLM in most cases. The posterior distributions are more predictive than the default parameter values in CLM. Climatologically averaging the observations does not modify the parameters' distributions significantly. The structural error model reveals a correlation time-scale which can be used to identify the physical process that could be contributing to it. While the calibrated CLM has a higher predictive skill, the calibration is under-dispersive.

Comparison of two Nd:YAG laser posterior capsulotomy: cruciate pattern vs circular pattern with vitreous strand cutting.

Science.gov (United States)

Kim, Jin-Soo; Choi, Jung Yeol; Kwon, Ji-Won; Wee, Won Ryang; Han, Young Keun

2018-01-01

To investigate the effects and safety of neodymium: yttrium-aluminium-garnet (Nd:YAG) laser posterior capsulotomy with vitreous strand cutting. A total of 40 eyes of 37 patients with symptomatic posterior capsular opacity (PCO) were included in this prospective randomized study and were randomly subjected to either cruciate pattern or round pattern Nd:YAG posterior capsulotomy with vitreous strand cutting (modified round pattern). The best corrected visual acuity (BCVA), intraocular pressure (IOP), refractive error, endothelial cell count (ECC), anterior segment parameters, including anterior chamber depth (ACD) and anterior chamber angle (ACA) were measured before and 1mo after the laser posterior capsulotomy. In both groups, the BCVA improved significantly ( P <0.001 for the modified round pattern group, P =0.001 for the cruciate pattern group); the IOP and ECC did not significantly change. The ACD significantly decreased ( P <0.001 for both) and the ACA significantly increased ( P =0.001 for the modified round pattern group and P =0.034 for the cruciate group). The extent of changes in these parameters was not significantly different between the groups. Modified round pattern Nd:YAG laser posterior capsulotomy is an effective and safe method for the treatment of PCO. This method significantly changes the ACD and ACA, but the change in refraction is not significant. Modified round pattern Nd:YAG laser posterior capsulotomy can be considered a good alternative procedure in patients with symptomatic PCO.

Comparison of two Nd:YAG laser posterior capsulotomy: cruciate pattern vs circular pattern with vitreous strand cutting

Directory of Open Access Journals (Sweden)

Jin-Soo Kim

2018-02-01

Full Text Available AIM: To investigate the effects and safety of neodymium: yttrium-aluminium-garnet (Nd:YAG laser posterior capsulotomy with vitreous strand cutting METHODS: A total of 40 eyes of 37 patients with symptomatic posterior capsular opacity (PCO were included in this prospective randomized study and were randomly subjected to either cruciate pattern or round pattern Nd:YAG posterior capsulotomy with vitreous strand cutting (modified round pattern. The best corrected visual acuity (BCVA, intraocular pressure (IOP, refractive error, endothelial cell count (ECC, anterior segment parameters, including anterior chamber depth (ACD and anterior chamber angle (ACA were measured before and 1mo after the laser posterior capsulotomy. RESULTS: In both groups, the BCVA improved significantly (P<0.001 for the modified round pattern group, P=0.001 for the cruciate pattern group; the IOP and ECC did not significantly change. The ACD significantly decreased (P<0.001 for both and the ACA significantly increased (P=0.001 for the modified round pattern group and P=0.034 for the cruciate group. The extent of changes in these parameters was not significantly different between the groups. CONCLUSION: Modified round pattern Nd:YAG laser posterior capsulotomy is an effective and safe method for the treatment of PCO. This method significantly changes the ACD and ACA, but the change in refraction is not significant. Modified round pattern Nd:YAG laser posterior capsulotomy can be considered a good alternative procedure in patients with symptomatic PCO.

The influence of model parameters on catchment-response

International Nuclear Information System (INIS)

Shah, S.M.S.; Gabriel, H.F.; Khan, A.A.

2002-01-01

This paper deals with the study of influence of influence of conceptual rainfall-runoff model parameters on catchment response (runoff). A conceptual modified watershed yield model is employed to study the effects of model-parameters on catchment-response, i.e. runoff. The model is calibrated, using manual parameter-fitting approach, also known as trial and error parameter-fitting. In all, there are twenty one (21) parameters that control the functioning of the model. A lumped parametric approach is used. The detailed analysis was performed on Ling River near Kahuta, having catchment area of 56 sq. miles. The model includes physical parameters like GWSM, PETS, PGWRO, etc. fitting coefficients like CINF, CGWS, etc. and initial estimates of the surface-water and groundwater storages i.e. srosp and gwsp. Sensitivity analysis offers a good way, without repetititious computations, the proper weight and consideration that must be taken when each of the influencing factor is evaluated. Sensitivity-analysis was performed to evaluate the influence of model-parameters on runoff. The sensitivity and relative contributions of model parameters influencing catchment-response are studied. (author)

Biomechanical study: resistance comparison of posterior antiglide plate and lateral plate on synthetic bone models simulating Danis-Weber B malleolar fractures

Directory of Open Access Journals (Sweden)

Bruna Buscharino

2013-06-01

Full Text Available OBJECTIVE : The purpose of this study was to compare different positions of plates in lateral malleolar Danis-Weber B fractures on synthetic bone: a lateral plate and a posterior antiglide plate. METHODS : Short oblique fractures of distal fibula at the level of the syndesmosys were simulated with a fibular osteotomy in sixteen synthetic fibula bones (Synbone®. Eight fractures were fixed with lateral plating associated with an independent lag screw, and the other eight were fixed with posterior antiglide plating with a lag screw through the plate. A strain gage was installed at the center of each plate at the osteotomy site. Supination and external rotation forces were applied to each of the two groups at the bend. RESULTS : The lateral position plate group suffered more deformity in response to supination forces compared to the group with the posterior antiglide plate, but this result was not statistically significant. In the tests with external rotation forces, the posterior antiglide plating group had significantly higher resistance (p < 0.05. CONCLUSION : When subjected to external rotation forces, osteosynthesis with posterior antiglide plate models simulating type B fractures of the lateral malleolus of the ankle is more resistant than that of the neutralization plate.

Calibrating the sqHIMMELI v1.0 wetland methane emission model with hierarchical modeling and adaptive MCMC

Science.gov (United States)

Susiluoto, Jouni; Raivonen, Maarit; Backman, Leif; Laine, Marko; Makela, Jarmo; Peltola, Olli; Vesala, Timo; Aalto, Tuula

2018-03-01

Estimating methane (CH4) emissions from natural wetlands is complex, and the estimates contain large uncertainties. The models used for the task are typically heavily parameterized and the parameter values are not well known. In this study, we perform a Bayesian model calibration for a new wetland CH4 emission model to improve the quality of the predictions and to understand the limitations of such models.The detailed process model that we analyze contains descriptions for CH4 production from anaerobic respiration, CH4 oxidation, and gas transportation by diffusion, ebullition, and the aerenchyma cells of vascular plants. The processes are controlled by several tunable parameters. We use a hierarchical statistical model to describe the parameters and obtain the posterior distributions of the parameters and uncertainties in the processes with adaptive Markov chain Monte Carlo (MCMC), importance resampling, and time series analysis techniques. For the estimation, the analysis utilizes measurement data from the Siikaneva flux measurement site in southern Finland. The uncertainties related to the parameters and the modeled processes are described quantitatively. At the process level, the flux measurement data are able to constrain the CH4 production processes, methane oxidation, and the different gas transport processes. The posterior covariance structures explain how the parameters and the processes are related. Additionally, the flux and flux component uncertainties are analyzed both at the annual and daily levels. The parameter posterior densities obtained provide information regarding importance of the different processes, which is also useful for development of wetland methane emission models other than the square root HelsinkI Model of MEthane buiLd-up and emIssion for peatlands (sqHIMMELI). The hierarchical modeling allows us to assess the effects of some of the parameters on an annual basis. The results of the calibration and the cross validation suggest that

On parameter estimation in deformable models

DEFF Research Database (Denmark)

Fisker, Rune; Carstensen, Jens Michael

1998-01-01

Deformable templates have been intensively studied in image analysis through the last decade, but despite its significance the estimation of model parameters has received little attention. We present a method for supervised and unsupervised model parameter estimation using a general Bayesian form...

Inverse Modeling Using Markov Chain Monte Carlo Aided by Adaptive Stochastic Collocation Method with Transformation

Science.gov (United States)

Zhang, D.; Liao, Q.

2016-12-01

The Bayesian inference provides a convenient framework to solve statistical inverse problems. In this method, the parameters to be identified are treated as random variables. The prior knowledge, the system nonlinearity, and the measurement errors can be directly incorporated in the posterior probability density function (PDF) of the parameters. The Markov chain Monte Carlo (MCMC) method is a powerful tool to generate samples from the posterior PDF. However, since the MCMC usually requires thousands or even millions of forward simulations, it can be a computationally intensive endeavor, particularly when faced with large-scale flow and transport models. To address this issue, we construct a surrogate system for the model responses in the form of polynomials by the stochastic collocation method. In addition, we employ interpolation based on the nested sparse grids and takes into account the different importance of the parameters, under the condition of high random dimensions in the stochastic space. Furthermore, in case of low regularity such as discontinuous or unsmooth relation between the input parameters and the output responses, we introduce an additional transform process to improve the accuracy of the surrogate model. Once we build the surrogate system, we may evaluate the likelihood with very little computational cost. We analyzed the convergence rate of the forward solution and the surrogate posterior by Kullback-Leibler divergence, which quantifies the difference between probability distributions. The fast convergence of the forward solution implies fast convergence of the surrogate posterior to the true posterior. We also tested the proposed algorithm on water-flooding two-phase flow reservoir examples. The posterior PDF calculated from a very long chain with direct forward simulation is assumed to be accurate. The posterior PDF calculated using the surrogate model is in reasonable agreement with the reference, revealing a great improvement in terms of

Fatal atypical reversible posterior leukoencephalopathy syndrome: a case report

Directory of Open Access Journals (Sweden)

Golombeck Stefanie Kristin

2013-01-01

Full Text Available Abstract Introduction Reversible posterior leukoencephalopathy syndrome – a reversible subacute global encephalopathy clinically presenting with headache, altered mental status, visual symptoms such as hemianopsia or cortical blindness, motor symptoms, and focal or generalized seizures – is characterized by a subcortical vasogenic edema symmetrically affecting posterior brain regions. Complete reversibility of both clinical signs and magnetic resonance imaging lesions is regarded as a defining feature of reversible posterior leukoencephalopathy syndrome. Reversible posterior leukoencephalopathy syndrome is almost exclusively seen in the setting of a predisposing clinical condition, such as pre-eclampsia, systemic infections, sepsis and shock, certain autoimmune diseases, various malignancies and cytotoxic chemotherapy, transplantation and concomitant immunosuppression (especially with calcineurin inhibitors as well as episodes of abrupt hypertension. We describe for the first time clinical, radiological and histological findings in a case of reversible posterior leukoencephalopathy syndrome with an irreversible and fatal outcome occurring in the absence of any of the known predisposing clinical conditions except for a hypertensive episode. Case presentation A 58-year-old Caucasian woman presented with a two-week history of subacute and progressive occipital headache, blurred vision and imbalance of gait and with no evidence for raised arterial blood pressure during the two weeks previous to admission. Her past medical history was unremarkable except for controlled arterial hypertension. Cerebral magnetic resonance imaging demonstrated cortical and subcortical lesions with combined vasogenic and cytotoxic edema atypical for both venous congestion and arterial infarction. Routine laboratory and cerebrospinal fluid parameters were normal. The diagnosis of reversible posterior leukoencephalopathy syndrome was established. Within hours after

Posterior Urethral Valves

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Steve J. Hodges

2009-01-01

Full Text Available The most common cause of lower urinary tract obstruction in male infants is posterior urethral valves. Although the incidence has remained stable, the neonatal mortality for this disorder has improved due to early diagnosis and intensive neonatal care, thanks in part to the widespread use of prenatal ultrasound evaluations. In fact, the most common reason for the diagnosis of posterior urethral valves presently is the evaluation of infants for prenatal hydronephrosis. Since these children are often diagnosed early, the urethral obstruction can be alleviated rapidly through catheter insertion and eventual surgery, and their metabolic derangements can be normalized without delay, avoiding preventable infant mortality. Of the children that survive, however, early diagnosis has not had much effect on their long-term prognosis, as 30% still develop renal insufficiency before adolescence. A better understanding of the exact cause of the congenital obstruction of the male posterior urethra, prevention of postnatal bladder and renal injury, and the development of safe methods to treat urethral obstruction prenatally (and thereby avoiding the bladder and renal damage due to obstructive uropathy are the goals for the care of children with posterior urethral valves[1].

Complexity, parameter sensitivity and parameter transferability in the modelling of floodplain inundation

Science.gov (United States)

Bates, P. D.; Neal, J. C.; Fewtrell, T. J.

2012-12-01

In this we paper we consider two related questions. First, we address the issue of how much physical complexity is necessary in a model in order to simulate floodplain inundation to within validation data error. This is achieved through development of a single code/multiple physics hydraulic model (LISFLOOD-FP) where different degrees of complexity can be switched on or off. Different configurations of this code are applied to four benchmark test cases, and compared to the results of a number of industry standard models. Second we address the issue of how parameter sensitivity and transferability change with increasing complexity using numerical experiments with models of different physical and geometric intricacy. Hydraulic models are a good example system with which to address such generic modelling questions as: (1) they have a strong physical basis; (2) there is only one set of equations to solve; (3) they require only topography and boundary conditions as input data; and (4) they typically require only a single free parameter, namely boundary friction. In terms of complexity required we show that for the problem of sub-critical floodplain inundation a number of codes of different dimensionality and resolution can be found to fit uncertain model validation data equally well, and that in this situation Occam's razor emerges as a useful logic to guide model selection. We find also find that model skill usually improves more rapidly with increases in model spatial resolution than increases in physical complexity, and that standard approaches to testing hydraulic models against laboratory data or analytical solutions may fail to identify this important fact. Lastly, we find that in benchmark testing studies significant differences can exist between codes with identical numerical solution techniques as a result of auxiliary choices regarding the specifics of model implementation that are frequently unreported by code developers. As a consequence, making sound

Trypan blue-assisted posterior capsulorhexis in pediatric cataract surgery

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Lotfy A

2017-01-01

Full Text Available Ayman Lotfy,1,2 Ayman Abdelrahman1,2 1Ophthalmology Department, Zagazig University Hospital, 2Alpha Vision Center, Zagazig, Egypt Purpose: To evaluate the safety and efficacy of staining the posterior capsule with trypan blue during capsulorhexis in pediatric cataract surgery.Patients and methods: This was a prospective randomized comparative study carried out at Alpha Vision Center, Zagazig, Egypt. This study included 2 groups of children with pediatric cataract randomly allocated to undergo irrigation and aspiration. In the trypan group, which included 11 eyes, trypan blue was used to stain the posterior capsule during posterior capsulorhexis. In the control group, which included 10 eyes, no staining was performed. All surgeries were performed by the same surgeon. The 2 groups were compared for criteria such as completion of capsulorhexis, disruption of vitreous face and in-the-bag intraocular lens implantation.Results: This study included 21 eyes of 16 patients (age range: 6 months–4 years. A statistically significant difference was observed for the following parameters between the 2 groups: capsulorhexis completion (P=0.04, vitreous face disruption (P=0.01 and in-the-bag intraocular lens implantation (P=0.022.Conclusion: This study suggests that staining of the posterior capsule during capsulorhexis in pediatric cataract operation gives better results than capsulorhexis without staining. The stain changes the capsule texture making capsulorhexis easier with fewer complications. Keywords: staining, capsulorhexis, pediatric, cataract, trypan

Parameter estimation of variable-parameter nonlinear Muskingum model using excel solver

Science.gov (United States)

Kang, Ling; Zhou, Liwei

2018-02-01

Abstract . The Muskingum model is an effective flood routing technology in hydrology and water resources Engineering. With the development of optimization technology, more and more variable-parameter Muskingum models were presented to improve effectiveness of the Muskingum model in recent decades. A variable-parameter nonlinear Muskingum model (NVPNLMM) was proposed in this paper. According to the results of two real and frequently-used case studies by various models, the NVPNLMM could obtain better values of evaluation criteria, which are used to describe the superiority of the estimated outflows and compare the accuracies of flood routing using various models, and the optimal estimated outflows by the NVPNLMM were closer to the observed outflows than the ones by other models.

SU-E-T-144: Bayesian Inference of Local Relapse Data Using a Poisson-Based Tumour Control Probability Model

Energy Technology Data Exchange (ETDEWEB)

La Russa, D [The Ottawa Hospital Cancer Centre, Ottawa, ON (Canada)

2015-06-15

Purpose: The purpose of this project is to develop a robust method of parameter estimation for a Poisson-based TCP model using Bayesian inference. Methods: Bayesian inference was performed using the PyMC3 probabilistic programming framework written in Python. A Poisson-based TCP regression model that accounts for clonogen proliferation was fit to observed rates of local relapse as a function of equivalent dose in 2 Gy fractions for a population of 623 stage-I non-small-cell lung cancer patients. The Slice Markov Chain Monte Carlo sampling algorithm was used to sample the posterior distributions, and was initiated using the maximum of the posterior distributions found by optimization. The calculation of TCP with each sample step required integration over the free parameter α, which was performed using an adaptive 24-point Gauss-Legendre quadrature. Convergence was verified via inspection of the trace plot and posterior distribution for each of the fit parameters, as well as with comparisons of the most probable parameter values with their respective maximum likelihood estimates. Results: Posterior distributions for α, the standard deviation of α (σ), the average tumour cell-doubling time (Td), and the repopulation delay time (Tk), were generated assuming α/β = 10 Gy, and a fixed clonogen density of 10{sup 7} cm−{sup 3}. Posterior predictive plots generated from samples from these posterior distributions are in excellent agreement with the observed rates of local relapse used in the Bayesian inference. The most probable values of the model parameters also agree well with maximum likelihood estimates. Conclusion: A robust method of performing Bayesian inference of TCP data using a complex TCP model has been established.

Bayesian near-boundary analysis in basic macroeconomic time series models

NARCIS (Netherlands)

M.D. de Pooter (Michiel); F. Ravazzolo (Francesco); R. Segers (René); H.K. van Dijk (Herman)

2008-01-01

textabstractSeveral lessons learnt from a Bayesian analysis of basic macroeconomic time series models are presented for the situation where some model parameters have substantial posterior probability near the boundary of the parameter region. This feature refers to near-instability within dynamic

Posterior colporrhaphy does not affect the urethral closure mechanism

DEFF Research Database (Denmark)

Khayyami, Yasmine; Lose, Gunnar; Klarskov, Niels

2018-01-01

prolapse ≥stage II were examined before and after posterior colporrhaphy. We performed prolapse staging according to the Pelvic Organ Prolapse Quantification system, UPR measurements at rest, during squeezing and straining, and standardized stress tests with 300 ml saline. The women filled out...... International Consultation on Incontinence-Urinary incontinence (ICIQ-UI) short forms. The sample size was 18, with a power of 99.9% and a level of significance of 5%. Parameters were compared using paired t tests or Fisher's exact test, where appropriate; p values ... significant. RESULTS: Eighteen women with posterior vaginal wall prolapse ≥stage II were recruited. One woman did not undergo surgery. There were no changes in urethral pressure at rest (p = 0.4), during squeezing (p = 0.2) or straining (p = 0.2), before and after surgery. The results of the stress tests...

Universally sloppy parameter sensitivities in systems biology models.

Directory of Open Access Journals (Sweden)

Ryan N Gutenkunst

2007-10-01

Full Text Available Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.

Universally sloppy parameter sensitivities in systems biology models.

Science.gov (United States)

Gutenkunst, Ryan N; Waterfall, Joshua J; Casey, Fergal P; Brown, Kevin S; Myers, Christopher R; Sethna, James P

2007-10-01

Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.

Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models.

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Jonathan R Karr

2015-05-01

Full Text Available Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model's structure and in silico "experimental" data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation.

Systematic parameter inference in stochastic mesoscopic modeling

Energy Technology Data Exchange (ETDEWEB)

Lei, Huan; Yang, Xiu [Pacific Northwest National Laboratory, Richland, WA 99352 (United States); Li, Zhen [Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States); Karniadakis, George Em, E-mail: george_karniadakis@brown.edu [Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States)

2017-02-01

We propose a method to efficiently determine the optimal coarse-grained force field in mesoscopic stochastic simulations of Newtonian fluid and polymer melt systems modeled by dissipative particle dynamics (DPD) and energy conserving dissipative particle dynamics (eDPD). The response surfaces of various target properties (viscosity, diffusivity, pressure, etc.) with respect to model parameters are constructed based on the generalized polynomial chaos (gPC) expansion using simulation results on sampling points (e.g., individual parameter sets). To alleviate the computational cost to evaluate the target properties, we employ the compressive sensing method to compute the coefficients of the dominant gPC terms given the prior knowledge that the coefficients are “sparse”. The proposed method shows comparable accuracy with the standard probabilistic collocation method (PCM) while it imposes a much weaker restriction on the number of the simulation samples especially for systems with high dimensional parametric space. Fully access to the response surfaces within the confidence range enables us to infer the optimal force parameters given the desirable values of target properties at the macroscopic scale. Moreover, it enables us to investigate the intrinsic relationship between the model parameters, identify possible degeneracies in the parameter space, and optimize the model by eliminating model redundancies. The proposed method provides an efficient alternative approach for constructing mesoscopic models by inferring model parameters to recover target properties of the physics systems (e.g., from experimental measurements), where those force field parameters and formulation cannot be derived from the microscopic level in a straight forward way.

International comparative evaluation of knee replacement with fixed or mobile-bearing posterior-stabilized prostheses.

Science.gov (United States)

Graves, Stephen; Sedrakyan, Art; Baste, Valborg; Gioe, Terence J; Namba, Robert; Martínez Cruz, Olga; Stea, Susanna; Paxton, Elizabeth; Banerjee, Samprit; Isaacs, Abby J; Robertsson, Otto

2014-12-17

Posterior-stabilized total knee prostheses were introduced to address instability secondary to loss of posterior cruciate ligament function, and they have either fixed or mobile bearings. Mobile bearings were developed to improve the function and longevity of total knee prostheses. In this study, the International Consortium of Orthopaedic Registries used a distributed health data network to study a large cohort of posterior-stabilized prostheses to determine if the outcome of a posterior-stabilized total knee prosthesis differs depending on whether it has a fixed or mobile-bearing design. Aggregated registry data were collected with a distributed health data network that was developed by the International Consortium of Orthopaedic Registries to reduce barriers to participation (e.g., security, proprietary, legal, and privacy issues) that have the potential to occur with the alternate centralized data warehouse approach. A distributed health data network is a decentralized model that allows secure storage and analysis of data from different registries. Each registry provided data on mobile and fixed-bearing posterior-stabilized prostheses implanted between 2001 and 2010. Only prostheses associated with primary total knee arthroplasties performed for the treatment of osteoarthritis were included. Prostheses with all types of fixation were included except for those with the rarely used reverse hybrid (cementless tibial and cemented femoral components) fixation. The use of patellar resurfacing was reported. The outcome of interest was time to first revision (for any reason). Multivariate meta-analysis was performed with linear mixed models with survival probability as the unit of analysis. This study includes 137,616 posterior-stabilized knee prostheses; 62% were in female patients, and 17.6% had a mobile bearing. The results of the fixed-effects model indicate that in the first year the mobile-bearing posterior-stabilized prostheses had a significantly higher hazard

Distrofia corneana policromática posterior Polychromatic posterior corneal dystrophy

OpenAIRE

Patrick Frensel de Moraes Tzelikis; Ulisses Roberto dos Santos; Marco Antônio Guarino Tanure; Fernando Cançado Trindade

2007-01-01

Os autores descrevem quatro raros casos de distrofia corneana policromática posterior, ainda não descrito na literatura nacional. Observam-se opacidades puntiformes, policromáticas, de tamanho uniforme, localização estromal profunda, distribuídas de limbo a limbo e que não interferem na acuidade visual. É apresentada uma revisão dos casos de distrofia pré-Descemet existentes na literatura.The authors describe four rare cases of polychromatic posterior corneal dystrophy, not describe in nation...

Test models for improving filtering with model errors through stochastic parameter estimation

International Nuclear Information System (INIS)

Gershgorin, B.; Harlim, J.; Majda, A.J.

2010-01-01

The filtering skill for turbulent signals from nature is often limited by model errors created by utilizing an imperfect model for filtering. Updating the parameters in the imperfect model through stochastic parameter estimation is one way to increase filtering skill and model performance. Here a suite of stringent test models for filtering with stochastic parameter estimation is developed based on the Stochastic Parameterization Extended Kalman Filter (SPEKF). These new SPEKF-algorithms systematically correct both multiplicative and additive biases and involve exact formulas for propagating the mean and covariance including the parameters in the test model. A comprehensive study is presented of robust parameter regimes for increasing filtering skill through stochastic parameter estimation for turbulent signals as the observation time and observation noise are varied and even when the forcing is incorrectly specified. The results here provide useful guidelines for filtering turbulent signals in more complex systems with significant model errors.

[Ultrasound measurement of fetal posterior fossa at 11 to 13⁺⁶ gestational weeks for screening open spina bifida].

Science.gov (United States)

Qin, Feng-Zhen; Li, Sheng-Li; Wen, Hua-Xuan; Ouyang, Yu-Rong; Zheng, Qiong; Bi, Jing-Ru

2014-06-01

To establish the normal reference ranges of transabdominal ultrasound measurements of the posterior fossa structure in fetuses at 11 to 13⁺⁶ gestational weeks and explore their clinical value in screening open spina bifida (OSB). Between January, 2013 and September, 541 randomly selected normal fetuses underwent nuchal translucency at the gestational age 11 to 13⁺⁶ weeks. The parameters of the posterior fossa were measured in mid-sagittal view of the fetal face and the axial view of the transverse cerebellum insonated through the anterior fontanel by transabdominal ultrasound to establish the normal reference ranges. The measurements were obtained from 3 fetuses with OSB for comparison with the reference ranges. In normal fetuses, the parameters of the posterior fossa measured in the two views showed no significant differences (P>0.05). Two high echogenic lines were observed in normal fetuses, as compared with one in fetuses with OSB representing the posterior border of the brain stem and the anterior border of the fourth ventricle. The line between the posterior border of the fourth ventricle and the anterior border of the cisterna magna was not displayed in fetuses with OSB. The anteroposterior diameters of the brain stem, the fourth ventricle, and cisterna magna all increased in positive correlation with the crown-lump length in normal fetuses. In the 3 OSB fetuses, the anteroposterior diameter of the brain stem exceeded the 95th percentile and the anteroposterior diameter of fourth ventrical-cisterner magena was below the 5th percentile of the reference range for CRL; the brain stem to fourth ventrical-cisterner magena anteroposterior diameter ratio was increased to above 1. The established normal reference ranges of the parameters of fetal posterior fossa may provide assistance in early OSB detection. The absence of the posterior border of the fourth ventricle and the anterior border of the cisterna magna and a brainstem to fourth ventrical

Bayesian calibration of terrestrial ecosystem models: a study of advanced Markov chain Monte Carlo methods

Science.gov (United States)

Lu, Dan; Ricciuto, Daniel; Walker, Anthony; Safta, Cosmin; Munger, William

2017-09-01

Calibration of terrestrial ecosystem models is important but challenging. Bayesian inference implemented by Markov chain Monte Carlo (MCMC) sampling provides a comprehensive framework to estimate model parameters and associated uncertainties using their posterior distributions. The effectiveness and efficiency of the method strongly depend on the MCMC algorithm used. In this work, a differential evolution adaptive Metropolis (DREAM) algorithm is used to estimate posterior distributions of 21 parameters for the data assimilation linked ecosystem carbon (DALEC) model using 14 years of daily net ecosystem exchange data collected at the Harvard Forest Environmental Measurement Site eddy-flux tower. The calibration of DREAM results in a better model fit and predictive performance compared to the popular adaptive Metropolis (AM) scheme. Moreover, DREAM indicates that two parameters controlling autumn phenology have multiple modes in their posterior distributions while AM only identifies one mode. The application suggests that DREAM is very suitable to calibrate complex terrestrial ecosystem models, where the uncertain parameter size is usually large and existence of local optima is always a concern. In addition, this effort justifies the assumptions of the error model used in Bayesian calibration according to the residual analysis. The result indicates that a heteroscedastic, correlated, Gaussian error model is appropriate for the problem, and the consequent constructed likelihood function can alleviate the underestimation of parameter uncertainty that is usually caused by using uncorrelated error models.

Posterior Pole Sparing Laser Photocoagulation Combined with Intravitreal Bevacizumab Injection in Posterior Retinopathy of Prematurity

Directory of Open Access Journals (Sweden)

Rebecca Kim

2014-01-01

Full Text Available Purpose. To report the results of the posterior pole sparing laser photocoagulation combined with intravitreal bevacizumab injection (IVB in retinopathy of prematurity (ROP. Methods. A retrospective chart review of premature babies with ROP, all of whom received laser photocoagulation with IVB. Eleven eyes of 6 infants with advanced zone I ROP underwent laser ablation sparing posterior pole with concurrent IVB. The results were compared with those of full-laser treatment combined with IVB to 8 eyes of 5 infants with advanced ROP without involvement of the posterior pole. Results. The posterior pole sparing laser with IVB was performed with zone I, stage 3+ ROP at the mean postmenstrual age of 36 weeks and 5 days. The plus sign decreased significantly at postoperative day 1, the neovascular proliferation regressed by postoperative week 1, and the normal vascularization started at postoperative day 32 on the average. Two months after treatment, vascularization of the spared avascular area was completed. There was no macular dragging, tractional retinal detachment, foveal destruction by laser scars, or any other adverse event. No significant anatomical differences were identified from those of full-laser ablation combined with IVB. Conclusions. Posterior pole sparing laser with IVB can give favorable results without destruction of posterior pole retina.

Multiclass Posterior Probability Twin SVM for Motor Imagery EEG Classification.

Science.gov (United States)

She, Qingshan; Ma, Yuliang; Meng, Ming; Luo, Zhizeng

2015-01-01

Motor imagery electroencephalography is widely used in the brain-computer interface systems. Due to inherent characteristics of electroencephalography signals, accurate and real-time multiclass classification is always challenging. In order to solve this problem, a multiclass posterior probability solution for twin SVM is proposed by the ranking continuous output and pairwise coupling in this paper. First, two-class posterior probability model is constructed to approximate the posterior probability by the ranking continuous output techniques and Platt's estimating method. Secondly, a solution of multiclass probabilistic outputs for twin SVM is provided by combining every pair of class probabilities according to the method of pairwise coupling. Finally, the proposed method is compared with multiclass SVM and twin SVM via voting, and multiclass posterior probability SVM using different coupling approaches. The efficacy on the classification accuracy and time complexity of the proposed method has been demonstrated by both the UCI benchmark datasets and real world EEG data from BCI Competition IV Dataset 2a, respectively.

Exploiting intrinsic fluctuations to identify model parameters.

Science.gov (United States)

Zimmer, Christoph; Sahle, Sven; Pahle, Jürgen

2015-04-01

Parameterisation of kinetic models plays a central role in computational systems biology. Besides the lack of experimental data of high enough quality, some of the biggest challenges here are identification issues. Model parameters can be structurally non-identifiable because of functional relationships. Noise in measured data is usually considered to be a nuisance for parameter estimation. However, it turns out that intrinsic fluctuations in particle numbers can make parameters identifiable that were previously non-identifiable. The authors present a method to identify model parameters that are structurally non-identifiable in a deterministic framework. The method takes time course recordings of biochemical systems in steady state or transient state as input. Often a functional relationship between parameters presents itself by a one-dimensional manifold in parameter space containing parameter sets of optimal goodness. Although the system's behaviour cannot be distinguished on this manifold in a deterministic framework it might be distinguishable in a stochastic modelling framework. Their method exploits this by using an objective function that includes a measure for fluctuations in particle numbers. They show on three example models, immigration-death, gene expression and Epo-EpoReceptor interaction, that this resolves the non-identifiability even in the case of measurement noise with known amplitude. The method is applied to partially observed recordings of biochemical systems with measurement noise. It is simple to implement and it is usually very fast to compute. This optimisation can be realised in a classical or Bayesian fashion.

Endoscopic Management of Posterior Epistaxis

OpenAIRE

Paul, J.; Kanotra, Sohit Paul; Kanotra, Sonika

2011-01-01

The traditional method of management of posterior epistaxis has been with anteroposterior nasal packing. Apart from the high failure rate of 26–50% reported in various series, nasal packing is associated with marked discomfort and several complications. In order to avoid nasal packing, we started doing endoscopic cauterization in cases of posterior epistaxis. A total of 23 patients with posterior epistaxis were subjected to nasal endoscopy with the intent to stop bleeding by cauterization of ...

Incorporating model parameter uncertainty into inverse treatment planning

International Nuclear Information System (INIS)

Lian Jun; Xing Lei

2004-01-01

Radiobiological treatment planning depends not only on the accuracy of the models describing the dose-response relation of different tumors and normal tissues but also on the accuracy of tissue specific radiobiological parameters in these models. Whereas the general formalism remains the same, different sets of model parameters lead to different solutions and thus critically determine the final plan. Here we describe an inverse planning formalism with inclusion of model parameter uncertainties. This is made possible by using a statistical analysis-based frameset developed by our group. In this formalism, the uncertainties of model parameters, such as the parameter a that describes tissue-specific effect in the equivalent uniform dose (EUD) model, are expressed by probability density function and are included in the dose optimization process. We found that the final solution strongly depends on distribution functions of the model parameters. Considering that currently available models for computing biological effects of radiation are simplistic, and the clinical data used to derive the models are sparse and of questionable quality, the proposed technique provides us with an effective tool to minimize the effect caused by the uncertainties in a statistical sense. With the incorporation of the uncertainties, the technique has potential for us to maximally utilize the available radiobiology knowledge for better IMRT treatment

Bayesian posterior distributions without Markov chains.

Science.gov (United States)

Cole, Stephen R; Chu, Haitao; Greenland, Sander; Hamra, Ghassan; Richardson, David B

2012-03-01

Bayesian posterior parameter distributions are often simulated using Markov chain Monte Carlo (MCMC) methods. However, MCMC methods are not always necessary and do not help the uninitiated understand Bayesian inference. As a bridge to understanding Bayesian inference, the authors illustrate a transparent rejection sampling method. In example 1, they illustrate rejection sampling using 36 cases and 198 controls from a case-control study (1976-1983) assessing the relation between residential exposure to magnetic fields and the development of childhood cancer. Results from rejection sampling (odds ratio (OR) = 1.69, 95% posterior interval (PI): 0.57, 5.00) were similar to MCMC results (OR = 1.69, 95% PI: 0.58, 4.95) and approximations from data-augmentation priors (OR = 1.74, 95% PI: 0.60, 5.06). In example 2, the authors apply rejection sampling to a cohort study of 315 human immunodeficiency virus seroconverters (1984-1998) to assess the relation between viral load after infection and 5-year incidence of acquired immunodeficiency syndrome, adjusting for (continuous) age at seroconversion and race. In this more complex example, rejection sampling required a notably longer run time than MCMC sampling but remained feasible and again yielded similar results. The transparency of the proposed approach comes at a price of being less broadly applicable than MCMC.

Posterior labral injury in contact athletes.

Science.gov (United States)

Mair, S D; Zarzour, R H; Speer, K P

1998-01-01

Nine athletes (seven football offensive linemen, one defensive lineman, and one lacrosse player) were found at arthroscopy to have posterior labral detachment from the glenoid. In our series, this lesion is specific to contact athletes who engage their opponents with arms in front of the body. All patients had pain with bench pressing and while participating in their sport, diminishing their ability to play effectively. Conservative measures were ineffective in relieving their symptoms. Examination under anesthesia revealed symmetric glenohumeral translation bilaterally, without evidence of posterior instability. Treatment consisted of glenoid rim abradement and posterior labral repair with a bioabsorbable tack. All patients returned to complete at least one full season of contact sports and weightlifting without pain (minimum follow-up, > or = 2 years). Although many injuries leading to subluxation of the glenohumeral joint occur when an unanticipated force is applied, contact athletes ready their shoulder muscles in anticipation of impact with opponents. This leads to a compressive force at the glenohumeral joint. We hypothesize that, in combination with a posteriorly directed force at impact, the resultant vector is a shearing force to the posterior labrum and articular surface. Repeated exposure leads to posterior labral detachment without capsular injury. Posterior labral reattachment provides consistently good results, allowing the athlete to return to competition.

Model parameters conditioning on regional hydrologic signatures for process-based design flood estimation in ungauged basins.

Science.gov (United States)

Biondi, Daniela; De Luca, Davide Luciano

2015-04-01

The use of rainfall-runoff models represents an alternative to statistical approaches (such as at-site or regional flood frequency analysis) for design flood estimation, and constitutes an answer to the increasing need for synthetic design hydrographs (SDHs) associated to a specific return period. However, the lack of streamflow observations and the consequent high uncertainty associated with parameter estimation, usually pose serious limitations to the use of process-based approaches in ungauged catchments, which in contrast represent the majority in practical applications. This work presents the application of a Bayesian procedure that, for a predefined rainfall-runoff model, allows for the assessment of posterior parameters distribution, using the limited and uncertain information available for the response of an ungauged catchment (Bulygina et al. 2009; 2011). The use of regional estimates of river flow statistics, interpreted as hydrological signatures that measure theoretically relevant system process behaviours (Gupta et al. 2008), within this framework represents a valuable option and has shown significant developments in recent literature to constrain the plausible model response and to reduce the uncertainty in ungauged basins. In this study we rely on the first three L-moments of annual streamflow maxima, for which regressions are available from previous studies (Biondi et al. 2012; Laio et al. 2011). The methodology was carried out for a catchment located in southern Italy, and used within a Monte Carlo scheme (MCs) considering both event-based and continuous simulation approaches for design flood estimation. The applied procedure offers promising perspectives to perform model calibration and uncertainty analysis in ungauged basins; moreover, in the context of design flood estimation, process-based methods coupled with MCs approach have the advantage of providing simulated floods uncertainty analysis that represents an asset in risk-based decision

Parameter discovery in stochastic biological models using simulated annealing and statistical model checking.

Science.gov (United States)

Hussain, Faraz; Jha, Sumit K; Jha, Susmit; Langmead, Christopher J

2014-01-01

Stochastic models are increasingly used to study the behaviour of biochemical systems. While the structure of such models is often readily available from first principles, unknown quantitative features of the model are incorporated into the model as parameters. Algorithmic discovery of parameter values from experimentally observed facts remains a challenge for the computational systems biology community. We present a new parameter discovery algorithm that uses simulated annealing, sequential hypothesis testing, and statistical model checking to learn the parameters in a stochastic model. We apply our technique to a model of glucose and insulin metabolism used for in-silico validation of artificial pancreata and demonstrate its effectiveness by developing parallel CUDA-based implementation for parameter synthesis in this model.

Bony landmark between the attachment of the medial meniscus posterior root and the posterior cruciate ligament: CT and MR imaging assessment

Energy Technology Data Exchange (ETDEWEB)

Fujii, Masataka; Furumatsu, Takayuki; Miyazawa, Shinichi; Kodama, Yuya; Hino, Tomohito; Kamatsuki, Yusuke; Ozaki, Toshifumi [Okayama University Graduate School of Medicine, Dentistry, and Pharmaceutical Sciences, Department of Orthopaedic Surgery, Science of Functional Recovery and Reconstruction, Okayama (Japan)

2017-08-15

(1) To reveal the prevalence of the bony recess (posterior dimple) and (2) to determine the position of the posterior dimple on the tibial plateau using three-dimensional computed tomography (3DCT). In this study, a retrospective review of 112 patients was performed to identify the posterior dimple and to evaluate its position on 3DCT. Magnetic resonance images (MRIs) were also used to determine the positional relationship among the posterior cruciate ligament (PCL), medial meniscus posterior insertion (MMPI), and posterior dimple. The posterior dimple was observed in 100 of 112 knees (89.3%) on 3DCT. The center of the posterior dimple was 13.6 ± 0.8 mm from the medial tibial eminence apex. MRI showed that the posterior dimple separated the tibial attachment of the PCL and MMPI. This is the first study to discuss the prevalence and position of the bony recess in the posterior intercondylar fossa. (orig.)

Bony landmark between the attachment of the medial meniscus posterior root and the posterior cruciate ligament: CT and MR imaging assessment

International Nuclear Information System (INIS)

Fujii, Masataka; Furumatsu, Takayuki; Miyazawa, Shinichi; Kodama, Yuya; Hino, Tomohito; Kamatsuki, Yusuke; Ozaki, Toshifumi

2017-01-01

(1) To reveal the prevalence of the bony recess (posterior dimple) and (2) to determine the position of the posterior dimple on the tibial plateau using three-dimensional computed tomography (3DCT). In this study, a retrospective review of 112 patients was performed to identify the posterior dimple and to evaluate its position on 3DCT. Magnetic resonance images (MRIs) were also used to determine the positional relationship among the posterior cruciate ligament (PCL), medial meniscus posterior insertion (MMPI), and posterior dimple. The posterior dimple was observed in 100 of 112 knees (89.3%) on 3DCT. The center of the posterior dimple was 13.6 ± 0.8 mm from the medial tibial eminence apex. MRI showed that the posterior dimple separated the tibial attachment of the PCL and MMPI. This is the first study to discuss the prevalence and position of the bony recess in the posterior intercondylar fossa. (orig.)

Establishing statistical models of manufacturing parameters

International Nuclear Information System (INIS)

Senevat, J.; Pape, J.L.; Deshayes, J.F.

1991-01-01

This paper reports on the effect of pilgering and cold-work parameters on contractile strain ratio and mechanical properties that were investigated using a large population of Zircaloy tubes. Statistical models were established between: contractile strain ratio and tooling parameters, mechanical properties (tensile test, creep test) and cold-work parameters, and mechanical properties and stress-relieving temperature

Some tests for parameter constancy in cointegrated VAR-models

DEFF Research Database (Denmark)

Hansen, Henrik; Johansen, Søren

1999-01-01

Some methods for the evaluation of parameter constancy in vector autoregressive (VAR) models are discussed. Two different ways of re-estimating the VAR model are proposed; one in which all parameters are estimated recursively based upon the likelihood function for the first observations, and anot...... be applied to test the constancy of the long-run parameters in the cointegrated VAR-model. All results are illustrated using a model for the term structure of interest rates on US Treasury securities. ......Some methods for the evaluation of parameter constancy in vector autoregressive (VAR) models are discussed. Two different ways of re-estimating the VAR model are proposed; one in which all parameters are estimated recursively based upon the likelihood function for the first observations......, and another in which the cointegrating relations are estimated recursively from a likelihood function, where the short-run parameters have been concentrated out. We suggest graphical procedures based on recursively estimated eigenvalues to evaluate the constancy of the long-run parameters in the model...

Edge Modeling by Two Blur Parameters in Varying Contrasts.

Science.gov (United States)

Seo, Suyoung

2018-06-01

This paper presents a method of modeling edge profiles with two blur parameters, and estimating and predicting those edge parameters with varying brightness combinations and camera-to-object distances (COD). First, the validity of the edge model is proven mathematically. Then, it is proven experimentally with edges from a set of images captured for specifically designed target sheets and with edges from natural images. Estimation of the two blur parameters for each observed edge profile is performed with a brute-force method to find parameters that produce global minimum errors. Then, using the estimated blur parameters, actual blur parameters of edges with arbitrary brightness combinations are predicted using a surface interpolation method (i.e., kriging). The predicted surfaces show that the two blur parameters of the proposed edge model depend on both dark-side edge brightness and light-side edge brightness following a certain global trend. This is similar across varying CODs. The proposed edge model is compared with a one-blur parameter edge model using experiments of the root mean squared error for fitting the edge models to each observed edge profile. The comparison results suggest that the proposed edge model has superiority over the one-blur parameter edge model in most cases where edges have varying brightness combinations.

Imaging findings in posterior instability of the shoulder

International Nuclear Information System (INIS)

Harish, Srinivasan; Rebello, Ryan; O'Neill, John; Nagar, Arpit; Moro, Jaydeep; Pugh, David

2008-01-01

Posterior shoulder instability refers to the symptoms and signs resulting from excessive posterior translation of the humerus. Magnetic resonance (MR) imaging is the radiological modality of choice in the diagnostic assessment of posterior instability. Computed tomography (CT) is useful in the evaluation of osseous abnormalities associated with posterior instability. A detailed description of the posterior osseous and labroligamentous abnormalities has evolved recently, and many variant lesions of the posteroinferior labrum and/or capsular structures have been described. As the recommended surgical management of lesions associated with posterior instability is a lesion-specific approach, awareness of the specific lesions that have been described in association with posterior instability helps in pre-surgical planning. The purpose of this article is to review the classification of, and injury mechanisms leading to, posterior shoulder instability and to describe imaging findings associated with posterior instability, with emphasis on MR imaging. (orig.)

Imaging findings in posterior instability of the shoulder

Energy Technology Data Exchange (ETDEWEB)

Harish, Srinivasan; Rebello, Ryan; O' Neill, John [St. Joseph' s Healthcare, Department of Diagnostic Imaging, Hamilton, ON (Canada); McMaster University, Faculty of Health Sciences, Hamilton (Canada); Nagar, Arpit [St. Joseph' s Healthcare, Department of Diagnostic Imaging, Hamilton, ON (Canada); Moro, Jaydeep [St. Joseph' s Healthcare, Department of Orthopedic Surgery, Hamilton, ON (Canada); McMaster University, Faculty of Health Sciences, Hamilton (Canada); Pugh, David [Brantford General Hospital, Department of Orthopedic Surgery, Brantford, ON (Canada)

2008-08-15

Posterior shoulder instability refers to the symptoms and signs resulting from excessive posterior translation of the humerus. Magnetic resonance (MR) imaging is the radiological modality of choice in the diagnostic assessment of posterior instability. Computed tomography (CT) is useful in the evaluation of osseous abnormalities associated with posterior instability. A detailed description of the posterior osseous and labroligamentous abnormalities has evolved recently, and many variant lesions of the posteroinferior labrum and/or capsular structures have been described. As the recommended surgical management of lesions associated with posterior instability is a lesion-specific approach, awareness of the specific lesions that have been described in association with posterior instability helps in pre-surgical planning. The purpose of this article is to review the classification of, and injury mechanisms leading to, posterior shoulder instability and to describe imaging findings associated with posterior instability, with emphasis on MR imaging. (orig.)

Primary Posterior Mediastinum Hydatid Cyst

International Nuclear Information System (INIS)

Ahmed, M.; Eid, A. F.; Sheikh, M. Y.; Yiannakou, N.

2014-01-01

Primary posterior mediastinal hydatid cyst is a serious health problem for the Mediterranean countries. We diagnosed a case of a 46-year-old female with a primary posterior mediastinum hydatid cyst on CT and MRI. It was provisionally identified as either a hydatid cyst or bronchogenic cyst or neuroenteric cyst. CT guided aspiration with 18 gauge needle confirmed as hydatid sand. This is very rare in this population but it should be kept in mind when one is looking at any cyst in the posterior mediastinum. (author)

Treatment implications of posterior fossa ependymoma subgroups.

Science.gov (United States)

Ramaswamy, Vijay; Taylor, Michael D

2016-11-15

Posterior fossa ependymoma comprises two distinct molecular entities, ependymoma_posterior fossa A (EPN_PFA) and ependymoma_posterior fossa B (EPN_PFB), with differentiable gene expression profiles. As yet, the response of the two entities to treatment is unclear. To determine the relationship between the two molecular subgroups of posterior fossa ependymoma and treatment, we studied a cohort of 820 patients with molecularly profiled, clinically annotated posterior fossa ependymomas. We found that the strongest predictor of poor outcome in patients with posterior fossa ependymoma across the entire age spectrum was molecular subgroup EPN_PFA, which was recently reported in the paper entitled "Therapeutic impact of cytoreductive surgery and irradiation of posterior fossa ependymoma in the molecular era: a retrospective multicohort analysis" in the Journal of Clinical Oncology. Patients with incompletely resected EPN_PFA tumors had a very poor outcome despite receiving adjuvant radiation therapy, whereas a substantial proportion of patients with EPN_PFB tumors can be cured with surgery alone.

Identifyability measures to select the parameters to be estimated in a solid-state fermentation distributed parameter model.

Science.gov (United States)

da Silveira, Christian L; Mazutti, Marcio A; Salau, Nina P G

2016-07-08

Process modeling can lead to of advantages such as helping in process control, reducing process costs and product quality improvement. This work proposes a solid-state fermentation distributed parameter model composed by seven differential equations with seventeen parameters to represent the process. Also, parameters estimation with a parameters identifyability analysis (PIA) is performed to build an accurate model with optimum parameters. Statistical tests were made to verify the model accuracy with the estimated parameters considering different assumptions. The results have shown that the model assuming substrate inhibition better represents the process. It was also shown that eight from the seventeen original model parameters were nonidentifiable and better results were obtained with the removal of these parameters from the estimation procedure. Therefore, PIA can be useful to estimation procedure, since it may reduce the number of parameters that can be evaluated. Further, PIA improved the model results, showing to be an important procedure to be taken. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:905-917, 2016. © 2016 American Institute of Chemical Engineers.

Environmental Transport Input Parameters for the Biosphere Model

Energy Technology Data Exchange (ETDEWEB)

M. A. Wasiolek

2003-06-27

This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (TWP) (BSC 2003 [163602]). Some documents in Figure 1-1 may be under development and not available when this report is issued. This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA), but access to the listed documents is not required to understand the contents of this report. This report is one of the reports that develops input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2003 [160699]) describes the conceptual model, the mathematical model, and the input parameters. The purpose of this analysis is to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or volcanic ash). The analysis was performed in accordance with the TWP (BSC 2003 [163602]). This analysis develops values of parameters associated with many features, events, and processes (FEPs) applicable to the reference biosphere (DTN: M00303SEPFEPS2.000 [162452]), which are addressed in the biosphere model (BSC 2003 [160699]). The treatment of these FEPs is described in BSC (2003 [160699

Environmental Transport Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

Wasiolek, M. A.

2003-01-01

This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (TWP) (BSC 2003 [163602]). Some documents in Figure 1-1 may be under development and not available when this report is issued. This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA), but access to the listed documents is not required to understand the contents of this report. This report is one of the reports that develops input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2003 [160699]) describes the conceptual model, the mathematical model, and the input parameters. The purpose of this analysis is to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or volcanic ash). The analysis was performed in accordance with the TWP (BSC 2003 [163602]). This analysis develops values of parameters associated with many features, events, and processes (FEPs) applicable to the reference biosphere (DTN: M00303SEPFEPS2.000 [162452]), which are addressed in the biosphere model (BSC 2003 [160699]). The treatment of these FEPs is described in BSC (2003 [160699], Section 6.2). Parameter values

Parameter estimation in stochastic rainfall-runoff models

DEFF Research Database (Denmark)

Jonsdottir, Harpa; Madsen, Henrik; Palsson, Olafur Petur

2006-01-01

A parameter estimation method for stochastic rainfall-runoff models is presented. The model considered in the paper is a conceptual stochastic model, formulated in continuous-discrete state space form. The model is small and a fully automatic optimization is, therefore, possible for estimating all...... the parameter values are optimal for simulation or prediction. The data originates from Iceland and the model is designed for Icelandic conditions, including a snow routine for mountainous areas. The model demands only two input data series, precipitation and temperature and one output data series...

Posterior column reconstruction improves fusion rates at the level of osteotomy in three-column posterior-based osteotomies.

Science.gov (United States)

Lewis, Stephen J; Mohanty, Chandan; Gazendam, Aaron M; Kato, So; Keshen, Sam G; Lewis, Noah D; Magana, Sofia P; Perlmutter, David; Cape, Jennifer

2018-03-01

To determine the incidence of pseudarthrosis at the osteotomy site after three-column spinal osteotomies (3-COs) with posterior column reconstruction. 82 consecutive adult 3-COs (66 patients) with a minimum of 2-year follow-up were retrospectively reviewed. All cases underwent posterior 3-COs with two-rod constructs. The inferior facets of the proximal level were reduced to the superior facets of the distal level. If that was not possible, a structural piece of bone graft either from the local resection or a local rib was slotted in the posterior column defect to re-establish continual structural posterior bone across the lateral margins of the resection. No interbody cages were used at the level of the osteotomy. There were 34 thoracic osteotomies, 47 lumbar osteotomies and one sacral osteotomy with a mean follow-up of 52 (24-126) months. All cases underwent posterior column reconstructions described above and the addition of interbody support or additional posterior rods was not performed for fusion at the osteotomy level. Among them, 29 patients underwent one or more revision surgeries. There were three definite cases of pseudarthrosis at the osteotomy site (4%). Six revisions were also performed for pseudarthrosis at other levels. Restoration of the structural integrity of the posterior column in three-column posterior-based osteotomies was associated with > 95% fusion rate at the level of the osteotomy. Pseudarthrosis at other levels was the second most common reason for revision following adjacent segment disease in the long-term follow-up.

A method for model identification and parameter estimation

International Nuclear Information System (INIS)

Bambach, M; Heinkenschloss, M; Herty, M

2013-01-01

We propose and analyze a new method for the identification of a parameter-dependent model that best describes a given system. This problem arises, for example, in the mathematical modeling of material behavior where several competing constitutive equations are available to describe a given material. In this case, the models are differential equations that arise from the different constitutive equations, and the unknown parameters are coefficients in the constitutive equations. One has to determine the best-suited constitutive equations for a given material and application from experiments. We assume that the true model is one of the N possible parameter-dependent models. To identify the correct model and the corresponding parameters, we can perform experiments, where for each experiment we prescribe an input to the system and observe a part of the system state. Our approach consists of two stages. In the first stage, for each pair of models we determine the experiment, i.e. system input and observation, that best differentiates between the two models, and measure the distance between the two models. Then we conduct N(N − 1) or, depending on the approach taken, N(N − 1)/2 experiments and use the result of the experiments as well as the previously computed model distances to determine the true model. We provide sufficient conditions on the model distances and measurement errors which guarantee that our approach identifies the correct model. Given the model, we identify the corresponding model parameters in the second stage. The problem in the second stage is a standard parameter estimation problem and we use a method suitable for the given application. We illustrate our approach on three examples, including one where the models are elliptic partial differential equations with different parameterized right-hand sides and an example where we identify the constitutive equation in a problem from computational viscoplasticity. (paper)

Building a Model Using Bayesian Network for Assessment of Posterior Probabilities of Falling From Height at Workplaces

Directory of Open Access Journals (Sweden)

Seyed Shamseddin Alizadeh

2014-12-01

Full Text Available Background: Falls from height are one of the main causes of fatal occupational injuries. The objective of this study was to present a model for estimating occurrence probability of falling from height. Methods: In order to make a list of factors affecting falls, we used four expert group's judgment, literature review and an available database. Then the validity and reliability of designed questionnaire were determined and Bayesian networks were built. The built network, nodes and curves were quantified. For network sensitivity analysis, four types of analysis carried out. Results: A Bayesian network for assessment of posterior probabilities of falling from height proposed. The presented Bayesian network model shows the interrelationships among 37 causes affecting the falling from height and can calculate its posterior probabilities. The most important factors affecting falling were Non-compliance with safety instructions for work at height (0.127, Lack of safety equipment for work at height (0.094 and Lack of safety instructions for work at height (0.071 respectively. Conclusion: The proposed Bayesian network used to determine how different causes could affect the falling from height at work. The findings of this study can be used to decide on the falling accident prevention programs.

Application of lumped-parameter models

DEFF Research Database (Denmark)

Ibsen, Lars Bo; Liingaard, Morten

This technical report concerns the lumped-parameter models for a suction caisson with a ratio between skirt length and foundation diameter equal to 1/2, embedded into an viscoelastic soil. The models are presented for three different values of the shear modulus of the subsoil (section 1.1). Subse...

Oral azithromycin for treatment of posterior blepharitis.

Science.gov (United States)

Igami, Thais Zamudio; Holzchuh, Ricardo; Osaki, Tammy Hentona; Santo, Ruth Miyuki; Kara-Jose, Newton; Hida, Richard Y

2011-10-01

To evaluate the effects of oral azithromycin in patients with posterior blepharitis. Twenty-six eyes of 13 patients with posterior blepharitis diagnosed by a qualified ophthalmologist were enrolled in this study. Patients were instructed to use oral azithromycin 500 mg per day for 3 days in 3 cycles with 7-day intervals. Subjective clinical outcomes were graded and scored 1 day before and 30 days after the end of the treatment (53 days after initiating the treatment) based on severity scores of: (1) eyelid debris; (2) eyelid telangiectasia; (3) swelling of the eyelid margin; (4) redness of the eyelid margin; and (5) ocular mucus secretion. For the assessment of global efficacy, patients were asked by the investigator to rate the subjective symptoms (eyelid itching, ocular itching, eyelid hyperemia, ocular hyperemia, ocular mucus secretion, photophobia, foreign body sensation, and dry eye sensation) on a scale of 0 (no symptoms) to 5 (severe symptoms). Break-up time, Schirmer I test, corneal fluorescein staining score, and rose bengal staining score were also performed in all patients. All clinical outcomes scoring showed statistically significant improvement after oral azithromycin, except for eyelid swelling. Average subjective symptom grading improved statistically after treatment with oral azithromycin, except for eyelid hyperemia, photophobia, and foreign body sensation. Average tear film break-up time values showed statistically significant improvement after the treatment with oral azithromycin. No statistically significant improvement was observed on average values of Schirmer I test, corneal fluorescein staining score, and rose bengal staining score. The combination of multiple clinical parameters shown in this study supports the clinical efficacy of pulsed oral azithromycin therapy for the management of posterior blepharitis.

Probabilistic parameter estimation of activated sludge processes using Markov Chain Monte Carlo.

Science.gov (United States)

Sharifi, Soroosh; Murthy, Sudhir; Takács, Imre; Massoudieh, Arash

2014-03-01

One of the most important challenges in making activated sludge models (ASMs) applicable to design problems is identifying the values of its many stoichiometric and kinetic parameters. When wastewater characteristics data from full-scale biological treatment systems are used for parameter estimation, several sources of uncertainty, including uncertainty in measured data, external forcing (e.g. influent characteristics), and model structural errors influence the value of the estimated parameters. This paper presents a Bayesian hierarchical modeling framework for the probabilistic estimation of activated sludge process parameters. The method provides the joint probability density functions (JPDFs) of stoichiometric and kinetic parameters by updating prior information regarding the parameters obtained from expert knowledge and literature. The method also provides the posterior correlations between the parameters, as well as a measure of sensitivity of the different constituents with respect to the parameters. This information can be used to design experiments to provide higher information content regarding certain parameters. The method is illustrated using the ASM1 model to describe synthetically generated data from a hypothetical biological treatment system. The results indicate that data from full-scale systems can narrow down the ranges of some parameters substantially whereas the amount of information they provide regarding other parameters is small, due to either large correlations between some of the parameters or a lack of sensitivity with respect to the parameters. Copyright © 2013 Elsevier Ltd. All rights reserved.

Mixed linear-nonlinear fault slip inversion: Bayesian inference of model, weighting, and smoothing parameters

Science.gov (United States)

Fukuda, J.; Johnson, K. M.

2009-12-01

Studies utilizing inversions of geodetic data for the spatial distribution of coseismic slip on faults typically present the result as a single fault plane and slip distribution. Commonly the geometry of the fault plane is assumed to be known a priori and the data are inverted for slip. However, sometimes there is not strong a priori information on the geometry of the fault that produced the earthquake and the data is not always strong enough to completely resolve the fault geometry. We develop a method to solve for the full posterior probability distribution of fault slip and fault geometry parameters in a Bayesian framework using Monte Carlo methods. The slip inversion problem is particularly challenging because it often involves multiple data sets with unknown relative weights (e.g. InSAR, GPS), model parameters that are related linearly (slip) and nonlinearly (fault geometry) through the theoretical model to surface observations, prior information on model parameters, and a regularization prior to stabilize the inversion. We present the theoretical framework and solution method for a Bayesian inversion that can handle all of these aspects of the problem. The method handles the mixed linear/nonlinear nature of the problem through combination of both analytical least-squares solutions and Monte Carlo methods. We first illustrate and validate the inversion scheme using synthetic data sets. We then apply the method to inversion of geodetic data from the 2003 M6.6 San Simeon, California earthquake. We show that the uncertainty in strike and dip of the fault plane is over 20 degrees. We characterize the uncertainty in the slip estimate with a volume around the mean fault solution in which the slip most likely occurred. Slip likely occurred somewhere in a volume that extends 5-10 km in either direction normal to the fault plane. We implement slip inversions with both traditional, kinematic smoothing constraints on slip and a simple physical condition of uniform stress

Pontine encephalocele and abnormalities of the posterior fossa following transclival endoscopic endonasal surgery.

Science.gov (United States)

Koutourousiou, Maria; Filho, Francisco Vaz Guimaraes; Costacou, Tina; Fernandez-Miranda, Juan C; Wang, Eric W; Snyderman, Carl H; Rothfus, William E; Gardner, Paul A

2014-08-01

Transclival endoscopic endonasal surgery (EES) has recently been used for the treatment of posterior fossa tumors. The optimal method of reconstruction of large clival defects following EES has not been established. A morphometric analysis of the posterior fossa was performed in patients who underwent transclival EES to compare those with observed postoperative anatomical changes (study group) to 50 normal individuals (anatomical control group) and 41 matched transclival cases with preserved posterior fossa anatomy (case-control group) using the same parameters. Given the absence of clival bone following transclival EES, the authors used the line between the anterior commissure and the basion as an equivalent to the clival plane to evaluate the location of the pons. Four parameters were studied and compared in the two populations: the pontine location/displacement, the maximum anteroposterior (AP) diameter of the pons, the maximum AP diameter of the fourth ventricle, and the cervicomedullary angle (CMA). All measurements were performed on midsagittal 3-month postoperative MR images in the study group. Among 103 posterior fossa tumors treated with transclival EES, 14 cases (13.6%) with postoperative posterior fossa anatomy changes were identified. The most significant change was anterior displacement of the pons (transclival pontine encephalocele) compared with the normal location in the anatomical control group (p 50% of the clivus) and dura. Nine (64.3%) of the 14 patients were overweight (body mass index [BMI] > 25 kg/m(2)). An association between BMI and the degree of pontine encephalocele was observed, but did not reach statistical significance. The use of a fat graft as part of the reconstruction technique following transclival EES with dural opening was the single significant factor that prevented pontine displacement (p = 0.02), associated with 91% lower odds of pontine encephalocele (OR = 0.09, 95% CI 0.01-0.77). The effect of fat graft reconstruction was

A simulation of water pollution model parameter estimation

Science.gov (United States)

Kibler, J. F.

1976-01-01

A parameter estimation procedure for a water pollution transport model is elaborated. A two-dimensional instantaneous-release shear-diffusion model serves as representative of a simple transport process. Pollution concentration levels are arrived at via modeling of a remote-sensing system. The remote-sensed data are simulated by adding Gaussian noise to the concentration level values generated via the transport model. Model parameters are estimated from the simulated data using a least-squares batch processor. Resolution, sensor array size, and number and location of sensor readings can be found from the accuracies of the parameter estimates.

Uncertainty Analysis Based on Sparse Grid Collocation and Quasi-Monte Carlo Sampling with Application in Groundwater Modeling

Science.gov (United States)

Zhang, G.; Lu, D.; Ye, M.; Gunzburger, M.

2011-12-01

Markov Chain Monte Carlo (MCMC) methods have been widely used in many fields of uncertainty analysis to estimate the posterior distributions of parameters and credible intervals of predictions in the Bayesian framework. However, in practice, MCMC may be computationally unaffordable due to slow convergence and the excessive number of forward model executions required, especially when the forward model is expensive to compute. Both disadvantages arise from the curse of dimensionality, i.e., the posterior distribution is usually a multivariate function of parameters. Recently, sparse grid method has been demonstrated to be an effective technique for coping with high-dimensional interpolation or integration problems. Thus, in order to accelerate the forward model and avoid the slow convergence of MCMC, we propose a new method for uncertainty analysis based on sparse grid interpolation and quasi-Monte Carlo sampling. First, we construct a polynomial approximation of the forward model in the parameter space by using the sparse grid interpolation. This approximation then defines an accurate surrogate posterior distribution that can be evaluated repeatedly at minimal computational cost. Second, instead of using MCMC, a quasi-Monte Carlo method is applied to draw samples in the parameter space. Then, the desired probability density function of each prediction is approximated by accumulating the posterior density values of all the samples according to the prediction values. Our method has the following advantages: (1) the polynomial approximation of the forward model on the sparse grid provides a very efficient evaluation of the surrogate posterior distribution; (2) the quasi-Monte Carlo method retains the same accuracy in approximating the PDF of predictions but avoids all disadvantages of MCMC. The proposed method is applied to a controlled numerical experiment of groundwater flow modeling. The results show that our method attains the same accuracy much more efficiently

Identification of ecosystem parameters by SDE-modelling

DEFF Research Database (Denmark)

Stochastic differential equations (SDEs) for ecosystem modelling have attracted increasing attention during recent years. The modelling has mostly been through simulation experiments in order to analyse how system noise propagates through the ordinary differential equation formulation of ecosystem...... models. Estimation of parameters in SDEs is, however, possible by combining Kalman filter techniques and likelihood estimation. By modelling parameters as random walks it is possible to identify linear as well as non-linear interactions between ecosystem components. By formulating a simple linear SDE...

Model-based Quantile Regression for Discrete Data

KAUST Repository

Padellini, Tullia

2018-04-10

Quantile regression is a class of methods voted to the modelling of conditional quantiles. In a Bayesian framework quantile regression has typically been carried out exploiting the Asymmetric Laplace Distribution as a working likelihood. Despite the fact that this leads to a proper posterior for the regression coefficients, the resulting posterior variance is however affected by an unidentifiable parameter, hence any inferential procedure beside point estimation is unreliable. We propose a model-based approach for quantile regression that considers quantiles of the generating distribution directly, and thus allows for a proper uncertainty quantification. We then create a link between quantile regression and generalised linear models by mapping the quantiles to the parameter of the response variable, and we exploit it to fit the model with R-INLA. We extend it also in the case of discrete responses, where there is no 1-to-1 relationship between quantiles and distribution\\'s parameter, by introducing continuous generalisations of the most common discrete variables (Poisson, Binomial and Negative Binomial) to be exploited in the fitting.

Endoscopic management of posterior epistaxis.

Science.gov (United States)

Paul, J; Kanotra, Sohit Paul; Kanotra, Sonika

2011-04-01

The traditional method of management of posterior epistaxis has been with anteroposterior nasal packing. Apart from the high failure rate of 26-50% reported in various series, nasal packing is associated with marked discomfort and several complications. In order to avoid nasal packing, we started doing endoscopic cauterization in cases of posterior epistaxis. A total of 23 patients with posterior epistaxis were subjected to nasal endoscopy with the intent to stop bleeding by cauterization of the bleeding vessel. Of these, in four cases unsuspected diagnosis was made. Of the remaining 19, in three patients, the bleeding point could not be localized accurately and these patients were managed by anteroposterior packing. The rest of the 16 patients were managed by endoscopic cauterization. In four patients, there was recurrence of bleeding within 24 h. In one of these, cauterization controlled the bleeding while in the rest nasal packing had to be resorted to. Thus, of the 23 patients of posterior epistaxis subjected to nasal endoscopy, we could avoid nasal packing in 17 (74%). To conclude, endoscopic nasal cauterization is recommended as the first line to treatment in all cases of posterior epistaxis. This will not only prevent the uncomfortable and potentially dangerous nasal packing but also help in finding the underlying pathology.

Application of Parameter Estimation for Diffusions and Mixture Models

DEFF Research Database (Denmark)

Nolsøe, Kim

The first part of this thesis proposes a method to determine the preferred number of structures, their proportions and the corresponding geometrical shapes of an m-membered ring molecule. This is obtained by formulating a statistical model for the data and constructing an algorithm which samples...... with the posterior score function. From an application point of view this methology is easy to apply, since the optimal estimating function G(;Xt1 ; : : : ;Xtn ) is equal to the classical optimal estimating function, plus a correction term which takes into account the prior information. The methology is particularly...

Incorporating rainfall uncertainty in a SWAT model: the river Zenne basin (Belgium) case study

Science.gov (United States)

Tolessa Leta, Olkeba; Nossent, Jiri; van Griensven, Ann; Bauwens, Willy

2013-04-01

. Subsequently, we only considered the most sensitive parameters for parameter optimization and UA. To explicitly account for the stream flow uncertainty, we assumed that the stream flow measurement error increases linearly with the stream flow value. To assess the uncertainty and infer posterior distributions of the parameters, we used a Markov Chain Monte Carlo (MCMC) sampler - differential evolution adaptive metropolis (DREAM) that uses sampling from an archive of past states to generate candidate points in each individual chain. It is shown that the marginal posterior distributions of the rainfall multipliers vary widely between individual events, as a consequence of rainfall measurement errors and the spatial variability of the rain. Only few of the rainfall events are well defined. The marginal posterior distributions of the SWAT model parameter values are well defined and identified by DREAM, within their prior ranges. The posterior distributions of output uncertainty parameter values also show that the stream flow data is highly uncertain. The approach of using rainfall multipliers to treat rainfall uncertainty for a complex model has an impact on the model parameter marginal posterior distributions and on the model results Corresponding author: Tel.: +32 (0)2629 3027; fax: +32(0)2629 3022. E-mail: otolessa@vub.ac.be

Spatio-temporal modeling of nonlinear distributed parameter systems

CERN Document Server

Li, Han-Xiong

2011-01-01

The purpose of this volume is to provide a brief review of the previous work on model reduction and identifi cation of distributed parameter systems (DPS), and develop new spatio-temporal models and their relevant identifi cation approaches. In this book, a systematic overview and classifi cation on the modeling of DPS is presented fi rst, which includes model reduction, parameter estimation and system identifi cation. Next, a class of block-oriented nonlinear systems in traditional lumped parameter systems (LPS) is extended to DPS, which results in the spatio-temporal Wiener and Hammerstein s

Models for estimating photosynthesis parameters from in situ production profiles

Science.gov (United States)

Kovač, Žarko; Platt, Trevor; Sathyendranath, Shubha; Antunović, Suzana

2017-12-01

The rate of carbon assimilation in phytoplankton primary production models is mathematically prescribed with photosynthesis irradiance functions, which convert a light flux (energy) into a material flux (carbon). Information on this rate is contained in photosynthesis parameters: the initial slope and the assimilation number. The exactness of parameter values is crucial for precise calculation of primary production. Here we use a model of the daily production profile based on a suite of photosynthesis irradiance functions and extract photosynthesis parameters from in situ measured daily production profiles at the Hawaii Ocean Time-series station Aloha. For each function we recover parameter values, establish parameter distributions and quantify model skill. We observe that the choice of the photosynthesis irradiance function to estimate the photosynthesis parameters affects the magnitudes of parameter values as recovered from in situ profiles. We also tackle the problem of parameter exchange amongst the models and the effect it has on model performance. All models displayed little or no bias prior to parameter exchange, but significant bias following parameter exchange. The best model performance resulted from using optimal parameter values. Model formulation was extended further by accounting for spectral effects and deriving a spectral analytical solution for the daily production profile. The daily production profile was also formulated with time dependent growing biomass governed by a growth equation. The work on parameter recovery was further extended by exploring how to extract photosynthesis parameters from information on watercolumn production. It was demonstrated how to estimate parameter values based on a linearization of the full analytical solution for normalized watercolumn production and from the solution itself, without linearization. The paper complements previous works on photosynthesis irradiance models by analysing the skill and consistency of

Management of posterior urethral disruption injuries.

Science.gov (United States)

Myers, Jeremy B; McAninch, Jack W

2009-03-01

Posterior urethral disruption is a traumatic injury to the male urethra, which most often results from pelvic fracture. After trauma, the distraction defect between the two ends of the urethra often scars and becomes fibrotic, blocking the urethra and bladder emptying. Increasing evidence suggests that many posterior urethral disruptions occur at the junction between the membranous urethra and the bulbar urethra, which is distal to the rhabdosphincter. In the acute setting, when a posterior urethral disruption is suspected, retrograde urethrography should be performed. Posterior urethral disruptions can be managed acutely by realignment of the urethra over a urethral catheter or by placement of a suprapubic catheter for bladder drainage only. Once fibrosis has stabilized, the patient can undergo posterior urethroplasty. In most cases, this procedure can be performed via a perineal approach in a single-stage surgery. The results of this single-stage perineal urethroplasty are excellent, and a patent urethra can be re-established in the majority of men who undergo surgery.

GEMSFITS: Code package for optimization of geochemical model parameters and inverse modeling

International Nuclear Information System (INIS)

Miron, George D.; Kulik, Dmitrii A.; Dmytrieva, Svitlana V.; Wagner, Thomas

2015-01-01

Highlights: • Tool for generating consistent parameters against various types of experiments. • Handles a large number of experimental data and parameters (is parallelized). • Has a graphical interface and can perform statistical analysis on the parameters. • Tested on fitting the standard state Gibbs free energies of aqueous Al species. • Example on fitting interaction parameters of mixing models and thermobarometry. - Abstract: GEMSFITS is a new code package for fitting internally consistent input parameters of GEM (Gibbs Energy Minimization) geochemical–thermodynamic models against various types of experimental or geochemical data, and for performing inverse modeling tasks. It consists of the gemsfit2 (parameter optimizer) and gfshell2 (graphical user interface) programs both accessing a NoSQL database, all developed with flexibility, generality, efficiency, and user friendliness in mind. The parameter optimizer gemsfit2 includes the GEMS3K chemical speciation solver ( (http://gems.web.psi.ch/GEMS3K)), which features a comprehensive suite of non-ideal activity- and equation-of-state models of solution phases (aqueous electrolyte, gas and fluid mixtures, solid solutions, (ad)sorption. The gemsfit2 code uses the robust open-source NLopt library for parameter fitting, which provides a selection between several nonlinear optimization algorithms (global, local, gradient-based), and supports large-scale parallelization. The gemsfit2 code can also perform comprehensive statistical analysis of the fitted parameters (basic statistics, sensitivity, Monte Carlo confidence intervals), thus supporting the user with powerful tools for evaluating the quality of the fits and the physical significance of the model parameters. The gfshell2 code provides menu-driven setup of optimization options (data selection, properties to fit and their constraints, measured properties to compare with computed counterparts, and statistics). The practical utility, efficiency, and

Inverse cutting of posterior lamellar corneal grafts by a femtosecond laser.

Science.gov (United States)

Hjortdal, Jesper; Nielsen, Esben; Vestergaard, Anders; Søndergaard, Anders

2012-01-01

Posterior lamellar grafting of the cornea has become the preferred technique for treatment of corneal endothelial dysfunction. Posterior lamellar grafts are usually cut by a micro-keratome or a femto-second laser after the epithelial side of the donor cornea has been applanated. This approach often results in variable central graft thickness in different grafts and an increase in graft thickness towards the periphery in every graft. The purpose of this study was to evaluate if posterior lamellar grafts can be prepared from the endothelial side by a femto-second laser, resulting in reproducible, thin grafts of even thickness. A CZM 500 kHz Visumax femto-second laser was used. Organ cultured donor grafts were mounted in an artifical anterior chamber with the endothelial side up and out. Posterior grafts of 7.8 mm diameter and 130 micron thickness were prepared by femto-second laser cutting. A standard DSAEK procedure was performed in 10 patients with Fuchs endothelial dystrophy. Patients were followed-up regularly and evaluated by measurement of complications, visual acuity, corneal thickness (Pentacam HR), and endothelial cell density. Femto-laser cutting of grafts and surgery was uncomplicated. Rebubbling was necessary in 5 of 10 cases (normally only in 1 of 20 cases). All grafts were attached and cleared up during the first few weeks. After six months, the average visual acuity was 0.30 (range: 0.16 to 0.50), corneal thickness was 0.58 mm (range 0.51 to 0.63), and endothelial cell density was 1.570 per sq. mm (range: 1.400 to 2.000 cells per sq. mm). The grafts were of uniform thickness, but substantial interface haze was present in most grafts. Posterior lamellar corneal grafts can be prepared from the endothelial side using a femto-second laser. All grafts were clear after 6 months with satisfying endothelial cell counts. Poor visual acuity caused by interface scatter was observed in most patients. Femto-second laser cutting parameters needs to be optimised to

Identification of parameters of discrete-continuous models

International Nuclear Information System (INIS)

Cekus, Dawid; Warys, Pawel

2015-01-01

In the paper, the parameters of a discrete-continuous model have been identified on the basis of experimental investigations and formulation of optimization problem. The discrete-continuous model represents a cantilever stepped Timoshenko beam. The mathematical model has been formulated and solved according to the Lagrange multiplier formalism. Optimization has been based on the genetic algorithm. The presented proceeding’s stages make the identification of any parameters of discrete-continuous systems possible

Identification of parameters of discrete-continuous models

Energy Technology Data Exchange (ETDEWEB)

Cekus, Dawid, E-mail: cekus@imipkm.pcz.pl; Warys, Pawel, E-mail: warys@imipkm.pcz.pl [Institute of Mechanics and Machine Design Foundations, Czestochowa University of Technology, Dabrowskiego 73, 42-201 Czestochowa (Poland)

2015-03-10

In the paper, the parameters of a discrete-continuous model have been identified on the basis of experimental investigations and formulation of optimization problem. The discrete-continuous model represents a cantilever stepped Timoshenko beam. The mathematical model has been formulated and solved according to the Lagrange multiplier formalism. Optimization has been based on the genetic algorithm. The presented proceeding’s stages make the identification of any parameters of discrete-continuous systems possible.

Identifying the connective strength between model parameters and performance criteria

Directory of Open Access Journals (Sweden)

B. Guse

2017-11-01

Full Text Available In hydrological models, parameters are used to represent the time-invariant characteristics of catchments and to capture different aspects of hydrological response. Hence, model parameters need to be identified based on their role in controlling the hydrological behaviour. For the identification of meaningful parameter values, multiple and complementary performance criteria are used that compare modelled and measured discharge time series. The reliability of the identification of hydrologically meaningful model parameter values depends on how distinctly a model parameter can be assigned to one of the performance criteria. To investigate this, we introduce the new concept of connective strength between model parameters and performance criteria. The connective strength assesses the intensity in the interrelationship between model parameters and performance criteria in a bijective way. In our analysis of connective strength, model simulations are carried out based on a latin hypercube sampling. Ten performance criteria including Nash–Sutcliffe efficiency (NSE, Kling–Gupta efficiency (KGE and its three components (alpha, beta and r as well as RSR (the ratio of the root mean square error to the standard deviation for different segments of the flow duration curve (FDC are calculated. With a joint analysis of two regression tree (RT approaches, we derive how a model parameter is connected to different performance criteria. At first, RTs are constructed using each performance criterion as the target variable to detect the most relevant model parameters for each performance criterion. Secondly, RTs are constructed using each parameter as the target variable to detect which performance criteria are impacted by changes in the values of one distinct model parameter. Based on this, appropriate performance criteria are identified for each model parameter. In this study, a high bijective connective strength between model parameters and performance criteria

Agricultural and Environmental Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

Kaylie Rasmuson; Kurt Rautenstrauch

2003-01-01

This analysis is one of nine technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. It documents input parameters for the biosphere model, and supports the use of the model to develop Biosphere Dose Conversion Factors (BDCF). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in the biosphere Technical Work Plan (TWP, BSC 2003a). It should be noted that some documents identified in Figure 1-1 may be under development and therefore not available at the time this document is issued. The ''Biosphere Model Report'' (BSC 2003b) describes the ERMYN and its input parameters. This analysis report, ANL-MGR-MD-000006, ''Agricultural and Environmental Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. This report defines and justifies values for twelve parameters required in the biosphere model. These parameters are related to use of contaminated groundwater to grow crops. The parameter values recommended in this report are used in the soil, plant, and carbon-14 submodels of the ERMYN

Delayed Single Stage Perineal Posterior Urethroplasty.

Science.gov (United States)

Ali, Shahzad; Shahnawaz; Shahzad, Iqbal; Baloch, Muhammad Umar

2015-06-01

To determine the delayed single stage perineal posterior urethroplasty for treatment of posterior urethral stricture/distraction defect. Descriptive case series. Department of Urology, Jinnah Postgraduate Medical Centre, Karachi, from January 2009 to December 2011. Patients were selected for delayed single stage perineal posterior urethroplasty for treatment of posterior urethral stricture / distraction defect. All were initially suprapubically catheterized followed by definitive surgery after at least 3 months. Thirty male patients were analyzed with a mean follow-up of 10 months, 2 patients were excluded as they developed failure in first 3 months postoperatively. Mean patient's age was 26.25 ± 7.9 years. On follow-up, 7 patients (23.3%) experienced recurrent stricture during first 10 months. Five (16.6%) patients were treated successfully with single direct visual internal urethrotomy. Two patients (6.6%) had more than one direct visual internal urethrotomy and considered failed. Re-do perineal urethroplasty was eventually performed. The overall success rate was 93.3% with permissive criteria allowing single direct visual internal urethrotomy and 76.6% with strict criteria allowing no more procedures postoperatively. Posterior anastomotic urethroplasty offers excellent long-term results to patients with posterior urethral trauma and distraction defect even after multiple prior procedures.

Verification Techniques for Parameter Selection and Bayesian Model Calibration Presented for an HIV Model

Science.gov (United States)

Wentworth, Mami Tonoe

Uncertainty quantification plays an important role when making predictive estimates of model responses. In this context, uncertainty quantification is defined as quantifying and reducing uncertainties, and the objective is to quantify uncertainties in parameter, model and measurements, and propagate the uncertainties through the model, so that one can make a predictive estimate with quantified uncertainties. Two of the aspects of uncertainty quantification that must be performed prior to propagating uncertainties are model calibration and parameter selection. There are several efficient techniques for these processes; however, the accuracy of these methods are often not verified. This is the motivation for our work, and in this dissertation, we present and illustrate verification frameworks for model calibration and parameter selection in the context of biological and physical models. First, HIV models, developed and improved by [2, 3, 8], describe the viral infection dynamics of an HIV disease. These are also used to make predictive estimates of viral loads and T-cell counts and to construct an optimal control for drug therapy. Estimating input parameters is an essential step prior to uncertainty quantification. However, not all the parameters are identifiable, implying that they cannot be uniquely determined by the observations. These unidentifiable parameters can be partially removed by performing parameter selection, a process in which parameters that have minimal impacts on the model response are determined. We provide verification techniques for Bayesian model calibration and parameter selection for an HIV model. As an example of a physical model, we employ a heat model with experimental measurements presented in [10]. A steady-state heat model represents a prototypical behavior for heat conduction and diffusion process involved in a thermal-hydraulic model, which is a part of nuclear reactor models. We employ this simple heat model to illustrate verification

Zener Diode Compact Model Parameter Extraction Using Xyce-Dakota Optimization.

Energy Technology Data Exchange (ETDEWEB)

Buchheit, Thomas E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Wilcox, Ian Zachary [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sandoval, Andrew J [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Reza, Shahed [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-12-01

This report presents a detailed process for compact model parameter extraction for DC circuit Zener diodes. Following the traditional approach of Zener diode parameter extraction, circuit model representation is defined and then used to capture the different operational regions of a real diode's electrical behavior. The circuit model contains 9 parameters represented by resistors and characteristic diodes as circuit model elements. The process of initial parameter extraction, the identification of parameter values for the circuit model elements, is presented in a way that isolates the dependencies between certain electrical parameters and highlights both the empirical nature of the extraction and portions of the real diode physical behavior which of the parameters are intended to represent. Optimization of the parameters, a necessary part of a robost parameter extraction process, is demonstrated using a 'Xyce-Dakota' workflow, discussed in more detail in the report. Among other realizations during this systematic approach of electrical model parameter extraction, non-physical solutions are possible and can be difficult to avoid because of the interdependencies between the different parameters. The process steps described are fairly general and can be leveraged for other types of semiconductor device model extractions. Also included in the report are recommendations for experiment setups for generating optimum dataset for model extraction and the Parameter Identification and Ranking Table (PIRT) for Zener diodes.

Hematomas na fossa craniana posterior Haematomata in the posterior fossa

Directory of Open Access Journals (Sweden)

Mário S. Cademartori

1969-09-01

Full Text Available São relatados 6 casos de hematomas sub-tentorias (um de hematoma subdural crônico, quatro de hematomas intra-cerebelares, um de hematoma extra-dural. Salientando a pequena freqüência dos hematomas da fossa craniana posterior, o autor mostra a necessidade de vários exames complementares para o diagnóstico exato, indispensável para a aplicação de terapêutica cirúrgica adequada.Six cases of sub-tentorial haematomata (one chronic sub-dural, four intra-cerebellar, one extra-dural are reported. Emphasizing the relative rarity of haematomata in the posterior cranial fossa, the author claims the necessity of complementary examinations for proper diagnosis, indispensable for adequate surgical treatment.

Posterior encephalopathy with vasospasm: MRI and angiography

International Nuclear Information System (INIS)

Weidauer, S.; Gaa, J.; Lanfermann, H.; Zanella, F.E.; Sitzer, M.; Hefner, R.

2003-01-01

Posterior encephalopathy is characterised by headache, impairment of consciousness, seizures and progressive visual loss. MRI shows bilateral, predominantly posterior, cortical and subcortical lesions with a distribution. Our aim was to analyse the MRI lesion pattern and angiographic findings because the pathophysiology of posterior encephalopathy is incompletely understood. We report three patients with clinical and imaging findings consistent with posterior encephalopathy who underwent serial MRI including diffusion-weighted imaging (DWI) and construction of apparent diffusion coefficient (ADC) maps, and four-vessel digital subtraction angiography (DSA). DWI revealed symmetrical subcortical and cortical parieto-occipital high signal. High and also low ADCs indicated probable vasogenic and cytotoxic oedema. On follow-up there was focal cortical laminar necrosis, while the white-matter lesions resolved almost completely, except in the arterial border zones. DSA revealed diffuse arterial narrowing, slightly more marked in the posterior circulation. These findings suggest that posterior encephalopathy may in some cases be due to diffuse, severe vasospasm affecting especially in the parieto-occipital grey matter, with its higher vulnerability to ischemia. Cerebral vasospasm due to digitoxin intoxication, resulting in posterior encephalopathy, has not yet been described previously. (orig.)

Brownian motion model with stochastic parameters for asset prices

Science.gov (United States)

Ching, Soo Huei; Hin, Pooi Ah

2013-09-01

The Brownian motion model may not be a completely realistic model for asset prices because in real asset prices the drift μ and volatility σ may change over time. Presently we consider a model in which the parameter x = (μ,σ) is such that its value x (t + Δt) at a short time Δt ahead of the present time t depends on the value of the asset price at time t + Δt as well as the present parameter value x(t) and m-1 other parameter values before time t via a conditional distribution. The Malaysian stock prices are used to compare the performance of the Brownian motion model with fixed parameter with that of the model with stochastic parameter.

Study on Parameters Modeling of Wind Turbines Using SCADA Data

Directory of Open Access Journals (Sweden)

Yonglong YAN

2014-08-01

Full Text Available Taking the advantage of the current massive monitoring data from Supervisory Control and Data Acquisition (SCADA system of wind farm, it is of important significance for anomaly detection, early warning and fault diagnosis to build the data model of state parameters of wind turbines (WTs. The operational conditions and the relationships between the state parameters of wind turbines are complex. It is difficult to establish the model of state parameter accurately, and the modeling method of state parameters of wind turbines considering parameter selection is proposed. Firstly, by analyzing the characteristic of SCADA data, a reasonable range of data and monitoring parameters are chosen. Secondly, neural network algorithm is adapted, and the selection method of input parameters in the model is presented. Generator bearing temperature and cooling air temperature are regarded as target parameters, and the two models are built and input parameters of the models are selected, respectively. Finally, the parameter selection method in this paper and the method using genetic algorithm-partial least square (GA-PLS are analyzed comparatively, and the results show that the proposed methods are correct and effective. Furthermore, the modeling of two parameters illustrate that the method in this paper can applied to other state parameters of wind turbines.

Seven-parameter statistical model for BRDF in the UV band.

Science.gov (United States)

Bai, Lu; Wu, Zhensen; Zou, Xiren; Cao, Yunhua

2012-05-21

A new semi-empirical seven-parameter BRDF model is developed in the UV band using experimentally measured data. The model is based on the five-parameter model of Wu and the fourteen-parameter model of Renhorn and Boreman. Surface scatter, bulk scatter and retro-reflection scatter are considered. An optimizing modeling method, the artificial immune network genetic algorithm, is used to fit the BRDF measurement data over a wide range of incident angles. The calculation time and accuracy of the five- and seven-parameter models are compared. After fixing the seven parameters, the model can well describe scattering data in the UV band.

One-stage posterior approaches for treatment of thoracic spinal infection: Transforaminal and costotransversectomy, compared with anterior approach with posterior instrumentation.

Science.gov (United States)

Kao, Fu-Cheng; Tsai, Tsung-Ting; Niu, Chi-Chien; Lai, Po-Liang; Chen, Lih-Huei; Chen, Wen-Jer

2017-10-01

Treating thoracic infective spondylodiscitis with anterior surgical approaches carry a relatively high risk of perioperative and postoperative complications. Posterior approaches have been reported to result in lower complication rates than anterior procedures, but more evidence is needed to demonstrate the safety and efficacy of 1-stage posterior approaches for treating infectious thoracic spondylodiscitis.Preoperative and postoperative clinical data, of 18 patients who underwent 2 types of 1-stage posterior procedures, costotransversectomy and transforaminal thoracic interbody debridement and fusion and 7 patients who underwent anterior debridement and reconstruction with posterior instrumentation, were retrospectively assessed.The clinical outcomes of patients treated with 1-stage posterior approaches were generally good, with good infection control, back pain relief, kyphotic angle correction, and either partial or solid union for fusion status. Furthermore, they achieved shorter surgical time, fewer postoperative complications, and shorter hospital stay than the patients underwent anterior debridement with posterior instrumentation.The results suggested that treating thoracic spondylodiscitis with a single-stage posterior approach might prevent postoperative complications and avoid respiratory problems associated with anterior approaches. Single-stage posterior approaches would be recommended for thoracic spine infection, especially for patients with medical comorbidities.

Lumped-parameter Model of a Bucket Foundation

DEFF Research Database (Denmark)

Andersen, Lars; Ibsen, Lars Bo; Liingaard, Morten

2009-01-01

efficient model that can be applied in aero-elastic codes for fast evaluation of the dynamic structural response of wind turbines. The target solutions, utilised for calibration of the lumped-parameter models, are obtained by a coupled finite-element/boundaryelement scheme in the frequency domain......, and the quality of the models are tested in the time and frequency domains. It is found that precise results are achieved by lumped-parameter models with two to four internal degrees of freedom per displacement or rotation of the foundation. Further, coupling between the horizontal sliding and rocking cannot...

Source term modelling parameters for Project-90

International Nuclear Information System (INIS)

Shaw, W.; Smith, G.; Worgan, K.; Hodgkinson, D.; Andersson, K.

1992-04-01

This document summarises the input parameters for the source term modelling within Project-90. In the first place, the parameters relate to the CALIBRE near-field code which was developed for the Swedish Nuclear Power Inspectorate's (SKI) Project-90 reference repository safety assessment exercise. An attempt has been made to give best estimate values and, where appropriate, a range which is related to variations around base cases. It should be noted that the data sets contain amendments to those considered by KBS-3. In particular, a completely new set of inventory data has been incorporated. The information given here does not constitute a complete set of parameter values for all parts of the CALIBRE code. Rather, it gives the key parameter values which are used in the constituent models within CALIBRE and the associated studies. For example, the inventory data acts as an input to the calculation of the oxidant production rates, which influence the generation of a redox front. The same data is also an initial value data set for the radionuclide migration component of CALIBRE. Similarly, the geometrical parameters of the near-field are common to both sub-models. The principal common parameters are gathered here for ease of reference and avoidance of unnecessary duplication and transcription errors. (au)

Polynomial Chaos–Based Bayesian Inference of K-Profile Parameterization in a General Circulation Model of the Tropical Pacific

KAUST Repository

Sraj, Ihab

2016-08-26

The authors present a polynomial chaos (PC)-based Bayesian inference method for quantifying the uncertainties of the K-profile parameterization (KPP) within the MIT general circulation model (MITgcm) of the tropical Pacific. The inference of the uncertain parameters is based on a Markov chain Monte Carlo (MCMC) scheme that utilizes a newly formulated test statistic taking into account the different components representing the structures of turbulent mixing on both daily and seasonal time scales in addition to the data quality, and filters for the effects of parameter perturbations over those as a result of changes in the wind. To avoid the prohibitive computational cost of integrating the MITgcm model at each MCMC iteration, a surrogate model for the test statistic using the PC method is built. Because of the noise in the model predictions, a basis-pursuit-denoising (BPDN) compressed sensing approach is employed to determine the PC coefficients of a representative surrogate model. The PC surrogate is then used to evaluate the test statistic in the MCMC step for sampling the posterior of the uncertain parameters. Results of the posteriors indicate good agreement with the default values for two parameters of the KPP model, namely the critical bulk and gradient Richardson numbers; while the posteriors of the remaining parameters were barely informative. © 2016 American Meteorological Society.

Evaluation of Gaussian approximations for data assimilation in reservoir models

KAUST Repository

Iglesias, Marco A.

2013-07-14

The Bayesian framework is the standard approach for data assimilation in reservoir modeling. This framework involves characterizing the posterior distribution of geological parameters in terms of a given prior distribution and data from the reservoir dynamics, together with a forward model connecting the space of geological parameters to the data space. Since the posterior distribution quantifies the uncertainty in the geologic parameters of the reservoir, the characterization of the posterior is fundamental for the optimal management of reservoirs. Unfortunately, due to the large-scale highly nonlinear properties of standard reservoir models, characterizing the posterior is computationally prohibitive. Instead, more affordable ad hoc techniques, based on Gaussian approximations, are often used for characterizing the posterior distribution. Evaluating the performance of those Gaussian approximations is typically conducted by assessing their ability at reproducing the truth within the confidence interval provided by the ad hoc technique under consideration. This has the disadvantage of mixing up the approximation properties of the history matching algorithm employed with the information content of the particular observations used, making it hard to evaluate the effect of the ad hoc approximations alone. In this paper, we avoid this disadvantage by comparing the ad hoc techniques with a fully resolved state-of-the-art probing of the Bayesian posterior distribution. The ad hoc techniques whose performance we assess are based on (1) linearization around the maximum a posteriori estimate, (2) randomized maximum likelihood, and (3) ensemble Kalman filter-type methods. In order to fully resolve the posterior distribution, we implement a state-of-the art Markov chain Monte Carlo (MCMC) method that scales well with respect to the dimension of the parameter space, enabling us to study realistic forward models, in two space dimensions, at a high level of grid refinement. Our

Agricultural and Environmental Input Parameters for the Biosphere Model

Energy Technology Data Exchange (ETDEWEB)

Kaylie Rasmuson; Kurt Rautenstrauch

2003-06-20

This analysis is one of nine technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. It documents input parameters for the biosphere model, and supports the use of the model to develop Biosphere Dose Conversion Factors (BDCF). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in the biosphere Technical Work Plan (TWP, BSC 2003a). It should be noted that some documents identified in Figure 1-1 may be under development and therefore not available at the time this document is issued. The ''Biosphere Model Report'' (BSC 2003b) describes the ERMYN and its input parameters. This analysis report, ANL-MGR-MD-000006, ''Agricultural and Environmental Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. This report defines and justifies values for twelve parameters required in the biosphere model. These parameters are related to use of contaminated groundwater to grow crops. The parameter values recommended in this report are used in the soil, plant, and carbon-14 submodels of the ERMYN.

Uncertainty Quantification of GEOS-5 L-band Radiative Transfer Model Parameters Using Bayesian Inference and SMOS Observations

Science.gov (United States)

DeLannoy, Gabrielle J. M.; Reichle, Rolf H.; Vrugt, Jasper A.

2013-01-01

Uncertainties in L-band (1.4 GHz) radiative transfer modeling (RTM) affect the simulation of brightness temperatures (Tb) over land and the inversion of satellite-observed Tb into soil moisture retrievals. In particular, accurate estimates of the microwave soil roughness, vegetation opacity and scattering albedo for large-scale applications are difficult to obtain from field studies and often lack an uncertainty estimate. Here, a Markov Chain Monte Carlo (MCMC) simulation method is used to determine satellite-scale estimates of RTM parameters and their posterior uncertainty by minimizing the misfit between long-term averages and standard deviations of simulated and observed Tb at a range of incidence angles, at horizontal and vertical polarization, and for morning and evening overpasses. Tb simulations are generated with the Goddard Earth Observing System (GEOS-5) and confronted with Tb observations from the Soil Moisture Ocean Salinity (SMOS) mission. The MCMC algorithm suggests that the relative uncertainty of the RTM parameter estimates is typically less than 25 of the maximum a posteriori density (MAP) parameter value. Furthermore, the actual root-mean-square-differences in long-term Tb averages and standard deviations are found consistent with the respective estimated total simulation and observation error standard deviations of m3.1K and s2.4K. It is also shown that the MAP parameter values estimated through MCMC simulation are in close agreement with those obtained with Particle Swarm Optimization (PSO).

The Efficacy of Consensus Tree Methods for Summarizing Phylogenetic Relationships from a Posterior Sample of Trees Estimated from Morphological Data.

Science.gov (United States)

O'Reilly, Joseph E; Donoghue, Philip C J

2018-03-01

Consensus trees are required to summarize trees obtained through MCMC sampling of a posterior distribution, providing an overview of the distribution of estimated parameters such as topology, branch lengths, and divergence times. Numerous consensus tree construction methods are available, each presenting a different interpretation of the tree sample. The rise of morphological clock and sampled-ancestor methods of divergence time estimation, in which times and topology are coestimated, has increased the popularity of the maximum clade credibility (MCC) consensus tree method. The MCC method assumes that the sampled, fully resolved topology with the highest clade credibility is an adequate summary of the most probable clades, with parameter estimates from compatible sampled trees used to obtain the marginal distributions of parameters such as clade ages and branch lengths. Using both simulated and empirical data, we demonstrate that MCC trees, and trees constructed using the similar maximum a posteriori (MAP) method, often include poorly supported and incorrect clades when summarizing diffuse posterior samples of trees. We demonstrate that the paucity of information in morphological data sets contributes to the inability of MCC and MAP trees to accurately summarise of the posterior distribution. Conversely, majority-rule consensus (MRC) trees represent a lower proportion of incorrect nodes when summarizing the same posterior samples of trees. Thus, we advocate the use of MRC trees, in place of MCC or MAP trees, in attempts to summarize the results of Bayesian phylogenetic analyses of morphological data.

Spondylolisthesis and Posterior Instability

International Nuclear Information System (INIS)

Niggemann, P.; Beyer, H.K.; Frey, H.; Grosskurth, D.; Simons, P.; Kuchta, J.

2009-01-01

We present the case of a patient with a spondylolisthesis of L5 on S1 due to spondylolysis at the level L5/S1. The vertebral slip was fixed and no anterior instability was found. Using functional magnetic resonance imaging (MRI) in an upright MRI scanner, posterior instability at the level of the spondylolytic defect of L5 was demonstrated. A structure, probably the hypertrophic ligament flava, arising from the spondylolytic defect was displaced toward the L5 nerve root, and a bilateral contact of the displaced structure with the L5 nerve root was shown in extension of the spine. To our knowledge, this is the first case described of posterior instability in patients with spondylolisthesis. The clinical implications of posterior instability are unknown; however, it is thought that this disorder is common and that it can only be diagnosed using upright MRI

Spondylolisthesis and Posterior Instability

Energy Technology Data Exchange (ETDEWEB)

Niggemann, P.; Beyer, H.K.; Frey, H.; Grosskurth, D. (Privatpraxis fuer Upright MRT, Koeln (Germany)); Simons, P.; Kuchta, J. (Media Park Klinik, Koeln (Germany))

2009-04-15

We present the case of a patient with a spondylolisthesis of L5 on S1 due to spondylolysis at the level L5/S1. The vertebral slip was fixed and no anterior instability was found. Using functional magnetic resonance imaging (MRI) in an upright MRI scanner, posterior instability at the level of the spondylolytic defect of L5 was demonstrated. A structure, probably the hypertrophic ligament flava, arising from the spondylolytic defect was displaced toward the L5 nerve root, and a bilateral contact of the displaced structure with the L5 nerve root was shown in extension of the spine. To our knowledge, this is the first case described of posterior instability in patients with spondylolisthesis. The clinical implications of posterior instability are unknown; however, it is thought that this disorder is common and that it can only be diagnosed using upright MRI.

Grading nuclear, cortical and posterior subcapsular cataracts using an objective scatter index measured with a double-pass system.

Science.gov (United States)

Vilaseca, Meritxell; Romero, Maria José; Arjona, Montserrat; Luque, Sergio Oscar; Ondategui, Juan Carlos; Salvador, Antoni; Güell, José L; Artal, Pablo; Pujol, Jaume

2012-09-01

To evaluate objectively intraocular scattering in eyes with nuclear, cortical and posterior subcapsular cataracts by means of an objective scatter index (OSI) obtained from double-pass images. To compare the results with those obtained using clinical conventional procedures. In this prospective, observational, cross-sectional, non-consecutive case series study, 188 eyes with cataracts of 136 patients were analysed (123 eyes had nuclear, 41 eyes had cortical and 24 eyes had posterior subcapsular cataracts). The control group consisted of 117 eyes of 68 healthy patients. Patient examination included subjective refraction, best spectacle-corrected visual acuity (BSCVA), cataract grade using the lens opacities classification system III (LOCS III) and OSI. We found a decrease in the BSCVA and an increase in the OSI with increasing cataract grade. Statistically significant differences were observed when the OSI of eyes without cataracts and those with different LOCS III were compared. The comparison between the OSI and LOCS III reported good percentages of agreement regarding the number of eyes classified in equivalent levels: 72.4% (nuclear cataracts), 86.6% (cortical cataracts) and 84.3% (posterior subcapsular cataracts). A non-linear regression model was applied between OSI and BSCVA, which resulted in the following multiple correlation coefficients: r=0.878 (nuclear), r=0.843 (cortical) and r=0.844 (posterior subcapsular). The results of the study showed that OSI is a useful parameter for evaluating large amounts of intraocular scattering that can be used, in combination with other conventional procedures, as a valuable tool in clinical practice to grade cataracts objectively.

The mobilisation model and parameter sensitivity

International Nuclear Information System (INIS)

Blok, B.M.

1993-12-01

In the PRObabillistic Safety Assessment (PROSA) of radioactive waste in a salt repository one of the nuclide release scenario's is the subrosion scenario. A new subrosion model SUBRECN has been developed. In this model the combined effect of a depth-dependent subrosion, glass dissolution, and salt rise has been taken into account. The subrosion model SUBRECN and the implementation of this model in the German computer program EMOS4 is presented. A new computer program PANTER is derived from EMOS4. PANTER models releases of radionuclides via subrosion from a disposal site in a salt pillar into the biosphere. For uncertainty and sensitivity analyses the new subrosion model Latin Hypercube Sampling has been used for determine the different values for the uncertain parameters. The influence of the uncertainty in the parameters on the dose calculations has been investigated by the following sensitivity techniques: Spearman Rank Correlation Coefficients, Partial Rank Correlation Coefficients, Standardised Rank Regression Coefficients, and the Smirnov Test. (orig./HP)

Bayes Factor Covariance Testing in Item Response Models.

Science.gov (United States)

Fox, Jean-Paul; Mulder, Joris; Sinharay, Sandip

2017-12-01

Two marginal one-parameter item response theory models are introduced, by integrating out the latent variable or random item parameter. It is shown that both marginal response models are multivariate (probit) models with a compound symmetry covariance structure. Several common hypotheses concerning the underlying covariance structure are evaluated using (fractional) Bayes factor tests. The support for a unidimensional factor (i.e., assumption of local independence) and differential item functioning are evaluated by testing the covariance components. The posterior distribution of common covariance components is obtained in closed form by transforming latent responses with an orthogonal (Helmert) matrix. This posterior distribution is defined as a shifted-inverse-gamma, thereby introducing a default prior and a balanced prior distribution. Based on that, an MCMC algorithm is described to estimate all model parameters and to compute (fractional) Bayes factor tests. Simulation studies are used to show that the (fractional) Bayes factor tests have good properties for testing the underlying covariance structure of binary response data. The method is illustrated with two real data studies.

Traumatic lesions of the posterior urethra.

Science.gov (United States)

Velarde-Ramos, L; Gómez-Illanes, R; Campos-Juanatey, F; Portillo-Martín, J A

2016-11-01

The posterior urethral lesions are associated with pelvis fractures in 5-10% of cases. The posterior urethra is attached to the pelvis bone by puboprostatic ligaments and the perineal membrane, which explains why disruption of the pelvic ring can injure the urethra at this level. To identify suspected cases of posterior urethral trauma and to perform the diagnosis and its immediate or deferred management. Search in PubMed of articles related to traumatic posterior urethral lesions, written in English or Spanish. We reviewed the relevant publications including literature reviews and chapters from books related to the topic. With patients with pelvis fractures, we must always rule out posterior urethral lesions. The diagnostic examination of choice is retrograde urethrography, which, along with the severity of the condition, will determine the management in the acute phase and whether the treatment will be performed immediately or deferred. Early diagnosis and proper acute management decrease the associated complications, such as strictures, urinary incontinence and erectile dysfunction. Despite the classical association between posterior urethral lesions and pelvic fractures, the management of those lesions (whether immediate or deferred) remains controversial. Thanks to the growing interest in urethral disease, there are an increasing number of studies that help us achieve better management of these lesions. Copyright © 2016 AEU. Publicado por Elsevier España, S.L.U. All rights reserved.

Delayed Single Stage Perineal Posterior Urethroplasty

International Nuclear Information System (INIS)

Ali, S.; Shahnawaz; Shahzad, I.; Baloch, M. U.

2015-01-01

Objective: To determine the delayed single stage perineal posterior urethroplasty for treatment of posterior urethral stricture/distraction defect. Study Design: Descriptive case series. Place and Duration of Study: Department of Urology, Jinnah Postgraduate Medical Centre, Karachi, from January 2009 to December 2011. Methodology: Patients were selected for delayed single stage perineal posterior urethroplasty for treatment of posterior urethral stricture / distraction defect. All were initially suprapubically catheterized followed by definitive surgery after at least 3 months. Results: Thirty male patients were analyzed with a mean follow-up of 10 months, 2 patients were excluded as they developed failure in first 3 months postoperatively. Mean patients age was 26.25 ± 7.9 years. On follow-up, 7 patients (23.3 percentage) experienced recurrent stricture during first 10 months. Five (16.6 percentage) patients were treated successfully with single direct visual internal urethrotomy. Two patients (6.6 percentage) had more than one direct visual internal urethrotomy and considered failed. Re-do perineal urethroplasty was eventually performed. The overall success rate was 93.3 percentage with permissive criteria allowing single direct visual internal urethrotomy and 76.6% with strict criteria allowing no more procedures postoperatively. Conclusion: Posterior anastomotic urethroplasty offers excellent long-term results to patients with posterior urethral trauma and distraction defect even after multiple prior procedures. (author)

Bringing metabolic networks to life: integration of kinetic, metabolic, and proteomic data

Directory of Open Access Journals (Sweden)

Klipp Edda

2006-12-01

Full Text Available Abstract Background Translating a known metabolic network into a dynamic model requires reasonable guesses of all enzyme parameters. In Bayesian parameter estimation, model parameters are described by a posterior probability distribution, which scores the potential parameter sets, showing how well each of them agrees with the data and with the prior assumptions made. Results We compute posterior distributions of kinetic parameters within a Bayesian framework, based on integration of kinetic, thermodynamic, metabolic, and proteomic data. The structure of the metabolic system (i.e., stoichiometries and enzyme regulation needs to be known, and the reactions are modelled by convenience kinetics with thermodynamically independent parameters. The parameter posterior is computed in two separate steps: a first posterior summarises the available data on enzyme kinetic parameters; an improved second posterior is obtained by integrating metabolic fluxes, concentrations, and enzyme concentrations for one or more steady states. The data can be heterogenous, incomplete, and uncertain, and the posterior is approximated by a multivariate log-normal distribution. We apply the method to a model of the threonine synthesis pathway: the integration of metabolic data has little effect on the marginal posterior distributions of individual model parameters. Nevertheless, it leads to strong correlations between the parameters in the joint posterior distribution, which greatly improve the model predictions by the following Monte-Carlo simulations. Conclusion We present a standardised method to translate metabolic networks into dynamic models. To determine the model parameters, evidence from various experimental data is combined and weighted using Bayesian parameter estimation. The resulting posterior parameter distribution describes a statistical ensemble of parameter sets; the parameter variances and correlations can account for missing knowledge, measurement

De novo formation of left-right asymmetry by posterior tilt of nodal cilia.

Directory of Open Access Journals (Sweden)

Shigenori Nonaka

2005-08-01

Full Text Available In the developing mouse embryo, leftward fluid flow on the ventral side of the node determines left-right (L-R asymmetry. However, the mechanism by which the rotational movement of node cilia can generate a unidirectional flow remains hypothetical. Here we have addressed this question by motion and morphological analyses of the node cilia and by fluid dynamic model experiments. We found that the cilia stand, not perpendicular to the node surface, but tilted posteriorly. We further confirmed that such posterior tilt can produce leftward flow in model experiments. These results strongly suggest that L-R asymmetry is not the descendant of pre-existing L-R asymmetry within each cell but is generated de novo by combining three sources of spatial information: antero-posterior and dorso-ventral axes, and the chirality of ciliary movement.

Effects of temporal and spatial resolution of calibration data on integrated hydrologic water quality model identification

Science.gov (United States)

Jiang, Sanyuan; Jomaa, Seifeddine; Büttner, Olaf; Rode, Michael

2014-05-01

Hydrological water quality modeling is increasingly used for investigating runoff and nutrient transport processes as well as watershed management but it is mostly unclear how data availablity determins model identification. In this study, the HYPE (HYdrological Predictions for the Environment) model, which is a process-based, semi-distributed hydrological water quality model, was applied in two different mesoscale catchments (Selke (463 km2) and Weida (99 km2)) located in central Germany to simulate discharge and inorganic nitrogen (IN) transport. PEST and DREAM(ZS) were combined with the HYPE model to conduct parameter calibration and uncertainty analysis. Split-sample test was used for model calibration (1994-1999) and validation (1999-2004). IN concentration and daily IN load were found to be highly correlated with discharge, indicating that IN leaching is mainly controlled by runoff. Both dynamics and balances of water and IN load were well captured with NSE greater than 0.83 during validation period. Multi-objective calibration (calibrating hydrological and water quality parameters simultaneously) was found to outperform step-wise calibration in terms of model robustness. Multi-site calibration was able to improve model performance at internal sites, decrease parameter posterior uncertainty and prediction uncertainty. Nitrogen-process parameters calibrated using continuous daily averages of nitrate-N concentration observations produced better and more robust simulations of IN concentration and load, lower posterior parameter uncertainty and IN concentration prediction uncertainty compared to the calibration against uncontinuous biweekly nitrate-N concentration measurements. Both PEST and DREAM(ZS) are efficient in parameter calibration. However, DREAM(ZS) is more sound in terms of parameter identification and uncertainty analysis than PEST because of its capability to evolve parameter posterior distributions and estimate prediction uncertainty based on global

Epidural hematomas of posterior fossa

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Radulović Danilo

2004-01-01

Full Text Available Background. Posterior fossa epidural hematomas represent 7-14% of all traumatic intracranial epidural hematomas. They are most frequently encountered posttraumatic mass lesions in the posterior fossa. The aim of this study was to identify clinical features that could lead to the early diagnosis of posterior fossa epidural hematoma. Methods. Between 1980 and 2002, 28 patients with epidural hematoma of the posterior fossa were operated on at the Institute for Neurosurgery, Belgrade. Clinical course neuroradiological investigations, and the results of surgical treatment of the patients with posterior fossa epidural hematomas were analyzed retrospectively. Results. Almost two thirds of patients were younger than 16 years of age. In 20 cases injury was caused by a fall, in 6 cases by a traffic accident, and in 2 by the assault. Clinical course was subacute or chronic in two thirds of the patients. On the admission Glasgow Coma Scale was 7 or less in 9 injured, 8-14 in 14 injured, and 15 in 5 injured patients. Linear fracture of the occipital bone was radiographically evident in 19 patients, but was intraoperatively encountered in all the patients except for a 4-year old child. In 25 patients the diagnosis was established by computer assisted tomography (CAT and in 3 by vertebral angiography. All the patients were operated on via suboccipital craniotomy. Four injured patients who were preoperatively comatose were with lethal outcome. Postoperatively, 24 patients were with sufficient neurologic recovery. Conclusion. Posterior fossa epidural hematoma should be suspected in cases of occipital injury, consciousness disturbances, and occipital bone fracture. In such cases urgent CAT-scan is recommended. Early recognition early diagnosis, and prompt treatment are crucial for good neurological recovery after surgery.

Distrofia corneana policromática posterior Polychromatic posterior corneal dystrophy

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Patrick Frensel de Moraes Tzelikis

2007-08-01

Full Text Available Os autores descrevem quatro raros casos de distrofia corneana policromática posterior, ainda não descrito na literatura nacional. Observam-se opacidades puntiformes, policromáticas, de tamanho uniforme, localização estromal profunda, distribuídas de limbo a limbo e que não interferem na acuidade visual. É apresentada uma revisão dos casos de distrofia pré-Descemet existentes na literatura.The authors describe four rare cases of polychromatic posterior corneal dystrophy, not describe in national literature. The opacities are deep in the stroma, dotlike, polychromatic, uniform in size, distributed from limbus to limbus, leading no reduction in visual acuity. It is also presented a bibliographic review of pre-Descemet's dystrophy.

Models and parameters for environmental radiological assessments

International Nuclear Information System (INIS)

Miller, C.W.

1983-01-01

This article reviews the forthcoming book Models and Parameters for Environmental Radiological Assessments, which presents a unified compilation of models and parameters for assessing the impact on man of radioactive discharges, both routine and accidental, into the environment. Models presented in this book include those developed for the prediction of atmospheric and hydrologic transport and deposition, for terrestrial and aquatic food-chain bioaccumulation, and for internal and external dosimetry. Summaries are presented for each of the transport and dosimetry areas previously for each of the transport and dosimetry areas previously mentioned, and details are available in the literature cited. A chapter of example problems illustrates many of the methodologies presented throughout the text. Models and parameters presented are based on the results of extensive literature reviews and evaluations performed primarily by the staff of the Health and Safety Research Division of Oak Ridge National Laboratory

Structural Parameters of Star Clusters: Signal to Noise Effects

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Narbutis D.

2015-09-01

Full Text Available We study the impact of photometric signal to noise on the accuracy of derived structural parameters of unresolved star clusters using MCMC model fitting techniques. Star cluster images were simulated as a smooth surface brightness distribution following a King profile convolved with a point spread function. The simulation grid was constructed by varying the levels of sky background and adjusting the cluster’s flux to a specified signal to noise. Poisson noise was introduced to a set of cluster images with the same input parameters at each node of the grid. Model fitting was performed using “emcee” algorithm. The presented posterior distributions of the parameters illustrate their uncertainty and degeneracies as a function of signal to noise. By defining the photometric aperture containing 80% of the cluster’s flux, we find that in all realistic sky background level conditions a signal to noise ratio of ~50 is necessary to constrain the cluster’s half-light radius to an accuracy better than ~20%. The presented technique can be applied to synthetic images simulating various observations of extragalactic star clusters.

Posterior alien hand syndrome: case report

International Nuclear Information System (INIS)

Rohde, S.; Weidauer, S.; Lanfermann, H.; Zanella, F.

2002-01-01

The alien hand syndrome (AHS) is involuntary uncontrolled movement of an arm with a sense of estrangement from the limb itself. AHS was initially used to describe interhemispheric disconnection phenomena in patients with lesions in the anterior corpus callosum, but it has been found in patients with posterior cerebral lesions without involvement of the corpus callosum, for example parietal infarcts or corticobasal degeneration. The posterior alien hand syndrome is less frequent and presents with nonpurposive behaviour like lifting the arm or writhing fingers. We report an 80-year-old woman with a posterior AHS of the dominant right hand. MRI showed atrophy of the pre- and postcentral gyri without involvement of the corpus callosum. We discuss the aetiology of the posterior AHS and the differences from the anterior varieties. (orig.)

Parameter Estimation of Nonlinear Models in Forestry.

OpenAIRE

Fekedulegn, Desta; Mac Siúrtáin, Máirtín Pádraig; Colbert, Jim J.

1999-01-01

Partial derivatives of the negative exponential, monomolecular, Mitcherlich, Gompertz, logistic, Chapman-Richards, von Bertalanffy, Weibull and the Richard’s nonlinear growth models are presented. The application of these partial derivatives in estimating the model parameters is illustrated. The parameters are estimated using the Marquardt iterative method of nonlinear regression relating top height to age of Norway spruce (Picea abies L.) from the Bowmont Norway Spruce Thinnin...

Learning about physical parameters: the importance of model discrepancy

International Nuclear Information System (INIS)

Brynjarsdóttir, Jenný; O'Hagan, Anthony

2014-01-01

Science-based simulation models are widely used to predict the behavior of complex physical systems. It is also common to use observations of the physical system to solve the inverse problem, that is, to learn about the values of parameters within the model, a process which is often called calibration. The main goal of calibration is usually to improve the predictive performance of the simulator but the values of the parameters in the model may also be of intrinsic scientific interest in their own right. In order to make appropriate use of observations of the physical system it is important to recognize model discrepancy, the difference between reality and the simulator output. We illustrate through a simple example that an analysis that does not account for model discrepancy may lead to biased and over-confident parameter estimates and predictions. The challenge with incorporating model discrepancy in statistical inverse problems is being confounded with calibration parameters, which will only be resolved with meaningful priors. For our simple example, we model the model-discrepancy via a Gaussian process and demonstrate that through accounting for model discrepancy our prediction within the range of data is correct. However, only with realistic priors on the model discrepancy do we uncover the true parameter values. Through theoretical arguments we show that these findings are typical of the general problem of learning about physical parameters and the underlying physical system using science-based mechanistic models. (paper)

Wind Farm Decentralized Dynamic Modeling With Parameters

DEFF Research Database (Denmark)

Soltani, Mohsen; Shakeri, Sayyed Mojtaba; Grunnet, Jacob Deleuran

2010-01-01

Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...... local models. The results of this report are especially useful, but not limited, to design a decentralized wind farm controller, since in centralized controller design one can also use the model and update it in a central computing node.......Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...

Diffusion tensor imaging in evaluation of posterior fossa tumors in children on a 3T MRI scanner

International Nuclear Information System (INIS)

Assis, Zarina Abdul; Saini, Jitender; Ranjan, Manish; Gupta, Arun Kumar; Sabharwal, Paramveer; Naidu, Purushotham R

2015-01-01

Primary intracranial tumors in children are commonly located in the posterior fossa. Conventional MRI offers limited information regarding the histopathological type of tumor which is essential for better patient management. The purpose of the study was to evaluate the usefulness of advanced MR imaging techniques like diffusion tensor imaging (DTI) in distinguishing the various histopathological types of posterior fossa tumors in children. DTI was performed on a 3T MRI scanner in 34 untreated children found to have posterior fossa lesions. Using third party software, various DTI parameters [apparent diffusion coefficient (ADC), fractional anisotropy (FA), radial diffusivity, planar index, spherical index, and linear index] were calculated for the lesion. Data were subjected to statistical analysis [analysis of variance (ANOVA)] using SPSS 15.0 software. We observed significant correlation (P < 0.01) between ADC mean and maximum, followed by radial diffusivity (RD) with the histopathological types of the lesions. Rest of the DTI parameters did not show any significant correlation in our study. The results of our study support the hypothesis that most cellular tumors and those with greater nuclear area like medulloblastoma would have the lowest ADC values, as compared to less cellular tumors like pilocytic astrocytoma

Optimizing incomplete sample designs for item response model parameters

NARCIS (Netherlands)

van der Linden, Willem J.

Several models for optimizing incomplete sample designs with respect to information on the item parameters are presented. The following cases are considered: (1) known ability parameters; (2) unknown ability parameters; (3) item sets with multiple ability scales; and (4) response models with

Modeling the vertical soil organic matter profile using Bayesian parameter estimation

Directory of Open Access Journals (Sweden)

M. C. Braakhekke

2013-01-01

Full Text Available The vertical distribution of soil organic matter (SOM in the profile may constitute an important factor for soil carbon cycling. However, the formation of the SOM profile is currently poorly understood due to equifinality, caused by the entanglement of several processes: input from roots, mixing due to bioturbation, and organic matter leaching. In this study we quantified the contribution of these three processes using Bayesian parameter estimation for the mechanistic SOM profile model SOMPROF. Based on organic carbon measurements, 13 parameters related to decomposition and transport of organic matter were estimated for two temperate forest soils: an Arenosol with a mor humus form (Loobos, the Netherlands, and a Cambisol with mull-type humus (Hainich, Germany. Furthermore, the use of the radioisotope ²¹⁰Pb_ex as tracer for vertical SOM transport was studied. For Loobos, the calibration results demonstrate the importance of organic matter transport with the liquid phase for shaping the vertical SOM profile, while the effects of bioturbation are generally negligible. These results are in good agreement with expectations given in situ conditions. For Hainich, the calibration offered three distinct explanations for the observations (three modes in the posterior distribution. With the addition of ²¹⁰Pb_ex data and prior knowledge, as well as additional information about in situ conditions, we were able to identify the most likely explanation, which indicated that root litter input is a dominant process for the SOM profile. For both sites the organic matter appears to comprise mainly adsorbed but potentially leachable material, pointing to the importance of organo-mineral interactions. Furthermore, organic matter in the mineral soil appears to be mainly derived from root litter, supporting previous studies that highlighted the importance of root input for soil carbon sequestration. The ²¹⁰

Approximate Bayesian Computation by Subset Simulation using hierarchical state-space models

Science.gov (United States)

Vakilzadeh, Majid K.; Huang, Yong; Beck, James L.; Abrahamsson, Thomas

2017-02-01

A new multi-level Markov Chain Monte Carlo algorithm for Approximate Bayesian Computation, ABC-SubSim, has recently appeared that exploits the Subset Simulation method for efficient rare-event simulation. ABC-SubSim adaptively creates a nested decreasing sequence of data-approximating regions in the output space that correspond to increasingly closer approximations of the observed output vector in this output space. At each level, multiple samples of the model parameter vector are generated by a component-wise Metropolis algorithm so that the predicted output corresponding to each parameter value falls in the current data-approximating region. Theoretically, if continued to the limit, the sequence of data-approximating regions would converge on to the observed output vector and the approximate posterior distributions, which are conditional on the data-approximation region, would become exact, but this is not practically feasible. In this paper we study the performance of the ABC-SubSim algorithm for Bayesian updating of the parameters of dynamical systems using a general hierarchical state-space model. We note that the ABC methodology gives an approximate posterior distribution that actually corresponds to an exact posterior where a uniformly distributed combined measurement and modeling error is added. We also note that ABC algorithms have a problem with learning the uncertain error variances in a stochastic state-space model and so we treat them as nuisance parameters and analytically integrate them out of the posterior distribution. In addition, the statistical efficiency of the original ABC-SubSim algorithm is improved by developing a novel strategy to regulate the proposal variance for the component-wise Metropolis algorithm at each level. We demonstrate that Self-regulated ABC-SubSim is well suited for Bayesian system identification by first applying it successfully to model updating of a two degree-of-freedom linear structure for three cases: globally

Posterior column acetabular fracture fixation using a W-shaped angular plate: A biomechanical analysis.

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Ke Su

Full Text Available The purpose of this study was to compare the stability and feasibility of four fixation constructs in a posterior column acetabular fracture: one reconstruction plate, one reconstruction plate and lag screw, two reconstruction plates, and a W-shaped acetabular angular plate.Twenty embalmed cadaveric pelvises with a posterior column acetabular fractures were allocated to one of four groups: 1 a reconstruction plate, 2 a reconstruction plate with a posterior column lag screw, 3 double reconstruction plates, and 4 a W-shaped acetabular angular plate. These constructs were mechanically loaded on a testing machine, and construct stiffness values were measured. Strain gauges were utilized to measure the mechanical behavior in the condition of compressive force.Final stiffness was not different between the two reconstruction plates (445.81±98.30 N/mm and the W-shaped acetabular angular plate (447.43±98.45 N/mm, p = 0.524, both of which were superior to a single reconstruction plate (248.90±61.95 N/mm and a combined plate and lag screw (326.41±94.34 N/mm. Following the fixation of the W-shaped acetabular angular plate, the strain distribution was similar to the intact condition around the acetabulum. The parameters of the W-shaped acetabular angular plate that were observed at the superior region of the acetabulum were less than those of a single reconstruction plate (p<0.05, a single reconstruction plate with lag screw (p<0.05, and two reconstruction plates (p<0.05.The novel W-shaped acetabular angular plate fixation technique was able to provide the biomechanically stiffest construct for stabilization of a posterior column acetabular fracture; it also resulted in a partial restoration of joint loading parameters toward the intact state.

Assessing Goodness of Fit in Item Response Theory with Nonparametric Models: A Comparison of Posterior Probabilities and Kernel-Smoothing Approaches

Science.gov (United States)

Sueiro, Manuel J.; Abad, Francisco J.

2011-01-01

The distance between nonparametric and parametric item characteristic curves has been proposed as an index of goodness of fit in item response theory in the form of a root integrated squared error index. This article proposes to use the posterior distribution of the latent trait as the nonparametric model and compares the performance of an index…

Environmental Transport Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

M. Wasiolek

2004-01-01

This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment for the license application (TSPA-LA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA-LA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]) (TWP). This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA). This report is one of the five reports that develop input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the conceptual model and the mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed description of the model input parameters. The output of this report is used as direct input in the ''Nominal Performance Biosphere Dose Conversion Factor Analysis'' and in the ''Disruptive Event Biosphere Dose Conversion Factor Analysis'' that calculate the values of biosphere dose conversion factors (BDCFs) for the groundwater and volcanic ash exposure scenarios, respectively. The purpose of this analysis was to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or in volcanic ash). The analysis was performed in accordance with the TWP (BSC 2004 [DIRS 169573])

Environmental Transport Input Parameters for the Biosphere Model

Energy Technology Data Exchange (ETDEWEB)

M. Wasiolek

2004-09-10

This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment for the license application (TSPA-LA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA-LA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]) (TWP). This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA). This report is one of the five reports that develop input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the conceptual model and the mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed description of the model input parameters. The output of this report is used as direct input in the ''Nominal Performance Biosphere Dose Conversion Factor Analysis'' and in the ''Disruptive Event Biosphere Dose Conversion Factor Analysis'' that calculate the values of biosphere dose conversion factors (BDCFs) for the groundwater and volcanic ash exposure scenarios, respectively. The purpose of this analysis was to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or in volcanic ash). The analysis

Distrofia corneana amorfa posterior: relato de caso Posterior amorphous corneal dystrophy: case report

Directory of Open Access Journals (Sweden)

Lauro Augusto de Oliveira

2006-12-01

Full Text Available O objetivo deste trabalho é alertar o oftalmologista da possibilidade de se deparar com casos raros de distrofias corneanas. Neste caso correlacionamos os achados clínicos da distrofia amorfa posterior com refração, topografia e biomicroscopia ultra-sônica.The purpose of this paper is to warn the ophthalmologist about the possibility of facing rare cases of corneal dystrophies. Clinical findings of a case of posterior amorphous dystrophy were correlated with refraction, topography, and ultrasound biomicroscopy.

Parameters and error of a theoretical model

International Nuclear Information System (INIS)

Moeller, P.; Nix, J.R.; Swiatecki, W.

1986-09-01

We propose a definition for the error of a theoretical model of the type whose parameters are determined from adjustment to experimental data. By applying a standard statistical method, the maximum-likelihoodlmethod, we derive expressions for both the parameters of the theoretical model and its error. We investigate the derived equations by solving them for simulated experimental and theoretical quantities generated by use of random number generators. 2 refs., 4 tabs

Can the anterior-posterior thigh diameter be used as an indicator for fetal age using two-dimensional sonography?

International Nuclear Information System (INIS)

Ismail, Saad Ramzi

2008-01-01

This study evaluated the usefulness and direct correlation of a simple new method of predicting fetal age by measurement of the anterior-posterior thigh diameter (APTD) in a normal 18 to 28 week pregnancies using two-dimensional sonography. Little published research exists in the area of fetal thigh biometry, specifically in the use of the anterior-posterior fetal thigh diameter (APTD). The only study I found was that of fetal thigh circumference. Continuing review of existing practices needs to be coupled with evaluation of alternate or additional methodology. Materials and methods: This was a quantitative prospective study of 55 patients in High Level General Hospital, Alberta, Canada. Anterior-posterior thigh diameters (APTD) were sonographically measured. The normal range for each week of pregnancy was determined five times for reliability. Results: Significant correlation was found between (APTD) and fetal age from simple line regression analysis, with 99.993% confidence intervals at each week from 18 to 28 weeks gestation. There was a correlation of 1 mm APTD per 1 week of fetal age. In addition R > 0.93, P < 0.001. The residual scatter plots confirmed the APTD validity. Conclusion: APTD is a reliable and valid method for assessing fetal age in a normal pregnancy and may be particularly useful when other parameters are unable to accurately predict fetal age. An accurate linear measurement of multiple fetal parameters allows a more complete profile of fetal growth and estimated date of delivery (EDD). APTD may also be useful in identifying fetal growth problems. All of the values of fetal age lie directly on the 'best-fit' regression line. Since the coefficient of determination (Rsq) is very high, this model is very effective

Application of multi-parameter chorus and plasmaspheric hiss wave models in radiation belt modeling

Science.gov (United States)

Aryan, H.; Kang, S. B.; Balikhin, M. A.; Fok, M. C. H.; Agapitov, O. V.; Komar, C. M.; Kanekal, S. G.; Nagai, T.; Sibeck, D. G.

2017-12-01

Numerical simulation studies of the Earth's radiation belts are important to understand the acceleration and loss of energetic electrons. The Comprehensive Inner Magnetosphere-Ionosphere (CIMI) model along with many other radiation belt models require inputs for pitch angle, energy, and cross diffusion of electrons, due to chorus and plasmaspheric hiss waves. These parameters are calculated using statistical wave distribution models of chorus and plasmaspheric hiss amplitudes. In this study we incorporate recently developed multi-parameter chorus and plasmaspheric hiss wave models based on geomagnetic index and solar wind parameters. We perform CIMI simulations for two geomagnetic storms and compare the flux enhancement of MeV electrons with data from the Van Allen Probes and Akebono satellites. We show that the relativistic electron fluxes calculated with multi-parameter wave models resembles the observations more accurately than the relativistic electron fluxes calculated with single-parameter wave models. This indicates that wave models based on a combination of geomagnetic index and solar wind parameters are more effective as inputs to radiation belt models.

Modelling hydrodynamic parameters to predict flow assisted corrosion

International Nuclear Information System (INIS)

Poulson, B.; Greenwell, B.; Chexal, B.; Horowitz, J.

1992-01-01

During the past 15 years, flow assisted corrosion has been a worldwide problem in the power generating industry. The phenomena is complex and depends on environment, material composition, and hydrodynamic factors. Recently, modeling of flow assisted corrosion has become a subject of great importance. A key part of this effort is modeling the hydrodynamic aspects of this issue. This paper examines which hydrodynamic parameter should be used to correlate the occurrence and rate of flow assisted corrosion with physically meaningful parameters, discusses ways of measuring the relevant hydrodynamic parameter, and describes how the hydrodynamic data is incorporated into the predictive model

Congenital abnormalities of the posterior fossa.

Science.gov (United States)

Bosemani, Thangamadhan; Orman, Gunes; Boltshauser, Eugen; Tekes, Aylin; Huisman, Thierry A G M; Poretti, Andrea

2015-01-01

The frequency and importance of the evaluation of the posterior fossa have increased significantly over the past 20 years owing to advances in neuroimaging. Nowadays, conventional and advanced neuroimaging techniques allow detailed evaluation of the complex anatomic structures within the posterior fossa. A wide spectrum of congenital abnormalities has been demonstrated, including malformations (anomalies due to an alteration of the primary developmental program caused by a genetic defect) and disruptions (anomalies due to the breakdown of a structure that had a normal developmental potential). Familiarity with the spectrum of congenital posterior fossa anomalies and their well-defined diagnostic criteria is crucial for optimal therapy, an accurate prognosis, and correct genetic counseling. The authors discuss the spectrum of posterior fossa malformations and disruptions, with emphasis on neuroimaging findings (including diagnostic criteria), neurologic presentation, systemic involvement, prognosis, and risk of recurrence. RSNA, 2015

WINKLER'S SINGLE-PARAMETER SUBGRADE MODEL FROM ...

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Page 1 ... corresponding single-parameter Winkler model presented in this work. Keywords: Heterogeneous subgrade, Reissner's simplified continuum, Shear interaction, Simplified continuum, Winkler ... model in practical applications and its long time familiarity among practical engineers, its usage has endured to this date ...

[Three dimensional finite element model of a modified posterior cervical single open-door laminoplasty].

Science.gov (United States)

Wang, Q; Yang, Y; Fei, Q; Li, D; Li, J J; Meng, H; Su, N; Fan, Z H; Wang, B Q

2017-06-06

Objective: To build a three-dimensional finite element models of a modified posterior cervical single open-door laminoplasty with short-segmental lateral mass screws fusion. Methods: The C(2)-C(7) segmental data were obtained from computed tomography (CT) scans of a male patient with cervical spondylotic myelopathy and spinal stenosis.Three-dimensional finite element models of a modified cervical single open-door laminoplasty (before and after surgery) were constructed by the combination of software package MIMICS, Geomagic and ABAQUS.The models were composed of bony vertebrae, articulating facets, intervertebral disc and associated ligaments.The loads of moments 1.5Nm at different directions (flexion, extension, lateral bending and axial rotation)were applied at preoperative model to calculate intersegmental ranges of motion.The results were compared with the previous studies to verify the validation of the models. Results: Three-dimensional finite element models of the modified cervical single open- door laminoplasty had 102258 elements (preoperative model) and 161 892 elements (postoperative model) respectively, including C(2-7) six bony vertebraes, C(2-3)-C(6-7) five intervertebral disc, main ligaments and lateral mass screws.The intersegmental responses at the preoperative model under the loads of moments 1.5 Nm at different directions were similar to the previous published data. Conclusion: Three-dimensional finite element models of the modified cervical single open- door laminoplasty were successfully established and had a good biological fidelity, which can be used for further study.

Insight into model mechanisms through automatic parameter fitting: a new methodological framework for model development.

Science.gov (United States)

Tøndel, Kristin; Niederer, Steven A; Land, Sander; Smith, Nicolas P

2014-05-20

Striking a balance between the degree of model complexity and parameter identifiability, while still producing biologically feasible simulations using modelling is a major challenge in computational biology. While these two elements of model development are closely coupled, parameter fitting from measured data and analysis of model mechanisms have traditionally been performed separately and sequentially. This process produces potential mismatches between model and data complexities that can compromise the ability of computational frameworks to reveal mechanistic insights or predict new behaviour. In this study we address this issue by presenting a generic framework for combined model parameterisation, comparison of model alternatives and analysis of model mechanisms. The presented methodology is based on a combination of multivariate metamodelling (statistical approximation of the input-output relationships of deterministic models) and a systematic zooming into biologically feasible regions of the parameter space by iterative generation of new experimental designs and look-up of simulations in the proximity of the measured data. The parameter fitting pipeline includes an implicit sensitivity analysis and analysis of parameter identifiability, making it suitable for testing hypotheses for model reduction. Using this approach, under-constrained model parameters, as well as the coupling between parameters within the model are identified. The methodology is demonstrated by refitting the parameters of a published model of cardiac cellular mechanics using a combination of measured data and synthetic data from an alternative model of the same system. Using this approach, reduced models with simplified expressions for the tropomyosin/crossbridge kinetics were found by identification of model components that can be omitted without affecting the fit to the parameterising data. Our analysis revealed that model parameters could be constrained to a standard deviation of on

Modelling of intermittent microwave convective drying: parameter sensitivity

Directory of Open Access Journals (Sweden)

Zhang Zhijun

2017-06-01

Full Text Available The reliability of the predictions of a mathematical model is a prerequisite to its utilization. A multiphase porous media model of intermittent microwave convective drying is developed based on the literature. The model considers the liquid water, gas and solid matrix inside of food. The model is simulated by COMSOL software. Its sensitivity parameter is analysed by changing the parameter values by ±20%, with the exception of several parameters. The sensitivity analysis of the process of the microwave power level shows that each parameter: ambient temperature, effective gas diffusivity, and evaporation rate constant, has significant effects on the process. However, the surface mass, heat transfer coefficient, relative and intrinsic permeability of the gas, and capillary diffusivity of water do not have a considerable effect. The evaporation rate constant has minimal parameter sensitivity with a ±20% value change, until it is changed 10-fold. In all results, the temperature and vapour pressure curves show the same trends as the moisture content curve. However, the water saturation at the medium surface and in the centre show different results. Vapour transfer is the major mass transfer phenomenon that affects the drying process.

Orthodontic treatment for posterior crossbites.

Science.gov (United States)

Agostino, Paola; Ugolini, Alessandro; Signori, Alessio; Silvestrini-Biavati, Armando; Harrison, Jayne E; Riley, Philip

2014-08-08

A posterior crossbite occurs when the top back teeth bite inside the bottom back teeth. When it affects one side of the mouth, the lower jaw may have to move to one side to allow the back teeth to meet together. Several treatments have been recommended to correct this problem. Some treatments widen the upper teeth while others are directed at treating the cause of the posterior crossbite (e.g. breathing problems or sucking habits). Most treatments have been used at each stage of dental development. This is an update of a Cochrane review first published in 2001. To assess the effects of orthodontic treatment for posterior crossbites. We searched the following electronic databases: the Cochrane Oral Health Group's Trials Register (to 21 January 2014), the Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library 2014, Issue 1), MEDLINE via OVID (1946 to 21 January 2014), and EMBASE via OVID (1980 to 21 January 2014). We searched the US National Institutes of Health Trials Register and the World Health Organization (WHO) Clinical Trials Registry Platform for ongoing trials. We placed no restrictions on the language or date of publication when searching the electronic databases. Randomised controlled trials (RCTs) of orthodontic treatment for posterior crossbites in children and adults. Two review authors, independently and in duplicate, screened the results of the electronic searches, and extracted data and assessed the risk of bias of the included studies. We attempted to contact the first named authors of the included studies for missing data and for clarification. We used risk ratios (RR) and 95% confidence intervals (CIs) to summarise dichotomous (event) data, and mean differences (MD) with 95% CIs to summarise continuous data. We performed meta-analyses using fixed-effect models (we would have used random-effects models if we had included four or more studies in a meta-analysis) when comparisons and outcomes were sufficiently similar. We

Retrospective forecast of ETAS model with daily parameters estimate

Science.gov (United States)

Falcone, Giuseppe; Murru, Maura; Console, Rodolfo; Marzocchi, Warner; Zhuang, Jiancang

2016-04-01

We present a retrospective ETAS (Epidemic Type of Aftershock Sequence) model based on the daily updating of free parameters during the background, the learning and the test phase of a seismic sequence. The idea was born after the 2011 Tohoku-Oki earthquake. The CSEP (Collaboratory for the Study of Earthquake Predictability) Center in Japan provided an appropriate testing benchmark for the five 1-day submitted models. Of all the models, only one was able to successfully predict the number of events that really happened. This result was verified using both the real time and the revised catalogs. The main cause of the failure was in the underestimation of the forecasted events, due to model parameters maintained fixed during the test. Moreover, the absence in the learning catalog of an event similar to the magnitude of the mainshock (M9.0), which drastically changed the seismicity in the area, made the learning parameters not suitable to describe the real seismicity. As an example of this methodological development we show the evolution of the model parameters during the last two strong seismic sequences in Italy: the 2009 L'Aquila and the 2012 Reggio Emilia episodes. The achievement of the model with daily updated parameters is compared with that of same model where the parameters remain fixed during the test time.

Parameter identification in multinomial processing tree models

NARCIS (Netherlands)

Schmittmann, V.D.; Dolan, C.V.; Raijmakers, M.E.J.; Batchelder, W.H.

2010-01-01

Multinomial processing tree models form a popular class of statistical models for categorical data that have applications in various areas of psychological research. As in all statistical models, establishing which parameters are identified is necessary for model inference and selection on the basis

Developmental origin of the posterior pigmented epithelium of iris.

Science.gov (United States)

Wang, Xiaobing; Xiong, Kai; Lu, Lei; Gu, Dandan; Wang, Songtao; Chen, Jing; Xiao, Honglei; Zhou, Guomin

2015-03-01

Iris epithelium is a double-layered pigmented cuboidal epithelium. According to the current model, the neural retina and the posterior iris pigment epithelium (IPE) are derived from the inner wall of the optic cup, while the retinal pigment epithelium (RPE) and the anterior IPE are derived from the outer wall of the optic cup during development. Our current study shows evidence, contradicting this model of fetal iris development. We demonstrate that human fetal iris expression patterns of Otx2 and Mitf transcription factors are similar, while the expressions of Otx2 and Sox2 are complementary. Furthermore, IPE and RPE exhibit identical morphologic development during the early embryonic period. Our results suggest that the outer layer of the optic cup forms two layers of the iris epithelium, and the posterior IPE is the inward-curling anterior rim of the outer layer of the optic cup. These findings provide a reasonable explanation of how IPE cells can be used as an appropriate substitute for RPE cells.

Elastic K-means using posterior probability.

Science.gov (United States)

Zheng, Aihua; Jiang, Bo; Li, Yan; Zhang, Xuehan; Ding, Chris

2017-01-01

The widely used K-means clustering is a hard clustering algorithm. Here we propose a Elastic K-means clustering model (EKM) using posterior probability with soft capability where each data point can belong to multiple clusters fractionally and show the benefit of proposed Elastic K-means. Furthermore, in many applications, besides vector attributes information, pairwise relations (graph information) are also available. Thus we integrate EKM with Normalized Cut graph clustering into a single clustering formulation. Finally, we provide several useful matrix inequalities which are useful for matrix formulations of learning models. Based on these results, we prove the correctness and the convergence of EKM algorithms. Experimental results on six benchmark datasets demonstrate the effectiveness of proposed EKM and its integrated model.

Modeling Site Heterogeneity with Posterior Mean Site Frequency Profiles Accelerates Accurate Phylogenomic Estimation.

Science.gov (United States)

Wang, Huai-Chun; Minh, Bui Quang; Susko, Edward; Roger, Andrew J

2018-03-01

Proteins have distinct structural and functional constraints at different sites that lead to site-specific preferences for particular amino acid residues as the sequences evolve. Heterogeneity in the amino acid substitution process between sites is not modeled by commonly used empirical amino acid exchange matrices. Such model misspecification can lead to artefacts in phylogenetic estimation such as long-branch attraction. Although sophisticated site-heterogeneous mixture models have been developed to address this problem in both Bayesian and maximum likelihood (ML) frameworks, their formidable computational time and memory usage severely limits their use in large phylogenomic analyses. Here we propose a posterior mean site frequency (PMSF) method as a rapid and efficient approximation to full empirical profile mixture models for ML analysis. The PMSF approach assigns a conditional mean amino acid frequency profile to each site calculated based on a mixture model fitted to the data using a preliminary guide tree. These PMSF profiles can then be used for in-depth tree-searching in place of the full mixture model. Compared with widely used empirical mixture models with $k$ classes, our implementation of PMSF in IQ-TREE (http://www.iqtree.org) speeds up the computation by approximately $k$/1.5-fold and requires a small fraction of the RAM. Furthermore, this speedup allows, for the first time, full nonparametric bootstrap analyses to be conducted under complex site-heterogeneous models on large concatenated data matrices. Our simulations and empirical data analyses demonstrate that PMSF can effectively ameliorate long-branch attraction artefacts. In some empirical and simulation settings PMSF provided more accurate estimates of phylogenies than the mixture models from which they derive.

Retention of the posterior cruciate ligament versus the posterior stabilized design in total knee arthroplasty: a prospective randomized controlled clinical trial

Directory of Open Access Journals (Sweden)

van den Akker-Scheek Inge

2009-09-01

Full Text Available Abstract Background Prosthetic design for the use in primary total knee arthroplasty has evolved into designs that preserve the posterior cruciate ligament (PCL and those in which the ligament is routinely sacrificed (posterior stabilized. In patients with a functional PCL the decision which design is chosen depends largely on the favour and training of the surgeon. The objective of this study is to determine whether the patient's perceived outcome and speed of recovery differs between a posterior cruciate retaining total knee arthroplasty and a posterior stabilized total knee arthroplasty. Methods/Design A randomized controlled trial will be conducted. Patients who are admitted for primary unilateral TKA due to primary osteoarthrosis are included when the following inclusion criteria are met: non-fixed fixed varus or valgus deformity less than 10 degrees, age between 55 and 85 years, body mass index less than 35 kg/m2 and ASA score (American Society of Anaesthesiologists I or II. Patients are randomized in 2 groups. Patients in the posterior cruciate retaining group will receive a prosthesis with a posterior cut-out for the posterior cruciate ligament and relatively flat topography. In patients allocated to the posterior stabilized group, in which the posterior cruciate ligament is excised, the design may substitute for this function by an intercondylar tibial prominence that articulates with the femur in flexion. Measurements will take place preoperatively and 6 weeks, 3 months, 6 months and 1 year postoperatively. At all measurement points patient's perceived outcome will be assessed using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC. Secondary outcome measures are quality of life (SF-36 and physician reported functional status and range of motion as determined with the Knee Society Clinical Rating System (KSS. Discussion In the current practice both posterior cruciate retaining and posterior stabilized designs

Optimal parameters for the FFA-Beddoes dynamic stall model

Energy Technology Data Exchange (ETDEWEB)

Bjoerck, A; Mert, M [FFA, The Aeronautical Research Institute of Sweden, Bromma (Sweden); Madsen, H A [Risoe National Lab., Roskilde (Denmark)

1999-03-01

Unsteady aerodynamic effects, like dynamic stall, must be considered in calculation of dynamic forces for wind turbines. Models incorporated in aero-elastic programs are of semi-empirical nature. Resulting aerodynamic forces therefore depend on values used for the semi-empiricial parameters. In this paper a study of finding appropriate parameters to use with the Beddoes-Leishman model is discussed. Minimisation of the `tracking error` between results from 2D wind tunnel tests and simulation with the model is used to find optimum values for the parameters. The resulting optimum parameters show a large variation from case to case. Using these different sets of optimum parameters in the calculation of blade vibrations, give rise to quite different predictions of aerodynamic damping which is discussed. (au)

Modelling the growth of Populus species using Ecosystem Demography (ED) model

Science.gov (United States)

Wang, D.; Lebauer, D. S.; Feng, X.; Dietze, M. C.

2010-12-01

Hybrid poplar plantations are an important source being evaluated for biomass production. Effective management of such plantations requires adequate growth and yield models. The Ecosystem Demography model (ED) makes predictions about the large scales of interest in above- and belowground ecosystem structure and the fluxes of carbon and water from a description of the fine-scale physiological processes. In this study, we used a workflow management tool, the Predictive Ecophysiological Carbon flux Analyzer (PECAn), to integrate literature data, field measurement and the ED model to provide predictions of ecosystem functioning. Parameters for the ED ensemble runs were sampled from the posterior distribution of ecophysiological traits of Populus species compiled from the literature using a Bayesian meta-analysis approach. Sensitivity analysis was performed to identify the parameters which contribute the most to the uncertainties of the ED model output. Model emulation techniques were used to update parameter posterior distributions using field-observed data in northern Wisconsin hybrid poplar plantations. Model results were evaluated with 5-year field-observed data in a hybrid poplar plantation at New Franklin, MO. ED was then used to predict the spatial variability of poplar yield in the coterminous United States (United States minus Alaska and Hawaii). Sensitivity analysis showed that root respiration, dark respiration, growth respiration, stomatal slope and specific leaf area contribute the most to the uncertainty, which suggests that our field measurements and data collection should focus on these parameters. The ED model successfully captured the inter-annual and spatial variability of the yield of poplar. Analyses in progress with the ED model focus on evaluating the ecosystem services of short-rotation woody plantations, such as impacts on soil carbon storage, water use, and nutrient retention.

Lumped-parameters equivalent circuit for condenser microphones modeling.

Science.gov (United States)

Esteves, Josué; Rufer, Libor; Ekeom, Didace; Basrour, Skandar

2017-10-01

This work presents a lumped parameters equivalent model of condenser microphone based on analogies between acoustic, mechanical, fluidic, and electrical domains. Parameters of the model were determined mainly through analytical relations and/or finite element method (FEM) simulations. Special attention was paid to the air gap modeling and to the use of proper boundary condition. Corresponding lumped-parameters were obtained as results of FEM simulations. Because of its simplicity, the model allows a fast simulation and is readily usable for microphone design. This work shows the validation of the equivalent circuit on three real cases of capacitive microphones, including both traditional and Micro-Electro-Mechanical Systems structures. In all cases, it has been demonstrated that the sensitivity and other related data obtained from the equivalent circuit are in very good agreement with available measurement data.

CT findings of posterior pararenal effusion

International Nuclear Information System (INIS)

Koh, Byung Hee; Cho, On Koo; Kim, Sonn Yong

1990-01-01

The posterior pararenal space(PPS) is a potential space between the posterior renal fascia and the transversalis fascia. We reviewed 12 cases of posterior pararenal effusion. The causes of the effusion were retroperitoneal hemorrhage due to trauma(7 cases) or rupture of renal tumor(1 case), pancreatitis(2 cases), urinoma (1 case) and amebic colitis of the cecum(1 case). The CT findings of the effusion were semilunar fluid density in the dependant portion of the PPS(9/12), partial obliteration of the PPS extending to the flank stripe(2/12), and total obliteration of the PPS extending to the anterior abdominal wall(1/12). The effusion in the ipsilateral perirenal space and thickening of the ipsilateral posterior renal fascia were combined in all cases. The effusion in the ipsilateral anterior pararenal space was associated in 11 cases of 12. The effusion in the PPS is not uncommon findings of retroperitoneal hemorrhage or effusion, but usually related with perirenal or anterior pararenal effusion with no clinical significance

Analysis of Modeling Parameters on Threaded Screws.

Energy Technology Data Exchange (ETDEWEB)

Vigil, Miquela S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Brake, Matthew Robert [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Vangoethem, Douglas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-06-01

Assembled mechanical systems often contain a large number of bolted connections. These bolted connections (joints) are integral aspects of the load path for structural dynamics, and, consequently, are paramount for calculating a structure's stiffness and energy dissipation prop- erties. However, analysts have not found the optimal method to model appropriately these bolted joints. The complexity of the screw geometry cause issues when generating a mesh of the model. This paper will explore different approaches to model a screw-substrate connec- tion. Model parameters such as mesh continuity, node alignment, wedge angles, and thread to body element size ratios are examined. The results of this study will give analysts a better understanding of the influences of these parameters and will aide in finding the optimal method to model bolted connections.

Assessing Heterogeneity for Factor Analysis Model with Continuous and Ordinal Outcomes

Directory of Open Access Journals (Sweden)

Ye-Mao Xia

2016-01-01

Full Text Available Factor analysis models with continuous and ordinal responses are a useful tool for assessing relations between the latent variables and mixed observed responses. These models have been successfully applied to many different fields, including behavioral, educational, and social-psychological sciences. However, within the Bayesian analysis framework, most developments are constrained within parametric families, of which the particular distributions are specified for the parameters of interest. This leads to difficulty in dealing with outliers and/or distribution deviations. In this paper, we propose a Bayesian semiparametric modeling for factor analysis model with continuous and ordinal variables. A truncated stick-breaking prior is used to model the distributions of the intercept and/or covariance structural parameters. Bayesian posterior analysis is carried out through the simulation-based method. Blocked Gibbs sampler is implemented to draw observations from the complicated posterior. For model selection, the logarithm of pseudomarginal likelihood is developed to compare the competing models. Empirical results are presented to illustrate the application of the methodology.

No difference in gait between posterior cruciate retention and the posterior stabilized design after total knee arthroplasty

NARCIS (Netherlands)

van den Boom, Lennard G. H.; Halbertsma, Jan P. K.; van Raaij, Jos J. A. M.; Brouwer, Reinoud W.; Bulstra, Sjoerd K.; van den Akker-Scheek, Inge

2014-01-01

In the present study, knee joint kinematics (e.g. knee flexion/extension) and kinetics (e.g. knee flexion moments) are assessed after total knee arthroplasty (TKA) between patients implanted with either a unilateral posterior stabilized (PS) and a posterior cruciate-retaining (PCR) design. It was

Parameter Estimates in Differential Equation Models for Chemical Kinetics

Science.gov (United States)

Winkel, Brian

2011-01-01

We discuss the need for devoting time in differential equations courses to modelling and the completion of the modelling process with efforts to estimate the parameters in the models using data. We estimate the parameters present in several differential equation models of chemical reactions of order n, where n = 0, 1, 2, and apply more general…

Simultaneous inference for model averaging of derived parameters

DEFF Research Database (Denmark)

Jensen, Signe Marie; Ritz, Christian

2015-01-01

Model averaging is a useful approach for capturing uncertainty due to model selection. Currently, this uncertainty is often quantified by means of approximations that do not easily extend to simultaneous inference. Moreover, in practice there is a need for both model averaging and simultaneous...... inference for derived parameters calculated in an after-fitting step. We propose a method for obtaining asymptotically correct standard errors for one or several model-averaged estimates of derived parameters and for obtaining simultaneous confidence intervals that asymptotically control the family...

Parameter identification in the logistic STAR model

DEFF Research Database (Denmark)

Ekner, Line Elvstrøm; Nejstgaard, Emil

We propose a new and simple parametrization of the so-called speed of transition parameter of the logistic smooth transition autoregressive (LSTAR) model. The new parametrization highlights that a consequence of the well-known identification problem of the speed of transition parameter is that th...

Regionalization of SWAT Model Parameters for Use in Ungauged Watersheds

Directory of Open Access Journals (Sweden)

Indrajeet Chaubey

2010-11-01

Full Text Available There has been a steady shift towards modeling and model-based approaches as primary methods of assessing watershed response to hydrologic inputs and land management, and of quantifying watershed-wide best management practice (BMP effectiveness. Watershed models often require some degree of calibration and validation to achieve adequate watershed and therefore BMP representation. This is, however, only possible for gauged watersheds. There are many watersheds for which there are very little or no monitoring data available, thus the question as to whether it would be possible to extend and/or generalize model parameters obtained through calibration of gauged watersheds to ungauged watersheds within the same region. This study explored the possibility of developing regionalized model parameter sets for use in ungauged watersheds. The study evaluated two regionalization methods: global averaging, and regression-based parameters, on the SWAT model using data from priority watersheds in Arkansas. Resulting parameters were tested and model performance determined on three gauged watersheds. Nash-Sutcliffe efficiencies (NS for stream flow obtained using regression-based parameters (0.53–0.83 compared well with corresponding values obtained through model calibration (0.45–0.90. Model performance obtained using global averaged parameter values was also generally acceptable (0.4 ≤ NS ≤ 0.75. Results from this study indicate that regionalized parameter sets for the SWAT model can be obtained and used for making satisfactory hydrologic response predictions in ungauged watersheds.

Soil-related Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

A. J. Smith

2003-01-01

This analysis is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the geologic repository at Yucca Mountain. The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A graphical representation of the documentation hierarchy for the ERMYN biosphere model is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (BSC 2003 [163602]). It should be noted that some documents identified in Figure 1-1 may be under development at the time this report is issued and therefore not available. This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this report. This report, ''Soil Related Input Parameters for the Biosphere Model'', is one of the five analysis reports that develop input parameters for use in the ERMYN model. This report is the source documentation for the six biosphere parameters identified in Table 1-1. ''The Biosphere Model Report'' (BSC 2003 [160699]) describes in detail the conceptual model as well as the mathematical model and its input parameters. The purpose of this analysis was to develop the biosphere model parameters needed to evaluate doses from pathways associated with the accumulation and depletion of radionuclides in the soil. These parameters support the calculation of radionuclide concentrations in soil from on-going irrigation and ash

Inhalation Exposure Input Parameters for the Biosphere Model

Energy Technology Data Exchange (ETDEWEB)

K. Rautenstrauch

2004-09-10

This analysis is one of 10 reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. Inhalation Exposure Input Parameters for the Biosphere Model is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the Technical Work Plan for Biosphere Modeling and Expert Support (BSC 2004 [DIRS 169573]). This analysis report defines and justifies values of mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception.

Inhalation Exposure Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

K. Rautenstrauch

2004-01-01

This analysis is one of 10 reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. Inhalation Exposure Input Parameters for the Biosphere Model is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the Technical Work Plan for Biosphere Modeling and Expert Support (BSC 2004 [DIRS 169573]). This analysis report defines and justifies values of mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception

Modeling and Parameter Estimation of a Small Wind Generation System

Directory of Open Access Journals (Sweden)

Carlos A. Ramírez Gómez

2013-11-01

Full Text Available The modeling and parameter estimation of a small wind generation system is presented in this paper. The system consists of a wind turbine, a permanent magnet synchronous generator, a three phase rectifier, and a direct current load. In order to estimate the parameters wind speed data are registered in a weather station located in the Fraternidad Campus at ITM. Wind speed data were applied to a reference model programed with PSIM software. From that simulation, variables were registered to estimate the parameters. The wind generation system model together with the estimated parameters is an excellent representation of the detailed model, but the estimated model offers a higher flexibility than the programed model in PSIM software.

Improving weather predictability by including land-surface model parameter uncertainty

Science.gov (United States)

Orth, Rene; Dutra, Emanuel; Pappenberger, Florian

2016-04-01

The land surface forms an important component of Earth system models and interacts nonlinearly with other parts such as ocean and atmosphere. To capture the complex and heterogenous hydrology of the land surface, land surface models include a large number of parameters impacting the coupling to other components of the Earth system model. Focusing on ECMWF's land-surface model HTESSEL we present in this study a comprehensive parameter sensitivity evaluation using multiple observational datasets in Europe. We select 6 poorly constrained effective parameters (surface runoff effective depth, skin conductivity, minimum stomatal resistance, maximum interception, soil moisture stress function shape, total soil depth) and explore their sensitivity to model outputs such as soil moisture, evapotranspiration and runoff using uncoupled simulations and coupled seasonal forecasts. Additionally we investigate the possibility to construct ensembles from the multiple land surface parameters. In the uncoupled runs we find that minimum stomatal resistance and total soil depth have the most influence on model performance. Forecast skill scores are moreover sensitive to the same parameters as HTESSEL performance in the uncoupled analysis. We demonstrate the robustness of our findings by comparing multiple best performing parameter sets and multiple randomly chosen parameter sets. We find better temperature and precipitation forecast skill with the best-performing parameter perturbations demonstrating representativeness of model performance across uncoupled (and hence less computationally demanding) and coupled settings. Finally, we construct ensemble forecasts from ensemble members derived with different best-performing parameterizations of HTESSEL. This incorporation of parameter uncertainty in the ensemble generation yields an increase in forecast skill, even beyond the skill of the default system. Orth, R., E. Dutra, and F. Pappenberger, 2016: Improving weather predictability by

Parameters-related uncertainty in modeling sugar cane yield with an agro-Land Surface Model

Science.gov (United States)

Valade, A.; Ciais, P.; Vuichard, N.; Viovy, N.; Ruget, F.; Gabrielle, B.

2012-12-01

Agro-Land Surface Models (agro-LSM) have been developed from the coupling of specific crop models and large-scale generic vegetation models. They aim at accounting for the spatial distribution and variability of energy, water and carbon fluxes within soil-vegetation-atmosphere continuum with a particular emphasis on how crop phenology and agricultural management practice influence the turbulent fluxes exchanged with the atmosphere, and the underlying water and carbon pools. A part of the uncertainty in these models is related to the many parameters included in the models' equations. In this study, we quantify the parameter-based uncertainty in the simulation of sugar cane biomass production with the agro-LSM ORCHIDEE-STICS on a multi-regional approach with data from sites in Australia, La Reunion and Brazil. First, the main source of uncertainty for the output variables NPP, GPP, and sensible heat flux (SH) is determined through a screening of the main parameters of the model on a multi-site basis leading to the selection of a subset of most sensitive parameters causing most of the uncertainty. In a second step, a sensitivity analysis is carried out on the parameters selected from the screening analysis at a regional scale. For this, a Monte-Carlo sampling method associated with the calculation of Partial Ranked Correlation Coefficients is used. First, we quantify the sensitivity of the output variables to individual input parameters on a regional scale for two regions of intensive sugar cane cultivation in Australia and Brazil. Then, we quantify the overall uncertainty in the simulation's outputs propagated from the uncertainty in the input parameters. Seven parameters are identified by the screening procedure as driving most of the uncertainty in the agro-LSM ORCHIDEE-STICS model output at all sites. These parameters control photosynthesis (optimal temperature of photosynthesis, optimal carboxylation rate), radiation interception (extinction coefficient), root

ESTIMATION OF DISTANCES TO STARS WITH STELLAR PARAMETERS FROM LAMOST

Energy Technology Data Exchange (ETDEWEB)

Carlin, Jeffrey L.; Newberg, Heidi Jo [Department of Physics, Applied Physics and Astronomy, Rensselaer Polytechnic Institute, Troy, NY 12180 (United States); Liu, Chao; Deng, Licai; Li, Guangwei; Luo, A-Li; Wu, Yue; Yang, Ming; Zhang, Haotong [Key Lab of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012 (China); Beers, Timothy C. [Department of Physics and JINA: Joint Institute for Nuclear Astrophysics, University of Notre Dame, 225 Nieuwland Science Hall, Notre Dame, IN 46556 (United States); Chen, Li; Hou, Jinliang; Smith, Martin C. [Shanghai Astronomical Observatory, 80 Nandan Road, Shanghai 200030 (China); Guhathakurta, Puragra [UCO/Lick Observatory, Department of Astronomy and Astrophysics, University of California, Santa Cruz, CA 95064 (United States); Hou, Yonghui [Nanjing Institute of Astronomical Optics and Technology, National Astronomical Observatories, Chinese Academy of Sciences, Nanjing 210042 (China); Lépine, Sébastien [Department of Physics and Astronomy, Georgia State University, 25 Park Place, Suite 605, Atlanta, GA 30303 (United States); Yanny, Brian [Fermi National Accelerator Laboratory, P.O. Box 500, Batavia, IL 60510 (United States); Zheng, Zheng, E-mail: jeffreylcarlin@gmail.com [Department of Physics and Astronomy, University of Utah, UT 84112 (United States)

2015-07-15

We present a method to estimate distances to stars with spectroscopically derived stellar parameters. The technique is a Bayesian approach with likelihood estimated via comparison of measured parameters to a grid of stellar isochrones, and returns a posterior probability density function for each star’s absolute magnitude. This technique is tailored specifically to data from the Large Sky Area Multi-object Fiber Spectroscopic Telescope (LAMOST) survey. Because LAMOST obtains roughly 3000 stellar spectra simultaneously within each ∼5° diameter “plate” that is observed, we can use the stellar parameters of the observed stars to account for the stellar luminosity function and target selection effects. This removes biasing assumptions about the underlying populations, both due to predictions of the luminosity function from stellar evolution modeling, and from Galactic models of stellar populations along each line of sight. Using calibration data of stars with known distances and stellar parameters, we show that our method recovers distances for most stars within ∼20%, but with some systematic overestimation of distances to halo giants. We apply our code to the LAMOST database, and show that the current precision of LAMOST stellar parameters permits measurements of distances with ∼40% error bars. This precision should improve as the LAMOST data pipelines continue to be refined.

MRI evaluation of the posterior meniscus root tear

International Nuclear Information System (INIS)

Zhang Jianjun; Zheng Zhuozhao; Li Xuan

2010-01-01

Objective: To determine the value of MRI for diagnosing the posterior meniscus root tear. Methods: MR examinations of 30 patients with tear of the posterior meniscus root confirmed by knee arthroscopies were retrospectively reviewed. Of the 30 patients, 17 with posterior medial meniscus root tear (MMRT) and 13 with posterior lateral meniscus root tear (LMRT). The diagnostic sensitivity of' MRI for the posterior meniscus root tear was analyzed. Fisher's exact test was used to compare the detection rate of MRI for MMRT with that for LMRT. Results: All 17 cases with MMRT and 9 cases out of 13 with LMRT were correctly diagnosed by MRI and the diagnostic sensitivity of MRI for the posterior meniscus root tear was 86.7% (26/30). The main MR appearance of the posterior meniscus root tear was distortion of the meniscal root, with its low signal replaced by abnormal high signal. The detection rate of MRI for MMRT (17/17) was significantly greater than that for LMRT (9/13) (P=0.026). The prevalence of MMRT associated with meniscus extrusion (15/17) was significantly greater than that of LMRT (6/13) (P=0.020), but the prevalence of MMRT associated with anterior cruciate ligament (ACL) injury (5/17) was significantly lower than that of LMRT (11/13) (P=0.004). Conclusion: MRI is a relatively good method for detection of posterior meniscus root tears and associated injuries. (authors)

Hybrid artificial bee colony algorithm for parameter optimization of five-parameter bidirectional reflectance distribution function model.

Science.gov (United States)

Wang, Qianqian; Zhao, Jing; Gong, Yong; Hao, Qun; Peng, Zhong

2017-11-20

A hybrid artificial bee colony (ABC) algorithm inspired by the best-so-far solution and bacterial chemotaxis was introduced to optimize the parameters of the five-parameter bidirectional reflectance distribution function (BRDF) model. To verify the performance of the hybrid ABC algorithm, we measured BRDF of three kinds of samples and simulated the undetermined parameters of the five-parameter BRDF model using the hybrid ABC algorithm and the genetic algorithm, respectively. The experimental results demonstrate that the hybrid ABC algorithm outperforms the genetic algorithm in convergence speed, accuracy, and time efficiency under the same conditions.

SPOTting Model Parameters Using a Ready-Made Python Package.

Directory of Open Access Journals (Sweden)

Tobias Houska

Full Text Available The choice for specific parameter estimation methods is often more dependent on its availability than its performance. We developed SPOTPY (Statistical Parameter Optimization Tool, an open source python package containing a comprehensive set of methods typically used to calibrate, analyze and optimize parameters for a wide range of ecological models. SPOTPY currently contains eight widely used algorithms, 11 objective functions, and can sample from eight parameter distributions. SPOTPY has a model-independent structure and can be run in parallel from the workstation to large computation clusters using the Message Passing Interface (MPI. We tested SPOTPY in five different case studies to parameterize the Rosenbrock, Griewank and Ackley functions, a one-dimensional physically based soil moisture routine, where we searched for parameters of the van Genuchten-Mualem function and a calibration of a biogeochemistry model with different objective functions. The case studies reveal that the implemented SPOTPY methods can be used for any model with just a minimal amount of code for maximal power of parameter optimization. They further show the benefit of having one package at hand that includes number of well performing parameter search methods, since not every case study can be solved sufficiently with every algorithm or every objective function.

Hydrological model parameter dimensionality is a weak measure of prediction uncertainty

Science.gov (United States)

Pande, S.; Arkesteijn, L.; Savenije, H.; Bastidas, L. A.

2015-04-01

This paper shows that instability of hydrological system representation in response to different pieces of information and associated prediction uncertainty is a function of model complexity. After demonstrating the connection between unstable model representation and model complexity, complexity is analyzed in a step by step manner. This is done measuring differences between simulations of a model under different realizations of input forcings. Algorithms are then suggested to estimate model complexity. Model complexities of the two model structures, SAC-SMA (Sacramento Soil Moisture Accounting) and its simplified version SIXPAR (Six Parameter Model), are computed on resampled input data sets from basins that span across the continental US. The model complexities for SIXPAR are estimated for various parameter ranges. It is shown that complexity of SIXPAR increases with lower storage capacity and/or higher recession coefficients. Thus it is argued that a conceptually simple model structure, such as SIXPAR, can be more complex than an intuitively more complex model structure, such as SAC-SMA for certain parameter ranges. We therefore contend that magnitudes of feasible model parameters influence the complexity of the model selection problem just as parameter dimensionality (number of parameters) does and that parameter dimensionality is an incomplete indicator of stability of hydrological model selection and prediction problems.

Parameter identification and global sensitivity analysis of Xin'anjiang model using meta-modeling approach

Directory of Open Access Journals (Sweden)

Xiao-meng Song

2013-01-01

Full Text Available Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity analysis of hydrological model is a key step in model uncertainty quantification, which can identify the dominant parameters, reduce the model calibration uncertainty, and enhance the model optimization efficiency. There are, however, some shortcomings in classical approaches, including the long duration of time and high computation cost required to quantitatively assess the sensitivity of a multiple-parameter hydrological model. For this reason, a two-step statistical evaluation framework using global techniques is presented. It is based on (1 a screening method (Morris for qualitative ranking of parameters, and (2 a variance-based method integrated with a meta-model for quantitative sensitivity analysis, i.e., the Sobol method integrated with the response surface model (RSMSobol. First, the Morris screening method was used to qualitatively identify the parameters' sensitivity, and then ten parameters were selected to quantify the sensitivity indices. Subsequently, the RSMSobol method was used to quantify the sensitivity, i.e., the first-order and total sensitivity indices based on the response surface model (RSM were calculated. The RSMSobol method can not only quantify the sensitivity, but also reduce the computational cost, with good accuracy compared to the classical approaches. This approach will be effective and reliable in the global sensitivity analysis of a complex large-scale distributed hydrological model.

Updating parameters of the chicken processing line model

DEFF Research Database (Denmark)

Kurowicka, Dorota; Nauta, Maarten; Jozwiak, Katarzyna

2010-01-01

A mathematical model of chicken processing that quantitatively describes the transmission of Campylobacter on chicken carcasses from slaughter to chicken meat product has been developed in Nauta et al. (2005). This model was quantified with expert judgment. Recent availability of data allows...... updating parameters of the model to better describe processes observed in slaughterhouses. We propose Bayesian updating as a suitable technique to update expert judgment with microbiological data. Berrang and Dickens’s data are used to demonstrate performance of this method in updating parameters...... of the chicken processing line model....

Can the human lumbar posterior columns be stimulated by transcutaneous spinal cord stimulation? A modeling study

OpenAIRE

Danner, Simon M.; Hofstoetter, Ursula S.; Ladenbauer, Josef; Rattay, Frank; Minassian, Karen

2011-01-01

Stimulation of different spinal cord segments in humans is a widely developed clinical practice for modification of pain, altered sensation and movement. The human lumbar cord has become a target for modification of motor control by epidural and more recently by transcutaneous spinal cord stimulation. Posterior columns of the lumbar spinal cord represent a vertical system of axons and when activated can add other inputs to the motor control of the spinal cord than stimulated posterior roots. ...

Variations of posterior vitreous detachment

OpenAIRE

Kakehashi, A.; Kado, M.; Akiba, J.; Hirokawa, H.

1997-01-01

AIMS—To identify variations in posterior vitreous detachment (PVD) and establish a clinical classification system for PVD.
METHODS—400 consecutive eyes were examined using biomicroscopy and vitreous photography and classified the PVD variations—complete PVD with collapse, complete PVD without collapse, partial PVD with thickened posterior vitreous cortex (TPVC), or partial PVD without TPVC.
RESULTS—In each PVD type, the most frequently seen ocular pathologies were as follows: in complete PVD ...

Precision of anterior and posterior corneal curvature measurements taken with the Oculus Pentacam

Directory of Open Access Journals (Sweden)

Elizabeth Chetty

2016-06-01

Full Text Available In the era of rapid advances in technology, new ophthalmic instruments are constantly influencing health sciences and necessitating investigations of the accuracy and precision of the new technology. The Oculus Pentacam (70700 has been available for some time now and numerous studies have investigated the precision of some of the parameters that the Pentacam is capable of measuring. Unfortunately some of these studies fall short in confusing the meaning of accuracy and precision and in not being able to analyse the data correctly or completely. The aim of this study was to investigate the precision of the anterior and posterior corneal curvature measurements taken with the Oculus Pentacam (70700 holistically with sound multivariate statistical methods. Twenty successive Pentacam measurements were taken over three different measuring sessions on one subject. Keratometric data for both the anterior and posterior corneal surfaces were analysed using multivariate statistics to determine the precision of the Oculus Pentacam. This instrument was found to have good precision both clinically and statistically for anterior corneal measurements but only good clinical precision for the posterior corneal surface. Key words: Oculus Pentacam; keratometric variation; corneal curvature; multivariate statistics

Seasonal and spatial variation in broadleaf forest model parameters

Science.gov (United States)

Groenendijk, M.; van der Molen, M. K.; Dolman, A. J.

2009-04-01

Process based, coupled ecosystem carbon, energy and water cycle models are used with the ultimate goal to project the effect of future climate change on the terrestrial carbon cycle. A typical dilemma in such exercises is how much detail the model must be given to describe the observations reasonably realistic while also be general. We use a simple vegetation model (5PM) with five model parameters to study the variability of the parameters. These parameters are derived from the observed carbon and water fluxes from the FLUXNET database. For 15 broadleaf forests the model parameters were derived for different time resolutions. It appears that in general for all forests, the correlation coefficient between observed and simulated carbon and water fluxes improves with a higher parameter time resolution. The quality of the simulations is thus always better when a higher time resolution is used. These results show that annual parameters are not capable of properly describing weather effects on ecosystem fluxes, and that two day time resolution yields the best results. A first indication of the climate constraints can be found by the seasonal variation of the covariance between Jm, which describes the maximum electron transport for photosynthesis, and climate variables. A general seasonality we found is that during winter the covariance with all climate variables is zero. Jm increases rapidly after initial spring warming, resulting in a large covariance with air temperature and global radiation. During summer Jm is less variable, but co-varies negatively with air temperature and vapour pressure deficit and positively with soil water content. A temperature response appears during spring and autumn for broadleaf forests. This shows that an annual model parameter cannot be representative for the entire year. And relations with mean annual temperature are not possible. During summer the photosynthesis parameters are constrained by water availability, soil water content and

Efficient Stochastic Inversion Using Adjoint Models and Kernel-PCA

Energy Technology Data Exchange (ETDEWEB)

Thimmisetty, Charanraj A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Center for Applied Scientific Computing; Zhao, Wenju [Florida State Univ., Tallahassee, FL (United States). Dept. of Scientific Computing; Chen, Xiao [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Center for Applied Scientific Computing; Tong, Charles H. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Center for Applied Scientific Computing; White, Joshua A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Atmospheric, Earth and Energy Division

2017-10-18

Performing stochastic inversion on a computationally expensive forward simulation model with a high-dimensional uncertain parameter space (e.g. a spatial random field) is computationally prohibitive even when gradient information can be computed efficiently. Moreover, the ‘nonlinear’ mapping from parameters to observables generally gives rise to non-Gaussian posteriors even with Gaussian priors, thus hampering the use of efficient inversion algorithms designed for models with Gaussian assumptions. In this paper, we propose a novel Bayesian stochastic inversion methodology, which is characterized by a tight coupling between the gradient-based Langevin Markov Chain Monte Carlo (LMCMC) method and a kernel principal component analysis (KPCA). This approach addresses the ‘curse-of-dimensionality’ via KPCA to identify a low-dimensional feature space within the high-dimensional and nonlinearly correlated parameter space. In addition, non-Gaussian posterior distributions are estimated via an efficient LMCMC method on the projected low-dimensional feature space. We will demonstrate this computational framework by integrating and adapting our recent data-driven statistics-on-manifolds constructions and reduction-through-projection techniques to a linear elasticity model.

An empirical multivariate log-normal distribution representing uncertainty of biokinetic parameters for 137Cs

International Nuclear Information System (INIS)

Miller, G.; Martz, H.; Bertelli, L.; Melo, D.

2008-01-01

A simplified biokinetic model for 137 Cs has six parameters representing transfer of material to and from various compartments. Using a Bayesian analysis, the joint probability distribution of these six parameters is determined empirically for two cases with quite a lot of bioassay data. The distribution is found to be a multivariate log-normal. Correlations between different parameters are obtained. The method utilises a fairly large number of pre-determined forward biokinetic calculations, whose results are stored in interpolation tables. Four different methods to sample the multidimensional parameter space with a limited number of samples are investigated: random, stratified, Latin Hypercube sampling with a uniform distribution of parameters and importance sampling using a lognormal distribution that approximates the posterior distribution. The importance sampling method gives much smaller sampling uncertainty. No sampling method-dependent differences are perceptible for the uniform distribution methods. (authors)

Temporal variation and scaling of parameters for a monthly hydrologic model

Science.gov (United States)

Deng, Chao; Liu, Pan; Wang, Dingbao; Wang, Weiguang

2018-03-01

The temporal variation of model parameters is affected by the catchment conditions and has a significant impact on hydrological simulation. This study aims to evaluate the seasonality and downscaling of model parameter across time scales based on monthly and mean annual water balance models with a common model framework. Two parameters of the monthly model, i.e., k and m, are assumed to be time-variant at different months. Based on the hydrological data set from 121 MOPEX catchments in the United States, we firstly analyzed the correlation between parameters (k and m) and catchment properties (NDVI and frequency of rainfall events, α). The results show that parameter k is positively correlated with NDVI or α, while the correlation is opposite for parameter m, indicating that precipitation and vegetation affect monthly water balance by controlling temporal variation of parameters k and m. The multiple linear regression is then used to fit the relationship between ε and the means and coefficient of variations of parameters k and m. Based on the empirical equation and the correlations between the time-variant parameters and NDVI, the mean annual parameter ε is downscaled to monthly k and m. The results show that it has lower NSEs than these from model with time-variant k and m being calibrated through SCE-UA, while for several study catchments, it has higher NSEs than that of the model with constant parameters. The proposed method is feasible and provides a useful tool for temporal scaling of model parameter.

An improved state-parameter analysis of ecosystem models using data assimilation

Science.gov (United States)

Chen, M.; Liu, S.; Tieszen, L.L.; Hollinger, D.Y.

2008-01-01

Much of the effort spent in developing data assimilation methods for carbon dynamics analysis has focused on estimating optimal values for either model parameters or state variables. The main weakness of estimating parameter values alone (i.e., without considering state variables) is that all errors from input, output, and model structure are attributed to model parameter uncertainties. On the other hand, the accuracy of estimating state variables may be lowered if the temporal evolution of parameter values is not incorporated. This research develops a smoothed ensemble Kalman filter (SEnKF) by combining ensemble Kalman filter with kernel smoothing technique. SEnKF has following characteristics: (1) to estimate simultaneously the model states and parameters through concatenating unknown parameters and state variables into a joint state vector; (2) to mitigate dramatic, sudden changes of parameter values in parameter sampling and parameter evolution process, and control narrowing of parameter variance which results in filter divergence through adjusting smoothing factor in kernel smoothing algorithm; (3) to assimilate recursively data into the model and thus detect possible time variation of parameters; and (4) to address properly various sources of uncertainties stemming from input, output and parameter uncertainties. The SEnKF is tested by assimilating observed fluxes of carbon dioxide and environmental driving factor data from an AmeriFlux forest station located near Howland, Maine, USA, into a partition eddy flux model. Our analysis demonstrates that model parameters, such as light use efficiency, respiration coefficients, minimum and optimum temperatures for photosynthetic activity, and others, are highly constrained by eddy flux data at daily-to-seasonal time scales. The SEnKF stabilizes parameter values quickly regardless of the initial values of the parameters. Potential ecosystem light use efficiency demonstrates a strong seasonality. Results show that the

Setting Parameters for Biological Models With ANIMO

NARCIS (Netherlands)

Schivo, Stefano; Scholma, Jetse; Karperien, Hermanus Bernardus Johannes; Post, Janine Nicole; van de Pol, Jan Cornelis; Langerak, Romanus; André, Étienne; Frehse, Goran

2014-01-01

ANIMO (Analysis of Networks with Interactive MOdeling) is a software for modeling biological networks, such as e.g. signaling, metabolic or gene networks. An ANIMO model is essentially the sum of a network topology and a number of interaction parameters. The topology describes the interactions

Isolated posterior capsular rupture following blunt head trauma

Directory of Open Access Journals (Sweden)

Mansour AM

2014-11-01

Full Text Available Ahmad M Mansour, Mahmoud O Jaroudi, Rola N Hamam, Fadi C Maalouf Department of Ophthalmology, American University of Beirut, Beirut, Lebanon Abstract: Closed-globe traumatic cataract is not uncommon in males in the pediatric age group. However, there is a relative paucity of literature on isolated posterior lens capsule rupture associated with closed-globe traumatic cataract. We report a case of a 6-year-old boy who presented with white cataract 1 day after blunt trauma to the forehead associated with posterior capsular rupture that was detected by B-scan ultrasonography preoperatively. No stigmata of trauma outside the posterior capsule could be detected by slit-lamp exam, funduscopy, and optical coherence tomography. Phacoemulsification with posterior chamber intraocular lens implant was performed 24 hours after trauma, with the patient achieving 6/6 visual acuity 1 week and 6 months after surgery. Our case is unique, being the youngest (amblyogenic age to be reported, with prompt surgical intervention, and with no signs of trauma outside the posterior capsule. Keywords: posterior capsule rupture, forehead trauma, traumatic cataract, pediatric cataract

Constant-parameter capture-recapture models

Science.gov (United States)

Brownie, C.; Hines, J.E.; Nichols, J.D.

1986-01-01

Jolly (1982, Biometrics 38, 301-321) presented modifications of the Jolly-Seber model for capture-recapture data, which assume constant survival and/or capture rates. Where appropriate, because of the reduced number of parameters, these models lead to more efficient estimators than the Jolly-Seber model. The tests to compare models given by Jolly do not make complete use of the data, and we present here the appropriate modifications, and also indicate how to carry out goodness-of-fit tests which utilize individual capture history information. We also describe analogous models for the case where young and adult animals are tagged. The availability of computer programs to perform the analysis is noted, and examples are given using output from these programs.

Ground level enhancement (GLE) energy spectrum parameters model

Science.gov (United States)

Qin, G.; Wu, S.

2017-12-01

We study the ground level enhancement (GLE) events in solar cycle 23 with the four energy spectra parameters, the normalization parameter C, low-energy power-law slope γ 1, high-energy power-law slope γ 2, and break energy E0, obtained by Mewaldt et al. 2012 who fit the observations to the double power-law equation. we divide the GLEs into two groups, one with strong acceleration by interplanetary (IP) shocks and another one without strong acceleration according to the condition of solar eruptions. We next fit the four parameters with solar event conditions to get models of the parameters for the two groups of GLEs separately. So that we would establish a model of energy spectrum for GLEs for the future space weather prediction.

Parameter Estimation of Spacecraft Fuel Slosh Model

Science.gov (United States)

Gangadharan, Sathya; Sudermann, James; Marlowe, Andrea; Njengam Charles

2004-01-01

Fuel slosh in the upper stages of a spinning spacecraft during launch has been a long standing concern for the success of a space mission. Energy loss through the movement of the liquid fuel in the fuel tank affects the gyroscopic stability of the spacecraft and leads to nutation (wobble) which can cause devastating control issues. The rate at which nutation develops (defined by Nutation Time Constant (NTC can be tedious to calculate and largely inaccurate if done during the early stages of spacecraft design. Pure analytical means of predicting the influence of onboard liquids have generally failed. A strong need exists to identify and model the conditions of resonance between nutation motion and liquid modes and to understand the general characteristics of the liquid motion that causes the problem in spinning spacecraft. A 3-D computerized model of the fuel slosh that accounts for any resonant modes found in the experimental testing will allow for increased accuracy in the overall modeling process. Development of a more accurate model of the fuel slosh currently lies in a more generalized 3-D computerized model incorporating masses, springs and dampers. Parameters describing the model include the inertia tensor of the fuel, spring constants, and damper coefficients. Refinement and understanding the effects of these parameters allow for a more accurate simulation of fuel slosh. The current research will focus on developing models of different complexity and estimating the model parameters that will ultimately provide a more realistic prediction of Nutation Time Constant obtained through simulation.

A Comparison of Grizzly Bear Demographic Parameters Estimated from Non-Spatial and Spatial Open Population Capture-Recapture Models.

Science.gov (United States)

Whittington, Jesse; Sawaya, Michael A

2015-01-01

Capture-recapture studies are frequently used to monitor the status and trends of wildlife populations. Detection histories from individual animals are used to estimate probability of detection and abundance or density. The accuracy of abundance and density estimates depends on the ability to model factors affecting detection probability. Non-spatial capture-recapture models have recently evolved into spatial capture-recapture models that directly include the effect of distances between an animal's home range centre and trap locations on detection probability. Most studies comparing non-spatial and spatial capture-recapture biases focussed on single year models and no studies have compared the accuracy of demographic parameter estimates from open population models. We applied open population non-spatial and spatial capture-recapture models to three years of grizzly bear DNA-based data from Banff National Park and simulated data sets. The two models produced similar estimates of grizzly bear apparent survival, per capita recruitment, and population growth rates but the spatial capture-recapture models had better fit. Simulations showed that spatial capture-recapture models produced more accurate parameter estimates with better credible interval coverage than non-spatial capture-recapture models. Non-spatial capture-recapture models produced negatively biased estimates of apparent survival and positively biased estimates of per capita recruitment. The spatial capture-recapture grizzly bear population growth rates and 95% highest posterior density averaged across the three years were 0.925 (0.786-1.071) for females, 0.844 (0.703-0.975) for males, and 0.882 (0.779-0.981) for females and males combined. The non-spatial capture-recapture population growth rates were 0.894 (0.758-1.024) for females, 0.825 (0.700-0.948) for males, and 0.863 (0.771-0.957) for both sexes. The combination of low densities, low reproductive rates, and predominantly negative population growth

A Comparison of Grizzly Bear Demographic Parameters Estimated from Non-Spatial and Spatial Open Population Capture-Recapture Models.

Directory of Open Access Journals (Sweden)

Jesse Whittington

Full Text Available Capture-recapture studies are frequently used to monitor the status and trends of wildlife populations. Detection histories from individual animals are used to estimate probability of detection and abundance or density. The accuracy of abundance and density estimates depends on the ability to model factors affecting detection probability. Non-spatial capture-recapture models have recently evolved into spatial capture-recapture models that directly include the effect of distances between an animal's home range centre and trap locations on detection probability. Most studies comparing non-spatial and spatial capture-recapture biases focussed on single year models and no studies have compared the accuracy of demographic parameter estimates from open population models. We applied open population non-spatial and spatial capture-recapture models to three years of grizzly bear DNA-based data from Banff National Park and simulated data sets. The two models produced similar estimates of grizzly bear apparent survival, per capita recruitment, and population growth rates but the spatial capture-recapture models had better fit. Simulations showed that spatial capture-recapture models produced more accurate parameter estimates with better credible interval coverage than non-spatial capture-recapture models. Non-spatial capture-recapture models produced negatively biased estimates of apparent survival and positively biased estimates of per capita recruitment. The spatial capture-recapture grizzly bear population growth rates and 95% highest posterior density averaged across the three years were 0.925 (0.786-1.071 for females, 0.844 (0.703-0.975 for males, and 0.882 (0.779-0.981 for females and males combined. The non-spatial capture-recapture population growth rates were 0.894 (0.758-1.024 for females, 0.825 (0.700-0.948 for males, and 0.863 (0.771-0.957 for both sexes. The combination of low densities, low reproductive rates, and predominantly negative

Markov Chain Monte Carlo (MCMC) methods for parameter estimation of a novel hybrid redundant robot

International Nuclear Information System (INIS)

Wang Yongbo; Wu Huapeng; Handroos, Heikki

2011-01-01

This paper presents a statistical method for the calibration of a redundantly actuated hybrid serial-parallel robot IWR (Intersector Welding Robot). The robot under study will be used to carry out welding, machining, and remote handing for the assembly of vacuum vessel of International Thermonuclear Experimental Reactor (ITER). The robot has ten degrees of freedom (DOF), among which six DOF are contributed by the parallel mechanism and the rest are from the serial mechanism. In this paper, a kinematic error model which involves 54 unknown geometrical error parameters is developed for the proposed robot. Based on this error model, the mean values of the unknown parameters are statistically analyzed and estimated by means of Markov Chain Monte Carlo (MCMC) approach. The computer simulation is conducted by introducing random geometric errors and measurement poses which represent the corresponding real physical behaviors. The simulation results of the marginal posterior distributions of the estimated model parameters indicate that our method is reliable and robust.

Abordagem cirúrgica posterior e posterolateral para neurinomas cervicais em ampulheta da raiz de C2 Posterior y posterolateral enfoque quirúrgico para los neurinomas de la raíz cervical C2 Posterior and posterior-lateral surgical approach for C2 hourglass-shaped cervical neurinomas

Directory of Open Access Journals (Sweden)

Asdrubal Falavigna

2010-06-01

Full Text Available OBJETIVO: os autores relatam a experiência cirúrgica de 11 neurinomas em ampulheta de C2 comparando à via de acesso posterior com a posterolateral. MÉTODOS: onze pacientes com neurinomas em ampulheta de raiz cervical de C2 foram tratados cirurgicamente. A via de acesso utilizada para a remoção dos tumores foi a abordagem posterior em sete pacientes, e a posterolateral em quatro pacientes. RESULTADOS: houve predominância do sexo feminino (n=6 e a média de idade foi de 55,9±8,16 anos. O tempo médio de sintoma até o diagnóstico foi de 16,3 meses (±8,02 meses. Houve ressecção completa do tumor em todos os pacientes. O tempo cirúrgico médio na abordagem posterior foi de 180 minutos (±39,15 e de 192 minutos (±22,17 pela via posterolateral (p=0,52. Não houve diferença estatisticamente significativa entre as abordagens em relação ao sangramento transoperatório (posterior: 70,71±16,93; posterolateral: 65,00±24,15; p=0,64. Ocorreu uma complicação com a via de acesso posterior ligada à presença de uma fístula de líquor, sendo necessária nova intervenção e reconstrução da dura-máter utilizando a fáscia lata. CONCLUSÃO: a retirada completa do tumor em ampulheta da raiz de C2 é possível através das abordagens posterior e posterolateral, entretanto, a abordagem posterior é preferível por ser a via de acesso mais familiar ao cirurgião.OBJETIVO: os autores describen la experiencia quirúrgica de 11 neurinomas en reloj de arena de la raíz de C2 comparando el camino de acceso posterior y el postero-lateral. MÉTODOS: se trataron con cirugía 11 pacientes con neurinoma en reloj de arena de raíz cervical de C2. El camino de acceso utilizado para la retirada de los tumores fue la aproximación posterior en siete pacientes, y la aproximación postero-lateral, en 4. RESULTADOS: hubo predominio del sexo femenino (n=6, siendo la edad promedio de 55,9 ± 8,16 años. El tiempo medio de los síntomas hasta su diagnóstico fue

Soil-Related Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

Smith, A. J.

2004-01-01

This report presents one of the analyses that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the details of the conceptual model as well as the mathematical model and the required input parameters. The biosphere model is one of a series of process models supporting the postclosure Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A schematic representation of the documentation flow for the Biosphere input to TSPA is presented in Figure 1-1. This figure shows the evolutionary relationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (TWP) (BSC 2004 [DIRS 169573]). This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this report. This report, ''Soil-Related Input Parameters for the Biosphere Model'', is one of the five analysis reports that develop input parameters for use in the ERMYN model. This report is the source documentation for the six biosphere parameters identified in Table 1-1. The purpose of this analysis was to develop the biosphere model parameters associated with the accumulation and depletion of radionuclides in the soil. These parameters support the calculation of radionuclide concentrations in soil from on-going irrigation or ash deposition and, as a direct consequence, radionuclide concentration in other environmental media that are affected by radionuclide concentrations in soil. The analysis was performed in accordance with the TWP (BSC 2004 [DIRS 169573]) where the governing procedure was defined as AP-SIII.9Q, ''Scientific Analyses''. This

On the estimation of stellar parameters with uncertainty prediction from Generative Artificial Neural Networks: application to Gaia RVS simulated spectra

Science.gov (United States)

Dafonte, C.; Fustes, D.; Manteiga, M.; Garabato, D.; Álvarez, M. A.; Ulla, A.; Allende Prieto, C.

2016-10-01

Aims: We present an innovative artificial neural network (ANN) architecture, called Generative ANN (GANN), that computes the forward model, that is it learns the function that relates the unknown outputs (stellar atmospheric parameters, in this case) to the given inputs (spectra). Such a model can be integrated in a Bayesian framework to estimate the posterior distribution of the outputs. Methods: The architecture of the GANN follows the same scheme as a normal ANN, but with the inputs and outputs inverted. We train the network with the set of atmospheric parameters (Teff, log g, [Fe/H] and [α/ Fe]), obtaining the stellar spectra for such inputs. The residuals between the spectra in the grid and the estimated spectra are minimized using a validation dataset to keep solutions as general as possible. Results: The performance of both conventional ANNs and GANNs to estimate the stellar parameters as a function of the star brightness is presented and compared for different Galactic populations. GANNs provide significantly improved parameterizations for early and intermediate spectral types with rich and intermediate metallicities. The behaviour of both algorithms is very similar for our sample of late-type stars, obtaining residuals in the derivation of [Fe/H] and [α/ Fe] below 0.1 dex for stars with Gaia magnitude Grvs satellite. Conclusions: Uncertainty estimation of computed astrophysical parameters is crucial for the validation of the parameterization itself and for the subsequent exploitation by the astronomical community. GANNs produce not only the parameters for a given spectrum, but a goodness-of-fit between the observed spectrum and the predicted one for a given set of parameters. Moreover, they allow us to obtain the full posterior distribution over the astrophysical parameters space once a noise model is assumed. This can be used for novelty detection and quality assessment.

Posterior Urethroplasty Complexity and Prognosis Can be Described by a Novel Method: Posterior Urethral Stenosis Score.

Science.gov (United States)

Wang, Lin; Lv, Xiangguo; Jin, Chongrui; Guo, Hailin; Shu, Huiquan; Fu, Qiang; Sa, Yinglong

2018-02-01

To develop a standardized PU-score (posterior urethral stenosis score), with the goal of using this scoring system as a preliminary predictor of surgical complexity and prognosis of posterior urethral stenosis. We retrospectively reviewed records of all patients who underwent posterior urethral surgery at our institution from 2013 to 2015. The PU-score is based on 5 components, namely etiology (1 or 2 points), location (1-3 points), length (1-3 points), urethral fistula (1 or 2 points), and posterior urethral false passage (1 point). We calculated the score of all patients and analyzed its association with surgical complexity, stenosis recurrence, intraoperative blood loss, erectile dysfunction, and urinary incontinence. There were 144 patients who underwent low complexity urethral surgery (direct vision internal urethrotomy, anastomosis with or without crural separation) with a mean score of 5.1 points, whereas 143 underwent high complexity urethroplasty (anastomosis with inferior pubectomy or urethrorectal fistula repair, perineal or scrotum skin flap urethroplasty, bladder flap urethroplasty) with a mean score of 6.9 points. The increase of PU-score was predictive of higher surgical complexity (P = .000), higher recurrence (P = .002), more intraoperative blood loss (P = .000), and decrease of preoperative (P = .037) or postoperative erectile function (P = .047). However, no association was observed between PU-score and urinary incontinence (P = .213). The PU-score is a novel and meaningful scoring system that describes the essential factors in determining the complexity and prognosis for posterior urethral stenosis. Copyright © 2017. Published by Elsevier Inc.

Bayesian Predictive Models for Rayleigh Wind Speed

DEFF Research Database (Denmark)

Shahirinia, Amir; Hajizadeh, Amin; Yu, David C

2017-01-01

predictive model of the wind speed aggregates the non-homogeneous distributions into a single continuous distribution. Therefore, the result is able to capture the variation among the probability distributions of the wind speeds at the turbines’ locations in a wind farm. More specifically, instead of using...... a wind speed distribution whose parameters are known or estimated, the parameters are considered as random whose variations are according to probability distributions. The Bayesian predictive model for a Rayleigh which only has a single model scale parameter has been proposed. Also closed-form posterior...... and predictive inferences under different reasonable choices of prior distribution in sensitivity analysis have been presented....

Quantifying Parameter Sensitivity, Interaction and Transferability in Hydrologically Enhanced Versions of Noah-LSM over Transition Zones

Science.gov (United States)

Rosero, Enrique; Yang, Zong-Liang; Wagener, Thorsten; Gulden, Lindsey E.; Yatheendradas, Soni; Niu, Guo-Yue

2009-01-01

We use sensitivity analysis to identify the parameters that are most responsible for shaping land surface model (LSM) simulations and to understand the complex interactions in three versions of the Noah LSM: the standard version (STD), a version enhanced with a simple groundwater module (GW), and version augmented by a dynamic phenology module (DV). We use warm season, high-frequency, near-surface states and turbulent fluxes collected over nine sites in the US Southern Great Plains. We quantify changes in the pattern of sensitive parameters, the amount and nature of the interaction between parameters, and the covariance structure of the distribution of behavioral parameter sets. Using Sobol s total and first-order sensitivity indexes, we show that very few parameters directly control the variance of the model output. Significant parameter interaction occurs so that not only the optimal parameter values differ between models, but the relationships between parameters change. GW decreases parameter interaction and appears to improve model realism, especially at wetter sites. DV increases parameter interaction and decreases identifiability, implying it is overparameterized and/or underconstrained. A case study at a wet site shows GW has two functional modes: one that mimics STD and a second in which GW improves model function by decoupling direct evaporation and baseflow. Unsupervised classification of the posterior distributions of behavioral parameter sets cannot group similar sites based solely on soil or vegetation type, helping to explain why transferability between sites and models is not straightforward. This evidence suggests a priori assignment of parameters should also consider climatic differences.

A new code for parameter estimation in searches for gravitational waves from known pulsars

International Nuclear Information System (INIS)

Pitkin, M; Gill, C; Macdonald, E; Woan, G; Veitch, J

2012-01-01

We describe the consistency testing of a new code for gravitational wave signal parameter estimation in known pulsar searches. The code uses an implementation of nested sampling to explore the likelihood volume. Using fake signals and simulated noise we compare this to a previous code that calculated the signal parameter posterior distributions on both a grid and using a crude Markov chain Monte Carlo (MCMC) method. We define a new parameterisation of two orientation angles of neutron stars used in the signal model (the initial phase and polarisation angle), which breaks a degeneracy between them and allows more efficient exploration of those parameters. Finally, we briefly describe potential areas for further study and the uses of this code in the future.

Head CT: Image quality improvement of posterior fossa and radiation dose reduction with ASiR - comparative studies of CT head examinations.

Science.gov (United States)

Guziński, Maciej; Waszczuk, Łukasz; Sąsiadek, Marek J

2016-10-01

To evaluate head CT protocol developed to improve visibility of the brainstem and cerebellum, lower bone-related artefacts in the posterior fossa and maintain patient radioprotection. A paired comparison of head CT performed without Adaptive Statistical Iterative Reconstruction (ASiR) and a clinically indicated follow-up with 40 % ASiR was acquired in one group of 55 patients. Patients were scanned in the axial mode with different scanner settings for the brain and the posterior fossa. Objective image quality analysis was performed with signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Subjective image quality analysis was based on brain structure visibility and evaluation of the artefacts. We achieved 19 % reduction of total DLP and significantly better image quality of posterior fossa structures. SNR for white and grey matter in the cerebellum were 34 % to 36 % higher, respectively, CNR was improved by 142 % and subjective analyses were better for images with ASiR. When imaging parameters are set independently for the brain and the posterior fossa imaging, ASiR has a great potential to improve CT performance: image quality of the brainstem and cerebellum is improved, and radiation dose for the brain as well as total radiation dose are reduced. •With ASiR it is possible to lower radiation dose or improve image quality •Sequentional imaging allows setting scan parameters for brain and posterior-fossa independently •We improved visibility of brainstem structures and decreased radiation dose •Total radiation dose (DLP) was decreased by 19.

Early endoscopic realignment in posterior urethral injuries.

Science.gov (United States)

Shrestha, B; Baidya, J L

2013-01-01

Posterior urethral injury requires meticulous tertiary care and optimum expertise to manage successfully. The aim of our study is to describe our experiences with pelvic injuries involving posterior urethra and their outcome after early endoscopic realignment. A prospective study was carried out in 20 patients with complete posterior urethral rupture, from November 2007 till October 2010. They presented with blunt traumatic pelvic fracture and underwent primary realignment of posterior urethra in our institute. The definitive diagnosis of urethral rupture was made after retrograde urethrography and antegrade urethrography where applicable. The initial management was suprapubic catheter insertion after primary trauma management in casualty. After a week of conservative management with intravenous antibiotics and pain management, patients were subjected to the endoscopic realignment. The follow up period was at least six months. The results were analyzed with SPSS software. After endoscopic realignment, all patients were advised CISC for the initial 3 months. All patients voided well after three months of CISC. However, 12 patients were lost to follow up by the end of 6 postoperative months. Out of eight remaining patients, two had features of restricture and were managed with DVU followed by CISC again. One patient with restricture had some degree of erectile dysfunction who improved significantly after phospodiesterase inhibitors. None of the patients had features of incontinence. Early endoscopic realignment of posterior urethra is a minimally invasive modality in the management of complete posterior urethral injury with low rates of incontinence and impotency.

Avaliação textural por ressonância magnética dos tumores da fossa posterior em crianças Magnetic resonance imaging textural evaluation of posterior cranial fossa tumors in childhood

Directory of Open Access Journals (Sweden)

Joelson Alves dos Santos

2004-08-01

Full Text Available OBJETIVO: Possibilitar a distinção entre tecidos sãos e patológicos em pacientes da faixa etária pediátrica portadores de tumores da fossa posterior, por meio da análise de parâmetros texturais calculados a partir de imagens de ressonância magnética. MATERIAIS E MÉTODOS: Foram analisados 14 pacientes da faixa etária pediátrica, portadores de tumores da fossa posterior, através da definição dos valores texturais das regiões de interesse representando tecidos sãos e patológicos, com base em imagens de ressonância magnética pesadas em T2 pelo "software" MaZda. RESULTADOS: Houve diferença estatisticamente significativa entre os tecidos normal e tumoral, bem como entre os tecidos presumidamente normais adjacentes e distantes da lesão. Não foi possível a distinção entre edema e tumor. CONCLUSÃO: A avaliação textural por ressonância magnética é uma técnica útil para a determinação de diferenças entre diversos tipos de tecidos, inclusive entre áreas de tecidos presumidamente normais à análise visual.OBJECTIVE: To distinguish healthy from pathological tissues in pediatric patients with posterior cranial fossa tumors using calculated textural parameters from magnetic resonance images. MATERIALS AND METHODS: We evaluated 14 pediatric patients with posterior cranial fossa tumors using the software MaZda to define the texture parameters in selected regions of interest representing healthy and pathological tissues based on T2-weighted magnetic resonance images. RESULTS: There was a statistically significant difference between normal and tumoral tissues as well as between supposedly normal tissues adjacent and distant from the tumoral lesion. CONCLUSION: Magnetic resonance textural evaluation is an useful tool for determining differences among various tissues, including tissues that appear apparently normal on visual analysis.

Parameter estimation in nonlinear models for pesticide degradation

International Nuclear Information System (INIS)

Richter, O.; Pestemer, W.; Bunte, D.; Diekkrueger, B.

1991-01-01

A wide class of environmental transfer models is formulated as ordinary or partial differential equations. With the availability of fast computers, the numerical solution of large systems became feasible. The main difficulty in performing a realistic and convincing simulation of the fate of a substance in the biosphere is not the implementation of numerical techniques but rather the incomplete data basis for parameter estimation. Parameter estimation is a synonym for statistical and numerical procedures to derive reasonable numerical values for model parameters from data. The classical method is the familiar linear regression technique which dates back to the 18th century. Because it is easy to handle, linear regression has long been established as a convenient tool for analysing relationships. However, the wide use of linear regression has led to an overemphasis of linear relationships. In nature, most relationships are nonlinear and linearization often gives a poor approximation of reality. Furthermore, pure regression models are not capable to map the dynamics of a process. Therefore, realistic models involve the evolution in time (and space). This leads in a natural way to the formulation of differential equations. To establish the link between data and dynamical models, numerical advanced parameter identification methods have been developed in recent years. This paper demonstrates the application of these techniques to estimation problems in the field of pesticide dynamics. (7 refs., 5 figs., 2 tabs.)

Biological parameters for lung cancer in mathematical models of carcinogenesis

International Nuclear Information System (INIS)

Jacob, P.; Jacob, V.

2003-01-01

Applications of the two-step model of carcinogenesis with clonal expansion (TSCE) to lung cancer data are reviewed, including those on atomic bomb survivors from Hiroshima and Nagasaki, British doctors, Colorado Plateau miners, and Chinese tin miners. Different sets of identifiable model parameters are used in the literature. The parameter set which could be determined with the lowest uncertainty consists of the net proliferation rate gamma of intermediate cells, the hazard h 55 at an intermediate age, and the hazard H? at an asymptotically large age. Also, the values of these three parameters obtained in the various studies are more consistent than other identifiable combinations of the biological parameters. Based on representative results for these three parameters, implications for the biological parameters in the TSCE model are derived. (author)

Parameter sensitivity and uncertainty analysis for a storm surge and wave model

Directory of Open Access Journals (Sweden)

L. A. Bastidas

2016-09-01

Full Text Available Development and simulation of synthetic hurricane tracks is a common methodology used to estimate hurricane hazards in the absence of empirical coastal surge and wave observations. Such methods typically rely on numerical models to translate stochastically generated hurricane wind and pressure forcing into coastal surge and wave estimates. The model output uncertainty associated with selection of appropriate model parameters must therefore be addressed. The computational overburden of probabilistic surge hazard estimates is exacerbated by the high dimensionality of numerical surge and wave models. We present a model parameter sensitivity analysis of the Delft3D model for the simulation of hazards posed by Hurricane Bob (1991 utilizing three theoretical wind distributions (NWS23, modified Rankine, and Holland. The sensitive model parameters (of 11 total considered include wind drag, the depth-induced breaking γB, and the bottom roughness. Several parameters show no sensitivity (threshold depth, eddy viscosity, wave triad parameters, and depth-induced breaking αB and can therefore be excluded to reduce the computational overburden of probabilistic surge hazard estimates. The sensitive model parameters also demonstrate a large number of interactions between parameters and a nonlinear model response. While model outputs showed sensitivity to several parameters, the ability of these parameters to act as tuning parameters for calibration is somewhat limited as proper model calibration is strongly reliant on accurate wind and pressure forcing data. A comparison of the model performance with forcings from the different wind models is also presented.

Calibration of discrete element model parameters: soybeans

Science.gov (United States)

Ghodki, Bhupendra M.; Patel, Manish; Namdeo, Rohit; Carpenter, Gopal

2018-05-01

Discrete element method (DEM) simulations are broadly used to get an insight of flow characteristics of granular materials in complex particulate systems. DEM input parameters for a model are the critical prerequisite for an efficient simulation. Thus, the present investigation aims to determine DEM input parameters for Hertz-Mindlin model using soybeans as a granular material. To achieve this aim, widely acceptable calibration approach was used having standard box-type apparatus. Further, qualitative and quantitative findings such as particle profile, height of kernels retaining the acrylic wall, and angle of repose of experiments and numerical simulations were compared to get the parameters. The calibrated set of DEM input parameters includes the following (a) material properties: particle geometric mean diameter (6.24 mm); spherical shape; particle density (1220 kg m^{-3} ), and (b) interaction parameters such as particle-particle: coefficient of restitution (0.17); coefficient of static friction (0.26); coefficient of rolling friction (0.08), and particle-wall: coefficient of restitution (0.35); coefficient of static friction (0.30); coefficient of rolling friction (0.08). The results may adequately be used to simulate particle scale mechanics (grain commingling, flow/motion, forces, etc) of soybeans in post-harvest machinery and devices.

The biomechanical effect of transverse connectors use in a pre- and postlaminectomy model of the posterior cervical spine: an in vitro cadaveric study.

Science.gov (United States)

Majid, Kamran; Gudipally, Manasa; Hussain, Mir; Moldavsky, Mark; Khalil, Saif

2011-12-15

An in vitro biomechanical study investigating the effect of transverse connectors on posterior cervical stabilization system in a laminectomy model. To evaluate the optimal design, number, and location of the transverse connectors in stabilizing long segment posterior instrumentation in the cervical spine. In the cervical spine, lateral mass screw (LMS) fixation is used for providing stability after decompression. Transverse connectors have been used to augment segmental posterior instrumentation. However, in the cervical region the optimal design, number, and the location of transverse connectors is not known. Seven fresh human cervicothoracic cadaveric spines (C2-T1) were tested by applying ±1.5 Nm moments in flexion (F), extension (E), lateral bending (LB), and axial rotation (AR). After testing the intact condition, LMS/rods were placed and then were tested with two different transverse connectors (top-loading connector [TL] and the head-to-head [HH] connector) in multiple levels, pre- and postlaminectomy (PL). LMS significantly reduced segmental motion by 77.2% in F, 75.6% in E, 86.6% in LB, and 86.1% in AR prelaminectomy and by 75.4% in F, 76% in E, 80.6% in LB, and 76.4% in AR postlaminectomy compared to intact (P transverse connectors is significant in AR, when using two connectors at the proximal and distal ends, compared to one connector. In a clinical setting, this data may guide surgeons on transverse connector configurations to consider during posterior cervical instrumentation.

Probabilistic inference of ecohydrological parameters using observations from point to satellite scales

Science.gov (United States)

Bassiouni, Maoya; Higgins, Chad W.; Still, Christopher J.; Good, Stephen P.

2018-06-01

Vegetation controls on soil moisture dynamics are challenging to measure and translate into scale- and site-specific ecohydrological parameters for simple soil water balance models. We hypothesize that empirical probability density functions (pdfs) of relative soil moisture or soil saturation encode sufficient information to determine these ecohydrological parameters. Further, these parameters can be estimated through inverse modeling of the analytical equation for soil saturation pdfs, derived from the commonly used stochastic soil water balance framework. We developed a generalizable Bayesian inference framework to estimate ecohydrological parameters consistent with empirical soil saturation pdfs derived from observations at point, footprint, and satellite scales. We applied the inference method to four sites with different land cover and climate assuming (i) an annual rainfall pattern and (ii) a wet season rainfall pattern with a dry season of negligible rainfall. The Nash-Sutcliffe efficiencies of the analytical model's fit to soil observations ranged from 0.89 to 0.99. The coefficient of variation of posterior parameter distributions ranged from interest. In these cases, model inversion converged more slowly but ultimately provided better goodness of fit and lower uncertainty. Results were robust using as few as 100 daily observations randomly sampled from the full records, demonstrating the advantage of analyzing soil saturation pdfs instead of time series to estimate ecohydrological parameters from sparse records. Our work combines modeling and empirical approaches in ecohydrology and provides a simple framework to obtain scale- and site-specific analytical descriptions of soil moisture dynamics consistent with soil moisture observations.

A three-dimensional cohesive sediment transport model with data assimilation: Model development, sensitivity analysis and parameter estimation

Science.gov (United States)

Wang, Daosheng; Cao, Anzhou; Zhang, Jicai; Fan, Daidu; Liu, Yongzhi; Zhang, Yue

2018-06-01

Based on the theory of inverse problems, a three-dimensional sigma-coordinate cohesive sediment transport model with the adjoint data assimilation is developed. In this model, the physical processes of cohesive sediment transport, including deposition, erosion and advection-diffusion, are parameterized by corresponding model parameters. These parameters are usually poorly known and have traditionally been assigned empirically. By assimilating observations into the model, the model parameters can be estimated using the adjoint method; meanwhile, the data misfit between model results and observations can be decreased. The model developed in this work contains numerous parameters; therefore, it is necessary to investigate the parameter sensitivity of the model, which is assessed by calculating a relative sensitivity function and the gradient of the cost function with respect to each parameter. The results of parameter sensitivity analysis indicate that the model is sensitive to the initial conditions, inflow open boundary conditions, suspended sediment settling velocity and resuspension rate, while the model is insensitive to horizontal and vertical diffusivity coefficients. A detailed explanation of the pattern of sensitivity analysis is also given. In ideal twin experiments, constant parameters are estimated by assimilating 'pseudo' observations. The results show that the sensitive parameters are estimated more easily than the insensitive parameters. The conclusions of this work can provide guidance for the practical applications of this model to simulate sediment transport in the study area.

Uncertainty of Modal Parameters Estimated by ARMA Models

DEFF Research Database (Denmark)

Jensen, Jacob Laigaard; Brincker, Rune; Rytter, Anders

1990-01-01

In this paper the uncertainties of identified modal parameters such as eidenfrequencies and damping ratios are assed. From the measured response of dynamic excited structures the modal parameters may be identified and provide important structural knowledge. However the uncertainty of the parameters...... by simulation study of a lightly damped single degree of freedom system. Identification by ARMA models has been choosen as system identification method. It is concluded that both the sampling interval and number of sampled points may play a significant role with respect to the statistical errors. Furthermore......, it is shown that the model errors may also contribute significantly to the uncertainty....

Information sensitivity functions to assess parameter information gain and identifiability of dynamical systems.

Science.gov (United States)

Pant, Sanjay

2018-05-01

A new class of functions, called the 'information sensitivity functions' (ISFs), which quantify the information gain about the parameters through the measurements/observables of a dynamical system are presented. These functions can be easily computed through classical sensitivity functions alone and are based on Bayesian and information-theoretic approaches. While marginal information gain is quantified by decrease in differential entropy, correlations between arbitrary sets of parameters are assessed through mutual information. For individual parameters, these information gains are also presented as marginal posterior variances, and, to assess the effect of correlations, as conditional variances when other parameters are given. The easy to interpret ISFs can be used to (a) identify time intervals or regions in dynamical system behaviour where information about the parameters is concentrated; (b) assess the effect of measurement noise on the information gain for the parameters; (c) assess whether sufficient information in an experimental protocol (input, measurements and their frequency) is available to identify the parameters; (d) assess correlation in the posterior distribution of the parameters to identify the sets of parameters that are likely to be indistinguishable; and (e) assess identifiability problems for particular sets of parameters. © 2018 The Authors.

Consistent Stochastic Modelling of Meteocean Design Parameters

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Sterndorff, M. J.

2000-01-01

Consistent stochastic models of metocean design parameters and their directional dependencies are essential for reliability assessment of offshore structures. In this paper a stochastic model for the annual maximum values of the significant wave height, and the associated wind velocity, current...

Soil-Related Input Parameters for the Biosphere Model

Energy Technology Data Exchange (ETDEWEB)

A. J. Smith

2004-09-09

This report presents one of the analyses that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the details of the conceptual model as well as the mathematical model and the required input parameters. The biosphere model is one of a series of process models supporting the postclosure Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A schematic representation of the documentation flow for the Biosphere input to TSPA is presented in Figure 1-1. This figure shows the evolutionary relationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (TWP) (BSC 2004 [DIRS 169573]). This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this report. This report, ''Soil-Related Input Parameters for the Biosphere Model'', is one of the five analysis reports that develop input parameters for use in the ERMYN model. This report is the source documentation for the six biosphere parameters identified in Table 1-1. The purpose of this analysis was to develop the biosphere model parameters associated with the accumulation and depletion of radionuclides in the soil. These parameters support the calculation of radionuclide concentrations in soil from on-going irrigation or ash deposition and, as a direct consequence, radionuclide concentration in other environmental media that are affected by radionuclide concentrations in soil. The analysis was performed in accordance with the TWP (BSC 2004 [DIRS 169573]) where the governing procedure

Inhalation Exposure Input Parameters for the Biosphere Model

Energy Technology Data Exchange (ETDEWEB)

M. Wasiolek

2006-06-05

This analysis is one of the technical reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), referred to in this report as the biosphere model. ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. ''Inhalation Exposure Input Parameters for the Biosphere Model'' is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the biosphere model is presented in Figure 1-1 (based on BSC 2006 [DIRS 176938]). This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and how this analysis report contributes to biosphere modeling. This analysis report defines and justifies values of atmospheric mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of the biosphere model to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception. This

Inhalation Exposure Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

M. Wasiolek

2006-01-01

This analysis is one of the technical reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), referred to in this report as the biosphere model. ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. ''Inhalation Exposure Input Parameters for the Biosphere Model'' is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the biosphere model is presented in Figure 1-1 (based on BSC 2006 [DIRS 176938]). This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and how this analysis report contributes to biosphere modeling. This analysis report defines and justifies values of atmospheric mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of the biosphere model to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception. This report is concerned primarily with the

Atividade lenta posterior: correlação eletro-clínica Posterior EEG slow activity: electro-clinical correlation

Directory of Open Access Journals (Sweden)

Salustiano Gomes Lins

1971-06-01

Full Text Available Inicialmente é feita breve exposição dos cinco principais tipos de atividade lenta posterior descritas na literatura eletrencefalográfica: variedade lenta do ritmo alfa, ritmo theta posterior, ondas lentas posteriores a 4 hertz, ritmo delta associado ao pequeno mal e ondas Pi. Em seguida o autor expõe seus achados, baseado num material clínico composto por 760 pacientes, colhidos ao acaso, dos dois sexos e com idades variáveis entre 5 e 24 anos. Excetuando a variedade lenta do ritmo alfa, um ou mais dos outros quatro grafo-elementos referidos foram observados em 131 destes pacientes (80 do sexo masculino e 51 do sexo feminino pertencentes aos 3 primeiros grupos etários (5 a 19 anos. Sua predominância no sexo masculino não alcançou nível de significação estatística, mas a maior incidência nos grupos de menor idade foi significativa a 0,01. O ritmo theta posterior associou-se significativamente apenas a distúrbios de conduta com forte agressividade. Dos 131 casos referidos, 10 eram portadores de pequeno mal e destes, 5 apresentavam ritmo delta posterior (3 do sexo masculino e 2 do sexo feminino. Apenas em dois casos foi observado o ritmo lento posterior a 4 hertz, ambos com comemorativos de traumatismo craniano, seguido de distúrbios da conduta e agressividade.The five principal types of posterior slow activity are reviwed: the slow alpha variant rhythm; the posterior theta rhythm; the posterior slow waves at 4 c/s; the delta rhythm associated with petit mal; the so called Pi waves. The results with EEG tracings of 760 patients of both sexes with ages between 5 and 24 years are reviewed. Except for the slow alpha variant, at least one of the four other phenomena as observed in 131 patients (80 males end 51 females. The theta rhythm was observed in 49 cases (29 males and 20 females. This higher frequence among the males is not significant but the higher frequence among the younger and the association with a clinical picture of

Bayesian inference of chemical kinetic models from proposed reactions

KAUST Repository

Galagali, Nikhil

2015-02-01

© 2014 Elsevier Ltd. Bayesian inference provides a natural framework for combining experimental data with prior knowledge to develop chemical kinetic models and quantify the associated uncertainties, not only in parameter values but also in model structure. Most existing applications of Bayesian model selection methods to chemical kinetics have been limited to comparisons among a small set of models, however. The significant computational cost of evaluating posterior model probabilities renders traditional Bayesian methods infeasible when the model space becomes large. We present a new framework for tractable Bayesian model inference and uncertainty quantification using a large number of systematically generated model hypotheses. The approach involves imposing point-mass mixture priors over rate constants and exploring the resulting posterior distribution using an adaptive Markov chain Monte Carlo method. The posterior samples are used to identify plausible models, to quantify rate constant uncertainties, and to extract key diagnostic information about model structure-such as the reactions and operating pathways most strongly supported by the data. We provide numerical demonstrations of the proposed framework by inferring kinetic models for catalytic steam and dry reforming of methane using available experimental data.

Parameter optimization for surface flux transport models

Science.gov (United States)

Whitbread, T.; Yeates, A. R.; Muñoz-Jaramillo, A.; Petrie, G. J. D.

2017-11-01

Accurate prediction of solar activity calls for precise calibration of solar cycle models. Consequently we aim to find optimal parameters for models which describe the physical processes on the solar surface, which in turn act as proxies for what occurs in the interior and provide source terms for coronal models. We use a genetic algorithm to optimize surface flux transport models using National Solar Observatory (NSO) magnetogram data for Solar Cycle 23. This is applied to both a 1D model that inserts new magnetic flux in the form of idealized bipolar magnetic regions, and also to a 2D model that assimilates specific shapes of real active regions. The genetic algorithm searches for parameter sets (meridional flow speed and profile, supergranular diffusivity, initial magnetic field, and radial decay time) that produce the best fit between observed and simulated butterfly diagrams, weighted by a latitude-dependent error structure which reflects uncertainty in observations. Due to the easily adaptable nature of the 2D model, the optimization process is repeated for Cycles 21, 22, and 24 in order to analyse cycle-to-cycle variation of the optimal solution. We find that the ranges and optimal solutions for the various regimes are in reasonable agreement with results from the literature, both theoretical and observational. The optimal meridional flow profiles for each regime are almost entirely within observational bounds determined by magnetic feature tracking, with the 2D model being able to accommodate the mean observed profile more successfully. Differences between models appear to be important in deciding values for the diffusive and decay terms. In like fashion, differences in the behaviours of different solar cycles lead to contrasts in parameters defining the meridional flow and initial field strength.

Global parameter estimation for thermodynamic models of transcriptional regulation.

Science.gov (United States)

Suleimenov, Yerzhan; Ay, Ahmet; Samee, Md Abul Hassan; Dresch, Jacqueline M; Sinha, Saurabh; Arnosti, David N

2013-07-15

Deciphering the mechanisms involved in gene regulation holds the key to understanding the control of central biological processes, including human disease, population variation, and the evolution of morphological innovations. New experimental techniques including whole genome sequencing and transcriptome analysis have enabled comprehensive modeling approaches to study gene regulation. In many cases, it is useful to be able to assign biological significance to the inferred model parameters, but such interpretation should take into account features that affect these parameters, including model construction and sensitivity, the type of fitness calculation, and the effectiveness of parameter estimation. This last point is often neglected, as estimation methods are often selected for historical reasons or for computational ease. Here, we compare the performance of two parameter estimation techniques broadly representative of local and global approaches, namely, a quasi-Newton/Nelder-Mead simplex (QN/NMS) method and a covariance matrix adaptation-evolutionary strategy (CMA-ES) method. The estimation methods were applied to a set of thermodynamic models of gene transcription applied to regulatory elements active in the Drosophila embryo. Measuring overall fit, the global CMA-ES method performed significantly better than the local QN/NMS method on high quality data sets, but this difference was negligible on lower quality data sets with increased noise or on data sets simplified by stringent thresholding. Our results suggest that the choice of parameter estimation technique for evaluation of gene expression models depends both on quality of data, the nature of the models [again, remains to be established] and the aims of the modeling effort. Copyright © 2013 Elsevier Inc. All rights reserved.

A distributed approach for parameters estimation in System Biology models

International Nuclear Information System (INIS)

Mosca, E.; Merelli, I.; Alfieri, R.; Milanesi, L.

2009-01-01

Due to the lack of experimental measurements, biological variability and experimental errors, the value of many parameters of the systems biology mathematical models is yet unknown or uncertain. A possible computational solution is the parameter estimation, that is the identification of the parameter values that determine the best model fitting respect to experimental data. We have developed an environment to distribute each run of the parameter estimation algorithm on a different computational resource. The key feature of the implementation is a relational database that allows the user to swap the candidate solutions among the working nodes during the computations. The comparison of the distributed implementation with the parallel one showed that the presented approach enables a faster and better parameter estimation of systems biology models.

Parameters Estimation of Geographically Weighted Ordinal Logistic Regression (GWOLR) Model

Science.gov (United States)

Zuhdi, Shaifudin; Retno Sari Saputro, Dewi; Widyaningsih, Purnami

2017-06-01

A regression model is the representation of relationship between independent variable and dependent variable. The dependent variable has categories used in the logistic regression model to calculate odds on. The logistic regression model for dependent variable has levels in the logistics regression model is ordinal. GWOLR model is an ordinal logistic regression model influenced the geographical location of the observation site. Parameters estimation in the model needed to determine the value of a population based on sample. The purpose of this research is to parameters estimation of GWOLR model using R software. Parameter estimation uses the data amount of dengue fever patients in Semarang City. Observation units used are 144 villages in Semarang City. The results of research get GWOLR model locally for each village and to know probability of number dengue fever patient categories.

Reflector modelization for neutronic diffusion and parameters identification

International Nuclear Information System (INIS)

Argaud, J.P.

1993-04-01

Physical parameters of neutronic diffusion equations can be adjusted to decrease calculations-measurements errors. The reflector being always difficult to modelize, we choose to elaborate a new reflector model and to use the parameters of this model as adjustment coefficients in the identification procedure. Using theoretical results, and also the physical behaviour of neutronic flux solutions, the reflector model consists then in its replacement by boundary conditions for the diffusion equations on the core only. This theoretical result of non-local operator relations leads then to some discrete approximations by taking into account the multiscaled behaviour, on the core-reflector interface, of neutronic diffusion solutions. The resulting model of this approach is then compared with previous reflector modelizations, and first results indicate that this new model gives the same representation of reflector for the core than previous. (author). 12 refs

Transient dynamic and modeling parameter sensitivity analysis of 1D solid oxide fuel cell model

International Nuclear Information System (INIS)

Huangfu, Yigeng; Gao, Fei; Abbas-Turki, Abdeljalil; Bouquain, David; Miraoui, Abdellatif

2013-01-01

Highlights: • A multiphysics, 1D, dynamic SOFC model is developed. • The presented model is validated experimentally in eight different operating conditions. • Electrochemical and thermal dynamic transient time expressions are given in explicit forms. • Parameter sensitivity is discussed for different semi-empirical parameters in the model. - Abstract: In this paper, a multiphysics solid oxide fuel cell (SOFC) dynamic model is developed by using a one dimensional (1D) modeling approach. The dynamic effects of double layer capacitance on the electrochemical domain and the dynamic effect of thermal capacity on thermal domain are thoroughly considered. The 1D approach allows the model to predict the non-uniform distributions of current density, gas pressure and temperature in SOFC during its operation. The developed model has been experimentally validated, under different conditions of temperature and gas pressure. Based on the proposed model, the explicit time constant expressions for different dynamic phenomena in SOFC have been given and discussed in detail. A parameters sensitivity study has also been performed and discussed by using statistical Multi Parameter Sensitivity Analysis (MPSA) method, in order to investigate the impact of parameters on the modeling accuracy

Selective posterior lumbosacral rhizotomy for the management ...

African Journals Online (AJOL)

tion in 95% of cases. The majority showed ... selective posterior rhizotomy technique whereby the cauda equina ... assessed pre- and postoperatively by means of clinical examination ... were attending cerebral palsy schools and receiving spe- cialised ... root sections on cats demonstrated clearly that posterior root section ...

A Matrix-Free Posterior Ensemble Kalman Filter Implementation Based on a Modified Cholesky Decomposition

Directory of Open Access Journals (Sweden)

Elias D. Nino-Ruiz

2017-07-01

Full Text Available In this paper, a matrix-free posterior ensemble Kalman filter implementation based on a modified Cholesky decomposition is proposed. The method works as follows: the precision matrix of the background error distribution is estimated based on a modified Cholesky decomposition. The resulting estimator can be expressed in terms of Cholesky factors which can be updated based on a series of rank-one matrices in order to approximate the precision matrix of the analysis distribution. By using this matrix, the posterior ensemble can be built by either sampling from the posterior distribution or using synthetic observations. Furthermore, the computational effort of the proposed method is linear with regard to the model dimension and the number of observed components from the model domain. Experimental tests are performed making use of the Lorenz-96 model. The results reveal that, the accuracy of the proposed implementation in terms of root-mean-square-error is similar, and in some cases better, to that of a well-known ensemble Kalman filter (EnKF implementation: the local ensemble transform Kalman filter. In addition, the results are comparable to those obtained by the EnKF with large ensemble sizes.

Coupled 1D-2D hydrodynamic inundation model for sewer overflow: Influence of modeling parameters

Directory of Open Access Journals (Sweden)

Adeniyi Ganiyu Adeogun

2015-10-01

Full Text Available This paper presents outcome of our investigation on the influence of modeling parameters on 1D-2D hydrodynamic inundation model for sewer overflow, developed through coupling of an existing 1D sewer network model (SWMM and 2D inundation model (BREZO. The 1D-2D hydrodynamic model was developed for the purpose of examining flood incidence due to surcharged water on overland surface. The investigation was carried out by performing sensitivity analysis on the developed model. For the sensitivity analysis, modeling parameters, such as mesh resolution Digital Elevation Model (DEM resolution and roughness were considered. The outcome of the study shows the model is sensitive to changes in these parameters. The performance of the model is significantly influenced, by the Manning's friction value, the DEM resolution and the area of the triangular mesh. Also, changes in the aforementioned modeling parameters influence the Flood characteristics, such as the inundation extent, the flow depth and the velocity across the model domain. Keywords: Inundation, DEM, Sensitivity analysis, Model coupling, Flooding

On the validity of evolutionary models with site-specific parameters.

Directory of Open Access Journals (Sweden)

Konrad Scheffler

Full Text Available Evolutionary models that make use of site-specific parameters have recently been criticized on the grounds that parameter estimates obtained under such models can be unreliable and lack theoretical guarantees of convergence. We present a simulation study providing empirical evidence that a simple version of the models in question does exhibit sensible convergence behavior and that additional taxa, despite not being independent of each other, lead to improved parameter estimates. Although it would be desirable to have theoretical guarantees of this, we argue that such guarantees would not be sufficient to justify the use of these models in practice. Instead, we emphasize the importance of taking the variance of parameter estimates into account rather than blindly trusting point estimates - this is standardly done by using the models to construct statistical hypothesis tests, which are then validated empirically via simulation studies.

Climate change decision-making: Model & parameter uncertainties explored

Energy Technology Data Exchange (ETDEWEB)

Dowlatabadi, H.; Kandlikar, M.; Linville, C.

1995-12-31

A critical aspect of climate change decision-making is uncertainties in current understanding of the socioeconomic, climatic and biogeochemical processes involved. Decision-making processes are much better informed if these uncertainties are characterized and their implications understood. Quantitative analysis of these uncertainties serve to inform decision makers about the likely outcome of policy initiatives, and help set priorities for research so that outcome ambiguities faced by the decision-makers are reduced. A family of integrated assessment models of climate change have been developed at Carnegie Mellon. These models are distinguished from other integrated assessment efforts in that they were designed from the outset to characterize and propagate parameter, model, value, and decision-rule uncertainties. The most recent of these models is ICAM 2.1. This model includes representation of the processes of demographics, economic activity, emissions, atmospheric chemistry, climate and sea level change and impacts from these changes and policies for emissions mitigation, and adaptation to change. The model has over 800 objects of which about one half are used to represent uncertainty. In this paper we show, that when considering parameter uncertainties, the relative contribution of climatic uncertainties are most important, followed by uncertainties in damage calculations, economic uncertainties and direct aerosol forcing uncertainties. When considering model structure uncertainties we find that the choice of policy is often dominated by model structure choice, rather than parameter uncertainties.

Ipsilateral Traumatic Posterior Hip Dislocation, Posterior Wall and Transverse Acetabular Fracture with Trochanteric Fracture in an adult: Report of First Case

Directory of Open Access Journals (Sweden)

Skand Sinha

2013-10-01

Full Text Available Introduction: Posterior dislocation of the hip joint with associated acetabular and intertrochanteric fracture is a complex injury. Early recognition, prompt and stable reduction is needed of successful outcome. Case Report: 45 year old male patient presented with posterior dislocation of the hip with transverse fracture with posterior wall fracture of acetabulam and intertrochanteric fracture on the ipsilateral side. The complex fracture geometry was confirmed by CT scan. The patient was successfully managed by open reduction and internal fixation of intertrochanteric fracture was achieved with dynamic hip screw (DHS plate fixation followed by fixation of acetabular fracture with reconstruction plate. Conclusion: Hip dislocation combined with acetabular fracture is an uncommon injury; this article presents a unique case of posterior wall and transverse fractures of ipsilateral acetabulum with intertrochanteric fracture in a patient who sustained traumatic posterior hip dislocation. Early surgical intervention is important for satisfactory outcomes of such complex fracture-dislocation injuries. Keywords: Hip dislocation; acetabular fractures; intertrochanteric fracture; operative treatment.

Error propagation of partial least squares for parameters optimization in NIR modeling

Science.gov (United States)

Du, Chenzhao; Dai, Shengyun; Qiao, Yanjiang; Wu, Zhisheng

2018-03-01

A novel methodology is proposed to determine the error propagation of partial least-square (PLS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type І and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models.

Error propagation of partial least squares for parameters optimization in NIR modeling.

Science.gov (United States)

Du, Chenzhao; Dai, Shengyun; Qiao, Yanjiang; Wu, Zhisheng

2018-03-05

A novel methodology is proposed to determine the error propagation of partial least-square (PLS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type І and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models. Copyright © 2017. Published by Elsevier B.V.

Inhalation Exposure Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

M. A. Wasiolek

2003-01-01

This analysis is one of the nine reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2003a) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents a set of input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for a Yucca Mountain repository. This report, ''Inhalation Exposure Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (BSC 2003b). It should be noted that some documents identified in Figure 1-1 may be under development at the time this report is issued and therefore not available at that time. This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this analysis report. This analysis report defines and justifies values of mass loading, which is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Measurements of mass loading are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air surrounding crops and concentrations in air inhaled by a receptor. Concentrations in air to which the

Modificaciones de la curvatura posterior corneal después de la cirugía refractiva láser Modifications in the corneal posterior curve after laser refractive surgery

Directory of Open Access Journals (Sweden)

Lorelei Ortega Díaz

2011-06-01

in an universe of 257 patients (504 eyes underwent to laser refractive surgery. Sample included 31 patients (59 eyes. Variables analyzed were: age, sex, spherical equivalent, preoperative pachymetry, ablation amount, residual stroma and difference of corneal posterior elevation, this latter achieved from the difference map of Galilei topography, with preoperative measurement at month and at three months after surgery. By multiple regression analysis the changes of pachymetry, the ablation amount and the residual stroma were assessed. RESULTS: The spherical equivalent, the pachymetry, the ablation amount and the residual stroma were within the established safety parameters. The mean difference of posterior corneal elevation was of 15,62 ?m at three months, with a significant decrease in time (p= 0,000. There was association with preoperative pachymetry and the residual stroma and also an inverse correlation between this latter and the posterior corneal elevation at three months. CONCLUSIONS: The laser refractive surgery produces an early increase in the posterior corneal elevation with a progressive decrease at third month. The factors that more influenced in such changes were the residual stroma and the preoperative pachymetry.

Parameter Optimisation for the Behaviour of Elastic Models over Time

DEFF Research Database (Denmark)

Mosegaard, Jesper

2004-01-01

Optimisation of parameters for elastic models is essential for comparison or finding equivalent behaviour of elastic models when parameters cannot simply be transferred or converted. This is the case with a large range of commonly used elastic models. In this paper we present a general method tha...

ASTM F1717 standard for the preclinical evaluation of posterior spinal fixators: can we improve it?

Science.gov (United States)

La Barbera, Luigi; Galbusera, Fabio; Villa, Tomaso; Costa, Francesco; Wilke, Hans-Joachim

2014-10-01

Preclinical evaluation of spinal implants is a necessary step to ensure their reliability and safety before implantation. The American Society for Testing and Materials reapproved F1717 standard for the assessment of mechanical properties of posterior spinal fixators, which simulates a vertebrectomy model and recommends mimicking vertebral bodies using polyethylene blocks. This set-up should represent the clinical use, but available data in the literature are few. Anatomical parameters depending on the spinal level were compared to published data or measurements on biplanar stereoradiography on 13 patients. Other mechanical variables, describing implant design were considered, and all parameters were investigated using a numerical parametric finite element model. Stress values were calculated by considering either the combination of the average values for each parameter or their worst-case combination depending on the spinal level. The standard set-up represents quite well the anatomy of an instrumented average thoracolumbar segment. The stress on the pedicular screw is significantly influenced by the lever arm of the applied load, the unsupported screw length, the position of the centre of rotation of the functional spine unit and the pedicular inclination with respect to the sagittal plane. The worst-case combination of parameters demonstrates that devices implanted below T5 could potentially undergo higher stresses than those described in the standard suggestions (maximum increase of 22.2% at L1). We propose to revise F1717 in order to describe the anatomical worst case condition we found at L1 level: this will guarantee higher safety of the implant for a wider population of patients. © IMechE 2014.

SENSITIVITY OF BODY SWAY PARAMETERS DURING QUIET STANDING TO MANIPULATION OF SUPPORT SURFACE SIZE

Directory of Open Access Journals (Sweden)

Sarabon Nejc

2010-09-01

Full Text Available The centre of pressure (COP movement during stance maintenance on a stable surface is commonly used to describe and evaluate static balance. The aim of our study was to test sensitivity of individual COP parameters to different stance positions which were used to address size specific changes in the support surface. Twenty-nine subjects participated in the study. They carried out three 60-second repetitions of each of the five balance tasks (parallel stance, semi-tandem stance, tandem stance, contra-tandem stance, single leg stance. Using the force plate, the monitored parameters included the total COP distance, the distance covered in antero-posterior and medio-lateral directions, the maximum oscillation amplitude in antero-posterior and medio-lateral directions, the total frequency of oscillation, as well as the frequency of oscillation in antero-posterior and medio-lateral directions. The parameters which describe the total COP distance were the most sensitive to changes in the balance task, whereas the frequency of oscillation proved to be sensitive to a slightly lesser extent. Reductions in the support surface size in each of the directions resulted in proportional changes of antero-posterior and medio- lateral directions. The frequency of oscillation did not increase evenly with the increase in the level of difficulty of the balance task, but reached a certain value, above which it did not increase. Our study revealed the monitored parameters of the COP to be sensitive to the support surface size manipulations. The results of the study provide an important source for clinical and research use of the body sway measurements.

Recommended direct simulation Monte Carlo collision model parameters for modeling ionized air transport processes

Energy Technology Data Exchange (ETDEWEB)

Swaminathan-Gopalan, Krishnan; Stephani, Kelly A., E-mail: ksteph@illinois.edu [Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (United States)

2016-02-15

A systematic approach for calibrating the direct simulation Monte Carlo (DSMC) collision model parameters to achieve consistency in the transport processes is presented. The DSMC collision cross section model parameters are calibrated for high temperature atmospheric conditions by matching the collision integrals from DSMC against ab initio based collision integrals that are currently employed in the Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA) and Data Parallel Line Relaxation (DPLR) high temperature computational fluid dynamics solvers. The DSMC parameter values are computed for the widely used Variable Hard Sphere (VHS) and the Variable Soft Sphere (VSS) models using the collision-specific pairing approach. The recommended best-fit VHS/VSS parameter values are provided over a temperature range of 1000-20 000 K for a thirteen-species ionized air mixture. Use of the VSS model is necessary to achieve consistency in transport processes of ionized gases. The agreement of the VSS model transport properties with the transport properties as determined by the ab initio collision integral fits was found to be within 6% in the entire temperature range, regardless of the composition of the mixture. The recommended model parameter values can be readily applied to any gas mixture involving binary collisional interactions between the chemical species presented for the specified temperature range.

CT findings of traumatic posterior hip dislocation after reduction

International Nuclear Information System (INIS)

Moon, Sung Kyoung; Park, Ji Seon; Ryu, Kyung Nam; Jin, Wook; Jin Wook

2008-01-01

To evaluate the CT images of reduced hips after posterior hip dislocation and to propose specific diagnostic criteria based on the CT results. We retrospectively reviewed the CT findings on 18 reduced hips from 17 patients with radiographs and clinical histories of traumatic posterior hip dislocations by evaluating 18 corresponding CT scans for joint space asymmetry, intra-articular abnormalities (intra-articular fat obliteration, loose bodies, and joint effusion), changes in posterior soft tissue (capsule, muscles, and adjacent fat), the presence, and location of fractures (acetabulum and femoral head). All 18 hips (100%) showed posterior soft tissue changes. In total, 17 hips (94.4%) had intra-articular abnormalities and 15 hips (83.3%) had joint space asymmetries. In addition, 17 hips (94.4%) had fractures involving the acetabula (15 cases, 88.2%) the femoral head (13 cases, 76.5%), or on both sides (11 cases, 64.7%). The most frequent fracture location was in he posterior wall (13/15, 86.7%) of the acetabulum and in the anterior aspect (10/13, 76.9%) of the femoral head. Patients with a prior history of posterior hip dislocation showed specific CT findings after reduction, suggesting the possibility of previous posterior hip dislocations in patients

Posterior Reversible Encephalopathy (PRES)

International Nuclear Information System (INIS)

Moron E, Fanny E; Diaz Marchan, Pedro

2005-01-01

The Posterior Reversible Encephalopathy Syndrome (PRES) is a clinical Syndrome composed of cephalea, alteration in vision and convulsions, usually observed in patients with sudden elevation of arterial pressure. The imagenologic evidence shows reversible vasogenic brain edema without stroke. Its location is predominantly posterior; it affects the cortex and the subcortical white matter of the occipital, parietal and temporal lobes. The treatment with antihypertensive drugs and the removing of immunosupressor medication are generally associated with complete neurological recovery; this is reflected also in the images which return to their basal condition. The untreated hypertension, on the other side, can result in a progressive defect of the autoregulation system of the central nervous system with cerebral hemorrhage, irreversible brain stroke, coma and death

Post-partum posterior reversible encephalopathy syndrome

OpenAIRE

B. V. Triveni; Salman Mohammed Sheikh; Deepak Shedde

2014-01-01

Posterior Reversible Encephalopathy Syndrome (PRES) is a clinicopathological syndrome associated with various clinical conditions presenting with headache, encephalopathy, seizure and cortical visual disturbances. Radiological findings in PRES are thought to be due to vasogenic edema predominantly in posterior cerebral hemispheres and are reversible with appropriate management. We present a case of post partum PRES,A 29 year old primigravida of 33 weeks 3 days period of gestation who prese...

Posterior longitudinal ligament status in cervical spine bilateral facet dislocations

International Nuclear Information System (INIS)

Carrino, John A.; Manton, Geoffrey L.; Morrison, William B.; Flanders, Adam E.; Vaccaro, Alex R.; Schweitzer, Mark E.

2006-01-01

It is generally accepted that cervical spine bilateral facet dislocation results in complete disruption of the posterior longitudinal ligament. The goal of this study was to evaluate the integrity of numerous spine-stabilizing structures by MRI, and to determine if any associations between injury patterns exist with respect to the posterior longitudinal ligament status. Retrospective case series. A retrospective review was performed of 30 cervical spine injury subjects with bilateral facet dislocation. Assessment of 1.5T MRI images was carried out for: intervertebral disc disruption, facet fracture, and ligamentous disruption. Statistical analyses were performed to evaluate for associations between various injury patterns and posterior longitudinal ligament status. The frequency of MRI abnormalities was: anterior longitudinal ligament disruption (26.7%), disc herniation or disruption (90%), posterior longitudinal ligament disruption (40%), facet fracture (63.3%) and disruption of the posterior column ligament complex (97%). There were no significant associations between injury to the posterior longitudinal ligament and other structures. Compared to surgical reports, MRI was accurate for determining the status for 24 of 26 ligaments (three of three anterior longitudinal ligament, seven of nine posterior longitudinal ligament, and 14 of 14 posterior column ligament complex) but generated false negatives in two instances (in both MRI showed an intact posterior longitudinal ligament that was torn at surgery). (orig.)

[Finite element analysis of stress changes of posterior spinal pedicle screw infixation].

Science.gov (United States)

Yan, Jia-Zhi; Wu, Zhi-Hong; Xu, Ri-Xin; Wang, Xue-Song; Xing, Ze-Jun; Zhao, Yu; Zhang, Jian-Guo; Shen, Jian-Xiong; Wang, Yi-Peng; Qiu, Gui-Xing

2009-01-06

To evaluate the mechanical response of L3-L4 segment after posterior interfixation with a transpedicle screw system. Spiral CT machine was used to conduct continuous parallel scan on the L3-L4 section of a 40-year-old healthy male Chinese. The image data thus obtained were introduced into MIMICS software to reconstruct the 2-D data into volume data and obtain 3-D models of every element.. Pro/3-D model construction software system was used to simulate the 3-D entity of L3-L4 fixed by screw robs through spinal pedicle via posterior approach that was introduced into the finite element software ABAQUS to construct a 3-D finite element model. The stress changes on the vertebrae and screw under the axial pressure of 0.5 mPa was analyzed. Under the evenly distributed pressure the displacement of the L4 model was 0.00125815 mm, with an error of only 0.8167% from the datum displacement. The convergence of the model was good. The stress of the fixed vertebral body, intervertebral disc, and internal fixators changed significantly. The stress concentration zone of the intervertebral disc turned from the posterolateral side to anterolateral side. The stress produced by the fixed vertebral bodies decreased significantly. Obvious stress concentration existed in the upper and lower sides of the base of screw and the fixed screw at the upper vertebral body bore greater stress than the lower vertebral body. Integration of computer aided device and finite element analysis can successfully stimulate the internal fixation of L3-IA visa posterior approach and observe the mechanic changes in the vertebral column more directly.

Finite element analysis of the three different posterior malleolus fixation strategies in relation to different fracture sizes.

Science.gov (United States)

Anwar, Adeel; Lv, Decheng; Zhao, Zhi; Zhang, Zhen; Lu, Ming; Nazir, Muhammad Umar; Qasim, Wasim

2017-04-01

Appropriate fixation method for the posterior malleolar fractures (PMF) according to the fracture size is still not clear. Aim of this study was to evaluate the outcomes of the different fixation methods used for fixation of PMF by finite element analysis (FEA) and to compare the effect of fixation constructs on the size of the fracture computationally. Three dimensional model of the tibia was reconstructed from computed tomography (CT) images. PMF of 30%, 40% and 50% fragment sizes were simulated through computational processing. Two antero-posterior (AP) lag screws, two postero-anterior (PA) lag screws and posterior buttress plate were analysed for three different fracture volumes. The simulated loads of 350N and 700N were applied to the proximal tibial end. Models were fixed distally in all degrees of freedom. In single limb standing condition, the posterior plate group produced the lowest relative displacement (RD) among all the groups (0.01, 0.03 and 0.06mm). Further nodal analysis of the highest RD fracture group showed a higher mean displacement of 4.77mm and 4.23mm in AP and PA lag screws model (p=0.000). The amounts of stress subjected to these implants, 134.36MPa and 140.75MPa were also significantly lower (p=0.000). There was a negative correlation (p=0.021) between implant stress and the displacement which signifies a less stable fixation using AP and PA lag screws. Progressively increasing fracture size demands more stable fixation construct because RD increases significantly. Posterior buttress plate produces superior stability and lowest RD in PMF models irrespective of the fragment size. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modelling tourists arrival using time varying parameter

Science.gov (United States)

Suciptawati, P.; Sukarsa, K. G.; Kencana, Eka N.

2017-06-01

The importance of tourism and its related sectors to support economic development and poverty reduction in many countries increase researchers’ attentions to study and model tourists’ arrival. This work is aimed to demonstrate time varying parameter (TVP) technique to model the arrival of Korean’s tourists to Bali. The number of Korean tourists whom visiting Bali for period January 2010 to December 2015 were used to model the number of Korean’s tourists to Bali (KOR) as dependent variable. The predictors are the exchange rate of Won to IDR (WON), the inflation rate in Korea (INFKR), and the inflation rate in Indonesia (INFID). Observing tourists visit to Bali tend to fluctuate by their nationality, then the model was built by applying TVP and its parameters were approximated using Kalman Filter algorithm. The results showed all of predictor variables (WON, INFKR, INFID) significantly affect KOR. For in-sample and out-of-sample forecast with ARIMA’s forecasted values for the predictors, TVP model gave mean absolute percentage error (MAPE) as much as 11.24 percent and 12.86 percent, respectively.

SPOTting model parameters using a ready-made Python package

Science.gov (United States)

Houska, Tobias; Kraft, Philipp; Breuer, Lutz

2015-04-01

The selection and parameterization of reliable process descriptions in ecological modelling is driven by several uncertainties. The procedure is highly dependent on various criteria, like the used algorithm, the likelihood function selected and the definition of the prior parameter distributions. A wide variety of tools have been developed in the past decades to optimize parameters. Some of the tools are closed source. Due to this, the choice for a specific parameter estimation method is sometimes more dependent on its availability than the performance. A toolbox with a large set of methods can support users in deciding about the most suitable method. Further, it enables to test and compare different methods. We developed the SPOT (Statistical Parameter Optimization Tool), an open source python package containing a comprehensive set of modules, to analyze and optimize parameters of (environmental) models. SPOT comes along with a selected set of algorithms for parameter optimization and uncertainty analyses (Monte Carlo, MC; Latin Hypercube Sampling, LHS; Maximum Likelihood, MLE; Markov Chain Monte Carlo, MCMC; Scuffled Complex Evolution, SCE-UA; Differential Evolution Markov Chain, DE-MCZ), together with several likelihood functions (Bias, (log-) Nash-Sutcliff model efficiency, Correlation Coefficient, Coefficient of Determination, Covariance, (Decomposed-, Relative-, Root-) Mean Squared Error, Mean Absolute Error, Agreement Index) and prior distributions (Binomial, Chi-Square, Dirichlet, Exponential, Laplace, (log-, multivariate-) Normal, Pareto, Poisson, Cauchy, Uniform, Weibull) to sample from. The model-independent structure makes it suitable to analyze a wide range of applications. We apply all algorithms of the SPOT package in three different case studies. Firstly, we investigate the response of the Rosenbrock function, where the MLE algorithm shows its strengths. Secondly, we study the Griewank function, which has a challenging response surface for

Model parameters estimation and sensitivity by genetic algorithms

International Nuclear Information System (INIS)

Marseguerra, Marzio; Zio, Enrico; Podofillini, Luca

2003-01-01

In this paper we illustrate the possibility of extracting qualitative information on the importance of the parameters of a model in the course of a Genetic Algorithms (GAs) optimization procedure for the estimation of such parameters. The Genetic Algorithms' search of the optimal solution is performed according to procedures that resemble those of natural selection and genetics: an initial population of alternative solutions evolves within the search space through the four fundamental operations of parent selection, crossover, replacement, and mutation. During the search, the algorithm examines a large amount of solution points which possibly carries relevant information on the underlying model characteristics. A possible utilization of this information amounts to create and update an archive with the set of best solutions found at each generation and then to analyze the evolution of the statistics of the archive along the successive generations. From this analysis one can retrieve information regarding the speed of convergence and stabilization of the different control (decision) variables of the optimization problem. In this work we analyze the evolution strategy followed by a GA in its search for the optimal solution with the aim of extracting information on the importance of the control (decision) variables of the optimization with respect to the sensitivity of the objective function. The study refers to a GA search for optimal estimates of the effective parameters in a lumped nuclear reactor model of literature. The supporting observation is that, as most optimization procedures do, the GA search evolves towards convergence in such a way to stabilize first the most important parameters of the model and later those which influence little the model outputs. In this sense, besides estimating efficiently the parameters values, the optimization approach also allows us to provide a qualitative ranking of their importance in contributing to the model output. The

WATGIS: A GIS-Based Lumped Parameter Water Quality Model

Science.gov (United States)

Glenn P. Fernandez; George M. Chescheir; R. Wayne Skaggs; Devendra M. Amatya

2002-01-01

A Geographic Information System (GIS)­based, lumped parameter water quality model was developed to estimate the spatial and temporal nitrogen­loading patterns for lower coastal plain watersheds in eastern North Carolina. The model uses a spatially distributed delivery ratio (DR) parameter to account for nitrogen retention or loss along a drainage network. Delivery...

An unusual and spectacular case of spindle cell lipoma of the posterior neck invading the spinal cervical canal and posterior cranial fossa.

Science.gov (United States)

Petit, Damien; Menei, Philippe; Fournier, Henri-Dominique

2011-11-01

The authors describe the first case of spindle cell lipoma of the posterior neck invading the upper cervical spinal canal and the posterior cranial fossa. Spindle cell lipoma is an extremely rare variant of benign lipoma. It usually occurs as a solitary subcutaneous well-circumscribed lesion in the posterior neck or shoulders of adult men. Local aggressiveness is unusual. This 61-year-old man presented with an increased left cerebellar syndrome and headaches. He also had a posterior neck tumefaction, which had been known about for a long time. Computed tomography and MR imaging studies revealed a voluminous mass extending to the upper cervical canal and posterior cranial fossa and eroding the neighboring bones. The lesion was well delimited, and contrast enhancement was intense and heterogeneous. The tumor, which had initially developed under the muscles of the posterior neck, was totally resected. Histological assessment revealed numerous fat cells with spindle cells secreting collagen. The large size of the tumor and the submuscular location, bone erosion, and compression of the CNS were unusual in this rare subtype of benign adipose tumor. Its presentation could simulate a sarcoma.

NONLINEAR PLANT PIECEWISE-CONTINUOUS MODEL MATRIX PARAMETERS ESTIMATION

Directory of Open Access Journals (Sweden)

Roman L. Leibov

2017-09-01

Full Text Available This paper presents a nonlinear plant piecewise-continuous model matrix parameters estimation technique using nonlinear model time responses and random search method. One of piecewise-continuous model application areas is defined. The results of proposed approach application for aircraft turbofan engine piecewisecontinuous model formation are presented

Validation of Bayesian analysis of compartmental kinetic models in medical imaging.

Science.gov (United States)

Sitek, Arkadiusz; Li, Quanzheng; El Fakhri, Georges; Alpert, Nathaniel M

2016-10-01

Kinetic compartmental analysis is frequently used to compute physiologically relevant quantitative values from time series of images. In this paper, a new approach based on Bayesian analysis to obtain information about these parameters is presented and validated. The closed-form of the posterior distribution of kinetic parameters is derived with a hierarchical prior to model the standard deviation of normally distributed noise. Markov chain Monte Carlo methods are used for numerical estimation of the posterior distribution. Computer simulations of the kinetics of F18-fluorodeoxyglucose (FDG) are used to demonstrate drawing statistical inferences about kinetic parameters and to validate the theory and implementation. Additionally, point estimates of kinetic parameters and covariance of those estimates are determined using the classical non-linear least squares approach. Posteriors obtained using methods proposed in this work are accurate as no significant deviation from the expected shape of the posterior was found (one-sided P>0.08). It is demonstrated that the results obtained by the standard non-linear least-square methods fail to provide accurate estimation of uncertainty for the same data set (P<0.0001). The results of this work validate new methods for a computer simulations of FDG kinetics. Results show that in situations where the classical approach fails in accurate estimation of uncertainty, Bayesian estimation provides an accurate information about the uncertainties in the parameters. Although a particular example of FDG kinetics was used in the paper, the methods can be extended for different pharmaceuticals and imaging modalities. Copyright © 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Kinematic analysis of a posterior-stabilized knee prosthesis.

Science.gov (United States)

Zhao, Zhi-Xin; Wen, Liang; Qu, Tie-Bing; Hou, Li-Li; Xiang, Dong; Bin, Jia

2015-01-20

The goal of total knee arthroplasty (TKA) is to restore knee kinematics. Knee prosthesis design plays a very important role in successful restoration. Here, kinematics models of normal and prosthetic knees were created and validated using previously published data. Computed tomography and magnetic resonance imaging scans of a healthy, anticorrosive female cadaver were used to establish a model of the entire lower limbs, including the femur, tibia, patella, fibula, distal femur cartilage, and medial and lateral menisci, as well as the anterior cruciate, posterior cruciate, medial collateral, and lateral collateral ligaments. The data from the three-dimensional models of the normal knee joint and a posterior-stabilized (PS) knee prosthesis were imported into finite element analysis software to create the final kinematic model of the TKA prosthesis, which was then validated by comparison with a previous study. The displacement of the medial/lateral femur and the internal rotation angle of the tibia were analyzed during 0-135° flexion. Both the output data trends and the measured values derived from the normal knee's kinematics model were very close to the results reported in a previous in vivo study, suggesting that this model can be used for further analyses. The PS knee prosthesis underwent an abnormal forward displacement compared with the normal knee and has insufficient, or insufficiently aggressive, "rollback" compared with the lateral femur of the normal knee. In addition, a certain degree of reverse rotation occurs during flexion of the PS knee prosthesis. There were still several differences between the kinematics of the PS knee prosthesis and a normal knee, suggesting room for improving the design of the PS knee prosthesis. The abnormal kinematics during early flexion shows that the design of the articular surface played a vital role in improving the kinematics of the PS knee prosthesis.

Kinematic Analysis of a Posterior-stabilized Knee Prosthesis

Directory of Open Access Journals (Sweden)

Zhi-Xin Zhao

2015-01-01

Full Text Available Background: The goal of total knee arthroplasty (TKA is to restore knee kinematics. Knee prosthesis design plays a very important role in successful restoration. Here, kinematics models of normal and prosthetic knees were created and validated using previously published data. Methods: Computed tomography and magnetic resonance imaging scans of a healthy, anticorrosive female cadaver were used to establish a model of the entire lower limbs, including the femur, tibia, patella, fibula, distal femur cartilage, and medial and lateral menisci, as well as the anterior cruciate, posterior cruciate, medial collateral, and lateral collateral ligaments. The data from the three-dimensional models of the normal knee joint and a posterior-stabilized (PS knee prosthesis were imported into finite element analysis software to create the final kinematic model of the TKA prosthesis, which was then validated by comparison with a previous study. The displacement of the medial/lateral femur and the internal rotation angle of the tibia were analyzed during 0-135° flexion. Results: Both the output data trends and the measured values derived from the normal knee′s kinematics model were very close to the results reported in a previous in vivo study, suggesting that this model can be used for further analyses. The PS knee prosthesis underwent an abnormal forward displacement compared with the normal knee and has insufficient, or insufficiently aggressive, "rollback" compared with the lateral femur of the normal knee. In addition, a certain degree of reverse rotation occurs during flexion of the PS knee prosthesis. Conclusions: There were still several differences between the kinematics of the PS knee prosthesis and a normal knee, suggesting room for improving the design of the PS knee prosthesis. The abnormal kinematics during early flexion shows that the design of the articular surface played a vital role in improving the kinematics of the PS knee prosthesis.

Kinematic Analysis of a Posterior-stabilized Knee Prosthesis

Science.gov (United States)

Zhao, Zhi-Xin; Wen, Liang; Qu, Tie-Bing; Hou, Li-Li; Xiang, Dong; Bin, Jia

2015-01-01

Background: The goal of total knee arthroplasty (TKA) is to restore knee kinematics. Knee prosthesis design plays a very important role in successful restoration. Here, kinematics models of normal and prosthetic knees were created and validated using previously published data. Methods: Computed tomography and magnetic resonance imaging scans of a healthy, anticorrosive female cadaver were used to establish a model of the entire lower limbs, including the femur, tibia, patella, fibula, distal femur cartilage, and medial and lateral menisci, as well as the anterior cruciate, posterior cruciate, medial collateral, and lateral collateral ligaments. The data from the three-dimensional models of the normal knee joint and a posterior-stabilized (PS) knee prosthesis were imported into finite element analysis software to create the final kinematic model of the TKA prosthesis, which was then validated by comparison with a previous study. The displacement of the medial/lateral femur and the internal rotation angle of the tibia were analyzed during 0–135° flexion. Results: Both the output data trends and the measured values derived from the normal knee's kinematics model were very close to the results reported in a previous in vivo study, suggesting that this model can be used for further analyses. The PS knee prosthesis underwent an abnormal forward displacement compared with the normal knee and has insufficient, or insufficiently aggressive, “rollback” compared with the lateral femur of the normal knee. In addition, a certain degree of reverse rotation occurs during flexion of the PS knee prosthesis. Conclusions: There were still several differences between the kinematics of the PS knee prosthesis and a normal knee, suggesting room for improving the design of the PS knee prosthesis. The abnormal kinematics during early flexion shows that the design of the articular surface played a vital role in improving the kinematics of the PS knee prosthesis. PMID:25591565

Analytic posteriors for Pearson's correlation coefficient.

Science.gov (United States)

Ly, Alexander; Marsman, Maarten; Wagenmakers, Eric-Jan

2018-02-01

Pearson's correlation is one of the most common measures of linear dependence. Recently, Bernardo (11th International Workshop on Objective Bayes Methodology, 2015) introduced a flexible class of priors to study this measure in a Bayesian setting. For this large class of priors, we show that the (marginal) posterior for Pearson's correlation coefficient and all of the posterior moments are analytic. Our results are available in the open-source software package JASP.

Analytic posteriors for Pearson's correlation coefficient

OpenAIRE

Ly, A.; Marsman, M.; Wagenmakers, E.-J.

2018-01-01

Pearson's correlation is one of the most common measures of linear dependence. Recently, Bernardo (11th International Workshop on Objective Bayes Methodology, 2015) introduced a flexible class of priors to study this measure in a Bayesian setting. For this large class of priors, we show that the (marginal) posterior for Pearson's correlation coefficient and all of the posterior moments are analytic. Our results are available in the open‐source software package JASP.

A note on modeling of tumor regression for estimation of radiobiological parameters

International Nuclear Information System (INIS)

Zhong, Hualiang; Chetty, Indrin

2014-01-01

Purpose: Accurate calculation of radiobiological parameters is crucial to predicting radiation treatment response. Modeling differences may have a significant impact on derived parameters. In this study, the authors have integrated two existing models with kinetic differential equations to formulate a new tumor regression model for estimation of radiobiological parameters for individual patients. Methods: A system of differential equations that characterizes the birth-and-death process of tumor cells in radiation treatment was analytically solved. The solution of this system was used to construct an iterative model (Z-model). The model consists of three parameters: tumor doubling time T d , half-life of dead cells T r , and cell survival fraction SF D under dose D. The Jacobian determinant of this model was proposed as a constraint to optimize the three parameters for six head and neck cancer patients. The derived parameters were compared with those generated from the two existing models: Chvetsov's model (C-model) and Lim's model (L-model). The C-model and L-model were optimized with the parameter T d fixed. Results: With the Jacobian-constrained Z-model, the mean of the optimized cell survival fractions is 0.43 ± 0.08, and the half-life of dead cells averaged over the six patients is 17.5 ± 3.2 days. The parameters T r and SF D optimized with the Z-model differ by 1.2% and 20.3% from those optimized with the T d -fixed C-model, and by 32.1% and 112.3% from those optimized with the T d -fixed L-model, respectively. Conclusions: The Z-model was analytically constructed from the differential equations of cell populations that describe changes in the number of different tumor cells during the course of radiation treatment. The Jacobian constraints were proposed to optimize the three radiobiological parameters. The generated model and its optimization method may help develop high-quality treatment regimens for individual patients

Vertebral body spread in thoracolumbar burst fractures can predict posterior construct failure.

Science.gov (United States)

De Iure, Federico; Lofrese, Giorgio; De Bonis, Pasquale; Cultrera, Francesco; Cappuccio, Michele; Battisti, Sofia

2018-06-01

The load sharing classification (LSC) laid foundations for a scoring system able to indicate which thoracolumbar fractures, after short-segment posterior-only fixations, would need longer instrumentations or additional anterior supports. We analyzed surgically treated thoracolumbar fractures, quantifying the vertebral body's fragment displacement with the aim of identifying a new parameter that could predict the posterior-only construct failure. This is a retrospective cohort study from a single institution. One hundred twenty-one consecutive patients were surgically treated for thoracolumbar burst fractures. Grade of kyphosis correction (GKC) expressed radiological outcome; Oswestry Disability Index and visual analog scale were considered. One hundred twenty-one consecutive patients who underwent posterior fixation for unstable thoracolumbar burst fractures were retrospectively evaluated clinically and radiologically. Supplementary anterior fixations were performed in 34 cases with posterior instrumentation failure, determined on clinic-radiological evidence or symptomatic loss of kyphosis correction. Segmental kyphosis angle and GKC were calculated according to the Cobb method. The displacement of fracture fragments was obtained from the mean of the adjacent end plate areas subtracted from the area enclosed by the maximum contour of vertebral fragmentation. The "spread" was derived from the ratio between this subtraction and the mean of the adjacent end plate areas. Analysis of variance, Mann-Whitney, and receiver operating characteristic were performed for statistical analysis. The authors report no conflict of interest concerning the materials or methods used in the present study or the findings specified in this paper. No funds or grants have been received for the present study. The spread revealed to be a helpful quantitative measurement of vertebral body fragment displacement, easily reproducible with the current computed tomography (CT) imaging technologies

On the effect of model parameters on forecast objects

Science.gov (United States)

Marzban, Caren; Jones, Corinne; Li, Ning; Sandgathe, Scott

2018-04-01

Many physics-based numerical models produce a gridded, spatial field of forecasts, e.g., a temperature map. The field for some quantities generally consists of spatially coherent and disconnected objects. Such objects arise in many problems, including precipitation forecasts in atmospheric models, eddy currents in ocean models, and models of forest fires. Certain features of these objects (e.g., location, size, intensity, and shape) are generally of interest. Here, a methodology is developed for assessing the impact of model parameters on the features of forecast objects. The main ingredients of the methodology include the use of (1) Latin hypercube sampling for varying the values of the model parameters, (2) statistical clustering algorithms for identifying objects, (3) multivariate multiple regression for assessing the impact of multiple model parameters on the distribution (across the forecast domain) of object features, and (4) methods for reducing the number of hypothesis tests and controlling the resulting errors. The final output of the methodology is a series of box plots and confidence intervals that visually display the sensitivities. The methodology is demonstrated on precipitation forecasts from a mesoscale numerical weather prediction model.

Evaluation of the outcomes after posterior urethroplasty.

Science.gov (United States)

Liberman, Daniel; Pagliara, Travis J; Pisansky, Andrew; Elliott, Sean P

2015-03-01

Posterior urethral injury is a clinically significant complication of pelvic fractures. The management is complicated by the associated organ injuries, distortion of the pelvic anatomy and the ensuing fibrosis that occurs with urethral injury. We report a review of the outcomes after posterior urethroplasty in the context of pelvic fracture urethral injury.

An automatic and effective parameter optimization method for model tuning

Directory of Open Access Journals (Sweden)

T. Zhang

2015-11-01

simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9 %. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameter tuning during the model development stage.

Frequency and determinants for hemorrhagic transformation of posterior cerebral stroke : Posterior ischemic stroke and hemorrhagic transformation.

Science.gov (United States)

Valentino, Francesca; Gentile, Luana; Terruso, Valeria; Mastrilli, Sergio; Aridon, Paolo; Ragonese, Paolo; Sarno, Caterina; Savettieri, Giovanni; D'Amelio, Marco

2017-11-13

hemorrhagic transformation is a threatening ischemic stroke complication. Frequency of hemorrhagic transformation differs greatly among studies, and its risk factors have been usually studied in patients with anterior ischemic stroke who received thrombolytic therapy. We evaluated, in a hospital-based series of patients with posterior ischemic stroke not treated with thrombolysis, frequency and risk factors of hemorrhagic transformation. Patients with posterior circulation stroke were seen in our Department during the period January 2004 to December 2009. Demographic and clinical information were collected. We estimated risk for spontaneous hemorrhagic transformation by means of uni- and multivariate logistic regression analyses. 119 consecutive patients were included (73 males, 61.3%). Hemorrhagic transformation was observed in 7 patients (5.9%). Only clinical worsening was significantly associated with hemorrhagic transformation (OR 6.8, 95% CI 1.3-34.5). Our findings indicate that patients with posterior have a low risk of spontaneous hemorrhagic transformation, suggesting that these patients might have greater advantage from intravenous thrombolysis.

A compact cyclic plasticity model with parameter evolution

DEFF Research Database (Denmark)

Krenk, Steen; Tidemann, L.

2017-01-01

The paper presents a compact model for cyclic plasticity based on energy in terms of external and internal variables, and plastic yielding described by kinematic hardening and a flow potential with an additive term controlling the nonlinear cyclic hardening. The model is basically described by five...... parameters: external and internal stiffness, a yield stress and a limiting ultimate stress, and finally a parameter controlling the gradual development of plastic deformation. Calibration against numerous experimental results indicates that typically larger plastic strains develop than predicted...

Management of Posterior Urethral Valves in Rural Kenya

African Journals Online (AJOL)

Management of Posterior Urethral Valves in Rural. Kenya .... Antwi S. Audit of Posterior Urethral Valve (PUV) in Children at ... Community Paediatrics Committee, Infectious. Diseases ... Effect of Circumcision on Risk of Urinary Tract. Infection in ...

Luminescence model with quantum impact parameter for low energy ions

CERN Document Server

Cruz-Galindo, H S; Martínez-Davalos, A; Belmont-Moreno, E; Galindo, S

2002-01-01

We have modified an analytical model of induced light production by energetic ions interacting in scintillating materials. The original model is based on the distribution of energy deposited by secondary electrons produced along the ion's track. The range of scattered electrons, and thus the energy distribution, depends on a classical impact parameter between the electron and the ion's track. The only adjustable parameter of the model is the quenching density rho sub q. The modification here presented, consists in proposing a quantum impact parameter that leads to a better fit of the model to the experimental data at low incident ion energies. The light output response of CsI(Tl) detectors to low energy ions (<3 MeV/A) is fitted with the modified model and comparison is made to the original model.

Inhalation Exposure Input Parameters for the Biosphere Model

Energy Technology Data Exchange (ETDEWEB)

M. A. Wasiolek

2003-09-24

This analysis is one of the nine reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2003a) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents a set of input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for a Yucca Mountain repository. This report, ''Inhalation Exposure Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (BSC 2003b). It should be noted that some documents identified in Figure 1-1 may be under development at the time this report is issued and therefore not available at that time. This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this analysis report. This analysis report defines and justifies values of mass loading, which is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Measurements of mass loading are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air surrounding crops and concentrations in air