Comparison of different statistical methods for estimation of extreme sea levels with wave set-up contribution

NASA Astrophysics Data System (ADS)

Kergadallan, Xavier; Bernardara, Pietro; Benoit, Michel; Andreewsky, Marc; Weiss, Jérôme

2013-04-01

Estimating the probability of occurrence of extreme sea levels is a central issue for the protection of the coast. Return periods of sea level with wave set-up contribution are estimated here in one site : Cherbourg in France in the English Channel. The methodology follows two steps : the first one is computation of joint probability of simultaneous wave height and still sea level, the second one is interpretation of that joint probabilities to assess a sea level for a given return period. Two different approaches were evaluated to compute joint probability of simultaneous wave height and still sea level : the first one is multivariate extreme values distributions of logistic type in which all components of the variables become large simultaneously, the second one is conditional approach for multivariate extreme values in which only one component of the variables have to be large. Two different methods were applied to estimate sea level with wave set-up contribution for a given return period : Monte-Carlo simulation in which estimation is more accurate but needs higher calculation time and classical ocean engineering design contours of type inverse-FORM in which the method is simpler and allows more complex estimation of wave setup part (wave propagation to the coast for example). We compare results from the two different approaches with the two different methods. To be able to use both Monte-Carlo simulation and design contours methods, wave setup is estimated with an simple empirical formula. We show advantages of the conditional approach compared to the multivariate extreme values approach when extreme sea-level occurs when either surge or wave height is large. We discuss the validity of the ocean engineering design contours method which is an alternative when computation of sea levels is too complex to use Monte-Carlo simulation method.

Joint detection and tracking of size-varying infrared targets based on block-wise sparse decomposition

NASA Astrophysics Data System (ADS)

Li, Miao; Lin, Zaiping; Long, Yunli; An, Wei; Zhou, Yiyu

2016-05-01

The high variability of target size makes small target detection in Infrared Search and Track (IRST) a challenging task. A joint detection and tracking method based on block-wise sparse decomposition is proposed to address this problem. For detection, the infrared image is divided into overlapped blocks, and each block is weighted on the local image complexity and target existence probabilities. Target-background decomposition is solved by block-wise inexact augmented Lagrange multipliers. For tracking, label multi-Bernoulli (LMB) tracker tracks multiple targets taking the result of single-frame detection as input, and provides corresponding target existence probabilities for detection. Unlike fixed-size methods, the proposed method can accommodate size-varying targets, due to no special assumption for the size and shape of small targets. Because of exact decomposition, classical target measurements are extended and additional direction information is provided to improve tracking performance. The experimental results show that the proposed method can effectively suppress background clutters, detect and track size-varying targets in infrared images.

Bivariate Rainfall and Runoff Analysis Using Shannon Entropy Theory

NASA Astrophysics Data System (ADS)

Rahimi, A.; Zhang, L.

2012-12-01

Rainfall-Runoff analysis is the key component for many hydrological and hydraulic designs in which the dependence of rainfall and runoff needs to be studied. It is known that the convenient bivariate distribution are often unable to model the rainfall-runoff variables due to that they either have constraints on the range of the dependence or fixed form for the marginal distributions. Thus, this paper presents an approach to derive the entropy-based joint rainfall-runoff distribution using Shannon entropy theory. The distribution derived can model the full range of dependence and allow different specified marginals. The modeling and estimation can be proceeded as: (i) univariate analysis of marginal distributions which includes two steps, (a) using the nonparametric statistics approach to detect modes and underlying probability density, and (b) fitting the appropriate parametric probability density functions; (ii) define the constraints based on the univariate analysis and the dependence structure; (iii) derive and validate the entropy-based joint distribution. As to validate the method, the rainfall-runoff data are collected from the small agricultural experimental watersheds located in semi-arid region near Riesel (Waco), Texas, maintained by the USDA. The results of unviariate analysis show that the rainfall variables follow the gamma distribution, whereas the runoff variables have mixed structure and follow the mixed-gamma distribution. With this information, the entropy-based joint distribution is derived using the first moments, the first moments of logarithm transformed rainfall and runoff, and the covariance between rainfall and runoff. The results of entropy-based joint distribution indicate: (1) the joint distribution derived successfully preserves the dependence between rainfall and runoff, and (2) the K-S goodness of fit statistical tests confirm the marginal distributions re-derived reveal the underlying univariate probability densities which further assure that the entropy-based joint rainfall-runoff distribution are satisfactorily derived. Overall, the study shows the Shannon entropy theory can be satisfactorily applied to model the dependence between rainfall and runoff. The study also shows that the entropy-based joint distribution is an appropriate approach to capture the dependence structure that cannot be captured by the convenient bivariate joint distributions. Joint Rainfall-Runoff Entropy Based PDF, and Corresponding Marginal PDF and Histogram for W12 Watershed The K-S Test Result and RMSE on Univariate Distributions Derived from the Maximum Entropy Based Joint Probability Distribution;

Reducing Interpolation Artifacts for Mutual Information Based Image Registration

PubMed Central

Soleimani, H.; Khosravifard, M.A.

2011-01-01

Medical image registration methods which use mutual information as similarity measure have been improved in recent decades. Mutual Information is a basic concept of Information theory which indicates the dependency of two random variables (or two images). In order to evaluate the mutual information of two images their joint probability distribution is required. Several interpolation methods, such as Partial Volume (PV) and bilinear, are used to estimate joint probability distribution. Both of these two methods yield some artifacts on mutual information function. Partial Volume-Hanning window (PVH) and Generalized Partial Volume (GPV) methods are introduced to remove such artifacts. In this paper we show that the acceptable performance of these methods is not due to their kernel function. It's because of the number of pixels which incorporate in interpolation. Since using more pixels requires more complex and time consuming interpolation process, we propose a new interpolation method which uses only four pixels (the same as PV and bilinear interpolations) and removes most of the artifacts. Experimental results of the registration of Computed Tomography (CT) images show superiority of the proposed scheme. PMID:22606673

The Efficacy of Using Diagrams When Solving Probability Word Problems in College

ERIC Educational Resources Information Center

Beitzel, Brian D.; Staley, Richard K.

2015-01-01

Previous experiments have shown a deleterious effect of visual representations on college students' ability to solve total- and joint-probability word problems. The present experiments used conditional-probability problems, known to be more difficult than total- and joint-probability problems. The diagram group was instructed in how to use tree…

Joint probabilities and quantum cognition

NASA Astrophysics Data System (ADS)

de Barros, J. Acacio

2012-12-01

In this paper we discuss the existence of joint probability distributions for quantumlike response computations in the brain. We do so by focusing on a contextual neural-oscillator model shown to reproduce the main features of behavioral stimulus-response theory. We then exhibit a simple example of contextual random variables not having a joint probability distribution, and describe how such variables can be obtained from neural oscillators, but not from a quantum observable algebra.

Scalable Joint Models for Reliable Uncertainty-Aware Event Prediction.

PubMed

Soleimani, Hossein; Hensman, James; Saria, Suchi

2017-08-21

Missing data and noisy observations pose significant challenges for reliably predicting events from irregularly sampled multivariate time series (longitudinal) data. Imputation methods, which are typically used for completing the data prior to event prediction, lack a principled mechanism to account for the uncertainty due to missingness. Alternatively, state-of-the-art joint modeling techniques can be used for jointly modeling the longitudinal and event data and compute event probabilities conditioned on the longitudinal observations. These approaches, however, make strong parametric assumptions and do not easily scale to multivariate signals with many observations. Our proposed approach consists of several key innovations. First, we develop a flexible and scalable joint model based upon sparse multiple-output Gaussian processes. Unlike state-of-the-art joint models, the proposed model can explain highly challenging structure including non-Gaussian noise while scaling to large data. Second, we derive an optimal policy for predicting events using the distribution of the event occurrence estimated by the joint model. The derived policy trades-off the cost of a delayed detection versus incorrect assessments and abstains from making decisions when the estimated event probability does not satisfy the derived confidence criteria. Experiments on a large dataset show that the proposed framework significantly outperforms state-of-the-art techniques in event prediction.

Analyzing multicomponent receptive fields from neural responses to natural stimuli

PubMed Central

Rowekamp, Ryan; Sharpee, Tatyana O

2011-01-01

The challenge of building increasingly better models of neural responses to natural stimuli is to accurately estimate the multiple stimulus features that may jointly affect the neural spike probability. The selectivity for combinations of features is thought to be crucial for achieving classical properties of neural responses such as contrast invariance. The joint search for these multiple stimulus features is difficult because estimating spike probability as a multidimensional function of stimulus projections onto candidate relevant dimensions is subject to the curse of dimensionality. An attractive alternative is to search for relevant dimensions sequentially, as in projection pursuit regression. Here we demonstrate using analytic arguments and simulations of model cells that different types of sequential search strategies exhibit systematic biases when used with natural stimuli. Simulations show that joint optimization is feasible for up to three dimensions with current algorithms. When applied to the responses of V1 neurons to natural scenes, models based on three jointly optimized dimensions had better predictive power in a majority of cases compared to dimensions optimized sequentially, with different sequential methods yielding comparable results. Thus, although the curse of dimensionality remains, at least several relevant dimensions can be estimated by joint information maximization. PMID:21780916

Comment on "constructing quantum games from nonfactorizable joint probabilities".

PubMed

Frąckiewicz, Piotr

2013-09-01

In the paper [Phys. Rev. E 76, 061122 (2007)], the authors presented a way of playing 2 × 2 games so that players were able to exploit nonfactorizable joint probabilities respecting the nonsignaling principle (i.e., relativistic causality). We are going to prove, however, that the scheme does not generalize the games studied in the commented paper. Moreover, it allows the players to obtain nonclassical results even if the factorizable joint probabilities are used.

Height probabilities in the Abelian sandpile model on the generalized finite Bethe lattice

NASA Astrophysics Data System (ADS)

Chen, Haiyan; Zhang, Fuji

2013-08-01

In this paper, we study the sandpile model on the generalized finite Bethe lattice with a particular boundary condition. Using a combinatorial method, we give the exact expressions for all single-site probabilities and some two-site joint probabilities. As a by-product, we prove that the height probabilities of bulk vertices are all the same for the Bethe lattice with certain given boundary condition, which was found from numerical evidence by Grassberger and Manna ["Some more sandpiles," J. Phys. (France) 51, 1077-1098 (1990)], 10.1051/jphys:0199000510110107700 but without a proof.

Comparison of Bootstrapping and Markov Chain Monte Carlo for Copula Analysis of Hydrological Droughts

NASA Astrophysics Data System (ADS)

Yang, P.; Ng, T. L.; Yang, W.

2015-12-01

Effective water resources management depends on the reliable estimation of the uncertainty of drought events. Confidence intervals (CIs) are commonly applied to quantify this uncertainty. A CI seeks to be at the minimal length necessary to cover the true value of the estimated variable with the desired probability. In drought analysis where two or more variables (e.g., duration and severity) are often used to describe a drought, copulas have been found suitable for representing the joint probability behavior of these variables. However, the comprehensive assessment of the parameter uncertainties of copulas of droughts has been largely ignored, and the few studies that have recognized this issue have not explicitly compared the various methods to produce the best CIs. Thus, the objective of this study to compare the CIs generated using two widely applied uncertainty estimation methods, bootstrapping and Markov Chain Monte Carlo (MCMC). To achieve this objective, (1) the marginal distributions lognormal, Gamma, and Generalized Extreme Value, and the copula functions Clayton, Frank, and Plackett are selected to construct joint probability functions of two drought related variables. (2) The resulting joint functions are then fitted to 200 sets of simulated realizations of drought events with known distribution and extreme parameters and (3) from there, using bootstrapping and MCMC, CIs of the parameters are generated and compared. The effect of an informative prior on the CIs generated by MCMC is also evaluated. CIs are produced for different sample sizes (50, 100, and 200) of the simulated drought events for fitting the joint probability functions. Preliminary results assuming lognormal marginal distributions and the Clayton copula function suggest that for cases with small or medium sample sizes (~50-100), MCMC to be superior method if an informative prior exists. Where an informative prior is unavailable, for small sample sizes (~50), both bootstrapping and MCMC yield the same level of performance, and for medium sample sizes (~100), bootstrapping is better. For cases with a large sample size (~200), there is little difference between the CIs generated using bootstrapping and MCMC regardless of whether or not an informative prior exists.

A linear programming model for protein inference problem in shotgun proteomics.

PubMed

Huang, Ting; He, Zengyou

2012-11-15

Assembling peptides identified from tandem mass spectra into a list of proteins, referred to as protein inference, is an important issue in shotgun proteomics. The objective of protein inference is to find a subset of proteins that are truly present in the sample. Although many methods have been proposed for protein inference, several issues such as peptide degeneracy still remain unsolved. In this article, we present a linear programming model for protein inference. In this model, we use a transformation of the joint probability that each peptide/protein pair is present in the sample as the variable. Then, both the peptide probability and protein probability can be expressed as a formula in terms of the linear combination of these variables. Based on this simple fact, the protein inference problem is formulated as an optimization problem: minimize the number of proteins with non-zero probabilities under the constraint that the difference between the calculated peptide probability and the peptide probability generated from peptide identification algorithms should be less than some threshold. This model addresses the peptide degeneracy issue by forcing some joint probability variables involving degenerate peptides to be zero in a rigorous manner. The corresponding inference algorithm is named as ProteinLP. We test the performance of ProteinLP on six datasets. Experimental results show that our method is competitive with the state-of-the-art protein inference algorithms. The source code of our algorithm is available at: https://sourceforge.net/projects/prolp/. zyhe@dlut.edu.cn. Supplementary data are available at Bioinformatics Online.

Joint Inversion of 1-D Magnetotelluric and Surface-Wave Dispersion Data with an Improved Multi-Objective Genetic Algorithm and Application to the Data of the Longmenshan Fault Zone

NASA Astrophysics Data System (ADS)

Wu, Pingping; Tan, Handong; Peng, Miao; Ma, Huan; Wang, Mao

2018-05-01

Magnetotellurics and seismic surface waves are two prominent geophysical methods for deep underground exploration. Joint inversion of these two datasets can help enhance the accuracy of inversion. In this paper, we describe a method for developing an improved multi-objective genetic algorithm (NSGA-SBX) and applying it to two numerical tests to verify the advantages of the algorithm. Our findings show that joint inversion with the NSGA-SBX method can improve the inversion results by strengthening structural coupling when the discontinuities of the electrical and velocity models are consistent, and in case of inconsistent discontinuities between these models, joint inversion can retain the advantages of individual inversions. By applying the algorithm to four detection points along the Longmenshan fault zone, we observe several features. The Sichuan Basin demonstrates low S-wave velocity and high conductivity in the shallow crust probably due to thick sedimentary layers. The eastern margin of the Tibetan Plateau shows high velocity and high resistivity in the shallow crust, while two low velocity layers and a high conductivity layer are observed in the middle lower crust, probably indicating the mid-crustal channel flow. Along the Longmenshan fault zone, a high conductivity layer from 8 to 20 km is observed beneath the northern segment and decreases with depth beneath the middle segment, which might be caused by the elevated fluid content of the fault zone.

Probabilistic Density Function Method for Stochastic ODEs of Power Systems with Uncertain Power Input

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Peng; Barajas-Solano, David A.; Constantinescu, Emil

Wind and solar power generators are commonly described by a system of stochastic ordinary differential equations (SODEs) where random input parameters represent uncertainty in wind and solar energy. The existing methods for SODEs are mostly limited to delta-correlated random parameters (white noise). Here we use the Probability Density Function (PDF) method for deriving a closed-form deterministic partial differential equation (PDE) for the joint probability density function of the SODEs describing a power generator with time-correlated power input. The resulting PDE is solved numerically. A good agreement with Monte Carlo Simulations shows accuracy of the PDF method.

Efficient pairwise RNA structure prediction using probabilistic alignment constraints in Dynalign

PubMed Central

2007-01-01

Background Joint alignment and secondary structure prediction of two RNA sequences can significantly improve the accuracy of the structural predictions. Methods addressing this problem, however, are forced to employ constraints that reduce computation by restricting the alignments and/or structures (i.e. folds) that are permissible. In this paper, a new methodology is presented for the purpose of establishing alignment constraints based on nucleotide alignment and insertion posterior probabilities. Using a hidden Markov model, posterior probabilities of alignment and insertion are computed for all possible pairings of nucleotide positions from the two sequences. These alignment and insertion posterior probabilities are additively combined to obtain probabilities of co-incidence for nucleotide position pairs. A suitable alignment constraint is obtained by thresholding the co-incidence probabilities. The constraint is integrated with Dynalign, a free energy minimization algorithm for joint alignment and secondary structure prediction. The resulting method is benchmarked against the previous version of Dynalign and against other programs for pairwise RNA structure prediction. Results The proposed technique eliminates manual parameter selection in Dynalign and provides significant computational time savings in comparison to prior constraints in Dynalign while simultaneously providing a small improvement in the structural prediction accuracy. Savings are also realized in memory. In experiments over a 5S RNA dataset with average sequence length of approximately 120 nucleotides, the method reduces computation by a factor of 2. The method performs favorably in comparison to other programs for pairwise RNA structure prediction: yielding better accuracy, on average, and requiring significantly lesser computational resources. Conclusion Probabilistic analysis can be utilized in order to automate the determination of alignment constraints for pairwise RNA structure prediction methods in a principled fashion. These constraints can reduce the computational and memory requirements of these methods while maintaining or improving their accuracy of structural prediction. This extends the practical reach of these methods to longer length sequences. The revised Dynalign code is freely available for download. PMID:17445273

Maximum aposteriori joint source/channel coding

NASA Technical Reports Server (NTRS)

Sayood, Khalid; Gibson, Jerry D.

1991-01-01

A maximum aposteriori probability (MAP) approach to joint source/channel coder design is presented in this paper. This method attempts to explore a technique for designing joint source/channel codes, rather than ways of distributing bits between source coders and channel coders. For a nonideal source coder, MAP arguments are used to design a decoder which takes advantage of redundancy in the source coder output to perform error correction. Once the decoder is obtained, it is analyzed with the purpose of obtaining 'desirable properties' of the channel input sequence for improving overall system performance. Finally, an encoder design which incorporates these properties is proposed.

Dose-volume histogram prediction using density estimation.

PubMed

Skarpman Munter, Johanna; Sjölund, Jens

2015-09-07

Knowledge of what dose-volume histograms can be expected for a previously unseen patient could increase consistency and quality in radiotherapy treatment planning. We propose a machine learning method that uses previous treatment plans to predict such dose-volume histograms. The key to the approach is the framing of dose-volume histograms in a probabilistic setting.The training consists of estimating, from the patients in the training set, the joint probability distribution of some predictive features and the dose. The joint distribution immediately provides an estimate of the conditional probability of the dose given the values of the predictive features. The prediction consists of estimating, from the new patient, the distribution of the predictive features and marginalizing the conditional probability from the training over this. Integrating the resulting probability distribution for the dose yields an estimate of the dose-volume histogram.To illustrate how the proposed method relates to previously proposed methods, we use the signed distance to the target boundary as a single predictive feature. As a proof-of-concept, we predicted dose-volume histograms for the brainstems of 22 acoustic schwannoma patients treated with stereotactic radiosurgery, and for the lungs of 9 lung cancer patients treated with stereotactic body radiation therapy. Comparing with two previous attempts at dose-volume histogram prediction we find that, given the same input data, the predictions are similar.In summary, we propose a method for dose-volume histogram prediction that exploits the intrinsic probabilistic properties of dose-volume histograms. We argue that the proposed method makes up for some deficiencies in previously proposed methods, thereby potentially increasing ease of use, flexibility and ability to perform well with small amounts of training data.

An Improved WiFi Indoor Positioning Algorithm by Weighted Fusion

PubMed Central

Ma, Rui; Guo, Qiang; Hu, Changzhen; Xue, Jingfeng

2015-01-01

The rapid development of mobile Internet has offered the opportunity for WiFi indoor positioning to come under the spotlight due to its low cost. However, nowadays the accuracy of WiFi indoor positioning cannot meet the demands of practical applications. To solve this problem, this paper proposes an improved WiFi indoor positioning algorithm by weighted fusion. The proposed algorithm is based on traditional location fingerprinting algorithms and consists of two stages: the offline acquisition and the online positioning. The offline acquisition process selects optimal parameters to complete the signal acquisition, and it forms a database of fingerprints by error classification and handling. To further improve the accuracy of positioning, the online positioning process first uses a pre-match method to select the candidate fingerprints to shorten the positioning time. After that, it uses the improved Euclidean distance and the improved joint probability to calculate two intermediate results, and further calculates the final result from these two intermediate results by weighted fusion. The improved Euclidean distance introduces the standard deviation of WiFi signal strength to smooth the WiFi signal fluctuation and the improved joint probability introduces the logarithmic calculation to reduce the difference between probability values. Comparing the proposed algorithm, the Euclidean distance based WKNN algorithm and the joint probability algorithm, the experimental results indicate that the proposed algorithm has higher positioning accuracy. PMID:26334278

An Improved WiFi Indoor Positioning Algorithm by Weighted Fusion.

PubMed

Ma, Rui; Guo, Qiang; Hu, Changzhen; Xue, Jingfeng

2015-08-31

The rapid development of mobile Internet has offered the opportunity for WiFi indoor positioning to come under the spotlight due to its low cost. However, nowadays the accuracy of WiFi indoor positioning cannot meet the demands of practical applications. To solve this problem, this paper proposes an improved WiFi indoor positioning algorithm by weighted fusion. The proposed algorithm is based on traditional location fingerprinting algorithms and consists of two stages: the offline acquisition and the online positioning. The offline acquisition process selects optimal parameters to complete the signal acquisition, and it forms a database of fingerprints by error classification and handling. To further improve the accuracy of positioning, the online positioning process first uses a pre-match method to select the candidate fingerprints to shorten the positioning time. After that, it uses the improved Euclidean distance and the improved joint probability to calculate two intermediate results, and further calculates the final result from these two intermediate results by weighted fusion. The improved Euclidean distance introduces the standard deviation of WiFi signal strength to smooth the WiFi signal fluctuation and the improved joint probability introduces the logarithmic calculation to reduce the difference between probability values. Comparing the proposed algorithm, the Euclidean distance based WKNN algorithm and the joint probability algorithm, the experimental results indicate that the proposed algorithm has higher positioning accuracy.

The impact of joint responses of devices in an airport security system.

PubMed

Nie, Xiaofeng; Batta, Rajan; Drury, Colin G; Lin, Li

2009-02-01

In this article, we consider a model for an airport security system in which the declaration of a threat is based on the joint responses of inspection devices. This is in contrast to the typical system in which each check station independently declares a passenger as having a threat or not having a threat. In our framework the declaration of threat/no-threat is based upon the passenger scores at the check stations he/she goes through. To do this we use concepts from classification theory in the field of multivariate statistics analysis and focus on the main objective of minimizing the expected cost of misclassification. The corresponding correct classification and misclassification probabilities can be obtained by using a simulation-based method. After computing the overall false alarm and false clear probabilities, we compare our joint response system with two other independently operated systems. A model that groups passengers in a manner that minimizes the false alarm probability while maintaining the false clear probability within specifications set by a security authority is considered. We also analyze the staffing needs at each check station for such an inspection scheme. An illustrative example is provided along with sensitivity analysis on key model parameters. A discussion is provided on some implementation issues, on the various assumptions made in the analysis, and on potential drawbacks of the approach.

Probability distributions for multimeric systems.

PubMed

Albert, Jaroslav; Rooman, Marianne

2016-01-01

We propose a fast and accurate method of obtaining the equilibrium mono-modal joint probability distributions for multimeric systems. The method necessitates only two assumptions: the copy number of all species of molecule may be treated as continuous; and, the probability density functions (pdf) are well-approximated by multivariate skew normal distributions (MSND). Starting from the master equation, we convert the problem into a set of equations for the statistical moments which are then expressed in terms of the parameters intrinsic to the MSND. Using an optimization package on Mathematica, we minimize a Euclidian distance function comprising of a sum of the squared difference between the left and the right hand sides of these equations. Comparison of results obtained via our method with those rendered by the Gillespie algorithm demonstrates our method to be highly accurate as well as efficient.

Supernova Cosmology Inference with Probabilistic Photometric Redshifts (SCIPPR)

NASA Astrophysics Data System (ADS)

Peters, Christina; Malz, Alex; Hlozek, Renée

2018-01-01

The Bayesian Estimation Applied to Multiple Species (BEAMS) framework employs probabilistic supernova type classifications to do photometric SN cosmology. This work extends BEAMS to replace high-confidence spectroscopic redshifts with photometric redshift probability density functions, a capability that will be essential in the era the Large Synoptic Survey Telescope and other next-generation photometric surveys where it will not be possible to perform spectroscopic follow up on every SN. We present the Supernova Cosmology Inference with Probabilistic Photometric Redshifts (SCIPPR) Bayesian hierarchical model for constraining the cosmological parameters from photometric lightcurves and host galaxy photometry, which includes selection effects and is extensible to uncertainty in the redshift-dependent supernova type proportions. We create a pair of realistic mock catalogs of joint posteriors over supernova type, redshift, and distance modulus informed by photometric supernova lightcurves and over redshift from simulated host galaxy photometry. We perform inference under our model to obtain a joint posterior probability distribution over the cosmological parameters and compare our results with other methods, namely: a spectroscopic subset, a subset of high probability photometrically classified supernovae, and reducing the photometric redshift probability to a single measurement and error bar.

Joint Probability Analysis of Extreme Precipitation and Storm Tide in a Coastal City under Changing Environment

PubMed Central

Xu, Kui; Ma, Chao; Lian, Jijian; Bin, Lingling

2014-01-01

Catastrophic flooding resulting from extreme meteorological events has occurred more frequently and drawn great attention in recent years in China. In coastal areas, extreme precipitation and storm tide are both inducing factors of flooding and therefore their joint probability would be critical to determine the flooding risk. The impact of storm tide or changing environment on flooding is ignored or underestimated in the design of drainage systems of today in coastal areas in China. This paper investigates the joint probability of extreme precipitation and storm tide and its change using copula-based models in Fuzhou City. The change point at the year of 1984 detected by Mann-Kendall and Pettitt’s tests divides the extreme precipitation series into two subsequences. For each subsequence the probability of the joint behavior of extreme precipitation and storm tide is estimated by the optimal copula. Results show that the joint probability has increased by more than 300% on average after 1984 (α = 0.05). The design joint return period (RP) of extreme precipitation and storm tide is estimated to propose a design standard for future flooding preparedness. For a combination of extreme precipitation and storm tide, the design joint RP has become smaller than before. It implies that flooding would happen more often after 1984, which corresponds with the observation. The study would facilitate understanding the change of flood risk and proposing the adaption measures for coastal areas under a changing environment. PMID:25310006

Joint probability analysis of extreme precipitation and storm tide in a coastal city under changing environment.

PubMed

Xu, Kui; Ma, Chao; Lian, Jijian; Bin, Lingling

2014-01-01

Catastrophic flooding resulting from extreme meteorological events has occurred more frequently and drawn great attention in recent years in China. In coastal areas, extreme precipitation and storm tide are both inducing factors of flooding and therefore their joint probability would be critical to determine the flooding risk. The impact of storm tide or changing environment on flooding is ignored or underestimated in the design of drainage systems of today in coastal areas in China. This paper investigates the joint probability of extreme precipitation and storm tide and its change using copula-based models in Fuzhou City. The change point at the year of 1984 detected by Mann-Kendall and Pettitt's tests divides the extreme precipitation series into two subsequences. For each subsequence the probability of the joint behavior of extreme precipitation and storm tide is estimated by the optimal copula. Results show that the joint probability has increased by more than 300% on average after 1984 (α = 0.05). The design joint return period (RP) of extreme precipitation and storm tide is estimated to propose a design standard for future flooding preparedness. For a combination of extreme precipitation and storm tide, the design joint RP has become smaller than before. It implies that flooding would happen more often after 1984, which corresponds with the observation. The study would facilitate understanding the change of flood risk and proposing the adaption measures for coastal areas under a changing environment.

LES/PDF studies of joint statistics of mixture fraction and progress variable in piloted methane jet flames with inhomogeneous inlet flows

NASA Astrophysics Data System (ADS)

Zhang, Pei; Barlow, Robert; Masri, Assaad; Wang, Haifeng

2016-11-01

The mixture fraction and progress variable are often used as independent variables for describing turbulent premixed and non-premixed flames. There is a growing interest in using these two variables for describing partially premixed flames. The joint statistical distribution of the mixture fraction and progress variable is of great interest in developing models for partially premixed flames. In this work, we conduct predictive studies of the joint statistics of mixture fraction and progress variable in a series of piloted methane jet flames with inhomogeneous inlet flows. The employed models combine large eddy simulations with the Monte Carlo probability density function (PDF) method. The joint PDFs and marginal PDFs are examined in detail by comparing the model predictions and the measurements. Different presumed shapes of the joint PDFs are also evaluated.

On the quantification and efficient propagation of imprecise probabilities resulting from small datasets

NASA Astrophysics Data System (ADS)

Zhang, Jiaxin; Shields, Michael D.

2018-01-01

This paper addresses the problem of uncertainty quantification and propagation when data for characterizing probability distributions are scarce. We propose a methodology wherein the full uncertainty associated with probability model form and parameter estimation are retained and efficiently propagated. This is achieved by applying the information-theoretic multimodel inference method to identify plausible candidate probability densities and associated probabilities that each method is the best model in the Kullback-Leibler sense. The joint parameter densities for each plausible model are then estimated using Bayes' rule. We then propagate this full set of probability models by estimating an optimal importance sampling density that is representative of all plausible models, propagating this density, and reweighting the samples according to each of the candidate probability models. This is in contrast with conventional methods that try to identify a single probability model that encapsulates the full uncertainty caused by lack of data and consequently underestimate uncertainty. The result is a complete probabilistic description of both aleatory and epistemic uncertainty achieved with several orders of magnitude reduction in computational cost. It is shown how the model can be updated to adaptively accommodate added data and added candidate probability models. The method is applied for uncertainty analysis of plate buckling strength where it is demonstrated how dataset size affects the confidence (or lack thereof) we can place in statistical estimates of response when data are lacking.

RADC Multi-Dimensional Signal-Processing Research Program.

DTIC Science & Technology

1980-09-30

Formulation 7 3.2.2 Methods of Accelerating Convergence 8 3.2.3 Application to Image Deblurring 8 3.2.4 Extensions 11 3.3 Convergence of Iterative Signal... noise -driven linear filters, permit development of the joint probability density function oz " kelihood function for the image. With an expression...spatial linear filter driven by white noise (see Fig. i). If the probability density function for the white noise is known, Fig. t. Model for image

Encounter risk analysis of rainfall and reference crop evapotranspiration in the irrigation district

NASA Astrophysics Data System (ADS)

Zhang, Jinping; Lin, Xiaomin; Zhao, Yong; Hong, Yang

2017-09-01

Rainfall and reference crop evapotranspiration are random but mutually affected variables in the irrigation district, and their encounter situation can determine water shortage risks under the contexts of natural water supply and demand. However, in reality, the rainfall and reference crop evapotranspiration may have different marginal distributions and their relations are nonlinear. In this study, based on the annual rainfall and reference crop evapotranspiration data series from 1970 to 2013 in the Luhun irrigation district of China, the joint probability distribution of rainfall and reference crop evapotranspiration are developed with the Frank copula function. Using the joint probability distribution, the synchronous-asynchronous encounter risk, conditional joint probability, and conditional return period of different combinations of rainfall and reference crop evapotranspiration are analyzed. The results show that the copula-based joint probability distributions of rainfall and reference crop evapotranspiration are reasonable. The asynchronous encounter probability of rainfall and reference crop evapotranspiration is greater than their synchronous encounter probability, and the water shortage risk associated with meteorological drought (i.e. rainfall variability) is more prone to appear. Compared with other states, there are higher conditional joint probability and lower conditional return period in either low rainfall or high reference crop evapotranspiration. For a specifically high reference crop evapotranspiration with a certain frequency, the encounter risk of low rainfall and high reference crop evapotranspiration is increased with the decrease in frequency. For a specifically low rainfall with a certain frequency, the encounter risk of low rainfall and high reference crop evapotranspiration is decreased with the decrease in frequency. When either the high reference crop evapotranspiration exceeds a certain frequency or low rainfall does not exceed a certain frequency, the higher conditional joint probability and lower conditional return period of various combinations likely cause a water shortage, but the water shortage is not severe.

A Probabilistic Approach to Predict Thermal Fatigue Life for Ball Grid Array Solder Joints

NASA Astrophysics Data System (ADS)

Wei, Helin; Wang, Kuisheng

2011-11-01

Numerous studies of the reliability of solder joints have been performed. Most life prediction models are limited to a deterministic approach. However, manufacturing induces uncertainty in the geometry parameters of solder joints, and the environmental temperature varies widely due to end-user diversity, creating uncertainties in the reliability of solder joints. In this study, a methodology for accounting for variation in the lifetime prediction for lead-free solder joints of ball grid array packages (PBGA) is demonstrated. The key aspects of the solder joint parameters and the cyclic temperature range related to reliability are involved. Probabilistic solutions of the inelastic strain range and thermal fatigue life based on the Engelmaier model are developed to determine the probability of solder joint failure. The results indicate that the standard deviation increases significantly when more random variations are involved. Using the probabilistic method, the influence of each variable on the thermal fatigue life is quantified. This information can be used to optimize product design and process validation acceptance criteria. The probabilistic approach creates the opportunity to identify the root causes of failed samples from product fatigue tests and field returns. The method can be applied to better understand how variation affects parameters of interest in an electronic package design with area array interconnections.

Bivariate categorical data analysis using normal linear conditional multinomial probability model.

PubMed

Sun, Bingrui; Sutradhar, Brajendra

2015-02-10

Bivariate multinomial data such as the left and right eyes retinopathy status data are analyzed either by using a joint bivariate probability model or by exploiting certain odds ratio-based association models. However, the joint bivariate probability model yields marginal probabilities, which are complicated functions of marginal and association parameters for both variables, and the odds ratio-based association model treats the odds ratios involved in the joint probabilities as 'working' parameters, which are consequently estimated through certain arbitrary 'working' regression models. Also, this later odds ratio-based model does not provide any easy interpretations of the correlations between two categorical variables. On the basis of pre-specified marginal probabilities, in this paper, we develop a bivariate normal type linear conditional multinomial probability model to understand the correlations between two categorical variables. The parameters involved in the model are consistently estimated using the optimal likelihood and generalized quasi-likelihood approaches. The proposed model and the inferences are illustrated through an intensive simulation study as well as an analysis of the well-known Wisconsin Diabetic Retinopathy status data. Copyright © 2014 John Wiley & Sons, Ltd.

[Comments on the use of the "life-table method" in orthopedics].

PubMed

Hassenpflug, J; Hahne, H J; Hedderich, J

1992-01-01

In the description of long term results, e.g. of joint replacements, survivorship analysis is used increasingly in orthopaedic surgery. The survivorship analysis is more useful to describe the frequency of failure rather than global statements in percentage. The relative probability of failure for fixed intervals is drawn from the number of controlled patients and the frequency of failure. The complementary probabilities of success are linked in their temporal sequence thus representing the probability of survival at a fixed endpoint. Necessary condition for the use of this procedure is the exact definition of moment and manner of failure. It is described how to establish survivorship tables.

A Bayesian joint probability modeling approach for seasonal forecasting of streamflows at multiple sites

NASA Astrophysics Data System (ADS)

Wang, Q. J.; Robertson, D. E.; Chiew, F. H. S.

2009-05-01

Seasonal forecasting of streamflows can be highly valuable for water resources management. In this paper, a Bayesian joint probability (BJP) modeling approach for seasonal forecasting of streamflows at multiple sites is presented. A Box-Cox transformed multivariate normal distribution is proposed to model the joint distribution of future streamflows and their predictors such as antecedent streamflows and El Niño-Southern Oscillation indices and other climate indicators. Bayesian inference of model parameters and uncertainties is implemented using Markov chain Monte Carlo sampling, leading to joint probabilistic forecasts of streamflows at multiple sites. The model provides a parametric structure for quantifying relationships between variables, including intersite correlations. The Box-Cox transformed multivariate normal distribution has considerable flexibility for modeling a wide range of predictors and predictands. The Bayesian inference formulated allows the use of data that contain nonconcurrent and missing records. The model flexibility and data-handling ability means that the BJP modeling approach is potentially of wide practical application. The paper also presents a number of statistical measures and graphical methods for verification of probabilistic forecasts of continuous variables. Results for streamflows at three river gauges in the Murrumbidgee River catchment in southeast Australia show that the BJP modeling approach has good forecast quality and that the fitted model is consistent with observed data.

How weak values emerge in joint measurements on cloned quantum systems.

PubMed

Hofmann, Holger F

2012-07-13

A statistical analysis of optimal universal cloning shows that it is possible to identify an ideal (but nonpositive) copying process that faithfully maps all properties of the original Hilbert space onto two separate quantum systems, resulting in perfect correlations for all observables. The joint probabilities for noncommuting measurements on separate clones then correspond to the real parts of the complex joint probabilities observed in weak measurements on a single system, where the measurements on the two clones replace the corresponding sequence of weak measurement and postselection. The imaginary parts of weak measurement statics can be obtained by replacing the cloning process with a partial swap operation. A controlled-swap operation combines both processes, making the complete weak measurement statistics accessible as a well-defined contribution to the joint probabilities of fully resolved projective measurements on the two output systems.

Improved decryption quality and security of a joint transform correlator-based encryption system

NASA Astrophysics Data System (ADS)

Vilardy, Juan M.; Millán, María S.; Pérez-Cabré, Elisabet

2013-02-01

Some image encryption systems based on modified double random phase encoding and joint transform correlator architecture produce low quality decrypted images and are vulnerable to a variety of attacks. In this work, we analyse the algorithm of some reported methods that optically implement the double random phase encryption in a joint transform correlator. We show that it is possible to significantly improve the quality of the decrypted image by introducing a simple nonlinear operation in the encrypted function that contains the joint power spectrum. This nonlinearity also makes the system more resistant to chosen-plaintext attacks. We additionally explore the system resistance against this type of attack when a variety of probability density functions are used to generate the two random phase masks of the encryption-decryption process. Numerical results are presented and discussed.

"Combined Diagnostic Tool" APPlication to a Retrospective Series of Patients Undergoing Total Joint Revision Surgery.

PubMed

Gallazzi, Enrico; Drago, Lorenzo; Baldini, Andrea; Stockley, Ian; George, David A; Scarponi, Sara; Romanò, Carlo L

2017-01-01

Background : Differentiating between septic and aseptic joint prosthesis may be challenging, since no single test is able to confirm or rule out infection. The choice and interpretation of the panel of tests performed in any case often relies on empirical evaluation and poorly validated scores. The "Combined Diagnostic Tool (CDT)" App, a smartphone application for iOS, was developed to allow to automatically calculate the probability of having a of periprosthetic joint infection, on the basis of the relative sensitivity and specificity of the positive and negative diagnostic tests performed in any given patient. Objective : The aim of the present study was to apply the CDT software to investigate the ability of the tests routinely performed in three high-volume European centers to diagnose a periprosthetic infection. Methods : This three-center retrospective study included 120 consecutive patients undergoing total hip or knee revision, and included 65 infected patients (Group A) and 55 patients without infection (Group B). The following parameters were evaluated: number and type of positive and negative diagnostic tests performed pre-, intra- and post-operatively and resultant probability calculated by the CDT App of having a peri-prosthetic joint infection, based on pre-, intra- and post-operative combined tests. Results : Serological tests were the most common performed, with an average 2.7 tests per patient for Group A and 2.2 for Group B, followed by joint aspiration (0.9 and 0.8 tests per patient, respectively) and imaging techniques (0.5 and 0.2 test per patient). Mean CDT App calculated probability of having an infection based on pre-operative tests was 79.4% for patients in Group A and 35.7 in Group B. Twenty-nine patients in Group A had > 10% chance of not having an infection, and 29 of Group B had > 10% chance of having an infection. Conclusion : This is the first retrospective study focused on investigating the number and type of tests commonly performed prior to joint revision surgery and aimed at evaluating their combined ability to diagnose a peri-prosthetic infection. CDT App allowed us to demonstrate that, on average, the routine combination of commonly used tests is unable to diagnose pre-operatively a peri-prosthetic infection with a probability higher than 90%.

Patient and implant survival following joint replacement because of metastatic bone disease

PubMed Central

2013-01-01

Background Patients suffering from a pathological fracture or painful bony lesion because of metastatic bone disease often benefit from a total joint replacement. However, these are large operations in patients who are often weak. We examined the patient survival and complication rates after total joint replacement as the treatment for bone metastasis or hematological diseases of the extremities. Patients and methods 130 patients (mean age 64 (30–85) years, 76 females) received 140 joint replacements due to skeletal metastases (n = 114) or hematological disease (n = 16) during the period 2003–2008. 21 replaced joints were located in the upper extremities and 119 in the lower extremities. Clinical and survival data were extracted from patient files and various registers. Results The probability of patient survival was 51% (95% CI: 42–59) after 6 months, 39% (CI: 31–48) after 12 months, and 29% (CI: 21–37) after 24 months. The following surgical complications were seen (8 of which led to additional surgery): 2–5 hip dislocations (n = 8), deep infection (n = 3), peroneal palsy (n = 2), a shoulder prosthesis penetrating the skin (n = 1), and disassembly of an elbow prosthesis (n = 1). The probability of avoiding all kinds of surgery related to the implanted prosthesis was 94% (CI: 89–99) after 1 year and 92% (CI: 85–98) after 2 years. Conclusion Joint replacement operations because of metastatic bone disease do not appear to have given a poorer rate of patient survival than other types of surgical treatment, and the reoperation rate was low. PMID:23530874

A concise evidence-based physical examination for diagnosis of acromioclavicular joint pathology: a systematic review.

PubMed

Krill, Michael K; Rosas, Samuel; Kwon, KiHyun; Dakkak, Andrew; Nwachukwu, Benedict U; McCormick, Frank

2018-02-01

The clinical examination of the shoulder joint is an undervalued diagnostic tool for evaluating acromioclavicular (AC) joint pathology. Applying evidence-based clinical tests enables providers to make an accurate diagnosis and minimize costly imaging procedures and potential delays in care. The purpose of this study was to create a decision tree analysis enabling simple and accurate diagnosis of AC joint pathology. A systematic review of the Medline, Ovid and Cochrane Review databases was performed to identify level one and two diagnostic studies evaluating clinical tests for AC joint pathology. Individual test characteristics were combined in series and in parallel to improve sensitivities and specificities. A secondary analysis utilized subjective pre-test probabilities to create a clinical decision tree algorithm with post-test probabilities. The optimal special test combination to screen and confirm AC joint pathology combined Paxinos sign and O'Brien's Test, with a specificity of 95.8% when performed in series; whereas, Paxinos sign and Hawkins-Kennedy Test demonstrated a sensitivity of 93.7% when performed in parallel. Paxinos sign and O'Brien's Test demonstrated the greatest positive likelihood ratio (2.71); whereas, Paxinos sign and Hawkins-Kennedy Test reported the lowest negative likelihood ratio (0.35). No combination of special tests performed in series or in parallel creates more than a small impact on post-test probabilities to screen or confirm AC joint pathology. Paxinos sign and O'Brien's Test is the only special test combination that has a small and sometimes important impact when used both in series and in parallel. Physical examination testing is not beneficial for diagnosis of AC joint pathology when pretest probability is unequivocal. In these instances, it is of benefit to proceed with procedural tests to evaluate AC joint pathology. Ultrasound-guided corticosteroid injections are diagnostic and therapeutic. An ultrasound-guided AC joint corticosteroid injection may be an appropriate new standard for treatment and surgical decision-making. II - Systematic Review.

Joint Segmentation and Deformable Registration of Brain Scans Guided by a Tumor Growth Model

PubMed Central

Gooya, Ali; Pohl, Kilian M.; Bilello, Michel; Biros, George; Davatzikos, Christos

2011-01-01

This paper presents an approach for joint segmentation and deformable registration of brain scans of glioma patients to a normal atlas. The proposed method is based on the Expectation Maximization (EM) algorithm that incorporates a glioma growth model for atlas seeding, a process which modifies the normal atlas into one with a tumor and edema. The modified atlas is registered into the patient space and utilized for the posterior probability estimation of various tissue labels. EM iteratively refines the estimates of the registration parameters, the posterior probabilities of tissue labels and the tumor growth model parameters. We have applied this approach to 10 glioma scans acquired with four Magnetic Resonance (MR) modalities (T1, T1-CE, T2 and FLAIR ) and validated the result by comparing them to manual segmentations by clinical experts. The resulting segmentations look promising and quantitatively match well with the expert provided ground truth. PMID:21995070

Joint segmentation and deformable registration of brain scans guided by a tumor growth model.

PubMed

Gooya, Ali; Pohl, Kilian M; Bilello, Michel; Biros, George; Davatzikos, Christos

2011-01-01

This paper presents an approach for joint segmentation and deformable registration of brain scans of glioma patients to a normal atlas. The proposed method is based on the Expectation Maximization (EM) algorithm that incorporates a glioma growth model for atlas seeding, a process which modifies the normal atlas into one with a tumor and edema. The modified atlas is registered into the patient space and utilized for the posterior probability estimation of various tissue labels. EM iteratively refines the estimates of the registration parameters, the posterior probabilities of tissue labels and the tumor growth model parameters. We have applied this approach to 10 glioma scans acquired with four Magnetic Resonance (MR) modalities (T1, T1-CE, T2 and FLAIR) and validated the result by comparing them to manual segmentations by clinical experts. The resulting segmentations look promising and quantitatively match well with the expert provided ground truth.

Probabilistic DHP adaptive critic for nonlinear stochastic control systems.

PubMed

Herzallah, Randa

2013-06-01

Following the recently developed algorithms for fully probabilistic control design for general dynamic stochastic systems (Herzallah & Káarnáy, 2011; Kárný, 1996), this paper presents the solution to the probabilistic dual heuristic programming (DHP) adaptive critic method (Herzallah & Káarnáy, 2011) and randomized control algorithm for stochastic nonlinear dynamical systems. The purpose of the randomized control input design is to make the joint probability density function of the closed loop system as close as possible to a predetermined ideal joint probability density function. This paper completes the previous work (Herzallah & Káarnáy, 2011; Kárný, 1996) by formulating and solving the fully probabilistic control design problem on the more general case of nonlinear stochastic discrete time systems. A simulated example is used to demonstrate the use of the algorithm and encouraging results have been obtained. Copyright © 2013 Elsevier Ltd. All rights reserved.

Bayesian Finite Mixtures for Nonlinear Modeling of Educational Data.

ERIC Educational Resources Information Center

Tirri, Henry; And Others

A Bayesian approach for finding latent classes in data is discussed. The approach uses finite mixture models to describe the underlying structure in the data and demonstrate that the possibility of using full joint probability models raises interesting new prospects for exploratory data analysis. The concepts and methods discussed are illustrated…

Real-time individual predictions of prostate cancer recurrence using joint models

PubMed Central

Taylor, Jeremy M. G.; Park, Yongseok; Ankerst, Donna P.; Proust-Lima, Cecile; Williams, Scott; Kestin, Larry; Bae, Kyoungwha; Pickles, Tom; Sandler, Howard

2012-01-01

Summary Patients who were previously treated for prostate cancer with radiation therapy are monitored at regular intervals using a laboratory test called Prostate Specific Antigen (PSA). If the value of the PSA test starts to rise, this is an indication that the prostate cancer is more likely to recur, and the patient may wish to initiate new treatments. Such patients could be helped in making medical decisions by an accurate estimate of the probability of recurrence of the cancer in the next few years. In this paper, we describe the methodology for giving the probability of recurrence for a new patient, as implemented on a web-based calculator. The methods use a joint longitudinal survival model. The model is developed on a training dataset of 2,386 patients and tested on a dataset of 846 patients. Bayesian estimation methods are used with one Markov chain Monte Carlo (MCMC) algorithm developed for estimation of the parameters from the training dataset and a second quick MCMC developed for prediction of the risk of recurrence that uses the longitudinal PSA measures from a new patient. PMID:23379600

The relationship between species detection probability and local extinction probability

USGS Publications Warehouse

Alpizar-Jara, R.; Nichols, J.D.; Hines, J.E.; Sauer, J.R.; Pollock, K.H.; Rosenberry, C.S.

2004-01-01

In community-level ecological studies, generally not all species present in sampled areas are detected. Many authors have proposed the use of estimation methods that allow detection probabilities that are < 1 and that are heterogeneous among species. These methods can also be used to estimate community-dynamic parameters such as species local extinction probability and turnover rates (Nichols et al. Ecol Appl 8:1213-1225; Conserv Biol 12:1390-1398). Here, we present an ad hoc approach to estimating community-level vital rates in the presence of joint heterogeneity of detection probabilities and vital rates. The method consists of partitioning the number of species into two groups using the detection frequencies and then estimating vital rates (e.g., local extinction probabilities) for each group. Estimators from each group are combined in a weighted estimator of vital rates that accounts for the effect of heterogeneity. Using data from the North American Breeding Bird Survey, we computed such estimates and tested the hypothesis that detection probabilities and local extinction probabilities were negatively related. Our analyses support the hypothesis that species detection probability covaries negatively with local probability of extinction and turnover rates. A simulation study was conducted to assess the performance of vital parameter estimators as well as other estimators relevant to questions about heterogeneity, such as coefficient of variation of detection probabilities and proportion of species in each group. Both the weighted estimator suggested in this paper and the original unweighted estimator for local extinction probability performed fairly well and provided no basis for preferring one to the other.

Multi-hazard Assessment and Scenario Toolbox (MhAST): A Framework for Analyzing Compounding Effects of Multiple Hazards

NASA Astrophysics Data System (ADS)

Sadegh, M.; Moftakhari, H.; AghaKouchak, A.

2017-12-01

Many natural hazards are driven by multiple forcing variables, and concurrence/consecutive extreme events significantly increases risk of infrastructure/system failure. It is a common practice to use univariate analysis based upon a perceived ruling driver to estimate design quantiles and/or return periods of extreme events. A multivariate analysis, however, permits modeling simultaneous occurrence of multiple forcing variables. In this presentation, we introduce the Multi-hazard Assessment and Scenario Toolbox (MhAST) that comprehensively analyzes marginal and joint probability distributions of natural hazards. MhAST also offers a wide range of scenarios of return period and design levels and their likelihoods. Contribution of this study is four-fold: 1. comprehensive analysis of marginal and joint probability of multiple drivers through 17 continuous distributions and 26 copulas, 2. multiple scenario analysis of concurrent extremes based upon the most likely joint occurrence, one ruling variable, and weighted random sampling of joint occurrences with similar exceedance probabilities, 3. weighted average scenario analysis based on a expected event, and 4. uncertainty analysis of the most likely joint occurrence scenario using a Bayesian framework.

[Endoprostheses in geriatric traumatology].

PubMed

Buecking, B; Eschbach, D; Bliemel, C; Knobe, M; Aigner, R; Ruchholtz, S

2017-01-01

Geriatric traumatology is increasing in importance due to the demographic transition. In cases of fractures close to large joints it is questionable whether primary joint replacement is advantageous compared to joint-preserving internal fixation. The aim of this study was to describe the importance of prosthetic joint replacement in the treatment of geriatric patients suffering from frequent periarticular fractures in comparison to osteosynthetic joint reconstruction and conservative methods. A selective search of the literature was carried out to identify studies and recommendations concerned with primary arthroplasty of fractures in the region of the various joints (hip, shoulder, elbow and knee). The importance of primary arthroplasty in geriatric traumatology differs greatly between the various joints. Implantation of a prosthesis has now become the gold standard for displaced fractures of the femoral neck. In addition, reverse shoulder arthroplasty has become an established alternative option to osteosynthesis in the treatment of complex proximal humeral fractures. Due to a lack of large studies definitive recommendations cannot yet be given for fractures around the elbow and the knee. Nowadays, joint replacement for these fractures is recommended only if reconstruction of the joint surface is not possible. The importance of primary joint replacement for geriatric fractures will probably increase in the future. Further studies with larger patient numbers must be conducted to achieve more confidence in decision making between joint replacement and internal fixation especially for shoulder, elbow and knee joints.

Temporal and spatial characteristics of extreme precipitation events in the Midwest of Jilin Province based on multifractal detrended fluctuation analysis method and copula functions

NASA Astrophysics Data System (ADS)

Guo, Enliang; Zhang, Jiquan; Si, Ha; Dong, Zhenhua; Cao, Tiehua; Lan, Wu

2017-10-01

Environmental changes have brought about significant changes and challenges to water resources and management in the world; these include increasing climate variability, land use change, intensive agriculture, and rapid urbanization and industrial development, especially much more frequency extreme precipitation events. All of which greatly affect water resource and the development of social economy. In this study, we take extreme precipitation events in the Midwest of Jilin Province as an example; daily precipitation data during 1960-2014 are used. The threshold of extreme precipitation events is defined by multifractal detrended fluctuation analysis (MF-DFA) method. Extreme precipitation (EP), extreme precipitation ratio (EPR), and intensity of extreme precipitation (EPI) are selected as the extreme precipitation indicators, and then the Kolmogorov-Smirnov (K-S) test is employed to determine the optimal probability distribution function of extreme precipitation indicators. On this basis, copulas connect nonparametric estimation method and the Akaike Information Criterion (AIC) method is adopted to determine the bivariate copula function. Finally, we analyze the characteristics of single variable extremum and bivariate joint probability distribution of the extreme precipitation events. The results show that the threshold of extreme precipitation events in semi-arid areas is far less than that in subhumid areas. The extreme precipitation frequency shows a significant decline while the extreme precipitation intensity shows a trend of growth; there are significant differences in spatiotemporal of extreme precipitation events. The spatial variation trend of the joint return period gets shorter from the west to the east. The spatial distribution of co-occurrence return period takes on contrary changes and it is longer than the joint return period.

Determining open cluster membership. A Bayesian framework for quantitative member classification

NASA Astrophysics Data System (ADS)

Stott, Jonathan J.

2018-01-01

Aims: My goal is to develop a quantitative algorithm for assessing open cluster membership probabilities. The algorithm is designed to work with single-epoch observations. In its simplest form, only one set of program images and one set of reference images are required. Methods: The algorithm is based on a two-stage joint astrometric and photometric assessment of cluster membership probabilities. The probabilities were computed within a Bayesian framework using any available prior information. Where possible, the algorithm emphasizes simplicity over mathematical sophistication. Results: The algorithm was implemented and tested against three observational fields using published survey data. M 67 and NGC 654 were selected as cluster examples while a third, cluster-free, field was used for the final test data set. The algorithm shows good quantitative agreement with the existing surveys and has a false-positive rate significantly lower than the astrometric or photometric methods used individually.

Applying the Hájek Approach in Formula-Based Variance Estimation. Research Report. ETS RR-17-24

ERIC Educational Resources Information Center

Qian, Jiahe

2017-01-01

The variance formula derived for a two-stage sampling design without replacement employs the joint inclusion probabilities in the first-stage selection of clusters. One of the difficulties encountered in data analysis is the lack of information about such joint inclusion probabilities. One way to solve this issue is by applying Hájek's…

Healthy Eating and Leisure-Time Activity: Cross-Sectional Analysis of that Role of Work Environments in the U.S.

PubMed

Williams, Jessica A R; Arcaya, Mariana; Subramanian, S V

2017-11-01

The aim of this study was to evaluate relationships between work context and two health behaviors, healthy eating and leisure-time physical activity (LTPA), in U.S. adults. Using data from the 2010 National Health Interview Survey (NHIS) and Occupational Information Network (N = 14,863), we estimated a regression model to predict the marginal and joint probabilities of healthy eating and adhering to recommended exercise guidelines. Decision-making freedom was positively related to healthy eating and both behaviors jointly. Higher physical load was associated with a lower marginal probability of LTPA, healthy eating, and both behaviors jointly. Smoke and vapor exposures were negatively related to healthy eating and both behaviors. Chemical exposure was positively related to LTPA and both behaviors. Characteristics associated with marginal probabilities were not always predictive of joint outcomes. On the basis of nationwide occupation-specific evidence, workplace characteristics are important for healthy eating and LTPA.

Independent Component Analysis of Textures

NASA Technical Reports Server (NTRS)

Manduchi, Roberto; Portilla, Javier

2000-01-01

A common method for texture representation is to use the marginal probability densities over the outputs of a set of multi-orientation, multi-scale filters as a description of the texture. We propose a technique, based on Independent Components Analysis, for choosing the set of filters that yield the most informative marginals, meaning that the product over the marginals most closely approximates the joint probability density function of the filter outputs. The algorithm is implemented using a steerable filter space. Experiments involving both texture classification and synthesis show that compared to Principal Components Analysis, ICA provides superior performance for modeling of natural and synthetic textures.

An information diffusion technique to assess integrated hazard risks.

PubMed

Huang, Chongfu; Huang, Yundong

2018-02-01

An integrated risk is a scene in the future associated with some adverse incident caused by multiple hazards. An integrated probability risk is the expected value of disaster. Due to the difficulty of assessing an integrated probability risk with a small sample, weighting methods and copulas are employed to avoid this obstacle. To resolve the problem, in this paper, we develop the information diffusion technique to construct a joint probability distribution and a vulnerability surface. Then, an integrated risk can be directly assessed by using a small sample. A case of an integrated risk caused by flood and earthquake is given to show how the suggested technique is used to assess the integrated risk of annual property loss. Copyright © 2017 Elsevier Inc. All rights reserved.

Diagnostics for Confounding of Time-varying and Other Joint Exposures.

PubMed

Jackson, John W

2016-11-01

The effects of joint exposures (or exposure regimes) include those of adhering to assigned treatment versus placebo in a randomized controlled trial, duration of exposure in a cohort study, interactions between exposures, and direct effects of exposure, among others. Unlike the setting of a single point exposure (e.g., propensity score matching), there are few tools to describe confounding for joint exposures or how well a method resolves it. Investigators need tools that describe confounding in ways that are conceptually grounded and intuitive for those who read, review, and use applied research to guide policy. We revisit the implications of exchangeability conditions that hold in sequentially randomized trials, and the bias structure that motivates the use of g-methods, such as marginal structural models. From these, we develop covariate balance diagnostics for joint exposures that can (1) describe time-varying confounding, (2) assess whether covariates are predicted by prior exposures given their past, the indication for g-methods, and (3) describe residual confounding after inverse probability weighting. For each diagnostic, we present time-specific metrics that encompass a wide class of joint exposures, including regimes of multivariate time-varying exposures in censored data, with multivariate point exposures as a special case. We outline how to estimate these directly or with regression and how to average them over person-time. Using a simulated example, we show how these metrics can be presented graphically. This conceptually grounded framework can potentially aid the transparent design, analysis, and reporting of studies that examine joint exposures. We provide easy-to-use tools to implement it.

Estimation of vegetation cover at subpixel resolution using LANDSAT data

NASA Technical Reports Server (NTRS)

Jasinski, Michael F.; Eagleson, Peter S.

1986-01-01

The present report summarizes the various approaches relevant to estimating canopy cover at subpixel resolution. The approaches are based on physical models of radiative transfer in non-homogeneous canopies and on empirical methods. The effects of vegetation shadows and topography are examined. Simple versions of the model are tested, using the Taos, New Mexico Study Area database. Emphasis has been placed on using relatively simple models requiring only one or two bands. Although most methods require some degree of ground truth, a two-band method is investigated whereby the percent cover can be estimated without ground truth by examining the limits of the data space. Future work is proposed which will incorporate additional surface parameters into the canopy cover algorithm, such as topography, leaf area, or shadows. The method involves deriving a probability density function for the percent canopy cover based on the joint probability density function of the observed radiances.

Joint modelling of longitudinal CEA tumour marker progression and survival data on breast cancer

NASA Astrophysics Data System (ADS)

Borges, Ana; Sousa, Inês; Castro, Luis

2017-06-01

This work proposes the use of Biostatistics methods to study breast cancer in patients of Braga's Hospital Senology Unit, located in Portugal. The primary motivation is to contribute to the understanding of the progression of breast cancer, within the Portuguese population, using a more complex statistical model assumptions than the traditional analysis that take into account a possible existence of a serial correlation structure within a same subject observations. We aim to infer which risk factors aect the survival of Braga's Hospital patients, diagnosed with breast tumour. Whilst analysing risk factors that aect a tumour markers used on the surveillance of disease progression the Carcinoembryonic antigen (CEA). As survival and longitudinal processes may be associated, it is important to model these two processes together. Hence, a joint modelling of these two processes to infer on the association of these was conducted. A data set of 540 patients, along with 50 variables, was collected from medical records of the Hospital. A joint model approach was used to analyse these data. Two dierent joint models were applied to the same data set, with dierent parameterizations which give dierent interpretations to model parameters. These were used by convenience as the ones implemented in R software. Results from the two models were compared. Results from joint models, showed that the longitudinal CEA values were signicantly associated with the survival probability of these patients. A comparison between parameter estimates obtained in this analysis and previous independent survival[4] and longitudinal analysis[5][6], lead us to conclude that independent analysis brings up bias parameter estimates. Hence, an assumption of association between the two processes in a joint model of breast cancer data is necessary. Results indicate that the longitudinal progression of CEA is signicantly associated with the probability of survival of these patients. Hence, an assumption of association between the two processes in a joint model of breast cancer data is necessary.

Birth/birth-death processes and their computable transition probabilities with biological applications.

PubMed

Ho, Lam Si Tung; Xu, Jason; Crawford, Forrest W; Minin, Vladimir N; Suchard, Marc A

2018-03-01

Birth-death processes track the size of a univariate population, but many biological systems involve interaction between populations, necessitating models for two or more populations simultaneously. A lack of efficient methods for evaluating finite-time transition probabilities of bivariate processes, however, has restricted statistical inference in these models. Researchers rely on computationally expensive methods such as matrix exponentiation or Monte Carlo approximation, restricting likelihood-based inference to small systems, or indirect methods such as approximate Bayesian computation. In this paper, we introduce the birth/birth-death process, a tractable bivariate extension of the birth-death process, where rates are allowed to be nonlinear. We develop an efficient algorithm to calculate its transition probabilities using a continued fraction representation of their Laplace transforms. Next, we identify several exemplary models arising in molecular epidemiology, macro-parasite evolution, and infectious disease modeling that fall within this class, and demonstrate advantages of our proposed method over existing approaches to inference in these models. Notably, the ubiquitous stochastic susceptible-infectious-removed (SIR) model falls within this class, and we emphasize that computable transition probabilities newly enable direct inference of parameters in the SIR model. We also propose a very fast method for approximating the transition probabilities under the SIR model via a novel branching process simplification, and compare it to the continued fraction representation method with application to the 17th century plague in Eyam. Although the two methods produce similar maximum a posteriori estimates, the branching process approximation fails to capture the correlation structure in the joint posterior distribution.

On the joint spectral density of bivariate random sequences. Thesis Technical Report No. 21

NASA Technical Reports Server (NTRS)

Aalfs, David D.

1995-01-01

For univariate random sequences, the power spectral density acts like a probability density function of the frequencies present in the sequence. This dissertation extends that concept to bivariate random sequences. For this purpose, a function called the joint spectral density is defined that represents a joint probability weighing of the frequency content of pairs of random sequences. Given a pair of random sequences, the joint spectral density is not uniquely determined in the absence of any constraints. Two approaches to constraining the sequences are suggested: (1) assume the sequences are the margins of some stationary random field, (2) assume the sequences conform to a particular model that is linked to the joint spectral density. For both approaches, the properties of the resulting sequences are investigated in some detail, and simulation is used to corroborate theoretical results. It is concluded that under either of these two constraints, the joint spectral density can be computed from the non-stationary cross-correlation.

Diffusion welding of MA 6000 and a conventional nickel-base superalloy

NASA Technical Reports Server (NTRS)

Moore, T. J.; Glasgow, T. K.

1985-01-01

A feasibility study of diffusion welding the oxide dispersion strengthened (ODS) alloy MA 6000 to itself and to conventional Ni-base superalloy Udimet 700 was conducted. Butt joints between MA 6000 pieces and lap joints between Udimet 700 and the ODS alloy were produced by hot pressing for 1.25 hr at temperatures ranging from 1000 to 1200 C (1832-2192 F) in vacuum. Following pressing, all weldments were heat treated and machined into mechanical property test specimens. While three different combinations of recrystallized and unrecrystallized MA 6000 butt joints were produced, the unrecrystallized to unrecrystallized joint was most successful as determined by mechanical properties and microstructural examination. Failure to weld the recrystallized material probably related to a lack of adequate deformation at the weld interface. While recrystallized MA 6000 could be diffusion welded to Udimet 700 in places, complete welding over the entire lap joint was not achieved, again due to the lack of sufficient deformation at the faying surfaces. Several methods are proposed to promote the intimate contact necessary for diffusion welding MA 6000 to itself and to superalloys.

Serial Spike Time Correlations Affect Probability Distribution of Joint Spike Events.

PubMed

Shahi, Mina; van Vreeswijk, Carl; Pipa, Gordon

2016-01-01

Detecting the existence of temporally coordinated spiking activity, and its role in information processing in the cortex, has remained a major challenge for neuroscience research. Different methods and approaches have been suggested to test whether the observed synchronized events are significantly different from those expected by chance. To analyze the simultaneous spike trains for precise spike correlation, these methods typically model the spike trains as a Poisson process implying that the generation of each spike is independent of all the other spikes. However, studies have shown that neural spike trains exhibit dependence among spike sequences, such as the absolute and relative refractory periods which govern the spike probability of the oncoming action potential based on the time of the last spike, or the bursting behavior, which is characterized by short epochs of rapid action potentials, followed by longer episodes of silence. Here we investigate non-renewal processes with the inter-spike interval distribution model that incorporates spike-history dependence of individual neurons. For that, we use the Monte Carlo method to estimate the full shape of the coincidence count distribution and to generate false positives for coincidence detection. The results show that compared to the distributions based on homogeneous Poisson processes, and also non-Poisson processes, the width of the distribution of joint spike events changes. Non-renewal processes can lead to both heavy tailed or narrow coincidence distribution. We conclude that small differences in the exact autostructure of the point process can cause large differences in the width of a coincidence distribution. Therefore, manipulations of the autostructure for the estimation of significance of joint spike events seem to be inadequate.

Serial Spike Time Correlations Affect Probability Distribution of Joint Spike Events

PubMed Central

Shahi, Mina; van Vreeswijk, Carl; Pipa, Gordon

2016-01-01

Detecting the existence of temporally coordinated spiking activity, and its role in information processing in the cortex, has remained a major challenge for neuroscience research. Different methods and approaches have been suggested to test whether the observed synchronized events are significantly different from those expected by chance. To analyze the simultaneous spike trains for precise spike correlation, these methods typically model the spike trains as a Poisson process implying that the generation of each spike is independent of all the other spikes. However, studies have shown that neural spike trains exhibit dependence among spike sequences, such as the absolute and relative refractory periods which govern the spike probability of the oncoming action potential based on the time of the last spike, or the bursting behavior, which is characterized by short epochs of rapid action potentials, followed by longer episodes of silence. Here we investigate non-renewal processes with the inter-spike interval distribution model that incorporates spike-history dependence of individual neurons. For that, we use the Monte Carlo method to estimate the full shape of the coincidence count distribution and to generate false positives for coincidence detection. The results show that compared to the distributions based on homogeneous Poisson processes, and also non-Poisson processes, the width of the distribution of joint spike events changes. Non-renewal processes can lead to both heavy tailed or narrow coincidence distribution. We conclude that small differences in the exact autostructure of the point process can cause large differences in the width of a coincidence distribution. Therefore, manipulations of the autostructure for the estimation of significance of joint spike events seem to be inadequate. PMID:28066225

Positive phase space distributions and uncertainty relations

NASA Technical Reports Server (NTRS)

Kruger, Jan

1993-01-01

In contrast to a widespread belief, Wigner's theorem allows the construction of true joint probabilities in phase space for distributions describing the object system as well as for distributions depending on the measurement apparatus. The fundamental role of Heisenberg's uncertainty relations in Schroedinger form (including correlations) is pointed out for these two possible interpretations of joint probability distributions. Hence, in order that a multivariate normal probability distribution in phase space may correspond to a Wigner distribution of a pure or a mixed state, it is necessary and sufficient that Heisenberg's uncertainty relation in Schroedinger form should be satisfied.

Joint model-based clustering of nonlinear longitudinal trajectories and associated time-to-event data analysis, linked by latent class membership: with application to AIDS clinical studies.

PubMed

Huang, Yangxin; Lu, Xiaosun; Chen, Jiaqing; Liang, Juan; Zangmeister, Miriam

2017-10-27

Longitudinal and time-to-event data are often observed together. Finite mixture models are currently used to analyze nonlinear heterogeneous longitudinal data, which, by releasing the homogeneity restriction of nonlinear mixed-effects (NLME) models, can cluster individuals into one of the pre-specified classes with class membership probabilities. This clustering may have clinical significance, and be associated with clinically important time-to-event data. This article develops a joint modeling approach to a finite mixture of NLME models for longitudinal data and proportional hazard Cox model for time-to-event data, linked by individual latent class indicators, under a Bayesian framework. The proposed joint models and method are applied to a real AIDS clinical trial data set, followed by simulation studies to assess the performance of the proposed joint model and a naive two-step model, in which finite mixture model and Cox model are fitted separately.

Quasi-Bell inequalities from symmetrized products of noncommuting qubit observables

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gamel, Omar E.; Fleming, Graham R.

Noncommuting observables cannot be simultaneously measured; however, under local hidden variable models, they must simultaneously hold premeasurement values, implying the existence of a joint probability distribution. We study the joint distributions of noncommuting observables on qubits, with possible criteria of positivity and the Fréchet bounds limiting the joint probabilities, concluding that the latter may be negative. We use symmetrization, justified heuristically and then more carefully via the Moyal characteristic function, to find the quantum operator corresponding to the product of noncommuting observables. This is then used to construct Quasi-Bell inequalities, Bell inequalities containing products of noncommuting observables, on two qubits.more » These inequalities place limits on the local hidden variable models that define joint probabilities for noncommuting observables. We also found that the Quasi-Bell inequalities have a quantum to classical violation as high as 3/2 on two qubit, higher than conventional Bell inequalities. Our result demonstrates the theoretical importance of noncommutativity in the nonlocality of quantum mechanics and provides an insightful generalization of Bell inequalities.« less

Quasi-Bell inequalities from symmetrized products of noncommuting qubit observables

DOE PAGES

Gamel, Omar E.; Fleming, Graham R.

2017-05-01

Noncommuting observables cannot be simultaneously measured; however, under local hidden variable models, they must simultaneously hold premeasurement values, implying the existence of a joint probability distribution. We study the joint distributions of noncommuting observables on qubits, with possible criteria of positivity and the Fréchet bounds limiting the joint probabilities, concluding that the latter may be negative. We use symmetrization, justified heuristically and then more carefully via the Moyal characteristic function, to find the quantum operator corresponding to the product of noncommuting observables. This is then used to construct Quasi-Bell inequalities, Bell inequalities containing products of noncommuting observables, on two qubits.more » These inequalities place limits on the local hidden variable models that define joint probabilities for noncommuting observables. We also found that the Quasi-Bell inequalities have a quantum to classical violation as high as 3/2 on two qubit, higher than conventional Bell inequalities. Our result demonstrates the theoretical importance of noncommutativity in the nonlocality of quantum mechanics and provides an insightful generalization of Bell inequalities.« less

Observation of non-classical correlations in sequential measurements of photon polarization

NASA Astrophysics Data System (ADS)

Suzuki, Yutaro; Iinuma, Masataka; Hofmann, Holger F.

2016-10-01

A sequential measurement of two non-commuting quantum observables results in a joint probability distribution for all output combinations that can be explained in terms of an initial joint quasi-probability of the non-commuting observables, modified by the resolution errors and back-action of the initial measurement. Here, we show that the error statistics of a sequential measurement of photon polarization performed at different measurement strengths can be described consistently by an imaginary correlation between the statistics of resolution and back-action. The experimental setup was designed to realize variable strength measurements with well-controlled imaginary correlation between the statistical errors caused by the initial measurement of diagonal polarizations, followed by a precise measurement of the horizontal/vertical polarization. We perform the experimental characterization of an elliptically polarized input state and show that the same complex joint probability distribution is obtained at any measurement strength.

An analytical approach to gravitational lensing by an ensemble of axisymmetric lenses

NASA Technical Reports Server (NTRS)

Lee, Man Hoi; Spergel, David N.

1990-01-01

The problem of gravitational lensing by an ensemble of identical axisymmetric lenses randomly distributed on a single lens plane is considered and a formal expression is derived for the joint probability density of finding shear and convergence at a random point on the plane. The amplification probability for a source can be accurately estimated from the distribution in shear and convergence. This method is applied to two cases: lensing by an ensemble of point masses and by an ensemble of objects with Gaussian surface mass density. There is no convergence for point masses whereas shear is negligible for wide Gaussian lenses.

Stochastic methods for analysis of power flow in electric networks

NASA Astrophysics Data System (ADS)

1982-09-01

The modeling and effects of probabilistic behavior on steady state power system operation were analyzed. A solution to the steady state network flow equations which adhere both to Kirchoff's Laws and probabilistic laws, using either combinatorial or functional approximation techniques was obtained. The development of sound techniques for producing meaningful data to serve as input is examined. Electric demand modeling, equipment failure analysis, and algorithm development are investigated. Two major development areas are described: a decomposition of stochastic processes which gives stationarity, ergodicity, and even normality; and a powerful surrogate probability approach using proportions of time which allows the calculation of joint events from one dimensional probability spaces.

Peelle's pertinent puzzle using the Monte Carlo technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kawano, Toshihiko; Talou, Patrick; Burr, Thomas

2009-01-01

We try to understand the long-standing problem of the Peelle's Pertinent Puzzle (PPP) using the Monte Carlo technique. We allow the probability density functions to be any kind of form to assume the impact of distribution, and obtain the least-squares solution directly from numerical simulations. We found that the standard least squares method gives the correct answer if a weighting function is properly provided. Results from numerical simulations show that the correct answer of PPP is 1.1 {+-} 0.25 if the common error is multiplicative. The thought-provoking answer of 0.88 is also correct, if the common error is additive, andmore » if the error is proportional to the measured values. The least squares method correctly gives us the most probable case, where the additive component has a negative value. Finally, the standard method fails for PPP due to a distorted (non Gaussian) joint distribution.« less

Bivariate normal, conditional and rectangular probabilities: A computer program with applications

NASA Technical Reports Server (NTRS)

Swaroop, R.; Brownlow, J. D.; Ashwworth, G. R.; Winter, W. R.

1980-01-01

Some results for the bivariate normal distribution analysis are presented. Computer programs for conditional normal probabilities, marginal probabilities, as well as joint probabilities for rectangular regions are given: routines for computing fractile points and distribution functions are also presented. Some examples from a closed circuit television experiment are included.

Joint distribution of temperature and precipitation in the Mediterranean, using the Copula method

NASA Astrophysics Data System (ADS)

Lazoglou, Georgia; Anagnostopoulou, Christina

2018-03-01

This study analyses the temperature and precipitation dependence among stations in the Mediterranean. The first station group is located in the eastern Mediterranean (EM) and includes two stations, Athens and Thessaloniki, while the western (WM) one includes Malaga and Barcelona. The data was organized in two time periods, the hot-dry period and the cold-wet one, composed of 5 months, respectively. The analysis is based on a new statistical technique in climatology: the Copula method. Firstly, the calculation of the Kendall tau correlation index showed that temperatures among stations are dependant during both time periods whereas precipitation presents dependency only between the stations located in EM or WM and only during the cold-wet period. Accordingly, the marginal distributions were calculated for each studied station, as they are further used by the copula method. Finally, several copula families, both Archimedean and Elliptical, were tested in order to choose the most appropriate one to model the relation of the studied data sets. Consequently, this study achieves to model the dependence of the main climate parameters (temperature and precipitation) with the Copula method. The Frank copula was identified as the best family to describe the joint distribution of temperature, for the majority of station groups. For precipitation, the best copula families are BB1 and Survival Gumbel. Using the probability distribution diagrams, the probability of a combination of temperature and precipitation values between stations is estimated.

Fully probabilistic control for stochastic nonlinear control systems with input dependent noise.

PubMed

Herzallah, Randa

2015-03-01

Robust controllers for nonlinear stochastic systems with functional uncertainties can be consistently designed using probabilistic control methods. In this paper a generalised probabilistic controller design for the minimisation of the Kullback-Leibler divergence between the actual joint probability density function (pdf) of the closed loop control system, and an ideal joint pdf is presented emphasising how the uncertainty can be systematically incorporated in the absence of reliable systems models. To achieve this objective all probabilistic models of the system are estimated from process data using mixture density networks (MDNs) where all the parameters of the estimated pdfs are taken to be state and control input dependent. Based on this dependency of the density parameters on the input values, explicit formulations to the construction of optimal generalised probabilistic controllers are obtained through the techniques of dynamic programming and adaptive critic methods. Using the proposed generalised probabilistic controller, the conditional joint pdfs can be made to follow the ideal ones. A simulation example is used to demonstrate the implementation of the algorithm and encouraging results are obtained. Copyright © 2014 Elsevier Ltd. All rights reserved.

Experimental investigation of the intensity fluctuation joint probability and conditional distributions of the twin-beam quantum state.

PubMed

Zhang, Yun; Kasai, Katsuyuki; Watanabe, Masayoshi

2003-01-13

We give the intensity fluctuation joint probability of the twin-beam quantum state, which was generated with an optical parametric oscillator operating above threshold. Then we present what to our knowledge is the first measurement of the intensity fluctuation conditional probability distributions of twin beams. The measured inference variance of twin beams 0.62+/-0.02, which is less than the standard quantum limit of unity, indicates inference with a precision better than that of separable states. The measured photocurrent variance exhibits a quantum correlation of as much as -4.9+/-0.2 dB between the signal and the idler.

Joint Processing of Envelope Alignment and Phase Compensation for Isar Imaging

NASA Astrophysics Data System (ADS)

Chen, Tao; Jin, Guanghu; Dong, Zhen

2018-04-01

Range envelope alignment and phase compensation are spilt into two isolated parts in the classical methods of translational motion compensation in Inverse Synthetic Aperture Radar (ISAR) imaging. In classic method of the rotating object imaging, the two reference points of the envelope alignment and the Phase Difference (PD) estimation are probably not the same point, making it difficult to uncouple the coupling term by conducting the correction of Migration Through Resolution Cell (MTRC). In this paper, an improved approach of joint processing which chooses certain scattering point as the sole reference point is proposed to perform with utilizing the Prominent Point Processing (PPP) method. With this end in view, we firstly get the initial image using classical methods from which a certain scattering point can be chose. The envelope alignment and phase compensation using the selected scattering point as the same reference point are subsequently conducted. The keystone transform is thus smoothly applied to further improve imaging quality. Both simulation experiments and real data processing are provided to demonstrate the performance of the proposed method compared with classical method.

Non-destructive and non-invasive observation of friction and wear of human joints and of fracture initiation by acoustic emission.

PubMed

Schwalbe, H J; Bamfaste, G; Franke, R P

1999-01-01

Quality control in orthopaedic diagnostics according to DIN EN ISO 9000ff requires methods of non-destructive process control, which do not harm the patient by radiation or by invasive examinations. To obtain an improvement in health economy, quality-controlled and non-destructive measurements have to be introduced into the diagnostics and therapy of human joints and bones. A non-invasive evaluation of the state of wear of human joints and of the cracking tendency of bones is, as of today's point of knowledge, not established. The analysis of acoustic emission signals allows the prediction of bone rupture far below the fracture load. The evaluation of dry and wet bone samples revealed that it is possible to conclude from crack initiation to the bone strength and thus to predict the probability of bone rupture.

Ceramic joints

DOEpatents

Miller, Bradley J.; Patten, Jr., Donald O.

1991-01-01

Butt joints between materials having different coefficients of thermal expansion are prepared having a reduced probability of failure of stress facture. This is accomplished by narrowing/tapering the material having the lower coefficient of thermal expansion in a direction away from the joint interface and not joining the narrow-tapered surface to the material having the higher coefficient of thermal expansion.

Stochastic optimal operation of reservoirs based on copula functions

NASA Astrophysics Data System (ADS)

Lei, Xiao-hui; Tan, Qiao-feng; Wang, Xu; Wang, Hao; Wen, Xin; Wang, Chao; Zhang, Jing-wen

2018-02-01

Stochastic dynamic programming (SDP) has been widely used to derive operating policies for reservoirs considering streamflow uncertainties. In SDP, there is a need to calculate the transition probability matrix more accurately and efficiently in order to improve the economic benefit of reservoir operation. In this study, we proposed a stochastic optimization model for hydropower generation reservoirs, in which 1) the transition probability matrix was calculated based on copula functions; and 2) the value function of the last period was calculated by stepwise iteration. Firstly, the marginal distribution of stochastic inflow in each period was built and the joint distributions of adjacent periods were obtained using the three members of the Archimedean copulas, based on which the conditional probability formula was derived. Then, the value in the last period was calculated by a simple recursive equation with the proposed stepwise iteration method and the value function was fitted with a linear regression model. These improvements were incorporated into the classic SDP and applied to the case study in Ertan reservoir, China. The results show that the transition probability matrix can be more easily and accurately obtained by the proposed copula function based method than conventional methods based on the observed or synthetic streamflow series, and the reservoir operation benefit can also be increased.

Comparison of dynamic treatment regimes via inverse probability weighting.

PubMed

Hernán, Miguel A; Lanoy, Emilie; Costagliola, Dominique; Robins, James M

2006-03-01

Appropriate analysis of observational data is our best chance to obtain answers to many questions that involve dynamic treatment regimes. This paper describes a simple method to compare dynamic treatment regimes by artificially censoring subjects and then using inverse probability weighting (IPW) to adjust for any selection bias introduced by the artificial censoring. The basic strategy can be summarized in four steps: 1) define two regimes of interest, 2) artificially censor individuals when they stop following one of the regimes of interest, 3) estimate inverse probability weights to adjust for the potential selection bias introduced by censoring in the previous step, 4) compare the survival of the uncensored individuals under each regime of interest by fitting an inverse probability weighted Cox proportional hazards model with the dichotomous regime indicator and the baseline confounders as covariates. In the absence of model misspecification, the method is valid provided data are available on all time-varying and baseline joint predictors of survival and regime discontinuation. We present an application of the method to compare the AIDS-free survival under two dynamic treatment regimes in a large prospective study of HIV-infected patients. The paper concludes by discussing the relative advantages and disadvantages of censoring/IPW versus g-estimation of nested structural models to compare dynamic regimes.

Rock Slide Risk Assessment: A Semi-Quantitative Approach

NASA Astrophysics Data System (ADS)

Duzgun, H. S. B.

2009-04-01

Rock slides can be better managed by systematic risk assessments. Any risk assessment methodology for rock slides involves identification of rock slide risk components, which are hazard, elements at risk and vulnerability. For a quantitative/semi-quantitative risk assessment for rock slides, a mathematical value the risk has to be computed and evaluated. The quantitative evaluation of risk for rock slides enables comparison of the computed risk with the risk of other natural and/or human-made hazards and providing better decision support and easier communication for the decision makers. A quantitative/semi-quantitative risk assessment procedure involves: Danger Identification, Hazard Assessment, Elements at Risk Identification, Vulnerability Assessment, Risk computation, Risk Evaluation. On the other hand, the steps of this procedure require adaptation of existing or development of new implementation methods depending on the type of landslide, data availability, investigation scale and nature of consequences. In study, a generic semi-quantitative risk assessment (SQRA) procedure for rock slides is proposed. The procedure has five consecutive stages: Data collection and analyses, hazard assessment, analyses of elements at risk and vulnerability and risk assessment. The implementation of the procedure for a single rock slide case is illustrated for a rock slope in Norway. Rock slides from mountain Ramnefjell to lake Loen are considered to be one of the major geohazards in Norway. Lake Loen is located in the inner part of Nordfjord in Western Norway. Ramnefjell Mountain is heavily jointed leading to formation of vertical rock slices with height between 400-450 m and width between 7-10 m. These slices threaten the settlements around Loen Valley and tourists visiting the fjord during summer season, as the released slides have potential of creating tsunami. In the past, several rock slides had been recorded from the Mountain Ramnefjell between 1905 and 1950. Among them, four of the slides caused formation of tsunami waves which washed up to 74 m above the lake level. Two of the slides resulted in many fatalities in the inner part of the Loen Valley as well as great damages. There are three predominant joint structures in Ramnefjell Mountain, which controls failure and the geometry of the slides. The first joint set is a foliation plane striking northeast-southwest and dipping 35˚ -40˚ to the east-southeast. The second and the third joint sets are almost perpendicular and parallel to the mountain side and scarp, respectively. These three joint sets form slices of rock columns with width ranging between 7-10 m and height of 400-450 m. It is stated that the joints in set II are opened between 1-2 m, which may bring about collection of water during heavy rainfall or snow melt causing the slices to be pressed out. It is estimated that water in the vertical joints both reduces the shear strength of sliding plane and causes reduction of normal stress on the sliding plane due to formation of uplift force. Hence rock slides in Ramnefjell mountain occur in plane failure mode. The quantitative evaluation of rock slide risk requires probabilistic analysis of rock slope stability and identification of consequences if the rock slide occurs. In this study failure probability of a rock slice is evaluated by first-order reliability method (FORM). Then in order to use the calculated probability of failure value (Pf) in risk analyses, it is required to associate this Pf with frequency based probabilities (i.ePf / year) since the computed failure probabilities is a measure of hazard and not a measure of risk unless they are associated with the consequences of the failure. This can be done by either considering the time dependent behavior of the basic variables in the probabilistic models or associating the computed Pf with frequency of the failures in the region. In this study, the frequency of previous rock slides in the previous century in Remnefjell is used for evaluation of frequency based probability to be used in risk assessment. The major consequence of a rock slide is generation of a tsunami in the lake Loen, causing inundation of residential areas around the lake. Risk is assessed by adapting damage probability matrix approach, which is originally developed for risk assessment for buildings in case of earthquake.

Large-scale-system effectiveness analysis. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Patton, A.D.; Ayoub, A.K.; Foster, J.W.

1979-11-01

Objective of the research project has been the investigation and development of methods for calculating system reliability indices which have absolute, and measurable, significance to consumers. Such indices are a necessary prerequisite to any scheme for system optimization which includes the economic consequences of consumer service interruptions. A further area of investigation has been joint consideration of generation and transmission in reliability studies. Methods for finding or estimating the probability distributions of some measures of reliability performance have been developed. The application of modern Monte Carlo simulation methods to compute reliability indices in generating systems has been studied.

Full statistical mode reconstruction of a light field via a photon-number-resolved measurement

NASA Astrophysics Data System (ADS)

Burenkov, I. A.; Sharma, A. K.; Gerrits, T.; Harder, G.; Bartley, T. J.; Silberhorn, C.; Goldschmidt, E. A.; Polyakov, S. V.

2017-05-01

We present a method to reconstruct the complete statistical mode structure and optical losses of multimode conjugated optical fields using an experimentally measured joint photon-number probability distribution. We demonstrate that this method evaluates classical and nonclassical properties using a single measurement technique and is well suited for quantum mesoscopic state characterization. We obtain a nearly perfect reconstruction of a field comprised of up to ten modes based on a minimal set of assumptions. To show the utility of this method, we use it to reconstruct the mode structure of an unknown bright parametric down-conversion source.

Analysis of capture-recapture models with individual covariates using data augmentation

USGS Publications Warehouse

Royle, J. Andrew

2009-01-01

I consider the analysis of capture-recapture models with individual covariates that influence detection probability. Bayesian analysis of the joint likelihood is carried out using a flexible data augmentation scheme that facilitates analysis by Markov chain Monte Carlo methods, and a simple and straightforward implementation in freely available software. This approach is applied to a study of meadow voles (Microtus pennsylvanicus) in which auxiliary data on a continuous covariate (body mass) are recorded, and it is thought that detection probability is related to body mass. In a second example, the model is applied to an aerial waterfowl survey in which a double-observer protocol is used. The fundamental unit of observation is the cluster of individual birds, and the size of the cluster (a discrete covariate) is used as a covariate on detection probability.

A Novel Wireless Power Transfer-Based Weighed Clustering Cooperative Spectrum Sensing Method for Cognitive Sensor Networks.

PubMed

Liu, Xin

2015-10-30

In a cognitive sensor network (CSN), the wastage of sensing time and energy is a challenge to cooperative spectrum sensing, when the number of cooperative cognitive nodes (CNs) becomes very large. In this paper, a novel wireless power transfer (WPT)-based weighed clustering cooperative spectrum sensing model is proposed, which divides all the CNs into several clusters, and then selects the most favorable CNs as the cluster heads and allows the common CNs to transfer the received radio frequency (RF) energy of the primary node (PN) to the cluster heads, in order to supply the electrical energy needed for sensing and cooperation. A joint resource optimization is formulated to maximize the spectrum access probability of the CSN, through jointly allocating sensing time and clustering number. According to the resource optimization results, a clustering algorithm is proposed. The simulation results have shown that compared to the traditional model, the cluster heads of the proposed model can achieve more transmission power and there exists optimal sensing time and clustering number to maximize the spectrum access probability.

On the apparent insignificance of the randomness of flexible joints on large space truss dynamics

NASA Technical Reports Server (NTRS)

Koch, R. M.; Klosner, J. M.

1993-01-01

Deployable periodic large space structures have been shown to exhibit high dynamic sensitivity to period-breaking imperfections and uncertainties. These can be brought on by manufacturing or assembly errors, structural imperfections, as well as nonlinear and/or nonconservative joint behavior. In addition, the necessity of precise pointing and position capability can require the consideration of these usually negligible and unknown parametric uncertainties and their effect on the overall dynamic response of large space structures. This work describes the use of a new design approach for the global dynamic solution of beam-like periodic space structures possessing parametric uncertainties. Specifically, the effect of random flexible joints on the free vibrations of simply-supported periodic large space trusses is considered. The formulation is a hybrid approach in terms of an extended Timoshenko beam continuum model, Monte Carlo simulation scheme, and first-order perturbation methods. The mean and mean-square response statistics for a variety of free random vibration problems are derived for various input random joint stiffness probability distributions. The results of this effort show that, although joint flexibility has a substantial effect on the modal dynamic response of periodic large space trusses, the effect of any reasonable uncertainty or randomness associated with these joint flexibilities is insignificant.

Improving the accurate assessment of a layered shear-wave velocity model using joint inversion of the effective Rayleigh wave and Love wave dispersion curves

NASA Astrophysics Data System (ADS)

Yin, X.; Xia, J.; Xu, H.

2016-12-01

Rayleigh and Love waves are two types of surface waves that travel along a free surface.Based on the assumption of horizontal layered homogenous media, Rayleigh-wave phase velocity can be defined as a function of frequency and four groups of earth parameters: P-wave velocity, SV-wave velocity, density and thickness of each layer. Unlike Rayleigh waves, Love-wave phase velocities of a layered homogenous earth model could be calculated using frequency and three groups of earth properties: SH-wave velocity, density, and thickness of each layer. Because the dispersion of Love waves is independent of P-wave velocities, Love-wave dispersion curves are much simpler than Rayleigh wave. The research of joint inversion methods of Rayleigh and Love dispersion curves is necessary. (1) This dissertation adopts the combinations of theoretical analysis and practical applications. In both lateral homogenous media and radial anisotropic media, joint inversion approaches of Rayleigh and Love waves are proposed to improve the accuracy of S-wave velocities.A 10% random white noise and a 20% random white noise are added to the synthetic dispersion curves to check out anti-noise ability of the proposed joint inversion method.Considering the influences of the anomalous layer, Rayleigh and Love waves are insensitive to those layers beneath the high-velocity layer or low-velocity layer and the high-velocity layer itself. Low sensitivities will give rise to high degree of uncertainties of the inverted S-wave velocities of these layers. Considering that sensitivity peaks of Rayleigh and Love waves separate at different frequency ranges, the theoretical analyses have demonstrated that joint inversion of these two types of waves would probably ameliorate the inverted model.The lack of surface-wave (Rayleigh or Love waves) dispersion data may lead to inaccuracy S-wave velocities through the single inversion of Rayleigh or Love waves, so this dissertation presents the joint inversion method of Rayleigh and Love waves which will improve the accuracy of S-wave velocities. Finally, a real-world example is applied to verify the accuracy and stability of the proposed joint inversion method. Keywords: Rayleigh wave; Love wave; Sensitivity analysis; Joint inversion method.

New color-based tracking algorithm for joints of the upper extremities

NASA Astrophysics Data System (ADS)

Wu, Xiangping; Chow, Daniel H. K.; Zheng, Xiaoxiang

2007-11-01

To track the joints of the upper limb of stroke sufferers for rehabilitation assessment, a new tracking algorithm which utilizes a developed color-based particle filter and a novel strategy for handling occlusions is proposed in this paper. Objects are represented by their color histogram models and particle filter is introduced to track the objects within a probability framework. Kalman filter, as a local optimizer, is integrated into the sampling stage of the particle filter that steers samples to a region with high likelihood and therefore fewer samples is required. A color clustering method and anatomic constraints are used in dealing with occlusion problem. Compared with the general basic particle filtering method, the experimental results show that the new algorithm has reduced the number of samples and hence the computational consumption, and has achieved better abilities of handling complete occlusion over a few frames.

Conditional maximum-entropy method for selecting prior distributions in Bayesian statistics

NASA Astrophysics Data System (ADS)

Abe, Sumiyoshi

2014-11-01

The conditional maximum-entropy method (abbreviated here as C-MaxEnt) is formulated for selecting prior probability distributions in Bayesian statistics for parameter estimation. This method is inspired by a statistical-mechanical approach to systems governed by dynamics with largely separated time scales and is based on three key concepts: conjugate pairs of variables, dimensionless integration measures with coarse-graining factors and partial maximization of the joint entropy. The method enables one to calculate a prior purely from a likelihood in a simple way. It is shown, in particular, how it not only yields Jeffreys's rules but also reveals new structures hidden behind them.

An estimation method of the direct benefit of a waterlogging control project applicable to the changing environment

NASA Astrophysics Data System (ADS)

Zengmei, L.; Guanghua, Q.; Zishen, C.

2015-05-01

The direct benefit of a waterlogging control project is reflected by the reduction or avoidance of waterlogging loss. Before and after the construction of a waterlogging control project, the disaster-inducing environment in the waterlogging-prone zone is generally different. In addition, the category, quantity and spatial distribution of the disaster-bearing bodies are also changed more or less. Therefore, under the changing environment, the direct benefit of a waterlogging control project should be the reduction of waterlogging losses compared to conditions with no control project. Moreover, the waterlogging losses with or without the project should be the mathematical expectations of the waterlogging losses when rainstorms of all frequencies meet various water levels in the drainage-accepting zone. So an estimation model of the direct benefit of waterlogging control is proposed. Firstly, on the basis of a Copula function, the joint distribution of the rainstorms and the water levels are established, so as to obtain their joint probability density function. Secondly, according to the two-dimensional joint probability density distribution, the dimensional domain of integration is determined, which is then divided into small domains so as to calculate the probability for each of the small domains and the difference between the average waterlogging loss with and without a waterlogging control project, called the regional benefit of waterlogging control project, under the condition that rainstorms in the waterlogging-prone zone meet the water level in the drainage-accepting zone. Finally, it calculates the weighted mean of the project benefit of all small domains, with probability as the weight, and gets the benefit of the waterlogging control project. Taking the estimation of benefit of a waterlogging control project in Yangshan County, Guangdong Province, as an example, the paper briefly explains the procedures in waterlogging control project benefit estimation. The results show that the waterlogging control benefit estimation model constructed is applicable to the changing conditions that occur in both the disaster-inducing environment of the waterlogging-prone zone and disaster-bearing bodies, considering all conditions when rainstorms of all frequencies meet different water levels in the drainage-accepting zone. Thus, the estimation method of waterlogging control benefit can reflect the actual situation more objectively, and offer a scientific basis for rational decision-making for waterlogging control projects.

Accounting for tagging-to-harvest mortality in a Brownie tag-recovery model by incorporating radio-telemetry data.

PubMed

Buderman, Frances E; Diefenbach, Duane R; Casalena, Mary Jo; Rosenberry, Christopher S; Wallingford, Bret D

2014-04-01

The Brownie tag-recovery model is useful for estimating harvest rates but assumes all tagged individuals survive to the first hunting season; otherwise, mortality between time of tagging and the hunting season will cause the Brownie estimator to be negatively biased. Alternatively, fitting animals with radio transmitters can be used to accurately estimate harvest rate but may be more costly. We developed a joint model to estimate harvest and annual survival rates that combines known-fate data from animals fitted with transmitters to estimate the probability of surviving the period from capture to the first hunting season, and data from reward-tagged animals in a Brownie tag-recovery model. We evaluated bias and precision of the joint estimator, and how to optimally allocate effort between animals fitted with radio transmitters and inexpensive ear tags or leg bands. Tagging-to-harvest survival rates from >20 individuals with radio transmitters combined with 50-100 reward tags resulted in an unbiased and precise estimator of harvest rates. In addition, the joint model can test whether transmitters affect an individual's probability of being harvested. We illustrate application of the model using data from wild turkey, Meleagris gallapavo, to estimate harvest rates, and data from white-tailed deer, Odocoileus virginianus, to evaluate whether the presence of a visible radio transmitter is related to the probability of a deer being harvested. The joint known-fate tag-recovery model eliminates the requirement to capture and mark animals immediately prior to the hunting season to obtain accurate and precise estimates of harvest rate. In addition, the joint model can assess whether marking animals with radio transmitters affects the individual's probability of being harvested, caused by hunter selectivity or changes in a marked animal's behavior.

Synchrony in Joint Action Is Directed by Each Participant’s Motor Control System

PubMed Central

Noy, Lior; Weiser, Netta; Friedman, Jason

2017-01-01

In this work, we ask how the probability of achieving synchrony in joint action is affected by the choice of motion parameters of each individual. We use the mirror game paradigm to study how changes in leader’s motion parameters, specifically frequency and peak velocity, affect the probability of entering the state of co-confidence (CC) motion: a dyadic state of synchronized, smooth and co-predictive motions. In order to systematically study this question, we used a one-person version of the mirror game, where the participant mirrored piece-wise rhythmic movements produced by a computer on a graphics tablet. We systematically varied the frequency and peak velocity of the movements to determine how these parameters affect the likelihood of synchronized joint action. To assess synchrony in the mirror game we used the previously developed marker of co-confident (CC) motions: smooth, jitter-less and synchronized motions indicative of co-predicative control. We found that when mirroring movements with low frequencies (i.e., long duration movements), the participants never showed CC, and as the frequency of the stimuli increased, the probability of observing CC also increased. This finding is discussed in the framework of motor control studies showing an upper limit on the duration of smooth motion. We confirmed the relationship between motion parameters and the probability to perform CC with three sets of data of open-ended two-player mirror games. These findings demonstrate that when performing movements together, there are optimal movement frequencies to use in order to maximize the possibility of entering a state of synchronized joint action. It also shows that the ability to perform synchronized joint action is constrained by the properties of our motor control systems. PMID:28443047

Accounting for tagging-to-harvest mortality in a Brownie tag-recovery model by incorporating radio-telemetry data

USGS Publications Warehouse

Buderman, Frances E.; Diefenbach, Duane R.; Casalena, Mary Jo; Rosenberry, Christopher S.; Wallingford, Bret D.

2014-01-01

The Brownie tag-recovery model is useful for estimating harvest rates but assumes all tagged individuals survive to the first hunting season; otherwise, mortality between time of tagging and the hunting season will cause the Brownie estimator to be negatively biased. Alternatively, fitting animals with radio transmitters can be used to accurately estimate harvest rate but may be more costly. We developed a joint model to estimate harvest and annual survival rates that combines known-fate data from animals fitted with transmitters to estimate the probability of surviving the period from capture to the first hunting season, and data from reward-tagged animals in a Brownie tag-recovery model. We evaluated bias and precision of the joint estimator, and how to optimally allocate effort between animals fitted with radio transmitters and inexpensive ear tags or leg bands. Tagging-to-harvest survival rates from >20 individuals with radio transmitters combined with 50–100 reward tags resulted in an unbiased and precise estimator of harvest rates. In addition, the joint model can test whether transmitters affect an individual's probability of being harvested. We illustrate application of the model using data from wild turkey, Meleagris gallapavo,to estimate harvest rates, and data from white-tailed deer, Odocoileus virginianus, to evaluate whether the presence of a visible radio transmitter is related to the probability of a deer being harvested. The joint known-fate tag-recovery model eliminates the requirement to capture and mark animals immediately prior to the hunting season to obtain accurate and precise estimates of harvest rate. In addition, the joint model can assess whether marking animals with radio transmitters affects the individual's probability of being harvested, caused by hunter selectivity or changes in a marked animal's behavior.

Joint modeling of longitudinal data and discrete-time survival outcome.

PubMed

Qiu, Feiyou; Stein, Catherine M; Elston, Robert C

2016-08-01

A predictive joint shared parameter model is proposed for discrete time-to-event and longitudinal data. A discrete survival model with frailty and a generalized linear mixed model for the longitudinal data are joined to predict the probability of events. This joint model focuses on predicting discrete time-to-event outcome, taking advantage of repeated measurements. We show that the probability of an event in a time window can be more precisely predicted by incorporating the longitudinal measurements. The model was investigated by comparison with a two-step model and a discrete-time survival model. Results from both a study on the occurrence of tuberculosis and simulated data show that the joint model is superior to the other models in discrimination ability, especially as the latent variables related to both survival times and the longitudinal measurements depart from 0. © The Author(s) 2013.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baker, Kyri; Toomey, Bridget

Evolving power systems with increasing levels of stochasticity call for a need to solve optimal power flow problems with large quantities of random variables. Weather forecasts, electricity prices, and shifting load patterns introduce higher levels of uncertainty and can yield optimization problems that are difficult to solve in an efficient manner. Solution methods for single chance constraints in optimal power flow problems have been considered in the literature, ensuring single constraints are satisfied with a prescribed probability; however, joint chance constraints, ensuring multiple constraints are simultaneously satisfied, have predominantly been solved via scenario-based approaches or by utilizing Boole's inequality asmore » an upper bound. In this paper, joint chance constraints are used to solve an AC optimal power flow problem while preventing overvoltages in distribution grids under high penetrations of photovoltaic systems. A tighter version of Boole's inequality is derived and used to provide a new upper bound on the joint chance constraint, and simulation results are shown demonstrating the benefit of the proposed upper bound. The new framework allows for a less conservative and more computationally efficient solution to considering joint chance constraints, specifically regarding preventing overvoltages.« less

The effects of the one-step replica symmetry breaking on the Sherrington-Kirkpatrick spin glass model in the presence of random field with a joint Gaussian probability density function for the exchange interactions and random fields

NASA Astrophysics Data System (ADS)

Hadjiagapiou, Ioannis A.; Velonakis, Ioannis N.

2018-07-01

The Sherrington-Kirkpatrick Ising spin glass model, in the presence of a random magnetic field, is investigated within the framework of the one-step replica symmetry breaking. The two random variables (exchange integral interaction Jij and random magnetic field hi) are drawn from a joint Gaussian probability density function characterized by a correlation coefficient ρ, assuming positive and negative values. The thermodynamic properties, the three different phase diagrams and system's parameters are computed with respect to the natural parameters of the joint Gaussian probability density function at non-zero and zero temperatures. The low temperature negative entropy controversy, a result of the replica symmetry approach, has been partly remedied in the current study, leading to a less negative result. In addition, the present system possesses two successive spin glass phase transitions with characteristic temperatures.

Investigation of the relation between the return periods of major drought characteristics using copula functions

NASA Astrophysics Data System (ADS)

Hüsami Afşar, Mehdi; Unal Şorman, Ali; Tugrul Yilmaz, Mustafa

2016-04-01

Different drought characteristics (e.g. duration, average severity, and average areal extent) often have monotonic relation that increased magnitude of one often follows a similar increase in the magnitude of the other drought characteristic. Hence it is viable to establish a relationship between different drought characteristics with the goal of predicting one using other ones. Copula functions that relate different variables using their joint and conditional cumulative probability distributions are often used to statistically model the drought characteristics. In this study bivariate and trivariate joint probabilities of these characteristics are obtained over Ankara (Turkey) between 1960 and 2013. Copula-based return period estimation of drought characteristics of duration, average severity, and average areal extent show joint probabilities of these characteristics can be satisfactorily achieved. Among different copula families investigated in this study, elliptical family (i.e. including normal and t-student copula functions) resulted in the lowest root mean square error. "This study was supported by TUBITAK fund #114Y676)."

Independent events in elementary probability theory

NASA Astrophysics Data System (ADS)

Csenki, Attila

2011-07-01

In Probability and Statistics taught to mathematicians as a first introduction or to a non-mathematical audience, joint independence of events is introduced by requiring that the multiplication rule is satisfied. The following statement is usually tacitly assumed to hold (and, at best, intuitively motivated): If the n events E 1, E 2, … , E n are jointly independent then any two events A and B built in finitely many steps from two disjoint subsets of E 1, E 2, … , E n are also independent. The operations 'union', 'intersection' and 'complementation' are permitted only when forming the events A and B. Here we examine this statement from the point of view of elementary probability theory. The approach described here is accessible also to users of probability theory and is believed to be novel.

On the uncertainty in single molecule fluorescent lifetime and energy emission measurements

NASA Technical Reports Server (NTRS)

Brown, Emery N.; Zhang, Zhenhua; Mccollom, Alex D.

1995-01-01

Time-correlated single photon counting has recently been combined with mode-locked picosecond pulsed excitation to measure the fluorescent lifetimes and energy emissions of single molecules in a flow stream. Maximum likelihood (ML) and least square methods agree and are optimal when the number of detected photons is large however, in single molecule fluorescence experiments the number of detected photons can be less than 20, 67% of those can be noise and the detection time is restricted to 10 nanoseconds. Under the assumption that the photon signal and background noise are two independent inhomogeneous poisson processes, we derive the exact joint arrival time probably density of the photons collected in a single counting experiment performed in the presence of background noise. The model obviates the need to bin experimental data for analysis, and makes it possible to analyze formally the effect of background noise on the photon detection experiment using both ML or Bayesian methods. For both methods we derive the joint and marginal probability densities of the fluorescent lifetime and fluorescent emission. the ML and Bayesian methods are compared in an analysis of simulated single molecule fluorescence experiments of Rhodamine 110 using different combinations of expected background nose and expected fluorescence emission. While both the ML or Bayesian procedures perform well for analyzing fluorescence emissions, the Bayesian methods provide more realistic measures of uncertainty in the fluorescent lifetimes. The Bayesian methods would be especially useful for measuring uncertainty in fluorescent lifetime estimates in current single molecule flow stream experiments where the expected fluorescence emission is low. Both the ML and Bayesian algorithms can be automated for applications in molecular biology.

On the Uncertainty in Single Molecule Fluorescent Lifetime and Energy Emission Measurements

NASA Technical Reports Server (NTRS)

Brown, Emery N.; Zhang, Zhenhua; McCollom, Alex D.

1996-01-01

Time-correlated single photon counting has recently been combined with mode-locked picosecond pulsed excitation to measure the fluorescent lifetimes and energy emissions of single molecules in a flow stream. Maximum likelihood (ML) and least squares methods agree and are optimal when the number of detected photons is large, however, in single molecule fluorescence experiments the number of detected photons can be less than 20, 67 percent of those can be noise, and the detection time is restricted to 10 nanoseconds. Under the assumption that the photon signal and background noise are two independent inhomogeneous Poisson processes, we derive the exact joint arrival time probability density of the photons collected in a single counting experiment performed in the presence of background noise. The model obviates the need to bin experimental data for analysis, and makes it possible to analyze formally the effect of background noise on the photon detection experiment using both ML or Bayesian methods. For both methods we derive the joint and marginal probability densities of the fluorescent lifetime and fluorescent emission. The ML and Bayesian methods are compared in an analysis of simulated single molecule fluorescence experiments of Rhodamine 110 using different combinations of expected background noise and expected fluorescence emission. While both the ML or Bayesian procedures perform well for analyzing fluorescence emissions, the Bayesian methods provide more realistic measures of uncertainty in the fluorescent lifetimes. The Bayesian methods would be especially useful for measuring uncertainty in fluorescent lifetime estimates in current single molecule flow stream experiments where the expected fluorescence emission is low. Both the ML and Bayesian algorithms can be automated for applications in molecular biology.

Stochastic Forecasting of Algae Blooms in Lakes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Peng; Tartakovsky, Daniel M.; Tartakovsky, Alexandre M.

We consider the development of harmful algae blooms (HABs) in a lake with uncertain nutrients inflow. Two general frameworks, Fokker-Planck equation and the PDF methods, are developed to quantify the resultant concentration uncertainty of various algae groups, via deriving a deterministic equation of their joint probability density function (PDF). A computational example is examined to study the evolution of cyanobacteria (the blue-green algae) and the impacts of initial concentration and inflow-outflow ratio.

Classification of cassava genotypes based on qualitative and quantitative data.

PubMed

Oliveira, E J; Oliveira Filho, O S; Santos, V S

2015-02-02

We evaluated the genetic variation of cassava accessions based on qualitative (binomial and multicategorical) and quantitative traits (continuous). We characterized 95 accessions obtained from the Cassava Germplasm Bank of Embrapa Mandioca e Fruticultura; we evaluated these accessions for 13 continuous, 10 binary, and 25 multicategorical traits. First, we analyzed the accessions based only on quantitative traits; next, we conducted joint analysis (qualitative and quantitative traits) based on the Ward-MLM method, which performs clustering in two stages. According to the pseudo-F, pseudo-t2, and maximum likelihood criteria, we identified five and four groups based on quantitative trait and joint analysis, respectively. The smaller number of groups identified based on joint analysis may be related to the nature of the data. On the other hand, quantitative data are more subject to environmental effects in the phenotype expression; this results in the absence of genetic differences, thereby contributing to greater differentiation among accessions. For most of the accessions, the maximum probability of classification was >0.90, independent of the trait analyzed, indicating a good fit of the clustering method. Differences in clustering according to the type of data implied that analysis of quantitative and qualitative traits in cassava germplasm might explore different genomic regions. On the other hand, when joint analysis was used, the means and ranges of genetic distances were high, indicating that the Ward-MLM method is very useful for clustering genotypes when there are several phenotypic traits, such as in the case of genetic resources and breeding programs.

Flood Frequency Analyses Using a Modified Stochastic Storm Transposition Method

NASA Astrophysics Data System (ADS)

Fang, N. Z.; Kiani, M.

2015-12-01

Research shows that areas with similar topography and climatic environment have comparable precipitation occurrences. Reproduction and realization of historical rainfall events provide foundations for frequency analysis and the advancement of meteorological studies. Stochastic Storm Transposition (SST) is a method for such a purpose and enables us to perform hydrologic frequency analyses by transposing observed historical storm events to the sites of interest. However, many previous studies in SST reveal drawbacks from simplified Probability Density Functions (PDFs) without considering restrictions for transposing rainfalls. The goal of this study is to stochastically examine the impacts of extreme events on all locations in a homogeneity zone. Since storms with the same probability of occurrence on homogenous areas do not have the identical hydrologic impacts, the authors utilize detailed precipitation parameters including the probability of occurrence of certain depth and the number of occurrence of extreme events, which are both incorporated into a joint probability function. The new approach can reduce the bias from uniformly transposing storms which erroneously increases the probability of occurrence of storms in areas with higher rainfall depths. This procedure is iterated to simulate storm events for one thousand years as the basis for updating frequency analysis curves such as IDF and FFA. The study area is the Upper Trinity River watershed including the Dallas-Fort Worth metroplex with a total area of 6,500 mi2. It is the first time that SST method is examined in such a wide scale with 20 years of radar rainfall data.

Does joint line elevation after revision knee arthroplasty affect tibio-femoral kinematics, contact pressure or collateral ligament lengths? An in vitro analysis

PubMed Central

Kowalczewski, Jacek B.; Chevalier, Yan; Okon, Tomasz; Innocenti, Bernardo; Bellemans, Johan

2015-01-01

Introduction Correct restoration of the joint line is generally considered as crucial when performing total knee arthroplasty (TKA). During revision knee arthroplasty however, elevation of the joint line occurs frequently. The general belief is that this negatively affects the clinical outcome, but the reasons are still not well understood. Material and methods In this cadaveric in vitro study the biomechanical consequences of joint line elevation were investigated using a previously validated cadaver model simulating active deep knee squats and passive flexion-extension cycles. Knee specimens were sequentially tested after total knee arthroplasty with joint line restoration and after 4 mm joint line elevation. Results The tibia rotated internally with increasing knee flexion during both passive and squatting motion (range: 17° and 7° respectively). Joint line elevation of 4 mm did not make a statistically significant difference. During passive motion, the tibia tended to become slightly more adducted with increasing knee flexion (range: 2°), while it went into slighlty less adduction during squatting (range: –2°). Neither of both trends was influenced by joint line elevation. Also anteroposterior translation of the femoral condyle centres was not affected by joint line elevation, although there was a tendency for a small posterior shift (of about 3 mm) during squatting after joint line elevation. In terms of kinetics, ligaments lengths and length changes, tibiofemoral contact pressures and quadriceps forces all showed the same patterns before and joint line elevation. No statistically significant changes could be detected. Conclusions Our study suggests that joint line elevation by 4 mm in revision total knee arthroplasty does not cause significant kinematic and kinetic differences during passive flexion/extension movement and squatting in the tibio-femoral joint, nor does it affect the elongation patterns of collateral ligaments. Therefore, clinical problems after joint line elevation are probably situated in the patello-femoral joint or caused by joint line elevation of more than 4 mm. PMID:25995746

Quasi-probabilities in conditioned quantum measurement and a geometric/statistical interpretation of Aharonov's weak value

NASA Astrophysics Data System (ADS)

Lee, Jaeha; Tsutsui, Izumi

2017-05-01

We show that the joint behavior of an arbitrary pair of (generally noncommuting) quantum observables can be described by quasi-probabilities, which are an extended version of the standard probabilities used for describing the outcome of measurement for a single observable. The physical situations that require these quasi-probabilities arise when one considers quantum measurement of an observable conditioned by some other variable, with the notable example being the weak measurement employed to obtain Aharonov's weak value. Specifically, we present a general prescription for the construction of quasi-joint probability (QJP) distributions associated with a given combination of observables. These QJP distributions are introduced in two complementary approaches: one from a bottom-up, strictly operational construction realized by examining the mathematical framework of the conditioned measurement scheme, and the other from a top-down viewpoint realized by applying the results of the spectral theorem for normal operators and their Fourier transforms. It is then revealed that, for a pair of simultaneously measurable observables, the QJP distribution reduces to the unique standard joint probability distribution of the pair, whereas for a noncommuting pair there exists an inherent indefiniteness in the choice of such QJP distributions, admitting a multitude of candidates that may equally be used for describing the joint behavior of the pair. In the course of our argument, we find that the QJP distributions furnish the space of operators in the underlying Hilbert space with their characteristic geometric structures such that the orthogonal projections and inner products of observables can be given statistical interpretations as, respectively, “conditionings” and “correlations”. The weak value Aw for an observable A is then given a geometric/statistical interpretation as either the orthogonal projection of A onto the subspace generated by another observable B, or equivalently, as the conditioning of A given B with respect to the QJP distribution under consideration.

Application of Archimedean copulas to the analysis of drought decadal variation in China

NASA Astrophysics Data System (ADS)

Zuo, Dongdong; Feng, Guolin; Zhang, Zengping; Hou, Wei

2017-12-01

Based on daily precipitation data collected from 1171 stations in China during 1961-2015, the monthly standardized precipitation index was derived and used to extract two major drought characteristics which are drought duration and severity. Next, a bivariate joint model was established based on the marginal distributions of the two variables and Archimedean copula functions. The joint probability and return period were calculated to analyze the drought characteristics and decadal variation. According to the fit analysis, the Gumbel-Hougaard copula provided the best fit to the observed data. Based on four drought duration classifications and four severity classifications, the drought events were divided into 16 drought types according to the different combinations of duration and severity classifications, and the probability and return period were analyzed for different drought types. The results showed that the occurring probability of six common drought types (0 < D ≤ 1 and 0.5 < S ≤ 1, 1 < D ≤ 3 and 0.5 < S ≤ 1, 1 < D ≤ 3 and 1 < S ≤ 1.5, 1 < D ≤ 3 and 1.5 < S ≤ 2, 1 < D ≤ 3 and 2 < S, and 3 < D ≤ 6 and 2 < S) accounted for 76% of the total probability of all types. Moreover, due to their greater variation, two drought types were particularly notable, i.e., the drought types where D ≥ 6 and S ≥ 2. Analyzing the joint probability in different decades indicated that the location of the drought center had a distinctive stage feature, which cycled from north to northeast to southwest during 1961-2015. However, southwest, north, and northeast China had a higher drought risk. In addition, the drought situation in southwest China should be noted because the joint probability values, return period, and the analysis of trends in the drought duration and severity all indicated a considerable risk in recent years.

Two-locus maximum lod score analysis of a multifactorial trait: joint consideration of IDDM2 and IDDM4 with IDDM1 in type 1 diabetes.

PubMed

Cordell, H J; Todd, J A; Bennett, S T; Kawaguchi, Y; Farrall, M

1995-10-01

To investigate the genetic component of multifactorial diseases such as type 1 (insulin-dependent) diabetes mellitus (IDDM), models involving the joint action of several disease loci are important. These models can give increased power to detect an effect and a greater understanding of etiological mechanisms. Here, we present an extension of the maximum lod score method of N. Risch, which allows the simultaneous detection and modeling of two unlinked disease loci. Genetic constraints on the identical-by-descent sharing probabilities, analogous to the "triangle" restrictions in the single-locus method, are derived, and the size and power of the test statistics are investigated. The method is applied to affected-sib-pair data, and the joint effects of IDDM1 (HLA) and IDDM2 (the INS VNTR) and of IDDM1 and IDDM4 (FGF3-linked) are assessed with relation to the development of IDDM. In the presence of genetic heterogeneity, there is seen to be a significant advantage in analyzing more than one locus simultaneously. Analysis of these families indicates that the effects at IDDM1 and IDDM2 are well described by a multiplicative genetic model, while those at IDDM1 and IDDM4 follow a heterogeneity model.

Two-locus maximum lod score analysis of a multifactorial trait: joint consideration of IDDM2 and IDDM4 with IDDM1 in type 1 diabetes.

PubMed Central

Cordell, H J; Todd, J A; Bennett, S T; Kawaguchi, Y; Farrall, M

1995-01-01

To investigate the genetic component of multifactorial diseases such as type 1 (insulin-dependent) diabetes mellitus (IDDM), models involving the joint action of several disease loci are important. These models can give increased power to detect an effect and a greater understanding of etiological mechanisms. Here, we present an extension of the maximum lod score method of N. Risch, which allows the simultaneous detection and modeling of two unlinked disease loci. Genetic constraints on the identical-by-descent sharing probabilities, analogous to the "triangle" restrictions in the single-locus method, are derived, and the size and power of the test statistics are investigated. The method is applied to affected-sib-pair data, and the joint effects of IDDM1 (HLA) and IDDM2 (the INS VNTR) and of IDDM1 and IDDM4 (FGF3-linked) are assessed with relation to the development of IDDM. In the presence of genetic heterogeneity, there is seen to be a significant advantage in analyzing more than one locus simultaneously. Analysis of these families indicates that the effects at IDDM1 and IDDM2 are well described by a multiplicative genetic model, while those at IDDM1 and IDDM4 follow a heterogeneity model. PMID:7573054

Statistical Analysis of Stress Signals from Bridge Monitoring by FBG System.

PubMed

Ye, Xiao-Wei; Su, You-Hua; Xi, Pei-Sen

2018-02-07

In this paper, a fiber Bragg grating (FBG)-based stress monitoring system instrumented on an orthotropic steel deck arch bridge is demonstrated. The FBG sensors are installed at two types of critical fatigue-prone welded joints to measure the strain and temperature signals. A total of 64 FBG sensors are deployed around the rib-to-deck and rib-to-diagram areas at the mid-span and quarter-span of the investigated orthotropic steel bridge. The local stress behaviors caused by the highway loading and temperature effect during the construction and operation periods are presented with the aid of a wavelet multi-resolution analysis approach. In addition, the multi-modal characteristic of the rainflow counted stress spectrum is modeled by the method of finite mixture distribution together with a genetic algorithm (GA)-based parameter estimation approach. The optimal probability distribution of the stress spectrum is determined by use of Bayesian information criterion (BIC). Furthermore, the hot spot stress of the welded joint is calculated by an extrapolation method recommended in the specification of International Institute of Welding (IIW). The stochastic characteristic of stress concentration factor (SCF) of the concerned welded joint is addressed. The proposed FBG-based stress monitoring system and probabilistic stress evaluation methods can provide an effective tool for structural monitoring and condition assessment of orthotropic steel bridges.

Climate Change Impact Assessment in Pacific North West Using Copula based Coupling of Temperature and Precipitation variables

NASA Astrophysics Data System (ADS)

Qin, Y.; Rana, A.; Moradkhani, H.

2014-12-01

The multi downscaled-scenario products allow us to better assess the uncertainty of the changes/variations of precipitation and temperature in the current and future periods. Joint Probability distribution functions (PDFs), of both the climatic variables, might help better understand the interdependence of the two, and thus in-turn help in accessing the future with confidence. Using the joint distribution of temperature and precipitation is also of significant importance in hydrological applications and climate change studies. In the present study, we have used multi-modelled statistically downscaled-scenario ensemble of precipitation and temperature variables using 2 different statistically downscaled climate dataset. The datasets used are, 10 Global Climate Models (GCMs) downscaled products from CMIP5 daily dataset, namely, those from the Bias Correction and Spatial Downscaling (BCSD) technique generated at Portland State University and from the Multivariate Adaptive Constructed Analogs (MACA) technique, generated at University of Idaho, leading to 2 ensemble time series from 20 GCM products. Thereafter the ensemble PDFs of both precipitation and temperature is evaluated for summer, winter, and yearly periods for all the 10 sub-basins across Columbia River Basin (CRB). Eventually, Copula is applied to establish the joint distribution of two variables enabling users to model the joint behavior of the variables with any level of correlation and dependency. Moreover, the probabilistic distribution helps remove the limitations on marginal distributions of variables in question. The joint distribution is then used to estimate the change trends of the joint precipitation and temperature in the current and future, along with estimation of the probabilities of the given change. Results have indicated towards varied change trends of the joint distribution of, summer, winter, and yearly time scale, respectively in all 10 sub-basins. Probabilities of changes, as estimated by the joint precipitation and temperature, will provide useful information/insights for hydrological and climate change predictions.

Clinical results of resection arthrodesis by triangular external fixation for posttraumatic arthrosis of the ankle joint in 89 cases

PubMed Central

2009-01-01

The methods for ankle arthrodesis differ significantly, probably a sign that no method is clearly superior to others. In the last ten years there is a clear favour toward internal fixation. We retrospectively evaluate the technique and evaluate the clinical long term results of external fixation in a triangular frame. Patients and Methods From 1994 to 2001 a consecutive series of 95 patients with end stage arthritis of the ankle joint were treated. Retrospectively the case notes were evaluated regarding trauma history, medical complaints, further injuries and illnesses, walking and pain status and occupational issues and the clinical examination before arthrodesis. Mean age at the index procedure was 45.4 years (18-82), 67 patients were male (70.5%). Via a bilateral approach the malleoli and the joint surfaces were resected. An AO fixator was applied with two Steinmann-nails inserted with approximately 8 cm distance in the distal tibia, one in the neck of the talus and one in the dorsal calcaneus. The fixator was removed after approximately 12 weeks. Follow up examination at mean 4.4 years included a standardised questionnaire and a clinical examination including the criteria of the AOFAS-Score and radiographs. Results: Due to different complications, 8 (8.9%) further surgical procedures were necessary including 1 below knee amputation. In 4 patients a non-union of the ankle arthrodesis developed (4.5%). The mean AOFAS score improved from 20.8 to 69.3 points. Conclusion Non-union rates and clinical results of arthrodesis by triangular external fixation of the ankle joint do not differ to internal fixation methods. The complication rate and the reduced patient comfort reserve this method mainly for infected arthritis and complicated soft tissue situations. PMID:19258207

Investigations of turbulent scalar fields using probability density function approach

NASA Technical Reports Server (NTRS)

Gao, Feng

1991-01-01

Scalar fields undergoing random advection have attracted much attention from researchers in both the theoretical and practical sectors. Research interest spans from the study of the small scale structures of turbulent scalar fields to the modeling and simulations of turbulent reacting flows. The probability density function (PDF) method is an effective tool in the study of turbulent scalar fields, especially for those which involve chemical reactions. It has been argued that a one-point, joint PDF approach is the one to choose from among many simulation and closure methods for turbulent combustion and chemically reacting flows based on its practical feasibility in the foreseeable future for multiple reactants. Instead of the multi-point PDF, the joint PDF of a scalar and its gradient which represents the roles of both scalar and scalar diffusion is introduced. A proper closure model for the molecular diffusion term in the PDF equation is investigated. Another direction in this research is to study the mapping closure method that has been recently proposed to deal with the PDF's in turbulent fields. This method seems to have captured the physics correctly when applied to diffusion problems. However, if the turbulent stretching is included, the amplitude mapping has to be supplemented by either adjusting the parameters representing turbulent stretching at each time step or by introducing the coordinate mapping. This technique is still under development and seems to be quite promising. The final objective of this project is to understand some fundamental properties of the turbulent scalar fields and to develop practical numerical schemes that are capable of handling turbulent reacting flows.

Markov Chain Monte Carlo Joint Analysis of Chandra X-Ray Imaging Spectroscopy and Sunyaev-Zel'dovich Effect Data

NASA Technical Reports Server (NTRS)

Bonamente, Massimillano; Joy, Marshall K.; Carlstrom, John E.; Reese, Erik D.; LaRoque, Samuel J.

2004-01-01

X-ray and Sunyaev-Zel'dovich effect data can be combined to determine the distance to galaxy clusters. High-resolution X-ray data are now available from Chandra, which provides both spatial and spectral information, and Sunyaev-Zel'dovich effect data were obtained from the BIMA and Owens Valley Radio Observatory (OVRO) arrays. We introduce a Markov Chain Monte Carlo procedure for the joint analysis of X-ray and Sunyaev- Zel'dovich effect data. The advantages of this method are the high computational efficiency and the ability to measure simultaneously the probability distribution of all parameters of interest, such as the spatial and spectral properties of the cluster gas and also for derivative quantities such as the distance to the cluster. We demonstrate this technique by applying it to the Chandra X-ray data and the OVRO radio data for the galaxy cluster A611. Comparisons with traditional likelihood ratio methods reveal the robustness of the method. This method will be used in follow-up paper to determine the distances to a large sample of galaxy cluster.

Fast approximation for joint optimization of segmentation, shape, and location priors, and its application in gallbladder segmentation.

PubMed

Saito, Atsushi; Nawano, Shigeru; Shimizu, Akinobu

2017-05-01

This paper addresses joint optimization for segmentation and shape priors, including translation, to overcome inter-subject variability in the location of an organ. Because a simple extension of the previous exact optimization method is too computationally complex, we propose a fast approximation for optimization. The effectiveness of the proposed approximation is validated in the context of gallbladder segmentation from a non-contrast computed tomography (CT) volume. After spatial standardization and estimation of the posterior probability of the target organ, simultaneous optimization of the segmentation, shape, and location priors is performed using a branch-and-bound method. Fast approximation is achieved by combining sampling in the eigenshape space to reduce the number of shape priors and an efficient computational technique for evaluating the lower bound. Performance was evaluated using threefold cross-validation of 27 CT volumes. Optimization in terms of translation of the shape prior significantly improved segmentation performance. The proposed method achieved a result of 0.623 on the Jaccard index in gallbladder segmentation, which is comparable to that of state-of-the-art methods. The computational efficiency of the algorithm is confirmed to be good enough to allow execution on a personal computer. Joint optimization of the segmentation, shape, and location priors was proposed, and it proved to be effective in gallbladder segmentation with high computational efficiency.

Inference of reaction rate parameters based on summary statistics from experiments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Khalil, Mohammad; Chowdhary, Kamaljit Singh; Safta, Cosmin

Here, we present the results of an application of Bayesian inference and maximum entropy methods for the estimation of the joint probability density for the Arrhenius rate para meters of the rate coefficient of the H 2/O 2-mechanism chain branching reaction H + O 2 → OH + O. Available published data is in the form of summary statistics in terms of nominal values and error bars of the rate coefficient of this reaction at a number of temperature values obtained from shock-tube experiments. Our approach relies on generating data, in this case OH concentration profiles, consistent with the givenmore » summary statistics, using Approximate Bayesian Computation methods and a Markov Chain Monte Carlo procedure. The approach permits the forward propagation of parametric uncertainty through the computational model in a manner that is consistent with the published statistics. A consensus joint posterior on the parameters is obtained by pooling the posterior parameter densities given each consistent data set. To expedite this process, we construct efficient surrogates for the OH concentration using a combination of Pad'e and polynomial approximants. These surrogate models adequately represent forward model observables and their dependence on input parameters and are computationally efficient to allow their use in the Bayesian inference procedure. We also utilize Gauss-Hermite quadrature with Gaussian proposal probability density functions for moment computation resulting in orders of magnitude speedup in data likelihood evaluation. Despite the strong non-linearity in the model, the consistent data sets all res ult in nearly Gaussian conditional parameter probability density functions. The technique also accounts for nuisance parameters in the form of Arrhenius parameters of other rate coefficients with prescribed uncertainty. The resulting pooled parameter probability density function is propagated through stoichiometric hydrogen-air auto-ignition computations to illustrate the need to account for correlation among the Arrhenius rate parameters of one reaction and across rate parameters of different reactions.« less

Inference of reaction rate parameters based on summary statistics from experiments

DOE PAGES

Khalil, Mohammad; Chowdhary, Kamaljit Singh; Safta, Cosmin; ...

2016-10-15

Here, we present the results of an application of Bayesian inference and maximum entropy methods for the estimation of the joint probability density for the Arrhenius rate para meters of the rate coefficient of the H 2/O 2-mechanism chain branching reaction H + O 2 → OH + O. Available published data is in the form of summary statistics in terms of nominal values and error bars of the rate coefficient of this reaction at a number of temperature values obtained from shock-tube experiments. Our approach relies on generating data, in this case OH concentration profiles, consistent with the givenmore » summary statistics, using Approximate Bayesian Computation methods and a Markov Chain Monte Carlo procedure. The approach permits the forward propagation of parametric uncertainty through the computational model in a manner that is consistent with the published statistics. A consensus joint posterior on the parameters is obtained by pooling the posterior parameter densities given each consistent data set. To expedite this process, we construct efficient surrogates for the OH concentration using a combination of Pad'e and polynomial approximants. These surrogate models adequately represent forward model observables and their dependence on input parameters and are computationally efficient to allow their use in the Bayesian inference procedure. We also utilize Gauss-Hermite quadrature with Gaussian proposal probability density functions for moment computation resulting in orders of magnitude speedup in data likelihood evaluation. Despite the strong non-linearity in the model, the consistent data sets all res ult in nearly Gaussian conditional parameter probability density functions. The technique also accounts for nuisance parameters in the form of Arrhenius parameters of other rate coefficients with prescribed uncertainty. The resulting pooled parameter probability density function is propagated through stoichiometric hydrogen-air auto-ignition computations to illustrate the need to account for correlation among the Arrhenius rate parameters of one reaction and across rate parameters of different reactions.« less

Bayesian data analysis tools for atomic physics

NASA Astrophysics Data System (ADS)

Trassinelli, Martino

2017-10-01

We present an introduction to some concepts of Bayesian data analysis in the context of atomic physics. Starting from basic rules of probability, we present the Bayes' theorem and its applications. In particular we discuss about how to calculate simple and joint probability distributions and the Bayesian evidence, a model dependent quantity that allows to assign probabilities to different hypotheses from the analysis of a same data set. To give some practical examples, these methods are applied to two concrete cases. In the first example, the presence or not of a satellite line in an atomic spectrum is investigated. In the second example, we determine the most probable model among a set of possible profiles from the analysis of a statistically poor spectrum. We show also how to calculate the probability distribution of the main spectral component without having to determine uniquely the spectrum modeling. For these two studies, we implement the program Nested_fit to calculate the different probability distributions and other related quantities. Nested_fit is a Fortran90/Python code developed during the last years for analysis of atomic spectra. As indicated by the name, it is based on the nested algorithm, which is presented in details together with the program itself.

On the motion of classical three-body system with consideration of quantum fluctuations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gevorkyan, A. S., E-mail: g-ashot@sci.am

2017-03-15

We obtained the systemof stochastic differential equations which describes the classicalmotion of the three-body system under influence of quantum fluctuations. Using SDEs, for the joint probability distribution of the total momentum of bodies system were obtained the partial differential equation of the second order. It is shown, that the equation for the probability distribution is solved jointly by classical equations, which in turn are responsible for the topological peculiarities of tubes of quantum currents, transitions between asymptotic channels and, respectively for arising of quantum chaos.

Computer simulation of random variables and vectors with arbitrary probability distribution laws

NASA Technical Reports Server (NTRS)

Bogdan, V. M.

1981-01-01

Assume that there is given an arbitrary n-dimensional probability distribution F. A recursive construction is found for a sequence of functions x sub 1 = f sub 1 (U sub 1, ..., U sub n), ..., x sub n = f sub n (U sub 1, ..., U sub n) such that if U sub 1, ..., U sub n are independent random variables having uniform distribution over the open interval (0,1), then the joint distribution of the variables x sub 1, ..., x sub n coincides with the distribution F. Since uniform independent random variables can be well simulated by means of a computer, this result allows one to simulate arbitrary n-random variables if their joint probability distribution is known.

No-signaling quantum key distribution: solution by linear programming

NASA Astrophysics Data System (ADS)

Hwang, Won-Young; Bae, Joonwoo; Killoran, Nathan

2015-02-01

We outline a straightforward approach for obtaining a secret key rate using only no-signaling constraints and linear programming. Assuming an individual attack, we consider all possible joint probabilities. Initially, we study only the case where Eve has binary outcomes, and we impose constraints due to the no-signaling principle and given measurement outcomes. Within the remaining space of joint probabilities, by using linear programming, we get bound on the probability of Eve correctly guessing Bob's bit. We then make use of an inequality that relates this guessing probability to the mutual information between Bob and a more general Eve, who is not binary-restricted. Putting our computed bound together with the Csiszár-Körner formula, we obtain a positive key generation rate. The optimal value of this rate agrees with known results, but was calculated in a more straightforward way, offering the potential of generalization to different scenarios.

Estimating Model Probabilities using Thermodynamic Markov Chain Monte Carlo Methods

NASA Astrophysics Data System (ADS)

Ye, M.; Liu, P.; Beerli, P.; Lu, D.; Hill, M. C.

2014-12-01

Markov chain Monte Carlo (MCMC) methods are widely used to evaluate model probability for quantifying model uncertainty. In a general procedure, MCMC simulations are first conducted for each individual model, and MCMC parameter samples are then used to approximate marginal likelihood of the model by calculating the geometric mean of the joint likelihood of the model and its parameters. It has been found the method of evaluating geometric mean suffers from the numerical problem of low convergence rate. A simple test case shows that even millions of MCMC samples are insufficient to yield accurate estimation of the marginal likelihood. To resolve this problem, a thermodynamic method is used to have multiple MCMC runs with different values of a heating coefficient between zero and one. When the heating coefficient is zero, the MCMC run is equivalent to a random walk MC in the prior parameter space; when the heating coefficient is one, the MCMC run is the conventional one. For a simple case with analytical form of the marginal likelihood, the thermodynamic method yields more accurate estimate than the method of using geometric mean. This is also demonstrated for a case of groundwater modeling with consideration of four alternative models postulated based on different conceptualization of a confining layer. This groundwater example shows that model probabilities estimated using the thermodynamic method are more reasonable than those obtained using the geometric method. The thermodynamic method is general, and can be used for a wide range of environmental problem for model uncertainty quantification.

Cellular Automata Generalized To An Inferential System

NASA Astrophysics Data System (ADS)

Blower, David J.

2007-11-01

Stephen Wolfram popularized elementary one-dimensional cellular automata in his book, A New Kind of Science. Among many remarkable things, he proved that one of these cellular automata was a Universal Turing Machine. Such cellular automata can be interpreted in a different way by viewing them within the context of the formal manipulation rules from probability theory. Bayes's Theorem is the most famous of such formal rules. As a prelude, we recapitulate Jaynes's presentation of how probability theory generalizes classical logic using modus ponens as the canonical example. We emphasize the important conceptual standing of Boolean Algebra for the formal rules of probability manipulation and give an alternative demonstration augmenting and complementing Jaynes's derivation. We show the complementary roles played in arguments of this kind by Bayes's Theorem and joint probability tables. A good explanation for all of this is afforded by the expansion of any particular logic function via the disjunctive normal form (DNF). The DNF expansion is a useful heuristic emphasized in this exposition because such expansions point out where relevant 0s should be placed in the joint probability tables for logic functions involving any number of variables. It then becomes a straightforward exercise to rely on Boolean Algebra, Bayes's Theorem, and joint probability tables in extrapolating to Wolfram's cellular automata. Cellular automata are seen as purely deductive systems, just like classical logic, which probability theory is then able to generalize. Thus, any uncertainties which we might like to introduce into the discussion about cellular automata are handled with ease via the familiar inferential path. Most importantly, the difficult problem of predicting what cellular automata will do in the far future is treated like any inferential prediction problem.

Validation of spatial variability in downscaling results from the VALUE perfect predictor experiment

NASA Astrophysics Data System (ADS)

Widmann, Martin; Bedia, Joaquin; Gutiérrez, Jose Manuel; Maraun, Douglas; Huth, Radan; Fischer, Andreas; Keller, Denise; Hertig, Elke; Vrac, Mathieu; Wibig, Joanna; Pagé, Christian; Cardoso, Rita M.; Soares, Pedro MM; Bosshard, Thomas; Casado, Maria Jesus; Ramos, Petra

2016-04-01

VALUE is an open European network to validate and compare downscaling methods for climate change research. Within VALUE a systematic validation framework to enable the assessment and comparison of both dynamical and statistical downscaling methods has been developed. In the first validation experiment the downscaling methods are validated in a setup with perfect predictors taken from the ERA-interim reanalysis for the period 1997 - 2008. This allows to investigate the isolated skill of downscaling methods without further error contributions from the large-scale predictors. One aspect of the validation is the representation of spatial variability. As part of the VALUE validation we have compared various properties of the spatial variability of downscaled daily temperature and precipitation with the corresponding properties in observations. We have used two test validation datasets, one European-wide set of 86 stations, and one higher-density network of 50 stations in Germany. Here we present results based on three approaches, namely the analysis of i.) correlation matrices, ii.) pairwise joint threshold exceedances, and iii.) regions of similar variability. We summarise the information contained in correlation matrices by calculating the dependence of the correlations on distance and deriving decorrelation lengths, as well as by determining the independent degrees of freedom. Probabilities for joint threshold exceedances and (where appropriate) non-exceedances are calculated for various user-relevant thresholds related for instance to extreme precipitation or frost and heat days. The dependence of these probabilities on distance is again characterised by calculating typical length scales that separate dependent from independent exceedances. Regionalisation is based on rotated Principal Component Analysis. The results indicate which downscaling methods are preferable if the dependency of variability at different locations is relevant for the user.

Probability distribution of haplotype frequencies under the two-locus Wright-Fisher model by diffusion approximation.

PubMed

Boitard, Simon; Loisel, Patrice

2007-05-01

The probability distribution of haplotype frequencies in a population, and the way it is influenced by genetical forces such as recombination, selection, random drift ...is a question of fundamental interest in population genetics. For large populations, the distribution of haplotype frequencies for two linked loci under the classical Wright-Fisher model is almost impossible to compute because of numerical reasons. However the Wright-Fisher process can in such cases be approximated by a diffusion process and the transition density can then be deduced from the Kolmogorov equations. As no exact solution has been found for these equations, we developed a numerical method based on finite differences to solve them. It applies to transient states and models including selection or mutations. We show by several tests that this method is accurate for computing the conditional joint density of haplotype frequencies given that no haplotype has been lost. We also prove that it is far less time consuming than other methods such as Monte Carlo simulations.

Probability density function modeling of scalar mixing from concentrated sources in turbulent channel flow

NASA Astrophysics Data System (ADS)

Bakosi, J.; Franzese, P.; Boybeyi, Z.

2007-11-01

Dispersion of a passive scalar from concentrated sources in fully developed turbulent channel flow is studied with the probability density function (PDF) method. The joint PDF of velocity, turbulent frequency and scalar concentration is represented by a large number of Lagrangian particles. A stochastic near-wall PDF model combines the generalized Langevin model of Haworth and Pope [Phys. Fluids 29, 387 (1986)] with Durbin's [J. Fluid Mech. 249, 465 (1993)] method of elliptic relaxation to provide a mathematically exact treatment of convective and viscous transport with a nonlocal representation of the near-wall Reynolds stress anisotropy. The presence of walls is incorporated through the imposition of no-slip and impermeability conditions on particles without the use of damping or wall-functions. Information on the turbulent time scale is supplied by the gamma-distribution model of van Slooten et al. [Phys. Fluids 10, 246 (1998)]. Two different micromixing models are compared that incorporate the effect of small scale mixing on the transported scalar: the widely used interaction by exchange with the mean and the interaction by exchange with the conditional mean model. Single-point velocity and concentration statistics are compared to direct numerical simulation and experimental data at Reτ=1080 based on the friction velocity and the channel half width. The joint model accurately reproduces a wide variety of conditional and unconditional statistics in both physical and composition space.

Sacroiliac Joint Fusion Using Triangular Titanium Implants vs. Non-Surgical Management: Six-Month Outcomes from a Prospective Randomized Controlled Trial

PubMed Central

Whang, Peter; Polly, David; Frank, Clay; Lockstadt, Harry; Glaser, John; Limoni, Robert; Sembrano, Jonathan

2015-01-01

Background Sacroiliac (SI) joint pain is a prevalent, underdiagnosed cause of lower back pain. SI joint fusion can relieve pain and improve quality of life in patients who have failed nonoperative care. To date, no study has concurrently compared surgical and non-surgical treatments for chronic SI joint dysfunction. Methods We conducted a prospective randomized controlled trial of 148 subjects with SI joint dysfunction due to degenerative sacroiliitis or sacroiliac joint disruptions who were assigned to either minimally invasive SI joint fusion with triangular titanium implants (N=102) or non-surgical management (NSM, n=46). SI joint pain scores, Oswestry Disability Index (ODI), Short-Form 36 (SF-36) and EuroQol-5D (EQ-5D) were collected at baseline and at 1, 3 and 6 months after treatment commencement. Six-month success rates, defined as the proportion of treated subjects with a 20-mm improvement in SI joint pain in the absence of severe device-related or neurologic SI joint-related adverse events or surgical revision, were compared using Bayesian methods. Results Subjects (mean age 51, 70% women) were highly debilitated at baseline (mean SI joint VAS pain score 82, mean ODI score 62). Six-month follow-up was obtained in 97.3%. By 6 months, success rates were 81.4% in the surgical group vs. 23.9% in the NSM group (difference of 56.6%, 95% posterior credible interval 41.4-70.0%, posterior probability of superiority >0.999). Clinically important (≥15 point) ODI improvement at 6 months occurred in 75% of surgery subjects vs. 27.3% of NSM subjects. At six months, quality of life improved more in the surgery group and satisfaction rates were high. The mean number of adverse events in the first six months was slightly higher in the surgical group compared to the non-surgical group (1.3 vs. 1.0 events per subject, p=0.1857). Conclusions Six-month follow-up from this level 1 study showed that minimally invasive SI joint fusion using triangular titanium implants was more effective than non-surgical management in relieving pain, improving function and improving quality of life in patients with SI joint dysfunction due to degenerative sacroiliitis or SI joint disruptions. Clinical relevance Minimally invasive SI joint fusion is an acceptable option for patients with chronic SI joint dysfunction due to degenerative sacroiliitis and sacroiliac joint disruptions unresponsive to non-surgical treatments. PMID:25785242

Improving the Rank Precision of Population Health Measures for Small Areas with Longitudinal and Joint Outcome Models

PubMed Central

Athens, Jessica K.; Remington, Patrick L.; Gangnon, Ronald E.

2015-01-01

Objectives The University of Wisconsin Population Health Institute has published the County Health Rankings since 2010. These rankings use population-based data to highlight health outcomes and the multiple determinants of these outcomes and to encourage in-depth health assessment for all United States counties. A significant methodological limitation, however, is the uncertainty of rank estimates, particularly for small counties. To address this challenge, we explore the use of longitudinal and pooled outcome data in hierarchical Bayesian models to generate county ranks with greater precision. Methods In our models we used pooled outcome data for three measure groups: (1) Poor physical and poor mental health days; (2) percent of births with low birth weight and fair or poor health prevalence; and (3) age-specific mortality rates for nine age groups. We used the fixed and random effects components of these models to generate posterior samples of rates for each measure. We also used time-series data in longitudinal random effects models for age-specific mortality. Based on the posterior samples from these models, we estimate ranks and rank quartiles for each measure, as well as the probability of a county ranking in its assigned quartile. Rank quartile probabilities for univariate, joint outcome, and/or longitudinal models were compared to assess improvements in rank precision. Results The joint outcome model for poor physical and poor mental health days resulted in improved rank precision, as did the longitudinal model for age-specific mortality rates. Rank precision for low birth weight births and fair/poor health prevalence based on the univariate and joint outcome models were equivalent. Conclusion Incorporating longitudinal or pooled outcome data may improve rank certainty, depending on characteristics of the measures selected. For measures with different determinants, joint modeling neither improved nor degraded rank precision. This approach suggests a simple way to use existing information to improve the precision of small-area measures of population health. PMID:26098858

Effect of stress concentration on the fatigue strength of A7N01S-T5 welded joints

NASA Astrophysics Data System (ADS)

Zhang, Mingyue; Gou, Guoqing; Hang, Zongqiu; Chen, Hui

2017-07-01

Stress concentration is a key factor that affects the fatigue strength of welded joints. In this study, the fatigue strengths of butt joints with and without the weld reinforcement were tested to quantify the effect of stress concentration. The fatigue strength of the welded joints was measured with a high-frequency fatigue machine. The P-S-N curves were drawn under different confidence levels and failure probabilities. The results show that butt joints with the weld reinforcement have much lower fatigue strength than joints without the weld reinforcement. Therefore, stress concentration introduced by the weld reinforcement should be controlled.

Lithostratigraphic interpretation from joint analysis of seismic tomography and magnetotelluric resistivity models using self-organizing map techniques

NASA Astrophysics Data System (ADS)

Bauer, K.; Muñoz, G.; Moeck, I.

2012-12-01

The combined interpretation of different models as derived from seismic tomography and magnetotelluric (MT) inversion represents a more efficient approach to determine the lithology of the subsurface compared with the separate treatment of each discipline. Such models can be developed independently or by application of joint inversion strategies. After the step of model generation using different geophysical methodologies, a joint interpretation work flow includes the following steps: (1) adjustment of a joint earth model based on the adapted, identical model geometry for the different methods, (2) classification of the model components (e.g. model blocks described by a set of geophysical parameters), and (3) re-mapping of the classified rock types to visualise their distribution within the earth model, and petrophysical characterization and interpretation. One possible approach for the classification of multi-parameter models is based on statistical pattern recognition, where different models are combined and translated into probability density functions. Classes of rock types are identified in these methods as isolated clusters with high probability density function values. Such techniques are well-established for the analysis of two-parameter models. Alternatively we apply self-organizing map (SOM) techniques, which have no limitations in the number of parameters to be analysed in the joint interpretation. Our SOM work flow includes (1) generation of a joint earth model described by so-called data vectors, (2) unsupervised learning or training, (3) analysis of the feature map by adopting image processing techniques, and (4) application of the knowledge to derive a lithological model which is based on the different geophysical parameters. We show the usage of the SOM work flow for a synthetic and a real data case study. Both tests rely on three geophysical properties: P velocity and vertical velocity gradient from seismic tomography, and electrical resistivity from MT inversion. The synthetic data are used as a benchmark test to demonstrate the performance of the SOM method. The real data were collected along a 40 km profile across parts of the NE German basin. The lithostratigraphic model from the joint SOM interpretation consists of eight litho-types and covers Cenozoic, Mesozoic and Paleozoic sediments down to 5 km depth. There is a remarkable agreement between the SOM based model and regional marker horizons interpolated from surrounding 2D industrial seismic data. The most interesting results include (1) distinct properties of the Jurassic (low P velocity gradients, low resistivities) interpreted as the signature of shaly clastics, and (2) a pattern within the Upper Permian Zechstein with decreased resistivities and increased P velocities within the salt depressions on the one hand, and increased resistivities and decreased P velocities in the salt pillows on the other hand. In our interpretation this pattern is related with flow of less dense salt matrix components into the pillows and remaining brittle evaporites within the depressions.

Probability of spacesuit-induced fingernail trauma is associated with hand circumference.

PubMed

Opperman, Roedolph A; Waldie, James M A; Natapoff, Alan; Newman, Dava J; Jones, Jeffrey A

2010-10-01

A significant number of astronauts sustain hand injuries during extravehicular activity training and operations. These hand injuries have been known to cause fingernail delamination (onycholysis) that requires medical intervention. This study investigated correlations between the anthropometrics of the hand and susceptibility to injury. The analysis explored the hypothesis that crewmembers with a high finger-to-hand size ratio are more likely to experience injuries. A database of 232 crewmembers' injury records and anthropometrics was sourced from NASA Johnson Space Center. No significant effect of finger-to-hand size was found on the probability of injury, but circumference and width of the metacarpophalangeal (MCP) joint were found to be significantly associated with injuries by the Kruskal-Wallis test. A multivariate logistic regression showed that hand circumference is the dominant effect on the likelihood of onycholysis. Male crewmembers with a hand circumference > 22.86 cm (9") have a 19.6% probability of finger injury, but those with hand circumferences < or = 22.86 cm (9") only have a 5.6% chance of injury. Findings were similar for female crewmembers. This increased probability may be due to constriction at large MCP joints by the current NASA Phase VI glove. Constriction may lead to occlusion of vascular flow to the fingers that may increase the chances of onycholysis. Injury rates are lower on gloves such as the superseded series 4000 and the Russian Orlan that provide more volume for the MCP joint. This suggests that we can reduce onycholysis by modifying the design of the current gloves at the MCP joint.

Joint coverage probability in a simulation study on Continuous-Time Markov Chain parameter estimation.

PubMed

Benoit, Julia S; Chan, Wenyaw; Doody, Rachelle S

2015-01-01

Parameter dependency within data sets in simulation studies is common, especially in models such as Continuous-Time Markov Chains (CTMC). Additionally, the literature lacks a comprehensive examination of estimation performance for the likelihood-based general multi-state CTMC. Among studies attempting to assess the estimation, none have accounted for dependency among parameter estimates. The purpose of this research is twofold: 1) to develop a multivariate approach for assessing accuracy and precision for simulation studies 2) to add to the literature a comprehensive examination of the estimation of a general 3-state CTMC model. Simulation studies are conducted to analyze longitudinal data with a trinomial outcome using a CTMC with and without covariates. Measures of performance including bias, component-wise coverage probabilities, and joint coverage probabilities are calculated. An application is presented using Alzheimer's disease caregiver stress levels. Comparisons of joint and component-wise parameter estimates yield conflicting inferential results in simulations from models with and without covariates. In conclusion, caution should be taken when conducting simulation studies aiming to assess performance and choice of inference should properly reflect the purpose of the simulation.

Correlations between polarisation states of W particles in the reaction e - e +→ W - W + at LEP2 energies 189-209 GeV

NASA Astrophysics Data System (ADS)

Abdallah, J.; Abreu, P.; Adam, W.; Adzic, P.; Albrecht, T.; Alemany-Fernandez, R.; Allmendinger, T.; Allport, P. P.; Amaldi, U.; Amapane, N.; Amato, S.; Anashkin, E.; Andreazza, A.; Andringa, S.; Anjos, N.; Antilogus, P.; Apel, W.-D.; Arnoud, Y.; Ask, S.; Asman, B.; Augustin, J. E.; Augustinus, A.; Baillon, P.; Ballestrero, A.; Bambade, P.; Barbier, R.; Bardin, D.; Barker, G. J.; Baroncelli, A.; Battaglia, M.; Baubillier, M.; Becks, K.-H.; Begalli, M.; Behrmann, A.; Ben-Haim, E.; Benekos, N.; Benvenuti, A.; Berat, C.; Berggren, M.; Bertrand, D.; Besancon, M.; Besson, N.; Bloch, D.; Blom, M.; Bluj, M.; Bonesini, M.; Boonekamp, M.; Booth, P. S. L.; Borisov, G.; Botner, O.; Bouquet, B.; Bowcock, T. J. V.; Boyko, I.; Bracko, M.; Brenner, R.; Brodet, E.; Bruckman, P.; Brunet, J. M.; Buschbeck, B.; Buschmann, P.; Calvi, M.; Camporesi, T.; Canale, V.; Carena, F.; Castro, N.; Cavallo, F.; Chapkin, M.; Charpentier, Ph.; Checchia, P.; Chierici, R.; Chliapnikov, P.; Chudoba, J.; Chung, S. U.; Cieslik, K.; Collins, P.; Contri, R.; Cosme, G.; Cossutti, F.; Costa, M. J.; Crennell, D.; Cuevas, J.; D'Hondt, J.; da Silva, T.; da Silva, W.; Della Ricca, G.; de Angelis, A.; de Boer, W.; de Clercq, C.; de Lotto, B.; de Maria, N.; de Min, A.; de Paula, L.; di Ciaccio, L.; di Simone, A.; Doroba, K.; Drees, J.; Eigen, G.; Ekelof, T.; Ellert, M.; Elsing, M.; Espirito Santo, M. C.; Fanourakis, G.; Fassouliotis, D.; Feindt, M.; Fernandez, J.; Ferrer, A.; Ferro, F.; Flagmeyer, U.; Foeth, H.; Fokitis, E.; Fulda-Quenzer, F.; Fuster, J.; Gandelman, M.; Garcia, C.; Gavillet, Ph.; Gazis, E.; Gokieli, R.; Golob, B.; Gomez-Ceballos, G.; Goncalves, P.; Graziani, E.; Grosdidier, G.; Grzelak, K.; Guy, J.; Haag, C.; Hallgren, A.; Hamacher, K.; Hamilton, K.; Haug, S.; Hauler, F.; Hedberg, V.; Hennecke, M.; Hoffman, J.; Holmgren, S.-O.; Holt, P. J.; Houlden, M. A.; Jackson, J. N.; Jarlskog, G.; Jarry, P.; Jeans, D.; Johansson, E. K.; Jonsson, P.; Joram, C.; Jungermann, L.; Kapusta, F.; Katsanevas, S.; Katsoufis, E.; Kernel, G.; Kersevan, B. P.; Kerzel, U.; King, B. T.; Kjaer, N. J.; Kluit, P.; Kokkinias, P.; Kourkoumelis, C.; Kouznetsov, O.; Krumstein, Z.; Kucharczyk, M.; Lamsa, J.; Leder, G.; Ledroit, F.; Leinonen, L.; Leitner, R.; Lemonne, J.; Lepeltier, V.; Lesiak, T.; Liebig, W.; Liko, D.; Lipniacka, A.; Lopes, J. H.; Lopez, J. M.; Loukas, D.; Lutz, P.; Lyons, L.; MacNaughton, J.; Malek, A.; Maltezos, S.; Mandl, F.; Marco, J.; Marco, R.; Marechal, B.; Margoni, M.; Marin, J.-C.; Mariotti, C.; Markou, A.; Martinez-Rivero, C.; Masik, J.; Mastroyiannopoulos, N.; Matorras, F.; Matteuzzi, C.; Mazzucato, F.; Mazzucato, M.; McNulty, R.; Meroni, C.; Migliore, E.; Mitaroff, W.; Mjoernmark, U.; Moa, T.; Moch, M.; Moenig, K.; Monge, R.; Montenegro, J.; Moraes, D.; Moreno, S.; Morettini, P.; Mueller, U.; Muenich, K.; Mulders, M.; Mundim, L.; Murray, W.; Muryn, B.; Myatt, G.; Myklebust, T.; Nassiakou, M.; Navarria, F.; Nawrocki, K.; Nemecek, S.; Nicolaidou, R.; Nikolenko, M.; Oblakowska-Mucha, A.; Obraztsov, V.; Olshevski, A.; Onofre, A.; Orava, R.; Osterberg, K.; Ouraou, A.; Oyanguren, A.; Paganoni, M.; Paiano, S.; Palacios, J. P.; Palka, H.; Papadopoulou, Th. D.; Pape, L.; Parkes, C.; Parodi, F.; Parzefall, U.; Passeri, A.; Passon, O.; Peralta, L.; Perepelitsa, V.; Perrotta, A.; Petrolini, A.; Piedra, J.; Pieri, L.; Pierre, F.; Pimenta, M.; Piotto, E.; Podobnik, T.; Poireau, V.; Pol, M. E.; Polok, G.; Pozdniakov, V.; Pukhaeva, N.; Pullia, A.; Radojicic, D.; Rebecchi, P.; Rehn, J.; Reid, D.; Reinhardt, R.; Renton, P.; Richard, F.; Ridky, J.; Rivero, M.; Rodriguez, D.; Romero, A.; Ronchese, P.; Roudeau, P.; Rovelli, T.; Ruhlmann-Kleider, V.; Ryabtchikov, D.; Sadovsky, A.; Salmi, L.; Salt, J.; Sander, C.; Savoy-Navarro, A.; Schwickerath, U.; Sekulin, R.; Siebel, M.; Sisakian, A.; Smadja, G.; Smirnova, O.; Sokolov, A.; Sopczak, A.; Sosnowski, R.; Spassov, T.; Stanitzki, M.; Stocchi, A.; Strauss, J.; Stugu, B.; Szczekowski, M.; Szeptycka, M.; Szumlak, T.; Tabarelli, T.; Tegenfeldt, F.; Timmermans, J.; Tkatchev, L.; Tobin, M.; Todorovova, S.; Tome, B.; Tonazzo, A.; Tortosa, P.; Travnicek, P.; Treille, D.; Tristram, G.; Trochimczuk, M.; Troncon, C.; Turluer, M.-L.; Tyapkin, I. A.; Tyapkin, P.; Tzamarias, S.; Uvarov, V.; Valenti, G.; van Dam, P.; van Eldik, J.; van Remortel, N.; van Vulpen, I.; Vegni, G.; Veloso, F.; Venus, W.; Verdier, P.; Verzi, V.; Vilanova, D.; Vitale, L.; Vrba, V.; Wahlen, H.; Washbrook, A. J.; Weiser, C.; Wicke, D.; Wickens, J.; Wilkinson, G.; Winter, M.; Witek, M.; Yushchenko, O.; Zalewska, A.; Zalewski, P.; Zavrtanik, D.; Zhuravlov, V.; Zimin, N. I.; Zintchenko, A.; Zupan, M.

2009-10-01

In a study of the reaction e - e +→ W - W + with the DELPHI detector, the probabilities of the two W particles occurring in the joint polarisation states transverse-transverse ( TT), longitudinal-transverse plus transverse-longitudinal ( LT) and longitudinal-longitudinal ( LL) have been determined using the final states WW{rightarrow}lν qbar{q} ( l= e, μ). The two-particle joint polarisation probabilities, i.e. the spin density matrix elements ρ TT , ρ LT , ρ LL , are measured as functions of the W - production angle, θ _{W-}, at an average reaction energy of 198.2 GeV. Averaged over all \\cosθ_{W-}, the following joint probabilities are obtained: bar{ρ}_{TT}=(67±8)%, bar{ρ}_{LT}=(30±8)%, bar{ρ}_{LL}=(3±7)%. These results are in agreement with the Standard Model predictions of 63.0%, 28.9% and 8.1%, respectively. The related polarisation cross-sections σ TT , σ LT and σ LL are also presented.

Clinical results of resection arthrodesis by triangular external fixation for posttraumatic arthrosis of the ankle joint in 89 cases.

PubMed

Kiene, J; Schulz, Arndt P; Hillbricht, S; Jürgens, Ch; Paech, A

2009-01-28

The methods for ankle arthrodesis differ significantly, probably a sign that no method is clearly superior to others. In the last ten years there is a clear favour toward internal fixation. We retrospectively evaluate the technique and evaluate the clinical long term results of external fixation in a triangular frame. From 1994 to 2001 a consecutive series of 95 patients with end stage arthritis of the ankle joint were treated. Retrospectively the case notes were evaluated regarding trauma history, medical complaints, further injuries and illnesses, walking and pain status and occupational issues and the clinical examination before arthrodesis. Mean age at the index procedure was 45.4 years (18-82), 67 patients were male (70.5%). Via a bilateral approach the malleoli and the joint surfaces were resected. An AO fixator was applied with two Steinmann-nails inserted with approximately 8 cm distance in the distal tibia, one in the neck of the talus and one in the dorsal calcaneus. The fixator was removed after approximately 12 weeks. Follow up examination at mean 4.4 years included a standardised questionnaire and a clinical examination including the criteria of the AOFAS-Score and radiographs. Due to different complications, 8 (8.9%) further surgical procedures were necessary including 1 below knee amputation. In 4 patients a non-union of the ankle arthrodesis developed (4.5%). The mean AOFAS score improved from 20.8 to 69.3 points. Non-union rates and clinical results of arthrodesis by triangular external fixation of the ankle joint do not differ to internal fixation methods. The complication rate and the reduced patient comfort reserve this method mainly for infected arthritis and complicated soft tissue situations.

Joint analysis of epistemic and aleatory uncertainty in stability analysis for geo-hazard assessments

NASA Astrophysics Data System (ADS)

Rohmer, Jeremy; Verdel, Thierry

2017-04-01

Uncertainty analysis is an unavoidable task of stability analysis of any geotechnical systems. Such analysis usually relies on the safety factor SF (if SF is below some specified threshold), the failure is possible). The objective of the stability analysis is then to estimate the failure probability P for SF to be below the specified threshold. When dealing with uncertainties, two facets should be considered as outlined by several authors in the domain of geotechnics, namely "aleatoric uncertainty" (also named "randomness" or "intrinsic variability") and "epistemic uncertainty" (i.e. when facing "vague, incomplete or imprecise information" such as limited databases and observations or "imperfect" modelling). The benefits of separating both facets of uncertainty can be seen from a risk management perspective because: - Aleatoric uncertainty, being a property of the system under study, cannot be reduced. However, practical actions can be taken to circumvent the potentially dangerous effects of such variability; - Epistemic uncertainty, being due to the incomplete/imprecise nature of available information, can be reduced by e.g., increasing the number of tests (lab or in site survey), improving the measurement methods or evaluating calculation procedure with model tests, confronting more information sources (expert opinions, data from literature, etc.). Uncertainty treatment in stability analysis usually restricts to the probabilistic framework to represent both facets of uncertainty. Yet, in the domain of geo-hazard assessments (like landslides, mine pillar collapse, rockfalls, etc.), the validity of this approach can be debatable. In the present communication, we propose to review the major criticisms available in the literature against the systematic use of probability in situations of high degree of uncertainty. On this basis, the feasibility of using a more flexible uncertainty representation tool is then investigated, namely Possibility distributions (e.g., Baudrit et al., 2007) for geo-hazard assessments. A graphical tool is then developed to explore: 1. the contribution of both types of uncertainty, aleatoric and epistemic; 2. the regions of the imprecise or random parameters which contribute the most to the imprecision on the failure probability P. The method is applied on two case studies (a mine pillar and a steep slope stability analysis, Rohmer and Verdel, 2014) to investigate the necessity for extra data acquisition on parameters whose imprecision can hardly be modelled by probabilities due to the scarcity of the available information (respectively the extraction ratio and the cliff geometry). References Baudrit, C., Couso, I., & Dubois, D. (2007). Joint propagation of probability and possibility in risk analysis: Towards a formal framework. International Journal of Approximate Reasoning, 45(1), 82-105. Rohmer, J., & Verdel, T. (2014). Joint exploration of regional importance of possibilistic and probabilistic uncertainty in stability analysis. Computers and Geotechnics, 61, 308-315.

Technology-enhanced Interactive Teaching of Marginal, Joint and Conditional Probabilities: The Special Case of Bivariate Normal Distribution

PubMed Central

Dinov, Ivo D.; Kamino, Scott; Bhakhrani, Bilal; Christou, Nicolas

2014-01-01

Summary Data analysis requires subtle probability reasoning to answer questions like What is the chance of event A occurring, given that event B was observed? This generic question arises in discussions of many intriguing scientific questions such as What is the probability that an adolescent weighs between 120 and 140 pounds given that they are of average height? and What is the probability of (monetary) inflation exceeding 4% and housing price index below 110? To address such problems, learning some applied, theoretical or cross-disciplinary probability concepts is necessary. Teaching such courses can be improved by utilizing modern information technology resources. Students’ understanding of multivariate distributions, conditional probabilities, correlation and causation can be significantly strengthened by employing interactive web-based science educational resources. Independent of the type of a probability course (e.g. majors, minors or service probability course, rigorous measure-theoretic, applied or statistics course) student motivation, learning experiences and knowledge retention may be enhanced by blending modern technological tools within the classical conceptual pedagogical models. We have designed, implemented and disseminated a portable open-source web-application for teaching multivariate distributions, marginal, joint and conditional probabilities using the special case of bivariate Normal distribution. A real adolescent height and weight dataset is used to demonstrate the classroom utilization of the new web-application to address problems of parameter estimation, univariate and multivariate inference. PMID:25419016

Technology-enhanced Interactive Teaching of Marginal, Joint and Conditional Probabilities: The Special Case of Bivariate Normal Distribution.

PubMed

Dinov, Ivo D; Kamino, Scott; Bhakhrani, Bilal; Christou, Nicolas

2013-01-01

Data analysis requires subtle probability reasoning to answer questions like What is the chance of event A occurring, given that event B was observed? This generic question arises in discussions of many intriguing scientific questions such as What is the probability that an adolescent weighs between 120 and 140 pounds given that they are of average height? and What is the probability of (monetary) inflation exceeding 4% and housing price index below 110? To address such problems, learning some applied, theoretical or cross-disciplinary probability concepts is necessary. Teaching such courses can be improved by utilizing modern information technology resources. Students' understanding of multivariate distributions, conditional probabilities, correlation and causation can be significantly strengthened by employing interactive web-based science educational resources. Independent of the type of a probability course (e.g. majors, minors or service probability course, rigorous measure-theoretic, applied or statistics course) student motivation, learning experiences and knowledge retention may be enhanced by blending modern technological tools within the classical conceptual pedagogical models. We have designed, implemented and disseminated a portable open-source web-application for teaching multivariate distributions, marginal, joint and conditional probabilities using the special case of bivariate Normal distribution. A real adolescent height and weight dataset is used to demonstrate the classroom utilization of the new web-application to address problems of parameter estimation, univariate and multivariate inference.

Combining Gravitational Wave Events with their Electromagnetic Counterparts: A Realistic Joint False-Alarm Rate

NASA Astrophysics Data System (ADS)

Ackley, Kendall; Eikenberry, Stephen; Klimenko, Sergey; LIGO Team

2017-01-01

We present a false-alarm rate for a joint detection of gravitational wave (GW) events and associated electromagnetic (EM) counterparts for Advanced LIGO and Virgo (LV) observations during the first years of operation. Using simulated GW events and their recostructed probability skymaps, we tile over the error regions using sets of archival wide-field telescope survey images and recover the number of astrophysical transients to be expected during LV-EM followup. With the known GW event injection coordinates we inject artificial electromagnetic (EM) sources at that site based on theoretical and observational models on a one-to-one basis. We calculate the EM false-alarm probability using an unsupervised machine learning algorithm based on shapelet analysis which has shown to be a strong discriminator between astrophysical transients and image artifacts while reducing the set of transients to be manually vetted by five orders of magnitude. We also show the performance of our method in context with other machine-learned transient classification and reduction algorithms, showing comparability without the need for a large set of training data opening the possibility for next-generation telescopes to take advantage of this pipeline for LV-EM followup missions.

Evaluation of joint probability density function models for turbulent nonpremixed combustion with complex chemistry

NASA Technical Reports Server (NTRS)

Smith, N. S. A.; Frolov, S. M.; Bowman, C. T.

1996-01-01

Two types of mixing sub-models are evaluated in connection with a joint-scalar probability density function method for turbulent nonpremixed combustion. Model calculations are made and compared to simulation results for homogeneously distributed methane-air reaction zones mixing and reacting in decaying turbulence within a two-dimensional enclosed domain. The comparison is arranged to ensure that both the simulation and model calculations a) make use of exactly the same chemical mechanism, b) do not involve non-unity Lewis number transport of species, and c) are free from radiation loss. The modified Curl mixing sub-model was found to provide superior predictive accuracy over the simple relaxation-to-mean submodel in the case studied. Accuracy to within 10-20% was found for global means of major species and temperature; however, nitric oxide prediction accuracy was lower and highly dependent on the choice of mixing sub-model. Both mixing submodels were found to produce non-physical mixing behavior for mixture fractions removed from the immediate reaction zone. A suggestion for a further modified Curl mixing sub-model is made in connection with earlier work done in the field.

Exact joint density-current probability function for the asymmetric exclusion process.

PubMed

Depken, Martin; Stinchcombe, Robin

2004-07-23

We study the asymmetric simple exclusion process with open boundaries and derive the exact form of the joint probability function for the occupation number and the current through the system. We further consider the thermodynamic limit, showing that the resulting distribution is non-Gaussian and that the density fluctuations have a discontinuity at the continuous phase transition, while the current fluctuations are continuous. The derivations are performed by using the standard operator algebraic approach and by the introduction of new operators satisfying a modified version of the original algebra. Copyright 2004 The American Physical Society

Probabilistic image modeling with an extended chain graph for human activity recognition and image segmentation.

PubMed

Zhang, Lei; Zeng, Zhi; Ji, Qiang

2011-09-01

Chain graph (CG) is a hybrid probabilistic graphical model (PGM) capable of modeling heterogeneous relationships among random variables. So far, however, its application in image and video analysis is very limited due to lack of principled learning and inference methods for a CG of general topology. To overcome this limitation, we introduce methods to extend the conventional chain-like CG model to CG model with more general topology and the associated methods for learning and inference in such a general CG model. Specifically, we propose techniques to systematically construct a generally structured CG, to parameterize this model, to derive its joint probability distribution, to perform joint parameter learning, and to perform probabilistic inference in this model. To demonstrate the utility of such an extended CG, we apply it to two challenging image and video analysis problems: human activity recognition and image segmentation. The experimental results show improved performance of the extended CG model over the conventional directed or undirected PGMs. This study demonstrates the promise of the extended CG for effective modeling and inference of complex real-world problems.

Seal Integrity of Selected Fuzes as Measured by Three Leak Test Methods

DTIC Science & Technology

1976-09-01

the worst fuze from the seal standpoint. The M503A-2 fuze body is made from a cast aluminum alloy . The casting process leaves voids which, after...leak resistance of the joint. WDU4A/A The design of this fuze depends upon ultrasonic welding to seal lid to case. The specified leak test merely...test is probably one of the better leakage tests from an effectiveness standpoint. However, from lot quantities of 690 and 480, reject rates of 20% were

Technology-Enhanced Interactive Teaching of Marginal, Joint and Conditional Probabilities: The Special Case of Bivariate Normal Distribution

ERIC Educational Resources Information Center

Dinov, Ivo D.; Kamino, Scott; Bhakhrani, Bilal; Christou, Nicolas

2013-01-01

Data analysis requires subtle probability reasoning to answer questions like "What is the chance of event A occurring, given that event B was observed?" This generic question arises in discussions of many intriguing scientific questions such as "What is the probability that an adolescent weighs between 120 and 140 pounds given that…

On probability-possibility transformations

NASA Technical Reports Server (NTRS)

Klir, George J.; Parviz, Behzad

1992-01-01

Several probability-possibility transformations are compared in terms of the closeness of preserving second-order properties. The comparison is based on experimental results obtained by computer simulation. Two second-order properties are involved in this study: noninteraction of two distributions and projections of a joint distribution.

Hydrologic risk analysis in the Yangtze River basin through coupling Gaussian mixtures into copulas

NASA Astrophysics Data System (ADS)

Fan, Y. R.; Huang, W. W.; Huang, G. H.; Li, Y. P.; Huang, K.; Li, Z.

2016-02-01

In this study, a bivariate hydrologic risk framework is proposed through coupling Gaussian mixtures into copulas, leading to a coupled GMM-copula method. In the coupled GMM-Copula method, the marginal distributions of flood peak, volume and duration are quantified through Gaussian mixture models and the joint probability distributions of flood peak-volume, peak-duration and volume-duration are established through copulas. The bivariate hydrologic risk is then derived based on the joint return period of flood variable pairs. The proposed method is applied to the risk analysis for the Yichang station on the main stream of the Yangtze River, China. The results indicate that (i) the bivariate risk for flood peak-volume would keep constant for the flood volume less than 1.0 × 105 m3/s day, but present a significant decreasing trend for the flood volume larger than 1.7 × 105 m3/s day; and (ii) the bivariate risk for flood peak-duration would not change significantly for the flood duration less than 8 days, and then decrease significantly as duration value become larger. The probability density functions (pdfs) of the flood volume and duration conditional on flood peak can also be generated through the fitted copulas. The results indicate that the conditional pdfs of flood volume and duration follow bimodal distributions, with the occurrence frequency of the first vertex decreasing and the latter one increasing as the increase of flood peak. The obtained conclusions from the bivariate hydrologic analysis can provide decision support for flood control and mitigation.

Aquatic predicted no-effect concentrations of 16 polycyclic aromatic hydrocarbons and their ecological risks in surface seawater of Liaodong Bay, China.

PubMed

Wang, Ying; Wang, Juying; Mu, Jingli; Wang, Zhen; Cong, Yi; Yao, Ziwei; Lin, Zhongsheng

2016-06-01

Polycyclic aromatic hydrocarbons (PAHs), a class of ubiquitous pollutants in marine environments, exhibit moderate to high adverse effects on aquatic organisms and humans. However, the lack of PAH toxicity data for aquatic organism has limited evaluation of their ecological risks. In the present study, aquatic predicted no-effect concentrations (PNECs) of 16 priority PAHs were derived based on species sensitivity distribution models, and their probabilistic ecological risks in seawater of Liaodong Bay, Bohai Sea, China, were assessed. A quantitative structure-activity relationship method was adopted to achieve the predicted chronic toxicity data for the PNEC derivation. Good agreement for aquatic PNECs of 8 PAHs based on predicted and experimental chronic toxicity data was observed (R(2)  = 0.746), and the calculated PNECs ranged from 0.011 µg/L to 205.3 µg/L. A significant log-linear relationship also existed between the octanol-water partition coefficient and PNECs derived from experimental toxicity data (R(2)  = 0.757). A similar order of ecological risks for the 16 PAH species in seawater of Liaodong Bay was found by probabilistic risk quotient and joint probability curve methods. The individual high ecological risk of benzo[a]pyrene, benzo[b]fluoranthene, and benz[a]anthracene needs to be determined. The combined ecological risk of PAHs in seawater of Liaodong Bay calculated by the joint probability curve method was 13.9%, indicating a high risk as a result of co-exposure to PAHs. Environ Toxicol Chem 2016;35:1587-1593. © 2015 SETAC. © 2015 SETAC.

Time- and temperature-dependent failures of a bonded joint

NASA Astrophysics Data System (ADS)

Sihn, Sangwook

This dissertation summarizes my study of time- and temperature-dependent behavior of a tubular lap bonded joint to provide a design methodology for windmill blade structures. The bonded joint is between a cast-iron rod and a GFRP composite pipe. The adhesive material is an epoxy containing chopped glass fibers. We proposed a new fabrication method to make concentric and void-less specimens of the tubular joint with a thick adhesive bondline to stimulate the root bond of a blade. The thick bondline facilitates the joint assembly of actual blades. For a better understanding of the behavior of the bonded joint, we studied viscoelastic behavior of the adhesive materials by measuring creep compliance at several temperatures during loading period. We observed that the creep compliance depends highly on the period of loading and the temperature. We applied time-temperature equivalence to the creep compliance of the adhesive material to obtain time-temperature shift factors. We also performed constant-rate of monotonically increased uniaxial tensile tests to measure static strength of the tubular lap joint at several temperatures and different strain-rates. We observed two failure modes from load-deflection curves and failed specimens. One is the brittle mode, which was caused by weakness of the interfacial strength occurring at low temperature and short period of loading. The other is the ductile mode, which was caused by weakness of the adhesive material at high temperature and long period of loading. Transition from the brittle to the ductile mode appeared as the temperature or the loading period increased. We also performed tests under uniaxial tensile-tensile cyclic loadings to measure fatigue strength of the bonded joint at several temperatures, frequencies and stress ratios. The fatigue data are analyzed statistically by applying the residual strength degradation model to calculate statistical distribution of the fatigue life. Combining the time-temperature equivalence and the residual strength degradation model enables us to estimate the fatigue life of the bonded joint at different load levels, frequencies and temperatures with a certain probability. A numerical example shows how to apply the life estimation method to a structure subjected to a random load history by rainflow cycle counting.

A Causal Model for Joint Evaluation of Placebo and Treatment-Specific Effects in Clinical Trials

PubMed Central

Zhang, Zhiwei; Kotz, Richard M.; Wang, Chenguang; Ruan, Shiling; Ho, Martin

2014-01-01

Summary Evaluation of medical treatments is frequently complicated by the presence of substantial placebo effects, especially on relatively subjective endpoints, and the standard solution to this problem is a randomized, double-blinded, placebo-controlled clinical trial. However, effective blinding does not guarantee that all patients have the same belief or mentality about which treatment they have received (or treatmentality, for brevity), making it difficult to interpret the usual intent-to-treat effect as a causal effect. We discuss the causal relationships among treatment, treatmentality and the clinical outcome of interest, and propose a causal model for joint evaluation of placebo and treatment-specific effects. The model highlights the importance of measuring and incorporating patient treatmentality and suggests that each treatment group should be considered a separate observational study with a patient's treatmentality playing the role of an uncontrolled exposure. This perspective allows us to adapt existing methods for dealing with confounding to joint estimation of placebo and treatment-specific effects using measured treatmentality data, commonly known as blinding assessment data. We first apply this approach to the most common type of blinding assessment data, which is categorical, and illustrate the methods using an example from asthma. We then propose that blinding assessment data can be collected as a continuous variable, specifically when a patient's treatmentality is measured as a subjective probability, and describe analytic methods for that case. PMID:23432119

Statistical Analysis of Stress Signals from Bridge Monitoring by FBG System

PubMed Central

Ye, Xiao-Wei; Xi, Pei-Sen

2018-01-01

In this paper, a fiber Bragg grating (FBG)-based stress monitoring system instrumented on an orthotropic steel deck arch bridge is demonstrated. The FBG sensors are installed at two types of critical fatigue-prone welded joints to measure the strain and temperature signals. A total of 64 FBG sensors are deployed around the rib-to-deck and rib-to-diagram areas at the mid-span and quarter-span of the investigated orthotropic steel bridge. The local stress behaviors caused by the highway loading and temperature effect during the construction and operation periods are presented with the aid of a wavelet multi-resolution analysis approach. In addition, the multi-modal characteristic of the rainflow counted stress spectrum is modeled by the method of finite mixture distribution together with a genetic algorithm (GA)-based parameter estimation approach. The optimal probability distribution of the stress spectrum is determined by use of Bayesian information criterion (BIC). Furthermore, the hot spot stress of the welded joint is calculated by an extrapolation method recommended in the specification of International Institute of Welding (IIW). The stochastic characteristic of stress concentration factor (SCF) of the concerned welded joint is addressed. The proposed FBG-based stress monitoring system and probabilistic stress evaluation methods can provide an effective tool for structural monitoring and condition assessment of orthotropic steel bridges. PMID:29414850

Automatic lung tumor segmentation on PET/CT images using fuzzy Markov random field model.

PubMed

Guo, Yu; Feng, Yuanming; Sun, Jian; Zhang, Ning; Lin, Wang; Sa, Yu; Wang, Ping

2014-01-01

The combination of positron emission tomography (PET) and CT images provides complementary functional and anatomical information of human tissues and it has been used for better tumor volume definition of lung cancer. This paper proposed a robust method for automatic lung tumor segmentation on PET/CT images. The new method is based on fuzzy Markov random field (MRF) model. The combination of PET and CT image information is achieved by using a proper joint posterior probability distribution of observed features in the fuzzy MRF model which performs better than the commonly used Gaussian joint distribution. In this study, the PET and CT simulation images of 7 non-small cell lung cancer (NSCLC) patients were used to evaluate the proposed method. Tumor segmentations with the proposed method and manual method by an experienced radiation oncologist on the fused images were performed, respectively. Segmentation results obtained with the two methods were similar and Dice's similarity coefficient (DSC) was 0.85 ± 0.013. It has been shown that effective and automatic segmentations can be achieved with this method for lung tumors which locate near other organs with similar intensities in PET and CT images, such as when the tumors extend into chest wall or mediastinum.

Tackling missing radiographic progression data: multiple imputation technique compared with inverse probability weights and complete case analysis.

PubMed

Descalzo, Miguel Á; Garcia, Virginia Villaverde; González-Alvaro, Isidoro; Carbonell, Jordi; Balsa, Alejandro; Sanmartí, Raimon; Lisbona, Pilar; Hernandez-Barrera, Valentín; Jiménez-Garcia, Rodrigo; Carmona, Loreto

2013-02-01

To describe the results of different statistical ways of addressing radiographic outcome affected by missing data--multiple imputation technique, inverse probability weights and complete case analysis--using data from an observational study. A random sample of 96 RA patients was selected for a follow-up study in which radiographs of hands and feet were scored. Radiographic progression was tested by comparing the change in the total Sharp-van der Heijde radiographic score (TSS) and the joint erosion score (JES) from baseline to the end of the second year of follow-up. MI technique, inverse probability weights in weighted estimating equation (WEE) and CC analysis were used to fit a negative binomial regression. Major predictors of radiographic progression were JES and joint space narrowing (JSN) at baseline, together with baseline disease activity measured by DAS28 for TSS and MTX use for JES. Results from CC analysis show larger coefficients and s.e.s compared with MI and weighted techniques. The results from the WEE model were quite in line with those of MI. If it seems plausible that CC or MI analysis may be valid, then MI should be preferred because of its greater efficiency. CC analysis resulted in inefficient estimates or, translated into non-statistical terminology, could guide us into inaccurate results and unwise conclusions. The methods discussed here will contribute to the use of alternative approaches for tackling missing data in observational studies.

A multivariate quadrature based moment method for LES based modeling of supersonic combustion

NASA Astrophysics Data System (ADS)

Donde, Pratik; Koo, Heeseok; Raman, Venkat

2012-07-01

The transported probability density function (PDF) approach is a powerful technique for large eddy simulation (LES) based modeling of scramjet combustors. In this approach, a high-dimensional transport equation for the joint composition-enthalpy PDF needs to be solved. Quadrature based approaches provide deterministic Eulerian methods for solving the joint-PDF transport equation. In this work, it is first demonstrated that the numerical errors associated with LES require special care in the development of PDF solution algorithms. The direct quadrature method of moments (DQMOM) is one quadrature-based approach developed for supersonic combustion modeling. This approach is shown to generate inconsistent evolution of the scalar moments. Further, gradient-based source terms that appear in the DQMOM transport equations are severely underpredicted in LES leading to artificial mixing of fuel and oxidizer. To overcome these numerical issues, a semi-discrete quadrature method of moments (SeQMOM) is formulated. The performance of the new technique is compared with the DQMOM approach in canonical flow configurations as well as a three-dimensional supersonic cavity stabilized flame configuration. The SeQMOM approach is shown to predict subfilter statistics accurately compared to the DQMOM approach.

Evidence-based Diagnostics: Adult Septic Arthritis

PubMed Central

Carpenter, Christopher R.; Schuur, Jeremiah D.; Everett, Worth W.; Pines, Jesse M.

2011-01-01

Background Acutely swollen or painful joints are common complaints in the emergency department (ED). Septic arthritis in adults is a challenging diagnosis, but prompt differentiation of a bacterial etiology is crucial to minimize morbidity and mortality. Objectives The objective was to perform a systematic review describing the diagnostic characteristics of history, physical examination, and bedside laboratory tests for nongonococcal septic arthritis. A secondary objective was to quantify test and treatment thresholds using derived estimates of sensitivity and specificity, as well as best-evidence diagnostic and treatment risks and anticipated benefits from appropriate therapy. Methods Two electronic search engines (PUBMED and EMBASE) were used in conjunction with a selected bibliography and scientific abstract hand search. Inclusion criteria included adult trials of patients presenting with monoarticular complaints if they reported sufficient detail to reconstruct partial or complete 2 × 2 contingency tables for experimental diagnostic test characteristics using an acceptable criterion standard. Evidence was rated by two investigators using the Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS). When more than one similarly designed trial existed for a diagnostic test, meta-analysis was conducted using a random effects model. Interval likelihood ratios (LRs) were computed when possible. To illustrate one method to quantify theoretical points in the probability of disease whereby clinicians might cease testing altogether and either withhold treatment (test threshold) or initiate definitive therapy in lieu of further diagnostics (treatment threshold), an interactive spreadsheet was designed and sample calculations were provided based on research estimates of diagnostic accuracy, diagnostic risk, and therapeutic risk/benefits. Results The prevalence of nongonococcal septic arthritis in ED patients with a single acutely painful joint is approximately 27% (95% confidence interval [CI] = 17% to 38%). With the exception of joint surgery (positive likelihood ratio [+LR] = 6.9) or skin infection overlying a prosthetic joint (+LR = 15.0), history, physical examination, and serum tests do not significantly alter posttest probability. Serum inflammatory markers such as white blood cell (WBC) counts, erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP) are not useful acutely. The interval LR for synovial white blood cell (sWBC) counts of 0 × 109–25 × 109/ L was 0.33; for 25 × 109–50 × 109/L, 1.06; for 50 × 109–100 × 109/L, 3.59; and exceeding 100 × 109/L, infinity. Synovial lactate may be useful to rule in or rule out the diagnosis of septic arthritis with a +LR ranging from 2.4 to infinity, and negative likelihood ratio (−LR) ranging from 0 to 0.46. Rapid polymerase chain reaction (PCR) of synovial fluid may identify the causative organism within 3 hours. Based on 56% sensitivity and 90% specificity for sWBC counts of >50 × 109/L in conjunction with best-evidence estimates for diagnosis-related risk and treatment-related risk/benefit, the arthrocentesis test threshold is 5%, with a treatment threshold of 39%. Conclusions Recent joint surgery or cellulitis overlying a prosthetic hip or knee were the only findings on history or physical examination that significantly alter the probability of nongonococcal septic arthritis. Extreme values of sWBC (>50 × 109/L) can increase, but not decrease, the probability of septic arthritis. Future ED-based diagnostic trials are needed to evaluate the role of clinical gestalt and the efficacy of nontraditional synovial markers such as lactate. PMID:21843213

Multiple data sources improve DNA-based mark-recapture population estimates of grizzly bears.

PubMed

Boulanger, John; Kendall, Katherine C; Stetz, Jeffrey B; Roon, David A; Waits, Lisette P; Paetkau, David

2008-04-01

A fundamental challenge to estimating population size with mark-recapture methods is heterogeneous capture probabilities and subsequent bias of population estimates. Confronting this problem usually requires substantial sampling effort that can be difficult to achieve for some species, such as carnivores. We developed a methodology that uses two data sources to deal with heterogeneity and applied this to DNA mark-recapture data from grizzly bears (Ursus arctos). We improved population estimates by incorporating additional DNA "captures" of grizzly bears obtained by collecting hair from unbaited bear rub trees concurrently with baited, grid-based, hair snag sampling. We consider a Lincoln-Petersen estimator with hair snag captures as the initial session and rub tree captures as the recapture session and develop an estimator in program MARK that treats hair snag and rub tree samples as successive sessions. Using empirical data from a large-scale project in the greater Glacier National Park, Montana, USA, area and simulation modeling we evaluate these methods and compare the results to hair-snag-only estimates. Empirical results indicate that, compared with hair-snag-only data, the joint hair-snag-rub-tree methods produce similar but more precise estimates if capture and recapture rates are reasonably high for both methods. Simulation results suggest that estimators are potentially affected by correlation of capture probabilities between sample types in the presence of heterogeneity. Overall, closed population Huggins-Pledger estimators showed the highest precision and were most robust to sparse data, heterogeneity, and capture probability correlation among sampling types. Results also indicate that these estimators can be used when a segment of the population has zero capture probability for one of the methods. We propose that this general methodology may be useful for other species in which mark-recapture data are available from multiple sources.

Under-reported data analysis with INAR-hidden Markov chains.

PubMed

Fernández-Fontelo, Amanda; Cabaña, Alejandra; Puig, Pedro; Moriña, David

2016-11-20

In this work, we deal with correlated under-reported data through INAR(1)-hidden Markov chain models. These models are very flexible and can be identified through its autocorrelation function, which has a very simple form. A naïve method of parameter estimation is proposed, jointly with the maximum likelihood method based on a revised version of the forward algorithm. The most-probable unobserved time series is reconstructed by means of the Viterbi algorithm. Several examples of application in the field of public health are discussed illustrating the utility of the models. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

A PDF closure model for compressible turbulent chemically reacting flows

NASA Technical Reports Server (NTRS)

Kollmann, W.

1992-01-01

The objective of the proposed research project was the analysis of single point closures based on probability density function (pdf) and characteristic functions and the development of a prediction method for the joint velocity-scalar pdf in turbulent reacting flows. Turbulent flows of boundary layer type and stagnation point flows with and without chemical reactions were be calculated as principal applications. Pdf methods for compressible reacting flows were developed and tested in comparison with available experimental data. The research work carried in this project was concentrated on the closure of pdf equations for incompressible and compressible turbulent flows with and without chemical reactions.

HABITAT ASSESSMENT USING A RANDOM PROBABILITY BASED SAMPLING DESIGN: ESCAMBIA RIVER DELTA, FLORIDA

EPA Science Inventory

Smith, Lisa M., Darrin D. Dantin and Steve Jordan. In press. Habitat Assessment Using a Random Probability Based Sampling Design: Escambia River Delta, Florida (Abstract). To be presented at the SWS/GERS Fall Joint Society Meeting: Communication and Collaboration: Coastal Systems...

Quantifying Hydroperiod, Fire and Nutrient Effects on the Composition of Plant Communities in Marl Prairie of the Everglades: a Joint Probability Method Based Model

NASA Astrophysics Data System (ADS)

Zhai, L.

2017-12-01

Plant community can be simultaneously affected by human activities and climate changes, and quantifying and predicting this combined effect on plant community by appropriate model framework which is validated by field data is complex, but very useful to conservation management. Plant communities in the Everglades provide an unique set of conditions to develop and validate this model framework, because they are both experiencing intensive effects of human activities (such as changing hydroperiod by drainage and restoration projects, nutrients from upstream agriculture, prescribed fire, etc.) and climate changes (such as warming, changing precipitation patter, sea level rise, etc.). More importantly, previous research attention focuses on plant communities in slough ecosystem (including ridge, slough and their tree islands), very few studies consider the marl prairie ecosystem. Comparing with slough ecosystem featured by remaining consistently flooded almost year-round, marl prairie has relatively shorter hydroperiod (just in wet-season of one year). Therefore, plant communities of marl prairie may receive more impacts from hydroperiod change. In addition to hydroperiod, fire and nutrients also affect the plant communities in the marl prairie. Therefore, to quantify the combined effects of water level, fire, and nutrients on the composition of the plant communities, we are developing a joint probability method based vegetation dynamic model. Further, the model is being validated by field data about changes of vegetation assemblage along environmental gradients in the marl prairie. Our poster showed preliminary data from our current project.

An EMAT-based shear horizontal (SH) wave technique for adhesive bond inspection

NASA Astrophysics Data System (ADS)

Arun, K.; Dhayalan, R.; Balasubramaniam, Krishnan; Maxfield, Bruce; Peres, Patrick; Barnoncel, David

2012-05-01

The evaluation of adhesively bonded structures has been a challenge over the several decades that these structures have been used. Applications within the aerospace industry often call for particularly high performance adhesive bonds. Several techniques have been proposed for the detection of disbonds and cohesive weakness but a reliable NDE method for detecting interfacial weakness (also sometimes called a kissing bond) has been elusive. Different techniques, including ultrasonic, thermal imaging and shearographic methods, have been proposed; all have had some degree of success. In particular, ultrasonic methods, including those based upon shear and guided waves, have been explored for the assessment of interfacial bond quality. Since 3-D guided shear horizontal (SH) waves in plates have predominantly shear displacement at the plate surfaces, we conjectured that SH guided waves should be influenced by interfacial conditions when they propagate between adhesively bonded plates of comparable thickness. This paper describes a new technique based on SH guided waves that propagate within and through a lap joint. Through mechanisms we have yet to fully understand, the propagation of an SH wave through a lap joint gives rise to a reverberation signal that is due to one or more reflections of an SH guided wave mode within that lap joint. Based upon a combination of numerical simulations and measurements, this method shows promise for detecting and classifying interfacial bonds. It is also apparent from our measurements that the SH wave modes can discriminate between adhesive and cohesive bond weakness in both Aluminum-Epoxy-Aluminum and Composite-Epoxy-Composite lap joints. All measurements reported here used periodic permanent magnet (PPM) Electro-Magnetic Acoustic Transducers (EMATs) to generate either or both of the two lowest order SH modes in the plates that comprise the lap joint. This exact configuration has been simulated using finite element (FE) models to describe the SH mode generation, propagation and reception. Of particular interest is that one SH guided wave mode (probably SH0) reverberates within the lap joint. Moreover, in both simulations and measurements, features of this so-called reverberation signal appear to be related to interfacial weakness between the plate (substrate) and the epoxy bond. The results of a hybrid numerical (FE) approach based on using COMSOL to calculate the driving forces within an elastic solid and ABAQUS to propagate the resulting elastic disturbances (waves) within the plates and lap joint are compared with measurements of SH wave generation and reception in lap joint specimens having different interfacial and cohesive bonding conditions.

Subplane collision probabilities method applied to control rod cusping in 2D/1D

DOE Office of Scientific and Technical Information (OSTI.GOV)

Graham, Aaron M.; Collins, Benjamin S.; Stimpson, Shane G.

The MPACT code is being jointly developed by the University of Michigan and Oak Ridge National Laboratory. It uses the 2D/1D method to solve neutron transport problems for reactors. The 2D/1D method decomposes the problem into a stack of 2D planes, and uses a high fidelity transport method to resolve all heterogeneity in each plane. These planes are then coupled axially using a lower order solver. Using this scheme, 3D solutions to the transport equation can be obtained at a much lower cost.One assumption made by the 2D/1D method is that the materials are axially homogeneous for each 2D plane.more » Violation of this assumption requires homogenization, which can significantly reduce the accuracy of the calculation. This paper presents two new subgrid methods to address this issue. The first method is polynomial decusping, a simple correction used to address control rods partially inserted into a 2D plane. The second is the subplane collision probabilities method, which is a more accurate, more robust subgrid method that can be applied to other axial heterogeneities.Each method was applied to a variety of problems. Results were compared to fine mesh solutions which had no axial heterogeneity and to Monte Carlo reference solutions generated using KENO-VI. It was shown that the polynomial decusping method was effective in many cases, but it had some limitations, with 3D pin power errors as high as 25% compared to KENO-VI. In conclusion, the subplane collision probabilities method performed much better, lowering the maximum pin power error to less than 5% in every calculation.« less

Subplane collision probabilities method applied to control rod cusping in 2D/1D

DOE PAGES

Graham, Aaron M.; Collins, Benjamin S.; Stimpson, Shane G.; ...

2018-04-06

The MPACT code is being jointly developed by the University of Michigan and Oak Ridge National Laboratory. It uses the 2D/1D method to solve neutron transport problems for reactors. The 2D/1D method decomposes the problem into a stack of 2D planes, and uses a high fidelity transport method to resolve all heterogeneity in each plane. These planes are then coupled axially using a lower order solver. Using this scheme, 3D solutions to the transport equation can be obtained at a much lower cost.One assumption made by the 2D/1D method is that the materials are axially homogeneous for each 2D plane.more » Violation of this assumption requires homogenization, which can significantly reduce the accuracy of the calculation. This paper presents two new subgrid methods to address this issue. The first method is polynomial decusping, a simple correction used to address control rods partially inserted into a 2D plane. The second is the subplane collision probabilities method, which is a more accurate, more robust subgrid method that can be applied to other axial heterogeneities.Each method was applied to a variety of problems. Results were compared to fine mesh solutions which had no axial heterogeneity and to Monte Carlo reference solutions generated using KENO-VI. It was shown that the polynomial decusping method was effective in many cases, but it had some limitations, with 3D pin power errors as high as 25% compared to KENO-VI. In conclusion, the subplane collision probabilities method performed much better, lowering the maximum pin power error to less than 5% in every calculation.« less

Interleaved Training and Training-Based Transmission Design for Hybrid Massive Antenna Downlink

NASA Astrophysics Data System (ADS)

Zhang, Cheng; Jing, Yindi; Huang, Yongming; Yang, Luxi

2018-06-01

In this paper, we study the beam-based training design jointly with the transmission design for hybrid massive antenna single-user (SU) and multiple-user (MU) systems where outage probability is adopted as the performance measure. For SU systems, we propose an interleaved training design to concatenate the feedback and training procedures, thus making the training length adaptive to the channel realization. Exact analytical expressions are derived for the average training length and the outage probability of the proposed interleaved training. For MU systems, we propose a joint design for the beam-based interleaved training, beam assignment, and MU data transmissions. Two solutions for the beam assignment are provided with different complexity-performance tradeoff. Analytical results and simulations show that for both SU and MU systems, the proposed joint training and transmission designs achieve the same outage performance as the traditional full-training scheme but with significant saving in the training overhead.

Multivariate hydrological frequency analysis for extreme events using Archimedean copula. Case study: Lower Tunjuelo River basin (Colombia)

NASA Astrophysics Data System (ADS)

Gómez, Wilmar

2017-04-01

By analyzing the spatial and temporal variability of extreme precipitation events we can prevent or reduce the threat and risk. Many water resources projects require joint probability distributions of random variables such as precipitation intensity and duration, which can not be independent with each other. The problem of defining a probability model for observations of several dependent variables is greatly simplified by the joint distribution in terms of their marginal by taking copulas. This document presents a general framework set frequency analysis bivariate and multivariate using Archimedean copulas for extreme events of hydroclimatological nature such as severe storms. This analysis was conducted in the lower Tunjuelo River basin in Colombia for precipitation events. The results obtained show that for a joint study of the intensity-duration-frequency, IDF curves can be obtained through copulas and thus establish more accurate and reliable information from design storms and associated risks. It shows how the use of copulas greatly simplifies the study of multivariate distributions that introduce the concept of joint return period used to represent the needs of hydrological designs properly in frequency analysis.

Application of multivariate Gaussian detection theory to known non-Gaussian probability density functions

NASA Astrophysics Data System (ADS)

Schwartz, Craig R.; Thelen, Brian J.; Kenton, Arthur C.

1995-06-01

A statistical parametric multispectral sensor performance model was developed by ERIM to support mine field detection studies, multispectral sensor design/performance trade-off studies, and target detection algorithm development. The model assumes target detection algorithms and their performance models which are based on data assumed to obey multivariate Gaussian probability distribution functions (PDFs). The applicability of these algorithms and performance models can be generalized to data having non-Gaussian PDFs through the use of transforms which convert non-Gaussian data to Gaussian (or near-Gaussian) data. An example of one such transform is the Box-Cox power law transform. In practice, such a transform can be applied to non-Gaussian data prior to the introduction of a detection algorithm that is formally based on the assumption of multivariate Gaussian data. This paper presents an extension of these techniques to the case where the joint multivariate probability density function of the non-Gaussian input data is known, and where the joint estimate of the multivariate Gaussian statistics, under the Box-Cox transform, is desired. The jointly estimated multivariate Gaussian statistics can then be used to predict the performance of a target detection algorithm which has an associated Gaussian performance model.

Model-assisted probability of detection of flaws in aluminum blocks using polynomial chaos expansions

NASA Astrophysics Data System (ADS)

Du, Xiaosong; Leifsson, Leifur; Grandin, Robert; Meeker, William; Roberts, Ronald; Song, Jiming

2018-04-01

Probability of detection (POD) is widely used for measuring reliability of nondestructive testing (NDT) systems. Typically, POD is determined experimentally, while it can be enhanced by utilizing physics-based computational models in combination with model-assisted POD (MAPOD) methods. With the development of advanced physics-based methods, such as ultrasonic NDT testing, the empirical information, needed for POD methods, can be reduced. However, performing accurate numerical simulations can be prohibitively time-consuming, especially as part of stochastic analysis. In this work, stochastic surrogate models for computational physics-based measurement simulations are developed for cost savings of MAPOD methods while simultaneously ensuring sufficient accuracy. The stochastic surrogate is used to propagate the random input variables through the physics-based simulation model to obtain the joint probability distribution of the output. The POD curves are then generated based on those results. Here, the stochastic surrogates are constructed using non-intrusive polynomial chaos (NIPC) expansions. In particular, the NIPC methods used are the quadrature, ordinary least-squares (OLS), and least-angle regression sparse (LARS) techniques. The proposed approach is demonstrated on the ultrasonic testing simulation of a flat bottom hole flaw in an aluminum block. The results show that the stochastic surrogates have at least two orders of magnitude faster convergence on the statistics than direct Monte Carlo sampling (MCS). Moreover, the evaluation of the stochastic surrogate models is over three orders of magnitude faster than the underlying simulation model for this case, which is the UTSim2 model.

Analysis on Flexural Strength of A36 Mild Steel by Design of Experiment (DOE)

NASA Astrophysics Data System (ADS)

Nurulhuda, A.; Hafizzal, Y.; Izzuddin, MZM; Sulawati, MRN; Rafidah, A.; Suhaila, Y.; Fauziah, AR

2017-08-01

Nowadays demand for high quality and reliable components and materials are increasing so flexural tests have become vital test method in both the research and manufacturing process and development to explain in details about the material’s ability to withstand deformation under load. Recently, there are lack research studies on the effect of thickness, welding type and joint design on the flexural condition by DOE approach method. Therefore, this research will come out with the flexural strength of mild steel since it is not well documented. By using Design of Experiment (DOE), a full factorial design with two replications has been used to study the effects of important parameters which are welding type, thickness and joint design. The measurement of output response is identified as flexural strength value. Randomize experiments was conducted based on table generated via Minitab software. A normal probability test was carried out using Anderson Darling Test and show that the P-value is <0.005. Thus, the data is not normal since there is significance different between the actual data with the ideal data. Referring to the ANOVA, only factor joint design is significant since the P-value is less than 0.05. From the main plot and interaction plot, the recommended setting for each of parameters were suggested as high level for welding type, high level for thickness and low level for joint design. The prediction model was developed thru regression in order to measure effect of output response for any changes on parameters setting. In the future, the experiments can be enhanced using Taguchi methods in order to do verification of result.

The World According to de Finetti: On de Finetti's Theory of Probability and Its Application to Quantum Mechanics

NASA Astrophysics Data System (ADS)

Berkovitz, Joseph

Bruno de Finetti is one of the founding fathers of the subjectivist school of probability, where probabilities are interpreted as rational degrees of belief. His work on the relation between the theorems of probability and rationality is among the corner stones of modern subjective probability theory. De Finetti maintained that rationality requires that degrees of belief be coherent, and he argued that the whole of probability theory could be derived from these coherence conditions. De Finetti's interpretation of probability has been highly influential in science. This paper focuses on the application of this interpretation to quantum mechanics. We argue that de Finetti held that the coherence conditions of degrees of belief in events depend on their verifiability. Accordingly, the standard coherence conditions of degrees of belief that are familiar from the literature on subjective probability only apply to degrees of belief in events which could (in principle) be jointly verified; and the coherence conditions of degrees of belief in events that cannot be jointly verified are weaker. While the most obvious explanation of de Finetti's verificationism is the influence of positivism, we argue that it could be motivated by the radical subjectivist and instrumental nature of probability in his interpretation; for as it turns out, in this interpretation it is difficult to make sense of the idea of coherent degrees of belief in, and accordingly probabilities of unverifiable events. We then consider the application of this interpretation to quantum mechanics, concentrating on the Einstein-Podolsky-Rosen experiment and Bell's theorem.

Review of probabilistic analysis of dynamic response of systems with random parameters

NASA Technical Reports Server (NTRS)

Kozin, F.; Klosner, J. M.

1989-01-01

The various methods that have been studied in the past to allow probabilistic analysis of dynamic response for systems with random parameters are reviewed. Dynamic response may have been obtained deterministically if the variations about the nominal values were small; however, for space structures which require precise pointing, the variations about the nominal values of the structural details and of the environmental conditions are too large to be considered as negligible. These uncertainties are accounted for in terms of probability distributions about their nominal values. The quantities of concern for describing the response of the structure includes displacements, velocities, and the distributions of natural frequencies. The exact statistical characterization of the response would yield joint probability distributions for the response variables. Since the random quantities will appear as coefficients, determining the exact distributions will be difficult at best. Thus, certain approximations will have to be made. A number of techniques that are available are discussed, even in the nonlinear case. The methods that are described were: (1) Liouville's equation; (2) perturbation methods; (3) mean square approximate systems; and (4) nonlinear systems with approximation by linear systems.

Independent Events in Elementary Probability Theory

ERIC Educational Resources Information Center

Csenki, Attila

2011-01-01

In Probability and Statistics taught to mathematicians as a first introduction or to a non-mathematical audience, joint independence of events is introduced by requiring that the multiplication rule is satisfied. The following statement is usually tacitly assumed to hold (and, at best, intuitively motivated): If the n events E[subscript 1],…

Back to Normal! Gaussianizing posterior distributions for cosmological probes

NASA Astrophysics Data System (ADS)

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.

Centralized Multi-Sensor Square Root Cubature Joint Probabilistic Data Association

PubMed Central

Liu, Jun; Li, Gang; Qi, Lin; Li, Yaowen; He, You

2017-01-01

This paper focuses on the tracking problem of multiple targets with multiple sensors in a nonlinear cluttered environment. To avoid Jacobian matrix computation and scaling parameter adjustment, improve numerical stability, and acquire more accurate estimated results for centralized nonlinear tracking, a novel centralized multi-sensor square root cubature joint probabilistic data association algorithm (CMSCJPDA) is proposed. Firstly, the multi-sensor tracking problem is decomposed into several single-sensor multi-target tracking problems, which are sequentially processed during the estimation. Then, in each sensor, the assignment of its measurements to target tracks is accomplished on the basis of joint probabilistic data association (JPDA), and a weighted probability fusion method with square root version of a cubature Kalman filter (SRCKF) is utilized to estimate the targets’ state. With the measurements in all sensors processed CMSCJPDA is derived and the global estimated state is achieved. Experimental results show that CMSCJPDA is superior to the state-of-the-art algorithms in the aspects of tracking accuracy, numerical stability, and computational cost, which provides a new idea to solve multi-sensor tracking problems. PMID:29113085

Centralized Multi-Sensor Square Root Cubature Joint Probabilistic Data Association.

PubMed

Liu, Yu; Liu, Jun; Li, Gang; Qi, Lin; Li, Yaowen; He, You

2017-11-05

This paper focuses on the tracking problem of multiple targets with multiple sensors in a nonlinear cluttered environment. To avoid Jacobian matrix computation and scaling parameter adjustment, improve numerical stability, and acquire more accurate estimated results for centralized nonlinear tracking, a novel centralized multi-sensor square root cubature joint probabilistic data association algorithm (CMSCJPDA) is proposed. Firstly, the multi-sensor tracking problem is decomposed into several single-sensor multi-target tracking problems, which are sequentially processed during the estimation. Then, in each sensor, the assignment of its measurements to target tracks is accomplished on the basis of joint probabilistic data association (JPDA), and a weighted probability fusion method with square root version of a cubature Kalman filter (SRCKF) is utilized to estimate the targets' state. With the measurements in all sensors processed CMSCJPDA is derived and the global estimated state is achieved. Experimental results show that CMSCJPDA is superior to the state-of-the-art algorithms in the aspects of tracking accuracy, numerical stability, and computational cost, which provides a new idea to solve multi-sensor tracking problems.

Joint search and sensor management for geosynchronous satellites

NASA Astrophysics Data System (ADS)

Zatezalo, A.; El-Fallah, A.; Mahler, R.; Mehra, R. K.; Pham, K.

2008-04-01

Joint search and sensor management for space situational awareness presents daunting scientific and practical challenges as it requires a simultaneous search for new, and the catalog update of the current space objects. We demonstrate a new approach to joint search and sensor management by utilizing the Posterior Expected Number of Targets (PENT) as the objective function, an observation model for a space-based EO/IR sensor, and a Probability Hypothesis Density Particle Filter (PHD-PF) tracker. Simulation and results using actual Geosynchronous Satellites are presented.

The difference between two random mixed quantum states: exact and asymptotic spectral analysis

NASA Astrophysics Data System (ADS)

Mejía, José; Zapata, Camilo; Botero, Alonso

2017-01-01

We investigate the spectral statistics of the difference of two density matrices, each of which is independently obtained by partially tracing a random bipartite pure quantum state. We first show how a closed-form expression for the exact joint eigenvalue probability density function for arbitrary dimensions can be obtained from the joint probability density function of the diagonal elements of the difference matrix, which is straightforward to compute. Subsequently, we use standard results from free probability theory to derive a relatively simple analytic expression for the asymptotic eigenvalue density (AED) of the difference matrix ensemble, and using Carlson’s theorem, we obtain an expression for its absolute moments. These results allow us to quantify the typical asymptotic distance between the two random mixed states using various distance measures; in particular, we obtain the almost sure asymptotic behavior of the operator norm distance and the trace distance.

Impact of communities, health, and emotional-related factors on smoking use: comparison of joint modeling of mean and dispersion and Bayes' hierarchical models on add health survey.

PubMed

Pu, Jie; Fang, Di; Wilson, Jeffrey R

2017-02-03

The analysis of correlated binary data is commonly addressed through the use of conditional models with random effects included in the systematic component as opposed to generalized estimating equations (GEE) models that addressed the random component. Since the joint distribution of the observations is usually unknown, the conditional distribution is a natural approach. Our objective was to compare the fit of different binary models for correlated data in Tabaco use. We advocate that the joint modeling of the mean and dispersion may be at times just as adequate. We assessed the ability of these models to account for the intraclass correlation. In so doing, we concentrated on fitting logistic regression models to address smoking behaviors. Frequentist and Bayes' hierarchical models were used to predict conditional probabilities, and the joint modeling (GLM and GAM) models were used to predict marginal probabilities. These models were fitted to National Longitudinal Study of Adolescent to Adult Health (Add Health) data for Tabaco use. We found that people were less likely to smoke if they had higher income, high school or higher education and religious. Individuals were more likely to smoke if they had abused drug or alcohol, spent more time on TV and video games, and been arrested. Moreover, individuals who drank alcohol early in life were more likely to be a regular smoker. Children who experienced mistreatment from their parents were more likely to use Tabaco regularly. The joint modeling of the mean and dispersion models offered a flexible and meaningful method of addressing the intraclass correlation. They do not require one to identify random effects nor distinguish from one level of the hierarchy to the other. Moreover, once one can identify the significant random effects, one can obtain similar results to the random coefficient models. We found that the set of marginal models accounting for extravariation through the additional dispersion submodel produced similar results with regards to inferences and predictions. Moreover, both marginal and conditional models demonstrated similar predictive power.

New stochastic approach for extreme response of slow drift motion of moored floating structures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kato, Shunji; Okazaki, Takashi

1995-12-31

A new stochastic method for investigating the flow drift response statistics of moored floating structures is described. Assuming that wave drift excitation process can be driven by a Gaussian white noise process, an exact stochastic equation governing a time evolution of the response Probability Density Function (PDF) is derived on a basis of Projection operator technique in the field of statistical physics. In order to get an approximate solution of the GFP equation, the authors develop the renormalized perturbation technique which is a kind of singular perturbation methods and solve the GFP equation taken into account up to third ordermore » moments of a non-Gaussian excitation. As an example of the present method, a closed form of the joint PDF is derived for linear response in surge motion subjected to a non-Gaussian wave drift excitation and it is represented by the product of a form factor and the quasi-Cauchy PDFs. In this case, the motion displacement and velocity processes are not mutually independent if the excitation process has a significant third order moment. From a comparison between the response PDF by the present solution and the exact one derived by Naess, it is found that the present solution is effective for calculating both the response PDF and the joint PDF. Furthermore it is shown that the displacement-velocity independence is satisfied if the damping coefficient in equation of motion is not so large and that both the non-Gaussian property of excitation and the damping coefficient should be taken into account for estimating the probability exceedance of the response.« less

Source Detection with Bayesian Inference on ROSAT All-Sky Survey Data Sample

NASA Astrophysics Data System (ADS)

Guglielmetti, F.; Voges, W.; Fischer, R.; Boese, G.; Dose, V.

2004-07-01

We employ Bayesian inference for the joint estimation of sources and background on ROSAT All-Sky Survey (RASS) data. The probabilistic method allows for detection improvement of faint extended celestial sources compared to the Standard Analysis Software System (SASS). Background maps were estimated in a single step together with the detection of sources without pixel censoring. Consistent uncertainties of background and sources are provided. The source probability is evaluated for single pixels as well as for pixel domains to enhance source detection of weak and extended sources.

Optimal Universal Uncertainty Relations

PubMed Central

Li, Tao; Xiao, Yunlong; Ma, Teng; Fei, Shao-Ming; Jing, Naihuan; Li-Jost, Xianqing; Wang, Zhi-Xi

2016-01-01

We study universal uncertainty relations and present a method called joint probability distribution diagram to improve the majorization bounds constructed independently in [Phys. Rev. Lett. 111, 230401 (2013)] and [J. Phys. A. 46, 272002 (2013)]. The results give rise to state independent uncertainty relations satisfied by any nonnegative Schur-concave functions. On the other hand, a remarkable recent result of entropic uncertainty relation is the direct-sum majorization relation. In this paper, we illustrate our bounds by showing how they provide a complement to that in [Phys. Rev. A. 89, 052115 (2014)]. PMID:27775010

A composition joint PDF method for the modeling of spray flames

NASA Technical Reports Server (NTRS)

Raju, M. S.

1995-01-01

This viewgraph presentation discusses an extension of the probability density function (PDF) method to the modeling of spray flames to evaluate the limitations and capabilities of this method in the modeling of gas-turbine combustor flows. The comparisons show that the general features of the flowfield are correctly predicted by the present solution procedure. The present solution appears to provide a better representation of the temperature field, particularly, in the reverse-velocity zone. The overpredictions in the centerline velocity could be attributed to the following reasons: (1) the use of k-epsilon turbulence model is known to be less precise in highly swirling flows and (2) the swirl number used here is reported to be estimated rather than measured.

A framework for conducting mechanistic based reliability assessments of components operating in complex systems

NASA Astrophysics Data System (ADS)

Wallace, Jon Michael

2003-10-01

Reliability prediction of components operating in complex systems has historically been conducted in a statistically isolated manner. Current physics-based, i.e. mechanistic, component reliability approaches focus more on component-specific attributes and mathematical algorithms and not enough on the influence of the system. The result is that significant error can be introduced into the component reliability assessment process. The objective of this study is the development of a framework that infuses the needs and influence of the system into the process of conducting mechanistic-based component reliability assessments. The formulated framework consists of six primary steps. The first three steps, identification, decomposition, and synthesis, are primarily qualitative in nature and employ system reliability and safety engineering principles to construct an appropriate starting point for the component reliability assessment. The following two steps are the most unique. They involve a step to efficiently characterize and quantify the system-driven local parameter space and a subsequent step using this information to guide the reduction of the component parameter space. The local statistical space quantification step is accomplished using two proposed multivariate probability models: Multi-Response First Order Second Moment and Taylor-Based Inverse Transformation. Where existing joint probability models require preliminary distribution and correlation information of the responses, these models combine statistical information of the input parameters with an efficient sampling of the response analyses to produce the multi-response joint probability distribution. Parameter space reduction is accomplished using Approximate Canonical Correlation Analysis (ACCA) employed as a multi-response screening technique. The novelty of this approach is that each individual local parameter and even subsets of parameters representing entire contributing analyses can now be rank ordered with respect to their contribution to not just one response, but the entire vector of component responses simultaneously. The final step of the framework is the actual probabilistic assessment of the component. Although the same multivariate probability tools employed in the characterization step can be used for the component probability assessment, variations of this final step are given to allow for the utilization of existing probabilistic methods such as response surface Monte Carlo and Fast Probability Integration. The overall framework developed in this study is implemented to assess the finite-element based reliability prediction of a gas turbine airfoil involving several failure responses. Results of this implementation are compared to results generated using the conventional 'isolated' approach as well as a validation approach conducted through large sample Monte Carlo simulations. The framework resulted in a considerable improvement to the accuracy of the part reliability assessment and an improved understanding of the component failure behavior. Considerable statistical complexity in the form of joint non-normal behavior was found and accounted for using the framework. Future applications of the framework elements are discussed.

Statistical Evaluation and Improvement of Methods for Combining Random and Harmonic Loads

NASA Technical Reports Server (NTRS)

Brown, A. M.; McGhee, D. S.

2003-01-01

Structures in many environments experience both random and harmonic excitation. A variety of closed-form techniques has been used in the aerospace industry to combine the loads resulting from the two sources. The resulting combined loads are then used to design for both yield/ultimate strength and high- cycle fatigue capability. This Technical Publication examines the cumulative distribution percentiles obtained using each method by integrating the joint probability density function of the sine and random components. A new Microsoft Excel spreadsheet macro that links with the software program Mathematica to calculate the combined value corresponding to any desired percentile is then presented along with a curve tit to this value. Another Excel macro that calculates the combination using Monte Carlo simulation is shown. Unlike the traditional techniques. these methods quantify the calculated load value with a consistent percentile. Using either of the presented methods can be extremely valuable in probabilistic design, which requires a statistical characterization of the loading. Additionally, since the CDF at high probability levels is very flat, the design value is extremely sensitive to the predetermined percentile; therefore, applying the new techniques can substantially lower the design loading without losing any of the identified structural reliability.

Statistical Comparison and Improvement of Methods for Combining Random and Harmonic Loads

NASA Technical Reports Server (NTRS)

Brown, Andrew M.; McGhee, David S.

2004-01-01

Structures in many environments experience both random and harmonic excitation. A variety of closed-form techniques has been used in the aerospace industry to combine the loads resulting from the two sources. The resulting combined loads are then used to design for both yield ultimate strength and high cycle fatigue capability. This paper examines the cumulative distribution function (CDF) percentiles obtained using each method by integrating the joint probability density function of the sine and random components. A new Microsoft Excel spreadsheet macro that links with the software program Mathematics is then used to calculate the combined value corresponding to any desired percentile along with a curve fit to this value. Another Excel macro is used to calculate the combination using a Monte Carlo simulation. Unlike the traditional techniques, these methods quantify the calculated load value with a Consistent percentile. Using either of the presented methods can be extremely valuable in probabilistic design, which requires a statistical characterization of the loading. Also, since the CDF at high probability levels is very flat, the design value is extremely sensitive to the predetermined percentile; therefore, applying the new techniques can lower the design loading substantially without losing any of the identified structural reliability.

A real-time method for autonomous passive acoustic detection-classification of humpback whales.

PubMed

Abbot, Ted A; Premus, Vincent E; Abbot, Philip A

2010-05-01

This paper describes a method for real-time, autonomous, joint detection-classification of humpback whale vocalizations. The approach adapts the spectrogram correlation method used by Mellinger and Clark [J. Acoust. Soc. Am. 107, 3518-3529 (2000)] for bowhead whale endnote detection to the humpback whale problem. The objective is the implementation of a system to determine the presence or absence of humpback whales with passive acoustic methods and to perform this classification with low false alarm rate in real time. Multiple correlation kernels are used due to the diversity of humpback song. The approach also takes advantage of the fact that humpbacks tend to vocalize repeatedly for extended periods of time, and identification is declared only when multiple song units are detected within a fixed time interval. Humpback whale vocalizations from Alaska, Hawaii, and Stellwagen Bank were used to train the algorithm. It was then tested on independent data obtained off Kaena Point, Hawaii in February and March of 2009. Results show that the algorithm successfully classified humpback whales autonomously in real time, with a measured probability of correct classification in excess of 74% and a measured probability of false alarm below 1%.

Prevalence of different temporomandibular joint sounds, with emphasis on disc-displacement, in patients with temporomandibular disorders and controls.

PubMed

Elfving, Lars; Helkimo, Martti; Magnusson, Tomas

2002-01-01

Temporomandibular joint (TMJ) sounds are very common among patients with temporomandibular disorders (TMD), but also in non-patient populations. A variety of different causes to TMJ-sounds have been suggested e.g. arthrotic changes in the TMJs, anatomical variations, muscular incoordination and disc displacement. In the present investigation, the prevalence and type of different joint sounds were registered in 125 consecutive patients with suspected TMD and in 125 matched controls. Some kind of joint sound was recorded in 56% of the TMD patients and in 36% of the controls. The awareness of joint sounds was higher among TMD patients as compared to controls (88% and 60% respectively). The most common sound recorded in both groups was reciprocal clickings indicative of a disc displacement, while not one single case fulfilling the criteria for clicking due to a muscular incoordination was found. In the TMD group women with disc displacement reported sleeping on the stomach significantly more often than women without disc displacement did. An increased general joint laxity was found in 39% of the TMD patients with disc displacement, while this was found in only 9% of the patients with disc displacement in the control group. To conclude, disc displacement is probably the most common cause to TMJ sounds, while the existence of TMJ sounds due to a muscular incoordination can be questioned. Furthermore, sleeping on the stomach might be associated with disc displacement, while general joint laxity is probably not a causative factor, but a seeking care factor in patients with disc displacement.

Comparison of Probabilistic Coastal Inundation Maps Based on Historical Storms and Statistically Modeled Storm Ensemble

NASA Astrophysics Data System (ADS)

Feng, X.; Sheng, Y.; Condon, A. J.; Paramygin, V. A.; Hall, T.

2012-12-01

A cost effective method, JPM-OS (Joint Probability Method with Optimal Sampling), for determining storm response and inundation return frequencies was developed and applied to quantify the hazard of hurricane storm surges and inundation along the Southwest FL,US coast (Condon and Sheng 2012). The JPM-OS uses piecewise multivariate regression splines coupled with dimension adaptive sparse grids to enable the generation of a base flood elevation (BFE) map. Storms are characterized by their landfall characteristics (pressure deficit, radius to maximum winds, forward speed, heading, and landfall location) and a sparse grid algorithm determines the optimal set of storm parameter combinations so that the inundation from any other storm parameter combination can be determined. The end result is a sample of a few hundred (197 for SW FL) optimal storms which are simulated using a dynamically coupled storm surge / wave modeling system CH3D-SSMS (Sheng et al. 2010). The limited historical climatology (1940 - 2009) is explored to develop probabilistic characterizations of the five storm parameters. The probability distributions are discretized and the inundation response of all parameter combinations is determined by the interpolation in five-dimensional space of the optimal storms. The surge response and the associated joint probability of the parameter combination is used to determine the flood elevation with a 1% annual probability of occurrence. The limited historical data constrains the accuracy of the PDFs of the hurricane characteristics, which in turn affect the accuracy of the BFE maps calculated. To offset the deficiency of limited historical dataset, this study presents a different method for producing coastal inundation maps. Instead of using the historical storm data, here we adopt 33,731 tracks that can represent the storm climatology in North Atlantic basin and SW Florida coasts. This large quantity of hurricane tracks is generated from a new statistical model which had been used for Western North Pacific (WNP) tropical cyclone (TC) genesis (Hall 2011) as well as North Atlantic tropical cyclone genesis (Hall and Jewson 2007). The introduction of these tracks complements the shortage of the historical samples and allows for more reliable PDFs required for implementation of JPM-OS. Using the 33,731 tracks and JPM-OS, an optimal storm ensemble is determined. This approach results in different storms/winds for storm surge and inundation modeling, and produces different Base Flood Elevation maps for coastal regions. Coastal inundation maps produced by the two different methods will be discussed in detail in the poster paper.

Mixture Modeling for Background and Sources Separation in x-ray Astronomical Images

NASA Astrophysics Data System (ADS)

Guglielmetti, Fabrizia; Fischer, Rainer; Dose, Volker

2004-11-01

A probabilistic technique for the joint estimation of background and sources in high-energy astrophysics is described. Bayesian probability theory is applied to gain insight into the coexistence of background and sources through a probabilistic two-component mixture model, which provides consistent uncertainties of background and sources. The present analysis is applied to ROSAT PSPC data (0.1-2.4 keV) in Survey Mode. A background map is modelled using a Thin-Plate spline. Source probability maps are obtained for each pixel (45 arcsec) independently and for larger correlation lengths, revealing faint and extended sources. We will demonstrate that the described probabilistic method allows for detection improvement of faint extended celestial sources compared to the Standard Analysis Software System (SASS) used for the production of the ROSAT All-Sky Survey (RASS) catalogues.

Modeling molecular mixing in a spatially inhomogeneous turbulent flow

NASA Astrophysics Data System (ADS)

Meyer, Daniel W.; Deb, Rajdeep

2012-02-01

Simulations of spatially inhomogeneous turbulent mixing in decaying grid turbulence with a joint velocity-concentration probability density function (PDF) method were conducted. The inert mixing scenario involves three streams with different compositions. The mixing model of Meyer ["A new particle interaction mixing model for turbulent dispersion and turbulent reactive flows," Phys. Fluids 22(3), 035103 (2010)], the interaction by exchange with the mean (IEM) model and its velocity-conditional variant, i.e., the IECM model, were applied. For reference, the direct numerical simulation data provided by Sawford and de Bruyn Kops ["Direct numerical simulation and lagrangian modeling of joint scalar statistics in ternary mixing," Phys. Fluids 20(9), 095106 (2008)] was used. It was found that velocity conditioning is essential to obtain accurate concentration PDF predictions. Moreover, the model of Meyer provides significantly better results compared to the IECM model at comparable computational expense.

NASA Instrument Cost/Schedule Model

NASA Technical Reports Server (NTRS)

Habib-Agahi, Hamid; Mrozinski, Joe; Fox, George

2011-01-01

NASA's Office of Independent Program and Cost Evaluation (IPCE) has established a number of initiatives to improve its cost and schedule estimating capabilities. 12One of these initiatives has resulted in the JPL developed NASA Instrument Cost Model. NICM is a cost and schedule estimator that contains: A system level cost estimation tool; a subsystem level cost estimation tool; a database of cost and technical parameters of over 140 previously flown remote sensing and in-situ instruments; a schedule estimator; a set of rules to estimate cost and schedule by life cycle phases (B/C/D); and a novel tool for developing joint probability distributions for cost and schedule risk (Joint Confidence Level (JCL)). This paper describes the development and use of NICM, including the data normalization processes, data mining methods (cluster analysis, principal components analysis, regression analysis and bootstrap cross validation), the estimating equations themselves and a demonstration of the NICM tool suite.

Probabilistic joint inversion of waveforms and polarity data for double-couple focal mechanisms of local earthquakes

NASA Astrophysics Data System (ADS)

Wéber, Zoltán

2018-06-01

Estimating the mechanisms of small (M < 4) earthquakes is quite challenging. A common scenario is that neither the available polarity data alone nor the well predictable near-station seismograms alone are sufficient to obtain reliable focal mechanism solutions for weak events. To handle this situation we introduce here a new method that jointly inverts waveforms and polarity data following a probabilistic approach. The procedure called joint waveform and polarity (JOWAPO) inversion maps the posterior probability density of the model parameters and estimates the maximum likelihood double-couple mechanism, the optimal source depth and the scalar seismic moment of the investigated event. The uncertainties of the solution are described by confidence regions. We have validated the method on two earthquakes for which well-determined focal mechanisms are available. The validation tests show that including waveforms in the inversion considerably reduces the uncertainties of the usually poorly constrained polarity solutions. The JOWAPO method performs best when it applies waveforms from at least two seismic stations. If the number of the polarity data is large enough, even single-station JOWAPO inversion can produce usable solutions. When only a few polarities are available, however, single-station inversion may result in biased mechanisms. In this case some caution must be taken when interpreting the results. We have successfully applied the JOWAPO method to an earthquake in North Hungary, whose mechanism could not be estimated by long-period waveform inversion. Using 17 P-wave polarities and waveforms at two nearby stations, the JOWAPO method produced a well-constrained focal mechanism. The solution is very similar to those obtained previously for four other events that occurred in the same earthquake sequence. The analysed event has a strike-slip mechanism with a P axis oriented approximately along an NE-SW direction.

Qualitative and Quantitative Proofs of Security Properties

DTIC Science & Technology

2013-04-01

Naples, Italy (September 2012) – Australasian Joint Conference on Artifical Intelligence (December 2012). • Causality, Responsibility, and Blame...realistic solution concept, Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI 2009), 2009, pp. 153–158. 17. J...Conference on Artificial Intelligence (AAAI-12), 2012, pp. 1917-1923. 29. J. Y. Halpern and S. Leung, Weighted sets of probabilities and minimax

Tomographic measurement of joint photon statistics of the twin-beam quantum state

PubMed

Vasilyev; Choi; Kumar; D'Ariano

2000-03-13

We report the first measurement of the joint photon-number probability distribution for a two-mode quantum state created by a nondegenerate optical parametric amplifier. The measured distributions exhibit up to 1.9 dB of quantum correlation between the signal and idler photon numbers, whereas the marginal distributions are thermal as expected for parametric fluorescence.

A Repeated Trajectory Class Model for Intensive Longitudinal Categorical Outcome

PubMed Central

Lin, Haiqun; Han, Ling; Peduzzi, Peter N.; Murphy, Terrence E.; Gill, Thomas M.; Allore, Heather G.

2014-01-01

This paper presents a novel repeated latent class model for a longitudinal response that is frequently measured as in our prospective study of older adults with monthly data on activities of daily living (ADL) for more than ten years. The proposed method is especially useful when the longitudinal response is measured much more frequently than other relevant covariates. The repeated trajectory classes represent distinct temporal patterns of the longitudinal response wherein an individual’s membership in the trajectory classes may renew or change over time. Within a trajectory class, the longitudinal response is modeled by a class-specific generalized linear mixed model. Effectively, an individual may remain in a trajectory class or switch to another as the class membership predictors are updated periodically over time. The identification of a common set of trajectory classes allows changes among the temporal patterns to be distinguished from local fluctuations in the response. An informative event such as death is jointly modeled by class-specific probability of the event through shared random effects. We do not impose the conditional independence assumption given the classes. The method is illustrated by analyzing the change over time in ADL trajectory class among 754 older adults with 70500 person-months of follow-up in the Precipitating Events Project. We also investigate the impact of jointly modeling the class-specific probability of the event on the parameter estimates in a simulation study. The primary contribution of our paper is the periodic updating of trajectory classes for a longitudinal categorical response without assuming conditional independence. PMID:24519416

Three-Dimensional Geometric Nonlinear Contact Stress Analysis of Riveted Joints

NASA Technical Reports Server (NTRS)

Shivakumar, Kunigal N.; Ramanujapuram, Vivek

1998-01-01

The problems associated with fatigue were brought into the forefront of research by the explosive decompression and structural failure of the Aloha Airlines Flight 243 in 1988. The structural failure of this airplane has been attributed to debonding and multiple cracking along the longitudinal lap splice riveted joint in the fuselage. This crash created what may be termed as a minor "Structural Integrity Revolution" in the commercial transport industry. Major steps have been taken by the manufacturers, operators and authorities to improve the structural airworthiness of the aging fleet of airplanes. Notwithstanding, this considerable effort there are still outstanding issues and concerns related to the formulation of Widespread Fatigue Damage which is believed to have been a contributing factor in the probable cause of the Aloha accident. The lesson from this accident was that Multiple-Site Damage (MSD) in "aging" aircraft can lead to extensive aircraft damage. A strong candidate in which MSD is highly probable to occur is the riveted lap joint.

Scalable Joint Segmentation and Registration Framework for Infant Brain Images.

PubMed

Dong, Pei; Wang, Li; Lin, Weili; Shen, Dinggang; Wu, Guorong

2017-03-15

The first year of life is the most dynamic and perhaps the most critical phase of postnatal brain development. The ability to accurately measure structure changes is critical in early brain development study, which highly relies on the performances of image segmentation and registration techniques. However, either infant image segmentation or registration, if deployed independently, encounters much more challenges than segmentation/registration of adult brains due to dynamic appearance change with rapid brain development. In fact, image segmentation and registration of infant images can assists each other to overcome the above challenges by using the growth trajectories (i.e., temporal correspondences) learned from a large set of training subjects with complete longitudinal data. Specifically, a one-year-old image with ground-truth tissue segmentation can be first set as the reference domain. Then, to register the infant image of a new subject at earlier age, we can estimate its tissue probability maps, i.e., with sparse patch-based multi-atlas label fusion technique, where only the training images at the respective age are considered as atlases since they have similar image appearance. Next, these probability maps can be fused as a good initialization to guide the level set segmentation. Thus, image registration between the new infant image and the reference image is free of difficulty of appearance changes, by establishing correspondences upon the reasonably segmented images. Importantly, the segmentation of new infant image can be further enhanced by propagating the much more reliable label fusion heuristics at the reference domain to the corresponding location of the new infant image via the learned growth trajectories, which brings image segmentation and registration to assist each other. It is worth noting that our joint segmentation and registration framework is also flexible to handle the registration of any two infant images even with significant age gap in the first year of life, by linking their joint segmentation and registration through the reference domain. Thus, our proposed joint segmentation and registration method is scalable to various registration tasks in early brain development studies. Promising segmentation and registration results have been achieved for infant brain MR images aged from 2-week-old to 1-year-old, indicating the applicability of our method in early brain development study.

On-line prognosis of fatigue crack propagation based on Gaussian weight-mixture proposal particle filter.

PubMed

Chen, Jian; Yuan, Shenfang; Qiu, Lei; Wang, Hui; Yang, Weibo

2018-01-01

Accurate on-line prognosis of fatigue crack propagation is of great meaning for prognostics and health management (PHM) technologies to ensure structural integrity, which is a challenging task because of uncertainties which arise from sources such as intrinsic material properties, loading, and environmental factors. The particle filter algorithm has been proved to be a powerful tool to deal with prognostic problems those are affected by uncertainties. However, most studies adopted the basic particle filter algorithm, which uses the transition probability density function as the importance density and may suffer from serious particle degeneracy problem. This paper proposes an on-line fatigue crack propagation prognosis method based on a novel Gaussian weight-mixture proposal particle filter and the active guided wave based on-line crack monitoring. Based on the on-line crack measurement, the mixture of the measurement probability density function and the transition probability density function is proposed to be the importance density. In addition, an on-line dynamic update procedure is proposed to adjust the parameter of the state equation. The proposed method is verified on the fatigue test of attachment lugs which are a kind of important joint components in aircraft structures. Copyright © 2017 Elsevier B.V. All rights reserved.

The Failure Models of Lead Free Sn-3.0Ag-0.5Cu Solder Joint Reliability Under Low-G and High-G Drop Impact

NASA Astrophysics Data System (ADS)

Gu, Jian; Lei, YongPing; Lin, Jian; Fu, HanGuang; Wu, Zhongwei

2017-02-01

The reliability of Sn-3.0Ag-0.5Cu (SAC 305) solder joint under a broad level of drop impacts was studied. The failure performance of solder joint, failure probability and failure position were analyzed under two shock test conditions, i.e., 1000 g for 1 ms and 300 g for 2 ms. The stress distribution on the solder joint was calculated by ABAQUS. The results revealed that the dominant reason was the tension due to the difference in stiffness between the print circuit board and ball grid array, and the maximum tension of 121.1 MPa and 31.1 MPa, respectively, under both 1000 g or 300 g drop impact, was focused on the corner of the solder joint which was located in the outmost corner of the solder ball row. The failure modes were summarized into the following four modes: initiation and propagation through the (1) intermetallic compound layer, (2) Ni layer, (3) Cu pad, or (4) Sn-matrix. The outmost corner of the solder ball row had a high failure probability under both 1000 g and 300 g drop impact. The number of failures of solder ball under the 300 g drop impact was higher than that under the 1000 g drop impact. The characteristic drop values for failure were 41 and 15,199, respectively, following the statistics.

Evaluating marginal likelihood with thermodynamic integration method and comparison with several other numerical methods

DOE PAGES

Liu, Peigui; Elshall, Ahmed S.; Ye, Ming; ...

2016-02-05

Evaluating marginal likelihood is the most critical and computationally expensive task, when conducting Bayesian model averaging to quantify parametric and model uncertainties. The evaluation is commonly done by using Laplace approximations to evaluate semianalytical expressions of the marginal likelihood or by using Monte Carlo (MC) methods to evaluate arithmetic or harmonic mean of a joint likelihood function. This study introduces a new MC method, i.e., thermodynamic integration, which has not been attempted in environmental modeling. Instead of using samples only from prior parameter space (as in arithmetic mean evaluation) or posterior parameter space (as in harmonic mean evaluation), the thermodynamicmore » integration method uses samples generated gradually from the prior to posterior parameter space. This is done through a path sampling that conducts Markov chain Monte Carlo simulation with different power coefficient values applied to the joint likelihood function. The thermodynamic integration method is evaluated using three analytical functions by comparing the method with two variants of the Laplace approximation method and three MC methods, including the nested sampling method that is recently introduced into environmental modeling. The thermodynamic integration method outperforms the other methods in terms of their accuracy, convergence, and consistency. The thermodynamic integration method is also applied to a synthetic case of groundwater modeling with four alternative models. The application shows that model probabilities obtained using the thermodynamic integration method improves predictive performance of Bayesian model averaging. As a result, the thermodynamic integration method is mathematically rigorous, and its MC implementation is computationally general for a wide range of environmental problems.« less

Combining Probability Distributions of Wind Waves and Sea Level Variations to Assess Return Periods of Coastal Floods

NASA Astrophysics Data System (ADS)

Leijala, U.; Bjorkqvist, J. V.; Pellikka, H.; Johansson, M. M.; Kahma, K. K.

2017-12-01

Predicting the behaviour of the joint effect of sea level and wind waves is of great significance due to the major impact of flooding events in densely populated coastal regions. As mean sea level rises, the effect of sea level variations accompanied by the waves will be even more harmful in the future. The main challenge when evaluating the effect of waves and sea level variations is that long time series of both variables rarely exist. Wave statistics are also highly location-dependent, thus requiring wave buoy measurements and/or high-resolution wave modelling. As an initial approximation of the joint effect, the variables may be treated as independent random variables, to achieve the probability distribution of their sum. We present results of a case study based on three probability distributions: 1) wave run-up constructed from individual wave buoy measurements, 2) short-term sea level variability based on tide gauge data, and 3) mean sea level projections based on up-to-date regional scenarios. The wave measurements were conducted during 2012-2014 on the coast of city of Helsinki located in the Gulf of Finland in the Baltic Sea. The short-term sea level distribution contains the last 30 years (1986-2015) of hourly data from Helsinki tide gauge, and the mean sea level projections are scenarios adjusted for the Gulf of Finland. Additionally, we present a sensitivity test based on six different theoretical wave height distributions representing different wave behaviour in relation to sea level variations. As these wave distributions are merged with one common sea level distribution, we can study how the different shapes of the wave height distribution affect the distribution of the sum, and which one of the components is dominating under different wave conditions. As an outcome of the method, we obtain a probability distribution of the maximum elevation of the continuous water mass, which enables a flexible tool for evaluating different risk levels in the current and future climate.

Dependent Neyman type A processes based on common shock Poisson approach

NASA Astrophysics Data System (ADS)

Kadilar, Gamze Özel; Kadilar, Cem

2016-04-01

The Neyman type A process is used for describing clustered data since the Poisson process is insufficient for clustering of events. In a multivariate setting, there may be dependencies between multivarite Neyman type A processes. In this study, dependent form of the Neyman type A process is considered under common shock approach. Then, the joint probability function are derived for the dependent Neyman type A Poisson processes. Then, an application based on forest fires in Turkey are given. The results show that the joint probability function of the dependent Neyman type A processes, which is obtained in this study, can be a good tool for the probabilistic fitness for the total number of burned trees in Turkey.

An information-theoretic approach to the modeling and analysis of whole-genome bisulfite sequencing data.

PubMed

Jenkinson, Garrett; Abante, Jordi; Feinberg, Andrew P; Goutsias, John

2018-03-07

DNA methylation is a stable form of epigenetic memory used by cells to control gene expression. Whole genome bisulfite sequencing (WGBS) has emerged as a gold-standard experimental technique for studying DNA methylation by producing high resolution genome-wide methylation profiles. Statistical modeling and analysis is employed to computationally extract and quantify information from these profiles in an effort to identify regions of the genome that demonstrate crucial or aberrant epigenetic behavior. However, the performance of most currently available methods for methylation analysis is hampered by their inability to directly account for statistical dependencies between neighboring methylation sites, thus ignoring significant information available in WGBS reads. We present a powerful information-theoretic approach for genome-wide modeling and analysis of WGBS data based on the 1D Ising model of statistical physics. This approach takes into account correlations in methylation by utilizing a joint probability model that encapsulates all information available in WGBS methylation reads and produces accurate results even when applied on single WGBS samples with low coverage. Using the Shannon entropy, our approach provides a rigorous quantification of methylation stochasticity in individual WGBS samples genome-wide. Furthermore, it utilizes the Jensen-Shannon distance to evaluate differences in methylation distributions between a test and a reference sample. Differential performance assessment using simulated and real human lung normal/cancer data demonstrate a clear superiority of our approach over DSS, a recently proposed method for WGBS data analysis. Critically, these results demonstrate that marginal methods become statistically invalid when correlations are present in the data. This contribution demonstrates clear benefits and the necessity of modeling joint probability distributions of methylation using the 1D Ising model of statistical physics and of quantifying methylation stochasticity using concepts from information theory. By employing this methodology, substantial improvement of DNA methylation analysis can be achieved by effectively taking into account the massive amount of statistical information available in WGBS data, which is largely ignored by existing methods.

Traumatic synovitis in a classical guitarist: a study of joint laxity.

PubMed

Bird, H A; Wright, V

1981-04-01

A classical guitarist performing for at least 5 hours each day developed a traumatic synovitis at the left wrist joint that was first erroneously considered to be rheumatoid arthritis. Comparison with members of the same guitar class suggested that unusual joint laxity of the fingers and wrist, probably inherited from the patient's father, was of more importance in the aetiology of the synovitis than a wide range of movement acquired by regular practice. Hyperextension of the metacarpophalangeal joint of the left index finger, quantified by the hyperextensometer, was less marked in the guitarists than in 100 normal individuals. This may be attributed to greater muscular control of the fingers. Lateral instability in the loaded joint may be the most important factor in the aetiology of traumatic synovitis.

Traumatic synovitis in a classical guitarist: a study of joint laxity.

PubMed Central

Bird, H A; Wright, V

1981-01-01

A classical guitarist performing for at least 5 hours each day developed a traumatic synovitis at the left wrist joint that was first erroneously considered to be rheumatoid arthritis. Comparison with members of the same guitar class suggested that unusual joint laxity of the fingers and wrist, probably inherited from the patient's father, was of more importance in the aetiology of the synovitis than a wide range of movement acquired by regular practice. Hyperextension of the metacarpophalangeal joint of the left index finger, quantified by the hyperextensometer, was less marked in the guitarists than in 100 normal individuals. This may be attributed to greater muscular control of the fingers. Lateral instability in the loaded joint may be the most important factor in the aetiology of traumatic synovitis. Images PMID:7224687

Background for Joint Systems Aspects of AIR 6000

DTIC Science & Technology

2000-04-01

Checkland’s Soft Systems Methodology [7, 8,9]. The analytical techniques that are proposed for joint systems work are based on calculating probability...Supporting Global Interests 21 DSTO-CR-0155 SLMP Structural Life Management Plan SOW Stand-Off Weapon SSM Soft Systems Methodology UAV Uninhabited Aerial... Systems Methodology in Action, John Wiley & Sons, Chichester, 1990. [101 Pearl, Judea, Probabilistic Reasoning in Intelligent Systems: Networks of Plausible

Arthroscopic Management of Scaphoid-Trapezium-Trapezoid Joint Arthritis.

PubMed

Pegoli, Loris; Pozzi, Alessandro

2017-11-01

Scaphoid-trapezium-trapezoid (STT) joint arthritis is a common condition consisting of pain on the radial side of the wrist and base of the thumb, swelling, and tenderness over the STT joint. Common symptoms are loss of grip strength and thumb function. There are several treatments, from symptomatic conservative treatment to surgical solutions, such as arthrodesis, arthroplasties, and prosthesis implant. The role of arthroscopy has grown and is probably the best treatment of this condition. Advantages of arthroscopic management of STT arthritis are faster recovery, better view of the joint during surgery, and possibility of creating less damage to the capsular and ligamentous structures. Copyright © 2017 Elsevier Inc. All rights reserved.

optBINS: Optimal Binning for histograms

NASA Astrophysics Data System (ADS)

Knuth, Kevin H.

2018-03-01

optBINS (optimal binning) determines the optimal number of bins in a uniform bin-width histogram by deriving the posterior probability for the number of bins in a piecewise-constant density model after assigning a multinomial likelihood and a non-informative prior. The maximum of the posterior probability occurs at a point where the prior probability and the the joint likelihood are balanced. The interplay between these opposing factors effectively implements Occam's razor by selecting the most simple model that best describes the data.

Nonstationary envelope process and first excursion probability.

NASA Technical Reports Server (NTRS)

Yang, J.-N.

1972-01-01

The definition of stationary random envelope proposed by Cramer and Leadbetter, is extended to the envelope of nonstationary random process possessing evolutionary power spectral densities. The density function, the joint density function, the moment function, and the crossing rate of a level of the nonstationary envelope process are derived. Based on the envelope statistics, approximate solutions to the first excursion probability of nonstationary random processes are obtained. In particular, applications of the first excursion probability to the earthquake engineering problems are demonstrated in detail.

Potential Use of a Bayesian Network for Discriminating Flash Type from Future GOES-R Geostationary Lightning Mapper (GLM) data

NASA Technical Reports Server (NTRS)

Solakiewiz, Richard; Koshak, William

2008-01-01

Continuous monitoring of the ratio of cloud flashes to ground flashes may provide a better understanding of thunderstorm dynamics, intensification, and evolution, and it may be useful in severe weather warning. The National Lighting Detection Network TM (NLDN) senses ground flashes with exceptional detection efficiency and accuracy over most of the continental United States. A proposed Geostationary Lightning Mapper (GLM) aboard the Geostationary Operational Environmental Satellite (GOES-R) will look at the western hemisphere, and among the lightning data products to be made available will be the fundamental optical flash parameters for both cloud and ground flashes: radiance, area, duration, number of optical groups, and number of optical events. Previous studies have demonstrated that the optical flash parameter statistics of ground and cloud lightning, which are observable from space, are significantly different. This study investigates a Bayesian network methodology for discriminating lightning flash type (ground or cloud) using the lightning optical data and ancillary GOES-R data. A Directed Acyclic Graph (DAG) is set up with lightning as a "root" and data observed by GLM as the "leaves." This allows for a direct calculation of the joint probability distribution function for the lighting type and radiance, area, etc. Initially, the conditional probabilities that will be required can be estimated from the Lightning Imaging Sensor (LIS) and the Optical Transient Detector (OTD) together with NLDN data. Directly manipulating the joint distribution will yield the conditional probability that a lightning flash is a ground flash given the evidence, which consists of the observed lightning optical data [and possibly cloud data retrieved from the GOES-R Advanced Baseline Imager (ABI) in a more mature Bayesian network configuration]. Later, actual GLM and NLDN data can be used to refine the estimates of the conditional probabilities used in the model; i.e., the Bayesian network is a learning network. Methods for efficient calculation of the conditional probabilities (e.g., an algorithm using junction trees), finding data conflicts, goodness of fit, and dealing with missing data will also be addressed.

Multivariate Bayesian modeling of known and unknown causes of events--an application to biosurveillance.

PubMed

Shen, Yanna; Cooper, Gregory F

2012-09-01

This paper investigates Bayesian modeling of known and unknown causes of events in the context of disease-outbreak detection. We introduce a multivariate Bayesian approach that models multiple evidential features of every person in the population. This approach models and detects (1) known diseases (e.g., influenza and anthrax) by using informative prior probabilities and (2) unknown diseases (e.g., a new, highly contagious respiratory virus that has never been seen before) by using relatively non-informative prior probabilities. We report the results of simulation experiments which support that this modeling method can improve the detection of new disease outbreaks in a population. A contribution of this paper is that it introduces a multivariate Bayesian approach for jointly modeling both known and unknown causes of events. Such modeling has general applicability in domains where the space of known causes is incomplete. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Training models of anatomic shape variability

PubMed Central

Merck, Derek; Tracton, Gregg; Saboo, Rohit; Levy, Joshua; Chaney, Edward; Pizer, Stephen; Joshi, Sarang

2008-01-01

Learning probability distributions of the shape of anatomic structures requires fitting shape representations to human expert segmentations from training sets of medical images. The quality of statistical segmentation and registration methods is directly related to the quality of this initial shape fitting, yet the subject is largely overlooked or described in an ad hoc way. This article presents a set of general principles to guide such training. Our novel method is to jointly estimate both the best geometric model for any given image and the shape distribution for the entire population of training images by iteratively relaxing purely geometric constraints in favor of the converging shape probabilities as the fitted objects converge to their target segmentations. The geometric constraints are carefully crafted both to obtain legal, nonself-interpenetrating shapes and to impose the model-to-model correspondences required for useful statistical analysis. The paper closes with example applications of the method to synthetic and real patient CT image sets, including same patient male pelvis and head and neck images, and cross patient kidney and brain images. Finally, we outline how this shape training serves as the basis for our approach to IGRT∕ART. PMID:18777919

Fracture network of the Ferron Sandstone Member of the Mancos Shale, east-central Utah, USA

USGS Publications Warehouse

Condon, S.M.

2003-01-01

The fracture network at the outcrop of the Ferron Sandstone Member of the Mancos Shale was studied to gain an understanding of the tectonic history of the region and to contribute data to studies of gas and water transmissivity related to the occurrence and production of coal-bed methane. About 1900 fracture readings were made at 40 coal outcrops and 62 sandstone outcrops in the area from Willow Springs Wash in the south to Farnham dome in the north of the study area in east-central Utah.Two sets of regional, vertical to nearly vertical, systematic face cleats were identified in Ferron coals. A northwest-striking set trends at a mean azimuth of 321??, and a northeast-striking set has a mean azimuth of 55??. Cleats were observed in all coal outcrops examined and are closely spaced and commonly coated with thin films of iron oxide.Two sets of regional, systematic joint sets in sandstone were also identified and have mean azimuths of 321?? and 34??. The joints of each set are planar, long, and extend vertically to nearly vertically through multiple beds; the northeast-striking set is more prevalent than the northwest-striking set. In some places, joints of the northeast-striking set occur in closely spaced clusters, or joint zones, flanked by unjointed rock. Both sets are mineralized with iron oxide and calcite, and the northwest-striking set is commonly tightly cemented, which allowed the northeast-striking set to propagate across it. All cleats and joints of these sets are interpreted as opening-mode (mode I) fractures. Abutting relations indicate that the northwest-striking cleats and joints formed first and were later overprinted by the northeast-striking cleats and joints. Burial curves constructed for the Ferron indicate rapid initial burial after deposition. The Ferron reached a depth of 3000 ft (1000 m) within 5.2 million years (m.y.), and this is considered a minimum depth and time for development of cleats and joints. The Sevier orogeny produced southeast-directed compressional stress at this time and is thought to be the likely mechanism for the northwest-striking systematic cleats and joints. The onset of the Laramide orogeny occurred at about 75 Ma, within 13.7 m.y. of burial, and is thought to be the probable mechanism for development of the northeast-striking systematic cleats and joints. Uplift of the Ferron in the late Tertiary contributed to development of butt cleats and secondary cross-joints and probably enhanced previously formed fracture sets. Using a study of the younger Blackhawk Formation as an analogy, the fracture pattern of the Ferron in the subsurface is probably similar to that at the surface, at least as far west as the Paradise fault and Joe's Valley graben. Farther to the west, on the Wasatch Plateau, the orientations of Ferron fractures may diverge from those measured at the outcrop. ?? 2003 Elsevier B.V. All rights reserved.

Joint time/frequency-domain inversion of reflection data for seabed geoacoustic profiles and uncertainties.

PubMed

Dettmer, Jan; Dosso, Stan E; Holland, Charles W

2008-03-01

This paper develops a joint time/frequency-domain inversion for high-resolution single-bounce reflection data, with the potential to resolve fine-scale profiles of sediment velocity, density, and attenuation over small seafloor footprints (approximately 100 m). The approach utilizes sequential Bayesian inversion of time- and frequency-domain reflection data, employing ray-tracing inversion for reflection travel times and a layer-packet stripping method for spherical-wave reflection-coefficient inversion. Posterior credibility intervals from the travel-time inversion are passed on as prior information to the reflection-coefficient inversion. Within the reflection-coefficient inversion, parameter information is passed from one layer packet inversion to the next in terms of marginal probability distributions rotated into principal components, providing an efficient approach to (partially) account for multi-dimensional parameter correlations with one-dimensional, numerical distributions. Quantitative geoacoustic parameter uncertainties are provided by a nonlinear Gibbs sampling approach employing full data error covariance estimation (including nonstationary effects) and accounting for possible biases in travel-time picks. Posterior examination of data residuals shows the importance of including data covariance estimates in the inversion. The joint inversion is applied to data collected on the Malta Plateau during the SCARAB98 experiment.

Sacroiliac Joint Fusion Using Triangular Titanium Implants vs. Non-Surgical Management: Six-Month Outcomes from a Prospective Randomized Controlled Trial.

PubMed

Whang, Peter; Cher, Daniel; Polly, David; Frank, Clay; Lockstadt, Harry; Glaser, John; Limoni, Robert; Sembrano, Jonathan

2015-01-01

Sacroiliac (SI) joint pain is a prevalent, underdiagnosed cause of lower back pain. SI joint fusion can relieve pain and improve quality of life in patients who have failed nonoperative care. To date, no study has concurrently compared surgical and non-surgical treatments for chronic SI joint dysfunction. We conducted a prospective randomized controlled trial of 148 subjects with SI joint dysfunction due to degenerative sacroiliitis or sacroiliac joint disruptions who were assigned to either minimally invasive SI joint fusion with triangular titanium implants (N=102) or non-surgical management (NSM, n=46). SI joint pain scores, Oswestry Disability Index (ODI), Short-Form 36 (SF-36) and EuroQol-5D (EQ-5D) were collected at baseline and at 1, 3 and 6 months after treatment commencement. Six-month success rates, defined as the proportion of treated subjects with a 20-mm improvement in SI joint pain in the absence of severe device-related or neurologic SI joint-related adverse events or surgical revision, were compared using Bayesian methods. Subjects (mean age 51, 70% women) were highly debilitated at baseline (mean SI joint VAS pain score 82, mean ODI score 62). Six-month follow-up was obtained in 97.3%. By 6 months, success rates were 81.4% in the surgical group vs. 23.9% in the NSM group (difference of 56.6%, 95% posterior credible interval 41.4-70.0%, posterior probability of superiority >0.999). Clinically important (≥15 point) ODI improvement at 6 months occurred in 75% of surgery subjects vs. 27.3% of NSM subjects. At six months, quality of life improved more in the surgery group and satisfaction rates were high. The mean number of adverse events in the first six months was slightly higher in the surgical group compared to the non-surgical group (1.3 vs. 1.0 events per subject, p=0.1857). Six-month follow-up from this level 1 study showed that minimally invasive SI joint fusion using triangular titanium implants was more effective than non-surgical management in relieving pain, improving function and improving quality of life in patients with SI joint dysfunction due to degenerative sacroiliitis or SI joint disruptions. Minimally invasive SI joint fusion is an acceptable option for patients with chronic SI joint dysfunction due to degenerative sacroiliitis and sacroiliac joint disruptions unresponsive to non-surgical treatments.

Improving Photometric Redshifts for Hyper Suprime-Cam

NASA Astrophysics Data System (ADS)

Speagle, Josh S.; Leauthaud, Alexie; Eisenstein, Daniel; Bundy, Kevin; Capak, Peter L.; Leistedt, Boris; Masters, Daniel C.; Mortlock, Daniel; Peiris, Hiranya; HSC Photo-z Team; HSC Weak Lensing Team

2017-01-01

Deriving accurate photometric redshift (photo-z) probability distribution functions (PDFs) are crucial science components for current and upcoming large-scale surveys. We outline how rigorous Bayesian inference and machine learning can be combined to quickly derive joint photo-z PDFs to individual galaxies and their parent populations. Using the first 170 deg^2 of data from the ongoing Hyper Suprime-Cam survey, we demonstrate our method is able to generate accurate predictions and reliable credible intervals over ~370k high-quality redshifts. We then use galaxy-galaxy lensing to empirically validate our predicted photo-z's over ~14M objects, finding a robust signal.

Joint symbolic dynamic analysis of cardiorespiratory interactions in patients on weaning trials.

PubMed

Caminal, P; Giraldo, B; Zabaleta, H; Vallverdu, M; Benito, S; Ballesteros, D; Lopez-Rodriguez, L; Esteban, A; Baumert, M; Voss, A

2005-01-01

Assessing autonomic control provides information about patho-physiological imbalances. Measures of variability of the cardiac interbeat duration RR(n) and the variability of the breath duration TTot(n) are sensitive to those changes. The interactions between RR(n) and TTot(n) are complex and strongly non-linear. A study of joint symbolic dynamics is presented as a new short-term non-linear analysis method to investigate these interactions in patients on weaning trials. 78 patients from mechanical ventilation are studied: Group A (patients that failed to maintain spontaneous breathing and were reconnected) and Group B (patients with successful trials). Using the concept of joint symbolic dynamics, cardiac and respiratory changes were transformed into a word series, and the probability of occurrence of each word type was calculated and compared between both groups. Significant differences were found in 13 words, and the most significant pn(Wc010, r010): 0.0041 ± 0.0036 (group A) against 0.0012 ± 0.0024 (group B), p-value = 0.00001. The number of seldom occurring word types (forbidden words) also presents significant differences fwcr: 6.9 ± 6.6 against 13.5 ± 5.3, p-value = 0.00004. Joint symbolic dynamics provides an efficient non-linear representation of cardiorespiratory interactions that offers simple physiological interpretations.

Novel Ultrasound Joint Selection Methods Using a Reduced Joint Number Demonstrate Inflammatory Improvement when Compared to Existing Methods and Disease Activity Score at 28 Joints.

PubMed

Tan, York Kiat; Allen, John C; Lye, Weng Kit; Conaghan, Philip G; D'Agostino, Maria Antonietta; Chew, Li-Ching; Thumboo, Julian

2016-01-01

A pilot study testing novel ultrasound (US) joint-selection methods in rheumatoid arthritis. Responsiveness of novel [individualized US (IUS) and individualized composite US (ICUS)] methods were compared with existing US methods and the Disease Activity Score at 28 joints (DAS28) for 12 patients followed for 3 months. IUS selected up to 7 and 12 most ultrasonographically inflamed joints, while ICUS additionally incorporated clinically symptomatic joints. The existing, IUS, and ICUS methods' standardized response means were -0.39, -1.08, and -1.11, respectively, for 7 joints; -0.49, -1.00, and -1.16, respectively, for 12 joints; and -0.94 for DAS28. Novel methods effectively demonstrate inflammatory improvement when compared with existing methods and DAS28.

Multi-GPU parallel algorithm design and analysis for improved inversion of probability tomography with gravity gradiometry data

NASA Astrophysics Data System (ADS)

Hou, Zhenlong; Huang, Danian

2017-09-01

In this paper, we make a study on the inversion of probability tomography (IPT) with gravity gradiometry data at first. The space resolution of the results is improved by multi-tensor joint inversion, depth weighting matrix and the other methods. Aiming at solving the problems brought by the big data in the exploration, we present the parallel algorithm and the performance analysis combining Compute Unified Device Architecture (CUDA) with Open Multi-Processing (OpenMP) based on Graphics Processing Unit (GPU) accelerating. In the test of the synthetic model and real data from Vinton Dome, we get the improved results. It is also proved that the improved inversion algorithm is effective and feasible. The performance of parallel algorithm we designed is better than the other ones with CUDA. The maximum speedup could be more than 200. In the performance analysis, multi-GPU speedup and multi-GPU efficiency are applied to analyze the scalability of the multi-GPU programs. The designed parallel algorithm is demonstrated to be able to process larger scale of data and the new analysis method is practical.

Detection of nuclear testing from surface concentration measurements: Analysis of radioxenon from the February 2013 underground test in North Korea

DOE PAGES

Kurzeja, R. J.; Buckley, R. L.; Werth, D. W.; ...

2017-12-28

A method is outlined and tested to detect low level nuclear or chemical sources from time series of concentration measurements. The method uses a mesoscale atmospheric model to simulate the concentration signature from a known or suspected source at a receptor which is then regressed successively against segments of the measurement series to create time series of metrics that measure the goodness of fit between the signatures and the measurement segments. The method was applied to radioxenon data from the Comprehensive Test Ban Treaty (CTBT) collection site in Ussuriysk, Russia (RN58) after the Democratic People's Republic of Korea (North Korea)more » underground nuclear test on February 12, 2013 near Punggye. The metrics were found to be a good screening tool to locate data segments with a strong likelihood of origin from Punggye, especially when multiplied together to a determine the joint probability. Metrics from RN58 were also used to find the probability that activity measured in February and April of 2013 originated from the Feb 12 test. A detailed analysis of an RN58 data segment from April 3/4, 2013 was also carried out for a grid of source locations around Punggye and identified Punggye as the most likely point of origin. Thus, the results support the strong possibility that radioxenon was emitted from the test site at various times in April and was detected intermittently at RN58, depending on the wind direction. The method does not locate unsuspected sources, but instead, evaluates the probability of a source at a specified location. However, it can be extended to include a set of suspected sources. Extension of the method to higher resolution data sets, arbitrary sampling, and time-varying sources is discussed along with a path to evaluate uncertainty in the calculated probabilities.« less

Detection of nuclear testing from surface concentration measurements: Analysis of radioxenon from the February 2013 underground test in North Korea

NASA Astrophysics Data System (ADS)

Kurzeja, R. J.; Buckley, R. L.; Werth, D. W.; Chiswell, S. R.

2018-03-01

A method is outlined and tested to detect low level nuclear or chemical sources from time series of concentration measurements. The method uses a mesoscale atmospheric model to simulate the concentration signature from a known or suspected source at a receptor which is then regressed successively against segments of the measurement series to create time series of metrics that measure the goodness of fit between the signatures and the measurement segments. The method was applied to radioxenon data from the Comprehensive Test Ban Treaty (CTBT) collection site in Ussuriysk, Russia (RN58) after the Democratic People's Republic of Korea (North Korea) underground nuclear test on February 12, 2013 near Punggye. The metrics were found to be a good screening tool to locate data segments with a strong likelihood of origin from Punggye, especially when multiplied together to a determine the joint probability. Metrics from RN58 were also used to find the probability that activity measured in February and April of 2013 originated from the Feb 12 test. A detailed analysis of an RN58 data segment from April 3/4, 2013 was also carried out for a grid of source locations around Punggye and identified Punggye as the most likely point of origin. Thus, the results support the strong possibility that radioxenon was emitted from the test site at various times in April and was detected intermittently at RN58, depending on the wind direction. The method does not locate unsuspected sources, but instead, evaluates the probability of a source at a specified location. However, it can be extended to include a set of suspected sources. Extension of the method to higher resolution data sets, arbitrary sampling, and time-varying sources is discussed along with a path to evaluate uncertainty in the calculated probabilities.

Detection of nuclear testing from surface concentration measurements: Analysis of radioxenon from the February 2013 underground test in North Korea

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kurzeja, R. J.; Buckley, R. L.; Werth, D. W.

A method is outlined and tested to detect low level nuclear or chemical sources from time series of concentration measurements. The method uses a mesoscale atmospheric model to simulate the concentration signature from a known or suspected source at a receptor which is then regressed successively against segments of the measurement series to create time series of metrics that measure the goodness of fit between the signatures and the measurement segments. The method was applied to radioxenon data from the Comprehensive Test Ban Treaty (CTBT) collection site in Ussuriysk, Russia (RN58) after the Democratic People's Republic of Korea (North Korea)more » underground nuclear test on February 12, 2013 near Punggye. The metrics were found to be a good screening tool to locate data segments with a strong likelihood of origin from Punggye, especially when multiplied together to a determine the joint probability. Metrics from RN58 were also used to find the probability that activity measured in February and April of 2013 originated from the Feb 12 test. A detailed analysis of an RN58 data segment from April 3/4, 2013 was also carried out for a grid of source locations around Punggye and identified Punggye as the most likely point of origin. Thus, the results support the strong possibility that radioxenon was emitted from the test site at various times in April and was detected intermittently at RN58, depending on the wind direction. The method does not locate unsuspected sources, but instead, evaluates the probability of a source at a specified location. However, it can be extended to include a set of suspected sources. Extension of the method to higher resolution data sets, arbitrary sampling, and time-varying sources is discussed along with a path to evaluate uncertainty in the calculated probabilities.« less

Snake River fall Chinook salmon life history investigations, annual report 2008

USGS Publications Warehouse

Tiffan, Kenneth F.; Connor, William P.; Bellgraph, Brian J.; Buchanan, Rebecca A.

2010-01-01

In 2009, we used radio and acoustic telemetry to evaluate the migratory behavior, survival, mortality, and delay of subyearling fall Chinook salmon in the Clearwater River and Lower Granite Reservoir. We released a total of 1,000 tagged hatchery subyearlings at Cherry Lane on the Clearwater River in mid August and we monitored them as they passed downstream through various river and reservoir reaches. Survival through the free-flowing river was high (>0.85) for both radio- and acoustic-tagged fish, but dropped substantially as fish delayed in the Transition Zone and Confluence areas. Estimates of the joint probability of migration and survival through the Transition Zone and Confluence reaches combined were similar for both radio- and acoustic-tagged fish, and ranged from about 0.30 to 0.35. Estimates of the joint probability of delaying and surviving in the combined Transition Zone and Confluence peaked at the beginning of the study, ranging from 0.323 ( SE =NA; radio-telemetry data) to 0.466 ( SE =0.024; acoustic-telemetry data), and then steadily declined throughout the remainder of the study. By the end of October, no live tagged juvenile salmon were detected in either the Transition Zone or the Confluence. As estimates of the probability of delay decreased throughout the study, estimates of the probability of mortality increased, as evidenced by the survival estimate of 0.650 ( SE =0.025) at the end of October (acoustic-telemetry data). Few fish were detected at Lower Granite Dam during our study and even fewer fish passed the dam before PIT-tag monitoring ended at the end of October. Five acoustic-tagged fish passed Lower Granite Dam in October and 12 passed the dam in November based on detections in the dam tailrace; however, too few detections were available to calculate the joint probabilities of migrating and surviving or delaying and surviving. Estimates of the joint probability of migrating and surviving through the reservoir was less than 0.2 based on acoustic-tagged fish. Migration rates of tagged fish were highest in the free-flowing river (median range = 36 to 43 km/d) but were generally less than 6 km/d in the reservoir reaches. In particular, median migration rates of radio-tagged fish through the Transition Zone and Confluence were 3.4 and 5.2 km/d, respectively. Median migration rate for acoustic-tagged fish though the Transition Zone and Confluence combined was 1 km/d.

A comprehensive model to determine the effects of temperature and species fluctuations on reactions in turbulent reacting flows

NASA Technical Reports Server (NTRS)

Antaki, P. J.

1981-01-01

The joint probability distribution function (pdf), which is a modification of the bivariate Gaussian pdf, is discussed and results are presented for a global reaction model using the joint pdf. An alternative joint pdf is discussed. A criterion which permits the selection of temperature pdf's in different regions of turbulent, reacting flow fields is developed. Two principal approaches to the determination of reaction rates in computer programs containing detailed chemical kinetics are outlined. These models represent a practical solution to the modeling of species reaction rates in turbulent, reacting flows.

Experimental joint weak measurement on a photon pair as a probe of Hardy's paradox.

PubMed

Lundeen, J S; Steinberg, A M

2009-01-16

It has been proposed that the ability to perform joint weak measurements on postselected systems would allow us to study quantum paradoxes. These measurements can investigate the history of those particles that contribute to the paradoxical outcome. Here we experimentally perform weak measurements of joint (i.e., nonlocal) observables. In an implementation of Hardy's paradox, we weakly measure the locations of two photons, the subject of the conflicting statements behind the paradox. Remarkably, the resulting weak probabilities verify all of these statements but, at the same time, resolve the paradox.

Idealized models of the joint probability distribution of wind speeds

NASA Astrophysics Data System (ADS)

Monahan, Adam H.

2018-05-01

The joint probability distribution of wind speeds at two separate locations in space or points in time completely characterizes the statistical dependence of these two quantities, providing more information than linear measures such as correlation. In this study, we consider two models of the joint distribution of wind speeds obtained from idealized models of the dependence structure of the horizontal wind velocity components. The bivariate Rice distribution follows from assuming that the wind components have Gaussian and isotropic fluctuations. The bivariate Weibull distribution arises from power law transformations of wind speeds corresponding to vector components with Gaussian, isotropic, mean-zero variability. Maximum likelihood estimates of these distributions are compared using wind speed data from the mid-troposphere, from different altitudes at the Cabauw tower in the Netherlands, and from scatterometer observations over the sea surface. While the bivariate Rice distribution is more flexible and can represent a broader class of dependence structures, the bivariate Weibull distribution is mathematically simpler and may be more convenient in many applications. The complexity of the mathematical expressions obtained for the joint distributions suggests that the development of explicit functional forms for multivariate speed distributions from distributions of the components will not be practical for more complicated dependence structure or more than two speed variables.

Context-invariant quasi hidden variable (qHV) modelling of all joint von Neumann measurements for an arbitrary Hilbert space

DOE Office of Scientific and Technical Information (OSTI.GOV)

Loubenets, Elena R.

We prove the existence for each Hilbert space of the two new quasi hidden variable (qHV) models, statistically noncontextual and context-invariant, reproducing all the von Neumann joint probabilities via non-negative values of real-valued measures and all the quantum product expectations—via the qHV (classical-like) average of the product of the corresponding random variables. In a context-invariant model, a quantum observable X can be represented by a variety of random variables satisfying the functional condition required in quantum foundations but each of these random variables equivalently models X under all joint von Neumann measurements, regardless of their contexts. The proved existence ofmore » this model negates the general opinion that, in terms of random variables, the Hilbert space description of all the joint von Neumann measurements for dimH≥3 can be reproduced only contextually. The existence of a statistically noncontextual qHV model, in particular, implies that every N-partite quantum state admits a local quasi hidden variable model introduced in Loubenets [J. Math. Phys. 53, 022201 (2012)]. The new results of the present paper point also to the generality of the quasi-classical probability model proposed in Loubenets [J. Phys. A: Math. Theor. 45, 185306 (2012)].« less

Development and application of a probability distribution retrieval scheme to the remote sensing of clouds and precipitation

NASA Astrophysics Data System (ADS)

McKague, Darren Shawn

2001-12-01

The statistical properties of clouds and precipitation on a global scale are important to our understanding of climate. Inversion methods exist to retrieve the needed cloud and precipitation properties from satellite data pixel-by-pixel that can then be summarized over large data sets to obtain the desired statistics. These methods can be quite computationally expensive, and typically don't provide errors on the statistics. A new method is developed to directly retrieve probability distributions of parameters from the distribution of measured radiances. The method also provides estimates of the errors on the retrieved distributions. The method can retrieve joint distributions of parameters that allows for the study of the connection between parameters. A forward radiative transfer model creates a mapping from retrieval parameter space to radiance space. A Monte Carlo procedure uses the mapping to transform probability density from the observed radiance histogram to a two- dimensional retrieval property probability distribution function (PDF). An estimate of the uncertainty in the retrieved PDF is calculated from random realizations of the radiance to retrieval parameter PDF transformation given the uncertainty of the observed radiances, the radiance PDF, the forward radiative transfer, the finite number of prior state vectors, and the non-unique mapping to retrieval parameter space. The retrieval method is also applied to the remote sensing of precipitation from SSM/I microwave data. A method of stochastically generating hydrometeor fields based on the fields from a numerical cloud model is used to create the precipitation parameter radiance space transformation. The impact of vertical and horizontal variability within the hydrometeor fields has a significant impact on algorithm performance. Beamfilling factors are computed from the simulated hydrometeor fields. The beamfilling factors vary quite a bit depending upon the horizontal structure of the rain. The algorithm is applied to SSM/I images from the eastern tropical Pacific and is compared to PDFs of rain rate computed using pixel-by-pixel retrievals from Wilheit and from Liu and Curry. Differences exist between the three methods, but good general agreement is seen between the PDF retrieval algorithm and the algorithm of Liu and Curry. (Abstract shortened by UMI.)

A Doubly Stochastic Change Point Detection Algorithm for Noisy Biological Signals.

PubMed

Gold, Nathan; Frasch, Martin G; Herry, Christophe L; Richardson, Bryan S; Wang, Xiaogang

2017-01-01

Experimentally and clinically collected time series data are often contaminated with significant confounding noise, creating short, noisy time series. This noise, due to natural variability and measurement error, poses a challenge to conventional change point detection methods. We propose a novel and robust statistical method for change point detection for noisy biological time sequences. Our method is a significant improvement over traditional change point detection methods, which only examine a potential anomaly at a single time point. In contrast, our method considers all suspected anomaly points and considers the joint probability distribution of the number of change points and the elapsed time between two consecutive anomalies. We validate our method with three simulated time series, a widely accepted benchmark data set, two geological time series, a data set of ECG recordings, and a physiological data set of heart rate variability measurements of fetal sheep model of human labor, comparing it to three existing methods. Our method demonstrates significantly improved performance over the existing point-wise detection methods.

Review: magnetically assisted resistance spot welding

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Y. B.; Li, D. L.; Lin, Z. Q.

2016-02-25

Currently, the use of advanced high strength steels (AHSSs) is the most cost effective means of reducing vehicle body weight and maintaining structural integrity at the same time. However, AHSSs present a big challenge to the traditional resistance spot welding (RSW) widely applied in automotive industries because the rapid heating and cooling procedures during RSW produce hardened weld microstructures, which lower the ductility and fatigue properties of welded joints and raise the probability of interfacial failure under external loads. Changing process parameters or post-weld heat treatment may reduce the weld brittleness, but those traditional quality control methods also increase energymore » consumption and prolong cycle time. In recent years, a magnetically assisted RSW (MA-RSW) method was proposed, in which an externally applied magnetic field would interact with the conduction current to produce a Lorentz force that would affect weld nugget formation. This paper is a review of an experimental MA-RSW platform, the mode of the external magnetic field and the mechanism that controls nugget shape, weld microstructures and joint performance. In conclusion, the advantages of the MA-RSW method in improving the weldability of AHSSs are given, a recent application of the MA-RSW process to light metals is described and the outlook for the MA-RSW process is presented.« less

A New Approach in Generating Meteorological Forecasts for Ensemble Streamflow Forecasting using Multivariate Functions

NASA Astrophysics Data System (ADS)

Khajehei, S.; Madadgar, S.; Moradkhani, H.

2014-12-01

The reliability and accuracy of hydrological predictions are subject to various sources of uncertainty, including meteorological forcing, initial conditions, model parameters and model structure. To reduce the total uncertainty in hydrological applications, one approach is to reduce the uncertainty in meteorological forcing by using the statistical methods based on the conditional probability density functions (pdf). However, one of the requirements for current methods is to assume the Gaussian distribution for the marginal distribution of the observed and modeled meteorology. Here we propose a Bayesian approach based on Copula functions to develop the conditional distribution of precipitation forecast needed in deriving a hydrologic model for a sub-basin in the Columbia River Basin. Copula functions are introduced as an alternative approach in capturing the uncertainties related to meteorological forcing. Copulas are multivariate joint distribution of univariate marginal distributions, which are capable to model the joint behavior of variables with any level of correlation and dependency. The method is applied to the monthly forecast of CPC with 0.25x0.25 degree resolution to reproduce the PRISM dataset over 1970-2000. Results are compared with Ensemble Pre-Processor approach as a common procedure used by National Weather Service River forecast centers in reproducing observed climatology during a ten-year verification period (2000-2010).

Understanding the joint behavior of temperature and precipitation for climate change impact studies

NASA Astrophysics Data System (ADS)

Rana, Arun; Moradkhani, Hamid; Qin, Yueyue

2017-07-01

The multiple downscaled scenario products allow us to assess the uncertainty of the variations of precipitation and temperature in the current and future periods. Probabilistic assessments of both climatic variables help better understand the interdependence of the two and thus, in turn, help in assessing the future with confidence. In the present study, we use ensemble of statistically downscaled precipitation and temperature from various models. The dataset used is multi-model ensemble of 10 global climate models (GCMs) downscaled product from CMIP5 daily dataset using the Bias Correction and Spatial Downscaling (BCSD) technique, generated at Portland State University. The multi-model ensemble of both precipitation and temperature is evaluated for dry and wet periods for 10 sub-basins across Columbia River Basin (CRB). Thereafter, copula is applied to establish the joint distribution of two variables on multi-model ensemble data. The joint distribution is then used to estimate the change in trends of said variables in future, along with estimation of the probabilities of the given change. The joint distribution trends vary, but certainly positive, for dry and wet periods in sub-basins of CRB. Dry season, generally, is indicating a higher positive change in precipitation than temperature (as compared to historical) across sub-basins with wet season inferring otherwise. Probabilities of changes in future, as estimated from the joint distribution, indicate varied degrees and forms during dry season whereas the wet season is rather constant across all the sub-basins.

Hereditary hemochromatosis is characterized by a clinically definable arthropathy that correlates with iron load.

PubMed

Carroll, G J; Breidahl, W H; Bulsara, M K; Olynyk, J K

2011-01-01

To determine the frequency and character of arthropathy in hereditary hemochromatosis (HH) and to investigate the relationship between this arthropathy, nodal interphalangeal osteoarthritis, and iron load. Participants were recruited from the community by newspaper advertisement and assigned to diagnostic confidence categories for HH (definite/probable or possible/unlikely). Arthropathy was determined by use of a predetermined clinical protocol, radiographs of the hands of all participants, and radiographs of other joints in which clinical criteria were met. An arthropathy considered typical for HH, involving metacarpophalangeal joints 2-5 and bilateral specified large joints, was observed in 10 of 41 patients with definite or probable HH (24%), all of whom were homozygous for the C282Y mutation in the HFE gene, while only 2 of 62 patients with possible/unlikely HH had such an arthropathy (P=0.0024). Arthropathy in definite/probable HH was more common with increasing age and was associated with ferritin concentrations>1,000 μg/liter at the time of diagnosis (odds ratio 14.0 [95% confidence interval 1.30-150.89], P=0.03). A trend toward more episodes requiring phlebotomy was also observed among those with arthropathy, but this was not statistically significant (odds ratio 1.03 [95% confidence interval 0.99-1.06], P=0.097). There was no significant association between arthropathy in definite/probable HH and a history of intensive physical labor (P=0.12). An arthropathy consistent with that commonly attributed to HH was found to occur in 24% of patients with definite/probable HH. The association observed between this arthropathy, homozygosity for C282Y, and serum ferritin concentrations at the time of diagnosis suggests that iron load is likely to be a major determinant of arthropathy in HH and to be more important than occupational factors. Copyright © 2011 by the American College of Rheumatology.

Characterization of friction stir welded joint of low nickel austenitic stainless steel and modified ferritic stainless steel

NASA Astrophysics Data System (ADS)

Mondal, Mounarik; Das, Hrishikesh; Ahn, Eun Yeong; Hong, Sung Tae; Kim, Moon-Jo; Han, Heung Nam; Pal, Tapan Kumar

2017-09-01

Friction stir welding (FSW) of dissimilar stainless steels, low nickel austenitic stainless steel and 409M ferritic stainless steel, is experimentally investigated. Process responses during FSW and the microstructures of the resultant dissimilar joints are evaluated. Material flow in the stir zone is investigated in detail by elemental mapping. Elemental mapping of the dissimilar joints clearly indicates that the material flow pattern during FSW depends on the process parameter combination. Dynamic recrystallization and recovery are also observed in the dissimilar joints. Among the two different stainless steels selected in the present study, the ferritic stainless steels shows more severe dynamic recrystallization, resulting in a very fine microstructure, probably due to the higher stacking fault energy.

Supervised Detection of Anomalous Light Curves in Massive Astronomical Catalogs

NASA Astrophysics Data System (ADS)

Nun, Isadora; Pichara, Karim; Protopapas, Pavlos; Kim, Dae-Won

2014-09-01

The development of synoptic sky surveys has led to a massive amount of data for which resources needed for analysis are beyond human capabilities. In order to process this information and to extract all possible knowledge, machine learning techniques become necessary. Here we present a new methodology to automatically discover unknown variable objects in large astronomical catalogs. With the aim of taking full advantage of all information we have about known objects, our method is based on a supervised algorithm. In particular, we train a random forest classifier using known variability classes of objects and obtain votes for each of the objects in the training set. We then model this voting distribution with a Bayesian network and obtain the joint voting distribution among the training objects. Consequently, an unknown object is considered as an outlier insofar it has a low joint probability. By leaving out one of the classes on the training set, we perform a validity test and show that when the random forest classifier attempts to classify unknown light curves (the class left out), it votes with an unusual distribution among the classes. This rare voting is detected by the Bayesian network and expressed as a low joint probability. Our method is suitable for exploring massive data sets given that the training process is performed offline. We tested our algorithm on 20 million light curves from the MACHO catalog and generated a list of anomalous candidates. After analysis, we divided the candidates into two main classes of outliers: artifacts and intrinsic outliers. Artifacts were principally due to air mass variation, seasonal variation, bad calibration, or instrumental errors and were consequently removed from our outlier list and added to the training set. After retraining, we selected about 4000 objects, which we passed to a post-analysis stage by performing a cross-match with all publicly available catalogs. Within these candidates we identified certain known but rare objects such as eclipsing Cepheids, blue variables, cataclysmic variables, and X-ray sources. For some outliers there was no additional information. Among them we identified three unknown variability types and a few individual outliers that will be followed up in order to perform a deeper analysis.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nun, Isadora; Pichara, Karim; Protopapas, Pavlos

The development of synoptic sky surveys has led to a massive amount of data for which resources needed for analysis are beyond human capabilities. In order to process this information and to extract all possible knowledge, machine learning techniques become necessary. Here we present a new methodology to automatically discover unknown variable objects in large astronomical catalogs. With the aim of taking full advantage of all information we have about known objects, our method is based on a supervised algorithm. In particular, we train a random forest classifier using known variability classes of objects and obtain votes for each ofmore » the objects in the training set. We then model this voting distribution with a Bayesian network and obtain the joint voting distribution among the training objects. Consequently, an unknown object is considered as an outlier insofar it has a low joint probability. By leaving out one of the classes on the training set, we perform a validity test and show that when the random forest classifier attempts to classify unknown light curves (the class left out), it votes with an unusual distribution among the classes. This rare voting is detected by the Bayesian network and expressed as a low joint probability. Our method is suitable for exploring massive data sets given that the training process is performed offline. We tested our algorithm on 20 million light curves from the MACHO catalog and generated a list of anomalous candidates. After analysis, we divided the candidates into two main classes of outliers: artifacts and intrinsic outliers. Artifacts were principally due to air mass variation, seasonal variation, bad calibration, or instrumental errors and were consequently removed from our outlier list and added to the training set. After retraining, we selected about 4000 objects, which we passed to a post-analysis stage by performing a cross-match with all publicly available catalogs. Within these candidates we identified certain known but rare objects such as eclipsing Cepheids, blue variables, cataclysmic variables, and X-ray sources. For some outliers there was no additional information. Among them we identified three unknown variability types and a few individual outliers that will be followed up in order to perform a deeper analysis.« less

Occurrence, distribution, and concentration of hydrocarbons in and near the Shell Valley Aquifer, North Dakota

USGS Publications Warehouse

Berkas, Wayne R.

2000-01-01

Water samples from 27 wells completed in and near the Shell Valley aquifer were analyzed for benzene, toluene, ethylbenzene, and xylene (BTEX), polynuclear aromatic hydrocarbons (PAH), polychlorinated biphenyls (PCB), and pentachlorophenol (PCP) using the enzyme-linked immunoassay method. The analyses indicated the presence of PAH, PCB, and PCP in the study area. However, an individual compound at a high concentration or many compounds at low concentrations could cause the detections. Therefore, selected samples were analyzed using the gas chromatography (GC) method, which can detect individual compounds and determine the concentrations of those compounds. Concentrations for all compounds detected using the GC method were less than the minimum reporting levels (MRLs) for each constituent, indicating numerous compounds at low concentrations probably caused the immunoassay detections. The GC method also can detect compounds other than BTEX, PAH, PCB, and PCP. Concentrations for 81 of the additional compounds were determined and were less than the MRLs.Four compounds that could not be quantified accurately using the requested analytical methods also were detected. Acetone was detected in 4 of the 27 wells, 2-butanone was detected in 3 of the 27 wells, prometon was detected in 1 of the 27 wells, and tetrahydrofuran was detected in 9 of the 27 wells. Acetone, 2-butanone, and tetrahydrofuran probably leached from the polyvinyl chloride (PVC) pipe and joint glue and probably are not contaminants from the aquifer. Prometon is a herbicide that controls most annual and many perennial broadleaf weeds and primarily is used on roads and railroad tracks. The one occurrence of prometon could be caused by overspraying for weeds.

Factors related to the joint probability of flooding on paired streams

USGS Publications Warehouse

Koltun, G.F.; Sherwood, J.M.

1998-01-01

The factors related to the joint probabilty of flooding on paired streams were investigated and quantified to provide information to aid in the design of hydraulic structures where the joint probabilty of flooding is an element of the design criteria. Stream pairs were considered to have flooded jointly at the design-year flood threshold (corresponding to the 2-, 10-, 25-, or 50-year instantaneous peak streamflow) if peak streamflows at both streams in the pair were observed or predicted to have equaled or exceeded the threshold on a given calendar day. Daily mean streamflow data were used as a substitute for instantaneous peak streamflow data to determine which flood thresholds were equaled or exceeded on any given day. Instantaneous peak streamflow data, when available, were used preferentially to assess flood-threshold exceedance. Daily mean streamflow data for each stream were paired with concurrent daily mean streamflow data at the other streams. Observed probabilities of joint flooding, determined for the 2-, 10-, 25-, and 50-year flood thresholds, were computed as the ratios of the total number of days when streamflows at both streams concurrently equaled or exceeded their flood thresholds (events) to the total number of days where streamflows at either stream equaled or exceeded its flood threshold (trials). A combination of correlation analyses, graphical analyses, and logistic-regression analyses were used to identify and quantify factors associated with the observed probabilities of joint flooding (event-trial ratios). The analyses indicated that the distance between drainage area centroids, the ratio of the smaller to larger drainage area, the mean drainage area, and the centroid angle adjusted 30 degrees were the basin characteristics most closely associated with the joint probabilty of flooding on paired streams in Ohio. In general, the analyses indicated that the joint probabilty of flooding decreases with an increase in centroid distance and increases with increases in drainage area ratio, mean drainage area, and centroid angle adjusted 30 degrees. Logistic-regression equations were developed, which can be used to estimate the probability that streamflows at two streams jointly equal or exceed the 2-year flood threshold given that the streamflow at one of the two streams equals or exceeds the 2-year flood threshold. The logistic-regression equations are applicable to stream pairs in Ohio (and border areas of adjacent states) that are unregulated, free of significant urban influences, and have characteristics similar to those of the 304 gaged stream pairs used in the logistic-regression analyses. Contingency tables were constructed and analyzed to provide information about the bivariate distribution of floods on paired streams. The contingency tables showed that the percentage of trials in which both streams in the pair concurrently flood at identical recurrence-interval ranges generally increased as centroid distances decreased and was greatest for stream pairs with adjusted centroid angles greater than or equal to 60 degrees and drainage area ratios greater than or equal to 0.01. Also, as centroid distance increased, streamflow at one stream in the pair was more likely to be in a less than 2-year recurrence-interval range when streamflow at the second stream was in a 2-year or greater recurrence-interval range.

Quantum probability assignment limited by relativistic causality.

PubMed

Han, Yeong Deok; Choi, Taeseung

2016-03-14

Quantum theory has nonlocal correlations, which bothered Einstein, but found to satisfy relativistic causality. Correlation for a shared quantum state manifests itself, in the standard quantum framework, by joint probability distributions that can be obtained by applying state reduction and probability assignment that is called Born rule. Quantum correlations, which show nonlocality when the shared state has an entanglement, can be changed if we apply different probability assignment rule. As a result, the amount of nonlocality in quantum correlation will be changed. The issue is whether the change of the rule of quantum probability assignment breaks relativistic causality. We have shown that Born rule on quantum measurement is derived by requiring relativistic causality condition. This shows how the relativistic causality limits the upper bound of quantum nonlocality through quantum probability assignment.

Gaussianization for fast and accurate inference from cosmological data

NASA Astrophysics Data System (ADS)

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

2016-06-01

We present a method to transform multivariate unimodal non-Gaussian posterior probability densities into approximately Gaussian ones via non-linear mappings, such as Box-Cox transformations and generalizations thereof. This permits an analytical reconstruction of the posterior from a point sample, like a Markov chain, and simplifies the subsequent joint analysis with other experiments. This way, a multivariate posterior density can be reported efficiently, by compressing the information contained in Markov Chain Monte Carlo samples. Further, the model evidence integral (I.e. the marginal likelihood) can be computed analytically. This method is analogous to the search for normal parameters in the cosmic microwave background, but is more general. The search for the optimally Gaussianizing transformation is performed computationally through a maximum-likelihood formalism; its quality can be judged by how well the credible regions of the posterior are reproduced. We demonstrate that our method outperforms kernel density estimates in this objective. Further, we select marginal posterior samples from Planck data with several distinct strongly non-Gaussian features, and verify the reproduction of the marginal contours. To demonstrate evidence computation, we Gaussianize the joint distribution of data from weak lensing and baryon acoustic oscillations, for different cosmological models, and find a preference for flat Λcold dark matter. Comparing to values computed with the Savage-Dickey density ratio, and Population Monte Carlo, we find good agreement of our method within the spread of the other two.

Multiple imputation to account for measurement error in marginal structural models

PubMed Central

Edwards, Jessie K.; Cole, Stephen R.; Westreich, Daniel; Crane, Heidi; Eron, Joseph J.; Mathews, W. Christopher; Moore, Richard; Boswell, Stephen L.; Lesko, Catherine R.; Mugavero, Michael J.

2015-01-01

Background Marginal structural models are an important tool for observational studies. These models typically assume that variables are measured without error. We describe a method to account for differential and non-differential measurement error in a marginal structural model. Methods We illustrate the method estimating the joint effects of antiretroviral therapy initiation and current smoking on all-cause mortality in a United States cohort of 12,290 patients with HIV followed for up to 5 years between 1998 and 2011. Smoking status was likely measured with error, but a subset of 3686 patients who reported smoking status on separate questionnaires composed an internal validation subgroup. We compared a standard joint marginal structural model fit using inverse probability weights to a model that also accounted for misclassification of smoking status using multiple imputation. Results In the standard analysis, current smoking was not associated with increased risk of mortality. After accounting for misclassification, current smoking without therapy was associated with increased mortality [hazard ratio (HR): 1.2 (95% CI: 0.6, 2.3)]. The HR for current smoking and therapy (0.4 (95% CI: 0.2, 0.7)) was similar to the HR for no smoking and therapy (0.4; 95% CI: 0.2, 0.6). Conclusions Multiple imputation can be used to account for measurement error in concert with methods for causal inference to strengthen results from observational studies. PMID:26214338

Multivariate normal maximum likelihood with both ordinal and continuous variables, and data missing at random.

PubMed

Pritikin, Joshua N; Brick, Timothy R; Neale, Michael C

2018-04-01

A novel method for the maximum likelihood estimation of structural equation models (SEM) with both ordinal and continuous indicators is introduced using a flexible multivariate probit model for the ordinal indicators. A full information approach ensures unbiased estimates for data missing at random. Exceeding the capability of prior methods, up to 13 ordinal variables can be included before integration time increases beyond 1 s per row. The method relies on the axiom of conditional probability to split apart the distribution of continuous and ordinal variables. Due to the symmetry of the axiom, two similar methods are available. A simulation study provides evidence that the two similar approaches offer equal accuracy. A further simulation is used to develop a heuristic to automatically select the most computationally efficient approach. Joint ordinal continuous SEM is implemented in OpenMx, free and open-source software.

Probabilistic density function method for nonlinear dynamical systems driven by colored noise

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barajas-Solano, David A.; Tartakovsky, Alexandre M.

2016-05-01

We present a probability density function (PDF) method for a system of nonlinear stochastic ordinary differential equations driven by colored noise. The method provides an integro-differential equation for the temporal evolution of the joint PDF of the system's state, which we close by means of a modified Large-Eddy-Diffusivity-type closure. Additionally, we introduce the generalized local linearization (LL) approximation for deriving a computable PDF equation in the form of the second-order partial differential equation (PDE). We demonstrate the proposed closure and localization accurately describe the dynamics of the PDF in phase space for systems driven by noise with arbitrary auto-correlation time.more » We apply the proposed PDF method to the analysis of a set of Kramers equations driven by exponentially auto-correlated Gaussian colored noise to study the dynamics and stability of a power grid.« less

Advances and Prospects in Tissue-Engineered Meniscal Scaffolds for Meniscus Regeneration

PubMed Central

Guo, Weimin; Liu, Shuyun; Zhu, Yun; Yu, Changlong; Lu, Shibi; Yuan, Mei; Huang, Jingxiang; Yuan, Zhiguo; Peng, Jiang; Wang, Aiyuan; Wang, Yu; Chen, Jifeng; Zhang, Li; Sui, Xiang; Xu, Wenjing; Guo, Quanyi

2015-01-01

The meniscus plays a crucial role in maintaining knee joint homoeostasis. Meniscal lesions are relatively common in the knee joint and are typically categorized into various types. However, it is difficult for inner avascular meniscal lesions to self-heal. Untreated meniscal lesions lead to meniscal extrusions in the long-term and gradually trigger the development of knee osteoarthritis (OA). The relationship between meniscal lesions and knee OA is complex. Partial meniscectomy, which is the primary method to treat a meniscal injury, only relieves short-term pain; however, it does not prevent the development of knee OA. Similarly, other current therapeutic strategies have intrinsic limitations in clinical practice. Tissue engineering technology will probably address this challenge by reconstructing a meniscus possessing an integrated configuration with competent biomechanical capacity. This review describes normal structure and biomechanical characteristics of the meniscus, discusses the relationship between meniscal lesions and knee OA, and summarizes the classifications and corresponding treatment strategies for meniscal lesions to understand meniscal regeneration from physiological and pathological perspectives. Last, we present current advances in meniscal scaffolds and provide a number of prospects that will potentially benefit the development of meniscal regeneration methods. PMID:26199629

Computational methods for efficient structural reliability and reliability sensitivity analysis

NASA Technical Reports Server (NTRS)

Wu, Y.-T.

1993-01-01

This paper presents recent developments in efficient structural reliability analysis methods. The paper proposes an efficient, adaptive importance sampling (AIS) method that can be used to compute reliability and reliability sensitivities. The AIS approach uses a sampling density that is proportional to the joint PDF of the random variables. Starting from an initial approximate failure domain, sampling proceeds adaptively and incrementally with the goal of reaching a sampling domain that is slightly greater than the failure domain to minimize over-sampling in the safe region. Several reliability sensitivity coefficients are proposed that can be computed directly and easily from the above AIS-based failure points. These probability sensitivities can be used for identifying key random variables and for adjusting design to achieve reliability-based objectives. The proposed AIS methodology is demonstrated using a turbine blade reliability analysis problem.

Cardiorespiratory and cardiovascular interactions in cardiomyopathy patients using joint symbolic dynamic analysis.

PubMed

Giraldo, Beatriz F; Rodriguez, Javier; Caminal, Pere; Bayes-Genis, Antonio; Voss, Andreas

2015-01-01

Cardiovascular diseases are the first cause of death in developed countries. Using electrocardiographic (ECG), blood pressure (BP) and respiratory flow signals, we obtained parameters for classifying cardiomyopathy patients. 42 patients with ischemic (ICM) and dilated (DCM) cardiomyopathies were studied. The left ventricular ejection fraction (LVEF) was used to stratify patients with low risk (LR: LVEF>35%, 14 patients) and high risk (HR: LVEF≤ 35%, 28 patients) of heart attack. RR, SBP and TTot time series were extracted from the ECG, BP and respiratory flow signals, respectively. The time series were transformed to a binary space and then analyzed using Joint Symbolic Dynamic with a word length of three, characterizing them by the probability of occurrence of the words. Extracted parameters were then reduced using correlation and statistical analysis. Principal component analysis and support vector machines methods were applied to characterize the cardiorespiratory and cardiovascular interactions in ICM and DCM cardiomyopathies, obtaining an accuracy of 85.7%.

Three-Dimensional Structural and Hydrologic Evolution of Sant Corneli Anticline, a Fault-Cored Fold in the Central Spanish Pyrenees

NASA Astrophysics Data System (ADS)

Shackleton, J. R.; Cooke, M. L.

2005-12-01

The Sant Corneli Anticline is a well-exposed example of a fault-cored fold whose hydrologic evolution and structural development are directly linked. The E-W striking anticline is ~ 5 km wide with abrupt westerly plunge, and formed in response to thrusting associated with the upper Cretaceous to Miocene collision of Iberia with Europe. The fold's core of fractured carbonates contains a variety of west dipping normal faults with meter to decameter scale displacement and abundant calcite fill. This carbonate unit is capped by a marl unit with low angle, calcite filled normal faults. The marl unit is overlain by clastic syn-tectonic strata whose sedimentary architecture records limb rotation during the evolution of the fold. The syn-tectonic strata contain a variety of joint sets that record the stresses before, during, and possibly after fold growth. Faulting in the marl and calcite-filled joints in the syn-tectonic strata suggest that normal faults within the carbonate core of the fold eventually breached the overlying marl unit. This breach may have connected the joints of the syn-tectonic strata to the underlying carbonate reservoir and eliminated previous compartmentalization of fluids. Furthermore, breaching of the marl units probably enhanced joint formation in the overlying syn-tectonic strata. Future geochemical studies of calcite compositions in the three units will address this hypothesis. Preliminary mapping of joint sets in the syn-tectonic strata reveal a multistage history of jointing. Early bed-perpendicular joints healed by calcite strike NE-SW, parallel to normal faults in the underlying carbonates, and may be related to an early regional extensional event. Younger healed bed-perpendicular joints cross cut the NE-SW striking set, and are closer to N-S in strike: these joints are interpreted to represent the initial stages of folding. Decameter scale, bed perpendicular, unfilled fractures that are sub-parallel to strike probably represent small joints and faults that formed in response to outer arc extension during folding. Many filled, late stage joints strike sub-parallel to, and increase in frequency near, normal faults and transverse structures observed in the carbonate fold core. This suggests that faulting in the underlying carbonates and marls significantly affected the joint patterns in the syn-tectonic strata. Preliminary three-dimensional finite element restorations using Dynel have allowed us to test our hypotheses and constrain the timing of jointing and marl breach.

Simultaneous dense coding affected by fluctuating massless scalar field

NASA Astrophysics Data System (ADS)

Huang, Zhiming; Ye, Yiyong; Luo, Darong

2018-04-01

In this paper, we investigate the simultaneous dense coding (SDC) protocol affected by fluctuating massless scalar field. The noisy model of SDC protocol is constructed and the master equation that governs the SDC evolution is deduced. The success probabilities of SDC protocol are discussed for different locking operators under the influence of vacuum fluctuations. We find that the joint success probability is independent of the locking operators, but other success probabilities are not. For quantum Fourier transform and double controlled-NOT operators, the success probabilities drop with increasing two-atom distance, but SWAP operator is not. Unlike the SWAP operator, the success probabilities of Bob and Charlie are different. For different noisy interval values, different locking operators have different robustness to noise.

Evidence-based diagnostics: adult septic arthritis.

PubMed

Carpenter, Christopher R; Schuur, Jeremiah D; Everett, Worth W; Pines, Jesse M

2011-08-01

Acutely swollen or painful joints are common complaints in the emergency department (ED). Septic arthritis in adults is a challenging diagnosis, but prompt differentiation of a bacterial etiology is crucial to minimize morbidity and mortality. The objective was to perform a systematic review describing the diagnostic characteristics of history, physical examination, and bedside laboratory tests for nongonococcal septic arthritis. A secondary objective was to quantify test and treatment thresholds using derived estimates of sensitivity and specificity, as well as best-evidence diagnostic and treatment risks and anticipated benefits from appropriate therapy. Two electronic search engines (PUBMED and EMBASE) were used in conjunction with a selected bibliography and scientific abstract hand search. Inclusion criteria included adult trials of patients presenting with monoarticular complaints if they reported sufficient detail to reconstruct partial or complete 2 × 2 contingency tables for experimental diagnostic test characteristics using an acceptable criterion standard. Evidence was rated by two investigators using the Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS). When more than one similarly designed trial existed for a diagnostic test, meta-analysis was conducted using a random effects model. Interval likelihood ratios (LRs) were computed when possible. To illustrate one method to quantify theoretical points in the probability of disease whereby clinicians might cease testing altogether and either withhold treatment (test threshold) or initiate definitive therapy in lieu of further diagnostics (treatment threshold), an interactive spreadsheet was designed and sample calculations were provided based on research estimates of diagnostic accuracy, diagnostic risk, and therapeutic risk/benefits. The prevalence of nongonococcal septic arthritis in ED patients with a single acutely painful joint is approximately 27% (95% confidence interval [CI] = 17% to 38%). With the exception of joint surgery (positive likelihood ratio [+LR] = 6.9) or skin infection overlying a prosthetic joint (+LR = 15.0), history, physical examination, and serum tests do not significantly alter posttest probability. Serum inflammatory markers such as white blood cell (WBC) counts, erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP) are not useful acutely. The interval LR for synovial white blood cell (sWBC) counts of 0 × 10(9)-25 × 10(9)/L was 0.33; for 25 × 10(9)-50 × 10(9)/L, 1.06; for 50 × 10(9)-100 × 10(9)/L, 3.59; and exceeding 100 × 10(9)/L, infinity. Synovial lactate may be useful to rule in or rule out the diagnosis of septic arthritis with a +LR ranging from 2.4 to infinity, and negative likelihood ratio (-LR) ranging from 0 to 0.46. Rapid polymerase chain reaction (PCR) of synovial fluid may identify the causative organism within 3 hours. Based on 56% sensitivity and 90% specificity for sWBC counts of >50 × 10(9)/L in conjunction with best-evidence estimates for diagnosis-related risk and treatment-related risk/benefit, the arthrocentesis test threshold is 5%, with a treatment threshold of 39%. Recent joint surgery or cellulitis overlying a prosthetic hip or knee were the only findings on history or physical examination that significantly alter the probability of nongonococcal septic arthritis. Extreme values of sWBC (>50 × 10(9)/L) can increase, but not decrease, the probability of septic arthritis. Future ED-based diagnostic trials are needed to evaluate the role of clinical gestalt and the efficacy of nontraditional synovial markers such as lactate. © 2011 by the Society for Academic Emergency Medicine.

[Conditional probability analysis between tinnitus and comorbidities in patients attending the National Rehabilitation Institute-LGII in the period 2012-2013].

PubMed

Gómez Toledo, Verónica; Gutiérrez Farfán, Ileana; Verduzco-Mendoza, Antonio; Arch-Tirado, Emilio

Tinnitus is defined as the conscious perception of a sensation of sound that occurs in the absence of an external stimulus. This audiological symptom affects 7% to 19% of the adult population. The aim of this study is to describe the associated comorbidities present in patients with tinnitus usingjoint and conditional probability analysis. Patients of both genders, diagnosed with unilateral or bilateral tinnitus, aged between 20 and 45 years, and had a full computerised medical record, were selected. Study groups were formed on the basis of the following clinical aspects: 1) audiological findings; 2) vestibular findings; 3) comorbidities such as, temporomandibular dysfunction, tubal dysfunction, otosclerosis and, 4) triggering factors of tinnitus noise exposure, respiratory tract infection, use of ototoxic and/or drugs. Of the patients with tinnitus, 27 (65%) reported hearing loss, 11 (26.19%) temporomandibular dysfunction, and 11 (26.19%) with vestibular disorders. When performing the joint probability analysis, it was found that the probability that a patient with tinnitus having hearing loss was 2742 0.65, and 2042 0.47 for bilateral type. The result for P (A ∩ B)=30%. Bayes' theorem P (AiB) = P(Ai∩B)P(B) was used, and various probabilities were calculated. Therefore, in patients with temporomandibulardysfunction and vestibular disorders, a posterior probability of P (Aі/B)=31.44% was calculated. Consideration should be given to the joint and conditional probability approach as tools for the study of different pathologies. Copyright © 2016 Academia Mexicana de Cirugía A.C. Publicado por Masson Doyma México S.A. All rights reserved.

Optimal Joint Remote State Preparation of Arbitrary Equatorial Multi-qudit States

NASA Astrophysics Data System (ADS)

Cai, Tao; Jiang, Min

2017-03-01

As an important communication technology, quantum information transmission plays an important role in the future network communication. It involves two kinds of transmission ways: quantum teleportation and remote state preparation. In this paper, we put forward a new scheme for optimal joint remote state preparation (JRSP) of an arbitrary equatorial two-qudit state with hybrid dimensions. Moreover, the receiver can reconstruct the target state with 100 % success probability in a deterministic manner via two spatially separated senders. Based on it, we can extend it to joint remote preparation of arbitrary equatorial multi-qudit states with hybrid dimensions using the same strategy.

Implicit Learning of Predictive Relationships in Three-element Visual Sequences by Young and Old Adults

PubMed Central

Howard, James H.; Howard, Darlene V.; Dennis, Nancy A.; Kelly, Andrew J.

2008-01-01

Knowledge of sequential relationships enables future events to be anticipated and processed efficiently. Research with the serial reaction time task (SRTT) has shown that sequence learning often occurs implicitly without effort or awareness. Here we report four experiments that use a triplet-learning task (TLT) to investigate sequence learning in young and older adults. In the TLT people respond only to the last target event in a series of discrete, three-event sequences or triplets. Target predictability is manipulated by varying the triplet frequency (joint probability) and/or the statistical relationships (conditional probabilities) among events within the triplets. Results revealed that both groups learned, though older adults showed less learning of both joint and conditional probabilities. Young people used the statistical information in both cues, but older adults relied primarily on information in the second cue alone. We conclude that the TLT complements and extends the SRTT and other tasks by offering flexibility in the kinds of sequential statistical regularities that may be studied as well as by controlling event timing and eliminating motor response sequencing. PMID:18763897

Applications of the Galton Watson process to human DNA evolution and demography

NASA Astrophysics Data System (ADS)

Neves, Armando G. M.; Moreira, Carlos H. C.

2006-08-01

We show that the problem of existence of a mitochondrial Eve can be understood as an application of the Galton-Watson process and presents interesting analogies with critical phenomena in Statistical Mechanics. In the approximation of small survival probability, and assuming limited progeny, we are able to find for a genealogic tree the maximum and minimum survival probabilities over all probability distributions for the number of children per woman constrained to a given mean. As a consequence, we can relate existence of a mitochondrial Eve to quantitative demographic data of early mankind. In particular, we show that a mitochondrial Eve may exist even in an exponentially growing population, provided that the mean number of children per woman Nbar is constrained to a small range depending on the probability p that a child is a female. Assuming that the value p≈0.488 valid nowadays has remained fixed for thousands of generations, the range where a mitochondrial Eve occurs with sizeable probability is 2.0492

Coupled Monte Carlo Probability Density Function/ SPRAY/CFD Code Developed for Modeling Gas-Turbine Combustor Flows

NASA Technical Reports Server (NTRS)

1995-01-01

The success of any solution methodology for studying gas-turbine combustor flows depends a great deal on how well it can model various complex, rate-controlling processes associated with turbulent transport, mixing, chemical kinetics, evaporation and spreading rates of the spray, convective and radiative heat transfer, and other phenomena. These phenomena often strongly interact with each other at disparate time and length scales. In particular, turbulence plays an important role in determining the rates of mass and heat transfer, chemical reactions, and evaporation in many practical combustion devices. Turbulence manifests its influence in a diffusion flame in several forms depending on how turbulence interacts with various flame scales. These forms range from the so-called wrinkled, or stretched, flamelets regime, to the distributed combustion regime. Conventional turbulence closure models have difficulty in treating highly nonlinear reaction rates. A solution procedure based on the joint composition probability density function (PDF) approach holds the promise of modeling various important combustion phenomena relevant to practical combustion devices such as extinction, blowoff limits, and emissions predictions because it can handle the nonlinear chemical reaction rates without any approximation. In this approach, mean and turbulence gas-phase velocity fields are determined from a standard turbulence model; the joint composition field of species and enthalpy are determined from the solution of a modeled PDF transport equation; and a Lagrangian-based dilute spray model is used for the liquid-phase representation with appropriate consideration of the exchanges of mass, momentum, and energy between the two phases. The PDF transport equation is solved by a Monte Carlo method, and existing state-of-the-art numerical representations are used to solve the mean gasphase velocity and turbulence fields together with the liquid-phase equations. The joint composition PDF approach was extended in our previous work to the study of compressible reacting flows. The application of this method to several supersonic diffusion flames associated with scramjet combustor flow fields provided favorable comparisons with the available experimental data. A further extension of this approach to spray flames, three-dimensional computations, and parallel computing was reported in a recent paper. The recently developed PDF/SPRAY/computational fluid dynamics (CFD) module combines the novelty of the joint composition PDF approach with the ability to run on parallel architectures. This algorithm was implemented on the NASA Lewis Research Center's Cray T3D, a massively parallel computer with an aggregate of 64 processor elements. The calculation procedure was applied to predict the flow properties of both open and confined swirl-stabilized spray flames.

Morphine Injection

MedlinePlus

... back or joint pain; widening of the pupils; irritability; anxiety; weakness; stomach cramps; difficulty falling asleep or staying asleep; nausea; loss of appetite; vomiting; diarrhea; fast breathing; or fast heartbeat. Your doctor will probably decrease your dose gradually.

Meperidine Injection

MedlinePlus

... back or joint pain; widening of the pupils; irritability; anxiety; weakness; stomach cramps; difficulty falling asleep or staying asleep; nausea; loss of appetite; vomiting; diarrhea; fast breathing; or fast heartbeat. Your doctor will probably decrease your dose gradually.

Glossary of Foot and Ankle Terms

MedlinePlus

... or she will probably outgrow the condition naturally. Inversion - Twisting in toward the midline of the body. ... with the leg; the subtalar joint, which allows inversion and eversion of the foot with the leg; ...

Optimal Information Processing in Biochemical Networks

NASA Astrophysics Data System (ADS)

Wiggins, Chris

2012-02-01

A variety of experimental results over the past decades provide examples of near-optimal information processing in biological networks, including in biochemical and transcriptional regulatory networks. Computing information-theoretic quantities requires first choosing or computing the joint probability distribution describing multiple nodes in such a network --- for example, representing the probability distribution of finding an integer copy number of each of two interacting reactants or gene products while respecting the `intrinsic' small copy number noise constraining information transmission at the scale of the cell. I'll given an overview of some recent analytic and numerical work facilitating calculation of such joint distributions and the associated information, which in turn makes possible numerical optimization of information flow in models of noisy regulatory and biochemical networks. Illustrating cases include quantification of form-function relations, ideal design of regulatory cascades, and response to oscillatory driving.

A joint probability approach for coincidental flood frequency analysis at ungauged basin confluences

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Cheng

2016-03-12

A reliable and accurate flood frequency analysis at the confluence of streams is of importance. Given that long-term peak flow observations are often unavailable at tributary confluences, at a practical level, this paper presents a joint probability approach (JPA) to address the coincidental flood frequency analysis at the ungauged confluence of two streams based on the flow rate data from the upstream tributaries. One case study is performed for comparison against several traditional approaches, including the position-plotting formula, the univariate flood frequency analysis, and the National Flood Frequency Program developed by US Geological Survey. It shows that the results generatedmore » by the JPA approach agree well with the floods estimated by the plotting position and univariate flood frequency analysis based on the observation data.« less

Lower extremity control during turns initiated with and without hip external rotation.

PubMed

Zaferiou, Antonia M; Flashner, Henryk; Wilcox, Rand R; McNitt-Gray, Jill L

2017-02-08

The pirouette turn is often initiated in neutral and externally rotated hip positions by dancers. This provides an opportunity to investigate how dancers satisfy the same mechanical objectives at the whole-body level when using different leg kinematics. The purpose of this study was to compare lower extremity control strategies during the turn initiation phase of pirouettes performed with and without hip external rotation. Skilled dancers (n=5) performed pirouette turns with and without hip external rotation. Joint kinetics during turn initiation were determined for both legs using ground reaction forces (GRFs) and segment kinematics. Hip muscle activations were monitored using electromyography. Using probability-based statistical methods, variables were compared across turn conditions as a group and within-dancer. Despite differences in GRFs and impulse generation between turn conditions, at least 90% of each GRF was aligned with the respective leg plane. A majority of the net joint moments at the ankle, knee, and hip acted about an axis perpendicular to the leg plane. However, differences in shank alignment relative to the leg plane affected the distribution of the knee net joint moment when represented with respect to the shank versus the thigh. During the initiation of both turns, most participants used ankle plantar flexor moments, knee extensor moments, flexor and abductor moments at the push leg׳s hip, and extensor and abductor moments at the turn leg׳s hip. Representation of joint kinetics using multiple reference systems assisted in understanding control priorities. Copyright © 2017 Elsevier Ltd. All rights reserved.

Impact of multiple joint impairments on the energetics and mechanics of walking in patients with haemophilia.

PubMed

Lobet, S; Detrembleur, C; Hermans, C

2013-03-01

Few studies have assessed the changes produced by multiple joint impairments (MJI) of the lower limbs on gait in patients with haemophilia (PWH). In patients with MJI, quantifiable outcome measures are necessary if treatment benefits are to be compared. This study was aimed at observing the metabolic cost, mechanical work and efficiency of walking among PWH with MJI and to investigate the relationship between joint damage and any changes in mechanical and energetic variables. This study used three-dimensional gait analysis to investigate the kinematics, cost, mechanical work and efficiency of walking in 31 PWH with MJI, with the results being compared with speed-matched values from a database of healthy subjects. Regarding energetics, the mass-specific net cost of transport (C(net)) was significantly higher for PWH with MJI compared with control and directly related to a loss in dynamic joint range of motion. Surprisingly, however, there was no substantial increase in mechanical work, with PWH being able to adopt a walking strategy to improve energy recovery via the pendulum mechanism. This probable compensatory mechanism to economize energy likely counterbalances the supplementary work associated with an increased vertical excursion of centre of mass (CoM) and lower muscle efficiency of locomotion. Metabolic variables were probably the most representative variables of gait disability for these subjects with complex orthopaedic degenerative disorders. © 2012 Blackwell Publishing Ltd.

A multi-scalar PDF approach for LES of turbulent spray combustion

NASA Astrophysics Data System (ADS)

Raman, Venkat; Heye, Colin

2011-11-01

A comprehensive joint-scalar probability density function (PDF) approach is proposed for large eddy simulation (LES) of turbulent spray combustion and tests are conducted to analyze the validity and modeling requirements. The PDF method has the advantage that the chemical source term appears closed but requires models for the small scale mixing process. A stable and consistent numerical algorithm for the LES/PDF approach is presented. To understand the modeling issues in the PDF method, direct numerical simulation of a spray flame at three different fuel droplet Stokes numbers and an equivalent gaseous flame are carried out. Assumptions in closing the subfilter conditional diffusion term in the filtered PDF transport equation are evaluated for various model forms. In addition, the validity of evaporation rate models in high Stokes number flows is analyzed.

A probabilistic multi-criteria decision making technique for conceptual and preliminary aerospace systems design

NASA Astrophysics Data System (ADS)

Bandte, Oliver

It has always been the intention of systems engineering to invent or produce the best product possible. Many design techniques have been introduced over the course of decades that try to fulfill this intention. Unfortunately, no technique has succeeded in combining multi-criteria decision making with probabilistic design. The design technique developed in this thesis, the Joint Probabilistic Decision Making (JPDM) technique, successfully overcomes this deficiency by generating a multivariate probability distribution that serves in conjunction with a criterion value range of interest as a universally applicable objective function for multi-criteria optimization and product selection. This new objective function constitutes a meaningful Xnetric, called Probability of Success (POS), that allows the customer or designer to make a decision based on the chance of satisfying the customer's goals. In order to incorporate a joint probabilistic formulation into the systems design process, two algorithms are created that allow for an easy implementation into a numerical design framework: the (multivariate) Empirical Distribution Function and the Joint Probability Model. The Empirical Distribution Function estimates the probability that an event occurred by counting how many times it occurred in a given sample. The Joint Probability Model on the other hand is an analytical parametric model for the multivariate joint probability. It is comprised of the product of the univariate criterion distributions, generated by the traditional probabilistic design process, multiplied with a correlation function that is based on available correlation information between pairs of random variables. JPDM is an excellent tool for multi-objective optimization and product selection, because of its ability to transform disparate objectives into a single figure of merit, the likelihood of successfully meeting all goals or POS. The advantage of JPDM over other multi-criteria decision making techniques is that POS constitutes a single optimizable function or metric that enables a comparison of all alternative solutions on an equal basis. Hence, POS allows for the use of any standard single-objective optimization technique available and simplifies a complex multi-criteria selection problem into a simple ordering problem, where the solution with the highest POS is best. By distinguishing between controllable and uncontrollable variables in the design process, JPDM can account for the uncertain values of the uncontrollable variables that are inherent to the design problem, while facilitating an easy adjustment of the controllable ones to achieve the highest possible POS. Finally, JPDM's superiority over current multi-criteria decision making techniques is demonstrated with an optimization of a supersonic transport concept and ten contrived equations as well as a product selection example, determining an airline's best choice among Boeing's B-747, B-777, Airbus' A340, and a Supersonic Transport. The optimization examples demonstrate JPDM's ability to produce a better solution with a higher POS than an Overall Evaluation Criterion or Goal Programming approach. Similarly, the product selection example demonstrates JPDM's ability to produce a better solution with a higher POS and different ranking than the Overall Evaluation Criterion or Technique for Order Preferences by Similarity to the Ideal Solution (TOPSIS) approach.

Craniovertebral junction realignment for the treatment of basilar invagination with syringomyelia: preliminary report of 12 cases.

PubMed

Goel, Atul; Sharma, Praveen

2005-10-01

Twelve selected patients, eight males and four females aged 14 to 50 years, with syringomyelia associated with congenital craniovertebral bony anomalies including basilar invagination and fixed atlantoaxial dislocation, and associated Chiari I malformation in eight, were treated by atlantoaxial joint manipulation and restoration of the craniovertebral region alignment between October 2002 and March 2004. Three patients had a history of trauma prior to the onset of symptoms. Spastic quadriparesis and ataxia were the most prominent symptoms. The mean duration of symptoms was 11 months. The atlantoaxial dislocation and basilar invagination were reduced by manual distraction of the facets of the atlas and axis, stabilization by placement of bone graft and metal spacers within the joint, and direct atlantoaxial fixation using an inter-articular plate and screw method technique. Following surgery all patients showed symptomatic improvement and restoration of craniovertebral alignment during follow up from 3 to 20 months (mean 7 months). Radiological improvement of the syrinx could not be evaluated as stainless steel metal plates, screws, and spacers were used for fixation. Manipulation of the atlantoaxial joints and restoring the anatomical craniovertebral alignments in selected cases of syringomyelia leads to remarkable and sustained clinical recovery, and is probably the optimum surgical treatment.

Probability density function evolution of power systems subject to stochastic variation of renewable energy

NASA Astrophysics Data System (ADS)

Wei, J. Q.; Cong, Y. C.; Xiao, M. Q.

2018-05-01

As renewable energies are increasingly integrated into power systems, there is increasing interest in stochastic analysis of power systems.Better techniques should be developed to account for the uncertainty caused by penetration of renewables and consequently analyse its impacts on stochastic stability of power systems. In this paper, the Stochastic Differential Equations (SDEs) are used to represent the evolutionary behaviour of the power systems. The stationary Probability Density Function (PDF) solution to SDEs modelling power systems excited by Gaussian white noise is analysed. Subjected to such random excitation, the Joint Probability Density Function (JPDF) solution to the phase angle and angular velocity is governed by the generalized Fokker-Planck-Kolmogorov (FPK) equation. To solve this equation, the numerical method is adopted. Special measure is taken such that the generalized FPK equation is satisfied in the average sense of integration with the assumed PDF. Both weak and strong intensities of the stochastic excitations are considered in a single machine infinite bus power system. The numerical analysis has the same result as the one given by the Monte Carlo simulation. Potential studies on stochastic behaviour of multi-machine power systems with random excitations are discussed at the end.

Spatial capture-recapture models for jointly estimating population density and landscape connectivity

USGS Publications Warehouse

Royle, J. Andrew; Chandler, Richard B.; Gazenski, Kimberly D.; Graves, Tabitha A.

2013-01-01

Population size and landscape connectivity are key determinants of population viability, yet no methods exist for simultaneously estimating density and connectivity parameters. Recently developed spatial capture–recapture (SCR) models provide a framework for estimating density of animal populations but thus far have not been used to study connectivity. Rather, all applications of SCR models have used encounter probability models based on the Euclidean distance between traps and animal activity centers, which implies that home ranges are stationary, symmetric, and unaffected by landscape structure. In this paper we devise encounter probability models based on “ecological distance,” i.e., the least-cost path between traps and activity centers, which is a function of both Euclidean distance and animal movement behavior in resistant landscapes. We integrate least-cost path models into a likelihood-based estimation scheme for spatial capture–recapture models in order to estimate population density and parameters of the least-cost encounter probability model. Therefore, it is possible to make explicit inferences about animal density, distribution, and landscape connectivity as it relates to animal movement from standard capture–recapture data. Furthermore, a simulation study demonstrated that ignoring landscape connectivity can result in negatively biased density estimators under the naive SCR model.

Spatial capture--recapture models for jointly estimating population density and landscape connectivity.

PubMed

Royle, J Andrew; Chandler, Richard B; Gazenski, Kimberly D; Graves, Tabitha A

2013-02-01

Population size and landscape connectivity are key determinants of population viability, yet no methods exist for simultaneously estimating density and connectivity parameters. Recently developed spatial capture--recapture (SCR) models provide a framework for estimating density of animal populations but thus far have not been used to study connectivity. Rather, all applications of SCR models have used encounter probability models based on the Euclidean distance between traps and animal activity centers, which implies that home ranges are stationary, symmetric, and unaffected by landscape structure. In this paper we devise encounter probability models based on "ecological distance," i.e., the least-cost path between traps and activity centers, which is a function of both Euclidean distance and animal movement behavior in resistant landscapes. We integrate least-cost path models into a likelihood-based estimation scheme for spatial capture-recapture models in order to estimate population density and parameters of the least-cost encounter probability model. Therefore, it is possible to make explicit inferences about animal density, distribution, and landscape connectivity as it relates to animal movement from standard capture-recapture data. Furthermore, a simulation study demonstrated that ignoring landscape connectivity can result in negatively biased density estimators under the naive SCR model.

Robot Position Sensor Fault Tolerance

NASA Technical Reports Server (NTRS)

Aldridge, Hal A.

1997-01-01

Robot systems in critical applications, such as those in space and nuclear environments, must be able to operate during component failure to complete important tasks. One failure mode that has received little attention is the failure of joint position sensors. Current fault tolerant designs require the addition of directly redundant position sensors which can affect joint design. A new method is proposed that utilizes analytical redundancy to allow for continued operation during joint position sensor failure. Joint torque sensors are used with a virtual passive torque controller to make the robot joint stable without position feedback and improve position tracking performance in the presence of unknown link dynamics and end-effector loading. Two Cartesian accelerometer based methods are proposed to determine the position of the joint. The joint specific position determination method utilizes two triaxial accelerometers attached to the link driven by the joint with the failed position sensor. The joint specific method is not computationally complex and the position error is bounded. The system wide position determination method utilizes accelerometers distributed on different robot links and the end-effector to determine the position of sets of multiple joints. The system wide method requires fewer accelerometers than the joint specific method to make all joint position sensors fault tolerant but is more computationally complex and has lower convergence properties. Experiments were conducted on a laboratory manipulator. Both position determination methods were shown to track the actual position satisfactorily. A controller using the position determination methods and the virtual passive torque controller was able to servo the joints to a desired position during position sensor failure.

Non-Kolmogorovian Approach to the Context-Dependent Systems Breaking the Classical Probability Law

NASA Astrophysics Data System (ADS)

Asano, Masanari; Basieva, Irina; Khrennikov, Andrei; Ohya, Masanori; Yamato, Ichiro

2013-07-01

There exist several phenomena breaking the classical probability laws. The systems related to such phenomena are context-dependent, so that they are adaptive to other systems. In this paper, we present a new mathematical formalism to compute the joint probability distribution for two event-systems by using concepts of the adaptive dynamics and quantum information theory, e.g., quantum channels and liftings. In physics the basic example of the context-dependent phenomena is the famous double-slit experiment. Recently similar examples have been found in biological and psychological sciences. Our approach is an extension of traditional quantum probability theory, and it is general enough to describe aforementioned contextual phenomena outside of quantum physics.

Mapping Irrigated Areas in the Tunisian Semi-Arid Context with Landsat Thermal and VNIR Data Imagery

NASA Astrophysics Data System (ADS)

Rivalland, Vincent; Drissi, Hsan; Simonneaux, Vincent; Tardy, Benjamin; Boulet, Gilles

2016-04-01

Our study area is the Merguellil semi-arid irrigated plain in Tunisia, where the water resource management is an important stake for governmental institutions, farmer communities and more generally for the environment. Indeed, groundwater abstraction for irrigation is the primary cause of aquifer depletion. Moreover, unregistered pumping practices are widespread and very difficult to survey by authorities. Thus, the identification of areas actually irrigated in the whole plain is of major interest. In order to map the irrigated areas, we tried out a methodology based on the use of Landsat 7 and 8 Land Surface Temperature (LST) data issued from atmospherically corrected thermal band using the LANDARTs Tool jointly with the NDVI vegetation indices obtained from visible ane near infrared (VNIR) bands. For each Landsat acquisition during the years 2012 to 2014, we computed a probability of irrigation based on the location of the pixel in the NDVI - LST space. Basically for a given NDVI value, the cooler the pixel the higher its probability to be irrigated is. For each date, pixels were classified in seven bins of irrigation probability ranges. Pixel probabilities for each date were then summed over the study period resulting in a probability map of irrigation. Comparison with ground data shows a consistent identification of irrigated plots and supports the potential operational interest of the method. However, results were hampered by the low Landsat LST data availability due to clouds and the inadequate revisit frequency of the sensor.

Virtual Passive Controller for Robot Systems Using Joint Torque Sensors

NASA Technical Reports Server (NTRS)

Aldridge, Hal A.; Juang, Jer-Nan

1997-01-01

This paper presents a control method based on virtual passive dynamic control that will stabilize a robot manipulator using joint torque sensors and a simple joint model. The method does not require joint position or velocity feedback for stabilization. The proposed control method is stable in the sense of Lyaponov. The control method was implemented on several joints of a laboratory robot. The controller showed good stability robustness to system parameter error and to the exclusion of nonlinear dynamic effects on the joints. The controller enhanced position tracking performance and, in the absence of position control, dissipated joint energy.

Performance analysis of simultaneous dense coding protocol under decoherence

NASA Astrophysics Data System (ADS)

Huang, Zhiming; Zhang, Cai; Situ, Haozhen

2017-09-01

The simultaneous dense coding (SDC) protocol is useful in designing quantum protocols. We analyze the performance of the SDC protocol under the influence of noisy quantum channels. Six kinds of paradigmatic Markovian noise along with one kind of non-Markovian noise are considered. The joint success probability of both receivers and the success probabilities of one receiver are calculated for three different locking operators. Some interesting properties have been found, such as invariance and symmetry. Among the three locking operators we consider, the SWAP gate is most resistant to noise and results in the same success probabilities for both receivers.

Bivariate at-site frequency analysis of simulated flood peak-volume data using copulas

NASA Astrophysics Data System (ADS)

Gaál, Ladislav; Viglione, Alberto; Szolgay, Ján.; Blöschl, Günter; Bacigál, Tomáå.¡

2010-05-01

In frequency analysis of joint hydro-climatological extremes (flood peaks and volumes, low flows and durations, etc.), usually, bivariate distribution functions are fitted to the observed data in order to estimate the probability of their occurrence. Bivariate models, however, have a number of limitations; therefore, in the recent past, dependence models based on copulas have gained increased attention to represent the joint probabilities of hydrological characteristics. Regardless of whether standard or copula based bivariate frequency analysis is carried out, one is generally interested in the extremes corresponding to low probabilities of the fitted joint cumulative distribution functions (CDFs). However, usually there is not enough flood data in the right tail of the empirical CDFs to derive reliable statistical inferences on the behaviour of the extremes. Therefore, different techniques are used to extend the amount of information for the statistical inference, i.e., temporal extension methods that allow for making use of historical data or spatial extension methods such as regional approaches. In this study, a different approach was adopted which uses simulated flood data by rainfall-runoff modelling, to increase the amount of data in the right tail of the CDFs. In order to generate artificial runoff data (i.e. to simulate flood records of lengths of approximately 106 years), a two-step procedure was used. (i) First, the stochastic rainfall generator proposed by Sivapalan et al. (2005) was modified for our purpose. This model is based on the assumption of discrete rainfall events whose arrival times, durations, mean rainfall intensity and the within-storm intensity patterns are all random, and can be described by specified distributions. The mean storm rainfall intensity is disaggregated further to hourly intensity patterns. (ii) Secondly, the simulated rainfall data entered a semi-distributed conceptual rainfall-runoff model that consisted of a snow routine, a soil moisture routine and a flow routing routine (Parajka et al., 2007). The applicability of the proposed method was demonstrated on selected sites in Slovakia and Austria. The pairs of simulated flood volumes and flood peaks were analysed in terms of their dependence structure and different families of copulas (Archimedean, extreme value, Gumbel-Hougaard, etc.) were fitted to the observed and simulated data. The question to what extent measured data can be used to find the right copula was discussed. The study is supported by the Austrian Academy of Sciences and the Austrian-Slovak Co-operation in Science and Education "Aktion". Parajka, J., Merz, R., Blöschl, G., 2007: Uncertainty and multiple objective calibration in regional water balance modeling - Case study in 320 Austrian catchments. Hydrological Processes, 21, 435-446. Sivapalan, M., Blöschl, G., Merz, R., Gutknecht, D., 2005: Linking flood frequency to long-term water balance: incorporating effects of seasonality. Water Resources Research, 41, W06012, doi:10.1029/2004WR003439.

Statistics of Optical Coherence Tomography Data From Human Retina

PubMed Central

de Juan, Joaquín; Ferrone, Claudia; Giannini, Daniela; Huang, David; Koch, Giorgio; Russo, Valentina; Tan, Ou; Bruni, Carlo

2010-01-01

Optical coherence tomography (OCT) has recently become one of the primary methods for noninvasive probing of the human retina. The pseudoimage formed by OCT (the so-called B-scan) varies probabilistically across pixels due to complexities in the measurement technique. Hence, sensitive automatic procedures of diagnosis using OCT may exploit statistical analysis of the spatial distribution of reflectance. In this paper, we perform a statistical study of retinal OCT data. We find that the stretched exponential probability density function can model well the distribution of intensities in OCT pseudoimages. Moreover, we show a small, but significant correlation between neighbor pixels when measuring OCT intensities with pixels of about 5 µm. We then develop a simple joint probability model for the OCT data consistent with known retinal features. This model fits well the stretched exponential distribution of intensities and their spatial correlation. In normal retinas, fit parameters of this model are relatively constant along retinal layers, but varies across layers. However, in retinas with diabetic retinopathy, large spikes of parameter modulation interrupt the constancy within layers, exactly where pathologies are visible. We argue that these results give hope for improvement in statistical pathology-detection methods even when the disease is in its early stages. PMID:20304733

Analysis of Bonded Joints Between the Facesheet and Flange of Corrugated Composite Panels

NASA Technical Reports Server (NTRS)

Yarrington, Phillip W.; Collier, Craig S.; Bednarcyk, Brett A.

2008-01-01

This paper outlines a method for the stress analysis of bonded composite corrugated panel facesheet to flange joints. The method relies on the existing HyperSizer Joints software, which analyzes the bonded joint, along with a beam analogy model that provides the necessary boundary loading conditions to the joint analysis. The method is capable of predicting the full multiaxial stress and strain fields within the flange to facesheet joint and thus can determine ply-level margins and evaluate delamination. Results comparing the method to NASTRAN finite element model stress fields are provided illustrating the accuracy of the method.

Developing a Methodology for Eliciting Subjective Probability Estimates During Expert Evaluations of Safety Interventions: Application for Bayesian Belief Networks

NASA Technical Reports Server (NTRS)

Wiegmann, Douglas A.a

2005-01-01

The NASA Aviation Safety Program (AvSP) has defined several products that will potentially modify airline and/or ATC operations, enhance aircraft systems, and improve the identification of potential hazardous situations within the National Airspace System (NAS). Consequently, there is a need to develop methods for evaluating the potential safety benefit of each of these intervention products so that resources can be effectively invested to produce the judgments to develop Bayesian Belief Networks (BBN's) that model the potential impact that specific interventions may have. Specifically, the present report summarizes methodologies for improving the elicitation of probability estimates during expert evaluations of AvSP products for use in BBN's. The work involved joint efforts between Professor James Luxhoj from Rutgers University and researchers at the University of Illinois. The Rutgers' project to develop BBN's received funding by NASA entitled "Probabilistic Decision Support for Evaluating Technology Insertion and Assessing Aviation Safety System Risk." The proposed project was funded separately but supported the existing Rutgers' program.

Multi-state models for colon cancer recurrence and death with a cured fraction.

PubMed

Conlon, A S C; Taylor, J M G; Sargent, D J

2014-05-10

In cancer clinical trials, patients often experience a recurrence of disease prior to the outcome of interest, overall survival. Additionally, for many cancers, there is a cured fraction of the population who will never experience a recurrence. There is often interest in how different covariates affect the probability of being cured of disease and the time to recurrence, time to death, and time to death after recurrence. We propose a multi-state Markov model with an incorporated cured fraction to jointly model recurrence and death in colon cancer. A Bayesian estimation strategy is used to obtain parameter estimates. The model can be used to assess how individual covariates affect the probability of being cured and each of the transition rates. Checks for the adequacy of the model fit and for the functional forms of covariates are explored. The methods are applied to data from 12 randomized trials in colon cancer, where we show common effects of specific covariates across the trials. Copyright © 2013 John Wiley & Sons, Ltd.

Parkinson Disease Detection from Speech Articulation Neuromechanics.

PubMed

Gómez-Vilda, Pedro; Mekyska, Jiri; Ferrández, José M; Palacios-Alonso, Daniel; Gómez-Rodellar, Andrés; Rodellar-Biarge, Victoria; Galaz, Zoltan; Smekal, Zdenek; Eliasova, Ilona; Kostalova, Milena; Rektorova, Irena

2017-01-01

Aim: The research described is intended to give a description of articulation dynamics as a correlate of the kinematic behavior of the jaw-tongue biomechanical system, encoded as a probability distribution of an absolute joint velocity. This distribution may be used in detecting and grading speech from patients affected by neurodegenerative illnesses, as Parkinson Disease. Hypothesis: The work hypothesis is that the probability density function of the absolute joint velocity includes information on the stability of phonation when applied to sustained vowels, as well as on fluency if applied to connected speech. Methods: A dataset of sustained vowels recorded from Parkinson Disease patients is contrasted with similar recordings from normative subjects. The probability distribution of the absolute kinematic velocity of the jaw-tongue system is extracted from each utterance. A Random Least Squares Feed-Forward Network (RLSFN) has been used as a binary classifier working on the pathological and normative datasets in a leave-one-out strategy. Monte Carlo simulations have been conducted to estimate the influence of the stochastic nature of the classifier. Two datasets for each gender were tested (males and females) including 26 normative and 53 pathological subjects in the male set, and 25 normative and 38 pathological in the female set. Results: Male and female data subsets were tested in single runs, yielding equal error rates under 0.6% (Accuracy over 99.4%). Due to the stochastic nature of each experiment, Monte Carlo runs were conducted to test the reliability of the methodology. The average detection results after 200 Montecarlo runs of a 200 hyperplane hidden layer RLSFN are given in terms of Sensitivity (males: 0.9946, females: 0.9942), Specificity (males: 0.9944, females: 0.9941) and Accuracy (males: 0.9945, females: 0.9942). The area under the ROC curve is 0.9947 (males) and 0.9945 (females). The equal error rate is 0.0054 (males) and 0.0057 (females). Conclusions: The proposed methodology avails that the use of highly normalized descriptors as the probability distribution of kinematic variables of vowel articulation stability, which has some interesting properties in terms of information theory, boosts the potential of simple yet powerful classifiers in producing quite acceptable detection results in Parkinson Disease.

Integrating Quantitative and Qualitative Results in Health Science Mixed Methods Research Through Joint Displays

PubMed Central

Guetterman, Timothy C.; Fetters, Michael D.; Creswell, John W.

2015-01-01

PURPOSE Mixed methods research is becoming an important methodology to investigate complex health-related topics, yet the meaningful integration of qualitative and quantitative data remains elusive and needs further development. A promising innovation to facilitate integration is the use of visual joint displays that bring data together visually to draw out new insights. The purpose of this study was to identify exemplar joint displays by analyzing the various types of joint displays being used in published articles. METHODS We searched for empirical articles that included joint displays in 3 journals that publish state-of-the-art mixed methods research. We analyzed each of 19 identified joint displays to extract the type of display, mixed methods design, purpose, rationale, qualitative and quantitative data sources, integration approaches, and analytic strategies. Our analysis focused on what each display communicated and its representation of mixed methods analysis. RESULTS The most prevalent types of joint displays were statistics-by-themes and side-by-side comparisons. Innovative joint displays connected findings to theoretical frameworks or recommendations. Researchers used joint displays for convergent, explanatory sequential, exploratory sequential, and intervention designs. We identified exemplars for each of these designs by analyzing the inferences gained through using the joint display. Exemplars represented mixed methods integration, presented integrated results, and yielded new insights. CONCLUSIONS Joint displays appear to provide a structure to discuss the integrated analysis and assist both researchers and readers in understanding how mixed methods provides new insights. We encourage researchers to use joint displays to integrate and represent mixed methods analysis and discuss their value. PMID:26553895

Techniques of Force and Pressure Measurement in the Small Joints of the Wrist.

PubMed

Schreck, Michael J; Kelly, Meghan; Canham, Colin D; Elfar, John C

2018-01-01

The alteration of forces across joints can result in instability and subsequent disability. Previous methods of force measurements such as pressure-sensitive films, load cells, and pressure-sensing transducers have been utilized to estimate biomechanical forces across joints and more recent studies have utilized a nondestructive method that allows for assessment of joint forces under ligamentous restraints. A comprehensive review of the literature was performed to explore the numerous biomechanical methods utilized to estimate intra-articular forces. Methods of biomechanical force measurements in joints are reviewed. Methods such as pressure-sensitive films, load cells, and pressure-sensing transducers require significant intra-articular disruption and thus may result in inaccurate measurements, especially in small joints such as those within the wrist and hand. Non-destructive methods of joint force measurements either utilizing distraction-based joint reaction force methods or finite element analysis may offer a more accurate assessment; however, given their recent inception, further studies are needed to improve and validate their use.

Joint Clustering and Component Analysis of Correspondenceless Point Sets: Application to Cardiac Statistical Modeling.

PubMed

Gooya, Ali; Lekadir, Karim; Alba, Xenia; Swift, Andrew J; Wild, Jim M; Frangi, Alejandro F

2015-01-01

Construction of Statistical Shape Models (SSMs) from arbitrary point sets is a challenging problem due to significant shape variation and lack of explicit point correspondence across the training data set. In medical imaging, point sets can generally represent different shape classes that span healthy and pathological exemplars. In such cases, the constructed SSM may not generalize well, largely because the probability density function (pdf) of the point sets deviates from the underlying assumption of Gaussian statistics. To this end, we propose a generative model for unsupervised learning of the pdf of point sets as a mixture of distinctive classes. A Variational Bayesian (VB) method is proposed for making joint inferences on the labels of point sets, and the principal modes of variations in each cluster. The method provides a flexible framework to handle point sets with no explicit point-to-point correspondences. We also show that by maximizing the marginalized likelihood of the model, the optimal number of clusters of point sets can be determined. We illustrate this work in the context of understanding the anatomical phenotype of the left and right ventricles in heart. To this end, we use a database containing hearts of healthy subjects, patients with Pulmonary Hypertension (PH), and patients with Hypertrophic Cardiomyopathy (HCM). We demonstrate that our method can outperform traditional PCA in both generalization and specificity measures.

Blind Compensation of I/Q Impairments in Wireless Transceivers

PubMed Central

Aziz, Mohsin; Ghannouchi, Fadhel M.; Helaoui, Mohamed

2017-01-01

The majority of techniques that deal with the mitigation of in-phase and quadrature-phase (I/Q) imbalance at the transmitter (pre-compensation) require long training sequences, reducing the throughput of the system. These techniques also require a feedback path, which adds more complexity and cost to the transmitter architecture. Blind estimation techniques are attractive for avoiding the use of long training sequences. In this paper, we propose a blind frequency-independent I/Q imbalance compensation method based on the maximum likelihood (ML) estimation of the imbalance parameters of a transceiver. A closed-form joint probability density function (PDF) for the imbalanced I and Q signals is derived and validated. ML estimation is then used to estimate the imbalance parameters using the derived joint PDF of the output I and Q signals. Various figures of merit have been used to evaluate the efficacy of the proposed approach using extensive computer simulations and measurements. Additionally, the bit error rate curves show the effectiveness of the proposed method in the presence of the wireless channel and Additive White Gaussian Noise. Real-world experimental results show an image rejection of greater than 30 dB as compared to the uncompensated system. This method has also been found to be robust in the presence of practical system impairments, such as time and phase delay mismatches. PMID:29257081

Comments on {open_quotes}interpretations of quantum mechanics, joint measurement of incompatible observables, and counterfactual definiteness{close_quotes}

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stapp, H.P.

1994-12-01

Some seeming logical deficiencies in a recent paper are described. The author responds to the arguments of the work by de Muynck, De Baere, and Martens (MDM), who argue it is widely accepted today that some sort of nonlocal effect is needed to resolve the problems raised by the works of Einstein, Podolsky, and Rosen (EPR) and John Bell. In MBM a variety of arguments are set forth that aim to invalidate the existing purported proofs of nonlocality and to provide, moreover, a local solution to the problems uncovered by EPR and Bell. Much of the argumentation in MBM ismore » based on the idea of introducing `nonideal` measurements, which, according to MBM, allow one to construct joint probability distributions for incompatible observables. The existence of a bona fide joint probability distribution for the incompatible observables occurring in the EPRB experiments would entail that Bell`s inequalities can be satisfied, and hence that the mathematical basis for the nonlocal effects would disappear. This relult would apparently allow one to eliminate the need for nonlocal effects by considering experiments of this new kind.« less

Proximal interphalangeal joint ankylosis in an early medieval horse from Wrocław Cathedral Island, Poland.

PubMed

Janeczek, Maciej; Chrószcz, Aleksander; Onar, Vedat; Henklewski, Radomir; Skalec, Aleksandra

2017-06-01

Animal remains that are unearthed during archaeological excavations often provide useful information about socio-cultural context, including human habits, beliefs, and ancestral relationships. In this report, we present pathologically altered equine first and second phalanges from an 11th century specimen that was excavated at Wrocław Cathedral Island, Poland. The results of gross examination, radiography, and computed tomography, indicate osteoarthritis of the proximal interphalangeal joint, with partial ankylosis. Based on comparison with living modern horses undergoing lameness examination, as well as with recent literature, we conclude that the horse likely was lame for at least several months prior to death. The ability of this horse to work probably was reduced, but the degree of compromise during life cannot be stated precisely. Present day medical knowledge indicates that there was little likelihood of successful treatment for this condition during the middle ages. However, modern horses with similar pathology can function reasonably well with appropriate treatment and management, particularly following joint ankylosis. Thus, we approach the cultural question of why such an individual would have been maintained with limitations, for a probably-significant period of time. Copyright © 2017 Elsevier Inc. All rights reserved.

In vitro validation and reliability study of electromagnetic skin sensors for evaluation of end range of motion positions of the hip.

PubMed

Audenaert, E A; Vigneron, L; Van Hoof, T; D'Herde, K; van Maele, G; Oosterlinck, D; Pattyn, C

2011-12-01

There is growing evidence that femoroacetabular impingement (FAI) is a probable risk factor for the development of early osteoarthritis in the nondysplastic hip. As FAI arises with end range of motion activities, measurement errors related to skin movement might be higher than anticipated when using previously reported methods for kinematic evaluation of the hip. We performed an in vitro validation and reliability study of a noninvasive method to define pelvic and femur positions in end range of motion activities of the hip using an electromagnetic tracking device. Motion data, collected from sensors attached to the bone and skin of 11 cadaver hips, were simultaneously obtained and compared in a global reference frame. Motion data were then transposed in the hip joint local coordinate systems. Observer-related variability in locating the anatomical landmarks required to define the local coordinate system and variability of determining the hip joint center was evaluated. Angular root mean square (RMS) differences between the bony and skin sensors averaged 3.2° (SD 3.5°) and 1.8° (SD 2.3°) in the global reference frame for the femur and pelvic sensors, respectively. Angular RMS differences between the bony and skin sensors in the hip joint local coordinate systems ranged at end range of motion and dependent on the motion under investigation from 1.91 to 5.81°. The presented protocol for evaluation of hip motion seems to be suited for the 3-D description of motion relevant to the experimental and clinical evaluation of femoroacetabular impingement.

Lessons from a non-domestic canid: joint disease in captive raccoon dogs (Nyctereutes procyonoides).

PubMed

Lawler, Dennis F; Evans, Richard H; Nieminen, Petteri; Mustonen, Anne-Mari; Smith, Gail K

2012-01-01

The purpose of this study was to describe pathological changes of the shoulder, elbow, hip and stifle joints of 16 museum skeletons of the raccoon dog (Nyctereutes procyonoides). The subjects had been held in long-term captivity and were probably used for fur farming or research, thus allowing sufficient longevity for joint disease to become recognisable. The prevalence of disorders that include osteochondrosis, osteoarthritis and changes compatible with hip dysplasia, was surprisingly high. Other changes that reflect near-normal or mild pathological conditions, including prominent articular margins and mild bony periarticular rim, were also prevalent. Our data form a basis for comparing joint pathology of captive raccoon dogs with other mammals and also suggest that contributing roles of captivity and genetic predisposition should be explored further in non-domestic canids.

Automatic Quantification of Radiographic Wrist Joint Space Width of Patients With Rheumatoid Arthritis.

PubMed

Huo, Yinghe; Vincken, Koen L; van der Heijde, Desiree; de Hair, Maria J H; Lafeber, Floris P; Viergever, Max A

2017-11-01

Objective: Wrist joint space narrowing is a main radiographic outcome of rheumatoid arthritis (RA). Yet, automatic radiographic wrist joint space width (JSW) quantification for RA patients has not been widely investigated. The aim of this paper is to present an automatic method to quantify the JSW of three wrist joints that are least affected by bone overlapping and are frequently involved in RA. These joints are located around the scaphoid bone, viz. the multangular-navicular, capitate-navicular-lunate, and radiocarpal joints. Methods: The joint space around the scaphoid bone is detected by using consecutive searches of separate path segments, where each segment location aids in constraining the subsequent one. For joint margin delineation, first the boundary not affected by X-ray projection is extracted, followed by a backtrace process to obtain the actual joint margin. The accuracy of the quantified JSW is evaluated by comparison with the manually obtained ground truth. Results: Two of the 50 radiographs used for evaluation of the method did not yield a correct path through all three wrist joints. The delineated joint margins of the remaining 48 radiographs were used for JSW quantification. It was found that 90% of the joints had a JSW deviating less than 20% from the mean JSW of manual indications, with the mean JSW error less than 10%. Conclusion: The proposed method is able to automatically quantify the JSW of radiographic wrist joints reliably. The proposed method may aid clinical researchers to study the progression of wrist joint damage in RA studies. Objective: Wrist joint space narrowing is a main radiographic outcome of rheumatoid arthritis (RA). Yet, automatic radiographic wrist joint space width (JSW) quantification for RA patients has not been widely investigated. The aim of this paper is to present an automatic method to quantify the JSW of three wrist joints that are least affected by bone overlapping and are frequently involved in RA. These joints are located around the scaphoid bone, viz. the multangular-navicular, capitate-navicular-lunate, and radiocarpal joints. Methods: The joint space around the scaphoid bone is detected by using consecutive searches of separate path segments, where each segment location aids in constraining the subsequent one. For joint margin delineation, first the boundary not affected by X-ray projection is extracted, followed by a backtrace process to obtain the actual joint margin. The accuracy of the quantified JSW is evaluated by comparison with the manually obtained ground truth. Results: Two of the 50 radiographs used for evaluation of the method did not yield a correct path through all three wrist joints. The delineated joint margins of the remaining 48 radiographs were used for JSW quantification. It was found that 90% of the joints had a JSW deviating less than 20% from the mean JSW of manual indications, with the mean JSW error less than 10%. Conclusion: The proposed method is able to automatically quantify the JSW of radiographic wrist joints reliably. The proposed method may aid clinical researchers to study the progression of wrist joint damage in RA studies.

Joint analysis of air pollution in street canyons in St. Petersburg and Copenhagen

NASA Astrophysics Data System (ADS)

Genikhovich, E. L.; Ziv, A. D.; Iakovleva, E. A.; Palmgren, F.; Berkowicz, R.

The bi-annual data set of concentrations of several traffic-related air pollutants, measured continuously in street canyons in St. Petersburg and Copenhagen, is analysed jointly using different statistical techniques. Annual mean concentrations of NO 2, NO x and, especially, benzene are found systematically higher in St. Petersburg than in Copenhagen but for ozone the situation is opposite. In both cities probability distribution functions (PDFs) of concentrations and their daily or weekly extrema are fitted with the Weibull and double exponential distributions, respectively. Sample estimates of bi-variate distributions of concentrations, concentration roses, and probabilities of concentration of one pollutant being extreme given that another one reaches its extremum are presented in this paper as well as auto- and co-spectra. It is demonstrated that there is a reasonably high correlation between seasonally averaged concentrations of pollutants in St. Petersburg and Copenhagen.

Generalized monogamy of contextual inequalities from the no-disturbance principle.

PubMed

Ramanathan, Ravishankar; Soeda, Akihito; Kurzyński, Paweł; Kaszlikowski, Dagomir

2012-08-03

In this Letter, we demonstrate that the property of monogamy of Bell violations seen for no-signaling correlations in composite systems can be generalized to the monogamy of contextuality in single systems obeying the Gleason property of no disturbance. We show how one can construct monogamies for contextual inequalities by using the graph-theoretic technique of vertex decomposition of a graph representing a set of measurements into subgraphs of suitable independence numbers that themselves admit a joint probability distribution. After establishing that all the subgraphs that are chordal graphs admit a joint probability distribution, we formulate a precise graph-theoretic condition that gives rise to the monogamy of contextuality. We also show how such monogamies arise within quantum theory for a single four-dimensional system and interpret violation of these relations in terms of a violation of causality. These monogamies can be tested with current experimental techniques.

Integrating Quantitative and Qualitative Results in Health Science Mixed Methods Research Through Joint Displays.

PubMed

Guetterman, Timothy C; Fetters, Michael D; Creswell, John W

2015-11-01

Mixed methods research is becoming an important methodology to investigate complex health-related topics, yet the meaningful integration of qualitative and quantitative data remains elusive and needs further development. A promising innovation to facilitate integration is the use of visual joint displays that bring data together visually to draw out new insights. The purpose of this study was to identify exemplar joint displays by analyzing the various types of joint displays being used in published articles. We searched for empirical articles that included joint displays in 3 journals that publish state-of-the-art mixed methods research. We analyzed each of 19 identified joint displays to extract the type of display, mixed methods design, purpose, rationale, qualitative and quantitative data sources, integration approaches, and analytic strategies. Our analysis focused on what each display communicated and its representation of mixed methods analysis. The most prevalent types of joint displays were statistics-by-themes and side-by-side comparisons. Innovative joint displays connected findings to theoretical frameworks or recommendations. Researchers used joint displays for convergent, explanatory sequential, exploratory sequential, and intervention designs. We identified exemplars for each of these designs by analyzing the inferences gained through using the joint display. Exemplars represented mixed methods integration, presented integrated results, and yielded new insights. Joint displays appear to provide a structure to discuss the integrated analysis and assist both researchers and readers in understanding how mixed methods provides new insights. We encourage researchers to use joint displays to integrate and represent mixed methods analysis and discuss their value. © 2015 Annals of Family Medicine, Inc.

[Influence of Restricting the Ankle Joint Complex Motions on Gait Stability of Human Body].

PubMed

Li, Yang; Zhang, Junxia; Su, Hailong; Wang, Xinting; Zhang, Yan

2016-10-01

The purpose of this study is to determine how restricting inversion-eversion and pronation-supination motions of the ankle joint complex influences the stability of human gait.The experiment was carried out on a slippery level ground walkway.Spatiotemporal gait parameter,kinematics and kinetics data as well as utilized coefficient of friction(UCOF)were compared between two conditions,i.e.with restriction of the ankle joint complex inversion-eversion and pronation-supination motions(FIXED)and without restriction(FREE).The results showed that FIXED could lead to a significant increase in velocity and stride length and an obvious decrease in double support time.Furthermore,FIXED might affect the motion angle range of knee joint and ankle joint in the sagittal plane.In FIXED condition,UCOF was significantly increased,which could lead to an increase of slip probability and a decrease of gait stability.Hence,in the design of a walker,bipedal robot or prosthetic,the structure design which is used to achieve the ankle joint complex inversion-eversion and pronation-supination motions should be implemented.

NESTOR: A Computer-Based Medical Diagnostic Aid That Integrates Causal and Probabilistic Knowledge.

DTIC Science & Technology

1984-11-01

indiidual conditional probabilities between one cause node and its effect node, but less common to know a joint conditional probability between a...PERFOAMING ORG. REPORT NUMBER * 7. AUTI4ORs) O Gregory F. Cooper 1 CONTRACT OR GRANT NUMBERIa) ONR N00014-81-K-0004 g PERFORMING ORGANIZATION NAME AND...ADDRESS 10. PROGRAM ELEMENT, PROJECT. TASK Department of Computer Science AREA & WORK UNIT NUMBERS Stanford University Stanford, CA 94305 USA 12. REPORT

Biomechanical Tolerance of Calcaneal Fractures

PubMed Central

Yoganandan, Narayan; Pintar, Frank A.; Gennarelli, Thomas A.; Seipel, Robert; Marks, Richard

1999-01-01

Biomechanical studies have been conducted in the past to understand the mechanisms of injury to the foot-ankle complex. However, statistically based tolerance criteria for calcaneal complex injuries are lacking. Consequently, this research was designed to derive a probability distribution that represents human calcaneal tolerance under impact loading such as those encountered in vehicular collisions. Information for deriving the distribution was obtained by experiments on unembalmed human cadaver lower extremities. Briefly, the protocol included the following. The knee joint was disarticulated such that the entire lower extremity distal to the knee joint remained intact. The proximal tibia was fixed in polymethylmethacrylate. The specimens were aligned and impact loading was applied using mini-sled pendulum equipment. The pendulum impactor dynamically loaded the plantar aspect of the foot once. Following the test, specimens were palpated and radiographs in multiple planes were obtained. Injuries were classified into no fracture, and extra-and intra-articular fractures of the calcaneus. There were 14 cases of no injury and 12 cases of calcaneal fracture. The fracture forces (mean: 7802 N) were significantly different (p<0.01) from the forces in the no injury (mean: 4144 N) group. The probability of calcaneal fracture determined using logistic regression indicated that a force of 6.2 kN corresponds to 50 percent probability of calcaneal fracture. The derived probability distribution is useful in the design of dummies and vehicular surfaces.

Joint estimation over multiple individuals improves behavioural state inference from animal movement data.

PubMed

Jonsen, Ian

2016-02-08

State-space models provide a powerful way to scale up inference of movement behaviours from individuals to populations when the inference is made across multiple individuals. Here, I show how a joint estimation approach that assumes individuals share identical movement parameters can lead to improved inference of behavioural states associated with different movement processes. I use simulated movement paths with known behavioural states to compare estimation error between nonhierarchical and joint estimation formulations of an otherwise identical state-space model. Behavioural state estimation error was strongly affected by the degree of similarity between movement patterns characterising the behavioural states, with less error when movements were strongly dissimilar between states. The joint estimation model improved behavioural state estimation relative to the nonhierarchical model for simulated data with heavy-tailed Argos location errors. When applied to Argos telemetry datasets from 10 Weddell seals, the nonhierarchical model estimated highly uncertain behavioural state switching probabilities for most individuals whereas the joint estimation model yielded substantially less uncertainty. The joint estimation model better resolved the behavioural state sequences across all seals. Hierarchical or joint estimation models should be the preferred choice for estimating behavioural states from animal movement data, especially when location data are error-prone.

Bilateral coxofemoral degenerative joint disease in a juvenile male yellow-eyed penguin (Megadyptes antipodes).

PubMed

Buckle, Kelly N; Alley, Maurice R

2011-08-01

A juvenile, male, yellow-eyed penguin (Megadyptes antipodes) with abnormal stance and decreased mobility was captured, held in captivity for approximately 6 weeks, and euthanized due to continued clinical signs. Radiographically, there was bilateral degenerative joint disease with coxofemoral periarticular osteophyte formation. Grossly, the bird had bilaterally distended, thickened coxofemoral joints with increased laxity, and small, roughened and angular femoral heads. Histologically, the left femoral articular cartilage and subchondral bone were absent, and the remaining femoral head consisted of trabecular bone overlain by fibrin and granulation tissue. There was no gross or histological evidence of infection. The historic, gross, radiographic, and histopathologic findings were most consistent with bilateral aseptic femoral head degeneration resulting in degenerative joint disease. Although the chronicity of the lesions masked the initiating cause, the probable underlying causes of aseptic bilateral femoral head degeneration in a young animal are osteonecrosis and osteochondrosis of the femoral head. To our knowledge, this is the first reported case of bilateral coxofemoral degenerative joint disease in a penguin.

Recent progress in the joint velocity-scalar PDF method

NASA Technical Reports Server (NTRS)

Anand, M. S.

1995-01-01

This viewgraph presentation discusses joint velocity-scalar PDF method; turbulent combustion modeling issues for gas turbine combustors; PDF calculations for a recirculating flow; stochastic dissipation model; joint PDF calculations for swirling flows; spray calculations; reduced kinetics/manifold methods; parallel processing; and joint PDF focus areas.

Joint Analysis of Binomial and Continuous Traits with a Recursive Model: A Case Study Using Mortality and Litter Size of Pigs

PubMed Central

Varona, Luis; Sorensen, Daniel

2014-01-01

This work presents a model for the joint analysis of a binomial and a Gaussian trait using a recursive parametrization that leads to a computationally efficient implementation. The model is illustrated in an analysis of mortality and litter size in two breeds of Danish pigs, Landrace and Yorkshire. Available evidence suggests that mortality of piglets increased partly as a result of successful selection for total number of piglets born. In recent years there has been a need to decrease the incidence of mortality in pig-breeding programs. We report estimates of genetic variation at the level of the logit of the probability of mortality and quantify how it is affected by the size of the litter. Several models for mortality are considered and the best fits are obtained by postulating linear and cubic relationships between the logit of the probability of mortality and litter size, for Landrace and Yorkshire, respectively. An interpretation of how the presence of genetic variation affects the probability of mortality in the population is provided and we discuss and quantify the prospects of selecting for reduced mortality, without affecting litter size. PMID:24414548

Integration within the Felsenstein equation for improved Markov chain Monte Carlo methods in population genetics

PubMed Central

Hey, Jody; Nielsen, Rasmus

2007-01-01

In 1988, Felsenstein described a framework for assessing the likelihood of a genetic data set in which all of the possible genealogical histories of the data are considered, each in proportion to their probability. Although not analytically solvable, several approaches, including Markov chain Monte Carlo methods, have been developed to find approximate solutions. Here, we describe an approach in which Markov chain Monte Carlo simulations are used to integrate over the space of genealogies, whereas other parameters are integrated out analytically. The result is an approximation to the full joint posterior density of the model parameters. For many purposes, this function can be treated as a likelihood, thereby permitting likelihood-based analyses, including likelihood ratio tests of nested models. Several examples, including an application to the divergence of chimpanzee subspecies, are provided. PMID:17301231

A sampling algorithm for segregation analysis

PubMed Central

Tier, Bruce; Henshall, John

2001-01-01

Methods for detecting Quantitative Trait Loci (QTL) without markers have generally used iterative peeling algorithms for determining genotype probabilities. These algorithms have considerable shortcomings in complex pedigrees. A Monte Carlo Markov chain (MCMC) method which samples the pedigree of the whole population jointly is described. Simultaneous sampling of the pedigree was achieved by sampling descent graphs using the Metropolis-Hastings algorithm. A descent graph describes the inheritance state of each allele and provides pedigrees guaranteed to be consistent with Mendelian sampling. Sampling descent graphs overcomes most, if not all, of the limitations incurred by iterative peeling algorithms. The algorithm was able to find the QTL in most of the simulated populations. However, when the QTL was not modeled or found then its effect was ascribed to the polygenic component. No QTL were detected when they were not simulated. PMID:11742631

A Single-Lap Joint Adhesive Bonding Optimization Method Using Gradient and Genetic Algorithms

NASA Technical Reports Server (NTRS)

Smeltzer, Stanley S., III; Finckenor, Jeffrey L.

1999-01-01

A natural process for any engineer, scientist, educator, etc. is to seek the most efficient method for accomplishing a given task. In the case of structural design, an area that has a significant impact on the structural efficiency is joint design. Unless the structure is machined from a solid block of material, the individual components which compose the overall structure must be joined together. The method for joining a structure varies depending on the applied loads, material, assembly and disassembly requirements, service life, environment, etc. Using both metallic and fiber reinforced plastic materials limits the user to two methods or a combination of these methods for joining the components into one structure. The first is mechanical fastening and the second is adhesive bonding. Mechanical fastening is by far the most popular joining technique; however, in terms of structural efficiency, adhesive bonding provides a superior joint since the load is distributed uniformly across the joint. The purpose of this paper is to develop a method for optimizing single-lap joint adhesive bonded structures using both gradient and genetic algorithms and comparing the solution process for each method. The goal of the single-lap joint optimization is to find the most efficient structure that meets the imposed requirements while still remaining as lightweight, economical, and reliable as possible. For the single-lap joint, an optimum joint is determined by minimizing the weight of the overall joint based on constraints from adhesive strengths as well as empirically derived rules. The analytical solution of the sin-le-lap joint is determined using the classical Goland-Reissner technique for case 2 type adhesive joints. Joint weight minimization is achieved using a commercially available routine, Design Optimization Tool (DOT), for the gradient solution while an author developed method is used for the genetic algorithm solution. Results illustrate the critical design variables as a function of adhesive properties and convergences of different joints based on the two optimization methods.

Mechanical and interfacial characterization of laser welded Co-Cr alloy with different joint configurations

PubMed Central

Kokolis, John; Chakmakchi, Makdad; Theocharopoulos, Antonios; Prombonas, Anthony

2015-01-01

PURPOSE The mechanical and interfacial characterization of laser welded Co-Cr alloy with two different joint designs. MATERIALS AND METHODS Dumbbell cast specimens (n=30) were divided into 3 groups (R, I, K, n=10). Group R consisted of intact specimens, group I of specimens sectioned with a straight cut, and group K of specimens with a 45° bevel made at the one welding edge. The microstructure and the elemental distributions of alloy and welding regions were examined by an SEM/EDX analysis and then specimens were loaded in tension up to fracture. The tensile strength (TS) and elongation (ε) were determined and statistically compared among groups employing 1-way ANOVA, SNK multiple comparison test (α=.05) and Weibull analysis where Weibull modulus m and characteristic strength σο were identified. Fractured surfaces were imaged by a SEM. RESULTS SEM/EDX analysis showed that cast alloy consists of two phases with differences in mean atomic number contrast, while no mean atomic number was identified for welded regions. EDX analysis revealed an increased Cr and Mo content at the alloy-joint interface. All mechanical properties of group I (TS, ε, m and σο) were found inferior to R while group K showed intermediated values without significant differences to R and I, apart from elongation with group R. The fractured surfaces of all groups showed extensive dendritic pattern although with a finer structure in the case of welded groups. CONCLUSION The K shape joint configuration should be preferred over the I, as it demonstrates improved mechanical strength and survival probability. PMID:25722836

Computer-Based Radiographic Quantification of Joint Space Narrowing Progression Using Sequential Hand Radiographs: Validation Study in Rheumatoid Arthritis Patients from Multiple Institutions.

PubMed

Ichikawa, Shota; Kamishima, Tamotsu; Sutherland, Kenneth; Fukae, Jun; Katayama, Kou; Aoki, Yuko; Okubo, Takanobu; Okino, Taichi; Kaneda, Takahiko; Takagi, Satoshi; Tanimura, Kazuhide

2017-10-01

We have developed a refined computer-based method to detect joint space narrowing (JSN) progression with the joint space narrowing progression index (JSNPI) by superimposing sequential hand radiographs. The purpose of this study is to assess the validity of a computer-based method using images obtained from multiple institutions in rheumatoid arthritis (RA) patients. Sequential hand radiographs of 42 patients (37 females and 5 males) with RA from two institutions were analyzed by a computer-based method and visual scoring systems as a standard of reference. The JSNPI above the smallest detectable difference (SDD) defined JSN progression on the joint level. The sensitivity and specificity of the computer-based method for JSN progression was calculated using the SDD and a receiver operating characteristic (ROC) curve. Out of 314 metacarpophalangeal joints, 34 joints progressed based on the SDD, while 11 joints widened. Twenty-one joints progressed in the computer-based method, 11 joints in the scoring systems, and 13 joints in both methods. Based on the SDD, we found lower sensitivity and higher specificity with 54.2 and 92.8%, respectively. At the most discriminant cutoff point according to the ROC curve, the sensitivity and specificity was 70.8 and 81.7%, respectively. The proposed computer-based method provides quantitative measurement of JSN progression using sequential hand radiographs and may be a useful tool in follow-up assessment of joint damage in RA patients.

Mutual Information between Discrete Variables with Many Categories using Recursive Adaptive Partitioning

PubMed Central

Seok, Junhee; Seon Kang, Yeong

2015-01-01

Mutual information, a general measure of the relatedness between two random variables, has been actively used in the analysis of biomedical data. The mutual information between two discrete variables is conventionally calculated by their joint probabilities estimated from the frequency of observed samples in each combination of variable categories. However, this conventional approach is no longer efficient for discrete variables with many categories, which can be easily found in large-scale biomedical data such as diagnosis codes, drug compounds, and genotypes. Here, we propose a method to provide stable estimations for the mutual information between discrete variables with many categories. Simulation studies showed that the proposed method reduced the estimation errors by 45 folds and improved the correlation coefficients with true values by 99 folds, compared with the conventional calculation of mutual information. The proposed method was also demonstrated through a case study for diagnostic data in electronic health records. This method is expected to be useful in the analysis of various biomedical data with discrete variables. PMID:26046461

Combining evidence using likelihood ratios in writer verification

NASA Astrophysics Data System (ADS)

Srihari, Sargur; Kovalenko, Dimitry; Tang, Yi; Ball, Gregory

2013-01-01

Forensic identification is the task of determining whether or not observed evidence arose from a known source. It involves determining a likelihood ratio (LR) - the ratio of the joint probability of the evidence and source under the identification hypothesis (that the evidence came from the source) and under the exclusion hypothesis (that the evidence did not arise from the source). In LR- based decision methods, particularly handwriting comparison, a variable number of input evidences is used. A decision based on many pieces of evidence can result in nearly the same LR as one based on few pieces of evidence. We consider methods for distinguishing between such situations. One of these is to provide confidence intervals together with the decisions and another is to combine the inputs using weights. We propose a new method that generalizes the Bayesian approach and uses an explicitly defined discount function. Empirical evaluation with several data sets including synthetically generated ones and handwriting comparison shows greater flexibility of the proposed method.

Is twin pregnancy a risk factor for devolopmental dysplasia of the hip - retrospective analysis using ultrasonography.

PubMed

Czubak, Jarosław; Mazela, Jan L; Majda, Waldemar; Woźniak, Waldemar

2003-12-30

Background. Disorders in development of the hip in the uterus are caused mainly by mechanical factors. Their influence has been established on the basis of the results of examinations of newborns from singleton pregancies. Malposition of the fetus and the lack of space in the uterus are present in higher frequency in twin pregnancies. Thus, it is probable, that twin pregnacy may be a risk factor in developmental dysplasia of the hip.
Material and methods. We examined clinically and ultrasonographically 308 hip joints of 154 newborn twins and compare the values of the alpha related to different position in uterus, birthweight, gender, length of gestation and mode of delivery. The only pathological position of the fetus in the uterus is the tranverse one.
Results and Conclusions. The results of ultrasound examinations reveal that in the cramped space inside the uterus in twin pregnancies hip joints develop in different conditions than in singleton pregnancies and the twin pregnancy cannot be regarded as a risk factor which may cause developmental dysplasia of the hip.

The Gaussian copula model for the joint deficit index for droughts

NASA Astrophysics Data System (ADS)

Van de Vyver, H.; Van den Bergh, J.

2018-06-01

The characterization of droughts and their impacts is very dependent on the time scale that is involved. In order to obtain an overall drought assessment, the cumulative effects of water deficits over different times need to be examined together. For example, the recently developed joint deficit index (JDI) is based on multivariate probabilities of precipitation over various time scales from 1- to 12-months, and was constructed from empirical copulas. In this paper, we examine the Gaussian copula model for the JDI. We model the covariance across the temporal scales with a two-parameter function that is commonly used in the specific context of spatial statistics or geostatistics. The validity of the covariance models is demonstrated with long-term precipitation series. Bootstrap experiments indicate that the Gaussian copula model has advantages over the empirical copula method in the context of drought severity assessment: (i) it is able to quantify droughts outside the range of the empirical copula, (ii) provides adequate drought quantification, and (iii) provides a better understanding of the uncertainty in the estimation.

A model to explain joint patterns found in ignimbrite deposits

NASA Astrophysics Data System (ADS)

Tibaldi, A.; Bonali, F. L.

2018-03-01

The study of fracture systems is of paramount importance for economic applications, such as CO2 storage in rock successions, geothermal and hydrocarbon exploration and exploitation, and also for a better knowledge of seismogenic fault formation. Understanding the origin of joints can be useful for tectonic studies and for a geotechnical characterisation of rock masses. Here, we illustrate a joint pattern discovered in ignimbrite deposits of South America, which can be confused with conjugate tectonic joint sets but which have another origin. The pattern is probably common, but recognisable only in plan view and before tectonic deformation obscures and overprints it. Key sites have been mostly studied by field surveys in Bolivia and Chile. The pattern is represented by hundreds-of-meters up to kilometre-long swarms of master joints, which show circular to semi-circular geometries and intersections that have "X" and "Y" patterns. Inside each swarm, joints are systematic, rectilinear or curvilinear in plan view, and as much as 900 m long. In section view, they are from sub-vertical to vertical and do not affect the underlying deposits. Joints with different orientation mostly interrupt each other, suggesting they have the same age. This joint architecture is here interpreted as resulting from differential contraction after emplacement of the ignimbrite deposit above a complex topography. The set of the joint pattern that has suitable orientation with respect to tectonic stresses may act to nucleate faults.

Balancing precision and risk: should multiple detection methods be analyzed separately in N-mixture models?

USGS Publications Warehouse

Graves, Tabitha A.; Royle, J. Andrew; Kendall, Katherine C.; Beier, Paul; Stetz, Jeffrey B.; Macleod, Amy C.

2012-01-01

Using multiple detection methods can increase the number, kind, and distribution of individuals sampled, which may increase accuracy and precision and reduce cost of population abundance estimates. However, when variables influencing abundance are of interest, if individuals detected via different methods are influenced by the landscape differently, separate analysis of multiple detection methods may be more appropriate. We evaluated the effects of combining two detection methods on the identification of variables important to local abundance using detections of grizzly bears with hair traps (systematic) and bear rubs (opportunistic). We used hierarchical abundance models (N-mixture models) with separate model components for each detection method. If both methods sample the same population, the use of either data set alone should (1) lead to the selection of the same variables as important and (2) provide similar estimates of relative local abundance. We hypothesized that the inclusion of 2 detection methods versus either method alone should (3) yield more support for variables identified in single method analyses (i.e. fewer variables and models with greater weight), and (4) improve precision of covariate estimates for variables selected in both separate and combined analyses because sample size is larger. As expected, joint analysis of both methods increased precision as well as certainty in variable and model selection. However, the single-method analyses identified different variables and the resulting predicted abundances had different spatial distributions. We recommend comparing single-method and jointly modeled results to identify the presence of individual heterogeneity between detection methods in N-mixture models, along with consideration of detection probabilities, correlations among variables, and tolerance to risk of failing to identify variables important to a subset of the population. The benefits of increased precision should be weighed against those risks. The analysis framework presented here will be useful for other species exhibiting heterogeneity by detection method.

Estimate of Probability of Crack Detection from Service Difficulty Report Data.

DOT National Transportation Integrated Search

1995-09-01

The initiation and growth of cracks in a fuselage lap joint were simulated. Stochastic distribution of crack initiation and rivet interference were included. The simulation also contained a simplified crack growth. Nominal crack growth behavior of la...

Estimate of probability of crack detection from service difficulty report data

DOT National Transportation Integrated Search

1994-09-01

The initiation and growth of cracks in a fuselage lap joint were simulated. Stochastic distribution of crack initiation and rivet interference were included. The simulation also contained a simplified crack growth. Nominal crack growth behavior of la...

A short walk in quantum probability

NASA Astrophysics Data System (ADS)

Hudson, Robin

2018-04-01

This is a personal survey of aspects of quantum probability related to the Heisenberg commutation relation for canonical pairs. Using the failure, in general, of non-negativity of the Wigner distribution for canonical pairs to motivate a more satisfactory quantum notion of joint distribution, we visit a central limit theorem for such pairs and a resulting family of quantum planar Brownian motions which deform the classical planar Brownian motion, together with a corresponding family of quantum stochastic areas. This article is part of the themed issue `Hilbert's sixth problem'.

Joint Information Theoretic and Differential Geometrical Approach for Robust Automated Target Recognition

DTIC Science & Technology

2012-02-29

surface and Swiss roll) and real-world data sets (UCI Machine Learning Repository [12] and USPS digit handwriting data). In our experiments, we use...less than µn ( say µ = 0.8), we can first use screening technique to select µn candidate nodes, and then apply BIPS on them for further selection and...identified from node j to node i. So we can say the probability for the existence of this connection is approximately 82%. Given the probability matrix

A Review of Natural Joint Systems and Numerical Investigation of Bio-Inspired GFRP-to-Steel Joints

PubMed Central

Avgoulas, Evangelos I.; Sutcliffe, Michael P. F.

2016-01-01

There are a great variety of joint types used in nature which can inspire engineering joints. In order to design such biomimetic joints, it is at first important to understand how biological joints work. A comprehensive literature review, considering natural joints from a mechanical point of view, was undertaken. This was used to develop a taxonomy based on the different methods/functions that nature successfully uses to attach dissimilar tissues. One of the key methods that nature uses to join dissimilar materials is a transitional zone of stiffness at the insertion site. This method was used to propose bio-inspired solutions with a transitional zone of stiffness at the joint site for several glass fibre reinforced plastic (GFRP) to steel adhesively bonded joint configurations. The transition zone was used to reduce the material stiffness mismatch of the joint parts. A numerical finite element model was used to identify the optimum variation in material stiffness that minimises potential failure of the joint. The best bio-inspired joints showed a 118% increase of joint strength compared to the standard joints. PMID:28773688

A Review of Natural Joint Systems and Numerical Investigation of Bio-Inspired GFRP-to-Steel Joints.

PubMed

Avgoulas, Evangelos I; Sutcliffe, Michael P F

2016-07-12

There are a great variety of joint types used in nature which can inspire engineering joints. In order to design such biomimetic joints, it is at first important to understand how biological joints work. A comprehensive literature review, considering natural joints from a mechanical point of view, was undertaken. This was used to develop a taxonomy based on the different methods/functions that nature successfully uses to attach dissimilar tissues. One of the key methods that nature uses to join dissimilar materials is a transitional zone of stiffness at the insertion site. This method was used to propose bio-inspired solutions with a transitional zone of stiffness at the joint site for several glass fibre reinforced plastic (GFRP) to steel adhesively bonded joint configurations. The transition zone was used to reduce the material stiffness mismatch of the joint parts. A numerical finite element model was used to identify the optimum variation in material stiffness that minimises potential failure of the joint. The best bio-inspired joints showed a 118% increase of joint strength compared to the standard joints.

Improving Constraints on Climate System Properties withAdditional Data and New Statistical and Sampling Methods

NASA Astrophysics Data System (ADS)

Forest, C. E.; Libardoni, A. G.; Sokolov, A. P.; Monier, E.

2017-12-01

We use the updated MIT Earth System Model (MESM) to derive the joint probability distribution function for Equilibrium Climate sensitivity (S), an effective heat diffusivity (Kv), and the net aerosol forcing (Faer). Using a new 1800-member ensemble of MESM runs, we derive PDFs by comparing model outputs against historical observations of surface temperature and global mean ocean heat content. We focus on how changes in (i) the MESM model, (ii) recent surface temperature and ocean heat content observations, and (iii) estimates of internal climate variability will all contribute to uncertainties. We show that estimates of S increase and Faer is less negative. These shifts result partly from new model forcing inputs but also from including recent temperature records that lead to higher values of S and Kv. We show that the parameter distributions are sensitive to the internal variability in the climate system. When considering these factors, we derive our best estimate for the joint probability distribution for the climate system properties. We estimate the 90-percent confidence intervals for climate sensitivity as 2.7-5.4 oC with a mode of 3.5 oC, for Kv as 1.9-23.0 cm2 s-1 with a mode of 4.41 cm2 s-1, and for Faer as -0.4 - -0.04 Wm-2 with a mode of -0.25 Wm-2. Lastly, we estimate TCR to be between 1.4 and 2.1 oC with a mode of 1.8 oC.

Bayesian multiple-source localization in an uncertain ocean environment.

PubMed

Dosso, Stan E; Wilmut, Michael J

2011-06-01

This paper considers simultaneous localization of multiple acoustic sources when properties of the ocean environment (water column and seabed) are poorly known. A Bayesian formulation is developed in which the environmental parameters, noise statistics, and locations and complex strengths (amplitudes and phases) of multiple sources are considered to be unknown random variables constrained by acoustic data and prior information. Two approaches are considered for estimating source parameters. Focalization maximizes the posterior probability density (PPD) over all parameters using adaptive hybrid optimization. Marginalization integrates the PPD using efficient Markov-chain Monte Carlo methods to produce joint marginal probability distributions for source ranges and depths, from which source locations are obtained. This approach also provides quantitative uncertainty analysis for all parameters, which can aid in understanding of the inverse problem and may be of practical interest (e.g., source-strength probability distributions). In both approaches, closed-form maximum-likelihood expressions for source strengths and noise variance at each frequency allow these parameters to be sampled implicitly, substantially reducing the dimensionality and difficulty of the inversion. Examples are presented of both approaches applied to single- and multi-frequency localization of multiple sources in an uncertain shallow-water environment, and a Monte Carlo performance evaluation study is carried out. © 2011 Acoustical Society of America

Modeling Finite-Time Failure Probabilities in Risk Analysis Applications.

PubMed

Dimitrova, Dimitrina S; Kaishev, Vladimir K; Zhao, Shouqi

2015-10-01

In this article, we introduce a framework for analyzing the risk of systems failure based on estimating the failure probability. The latter is defined as the probability that a certain risk process, characterizing the operations of a system, reaches a possibly time-dependent critical risk level within a finite-time interval. Under general assumptions, we define two dually connected models for the risk process and derive explicit expressions for the failure probability and also the joint probability of the time of the occurrence of failure and the excess of the risk process over the risk level. We illustrate how these probabilistic models and results can be successfully applied in several important areas of risk analysis, among which are systems reliability, inventory management, flood control via dam management, infectious disease spread, and financial insolvency. Numerical illustrations are also presented. © 2015 Society for Risk Analysis.

Developing the fuzzy c-means clustering algorithm based on maximum entropy for multitarget tracking in a cluttered environment

NASA Astrophysics Data System (ADS)

Chen, Xiao; Li, Yaan; Yu, Jing; Li, Yuxing

2018-01-01

For fast and more effective implementation of tracking multiple targets in a cluttered environment, we propose a multiple targets tracking (MTT) algorithm called maximum entropy fuzzy c-means clustering joint probabilistic data association that combines fuzzy c-means clustering and the joint probabilistic data association (PDA) algorithm. The algorithm uses the membership value to express the probability of the target originating from measurement. The membership value is obtained through fuzzy c-means clustering objective function optimized by the maximum entropy principle. When considering the effect of the public measurement, we use a correction factor to adjust the association probability matrix to estimate the state of the target. As this algorithm avoids confirmation matrix splitting, it can solve the high computational load problem of the joint PDA algorithm. The results of simulations and analysis conducted for tracking neighbor parallel targets and cross targets in a different density cluttered environment show that the proposed algorithm can realize MTT quickly and efficiently in a cluttered environment. Further, the performance of the proposed algorithm remains constant with increasing process noise variance. The proposed algorithm has the advantages of efficiency and low computational load, which can ensure optimum performance when tracking multiple targets in a dense cluttered environment.

Investigation of 2‐stage meta‐analysis methods for joint longitudinal and time‐to‐event data through simulation and real data application

PubMed Central

Tudur Smith, Catrin; Gueyffier, François; Kolamunnage‐Dona, Ruwanthi

2017-01-01

Background Joint modelling of longitudinal and time‐to‐event data is often preferred over separate longitudinal or time‐to‐event analyses as it can account for study dropout, error in longitudinally measured covariates, and correlation between longitudinal and time‐to‐event outcomes. The joint modelling literature focuses mainly on the analysis of single studies with no methods currently available for the meta‐analysis of joint model estimates from multiple studies. Methods We propose a 2‐stage method for meta‐analysis of joint model estimates. These methods are applied to the INDANA dataset to combine joint model estimates of systolic blood pressure with time to death, time to myocardial infarction, and time to stroke. Results are compared to meta‐analyses of separate longitudinal or time‐to‐event models. A simulation study is conducted to contrast separate versus joint analyses over a range of scenarios. Results Using the real dataset, similar results were obtained by using the separate and joint analyses. However, the simulation study indicated a benefit of use of joint rather than separate methods in a meta‐analytic setting where association exists between the longitudinal and time‐to‐event outcomes. Conclusions Where evidence of association between longitudinal and time‐to‐event outcomes exists, results from joint models over standalone analyses should be pooled in 2‐stage meta‐analyses. PMID:29250814

JDINAC: joint density-based non-parametric differential interaction network analysis and classification using high-dimensional sparse omics data.

PubMed

Ji, Jiadong; He, Di; Feng, Yang; He, Yong; Xue, Fuzhong; Xie, Lei

2017-10-01

A complex disease is usually driven by a number of genes interwoven into networks, rather than a single gene product. Network comparison or differential network analysis has become an important means of revealing the underlying mechanism of pathogenesis and identifying clinical biomarkers for disease classification. Most studies, however, are limited to network correlations that mainly capture the linear relationship among genes, or rely on the assumption of a parametric probability distribution of gene measurements. They are restrictive in real application. We propose a new Joint density based non-parametric Differential Interaction Network Analysis and Classification (JDINAC) method to identify differential interaction patterns of network activation between two groups. At the same time, JDINAC uses the network biomarkers to build a classification model. The novelty of JDINAC lies in its potential to capture non-linear relations between molecular interactions using high-dimensional sparse data as well as to adjust confounding factors, without the need of the assumption of a parametric probability distribution of gene measurements. Simulation studies demonstrate that JDINAC provides more accurate differential network estimation and lower classification error than that achieved by other state-of-the-art methods. We apply JDINAC to a Breast Invasive Carcinoma dataset, which includes 114 patients who have both tumor and matched normal samples. The hub genes and differential interaction patterns identified were consistent with existing experimental studies. Furthermore, JDINAC discriminated the tumor and normal sample with high accuracy by virtue of the identified biomarkers. JDINAC provides a general framework for feature selection and classification using high-dimensional sparse omics data. R scripts available at https://github.com/jijiadong/JDINAC. lxie@iscb.org. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

A case cluster of variant Creutzfeldt-Jakob disease linked to the Kingdom of Saudi Arabia.

PubMed

Coulthart, Michael B; Geschwind, Michael D; Qureshi, Shireen; Phielipp, Nicolas; Demarsh, Alex; Abrams, Joseph Y; Belay, Ermias; Gambetti, Pierluigi; Jansen, Gerard H; Lang, Anthony E; Schonberger, Lawrence B

2016-10-01

As of mid-2016, 231 cases of variant Creutzfeldt-Jakob disease-the human form of a prion disease of cattle, bovine spongiform encephalopathy-have been reported from 12 countries. With few exceptions, the affected individuals had histories of extended residence in the UK or other Western European countries during the period (1980-96) of maximum global risk for human exposure to bovine spongiform encephalopathy. However, the possibility remains that other geographic foci of human infection exist, identification of which may help to foreshadow the future of the epidemic. We report results of a quantitative analysis of country-specific relative risks of infection for three individuals diagnosed with variant Creutzfeldt-Jakob disease in the USA and Canada. All were born and raised in Saudi Arabia, but had histories of residence and travel in other countries. To calculate country-specific relative probabilities of infection, we aligned each patient's life history with published estimates of probability distributions of incubation period and age at infection parameters from a UK cohort of 171 variant Creutzfeldt-Jakob disease cases. The distributions were then partitioned into probability density fractions according to time intervals of the patient's residence and travel history, and the density fractions were combined by country. This calculation was performed for incubation period alone, age at infection alone, and jointly for incubation and age at infection. Country-specific fractions were normalized either to the total density between the individual's dates of birth and symptom onset ('lifetime'), or to that between 1980 and 1996, for a total of six combinations of parameter and interval. The country-specific relative probability of infection for Saudi Arabia clearly ranked highest under each of the six combinations of parameter × interval for Patients 1 and 2, with values ranging from 0.572 to 0.998, respectively, for Patient 2 (age at infection × lifetime) and Patient 1 (joint incubation and age at infection × 1980-96). For Patient 3, relative probabilities for Saudi Arabia were not as distinct from those for other countries using the lifetime interval: 0.394, 0.360 and 0.378, respectively, for incubation period, age at infection and jointly for incubation and age at infection. However, for this patient Saudi Arabia clearly ranked highest within the 1980-96 period: 0.859, 0.871 and 0.865, respectively, for incubation period, age at infection and jointly for incubation and age at infection. These findings support the hypothesis that human infection with bovine spongiform encephalopathy occurred in Saudi Arabia. © Her Majesty the Queen in Right of Canada 2016. Reproduced with the permission of the Minister of Public Health.

Effect of joint spacing and joint dip on the stress distribution around tunnels using different numerical methods

NASA Astrophysics Data System (ADS)

Nikadat, Nooraddin; Fatehi Marji, Mohammad; Rahmannejad, Reza; Yarahmadi Bafghi, Alireza

2016-11-01

Different conditions may affect the stability of tunnels by the geometry (spacing and orientation) of joints in the surrounded rock mass. In this study, by comparing the results obtained by the three novel numerical methods i.e. finite element method (Phase2), discrete element method (UDEC) and indirect boundary element method (TFSDDM), the effects of joint spacing and joint dips on the stress distribution around rock tunnels are numerically studied. These comparisons indicate the validity of the stress analyses around circular rock tunnels. These analyses also reveal that for a semi-continuous environment, boundary element method gives more accurate results compared to the results of finite element and distinct element methods. In the indirect boundary element method, the displacements due to joints of different spacing and dips are estimated by using displacement discontinuity (DD) formulations and the total stress distribution around the tunnel are obtained by using fictitious stress (FS) formulations.

Structural behavior of the space shuttle SRM Tang-Clevis joint

NASA Technical Reports Server (NTRS)

Greene, W. H.; Knight, N. F., Jr.; Stockwell, A. E.

1986-01-01

The space shuttle Challenger accident investigation focused on the failure of a tang-clevis joint on the right solid rocket motor. The existence of relative motion between the inner arm of the clevis and the O-ring sealing surface on the tang has been identified as a potential contributor to this failure. This motion can cause the O-rings to become unseated and therefore lose their sealing capability. Finite element structural analyses have been performed to predict both deflections and stresses in the joint under the primary, pressure loading condition. These analyses have demonstrated the difficulty of accurately predicting the structural behavior of the tang-clevis joint. Stresses in the vicinity of the connecting pins, obtained from elastic analyses, considerably exceed the material yield allowables indicating that inelastic analyses are probably necessary. Two modifications have been proposed to control the relative motion between the inner clevis arm and the tang at the O-ring sealing surface. One modification, referred to as the capture feature, uses additional material on the inside of the tang to restrict motion of the inner clevis arm. The other modification uses external stiffening rings above and below the joint to control the local bending in the shell near the joint. Both of these modifications are shown to be effective in controlling the relative motion in the joint.

Structural behavior of the space shuttle SRM tang-clevis joint

NASA Technical Reports Server (NTRS)

Greene, William H.; Knight, Norman F., Jr.; Stockwell, Alan E.

1988-01-01

The space shuttle Challenger accident investigation focused on the failure of a tang-clevis joint on the right solid rocket motor. The existence of relative motion between the inner arm of the clevis and the O-ring sealing surface on the tang has been identified as a potential contributor to this failure. This motion can cause the O-rings to become unseated and therefore lose their sealing capability. Finite element structural analyses have been performed to predict both deflections and stresses in the joint under the primary, pressure loading condition. These analyses have demonstrated the difficulty of accurately predicting the structural behavior of the tang-clevis joint. Stresses in the vicinity of the connecting pins, obtained from elastic analyses, considerably exceed the material yield allowables indicating that inelastic analyses are probably necessary. Two modifications have been proposed to control the relative motion between the inner clevis arm and the tang at the O-ring sealing surface. One modification, referred to as the capture feature, uses additional material on the inside of the tang to restrict motion of the inner clevis arm. The other modification uses external stiffening rings above and below the joint to control the local bending in the shell near the joint. Both of these modifications are shown to be effective in controlling the relative motion in the joint.

Regional analysis and derivation of copula-based drought Severity-Area-Frequency curve in Lake Urmia basin, Iran.

PubMed

Amirataee, Babak; Montaseri, Majid; Rezaie, Hossein

2018-01-15

Droughts are extreme events characterized by temporal duration and spatial large-scale effects. In general, regional droughts are affected by general circulation of the atmosphere (at large-scale) and regional natural factors, including the topography, natural lakes, the position relative to the center and the path of the ocean currents (at small-scale), and they don't cover the exact same effects in a wide area. Therefore, drought Severity-Area-Frequency (S-A-F) curve investigation is an essential task to develop decision making rule for regional drought management. This study developed the copula-based joint probability distribution of drought severity and percent of area under drought across the Lake Urmia basin, Iran. To do this end, one-month Standardized Precipitation Index (SPI) values during the 1971-2013 were applied across 24 rainfall stations in the study area. Then, seven copula functions of various families, including Clayton, Gumbel, Frank, Joe, Galambos, Plackett and Normal copulas, were used to model the joint probability distribution of drought severity and drought area. Using AIC, BIC and RMSE criteria, the Frank copula was selected as the most appropriate copula in order to develop the joint probability distribution of severity-percent of area under drought across the study area. Based on the Frank copula, the drought S-A-F curve for the study area was derived. The results indicated that severe/extreme drought and non-drought (wet) behaviors have affected the majority of study areas (Lake Urmia basin). However, the area covered by the specific semi-drought effects is limited and has been subject to significant variations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Using DNA to track the origin of the largest ivory seizure since the 1989 trade ban.

PubMed

Wasser, Samuel K; Mailand, Celia; Booth, Rebecca; Mutayoba, Benezeth; Kisamo, Emily; Clark, Bill; Stephens, Matthew

2007-03-06

The illegal ivory trade recently intensified to the highest levels ever reported. Policing this trafficking has been hampered by the inability to reliably determine geographic origin of contraband ivory. Ivory can be smuggled across multiple international borders and along numerous trade routes, making poaching hotspots and potential trade routes difficult to identify. This fluidity also makes it difficult to refute a country's denial of poaching problems. We extend an innovative DNA assignment method to determine the geographic origin(s) of large elephant ivory seizures. A Voronoi tessellation method is used that utilizes genetic similarities across tusks to simultaneously infer the origin of multiple samples that could have one or more common origin(s). We show that this joint analysis performs better than sample-by-sample methods in assigning sample clusters of known origin. The joint method is then used to infer the geographic origin of the largest ivory seizure since the 1989 ivory trade ban. Wildlife authorities initially suspected that this ivory came from multiple locations across forest and savanna Africa. However, we show that the ivory was entirely from savanna elephants, most probably originating from a narrow east-to-west band of southern Africa, centered on Zambia. These findings enabled law enforcement to focus their investigation to a smaller area and fewer trade routes and led to changes within the Zambian government to improve antipoaching efforts. Such outcomes demonstrate the potential of genetic analyses to help combat the expanding wildlife trade by identifying origin(s) of large seizures of contraband ivory. Broader applications to wildlife trade are discussed.

Using DNA to track the origin of the largest ivory seizure since the 1989 trade ban

PubMed Central

Wasser, Samuel K.; Mailand, Celia; Booth, Rebecca; Mutayoba, Benezeth; Kisamo, Emily; Clark, Bill; Stephens, Matthew

2007-01-01

The illegal ivory trade recently intensified to the highest levels ever reported. Policing this trafficking has been hampered by the inability to reliably determine geographic origin of contraband ivory. Ivory can be smuggled across multiple international borders and along numerous trade routes, making poaching hotspots and potential trade routes difficult to identify. This fluidity also makes it difficult to refute a country's denial of poaching problems. We extend an innovative DNA assignment method to determine the geographic origin(s) of large elephant ivory seizures. A Voronoi tessellation method is used that utilizes genetic similarities across tusks to simultaneously infer the origin of multiple samples that could have one or more common origin(s). We show that this joint analysis performs better than sample-by-sample methods in assigning sample clusters of known origin. The joint method is then used to infer the geographic origin of the largest ivory seizure since the 1989 ivory trade ban. Wildlife authorities initially suspected that this ivory came from multiple locations across forest and savanna Africa. However, we show that the ivory was entirely from savanna elephants, most probably originating from a narrow east-to-west band of southern Africa, centered on Zambia. These findings enabled law enforcement to focus their investigation to a smaller area and fewer trade routes and led to changes within the Zambian government to improve antipoaching efforts. Such outcomes demonstrate the potential of genetic analyses to help combat the expanding wildlife trade by identifying origin(s) of large seizures of contraband ivory. Broader applications to wildlife trade are discussed. PMID:17360505

A Modelling Method of Bolt Joints Based on Basic Characteristic Parameters of Joint Surfaces

NASA Astrophysics Data System (ADS)

Yuansheng, Li; Guangpeng, Zhang; Zhen, Zhang; Ping, Wang

2018-02-01

Bolt joints are common in machine tools and have a direct impact on the overall performance of the tools. Therefore, the understanding of bolt joint characteristics is essential for improving machine design and assembly. Firstly, According to the experimental data obtained from the experiment, the stiffness curve formula was fitted. Secondly, a finite element model of unit bolt joints such as bolt flange joints, bolt head joints, and thread joints was constructed, and lastly the stiffness parameters of joint surfaces were implemented in the model by the secondary development of ABAQUS. The finite element model of the bolt joint established by this method can simulate the contact state very well.

Evaluation of a Consistent LES/PDF Method Using a Series of Experimental Spray Flames

NASA Astrophysics Data System (ADS)

Heye, Colin; Raman, Venkat

2012-11-01

A consistent method for the evolution of the joint-scalar probability density function (PDF) transport equation is proposed for application to large eddy simulation (LES) of turbulent reacting flows containing evaporating spray droplets. PDF transport equations provide the benefit of including the chemical source term in closed form, however, additional terms describing LES subfilter mixing must be modeled. The recent availability of detailed experimental measurements provide model validation data for a wide range of evaporation rates and combustion regimes, as is well-known to occur in spray flames. In this work, the experimental data will used to investigate the impact of droplet mass loading and evaporation rates on the subfilter scalar PDF shape in comparison with conventional flamelet models. In addition, existing model term closures in the PDF transport equations are evaluated with a focus on their validity in the presence of regime changes.

Association between disk position and degenerative bone changes of the temporomandibular joints: an imaging study in subjects with TMD.

PubMed

Cortés, Daniel; Sylvester, Daniel Cortés; Exss, Eduardo; Marholz, Carlos; Millas, Rodrigo; Moncada, Gustavo

2011-04-01

The aim of this study was to determine the frequency and relationship between disk position and degenerative bone changes in the temporomandibular joints (TMJ), in subjects with internal derangement (ID). MRI and CT scans of 180 subjects with temporomandibular disorders (TMD) were studied. Different image parameters or characteristics were observed, such as disk position, joint effusion, condyle movement, degenerative bone changes (flattened, cortical erosions and irregularities), osteophytes, subchondral cysts and idiopathic condyle resorption. The present study concluded that there is a significant association between disk displacement without reduction and degenerative bone changes in patients with TMD. The study also found a high probability of degenerative bone changes when disk displacement without reduction is present. No association was found between TMD and condyle range of motion, joint effusion and/or degenerative bone changes. The following were the most frequent morphological changes observed: flattening of the anterior surface of the condyle; followed by erosions and irregularities of the joint surfaces; flattening of the articular surface of the temporal eminence, subchondral cysts, osteophytes; and idiopathic condyle resorption, in decreasing order.

Making Peace Pay: Post-Conflict Economic and Infrastructure Development in Kosovo and Iraq

DTIC Science & Technology

probability that a post-conflict state will return to war. Additionally, consecutive presidential administrations and joint doctrine have declared...and Iraqi Freedom as historical case studies to demonstrate that the armed forces possess unique advantages, to include physical presence and

An Integrated Model of Application, Admission, Enrollment, and Financial Aid

ERIC Educational Resources Information Center

DesJardins, Stephen L.; Ahlburg, Dennis A.; McCall, Brian Patrick

2006-01-01

We jointly model the application, admission, financial aid determination, and enrollment decision process. We find that expectations of admission affect application probabilities, financial aid expectations affect enrollment and application behavior, and deviations from aid expectations are strongly related to enrollment. We also conduct…

The emergence of different tail exponents in the distributions of firm size variables

NASA Astrophysics Data System (ADS)

Ishikawa, Atushi; Fujimoto, Shouji; Watanabe, Tsutomu; Mizuno, Takayuki

2013-05-01

We discuss a mechanism through which inversion symmetry (i.e., invariance of a joint probability density function under the exchange of variables) and Gibrat’s law generate power-law distributions with different tail exponents. Using a dataset of firm size variables, that is, tangible fixed assets K, the number of workers L, and sales Y, we confirm that these variables have power-law tails with different exponents, and that inversion symmetry and Gibrat’s law hold. Based on these findings, we argue that there exists a plane in the three dimensional space (logK,logL,logY), with respect to which the joint probability density function for the three variables is invariant under the exchange of variables. We provide empirical evidence suggesting that this plane fits the data well, and argue that the plane can be interpreted as the Cobb-Douglas production function, which has been extensively used in various areas of economics since it was first introduced almost a century ago.

Breakdown of the classical description of a local system.

PubMed

Kot, Eran; Grønbech-Jensen, Niels; Nielsen, Bo M; Neergaard-Nielsen, Jonas S; Polzik, Eugene S; Sørensen, Anders S

2012-06-08

We provide a straightforward demonstration of a fundamental difference between classical and quantum mechanics for a single local system: namely, the absence of a joint probability distribution of the position x and momentum p. Elaborating on a recently reported criterion by Bednorz and Belzig [Phys. Rev. A 83, 052113 (2011)] we derive a simple criterion that must be fulfilled for any joint probability distribution in classical physics. We demonstrate the violation of this criterion using the homodyne measurement of a single photon state, thus proving a straightforward signature of the breakdown of a classical description of the underlying state. Most importantly, the criterion used does not rely on quantum mechanics and can thus be used to demonstrate nonclassicality of systems not immediately apparent to exhibit quantum behavior. The criterion is directly applicable to any system described by the continuous canonical variables x and p, such as a mechanical or an electrical oscillator and a collective spin of a large ensemble.

Outcome and predicting factors of single and multiple intra-articular corticosteroid injections in children with juvenile idiopathic arthritis.

PubMed

Lanni, Stefano; Bertamino, Marta; Consolaro, Alessandro; Pistorio, Angela; Magni-Manzoni, Silvia; Galasso, Roberta; Lattanzi, Bianca; Calvo-Aranda, Enrique; Martini, Alberto; Ravelli, Angelo

2011-09-01

To investigate the efficacy of IA CS (IAC) therapy in single and multiple joints in children with JIA and to seek for predictors of synovitis flare. The clinical charts of patients who received their first IAC injection between January 2002 and December 2008 were reviewed. The CS used was triamcinolone hexacetonide for large joints and methylprednisolone acetate for small or difficult to access joints. Patients were stratified as follows: one joint injected; two joints injected; and three or more joints injected. Predictors included sex, age at disease onset, JIA category, age and disease duration, ANA status, iridocyclitis, general anaesthesia, number and type of injected joints, acute-phase reactants and concomitant MTX therapy. The cumulative probability of survival without synovitis flare for patients injected in one, two, or three or more joints was 70, 45 and 44%, respectively, at 1 year; 61, 32 and 30%, respectively, at 2 years; and 37, 22 and 19%, respectively, at 3 years. On Cox regression analysis, positive CRP, negative ANA and injection in the ankle were the strongest predictors for synovitis flare. The only significant side effect was skin hypopigmentation or s.c. atrophy, which occurred in <2% of patients. IAC therapy-induced sustained remission of synovitis in a substantial proportion of patients injected either in single or multiple joints, with a good safety profile. The risk of synovitis flare was higher in patients who had positive CRP, negative ANA and were injected in the ankle.

General methods for sensitivity analysis of equilibrium dynamics in patch occupancy models

USGS Publications Warehouse

Miller, David A.W.

2012-01-01

Sensitivity analysis is a useful tool for the study of ecological models that has many potential applications for patch occupancy modeling. Drawing from the rich foundation of existing methods for Markov chain models, I demonstrate new methods for sensitivity analysis of the equilibrium state dynamics of occupancy models. Estimates from three previous studies are used to illustrate the utility of the sensitivity calculations: a joint occupancy model for a prey species, its predators, and habitat used by both; occurrence dynamics from a well-known metapopulation study of three butterfly species; and Golden Eagle occupancy and reproductive dynamics. I show how to deal efficiently with multistate models and how to calculate sensitivities involving derived state variables and lower-level parameters. In addition, I extend methods to incorporate environmental variation by allowing for spatial and temporal variability in transition probabilities. The approach used here is concise and general and can fully account for environmental variability in transition parameters. The methods can be used to improve inferences in occupancy studies by quantifying the effects of underlying parameters, aiding prediction of future system states, and identifying priorities for sampling effort.

Bivariate frequency analysis of rainfall intensity and duration for urban stormwater infrastructure design

NASA Astrophysics Data System (ADS)

Jun, Changhyun; Qin, Xiaosheng; Gan, Thian Yew; Tung, Yeou-Koung; De Michele, Carlo

2017-10-01

This study presents a storm-event based bivariate frequency analysis approach to determine design rainfalls in which, the number, intensity and duration of actual rainstorm events were considered. To derive more realistic design storms, the occurrence probability of an individual rainstorm event was determined from the joint distribution of storm intensity and duration through a copula model. Hourly rainfall data were used at three climate stations respectively located in Singapore, South Korea and Canada. It was found that the proposed approach could give a more realistic description of rainfall characteristics of rainstorm events and design rainfalls. As results, the design rainfall quantities from actual rainstorm events at the three studied sites are consistently lower than those obtained from the conventional rainfall depth-duration-frequency (DDF) method, especially for short-duration storms (such as 1-h). It results from occurrence probabilities of each rainstorm event and a different angle for rainfall frequency analysis, and could offer an alternative way of describing extreme rainfall properties and potentially help improve the hydrologic design of stormwater management facilities in urban areas.

Maximum likelihood sequence estimation for optical complex direct modulation.

PubMed

Che, Di; Yuan, Feng; Shieh, William

2017-04-17

Semiconductor lasers are versatile optical transmitters in nature. Through the direct modulation (DM), the intensity modulation is realized by the linear mapping between the injection current and the light power, while various angle modulations are enabled by the frequency chirp. Limited by the direct detection, DM lasers used to be exploited only as 1-D (intensity or angle) transmitters by suppressing or simply ignoring the other modulation. Nevertheless, through the digital coherent detection, simultaneous intensity and angle modulations (namely, 2-D complex DM, CDM) can be realized by a single laser diode. The crucial technique of CDM is the joint demodulation of intensity and differential phase with the maximum likelihood sequence estimation (MLSE), supported by a closed-form discrete signal approximation of frequency chirp to characterize the MLSE transition probability. This paper proposes a statistical method for the transition probability to significantly enhance the accuracy of the chirp model. Using the statistical estimation, we demonstrate the first single-channel 100-Gb/s PAM-4 transmission over 1600-km fiber with only 10G-class DM lasers.

Slant path rain attenuation and path diversity statistics obtained through radar modeling of rain structure

NASA Technical Reports Server (NTRS)

Goldhirsh, J.

1984-01-01

Single and joint terminal slant path attenuation statistics at frequencies of 28.56 and 19.04 GHz have been derived, employing a radar data base obtained over a three-year period at Wallops Island, VA. Statistics were independently obtained for path elevation angles of 20, 45, and 90 deg for purposes of examining how elevation angles influences both single-terminal and joint probability distributions. Both diversity gains and autocorrelation function dependence on site spacing and elevation angles were determined employing the radar modeling results. Comparisons with other investigators are presented. An independent path elevation angle prediction technique was developed and demonstrated to fit well with the radar-derived single and joint terminal radar-derived cumulative fade distributions at various elevation angles.

Discrete-time moment closure models for epidemic spreading in populations of interacting individuals.

PubMed

Frasca, Mattia; Sharkey, Kieran J

2016-06-21

Understanding the dynamics of spread of infectious diseases between individuals is essential for forecasting the evolution of an epidemic outbreak or for defining intervention policies. The problem is addressed by many approaches including stochastic and deterministic models formulated at diverse scales (individuals, populations) and different levels of detail. Here we consider discrete-time SIR (susceptible-infectious-removed) dynamics propagated on contact networks. We derive a novel set of 'discrete-time moment equations' for the probability of the system states at the level of individual nodes and pairs of nodes. These equations form a set which we close by introducing appropriate approximations of the joint probabilities appearing in them. For the example case of SIR processes, we formulate two types of model, one assuming statistical independence at the level of individuals and one at the level of pairs. From the pair-based model we then derive a model at the level of the population which captures the behavior of epidemics on homogeneous random networks. With respect to their continuous-time counterparts, the models include a larger number of possible transitions from one state to another and joint probabilities with a larger number of individuals. The approach is validated through numerical simulation over different network topologies. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Statistics of cosmic density profiles from perturbation theory

NASA Astrophysics Data System (ADS)

Bernardeau, Francis; Pichon, Christophe; Codis, Sandrine

2014-11-01

The joint probability distribution function (PDF) of the density within multiple concentric spherical cells is considered. It is shown how its cumulant generating function can be obtained at tree order in perturbation theory as the Legendre transform of a function directly built in terms of the initial moments. In the context of the upcoming generation of large-scale structure surveys, it is conjectured that this result correctly models such a function for finite values of the variance. Detailed consequences of this assumption are explored. In particular the corresponding one-cell density probability distribution at finite variance is computed for realistic power spectra, taking into account its scale variation. It is found to be in agreement with Λ -cold dark matter simulations at the few percent level for a wide range of density values and parameters. Related explicit analytic expansions at the low and high density tails are given. The conditional (at fixed density) and marginal probability of the slope—the density difference between adjacent cells—and its fluctuations is also computed from the two-cell joint PDF; it also compares very well to simulations. It is emphasized that this could prove useful when studying the statistical properties of voids as it can serve as a statistical indicator to test gravity models and/or probe key cosmological parameters.

Uncertainty quantification of reaction mechanisms accounting for correlations introduced by rate rules and fitted Arrhenius parameters

DOE PAGES

Prager, Jens; Najm, Habib N.; Sargsyan, Khachik; ...

2013-02-23

We study correlations among uncertain Arrhenius rate parameters in a chemical model for hydrocarbon fuel-air combustion. We consider correlations induced by the use of rate rules for modeling reaction rate constants, as well as those resulting from fitting rate expressions to empirical measurements arriving at a joint probability density for all Arrhenius parameters. We focus on homogeneous ignition in a fuel-air mixture at constant-pressure. We also outline a general methodology for this analysis using polynomial chaos and Bayesian inference methods. Finally, we examine the uncertainties in both the Arrhenius parameters and in predicted ignition time, outlining the role of correlations,more » and considering both accuracy and computational efficiency.« less

Generation of degenerate, factorizable, pulsed squeezed light at telecom wavelengths

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gerrits, Thomas; Stevens, Martin; Baek, Burm

We characterize a periodically poled KTP crystal that produces an entangled, two-mode, squeezed state with orthogonal polarizations, nearly identical, factorizable frequency modes, and few photons in unwanted frequency modes. We focus the pump beam to create a nearly circular joint spectral probability distribution between the two modes. After disentangling the two modes, we observe Hong-Ou-Mandel interference with a raw (background corrected) visibility of 86% (95%) when an 8.6 nm bandwidth spectral filter is applied. We measure second order photon correlations of the entangled and disentangled squeezed states with both superconducting nanowire single-photon detectors and photon-number-resolving transition-edge sensors. Both methods agreemore » and verify that the detected modes contain the desired photon number distributions.« less

Statistical Characterization and Classification of Edge-Localized Plasma Instabilities

NASA Astrophysics Data System (ADS)

Webster, A. J.; Dendy, R. O.

2013-04-01

The statistics of edge-localized plasma instabilities (ELMs) in toroidal magnetically confined fusion plasmas are considered. From first principles, standard experimentally motivated assumptions are shown to determine a specific probability distribution for the waiting times between ELMs: the Weibull distribution. This is confirmed empirically by a statistically rigorous comparison with a large data set from the Joint European Torus. The successful characterization of ELM waiting times enables future work to progress in various ways. Here we present a quantitative classification of ELM types, complementary to phenomenological approaches. It also informs us about the nature of ELM processes, such as whether they are random or deterministic. The methods are extremely general and can be applied to numerous other quasiperiodic intermittent phenomena.

Joint sparse reconstruction of multi-contrast MRI images with graph based redundant wavelet transform.

PubMed

Lai, Zongying; Zhang, Xinlin; Guo, Di; Du, Xiaofeng; Yang, Yonggui; Guo, Gang; Chen, Zhong; Qu, Xiaobo

2018-05-03

Multi-contrast images in magnetic resonance imaging (MRI) provide abundant contrast information reflecting the characteristics of the internal tissues of human bodies, and thus have been widely utilized in clinical diagnosis. However, long acquisition time limits the application of multi-contrast MRI. One efficient way to accelerate data acquisition is to under-sample the k-space data and then reconstruct images with sparsity constraint. However, images are compromised at high acceleration factor if images are reconstructed individually. We aim to improve the images with a jointly sparse reconstruction and Graph-based redundant wavelet transform (GBRWT). First, a sparsifying transform, GBRWT, is trained to reflect the similarity of tissue structures in multi-contrast images. Second, joint multi-contrast image reconstruction is formulated as a ℓ 2, 1 norm optimization problem under GBRWT representations. Third, the optimization problem is numerically solved using a derived alternating direction method. Experimental results in synthetic and in vivo MRI data demonstrate that the proposed joint reconstruction method can achieve lower reconstruction errors and better preserve image structures than the compared joint reconstruction methods. Besides, the proposed method outperforms single image reconstruction with joint sparsity constraint of multi-contrast images. The proposed method explores the joint sparsity of multi-contrast MRI images under graph-based redundant wavelet transform and realizes joint sparse reconstruction of multi-contrast images. Experiment demonstrate that the proposed method outperforms the compared joint reconstruction methods as well as individual reconstructions. With this high quality image reconstruction method, it is possible to achieve the high acceleration factors by exploring the complementary information provided by multi-contrast MRI.

Movement of the sacroiliac joint during the Active Straight Leg Raise test in patients with long-lasting severe sacroiliac joint pain.

PubMed

Kibsgård, Thomas J; Röhrl, Stephan M; Røise, Olav; Sturesson, Bengt; Stuge, Britt

2017-08-01

The Active Straight Leg Raise is a functional test used in the assessment of pelvic girdle pain, and has shown to have good validity, reliability and responsiveness. The Active Straight Leg Raise is considered to examine the patients' ability to transfer load through the pelvis. It has been hypothesized that patients with pelvic girdle pain lack the ability to stabilize the pelvic girdle, probably due to instability or increased movement of the sacroiliac joint. This study examines the movement of the sacroiliac joints during the Active Straight Leg Raise in patients with pelvic girdle pain. Tantalum markers were inserted in the dorsal sacrum and ilium of 12 patients with long-lasting pelvic girdle pain scheduled for sacroiliac joint fusion surgery. Two to three weeks later movement of the sacroiliac joints during the Active Straight Leg Raise was measured with radiostereometric analysis. Small movements were detected. There was larger movement of the sacroiliac joint of the rested leg's sacroiliac joint compared to the lifted leg's side. A mean backward rotation of 0.8° and inward tilt of 0.3° were seen in the rested leg's sacroiliac joint. The movements of the sacroiliac joints during the Active Straight Leg Raise are small. There was a small backward rotation of the innominate bone relative to sacrum on the rested leg's side. Our findings contradict an earlier understanding that a forward rotation of the lifted leg's innominate occur while performing the Active Straight Leg Raise. Copyright © 2017. Published by Elsevier Ltd.

Joint nociceptor nerve activity and pain in an animal model of acute gout and its modulation by intra-articular hyaluronan

PubMed Central

Marcotti, Aida; Miralles, Ana; Dominguez, Eduardo; Pascual, Eliseo; Gomis, Ana; Belmonte, Carlos; de la Peña, Elvira

2018-01-01

Abstract The mechanisms whereby deposition of monosodium urate (MSU) crystals in gout activates nociceptors to induce joint pain are incompletely understood. We tried to reproduce the signs of painful gouty arthritis, injecting into the knee joint of rats suspensions containing amorphous or triclinic, needle MSU crystals. The magnitude of MSU-induced inflammation and pain behavior signs were correlated with the changes in firing frequency of spontaneous and movement-evoked nerve impulse activity recorded in single knee joint nociceptor saphenous nerve fibers. Joint swelling, mechanical and cold allodynia, and hyperalgesia appeared 3 hours after joint injection of MSU crystals. In parallel, spontaneous and movement-evoked joint nociceptor impulse activity raised significantly. Solutions containing amorphous or needle-shaped MSU crystals had similar inflammatory and electrophysiological effects. Intra-articular injection of hyaluronan (HA, Synvisc), a high-MW glycosaminoglycan present in the synovial fluid with analgesic effects in osteoarthritis, significantly reduced MSU-induced behavioral signs of pain and decreased the enhanced joint nociceptor activity. Our results support the interpretation that pain and nociceptor activation are not triggered by direct mechanical stimulation of nociceptors by MSU crystals, but are primarily caused by the release of excitatory mediators by inflammatory cells activated by MSU crystals. Intra-articular HA decreased behavioral and electrophysiological signs of pain, possibly through its viscoelastic filtering effect on the mechanical forces acting over sensitized joint sensory endings and probably also by a direct interaction of HA molecules with the transducing channels expressed in joint nociceptor terminals. PMID:29319609

Lithospheric architecture of NE China from joint Inversions of receiver functions and surface wave dispersion through Bayesian optimisation

NASA Astrophysics Data System (ADS)

Sebastian, Nita; Kim, Seongryong; Tkalčić, Hrvoje; Sippl, Christian

2017-04-01

The purpose of this study is to develop an integrated inference on the lithospheric structure of NE China using three passive seismic networks comprised of 92 stations. The NE China plain consists of complex lithospheric domains characterised by the co-existence of complex geodynamic processes such as crustal thinning, active intraplate cenozoic volcanism and low velocity anomalies. To estimate lithospheric structures with greater detail, we chose to perform the joint inversion of independent data sets such as receiver functions and surface wave dispersion curves (group and phase velocity). We perform a joint inversion based on principles of Bayesian transdimensional optimisation techniques (Kim etal., 2016). Unlike in the previous studies of NE China, the complexity of the model is determined from the data in the first stage of the inversion, and the data uncertainty is computed based on Bayesian statistics in the second stage of the inversion. The computed crustal properties are retrieved from an ensemble of probable models. We obtain major structural inferences with well constrained absolute velocity estimates, which are vital for inferring properties of the lithosphere and bulk crustal Vp/Vs ratio. The Vp/Vs estimate obtained from joint inversions confirms the high Vp/Vs ratio ( 1.98) obtained using the H-Kappa method beneath some stations. Moreover, we could confirm the existence of a lower crustal velocity beneath several stations (eg: station SHS) within the NE China plain. Based on these findings we attempt to identify a plausible origin for structural complexity. We compile a high-resolution 3D image of the lithospheric architecture of the NE China plain.

Blood management and transfusion strategies in 600 patients undergoing total joint arthroplasty: an analysis of pre-operative autologous blood donation

PubMed Central

Perazzo, Paolo; Viganò, Marco; de Girolamo, Laura; Verde, Francesco; Vinci, Anna; Banfi, Giuseppe; Romagnoli, Sergio

2013-01-01

Background Blood loss during total joint arthroplasty strongly influences the time to recover after surgery and the quality of the recovery. Blood conservation strategies such as pre-operative autologous blood donation and post-operative cell salvage are intended to avoid allogeneic blood transfusions and their associated risks. Although widely investigated, the real effectiveness of these alternative transfusion practices remains controversial. Materials and methods The surgery reports of 600 patients undergoing total joint arthroplasty (312 hip and 288 knee replacements) were retrospectively reviewed to assess transfusion needs and related blood management at our institute. Evaluation parameters included post-operative blood loss, haemoglobin concentration measured at different time points, ASA score, and blood transfusion strategies. Results Autologous blood donation increased the odds of receiving a red blood cell transfusion. Reinfusion by a cell salvage system of post-operative shed blood was found to limit adverse effects in cases of severe post-operative blood loss. The peri-operative net decrease in haemoglobin concentration was higher in patients who had predeposited autologous blood than in those who had not. Discussion The strengths of this study are the high number of cases and the standardised procedures, all operations having been performed by a single orthopaedic surgeon and a single anaesthesiologist. Our data suggest that a pre-operative autologous donation programme may often be useless, if not harmful. Conversely, the use of a cell salvage system may be effective in reducing the impact of blood transfusion on a patient’s physiological status. Basal haemoglobin concentration emerged as a useful indicator of transfusion probability in total joint replacement procedures. PMID:23736922

Probabilistic liquefaction hazard analysis at liquefied sites of 1956 Dunaharaszti earthquake, in Hungary

NASA Astrophysics Data System (ADS)

Győri, Erzsébet; Gráczer, Zoltán; Tóth, László; Bán, Zoltán; Horváth, Tibor

2017-04-01

Liquefaction potential evaluations are generally made to assess the hazard from specific scenario earthquakes. These evaluations may estimate the potential in a binary fashion (yes/no), define a factor of safety or predict the probability of liquefaction given a scenario event. Usually the level of ground shaking is obtained from the results of PSHA. Although it is determined probabilistically, a single level of ground shaking is selected and used within the liquefaction potential evaluation. In contrary, the fully probabilistic liquefaction potential assessment methods provide a complete picture of liquefaction hazard, namely taking into account the joint probability distribution of PGA and magnitude of earthquake scenarios; both of which are key inputs in the stress-based simplified methods. Kramer and Mayfield (2007) has developed a fully probabilistic liquefaction potential evaluation method using a performance-based earthquake engineering (PBEE) framework. The results of the procedure are the direct estimate of the return period of liquefaction and the liquefaction hazard curves in function of depth. The method combines the disaggregation matrices computed for different exceedance frequencies during probabilistic seismic hazard analysis with one of the recent models for the conditional probability of liquefaction. We have developed a software for the assessment of performance-based liquefaction triggering on the basis of Kramer and Mayfield method. Originally the SPT based probabilistic method of Cetin et al. (2004) was built-in into the procedure of Kramer and Mayfield to compute the conditional probability however there is no professional consensus about its applicability. Therefore we have included not only Cetin's method but Idriss and Boulanger (2012) SPT based moreover Boulanger and Idriss (2014) CPT based procedures into our computer program. In 1956, a damaging earthquake of magnitude 5.6 occurred in Dunaharaszti, in Hungary. Its epicenter was located about 5 km from the southern boundary of Budapest. The quake caused serious damages in the epicentral area and in the southern districts of the capital. The epicentral area of the earthquake is located along the Danube River. Sand boils were observed in some locations that indicated the occurrence of liquefaction. Because their exact locations were recorded at the time of the earthquake, in situ geotechnical measurements (CPT and SPT) could be performed at two (Dunaharaszti and Taksony) sites. The different types of measurements enabled the probabilistic liquefaction hazard computations at the two studied sites. We have compared the return periods of liquefaction that were computed using different built-in simplified stress based methods.

Time-varying SMART design and data analysis methods for evaluating adaptive intervention effects.

PubMed

Dai, Tianjiao; Shete, Sanjay

2016-08-30

In a standard two-stage SMART design, the intermediate response to the first-stage intervention is measured at a fixed time point for all participants. Subsequently, responders and non-responders are re-randomized and the final outcome of interest is measured at the end of the study. To reduce the side effects and costs associated with first-stage interventions in a SMART design, we proposed a novel time-varying SMART design in which individuals are re-randomized to the second-stage interventions as soon as a pre-fixed intermediate response is observed. With this strategy, the duration of the first-stage intervention will vary. We developed a time-varying mixed effects model and a joint model that allows for modeling the outcomes of interest (intermediate and final) and the random durations of the first-stage interventions simultaneously. The joint model borrows strength from the survival sub-model in which the duration of the first-stage intervention (i.e., time to response to the first-stage intervention) is modeled. We performed a simulation study to evaluate the statistical properties of these models. Our simulation results showed that the two modeling approaches were both able to provide good estimations of the means of the final outcomes of all the embedded interventions in a SMART. However, the joint modeling approach was more accurate for estimating the coefficients of first-stage interventions and time of the intervention. We conclude that the joint modeling approach provides more accurate parameter estimates and a higher estimated coverage probability than the single time-varying mixed effects model, and we recommend the joint model for analyzing data generated from time-varying SMART designs. In addition, we showed that the proposed time-varying SMART design is cost-efficient and equally effective in selecting the optimal embedded adaptive intervention as the standard SMART design.

Process, System, Causality, and Quantum Mechanics: A Psychoanalysis of Animal Faith

NASA Astrophysics Data System (ADS)

Etter, Tom; Noyes, H. Pierre

We shall argue in this paper that a central piece of modern physics does not really belong to physics at all but to elementary probability theory. Given a joint probability distribution J on a set of random variables containing x and y, define a link between x and y to be the condition x=y on J. Define the {\\it state} D of a link x=y as the joint probability distribution matrix on x and y without the link. The two core laws of quantum mechanics are the Born probability rule, and the unitary dynamical law whose best known form is the Schrodinger's equation. Von Neumann formulated these two laws in the language of Hilbert space as prob(P) = trace(PD) and D'T = TD respectively, where P is a projection, D and D' are (von Neumann) density matrices, and T is a unitary transformation. We'll see that if we regard link states as density matrices, the algebraic forms of these two core laws occur as completely general theorems about links. When we extend probability theory by allowing cases to count negatively, we find that the Hilbert space framework of quantum mechanics proper emerges from the assumption that all D's are symmetrical in rows and columns. On the other hand, Markovian systems emerge when we assume that one of every linked variable pair has a uniform probability distribution. By representing quantum and Markovian structure in this way, we see clearly both how they differ, and also how they can coexist in natural harmony with each other, as they must in quantum measurement, which we'll examine in some detail. Looking beyond quantum mechanics, we see how both structures have their special places in a much larger continuum of formal systems that we have yet to look for in nature.

A short walk in quantum probability.

PubMed

Hudson, Robin

2018-04-28

This is a personal survey of aspects of quantum probability related to the Heisenberg commutation relation for canonical pairs. Using the failure, in general, of non-negativity of the Wigner distribution for canonical pairs to motivate a more satisfactory quantum notion of joint distribution, we visit a central limit theorem for such pairs and a resulting family of quantum planar Brownian motions which deform the classical planar Brownian motion, together with a corresponding family of quantum stochastic areas.This article is part of the themed issue 'Hilbert's sixth problem'. © 2018 The Author(s).

Correlation signatures of wet soils and snows. [algorithm development and computer programming

NASA Technical Reports Server (NTRS)

Phillips, M. R.

1972-01-01

Interpretation, analysis, and development of algorithms have provided the necessary computational programming tools for soil data processing, data handling and analysis. Algorithms that have been developed thus far, are adequate and have been proven successful for several preliminary and fundamental applications such as software interfacing capabilities, probability distributions, grey level print plotting, contour plotting, isometric data displays, joint probability distributions, boundary mapping, channel registration and ground scene classification. A description of an Earth Resources Flight Data Processor, (ERFDP), which handles and processes earth resources data under a users control is provided.

Dichotomous versus semi-quantitative scoring of ultrasound joint inflammation in rheumatoid arthritis using novel individualized joint selection methods.

PubMed

Tan, York Kiat; Allen, John C; Lye, Weng Kit; Conaghan, Philip G; Chew, Li-Ching; Thumboo, Julian

2017-05-01

The aim of the study is to compare the responsiveness of two joint inflammation scoring systems (dichotomous scoring (DS) versus semi-quantitative scoring (SQS)) using novel individualized ultrasound joint selection methods and existing ultrasound joint selection methods. Responsiveness measured by the standardized response means (SRMs) using the DS and the SQS system (for both the novel and existing ultrasound joint selection methods) was derived using the baseline and the 3-month total inflammatory scores from 20 rheumatoid arthritis patients. The relative SRM gain ratios (SRM-Gains) for both scoring system (DS and SQS) comparing the novel to the existing methods were computed. Both scoring systems (DS and SQS) demonstrated substantial SRM-Gains (ranged from 3.31 to 5.67 for the DS system and ranged from 1.82 to 3.26 for the SQS system). The SRMs using the novel methods ranged from 0.94 to 1.36 for the DS system and ranged from 0.89 to 1.11 for the SQS system. The SRMs using the existing methods ranged from 0.24 to 0.32 for the DS system and ranged from 0.34 to 0.49 for the SQS system. The DS system appears to achieve high responsiveness comparable to SQS for the novel individualized ultrasound joint selection methods.

Experimental Robot Position Sensor Fault Tolerance Using Accelerometers and Joint Torque Sensors

NASA Technical Reports Server (NTRS)

Aldridge, Hal A.; Juang, Jer-Nan

1997-01-01

Robot systems in critical applications, such as those in space and nuclear environments, must be able to operate during component failure to complete important tasks. One failure mode that has received little attention is the failure of joint position sensors. Current fault tolerant designs require the addition of directly redundant position sensors which can affect joint design. The proposed method uses joint torque sensors found in most existing advanced robot designs along with easily locatable, lightweight accelerometers to provide a joint position sensor fault recovery mode. This mode uses the torque sensors along with a virtual passive control law for stability and accelerometers for joint position information. Two methods for conversion from Cartesian acceleration to joint position based on robot kinematics, not integration, are presented. The fault tolerant control method was tested on several joints of a laboratory robot. The controllers performed well with noisy, biased data and a model with uncertain parameters.

Framing 100-year overflowing and overtopping marine submersion hazard resulting from the propagation of 100-year joint hydrodynamic conditions

NASA Astrophysics Data System (ADS)

Nicolae Lerma, A.; Bulteau, T.; Elineau, S.; Paris, F.; Pedreros, R.

2016-12-01

Marine submersion is an increasing concern for coastal cities as urban development reinforces their vulnerabilities while climate change is likely to foster the frequency and magnitude of submersions. Characterising the coastal flooding hazard is therefore of paramount importance to ensure the security of people living in such places and for coastal planning. A hazard is commonly defined as an adverse phenomenon, often represented by a magnitude of a variable of interest (e.g. flooded area), hereafter called response variable, associated with a probability of exceedance or, alternatively, a return period. Characterising the coastal flooding hazard consists in finding the correspondence between the magnitude and the return period. The difficulty lies in the fact that the assessment is usually performed using physical numerical models taking as inputs scenarios composed by multiple forcing conditions that are most of the time interdependent. Indeed, a time series of the response variable is usually not available so we have to deal instead with time series of forcing variables (e.g. water level, waves). Thus, the problem is twofold: on the one hand, the definition of scenarios is a multivariate matter; on the other hand, it is tricky and approximate to associate the resulting response, being the output of the physical numerical model, to the return period defined for the scenarios. In this study, we illustrate the problem on the district of Leucate, located in the French Mediterranean coast. A multivariate extreme value analysis of waves and water levels is performed offshore using a conditional extreme model, then two different methods are used to define and select 100-year scenarios of forcing variables: one based on joint exceedance probability contours, a method classically used in coastal risks studies, the other based on environmental contours, which are commonly used in the field of structure design engineering. We show that these two methods enable one to frame the true 100-year response variable. The selected scenarios are propagated to the shore through a high resolution flood modelling coupling overflowing and overtopping processes. Results in terms of inundated areas and inland water volumes are finally compared for the two methods, giving upper and lower bounds for the true response variables.

Intelligent screening of electrofusion-polyethylene joints based on a thermal NDT method

NASA Astrophysics Data System (ADS)

Doaei, Marjan; Tavallali, M. Sadegh

2018-05-01

The combinations of infrared thermal images and artificial intelligence methods have opened new avenues for pushing the boundaries of available testing methods. Hence, in the current study, a novel thermal non-destructive testing method for polyethylene electrofusion joints was combined with k-means clustering algorithms as an intelligent screening tool. The experiments focused on ovality of pipes in the coupler, as well as misalignment of pipes-couplers in 25 mm diameter joints. The temperature responses of each joint to an internal heat pulse were recorded by an IR thermal camera, and further processed to identify the faulty joints. The results represented clustering accuracy of 92%, as well as more than 90% abnormality detection capabilities.

The Waist Width of Skis Influences the Kinematics of the Knee Joint in Alpine Skiing

PubMed Central

Zorko, Martin; Nemec, Bojan; Babič, Jan; Lešnik, Blaz; Supej, Matej

2015-01-01

Recently alpine skis with a wider waist width, which medially shifts the contact between the ski edge and the snow while turning, have appeared on the market. The aim of this study was to determine the knee joint kinematics during turning while using skis of different waist widths (65mm, 88mm, 110mm). Six highly skilled skiers performed ten turns on a predefined course (similar to a giant slalom course). The relation of femur and tibia in the sagital, frontal and coronal planes was captured by using an inertial motion capture suit, and Global Navigation Satellite System was used to determine the skiers’ trajectories. With respect of the outer ski the knee joint flexion, internal rotation and abduction significantly decreased with the increase of the ski waist width for the greatest part of the ski turn. The greatest abduction with the narrow ski and the greatest external rotation (lowest internal rotation) with the wide ski are probably the reflection of two different strategies of coping the biomechanical requirements in the ski turn. These changes in knee kinematics were most probably due to an active adaptation of the skier to the changed biomechanical conditions using wider skis. The results indicated that using skis with large waist widths on hard, frozen surfaces could bring the knee joint unfavorably closer to the end of the range of motion in transversal and frontal planes as well as potentially increasing the risk of degenerative knee injuries. Key points The change in the skis’ waist width caused a change in the knee joint movement strategies, which had a tendency to adapt the skier to different biomechanical conditions. The use of wider skis or, in particular, skis with a large waist width, on a hard or frozen surface, could unfavourably bring the knee joint closer to the end of range of motion in transversal and frontal planes as well as may potentially increase the risk of degenerative knee injuries. The overall results of the abduction and internal rotation in respect to turn radii and ground reaction forces indicated that the knee joint movements are likely one of the key points in alpine skiing techniques. However, the skiing equipment used can still significantly influence the movement strategy. PMID:26336348

Malignant Peritoneal Mesothelioma: Prognostic Factors and Oncologic Outcome Analysis

PubMed Central

Magge, Deepa; Zenati, Mazen S.; Austin, Frances; Mavanur, Arun; Sathaiah, Magesh; Ramalingam, Lekshmi; Jones, Heather; Zureikat, Amer H.; Holtzman, Matthew; Ahrendt, Steven; Pingpank, James; Zeh, Herbert J.; Bartlett, David L.; Choudry, Haroon A.

2014-01-01

Background Most patients with malignant peritoneal mesothelioma (MPM) present with late-stage, unresectable disease that responds poorly to systemic chemotherapy while, at the same time, effective targeted therapies are lacking. We assessed the efficacy of cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemoperfusion (HIPEC) in MPM. Methods We prospectively analyzed 65 patients with MPM undergoing CRS/HIPEC between 2001 and 2010. Kaplan–Meier survival curves and multivariate Cox-regression models identified prognostic factors affecting oncologic outcomes. Results Adequate CRS was achieved in 56 patients (CC-0 = 35; CC-1 = 21), and median simplified peritoneal cancer index (SPCI) was 12. Pathologic assessment revealed predominantly epithelioid histology (81 %) and biphasic histology (8 %), while lymph node involvement was uncommon (8 %). Major postoperative morbidity (grade III/IV) occurred in 23 patients (35 %), and 60-day mortality rate was 6 %. With median follow-up of 37 months, median overall survival was 46.2 months, with 1-, 2-, and 5-year overall survival probability of 77, 57, and 39 %, respectively. Median progression-free survival was 13.9 months, with 1-, 2-, and 5-year disease failure probability of 47, 68, and 83 %, respectively. In a multivariate Cox-regression model, age at surgery, SPCI >15, incomplete cytoreduction (CC-2/3), aggressive histology (epithelioid, biphasic), and postoperative sepsis were joint significant predictors of poor survival (chi square = 42.8; p = 0.00001), while age at surgery, SPCI >15, incomplete cytoreduction (CC-2/3), and aggressive histology (epithelioid, biphasic) were joint significant predictors of disease progression (Chi square = 30.6; p = 0.00001). Conclusions Tumor histology, disease burden, and the ability to achieve adequate surgical cytoreduction are essential prognostic factors in MPM patients undergoing CRS/HIPEC. PMID:24322529

Benefits of listening to a recording of euphoric joint music making in polydrug abusers

PubMed Central

Fritz, Thomas Hans; Vogt, Marius; Lederer, Annette; Schneider, Lydia; Fomicheva, Eira; Schneider, Martha; Villringer, Arno

2015-01-01

Background and Aims: Listening to music can have powerful physiological and therapeutic effects. Some essential features of the mental mechanism underlying beneficial effects of music are probably strong physiological and emotional associations with music created during the act of music making. Here we tested this hypothesis in a clinical population of polydrug abusers in rehabilitation listening to a previously performed act of physiologically and emotionally intense music making. Methods: Psychological effects of listening to self-made music that was created in a previous musical feedback intervention were assessed. In this procedure, participants produced music with exercise machines (Jymmin) which modulate musical sounds. Results: The data showed a positive effect of listening to the recording of joint music making on self-efficacy, mood, and a readiness to engage socially. Furthermore, the data showed the powerful influence of context on how the recording evoked psychological benefits. The effects of listening to the self-made music were only observable when participants listened to their own performance first; listening to a control music piece first caused effects to deteriorate. We observed a positive correlation between participants’ mood and their desire to engage in social activities with their former training partners after listening to the self-made music. This shows that the observed effects of listening to the recording of the single musical feedback intervention are influenced by participants recapitulating intense pleasant social interactions during the Jymmin intervention. Conclusions: Listening to music that was the outcome of a previous musical feedback (Jymmin) intervention has beneficial psychological and probably social effects in patients that had suffered from polydrug addiction, increasing self-efficacy, mood, and a readiness to engage socially. These intervention effects, however, depend on the context in which the music recordings are presented. PMID:26124713

Investigation of 2-stage meta-analysis methods for joint longitudinal and time-to-event data through simulation and real data application.

PubMed

Sudell, Maria; Tudur Smith, Catrin; Gueyffier, François; Kolamunnage-Dona, Ruwanthi

2018-04-15

Joint modelling of longitudinal and time-to-event data is often preferred over separate longitudinal or time-to-event analyses as it can account for study dropout, error in longitudinally measured covariates, and correlation between longitudinal and time-to-event outcomes. The joint modelling literature focuses mainly on the analysis of single studies with no methods currently available for the meta-analysis of joint model estimates from multiple studies. We propose a 2-stage method for meta-analysis of joint model estimates. These methods are applied to the INDANA dataset to combine joint model estimates of systolic blood pressure with time to death, time to myocardial infarction, and time to stroke. Results are compared to meta-analyses of separate longitudinal or time-to-event models. A simulation study is conducted to contrast separate versus joint analyses over a range of scenarios. Using the real dataset, similar results were obtained by using the separate and joint analyses. However, the simulation study indicated a benefit of use of joint rather than separate methods in a meta-analytic setting where association exists between the longitudinal and time-to-event outcomes. Where evidence of association between longitudinal and time-to-event outcomes exists, results from joint models over standalone analyses should be pooled in 2-stage meta-analyses. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Controlling the joint local false discovery rate is more powerful than meta-analysis methods in joint analysis of summary statistics from multiple genome-wide association studies.

PubMed

Jiang, Wei; Yu, Weichuan

2017-02-15

In genome-wide association studies (GWASs) of common diseases/traits, we often analyze multiple GWASs with the same phenotype together to discover associated genetic variants with higher power. Since it is difficult to access data with detailed individual measurements, summary-statistics-based meta-analysis methods have become popular to jointly analyze datasets from multiple GWASs. In this paper, we propose a novel summary-statistics-based joint analysis method based on controlling the joint local false discovery rate (Jlfdr). We prove that our method is the most powerful summary-statistics-based joint analysis method when controlling the false discovery rate at a certain level. In particular, the Jlfdr-based method achieves higher power than commonly used meta-analysis methods when analyzing heterogeneous datasets from multiple GWASs. Simulation experiments demonstrate the superior power of our method over meta-analysis methods. Also, our method discovers more associations than meta-analysis methods from empirical datasets of four phenotypes. The R-package is available at: http://bioinformatics.ust.hk/Jlfdr.html . eeyu@ust.hk. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Benefits of Accumulating versus Diminishing Cues in Recall

ERIC Educational Resources Information Center

Finley, Jason R.; Benjamin, Aaron S.; Hays, Matthew J.; Bjork, Robert A.; Kornell, Nate

2011-01-01

Optimizing learning over multiple retrieval opportunities requires a joint consideration of both the probability and the mnemonic value of a successful retrieval. Previous research has addressed this trade-off by manipulating the schedule of practice trials, suggesting that a pattern of increasingly long lags--"expanding retrieval practice"--may…

Modification and Adaptation of the Program Evaluation Standards in Saudi Arabia

ERIC Educational Resources Information Center

Alyami, Mohammed

2013-01-01

The Joint Committee on Standards for Educational Evaluation's Program Evaluation Standards is probably the most recognized and applied set of evaluation standards globally. The most recent edition of The Program Evaluation Standards includes five categories and 30 standards. The five categories are Utility, Feasibility, Propriety, Accuracy, and…

Bayesian Estimation of the DINA Model with Gibbs Sampling

ERIC Educational Resources Information Center

Culpepper, Steven Andrew

2015-01-01

A Bayesian model formulation of the deterministic inputs, noisy "and" gate (DINA) model is presented. Gibbs sampling is employed to simulate from the joint posterior distribution of item guessing and slipping parameters, subject attribute parameters, and latent class probabilities. The procedure extends concepts in Béguin and Glas,…

Recognizing human actions by learning and matching shape-motion prototype trees.

PubMed

Jiang, Zhuolin; Lin, Zhe; Davis, Larry S

2012-03-01

A shape-motion prototype-based approach is introduced for action recognition. The approach represents an action as a sequence of prototypes for efficient and flexible action matching in long video sequences. During training, an action prototype tree is learned in a joint shape and motion space via hierarchical K-means clustering and each training sequence is represented as a labeled prototype sequence; then a look-up table of prototype-to-prototype distances is generated. During testing, based on a joint probability model of the actor location and action prototype, the actor is tracked while a frame-to-prototype correspondence is established by maximizing the joint probability, which is efficiently performed by searching the learned prototype tree; then actions are recognized using dynamic prototype sequence matching. Distance measures used for sequence matching are rapidly obtained by look-up table indexing, which is an order of magnitude faster than brute-force computation of frame-to-frame distances. Our approach enables robust action matching in challenging situations (such as moving cameras, dynamic backgrounds) and allows automatic alignment of action sequences. Experimental results demonstrate that our approach achieves recognition rates of 92.86 percent on a large gesture data set (with dynamic backgrounds), 100 percent on the Weizmann action data set, 95.77 percent on the KTH action data set, 88 percent on the UCF sports data set, and 87.27 percent on the CMU action data set.

Joint probability of statistical success of multiple phase III trials.

PubMed

Zhang, Jianliang; Zhang, Jenny J

2013-01-01

In drug development, after completion of phase II proof-of-concept trials, the sponsor needs to make a go/no-go decision to start expensive phase III trials. The probability of statistical success (PoSS) of the phase III trials based on data from earlier studies is an important factor in that decision-making process. Instead of statistical power, the predictive power of a phase III trial, which takes into account the uncertainty in the estimation of treatment effect from earlier studies, has been proposed to evaluate the PoSS of a single trial. However, regulatory authorities generally require statistical significance in two (or more) trials for marketing licensure. We show that the predictive statistics of two future trials are statistically correlated through use of the common observed data from earlier studies. Thus, the joint predictive power should not be evaluated as a simplistic product of the predictive powers of the individual trials. We develop the relevant formulae for the appropriate evaluation of the joint predictive power and provide numerical examples. Our methodology is further extended to the more complex phase III development scenario comprising more than two (K > 2) trials, that is, the evaluation of the PoSS of at least k₀ (k₀≤ K) trials from a program of K total trials. Copyright © 2013 John Wiley & Sons, Ltd.

Analytical approach to an integrate-and-fire model with spike-triggered adaptation

NASA Astrophysics Data System (ADS)

Schwalger, Tilo; Lindner, Benjamin

2015-12-01

The calculation of the steady-state probability density for multidimensional stochastic systems that do not obey detailed balance is a difficult problem. Here we present the analytical derivation of the stationary joint and various marginal probability densities for a stochastic neuron model with adaptation current. Our approach assumes weak noise but is valid for arbitrary adaptation strength and time scale. The theory predicts several effects of adaptation on the statistics of the membrane potential of a tonically firing neuron: (i) a membrane potential distribution with a convex shape, (ii) a strongly increased probability of hyperpolarized membrane potentials induced by strong and fast adaptation, and (iii) a maximized variability associated with the adaptation current at a finite adaptation time scale.

Influences of Patellofemoral Pain and Fatigue in Female Dancers during Ballet Jump-Landing.

PubMed

Peng, H-T; Chen, W C; Kernozek, T W; Kim, K; Song, C-Y

2015-08-01

This study investigated the influence of patellofemoral pain (PFP) and fatigue on lower-extremity joint biomechanics in female dancers during consecutive simple ground échappé. 3-dimensional joint mechanics were analyzed from the no-fatigue to fatigue conditions. 2-way mixed ANOVAs were used to compare the differences of the kinematic and kinetic variables between groups and conditions. Group main effects were seen in increased jump height (p=0.03), peak vertical ground reaction force (p=0.01), knee joint power absorption (p=0.04), and patellofemoral joint stress (PFJS, p=0.04) for PFP group. Fatigue main effects were found for decreased jump height (p<0.01), decreased ankle plantarflexion at initial foot-ground contact (p=0.01), and decreased ankle displacement (p<0.01). Hip external rotation impulse and hip joint stiffness increased (both p<0.01) while knee extension and external rotation moment, and ankle joint power absorption decreased (p<0.01, p=0.02, p<0.01, respectively) after fatigue. The peak PFJS also decreased after fatigue (p<0.01). Female ballet dancers with PFP sustained great ground impact and loads on the knee probably due to higher jump height compared to the controls. All dancers presented diminished knee joint loading for the protective mechanism and endurance of ankle joint musculature required for the dissipation of loads and displayed a distal-to-proximal dissipation strategy after fatigue. © Georg Thieme Verlag KG Stuttgart · New York.

Joint modeling and registration of cell populations in cohorts of high-dimensional flow cytometric data.

PubMed

Pyne, Saumyadipta; Lee, Sharon X; Wang, Kui; Irish, Jonathan; Tamayo, Pablo; Nazaire, Marc-Danie; Duong, Tarn; Ng, Shu-Kay; Hafler, David; Levy, Ronald; Nolan, Garry P; Mesirov, Jill; McLachlan, Geoffrey J

2014-01-01

In biomedical applications, an experimenter encounters different potential sources of variation in data such as individual samples, multiple experimental conditions, and multivariate responses of a panel of markers such as from a signaling network. In multiparametric cytometry, which is often used for analyzing patient samples, such issues are critical. While computational methods can identify cell populations in individual samples, without the ability to automatically match them across samples, it is difficult to compare and characterize the populations in typical experiments, such as those responding to various stimulations or distinctive of particular patients or time-points, especially when there are many samples. Joint Clustering and Matching (JCM) is a multi-level framework for simultaneous modeling and registration of populations across a cohort. JCM models every population with a robust multivariate probability distribution. Simultaneously, JCM fits a random-effects model to construct an overall batch template--used for registering populations across samples, and classifying new samples. By tackling systems-level variation, JCM supports practical biomedical applications involving large cohorts. Software for fitting the JCM models have been implemented in an R package EMMIX-JCM, available from http://www.maths.uq.edu.au/~gjm/mix_soft/EMMIX-JCM/.

Statistical learning of action: the role of conditional probability.

PubMed

Meyer, Meredith; Baldwin, Dare

2011-12-01

Identification of distinct units within a continuous flow of human action is fundamental to action processing. Such segmentation may rest in part on statistical learning. In a series of four experiments, we examined what types of statistics people can use to segment a continuous stream involving many brief, goal-directed action elements. The results of Experiment 1 showed no evidence for sensitivity to conditional probability, whereas Experiment 2 displayed learning based on joint probability. In Experiment 3, we demonstrated that additional exposure to the input failed to engender sensitivity to conditional probability. However, the results of Experiment 4 showed that a subset of adults-namely, those more successful at identifying actions that had been seen more frequently than comparison sequences-were also successful at learning conditional-probability statistics. These experiments help to clarify the mechanisms subserving processing of intentional action, and they highlight important differences from, as well as similarities to, prior studies of statistical learning in other domains, including language.

Partial least squares density modeling (PLS-DM) - a new class-modeling strategy applied to the authentication of olives in brine by near-infrared spectroscopy.

PubMed

Oliveri, Paolo; López, M Isabel; Casolino, M Chiara; Ruisánchez, Itziar; Callao, M Pilar; Medini, Luca; Lanteri, Silvia

2014-12-03

A new class-modeling method, referred to as partial least squares density modeling (PLS-DM), is presented. The method is based on partial least squares (PLS), using a distance-based sample density measurement as the response variable. Potential function probability density is subsequently calculated on PLS scores and used, jointly with residual Q statistics, to develop efficient class models. The influence of adjustable model parameters on the resulting performances has been critically studied by means of cross-validation and application of the Pareto optimality criterion. The method has been applied to verify the authenticity of olives in brine from cultivar Taggiasca, based on near-infrared (NIR) spectra recorded on homogenized solid samples. Two independent test sets were used for model validation. The final optimal model was characterized by high efficiency and equilibrate balance between sensitivity and specificity values, if compared with those obtained by application of well-established class-modeling methods, such as soft independent modeling of class analogy (SIMCA) and unequal dispersed classes (UNEQ). Copyright © 2014 Elsevier B.V. All rights reserved.

A Bayesian inversion for slip distribution of 1 Apr 2007 Mw8.1 Solomon Islands Earthquake

NASA Astrophysics Data System (ADS)

Chen, T.; Luo, H.

2013-12-01

On 1 Apr 2007 the megathrust Mw8.1 Solomon Islands earthquake occurred in the southeast pacific along the New Britain subduction zone. 102 vertical displacement measurements over the southeastern end of the rupture zone from two field surveys after this event provide a unique constraint for slip distribution inversion. In conventional inversion method (such as bounded variable least squares) the smoothing parameter that determines the relative weight placed on fitting the data versus smoothing the slip distribution is often subjectively selected at the bend of the trade-off curve. Here a fully probabilistic inversion method[Fukuda,2008] is applied to estimate distributed slip and smoothing parameter objectively. The joint posterior probability density function of distributed slip and the smoothing parameter is formulated under a Bayesian framework and sampled with Markov chain Monte Carlo method. We estimate the spatial distribution of dip slip associated with the 1 Apr 2007 Solomon Islands earthquake with this method. Early results show a shallower dip angle than previous study and highly variable dip slip both along-strike and down-dip.

A methodological approach for the biomechanical cause analysis of golf-related lumbar spine injuries.

PubMed

Sim, Taeyong; Jang, Dong-Jin; Oh, Euichaul

2014-01-01

A new methodological approach employing mechanical work (MW) determination and relative portion of its elemental analysis was applied to investigate the biomechanical causes of golf-related lumbar spine injuries. Kinematic and kinetic parameters at the lumbar and lower limb joints were measured during downswing in 18 golfers. The MW at the lumbar joint (LJ) was smaller than at the right hip but larger than the MWs at other joints. The contribution of joint angular velocity (JAV) to MW was much greater than that of net muscle moment (NMM) at the LJ, whereas the contribution of NMM to MW was greater rather than or similar to that of JAV at other joints. Thus, the contribution of JAV to MW is likely more critical in terms of the probability of golf-related injury than that of NMM. The MW-based golf-related injury index (MWGII), proposed as the ratio of the contribution of JAV to MW to that of NMM, at the LJ (1.55) was significantly greater than those at other joints ( < 1.05). This generally corresponds to the most frequent occurrence of golf-related injuries around the lumbar spine. Therefore, both MW and MWGII should be considered when investigating the biomechanical causes of lumbar spine injuries.

Joint weak value for all order coupling using continuous variable and qubit probe

NASA Astrophysics Data System (ADS)

Kumari, Asmita; Pan, Alok Kumar; Panigrahi, Prasanta K.

2017-11-01

The notion of weak measurement in quantum mechanics has gained a significant and wide interest in realizing apparently counterintuitive quantum effects. In recent times, several theoretical and experimental works have been reported for demonstrating the joint weak value of two observables where the coupling strength is restricted to the second order. In this paper, we extend such a formulation by providing a complete treatment of joint weak measurement scenario for all-order-coupling for the observable satisfying A 2 = 𝕀 and A 2 = A, which allows us to reveal several hitherto unexplored features. By considering the probe state to be discrete as well as continuous variable, we demonstrate how the joint weak value can be inferred for any given strength of the coupling. A particularly interesting result we pointed out that even if the initial pointer state is uncorrelated, the single pointer displacement can provide the information about the joint weak value, if at least third order of the coupling is taken into account. As an application of our scheme, we provide an all-order-coupling treatment of the well-known Hardy paradox by considering the continuous as well as discrete meter states and show how the negative joint weak probabilities emerge in the quantum paradoxes at the weak coupling limit.

Predicting balance improvements following STARS treatments in chronic ankle instability participants.

PubMed

Wikstrom, Erik A; McKeon, Patrick O

2017-04-01

Sensory Targeted Ankle Rehabilitation Strategies that stimulate sensory receptors improve postural control in chronic ankle instability participants. However, not all participants have equal responses. Therefore, identifying predictors of treatment success is needed to improve clinician efficiency when treating chronic ankle instability. Therefore, the purpose was to identify predictors of successfully improving postural control in chronic ankle instability participants. Secondary data analysis. Fifty-nine participants with self-reported chronic ankle instability participated. The condition was defined as a history of at least two episodes of "giving way" within the past 6 months; and limitations in self-reported function as measured by the Foot and Ankle Ability Measure. Participants were randomized into three treatment groups (plantar massage, ankle joint mobilization, calf stretching) that received 6, 5-min treatment sessions over a 2-week period. The main outcome measure was treatment success, defined as a participant exceeding the minimal detectable change score for a clinician-oriented single limb balance test. Participants with ≥3 balance test errors had a 73% probability of treatment success following ankle joint mobilizations. Participants with a self-reported function between limb difference <16.07% and who made >2.5 errors had a 99% probability of treatment success following plantar massage. Those who sustained ≥11 ankle sprains had a 94% treatment success probability following calf stretching. Self-reported functional deficits, worse single limb balance, and number of previous ankle sprains are important characteristics when determining if chronic ankle instability participants will have an increased probability of treatment success. Copyright © 2016 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Damage prognosis of adhesively-bonded joints in laminated composite structural components of unmanned aerial vehicles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Farrar, Charles R; Gobbato, Maurizio; Conte, Joel

2009-01-01

The extensive use of lightweight advanced composite materials in unmanned aerial vehicles (UAVs) drastically increases the sensitivity to both fatigue- and impact-induced damage of their critical structural components (e.g., wings and tail stabilizers) during service life. The spar-to-skin adhesive joints are considered one of the most fatigue sensitive subcomponents of a lightweight UAV composite wing with damage progressively evolving from the wing root. This paper presents a comprehensive probabilistic methodology for predicting the remaining service life of adhesively-bonded joints in laminated composite structural components of UAVs. Non-destructive evaluation techniques and Bayesian inference are used to (i) assess the current statemore » of damage of the system and, (ii) update the probability distribution of the damage extent at various locations. A probabilistic model for future loads and a mechanics-based damage model are then used to stochastically propagate damage through the joint. Combined local (e.g., exceedance of a critical damage size) and global (e.g.. flutter instability) failure criteria are finally used to compute the probability of component failure at future times. The applicability and the partial validation of the proposed methodology are then briefly discussed by analyzing the debonding propagation, along a pre-defined adhesive interface, in a simply supported laminated composite beam with solid rectangular cross section, subjected to a concentrated load applied at mid-span. A specially developed Eliler-Bernoulli beam finite element with interlaminar slip along the damageable interface is used in combination with a cohesive zone model to study the fatigue-induced degradation in the adhesive material. The preliminary numerical results presented are promising for the future validation of the methodology.« less

Multivariate meta-analysis of individual participant data helped externally validate the performance and implementation of a prediction model.

PubMed

Snell, Kym I E; Hua, Harry; Debray, Thomas P A; Ensor, Joie; Look, Maxime P; Moons, Karel G M; Riley, Richard D

2016-01-01

Our aim was to improve meta-analysis methods for summarizing a prediction model's performance when individual participant data are available from multiple studies for external validation. We suggest multivariate meta-analysis for jointly synthesizing calibration and discrimination performance, while accounting for their correlation. The approach estimates a prediction model's average performance, the heterogeneity in performance across populations, and the probability of "good" performance in new populations. This allows different implementation strategies (e.g., recalibration) to be compared. Application is made to a diagnostic model for deep vein thrombosis (DVT) and a prognostic model for breast cancer mortality. In both examples, multivariate meta-analysis reveals that calibration performance is excellent on average but highly heterogeneous across populations unless the model's intercept (baseline hazard) is recalibrated. For the cancer model, the probability of "good" performance (defined by C statistic ≥0.7 and calibration slope between 0.9 and 1.1) in a new population was 0.67 with recalibration but 0.22 without recalibration. For the DVT model, even with recalibration, there was only a 0.03 probability of "good" performance. Multivariate meta-analysis can be used to externally validate a prediction model's calibration and discrimination performance across multiple populations and to evaluate different implementation strategies. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

Uncontrolled Manifold Reference Feedback Control of Multi-Joint Robot Arms

PubMed Central

Togo, Shunta; Kagawa, Takahiro; Uno, Yoji

2016-01-01

The brain must coordinate with redundant bodies to perform motion tasks. The aim of the present study is to propose a novel control model that predicts the characteristics of human joint coordination at a behavioral level. To evaluate the joint coordination, an uncontrolled manifold (UCM) analysis that focuses on the trial-to-trial variance of joints has been proposed. The UCM is a nonlinear manifold associated with redundant kinematics. In this study, we directly applied the notion of the UCM to our proposed control model called the “UCM reference feedback control.” To simplify the problem, the present study considered how the redundant joints were controlled to regulate a given target hand position. We considered a conventional method that pre-determined a unique target joint trajectory by inverse kinematics or any other optimization method. In contrast, our proposed control method generates a UCM as a control target at each time step. The target UCM is a subspace of joint angles whose variability does not affect the hand position. The joint combination in the target UCM is then selected so as to minimize the cost function, which consisted of the joint torque and torque change. To examine whether the proposed method could reproduce human-like joint coordination, we conducted simulation and measurement experiments. In the simulation experiments, a three-link arm with a shoulder, elbow, and wrist regulates a one-dimensional target of a hand through proposed method. In the measurement experiments, subjects performed a one-dimensional target-tracking task. The kinematics, dynamics, and joint coordination were quantitatively compared with the simulation data of the proposed method. As a result, the UCM reference feedback control could quantitatively reproduce the difference of the mean value for the end hand position between the initial postures, the peaks of the bell-shape tangential hand velocity, the sum of the squared torque, the mean value for the torque change, the variance components, and the index of synergy as well as the human subjects. We concluded that UCM reference feedback control can reproduce human-like joint coordination. The inference for motor control of the human central nervous system based on the proposed method was discussed. PMID:27462215

Anticipating abrupt shifts in temporal evolution of probability of eruption

NASA Astrophysics Data System (ADS)

Rohmer, J.; Loschetter, A.

2016-04-01

Estimating the probability of eruption by jointly accounting for different sources of monitoring parameters over time is a key component for volcano risk management. In the present study, we are interested in the transition from a state of low-to-moderate probability value to a state of high probability value. By using the data of MESIMEX exercise at the Vesuvius volcano, we investigated the potential for time-varying indicators related to the correlation structure or to the variability of the probability time series for detecting in advance this critical transition. We found that changes in the power spectra and in the standard deviation estimated over a rolling time window both present an abrupt increase, which marks the approaching shift. Our numerical experiments revealed that the transition from an eruption probability of 10-15% to > 70% could be identified up to 1-3 h in advance. This additional lead time could be useful to place different key services (e.g., emergency services for vulnerable groups, commandeering additional transportation means, etc.) on a higher level of alert before the actual call for evacuation.

Joint Center Estimation Using Single-Frame Optimization: Part 1: Numerical Simulation.

PubMed

Frick, Eric; Rahmatalla, Salam

2018-04-04

The biomechanical models used to refine and stabilize motion capture processes are almost invariably driven by joint center estimates, and any errors in joint center calculation carry over and can be compounded when calculating joint kinematics. Unfortunately, accurate determination of joint centers is a complex task, primarily due to measurements being contaminated by soft-tissue artifact (STA). This paper proposes a novel approach to joint center estimation implemented via sequential application of single-frame optimization (SFO). First, the method minimizes the variance of individual time frames’ joint center estimations via the developed variance minimization method to obtain accurate overall initial conditions. These initial conditions are used to stabilize an optimization-based linearization of human motion that determines a time-varying joint center estimation. In this manner, the complex and nonlinear behavior of human motion contaminated by STA can be captured as a continuous series of unique rigid-body realizations without requiring a complex analytical model to describe the behavior of STA. This article intends to offer proof of concept, and the presented method must be further developed before it can be reasonably applied to human motion. Numerical simulations were introduced to verify and substantiate the efficacy of the proposed methodology. When directly compared with a state-of-the-art inertial method, SFO reduced the error due to soft-tissue artifact in all cases by more than 45%. Instead of producing a single vector value to describe the joint center location during a motion capture trial as existing methods often do, the proposed method produced time-varying solutions that were highly correlated ( r > 0.82) with the true, time-varying joint center solution.

Control of early-formed vesicle cylinders on upper crustal prismatic jointing in compound pāhoehoe lavas of Elephanta Island, western Deccan Traps, India

NASA Astrophysics Data System (ADS)

Sheth, Hetu; Patel, Vanit; Samant, Hrishikesh

2017-08-01

Upper crustal prismatic joints and vesicle cylinders, common in pāhoehoe lava flows, form early and late, respectively, and are therefore independent features. However, small-scale compound pāhoehoe lava lobes on Elephanta Island (western Deccan Traps, India), which resemble S-type (spongy) pāhoehoe in some aspects, contain vesicle cylinders which apparently controlled the locations of upper crustal prismatic joints. The lobes are decimeters thick, did not experience inflation after emplacement, and solidified rapidly. They have meter-scale areas that are exceptionally rich in vesicle cylinders (up to 68 cylinders in 1 m2, with a mean spacing of 12.1 cm), separated by cylinder-free areas, and pervasive upper crustal prismatic jointing with T, curved T, and quadruple joint intersections. A majority (≥76.5%) of the cylinders are located exactly on joints or at joint intersections, and were not simply captured by downward growing joints, as the cylinders show no deflection in vertical section. We suggest that large numbers of cylinders originated in a layer of bubble-rich residual liquid at the top of a basal diktytaxitic crystal mush zone which was formed very early (probably within the first few minutes of the emplacement history). The locations where the rising cylinders breached the crust provided weak points or mechanical flaws towards which any existing joints (formed by thermal contraction) propagated. New joints may also have propagated outwards from the cylinders and linked up laterally. Some cylinders breached the crust between the joints, and thus formed a little later than most others. The Elephanta Island example reveals that, whereas thermal contraction is undoubtedly valid as a standard mechanism for forming upper crustal prismatic joints, abundant mechanical flaws (such as large concentrations of early-formed, crust-breaching vesicle cylinders) can also control the joint formation process.

General formulation of long-range degree correlations in complex networks

NASA Astrophysics Data System (ADS)

Fujiki, Yuka; Takaguchi, Taro; Yakubo, Kousuke

2018-06-01

We provide a general framework for analyzing degree correlations between nodes separated by more than one step (i.e., beyond nearest neighbors) in complex networks. One joint and four conditional probability distributions are introduced to fully describe long-range degree correlations with respect to degrees k and k' of two nodes and shortest path length l between them. We present general relations among these probability distributions and clarify the relevance to nearest-neighbor degree correlations. Unlike nearest-neighbor correlations, some of these probability distributions are meaningful only in finite-size networks. Furthermore, as a baseline to determine the existence of intrinsic long-range degree correlations in a network other than inevitable correlations caused by the finite-size effect, the functional forms of these probability distributions for random networks are analytically evaluated within a mean-field approximation. The utility of our argument is demonstrated by applying it to real-world networks.

Reward and uncertainty in exploration programs

NASA Technical Reports Server (NTRS)

Kaufman, G. M.; Bradley, P. G.

1971-01-01

A set of variables which are crucial to the economic outcome of petroleum exploration are discussed. These are treated as random variables; the values they assume indicate the number of successes that occur in a drilling program and determine, for a particular discovery, the unit production cost and net economic return if that reservoir is developed. In specifying the joint probability law for those variables, extreme and probably unrealistic assumptions are made. In particular, the different random variables are assumed to be independently distributed. Using postulated probability functions and specified parameters, values are generated for selected random variables, such as reservoir size. From this set of values the economic magnitudes of interest, net return and unit production cost are computed. This constitutes a single trial, and the procedure is repeated many times. The resulting histograms approximate the probability density functions of the variables which describe the economic outcomes of an exploratory drilling program.

Human joint motion estimation for electromyography (EMG)-based dynamic motion control.

PubMed

Zhang, Qin; Hosoda, Ryo; Venture, Gentiane

2013-01-01

This study aims to investigate a joint motion estimation method from Electromyography (EMG) signals during dynamic movement. In most EMG-based humanoid or prosthetics control systems, EMG features were directly or indirectly used to trigger intended motions. However, both physiological and nonphysiological factors can influence EMG characteristics during dynamic movements, resulting in subject-specific, non-stationary and crosstalk problems. Particularly, when motion velocity and/or joint torque are not constrained, joint motion estimation from EMG signals are more challenging. In this paper, we propose a joint motion estimation method based on muscle activation recorded from a pair of agonist and antagonist muscles of the joint. A linear state-space model with multi input single output is proposed to map the muscle activity to joint motion. An adaptive estimation method is proposed to train the model. The estimation performance is evaluated in performing a single elbow flexion-extension movement in two subjects. All the results in two subjects at two load levels indicate the feasibility and suitability of the proposed method in joint motion estimation. The estimation root-mean-square error is within 8.3% ∼ 10.6%, which is lower than that being reported in several previous studies. Moreover, this method is able to overcome subject-specific problem and compensate non-stationary EMG properties.

[Polyethylene disease].

PubMed

Sosna, A; Radonský, T; Pokorný, D; Veigl, D; Horák, Z; Jahoda, D

2003-01-01

The experience obtained during revision surgery and findings of polyethylene granulomas in surrounding tissues of replacement as well as marked differences in the viability of implants resulted in the study of polyethylene disease and its basic mechanisms producing the development of osteoaggressive granulomas. We investigated the morphology of particles and their number in tissues surrounding the implant. The aim of our study was to develop a method for the detection of polyethylene particles in tissues, to identify different types of wear and to assess factors that may influence the viability of joint arthroplasty in general. Every revizion of joint arthroplasty performed during the last five years was evaluated in terms of the presence of polyethylene granules and the viability state of articular polyethylene inserts. A total of 55 samples were taken from tissues around loosened endoprostheses. The location of each sample was exactly determined. A technique was developed to identify wear particles and to visualize them after all organic structures of a polyethylene granuloma were dissolved with nitrogenic acid. The viability of articular polyethylene implants showed extreme differences in relation to different periods of manufacture and probably also to different methods of sterilization. Articular inserts sterilized with formaldehyde (the method used at the beginning of arthroplasty in our country) showed the highest viability and the lowest wear. The polyethylene particles present in tissues surrounding the implant were characterized in terms of morphology and size. The comparison of literature data and our results has revealed that there are many unknown facts about the quality and structure of polyethylene. The method of sterilization also appears to play a role. Because the issue is complex, we were not able to identify all factors leading, in some cases, to an early and unexpected failure of the implant and we consider further investigation to be necessary. Polyethylene disease is an important factor limiting the viability of joint arthroplasty. It results from a complex interaction of polyethylene particles arising by wear with surrounding tissues. The particles, less than 0.5 micron in size, are phagocytized by macrophages and, by complex mechanism of expression of inflammation mediators, they result in the inhibition of osteogenesis and activation of osteoclastic processes. The previous methods of sterilization with formaldehyde vapors apparently reduced wear influenced the resistance of polyethylene to wear to a lesser degree. A method was developed to detect these particles and to characterize their morphology in the tissues of a polyethylene granuloma.

Probabilistic modelling of drought events in China via 2-dimensional joint copula

NASA Astrophysics Data System (ADS)

Ayantobo, Olusola O.; Li, Yi; Song, Songbai; Javed, Tehseen; Yao, Ning

2018-04-01

Probabilistic modelling of drought events is a significant aspect of water resources management and planning. In this study, popularly applied and several relatively new bivariate Archimedean copulas were employed to derive regional and spatial based copula models to appraise drought risk in mainland China over 1961-2013. Drought duration (Dd), severity (Ds), and peak (Dp), as indicated by Standardized Precipitation Evapotranspiration Index (SPEI), were extracted according to the run theory and fitted with suitable marginal distributions. The maximum likelihood estimation (MLE) and curve fitting method (CFM) were used to estimate the copula parameters of nineteen bivariate Archimedean copulas. Drought probabilities and return periods were analysed based on appropriate bivariate copula in sub-region I-VII and entire mainland China. The goodness-of-fit tests as indicated by the CFM showed that copula NN19 in sub-regions III, IV, V, VI and mainland China, NN20 in sub-region I and NN13 in sub-region VII are the best for modeling drought variables. Bivariate drought probability across mainland China is relatively high, and the highest drought probabilities are found mainly in the Northwestern and Southwestern China. Besides, the result also showed that different sub-regions might suffer varying drought risks. The drought risks as observed in Sub-region III, VI and VII, are significantly greater than other sub-regions. Higher probability of droughts of longer durations in the sub-regions also corresponds to shorter return periods with greater drought severity. These results may imply tremendous challenges for the water resources management in different sub-regions, particularly the Northwestern and Southwestern China.

The effects of local anaesthetic solution in the navicular bursa of horses with lameness caused by distal interphalangeal joint pain.

PubMed

Schumacher, John; Schumacher, Jim; Gillette, R; DeGraves, F; Schramme, M; Smith, R; Perkins, J; Coker, M

2003-07-01

Analgesia of the palmar digital (PD) nerves has been demonstrated to cause analgesia of the distal interphalangeal (DIP) joint as well as the sole. Because the PD nerves lie in close proximity to the navicular bursa, we suspected that that analgesia of the navicular bursa would anaesthetise the PD nerves, which would result in analgesia of the DIP joint. To determine the response of horses with pain in the DIP joint to instillation of local anaesthetic solution into the navicular bursa. Lameness was induced in 6 horses by creating painful synovitis in the DIP joint of one forefoot by administering endotoxin into the joint. Horses were videorecorded while trotting, before and after induction of lameness, at three 10 min intervals after instilling 3.5 ml local anaesthetic solution into the navicular bursa and, finally, after instilling 6 ml solution into the DIP joint. Lameness scores were assigned by grading the videorecorded gaits subjectively. At the 10 and -20 min observations, median lameness scores were not significantly different from those before administration of local anaesthetic solution into the navicular bursa (P > or = 0.05), although lameness scores of 3 of 6 horses improved during this period, and the 20 min observation scores tended toward significance (P = 0.07). At the 30 min observation, and after analgesia of the DIP joint, median lameness scores were significantly improved (P < or = 0.05). These results indicate that pain arising from the DIP joint can probably be excluded as a cause of lameness, when lameness is attenuated within 10 mins by analgesia of the navicular bursa. Pain arising from the DIP joint cannot be excluded as a cause of lameness when lameness is attenuated after 20 mins after analgesia of the navicular bursa.

Randomized Controlled Trial of Minimally Invasive Sacroiliac Joint Fusion Using Triangular Titanium Implants vs Nonsurgical Management for Sacroiliac Joint Dysfunction: 12-Month Outcomes

PubMed Central

Polly, David W.; Wine, Kathryn D.; Whang, Peter G.; Frank, Clay J.; Harvey, Charles F.; Lockstadt, Harry; Glaser, John A.; Limoni, Robert P.; Sembrano, Jonathan N.

2015-01-01

BACKGROUND: Sacroiliac joint (SIJ) dysfunction is a prevalent cause of chronic, unremitting lower back pain. OBJECTIVE: To concurrently compare outcomes after surgical and nonsurgical treatment for chronic SIJ dysfunction. METHODS: A total of 148 subjects with SIJ dysfunction were randomly assigned to minimally invasive SIJ fusion with triangular titanium implants (n = 102) or nonsurgical management (n = 46). Pain, disability, and quality-of-life scores were collected at baseline and at 1, 3, 6, and 12 months. Success rates were compared using Bayesian methods. Crossover from nonsurgical to surgical care was allowed after the 6-month study visit was complete. RESULTS: Six-month success rates were higher in the surgical group (81.4% vs 26.1%; posterior probability of superiority > 0.9999). Clinically important (≥ 15 point) Oswestry Disability Index improvement at 6 months occurred in 73.3% of the SIJ fusion group vs 13.6% of the nonsurgical management group (P < .001). At 12 months, improvements in SIJ pain and Oswestry Disability Index were sustained in the surgical group. Subjects who crossed over had improvements in pain, disability, and quality of life similar to those in the original surgical group. Adverse events were slightly more common in the surgical group (1.3 vs 1.1 events per subject; P = .31). CONCLUSION: This Level 1 study showed that minimally invasive SIJ fusion using triangular titanium implants was more effective than nonsurgical management at 1 year in relieving pain, improving function, and improving quality of life in patients with SIJ dysfunction caused by degenerative sacroiliitis or SIJ disruptions. Pain, disability, and quality of life also improved after crossover from nonsurgical to surgical treatment. ABBREVIATIONS: EQ-5D, EuroQoL-5D INSITE, Investigation of Sacroiliac Fusion Treatment MCS, mental component summary NSM, nonsurgical management ODI, Oswestry Disability Index PCS, physical component summary RFA, radiofrequency ablation SF-36, Short Form-36 SIJ, sacroiliac joint TTO, time trade-off VAS, visual analog scale PMID:26291338

Statistical inference for noisy nonlinear ecological dynamic systems.

PubMed

Wood, Simon N

2010-08-26

Chaotic ecological dynamic systems defy conventional statistical analysis. Systems with near-chaotic dynamics are little better. Such systems are almost invariably driven by endogenous dynamic processes plus demographic and environmental process noise, and are only observable with error. Their sensitivity to history means that minute changes in the driving noise realization, or the system parameters, will cause drastic changes in the system trajectory. This sensitivity is inherited and amplified by the joint probability density of the observable data and the process noise, rendering it useless as the basis for obtaining measures of statistical fit. Because the joint density is the basis for the fit measures used by all conventional statistical methods, this is a major theoretical shortcoming. The inability to make well-founded statistical inferences about biological dynamic models in the chaotic and near-chaotic regimes, other than on an ad hoc basis, leaves dynamic theory without the methods of quantitative validation that are essential tools in the rest of biological science. Here I show that this impasse can be resolved in a simple and general manner, using a method that requires only the ability to simulate the observed data on a system from the dynamic model about which inferences are required. The raw data series are reduced to phase-insensitive summary statistics, quantifying local dynamic structure and the distribution of observations. Simulation is used to obtain the mean and the covariance matrix of the statistics, given model parameters, allowing the construction of a 'synthetic likelihood' that assesses model fit. This likelihood can be explored using a straightforward Markov chain Monte Carlo sampler, but one further post-processing step returns pure likelihood-based inference. I apply the method to establish the dynamic nature of the fluctuations in Nicholson's classic blowfly experiments.

A Groupwise Association Test for Rare Mutations Using a Weighted Sum Statistic

PubMed Central

Madsen, Bo Eskerod; Browning, Sharon R.

2009-01-01

Resequencing is an emerging tool for identification of rare disease-associated mutations. Rare mutations are difficult to tag with SNP genotyping, as genotyping studies are designed to detect common variants. However, studies have shown that genetic heterogeneity is a probable scenario for common diseases, in which multiple rare mutations together explain a large proportion of the genetic basis for the disease. Thus, we propose a weighted-sum method to jointly analyse a group of mutations in order to test for groupwise association with disease status. For example, such a group of mutations may result from resequencing a gene. We compare the proposed weighted-sum method to alternative methods and show that it is powerful for identifying disease-associated genes, both on simulated and Encode data. Using the weighted-sum method, a resequencing study can identify a disease-associated gene with an overall population attributable risk (PAR) of 2%, even when each individual mutation has much lower PAR, using 1,000 to 7,000 affected and unaffected individuals, depending on the underlying genetic model. This study thus demonstrates that resequencing studies can identify important genetic associations, provided that specialised analysis methods, such as the weighted-sum method, are used. PMID:19214210

Anatomy-guided joint tissue segmentation and topological correction for 6-month infant brain MRI with risk of autism.

PubMed

Wang, Li; Li, Gang; Adeli, Ehsan; Liu, Mingxia; Wu, Zhengwang; Meng, Yu; Lin, Weili; Shen, Dinggang

2018-06-01

Tissue segmentation of infant brain MRIs with risk of autism is critically important for characterizing early brain development and identifying biomarkers. However, it is challenging due to low tissue contrast caused by inherent ongoing myelination and maturation. In particular, at around 6 months of age, the voxel intensities in both gray matter and white matter are within similar ranges, thus leading to the lowest image contrast in the first postnatal year. Previous studies typically employed intensity images and tentatively estimated tissue probabilities to train a sequence of classifiers for tissue segmentation. However, the important prior knowledge of brain anatomy is largely ignored during the segmentation. Consequently, the segmentation accuracy is still limited and topological errors frequently exist, which will significantly degrade the performance of subsequent analyses. Although topological errors could be partially handled by retrospective topological correction methods, their results may still be anatomically incorrect. To address these challenges, in this article, we propose an anatomy-guided joint tissue segmentation and topological correction framework for isointense infant MRI. Particularly, we adopt a signed distance map with respect to the outer cortical surface as anatomical prior knowledge, and incorporate such prior information into the proposed framework to guide segmentation in ambiguous regions. Experimental results on the subjects acquired from National Database for Autism Research demonstrate the effectiveness to topological errors and also some levels of robustness to motion. Comparisons with the state-of-the-art methods further demonstrate the advantages of the proposed method in terms of both segmentation accuracy and topological correctness. © 2018 Wiley Periodicals, Inc.

Distributed Constrained Optimization with Semicoordinate Transformations

NASA Technical Reports Server (NTRS)

Macready, William; Wolpert, David

2006-01-01

Recent work has shown how information theory extends conventional full-rationality game theory to allow bounded rational agents. The associated mathematical framework can be used to solve constrained optimization problems. This is done by translating the problem into an iterated game, where each agent controls a different variable of the problem, so that the joint probability distribution across the agents moves gives an expected value of the objective function. The dynamics of the agents is designed to minimize a Lagrangian function of that joint distribution. Here we illustrate how the updating of the Lagrange parameters in the Lagrangian is a form of automated annealing, which focuses the joint distribution more and more tightly about the joint moves that optimize the objective function. We then investigate the use of "semicoordinate" variable transformations. These separate the joint state of the agents from the variables of the optimization problem, with the two connected by an onto mapping. We present experiments illustrating the ability of such transformations to facilitate optimization. We focus on the special kind of transformation in which the statistically independent states of the agents induces a mixture distribution over the optimization variables. Computer experiment illustrate this for &sat constraint satisfaction problems and for unconstrained minimization of NK functions.

Calculating the axes of rotation for the subtalar and talocrural joints using 3D bone reconstructions.

PubMed

Parr, W C H; Chatterjee, H J; Soligo, C

2012-04-05

Orientation of the subtalar joint axis dictates inversion and eversion movements of the foot and has been the focus of evolutionary and clinical studies for a number of years. Previous studies have measured the subtalar joint axis against the axis of the whole foot, the talocrural joint axis and, recently, the principal axes of the talus. The present study introduces a new method for estimating average joint axes from 3D reconstructions of bones and applies the method to the talus to calculate the subtalar and talocrural joint axes. The study also assesses the validity of the principal axes as a reference coordinate system against which to measure the subtalar joint axis. In order to define the angle of the subtalar joint axis relative to that of another axis in the talus, we suggest measuring the subtalar joint axis against the talocrural joint axis. We present corresponding 3D vector angles calculated from a modern human skeletal sample. This method is applicable to virtual 3D models acquired through surface-scanning of disarticulated 'dry' osteological samples, as well as to 3D models created from CT or MRI scans. Copyright © 2012 Elsevier Ltd. All rights reserved.

Bayesian model averaging using particle filtering and Gaussian mixture modeling: Theory, concepts, and simulation experiments

NASA Astrophysics Data System (ADS)

Rings, Joerg; Vrugt, Jasper A.; Schoups, Gerrit; Huisman, Johan A.; Vereecken, Harry

2012-05-01

Bayesian model averaging (BMA) is a standard method for combining predictive distributions from different models. In recent years, this method has enjoyed widespread application and use in many fields of study to improve the spread-skill relationship of forecast ensembles. The BMA predictive probability density function (pdf) of any quantity of interest is a weighted average of pdfs centered around the individual (possibly bias-corrected) forecasts, where the weights are equal to posterior probabilities of the models generating the forecasts, and reflect the individual models skill over a training (calibration) period. The original BMA approach presented by Raftery et al. (2005) assumes that the conditional pdf of each individual model is adequately described with a rather standard Gaussian or Gamma statistical distribution, possibly with a heteroscedastic variance. Here we analyze the advantages of using BMA with a flexible representation of the conditional pdf. A joint particle filtering and Gaussian mixture modeling framework is presented to derive analytically, as closely and consistently as possible, the evolving forecast density (conditional pdf) of each constituent ensemble member. The median forecasts and evolving conditional pdfs of the constituent models are subsequently combined using BMA to derive one overall predictive distribution. This paper introduces the theory and concepts of this new ensemble postprocessing method, and demonstrates its usefulness and applicability by numerical simulation of the rainfall-runoff transformation using discharge data from three different catchments in the contiguous United States. The revised BMA method receives significantly lower-prediction errors than the original default BMA method (due to filtering) with predictive uncertainty intervals that are substantially smaller but still statistically coherent (due to the use of a time-variant conditional pdf).

Estimation of Time-Varying, Intrinsic and Reflex Dynamic Joint Stiffness during Movement. Application to the Ankle Joint

PubMed Central

Guarín, Diego L.; Kearney, Robert E.

2017-01-01

Dynamic joint stiffness determines the relation between joint position and torque, and plays a vital role in the control of posture and movement. Dynamic joint stiffness can be quantified during quasi-stationary conditions using disturbance experiments, where small position perturbations are applied to the joint and the torque response is recorded. Dynamic joint stiffness is composed of intrinsic and reflex mechanisms that act and change together, so that nonlinear, mathematical models and specialized system identification techniques are necessary to estimate their relative contributions to overall joint stiffness. Quasi-stationary experiments have demonstrated that dynamic joint stiffness is heavily modulated by joint position and voluntary torque. Consequently, during movement, when joint position and torque change rapidly, dynamic joint stiffness will be Time-Varying (TV). This paper introduces a new method to quantify the TV intrinsic and reflex components of dynamic joint stiffness during movement. The algorithm combines ensemble and deterministic approaches for estimation of TV systems; and uses a TV, parallel-cascade, nonlinear system identification technique to separate overall dynamic joint stiffness into intrinsic and reflex components from position and torque records. Simulation studies of a stiffness model, whose parameters varied with time as is expected during walking, demonstrated that the new algorithm accurately tracked the changes in dynamic joint stiffness using as little as 40 gait cycles. The method was also used to estimate the intrinsic and reflex dynamic ankle stiffness from an experiment with a healthy subject during which ankle movements were imposed while the subject maintained a constant muscle contraction. The method identified TV stiffness model parameters that predicted the measured torque very well, accounting for more than 95% of its variance. Moreover, both intrinsic and reflex dynamic stiffness were heavily modulated through the movement in a manner that could not be predicted from quasi-stationary experiments. The new method provides the tool needed to explore the role of dynamic stiffness in the control of movement. PMID:28649196

Determination of Parachute Joint Factors using Seam and Joint Testing

NASA Technical Reports Server (NTRS)

Mollmann, Catherine

2015-01-01

This paper details the methodology for determining the joint factor for all parachute components. This method has been successfully implemented on the Capsule Parachute Assembly System (CPAS) for the NASA Orion crew module for use in determining the margin of safety for each component under peak loads. Also discussed are concepts behind the joint factor and what drives the loss of material strength at joints. The joint factor is defined as a "loss in joint strength...relative to the basic material strength" that occurs when "textiles are connected to each other or to metals." During the CPAS engineering development phase, a conservative joint factor of 0.80 was assumed for each parachute component. In order to refine this factor and eliminate excess conservatism, a seam and joint testing program was implemented as part of the structural validation. This method split each of the parachute structural joints into discrete tensile tests designed to duplicate the loading of each joint. Breaking strength data collected from destructive pull testing was then used to calculate the joint factor in the form of an efficiency. Joint efficiency is the percentage of the base material strength that remains after degradation due to sewing or interaction with other components; it is used interchangeably with joint factor in this paper. Parachute materials vary in type-mainly cord, tape, webbing, and cloth -which require different test fixtures and joint sample construction methods. This paper defines guidelines for designing and testing samples based on materials and test goals. Using the test methodology and analysis approach detailed in this paper, the minimum joint factor for each parachute component can be formulated. The joint factors can then be used to calculate the design factor and margin of safety for that component, a critical part of the design verification process.

Statistical inference of the generation probability of T-cell receptors from sequence repertoires.

PubMed

Murugan, Anand; Mora, Thierry; Walczak, Aleksandra M; Callan, Curtis G

2012-10-02

Stochastic rearrangement of germline V-, D-, and J-genes to create variable coding sequence for certain cell surface receptors is at the origin of immune system diversity. This process, known as "VDJ recombination", is implemented via a series of stochastic molecular events involving gene choices and random nucleotide insertions between, and deletions from, genes. We use large sequence repertoires of the variable CDR3 region of human CD4+ T-cell receptor beta chains to infer the statistical properties of these basic biochemical events. Because any given CDR3 sequence can be produced in multiple ways, the probability distribution of hidden recombination events cannot be inferred directly from the observed sequences; we therefore develop a maximum likelihood inference method to achieve this end. To separate the properties of the molecular rearrangement mechanism from the effects of selection, we focus on nonproductive CDR3 sequences in T-cell DNA. We infer the joint distribution of the various generative events that occur when a new T-cell receptor gene is created. We find a rich picture of correlation (and absence thereof), providing insight into the molecular mechanisms involved. The generative event statistics are consistent between individuals, suggesting a universal biochemical process. Our probabilistic model predicts the generation probability of any specific CDR3 sequence by the primitive recombination process, allowing us to quantify the potential diversity of the T-cell repertoire and to understand why some sequences are shared between individuals. We argue that the use of formal statistical inference methods, of the kind presented in this paper, will be essential for quantitative understanding of the generation and evolution of diversity in the adaptive immune system.

qPR: An adaptive partial-report procedure based on Bayesian inference.

PubMed

Baek, Jongsoo; Lesmes, Luis Andres; Lu, Zhong-Lin

2016-08-01

Iconic memory is best assessed with the partial report procedure in which an array of letters appears briefly on the screen and a poststimulus cue directs the observer to report the identity of the cued letter(s). Typically, 6-8 cue delays or 600-800 trials are tested to measure the iconic memory decay function. Here we develop a quick partial report, or qPR, procedure based on a Bayesian adaptive framework to estimate the iconic memory decay function with much reduced testing time. The iconic memory decay function is characterized by an exponential function and a joint probability distribution of its three parameters. Starting with a prior of the parameters, the method selects the stimulus to maximize the expected information gain in the next test trial. It then updates the posterior probability distribution of the parameters based on the observer's response using Bayesian inference. The procedure is reiterated until either the total number of trials or the precision of the parameter estimates reaches a certain criterion. Simulation studies showed that only 100 trials were necessary to reach an average absolute bias of 0.026 and a precision of 0.070 (both in terms of probability correct). A psychophysical validation experiment showed that estimates of the iconic memory decay function obtained with 100 qPR trials exhibited good precision (the half width of the 68.2% credible interval = 0.055) and excellent agreement with those obtained with 1,600 trials of the conventional method of constant stimuli procedure (RMSE = 0.063). Quick partial-report relieves the data collection burden in characterizing iconic memory and makes it possible to assess iconic memory in clinical populations.

qPR: An adaptive partial-report procedure based on Bayesian inference

PubMed Central

Baek, Jongsoo; Lesmes, Luis Andres; Lu, Zhong-Lin

2016-01-01

Iconic memory is best assessed with the partial report procedure in which an array of letters appears briefly on the screen and a poststimulus cue directs the observer to report the identity of the cued letter(s). Typically, 6–8 cue delays or 600–800 trials are tested to measure the iconic memory decay function. Here we develop a quick partial report, or qPR, procedure based on a Bayesian adaptive framework to estimate the iconic memory decay function with much reduced testing time. The iconic memory decay function is characterized by an exponential function and a joint probability distribution of its three parameters. Starting with a prior of the parameters, the method selects the stimulus to maximize the expected information gain in the next test trial. It then updates the posterior probability distribution of the parameters based on the observer's response using Bayesian inference. The procedure is reiterated until either the total number of trials or the precision of the parameter estimates reaches a certain criterion. Simulation studies showed that only 100 trials were necessary to reach an average absolute bias of 0.026 and a precision of 0.070 (both in terms of probability correct). A psychophysical validation experiment showed that estimates of the iconic memory decay function obtained with 100 qPR trials exhibited good precision (the half width of the 68.2% credible interval = 0.055) and excellent agreement with those obtained with 1,600 trials of the conventional method of constant stimuli procedure (RMSE = 0.063). Quick partial-report relieves the data collection burden in characterizing iconic memory and makes it possible to assess iconic memory in clinical populations. PMID:27580045

Output Error Analysis of Planar 2-DOF Five-bar Mechanism

NASA Astrophysics Data System (ADS)

Niu, Kejia; Wang, Jun; Ting, Kwun-Lon; Tao, Fen; Cheng, Qunchao; Wang, Quan; Zhang, Kaiyang

2018-03-01

Aiming at the mechanism error caused by clearance of planar 2-DOF Five-bar motion pair, the method of equivalent joint clearance of kinematic pair to virtual link is applied. The structural error model of revolute joint clearance is established based on the N-bar rotation laws and the concept of joint rotation space, The influence of the clearance of the moving pair is studied on the output error of the mechanis. and the calculation method and basis of the maximum error are given. The error rotation space of the mechanism under the influence of joint clearance is obtained. The results show that this method can accurately calculate the joint space error rotation space, which provides a new way to analyze the planar parallel mechanism error caused by joint space.

A Method for and Issues Associated with the Determination of Space Suit Joint Requirements

NASA Technical Reports Server (NTRS)

Matty, Jennifer E.; Aitchison, Lindsay

2010-01-01

This joint mobility KC lecture included information from two papers, "A Method for and Issues Associated with the Determination of Space Suit Joint Requirements" and "Results and Analysis from Space Suit Joint Torque Testing," as presented for the International Conference on Environmental Systems in 2009 and 2010, respectively. The first paper discusses historical joint torque testing methodologies and approaches that were tested in 2008 and 2009. The second paper discusses the testing that was completed in 2009 and 2010.

Impact of meteorological inflow uncertainty on tracer transport and source estimation in urban atmospheres

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lucas, Donald D.; Gowardhan, Akshay; Cameron-Smith, Philip

2015-08-08

Here, a computational Bayesian inverse technique is used to quantify the effects of meteorological inflow uncertainty on tracer transport and source estimation in a complex urban environment. We estimate a probability distribution of meteorological inflow by comparing wind observations to Monte Carlo simulations from the Aeolus model. Aeolus is a computational fluid dynamics model that simulates atmospheric and tracer flow around buildings and structures at meter-scale resolution. Uncertainty in the inflow is propagated through forward and backward Lagrangian dispersion calculations to determine the impact on tracer transport and the ability to estimate the release location of an unknown source. Ourmore » uncertainty methods are compared against measurements from an intensive observation period during the Joint Urban 2003 tracer release experiment conducted in Oklahoma City.« less

An integrated logit model for contamination event detection in water distribution systems.

PubMed

Housh, Mashor; Ostfeld, Avi

2015-05-15

The problem of contamination event detection in water distribution systems has become one of the most challenging research topics in water distribution systems analysis. Current attempts for event detection utilize a variety of approaches including statistical, heuristics, machine learning, and optimization methods. Several existing event detection systems share a common feature in which alarms are obtained separately for each of the water quality indicators. Unifying those single alarms from different indicators is usually performed by means of simple heuristics. A salient feature of the current developed approach is using a statistically oriented model for discrete choice prediction which is estimated using the maximum likelihood method for integrating the single alarms. The discrete choice model is jointly calibrated with other components of the event detection system framework in a training data set using genetic algorithms. The fusing process of each indicator probabilities, which is left out of focus in many existing event detection system models, is confirmed to be a crucial part of the system which could be modelled by exploiting a discrete choice model for improving its performance. The developed methodology is tested on real water quality data, showing improved performances in decreasing the number of false positive alarms and in its ability to detect events with higher probabilities, compared to previous studies. Copyright © 2015 Elsevier Ltd. All rights reserved.

Gaussian closure technique applied to the hysteretic Bouc model with non-zero mean white noise excitation

NASA Astrophysics Data System (ADS)

Waubke, Holger; Kasess, Christian H.

2016-11-01

Devices that emit structure-borne sound are commonly decoupled by elastic components to shield the environment from acoustical noise and vibrations. The elastic elements often have a hysteretic behavior that is typically neglected. In order to take hysteretic behavior into account, Bouc developed a differential equation for such materials, especially joints made of rubber or equipped with dampers. In this work, the Bouc model is solved by means of the Gaussian closure technique based on the Kolmogorov equation. Kolmogorov developed a method to derive probability density functions for arbitrary explicit first-order vector differential equations under white noise excitation using a partial differential equation of a multivariate conditional probability distribution. Up to now no analytical solution of the Kolmogorov equation in conjunction with the Bouc model exists. Therefore a wide range of approximate solutions, especially the statistical linearization, were developed. Using the Gaussian closure technique that is an approximation to the Kolmogorov equation assuming a multivariate Gaussian distribution an analytic solution is derived in this paper for the Bouc model. For the stationary case the two methods yield equivalent results, however, in contrast to statistical linearization the presented solution allows to calculate the transient behavior explicitly. Further, stationary case leads to an implicit set of equations that can be solved iteratively with a small number of iterations and without instabilities for specific parameter sets.

A study of parameter identification

NASA Technical Reports Server (NTRS)

Herget, C. J.; Patterson, R. E., III

1978-01-01

A set of definitions for deterministic parameter identification ability were proposed. Deterministic parameter identificability properties are presented based on four system characteristics: direct parameter recoverability, properties of the system transfer function, properties of output distinguishability, and uniqueness properties of a quadratic cost functional. Stochastic parameter identifiability was defined in terms of the existence of an estimation sequence for the unknown parameters which is consistent in probability. Stochastic parameter identifiability properties are presented based on the following characteristics: convergence properties of the maximum likelihood estimate, properties of the joint probability density functions of the observations, and properties of the information matrix.

Units of analysis and kinetic structure of behavioral repertoires

PubMed Central

Thompson, Travis; Lubinski, David

1986-01-01

It is suggested that molar streams of behavior are constructed of various arrangements of three elementary constituents (elicited, evoked, and emitted response classes). An eight-cell taxonomy is elaborated as a framework for analyzing and synthesizing complex behavioral repertoires based on these functional units. It is proposed that the local force binding functional units into a smoothly articulated kinetic sequence arises from temporally arranged relative response probability relationships. Behavioral integration is thought to reflect the joint influence of the organism's hierarchy of relative response probabilities, fluctuating biological states, and the arrangement of environmental and behavioral events in time. PMID:16812461

Simulation of Stochastic Processes by Coupled ODE-PDE

NASA Technical Reports Server (NTRS)

Zak, Michail

2008-01-01

A document discusses the emergence of randomness in solutions of coupled, fully deterministic ODE-PDE (ordinary differential equations-partial differential equations) due to failure of the Lipschitz condition as a new phenomenon. It is possible to exploit the special properties of ordinary differential equations (represented by an arbitrarily chosen, dynamical system) coupled with the corresponding Liouville equations (used to describe the evolution of initial uncertainties in terms of joint probability distribution) in order to simulate stochastic processes with the proscribed probability distributions. The important advantage of the proposed approach is that the simulation does not require a random-number generator.

TIMS/ORSA (Operations Research Society of America) Special Interest Conference on Applied Probability; Statistical and Computational Problems in Probability Modeling (3rd) Held at Williamsburg, Virginia on 7-9 January 1985.

DTIC Science & Technology

1985-01-01

Marchetti (**) (*) National Institutes of Health. Bethesda, MD 20205 (**) Dipartimento di Matematica . Universit& " La Sapienza". 1-00184 Roma, Italy. ABSTRACT...CANCER MODEL’ DIPARTIMENTO DI MATEMATICA (JOINT WITH DAVIS COVELL) UNIVERSITA LA SAPIENZA 1-00184 ROMAP ITALY SESSION NUMBER W91 PROFESSOR JOHN M...8217i ~ eL : .- "-: (1) Marcel F. Neuts, "Profile Curves of Queues" (2) I. V. Basawa, "Statistical Forecasting for Stochastic Processes" (3) George S

Two tandem queues with general renewal input. 2: Asymptotic expansions for the diffusion model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Knessl, C.; Tier, C.

1999-10-01

In Part 1 the authors formulated and solved a diffusion model for two tandem queues with exponential servers and general renewal arrivals. They thus obtained the easy traffic diffusion approximation to the steady state joint queue length distribution for this network. Here they study asymptotic and numerical properties of the diffusion approximation. In particular, analytical expressions are obtained for the tail probabilities. Both the joint distribution of the two queues and the marginal distribution of the second queue are considered. They also give numerical illustrations of how this marginal is affected by changes in the arrival and service processes.

Coordinated Optimization of Aircraft Routes and Locations of Ground Sensors

DTIC Science & Technology

2014-09-17

d U γ P p w dw    r sr s , (6) where γ is the detection threshold determined from the following equa- tion for some given faP : ( )( ) ,fa N γ...normal with the mean Uμ 7 and variance Uσ  2 3 . Suppose, the threshold for the false alarm is faP  410 . Then, from equation (7), .γ6 7190 ; and...functions; and the joint probability of false alarm would be ( , ) faP     s s 4 4 81 2 10 10 10 whereas the joint probabil- ity of detection would

Parameters Estimation For A Patellofemoral Joint Of A Human Knee Using A Vector Method

NASA Astrophysics Data System (ADS)

Ciszkiewicz, A.; Knapczyk, J.

2015-08-01

Position and displacement analysis of a spherical model of a human knee joint using the vector method was presented. Sensitivity analysis and parameter estimation were performed using the evolutionary algorithm method. Computer simulations for the mechanism with estimated parameters proved the effectiveness of the prepared software. The method itself can be useful when solving problems concerning the displacement and loads analysis in the knee joint.

Labor Force Participation of Older Workers: Prospective Changes and Potential Policy Responses.

ERIC Educational Resources Information Center

Favreault, Melissa; Ratcliffe, Caroline; Toder, Eric

1999-01-01

Data from the Survey of Income and Program Participation were matched with longitudinal earnings histories and Social Security benefit data to estimate joint work and benefit receipt choices for people age 62 and older. The probability of working is shown to depend on worker characteristics and policy variables. (Author)

Some Factor Analytic Approximations to Latent Class Structure.

ERIC Educational Resources Information Center

Dziuban, Charles D.; Denton, William T.

Three procedures, alpha, image, and uniqueness rescaling, were applied to a joint occurrence probability matrix. That matrix was the basis of a well-known latent class structure. The values of the recurring subscript elements were varied as follows: Case 1 - The known elements were input; Case 2 - The upper bounds to the recurring subscript…

Economic Statistical Design of Integrated X-bar-S Control Chart with Preventive Maintenance and General Failure Distribution

PubMed Central

Caballero Morales, Santiago Omar

2013-01-01

The application of Preventive Maintenance (PM) and Statistical Process Control (SPC) are important practices to achieve high product quality, small frequency of failures, and cost reduction in a production process. However there are some points that have not been explored in depth about its joint application. First, most SPC is performed with the X-bar control chart which does not fully consider the variability of the production process. Second, many studies of design of control charts consider just the economic aspect while statistical restrictions must be considered to achieve charts with low probabilities of false detection of failures. Third, the effect of PM on processes with different failure probability distributions has not been studied. Hence, this paper covers these points, presenting the Economic Statistical Design (ESD) of joint X-bar-S control charts with a cost model that integrates PM with general failure distribution. Experiments showed statistically significant reductions in costs when PM is performed on processes with high failure rates and reductions in the sampling frequency of units for testing under SPC. PMID:23527082

Probabilistic inversion of expert assessments to inform projections about Antarctic ice sheet responses.

PubMed

Fuller, Robert William; Wong, Tony E; Keller, Klaus

2017-01-01

The response of the Antarctic ice sheet (AIS) to changing global temperatures is a key component of sea-level projections. Current projections of the AIS contribution to sea-level changes are deeply uncertain. This deep uncertainty stems, in part, from (i) the inability of current models to fully resolve key processes and scales, (ii) the relatively sparse available data, and (iii) divergent expert assessments. One promising approach to characterizing the deep uncertainty stemming from divergent expert assessments is to combine expert assessments, observations, and simple models by coupling probabilistic inversion and Bayesian inversion. Here, we present a proof-of-concept study that uses probabilistic inversion to fuse a simple AIS model and diverse expert assessments. We demonstrate the ability of probabilistic inversion to infer joint prior probability distributions of model parameters that are consistent with expert assessments. We then confront these inferred expert priors with instrumental and paleoclimatic observational data in a Bayesian inversion. These additional constraints yield tighter hindcasts and projections. We use this approach to quantify how the deep uncertainty surrounding expert assessments affects the joint probability distributions of model parameters and future projections.

Role of beach morphology in wave overtopping hazard assessment

NASA Astrophysics Data System (ADS)

Phillips, Benjamin; Brown, Jennifer; Bidlot, Jean-Raymond; Plater, Andrew

2017-04-01

Understanding the role of beach morphology in controlling wave overtopping volume will further minimise uncertainties in flood risk assessments at coastal locations defended by engineered structures worldwide. XBeach is used to model wave overtopping volume for a 1:200 yr joint probability distribution of waves and water levels with measured, pre- and post-storm beach profiles. The simulation with measured bathymetry is repeated with and without morphological evolution enabled during the modelled storm event. This research assesses the role of morphology in controlling wave overtopping volumes for hazardous events that meet the typical design level of coastal defence structures. Results show disabling storm-driven morphology under-represents modelled wave overtopping volumes by up to 39% under high Hs conditions, and has a greater impact on the wave overtopping rate than the variability applied within the boundary conditions due to the range of wave-water level combinations that meet the 1:200 yr joint probability criterion. Accounting for morphology in flood modelling is therefore critical for accurately predicting wave overtopping volumes and the resulting flood hazard and to assess economic losses.

[Determination of joint contact area using MRI].

PubMed

Yoshida, Hidenori; Kobayashi, Koichi; Sakamoto, Makoto; Tanabe, Yuji

2009-10-20

Elevated contact stress on the articular joints has been hypothesized to contribute to articular cartilage wear and joint pain. However, given the limitations of using contact stress and areas from human cadaver specimens to estimate articular joint stress, there is need for an in vivo method to obtain such data. Magnetic resonance imaging (MRI) has been shown to be a valid method of quantifying the human joint contact area, indicating the potential for in vivo assessment. The purpose of this study was to describe a method of quantifying the tibiofemoral joint contact area using MRI. The validity of this technique was established in porcine cadaver specimens by comparing the contact area obtained from MRI with the contact area obtained using pressure-sensitive film (PSF). In particular, we assessed the actual condition of contact by using the ratio of signal intensity of MR images of cartilage surfaces. Two fresh porcine cadaver knees were used. A custom loading apparatus was designed to apply a compressive load to the tibiofemoral joint. We measured the contact area by using MRI and PSF methods. When the ratio of signal intensity of the cartilage surface was 0.9, the error of the contact area between the MR image and PSF was about 6%. These results suggest that this MRI method may be a valuable tool in quantifying joint contact area in vivo.

Segmentation of hand radiographs using fast marching methods

NASA Astrophysics Data System (ADS)

Chen, Hong; Novak, Carol L.

2006-03-01

Rheumatoid Arthritis is one of the most common chronic diseases. Joint space width in hand radiographs is evaluated to assess joint damage in order to monitor progression of disease and response to treatment. Manual measurement of joint space width is time-consuming and highly prone to inter- and intra-observer variation. We propose a method for automatic extraction of finger bone boundaries using fast marching methods for quantitative evaluation of joint space width. The proposed algorithm includes two stages: location of hand joints followed by extraction of bone boundaries. By setting the propagation speed of the wave front as a function of image intensity values, the fast marching algorithm extracts the skeleton of the hands, in which each branch corresponds to a finger. The finger joint locations are then determined by using the image gradients along the skeletal branches. In order to extract bone boundaries at joints, the gradient magnitudes are utilized for setting the propagation speed, and the gradient phases are used for discriminating the boundaries of adjacent bones. The bone boundaries are detected by searching for the fastest paths from one side of each joint to the other side. Finally, joint space width is computed based on the extracted upper and lower bone boundaries. The algorithm was evaluated on a test set of 8 two-hand radiographs, including images from healthy patients and from patients suffering from arthritis, gout and psoriasis. Using our method, 97% of 208 joints were accurately located and 89% of 416 bone boundaries were correctly extracted.

Measurement of the top-quark mass with dilepton events selected using neuroevolution at CDF.

PubMed

Aaltonen, T; Adelman, J; Akimoto, T; Albrow, M G; Alvarez González, B; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Apollinari, G; Apresyan, A; Arisawa, T; Artikov, A; Ashmanskas, W; Attal, A; Aurisano, A; Azfar, F; Azzurri, P; Badgett, W; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Bartsch, V; Bauer, G; Beauchemin, P-H; Bedeschi, F; Bednar, P; Beecher, D; Behari, S; Bellettini, G; Bellinger, J; Benjamin, D; Beretvas, A; Beringer, J; Bhatti, A; Binkley, M; Bisello, D; Bizjak, I; Blair, R E; Blocker, C; Blumenfeld, B; Bocci, A; Bodek, A; Boisvert, V; Bolla, G; Bortoletto, D; Boudreau, J; Boveia, A; Brau, B; Bridgeman, A; Brigliadori, L; Bromberg, C; Brubaker, E; Budagov, J; Budd, H S; Budd, S; Burkett, K; Busetto, G; Bussey, P; Buzatu, A; Byrum, K L; Cabrera, S; Calancha, C; Campanelli, M; Campbell, M; Canelli, F; Canepa, A; Carlsmith, D; Carosi, R; Carrillo, S; Carron, S; Casal, B; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavaliere, V; Cavalli-Sforza, M; Cerri, A; Cerrito, L; Chang, S H; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, K; Chokheli, D; Chou, J P; Choudalakis, G; Chuang, S H; Chung, K; Chung, W H; Chung, Y S; Ciobanu, C I; Ciocci, M A; Clark, A; Clark, D; Compostella, G; Convery, M E; Conway, J; Copic, K; Cordelli, M; Cortiana, G; Cox, D J; Crescioli, F; Cuenca Almenar, C; Cuevas, J; Culbertson, R; Cully, J C; Dagenhart, D; Datta, M; Davies, T; de Barbaro, P; De Cecco, S; Deisher, A; De Lorenzo, G; Dell'orso, M; Deluca, C; Demortier, L; Deng, J; Deninno, M; Derwent, P F; di Giovanni, G P; Dionisi, C; Di Ruzza, B; Dittmann, J R; D'Onofrio, M; Donati, S; Dong, P; Donini, J; Dorigo, T; Dube, S; Efron, J; Elagin, A; Erbacher, R; Errede, D; Errede, S; Eusebi, R; Fang, H C; Farrington, S; Fedorko, W T; Feild, R G; Feindt, M; Fernandez, J P; Ferrazza, C; Field, R; Flanagan, G; Forrest, R; Franklin, M; Freeman, J C; Furic, I; Gallinaro, M; Galyardt, J; Garberson, F; Garcia, J E; Garfinkel, A F; Genser, K; Gerberich, H; Gerdes, D; Gessler, A; Giagu, S; Giakoumopoulou, V; Giannetti, P; Gibson, K; Gimmell, J L; Ginsburg, C M; Giokaris, N; Giordani, M; Giromini, P; Giunta, M; Giurgiu, G; Glagolev, V; Glenzinski, D; Gold, M; Goldschmidt, N; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Goulianos, K; Gresele, A; Grinstein, S; Grosso-Pilcher, C; Grundler, U; Guimaraes da Costa, J; Gunay-Unalan, Z; Haber, C; Hahn, K; Hahn, S R; Halkiadakis, E; Han, B-Y; Han, J Y; Handler, R; Happacher, F; Hara, K; Hare, D; Hare, M; Harper, S; Harr, R F; Harris, R M; Hartz, M; Hatakeyama, K; Hauser, J; Hays, C; Heck, M; Heijboer, A; Heinemann, B; Heinrich, J; Henderson, C; Herndon, M; Heuser, J; Hewamanage, S; Hidas, D; Hill, C S; Hirschbuehl, D; Hocker, A; Hou, S; Houlden, M; Hsu, S-C; Huffman, B T; Hughes, R E; Husemann, U; Huston, J; Incandela, J; Introzzi, G; Iori, M; Ivanov, A; James, E; Jayatilaka, B; Jeon, E J; Jha, M K; Jindariani, S; Johnson, W; Jones, M; Joo, K K; Jun, S Y; Jung, J E; Junk, T R; Kamon, T; Kar, D; Karchin, P E; Kato, Y; Kephart, R; Keung, J; Khotilovich, V; Kilminster, B; Kim, D H; Kim, H S; Kim, J E; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kimura, N; Kirsch, L; Klimenko, S; Knuteson, B; Ko, B R; Koay, S A; Kondo, K; Kong, D J; Konigsberg, J; Korytov, A; Kotwal, A V; Kreps, M; Kroll, J; Krop, D; Krumnack, N; Kruse, M; Krutelyov, V; Kubo, T; Kuhr, T; Kulkarni, N P; Kurata, M; Kusakabe, Y; Kwang, S; Laasanen, A T; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; Lazzizzera, I; Lecompte, T; Lee, E; Lee, S W; Leone, S; Lewis, J D; Lin, C S; Linacre, J; Lindgren, M; Lipeles, E; Lister, A; Litvintsev, D O; Liu, C; Liu, T; Lockyer, N S; Loginov, A; Loreti, M; Lovas, L; Lu, R-S; Lucchesi, D; Lueck, J; Luci, C; Lujan, P; Lukens, P; Lungu, G; Lyons, L; Lys, J; Lysak, R; Lytken, E; Mack, P; Macqueen, D; Madrak, R; Maeshima, K; Makhoul, K; Maki, T; Maksimovic, P; Malde, S; Malik, S; Manca, G; Manousakis-Katsikakis, A; Margaroli, F; Marino, C; Marino, C P; Martin, A; Martin, V; Martínez, M; Martínez-Ballarín, R; Maruyama, T; Mastrandrea, P; Masubuchi, T; Mattson, M E; Mazzanti, P; McFarland, K S; McIntyre, P; McNulty, R; Mehta, A; Mehtala, P; Menzione, A; Merkel, P; Mesropian, C; Miao, T; Miladinovic, N; Miller, R; Mills, C; Milnik, M; Mitra, A; Mitselmakher, G; Miyake, H; Moggi, N; Moon, C S; Moore, R; Morello, M J; Morlok, J; Movilla Fernandez, P; Mülmenstädt, J; Mukherjee, A; Muller, Th; Mumford, R; Murat, P; Mussini, M; Nachtman, J; Nagai, Y; Nagano, A; Naganoma, J; Nakamura, K; Nakano, I; Napier, A; Necula, V; Neu, C; Neubauer, M S; Nielsen, J; Nodulman, L; Norman, M; Norniella, O; Nurse, E; Oakes, L; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Orava, R; Osterberg, K; Pagan Griso, S; Pagliarone, C; Palencia, E; Papadimitriou, V; Papaikonomou, A; Paramonov, A A; Parks, B; Pashapour, S; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Pellett, D E; Penzo, A; Phillips, T J; Piacentino, G; Pianori, E; Pinera, L; Pitts, K; Plager, C; Pondrom, L; Poukhov, O; Pounder, N; Prakoshyn, F; Pronko, A; Proudfoot, J; Ptohos, F; Pueschel, E; Punzi, G; Pursley, J; Rademacker, J; Rahaman, A; Ramakrishnan, V; Ranjan, N; Redondo, I; Reisert, B; Rekovic, V; Renton, P; Rescigno, M; Richter, S; Rimondi, F; Ristori, L; Robson, A; Rodrigo, T; Rodriguez, T; Rogers, E; Rolli, S; Roser, R; Rossi, M; Rossin, R; Roy, P; Ruiz, A; Russ, J; Rusu, V; Saarikko, H; Safonov, A; Sakumoto, W K; Saltó, O; Santi, L; Sarkar, S; Sartori, L; Sato, K; Savoy-Navarro, A; Scheidle, T; Schlabach, P; Schmidt, A; Schmidt, E E; Schmidt, M A; Schmidt, M P; Schmitt, M; Schwarz, T; Scodellaro, L; Scott, A L; Scribano, A; Scuri, F; Sedov, A; Seidel, S; Seiya, Y; Semenov, A; Sexton-Kennedy, L; Sfyrla, A; Shalhout, S Z; Shears, T; Shekhar, R; Shepard, P F; Sherman, D; Shimojima, M; Shiraishi, S; Shochet, M; Shon, Y; Shreyber, I; Sidoti, A; Sinervo, P; Sisakyan, A; Slaughter, A J; Slaunwhite, J; Sliwa, K; Smith, J R; Snider, F D; Snihur, R; Soha, A; Somalwar, S; Sorin, V; Spalding, J; Spreitzer, T; Squillacioti, P; Stanitzki, M; St Denis, R; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Stuart, D; Suh, J S; Sukhanov, A; Suslov, I; Suzuki, T; Taffard, A; Takashima, R; Takeuchi, Y; Tanaka, R; Tecchio, M; Teng, P K; Terashi, K; Thom, J; Thompson, A S; Thompson, G A; Thomson, E; Tipton, P; Tiwari, V; Tkaczyk, S; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Totaro, P; Tourneur, S; Tu, Y; Turini, N; Ukegawa, F; Vallecorsa, S; van Remortel, N; Varganov, A; Vataga, E; Vázquez, F; Velev, G; Vellidis, C; Veszpremi, V; Vidal, M; Vidal, R; Vila, I; Vilar, R; Vine, T; Vogel, M; Volobouev, I; Volpi, G; Würthwein, F; Wagner, P; Wagner, R G; Wagner, R L; Wagner-Kuhr, J; Wagner, W; Wakisaka, T; Wallny, R; Wang, S M; Warburton, A; Waters, D; Weinberger, M; Wester, W C; Whitehouse, B; Whiteson, D; Whiteson, S; Wicklund, A B; Wicklund, E; Williams, G; Williams, H H; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, C; Wright, T; Wu, X; Wynne, S M; Xie, S; Yagil, A; Yamamoto, K; Yamaoka, J; Yang, U K; Yang, Y C; Yao, W M; Yeh, G P; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Yu, S S; Yun, J C; Zanello, L; Zanetti, A; Zaw, I; Zhang, X; Zheng, Y; Zucchelli, S

2009-04-17

We report a measurement of the top-quark mass M_{t} in the dilepton decay channel tt[over ] --> bl;{'+} nu_{l};{'}b[over ]l;{-}nu[over ]_{l}. Events are selected with a neural network which has been directly optimized for statistical precision in top-quark mass using neuroevolution, a technique modeled on biological evolution. The top-quark mass is extracted from per-event probability densities that are formed by the convolution of leading order matrix elements and detector resolution functions. The joint probability is the product of the probability densities from 344 candidate events in 2.0 fb;{-1} of pp[over ] collisions collected with the CDF II detector, yielding a measurement of M_{t} = 171.2 +/- 2.7(stat) +/- 2.9(syst) GeV / c;{2}.

Comparison Of Semi-Automatic And Automatic Slick Detection Algorithms For Jiyeh Power Station Oil Spill, Lebanon

NASA Astrophysics Data System (ADS)

Osmanoglu, B.; Ozkan, C.; Sunar, F.

2013-10-01

After air strikes on July 14 and 15, 2006 the Jiyeh Power Station started leaking oil into the eastern Mediterranean Sea. The power station is located about 30 km south of Beirut and the slick covered about 170 km of coastline threatening the neighboring countries Turkey and Cyprus. Due to the ongoing conflict between Israel and Lebanon, cleaning efforts could not start immediately resulting in 12 000 to 15 000 tons of fuel oil leaking into the sea. In this paper we compare results from automatic and semi-automatic slick detection algorithms. The automatic detection method combines the probabilities calculated for each pixel from each image to obtain a joint probability, minimizing the adverse effects of atmosphere on oil spill detection. The method can readily utilize X-, C- and L-band data where available. Furthermore wind and wave speed observations can be used for a more accurate analysis. For this study, we utilize Envisat ASAR ScanSAR data. A probability map is generated based on the radar backscatter, effect of wind and dampening value. The semi-automatic algorithm is based on supervised classification. As a classifier, Artificial Neural Network Multilayer Perceptron (ANN MLP) classifier is used since it is more flexible and efficient than conventional maximum likelihood classifier for multisource and multi-temporal data. The learning algorithm for ANN MLP is chosen as the Levenberg-Marquardt (LM). Training and test data for supervised classification are composed from the textural information created from SAR images. This approach is semiautomatic because tuning the parameters of classifier and composing training data need a human interaction. We point out the similarities and differences between the two methods and their results as well as underlining their advantages and disadvantages. Due to the lack of ground truth data, we compare obtained results to each other, as well as other published oil slick area assessments.

Pneumococcal septic arthritis in adults: clinical analysis and review.

PubMed

Belkhir, L; Rodriguez-Villalobos, H; Vandercam, B; Marot, J C; Cornu, O; Lambert, M; Yombi, J C

2014-01-01

Septic arthritis (SA) is a rheumatological emergency that can lead to rapid joint destruction and irreversible loss of function. The most common pathogen causing SA is Staphylococcus aureus which is responsible for 37-65% of cases. Streptococcus pneumoniae is traditionally described as an uncommon cause of SA of a native joint. The objective of our study was to analyse clinical characteristics, treatment, and outcome of all cases of pneumococcal septic arthritis treated in our institution, and to compare them with other series published in the literature. We conducted a retrospective study of pneumococcal SA identified among all cases of SA diagnosed in a teaching hospital of one thousand beds between 2004 and 2009. Diagnosis was based on culture of joint liquid or by the presence of pneumococcal bacteraemia and purulent (more than 50 000/mm(3) white blood cells with more than 90% neutrophils) joint fluid aspiration. Among 266 cases of SA, nine patients (3·3%) were diagnosed as having pneumococcal SA. The median age was 75 years. The main affected joint was the knee (7/9). No patient had more than one joint involved. Four patients suffered from concomitant pneumonia. Joint culture and blood cultures were positive in 7/9 and 5/9, respectively. Median (range) length of stay was 18 days (3-47 days). One patient with associated pneumococcal bacteraemia died 19 days after admission. Seven patients recovered completely. Streptococcus pneumoniae is now being increasingly recognized as a common agent of SA. This organism is frequently associated with pneumococcal pneumonia or bacteraemia, particularly in patients with advanced age and comorbidities. Direct inoculation of joint fluid into blood culture medium BACTEC system increases the probability of microbiological diagnosis. The prognosis is usually favourable if the disease is promptly recognized and treated (antibiotic therapy combined with joint drainage).

One Photon Can Simultaneously Excite Two or More Atoms.

PubMed

Garziano, Luigi; Macrì, Vincenzo; Stassi, Roberto; Di Stefano, Omar; Nori, Franco; Savasta, Salvatore

2016-07-22

We consider two separate atoms interacting with a single-mode optical or microwave resonator. When the frequency of the resonator field is twice the atomic transition frequency, we show that there exists a resonant coupling between one photon and two atoms, via intermediate virtual states connected by counterrotating processes. If the resonator is prepared in its one-photon state, the photon can be jointly absorbed by the two atoms in their ground state which will both reach their excited state with a probability close to one. Like ordinary quantum Rabi oscillations, this process is coherent and reversible, so that two atoms in their excited state will undergo a downward transition jointly emitting a single cavity photon. This joint absorption and emission process can also occur with three atoms. The parameters used to investigate this process correspond to experimentally demonstrated values in circuit quantum electrodynamics systems.

Can a quantum state over time resemble a quantum state at a single time?

NASA Astrophysics Data System (ADS)

Horsman, Dominic; Heunen, Chris; Pusey, Matthew F.; Barrett, Jonathan; Spekkens, Robert W.

2017-09-01

The standard formalism of quantum theory treats space and time in fundamentally different ways. In particular, a composite system at a given time is represented by a joint state, but the formalism does not prescribe a joint state for a composite of systems at different times. If there were a way of defining such a joint state, this would potentially permit a more even-handed treatment of space and time, and would strengthen the existing analogy between quantum states and classical probability distributions. Under the assumption that the joint state over time is an operator on the tensor product of single-time Hilbert spaces, we analyse various proposals for such a joint state, including one due to Leifer and Spekkens, one due to Fitzsimons, Jones and Vedral, and another based on discrete Wigner functions. Finding various problems with each, we identify five criteria for a quantum joint state over time to satisfy if it is to play a role similar to the standard joint state for a composite system: that it is a Hermitian operator on the tensor product of the single-time Hilbert spaces; that it represents probabilistic mixing appropriately; that it has the appropriate classical limit; that it has the appropriate single-time marginals; that composing over multiple time steps is associative. We show that no construction satisfies all these requirements. If Hermiticity is dropped, then there is an essentially unique construction that satisfies the remaining four criteria.

Factors affecting results of fluoroscopy-guided facet joint injection: Probable differences in the outcome of treatment between pure facet joint hypertrophy and concomitant diseases.

PubMed

Albayrak, Akif; Ozkul, Baris; Balioglu, Mehmet Bulent; Atici, Yunus; Gultekin, Muhammet Zeki; Albayrak, Merih Dilan

2016-01-01

Retrospective cohort study. Facet joints are considered a common source of chronic low-back pain. To determine whether pathogens related to the facet joint arthritis have any effect on treatment failure. Facet joint injection was applied to 94 patients treated at our hospital between 2011 and 2012 (mean age 59.5 years; 80 women and 14 men). For the purpose of analysis, the patients were divided into two groups. Patients who only had facet hypertrophy were placed in group A (47 patients, 41 women and 6 men, mean age 55.3 years) and patients who had any additional major pathology to facet hypertrophy were placed in group B (47 patients, 39 women and 8 men, mean age 58.9 years). Injections were applied around the facet joint under surgical conditions utilizing fluoroscopy device guidance. A mixture of methylprednisolone and lidocaine was used as the injection ingredient. In terms of Oswestry Disability Index (ODI) and visual analog scale (VAS) scores, no significant difference was found between preinjection and immediate postinjection values in both groups, and the scores of group A patients were significantly lower (P < 0.005) compared with that of group B patients at the end of the third, sixth, and twelfth month. For low-back pain caused by facet hypertrophy, steroid injection around the facet joint is an effective treatment, but if there is an existing major pathology, it is not as effective.

Prosthetic joint infection caused by Granulicatella adiacens: a case series and review of literature.

PubMed

Quénard, Fanny; Seng, Piseth; Lagier, Jean-Christophe; Fenollar, Florence; Stein, Andreas

2017-06-23

Bone and joint infection involving Granulicatella adiacens is rare, and mainly involved in cases of bacteremia and infectious endocarditis. Here we report three cases of prosthetic joint infection involving G. adiacens that were successfully treated with surgery and prolonged antimicrobial treatment. We also review the two cases of prosthetic joint infection involving G. adiacens that are reported in the literature. Not all five cases of prosthetic joint infection caused by G. adiacens were associated with bacteremia or infectious endocarditis. Dental care before the onset of infection was observed in two cases. The median time delay between arthroplasty implantation and the onset of infection was of 4 years (ranging between 2 and 10 years). One of our cases was identified with 16srRNA gene sequencing, one case with MALDI-TOF mass spectrometry, and one case with both techniques. Two literature cases were diagnosed by 16srRNA gene sequencing. All five cases were cured after surgery including a two-stage prosthesis exchange in three cases, a one-stage prosthesis exchange in one case, and debridement, antibiotics, irrigation, and retention of the prosthesis in one case, and prolonged antimicrobial treatment. Prosthetic joint infection involving G. adiacens is probably often dismissed due to difficult culture or misdiagnosis, in particular in the cases of polymicrobial infection. Debridement, antibiotics, irrigation, and retention of the prosthesis associated with prolonged antimicrobial treatment (≥ 8 weeks) should be considered as a treatment strategy for prosthetic joint infection involving G. adiacens.

Joint genome-wide prediction in several populations accounting for randomness of genotypes: A hierarchical Bayes approach. I: Multivariate Gaussian priors for marker effects and derivation of the joint probability mass function of genotypes.

PubMed

Martínez, Carlos Alberto; Khare, Kshitij; Banerjee, Arunava; Elzo, Mauricio A

2017-03-21

It is important to consider heterogeneity of marker effects and allelic frequencies in across population genome-wide prediction studies. Moreover, all regression models used in genome-wide prediction overlook randomness of genotypes. In this study, a family of hierarchical Bayesian models to perform across population genome-wide prediction modeling genotypes as random variables and allowing population-specific effects for each marker was developed. Models shared a common structure and differed in the priors used and the assumption about residual variances (homogeneous or heterogeneous). Randomness of genotypes was accounted for by deriving the joint probability mass function of marker genotypes conditional on allelic frequencies and pedigree information. As a consequence, these models incorporated kinship and genotypic information that not only permitted to account for heterogeneity of allelic frequencies, but also to include individuals with missing genotypes at some or all loci without the need for previous imputation. This was possible because the non-observed fraction of the design matrix was treated as an unknown model parameter. For each model, a simpler version ignoring population structure, but still accounting for randomness of genotypes was proposed. Implementation of these models and computation of some criteria for model comparison were illustrated using two simulated datasets. Theoretical and computational issues along with possible applications, extensions and refinements were discussed. Some features of the models developed in this study make them promising for genome-wide prediction, the use of information contained in the probability distribution of genotypes is perhaps the most appealing. Further studies to assess the performance of the models proposed here and also to compare them with conventional models used in genome-wide prediction are needed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spatial Lattice Modulation for MIMO Systems

NASA Astrophysics Data System (ADS)

Choi, Jiwook; Nam, Yunseo; Lee, Namyoon

2018-06-01

This paper proposes spatial lattice modulation (SLM), a spatial modulation method for multipleinput-multiple-output (MIMO) systems. The key idea of SLM is to jointly exploit spatial, in-phase, and quadrature dimensions to modulate information bits into a multi-dimensional signal set that consists oflattice points. One major finding is that SLM achieves a higher spectral efficiency than the existing spatial modulation and spatial multiplexing methods for the MIMO channel under the constraint ofM-ary pulseamplitude-modulation (PAM) input signaling per dimension. In particular, it is shown that when the SLM signal set is constructed by using dense lattices, a significant signal-to-noise-ratio (SNR) gain, i.e., a nominal coding gain, is attainable compared to the existing methods. In addition, closed-form expressions for both the average mutual information and average symbol-vector-error-probability (ASVEP) of generic SLM are derived under Rayleigh-fading environments. To reduce detection complexity, a low-complexity detection method for SLM, which is referred to as lattice sphere decoding, is developed by exploiting lattice theory. Simulation results verify the accuracy of the conducted analysis and demonstrate that the proposed SLM techniques achieve higher average mutual information and lower ASVEP than do existing methods.

Determination of Cluster Distances from Chandra Imaging Spectroscopy and Sunyaev-Zeldovich Effect Measurements. I; Analysis Methods and Initial Results

NASA Technical Reports Server (NTRS)

Bonamente, Massimiliano; Joy, Marshall K.; Carlstrom, John E.; LaRoque, Samuel J.

2004-01-01

X-ray and Sunyaev-Zeldovich Effect data ca,n be combined to determine the distance to galaxy clusters. High-resolution X-ray data are now available from the Chandra Observatory, which provides both spatial and spectral information, and interferometric radio measurements of the Sunyam-Zeldovich Effect are available from the BIMA and 0VR.O arrays. We introduce a Monte Carlo Markov chain procedure for the joint analysis of X-ray and Sunyaev-Zeldovich Effect data. The advantages of this method are the high computational efficiency and the ability to measure the full probability distribution of all parameters of interest, such as the spatial and spectral properties of the cluster gas and the cluster distance. We apply this technique to the Chandra X-ray data and the OVRO radio data for the galaxy cluster Abell 611. Comparisons with traditional likelihood-ratio methods reveal the robustness of the method. This method will be used in a follow-up paper to determine the distance of a large sample of galaxy clusters for which high-resolution Chandra X-ray and BIMA/OVRO radio data are available.

Labeled RFS-Based Track-Before-Detect for Multiple Maneuvering Targets in the Infrared Focal Plane Array.

PubMed

Li, Miao; Li, Jun; Zhou, Yiyu

2015-12-08

The problem of jointly detecting and tracking multiple targets from the raw observations of an infrared focal plane array is a challenging task, especially for the case with uncertain target dynamics. In this paper a multi-model labeled multi-Bernoulli (MM-LMB) track-before-detect method is proposed within the labeled random finite sets (RFS) framework. The proposed track-before-detect method consists of two parts-MM-LMB filter and MM-LMB smoother. For the MM-LMB filter, original LMB filter is applied to track-before-detect based on target and measurement models, and is integrated with the interacting multiple models (IMM) approach to accommodate the uncertainty of target dynamics. For the MM-LMB smoother, taking advantage of the track labels and posterior model transition probability, the single-model single-target smoother is extended to a multi-model multi-target smoother. A Sequential Monte Carlo approach is also presented to implement the proposed method. Simulation results show the proposed method can effectively achieve tracking continuity for multiple maneuvering targets. In addition, compared with the forward filtering alone, our method is more robust due to its combination of forward filtering and backward smoothing.

Labeled RFS-Based Track-Before-Detect for Multiple Maneuvering Targets in the Infrared Focal Plane Array

PubMed Central

Li, Miao; Li, Jun; Zhou, Yiyu

2015-01-01

The problem of jointly detecting and tracking multiple targets from the raw observations of an infrared focal plane array is a challenging task, especially for the case with uncertain target dynamics. In this paper a multi-model labeled multi-Bernoulli (MM-LMB) track-before-detect method is proposed within the labeled random finite sets (RFS) framework. The proposed track-before-detect method consists of two parts—MM-LMB filter and MM-LMB smoother. For the MM-LMB filter, original LMB filter is applied to track-before-detect based on target and measurement models, and is integrated with the interacting multiple models (IMM) approach to accommodate the uncertainty of target dynamics. For the MM-LMB smoother, taking advantage of the track labels and posterior model transition probability, the single-model single-target smoother is extended to a multi-model multi-target smoother. A Sequential Monte Carlo approach is also presented to implement the proposed method. Simulation results show the proposed method can effectively achieve tracking continuity for multiple maneuvering targets. In addition, compared with the forward filtering alone, our method is more robust due to its combination of forward filtering and backward smoothing. PMID:26670234

Comparison of the use of notched wedge joints vs. traditional butt joints in Connecticut

DOT National Transportation Integrated Search

2008-11-07

Performance of Hot Mix Asphalt (HMA) longitudinal joints have been an item of increasing scrutiny in : Connecticut. The traditional butt joint has typically been the method used in Connecticut. These joints : have been reportedly opening up, creating...

An activity canyon characterization of the pharmacological topography.

PubMed

Kulkarni, Varsha S; Wild, David J

2016-01-01

Highly chemically similar drugs usually possess similar biological activities, but sometimes, small changes in chemistry can result in a large difference in biological effects. Chemically similar drug pairs that show extreme deviations in activity represent distinctive drug interactions having important implications. These associations between chemical and biological similarity are studied as discontinuities in activity landscapes. Particularly, activity cliffs are quantified by the drop in similar activity of chemically similar drugs. In this paper, we construct a landscape using a large drug-target network and consider the rises in similarity and variation in activity along the chemical space. Detailed analysis of structure and activity gives a rigorous quantification of distinctive pairs and the probability of their occurrence. We analyze pairwise similarity (s) and variation (d) in activity of drugs on proteins. Interactions between drugs are quantified by considering pairwise s and d weights jointly with corresponding chemical similarity (c) weights. Similarity and variation in activity are measured as the number of common and uncommon targets of two drugs respectively. Distinctive interactions occur between drugs having high c and above (below) average d (s). Computation of predicted probability of distinctiveness employs joint probability of c, s and of c, d assuming independence of structure and activity. Predictions conform with the observations at different levels of distinctiveness. Results are validated on the data used and another drug ensemble. In the landscape, while s and d decrease as c increases, d maintains value more than s. c ∈ [0.3, 0.64] is the transitional region where rises in d are significantly greater than drops in s. It is fascinating that distinctive interactions filtered with high d and low s are different in nature. It is crucial that high c interactions are more probable of having above average d than s. Identification of distinctive interactions is better with high d than low s. These interactions belong to diverse classes. d is greatest between drugs and analogs prepared for treatment of same class of ailments but with different therapeutic specifications. In contrast, analogs having low s would treat ailments from distinct classes. Intermittent spikes in d along the axis of c represent canyons in the activity landscape. This new representation accounts for distinctiveness through relative rises in s and d. It provides a mathematical basis for predicting the probability of occurrence of distinctiveness. It identifies the drug pairs at varying levels of distinctiveness and non-distinctiveness. The predicted probability formula is validated even if data approximately satisfy the conditions of its construction. Also, the postulated independence of structure and activity is of little significance to the overall assessment. The difference in distinctive interactions obtained by s and d highlights the importance of studying both of them, and reveals how the choice of measurement can affect the interpretation. The methods in this paper can be used to interpret whether or not drug interactions are distinctive and the probability of their occurrence. Practitioners and researchers can rely on this identification for quantitative modeling and assessment.

A parameters optimization method for planar joint clearance model and its application for dynamics simulation of reciprocating compressor

NASA Astrophysics Data System (ADS)

Hai-yang, Zhao; Min-qiang, Xu; Jin-dong, Wang; Yong-bo, Li

2015-05-01

In order to improve the accuracy of dynamics response simulation for mechanism with joint clearance, a parameter optimization method for planar joint clearance contact force model was presented in this paper, and the optimized parameters were applied to the dynamics response simulation for mechanism with oversized joint clearance fault. By studying the effect of increased clearance on the parameters of joint clearance contact force model, the relation of model parameters between different clearances was concluded. Then the dynamic equation of a two-stage reciprocating compressor with four joint clearances was developed using Lagrange method, and a multi-body dynamic model built in ADAMS software was used to solve this equation. To obtain a simulated dynamic response much closer to that of experimental tests, the parameters of joint clearance model, instead of using the designed values, were optimized by genetic algorithms approach. Finally, the optimized parameters were applied to simulate the dynamics response of model with oversized joint clearance fault according to the concluded parameter relation. The dynamics response of experimental test verified the effectiveness of this application.

The Standard Deviation of Differential Index as an innovation diagnostic tool based on kinematic parameters for objective assessment of a upper limb motion pathology.

PubMed

Jurkojć, Jacek; Wodarski, Piotr; Michnik, Robert A; Bieniek, Andrzej; Gzik, Marek; Granek, Arkadiusz

2017-01-01

Indexing methods are very popular in terms of determining the degree of disability associated with motor dysfunctions. Currently, indexing methods dedicated to the upper limbs are not very popular, probably due to difficulties in their interpretation. This work presents the calculation algorithm of new SDDI index and the attempt is made to determine the level of physical dysfunction along with description of its kind, based on the interpretation of the calculation results of SDDI and PULMI indices. 23 healthy people (10 women and 13 men), which constituted a reference group, and a group of 3 people with mobility impairments participated in the tests. In order to examine possibilities of the utilization of the SDDI index the participants had to repetitively perform two selected rehabilitation movements of upper extremities. During the tests the kinematic value was registered using inertial motion analysis system MVN BIOMECH. The results of the test were collected in waveforms of 9 anatomical angles in 4 joints of upper extremities. Then, SDDI and PULMI indices were calculated for each person with mobility impairments. Next, the analysis was performed to check which abnormalities in upper extremity motion can influence the value of both indexes and interpretation of those indexes was shown. Joint analysis of the both indices provides information on whether the patient has correctly performed the set sequence of movement and enables the determination of possible irregularities in the performance of movement given.

Clinical outcomes of the Cadenat procedure in the treatment of acromioclavicular joint dislocations.

PubMed

Moriyama, Hiroaki; Gotoh, Masafumi; Mitsui, Yasuhiro; Yoshikawa, Eiichirou; Uryu, Takuya; Okawa, Takahiro; Higuchi, Fujio; Shirahama, Masahiro; Shiba, Naoto

2014-01-01

We report our clinical experience using the modified Cadenat method to treat acromioclavicular joint dislocation, and discuss the usefulness of this method. This study examined 6 shoulders in 6 patients (5 males, 1 female) who were diagnosed with acromioclavicular joint dislocation and treated with the modified Cadenat method at our hospital. Average age at onset was 49.3 years (26-78 years), average time interval from injury until surgery was 263.8 days (10 to 1100 days), and the average follow-up period was 21.7 months (12 to 42 months). Post-operative assessment was performed using plain radiographs to determine shoulder joint dislocation rate and Japanese Orthopaedic Association (JOA) score. The average post-operative JOA score was 94.1 points (91 to 100 points). The acromioclavicular joint dislocation rate improved from 148.7% (72 to 236%) before surgery to 28.6% (0 to 60%) after surgery. Conservative treatment has been reported to achieve good outcomes in acromioclavicular joint dislocations. However, many patients also experience chronic pain or a sensation of fatigue upon putting the extremity in an elevated posture, and therefore ensuring the stability of the acromioclavicular joint is crucial for highly active patients. In this study, we treated acromioclavicular joint dislocations by the modified Cadenat method, and were able to achieve favorable outcomes.

Clustered multistate models with observation level random effects, mover-stayer effects and dynamic covariates: modelling transition intensities and sojourn times in a study of psoriatic arthritis.

PubMed

Yiu, Sean; Farewell, Vernon T; Tom, Brian D M

2018-02-01

In psoriatic arthritis, it is important to understand the joint activity (represented by swelling and pain) and damage processes because both are related to severe physical disability. The paper aims to provide a comprehensive investigation into both processes occurring over time, in particular their relationship, by specifying a joint multistate model at the individual hand joint level, which also accounts for many of their important features. As there are multiple hand joints, such an analysis will be based on the use of clustered multistate models. Here we consider an observation level random-effects structure with dynamic covariates and allow for the possibility that a subpopulation of patients is at minimal risk of damage. Such an analysis is found to provide further understanding of the activity-damage relationship beyond that provided by previous analyses. Consideration is also given to the modelling of mean sojourn times and jump probabilities. In particular, a novel model parameterization which allows easily interpretable covariate effects to act on these quantities is proposed.

POPPER, a simple programming language for probabilistic semantic inference in medicine.

PubMed

Robson, Barry

2015-01-01

Our previous reports described the use of the Hyperbolic Dirac Net (HDN) as a method for probabilistic inference from medical data, and a proposed probabilistic medical Semantic Web (SW) language Q-UEL to provide that data. Rather like a traditional Bayes Net, that HDN provided estimates of joint and conditional probabilities, and was static, with no need for evolution due to "reasoning". Use of the SW will require, however, (a) at least the semantic triple with more elaborate relations than conditional ones, as seen in use of most verbs and prepositions, and (b) rules for logical, grammatical, and definitional manipulation that can generate changes in the inference net. Here is described the simple POPPER language for medical inference. It can be automatically written by Q-UEL, or by hand. Based on studies with our medical students, it is believed that a tool like this may help in medical education and that a physician unfamiliar with SW science can understand it. It is here used to explore the considerable challenges of assigning probabilities, and not least what the meaning and utility of inference net evolution would be for a physician. Copyright © 2014 Elsevier Ltd. All rights reserved.

[Multivariate analysis of factors influencing the effect of radiosynovectomy].

PubMed

Farahati, J; Schulz, G; Wendler, J; Körber, C; Geling, M; Kenn, W; Schmeider, P; Reidemeister, C; Reiners, Chr

2002-04-01

In this prospective study, the time to remission after Radiosynovectomy (RSV) was analyzed and the influence of age, sex, underlying disease, type of joint, and duration of illness on the success rate of RSV was determined. A total number of 57 patients with rheumatoid arthritis (n = 33) and arthrosis (n = 21) with a total number of 130 treated joints (36 knee, 66 small and 28 medium-size joints) were monitored using visual analogue scales (VAS) from one week before RSV up to four to six months after RSV. The patients had to answer 3 times daily for pain intensity of the treated joint. The time until remission was determined according to the Kaplan-Meier survivorship function. The influence of the prognosis parameters on outcome of RSV was determined by multivariate discriminant analysis. After six months, the probability of pain relief of more than 20% amounted to 78% and was significantly dependent on the age of the patient (p = 0.02) and the duration of illness (p = 0.05), however not on sex (p = 0.17), underlying disease (p = 0.23), and type of joint (p = 0.69). Irrespective of sex, type of joint and underlying disease, a measurable pain relief can be achieved with RSV in 78% of the patients with synovitis, whereby effectiveness is decreasing with increasing age and progress of illness.

Generalized Cross Entropy Method for estimating joint distribution from incomplete information

NASA Astrophysics Data System (ADS)

Xu, Hai-Yan; Kuo, Shyh-Hao; Li, Guoqi; Legara, Erika Fille T.; Zhao, Daxuan; Monterola, Christopher P.

2016-07-01

Obtaining a full joint distribution from individual marginal distributions with incomplete information is a non-trivial task that continues to challenge researchers from various domains including economics, demography, and statistics. In this work, we develop a new methodology referred to as ;Generalized Cross Entropy Method; (GCEM) that is aimed at addressing the issue. The objective function is proposed to be a weighted sum of divergences between joint distributions and various references. We show that the solution of the GCEM is unique and global optimal. Furthermore, we illustrate the applicability and validity of the method by utilizing it to recover the joint distribution of a household profile of a given administrative region. In particular, we estimate the joint distribution of the household size, household dwelling type, and household home ownership in Singapore. Results show a high-accuracy estimation of the full joint distribution of the household profile under study. Finally, the impact of constraints and weight on the estimation of joint distribution is explored.

An algorithm for continuum modeling of rocks with multiple embedded nonlinearly-compliant joints [Continuum modeling of elasto-plastic media with multiple embedded nonlinearly-compliant joints

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hurley, R. C.; Vorobiev, O. Y.; Ezzedine, S. M.

Here, we present a numerical method for modeling the mechanical effects of nonlinearly-compliant joints in elasto-plastic media. The method uses a series of strain-rate and stress update algorithms to determine joint closure, slip, and solid stress within computational cells containing multiple “embedded” joints. This work facilitates efficient modeling of nonlinear wave propagation in large spatial domains containing a large number of joints that affect bulk mechanical properties. We implement the method within the massively parallel Lagrangian code GEODYN-L and provide verification and examples. We highlight the ability of our algorithms to capture joint interactions and multiple weakness planes within individualmore » computational cells, as well as its computational efficiency. We also discuss the motivation for developing the proposed technique: to simulate large-scale wave propagation during the Source Physics Experiments (SPE), a series of underground explosions conducted at the Nevada National Security Site (NNSS).« less

An algorithm for continuum modeling of rocks with multiple embedded nonlinearly-compliant joints [Continuum modeling of elasto-plastic media with multiple embedded nonlinearly-compliant joints

DOE PAGES

Hurley, R. C.; Vorobiev, O. Y.; Ezzedine, S. M.

2017-04-06

Here, we present a numerical method for modeling the mechanical effects of nonlinearly-compliant joints in elasto-plastic media. The method uses a series of strain-rate and stress update algorithms to determine joint closure, slip, and solid stress within computational cells containing multiple “embedded” joints. This work facilitates efficient modeling of nonlinear wave propagation in large spatial domains containing a large number of joints that affect bulk mechanical properties. We implement the method within the massively parallel Lagrangian code GEODYN-L and provide verification and examples. We highlight the ability of our algorithms to capture joint interactions and multiple weakness planes within individualmore » computational cells, as well as its computational efficiency. We also discuss the motivation for developing the proposed technique: to simulate large-scale wave propagation during the Source Physics Experiments (SPE), a series of underground explosions conducted at the Nevada National Security Site (NNSS).« less

Marker-based reconstruction of the kinematics of a chain of segments: a new method that incorporates joint kinematic constraints.

PubMed

Klous, Miriam; Klous, Sander

2010-07-01

The aim of skin-marker-based motion analysis is to reconstruct the motion of a kinematical model from noisy measured motion of skin markers. Existing kinematic models for reconstruction of chains of segments can be divided into two categories: analytical methods that do not take joint constraints into account and numerical global optimization methods that do take joint constraints into account but require numerical optimization of a large number of degrees of freedom, especially when the number of segments increases. In this study, a new and largely analytical method for a chain of rigid bodies is presented, interconnected in spherical joints (chain-method). In this method, the number of generalized coordinates to be determined through numerical optimization is three, irrespective of the number of segments. This new method is compared with the analytical method of Veldpaus et al. [1988, "A Least-Squares Algorithm for the Equiform Transformation From Spatial Marker Co-Ordinates," J. Biomech., 21, pp. 45-54] (Veldpaus-method, a method of the first category) and the numerical global optimization method of Lu and O'Connor [1999, "Bone Position Estimation From Skin-Marker Co-Ordinates Using Global Optimization With Joint Constraints," J. Biomech., 32, pp. 129-134] (Lu-method, a method of the second category) regarding the effects of continuous noise simulating skin movement artifacts and regarding systematic errors in joint constraints. The study is based on simulated data to allow a comparison of the results of the different algorithms with true (noise- and error-free) marker locations. Results indicate a clear trend that accuracy for the chain-method is higher than the Veldpaus-method and similar to the Lu-method. Because large parts of the equations in the chain-method can be solved analytically, the speed of convergence in this method is substantially higher than in the Lu-method. With only three segments, the average number of required iterations with the chain-method is 3.0+/-0.2 times lower than with the Lu-method when skin movement artifacts are simulated by applying a continuous noise model. When simulating systematic errors in joint constraints, the number of iterations for the chain-method was almost a factor 5 lower than the number of iterations for the Lu-method. However, the Lu-method performs slightly better than the chain-method. The RMSD value between the reconstructed and actual marker positions is approximately 57% of the systematic error on the joint center positions for the Lu-method compared with 59% for the chain-method.

A Basis Function Approach to Simulate Storm Surge Events for Coastal Flood Risk Assessment

NASA Astrophysics Data System (ADS)

Wu, Wenyan; Westra, Seth; Leonard, Michael

2017-04-01

Storm surge is a significant contributor to flooding in coastal and estuarine regions, especially when it coincides with other flood producing mechanisms, such as extreme rainfall. Therefore, storm surge has always been a research focus in coastal flood risk assessment. Often numerical models have been developed to understand storm surge events for risk assessment (Kumagai et al. 2016; Li et al. 2016; Zhang et al. 2016) (Bastidas et al. 2016; Bilskie et al. 2016; Dalledonne and Mayerle 2016; Haigh et al. 2014; Kodaira et al. 2016; Lapetina and Sheng 2015), and assess how these events may change or evolve in the future (Izuru et al. 2015; Oey and Chou 2016). However, numeric models often require a lot of input information and difficulties arise when there are not sufficient data available (Madsen et al. 2015). Alternative, statistical methods have been used to forecast storm surge based on historical data (Hashemi et al. 2016; Kim et al. 2016) or to examine the long term trend in the change of storm surge events, especially under climate change (Balaguru et al. 2016; Oh et al. 2016; Rueda et al. 2016). In these studies, often the peak of surge events is used, which result in the loss of dynamic information within a tidal cycle or surge event (i.e. a time series of storm surge values). In this study, we propose an alternative basis function (BF) based approach to examine the different attributes (e.g. peak and durations) of storm surge events using historical data. Two simple two-parameter BFs were used: the exponential function and the triangular function. High quality hourly storm surge record from 15 tide gauges around Australia were examined. It was found that there are significantly location and seasonal variability in the peak and duration of storm surge events, which provides additional insights in coastal flood risk. In addition, the simple form of these BFs allows fast simulation of storm surge events and minimises the complexity of joint probability analysis for flood risk analysis considering multiple flood producing mechanisms. This is the first step in applying a Monte Carlo based joint probability method for flood risk assessment.

Lithological and Surface Geometry Joint Inversions Using Multi-Objective Global Optimization Methods

NASA Astrophysics Data System (ADS)

Lelièvre, Peter; Bijani, Rodrigo; Farquharson, Colin

2016-04-01

Geologists' interpretations about the Earth typically involve distinct rock units with contacts (interfaces) between them. In contrast, standard minimum-structure geophysical inversions are performed on meshes of space-filling cells (typically prisms or tetrahedra) and recover smoothly varying physical property distributions that are inconsistent with typical geological interpretations. There are several approaches through which mesh-based minimum-structure geophysical inversion can help recover models with some of the desired characteristics. However, a more effective strategy may be to consider two fundamentally different types of inversions: lithological and surface geometry inversions. A major advantage of these two inversion approaches is that joint inversion of multiple types of geophysical data is greatly simplified. In a lithological inversion, the subsurface is discretized into a mesh and each cell contains a particular rock type. A lithological model must be translated to a physical property model before geophysical data simulation. Each lithology may map to discrete property values or there may be some a priori probability density function associated with the mapping. Through this mapping, lithological inverse problems limit the parameter domain and consequently reduce the non-uniqueness from that presented by standard mesh-based inversions that allow physical property values on continuous ranges. Furthermore, joint inversion is greatly simplified because no additional mathematical coupling measure is required in the objective function to link multiple physical property models. In a surface geometry inversion, the model comprises wireframe surfaces representing contacts between rock units. This parameterization is then fully consistent with Earth models built by geologists, which in 3D typically comprise wireframe contact surfaces of tessellated triangles. As for the lithological case, the physical properties of the units lying between the contact surfaces are set to a priori values. The inversion is tasked with calculating the geometry of the contact surfaces instead of some piecewise distribution of properties in a mesh. Again, no coupling measure is required and joint inversion is simplified. Both of these inverse problems involve high nonlinearity and discontinuous or non-obtainable derivatives. They can also involve the existence of multiple minima. Hence, one can not apply the standard descent-based local minimization methods used to solve typical minimum-structure inversions. Instead, we are applying Pareto multi-objective global optimization (PMOGO) methods, which generate a suite of solutions that minimize multiple objectives (e.g. data misfits and regularization terms) in a Pareto-optimal sense. Providing a suite of models, as opposed to a single model that minimizes a weighted sum of objectives, allows a more complete assessment of the possibilities and avoids the often difficult choice of how to weight each objective. While there are definite advantages to PMOGO joint inversion approaches, the methods come with significantly increased computational requirements. We are researching various strategies to ameliorate these computational issues including parallelization and problem dimension reduction.

Bayesian analysis of the flutter margin method in aeroelasticity

DOE PAGES

Khalil, Mohammad; Poirel, Dominique; Sarkar, Abhijit

2016-08-27

A Bayesian statistical framework is presented for Zimmerman and Weissenburger flutter margin method which considers the uncertainties in aeroelastic modal parameters. The proposed methodology overcomes the limitations of the previously developed least-square based estimation technique which relies on the Gaussian approximation of the flutter margin probability density function (pdf). Using the measured free-decay responses at subcritical (preflutter) airspeeds, the joint non-Gaussain posterior pdf of the modal parameters is sampled using the Metropolis–Hastings (MH) Markov chain Monte Carlo (MCMC) algorithm. The posterior MCMC samples of the modal parameters are then used to obtain the flutter margin pdfs and finally the fluttermore » speed pdf. The usefulness of the Bayesian flutter margin method is demonstrated using synthetic data generated from a two-degree-of-freedom pitch-plunge aeroelastic model. The robustness of the statistical framework is demonstrated using different sets of measurement data. In conclusion, it will be shown that the probabilistic (Bayesian) approach reduces the number of test points required in providing a flutter speed estimate for a given accuracy and precision.« less

Sequential bearings-only-tracking initiation with particle filtering method.

PubMed

Liu, Bin; Hao, Chengpeng

2013-01-01

The tracking initiation problem is examined in the context of autonomous bearings-only-tracking (BOT) of a single appearing/disappearing target in the presence of clutter measurements. In general, this problem suffers from a combinatorial explosion in the number of potential tracks resulted from the uncertainty in the linkage between the target and the measurement (a.k.a the data association problem). In addition, the nonlinear measurements lead to a non-Gaussian posterior probability density function (pdf) in the optimal Bayesian sequential estimation framework. The consequence of this nonlinear/non-Gaussian context is the absence of a closed-form solution. This paper models the linkage uncertainty and the nonlinear/non-Gaussian estimation problem jointly with solid Bayesian formalism. A particle filtering (PF) algorithm is derived for estimating the model's parameters in a sequential manner. Numerical results show that the proposed solution provides a significant benefit over the most commonly used methods, IPDA and IMMPDA. The posterior Cramér-Rao bounds are also involved for performance evaluation.

Fuzzy Intervals for Designing Structural Signature: An Application to Graphic Symbol Recognition

NASA Astrophysics Data System (ADS)

Luqman, Muhammad Muzzamil; Delalandre, Mathieu; Brouard, Thierry; Ramel, Jean-Yves; Lladós, Josep

The motivation behind our work is to present a new methodology for symbol recognition. The proposed method employs a structural approach for representing visual associations in symbols and a statistical classifier for recognition. We vectorize a graphic symbol, encode its topological and geometrical information by an attributed relational graph and compute a signature from this structural graph. We have addressed the sensitivity of structural representations to noise, by using data adapted fuzzy intervals. The joint probability distribution of signatures is encoded by a Bayesian network, which serves as a mechanism for pruning irrelevant features and choosing a subset of interesting features from structural signatures of underlying symbol set. The Bayesian network is deployed in a supervised learning scenario for recognizing query symbols. The method has been evaluated for robustness against degradations & deformations on pre-segmented 2D linear architectural & electronic symbols from GREC databases, and for its recognition abilities on symbols with context noise i.e. cropped symbols.

A method for the automated construction of the joint system of equations to solve the problem of the flow distribution in hydraulic networks

NASA Astrophysics Data System (ADS)

Novikov, A. E.

1993-10-01

There are several methods of solving the problem of the flow distribution in hydraulic networks. But all these methods have no mathematical tools for forming joint systems of equations to solve this problem. This paper suggests a method of constructing joint systems of equations to calculate hydraulic circuits of the arbitrary form. The graph concept, according to Kirchhoff, has been introduced.

Method of forming a ceramic to ceramic joint

DOEpatents

Cutler, Raymond Ashton; Hutchings, Kent Neal; Kleinlein, Brian Paul; Carolan, Michael Francis

2010-04-13

A method of joining at least two sintered bodies to form a composite structure, includes: providing a joint material between joining surfaces of first and second sintered bodies; applying pressure from 1 kP to less than 5 MPa to provide an assembly; heating the assembly to a conforming temperature sufficient to allow the joint material to conform to the joining surfaces; and further heating the assembly to a joining temperature below a minimum sintering temperature of the first and second sintered bodies. The joint material includes organic component(s) and ceramic particles. The ceramic particles constitute 40-75 vol. % of the joint material, and include at least one element of the first and/or second sintered bodies. Composite structures produced by the method are also disclosed.

Comparison of the use of a notched wedge joint vs. traditional butt joints in Connecticut : phase 1 report.

DOT National Transportation Integrated Search

2008-05-14

Performance of Hot Mix Asphalt (HMA) longitudinal joints have been an : item of increasing scrutiny in Connecticut. The traditional butt joint : has typically been the method used in Connecticut. These joints have : been reportedly opening up creatin...

Fluoroscopy-Guided Sacroiliac Intraarticular Injection via the Middle Portion of the Joint.

PubMed

Kurosawa, Daisuke; Murakami, Eiichi; Aizawa, Toshimi

2017-09-01

Sacroiliac intraarticular injection is necessary to confirm sacroiliac joint (SIJ) pain and is usually performed via the caudal one-third portion of the joint. However, this is occasionally impossible for anatomical reasons, and the success rate is low in clinical settings. We describe a technique via the middle portion of the joint. Observational study. Enrolled were 69 consecutive patients (27 men and 42 women, with an average age of 53 years) in whom the middle portion of 100 joints was targeted. With the patient lying prone-oblique with the painful side down, a spinal needle was inserted into the middle portion of the joint. Subsequently, the fluoroscopy tube was angled at a caudal tilt of 25-30° to clearly detect the recess between the ilium and sacrum and the needle depth and direction. When the needle reached the posterior joint line, 2% lidocaine was injected after the contrast medium outlined the joint. The success rate of the injection method was 80% (80/100). Among 80 successful cases, four were previously unsuccessful when the conventional method was used. Intraarticular injection using the new technique was unsuccessful in 20 joints; in three of these cases, the conventional method proved successful, and no techniques were successful in the other 17 cases. The injection technique via the middle portion of the joint can overcome some of the difficulties of the conventional injection method and can improve the chances of successful intraarticular injection. © 2016 American Academy of Pain Medicine. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Central sensitization as the mechanism underlying pain in joint hypermobility syndrome/Ehlers-Danlos syndrome, hypermobility type.

PubMed

Di Stefano, G; Celletti, C; Baron, R; Castori, M; Di Franco, M; La Cesa, S; Leone, C; Pepe, A; Cruccu, G; Truini, A; Camerota, F

2016-09-01

Patients with joint hypermobility syndrome/Ehlers-Danlos syndrome, hypermobility type (JHS/EDS-HT) commonly suffer from pain. How this hereditary connective tissue disorder causes pain remains unclear although previous studies suggested it shares similar mechanisms with neuropathic pain and fibromyalgia. In this prospective study seeking information on the mechanisms underlying pain in patients with JHS/EDS-HT, we enrolled 27 consecutive patients with this connective tissue disorder. Patients underwent a detailed clinical examination, including the neuropathic pain questionnaire DN4 and the fibromyalgia rapid screening tool. As quantitative sensory testing methods, we included thermal-pain perceptive thresholds and the wind-up ratio and recorded a standard nerve conduction study to assess non-nociceptive fibres and laser-evoked potentials, assessing nociceptive fibres. Clinical examination and diagnostic tests disclosed no somatosensory nervous system damage. Conversely, most patients suffered from widespread pain, the fibromyalgia rapid screening tool elicited positive findings, and quantitative sensory testing showed lowered cold and heat pain thresholds and an increased wind-up ratio. While the lack of somatosensory nervous system damage is incompatible with neuropathic pain as the mechanism underlying pain in JHS/EDS-HT, the lowered cold and heat pain thresholds and increased wind-up ratio imply that pain in JHS/EDS-HT might arise through central sensitization. Hence, this connective tissue disorder and fibromyalgia share similar pain mechanisms. WHAT DOES THIS STUDY ADD?: In patients with JHS/EDS-HT, the persistent nociceptive input due to joint abnormalities probably triggers central sensitization in the dorsal horn neurons and causes widespread pain. © 2016 European Pain Federation - EFIC®

On the use of information theory for the analysis of synchronous nociceptive withdrawal reflexes and somatosensory evoked potentials elicited by graded electrical stimulation.

PubMed

Arguissain, Federico G; Biurrun Manresa, José A; Mørch, Carsten D; Andersen, Ole K

2015-01-30

To date, few studies have combined the simultaneous acquisition of nociceptive withdrawal reflexes (NWR) and somatosensory evoked potentials (SEPs). In fact, it is unknown whether the combination of these two signals acquired simultaneously could provide additional information on somatosensory processing at spinal and supraspinal level compared to individual NWR and SEP signals. By using the concept of mutual information (MI), it is possible to quantify the relation between electrical stimuli and simultaneous elicited electrophysiological responses in humans based on the estimated stimulus-response signal probability distributions. All selected features from NWR and SEPs were informative in regard to the stimulus when considered individually. Specifically, the information carried by NWR features was significantly higher than the information contained in the SEP features (p<0.05). Moreover, the joint information carried by the combination of features showed an overall redundancy compared to the sum of the individual contributions. Comparison with existing methods MI can be used to quantify the information that single-trial NWR and SEP features convey, as well as the information carried jointly by NWR and SEPs. This is a model-free approach that considers linear and non-linear correlations at any order and is not constrained by parametric assumptions. The current study introduces a novel approach that allows the quantification of the individual and joint information content of single-trial NWR and SEP features. This methodology could be used to decode and interpret spinal and supraspinal interaction in studies modulating the responsiveness of the nociceptive system. Copyright © 2014 Elsevier B.V. All rights reserved.

Better Informing Decision Making with Multiple Outcomes Cost-Effectiveness Analysis under Uncertainty in Cost-Disutility Space

PubMed Central

McCaffrey, Nikki; Agar, Meera; Harlum, Janeane; Karnon, Jonathon; Currow, David; Eckermann, Simon

2015-01-01

Introduction Comparing multiple, diverse outcomes with cost-effectiveness analysis (CEA) is important, yet challenging in areas like palliative care where domains are unamenable to integration with survival. Generic multi-attribute utility values exclude important domains and non-health outcomes, while partial analyses—where outcomes are considered separately, with their joint relationship under uncertainty ignored—lead to incorrect inference regarding preferred strategies. Objective The objective of this paper is to consider whether such decision making can be better informed with alternative presentation and summary measures, extending methods previously shown to have advantages in multiple strategy comparison. Methods Multiple outcomes CEA of a home-based palliative care model (PEACH) relative to usual care is undertaken in cost disutility (CDU) space and compared with analysis on the cost-effectiveness plane. Summary measures developed for comparing strategies across potential threshold values for multiple outcomes include: expected net loss (ENL) planes quantifying differences in expected net benefit; the ENL contour identifying preferred strategies minimising ENL and their expected value of perfect information; and cost-effectiveness acceptability planes showing probability of strategies minimising ENL. Results Conventional analysis suggests PEACH is cost-effective when the threshold value per additional day at home ( 1) exceeds $1,068 or dominated by usual care when only the proportion of home deaths is considered. In contrast, neither alternative dominate in CDU space where cost and outcomes are jointly considered, with the optimal strategy depending on threshold values. For example, PEACH minimises ENL when 1=$2,000 and 2=$2,000 (threshold value for dying at home), with a 51.6% chance of PEACH being cost-effective. Conclusion Comparison in CDU space and associated summary measures have distinct advantages to multiple domain comparisons, aiding transparent and robust joint comparison of costs and multiple effects under uncertainty across potential threshold values for effect, better informing net benefit assessment and related reimbursement and research decisions. PMID:25751629

Evaluation of the topological characteristics of the turbulent flow in a `box of turbulence' through 2D time-resolved particle image velocimetry

NASA Astrophysics Data System (ADS)

Lian, Huan; Soulopoulos, Nikolaos; Hardalupas, Yannis

2017-09-01

The experimental evaluation of the topological characteristics of the turbulent flow in a `box' of homogeneous and isotropic turbulence (HIT) with zero mean velocity is presented. This requires an initial evaluation of the effect of signal noise on measurement of velocity invariants. The joint probability distribution functions (pdfs) of experimentally evaluated, noise contaminated, velocity invariants have a different shape than the corresponding noise-free joint pdfs obtained from the DNS data of the Johns Hopkins University (JHU) open resource HIT database. A noise model, based on Gaussian and impulsive Salt and Pepper noise, is established and added artificially to the DNS velocity vector field of the JHU database. Digital filtering methods, based on Median and Wiener Filters, are chosen to eliminate the modeled noise source and their capacity to restore the joint pdfs of velocity invariants to that of the noise-free DNS data is examined. The remaining errors after filtering are quantified by evaluating the global mean velocity, turbulent kinetic energy and global turbulent homogeneity, assessed through the behavior of the ratio of the standard deviation of the velocity fluctuations in two directions, the energy spectrum of the velocity fluctuations and the eigenvalues of the rate-of-strain tensor. A method of data filtering, based on median filtered velocity using different median filter window size, is used to quantify the clustering of zero velocity points of the turbulent field using the radial distribution function (RDF) and Voronoï analysis to analyze the 2D time-resolved particle image velocimetry (TR-PIV) velocity measurements. It was found that a median filter with window size 3 × 3 vector spacing is the effective and efficient approach to eliminate the experimental noise from PIV measured velocity images to a satisfactory level and extract the statistical two-dimensional topological turbulent flow patterns.

Joint Probability Models of Radiology Images and Clinical Annotations

ERIC Educational Resources Information Center

Arnold, Corey Wells

2009-01-01

Radiology data, in the form of images and reports, is growing at a high rate due to the introduction of new imaging modalities, new uses of existing modalities, and the growing importance of objective image information in the diagnosis and treatment of patients. This increase has resulted in an enormous set of image data that is richly annotated…

An MDI (Minimum Discrimination Information) Model and an Algorithm for Composite Hypotheses Testing and Estimation in Marketing. Revision 2.

DTIC Science & Technology

1982-09-01

considered to be Markovian and the fact that Ehrenberg has been openly critical of the use of first-order Markov processes in describing consumer ... behavior -/ disinclines us to treating these data in this manner. We Shall therefore interpret the p (i,i) as joint rather than conditional probabilities

INVESTIGATION OF THE USE OF STATISTICS IN COUNSELING STUDENTS.

ERIC Educational Resources Information Center

HEWES, ROBERT F.

THE OBJECTIVE WAS TO EMPLOY TECHNIQUES OF PROFILE ANALYSIS TO DEVELOP THE JOINT PROBABILITY OF SELECTING A SUITABLE SUBJECT MAJOR AND OF ASSURING TO A HIGH DEGREE GRADUATION FROM COLLEGE WITH THAT MAJOR. THE SAMPLE INCLUDED 1,197 MIT FRESHMEN STUDENTS IN 1952-53, AND THE VALIDATION GROUP INCLUDED 699 ENTRANTS IN 1954. DATA INCLUDED SECONDARY…

Enhancing the Classification Accuracy of IP Geolocation

DTIC Science & Technology

2013-10-01

accurately identify the geographic location of Internet devices has signficant implications for online- advertisers, application developers , network...Real Media, Comedy Central, Netflix and Spotify) and target advertising (e.g., Google). More re- cently, IP geolocation techniques have been deployed...distance to delay function and how they triangulate the position of the target. Statistical Geolocation [14] develops a joint probability density

Poliomyelitis causing TMJ ankylosis?--report of two intriguing cases.

PubMed

Pasupathy, Sanjay; Yuvaraj, V

2010-12-01

Temporomandibular joint (TMJ) ankylosis is one of the common diseases which affect the TMJ especially in children. We are reporting two rare cases of TMJ ankylosis which occurred along with poliomyelitis and which are not reported in literature so far. In this article, we discussed about the most probable causes which resulted in TMJ ankylosis in these patients.

Joint Bayesian Estimation of Quasar Continua and the Lyα Forest Flux Probability Distribution Function

NASA Astrophysics Data System (ADS)

Eilers, Anna-Christina; Hennawi, Joseph F.; Lee, Khee-Gan

2017-08-01

We present a new Bayesian algorithm making use of Markov Chain Monte Carlo sampling that allows us to simultaneously estimate the unknown continuum level of each quasar in an ensemble of high-resolution spectra, as well as their common probability distribution function (PDF) for the transmitted Lyα forest flux. This fully automated PDF regulated continuum fitting method models the unknown quasar continuum with a linear principal component analysis (PCA) basis, with the PCA coefficients treated as nuisance parameters. The method allows one to estimate parameters governing the thermal state of the intergalactic medium (IGM), such as the slope of the temperature-density relation γ -1, while marginalizing out continuum uncertainties in a fully Bayesian way. Using realistic mock quasar spectra created from a simplified semi-numerical model of the IGM, we show that this method recovers the underlying quasar continua to a precision of ≃ 7 % and ≃ 10 % at z = 3 and z = 5, respectively. Given the number of principal component spectra, this is comparable to the underlying accuracy of the PCA model itself. Most importantly, we show that we can achieve a nearly unbiased estimate of the slope γ -1 of the IGM temperature-density relation with a precision of +/- 8.6 % at z = 3 and +/- 6.1 % at z = 5, for an ensemble of ten mock high-resolution quasar spectra. Applying this method to real quasar spectra and comparing to a more realistic IGM model from hydrodynamical simulations would enable precise measurements of the thermal and cosmological parameters governing the IGM, albeit with somewhat larger uncertainties, given the increased flexibility of the model.

Simplified Design Method for Tension Fasteners

NASA Astrophysics Data System (ADS)

Olmstead, Jim; Barker, Paul; Vandersluis, Jonathan

2012-07-01

Tension fastened joints design has traditionally been an iterative tradeoff between separation and strength requirements. This paper presents equations for the maximum external load that a fastened joint can support and the optimal preload to achieve this load. The equations, based on linear joint theory, account for separation and strength safety factors and variations in joint geometry, materials, preload, load-plane factor and thermal loading. The strength-normalized versions of the equations are applicable to any fastener and can be plotted to create a "Fastener Design Space", FDS. Any combination of preload and tension that falls within the FDS represents a safe joint design. The equation for the FDS apex represents the optimal preload and load capacity of a set of joints. The method can be used for preliminary design or to evaluate multiple pre-existing joints.

Naive Probability: Model-Based Estimates of Unique Events.

PubMed

Khemlani, Sangeet S; Lotstein, Max; Johnson-Laird, Philip N

2015-08-01

We describe a dual-process theory of how individuals estimate the probabilities of unique events, such as Hillary Clinton becoming U.S. President. It postulates that uncertainty is a guide to improbability. In its computer implementation, an intuitive system 1 simulates evidence in mental models and forms analog non-numerical representations of the magnitude of degrees of belief. This system has minimal computational power and combines evidence using a small repertoire of primitive operations. It resolves the uncertainty of divergent evidence for single events, for conjunctions of events, and for inclusive disjunctions of events, by taking a primitive average of non-numerical probabilities. It computes conditional probabilities in a tractable way, treating the given event as evidence that may be relevant to the probability of the dependent event. A deliberative system 2 maps the resulting representations into numerical probabilities. With access to working memory, it carries out arithmetical operations in combining numerical estimates. Experiments corroborated the theory's predictions. Participants concurred in estimates of real possibilities. They violated the complete joint probability distribution in the predicted ways, when they made estimates about conjunctions: P(A), P(B), P(A and B), disjunctions: P(A), P(B), P(A or B or both), and conditional probabilities P(A), P(B), P(B|A). They were faster to estimate the probabilities of compound propositions when they had already estimated the probabilities of each of their components. We discuss the implications of these results for theories of probabilistic reasoning. © 2014 Cognitive Science Society, Inc.

Probability and possibility-based representations of uncertainty in fault tree analysis.

PubMed

Flage, Roger; Baraldi, Piero; Zio, Enrico; Aven, Terje

2013-01-01

Expert knowledge is an important source of input to risk analysis. In practice, experts might be reluctant to characterize their knowledge and the related (epistemic) uncertainty using precise probabilities. The theory of possibility allows for imprecision in probability assignments. The associated possibilistic representation of epistemic uncertainty can be combined with, and transformed into, a probabilistic representation; in this article, we show this with reference to a simple fault tree analysis. We apply an integrated (hybrid) probabilistic-possibilistic computational framework for the joint propagation of the epistemic uncertainty on the values of the (limiting relative frequency) probabilities of the basic events of the fault tree, and we use possibility-probability (probability-possibility) transformations for propagating the epistemic uncertainty within purely probabilistic and possibilistic settings. The results of the different approaches (hybrid, probabilistic, and possibilistic) are compared with respect to the representation of uncertainty about the top event (limiting relative frequency) probability. Both the rationale underpinning the approaches and the computational efforts they require are critically examined. We conclude that the approaches relevant in a given setting depend on the purpose of the risk analysis, and that further research is required to make the possibilistic approaches operational in a risk analysis context. © 2012 Society for Risk Analysis.

Finite Element Analysis of Increasing Column Section and CFRP Reinforcement Method under Different Axial Compression Ratio

NASA Astrophysics Data System (ADS)

Jinghai, Zhou; Tianbei, Kang; Fengchi, Wang; Xindong, Wang

2017-11-01

Eight less stirrups in the core area frame joints are simulated by ABAQUS finite element numerical software. The composite reinforcement method is strengthened with carbon fiber and increasing column section, the axial compression ratio of reinforced specimens is 0.3, 0.45 and 0.6 respectively. The results of the load-displacement curve, ductility and stiffness are analyzed, and it is found that the different axial compression ratio has great influence on the bearing capacity of increasing column section strengthening method, and has little influence on carbon fiber reinforcement method. The different strengthening schemes improve the ultimate bearing capacity and ductility of frame joints in a certain extent, composite reinforcement joints strengthening method to improve the most significant, followed by increasing column section, reinforcement method of carbon fiber reinforced joints to increase the minimum.

Characterization of 3D joint space morphology using an electrostatic model (with application to osteoarthritis)

NASA Astrophysics Data System (ADS)

Cao, Qian; Thawait, Gaurav; Gang, Grace J.; Zbijewski, Wojciech; Reigel, Thomas; Brown, Tyler; Corner, Brian; Demehri, Shadpour; Siewerdsen, Jeffrey H.

2015-02-01

Joint space morphology can be indicative of the risk, presence, progression, and/or treatment response of disease or trauma. We describe a novel methodology of characterizing joint space morphology in high-resolution 3D images (e.g. cone-beam CT (CBCT)) using a model based on elementary electrostatics that overcomes a variety of basic limitations of existing 2D and 3D methods. The method models each surface of a joint as a conductor at fixed electrostatic potential and characterizes the intra-articular space in terms of the electric field lines resulting from the solution of Gauss’ Law and the Laplace equation. As a test case, the method was applied to discrimination of healthy and osteoarthritic subjects (N = 39) in 3D images of the knee acquired on an extremity CBCT system. The method demonstrated improved diagnostic performance (area under the receiver operating characteristic curve, AUC > 0.98) compared to simpler methods of quantitative measurement and qualitative image-based assessment by three expert musculoskeletal radiologists (AUC = 0.87, p-value = 0.007). The method is applicable to simple (e.g. the knee or elbow) or multi-axial joints (e.g. the wrist or ankle) and may provide a useful means of quantitatively assessing a variety of joint pathologies.

Note: Progress on the use of MgB2 superconducting joint technique for the development of MgB2 magnets for magnetic resonance imaging (MRI).

PubMed

Kim, Y G; Song, J B; Kim, J C; Kim, J M; Yoo, B H; Yun, S B; Hwang, D Y; Lee, H G

2017-08-01

This note presents a superconducting joint technique for the development of MgB 2 magnetic resonance imaging (MRI) magnets. The MgB 2 superconducting joint was fabricated by a powder processing method using Mg and B powders to establish a wire-bulk-wire connection. The joint resistance measured using a field-decay method was <10 -14 Ω, demonstrating that the proposed joint technique could be employed for developing "next-generation" MgB 2 MRI magnets operating in the persistent current mode.

Tiagabine May Reduce Bruxism and Associated Temporomandibular Joint Pain

PubMed Central

Kast, R. E.

2005-01-01

Tiagabine is an anticonvulsant gamma-aminobutyric acid reuptake inhibitor commonly used as an add-on treatment of refractory partial seizures in persons over 12 years old. Four of the 5 cases reported here indicate that tiagabine might also be remarkably effective in suppressing nocturnal bruxism, trismus, and consequent morning pain in the teeth, masticatory musculature, jaw, and temporomandibular joint areas. Tiagabine has a benign adverse-effect profile, is easily tolerated, and retains effectiveness over time. Bed partners of these patients report that grinding noises have stopped; therefore, the tiagabine effect is probably not simply antinociceptive. The doses used to suppress nocturnal bruxism at bedtime (4–8 mg) are lower than those used to treat seizures. PMID:16252740

Distributed Optimization

NASA Technical Reports Server (NTRS)

Macready, William; Wolpert, David

2005-01-01

We demonstrate a new framework for analyzing and controlling distributed systems, by solving constrained optimization problems with an algorithm based on that framework. The framework is ar. information-theoretic extension of conventional full-rationality game theory to allow bounded rational agents. The associated optimization algorithm is a game in which agents control the variables of the optimization problem. They do this by jointly minimizing a Lagrangian of (the probability distribution of) their joint state. The updating of the Lagrange parameters in that Lagrangian is a form of automated annealing, one that focuses the multi-agent system on the optimal pure strategy. We present computer experiments for the k-sat constraint satisfaction problem and for unconstrained minimization of NK functions.

Spacing distribution functions for the one-dimensional point-island model with irreversible attachment

NASA Astrophysics Data System (ADS)

González, Diego Luis; Pimpinelli, Alberto; Einstein, T. L.

2011-07-01

We study the configurational structure of the point-island model for epitaxial growth in one dimension. In particular, we calculate the island gap and capture zone distributions. Our model is based on an approximate description of nucleation inside the gaps. Nucleation is described by the joint probability density pnXY(x,y), which represents the probability density to have nucleation at position x within a gap of size y. Our proposed functional form for pnXY(x,y) describes excellently the statistical behavior of the system. We compare our analytical model with extensive numerical simulations. Our model retains the most relevant physical properties of the system.

[Risk analysis of naphthalene pollution in soils of Tianjin].

PubMed

Yang, Yu; Shi, Xuan; Xu, Fu-liu; Tao, Shu

2004-03-01

Three approaches were applied and evaluated for probabilistic risk assessment of naphthalene in soils of Tianjin, China, based on the observed naphthalene concentration of 188 top soil samples from the area and LC50 of naphthalene to ten typical soil fauna species from the literature. It was found that the overlapping area of the two probability density functions of concentration and LC50 was 6.4%, the joint probability curve bend towards and very close to the bottom and left axis, and the calculated probability that exposure concentration exceeds LC50 of various species was as low as 1.67%, all indicating a very much acceptable risk of naphthalene to the soil fauna ecosystem and only some of very sensitive species or individual animals are threaten by localized extremely high concentration. The three approaches revealed similar results from different viewpoints.

Fast super-resolution estimation of DOA and DOD in bistatic MIMO Radar with off-grid targets

NASA Astrophysics Data System (ADS)

Zhang, Dong; Zhang, Yongshun; Zheng, Guimei; Feng, Cunqian; Tang, Jun

2018-05-01

In this paper, we focus on the problem of joint DOA and DOD estimation in Bistatic MIMO Radar using sparse reconstruction method. In traditional ways, we usually convert the 2D parameter estimation problem into 1D parameter estimation problem by Kronecker product which will enlarge the scale of the parameter estimation problem and bring more computational burden. Furthermore, it requires that the targets must fall on the predefined grids. In this paper, a 2D-off-grid model is built which can solve the grid mismatch problem of 2D parameters estimation. Then in order to solve the joint 2D sparse reconstruction problem directly and efficiently, three kinds of fast joint sparse matrix reconstruction methods are proposed which are Joint-2D-OMP algorithm, Joint-2D-SL0 algorithm and Joint-2D-SOONE algorithm. Simulation results demonstrate that our methods not only can improve the 2D parameter estimation accuracy but also reduce the computational complexity compared with the traditional Kronecker Compressed Sensing method.

Modeling Anisotropic Elastic Wave Propagation in Jointed Rock Masses

NASA Astrophysics Data System (ADS)

Hurley, R.; Vorobiev, O.; Ezzedine, S. M.; Antoun, T.

2016-12-01

We present a numerical approach for determining the anisotropic stiffness of materials with nonlinearly-compliant joints capable of sliding. The proposed method extends existing ones for upscaling the behavior of a medium with open cracks and inclusions to cases relevant to natural fractured and jointed rocks, where nonlinearly-compliant joints can undergo plastic slip. The method deviates from existing techniques by incorporating the friction and closure states of the joints, and recovers an anisotropic elastic form in the small-strain limit when joints are not sliding. We present the mathematical formulation of our method and use Representative Volume Element (RVE) simulations to evaluate its accuracy for joint sets with varying complexity. We then apply the formulation to determine anisotropic elastic constants of jointed granite found at the Nevada Nuclear Security Site (NNSS) where the Source Physics Experiments (SPE), a campaign of underground chemical explosions, are performed. Finally, we discuss the implementation of our numerical approach in a massively parallel Lagrangian code Geodyn-L and its use for studying wave propagation from underground explosions. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Joint Stochastic Inversion of Pre-Stack 3D Seismic Data and Well Logs for High Resolution Hydrocarbon Reservoir Characterization

NASA Astrophysics Data System (ADS)

Torres-Verdin, C.

2007-05-01

This paper describes the successful implementation of a new 3D AVA stochastic inversion algorithm to quantitatively integrate pre-stack seismic amplitude data and well logs. The stochastic inversion algorithm is used to characterize flow units of a deepwater reservoir located in the central Gulf of Mexico. Conventional fluid/lithology sensitivity analysis indicates that the shale/sand interface represented by the top of the hydrocarbon-bearing turbidite deposits generates typical Class III AVA responses. On the other hand, layer- dependent Biot-Gassmann analysis shows significant sensitivity of the P-wave velocity and density to fluid substitution. Accordingly, AVA stochastic inversion, which combines the advantages of AVA analysis with those of geostatistical inversion, provided quantitative information about the lateral continuity of the turbidite reservoirs based on the interpretation of inverted acoustic properties (P-velocity, S-velocity, density), and lithotype (sand- shale) distributions. The quantitative use of rock/fluid information through AVA seismic amplitude data, coupled with the implementation of co-simulation via lithotype-dependent multidimensional joint probability distributions of acoustic/petrophysical properties, yields accurate 3D models of petrophysical properties such as porosity and permeability. Finally, by fully integrating pre-stack seismic amplitude data and well logs, the vertical resolution of inverted products is higher than that of deterministic inversions methods.

Fast formation and growth of high-density Sn whiskers in Mg/Sn-based solder/Mg joints by ultrasonic-assisted soldering: Phenomena, mechanism and prevention.

PubMed

Li, M Y; Yang, H F; Zhang, Z H; Gu, J H; Yang, S H

2016-06-08

A universally applicable method for promoting the fast formation and growth of high-density Sn whiskers on solders was developed by fabricating Mg/Sn-based solder/Mg joints using ultrasonic-assisted soldering at 250 °C for 6 s and then subjected to thermal aging at 25 °C for 7 d. The results showed that the use of the ultrasonic-assisted soldering could produce the supersaturated dissolution of Mg in the liquid Sn and lead to the existence of two forms of Mg in Sn after solidification. Moreover, the formation and growth of the high-density whiskers were facilitated by the specific contributions of both of the Mg forms in the solid Sn. Specifically, interstitial Mg can provide the persistent driving force for Sn whisker growth, whereas the Mg2Sn phase can increase the formation probability of Sn whiskers. In addition, we presented that the formation and growth of Sn whiskers in the Sn-based solders can be significantly restricted by a small amount of Zn addition (≥3 wt.%), and the prevention mechanisms are attributed to the segregation of Zn atoms at grain or phase boundaries and the formation of the lamellar-type Zn-rich structures in the solder.

Joint distraction attenuates osteoarthritis by reducing secondary inflammation, cartilage degeneration and subchondral bone aberrant change.

PubMed

Chen, Y; Sun, Y; Pan, X; Ho, K; Li, G

2015-10-01

Osteoarthritis (OA) is a progressive joint disorder. To date, there is not effective medical therapy. Joint distraction has given us hope for slowing down the OA progression. In this study, we investigated the benefits of joint distraction in OA rat model and the probable underlying mechanisms. OA was induced in the right knee joint of rats through anterior cruciate ligament transaction (ACLT) plus medial meniscus resection. The animals were randomized into three groups: two groups were treated with an external fixator for a subsequent 3 weeks, one with and one without joint distraction; and one group without external fixator as OA control. Serum interleukin-1β level was evaluated by ELISA; cartilage quality was assessed by histology examinations (gross appearance, Safranin-O/Fast green stain) and immunohistochemistry examinations (MMP13, Col X); subchondral bone aberrant changes was analyzed by micro-CT and immunohistochemistry (Nestin, Osterix) examinations. Characters of OA were present in the OA group, contrary to in general less severe damage after distraction treatment: firstly, IL-1β level was significantly decreased; secondly, cartilage degeneration was attenuated with lower histologic damage scores and the lower percentage of MMP13 or Col X positive chondrocytes; finally, subchondral bone abnormal change was attenuated, with reduced bone mineral density (BMD) and bone volume/total tissue volume (BV/TV) and the number of Nestin or Osterix positive cells in the subchondral bone. In the present study, we demonstrated that joint distraction reduced the level of secondary inflammation, cartilage degeneration and subchondral bone aberrant change, joint distraction may be a strategy for slowing OA progression. Copyright © 2015 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Numerical built-in method for the nonlinear JRC/JCS model in rock joint.

PubMed

Liu, Qunyi; Xing, Wanli; Li, Ying

2014-01-01

The joint surface is widely distributed in the rock, thus leading to the nonlinear characteristics of rock mass strength and limiting the effectiveness of the linear model in reflecting characteristics. The JRC/JCS model is the nonlinear failure criterion and generally believed to describe the characteristics of joints better than other models. In order to develop the numerical program for JRC/JCS model, this paper established the relationship between the parameters of the JRC/JCS and Mohr-Coulomb models. Thereafter, the numerical implement method and implementation process of the JRC/JCS model were discussed and the reliability of the numerical method was verified by the shear tests of jointed rock mass. Finally, the effect of the JRC/JCS model parameters on the shear strength of the joint was analyzed.

High resolution three-dimensional photoacoustic imaging of human finger joints in vivo

NASA Astrophysics Data System (ADS)

Xi, Lei; Jiang, Huabei

2015-08-01

We present a method for noninvasively imaging the hand joints using a three-dimensional (3D) photoacoustic imaging (PAI) system. This 3D PAI system utilizes cylindrical scanning in data collection and virtual-detector concept in image reconstruction. The maximum lateral and axial resolutions of the PAI system are 70 μm and 240 μm. The cross-sectional photoacoustic images of a healthy joint clearly exhibited major internal structures including phalanx and tendons, which are not available from the current photoacoustic imaging methods. The in vivo PAI results obtained are comparable with the corresponding 3.0 T MRI images of the finger joint. This study suggests that the proposed method has the potential to be used in early detection of joint diseases such as osteoarthritis.

A mass reconstruction technique for a heavy resonance decaying to τ + τ -

NASA Astrophysics Data System (ADS)

Xia, Li-Gang

2016-11-01

For a resonance decaying to τ + τ -, it is difficult to reconstruct its mass accurately because of the presence of neutrinos in the decay products of the τ leptons. If the resonance is heavy enough, we show that its mass can be well determined by the momentum component of the τ decay products perpendicular to the velocity of the τ lepton, p ⊥, and the mass of the visible/invisible decay products, m vis/inv, for τ decaying to hadrons/leptons. By sampling all kinematically allowed values of p ⊥ and m vis/inv according to their joint probability distributions determined by the MC simulations, the mass of the mother resonance is assumed to lie at the position with the maximal probability. Since p ⊥ and m vis/inv are invariant under the boost in the τ lepton direction, the joint probability distributions are independent upon the τ’s origin. Thus this technique is able to determine the mass of an unknown resonance with no efficiency loss. It is tested using MC simulations of the physics processes pp → Z/h(125)/h(750) + X → ττ + X at 13 TeV. The ratio of the full width at half maximum and the peak value of the reconstructed mass distribution is found to be 20%-40% using the information of missing transverse energy. Supported by General Financial Grant from the China Postdoctoral Science Foundation (2015M581062)

Quantum fluctuation theorems and generalized measurements during the force protocol.

PubMed

Watanabe, Gentaro; Venkatesh, B Prasanna; Talkner, Peter; Campisi, Michele; Hänggi, Peter

2014-03-01

Generalized measurements of an observable performed on a quantum system during a force protocol are investigated and conditions that guarantee the validity of the Jarzynski equality and the Crooks relation are formulated. In agreement with previous studies by M. Campisi, P. Talkner, and P. Hänggi [Phys. Rev. Lett. 105, 140601 (2010); Phys. Rev. E 83, 041114 (2011)], we find that these fluctuation relations are satisfied for projective measurements; however, for generalized measurements special conditions on the operators determining the measurements need to be met. For the Jarzynski equality to hold, the measurement operators of the forward protocol must be normalized in a particular way. The Crooks relation additionally entails that the backward and forward measurement operators depend on each other. Yet, quite some freedom is left as to how the two sets of operators are interrelated. This ambiguity is removed if one considers selective measurements, which are specified by a joint probability density function of work and measurement results of the considered observable. We find that the respective forward and backward joint probabilities satisfy the Crooks relation only if the measurement operators of the forward and backward protocols are the time-reversed adjoints of each other. In this case, the work probability density function conditioned on the measurement result satisfies a modified Crooks relation. The modification appears as a protocol-dependent factor that can be expressed by the information gained by the measurements during the forward and backward protocols. Finally, detailed fluctuation theorems with an arbitrary number of intervening measurements are obtained.

Stochastic Inversion of 2D Magnetotelluric Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Jinsong

2010-07-01

The algorithm is developed to invert 2D magnetotelluric (MT) data based on sharp boundary parametrization using a Bayesian framework. Within the algorithm, we consider the locations and the resistivity of regions formed by the interfaces are as unknowns. We use a parallel, adaptive finite-element algorithm to forward simulate frequency-domain MT responses of 2D conductivity structure. Those unknown parameters are spatially correlated and are described by a geostatistical model. The joint posterior probability distribution function is explored by Markov Chain Monte Carlo (MCMC) sampling methods. The developed stochastic model is effective for estimating the interface locations and resistivity. Most importantly, itmore » provides details uncertainty information on each unknown parameter. Hardware requirements: PC, Supercomputer, Multi-platform, Workstation; Software requirements C and Fortan; Operation Systems/version is Linux/Unix or Windows« less

A Bayesian method for inferring transmission chains in a partially observed epidemic.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marzouk, Youssef M.; Ray, Jaideep

2008-10-01

We present a Bayesian approach for estimating transmission chains and rates in the Abakaliki smallpox epidemic of 1967. The epidemic affected 30 individuals in a community of 74; only the dates of appearance of symptoms were recorded. Our model assumes stochastic transmission of the infections over a social network. Distinct binomial random graphs model intra- and inter-compound social connections, while disease transmission over each link is treated as a Poisson process. Link probabilities and rate parameters are objects of inference. Dates of infection and recovery comprise the remaining unknowns. Distributions for smallpox incubation and recovery periods are obtained from historicalmore » data. Using Markov chain Monte Carlo, we explore the joint posterior distribution of the scalar parameters and provide an expected connectivity pattern for the social graph and infection pathway.« less

A stochastic diffusion process for Lochner's generalized Dirichlet distribution

DOE PAGES

Bakosi, J.; Ristorcelli, J. R.

2013-10-01

The method of potential solutions of Fokker-Planck equations is used to develop a transport equation for the joint probability of N stochastic variables with Lochner’s generalized Dirichlet distribution as its asymptotic solution. Individual samples of a discrete ensemble, obtained from the system of stochastic differential equations, equivalent to the Fokker-Planck equation developed here, satisfy a unit-sum constraint at all times and ensure a bounded sample space, similarly to the process developed in for the Dirichlet distribution. Consequently, the generalized Dirichlet diffusion process may be used to represent realizations of a fluctuating ensemble of N variables subject to a conservation principle.more » Compared to the Dirichlet distribution and process, the additional parameters of the generalized Dirichlet distribution allow a more general class of physical processes to be modeled with a more general covariance matrix.« less

Methode d'identification parametrique pour la surveillance in situ des joints a recouvrement par propagation d'ondes vibratoires

NASA Astrophysics Data System (ADS)

Francoeur, Dany

Cette these de doctorat s'inscrit dans le cadre de projets CRIAQ (Consortium de recherche et d'innovation en aerospatiale du Quebec) orientes vers le developpement d'approches embarquees pour la detection de defauts dans des structures aeronautiques. L'originalite de cette these repose sur le developpement et la validation d'une nouvelle methode de detection, quantification et localisation d'une entaille dans une structure de joint a recouvrement par la propagation d'ondes vibratoires. La premiere partie expose l'etat des connaissances sur l'identification d'un defaut dans le contexte du Structural Health Monitoring (SHM), ainsi que la modelisation de joint a recouvrements. Le chapitre 3 developpe le modele de propagation d'onde d'un joint a recouvrement endommage par une entaille pour une onde de flexion dans la plage des moyennes frequences (10-50 kHz). A cette fin, un modele de transmission de ligne (TLM) est realise pour representer un joint unidimensionnel (1D). Ce modele 1D est ensuite adapte a un joint bi-dimensionnel (2D) en faisant l'hypothese d'un front d'onde plan incident et perpendiculaire au joint. Une methode d'identification parametrique est ensuite developpee pour permettre a la fois la calibration du modele du joint a recouvrement sain, la detection puis la caracterisation de l'entaille situee sur le joint. Cette methode est couplee a un algorithme qui permet une recherche exhaustive de tout l'espace parametrique. Cette technique permet d'extraire une zone d'incertitude reliee aux parametres du modele optimal. Une etude de sensibilite est egalement realisee sur l'identification. Plusieurs resultats de mesure sur des joints a recouvrements 1D et 2D sont realisees permettant ainsi l'etude de la repetabilite des resultats et la variabilite de differents cas d'endommagement. Les resultats de cette etude demontrent d'abord que la methode de detection proposee est tres efficace et permet de suivre la progression d'endommagement. De tres bons resultats de quantification et de localisation d'entailles ont ete obtenus dans les divers joints testes (1D et 2D). Il est prevu que l'utilisation d'ondes de Lamb permettraient d'etendre la plage de validite de la methode pour de plus petits dommages. Ces travaux visent d'abord la surveillance in-situ des structures de joint a recouvrements, mais d'autres types de defauts. (comme les disbond) et. de structures complexes sont egalement envisageables. Mots cles : joint a recouvrement, surveillance in situ, localisation et caracterisation de dommages

Non-Gaussian probabilistic MEG source localisation based on kernel density estimation☆

PubMed Central

Mohseni, Hamid R.; Kringelbach, Morten L.; Woolrich, Mark W.; Baker, Adam; Aziz, Tipu Z.; Probert-Smith, Penny

2014-01-01

There is strong evidence to suggest that data recorded from magnetoencephalography (MEG) follows a non-Gaussian distribution. However, existing standard methods for source localisation model the data using only second order statistics, and therefore use the inherent assumption of a Gaussian distribution. In this paper, we present a new general method for non-Gaussian source estimation of stationary signals for localising brain activity from MEG data. By providing a Bayesian formulation for MEG source localisation, we show that the source probability density function (pdf), which is not necessarily Gaussian, can be estimated using multivariate kernel density estimators. In the case of Gaussian data, the solution of the method is equivalent to that of widely used linearly constrained minimum variance (LCMV) beamformer. The method is also extended to handle data with highly correlated sources using the marginal distribution of the estimated joint distribution, which, in the case of Gaussian measurements, corresponds to the null-beamformer. The proposed non-Gaussian source localisation approach is shown to give better spatial estimates than the LCMV beamformer, both in simulations incorporating non-Gaussian signals, and in real MEG measurements of auditory and visual evoked responses, where the highly correlated sources are known to be difficult to estimate. PMID:24055702

Numerically correcting the joint misplacement of the sub-holograms in spatial synthetic aperture digital Fresnel holography.

PubMed

Jiang, Hongzhen; Zhao, Jianlin; Di, Jianglei; Qin, Chuan

2009-10-12

We propose an effective reconstruction method for correcting the joint misplacement of the sub-holograms caused by the displacement error of CCD in spatial synthetic aperture digital Fresnel holography. For every two adjacent sub-holograms along the motion path of CCD, we reconstruct the corresponding holographic images under different joint distances between the sub-holograms and then find out the accurate joint distance by evaluating the quality of the corresponding synthetic reconstructed images. Then the accurate relative position relationships of the sub-holograms can be confirmed according to all of the identified joint distances, with which the accurate synthetic reconstructed image can be obtained by superposing the reconstruction results of the sub-holograms. The numerical reconstruction results are in agreement with the theoretical analysis. Compared with the traditional reconstruction method, this method could be used to not only correct the joint misplacement of the sub-holograms without the limitation of the actually overlapping circumstances of the adjacent sub-holograms, but also make the joint precision of the sub-holograms reach sub-pixel accuracy.