Generalized canonical correlation analysis with missing values
M. van de Velden (Michel); Y. Takane
2012-01-01
textabstractGeneralized canonical correlation analysis is a versatile technique that allows the joint analysis of several sets of data matrices. The generalized canonical correlation analysis solution can be obtained through an eigenequation and distributional assumptions are not required. When
Generalized canonical correlation analysis with missing values
M. van de Velden (Michel); Y. Takane
2009-01-01
textabstractTwo new methods for dealing with missing values in generalized canonical correlation analysis are introduced. The first approach, which does not require iterations, is a generalization of the Test Equating method available for principal component analysis. In the second approach,
WenJun Zhang; Xin Li
2015-01-01
Between-taxon interactions can be detected by calculating the sampling data of taxon sample type. In present study, Spearman rank correlation and proportion correlation are chosen as the general correlation measures, and their partial correlations are calculated and compared. The results show that for Spearman rank correlation measure, in all predicted candidate direct interactions by partial correlation, about 16.77% (x, 0-45.4%) of them are not successfully detected by Spearman rank correla...
Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data.
Tan, Qihua; Thomassen, Mads; Burton, Mark; Mose, Kristian Fredløv; Andersen, Klaus Ejner; Hjelmborg, Jacob; Kruse, Torben
2017-06-06
Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health.
Generalized canonical analysis based on optimizing matrix correlations and a relation with IDIOSCAL
Kiers, Henk A.L.; Cléroux, R.; Ten Berge, Jos M.F.
1994-01-01
Carroll's method for generalized canonical analysis of two or more sets of variables is shown to optimize the sum of squared inner-product matrix correlations between a consensus matrix and matrices with canonical variates for each set of variables. In addition, the method that analogously optimizes
Generalized canonical correlation analysis of matrices with missing rows : A simulation study
van de Velden, Michel; Bijmolt, Tammo H. A.
A method is presented for generalized canonical correlation analysis of two or more matrices with missing rows. The method is a combination of Carroll's (1968) method and the missing data approach of the OVERALS technique (Van der Burg, 1988). In a simulation study we assess the performance of the
Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data
Tan, Qihua; Thomassen, Mads; Burton, Mark
2017-01-01
the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray...... time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health....
Han, Fang; Liu, Han
2017-02-01
Correlation matrix plays a key role in many multivariate methods (e.g., graphical model estimation and factor analysis). The current state-of-the-art in estimating large correlation matrices focuses on the use of Pearson's sample correlation matrix. Although Pearson's sample correlation matrix enjoys various good properties under Gaussian models, its not an effective estimator when facing heavy-tail distributions with possible outliers. As a robust alternative, Han and Liu (2013b) advocated the use of a transformed version of the Kendall's tau sample correlation matrix in estimating high dimensional latent generalized correlation matrix under the transelliptical distribution family (or elliptical copula). The transelliptical family assumes that after unspecified marginal monotone transformations, the data follow an elliptical distribution. In this paper, we study the theoretical properties of the Kendall's tau sample correlation matrix and its transformed version proposed in Han and Liu (2013b) for estimating the population Kendall's tau correlation matrix and the latent Pearson's correlation matrix under both spectral and restricted spectral norms. With regard to the spectral norm, we highlight the role of "effective rank" in quantifying the rate of convergence. With regard to the restricted spectral norm, we for the first time present a "sign subgaussian condition" which is sufficient to guarantee that the rank-based correlation matrix estimator attains the optimal rate of convergence. In both cases, we do not need any moment condition.
Felix Tobias Kurz
2016-12-01
Full Text Available In biological tissue, an accumulation of similarly shaped objects with a susceptibility difference to the surrounding tissue generates a local distortion of the external magnetic field in magnetic resonance imaging. It induces stochastic field fluctuations that characteristically influence proton spin diffusion in the vicinity of these magnetic perturbers. The magnetic field correlation that is associated with such local magnetic field inhomogeneities can be expressed in the form of a dynamic frequency autocorrelation function that is related to the time evolution of the measured magnetization. Here, an eigenfunction expansion for two simple magnetic perturber shapes, that of spheres and cylinders, is considered for restricted spin diffusion in a simple model geometry. Then, the concept of generalized moment analysis, an approximation technique that is applied in the study of (non-reactive processes that involve Brownian motion, allows to provide analytical expressions for the correlation function for different exponential decay forms. Results for the biexponential decay for both spherical and cylindrical magnetized objects are derived and compared with the frequently used (less accurate monoexponential decay forms. They are in asymptotic agreement with the numerically exact value of the correlation function for long and short times.
Yang, Chun; Miller, Mikel; Nguyen, Thao; Akos, Dennis
2006-01-01
.... The use of a GFDC can offer several advantages. First, as a generalization of the FFT-implemented correlation with a block repetitive processing capability, it enables fast acquisition through simultaneous code delay and Doppler frequency search...
Extending Local Canonical Correlation Analysis to Handle General Linear Contrasts for fMRI Data
Mingwu Jin
2012-01-01
Full Text Available Local canonical correlation analysis (CCA is a multivariate method that has been proposed to more accurately determine activation patterns in fMRI data. In its conventional formulation, CCA has several drawbacks that limit its usefulness in fMRI. A major drawback is that, unlike the general linear model (GLM, a test of general linear contrasts of the temporal regressors has not been incorporated into the CCA formalism. To overcome this drawback, a novel directional test statistic was derived using the equivalence of multivariate multiple regression (MVMR and CCA. This extension will allow CCA to be used for inference of general linear contrasts in more complicated fMRI designs without reparameterization of the design matrix and without reestimating the CCA solutions for each particular contrast of interest. With the proper constraints on the spatial coefficients of CCA, this test statistic can yield a more powerful test on the inference of evoked brain regional activations from noisy fMRI data than the conventional t-test in the GLM. The quantitative results from simulated and pseudoreal data and activation maps from fMRI data were used to demonstrate the advantage of this novel test statistic.
Han, Fang; Liu, Han
2016-01-01
Correlation matrices play a key role in many multivariate methods (e.g., graphical model estimation and factor analysis). The current state-of-the-art in estimating large correlation matrices focuses on the use of Pearson's sample correlation matrix. Although Pearson's sample correlation matrix enjoys various good properties under Gaussian models, it is not an effective estimator when facing heavy-tailed distributions. As a robust alternative, Han and Liu [J. Am. Stat. Assoc. 109 (2015) 275-2...
Kashiwase, Takako; Nagasaka, Hideo
2000-01-01
The present paper dealt with the extension of tendon friction coefficient correlation as a function of loading end load and circumferential angle, proposed in the former paper. The extended correlation further included the effects of the number of strands contacted with sheath, tendon diameter, politicization of tendon and tendon local curvature. The validity of the correlation was confirmed by several published measured data. The structural analysis of middle cylinder part of 1/4 PCCV (Prestressed Concrete Containment Vessel) model was conducted using the present friction coefficient correlation. The results were compared with the analysis using constant friction coefficient, focused on the tendon tension force distribution. (author)
A General Analysis of the Impact of Digitization in Microwave Correlation Radiometers
Hyuk Park
2011-06-01
Full Text Available This study provides a general framework to analyze the effects on correlation radiometers of a generic quantization scheme and sampling process. It reviews, unifies and expands several previous works that focused on these effects separately. In addition, it provides a general theoretical background that allows analyzing any digitization scheme including any number of quantization levels, irregular quantization steps, gain compression, clipping, jitter and skew effects of the sampling period.
Satomura, Hironori; Adachi, Kohei
2013-07-01
To facilitate the interpretation of canonical correlation analysis (CCA) solutions, procedures have been proposed in which CCA solutions are orthogonally rotated to a simple structure. In this paper, we consider oblique rotation for CCA to provide solutions that are much easier to interpret, though only orthogonal rotation is allowed in the existing formulations of CCA. Our task is thus to reformulate CCA so that its solutions have the freedom of oblique rotation. Such a task can be achieved using Yanai's (Jpn. J. Behaviormetrics 1:46-54, 1974; J. Jpn. Stat. Soc. 11:43-53, 1981) generalized coefficient of determination for the objective function to be maximized in CCA. The resulting solutions are proved to include the existing orthogonal ones as special cases and to be rotated obliquely without affecting the objective function value, where ten Berge's (Psychometrika 48:519-523, 1983) theorems on suborthonormal matrices are used. A real data example demonstrates that the proposed oblique rotation can provide simple, easily interpreted CCA solutions.
Correlated electrons and generalized statistics
Wang, Q.A.
2003-01-01
Several important generalizations of Fermi-Dirac distribution are compared to numerical and experimental results for correlated electron systems. It is found that the quantum distributions based on incomplete information hypothesis can be useful for describing this kind of systems. We show that the additive incomplete fermion distribution gives very good description of weakly correlated electrons and that the non-additive one is suitable to very strong correlated cases. (author)
Generalized drift-flux correlation
Takeuchi, K.; Young, M.Y.; Hochreiter, L.E.
1991-01-01
A one-dimensional drift-flux model with five conservation equations is frequently employed in major computer codes, such as TRAC-PD2, and in simulator codes. In this method, the relative velocity between liquid and vapor phases, or slip ratio, is given by correlations, rather than by direct solution of the phasic momentum equations, as in the case of the two-fluid model used in TRAC-PF1. The correlations for churn-turbulent bubbly flow and slug flow regimes were given in terms of drift velocities by Zuber and Findlay. For the annular flow regime, the drift velocity correlations were developed by Ishii et al., using interphasic force balances. Another approach is to define the drift velocity so that flooding and liquid hold-up conditions are properly simulated, as reported here. The generalized correlation is used to reanalyze the MB-2 test data for two-phase flow in a large-diameter pipe. The results are applied to the generalized drift flux velocity, whose relationship to the other correlations is discussed. Finally, the generalized drift flux correlation is implemented in TRAC-PD2. Flow reversal from countercurrent to cocurrent flow is computed in small-diameter U-shaped tubes and is compared with the flooding curve
Hobeika, Lucie; Diard-Detoeuf, Capucine; Garcin, Béatrice; Levy, Richard; Volle, Emmanuelle
2016-05-01
Reasoning by analogy allows us to link distinct domains of knowledge and to transfer solutions from one domain to another. Analogical reasoning has been studied using various tasks that have generally required the consideration of the relationships between objects and their integration to infer an analogy schema. However, these tasks varied in terms of the level and the nature of the relationships to consider (e.g., semantic, visuospatial). The aim of this study was to identify the cerebral network involved in analogical reasoning and its specialization based on the domains of information and task specificity. We conducted a coordinate-based meta-analysis of 27 experiments that used analogical reasoning tasks. The left rostrolateral prefrontal cortex was one of the regions most consistently activated across the studies. A comparison between semantic and visuospatial analogy tasks showed both domain-oriented regions in the inferior and middle frontal gyri and a domain-general region, the left rostrolateral prefrontal cortex, which was specialized for analogy tasks. A comparison of visuospatial analogy to matrix problem tasks revealed that these two relational reasoning tasks engage, at least in part, distinct right and left cerebral networks, particularly separate areas within the left rostrolateral prefrontal cortex. These findings highlight several cognitive and cerebral differences between relational reasoning tasks that can allow us to make predictions about the respective roles of distinct brain regions or networks. These results also provide new, testable anatomical hypotheses about reasoning disorders that are induced by brain damage. Hum Brain Mapp 37:1953-1969, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Generalized hydrodynamic correlations and fractional memory functions
Rodríguez, Rosalio F.; Fujioka, Jorge
2015-12-01
A fractional generalized hydrodynamic (GH) model of the longitudinal velocity fluctuations correlation, and its associated memory function, for a complex fluid is analyzed. The adiabatic elimination of fast variables introduces memory effects in the transport equations, and the dynamic of the fluctuations is described by a generalized Langevin equation with long-range noise correlations. These features motivate the introduction of Caputo time fractional derivatives and allows us to calculate analytic expressions for the fractional longitudinal velocity correlation function and its associated memory function. Our analysis eliminates a spurious constant term in the non-fractional memory function found in the non-fractional description. It also produces a significantly slower power-law decay of the memory function in the GH regime that reduces to the well-known exponential decay in the non-fractional Navier-Stokes limit.
Zhao, Xuemin; Wang, Hailong; Li, Jing; Shan, Zhongyan; Teng, Weiping; Teng, Xiaochun
2015-01-01
Certain epidemiological studies have suggested exposure to polybrominated diphenyl ethers (PBDEs) affect the production and secretion of thyroid hormones (TH); however, conflicting results have been reported in different studies. There is not a convincing conclusion about this debate to date. To perform a meta-analysis determining if there are correlations between PBDEs exposure and the serum levels of TH. Medical and scientific literature databases were searched for articles that met the eligibility criteria. The included articles were assessed for methodological quality. The correlation coefficient values or regression coefficient values between PBDEs and thyroid stimulating hormone (TSH) or total thyroxine (TT4) from each article were used for analysis. Sixteen articles were included in this meta-analysis. Pearson correlation coefficients (r) were directly collected or calculated from data given in the articles. Then, Fisher's z transformation was performed to convert each correlation coefficient to an approximately normal distribution. For z values between PBDEs exposure and TSH levels, the pooled z value for 18 studies was 0.08 (95% CI: -0.06, 0.22), and indicated significant heterogeneity (I2 values = 90.7%). Subgroup analysis was performed based on the median values of serum PBDEs in each study, there was not significant heterogeneity in each of the four subgroups (I2 values <30%). In meta-analysis of z values between PBDEs exposure and the levels of TT4, the pooled z value for 11 studies was -0.02 (95% CI: -0.11, 0.08), and also indicated significant heterogeneity (I2 values = 57.6%). Similar subgroup analysis was done for the PBDEs exposures and the levels of TT4. No significant heterogeneity was shown in either of the two subgroups (I2 values = 0). The findings in our meta-analysis indicate the effects of PBDEs on thyroid function may mainly depend on PBDEs exposure and their levels found in serum. The relationship between PBDEs exposure and changes in
Xuemin Zhao
Full Text Available Certain epidemiological studies have suggested exposure to polybrominated diphenyl ethers (PBDEs affect the production and secretion of thyroid hormones (TH; however, conflicting results have been reported in different studies. There is not a convincing conclusion about this debate to date.To perform a meta-analysis determining if there are correlations between PBDEs exposure and the serum levels of TH. Medical and scientific literature databases were searched for articles that met the eligibility criteria. The included articles were assessed for methodological quality. The correlation coefficient values or regression coefficient values between PBDEs and thyroid stimulating hormone (TSH or total thyroxine (TT4 from each article were used for analysis.Sixteen articles were included in this meta-analysis. Pearson correlation coefficients (r were directly collected or calculated from data given in the articles. Then, Fisher's z transformation was performed to convert each correlation coefficient to an approximately normal distribution. For z values between PBDEs exposure and TSH levels, the pooled z value for 18 studies was 0.08 (95% CI: -0.06, 0.22, and indicated significant heterogeneity (I2 values = 90.7%. Subgroup analysis was performed based on the median values of serum PBDEs in each study, there was not significant heterogeneity in each of the four subgroups (I2 values <30%. In meta-analysis of z values between PBDEs exposure and the levels of TT4, the pooled z value for 11 studies was -0.02 (95% CI: -0.11, 0.08, and also indicated significant heterogeneity (I2 values = 57.6%. Similar subgroup analysis was done for the PBDEs exposures and the levels of TT4. No significant heterogeneity was shown in either of the two subgroups (I2 values = 0.The findings in our meta-analysis indicate the effects of PBDEs on thyroid function may mainly depend on PBDEs exposure and their levels found in serum. The relationship between PBDEs exposure and changes
Spectral analysis by correlation
Fauque, J.M.; Berthier, D.; Max, J.; Bonnet, G.
1969-01-01
The spectral density of a signal, which represents its power distribution along the frequency axis, is a function which is of great importance, finding many uses in all fields concerned with the processing of the signal (process identification, vibrational analysis, etc...). Amongst all the possible methods for calculating this function, the correlation method (correlation function calculation + Fourier transformation) is the most promising, mainly because of its simplicity and of the results it yields. The study carried out here will lead to the construction of an apparatus which, coupled with a correlator, will constitute a set of equipment for spectral analysis in real time covering the frequency range 0 to 5 MHz. (author) [fr
Generalized interferometry - I: theory for interstation correlations
Fichtner, Andreas; Stehly, Laurent; Ermert, Laura; Boehm, Christian
2017-02-01
We develop a general theory for interferometry by correlation that (i) properly accounts for heterogeneously distributed sources of continuous or transient nature, (ii) fully incorporates any type of linear and nonlinear processing, such as one-bit normalization, spectral whitening and phase-weighted stacking, (iii) operates for any type of medium, including 3-D elastic, heterogeneous and attenuating media, (iv) enables the exploitation of complete correlation waveforms, including seemingly unphysical arrivals, and (v) unifies the earthquake-based two-station method and ambient noise correlations. Our central theme is not to equate interferometry with Green function retrieval, and to extract information directly from processed interstation correlations, regardless of their relation to the Green function. We demonstrate that processing transforms the actual wavefield sources and actual wave propagation physics into effective sources and effective wave propagation. This transformation is uniquely determined by the processing applied to the observed data, and can be easily computed. The effective forward model, that links effective sources and propagation to synthetic interstation correlations, may not be perfect. A forward modelling error, induced by processing, describes the extent to which processed correlations can actually be interpreted as proper correlations, that is, as resulting from some effective source and some effective wave propagation. The magnitude of the forward modelling error is controlled by the processing scheme and the temporal variability of the sources. Applying adjoint techniques to the effective forward model, we derive finite-frequency Fréchet kernels for the sources of the wavefield and Earth structure, that should be inverted jointly. The structure kernels depend on the sources of the wavefield and the processing scheme applied to the raw data. Therefore, both must be taken into account correctly in order to make accurate inferences on
[Correlation between iridology and general pathology].
Demea, Sorina
2002-01-01
The research proposal is to evaluate the association between certain irian signs and general pathology of studied patients. There were studied 57 hospitalized patients; there was taken over all their iris images, which were analyzed through iridological protocols; in the same time the pathology of these patients was noted from their records in the hospital, concordant with the clinical diagnosis; all these information were included in a database for a computerised processing. The correlations resulted from, shows a high connection between the irian constitution establish through iridological criteria and the existent pathology. Iris examination can be very useful for diagnosis of a certain general pathology, in a holistic approach of the patient.
A Generalized Correlation Plot Package for the CEBAF Control System
D. Wu; W. Akers; S. Schaffner; H. Shoaee; W. A. Watson; D. Wetherholt
1996-01-01
The Correlation Package is a general facility for data acquisition and analysis serving as an online environment for performing a wide variety of machine physics experiments and engineering diagnostics. Typical correlation experiments consist of an initial set of actions followed by stepping one or two accelerator parameters while measuring up to several hundred control system parameters. The package utilizes the CDEV [1] device API to access accelerator systems. A variety of analysis and graphics tools are included through integration with the Matlab math modeling package. A post- acquisition script capability is available to automate the data reduction process. A callable interface allows this facility to serve as the data acquisition and analysis engine for high level applications. A planned interface to archived accelerator data will allow the same analysis and graphics tools to be used for viewing and correlating history data. The object oriented design and C++ implementation details as well as the current status of the Correlation Package will be presented
Cosmological measurements with general relativistic galaxy correlations
Raccanelli, Alvise; Montanari, Francesco; Durrer, Ruth; Bertacca, Daniele; Doré, Olivier
2016-01-01
We investigate the cosmological dependence and the constraining power of large-scale galaxy correlations, including all redshift-distortions, wide-angle, lensing and gravitational potential effects on linear scales. We analyze the cosmological information present in the lensing convergence and in the gravitational potential terms describing the so-called ''relativistic effects'', and we find that, while smaller than the information contained in intrinsic galaxy clustering, it is not negligible. We investigate how neglecting them does bias cosmological measurements performed by future spectroscopic and photometric large-scale surveys such as SKA and Euclid. We perform a Fisher analysis using the CLASS code, modified to include scale-dependent galaxy bias and redshift-dependent magnification and evolution bias. Our results show that neglecting relativistic terms, especially lensing convergence, introduces an error in the forecasted precision in measuring cosmological parameters of the order of a few tens of percent, in particular when measuring the matter content of the Universe and primordial non-Gaussianity parameters. The analysis suggests a possible substantial systematic error in cosmological parameter constraints. Therefore, we argue that radial correlations and integrated relativistic terms need to be taken into account when forecasting the constraining power of future large-scale number counts of galaxy surveys.
Generalized quantum interference of correlated photon pairs
Kim, Heonoh; Lee, Sang Min; Moon, Han Seb
2015-01-01
Superposition and indistinguishablility between probability amplitudes have played an essential role in observing quantum interference effects of correlated photons. The Hong-Ou-Mandel interference and interferences of the path-entangled photon number state are of special interest in the field of quantum information technologies. However, a fully generalized two-photon quantum interferometric scheme accounting for the Hong-Ou-Mandel scheme and path-entangled photon number states has not yet been proposed. Here we report the experimental demonstrations of the generalized two-photon interferometry with both the interferometric properties of the Hong-Ou-Mandel effect and the fully unfolded version of the path-entangled photon number state using photon-pair sources, which are independently generated by spontaneous parametric down-conversion. Our experimental scheme explains two-photon interference fringes revealing single- and two-photon coherence properties in a single interferometer setup. Using the proposed interferometric measurement, it is possible to directly estimate the joint spectral intensity of a photon pair source. PMID:25951143
Hamarová, Ivana; Šmíd, Petr; Horváth, P.; Hrabovský, M.
2014-01-01
Roč. 2014, č. 1 (2014), "704368-1"-"704368-12" ISSN 1537-744X R&D Projects: GA ČR GA13-12301S Institutional support: RVO:68378271 Keywords : one-dimensional speckle correlation * speckle * general In-plane translation Subject RIV: BH - Optics, Masers, Lasers Impact factor: 1.219, year: 2013
General Correlation Theorem for Trinion Fourier Transform
Bahri, Mawardi
2017-01-01
- The trinion Fourier transform is an extension of the Fourier transform in the trinion numbers setting. In this work we derive the correlation theorem for the trinion Fourier transform by using the relation between trinion convolution and correlation definitions in the trinion Fourier transform domains.
Multiview Bayesian Correlated Component Analysis
Kamronn, Simon Due; Poulsen, Andreas Trier; Hansen, Lars Kai
2015-01-01
are identical. Here we propose a hierarchical probabilistic model that can infer the level of universality in such multiview data, from completely unrelated representations, corresponding to canonical correlation analysis, to identical representations as in correlated component analysis. This new model, which...... we denote Bayesian correlated component analysis, evaluates favorably against three relevant algorithms in simulated data. A well-established benchmark EEG data set is used to further validate the new model and infer the variability of spatial representations across multiple subjects....
Structural Analysis of Covariance and Correlation Matrices.
Joreskog, Karl G.
1978-01-01
A general approach to analysis of covariance structures is considered, in which the variances and covariances or correlations of the observed variables are directly expressed in terms of the parameters of interest. The statistical problems of identification, estimation and testing of such covariance or correlation structures are discussed.…
Generalized Linear Covariance Analysis
Carpenter, James R.; Markley, F. Landis
2014-01-01
This talk presents a comprehensive approach to filter modeling for generalized covariance analysis of both batch least-squares and sequential estimators. We review and extend in two directions the results of prior work that allowed for partitioning of the state space into solve-for'' and consider'' parameters, accounted for differences between the formal values and the true values of the measurement noise, process noise, and textita priori solve-for and consider covariances, and explicitly partitioned the errors into subspaces containing only the influence of the measurement noise, process noise, and solve-for and consider covariances. In this work, we explicitly add sensitivity analysis to this prior work, and relax an implicit assumption that the batch estimator's epoch time occurs prior to the definitive span. We also apply the method to an integrated orbit and attitude problem, in which gyro and accelerometer errors, though not estimated, influence the orbit determination performance. We illustrate our results using two graphical presentations, which we call the variance sandpile'' and the sensitivity mosaic,'' and we compare the linear covariance results to confidence intervals associated with ensemble statistics from a Monte Carlo analysis.
Generalized Smoluchowski equation with correlation between clusters
Sittler, Lionel
2008-01-01
In this paper we compute new reaction rates of the Smoluchowski equation which takes into account correlations. The new rate K = K MF + K C is the sum of two terms. The first term is the known Smoluchowski rate with the mean-field approximation. The second takes into account a correlation between clusters. For this purpose we introduce the average path of a cluster. We relate the length of this path to the reaction rate of the Smoluchowski equation. We solve the implicit dependence between the average path and the density of clusters. We show that this correlation length is the same for all clusters. Our result depends strongly on the spatial dimension d. The mean-field term K MF i,j = (D i + D j )(r j + r i ) d-2 , which vanishes for d = 1 and is valid up to logarithmic correction for d = 2, is the usual rate found with the Smoluchowski model without correlation (where r i is the radius and D i is the diffusion constant of the cluster). We compute a new rate: the correlation rate K i,j C = (D i +D j )(r j +r i ) d-1 M((d-1)/d f ) is valid for d ≥ 1(where M(α) = Σ +∞ i=1 i α N i is the moment of the density of clusters and d f is the fractal dimension of the cluster). The result is valid for a large class of diffusion processes and mass-radius relations. This approach confirms some analytical solutions in d = 1 found with other methods. We also show Monte Carlo simulations which illustrate some exact new solvable models
Intermittency analysis of correlated data
Wosiek, B.
1992-01-01
We describe the method of the analysis of the dependence of the factorial moments on the bin size in which the correlations between the moments computed for different bin sizes are taken into account. For large multiplicity nucleus-nucleus data inclusion of the correlations does not change the values of the slope parameter, but gives errors significantly reduced as compared to the case of fits with no correlations. (author)
Generalization of Clustering Coefficients to Signed Correlation Networks
Costantini, Giulio; Perugini, Marco
2014-01-01
The recent interest in network analysis applications in personality psychology and psychopathology has put forward new methodological challenges. Personality and psychopathology networks are typically based on correlation matrices and therefore include both positive and negative edge signs. However, some applications of network analysis disregard negative edges, such as computing clustering coefficients. In this contribution, we illustrate the importance of the distinction between positive and negative edges in networks based on correlation matrices. The clustering coefficient is generalized to signed correlation networks: three new indices are introduced that take edge signs into account, each derived from an existing and widely used formula. The performances of the new indices are illustrated and compared with the performances of the unsigned indices, both on a signed simulated network and on a signed network based on actual personality psychology data. The results show that the new indices are more resistant to sample variations in correlation networks and therefore have higher convergence compared with the unsigned indices both in simulated networks and with real data. PMID:24586367
Butler, Thomas G.
1993-09-01
There is a constant need to be able to solve for enforced motion of structures. Spacecraft need to be qualified for acceleration inputs. Truck cargoes need to be safeguarded from road mishaps. Office buildings need to withstand earthquake shocks. Marine machinery needs to be able to withstand hull shocks. All of these kinds of enforced motions are being grouped together under the heading of seismic inputs. Attempts have been made to cope with this problem over the years and they usually have ended up with some limiting or compromise conditions. The crudest approach was to limit the problem to acceleration occurring only at a base of a structure, constrained to be rigid. The analyst would assign arbitrarily outsized masses to base points. He would then calculate the magnitude of force to apply to the base mass (or masses) in order to produce the specified acceleration. He would of necessity have to sacrifice the determination of stresses in the vicinity of the base, because of the artificial nature of the input forces. The author followed the lead of John M. Biggs by using relative coordinates for a rigid base in a 1975 paper, and again in a 1981 paper . This method of relative coordinates was extended and made operational as DMAP ALTER packets to rigid formats 9, 10, 11, and 12 under contract N60921-82-C-0128. This method was presented at the twelfth NASTRAN Colloquium. Another analyst in the field developed a method that computed the forces from enforced motion then applied them as a forcing to the remaining unknowns after the knowns were partitioned off. The method was translated into DMAP ALTER's but was never made operational. All of this activity jelled into the current effort. Much thought was invested in working out ways to unshakle the analysis of enforced motions from the limitations that persisted.
Correlation between generalized joint hypermobility and hallux valgus
A. A. Kardanov
2015-01-01
Full Text Available Purpose: to evaluate correlation between generalized joint hypermobility, forefoot deformities and elasticity of the first ray of the foot. Material and methods. We examined 138 patients with complaints related with deformities at the forefoot level. During this study the medical history was obtained, the elasticity type of the feet was defined and the degree of motion of the medial metatarsal-cuneiform joint was evaluated. Forefoot elasticity was identified by bringing together the heads I and V metatarsal bones with fingers. If convergence occurred with little resistance, those feet were called hyperelastic. The convergence of the heads I and V metatarsal bones of the foot with an average type of elasticity occurred with resistance. It was impossible to converge the heads of I and V metatarsal bones. Due to the results of weight-bearing and non-weight bearing X-ray, analysis of the main radiographic angles of the foot was performed: between I and V metatarsal bones, between the first and second metatarsal bones and between the first metatarsal bone and proximal phalanx of the great toe. Calculation formula of the forefoot flatness index, showing the average ratios of basic radiographic angles of the foot on the x-ray images (weight-bearing and non-weight bearing was created. An assessment of total joint hypermobility using Beighton scale and evaluation of first ray deformity using DuPont scale were performed. Statistical analysis of obtained data was performed, as a result of which significantly strong correlation between total joint hypermobility, forefoot elasticity and valgus deviation of the great toe were revealed. Results. 11% of the feet were hyperelastic. Calculation of the index of forefoot flatness showed that forefoot flatness wasn’t significant for a rigid foot - 5.6 %, for the feet with an average degree of mobility it was 6.0% and it was expressed for hypemobile feet - 12.3 %. Strong correlation relation between the forefeet
Transform analysis of generalized functions
Misra, O P
1986-01-01
Transform Analysis of Generalized Functions concentrates on finite parts of integrals, generalized functions and distributions. It gives a unified treatment of the distributional setting with transform analysis, i.e. Fourier, Laplace, Stieltjes, Mellin, Hankel and Bessel Series.Included are accounts of applications of the theory of integral transforms in a distributional setting to the solution of problems arising in mathematical physics. Information on distributional solutions of differential, partial differential equations and integral equations is conveniently collected here.The volume will
Generalized laws of thermodynamics in the presence of correlations.
Bera, Manabendra N; Riera, Arnau; Lewenstein, Maciej; Winter, Andreas
2017-12-19
The laws of thermodynamics, despite their wide range of applicability, are known to break down when systems are correlated with their environments. Here we generalize thermodynamics to physical scenarios which allow presence of correlations, including those where strong correlations are present. We exploit the connection between information and physics, and introduce a consistent redefinition of heat dissipation by systematically accounting for the information flow from system to bath in terms of the conditional entropy. As a consequence, the formula for the Helmholtz free energy is accordingly modified. Such a remedy not only fixes the apparent violations of Landauer's erasure principle and the second law due to anomalous heat flows, but also leads to a generally valid reformulation of the laws of thermodynamics. In this information-theoretic approach, correlations between system and environment store work potential. Thus, in this view, the apparent anomalous heat flows are the refrigeration processes driven by such potentials.
General renormalized statistical approach with finite cross-field correlations
Vakulenko, M.O.
1992-01-01
The renormalized statistical approach is proposed, accounting for finite correlations of potential and magnetic fluctuations. It may be used for analysis of a wide class of nonlinear model equations describing the cross-correlated plasma states. The influence of a cross spectrum on stationary potential and magnetic ones is investigated. 10 refs. (author)
Langenbucher, Frieder
2005-01-01
A linear system comprising n compartments is completely defined by the rate constants between any of the compartments and the initial condition in which compartment(s) the drug is present at the beginning. The generalized solution is the time profiles of drug amount in each compartment, described by polyexponential equations. Based on standard matrix operations, an Excel worksheet computes the rate constants and the coefficients, finally the full time profiles for a specified range of time values.
Generalized inequalities for quantum correlations with hidden variables
Vinduska, M.
1991-01-01
Renowned inequalities for quantum correlations are generalized for the case when quantum system cannot be described with an absolute independent measure of the probability. Such a formulation appears to be suitable for the formulation of the hidden variables theory in terms of non-Euclidean geometry. 10 refs
Testing general relativity at cosmological scales: Implementation and parameter correlations
Dossett, Jason N.; Ishak, Mustapha; Moldenhauer, Jacob
2011-01-01
The testing of general relativity at cosmological scales has become a possible and timely endeavor that is not only motivated by the pressing question of cosmic acceleration but also by the proposals of some extensions to general relativity that would manifest themselves at large scales of distance. We analyze here correlations between modified gravity growth parameters and some core cosmological parameters using the latest cosmological data sets including the refined Cosmic Evolution Survey 3D weak lensing. We provide the parametrized modified growth equations and their evolution. We implement known functional and binning approaches, and propose a new hybrid approach to evolve the modified gravity parameters in redshift (time) and scale. The hybrid parametrization combines a binned redshift dependence and a smooth evolution in scale avoiding a jump in the matter power spectrum. The formalism developed to test the consistency of current and future data with general relativity is implemented in a package that we make publicly available and call ISiTGR (Integrated Software in Testing General Relativity), an integrated set of modified modules for the publicly available packages CosmoMC and CAMB, including a modified version of the integrated Sachs-Wolfe-galaxy cross correlation module of Ho et al. and a new weak-lensing likelihood module for the refined Hubble Space Telescope Cosmic Evolution Survey weak gravitational lensing tomography data. We obtain parameter constraints and correlation coefficients finding that modified gravity parameters are significantly correlated with σ 8 and mildly correlated with Ω m , for all evolution methods. The degeneracies between σ 8 and modified gravity parameters are found to be substantial for the functional form and also for some specific bins in the hybrid and binned methods indicating that these degeneracies will need to be taken into consideration when using future high precision data.
MRI correlates of general intelligence in neurotypical adults.
Malpas, Charles B; Genc, Sila; Saling, Michael M; Velakoulis, Dennis; Desmond, Patricia M; O'Brien, Terence J
2016-02-01
There is growing interest in the neurobiological substrate of general intelligence. Psychometric estimates of general intelligence are reduced in a range of neurological disorders, leading to practical application as sensitive, but non-specific, markers of cerebral disorder. This study examined estimates of general intelligence in neurotypical adults using diffusion tensor imaging and resting-state functional connectivity analysis. General intelligence was related to white matter organisation across multiple brain regions, confirming previous work in older healthy adults. We also found that variation in general intelligence was related to a large functional sub-network involving all cortical lobes of the brain. These findings confirm that individual variance in general intelligence is related to diffusely represented brain networks. Copyright © 2015 Elsevier Ltd. All rights reserved.
Correlated quadratures of resonance fluorescence and the generalized uncertainty relation
Arnoldus, Henk F.; George, Thomas F.; Gross, Rolf W. F.
1994-01-01
Resonance fluorescence from a two-state atom has been predicted to exhibit quadrature squeezing below the Heisenberg uncertainty limit, provided that the optical parameters (Rabi frequency, detuning, laser linewidth, etc.) are chosen carefully. When the correlation between two quadratures of the radiation field does not vanish, however, the Heisenberg limit for quantum fluctuations might be an unrealistic lower bound. A generalized uncertainty relation, due to Schroedinger, takes into account the possible correlation between the quadrature components of the radiation, and it suggests a modified definition of squeezing. We show that the coherence between the two levels of a laser-driven atom is responsible for the correlation between the quadrature components of the emitted fluorescence, and that the Schrodinger uncertainty limit increases monotonically with the coherence. On the other hand, the fluctuations in the quadrature field diminish with an increasing coherence, and can disappear completely when the coherence reaches 1/2, provided that certain phase relations hold.
Functional Multiple-Set Canonical Correlation Analysis
Hwang, Heungsun; Jung, Kwanghee; Takane, Yoshio; Woodward, Todd S.
2012-01-01
We propose functional multiple-set canonical correlation analysis for exploring associations among multiple sets of functions. The proposed method includes functional canonical correlation analysis as a special case when only two sets of functions are considered. As in classical multiple-set canonical correlation analysis, computationally, the…
A Systems-Theoretical Generalization of Non-Local Correlations
von Stillfried, Nikolaus
Non-local correlations between quantum events are not due to a causal interaction in the sense of one being the cause for the other. In principle, the correlated events can thus occur simultaneously. Generalized Quantum Theory (GQT) formalizes the idea that non-local phenomena are not exclusive to quantum mechanics, e.g. due to some specific properties of (sub)atomic particles, but that they instead arise as a consequence of the way such particles are arranged into systems. Non-local phenomena should hence occur in any system which fulfils the necessary systems-theoretical parameters. The two most important parameters with respect to non-local correlations seem to be a conserved global property of the system as a whole and sufficient degrees of freedom of the corresponding property of its subsystems. Both factors place severe limitations on experimental observability of the phenomena, especially in terms of replicability. It has been suggested that reported phenomena of a so-called synchronistic, parapsychological or paranormal kind could be understood as instances of systems-inherent non-local correlations. From a systems-theoretical perspective, their phenomenology (including the favorable conditions for their occurrence and their lack of replicability) displays substantial similarities to non-local correlations in quantum systems and matches well with systems-theoretical parameters, thus providing circumstantial evidence for this hypothesis.
General theory of intensity correlation on light scattering
Villaeys, A.A.
1978-01-01
A general theory for spatio-temporal intensity correlations measurements for a scattered beam is developed. A completely quantum mechanical description for both excitation and detection set up is used. This description is essentially valid for weak incident light beams and single photon absorption processes. From a unified point of view both, stationary as well as, time resolved experiments are described. The interest for such experiments in the study of processes like resonance raman scattering and resonance fluorescence is emphasized. Also an observable coherent contribution associated to different final levels of the target-atoms or molecules is obtained a result which cannot be reached by intensity measurements
Functional Generalized Structured Component Analysis.
Suk, Hye Won; Hwang, Heungsun
2016-12-01
An extension of Generalized Structured Component Analysis (GSCA), called Functional GSCA, is proposed to analyze functional data that are considered to arise from an underlying smooth curve varying over time or other continua. GSCA has been geared for the analysis of multivariate data. Accordingly, it cannot deal with functional data that often involve different measurement occasions across participants and a large number of measurement occasions that exceed the number of participants. Functional GSCA addresses these issues by integrating GSCA with spline basis function expansions that represent infinite-dimensional curves onto a finite-dimensional space. For parameter estimation, functional GSCA minimizes a penalized least squares criterion by using an alternating penalized least squares estimation algorithm. The usefulness of functional GSCA is illustrated with gait data.
Contributions to sensitivity analysis and generalized discriminant analysis
Jacques, J.
2005-12-01
Two topics are studied in this thesis: sensitivity analysis and generalized discriminant analysis. Global sensitivity analysis of a mathematical model studies how the output variables of this last react to variations of its inputs. The methods based on the study of the variance quantify the part of variance of the response of the model due to each input variable and each subset of input variables. The first subject of this thesis is the impact of a model uncertainty on results of a sensitivity analysis. Two particular forms of uncertainty are studied: that due to a change of the model of reference, and that due to the use of a simplified model with the place of the model of reference. A second problem was studied during this thesis, that of models with correlated inputs. Indeed, classical sensitivity indices not having significance (from an interpretation point of view) in the presence of correlation of the inputs, we propose a multidimensional approach consisting in expressing the sensitivity of the output of the model to groups of correlated variables. Applications in the field of nuclear engineering illustrate this work. Generalized discriminant analysis consists in classifying the individuals of a test sample in groups, by using information contained in a training sample, when these two samples do not come from the same population. This work extends existing methods in a Gaussian context to the case of binary data. An application in public health illustrates the utility of generalized discrimination models thus defined. (author)
Nonlinear canonical correlation analysis with k sets of variables
van der Burg, Eeke; de Leeuw, Jan
1987-01-01
The multivariate technique OVERALS is introduced as a non-linear generalization of canonical correlation analysis (CCA). First, two sets CCA is introduced. Two sets CCA is a technique that computes linear combinations of sets of variables that correlate in an optimal way. Two sets CCA is then
Multifractal detrended cross-correlation analysis in the MENA area
El Alaoui, Marwane; Benbachir, Saâd
2013-12-01
In this paper, we investigated multifractal cross-correlations qualitatively and quantitatively using a cross-correlation test and the Multifractal detrended cross-correlation analysis method (MF-DCCA) for markets in the MENA area. We used cross-correlation coefficients to measure the level of this correlation. The analysis concerns four stock market indices of Morocco, Tunisia, Egypt and Jordan. The countries chosen are signatory of the Agadir agreement concerning the establishment of a free trade area comprising Arab Mediterranean countries. We computed the bivariate generalized Hurst exponent, Rényi exponent and spectrum of singularity for each pair of indices to measure quantitatively the cross-correlations. By analyzing the results, we found the existence of multifractal cross-correlations between all of these markets. We compared the spectrum width of these indices; we also found which pair of indices has a strong multifractal cross-correlation.
Meta-Analysis of Correlations Among Usability Measures
Hornbæk, Kasper Anders Søren; Effie Lai Chong, Law
2007-01-01
are generally low: effectiveness measures (e.g., errors) and efficiency measures (e.g., time) has a correlation of .247 ± .059 (Pearson's product-moment correlation with 95% confidence interval), efficiency and satisfaction (e.g., preference) one of .196 ± .064, and effectiveness and satisfaction one of .164......Understanding the relation between usability measures seems crucial to deepen our conception of usability and to select the right measures for usability studies. We present a meta-analysis of correlations among usability measures calculated from the raw data of 73 studies. Correlations...... ± .062. Changes in task complexity do not influence these correlations, but use of more complex measures attenuates them. Standard questionnaires for measuring satisfaction appear more reliable than homegrown ones. Measures of users' perceptions of phenomena are generally not correlated with objective...
Correlation analysis in chemistry: recent advances
Shorter, John; Chapman, Norman Bellamy
1978-01-01
..., and applications of LFER to polycyclic arenes, heterocyclic compounds, and olefinic systems. Of particular interest is the extensive critical compilation of substituent constants and the numerous applications of correlation analysis to spectroscopy...
Dimensional Analysis and General Relativity
Lovatt, Ian
2009-01-01
Newton's law of gravitation is a central topic in the first-year physics curriculum. A lecturer can go beyond the physical details and use the history of gravitation to discuss the development of scientific ideas; unfortunately, the most recent chapter in this history, general relativity, is not covered in first-year courses. This paper discusses…
Analytic uncertainty and sensitivity analysis of models with input correlations
Zhu, Yueying; Wang, Qiuping A.; Li, Wei; Cai, Xu
2018-03-01
Probabilistic uncertainty analysis is a common means of evaluating mathematical models. In mathematical modeling, the uncertainty in input variables is specified through distribution laws. Its contribution to the uncertainty in model response is usually analyzed by assuming that input variables are independent of each other. However, correlated parameters are often happened in practical applications. In the present paper, an analytic method is built for the uncertainty and sensitivity analysis of models in the presence of input correlations. With the method, it is straightforward to identify the importance of the independence and correlations of input variables in determining the model response. This allows one to decide whether or not the input correlations should be considered in practice. Numerical examples suggest the effectiveness and validation of our analytic method in the analysis of general models. A practical application of the method is also proposed to the uncertainty and sensitivity analysis of a deterministic HIV model.
Multivariate Generalized Multiscale Entropy Analysis
Anne Humeau-Heurtier
2016-11-01
Full Text Available Multiscale entropy (MSE was introduced in the 2000s to quantify systems’ complexity. MSE relies on (i a coarse-graining procedure to derive a set of time series representing the system dynamics on different time scales; (ii the computation of the sample entropy for each coarse-grained time series. A refined composite MSE (rcMSE—based on the same steps as MSE—also exists. Compared to MSE, rcMSE increases the accuracy of entropy estimation and reduces the probability of inducing undefined entropy for short time series. The multivariate versions of MSE (MMSE and rcMSE (MrcMSE have also been introduced. In the coarse-graining step used in MSE, rcMSE, MMSE, and MrcMSE, the mean value is used to derive representations of the original data at different resolutions. A generalization of MSE was recently published, using the computation of different moments in the coarse-graining procedure. However, so far, this generalization only exists for univariate signals. We therefore herein propose an extension of this generalized MSE to multivariate data. The multivariate generalized algorithms of MMSE and MrcMSE presented herein (MGMSE and MGrcMSE, respectively are first analyzed through the processing of synthetic signals. We reveal that MGrcMSE shows better performance than MGMSE for short multivariate data. We then study the performance of MGrcMSE on two sets of short multivariate electroencephalograms (EEG available in the public domain. We report that MGrcMSE may show better performance than MrcMSE in distinguishing different types of multivariate EEG data. MGrcMSE could therefore supplement MMSE or MrcMSE in the processing of multivariate datasets.
Detrended cross-correlation analysis of electroencephalogram
Wang Jun; Zhao Da-Qing
2012-01-01
In the paper we use detrended cross-correlation analysis (DCCA) to study the electroencephalograms of healthy young subjects and healthy old subjects. It is found that the cross-correlation between different leads of a healthy young subject is larger than that of a healthy old subject. It was shown that the cross-correlation relationship decreases with the aging process and the phenomenon can help to diagnose whether the subject's brain function is healthy or not. (interdisciplinary physics and related areas of science and technology)
Multicollinearity in canonical correlation analysis in maize.
Alves, B M; Cargnelutti Filho, A; Burin, C
2017-03-30
The objective of this study was to evaluate the effects of multicollinearity under two methods of canonical correlation analysis (with and without elimination of variables) in maize (Zea mays L.) crop. Seventy-six maize genotypes were evaluated in three experiments, conducted in a randomized block design with three replications, during the 2009/2010 crop season. Eleven agronomic variables (number of days from sowing until female flowering, number of days from sowing until male flowering, plant height, ear insertion height, ear placement, number of plants, number of ears, ear index, ear weight, grain yield, and one thousand grain weight), 12 protein-nutritional variables (crude protein, lysine, methionine, cysteine, threonine, tryptophan, valine, isoleucine, leucine, phenylalanine, histidine, and arginine), and 6 energetic-nutritional variables (apparent metabolizable energy, apparent metabolizable energy corrected for nitrogen, ether extract, crude fiber, starch, and amylose) were measured. A phenotypic correlation matrix was first generated among the 29 variables for each of the experiments. A multicollinearity diagnosis was later performed within each group of variables using methodologies such as variance inflation factor and condition number. Canonical correlation analysis was then performed, with and without the elimination of variables, among groups of agronomic and protein-nutritional, and agronomic and energetic-nutritional variables. The canonical correlation analysis in the presence of multicollinearity (without elimination of variables) overestimates the variability of canonical coefficients. The elimination of variables is an efficient method to circumvent multicollinearity in canonical correlation analysis.
Bayesian Correlation Analysis for Sequence Count Data.
Daniel Sánchez-Taltavull
Full Text Available Evaluating the similarity of different measured variables is a fundamental task of statistics, and a key part of many bioinformatics algorithms. Here we propose a Bayesian scheme for estimating the correlation between different entities' measurements based on high-throughput sequencing data. These entities could be different genes or miRNAs whose expression is measured by RNA-seq, different transcription factors or histone marks whose expression is measured by ChIP-seq, or even combinations of different types of entities. Our Bayesian formulation accounts for both measured signal levels and uncertainty in those levels, due to varying sequencing depth in different experiments and to varying absolute levels of individual entities, both of which affect the precision of the measurements. In comparison with a traditional Pearson correlation analysis, we show that our Bayesian correlation analysis retains high correlations when measurement confidence is high, but suppresses correlations when measurement confidence is low-especially for entities with low signal levels. In addition, we consider the influence of priors on the Bayesian correlation estimate. Perhaps surprisingly, we show that naive, uniform priors on entities' signal levels can lead to highly biased correlation estimates, particularly when different experiments have widely varying sequencing depths. However, we propose two alternative priors that provably mitigate this problem. We also prove that, like traditional Pearson correlation, our Bayesian correlation calculation constitutes a kernel in the machine learning sense, and thus can be used as a similarity measure in any kernel-based machine learning algorithm. We demonstrate our approach on two RNA-seq datasets and one miRNA-seq dataset.
Evaluation of time correlation functions from a generalized Enskog equation
Yip, S.; Alley, W.E.; Alder, B.J.
1982-01-01
Numerical results for the density and current correlation functions in dense hard-shape fluids are obtained from a kinetic equation which is the extension of the linearized Enskog equation to finite wavelengths in order to demonstrate the convergence of the method of solution. Comparison is made to a previously proposed approximate solution.
Evaluation of time correlation functions from a generalized Enskog equation
Yip, S.; Alley, W.E.; Alder, B.J.
1982-01-01
Numerical results for the density and current correlation functions in dense hard-shape fluids are obtained from a kinetic equation which is the extension of the linearized Enskog equation to finite wavelengths in order to demonstrate the convergence of the method of solution. Comparison is made to a previously proposed approximate solution
Generalized Analysis of a Distribution Separation Method
Peng Zhang
2016-04-01
Full Text Available Separating two probability distributions from a mixture model that is made up of the combinations of the two is essential to a wide range of applications. For example, in information retrieval (IR, there often exists a mixture distribution consisting of a relevance distribution that we need to estimate and an irrelevance distribution that we hope to get rid of. Recently, a distribution separation method (DSM was proposed to approximate the relevance distribution, by separating a seed irrelevance distribution from the mixture distribution. It was successfully applied to an IR task, namely pseudo-relevance feedback (PRF, where the query expansion model is often a mixture term distribution. Although initially developed in the context of IR, DSM is indeed a general mathematical formulation for probability distribution separation. Thus, it is important to further generalize its basic analysis and to explore its connections to other related methods. In this article, we first extend DSM’s theoretical analysis, which was originally based on the Pearson correlation coefficient, to entropy-related measures, including the KL-divergence (Kullback–Leibler divergence, the symmetrized KL-divergence and the JS-divergence (Jensen–Shannon divergence. Second, we investigate the distribution separation idea in a well-known method, namely the mixture model feedback (MMF approach. We prove that MMF also complies with the linear combination assumption, and then, DSM’s linear separation algorithm can largely simplify the EM algorithm in MMF. These theoretical analyses, as well as further empirical evaluation results demonstrate the advantages of our DSM approach.
Graphology and personality: a correlational analysis
2008-01-01
M.A. The title of this dissertation reads as follows: Graphology and Personality: A Correlational Analysis. The aim of this dissertation is to introduce a different projective technique (as of yet not very widely used) into the psychological arena of assessment. Graphology is a projective technique that allows the analyst to delve into the personality of the individual. Very shortly, graphology can be defined as the assessment or analysis of a person’s handwriting. When a child first attem...
Lectures on general quantum correlations and their applications
Pinto, Diogo; Adesso, Gerardo
2017-01-01
This book presents a distinctive way of understanding quantum correlations beyond entanglement, introducing readers to this less explored yet very fundamental aspect of quantum theory. It takes into account most of the new ideas involving quantum phenomena, resources, and applications without entanglement, both from a theoretical and an experimental point of view. This book serves as a reference for both beginner students and experienced researchers in physics and applied mathematics, with an interest in joining this novel venture towards understanding the quantum nature of the world.
Solving the generalized Langevin equation with the algebraically correlated noise
Srokowski, T.; Ploszajczak, M.
1997-01-01
The Langevin equation with the memory kernel is solved. The stochastic force possesses algebraic correlations, proportional to 1/t. The velocity autocorrelation function and related quantities characterizing transport properties are calculated at the assumption that the system is in the thermal equilibrium. Stochastic trajectories are simulated numerically, using the kangaroo process as a noise generator. Results of this simulation resemble Levy walks with divergent moments of the velocity distribution. The motion of a Brownian particle is considered both without any external potential and in the harmonic oscillator field, in particular the escape from a potential well. The results are compared with memory-free calculations for the Brownian particle. (author)
Two general models that generate long range correlation
Gan, Xiaocong; Han, Zhangang
2012-06-01
In this paper we study two models that generate sequences with LRC (long range correlation). For the IFT (inverse Fourier transform) model, our conclusion is the low frequency part leads to LRC, while the high frequency part tends to eliminate it. Therefore, a typical method to generate a sequence with LRC is multiplying the spectrum of a white noise sequence by a decaying function. A special case is analyzed: the linear combination of a smooth curve and a white noise sequence, in which the DFA plot consists of two line segments. For the patch model, our conclusion is long subsequences leads to LRC, while short subsequences tend to eliminate it. Therefore, we can generate a sequence with LRC by using a fat-tailed PDF (probability distribution function) of the length of the subsequences. A special case is also analyzed: if a patch model with long subsequences is mixed with a white noise sequence, the DFA plot will consist of two line segments. We have checked known models and actual data, and found they are all consistent with this study.
International Space Station Future Correlation Analysis Improvements
Laible, Michael R.; Pinnamaneni, Murthy; Sugavanam, Sujatha; Grygier, Michael
2018-01-01
Ongoing modal analyses and model correlation are performed on different configurations of the International Space Station (ISS). These analyses utilize on-orbit dynamic measurements collected using four main ISS instrumentation systems: External Wireless Instrumentation System (EWIS), Internal Wireless Instrumentation System (IWIS), Space Acceleration Measurement System (SAMS), and Structural Dynamic Measurement System (SDMS). Remote Sensor Units (RSUs) are network relay stations that acquire flight data from sensors. Measured data is stored in the Remote Sensor Unit (RSU) until it receives a command to download data via RF to the Network Control Unit (NCU). Since each RSU has its own clock, it is necessary to synchronize measurements before analysis. Imprecise synchronization impacts analysis results. A study was performed to evaluate three different synchronization techniques: (i) measurements visually aligned to analytical time-response data using model comparison, (ii) Frequency Domain Decomposition (FDD), and (iii) lag from cross-correlation to align measurements. This paper presents the results of this study.
A general first-order global sensitivity analysis method
Xu Chonggang; Gertner, George Zdzislaw
2008-01-01
Fourier amplitude sensitivity test (FAST) is one of the most popular global sensitivity analysis techniques. The main mechanism of FAST is to assign each parameter with a characteristic frequency through a search function. Then, for a specific parameter, the variance contribution can be singled out of the model output by the characteristic frequency. Although FAST has been widely applied, there are two limitations: (1) the aliasing effect among parameters by using integer characteristic frequencies and (2) the suitability for only models with independent parameters. In this paper, we synthesize the improvement to overcome the aliasing effect limitation [Tarantola S, Gatelli D, Mara TA. Random balance designs for the estimation of first order global sensitivity indices. Reliab Eng Syst Safety 2006; 91(6):717-27] and the improvement to overcome the independence limitation [Xu C, Gertner G. Extending a global sensitivity analysis technique to models with correlated parameters. Comput Stat Data Anal 2007, accepted for publication]. In this way, FAST can be a general first-order global sensitivity analysis method for linear/nonlinear models with as many correlated/uncorrelated parameters as the user specifies. We apply the general FAST to four test cases with correlated parameters. The results show that the sensitivity indices derived by the general FAST are in good agreement with the sensitivity indices derived by the correlation ratio method, which is a non-parametric method for models with correlated parameters
Correlation between effective dose and radiological risk: general concepts
Costa, Paulo Roberto; Yoshimura, Elisabeth Mateus; Nersissian, Denise Yanikian; Melo, Camila Souza, E-mail: pcosta@if.usp.br [Universidade de Sao Paulo (IF/USP), Sao Paulo, SP (Brazil). Instituto de Fisica
2016-05-15
The present review aims to offer an educational approach related to the limitations in the use of the effective dose magnitude as a tool for the quantification of doses resulting from diagnostic applications of ionizing radiation. We present a critical analysis of the quantities accepted and currently used for dosimetric evaluation in diagnostic imaging procedures, based on studies published in the literature. It is highlighted the use of these quantities to evaluate the risk attributed to the procedure and to calculate the effective dose, as well as to determine its correct use and interpretation. (author)
Tolerating Correlated Failures for Generalized Cartesian Distributions via Bipartite Matching
Ali, Nawab; Krishnamoorthy, Sriram; Halappanavar, Mahantesh; Daily, Jeffrey A.
2011-01-01
Faults are expected to play an increasingly important role in how algorithms and applications are designed to run on future extreme-scale systems. A key ingredient of any approach to fault tolerance is effective support for fault tolerant data storage. A typical application execution consists of phases in which certain data structures are modified while others are read-only. Often, read-only data structures constitute a large fraction of total memory consumed. Fault tolerance for read-only data can be ensured through the use of checksums or parities, without resorting to expensive in-memory duplication or checkpointing to secondary storage. In this paper, we present a graph-matching approach to compute and store parity data for read-only matrices that are compatible with fault tolerant linear algebra (FTLA). Typical approaches only support blocked data distributions with each process holding one block with the parity located on additional processes. The matrices are assumed to be blocked by a cartesian grid with each block assigned to a process. We consider a generalized distribution in which each process can be assigned arbitrary blocks. We also account for the fact that multiple processes might be part of the same failure unit, say an SMP node. The flexibility enabled by our novel application of graph matching extends fault tolerance support to data distributions beyond those supported by prior work. We evaluate the matching implementations and cost to compute the parity and recover lost data, demonstrating the low overhead incurred by our approach.
Linear and Nonlinear Multiset Canonical Correlation Analysis (invited talk)
Hilger, Klaus Baggesen; Nielsen, Allan Aasbjerg; Larsen, Rasmus
2002-01-01
This paper deals with decompositioning of multiset data. Friedman's alternating conditional expectations (ACE) algorithm is extended to handle multiple sets of variables of different mixtures. The new algorithm finds estimates of the optimal transformations of the involved variables that maximize...... the sum of the pair-wise correlations over all sets. The new algorithm is termed multi-set ACE (MACE) and can find multiple orthogonal eigensolutions. MACE is a generalization of the linear multiset correlations analysis (MCCA). It handles multivariate multisets of arbitrary mixtures of both continuous...
Gait Correlation Analysis Based Human Identification
Jinyan Chen
2014-01-01
Full Text Available Human gait identification aims to identify people by a sequence of walking images. Comparing with fingerprint or iris based identification, the most important advantage of gait identification is that it can be done at a distance. In this paper, silhouette correlation analysis based human identification approach is proposed. By background subtracting algorithm, the moving silhouette figure can be extracted from the walking images sequence. Every pixel in the silhouette has three dimensions: horizontal axis (x, vertical axis (y, and temporal axis (t. By moving every pixel in the silhouette image along these three dimensions, we can get a new silhouette. The correlation result between the original silhouette and the new one can be used as the raw feature of human gait. Discrete Fourier transform is used to extract features from this correlation result. Then, these features are normalized to minimize the affection of noise. Primary component analysis method is used to reduce the features’ dimensions. Experiment based on CASIA database shows that this method has an encouraging recognition performance.
International Space Station Model Correlation Analysis
Laible, Michael R.; Fitzpatrick, Kristin; Hodge, Jennifer; Grygier, Michael
2018-01-01
This paper summarizes the on-orbit structural dynamic data and the related modal analysis, model validation and correlation performed for the International Space Station (ISS) configuration ISS Stage ULF7, 2015 Dedicated Thruster Firing (DTF). The objective of this analysis is to validate and correlate the analytical models used to calculate the ISS internal dynamic loads and compare the 2015 DTF with previous tests. During the ISS configurations under consideration, on-orbit dynamic measurements were collected using the three main ISS instrumentation systems; Internal Wireless Instrumentation System (IWIS), External Wireless Instrumentation System (EWIS) and the Structural Dynamic Measurement System (SDMS). The measurements were recorded during several nominal on-orbit DTF tests on August 18, 2015. Experimental modal analyses were performed on the measured data to extract modal parameters including frequency, damping, and mode shape information. Correlation and comparisons between test and analytical frequencies and mode shapes were performed to assess the accuracy of the analytical models for the configurations under consideration. These mode shapes were also compared to earlier tests. Based on the frequency comparisons, the accuracy of the mathematical models is assessed and model refinement recommendations are given. In particular, results of the first fundamental mode will be discussed, nonlinear results will be shown, and accelerometer placement will be assessed.
The generalized correlation method for estimation of time delay in power plants
Kostic, Lj.
1981-01-01
The generalized correlation estimation is developed for determining time delay between signals received at two spatially separated sensors in the presence of uncorrelated noise in a power plant. This estimator can be realized as a pair of receiver prefilters followed by a cross correlator. The time argument at which the correlator achieves a maximum is the delay estimate. (author)
System Reliability Analysis Considering Correlation of Performances
Kim, Saekyeol; Lee, Tae Hee [Hanyang Univ., Seoul (Korea, Republic of); Lim, Woochul [Mando Corporation, Seongnam (Korea, Republic of)
2017-04-15
Reliability analysis of a mechanical system has been developed in order to consider the uncertainties in the product design that may occur from the tolerance of design variables, uncertainties of noise, environmental factors, and material properties. In most of the previous studies, the reliability was calculated independently for each performance of the system. However, the conventional methods cannot consider the correlation between the performances of the system that may lead to a difference between the reliability of the entire system and the reliability of the individual performance. In this paper, the joint probability density function (PDF) of the performances is modeled using a copula which takes into account the correlation between performances of the system. The system reliability is proposed as the integral of joint PDF of performances and is compared with the individual reliability of each performance by mathematical examples and two-bar truss example.
Metrics correlation and analysis service (MCAS)
Baranovski, Andrew; Dykstra, Dave; Garzoglio, Gabriele; Hesselroth, Ted; Mhashilkar, Parag; Levshina, Tanya
2010-01-01
The complexity of Grid workflow activities and their associated software stacks inevitably involves multiple organizations, ownership, and deployment domains. In this setting, important and common tasks such as the correlation and display of metrics and debugging information (fundamental ingredients of troubleshooting) are challenged by the informational entropy inherent to independently maintained and operated software components. Because such an information pool is disorganized, it is a difficult environment for business intelligence analysis i.e. troubleshooting, incident investigation, and trend spotting. The mission of the MCAS project is to deliver a software solution to help with adaptation, retrieval, correlation, and display of workflow-driven data and of type-agnostic events, generated by loosely coupled or fully decoupled middleware.
Metrics correlation and analysis service (MCAS)
Baranovski, Andrew; Dykstra, Dave; Garzoglio, Gabriele; Hesselroth, Ted; Mhashilkar, Parag; Levshina, Tanya
2009-01-01
The complexity of Grid workflow activities and their associated software stacks inevitably involves multiple organizations, ownership, and deployment domains. In this setting, important and common tasks such as the correlation and display of metrics and debugging information (fundamental ingredients of troubleshooting) are challenged by the informational entropy inherent to independently maintained and operated software components. Because such an information 'pond' is disorganized, it a difficult environment for business intelligence analysis i.e. troubleshooting, incident investigation and trend spotting. The mission of the MCAS project is to deliver a software solution to help with adaptation, retrieval, correlation, and display of workflow-driven data and of type-agnostic events, generated by disjoint middleware.
System Reliability Analysis Considering Correlation of Performances
Kim, Saekyeol; Lee, Tae Hee; Lim, Woochul
2017-01-01
Reliability analysis of a mechanical system has been developed in order to consider the uncertainties in the product design that may occur from the tolerance of design variables, uncertainties of noise, environmental factors, and material properties. In most of the previous studies, the reliability was calculated independently for each performance of the system. However, the conventional methods cannot consider the correlation between the performances of the system that may lead to a difference between the reliability of the entire system and the reliability of the individual performance. In this paper, the joint probability density function (PDF) of the performances is modeled using a copula which takes into account the correlation between performances of the system. The system reliability is proposed as the integral of joint PDF of performances and is compared with the individual reliability of each performance by mathematical examples and two-bar truss example.
Ruemper, Alia; Watkins, Katherine
2012-12-01
The first objective of this study was to ascertain the prevalence of general joint hypermobility (GJH) and joint hypermobility syndrome (JHS) in BA Dance Theatre 1st and 3rd year students at a contemporary dance conservatory. The second objective was to determine the statistical correlation between GJH, JHS, and injury in this population. A total of 85 (female, N = 78; male, N = 7) contemporary dance students participated in the study. The Beighton score (with a forward flexion test modification) was used to determine GJH, and the Brighton criteria were used to verify JHS. Participants completed a self-reported injury questionnaire that included type of injury (physical complaint, medical diagnosis, or time-loss) and injury frequency. Statistical analysis (Pearson correlation) was used to correlate GJH, JHS, and frequency-of-injury scores. Overall, 69% of the students were found to have GJH, and 33% had JHS. A statistical correlation of r = + 0.331 (p dance students and suggests that screening programs should include the Brighton criteria to identify JHS in these dancers. Subsequent injury tracking and injury prevention programs would then provide data for further research in this area.
Cross-correlation analysis of Ge/Li/ spectra
MacDonald, R.; Robertson, A.; Kennett, T.J.; Prestwich, W.V.
1974-01-01
A sensitive technique is proposed for activation analysis using cross-correlation and improved spectral orthogonality achieved through use of a rectangular zero area digital filter. To test the accuracy and reliability of the cross-correlation procedure five spectra obtained with a Ge/Li detector were combined in different proportions. Gaussian distributed statistics were then added to the composite spectra by means of a pseudo-random number generator. The basis spectra used were 76 As, 82 Br, 72 Ga, 77 Ge, and room background. In general, when the basis spectra were combined in roughly comparable proportions the accuracy of the techique proved to be excelent (>1%). However, of primary importance was the ability of the correlation technique to identify low intensity components in the presence of high intensity components. It was found that the detection threshold for Ge, for example, was not reached until the Ge content in the unfiltered spectrum was <0.16%. (T.G.)
A General Approach to Causal Mediation Analysis
Imai, Kosuke; Keele, Luke; Tingley, Dustin
2010-01-01
Traditionally in the social sciences, causal mediation analysis has been formulated, understood, and implemented within the framework of linear structural equation models. We argue and demonstrate that this is problematic for 3 reasons: the lack of a general definition of causal mediation effects independent of a particular statistical model, the…
Texture analysis using Renyi's generalized entropies
Grigorescu, SE; Petkov, N
2003-01-01
We propose a texture analysis method based on Renyi's generalized entropies. The method aims at identifying texels in regular textures by searching for the smallest window through which the minimum number of different visual patterns is observed when moving the window over a given texture. The
Semiclassical analysis spectral correlations in mesoscopic systems
Argaman, N.; Imry, Y.; Smilansky, U.
1991-07-01
We consider the recently developed semiclassical analysis of the quantum mechanical spectral form factor, which may be expressed in terms of classically defiable properties. When applied to electrons whose classical behaviour is diffusive, the results of earlier quantum mechanical perturbative derivations, which were developed under a different set of assumptions, are reproduced. The comparison between the two derivations shows that the results depends not on their specific details, but to a large extent on the principle of quantum coherent superposition, and on the generality of the notion of diffusion. The connection with classical properties facilitates application to many physical situations. (author)
Pekár, S.; Brabec, Marek
2018-01-01
Roč. 124, č. 2 (2018), s. 86-93 ISSN 0179-1613 Institutional support: RVO:67985807 Keywords : correlated data * generalized estimating equations * marginal model * regression models * statistical analysis Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.398, year: 2016
Automatic movie skimming with general tempo analysis
Lee, Shih-Hung; Yeh, Chia-Hung; Kuo, C. C. J.
2003-11-01
Story units are extracted by general tempo analysis including tempos analysis including tempos of audio and visual information in this research. Although many schemes have been proposed to successfully segment video data into shots using basic low-level features, how to group shots into meaningful units called story units is still a challenging problem. By focusing on a certain type of video such as sport or news, we can explore models with the specific application domain knowledge. For movie contents, many heuristic rules based on audiovisual clues have been proposed with limited success. We propose a method to extract story units using general tempo analysis. Experimental results are given to demonstrate the feasibility and efficiency of the proposed technique.
General aviation air traffic pattern safety analysis
Parker, L. C.
1973-01-01
A concept is described for evaluating the general aviation mid-air collision hazard in uncontrolled terminal airspace. Three-dimensional traffic pattern measurements were conducted at uncontrolled and controlled airports. Computer programs for data reduction, storage retrieval and statistical analysis have been developed. Initial general aviation air traffic pattern characteristics are presented. These preliminary results indicate that patterns are highly divergent from the expected standard pattern, and that pattern procedures observed can affect the ability of pilots to see and avoid each other.
Nuclear-data evaluation based on direct and indirect measurements with general correlations
Muir, D.W.
1988-01-01
Optimum procedures for the statistical improvement, or updating, of an existing nuclear-data evaluation are reviewed and redeveloped from first principles, consistently employing a minimum-variance viewpoint. A set of equations is derived which provides improved values of the data and their covariances, taking into account information from supplementary measurements and allowing for general correlations among all measurements. The minimum-variance solutions thus obtained, which we call the method of 'partitioned least squares,' are found to be equivalent to a method suggested by Yu. V. Linnik and applied by a number of authors to the analysis of fission-reactor integral experiments; however, up to now, the partitioned-least-squares formulae have not found widespread use in the field of basic data evaluation. This approach is shown to give the same results as the more commonly applied Normal equations, but with reduced matrix inversion requirements. Examples are provided to indicate potential areas of application. (author)
Interpreting canonical correlation analysis through biplots of stucture correlations and weights
Braak, ter C.J.F.
1990-01-01
This paper extends the biplot technique to canonical correlation analysis and redundancy analysis. The plot of structure correlations is shown to the optimal for displaying the pairwise correlations between the variables of the one set and those of the second. The link between multivariate
Functional data analysis of generalized regression quantiles
Guo, Mengmeng
2013-11-05
Generalized regression quantiles, including the conditional quantiles and expectiles as special cases, are useful alternatives to the conditional means for characterizing a conditional distribution, especially when the interest lies in the tails. We develop a functional data analysis approach to jointly estimate a family of generalized regression quantiles. Our approach assumes that the generalized regression quantiles share some common features that can be summarized by a small number of principal component functions. The principal component functions are modeled as splines and are estimated by minimizing a penalized asymmetric loss measure. An iterative least asymmetrically weighted squares algorithm is developed for computation. While separate estimation of individual generalized regression quantiles usually suffers from large variability due to lack of sufficient data, by borrowing strength across data sets, our joint estimation approach significantly improves the estimation efficiency, which is demonstrated in a simulation study. The proposed method is applied to data from 159 weather stations in China to obtain the generalized quantile curves of the volatility of the temperature at these stations. © 2013 Springer Science+Business Media New York.
Functional data analysis of generalized regression quantiles
Guo, Mengmeng; Zhou, Lan; Huang, Jianhua Z.; Hä rdle, Wolfgang Karl
2013-01-01
Generalized regression quantiles, including the conditional quantiles and expectiles as special cases, are useful alternatives to the conditional means for characterizing a conditional distribution, especially when the interest lies in the tails. We develop a functional data analysis approach to jointly estimate a family of generalized regression quantiles. Our approach assumes that the generalized regression quantiles share some common features that can be summarized by a small number of principal component functions. The principal component functions are modeled as splines and are estimated by minimizing a penalized asymmetric loss measure. An iterative least asymmetrically weighted squares algorithm is developed for computation. While separate estimation of individual generalized regression quantiles usually suffers from large variability due to lack of sufficient data, by borrowing strength across data sets, our joint estimation approach significantly improves the estimation efficiency, which is demonstrated in a simulation study. The proposed method is applied to data from 159 weather stations in China to obtain the generalized quantile curves of the volatility of the temperature at these stations. © 2013 Springer Science+Business Media New York.
Long-range correlation analysis of urban traffic data
Peng, Sheng; Jun-Feng, Wang; Shu-Long, Zhao; Tie-Qiao, Tang
2010-01-01
This paper investigates urban traffic data by analysing the long-range correlation with detrended fluctuation analysis. Through a large number of real data collected by the travel time detection system in Beijing, the variation of flow in different time periods and intersections is studied. According to the long-range correlation in different time scales, it mainly discusses the effect of intersection location in road net, people activity customs and special traffic controls on urban traffic flow. As demonstrated by the obtained results, the urban traffic flow represents three-phase characters similar to highway traffic. Moreover, compared by the two groups of data obtained before and after the special traffic restrictions (vehicles with special numbered plates only run in a special workday) enforcement, it indicates that the rules not only reduce the flow but also avoid irregular fluctuation. (general)
A new methodology of spatial cross-correlation analysis.
Chen, Yanguang
2015-01-01
Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran's index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson's correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China's urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes.
A New Methodology of Spatial Cross-Correlation Analysis
Chen, Yanguang
2015-01-01
Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran’s index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson’s correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China’s urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes. PMID:25993120
Waaijenborg, S.; Zwinderman, A.H.
2009-01-01
ABSTRACT: BACKGROUND: We generalized penalized canonical correlation analysis for analyzing microarray gene-expression measurements for checking completeness of known metabolic pathways and identifying candidate genes for incorporation in the pathway. We used Wold's method for calculation of the
Attitudes to Mental Illness and Its Demographic Correlates among General Population in Singapore.
Qi Yuan
Full Text Available Public attitudes to mental illness could influence how the public interact with, provide opportunities for, and help people with mental illness.This study aims to explore the underlying factors of the Attitudes to Mental Illness questionnaire among the general population in Singapore and the socio-demographic correlates of each factor.From March 2014 to April 2015, a nation-wide cross-sectional survey on mental health literacy with 3,006 participants was conducted in Singapore.Factor analysis revealed a 4-factor structure for the Attitudes to Mental Illness questionnaire among the Singapore general population, namely social distancing, tolerance/support for community care, social restrictiveness, and prejudice and misconception. Older age, male gender, lower education and socio-economic status were associated with more negative attitudes towards the mentally ill. Chinese showed more negative attitudes than Indians and Malays (except for prejudice and misconception.There is a need for culture-specific interventions, and the associated factors identified in this study should be considered for future attitude campaigns.
Attitudes to Mental Illness and Its Demographic Correlates among General Population in Singapore.
Yuan, Qi; Abdin, Edimansyah; Picco, Louisa; Vaingankar, Janhavi Ajit; Shahwan, Shazana; Jeyagurunathan, Anitha; Sagayadevan, Vathsala; Shafie, Saleha; Tay, Jenny; Chong, Siow Ann; Subramaniam, Mythily
2016-01-01
Public attitudes to mental illness could influence how the public interact with, provide opportunities for, and help people with mental illness. This study aims to explore the underlying factors of the Attitudes to Mental Illness questionnaire among the general population in Singapore and the socio-demographic correlates of each factor. From March 2014 to April 2015, a nation-wide cross-sectional survey on mental health literacy with 3,006 participants was conducted in Singapore. Factor analysis revealed a 4-factor structure for the Attitudes to Mental Illness questionnaire among the Singapore general population, namely social distancing, tolerance/support for community care, social restrictiveness, and prejudice and misconception. Older age, male gender, lower education and socio-economic status were associated with more negative attitudes towards the mentally ill. Chinese showed more negative attitudes than Indians and Malays (except for prejudice and misconception). There is a need for culture-specific interventions, and the associated factors identified in this study should be considered for future attitude campaigns.
Attitudes to Mental Illness and Its Demographic Correlates among General Population in Singapore
Yuan, Qi; Abdin, Edimansyah; Picco, Louisa; Vaingankar, Janhavi Ajit; Shahwan, Shazana; Jeyagurunathan, Anitha; Sagayadevan, Vathsala; Shafie, Saleha; Tay, Jenny; Chong, Siow Ann; Subramaniam, Mythily
2016-01-01
Background Public attitudes to mental illness could influence how the public interact with, provide opportunities for, and help people with mental illness. Aims This study aims to explore the underlying factors of the Attitudes to Mental Illness questionnaire among the general population in Singapore and the socio-demographic correlates of each factor. Methods From March 2014 to April 2015, a nation-wide cross-sectional survey on mental health literacy with 3,006 participants was conducted in Singapore. Results Factor analysis revealed a 4-factor structure for the Attitudes to Mental Illness questionnaire among the Singapore general population, namely social distancing, tolerance/support for community care, social restrictiveness, and prejudice and misconception. Older age, male gender, lower education and socio-economic status were associated with more negative attitudes towards the mentally ill. Chinese showed more negative attitudes than Indians and Malays (except for prejudice and misconception). Conclusions There is a need for culture-specific interventions, and the associated factors identified in this study should be considered for future attitude campaigns. PMID:27893796
Process correlation analysis model for process improvement identification.
Choi, Su-jin; Kim, Dae-Kyoo; Park, Sooyong
2014-01-01
Software process improvement aims at improving the development process of software systems. It is initiated by process assessment identifying strengths and weaknesses and based on the findings, improvement plans are developed. In general, a process reference model (e.g., CMMI) is used throughout the process of software process improvement as the base. CMMI defines a set of process areas involved in software development and what to be carried out in process areas in terms of goals and practices. Process areas and their elements (goals and practices) are often correlated due to the iterative nature of software development process. However, in the current practice, correlations of process elements are often overlooked in the development of an improvement plan, which diminishes the efficiency of the plan. This is mainly attributed to significant efforts and the lack of required expertise. In this paper, we present a process correlation analysis model that helps identify correlations of process elements from the results of process assessment. This model is defined based on CMMI and empirical data of improvement practices. We evaluate the model using industrial data.
Correlation analysis of fracture arrangement in space
Marrett, Randall; Gale, Julia F. W.; Gómez, Leonel A.; Laubach, Stephen E.
2018-03-01
We present new techniques that overcome limitations of standard approaches to documenting spatial arrangement. The new techniques directly quantify spatial arrangement by normalizing to expected values for randomly arranged fractures. The techniques differ in terms of computational intensity, robustness of results, ability to detect anti-correlation, and use of fracture size data. Variation of spatial arrangement across a broad range of length scales facilitates distinguishing clustered and periodic arrangements-opposite forms of organization-from random arrangements. Moreover, self-organized arrangements can be distinguished from arrangements due to extrinsic organization. Traditional techniques for analysis of fracture spacing are hamstrung because they account neither for the sequence of fracture spacings nor for possible coordination between fracture size and position, attributes accounted for by our methods. All of the new techniques reveal fractal clustering in a test case of veins, or cement-filled opening-mode fractures, in Pennsylvanian Marble Falls Limestone. The observed arrangement is readily distinguishable from random and periodic arrangements. Comparison of results that account for fracture size with results that ignore fracture size demonstrates that spatial arrangement is dominated by the sequence of fracture spacings, rather than coordination of fracture size with position. Fracture size and position are not completely independent in this example, however, because large fractures are more clustered than small fractures. Both spatial and size organization of veins here probably emerged from fracture interaction during growth. The new approaches described here, along with freely available software to implement the techniques, can be applied with effect to a wide range of structures, or indeed many other phenomena such as drilling response, where spatial heterogeneity is an issue.
Analysis of Baryon Angular Correlations with Pythia
Mccune, Amara
2017-01-01
Our current understanding of baryon production is encompassed in the framework of the Lund String Fragmentation Model, which is then encoded in the Monte Carlo event generator program Pythia. In proton-proton collisions, daughter particles of the same baryon number produce an anti-correlation in $\\Delta\\eta\\Delta\\varphi$ space in ALICE data, while Pythia programs predict a correlation. To understand this unusual effect, where it comes from, and where our models of baryon production go wrong, correlation functions were systematically generated with Pythia. Effects of energy scaling, color reconnection, and popcorn parameters were investigated.
Signal correlations in biomass combustion. An information theoretic analysis
Ruusunen, M.
2013-09-01
Increasing environmental and economic awareness are driving the development of combustion technologies to efficient biomass use and clean burning. To accomplish these goals, quantitative information about combustion variables is needed. However, for small-scale combustion units the existing monitoring methods are often expensive or complex. This study aimed to quantify correlations between flue gas temperatures and combustion variables, namely typical emission components, heat output, and efficiency. For this, data acquired from four small-scale combustion units and a large circulating fluidised bed boiler was studied. The fuel range varied from wood logs, wood chips, and wood pellets to biomass residue. Original signals and a defined set of their mathematical transformations were applied to data analysis. In order to evaluate the strength of the correlations, a multivariate distance measure based on information theory was derived. The analysis further assessed time-varying signal correlations and relative time delays. Ranking of the analysis results was based on the distance measure. The uniformity of the correlations in the different data sets was studied by comparing the 10-quantiles of the measured signal. The method was validated with two benchmark data sets. The flue gas temperatures and the combustion variables measured carried similar information. The strongest correlations were mainly linear with the transformed signal combinations and explicable by the combustion theory. Remarkably, the results showed uniformity of the correlations across the data sets with several signal transformations. This was also indicated by simulations using a linear model with constant structure to monitor carbon dioxide in flue gas. Acceptable performance was observed according to three validation criteria used to quantify modelling error in each data set. In general, the findings demonstrate that the presented signal transformations enable real-time approximation of the studied
General classification and analysis of neutron β-decay experiments
Gudkov, V.; Greene, G.L.; Calarco, J.R.
2006-01-01
A general analysis of the sensitivities of neutron β-decay experiments to manifestations of possible interaction beyond the standard model is carried out. In a consistent fashion, we take into account all known radiative and recoil corrections arising in the standard model. This provides a description of angular correlations in neutron decay in terms of one parameter, which is accurate to the level of ∼10 -5 . Based on this general expression, we present an analysis of the sensitivities to new physics for selected neutron decay experiments. We emphasize that the usual parametrization of experiments in terms of the tree-level coefficients a,A, and B is inadequate when the experimental sensitivities are at the same or higher level relative to the size of the corrections to the tree-level description
A general method dealing with correlations in uncertainty propagation in fault trees
Qin Zhang
1989-01-01
This paper deals with the correlations among the failure probabilities (frequencies) of not only the identical basic events but also other basic events in a fault tree. It presents a general and simple method to include these correlations in uncertainty propagation. Two examples illustrate this method and show that neglecting these correlations results in large underestimation of the top event failure probability (frequency). One is the failure of the primary pump in a chemical reactor cooling system, the other example is an accident to a road transport truck carrying toxic waste. (author)
Complexity analysis based on generalized deviation for financial markets
Li, Chao; Shang, Pengjian
2018-03-01
In this paper, a new modified method is proposed as a measure to investigate the correlation between past price and future volatility for financial time series, known as the complexity analysis based on generalized deviation. In comparison with the former retarded volatility model, the new approach is both simple and computationally efficient. The method based on the generalized deviation function presents us an exhaustive way showing the quantization of the financial market rules. Robustness of this method is verified by numerical experiments with both artificial and financial time series. Results show that the generalized deviation complexity analysis method not only identifies the volatility of financial time series, but provides a comprehensive way distinguishing the different characteristics between stock indices and individual stocks. Exponential functions can be used to successfully fit the volatility curves and quantify the changes of complexity for stock market data. Then we study the influence for negative domain of deviation coefficient and differences during the volatile periods and calm periods. after the data analysis of the experimental model, we found that the generalized deviation model has definite advantages in exploring the relationship between the historical returns and future volatility.
Yuan, Sihan; Eisenstein, Daniel J.; Garrison, Lehman H.
2018-04-01
We present the GeneRalized ANd Differentiable Halo Occupation Distribution (GRAND-HOD) routine that generalizes the standard 5 parameter halo occupation distribution model (HOD) with various halo-scale physics and assembly bias. We describe the methodology of 4 different generalizations: satellite distribution generalization, velocity bias, closest approach distance generalization, and assembly bias. We showcase the signatures of these generalizations in the 2-point correlation function (2PCF) and the squeezed 3-point correlation function (squeezed 3PCF). We identify generalized HOD prescriptions that are nearly degenerate in the projected 2PCF and demonstrate that these degeneracies are broken in the redshift-space anisotropic 2PCF and the squeezed 3PCF. We also discuss the possibility of identifying degeneracies in the anisotropic 2PCF and further demonstrate the extra constraining power of the squeezed 3PCF on galaxy-halo connection models. We find that within our current HOD framework, the anisotropic 2PCF can predict the squeezed 3PCF better than its statistical error. This implies that a discordant squeezed 3PCF measurement could falsify the particular HOD model space. Alternatively, it is possible that further generalizations of the HOD model would open opportunities for the squeezed 3PCF to provide novel parameter measurements. The GRAND-HOD Python package is publicly available at https://github.com/SandyYuan/GRAND-HOD.
Statistical analysis of angular correlation measurements
Oliveira, R.A.A.M. de.
1986-01-01
Obtaining the multipole mixing ratio, δ, of γ transitions in angular correlation measurements is a statistical problem characterized by the small number of angles in which the observation is made and by the limited statistic of counting, α. The inexistence of a sufficient statistics for the estimator of δ, is shown. Three different estimators for δ were constructed and their properties of consistency, bias and efficiency were tested. Tests were also performed in experimental results obtained in γ-γ directional correlation measurements. (Author) [pt
Uncertainty analysis with statistically correlated failure data
Modarres, M.; Dezfuli, H.; Roush, M.L.
1987-01-01
Likelihood of occurrence of the top event of a fault tree or sequences of an event tree is estimated from the failure probability of components that constitute the events of the fault/event tree. Component failure probabilities are subject to statistical uncertainties. In addition, there are cases where the failure data are statistically correlated. At present most fault tree calculations are based on uncorrelated component failure data. This chapter describes a methodology for assessing the probability intervals for the top event failure probability of fault trees or frequency of occurrence of event tree sequences when event failure data are statistically correlated. To estimate mean and variance of the top event, a second-order system moment method is presented through Taylor series expansion, which provides an alternative to the normally used Monte Carlo method. For cases where component failure probabilities are statistically correlated, the Taylor expansion terms are treated properly. Moment matching technique is used to obtain the probability distribution function of the top event through fitting the Johnson Ssub(B) distribution. The computer program, CORRELATE, was developed to perform the calculations necessary for the implementation of the method developed. (author)
No Eigenvalues Outside the Limiting Support of Generally Correlated Gaussian Matrices
Kammoun, Abla
2016-05-04
This paper investigates the behaviour of the spectrum of generally correlated Gaussian random matrices whose columns are zero-mean independent vectors but have different correlations, under the specific regime where the number of their columns and that of their rows grow at infinity with the same pace. Following the approach proposed in [1], we prove that under some mild conditions, there is no eigenvalue outside the limiting support of generally correlated Gaussian matrices. As an outcome of this result, we establish that the smallest singular value of these matrices is almost surely greater than zero. From a practical perspective, this control of the smallest singular value is paramount to applications from statistical signal processing and wireless communication, in which this kind of matrices naturally arise.
No Eigenvalues Outside the Limiting Support of Generally Correlated Gaussian Matrices
Kammoun, Abla; Alouini, Mohamed-Slim
2016-01-01
This paper investigates the behaviour of the spectrum of generally correlated Gaussian random matrices whose columns are zero-mean independent vectors but have different correlations, under the specific regime where the number of their columns and that of their rows grow at infinity with the same pace. Following the approach proposed in [1], we prove that under some mild conditions, there is no eigenvalue outside the limiting support of generally correlated Gaussian matrices. As an outcome of this result, we establish that the smallest singular value of these matrices is almost surely greater than zero. From a practical perspective, this control of the smallest singular value is paramount to applications from statistical signal processing and wireless communication, in which this kind of matrices naturally arise.
Group sparse canonical correlation analysis for genomic data integration.
Lin, Dongdong; Zhang, Jigang; Li, Jingyao; Calhoun, Vince D; Deng, Hong-Wen; Wang, Yu-Ping
2013-08-12
The emergence of high-throughput genomic datasets from different sources and platforms (e.g., gene expression, single nucleotide polymorphisms (SNP), and copy number variation (CNV)) has greatly enhanced our understandings of the interplay of these genomic factors as well as their influences on the complex diseases. It is challenging to explore the relationship between these different types of genomic data sets. In this paper, we focus on a multivariate statistical method, canonical correlation analysis (CCA) method for this problem. Conventional CCA method does not work effectively if the number of data samples is significantly less than that of biomarkers, which is a typical case for genomic data (e.g., SNPs). Sparse CCA (sCCA) methods were introduced to overcome such difficulty, mostly using penalizations with l-1 norm (CCA-l1) or the combination of l-1and l-2 norm (CCA-elastic net). However, they overlook the structural or group effect within genomic data in the analysis, which often exist and are important (e.g., SNPs spanning a gene interact and work together as a group). We propose a new group sparse CCA method (CCA-sparse group) along with an effective numerical algorithm to study the mutual relationship between two different types of genomic data (i.e., SNP and gene expression). We then extend the model to a more general formulation that can include the existing sCCA models. We apply the model to feature/variable selection from two data sets and compare our group sparse CCA method with existing sCCA methods on both simulation and two real datasets (human gliomas data and NCI60 data). We use a graphical representation of the samples with a pair of canonical variates to demonstrate the discriminating characteristic of the selected features. Pathway analysis is further performed for biological interpretation of those features. The CCA-sparse group method incorporates group effects of features into the correlation analysis while performs individual feature
A hybrid correlation analysis with application to imaging genetics
Hu, Wenxing; Fang, Jian; Calhoun, Vince D.; Wang, Yu-Ping
2018-03-01
Investigating the association between brain regions and genes continues to be a challenging topic in imaging genetics. Current brain region of interest (ROI)-gene association studies normally reduce data dimension by averaging the value of voxels in each ROI. This averaging may lead to a loss of information due to the existence of functional sub-regions. Pearson correlation is widely used for association analysis. However, it only detects linear correlation whereas nonlinear correlation may exist among ROIs. In this work, we introduced distance correlation to ROI-gene association analysis, which can detect both linear and nonlinear correlations and overcome the limitation of averaging operations by taking advantage of the information at each voxel. Nevertheless, distance correlation usually has a much lower value than Pearson correlation. To address this problem, we proposed a hybrid correlation analysis approach, by applying canonical correlation analysis (CCA) to the distance covariance matrix instead of directly computing distance correlation. Incorporating CCA into distance correlation approach may be more suitable for complex disease study because it can detect highly associated pairs of ROI and gene groups, and may improve the distance correlation level and statistical power. In addition, we developed a novel nonlinear CCA, called distance kernel CCA, which seeks the optimal combination of features with the most significant dependence. This approach was applied to imaging genetic data from the Philadelphia Neurodevelopmental Cohort (PNC). Experiments showed that our hybrid approach produced more consistent results than conventional CCA across resampling and both the correlation and statistical significance were increased compared to distance correlation analysis. Further gene enrichment analysis and region of interest (ROI) analysis confirmed the associations of the identified genes with brain ROIs. Therefore, our approach provides a powerful tool for finding
Sandev, Trifce; Metzler, Ralf; Tomovski, Živorad
2014-01-01
We study generalized fractional Langevin equations in the presence of a harmonic potential. General expressions for the mean velocity and particle displacement, the mean squared displacement, position and velocity correlation functions, as well as normalized displacement correlation function are derived. We report exact results for the cases of internal and external friction, that is, when the driving noise is either internal and thus the fluctuation-dissipation relation is fulfilled or when the noise is external. The asymptotic behavior of the generalized stochastic oscillator is investigated, and the case of high viscous damping (overdamped limit) is considered. Additional behaviors of the normalized displacement correlation functions different from those for the regular damped harmonic oscillator are observed. In addition, the cases of a constant external force and the force free case are obtained. The validity of the generalized Einstein relation for this process is discussed. The considered fractional generalized Langevin equation may be used to model anomalous diffusive processes including single file-type diffusion
Breakdown of long-range temporal correlations in brain oscillations during general anesthesia.
Krzemiński, Dominik; Kamiński, Maciej; Marchewka, Artur; Bola, Michał
2017-10-01
Consciousness has been hypothesized to emerge from complex neuronal dynamics, which prevails when brain operates in a critical state. Evidence supporting this hypothesis comes mainly from studies investigating neuronal activity on a short time-scale of seconds. However, a key aspect of criticality is presence of scale-free temporal dependencies occurring across a wide range of time-scales. Indeed, robust long-range temporal correlations (LRTCs) are found in neuronal oscillations during conscious states, but it is not known how LRTCs are affected by loss of consciousness. To further test a relation between critical dynamics and consciousness, we investigated LRTCs in electrocorticography signals recorded from four macaque monkeys during resting wakefulness and general anesthesia induced by various anesthetics (ketamine, medetomidine, or propofol). Detrended Fluctuation Analysis was used to estimate LRTCs in amplitude fluctuations (envelopes) of band-pass filtered signals. We demonstrate two main findings. First, during conscious states all lateral cortical regions are characterized by significant LRTCs of alpha-band activity (7-14 Hz). LRTCs are stronger in the eyes-open than eyes-closed state, but in both states they form a spatial gradient, with anterior brain regions exhibiting stronger LRTCs than posterior regions. Second, we observed a substantial decrease of LRTCs during loss of consciousness, the magnitude of which was associated with the baseline (i.e. pre-anesthesia) state of the brain. Specifically, brain regions characterized by strongest LRTCs during a wakeful baseline exhibited greatest decreases during anesthesia (i.e. "the rich got poorer"), which consequently disturbed the posterior-anterior gradient. Therefore, our results suggest that general anesthesia affects mainly brain areas characterized by strongest LRTCs during wakefulness, which might account for lack of capacities for extensive temporal integration during loss of consciousness. Copyright
Soave, David; Sun, Lei
2017-09-01
We generalize Levene's test for variance (scale) heterogeneity between k groups for more complex data, when there are sample correlation and group membership uncertainty. Following a two-stage regression framework, we show that least absolute deviation regression must be used in the stage 1 analysis to ensure a correct asymptotic χk-12/(k-1) distribution of the generalized scale (gS) test statistic. We then show that the proposed gS test is independent of the generalized location test, under the joint null hypothesis of no mean and no variance heterogeneity. Consequently, we generalize the recently proposed joint location-scale (gJLS) test, valuable in settings where there is an interaction effect but one interacting variable is not available. We evaluate the proposed method via an extensive simulation study and two genetic association application studies. © 2017 The Authors Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.
Metabolic correlates of general cognitive function in nondemented elderly subjects: an FDG PET study
Cho, Sang Soo; Kwak, Young Bin; Lee, Eun Ju; Ryu, Chang Hyung; Chey, Jean Yung; Kim, Sang Eun
2004-01-01
While many studies examined the neural correlates of individual cognitive functions, few made efforts to identify the neural networks associated with general cognitive function. General cognitive function decline in the elderly population is not infrequent. This study examined the brain areas associated with general cognitive function in the elderly subjects. Community-dwelling 116 elderly subjects without dementing illnesses (age, 71±5 y; 13 males and 103 females) participated. General cognitive ability was assessed with the Dementia Rating Scale (K-DRS), which is composed of five subtests of attention, initiation and perseveration, construction, conceptualization, and memory. The EVLT (Elderly Verbal Learning Test), a nine-word list learning test, was used for general memory assessment. Brain FDG PET scans were acquired in all subjects. Brain regions where metabolic levels are correlated with the total scores of K-DRS and EVLT were examined using SPM99. There was a significant positive correlation (P < 0.01 uncorrected, k=100) between the total score of K-DRS and glucose metabolism in the bilateral posterior cingulate gyri, bilateral inferior frontal gyri, left caudate, left inferior parietal lobule, right precuneus, bilateral unci, right parahippocampal gyrus, and right anterior cingulate gyrus. A significant positive correlation between the total score of EVLT and glucose metabolism was shown in the right precuneus, right posterior cingulate gyrus, left insula, bilateral inferior parietal lobules, left anterior cingulate gyrus, left caudate, right inferior frontal gyrus (P < 0.01 uncorrected, k=100). Our data showed the brain regions that are associated with general cognitive function in the elderly. Those regions may serve as the neural substrated of cognitive dysfunction associated with neurodegenerative and cerebrovascular diseases in elderly subjects
Multifractal Detrended Cross-Correlation Analysis of agricultural futures markets
He Lingyun; Chen Shupeng
2011-01-01
Highlights: → We investigated cross-correlations between China's and US agricultural futures markets. → Power-law cross-correlations are found between the geographically far but correlated markets. → Multifractal features are significant in all the markets. → Cross-correlation exponent is less than averaged GHE when q 0. - Abstract: We investigated geographically far but temporally correlated China's and US agricultural futures markets. We found that there exists a power-law cross-correlation between them, and that multifractal features are significant in all the markets. It is very interesting that the geographically far markets show strong cross-correlations and share much of their multifractal structure. Furthermore, we found that for all the agricultural futures markets in our studies, the cross-correlation exponent is less than the averaged generalized Hurst exponents (GHE) when q 0.
Scalable and Flexible Multiview MAX-VAR Canonical Correlation Analysis
Fu, Xiao; Huang, Kejun; Hong, Mingyi; Sidiropoulos, Nicholas D.; So, Anthony Man-Cho
2017-08-01
Generalized canonical correlation analysis (GCCA) aims at finding latent low-dimensional common structure from multiple views (feature vectors in different domains) of the same entities. Unlike principal component analysis (PCA) that handles a single view, (G)CCA is able to integrate information from different feature spaces. Here we focus on MAX-VAR GCCA, a popular formulation which has recently gained renewed interest in multilingual processing and speech modeling. The classic MAX-VAR GCCA problem can be solved optimally via eigen-decomposition of a matrix that compounds the (whitened) correlation matrices of the views; but this solution has serious scalability issues, and is not directly amenable to incorporating pertinent structural constraints such as non-negativity and sparsity on the canonical components. We posit regularized MAX-VAR GCCA as a non-convex optimization problem and propose an alternating optimization (AO)-based algorithm to handle it. Our algorithm alternates between {\\em inexact} solutions of a regularized least squares subproblem and a manifold-constrained non-convex subproblem, thereby achieving substantial memory and computational savings. An important benefit of our design is that it can easily handle structure-promoting regularization. We show that the algorithm globally converges to a critical point at a sublinear rate, and approaches a global optimal solution at a linear rate when no regularization is considered. Judiciously designed simulations and large-scale word embedding tasks are employed to showcase the effectiveness of the proposed algorithm.
General correlation for prediction of critical heat flux ratio in water cooled channels
Pernica, R.; Cizek, J.
1995-09-01
The paper present the general empirical Critical Heat Flux Ration (CHFR) correlation which is valid for vertical water upflow through tubes, internally heated concentric annuli and rod bundles geometries with both wide and very tight square and triangular rods lattices. The proposed general PG correlation directly predicts the CHFR, it comprises axial and radial non-uniform heating, and is valid in a wider range of thermal hydraulic conditions than previously published critical heat flux correlations. The PG correlation has been developed using the critical heat flux Czech data bank which includes more than 9500 experimental data on tubes, 7600 data on rod bundles and 713 data on internally heated concentric annuli. Accuracy of the CHFR prediction, statistically assessed by the constant dryout conditions approach, is characterized by the mean value nearing 1.00 and the standard deviation less than 0.06. Moverover, a subchannel form of the PG correlations is statistically verified on Westinghouse and Combustion Engineering rod bundle data bases, i.e. more than 7000 experimental CHF points of Columbia University data bank were used.
A flexible time recording and time correlation analysis system
Shenhav, N.J.; Leiferman, G.; Segal, Y.; Notea, A.
1983-01-01
A system was developed to digitize and record the time intervals between detection event pulses, feed to its input channels from a detection device. The accumulated data is transferred continuously in real time to a disc through a PDP 11/34 minicomputer. Even though the system was designed for a specific scope, i.e., the comparative study of passive neutron nondestructive assay methods, it can be characterized by its features as a general purpose time series recorder. The time correlation analysis is performed by software after completion of the data accumulation. The digitizing clock period is selectable and any value, larger than a minimum of 100 ns, may be selected. Bursts of up to 128 events with a frequency up to 10 MHz may be recorded. With the present recorder-minicomputer combination, the maximal average recording frequency is 40 kHz. (orig.)
Thematic mapper studies band correlation analysis
Ungar, S. G.; Kiang, R.
1976-01-01
Spectral data representative of thematic mapper candidate bands 1 and 3 to 7 were obtained by selecting appropriate combinations of bands from the JSC 24 channel multispectral scanner. Of all the bands assigned, only candidate bands 4 (.74 mu to .80 mu) and 5 (.80 mu to .91 mu) showed consistently high intercorrelation from region to region and time to time. This extremely high correlation persisted when looking at the composite data set in a multitemporal, multilocation domain. The GISS investigations lend positive confirmation to the hypothesis, that TM bands 4 and 5 are redundant.
Stochastic wave-function unravelling of the generalized Lindblad equation using correlated states
Moodley, Mervlyn; Nsio Nzundu, T; Paul, S
2012-01-01
We perform a stochastic wave-function unravelling of the generalized Lindblad master equation using correlated states, a combination of the system state vectors and the environment population. The time-convolutionless projection operator method using correlated projection superoperators is applied to a two-state system, a qubit, that is coupled to an environment consisting of two energy bands which are both populated. These results are compared to the data obtained from Monte Carlo wave-function simulations based on the unravelling of the master equation. We also show a typical quantum trajectory and the average time evolution of the state vector on the Bloch sphere. (paper)
Handwriting: Feature Correlation Analysis for Biometric Hashes
Vielhauer, Claus; Steinmetz, Ralf
2004-12-01
In the application domain of electronic commerce, biometric authentication can provide one possible solution for the key management problem. Besides server-based approaches, methods of deriving digital keys directly from biometric measures appear to be advantageous. In this paper, we analyze one of our recently published specific algorithms of this category based on behavioral biometrics of handwriting, the biometric hash. Our interest is to investigate to which degree each of the underlying feature parameters contributes to the overall intrapersonal stability and interpersonal value space. We will briefly discuss related work in feature evaluation and introduce a new methodology based on three components: the intrapersonal scatter (deviation), the interpersonal entropy, and the correlation between both measures. Evaluation of the technique is presented based on two data sets of different size. The method presented will allow determination of effects of parameterization of the biometric system, estimation of value space boundaries, and comparison with other feature selection approaches.
Handwriting: Feature Correlation Analysis for Biometric Hashes
Ralf Steinmetz
2004-04-01
Full Text Available In the application domain of electronic commerce, biometric authentication can provide one possible solution for the key management problem. Besides server-based approaches, methods of deriving digital keys directly from biometric measures appear to be advantageous. In this paper, we analyze one of our recently published specific algorithms of this category based on behavioral biometrics of handwriting, the biometric hash. Our interest is to investigate to which degree each of the underlying feature parameters contributes to the overall intrapersonal stability and interpersonal value space. We will briefly discuss related work in feature evaluation and introduce a new methodology based on three components: the intrapersonal scatter (deviation, the interpersonal entropy, and the correlation between both measures. Evaluation of the technique is presented based on two data sets of different size. The method presented will allow determination of effects of parameterization of the biometric system, estimation of value space boundaries, and comparison with other feature selection approaches.
Sukhanov, A.D.
2004-01-01
Generalized correlations of the Schroedinger indefinitenesses are shown to have the meaning of the fundamental restrictions as to characteristics of space of states in any probability-like theory. Quantum mechanics, as well as, theory of the brownian movement at arbitrary space of time fall in the category of the mentioned theories. One compared correlations of coordinates-pulse indefinitenesses within the mentioned theory with the similar correlation of indefinitenesses for microparticle under the Gaussian wave packet state. One determined that in case of profound distinction in mathematical tools of two theories one observes their conceptual resemblance. It manifests itself under the alternative conditions - short times in one theory correspond to long ones in another theory and vice versa, while in any of the mentioned theories uncontrollable effect of either quantum or thermal type is of crucial importance [ru
Insight into Resolution Enhancement in Generalized Two-Dimensional Correlation Spectroscopy
Ma, Lu; Sikirzhytski, Vitali; Hong, Zhenmin; Lednev, Igor K.; Asher, Sanford A.
2013-01-01
Generalized two-dimensional correlation spectroscopy (2D COS) can be used to enhance spectral resolution in order to help differentiate highly overlapped spectral bands. Despite the numerous extensive 2D COS investigations, the origin of the 2D spectral resolution enhancement mechanism(s) are not completely understood. In the work here we studied the 2D COS of simulated spectra in order to develop new insights into the dependence of the 2D COS spectral features on the overlapping band separat...
Analysis of correlations between sites in models of protein sequences
Giraud, B.G.; Lapedes, A.; Liu, L.C.
1998-01-01
A criterion based on conditional probabilities, related to the concept of algorithmic distance, is used to detect correlated mutations at noncontiguous sites on sequences. We apply this criterion to the problem of analyzing correlations between sites in protein sequences; however, the analysis applies generally to networks of interacting sites with discrete states at each site. Elementary models, where explicit results can be derived easily, are introduced. The number of states per site considered ranges from 2, illustrating the relation to familiar classical spin systems, to 20 states, suitable for representing amino acids. Numerical simulations show that the criterion remains valid even when the genetic history of the data samples (e.g., protein sequences), as represented by a phylogenetic tree, introduces nonindependence between samples. Statistical fluctuations due to finite sampling are also investigated and do not invalidate the criterion. A subsidiary result is found: The more homogeneous a population, the more easily its average properties can drift from the properties of its ancestor. copyright 1998 The American Physical Society
Development of Generalized Correlation Equation for the Local Wall Shear Stress
Jeon, Yu Mi; Park, Ju Hwan
2010-06-01
The pressure drop characteristics for a fuel channel are essential for the design and reliable operation of a nuclear reactor. Over several decades, analytical methods have been developed to predict the friction factor in the fuel bundle flows. In order to enhance the accuracy of prediction for the pressure drop in a rod bundle, the influences of a channel wall and the local shear stress distribution should be considered. Therefore, the correlation equation for a local wall shear stress distribution should be developed in order to secure an analytical solution for the friction factor of a rod bundle. For a side subchannel, which has the influence of the channel wall, the local wall shear stress distribution is dependent on the ratio of wall to diameter (W/D) as well as the ratio of pitch to diameter (P/D). In the case that W/D has the same value with P/D, the local shear stress distribution can be simply correlated with the function of angular position for each value of P/D. While in the case where W/D has a different value than P/D, the correlation equation should be developed for each case of P/D and W/D. Therefore, in the present study, the generalized correlation equation of the local wall shear stress distribution was developed for a side subchannel in the case where W/D has a different value than P/D. Consequently, the generalized correlation equation of a local wall shear stress distribution can be represented by the equivalent pitch to diameter ratio, P'/D for the case that P/D and W/D had a different value
Westgate, Philip M
2013-07-20
Generalized estimating equations (GEEs) are routinely used for the marginal analysis of correlated data. The efficiency of GEE depends on how closely the working covariance structure resembles the true structure, and therefore accurate modeling of the working correlation of the data is important. A popular approach is the use of an unstructured working correlation matrix, as it is not as restrictive as simpler structures such as exchangeable and AR-1 and thus can theoretically improve efficiency. However, because of the potential for having to estimate a large number of correlation parameters, variances of regression parameter estimates can be larger than theoretically expected when utilizing the unstructured working correlation matrix. Therefore, standard error estimates can be negatively biased. To account for this additional finite-sample variability, we derive a bias correction that can be applied to typical estimators of the covariance matrix of parameter estimates. Via simulation and in application to a longitudinal study, we show that our proposed correction improves standard error estimation and statistical inference. Copyright © 2012 John Wiley & Sons, Ltd.
Two-dimensional multifractal cross-correlation analysis
Xi, Caiping; Zhang, Shuning; Xiong, Gang; Zhao, Huichang; Yang, Yonghong
2017-01-01
Highlights: • We study the mathematical models of 2D-MFXPF, 2D-MFXDFA and 2D-MFXDMA. • Present the definition of the two-dimensional N 2 -partitioned multiplicative cascading process. • Do the comparative analysis of 2D-MC by 2D-MFXPF, 2D-MFXDFA and 2D-MFXDMA. • Provide a reference on the choice and parameter settings of these methods in practice. - Abstract: There are a number of situations in which several signals are simultaneously recorded in complex systems, which exhibit long-term power-law cross-correlations. This paper presents two-dimensional multifractal cross-correlation analysis based on the partition function (2D-MFXPF), two-dimensional multifractal cross-correlation analysis based on the detrended fluctuation analysis (2D-MFXDFA) and two-dimensional multifractal cross-correlation analysis based on the detrended moving average analysis (2D-MFXDMA). We apply these methods to pairs of two-dimensional multiplicative cascades (2D-MC) to do a comparative study. Then, we apply the two-dimensional multifractal cross-correlation analysis based on the detrended fluctuation analysis (2D-MFXDFA) to real images and unveil intriguing multifractality in the cross correlations of the material structures. At last, we give the main conclusions and provide a valuable reference on how to choose the multifractal algorithms in the potential applications in the field of SAR image classification and detection.
Psychobiological Correlates of Vaginismus: An Exploratory Analysis.
Maseroli, Elisa; Scavello, Irene; Cipriani, Sarah; Palma, Manuela; Fambrini, Massimiliano; Corona, Giovanni; Mannucci, Edoardo; Maggi, Mario; Vignozzi, Linda
2017-11-01
Evidence concerning the determinants of vaginismus (V), in particular medical conditions, is inconclusive. To investigate, in a cohort of subjects consulting for female sexual dysfunction, whether there is a difference in medical and psychosocial parameters between women with V and women with other sexual complaints. A series of 255 women attending our clinic for female sexual dysfunction was consecutively recruited. V was diagnosed according to Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision criteria. Lifelong and acquired V cases were included. Patients underwent a structured interview and physical, gynecologic, laboratory, and clitoral ultrasound examinations; they completed the Female Sexual Function Index (FSFI), the Middlesex Hospital Questionnaire, the Female Sexual Distress Scale-Revised (FSDS), and the Body Uneasiness Test. V was diagnosed in 20 patients (7.8%). Women with V were significantly younger than the rest of the sample (P Vaginismus: An Exploratory Analysis. J Sex Med 2017;14:1392-1402. Copyright © 2017 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.
General solution of an exact correlation function factorization in conformal field theory
Simmons, Jacob J H; Kleban, Peter
2009-01-01
The correlation function factorization with K a boundary operator product expansion coefficient, is known to hold for certain scaling operators at the two-dimensional percolation point and in a few other cases. Here the correlation functions are evaluated in the upper half-plane (or any conformally equivalent region) with x 1 and x 2 arbitrary points on the real axis, and z an arbitrary point in the interior. This type of result is of interest because it is both exact and universal, relates higher-order correlation functions to lower-order ones and has a simple interpretation in terms of cluster or loop probabilities in several statistical models. This motivated us to use the techniques of conformal field theory to determine the general conditions for its validity. Here, we discover that either (see display) factorizes in this way for any central charge c, generalizing previous results. In particular, the factorization holds for either FK (Fortuin–Kasteleyn) or spin clusters in the Q-state Potts models; it also applies to either the dense or dilute phases of the O(n) loop models. Further, only one other non-trivial set of highest-weight operators (in an irreducible Verma module) factorizes in this way. In this case the operators have negative dimension (for c<1) and do not seem to have a physical realization
Hansen, J S; Daivis, Peter J; Dyre, Jeppe C; Todd, B D; Bruus, Henrik
2013-01-21
The extended Navier-Stokes theory accounts for the coupling between the translational and rotational molecular degrees of freedom. In this paper, we generalize this theory to non-zero frequencies and wavevectors, which enables a new study of spatio-temporal correlation phenomena present in molecular fluids. To discuss these phenomena in detail, molecular dynamics simulations of molecular chlorine are performed for three different state points. In general, the theory captures the behavior for small wavevector and frequencies as expected. For example, in the hydrodynamic regime and for molecular fluids with small moment of inertia like chlorine, the theory predicts that the longitudinal and transverse intrinsic angular velocity correlation functions are almost identical, which is also seen in the molecular dynamics simulations. However, the theory fails at large wavevector and frequencies. To account for the correlations at these scales, we derive a phenomenological expression for the frequency dependent rotational viscosity and wavevector and frequency dependent longitudinal spin viscosity. From this we observe a significant coupling enhancement between the molecular angular velocity and translational velocity for large frequencies in the gas phase; this is not observed for the supercritical fluid and liquid state points.
Qian, Xi-Yuan; Liu, Ya-Min; Jiang, Zhi-Qiang; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H. Eugene
2015-06-01
When common factors strongly influence two power-law cross-correlated time series recorded in complex natural or social systems, using detrended cross-correlation analysis (DCCA) without considering these common factors will bias the results. We use detrended partial cross-correlation analysis (DPXA) to uncover the intrinsic power-law cross correlations between two simultaneously recorded time series in the presence of nonstationarity after removing the effects of other time series acting as common forces. The DPXA method is a generalization of the detrended cross-correlation analysis that takes into account partial correlation analysis. We demonstrate the method by using bivariate fractional Brownian motions contaminated with a fractional Brownian motion. We find that the DPXA is able to recover the analytical cross Hurst indices, and thus the multiscale DPXA coefficients are a viable alternative to the conventional cross-correlation coefficient. We demonstrate the advantage of the DPXA coefficients over the DCCA coefficients by analyzing contaminated bivariate fractional Brownian motions. We calculate the DPXA coefficients and use them to extract the intrinsic cross correlation between crude oil and gold futures by taking into consideration the impact of the U.S. dollar index. We develop the multifractal DPXA (MF-DPXA) method in order to generalize the DPXA method and investigate multifractal time series. We analyze multifractal binomial measures masked with strong white noises and find that the MF-DPXA method quantifies the hidden multifractal nature while the multifractal DCCA method fails.
Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology
Rupert Faltermeier
2015-01-01
Full Text Available Recently we proposed a mathematical tool set, called selected correlation analysis, that reliably detects positive and negative correlations between arterial blood pressure (ABP and intracranial pressure (ICP. Such correlations are associated with severe impairment of the cerebral autoregulation and intracranial compliance, as predicted by a mathematical model. The time resolved selected correlation analysis is based on a windowing technique combined with Fourier-based coherence calculations and therefore depends on several parameters. For real time application of this method at an ICU it is inevitable to adjust this mathematical tool for high sensitivity and distinct reliability. In this study, we will introduce a method to optimize the parameters of the selected correlation analysis by correlating an index, called selected correlation positive (SCP, with the outcome of the patients represented by the Glasgow Outcome Scale (GOS. For that purpose, the data of twenty-five patients were used to calculate the SCP value for each patient and multitude of feasible parameter sets of the selected correlation analysis. It could be shown that an optimized set of parameters is able to improve the sensitivity of the method by a factor greater than four in comparison to our first analyses.
Ten Years Trend Analysis of Malaria Prevalence and its Correlation ...
The data were analyzed using SPSS software package 16.0. Pearson's correlation analysis was conducted to see the correlation between plasmodium species and climatic variables. Within the last decade (2004–2013) a total of 30,070 blood films were examined for malaria in Sire health center and of this 6036 (20.07%) ...
Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology.
Faltermeier, Rupert; Proescholdt, Martin A; Bele, Sylvia; Brawanski, Alexander
2015-01-01
Recently we proposed a mathematical tool set, called selected correlation analysis, that reliably detects positive and negative correlations between arterial blood pressure (ABP) and intracranial pressure (ICP). Such correlations are associated with severe impairment of the cerebral autoregulation and intracranial compliance, as predicted by a mathematical model. The time resolved selected correlation analysis is based on a windowing technique combined with Fourier-based coherence calculations and therefore depends on several parameters. For real time application of this method at an ICU it is inevitable to adjust this mathematical tool for high sensitivity and distinct reliability. In this study, we will introduce a method to optimize the parameters of the selected correlation analysis by correlating an index, called selected correlation positive (SCP), with the outcome of the patients represented by the Glasgow Outcome Scale (GOS). For that purpose, the data of twenty-five patients were used to calculate the SCP value for each patient and multitude of feasible parameter sets of the selected correlation analysis. It could be shown that an optimized set of parameters is able to improve the sensitivity of the method by a factor greater than four in comparison to our first analyses.
Development of generalized correlation equation for the local wall shear stress
Jeon, Yu Mi; Bae, Jun Ho; Park, Joo Hwan
2010-01-01
The pressure drop characteristics for a fuel channel are essential for the design and reliable operation of a nuclear reactor. Over several decades, analytical methods have been developed to predict the friction factor in the fuel bundle flows. In order to enhance the accuracy of prediction for the pressure drop in a rod bundle, the influences of a channel wall and the local shear stress distribution should be considered. Hence, the correlation equation for a local shear stress distribution should be developed in order to secure an analytical solution for the friction factor of a rod bundle. For a side subchannel, which has the influence of the channel wall, the local shear stress distribution is dependent on the ratio of wall to diameter (W/D) as well as the ratio of pitch to diameter (P/D). In the case that W/D has the same value with P/D, the local shear stress distribution can be simply correlated with the function of angular position for each value of P/D. While, in the case that W/D has the different value with P/D, the correlation equation should be developed for each case of P/D and W/D. Hence, in the present study, the generalized correlation equation of a local shear stress distribution is developed for a side subchannel in the case that W/D has the different value with P/D
Chi Zhang
2015-05-01
Full Text Available To model correlated bivariate count data with extra zero observations, this paper proposes two new bivariate zero-inflated generalized Poisson (ZIGP distributions by incorporating a multiplicative factor (or dependency parameter λ, named as Type I and Type II bivariate ZIGP distributions, respectively. The proposed distributions possess a flexible correlation structure and can be used to fit either positively or negatively correlated and either over- or under-dispersed count data, comparing to the existing models that can only fit positively correlated count data with over-dispersion. The two marginal distributions of Type I bivariate ZIGP share a common parameter of zero inflation while the two marginal distributions of Type II bivariate ZIGP have their own parameters of zero inflation, resulting in a much wider range of applications. The important distributional properties are explored and some useful statistical inference methods including maximum likelihood estimations of parameters, standard errors estimation, bootstrap confidence intervals and related testing hypotheses are developed for the two distributions. A real data are thoroughly analyzed by using the proposed distributions and statistical methods. Several simulation studies are conducted to evaluate the performance of the proposed methods.
GIS and correlation analysis of geo-environmental variables ...
Key words: Correlation, GIS, malaria geography, malaria incidence ... problems, as it has created the possibility for geocoding, extracting and spatial analysis of health ...... Bulletin of the World Health Organization, 78(12), 1438–1444. Carter ...
Staraselski, Y; Brahme, A; Inal, K; Mishra, R K
2015-01-01
This paper presents the first application of three-dimensional (3D) cross-correlation microstructure reconstruction implemented for a representative volume element (RVE) to facilitate the microstructure engineering of materials. This has been accomplished by developing a new methodology for reconstructing 3D microstructure using experimental two-dimensional electron backscatter diffraction data. The proposed methodology is based on the analytical representation of the generalized form of the two-point correlation function—the distance-disorientation function (DDF). Microstructure reconstruction is accomplished by extending the simulated annealing techniques to perform three term reconstruction with a minimization of the DDF. The new 3D microstructure reconstruction algorithm is employed to determine the 3D RVE containing all of the relevant microstructure information for accurately computing the mechanical response of solids, especially when local microstructural variations influence the global response of the material as in the case of fracture initiation. (paper)
Śmiga, Szymon; Fabiano, Eduardo; Laricchia, Savio; Constantin, Lucian A; Della Sala, Fabio
2015-04-21
We analyze the methodology and the performance of subsystem density functional theory (DFT) with meta-generalized gradient approximation (meta-GGA) exchange-correlation functionals for non-bonded molecular systems. Meta-GGA functionals depend on the Kohn-Sham kinetic energy density (KED), which is not known as an explicit functional of the density. Therefore, they cannot be directly applied in subsystem DFT calculations. We propose a Laplacian-level approximation to the KED which overcomes this limitation and provides a simple and accurate way to apply meta-GGA exchange-correlation functionals in subsystem DFT calculations. The so obtained density and energy errors, with respect to the corresponding supermolecular calculations, are comparable with conventional approaches, depending almost exclusively on the approximations in the non-additive kinetic embedding term. An embedding energy error decomposition explains the accuracy of our method.
A general analysis of Wtb anomalous couplings
Cao, Qing-Hong; Yan, Bin; Yu, Jiang-Hao; Zhang, Chen
2017-06-01
We investigate new physics effects on the Wtb effective couplings in a model-independent framework. The new physics effects can be parametrized by four independent couplings, , , and . We further introduce a set of parameters x 0, x m , x p and x 5 which exhibit a linear relation to the single top production cross sections. Using recent data for the t-channel single top production cross section σ t , tW associated production cross section σ tW, s-channel single top production cross section σ s , and W-helicity fractions F 0, F L and F R collected at the 8 TeV LHC and Tevatron, we perform a global fit to impose constraints on the top quark effective couplings. Our global fitting results show that the top quark effective couplings are strongly correlated. We show that (i) improving the measurements of σ t and σ tW is important in constraining the correlation of (,) and (,); (ii) and are anti-correlated, and are sensitive to all the four experiments; (iii) and are also anti-correlated, and are sensitive to the F 0 and F L measurements; (iv) the correlation between and is sensitive to the precision of the σ t , σ tW and F 0 measurements. The effective Wtb couplings are studied in three kinds of new physics models: the G(221) = SU(2)1 ⊗ SU(2)2 ⊗ U(1) X models, the vector-like quark models and the Littlest Higgs model with and without T-parity. We show that the Wtb couplings in the left-right model and the un-unified model are sensitive to the ratio of gauge couplings when the new heavy gauge boson’s mass (M W‧) is less than several hundred GeV, but the constraint is loose if M W‧ > 1 TeV. Furthermore, the Wtb couplings in vector-like quark models and the Littlest Higgs models are sensitive to the mixing angles of new heavy particles and SM particles. Supported by National Science Foundation of China (11275009, 11675002, 11635001), National Science Foundation (PHY-1315983, PHY-1316033) and DOE (DE- SC0011095)
Pal, Mayukha; Madhusudana Rao, P.; Manimaran, P.
2014-12-01
We apply the recently developed multifractal detrended cross-correlation analysis method to investigate the cross-correlation behavior and fractal nature between two non-stationary time series. We analyze the daily return price of gold, West Texas Intermediate and Brent crude oil, foreign exchange rate data, over a period of 18 years. The cross correlation has been measured from the Hurst scaling exponents and the singularity spectrum quantitatively. From the results, the existence of multifractal cross-correlation between all of these time series is found. We also found that the cross correlation between gold and oil prices possess uncorrelated behavior and the remaining bivariate time series possess persistent behavior. It was observed for five bivariate series that the cross-correlation exponents are less than the calculated average generalized Hurst exponents (GHE) for q0 and for one bivariate series the cross-correlation exponent is greater than GHE for all q values.
Harmonic Analysis Associated with the Generalized q-Bessel Operator
Ahmed Abouelaz
2016-01-01
Full Text Available In this article, we give a new harmonic analysis associated with the generalized q-Bessel operator. We introduce the generalized $q$-Bessel transform, the generalized q-Bessel translation and the generalized $q$-Bessel convolution product.
Multiscale Detrended Cross-Correlation Analysis of STOCK Markets
Yin, Yi; Shang, Pengjian
2014-06-01
In this paper, we employ the detrended cross-correlation analysis (DCCA) to investigate the cross-correlations between different stock markets. We report the results of cross-correlated behaviors in US, Chinese and European stock markets in period 1997-2012 by using DCCA method. The DCCA shows the cross-correlated behaviors of intra-regional and inter-regional stock markets in the short and long term which display the similarities and differences of cross-correlated behaviors simply and roughly and the persistence of cross-correlated behaviors of fluctuations. Then, because of the limitation and inapplicability of DCCA method, we propose multiscale detrended cross-correlation analysis (MSDCCA) method to avoid "a priori" selecting the ranges of scales over which two coefficients of the classical DCCA method are identified, and employ MSDCCA to reanalyze these cross-correlations to exhibit some important details such as the existence and position of minimum, maximum and bimodal distribution which are lost if the scale structure is described by two coefficients only and essential differences and similarities in the scale structures of cross-correlation of intra-regional and inter-regional markets. More statistical characteristics of cross-correlation obtained by MSDCCA method help us to understand how two different stock markets influence each other and to analyze the influence from thus two inter-regional markets on the cross-correlation in detail, thus we get a richer and more detailed knowledge of the complex evolutions of dynamics of the cross-correlations between stock markets. The application of MSDCCA is important to promote our understanding of the internal mechanisms and structures of financial markets and helps to forecast the stock indices based on our current results demonstrated the cross-correlations between stock indices. We also discuss the MSDCCA methods of secant rolling window with different sizes and, lastly, provide some relevant implications and
Development of Test-Analysis Models (TAM) for correlation of dynamic test and analysis results
Angelucci, Filippo; Javeed, Mehzad; Mcgowan, Paul
1992-01-01
The primary objective of structural analysis of aerospace applications is to obtain a verified finite element model (FEM). The verified FEM can be used for loads analysis, evaluate structural modifications, or design control systems. Verification of the FEM is generally obtained as the result of correlating test and FEM models. A test analysis model (TAM) is very useful in the correlation process. A TAM is essentially a FEM reduced to the size of the test model, which attempts to preserve the dynamic characteristics of the original FEM in the analysis range of interest. Numerous methods for generating TAMs have been developed in the literature. The major emphasis of this paper is a description of the procedures necessary for creation of the TAM and the correlation of the reduced models with the FEM or the test results. Herein, three methods are discussed, namely Guyan, Improved Reduced System (IRS), and Hybrid. Also included are the procedures for performing these analyses using MSC/NASTRAN. Finally, application of the TAM process is demonstrated with an experimental test configuration of a ten bay cantilevered truss structure.
The effects of observational correlated noises on multifractal detrended fluctuation analysis
Gulich, Damián; Zunino, Luciano
2012-08-01
We have numerically investigated the effects that observational correlated noises have on the generalized Hurst exponents, h(q), estimated by using the multifractal generalization of detrended fluctuation analysis (MF-DFA). More precisely, artificially generated stochastic binomial multifractals with increased amount of colored noises were analyzed via MF-DFA. It has been recently shown that for moderate additions of white noise, the generalized Hurst exponents are significantly underestimated for qeffects of additive noise, short- term memory and periodic trends, Physica A 390 (2011) 2480-2490]. In this paper, we have found that h(q) with q≥2 are also affected when correlated noises are considered. This is due to the fact that the spurious correlations influence the scaling behaviors associated to large fluctuations. The results obtained are significant for practical situations, where noises with different correlations are inherently present.
Spatio-chromatic adaptation via higher-order canonical correlation analysis of natural images.
Gutmann, Michael U; Laparra, Valero; Hyvärinen, Aapo; Malo, Jesús
2014-01-01
Independent component and canonical correlation analysis are two general-purpose statistical methods with wide applicability. In neuroscience, independent component analysis of chromatic natural images explains the spatio-chromatic structure of primary cortical receptive fields in terms of properties of the visual environment. Canonical correlation analysis explains similarly chromatic adaptation to different illuminations. But, as we show in this paper, neither of the two methods generalizes well to explain both spatio-chromatic processing and adaptation at the same time. We propose a statistical method which combines the desirable properties of independent component and canonical correlation analysis: It finds independent components in each data set which, across the two data sets, are related to each other via linear or higher-order correlations. The new method is as widely applicable as canonical correlation analysis, and also to more than two data sets. We call it higher-order canonical correlation analysis. When applied to chromatic natural images, we found that it provides a single (unified) statistical framework which accounts for both spatio-chromatic processing and adaptation. Filters with spatio-chromatic tuning properties as in the primary visual cortex emerged and corresponding-colors psychophysics was reproduced reasonably well. We used the new method to make a theory-driven testable prediction on how the neural response to colored patterns should change when the illumination changes. We predict shifts in the responses which are comparable to the shifts reported for chromatic contrast habituation.
Generalized indices for radiation risk analysis
Bykov, A.A.; Demin, V.F.
1989-01-01
A new approach to ensuring nuclear safety has begun forming since the early eighties. The approach based on the probabilistic safety analysis, the principles of acceptable risk, the optimization of safety measures, etc. has forced a complex of adequate quantitative methods of assessment, safety analysis and risk management to be developed. The method of radiation risk assessment and analysis hold a prominent place in the complex. National and international research and regulatory organizations ICRP, IAEA, WHO, UNSCEAR, OECD/NEA have given much attention to the development of the conceptual and methodological basis of those methods. Some resolutions of the National Commission of Radiological Protection (NCRP) and the Problem Commission on Radiation Hygiene of the USSR Ministry of Health should be also noted. Both CBA (cost benefit analysis) and other methods of radiation risk analysis and safety management use a system of natural and socio-economic indices characterizing the radiation risk or damage. There exist a number of problems associated with the introduction, justification and use of these indices. For example, the price, a, of radiation damage, or collective dose unit, is a noteworthy index. The difficulties in its qualitative and quantitative determination are still an obstacle for a wide application of CBA to the radiation risk analysis and management. During recent 10-15 years these problems have been a subject of consideration for many authors. The present paper also considers the issues of the qualitative and quantitative justification of the indices of radiation risk analysis
Tsai, Tien-Lung; Shau, Wen-Yi; Hu, Fu-Chang
2006-01-01
This article generalizes linear path analysis (PA) and simultaneous equations models (SiEM) to deal with mixed responses of different types in a recursive or triangular system. An efficient instrumental variable (IV) method for estimating the structural coefficients of a 2-equation partially recursive generalized path analysis (GPA) model and…
[Electroencephalogram Feature Selection Based on Correlation Coefficient Analysis].
Zhou, Jinzhi; Tang, Xiaofang
2015-08-01
In order to improve the accuracy of classification with small amount of motor imagery training data on the development of brain-computer interface (BCD systems, we proposed an analyzing method to automatically select the characteristic parameters based on correlation coefficient analysis. Throughout the five sample data of dataset IV a from 2005 BCI Competition, we utilized short-time Fourier transform (STFT) and correlation coefficient calculation to reduce the number of primitive electroencephalogram dimension, then introduced feature extraction based on common spatial pattern (CSP) and classified by linear discriminant analysis (LDA). Simulation results showed that the average rate of classification accuracy could be improved by using correlation coefficient feature selection method than those without using this algorithm. Comparing with support vector machine (SVM) optimization features algorithm, the correlation coefficient analysis can lead better selection parameters to improve the accuracy of classification.
WGCNA: an R package for weighted correlation network analysis.
Langfelder, Peter; Horvath, Steve
2008-12-29
Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/Rpackages/WGCNA.
Correlation analysis of respiratory signals by using parallel coordinate plots.
Saatci, Esra
2018-01-01
The understanding of the bonds and the relationships between the respiratory signals, i.e. the airflow, the mouth pressure, the relative temperature and the relative humidity during breathing may provide the improvement on the measurement methods of respiratory mechanics and sensor designs or the exploration of the several possible applications in the analysis of respiratory disorders. Therefore, the main objective of this study was to propose a new combination of methods in order to determine the relationship between respiratory signals as a multidimensional data. In order to reveal the coupling between the processes two very different methods were used: the well-known statistical correlation analysis (i.e. Pearson's correlation and cross-correlation coefficient) and parallel coordinate plots (PCPs). Curve bundling with the number intersections for the correlation analysis, Least Mean Square Time Delay Estimator (LMS-TDE) for the point delay detection and visual metrics for the recognition of the visual structures were proposed and utilized in PCP. The number of intersections was increased when the correlation coefficient changed from high positive to high negative correlation between the respiratory signals, especially if whole breath was processed. LMS-TDE coefficients plotted in PCP indicated well-matched point delay results to the findings in the correlation analysis. Visual inspection of PCB by visual metrics showed range, dispersions, entropy comparisons and linear and sinusoidal-like relationships between the respiratory signals. It is demonstrated that the basic correlation analysis together with the parallel coordinate plots perceptually motivates the visual metrics in the display and thus can be considered as an aid to the user analysis by providing meaningful views of the data. Copyright © 2017 Elsevier B.V. All rights reserved.
Insight into resolution enhancement in generalized two-dimensional correlation spectroscopy.
Ma, Lu; Sikirzhytski, Vitali; Hong, Zhenmin; Lednev, Igor K; Asher, Sanford A
2013-03-01
Generalized two-dimensional correlation spectroscopy (2D-COS) can be used to enhance spectral resolution in order to help differentiate highly overlapped spectral bands. Despite the numerous extensive 2D-COS investigations, the origin of the 2D spectral resolution enhancement mechanism(s) is not completely understood. In the work here, we studied the 2D-COS of simulated spectra in order to develop new insights into the dependence of 2D-COS spectral features on the overlapping band separations, their intensities and bandwidths, and their band intensity change rates. We found that the features in the 2D-COS maps that are derived from overlapping bands were determined by the spectral normalized half-intensities and the total intensity changes of the correlated bands. We identified the conditions required to resolve overlapping bands. In particular, 2D-COS peak resolution requires that the normalized half-intensities of a correlating band have amplitudes between the maxima and minima of the normalized half-intensities of the overlapping bands.
Kohut, Sviataslau V; Staroverov, Viktor N
2013-10-28
The exchange-correlation potential of Kohn-Sham density-functional theory, vXC(r), can be thought of as an electrostatic potential produced by the static charge distribution qXC(r) = -(1∕4π)∇(2)vXC(r). The total exchange-correlation charge, QXC = ∫qXC(r) dr, determines the rate of the asymptotic decay of vXC(r). If QXC ≠ 0, the potential falls off as QXC∕r; if QXC = 0, the decay is faster than coulombic. According to this rule, exchange-correlation potentials derived from standard generalized gradient approximations (GGAs) should have QXC = 0, but accurate numerical calculations give QXC ≠ 0. We resolve this paradox by showing that the charge density qXC(r) associated with every GGA consists of two types of contributions: a continuous distribution and point charges arising from the singularities of vXC(r) at each nucleus. Numerical integration of qXC(r) accounts for the continuous charge but misses the point charges. When the point-charge contributions are included, one obtains the correct QXC value. These findings provide an important caveat for attempts to devise asymptotically correct Kohn-Sham potentials by modeling the distribution qXC(r).
Johansson, B.; Rosengren, A.
1975-01-01
A ''generalized'' phase diagram is constructed empirically for the lanthanides. This diagram makes it possible, not only in one picture, to assemble a lot of information but also to predict phase transitions not yet experimentally accessible. Further, it clearly illustrates the close relation between the members of the lanthanide group. To account for some of its features, the pseudopotential method is applied. The trend in crystal structure through the lanthanide series can thereby be qualitatively accounted for, as can the trend in crystal structure for an individual element, when compressed. A scaling procedure makes it possible to extend the treatment to elements neighboring the lanthanides in the Periodic Table. In total 25 elements are considered. An atomic parameter f (relatable to the pseudopotential) is introduced, by means of which different phase transitions, both for an individual rare-earth element and intra-rare-earth alloys, can be correlated to certain critical values of this parameter. A nonmagnetic rare-earth series (Sc, Lu, Y, La, and Ac) is introduced and the occurrence of superconductivity is discussed with special emphasis on the pressure dependence of the transition temperature. This temperature can be correlated to the above-mentioned parameter f, both for intra-rare-earth alloys and pure elements at different pressures. The correlation implies that actinium is a superconductor with a critical temperature which could be as high as (11--12) degree K
Uma, B.; Swaminathan, T. N.; Ayyaswamy, P. S.; Eckmann, D. M.; Radhakrishnan, R.
2011-09-01
A direct numerical simulation (DNS) procedure is employed to study the thermal motion of a nanoparticle in an incompressible Newtonian stationary fluid medium with the generalized Langevin approach. We consider both the Markovian (white noise) and non-Markovian (Ornstein-Uhlenbeck noise and Mittag-Leffler noise) processes. Initial locations of the particle are at various distances from the bounding wall to delineate wall effects. At thermal equilibrium, the numerical results are validated by comparing the calculated translational and rotational temperatures of the particle with those obtained from the equipartition theorem. The nature of the hydrodynamic interactions is verified by comparing the velocity autocorrelation functions and mean square displacements with analytical results. Numerical predictions of wall interactions with the particle in terms of mean square displacements are compared with analytical results. In the non-Markovian Langevin approach, an appropriate choice of colored noise is required to satisfy the power-law decay in the velocity autocorrelation function at long times. The results obtained by using non-Markovian Mittag-Leffler noise simultaneously satisfy the equipartition theorem and the long-time behavior of the hydrodynamic correlations for a range of memory correlation times. The Ornstein-Uhlenbeck process does not provide the appropriate hydrodynamic correlations. Comparing our DNS results to the solution of an one-dimensional generalized Langevin equation, it is observed that where the thermostat adheres to the equipartition theorem, the characteristic memory time in the noise is consistent with the inherent time scale of the memory kernel. The performance of the thermostat with respect to equilibrium and dynamic properties for various noise schemes is discussed.
Morphosyntactic Neural Analysis for Generalized Lexical Normalization
Leeman-Munk, Samuel Paul
2016-01-01
The phenomenal growth of social media, web forums, and online reviews has spurred a growing interest in automated analysis of user-generated text. At the same time, a proliferation of voice recordings and efforts to archive culture heritage documents are fueling demand for effective automatic speech recognition (ASR) and optical character…
General principles of neutron activation analysis
Dostal, J.; Elson, C.
1980-01-01
Aspects of the principles of atomic and nuclear structure and the processes of radioactivity, nuclear transformation, and the interaction of radiations with matter which are of direct relevance to neutron activation analysis and its application to geologic materials are discussed. (L.L.)
The correlation between sports results in swimming and general and special muscle strength
Wioletta Lubkowska
2017-12-01
Full Text Available Introduction. Swimming as a sport encompasses various styles and distances (from 50 up to 1,500 meters. The correlation between sports results and general/special muscle strength seems unquestionable. Aim. The purpose of this paper is to answer the question related to maintaining the proportion between muscle strength development (which depends mainly on land-based trainings and endurance trainings in water. Material and methods. The study covered 14 leading swimmers from MKP Szczecin who specialized mainly in short and medium distances; they were members of the national senior and junior teams in the 2013/14 training year. The general strength tests were conducted at the beginning and at the end of the winter and summer preparatory periods. The following tests were performed: bench-pressing, pull-ups and bar dips. At the end of the main research period, a thrust test was conducted on land (on a swim bench, as well as a thrust test in the water. Results. All participants demonstrated progress in results between the summer season and the winter season. The range of training loads was higher in the summer due to the length of preparation (by about 100%. The individual progress was, however, very varied. Conclusions. The level of sports progress achieved by individual swimmers was greatly diversified. The relatively high level of general and special strength in the tested swimmers was linked to their need to display these motor skills while swimming. Subjects who showed the greatest progress in the general and special strength trials, displayed the biggest improvement in their swimming performance during the competition season. Swimmers with a fairly high level of strength, but a moderate sports level should analyze and improve their swimming technique. Subjects whose progress in general and special strength tests was the least significant, should try and achieve progress by developing other technical and coordination skills.
Alarm reduction with correlation analysis; Larmsanering genom korrelationsanalys
Bergquist, Tord; Ahnlund, Jonas; Johansson, Bjoern; Gaardman, Lennart; Raaberg, Martin [Lund Univ. (Sweden). Dept. of Information Technology
2004-09-01
This project's main interest is to improve the overall alarm situation in the control rooms. By doing so, the operators working environment is less overstrained, which simplifies the decision-making. According to a study of the British refinery industry, the operators make wrong decisions in four times out of ten due to badly tuned alarm systems, with heavy expenses as a result. Furthermore, a more efficiently alarm handling is estimated to decrease the production loss with between three and eight percent. This sounds, according to Swedish standards, maybe a bit extreme, but there is no doubt about the benefits of having a well-tuned alarm system. This project can be seen as an extension of 'General Methods for Alarm Reduction' (VARMEFORSK--835), where the process improvements were the result of suggestions tailored for every signal. Here, instead causal dependences in the process are examined. A method for this, specially designed to fit process signals, has been developed. It is called MLPC (Multiple Local Property Correlation) and could be seen as an unprejudiced way of increase the information value in the process. There are a number of ways to make use of the additional process understanding a correlation analysis provides. In the report some are mentioned, foremost aiming to improve the alarm situation for operators. Signals from two heating plants have been analyzed with MLPC. In simulations, with the use of the result from these analyses as a base, a large number of alarms have been successfully suppressed. The results have been studied by personal with process knowledge, and they are very positive to the use of MLPC and they express many benefits by the clarification of process relations. It was established in 'General Methods for Alarm Reduction' that low pass filter are superior to mean value filter and time delay when trying to suppress alarms. As a result, a module for signal processing has been developed. The main purpose is
General analysis of HERA II data
Schoening, A
2008-01-01
A model-independent search for deviations from the Standard Model prediction is performed in e ± p collisions. Data collected in the years 2003-2007 corresponding to an integrated luminosity of about 340 pb -1 are analyzed. All event topologies involving isolated electrons, photons, muons, neutrinos and jets with high transverse momenta are investigated in a single analysis. Events are assigned to exclusive classes according to their final state. A statistical algorithm is applied to search for deviations from the Standard Model in the distributions of the scalar sum of transverse momenta or invariant mass of final state particles and to quantify their significance. A good agreement with the Standard Model prediction is observed in most of the event classes. No significant deviation is observed in the phase-space and in the event topologies covered by this analysis
Mona Maneshi
Full Text Available INTRODUCTION: In idiopathic generalized epilepsy (IGE, a normal electroencephalogram between generalized spike and wave (GSW discharges is believed to reflect normal brain function. However, some studies indicate that even excluding GSW-related errors, IGE patients perform poorly on sustained attention task, the deficit being worse as a function of disease duration. We hypothesized that at least in a subset of structures which are normally involved in sustained attention, resting-state functional connectivity (FC is different in IGE patients compared to controls and that some of the changes are related to disease duration. METHOD: Seeds were selected based on a sustained attention study in controls. Resting-state functional magnetic resonance imaging (fMRI data was obtained from 14 IGE patients and 14 matched controls. After physiological noise removal, the mean time-series of each seed was used as a regressor in a general linear model to detect regions that showed correlation with the seed. In patients, duration factor was defined based on epilepsy duration. Between-group differences weighted by the duration factor were evaluated with mixed-effects model. Correlation was then evaluated in IGE patients between the FC, averaged over each significant cluster, and the duration factor. RESULTS: Eight of 18 seeds showed significant difference in FC across groups. However, only for seeds in the medial superior frontal and precentral gyri and in the medial prefrontal area, average FC taken over significant clusters showed high correlation with the duration factor. These 3 seeds showed changes in FC respectively with the premotor and superior frontal gyrus, the dorsal premotor, and the supplementary motor area plus precentral gyrus. CONCLUSION: Alterations of FC in IGE patients are not limited to the frontal areas. However, as indicated by specificity analysis, patients with long history of disease show changes in FC mainly within the frontal areas.
Correlation analysis of the Taurus molecular cloud complex
Kleiner, S.C.
1985-01-01
Autocorrelation and power spectrum methods were applied to the analysis of the density and velocity structure of the Taurus Complex and Heiles Cloud 2 as traced out by 13 CO J = 1 → 0 molecular line observations obtained with the 14m antenna of the Five College Radio Astronomy Observatory. Statistically significant correlations in the spacing of density fluctuations within the Taurus Complex and Heiles 2 were uncovered. The length scales of the observed correlations correspond in magnitude to the Jeans wavelengths characterizing gravitational instabilities with (i) interstellar atomic hydrogen gas for the case of the Taurus complex, and (ii) molecular hydrogen for Heiles 2. The observed correlations may be the signatures of past and current gravitational instabilities frozen into the structure of the molecular gas. The appendices provide a comprehensive description of the analytical and numerical methods developed for the correlation analysis of molecular clouds
Canonical correlation analysis of course and teacher evaluation
Sliusarenko, Tamara; Ersbøll, Bjarne Kjær
2010-01-01
At the Technical University of Denmark course evaluations are performed by the students on a questionnaire. On one form the students are asked specific questions regarding the course. On a second form they are asked specific questions about the teacher. This study investigates the extent to which...... information obtained from the course evaluation form overlaps with information obtained from the teacher evaluation form. Employing canonical correlation analysis it was found that course and teacher evaluations are correlated. However, the structure of the canonical correlation is subject to change...
Analysis of charge-dependent azimuthal correlations with HADES
Kornas, Frederic [TU Darmstadt (Germany); Selyuzhenkov, Ilya [GSI (Germany); Galatyuk, Tetyana [TU Darmstadt (Germany); GSI (Germany); Collaboration: HADES-Collaboration
2016-07-01
Charge-dependent azimuthal correlations relative to the reaction plane have been proposed as a probe in the search for the chiral magnetic effect in relativistic heavy-ion collisions. These type of correlations have been measured at the RHIC BES by STAR and at the LHC by ALICE. This contribution discusses two charged particle correlations with respect to the reaction plane measured with high statistic sample of Au+Au collisions at 1.23 AGeV collected by HADES. The Forward wall detector allows to reconstruct the reaction plane using the spectator fragments. The status of the analysis with protons and charged pions will be presented.
Provider attributes correlation analysis to their referral frequency and awards.
Wiley, Matthew T; Rivas, Ryan L; Hristidis, Vagelis
2016-03-14
There has been a recent growth in health provider search portals, where patients specify filters-such as specialty or insurance-and providers are ranked by patient ratings or other attributes. Previous work has identified attributes associated with a provider's quality through user surveys. Other work supports that intuitive quality-indicating attributes are associated with a provider's quality. We adopt a data-driven approach to study how quality indicators of providers are associated with a rich set of attributes including medical school, graduation year, procedures, fellowships, patient reviews, location, and technology usage. In this work, we only consider providers as individuals (e.g., general practitioners) and not organizations (e.g., hospitals). As quality indicators, we consider the referral frequency of a provider and a peer-nominated quality designation. We combined data from the Centers for Medicare and Medicaid Services (CMS) and several provider rating web sites to perform our analysis. Our data-driven analysis identified several attributes that correlate with and discriminate against referral volume and peer-nominated awards. In particular, our results consistently demonstrate that these attributes vary by locality and that the frequency of an attribute is more important than its value (e.g., the number of patient reviews or hospital affiliations are more important than the average review rating or the ranking of the hospital affiliations, respectively). We demonstrate that it is possible to build accurate classifiers for referral frequency and quality designation, with accuracies over 85 %. Our findings show that a one-size-fits-all approach to ranking providers is inadequate and that provider search portals should calibrate their ranking function based on location and specialty. Further, traditional filters of provider search portals should be reconsidered, and patients should be aware of existing pitfalls with these filters and educated on local
Data analytics using canonical correlation analysis and Monte Carlo simulation
Rickman, Jeffrey M.; Wang, Yan; Rollett, Anthony D.; Harmer, Martin P.; Compson, Charles
2017-07-01
A canonical correlation analysis is a generic parametric model used in the statistical analysis of data involving interrelated or interdependent input and output variables. It is especially useful in data analytics as a dimensional reduction strategy that simplifies a complex, multidimensional parameter space by identifying a relatively few combinations of variables that are maximally correlated. One shortcoming of the canonical correlation analysis, however, is that it provides only a linear combination of variables that maximizes these correlations. With this in mind, we describe here a versatile, Monte-Carlo based methodology that is useful in identifying non-linear functions of the variables that lead to strong input/output correlations. We demonstrate that our approach leads to a substantial enhancement of correlations, as illustrated by two experimental applications of substantial interest to the materials science community, namely: (1) determining the interdependence of processing and microstructural variables associated with doped polycrystalline aluminas, and (2) relating microstructural decriptors to the electrical and optoelectronic properties of thin-film solar cells based on CuInSe2 absorbers. Finally, we describe how this approach facilitates experimental planning and process control.
Majumdar, Alok; Leclair, Andre; Moore, Ric; Schallhorn, Paul
2011-01-01
GFSSP stands for Generalized Fluid System Simulation Program. It is a general-purpose computer program to compute pressure, temperature and flow distribution in a flow network. GFSSP calculates pressure, temperature, and concentrations at nodes and calculates flow rates through branches. It was primarily developed to analyze Internal Flow Analysis of a Turbopump Transient Flow Analysis of a Propulsion System. GFSSP development started in 1994 with an objective to provide a generalized and easy to use flow analysis tool for thermo-fluid systems.
Probabilistic leak-before-break analysis with correlated input parameters
Qian Guian; Niffenegger, Markus; Karanki, Durga Rao; Li Shuxin
2013-01-01
Highlights: ► The correlation of crack growth has the most significant impact on LBB behavior. ► The correlation impact increases with the correlation coefficients. ► The correlation impact increases with the number of cracks. ► Independent assumption may lead to nonconservative result. - Abstract: The paper presents a probabilistic methodology considering the correlations between the input variables for the analysis of leak-before-break (LBB) behavior of a pressure tube. A computer program based on Monte Carlo (MC) simulation with Nataf transformation has been developed to allow the proposed methodology to calculate both the time from the first leakage to unstable fracture and the time from leakage detection to unstable fracture. The results show that the correlation of the crack growth rates between different cracks has the most significant impact on the LBB behavior of the pressure tube. The impact of the parameters correlation on LBB behavior increases with the crack numbers. If the correlations between different parameters for an individual crack are not considered, the predicted results are nonconservative when the cumulative probability is below 50% and conservative when it is above 50%.
Westgate, Philip M
2016-01-01
When generalized estimating equations (GEE) incorporate an unstructured working correlation matrix, the variances of regression parameter estimates can inflate due to the estimation of the correlation parameters. In previous work, an approximation for this inflation that results in a corrected version of the sandwich formula for the covariance matrix of regression parameter estimates was derived. Use of this correction for correlation structure selection also reduces the over-selection of the unstructured working correlation matrix. In this manuscript, we conduct a simulation study to demonstrate that an increase in variances of regression parameter estimates can occur when GEE incorporates structured working correlation matrices as well. Correspondingly, we show the ability of the corrected version of the sandwich formula to improve the validity of inference and correlation structure selection. We also study the relative influences of two popular corrections to a different source of bias in the empirical sandwich covariance estimator.
Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient.
Yao, Jianchao; Chang, Chunqi; Salmi, Mari L; Hung, Yeung Sam; Loraine, Ann; Roux, Stanley J
2008-06-18
correlation coefficient and the SD-weighted correlation coefficient, and is particularly useful for clustering replicated microarray data. This computational approach should be generally useful for proteomic data or other high-throughput analysis methodology.
Basic general concepts in the network analysis
Boja Nicolae
2004-01-01
Full Text Available This survey is concerned oneself with the study of those types of material networks which can be met both in civil engineering and also in electrotechnics, in mechanics, or in hydrotechnics, and of which behavior lead to linear problems, solvable by means of Finite Element Method and adequate algorithms. Here, it is presented a unitary theory of networks met in the domains mentioned above and this one is illustrated with examples for the structural networks in civil engineering, electric circuits, and water supply networks, but also planar or spatial mechanisms can be comprised in this theory. The attention is focused to make evident the essential proper- ties and concepts in the network analysis, which differentiate the networks under force from other types of material networks. To such a network a planar, connected, and directed or undirected graph is associated, and with some vector fields on the vertex set this graph is endowed. .
Zhou, Chenyi; Guo, Hong
2017-01-01
We report a diagrammatic method to solve the general problem of calculating configurationally averaged Green's function correlators that appear in quantum transport theory for nanostructures containing disorder. The theory treats both equilibrium and nonequilibrium quantum statistics on an equal footing. Since random impurity scattering is a problem that cannot be solved exactly in a perturbative approach, we combine our diagrammatic method with the coherent potential approximation (CPA) so that a reliable closed-form solution can be obtained. Our theory not only ensures the internal consistency of the diagrams derived at different levels of the correlators but also satisfies a set of Ward-like identities that corroborate the conserving consistency of transport calculations within the formalism. The theory is applied to calculate the quantum transport properties such as average ac conductance and transmission moments of a disordered tight-binding model, and results are numerically verified to high precision by comparing to the exact solutions obtained from enumerating all possible disorder configurations. Our formalism can be employed to predict transport properties of a wide variety of physical systems where disorder scattering is important.
Measuring time-of-flight in an ultrasonic LPS system using generalized cross-correlation.
Villladangos, José Manuel; Ureña, Jesús; García, Juan Jesús; Mazo, Manuel; Hernández, Alvaro; Jiménez, Ana; Ruíz, Daniel; De Marziani, Carlos
2011-01-01
In this article, a time-of-flight detection technique in the frequency domain is described for an ultrasonic local positioning system (LPS) based on encoded beacons. Beacon transmissions have been synchronized and become simultaneous by means of the DS-CDMA (direct-sequence code Division multiple access) technique. Every beacon has been associated to a 255-bit Kasami code. The detection of signal arrival instant at the receiver, from which the distance to each beacon can be obtained, is based on the application of the generalized cross-correlation (GCC), by using the cross-spectral density between the received signal and the sequence to be detected. Prior filtering to enhance the frequency components around the carrier frequency (40 kHz) has improved estimations when obtaining the correlation function maximum, which implies an improvement in distance measurement precision. Positioning has been achieved by using hyperbolic trilateration, based on the time differences of arrival (TDOA) between a reference beacon and the others.
Confinement and correlation effects in the Xe-C{sub 60} generalized oscillator strengths
Amusia, M. Ya. [Racah Institute of Physics, Hebrew University, 91904 Jerusalem (Israel); A. F. Ioffe Physical-Technical Institute, 194021 St. Petersburg (Russian Federation); Chernysheva, L. V. [A. F. Ioffe Physical-Technical Institute, 194021 St. Petersburg (Russian Federation); Dolmatov, V. K. [Department of Physics and Earth Science, University of North Alabama, Florence, Alabama 35632 (United States)
2011-12-15
The impact of both confinement and electron correlation on generalized oscillator strengths (GOS's) of endohedral atoms, A-C{sub 60}, is theoretically studied choosing the Xe-C{sub 60} 4d, 5s, and 5p fast electron impact ionization as the case study. Calculations are performed in the transferred to the atom energy region beyond the 4d threshold, {omega}=75-175 eV. The calculation methodology combines the plane-wave Born approximation, Hartree-Fock approximation, and random-phase approximation with exchange in the presence of the C{sub 60} confinement. The confinement is modeled by a spherical {delta}-function-like potential as well as by a square well potential to evaluate the effect of the finite thickness of the C{sub 60} cage on the Xe-C{sub 60} GOS's. Dramatic distortion of the 4d, 5p, and 5s GOS's by the confinement is demonstrated, compared to the free atom. Considerable contributions of multipolar transitions beyond dipole transitions in the calculated GOS's are revealed, in some instances. The vitality of accounting for electron correlation in calculation of the Xe-C{sub 60} 5s and 5p GOS's is shown.
Vilardy, Juan M; Millán, María S; Pérez-Cabré, Elisabet; Torres, Yezid
2014-01-01
We propose a generalization of the encryption system based on double random phase encoding (DRPE) and a joint transform correlator (JTC), from the Fourier domain to the fractional Fourier domain (FrFD) by using the fractional Fourier operators, such as the fractional Fourier transform (FrFT), fractional traslation, fractional convolution and fractional correlation. Image encryption systems based on a JTC architecture in the FrFD usually produce low quality decrypted images. In this work, we present two approaches to improve the quality of the decrypted images, which are based on nonlinear processing applied to the encrypted function (that contains the joint fractional power spectrum, JFPS) and the nonzero-order JTC in the FrFD. When the two approaches are combined, the quality of the decrypted image is higher. In addition to the advantages introduced by the implementation of the DRPE using a JTC, we demonstrate that the proposed encryption system in the FrFD preserves the shift-invariance property of the JTC-based encryption system in the Fourier domain, with respect to the lateral displacement of both the key random mask in the decryption process and the retrieval of the primary image. The feasibility of this encryption system is verified and analyzed by computer simulations. (paper)
Ranta, Klaus; Kaltiala-Heino, Riittakerttu; Rantanen, Päivi; Marttunen, Mauri
2009-01-01
Few studies have investigated the epidemiology of social phobia (SP) among early to middle adolescents, at the time of suggested mean onset of the disorder. The objective of this study was to investigate the prevalence, comorbidity, individual and familial correlates, and service use associated with SP among Finnish 12-17-year-old adolescents in general population. A sample of 784 adolescents was screened with the Social Phobia Inventory, and a sub-sample (n=350) was interviewed with a semi-structured clinical interview to identify SP, sub-clinical SP (SSP), and a range of other axis I DSM-IV disorders. Individual and familial correlates, and service use associated with SP were also inquired. We found a 12-month prevalence of 3.2% for SP, and 4.6% for SSP. The prevalence rose and the gender ratio shifted to female preponderance as age increased. SP was frequently comorbid with other anxiety disorders (41%) and depressive disorders (41%). Adolescents with SP/SSP were impaired in their academic and global functioning, and reported more parental psychiatric treatment contacts. Two thirds (68%) of adolescents with SP reported having been bullied by peers. Only one fifth of adolescents with non-comorbid SP had been in contact with a mental health professional. We conclude that adolescent SP is a relatively frequent, undertreated and highly comorbid condition, associated with educational impairment, depression and anxiety in parents, and peer victimization. (c) 2009 Wiley-Liss, Inc.
Moon, Chung-Man [Chonnam National University Hospital, Research Institute for Medical Imaging, Gwangju (Korea, Republic of); Jeong, Gwang-Woo [Chonnam National University Hospital, Research Institute for Medical Imaging, Gwangju (Korea, Republic of); Chonnam National University Medical School, Department of Radiology, Chonnam National University Hospital, Gwangju (Korea, Republic of)
2015-11-15
Only a few morphological studies have focused on changes in white matter (WM) volume in patients with generalized anxiety disorder (GAD). We evaluated alterations in WM volume and its correlation with symptom severity and duration of illness in adults with GAD. The 44 subjects were comprised of 22 patients with GAD (13 males and nine females) diagnosed using the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) and 22 age-matched healthy controls (13 males and nine females). High-resolution magnetic resonance imaging (MRI) data were processed by voxel-based morphometry (VBM) analysis based on diffeomorphic anatomical registration using the exponentiated Lie algebra (DARTEL) algorithm in SPM8. Patients with GAD showed significantly reduced WM volume, particularly in the dorsolateral prefrontal cortex (DLPFC), anterior limb of the internal capsule (ALIC), and midbrain. In addition, DLPFC volume was negatively correlated with GAD-7 score and illness duration. ALIC volume was negatively correlated with GAD-7 score. Female patients had significantly less orbitofrontal cortex volume compared to that in male patients. The findings demonstrate localized changes in WM volume associated with cognitive and emotional dysfunction in patients with GAD. The finding will be helpful for understanding the neuropathology in patients with GAD. (orig.)
Moon, Chung-Man; Jeong, Gwang-Woo
2015-01-01
Only a few morphological studies have focused on changes in white matter (WM) volume in patients with generalized anxiety disorder (GAD). We evaluated alterations in WM volume and its correlation with symptom severity and duration of illness in adults with GAD. The 44 subjects were comprised of 22 patients with GAD (13 males and nine females) diagnosed using the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) and 22 age-matched healthy controls (13 males and nine females). High-resolution magnetic resonance imaging (MRI) data were processed by voxel-based morphometry (VBM) analysis based on diffeomorphic anatomical registration using the exponentiated Lie algebra (DARTEL) algorithm in SPM8. Patients with GAD showed significantly reduced WM volume, particularly in the dorsolateral prefrontal cortex (DLPFC), anterior limb of the internal capsule (ALIC), and midbrain. In addition, DLPFC volume was negatively correlated with GAD-7 score and illness duration. ALIC volume was negatively correlated with GAD-7 score. Female patients had significantly less orbitofrontal cortex volume compared to that in male patients. The findings demonstrate localized changes in WM volume associated with cognitive and emotional dysfunction in patients with GAD. The finding will be helpful for understanding the neuropathology in patients with GAD. (orig.)
Comprehensive analysis of electron correlations in three-electron atoms
Morishita, T.; Lin, C.D.
1999-01-01
We study the electron correlations in singly, doubly, and triply excited states of a three-electron atom. While electron correlation in general is weak for singly excited states, correlation plays major roles in determining the characteristics of doubly and triply excited states. Using the adiabatic approximation in hyperspherical coordinates, we show that the distinction between singly, doubly, and triply excited states is determined by the radial correlations, while finer distinctions within doubly or triply excited states lie in the angular correlations. Partial projections of the body-fixed frame wave functions are used to demonstrate the characteristic nodal surfaces which provide clues to the energy ordering of the states. We show that doubly excited states of a three-electron atom exhibit correlations that are similar to the doubly excited states of a two-electron atom. For the triply excited states, we show that the motion of the three electrons resemble approximately that of a symmetric top. copyright 1999 The American Physical Society
Cross-cultural differences in the neural correlates of specific and general recognition.
Paige, Laura E; Ksander, John C; Johndro, Hunter A; Gutchess, Angela H
2017-06-01
Research suggests that culture influences how people perceive the world, which extends to memory specificity, or how much perceptual detail is remembered. The present study investigated cross-cultural differences (Americans vs East Asians) at the time of encoding in the neural correlates of specific versus general memory formation. Participants encoded photos of everyday items in the scanner and 48 h later completed a surprise recognition test. The recognition test consisted of same (i.e., previously seen in scanner), similar (i.e., same name, different features), or new photos (i.e., items not previously seen in scanner). For Americans compared to East Asians, we predicted greater activation in the hippocampus and right fusiform for specific memory at recognition, as these regions were implicated previously in encoding perceptual details. Results revealed that East Asians activated the left fusiform and left hippocampus more than Americans for specific versus general memory. Follow-up analyses ruled out alternative explanations of retrieval difficulty and familiarity for this pattern of cross-cultural differences at encoding. Results overall suggest that culture should be considered as another individual difference that affects memory specificity and modulates neural regions underlying these processes. Copyright © 2017 Elsevier Ltd. All rights reserved.
Mejia-Rodriguez, Daniel; Trickey, S. B.
2017-11-01
We explore the simplification of widely used meta-generalized-gradient approximation (mGGA) exchange-correlation functionals to the Laplacian level of refinement by use of approximate kinetic-energy density functionals (KEDFs). Such deorbitalization is motivated by the prospect of reducing computational cost while recovering a strictly Kohn-Sham local potential framework (rather than the usual generalized Kohn-Sham treatment of mGGAs). A KEDF that has been rather successful in solid simulations proves to be inadequate for deorbitalization, but we produce other forms which, with parametrization to Kohn-Sham results (not experimental data) on a small training set, yield rather good results on standard molecular test sets when used to deorbitalize the meta-GGA made very simple, Tao-Perdew-Staroverov-Scuseria, and strongly constrained and appropriately normed functionals. We also study the difference between high-fidelity and best-performing deorbitalizations and discuss possible implications for use in ab initio molecular dynamics simulations of complicated condensed phase systems.
Comparative analysis of heat transfer correlations for forced convection boiling
Guglielmini, G.; Nannei, E.; Pisoni, C.
1978-01-01
A critical survey was conducted of the most relevant correlations of boiling heat transfer in forced convection flow. Most of the investigations carried out on partial nucleate boiling and fully developed nucleate boiling have led to the formulation of correlations that are not able to cover a wide range of operating conditions, due to the empirical approach of the problem. A comparative analysis is therefore required in order to delineate the relative accuracy of the proposed correlations, on the basis of the experimental data presently available. The survey performed allows the evaluation of the accuracy of the different calculating procedure; the results obtained, moreover, indicate the most reliable heat transfer correlations for the different operating conditions investigated. This survey was developed for five pressure range (up to 180bar) and for both saturation and subcooled boiling condition
Discourse analysis in general practice: a sociolinguistic approach.
Nessa, J; Malterud, K
1990-06-01
It is a simple but important fact that as general practitioners we talk to our patients. The quality of the conversation is of vital importance for the outcome of the consultation. The purpose of this article is to discuss a methodological tool borrowed from sociolinguistics--discourse analysis. To assess the suitability of this method for analysis of general practice consultations, the authors have performed a discourse analysis of one single consultation. Our experiences are presented here.
The Neural Correlates of Moral Thinking: A Meta-Analysis
Douglas J. Bryant; Wang F; Kelley Deardeuff; Emily Zoccoli; Chang S. Nam
2016-01-01
We conducted a meta-analysis to evaluate current research that aims to map the neural correlates of two typical conditions of moral judgment: right-wrong moral judgments and decision-making in moral dilemmas. Utilizing the activation likelihood estimation (ALE) method, we conducted a meta-analysis using neuroimaging data obtained from twenty-one previous studies that measured responses in one or the other of these conditions. We found that across the studies (n = 400), distinct neural circuit...
GIS and correlation analysis of geo-environmental variables ...
GIS and correlation analysis of geo-environmental variables influencing malaria prevalence in the Saboba district of Northern Ghana. ... The study also applied spline interpolation technique to map malaria prevalence in the district using standardised malaria incidence. The result indicates that distance to marshy areas is ...
Variability, correlation and path coefficient analysis of seedling traits ...
Indirect selection is a useful means for improving yield in cotton crop. The objective of the present study was to determine the genetic variability, broad sense heritability, genetic advance and correlation among the six seedling traits and their direct and indirect effects on cotton yield by using path coefficient analysis.
Use of fuel failure correlations in accident analysis
O'Dell, L.D.; Baars, R.E.; Waltar, A.E.
1975-05-01
The MELT-III code for analysis of a Transient Overpower (TOP) accident in an LMFBR is briefly described, including failure criteria currently applied in the code. Preliminary results of calculations exploring failure patterns in time and space in the reactor core are reported and compared for the two empirical fuel failure correlations employed in the code. (U.S.)
Model-independent analysis with BPM correlation matrices
Irwin, J.; Wang, C.X.; Yan, Y.T.; Bane, K.; Cai, Y.; Decker, F.; Minty, M.; Stupakov, G.; Zimmermann, F.
1998-06-01
The authors discuss techniques for Model-Independent Analysis (MIA) of a beamline using correlation matrices of physical variables and Singular Value Decomposition (SVD) of a beamline BPM matrix. The beamline matrix is formed from BPM readings for a large number of pulses. The method has been applied to the Linear Accelerator of the SLAC Linear Collider (SLC)
A learning algorithm for adaptive canonical correlation analysis of several data sets.
Vía, Javier; Santamaría, Ignacio; Pérez, Jesús
2007-01-01
Canonical correlation analysis (CCA) is a classical tool in statistical analysis to find the projections that maximize the correlation between two data sets. In this work we propose a generalization of CCA to several data sets, which is shown to be equivalent to the classical maximum variance (MAXVAR) generalization proposed by Kettenring. The reformulation of this generalization as a set of coupled least squares regression problems is exploited to develop a neural structure for CCA. In particular, the proposed CCA model is a two layer feedforward neural network with lateral connections in the output layer to achieve the simultaneous extraction of all the CCA eigenvectors through deflation. The CCA neural model is trained using a recursive least squares (RLS) algorithm. Finally, the convergence of the proposed learning rule is proved by means of stochastic approximation techniques and their performance is analyzed through simulations.
Wang Shijun; Yao Jianhua; Liu Jiamin; Petrick, Nicholas; Van Uitert, Robert L.; Periaswamy, Senthil; Summers, Ronald M.
2009-01-01
Purpose: In computed tomographic colonography (CTC), a patient will be scanned twice--Once supine and once prone--to improve the sensitivity for polyp detection. To assist radiologists in CTC reading, in this paper we propose an automated method for colon registration from supine and prone CTC scans. Methods: We propose a new colon centerline registration method for prone and supine CTC scans using correlation optimized warping (COW) and canonical correlation analysis (CCA) based on the anatomical structure of the colon. Four anatomical salient points on the colon are first automatically distinguished. Then correlation optimized warping is applied to the segments defined by the anatomical landmarks to improve the global registration based on local correlation of segments. The COW method was modified by embedding canonical correlation analysis to allow multiple features along the colon centerline to be used in our implementation. Results: We tested the COW algorithm on a CTC data set of 39 patients with 39 polyps (19 training and 20 test cases) to verify the effectiveness of the proposed COW registration method. Experimental results on the test set show that the COW method significantly reduces the average estimation error in a polyp location between supine and prone scans by 67.6%, from 46.27±52.97 to 14.98 mm±11.41 mm, compared to the normalized distance along the colon centerline algorithm (p<0.01). Conclusions: The proposed COW algorithm is more accurate for the colon centerline registration compared to the normalized distance along the colon centerline method and the dynamic time warping method. Comparison results showed that the feature combination of z-coordinate and curvature achieved lowest registration error compared to the other feature combinations used by COW. The proposed method is tolerant to centerline errors because anatomical landmarks help prevent the propagation of errors across the entire colon centerline.
MAGMA: generalized gene-set analysis of GWAS data.
de Leeuw, C.A.; Mooij, J.M.; Heskes, T.; Posthuma, D.
2015-01-01
By aggregating data for complex traits in a biologically meaningful way, gene and gene-set analysis constitute a valuable addition to single-marker analysis. However, although various methods for gene and gene-set analysis currently exist, they generally suffer from a number of issues. Statistical
MAGMA: Generalized Gene-Set Analysis of GWAS Data
de Leeuw, C.A.; Mooij, J.M.; Heskes, T.; Posthuma, D.
2015-01-01
By aggregating data for complex traits in a biologically meaningful way, gene and gene-set analysis constitute a valuable addition to single-marker analysis. However, although various methods for gene and gene-set analysis currently exist, they generally suffer from a number of issues. Statistical
A Note on McDonald's Generalization of Principal Components Analysis
Shine, Lester C., II
1972-01-01
It is shown that McDonald's generalization of Classical Principal Components Analysis to groups of variables maximally channels the totalvariance of the original variables through the groups of variables acting as groups. An equation is obtained for determining the vectors of correlations of the L2 components with the original variables.…
Sparse canonical correlation analysis: new formulation and algorithm.
Chu, Delin; Liao, Li-Zhi; Ng, Michael K; Zhang, Xiaowei
2013-12-01
In this paper, we study canonical correlation analysis (CCA), which is a powerful tool in multivariate data analysis for finding the correlation between two sets of multidimensional variables. The main contributions of the paper are: 1) to reveal the equivalent relationship between a recursive formula and a trace formula for the multiple CCA problem, 2) to obtain the explicit characterization for all solutions of the multiple CCA problem even when the corresponding covariance matrices are singular, 3) to develop a new sparse CCA algorithm, and 4) to establish the equivalent relationship between the uncorrelated linear discriminant analysis and the CCA problem. We test several simulated and real-world datasets in gene classification and cross-language document retrieval to demonstrate the effectiveness of the proposed algorithm. The performance of the proposed method is competitive with the state-of-the-art sparse CCA algorithms.
Information-Pooling Bias in Collaborative Security Incident Correlation Analysis.
Rajivan, Prashanth; Cooke, Nancy J
2018-03-01
Incident correlation is a vital step in the cybersecurity threat detection process. This article presents research on the effect of group-level information-pooling bias on collaborative incident correlation analysis in a synthetic task environment. Past research has shown that uneven information distribution biases people to share information that is known to most team members and prevents them from sharing any unique information available with them. The effect of such biases on security team collaborations are largely unknown. Thirty 3-person teams performed two threat detection missions involving information sharing and correlating security incidents. Incidents were predistributed to each person in the team based on the hidden profile paradigm. Participant teams, randomly assigned to three experimental groups, used different collaboration aids during Mission 2. Communication analysis revealed that participant teams were 3 times more likely to discuss security incidents commonly known to the majority. Unaided team collaboration was inefficient in finding associations between security incidents uniquely available to each member of the team. Visualizations that augment perceptual processing and recognition memory were found to mitigate the bias. The data suggest that (a) security analyst teams, when conducting collaborative correlation analysis, could be inefficient in pooling unique information from their peers; (b) employing off-the-shelf collaboration tools in cybersecurity defense environments is inadequate; and (c) collaborative security visualization tools developed considering the human cognitive limitations of security analysts is necessary. Potential applications of this research include development of team training procedures and collaboration tool development for security analysts.
Analysis of the Correlation between GDP and the Final Consumption
Constantin ANGHELACHE
2011-09-01
Full Text Available This paper presents the results of the researches performed by the author regarding the evolution of Gross Domestic Product. One of the main aspects of GDP analysis is the correlation with the final consumption, an important macroeconomic indicator. The evolution of the Gross Domestic Product is highly influenced by the evolution of the final consumption. To analyze the correlation, the paper proposes the use of the linear regression model, as one of the most appropriate instruments for such scientific approach. The regression model described in the article uses the GDP as resultant variable and the final consumption as factorial variable.
A multimodal stress monitoring system with canonical correlation analysis.
Unsoo Ha; Changhyeon Kim; Yongsu Lee; Hyunki Kim; Taehwan Roh; Hoi-Jun Yoo
2015-08-01
The multimodal stress monitoring headband is proposed for mobile stress management system. It is composed of headband and earplugs. Electroencephalography (EEG), hemoencephalography (HEG) and heart-rate variability (HRV) can be achieved simultaneously in the proposed system for user status estimation. With canonical correlation analysis (CCA) and temporal-kernel CCA (tkCCA) algorithm, those different signals can be combined for maximum correlation. Thanks to the proposed combination algorithm, the accuracy of the proposed system increased up to 19 percentage points than unimodal monitoring system in n-back task.
Wang Jun-Song; Yuan Jing; Li Qiang; Yuan Rui-Xi
2011-01-01
This paper uses a correlation dimension based nonlinear analysis approach to analyse the dynamics of network traffics with three different application protocols—HTTP, FTP and SMTP. First, the phase space is reconstructed and the embedding parameters are obtained by the mutual information method. Secondly, the correlation dimensions of three different traffics are calculated and the results of analysis have demonstrated that the dynamics of the three different application protocol traffics is different from each other in nature, i.e. HTTP and FTP traffics are chaotic, furthermore, the former is more complex than the later; on the other hand, SMTP traffic is stochastic. It is shown that correlation dimension approach is an efficient method to understand and to characterize the nonlinear dynamics of HTTP, FTP and SMTP protocol network traffics. This analysis provided insight into and a more accurate understanding of nonlinear dynamics of internet traffics which have a complex mixture of chaotic and stochastic components. (general)
Block correlated second order perturbation theory with a generalized valence bond reference function
Xu, Enhua; Li, Shuhua
2013-01-01
The block correlated second-order perturbation theory with a generalized valence bond (GVB) reference (GVB-BCPT2) is proposed. In this approach, each geminal in the GVB reference is considered as a “multi-orbital” block (a subset of spin orbitals), and each occupied or virtual spin orbital is also taken as a single block. The zeroth-order Hamiltonian is set to be the summation of the individual Hamiltonians of all blocks (with explicit two-electron operators within each geminal) so that the GVB reference function and all excited configuration functions are its eigenfunctions. The GVB-BCPT2 energy can be directly obtained without iteration, just like the second order Møller–Plesset perturbation method (MP2), both of which are size consistent. We have applied this GVB-BCPT2 method to investigate the equilibrium distances and spectroscopic constants of 7 diatomic molecules, conformational energy differences of 8 small molecules, and bond-breaking potential energy profiles in 3 systems. GVB-BCPT2 is demonstrated to have noticeably better performance than MP2 for systems with significant multi-reference character, and provide reasonably accurate results for some systems with large active spaces, which are beyond the capability of all CASSCF-based methods
Xu, Enhua; Li, Shuhua
2013-11-07
The block correlated second-order perturbation theory with a generalized valence bond (GVB) reference (GVB-BCPT2) is proposed. In this approach, each geminal in the GVB reference is considered as a "multi-orbital" block (a subset of spin orbitals), and each occupied or virtual spin orbital is also taken as a single block. The zeroth-order Hamiltonian is set to be the summation of the individual Hamiltonians of all blocks (with explicit two-electron operators within each geminal) so that the GVB reference function and all excited configuration functions are its eigenfunctions. The GVB-BCPT2 energy can be directly obtained without iteration, just like the second order Mo̸ller-Plesset perturbation method (MP2), both of which are size consistent. We have applied this GVB-BCPT2 method to investigate the equilibrium distances and spectroscopic constants of 7 diatomic molecules, conformational energy differences of 8 small molecules, and bond-breaking potential energy profiles in 3 systems. GVB-BCPT2 is demonstrated to have noticeably better performance than MP2 for systems with significant multi-reference character, and provide reasonably accurate results for some systems with large active spaces, which are beyond the capability of all CASSCF-based methods.
Parallel Enhancements of the General Mission Analysis Tool, Phase I
National Aeronautics and Space Administration — The General Mission Analysis Tool (GMAT) is a state of the art spacecraft mission design tool under active development at NASA's Goddard Space Flight Center (GSFC)....
Windowed Multitaper Correlation Analysis of Multimodal Brain Monitoring Parameters
Rupert Faltermeier
2015-01-01
Full Text Available Although multimodal monitoring sets the standard in daily practice of neurocritical care, problem-oriented analysis tools to interpret the huge amount of data are lacking. Recently a mathematical model was presented that simulates the cerebral perfusion and oxygen supply in case of a severe head trauma, predicting the appearance of distinct correlations between arterial blood pressure and intracranial pressure. In this study we present a set of mathematical tools that reliably detect the predicted correlations in data recorded at a neurocritical care unit. The time resolved correlations will be identified by a windowing technique combined with Fourier-based coherence calculations. The phasing of the data is detected by means of Hilbert phase difference within the above mentioned windows. A statistical testing method is introduced that allows tuning the parameters of the windowing method in such a way that a predefined accuracy is reached. With this method the data of fifteen patients were examined in which we found the predicted correlation in each patient. Additionally it could be shown that the occurrence of a distinct correlation parameter, called scp, represents a predictive value of high quality for the patients outcome.
Windowed multitaper correlation analysis of multimodal brain monitoring parameters.
Faltermeier, Rupert; Proescholdt, Martin A; Bele, Sylvia; Brawanski, Alexander
2015-01-01
Although multimodal monitoring sets the standard in daily practice of neurocritical care, problem-oriented analysis tools to interpret the huge amount of data are lacking. Recently a mathematical model was presented that simulates the cerebral perfusion and oxygen supply in case of a severe head trauma, predicting the appearance of distinct correlations between arterial blood pressure and intracranial pressure. In this study we present a set of mathematical tools that reliably detect the predicted correlations in data recorded at a neurocritical care unit. The time resolved correlations will be identified by a windowing technique combined with Fourier-based coherence calculations. The phasing of the data is detected by means of Hilbert phase difference within the above mentioned windows. A statistical testing method is introduced that allows tuning the parameters of the windowing method in such a way that a predefined accuracy is reached. With this method the data of fifteen patients were examined in which we found the predicted correlation in each patient. Additionally it could be shown that the occurrence of a distinct correlation parameter, called scp, represents a predictive value of high quality for the patients outcome.
Detrended fluctuation analysis made flexible to detect range of cross-correlated fluctuations
Kwapień, Jarosław; Oświecimka, Paweł; DroŻdŻ, Stanisław
2015-11-01
The detrended cross-correlation coefficient ρDCCA has recently been proposed to quantify the strength of cross-correlations on different temporal scales in bivariate, nonstationary time series. It is based on the detrended cross-correlation and detrended fluctuation analyses (DCCA and DFA, respectively) and can be viewed as an analog of the Pearson coefficient in the case of the fluctuation analysis. The coefficient ρDCCA works well in many practical situations but by construction its applicability is limited to detection of whether two signals are generally cross-correlated, without the possibility to obtain information on the amplitude of fluctuations that are responsible for those cross-correlations. In order to introduce some related flexibility, here we propose an extension of ρDCCA that exploits the multifractal versions of DFA and DCCA: multifractal detrended fluctuation analysis and multifractal detrended cross-correlation analysis, respectively. The resulting new coefficient ρq not only is able to quantify the strength of correlations but also allows one to identify the range of detrended fluctuation amplitudes that are correlated in two signals under study. We show how the coefficient ρq works in practical situations by applying it to stochastic time series representing processes with long memory: autoregressive and multiplicative ones. Such processes are often used to model signals recorded from complex systems and complex physical phenomena like turbulence, so we are convinced that this new measure can successfully be applied in time-series analysis. In particular, we present an example of such application to highly complex empirical data from financial markets. The present formulation can straightforwardly be extended to multivariate data in terms of the q -dependent counterpart of the correlation matrices and then to the network representation.
Message Correlation Analysis Tool for NOvA
CERN. Geneva
2012-01-01
A complex running system, such as the NOvA online data acquisition, consists of a large number of distributed but closely interacting components. This paper describes a generic realtime correlation analysis and event identification engine, named Message Analyzer. Its purpose is to capture run time abnormalities and recognize system failures based on log messages from participating components. The initial design of analysis engine is driven by the DAQ of the NOvA experiment. The Message Analyzer performs filtering and pattern recognition on the log messages and reacts to system failures identified by associated triggering rules. The tool helps the system maintain a healthy running state and to minimize data corruption. This paper also describes a domain specific language that allows the recognition patterns and correlation rules to be specified in a clear and flexible way. In addition, the engine provides a plugin mechanism for users to implement specialized patterns or rules in generic languages such as C++.
Message Correlation Analysis Tool for NOvA
Lu Qiming; Biery, Kurt A; Kowalkowski, James B
2012-01-01
A complex running system, such as the NOvA online data acquisition, consists of a large number of distributed but closely interacting components. This paper describes a generic real-time correlation analysis and event identification engine, named Message Analyzer. Its purpose is to capture run time abnormalities and recognize system failures based on log messages from participating components. The initial design of analysis engine is driven by the data acquisition (DAQ) of the NOvA experiment. The Message Analyzer performs filtering and pattern recognition on the log messages and reacts to system failures identified by associated triggering rules. The tool helps the system maintain a healthy running state and to minimize data corruption. This paper also describes a domain specific language that allows the recognition patterns and correlation rules to be specified in a clear and flexible way. In addition, the engine provides a plugin mechanism for users to implement specialized patterns or rules in generic languages such as C++.
Message correlation analysis tool for NOvA
Lu, Qiming [Fermilab; Biery, Kurt A. [Fermilab; Kowalkowski, James B. [Fermilab
2012-01-01
A complex running system, such as the NOvA online data acquisition, consists of a large number of distributed but closely interacting components. This paper describes a generic real-time correlation analysis and event identification engine, named Message Analyzer. Its purpose is to capture run time abnormalities and recognize system failures based on log messages from participating components. The initial design of analysis engine is driven by the data acquisition (DAQ) of the NOvA experiment. The Message Analyzer performs filtering and pattern recognition on the log messages and reacts to system failures identified by associated triggering rules. The tool helps the system maintain a healthy running state and to minimize data corruption. This paper also describes a domain specific language that allows the recognition patterns and correlation rules to be specified in a clear and flexible way. In addition, the engine provides a plugin mechanism for users to implement specialized patterns or rules in generic languages such as C++.
Harmonic Analysis Associated with the Generalized Weinstein Operator
Ahmed Abouelaz
2015-11-01
Full Text Available In this paper we consider a generalized Weinstein operator ∆d,α,n on Rd−1×]0,∞[, which generalizes the Weinstein operator ∆d,α, we define the generalized Weinstein intertwining operator Rα,n which turn out to be transmutation operator between ∆d,α,n and the Laplacian operator ∆d. We build the dual of the generalized Weinstein intertwining operatortRα,n, another hand we prove the formula related Rα,n andtRα,n . We exploit these transmutation operators to develop a new harmonic analysis corresponding to ∆d,α,n.
Analysis of Cell Phone Usage Using Correlation Techniques
T S R MURTHY; D. SIVA RAMA KRISHNA
2011-01-01
The present paper is a sample survey analysis, examined based on correlation techniques. The usage ofmobile phones is clearly almost un-avoidable these days and as such the authors have made a systematicsurvey through a well prepared questionnaire on making use of mobile phones to the maximum extent.These samples are various economical groups across a population of over one-lakh people. The resultsare scientifically categorized and interpreted to match the ground reality.
Costa, Valter Magalhaes
2011-01-01
was trained and the results were satisfactory since the IEA-R1 Data Acquisition System reactor monitors 64 variables and, with a set of 9 input variables resulting from the correlation analysis, it was possible to monitor 51 variables using neural networks. (author)
Correlative SEM SERS for quantitative analysis of dimer nanoparticles.
Timmermans, F J; Lenferink, A T M; van Wolferen, H A G M; Otto, C
2016-11-14
A Raman microscope integrated with a scanning electron microscope was used to investigate plasmonic structures by correlative SEM-SERS analysis. The integrated Raman-SEM microscope combines high-resolution electron microscopy information with SERS signal enhancement from selected nanostructures with adsorbed Raman reporter molecules. Correlative analysis is performed for dimers of two gold nanospheres. Dimers were selected on the basis of SEM images from multi aggregate samples. The effect of the orientation of the dimer with respect to the polarization state of the laser light and the effect of the particle gap size on the Raman signal intensity is observed. Additionally, calculations are performed to simulate the electric near field enhancement. These simulations are based on the morphologies observed by electron microscopy. In this way the experiments are compared with the enhancement factor calculated with near field simulations and are subsequently used to quantify the SERS enhancement factor. Large differences between experimentally observed and calculated enhancement factors are regularly detected, a phenomenon caused by nanoscale differences between the real and 'simplified' simulated structures. Quantitative SERS experiments reveal the structure induced enhancement factor, ranging from ∼200 to ∼20 000, averaged over the full nanostructure surface. The results demonstrate correlative Raman-SEM microscopy for the quantitative analysis of plasmonic particles and structures, thus enabling a new analytical method in the field of SERS and plasmonics.
General Nature of Multicollinearity in Multiple Regression Analysis.
Liu, Richard
1981-01-01
Discusses multiple regression, a very popular statistical technique in the field of education. One of the basic assumptions in regression analysis requires that independent variables in the equation should not be highly correlated. The problem of multicollinearity and some of the solutions to it are discussed. (Author)
Structural dynamic analysis with generalized damping models analysis
Adhikari , Sondipon
2013-01-01
Since Lord Rayleigh introduced the idea of viscous damping in his classic work ""The Theory of Sound"" in 1877, it has become standard practice to use this approach in dynamics, covering a wide range of applications from aerospace to civil engineering. However, in the majority of practical cases this approach is adopted more for mathematical convenience than for modeling the physics of vibration damping. Over the past decade, extensive research has been undertaken on more general ""non-viscous"" damping models and vibration of non-viscously damped systems. This book, along with a related book
Correlation analysis between ceramic insulator pollution and acoustic emissions
Benjamín Álvarez-Nasrallah
2015-01-01
Full Text Available Most of the studies related to insulator pollution are normally performed based on individual analysis among leakage current, relative humidity and equivalent salt deposit density (ESDD. This paper presents a correlation analysis between the leakage current and the acoustic emissions measured in a 230 kV electrical substations in the city of Barranquilla, Colombia. Furthermore, atmospheric variables were considered to develop a characterization model of the insulator contamination process. This model was used to demonstrate that noise emission levels are a reliable indicator to detect and characterize pollution on high voltage insulators. The correlation found amount the atmospheric, electrical and sound variables allowed to determine the relations for the maintenance of ceramic insulators in high-polluted areas. In this article, the results on the behavior of the leakage current in ceramic insulators and the sound produced with different atmospheric conditions are shown, which allow evaluating the best time to clean the insulator at the substation. Furthermore, by experimentation on site and using statistical models, the correlation between ambient variables and the leakage current of insulators in an electrical substation was obtained. Some of the problems that bring the external noise were overcome using multiple microphones and specialized software that enabled properly filter the sound and better measure the variables.
Direct formulation to Cholesky decomposition of a general nonsingular correlation matrix.
Madar, Vered
2015-08-01
We present two novel and explicit parametrizations of Cholesky factor of a nonsingular correlation matrix. One that uses semi-partial correlation coefficients, and a second that utilizes differences between the successive ratios of two determinants. To each, we offer a useful application.
Kistner, Emily O.; Muller, Keith E.
2004-01-01
Intraclass correlation and Cronbach's alpha are widely used to describe reliability of tests and measurements. Even with Gaussian data, exact distributions are known only for compound symmetric covariance (equal variances and equal correlations). Recently, large sample Gaussian approximations were derived for the distribution functions. New exact…
Generalized linear models with random effects unified analysis via H-likelihood
Lee, Youngjo; Pawitan, Yudi
2006-01-01
Since their introduction in 1972, generalized linear models (GLMs) have proven useful in the generalization of classical normal models. Presenting methods for fitting GLMs with random effects to data, Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood explores a wide range of applications, including combining information over trials (meta-analysis), analysis of frailty models for survival data, genetic epidemiology, and analysis of spatial and temporal models with correlated errors.Written by pioneering authorities in the field, this reference provides an introduction to various theories and examines likelihood inference and GLMs. The authors show how to extend the class of GLMs while retaining as much simplicity as possible. By maximizing and deriving other quantities from h-likelihood, they also demonstrate how to use a single algorithm for all members of the class, resulting in a faster algorithm as compared to existing alternatives. Complementing theory with examples, many of...
Correlation analysis of the physiological factors controlling fundamental voice frequency.
Atkinson, J E
1978-01-01
A technique has been developed to obtain a quantitative measure of correlation between electromyographic (EMG) activity of various laryngeal muscles, subglottal air pressure, and the fundamental frequency of vibration of the vocal folds (Fo). Data were collected and analyzed on one subject, a native speaker of American English. The results show that an analysis of this type can provide a useful measure of correlation between the physiological and acoustical events in speech and, furthermore, can yield detailed insights into the organization and nature of the speech production process. In particular, based on these results, a model is suggested of Fo control involving laryngeal state functions that seems to agree with present knowledge of laryngeal control and experimental evidence.
On discriminant analysis techniques and correlation structures in high dimensions
Clemmensen, Line Katrine Harder
This paper compares several recently proposed techniques for performing discriminant analysis in high dimensions, and illustrates that the various sparse methods dier in prediction abilities depending on their underlying assumptions about the correlation structures in the data. The techniques...... the methods in two: Those who assume independence between the variables and thus use a diagonal estimate of the within-class covariance matrix, and those who assume dependence between the variables and thus use an estimate of the within-class covariance matrix, which also estimates the correlations between...... variables. The two groups of methods are compared and the pros and cons are exemplied using dierent cases of simulated data. The results illustrate that the estimate of the covariance matrix is an important factor with respect to choice of method, and the choice of method should thus be driven by the nature...
Costa, Valter Magalhaes; Pereira, Iraci Martinez, E-mail: valter.costa@usp.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)
2011-07-01
The monitoring of variables and diagnosis of sensor fault in nuclear power plants or processes industries is very important because a previous diagnosis allows the correction of the fault and, like this, to prevent the production stopped, improving operator's security and it's not provoking economics losses. The objective of this work is to build a set, using bivariate correlation and canonical correlation, which will be the set of input variables of an artificial neural network to monitor the greater number of variables. This methodology was applied to the IEA-R1 Research Reactor at IPEN. Initially, for the input set of neural network we selected the variables: nuclear power, primary circuit flow rate, control/safety rod position and difference in pressure in the core of the reactor, because almost whole of monitoring variables have relation with the variables early described or its effect can be result of the interaction of two or more. The nuclear power is related to the increasing and decreasing of temperatures as well as the amount radiation due fission of the uranium; the rods are controls of power and influence in the amount of radiation and increasing and decreasing of temperatures; the primary circuit flow rate has the function of energy transport by removing the nucleus heat. An artificial neural network was trained and the results were satisfactory since the IEA-R1 Data Acquisition System reactor monitors 64 variables and, with a set of 9 input variables resulting from the correlation analysis, it was possible to monitor 51 variables. (author)
Costa, Valter Magalhaes; Pereira, Iraci Martinez
2011-01-01
The monitoring of variables and diagnosis of sensor fault in nuclear power plants or processes industries is very important because a previous diagnosis allows the correction of the fault and, like this, to prevent the production stopped, improving operator's security and it's not provoking economics losses. The objective of this work is to build a set, using bivariate correlation and canonical correlation, which will be the set of input variables of an artificial neural network to monitor the greater number of variables. This methodology was applied to the IEA-R1 Research Reactor at IPEN. Initially, for the input set of neural network we selected the variables: nuclear power, primary circuit flow rate, control/safety rod position and difference in pressure in the core of the reactor, because almost whole of monitoring variables have relation with the variables early described or its effect can be result of the interaction of two or more. The nuclear power is related to the increasing and decreasing of temperatures as well as the amount radiation due fission of the uranium; the rods are controls of power and influence in the amount of radiation and increasing and decreasing of temperatures; the primary circuit flow rate has the function of energy transport by removing the nucleus heat. An artificial neural network was trained and the results were satisfactory since the IEA-R1 Data Acquisition System reactor monitors 64 variables and, with a set of 9 input variables resulting from the correlation analysis, it was possible to monitor 51 variables. (author)
Two-Dimensional Raman Correlation Analysis of Diseased Esophagus in a Rat
Takanezawa, Sota; Morita, Shin-ichi; Maruyama, Atsushi; Murakami, Takurou N.; Kawashima, Norimichi; Endo, Hiroyuki; Iijima, Katsunori; Asakura, Tohru; Shimosegawa, Tooru; Sato, Hidetoshi
2010-07-01
Generalized two-dimensional (2D) Raman correlation analysis effectively distinguished a benign tumor from normal tissue. Line profiling Raman spectra of a rat esophagus, including a benign tumor, were measured and the generalized 2D synchronous and asynchronous spectra were calculated. In the autocorrelation area of the amide I band of proteins in the asynchronous map, a cross-like pattern was observed. A simulation study indicated that the pattern was caused by a sharp band component in the amide I band region. We considered that the benign tumor corresponded to the sharp component.
Analysis of Lamellar Structures with Application of Generalized Functions
Kipiani Gela
2016-12-01
Full Text Available Theory of differential equations in respect of the functional area is based on the basic concepts on generalized functions and splines. There are some basic concepts related to the theory of generalized functions and their properties are considered in relation to the rod systems and lamellar structures. The application of generalized functions gives the possibility to effectively calculate step-variable stiffness lamellar structures. There are also widely applied structures, in that several in which a number of parallel load bearing layers are interconnected by discrete-elastic links. For analysis of system under study, such as design diagrams, there are applied discrete and discrete-continual models.
Protein structure similarity from principle component correlation analysis
Chou James
2006-01-01
Full Text Available Abstract Background Owing to rapid expansion of protein structure databases in recent years, methods of structure comparison are becoming increasingly effective and important in revealing novel information on functional properties of proteins and their roles in the grand scheme of evolutionary biology. Currently, the structural similarity between two proteins is measured by the root-mean-square-deviation (RMSD in their best-superimposed atomic coordinates. RMSD is the golden rule of measuring structural similarity when the structures are nearly identical; it, however, fails to detect the higher order topological similarities in proteins evolved into different shapes. We propose new algorithms for extracting geometrical invariants of proteins that can be effectively used to identify homologous protein structures or topologies in order to quantify both close and remote structural similarities. Results We measure structural similarity between proteins by correlating the principle components of their secondary structure interaction matrix. In our approach, the Principle Component Correlation (PCC analysis, a symmetric interaction matrix for a protein structure is constructed with relationship parameters between secondary elements that can take the form of distance, orientation, or other relevant structural invariants. When using a distance-based construction in the presence or absence of encoded N to C terminal sense, there are strong correlations between the principle components of interaction matrices of structurally or topologically similar proteins. Conclusion The PCC method is extensively tested for protein structures that belong to the same topological class but are significantly different by RMSD measure. The PCC analysis can also differentiate proteins having similar shapes but different topological arrangements. Additionally, we demonstrate that when using two independently defined interaction matrices, comparison of their maximum
Groen, E.A., E-mail: Evelyne.Groen@gmail.com [Wageningen University, P.O. Box 338, Wageningen 6700 AH (Netherlands); Heijungs, R. [Vrije Universiteit Amsterdam, De Boelelaan 1105, Amsterdam 1081 HV (Netherlands); Leiden University, Einsteinweg 2, Leiden 2333 CC (Netherlands)
2017-01-15
Life cycle assessment (LCA) is an established tool to quantify the environmental impact of a product. A good assessment of uncertainty is important for making well-informed decisions in comparative LCA, as well as for correctly prioritising data collection efforts. Under- or overestimation of output uncertainty (e.g. output variance) will lead to incorrect decisions in such matters. The presence of correlations between input parameters during uncertainty propagation, can increase or decrease the the output variance. However, most LCA studies that include uncertainty analysis, ignore correlations between input parameters during uncertainty propagation, which may lead to incorrect conclusions. Two approaches to include correlations between input parameters during uncertainty propagation and global sensitivity analysis were studied: an analytical approach and a sampling approach. The use of both approaches is illustrated for an artificial case study of electricity production. Results demonstrate that both approaches yield approximately the same output variance and sensitivity indices for this specific case study. Furthermore, we demonstrate that the analytical approach can be used to quantify the risk of ignoring correlations between input parameters during uncertainty propagation in LCA. We demonstrate that: (1) we can predict if including correlations among input parameters in uncertainty propagation will increase or decrease output variance; (2) we can quantify the risk of ignoring correlations on the output variance and the global sensitivity indices. Moreover, this procedure requires only little data. - Highlights: • Ignoring correlation leads to under- or overestimation of the output variance. • We demonstrated that the risk of ignoring correlation can be quantified. • The procedure proposed is generally applicable in life cycle assessment. • In some cases, ignoring correlation has a minimal effect on decision-making tools.
Jianhua Ni
2016-08-01
Full Text Available The spatial distribution of urban service facilities is largely constrained by the road network. In this study, network point pattern analysis and correlation analysis were used to analyze the relationship between road network and healthcare facility distribution. The weighted network kernel density estimation method proposed in this study identifies significant differences between the outside and inside areas of the Ming city wall. The results of network K-function analysis show that private hospitals are more evenly distributed than public hospitals, and pharmacy stores tend to cluster around hospitals along the road network. After computing the correlation analysis between different categorized hospitals and street centrality, we find that the distribution of these hospitals correlates highly with the street centralities, and that the correlations are higher with private and small hospitals than with public and large hospitals. The comprehensive analysis results could help examine the reasonability of existing urban healthcare facility distribution and optimize the location of new healthcare facilities.
MAGMA: generalized gene-set analysis of GWAS data.
de Leeuw, Christiaan A; Mooij, Joris M; Heskes, Tom; Posthuma, Danielle
2015-04-01
By aggregating data for complex traits in a biologically meaningful way, gene and gene-set analysis constitute a valuable addition to single-marker analysis. However, although various methods for gene and gene-set analysis currently exist, they generally suffer from a number of issues. Statistical power for most methods is strongly affected by linkage disequilibrium between markers, multi-marker associations are often hard to detect, and the reliance on permutation to compute p-values tends to make the analysis computationally very expensive. To address these issues we have developed MAGMA, a novel tool for gene and gene-set analysis. The gene analysis is based on a multiple regression model, to provide better statistical performance. The gene-set analysis is built as a separate layer around the gene analysis for additional flexibility. This gene-set analysis also uses a regression structure to allow generalization to analysis of continuous properties of genes and simultaneous analysis of multiple gene sets and other gene properties. Simulations and an analysis of Crohn's Disease data are used to evaluate the performance of MAGMA and to compare it to a number of other gene and gene-set analysis tools. The results show that MAGMA has significantly more power than other tools for both the gene and the gene-set analysis, identifying more genes and gene sets associated with Crohn's Disease while maintaining a correct type 1 error rate. Moreover, the MAGMA analysis of the Crohn's Disease data was found to be considerably faster as well.
Generalized fault tree analysis combined with state analysis
Caldarola, L.
1980-02-01
An analytical theory has been developed which allows one to calculate the occurrence probability of the top event of a fault tree with multistate (two or more than two states) components. It is shown that, in order to correctly describe a system with multistate components, a special type of boolean algebra is required. This is called 'boolean algebra with restrictions on variables' and its basic rules are the same as those of the traditional boolean algebra with some additional restrictions on the variables. These restrictions are extensively discussed in the paper. It is also shown that the boolean algebra with restrictions on variables facilitates the task of formally combining fault tree analysis with state analysis. The computer program MUSTAFA 1 based on the above theory has been developed. It can analyse fault trees of system containing statistically independent as well as dependent components with two or more than two states. MUSTAFA 1 can handle coherent as well as non coherent boolean functions. (orig.) 891 HP/orig. 892 MB [de
Partial correlation analysis method in ultrarelativistic heavy-ion collisions
Olszewski, Adam; Broniowski, Wojciech
2017-11-01
We argue that statistical data analysis of two-particle longitudinal correlations in ultrarelativistic heavy-ion collisions may be efficiently carried out with the technique of partial covariance. In this method, the spurious event-by-event fluctuations due to imprecise centrality determination are eliminated via projecting out the component of the covariance influenced by the centrality fluctuations. We bring up the relationship of the partial covariance to the conditional covariance. Importantly, in the superposition approach, where hadrons are produced independently from a collection of sources, the framework allows us to impose centrality constraints on the number of sources rather than hadrons, that way unfolding of the trivial fluctuations from statistical hadronization and focusing better on the initial-state physics. We show, using simulated data from hydrodynamics followed with statistical hadronization, that the technique is practical and very simple to use, giving insight into the correlations generated in the initial stage. We also discuss the issues related to separation of the short- and long-range components of the correlation functions and show that in our example the short-range component from the resonance decays is largely reduced by considering pions of the same sign. We demonstrate the method explicitly on the cases where centrality is determined with a single central control bin or with two peripheral control bins.
CORRELATION ANALYSIS OF THE AUDIT COMMITTEE AND STRUCTURAL INDICATORS
FÜLÖP MELINDA TIMEA
2014-02-01
Full Text Available The main role of corporate governance is to restore market confidence and in this process plays an important role the audit committee. The purpose of this case study is to analyze the correlations between the Audit Committee and structural indicators. Considering the achievement of the objectives proposed in this research, our research is based on a deductive approach from general aspects to particular aspects that combines quantitative and qualitative studies. Theoretical knowledge is used for a better understanding of a phenomenon and not for making assumptions. Thus, in order to achieve our study, we selected 25 companies listed on Berlin Stock Exchange. Following this study, we concluded that the role of the audit committee is crucial.
CORRELATION ANALYSIS OF THE AUDIT COMMITTEE AND PROFITABILITY INDICATORS
MELINDA TIMEA FÜLÖP
2013-10-01
Full Text Available The main role of corporate governance is to restore market confidence and in this process plays an important role the audit committee. The purpose of this case study is to analyze the correlations between the Audit Committee and profitability indicators. Considering the achievement of the objectives proposed in this research, our research is based on a deductive approach from general aspects to particular aspects that combines quantitative and qualitative studies. Theoretical knowledge is used for a better understanding of a phenomenon and not for making assumptions. Thus, in order to achieve our study, we selected 25 companies listed on Berlin Stock Exchange. Following this study, we concluded that the role of the audit committee is crucial.
Kim, Jibum; Shin, Hee-Choon; Rosen, Zohn; Kang, Jeong-han; Dykema, Jennifer; Muennig, Peter
2015-01-01
Privacy and confidentiality are often of great concern to respondents answering sensitive questions posed by interviewers. Using the 1993-2010 General Social Survey, we examined trends in the provision of social security numbers (SSNs) and correlates of those responses. Results indicate that the rate of SSN provision has declined over the past…
Automated modal parameter estimation using correlation analysis and bootstrap sampling
Yaghoubi, Vahid; Vakilzadeh, Majid K.; Abrahamsson, Thomas J. S.
2018-02-01
The estimation of modal parameters from a set of noisy measured data is a highly judgmental task, with user expertise playing a significant role in distinguishing between estimated physical and noise modes of a test-piece. Various methods have been developed to automate this procedure. The common approach is to identify models with different orders and cluster similar modes together. However, most proposed methods based on this approach suffer from high-dimensional optimization problems in either the estimation or clustering step. To overcome this problem, this study presents an algorithm for autonomous modal parameter estimation in which the only required optimization is performed in a three-dimensional space. To this end, a subspace-based identification method is employed for the estimation and a non-iterative correlation-based method is used for the clustering. This clustering is at the heart of the paper. The keys to success are correlation metrics that are able to treat the problems of spatial eigenvector aliasing and nonunique eigenvectors of coalescent modes simultaneously. The algorithm commences by the identification of an excessively high-order model from frequency response function test data. The high number of modes of this model provides bases for two subspaces: one for likely physical modes of the tested system and one for its complement dubbed the subspace of noise modes. By employing the bootstrap resampling technique, several subsets are generated from the same basic dataset and for each of them a model is identified to form a set of models. Then, by correlation analysis with the two aforementioned subspaces, highly correlated modes of these models which appear repeatedly are clustered together and the noise modes are collected in a so-called Trashbox cluster. Stray noise modes attracted to the mode clusters are trimmed away in a second step by correlation analysis. The final step of the algorithm is a fuzzy c-means clustering procedure applied to
Prevalence and Correlates of Self-Harm in the German General Population.
Astrid Müller
Full Text Available The study aimed at evaluating the psychometric properties of the German version of the Self- Harm Inventory (SHI and examining the lifetime prevalence and correlates of self-harm in a representative German population sample (N = 2,507; age mean = 48.79, SD = 18.11; range 14 to 94 years; 55.5% women using the SHI. All participants answered the German SHI, the short form of the Barratt Impulsiveness Scale (BIS-15, the ultra-brief Patient Health Questionnaire for Depression and Anxiety (PHQ-4, and provided sociodemographic information. The one-factorial structure of the SHI was replicated using a confirmatory factor analysis. Internal consistency coefficients were sufficient and in line with previous studies. Almost half of the sample (49% acknowledged at least one self-harming behavior over the life-span, most frequently indirect forms of self-harm. The rate of participants who engaged in at least one SHI behavior was higher among men than women (51.6% vs. 46.9%, respectively, χ2 = 5.38, p = 0.020. Higher SHI scores were related to younger age, male gender, living alone, more symptoms of anxiety and depression (PHQ-4, higher impulsivity scores (BIS-15, and suffering from obesity grade 2. Women engaged more often in discreet forms of self-harm than men, e.g., preventing wounds from healing, exercising an injury, starving, and abusing laxatives. In terms of other indirect self-harming behaviors, men admitted more often driving recklessly, being promiscuous and losing a job on purpose, while women reported more frequently engaging in emotionally abusive relationships. With respect to direct self-harm, women were more likely to endorse suicide attempts and cutting, while men admitted more often head-banging. The findings suggest that self-harm constitutes a common problem. Future longitudinal studies are required to examine the natural course, sociodemographic and psychopathological risk factors, as well as possible time-trends of self
Prevalence and Correlates of Self-Harm in the German General Population.
Müller, Astrid; Claes, Laurence; Smits, Dirk; Brähler, Elmar; de Zwaan, Martina
2016-01-01
The study aimed at evaluating the psychometric properties of the German version of the Self- Harm Inventory (SHI) and examining the lifetime prevalence and correlates of self-harm in a representative German population sample (N = 2,507; age mean = 48.79, SD = 18.11; range 14 to 94 years; 55.5% women) using the SHI. All participants answered the German SHI, the short form of the Barratt Impulsiveness Scale (BIS-15), the ultra-brief Patient Health Questionnaire for Depression and Anxiety (PHQ-4), and provided sociodemographic information. The one-factorial structure of the SHI was replicated using a confirmatory factor analysis. Internal consistency coefficients were sufficient and in line with previous studies. Almost half of the sample (49%) acknowledged at least one self-harming behavior over the life-span, most frequently indirect forms of self-harm. The rate of participants who engaged in at least one SHI behavior was higher among men than women (51.6% vs. 46.9%, respectively, χ2 = 5.38, p = 0.020). Higher SHI scores were related to younger age, male gender, living alone, more symptoms of anxiety and depression (PHQ-4), higher impulsivity scores (BIS-15), and suffering from obesity grade 2. Women engaged more often in discreet forms of self-harm than men, e.g., preventing wounds from healing, exercising an injury, starving, and abusing laxatives. In terms of other indirect self-harming behaviors, men admitted more often driving recklessly, being promiscuous and losing a job on purpose, while women reported more frequently engaging in emotionally abusive relationships. With respect to direct self-harm, women were more likely to endorse suicide attempts and cutting, while men admitted more often head-banging. The findings suggest that self-harm constitutes a common problem. Future longitudinal studies are required to examine the natural course, sociodemographic and psychopathological risk factors, as well as possible time-trends of self-harming behaviors in more
Nanoscale protein diffusion by STED-based pair correlation analysis.
Paolo Bianchini
Full Text Available We describe for the first time the combination between cross-pair correlation function analysis (pair correlation analysis or pCF and stimulated emission depletion (STED to obtain diffusion maps at spatial resolution below the optical diffraction limit (super-resolution. Our approach was tested in systems characterized by high and low signal to noise ratio, i.e. Capsid Like Particles (CLPs bearing several (>100 active fluorescent proteins and monomeric fluorescent proteins transiently expressed in living Chinese Hamster Ovary cells, respectively. The latter system represents the usual condition encountered in living cell studies on fluorescent protein chimeras. Spatial resolution of STED-pCF was found to be about 110 nm, with a more than twofold improvement over conventional confocal acquisition. We successfully applied our method to highlight how the proximity to nuclear envelope affects the mobility features of proteins actively imported into the nucleus in living cells. Remarkably, STED-pCF unveiled the existence of local barriers to diffusion as well as the presence of a slow component at distances up to 500-700 nm from either sides of nuclear envelope. The mobility of this component is similar to that previously described for transport complexes. Remarkably, all these features were invisible in conventional confocal mode.
Variational analysis and generalized differentiation I basic theory
Mordukhovich, Boris S
2006-01-01
Contains a study of the basic concepts and principles of variational analysis and generalized differentiation in both finite-dimensional and infinite-dimensional spaces. This title presents many applications to problems in optimization, equilibria, stability and sensitivity, control theory, economics, mechanics, and more.
Texture Analysis Using Rényi’s Generalized Entropies
Grigorescu, S.E.; Petkov, N.
2003-01-01
We propose a texture analysis method based on Rényi’s generalized entropies. The method aims at identifying texels in regular textures by searching for the smallest window through which the minimum number of different visual patterns is observed when moving the window over a given texture. The
Psychological treatment of generalized anxiety disorder: A meta-analysis.
Cuijpers, P.; Sijbrandij, M.; Koole, S.L.; Huibers, M.J.H.; Berking, M.; Andersson, G.
2014-01-01
Recent years have seen a near-doubling of the number of studies examining the effects of psychotherapies for generalized anxiety disorder (GAD) in adults. The present article integrates this new evidence with the older literature through a quantitative meta-analysis. A total of 41 studies (with 2132
Stability analysis for a general age-dependent vaccination model
El Doma, M.
1995-05-01
An SIR epidemic model of a general age-dependent vaccination model is investigated when the fertility, mortality and removal rates depends on age. We give threshold criteria of the existence of equilibriums and perform stability analysis. Furthermore a critical vaccination coverage that is sufficient to eradicate the disease is determined. (author). 12 refs
Yingjun Zheng
2016-11-01
Full Text Available Patients with schizophrenia exhibit consistent abnormalities in face-evoked N170. However, the relation between face-specific N170 abnormalities in schizophrenic patients and schizophrenia clinical characters, which probably based on common neural mechanisms, is still rarely discovered. Using event-related potentials (ERPs recording in both schizophrenic patients and healthy controls, the amplitude and latency of N170 were recorded when participants were passively watching face and non-face (table pictures. The results showed a face-specific N170 latency sluggishness in schizophrenic patients, i.e., the N170 latencies of schizophrenic patients were significantly longer than those of healthy controls under both upright face and inverted face conditions. Importantly, the face-related N170 latencies of the left temporo-occipital electrodes (P7 and PO7 were positively correlated with negative symptoms and general psychiatric symptoms. Besides the analysis of latencies, the N170 amplitudes became weaker in schizophrenic patients under both inverted face and inverted table conditions, with a left hemisphere dominant. More interestingly, the FIEs (the difference of N170 amplitudes between upright and inverted faces were absent in schizophrenic patients, which suggested the abnormality of holistic face processing. These results above revealed a marked symptom-relevant neural sluggishness of face-specific processing in schizophrenic patients, supporting the demyelinating hypothesis of schizophrenia.
Using general-purpose compression algorithms for music analysis
Louboutin, Corentin; Meredith, David
2016-01-01
General-purpose compression algorithms encode files as dictionaries of substrings with the positions of these strings’ occurrences. We hypothesized that such algorithms could be used for pattern discovery in music. We compared LZ77, LZ78, Burrows–Wheeler and COSIATEC on classifying folk song...... in the input data, COSIATEC outperformed LZ77 with a mean F1 score of 0.123, compared with 0.053 for LZ77. However, when the music was processed a voice at a time, the F1 score for LZ77 more than doubled to 0.124. We also discovered a significant correlation between compression factor and F1 score for all...
Solar activity and terrestrial climate: an analysis of some purported correlations
Laut, Peter
2003-01-01
claimed to support solar hypotheses. My analyses show that the apparent strong correlations displayed on these graphs have been obtained by an incorrect handling of the physical data. Since the graphs are still widely referred to in the literature and their misleading character has not yet been generally......The last decade has seen a revival of various hypotheses claiming a strong correlation between solar activity and a number of terrestrial climate parameters: Links between cosmic rays and cloud cover, first total cloud cover and then only low clouds, and between solar cycle lengths and Northern...... the existence of important links between solar activity and terrestrial climate. Such links have over the years been demonstrated by many authors. The sole objective of the present analysis is to draw attention to the fact that some of the widely publicized, apparent correlations do not properly reflect...
Linearized spectrum correlation analysis for line emission measurements.
Nishizawa, T; Nornberg, M D; Den Hartog, D J; Sarff, J S
2017-08-01
A new spectral analysis method, Linearized Spectrum Correlation Analysis (LSCA), for charge exchange and passive ion Doppler spectroscopy is introduced to provide a means of measuring fast spectral line shape changes associated with ion-scale micro-instabilities. This analysis method is designed to resolve the fluctuations in the emission line shape from a stationary ion-scale wave. The method linearizes the fluctuations around a time-averaged line shape (e.g., Gaussian) and subdivides the spectral output channels into two sets to reduce contributions from uncorrelated fluctuations without averaging over the fast time dynamics. In principle, small fluctuations in the parameters used for a line shape model can be measured by evaluating the cross spectrum between different channel groupings to isolate a particular fluctuating quantity. High-frequency ion velocity measurements (100-200 kHz) were made by using this method. We also conducted simulations to compare LSCA with a moment analysis technique under a low photon count condition. Both experimental and synthetic measurements demonstrate the effectiveness of LSCA.
Jung, Young Mee
2003-01-01
Principal component analysis based two-dimensional (PCA-2D) correlation analysis is applied to FTIR spectra of polystyrene/methyl ethyl ketone/toluene solution mixture during the solvent evaporation. Substantial amount of artificial noise were added to the experimental data to demonstrate the practical noise-suppressing benefit of PCA-2D technique. 2D correlation analysis of the reconstructed data matrix from PCA loading vectors and scores successfully extracted only the most important features of synchronicity and asynchronicity without interference from noise or insignificant minor components. 2D correlation spectra constructed with only one principal component yield strictly synchronous response with no discernible a asynchronous features, while those involving at least two or more principal components generated meaningful asynchronous 2D correlation spectra. Deliberate manipulation of the rank of the reconstructed data matrix, by choosing the appropriate number and type of PCs, yields potentially more refined 2D correlation spectra
The cross-correlation analysis of multi property of stock markets based on MM-DFA
Yang, Yujun; Li, Jianping; Yang, Yimei
2017-09-01
In this paper, we propose a new method called DH-MXA based on distribution histograms of Hurst surface and multiscale multifractal detrended fluctuation analysis. The method allows us to investigate the cross-correlation characteristics among multiple properties of different stock time series. It may provide a new way of measuring the nonlinearity of several signals. It also can provide a more stable and faithful description of cross-correlation of multiple properties of stocks. The DH-MXA helps us to present much richer information than multifractal detrented cross-correlation analysis and allows us to assess many universal and subtle cross-correlation characteristics of stock markets. We show DH-MXA by selecting four artificial data sets and five properties of four stock time series from different countries. The results show that our proposed method can be adapted to investigate the cross-correlation of stock markets. In general, the American stock markets are more mature and less volatile than the Chinese stock markets.
Multi-loop correlators for rational theories of 2D gravity from the generalized Kontsevich models
Kristjansen, C.
1994-01-01
functions of the susceptibilities and the eigenvalues of the external field. We furthermore use the moment technique to derive a closed expression for the genus zero multi-loop correlators for $(3,3m-1)$ and $(3,3m-2)$ rational matter fields coupled to gravity. We comment on the relation between the two-matrix...
Investigations of a thermal plasma jet structure by generalized correlation dimension
Gruber, Jan; Hlína, Jan; Šonský, Jiří
2013-01-01
Roč. 46, č. 1 (2013), s. 1-8 ISSN 0022-3727 Institutional research plan: CEZ:AV0Z20570509 Keywords : correlation dimension * turbulence * thermal plasma Subject RIV: BL - Plasma and Gas Discharge Physics Impact factor: 2.521, year: 2013
Nasution, I. K.; Lubis, N. D. A.; Amelia, S.; Hocin, K.
2018-03-01
Low back pain (LBP) is a world health problems and a major cause of disability. The study is to determine the correlation between pain intensity and quality of life (QoL) in patients with chronic LBP. This study was a descriptive, analytical research with the cross sectional design. Twenty-nine chronic LBP outpatients that have visited the Neurology Clinic of Adam Malik General Hospital Medan. Patients from July to November 2015 were selected by consecutive sampling. A questionnaire and interview are asking the information about subjects’ characteristics, diagnosis, medical history, pain intensity and quality of life-based on WHO QoL criteria were used to collect the data. Using Spearman correlation test, we found correlation among VAS and physical function (pphysical problems (phealth (p=0.040, r=-0.330). On the other hand, there was no correlation between VAS and mental health (p=0.110, r=-0.235). We concluded that pain intensity in outpatients with chronic LBP in the Neurology Clinic at Adam Malik General Hospital Medan correlates with the patients’ quality of life.
Extreme learning machine for ranking: generalization analysis and applications.
Chen, Hong; Peng, Jiangtao; Zhou, Yicong; Li, Luoqing; Pan, Zhibin
2014-05-01
The extreme learning machine (ELM) has attracted increasing attention recently with its successful applications in classification and regression. In this paper, we investigate the generalization performance of ELM-based ranking. A new regularized ranking algorithm is proposed based on the combinations of activation functions in ELM. The generalization analysis is established for the ELM-based ranking (ELMRank) in terms of the covering numbers of hypothesis space. Empirical results on the benchmark datasets show the competitive performance of the ELMRank over the state-of-the-art ranking methods. Copyright © 2014 Elsevier Ltd. All rights reserved.
Foster, S; Mohler-Kuo, M
2018-06-01
Previous research failed to uncover a replicable dimensional structure underlying the symptoms of depression. We aimed to examine two neglected methodological issues in this research: (a) adjusting symptom correlations for overall depression severity; and (b) analysing general population samples v. subsamples of currently depressed individuals. Using population-based cross-sectional and longitudinal data from two nations (Switzerland, 5883 young men; USA, 2174 young men and 2244 young women) we assessed the dimensions of the nine DSM-IV depression symptoms in young adults. In each general-population sample and each subsample of currently depressed participants, we conducted a standardised process of three analytical steps, based on exploratory and confirmatory factor and bifactor analysis, to reveal any replicable dimensional structure underlying symptom correlations while controlling for overall depression severity. We found no evidence of a replicable dimensional structure across samples when adjusting symptom correlations for overall depression severity. In the general-population samples, symptoms correlated strongly and a single dimension of depression severity was revealed. Among depressed participants, symptom correlations were surprisingly weak and no replicable dimensions were identified, regardless of severity-adjustment. First, caution is warranted when considering studies assessing dimensions of depression because general population-based studies and studies of depressed individuals generate different data that can lead to different conclusions. This problem likely generalises to other models based on the symptoms' inter-relationships such as network models. Second, whereas the overall severity aligns individuals on a continuum of disorder intensity that allows non-affected individuals to be distinguished from affected individuals, the clinical evaluation and treatment of depressed individuals should focus directly on each individual's symptom profile.
Comparison of correlation analysis techniques for irregularly sampled time series
K. Rehfeld
2011-06-01
Full Text Available Geoscientific measurements often provide time series with irregular time sampling, requiring either data reconstruction (interpolation or sophisticated methods to handle irregular sampling. We compare the linear interpolation technique and different approaches for analyzing the correlation functions and persistence of irregularly sampled time series, as Lomb-Scargle Fourier transformation and kernel-based methods. In a thorough benchmark test we investigate the performance of these techniques.
All methods have comparable root mean square errors (RMSEs for low skewness of the inter-observation time distribution. For high skewness, very irregular data, interpolation bias and RMSE increase strongly. We find a 40 % lower RMSE for the lag-1 autocorrelation function (ACF for the Gaussian kernel method vs. the linear interpolation scheme,in the analysis of highly irregular time series. For the cross correlation function (CCF the RMSE is then lower by 60 %. The application of the Lomb-Scargle technique gave results comparable to the kernel methods for the univariate, but poorer results in the bivariate case. Especially the high-frequency components of the signal, where classical methods show a strong bias in ACF and CCF magnitude, are preserved when using the kernel methods.
We illustrate the performances of interpolation vs. Gaussian kernel method by applying both to paleo-data from four locations, reflecting late Holocene Asian monsoon variability as derived from speleothem δ^{18}O measurements. Cross correlation results are similar for both methods, which we attribute to the long time scales of the common variability. The persistence time (memory is strongly overestimated when using the standard, interpolation-based, approach. Hence, the Gaussian kernel is a reliable and more robust estimator with significant advantages compared to other techniques and suitable for large scale application to paleo-data.
Meconium microbiome analysis identifies bacteria correlated with premature birth.
Alexandria N Ardissone
Full Text Available Preterm birth is the second leading cause of death in children under the age of five years worldwide, but the etiology of many cases remains enigmatic. The dogma that the fetus resides in a sterile environment is being challenged by recent findings and the question has arisen whether microbes that colonize the fetus may be related to preterm birth. It has been posited that meconium reflects the in-utero microbial environment. In this study, correlations between fetal intestinal bacteria from meconium and gestational age were examined in order to suggest underlying mechanisms that may contribute to preterm birth.Meconium from 52 infants ranging in gestational age from 23 to 41 weeks was collected, the DNA extracted, and 16S rRNA analysis performed. Resulting taxa of microbes were correlated to clinical variables and also compared to previous studies of amniotic fluid and other human microbiome niches.Increased detection of bacterial 16S rRNA in meconium of infants of <33 weeks gestational age was observed. Approximately 61·1% of reads sequenced were classified to genera that have been reported in amniotic fluid. Gestational age had the largest influence on microbial community structure (R = 0·161; p = 0·029, while mode of delivery (C-section versus vaginal delivery had an effect as well (R = 0·100; p = 0·044. Enterobacter, Enterococcus, Lactobacillus, Photorhabdus, and Tannerella, were negatively correlated with gestational age and have been reported to incite inflammatory responses, suggesting a causative role in premature birth.This provides the first evidence to support the hypothesis that the fetal intestinal microbiome derived from swallowed amniotic fluid may be involved in the inflammatory response that leads to premature birth.
Bai, Libiao; Wang, Hailing; Shi, Chunming; Du, Qiang; Li, Yi
2017-10-25
Traditional rural residential construction has the problems of high energy consumption and severe pollution. In general, with sustainable development in the construction industry, rural residential construction should be aimed towards low energy consumption and low carbon emissions. To help achieve this objective, in this paper, we evaluated four different possible building structures using AHP-Grey Correlation Analysis, which consists of the Analytic Hierarchy Process (AHP) and the Grey Correlation Analysis. The four structures included the traditional and currently widely used brick and concrete structure, as well as structure insulated panels (SIPs). Comparing the performances of economic benefit and carbon emission, the conclusion that SIPs have the best overall performance can be obtained, providing a reference to help builders choose the most appropriate building structure in rural China.
Forecast Correlation Coefficient Matrix of Stock Returns in Portfolio Analysis
Zhao, Feng
2013-01-01
In Modern Portfolio Theory, the correlation coefficients decide the risk of a set of stocks in the portfolio. So, to understand the correlation coefficients between returns of stocks, is a challenge but is very important for the portfolio management. Usually, the stocks with small correlation coefficients or even negative correlation coefficients are preferred. One can calculate the correlation coefficients of stock returns based on the historical stock data. However, in order to control the ...
Generalized Whittle-Matern random field as a model of correlated fluctuations
Lim, S C; Teo, L P
2009-01-01
This paper considers a generalization of the Gaussian random field with covariance function of the Whittle-Matern family. Such a random field can be obtained as the solution to the fractional stochastic differential equation with two fractional orders. Asymptotic properties of the covariance functions belonging to this generalized Whittle-Matern family are studied, which are used to deduce the sample path properties of the random field. The Whittle-Matern field has been widely used in modeling geostatistical data such as sea beam data, wind speed, field temperature and soil data. In this paper we show that the generalized Whittle-Matern field provides a more flexible model for wind speed data
Tutorial on Biostatistics: Linear Regression Analysis of Continuous Correlated Eye Data.
Ying, Gui-Shuang; Maguire, Maureen G; Glynn, Robert; Rosner, Bernard
2017-04-01
To describe and demonstrate appropriate linear regression methods for analyzing correlated continuous eye data. We describe several approaches to regression analysis involving both eyes, including mixed effects and marginal models under various covariance structures to account for inter-eye correlation. We demonstrate, with SAS statistical software, applications in a study comparing baseline refractive error between one eye with choroidal neovascularization (CNV) and the unaffected fellow eye, and in a study determining factors associated with visual field in the elderly. When refractive error from both eyes were analyzed with standard linear regression without accounting for inter-eye correlation (adjusting for demographic and ocular covariates), the difference between eyes with CNV and fellow eyes was 0.15 diopters (D; 95% confidence interval, CI -0.03 to 0.32D, p = 0.10). Using a mixed effects model or a marginal model, the estimated difference was the same but with narrower 95% CI (0.01 to 0.28D, p = 0.03). Standard regression for visual field data from both eyes provided biased estimates of standard error (generally underestimated) and smaller p-values, while analysis of the worse eye provided larger p-values than mixed effects models and marginal models. In research involving both eyes, ignoring inter-eye correlation can lead to invalid inferences. Analysis using only right or left eyes is valid, but decreases power. Worse-eye analysis can provide less power and biased estimates of effect. Mixed effects or marginal models using the eye as the unit of analysis should be used to appropriately account for inter-eye correlation and maximize power and precision.
Brillouin optical correlation domain analysis in composite material beams
Stern, Yonatan; London, Yosef; Preter, Eyal
2017-01-01
Structural health monitoring is a critical requirement in many composites. Numerous monitoring strategies rely on measurements of temperature or strain (or both), however these are often restricted to point-sensing or to the coverage of small areas. Spatially-continuous data can be obtained...... with optical fiber sensors. In this work, we report high-resolution distributed Brillouin sensing over standard fibers that are embedded in composite structures. A phase-coded, Brillouin optical correlation domain analysis (B-OCDA) protocol was employed, with spatial resolution of 2 cm and sensitivity of 1 °K...... or 20 micro-strain. A portable measurement setup was designed and assembled on the premises of a composite structures manufacturer. The setup was successfully utilized in several structural health monitoring scenarios: (a) monitoring the production and curing of a composite beam over 60 h; (b...
A Visual Analytics Approach for Correlation, Classification, and Regression Analysis
Steed, Chad A [ORNL; SwanII, J. Edward [Mississippi State University (MSU); Fitzpatrick, Patrick J. [Mississippi State University (MSU); Jankun-Kelly, T.J. [Mississippi State University (MSU)
2012-02-01
New approaches that combine the strengths of humans and machines are necessary to equip analysts with the proper tools for exploring today's increasing complex, multivariate data sets. In this paper, a novel visual data mining framework, called the Multidimensional Data eXplorer (MDX), is described that addresses the challenges of today's data by combining automated statistical analytics with a highly interactive parallel coordinates based canvas. In addition to several intuitive interaction capabilities, this framework offers a rich set of graphical statistical indicators, interactive regression analysis, visual correlation mining, automated axis arrangements and filtering, and data classification techniques. The current work provides a detailed description of the system as well as a discussion of key design aspects and critical feedback from domain experts.
Generalized virial theorem and pressure relation for a strongly correlated Fermi gas
Tan, Shina
2008-01-01
For a two-component Fermi gas in the unitarity limit (i.e., with infinite scattering length), there is a well-known virial theorem, first shown by J.E. Thomas et al. A few people rederived this result, and extended it to few-body systems, but their results are all restricted to the unitarity limit. Here I show that there is a generalized virial theorem for FINITE scattering lengths. I also generalize an exact result concerning the pressure to the case of imbalanced populations
Reduced density matrix embedding. General formalism and inter-domain correlation functional.
Pernal, Katarzyna
2016-08-03
An embedding method for a one-electron reduced density matrix (1-RDM) is proposed. It is based on partitioning of 1-RDM into domains and describing each domain in the effective potential of the other ones. To assure N-representability of the total 1-RDM N-representability and strong-orthogonality conditions are imposed on the domains. The total energy is given as a sum of single-domain energies and domain-domain electron interaction contributions. Higher than two-body inter-domain interaction terms are neglected. The two-body correlation terms are approximated by deriving inter-domain correlation from couplings of density fluctuations of two domains at a time. Unlike in most density embedding methods kinetic energy is treated exactly and it is not required that densities pertaining to the domains are only weakly overlapping. We propose to treat each domain by a corrected perfect-pairing functional. On a few examples it is shown that the embedding reduced density matrix functional method (ERDMF) yields excellent results for molecules that are well described by a single Lewis structure even if strong static intra-domain or dynamic inter-domain correlation effects must be accounted for.
Application of generalized function to dynamic analysis of thick plates
Zheng, D.; Weng, Z.
1987-01-01
The structures with thick plates have been used extensively in national defence, mechanical engineering, chemical engineering, nuclear engineering, civil engineering, etc.. Various theories have been established to deal with the problems of elastic plates, which include the classical theory of thin plates, the improved theory of thick plates, three-dimensional elastical theory. In this paper, the derivative of δ-function is handled by using the generalized function. The dynamic analysis of thick plates subjected the concentrated load is presented. The improved Donnell's equation of thick plates is deduced and employed as the basic equation. The generalized coordinates are solved by using the method of MWR. The general expressions for the dynamic response of elastic thick plates subjected the concentrated load are given. The numerical results for rectangular plates are given herein. The results are compared with those obtained from the improved theory and the classical theory of plates. (orig./GL)
Generalized concavity in fuzzy optimization and decision analysis
Ramík, Jaroslav
2002-01-01
Convexity of sets in linear spaces, and concavity and convexity of functions, lie at the root of beautiful theoretical results that are at the same time extremely useful in the analysis and solution of optimization problems, including problems of either single objective or multiple objectives. Not all of these results rely necessarily on convexity and concavity; some of the results can guarantee that each local optimum is also a global optimum, giving these methods broader application to a wider class of problems. Hence, the focus of the first part of the book is concerned with several types of generalized convex sets and generalized concave functions. In addition to their applicability to nonconvex optimization, these convex sets and generalized concave functions are used in the book's second part, where decision-making and optimization problems under uncertainty are investigated. Uncertainty in the problem data often cannot be avoided when dealing with practical problems. Errors occur in real-world data for...
Dehbi, A.
2015-01-01
In the past several decades, experimentalists have proposed a large number of correlations to estimate steam condensation rates in the presence of noncondensable gases in free convection regimes. These correlations are largely empirical, and usually of limited scope, which often leads to their use outside their range of validity, thus incurring the risk of significant errors. In this investigation, we disregard the correlations altogether, and instead go back to their underlying original data, consolidate them in a single set, and propose a generalized correlation that is compatible with the heat and mass transfer analogy. This best-estimate correlation for steam-air mixtures, based on six different investigations and 350 data points, covers two orders of magnitude in the heat transfer coefficient, and is valid for pressures up to 20 bars and steam mass fraction from 0.1 to 0.95. The consolidated raw data are self-consistent and collapse around a curve with a standard deviation of 16 %, thus well within typical experimental error bands. This demonstrates that there is no physical justification for the large deviations (factor 2 or more) observed sometimes when one compares the heat transfer coefficients predicted by different empirical correlations. (author)
Ravigururajan, T.S.; Bergles, A.E.
1985-01-01
General correlations for friction factors and heat transfer coefficients for single-phase turbulent flow in internally ribbed tubes are presented. Data from previous investigations are gathered for a wide range of tube parameters with e/d: 0.01 to 0.2; p/d: 0.1 to 7.0; α/90: 0.3 to 1.0, and flow parameters Re: 5000 to 250,000 and Pr: 0.66 to 37.6. The data were applied to a linear model to get normalized correlations that were then modified to fit tubes with extremely small parametric values. A shape function was included in the friction correlation to account for different rib profiles. The friction correlation predicts 96% of the data base to within +. 50% and 77% of the data base to within +. 20%. Corresponding figures for the heat transfer correlation are 99% and 69%. The present correlations are superior, for this extensive data base, to those presented by other investigators
Current Density Functional Theory Using Meta-Generalized Gradient Exchange-Correlation Functionals.
Furness, James W; Verbeke, Joachim; Tellgren, Erik I; Stopkowicz, Stella; Ekström, Ulf; Helgaker, Trygve; Teale, Andrew M
2015-09-08
We present the self-consistent implementation of current-dependent (hybrid) meta-generalized gradient approximation (mGGA) density functionals using London atomic orbitals. A previously proposed generalized kinetic energy density is utilized to implement mGGAs in the framework of Kohn-Sham current density functional theory (KS-CDFT). A unique feature of the nonperturbative implementation of these functionals is the ability to seamlessly explore a wide range of magnetic fields up to 1 au (∼235 kT) in strength. CDFT functionals based on the TPSS and B98 forms are investigated, and their performance is assessed by comparison with accurate coupled-cluster singles, doubles, and perturbative triples (CCSD(T)) data. In the weak field regime, magnetic properties such as magnetizabilities and nuclear magnetic resonance shielding constants show modest but systematic improvements over generalized gradient approximations (GGA). However, in the strong field regime, the mGGA-based forms lead to a significantly improved description of the recently proposed perpendicular paramagnetic bonding mechanism, comparing well with CCSD(T) data. In contrast to functionals based on the vorticity, these forms are found to be numerically stable, and their accuracy at high field suggests that the extension of mGGAs to CDFT via the generalized kinetic energy density should provide a useful starting point for further development of CDFT approximations.
Tritium analysis of urine samples from the general Korean public.
Yoon, Seokwon; Ha, Wi-Ho; Lee, Seung-Sook
2013-11-01
The tritium concentrations of urine samples and the effective dose of the general Korean public were evaluated. To achieve accurate HTO analysis of urine samples, we established the optimal conditions for measuring the HTO content of urine samples. Urine samples from 50 Koreans who do not work at a nuclear facility were analyzed on the basis of the results. The average urine analysis result was 2.8 ±1 .4 Bq/L, and the range was 1.8-5.6 Bq/L. The measured values were lower than those reported for other countries. These results show that environmental factors and lifestyle differences are the main factors affecting the tritium level of the general public. © 2013 Elsevier Ltd. All rights reserved.
A general numerical analysis of the superconducting quasiparticle mixer
Hicks, R. G.; Feldman, M. J.; Kerr, A. R.
1985-01-01
For very low noise millimeter-wave receivers, the superconductor-insulator-superconductor (SIS) quasiparticle mixer is now competitive with conventional Schottky mixers. Tucker (1979, 1980) has developed a quantum theory of mixing which has provided a basis for the rapid improvement in SIS mixer performance. The present paper is concerned with a general method of numerical analysis for SIS mixers which allows arbitrary terminating impedances for all the harmonic frequencies. This analysis provides an approach for an examination of the range of validity of the three-frequency results of the quantum mixer theory. The new method has been implemented with the aid of a Fortran computer program.
General overview and perspectives of risk analysis in Cuba
Torres, A.; Rodriguez, J.M.; Vilaragut, J.J.; Valhuerdi, C.
1995-01-01
This papers shows a general overview of the application of risk analysis techniques in some potentially dangerous industries in Cuba. This paper summarizes the experiences of these sectors in the risk analysis with different specification levels and different approaches. Some experiences in the application of these analyses in the nuclear and aeronautical industries are shown. Some analyses of consequences in cases of accidents in the chemical industries in order to work due and improve emergency plans for responding to accident situations are presented in a more succinct manner. Also the perspectives to develop some of these tendencies and cooperation forms between them are summarized
A general numerical analysis program for the superconducting quasiparticle mixer
Hicks, R. G.; Feldman, M. J.; Kerr, A. R.
1986-01-01
A user-oriented computer program SISCAP (SIS Computer Analysis Program) for analyzing SIS mixers is described. The program allows arbitrary impedance terminations to be specified at all LO harmonics and sideband frequencies. It is therefore able to treat a much more general class of SIS mixers than the widely used three-frequency analysis, for which the harmonics are assumed to be short-circuited. An additional program, GETCHI, provides the necessary input data to program SISCAP. The SISCAP program performs a nonlinear analysis to determine the SIS junction voltage waveform produced by the local oscillator. The quantum theory of mixing is used in its most general form, treating the large signal properties of the mixer in the time domain. A small signal linear analysis is then used to find the conversion loss and port impedances. The noise analysis includes thermal noise from the termination resistances and shot noise from the periodic LO current. Quantum noise is not considered. Many aspects of the program have been adequately verified and found accurate.
MK Fakhri
2012-07-01
Full Text Available
Background and Objectives: Medical students are a particular class of students that Because of their specific problems, investigation of their general health has always been considered. This study is concerned with investigation of relationship between general health and emotional intelligence and creativity in medical college students at Islamic Azad University, Sari branch.
Methods: 150 medical college students at Islamic Azad University, Sari branch (45 males and 105 females, were randomly selected and Goldberg general health, Shring emotional intelligence and Abedi creativity questionnaire were completed. For data analysis, Pearson correlation and independent t-test were used.
Results: Results showed that: there is positive relationship between general health and emotional intelligence (r=0.53 and p<0.05, there is a positive relationship between general health and creativity (r=0.60 and p<0.01, and female college students are healthier than males (p<0.05.
Conclusion: results of this research indicated that there is a positive relationship between general health and emotional intelligence and creativity, and since these variables are effective in professional prospect of Medical students, employing cognitive and behavioral methods in promotion of general health in these students seem necessary.
Brillouin Optical Correlation Domain Analysis in Composite Material Beams
Yonatan Stern
2017-10-01
Full Text Available Structural health monitoring is a critical requirement in many composites. Numerous monitoring strategies rely on measurements of temperature or strain (or both, however these are often restricted to point-sensing or to the coverage of small areas. Spatially-continuous data can be obtained with optical fiber sensors. In this work, we report high-resolution distributed Brillouin sensing over standard fibers that are embedded in composite structures. A phase-coded, Brillouin optical correlation domain analysis (B-OCDA protocol was employed, with spatial resolution of 2 cm and sensitivity of 1 °K or 20 micro-strain. A portable measurement setup was designed and assembled on the premises of a composite structures manufacturer. The setup was successfully utilized in several structural health monitoring scenarios: (a monitoring the production and curing of a composite beam over 60 h; (b estimating the stiffness and Young’s modulus of a composite beam; and (c distributed strain measurements across the surfaces of a model wing of an unmanned aerial vehicle. The measurements are supported by the predictions of structural analysis calculations. The results illustrate the potential added values of high-resolution, distributed Brillouin sensing in the structural health monitoring of composites.
Brillouin Optical Correlation Domain Analysis in Composite Material Beams.
Stern, Yonatan; London, Yosef; Preter, Eyal; Antman, Yair; Diamandi, Hilel Hagai; Silbiger, Maayan; Adler, Gadi; Levenberg, Eyal; Shalev, Doron; Zadok, Avi
2017-10-02
Structural health monitoring is a critical requirement in many composites. Numerous monitoring strategies rely on measurements of temperature or strain (or both), however these are often restricted to point-sensing or to the coverage of small areas. Spatially-continuous data can be obtained with optical fiber sensors. In this work, we report high-resolution distributed Brillouin sensing over standard fibers that are embedded in composite structures. A phase-coded, Brillouin optical correlation domain analysis (B-OCDA) protocol was employed, with spatial resolution of 2 cm and sensitivity of 1 °K or 20 micro-strain. A portable measurement setup was designed and assembled on the premises of a composite structures manufacturer. The setup was successfully utilized in several structural health monitoring scenarios: (a) monitoring the production and curing of a composite beam over 60 h; (b) estimating the stiffness and Young's modulus of a composite beam; and (c) distributed strain measurements across the surfaces of a model wing of an unmanned aerial vehicle. The measurements are supported by the predictions of structural analysis calculations. The results illustrate the potential added values of high-resolution, distributed Brillouin sensing in the structural health monitoring of composites.
Interactive Correlation Analysis and Visualization of Climate Data
Ma, Kwan-Liu [Univ. of California, Davis, CA (United States)
2016-09-21
The relationship between our ability to analyze and extract insights from visualization of climate model output and the capability of the available resources to make those visualizations has reached a crisis point. The large volume of data currently produced by climate models is overwhelming the current, decades-old visualization workflow. The traditional methods for visualizing climate output also have not kept pace with changes in the types of grids used, the number of variables involved, and the number of different simulations performed with a climate model or the feature-richness of high-resolution simulations. This project has developed new and faster methods for visualization in order to get the most knowledge out of the new generation of high-resolution climate models. While traditional climate images will continue to be useful, there is need for new approaches to visualization and analysis of climate data if we are to gain all the insights available in ultra-large data sets produced by high-resolution model output and ensemble integrations of climate models such as those produced for the Coupled Model Intercomparison Project. Towards that end, we have developed new visualization techniques for performing correlation analysis. We have also introduced highly scalable, parallel rendering methods for visualizing large-scale 3D data. This project was done jointly with climate scientists and visualization researchers at Argonne National Laboratory and NCAR.
Rosenkranz, Tabea; Müller, Kai W; Dreier, Michael; Beutel, Manfred E; Wölfling, Klaus
2017-01-01
This paper examines the addictive potential of 8 different Internet applications, distinguishing male and female users. Moreover, differential correlates of problematic use are investigated in Internet gamers (IG) and generalized Internet users (GIU). In a representative sample of 5,667 adolescents aged 12-19 years, use of Internet applications, problematic Internet use, psychopathologic symptoms (emotional problems, hyperactivity/inattention, and psychosomatic complaints), personality (conscientiousness and extraversion), psychosocial correlates (perceived stress and self-efficacy), and coping strategies were assessed. The addictive potential of Internet applications was examined in boys and girls using regression analysis. MANOVAs were conducted to examine differential correlates of problematic Internet use between IG and GIU. Chatting and social networking most strongly predicted problematic Internet use in girls, while gaming was the strongest predictor in boys. Problematic IG exhibited multiple psychosocial problems compared to non-problematic IG. In problematic Internet users, GIU reported even higher psychosocial burden and displayed dysfunctional coping strategies more frequently than gamers. The results extend previous findings on the addictive potential of Internet applications and validate the proposed distinction between specific and generalized problematic Internet use. In addition to Internet gaming disorder, future studies should also focus on other highly addictive Internet applications, that is, chatting or social networking, regarding differential correlates of problematic use. © 2017 S. Karger AG, Basel.
Sgaier, S K; Mony, P; Jayakumar, S; McLaughlin, C; Arora, P; Kumar, R; Bhatia, P; Jha, P
2011-03-01
To determine the prevalence and correlates of Herpes Simplex Virus-2 (HSV-2) and syphilis infections in the general population in India. 2456 adults were surveyed in Hyderabad, Bangalore and Chandigarh in India. Socio-demographic and lifestyle characteristics were obtained through a questionnaire, and a dried blood spot (DBS) was collected from all individuals aged 18 years and over; sexual behaviour was collected from those aged 18-49 years. DBS samples were tested for HSV-2 and syphilis serology. The association between HSV-2 and syphilis infections with socio-demographic and behavioural variables was analysed using multivariable logistic regression. The prevalence of HSV-2 and syphilis was 10.1% and 1.7%, respectively. Geographic differences in HSV-2 prevalence were significant, while for syphilis it was comparable. Urban-rural differences in prevalence were only seen for syphilis. For both infections, the prevalence between males and females was not significantly different. In males and females, HSV-2 prevalence increased significantly with increasing age; for syphilis, a slight trend was seen only in females. In a multivariable analysis, HSV-2 infection in males and females was associated with site, religion and testing positive for syphilis, in addition to reporting ≥ 2 lifetime partners in the previous year among males and being ever married or having had sex with a non-regular partner in the last year among females. The burden and geographic heterogeneity of HSV-2 and syphilis infections in India are significant. A national household and DBS-based sexually transmitted infection (STI) surveillance system would enable monitoring, especially in relation to the HIV epidemic, and planning of evidence-based prevention and treatment programmes.
Abdelsattar, Jad M; AlJamal, Yazan N; Ruparel, Raaj K; Rowse, Phillip G; Heller, Stephanie F; Farley, David R
2018-05-14
Faculty evaluations, ABSITE scores, and operative case volumes often tell little about true resident performance. We developed an objective structured clinical examination called the Surgical X-Games (5 rooms, 15 minutes each, 12-15 tests total, different for each postgraduate [PGY] level). We hypothesized that performance in X-Games will prove more useful in identifying areas of strength or weakness among general surgery (GS) residents than faculty evaluations, ABSITE scores, or operative cases volumes. PGY 2 to 5 GS residents (n = 35) were tested in a semiannual X-Games assessment using multiple simulation tasks: laparoscopic skills, bowel anastomosis, CT/CXR analysis, chest tube placement, etc. over 1 academic year. Resident scores were compared to their ABSITE, in-training evaluation reports, and operating room case numbers. Academic medical center. PGY-2, 3, 4, and 5 GS residents at Mayo Clinic in Rochester, MN. Results varied greatly within each class except for staff evaluations: in-training evaluation reports medians for PGY-2s were 5.3 (range: 5.0-6.0), PGY-3s 5.9 (5.5-6.3), PGY-4s 5.6 (5.0-6.0), and PGY-5s were 6.1 (5.6-6.9). Although ABSITE and operating room case volumes fluctated greatly with each PGY class, only X-Games scores (median: PGY-2 = 82, PGY-3 = 61, PGY-4 = 76, and PGY-5 = 60) correlated positively (p < 0.05) with operative case volume and negatively (p < 0.05) with staff evaluations. X-Games assessment generated wide differentiation of resident performance quickly, inexpensively, and objectively. Although "Minnesota-nice" surgical staff may feel all GS trainees are "above average," objective assessment tells us otherwise. Copyright © 2018 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.
Correlation and network analysis of global financial indices.
Kumar, Sunil; Deo, Nivedita
2012-08-01
Random matrix theory (RMT) and network methods are applied to investigate the correlation and network properties of 20 financial indices. The results are compared before and during the financial crisis of 2008. In the RMT method, the components of eigenvectors corresponding to the second largest eigenvalue form two clusters of indices in the positive and negative directions. The components of these two clusters switch in opposite directions during the crisis. The network analysis uses the Fruchterman-Reingold layout to find clusters in the network of indices at different thresholds. At a threshold of 0.6, before the crisis, financial indices corresponding to the Americas, Europe, and Asia-Pacific form separate clusters. On the other hand, during the crisis at the same threshold, the American and European indices combine together to form a strongly linked cluster while the Asia-Pacific indices form a separate weakly linked cluster. If the value of the threshold is further increased to 0.9 then the European indices (France, Germany, and the United Kingdom) are found to be the most tightly linked indices. The structure of the minimum spanning tree of financial indices is more starlike before the crisis and it changes to become more chainlike during the crisis. The average linkage hierarchical clustering algorithm is used to find a clearer cluster structure in the network of financial indices. The cophenetic correlation coefficients are calculated and found to increase significantly, which indicates that the hierarchy increases during the financial crisis. These results show that there is substantial change in the structure of the organization of financial indices during a financial crisis.
Stoichiometric Correlation Analysis: Principles of Metabolic Functionality from Metabolomics Data
Kevin Schwahn
2017-12-01
Full Text Available Recent advances in metabolomics technologies have resulted in high-quality (time-resolved metabolic profiles with an increasing coverage of metabolic pathways. These data profiles represent read-outs from often non-linear dynamics of metabolic networks. Yet, metabolic profiles have largely been explored with regression-based approaches that only capture linear relationships, rendering it difficult to determine the extent to which the data reflect the underlying reaction rates and their couplings. Here we propose an approach termed Stoichiometric Correlation Analysis (SCA based on correlation between positive linear combinations of log-transformed metabolic profiles. The log-transformation is due to the evidence that metabolic networks can be modeled by mass action law and kinetics derived from it. Unlike the existing approaches which establish a relation between pairs of metabolites, SCA facilitates the discovery of higher-order dependence between more than two metabolites. By using a paradigmatic model of the tricarboxylic acid cycle we show that the higher-order dependence reflects the coupling of concentration of reactant complexes, capturing the subtle difference between the employed enzyme kinetics. Using time-resolved metabolic profiles from Arabidopsis thaliana and Escherichia coli, we show that SCA can be used to quantify the difference in coupling of reactant complexes, and hence, reaction rates, underlying the stringent response in these model organisms. By using SCA with data from natural variation of wild and domesticated wheat and tomato accession, we demonstrate that the domestication is accompanied by loss of such couplings, in these species. Therefore, application of SCA to metabolomics data from natural variation in wild and domesticated populations provides a mechanistic way to understanding domestication and its relation to metabolic networks.
Canonical correlation analysis for gene-based pleiotropy discovery.
Jose A Seoane
2014-10-01
Full Text Available Genome-wide association studies have identified a wealth of genetic variants involved in complex traits and multifactorial diseases. There is now considerable interest in testing variants for association with multiple phenotypes (pleiotropy and for testing multiple variants for association with a single phenotype (gene-based association tests. Such approaches can increase statistical power by combining evidence for association over multiple phenotypes or genetic variants respectively. Canonical Correlation Analysis (CCA measures the correlation between two sets of multidimensional variables, and thus offers the potential to combine these two approaches. To apply CCA, we must restrict the number of attributes relative to the number of samples. Hence we consider modules of genetic variation that can comprise a gene, a pathway or another biologically relevant grouping, and/or a set of phenotypes. In order to do this, we use an attribute selection strategy based on a binary genetic algorithm. Applied to a UK-based prospective cohort study of 4286 women (the British Women's Heart and Health Study, we find improved statistical power in the detection of previously reported genetic associations, and identify a number of novel pleiotropic associations between genetic variants and phenotypes. New discoveries include gene-based association of NSF with triglyceride levels and several genes (ACSM3, ERI2, IL18RAP, IL23RAP and NRG1 with left ventricular hypertrophy phenotypes. In multiple-phenotype analyses we find association of NRG1 with left ventricular hypertrophy phenotypes, fibrinogen and urea and pleiotropic relationships of F7 and F10 with Factor VII, Factor IX and cholesterol levels.
Prognostic value of correlation analysis of perinatal anamnesis
V. V. Sofronov
2017-01-01
Full Text Available Objective research: is to establish the prognostic value of the analysis of correlative relationships of qualitative indicators of the perinatal history. Correlative groups of interactions of the investigated qualitative indicators in the antenatal, intranatal and postnatal periods are constructed. It was shown that in antenatal history for newborns 22–37 weeks. gestation (group 1 the most important parameters are the «gestational age», «chronic respiratory diseases in the mother,» «premature birth in an anamnesis,» and «exacerbation of chronic infections during pregnancy»; for newborns 38–41 weeks. gestation (2nd group – «cervical erosion», «ovarian cyst», «fibromyoma» and «colpitis ». In the intranatal history for children of the 1st group, the most important parameters are «anhydrous period» and «prolonged labor»; for children of the second group – only «prolonged labor». In the postnatal history for the first group, the two most important parameters are the «gestational age» and the «zonal elevation of the brain echogenicity,» and for the 2 nd group only the parameter «degree of asphyxia» is as important. The obtained results confirm the main known interrelationships of parameters of the perinatal history. At the same time, nontrivial connections between the parameters of the perinatal history: «allergic diseases in the mother» – «threatened miscarriage » – «ovarian cyst»; «chronic respiratory diseases in the mother» – «allergic diseases of the mother» – «diseases of the digestive system in the father.»
A general statistical test for correlations in a finite-length time series.
Hanson, Jeffery A; Yang, Haw
2008-06-07
The statistical properties of the autocorrelation function from a time series composed of independently and identically distributed stochastic variables has been studied. Analytical expressions for the autocorrelation function's variance have been derived. It has been found that two common ways of calculating the autocorrelation, moving-average and Fourier transform, exhibit different uncertainty characteristics. For periodic time series, the Fourier transform method is preferred because it gives smaller uncertainties that are uniform through all time lags. Based on these analytical results, a statistically robust method has been proposed to test the existence of correlations in a time series. The statistical test is verified by computer simulations and an application to single-molecule fluorescence spectroscopy is discussed.
2017-09-01
satisfying the strict avalanche criterion,” Discrete Math ., vol. 185, pp. 29–39, 1998. [2] R.C. Bose, “On some connections between the design of... Discrete Appl. Math ., vol. 149, pp. 73–86, 2005. [11] T.W. Cusick and P. Stănică, Cryptographic Boolean Functions and Applications, 2nd ed., San Diego...Stănică, “Bisecting binomial coefficients,” Discrete Appl. Math ., vol. 227, pp. 70–83, 2017. [28] T. Martinsen, W. Meidl, and P. Stănică, “Generalized
Modal Analysis and Model Correlation of the Mir Space Station
Kim, Hyoung M.; Kaouk, Mohamed
2000-01-01
This paper will discuss on-orbit dynamic tests, modal analysis, and model refinement studies performed as part of the Mir Structural Dynamics Experiment (MiSDE). Mir is the Russian permanently manned Space Station whose construction first started in 1986. The MiSDE was sponsored by the NASA International Space Station (ISS) Phase 1 Office and was part of the Shuttle-Mir Risk Mitigation Experiment (RME). One of the main objectives for MiSDE is to demonstrate the feasibility of performing on-orbit modal testing on large space structures to extract modal parameters that will be used to correlate mathematical models. The experiment was performed over a one-year span on the Mir-alone and Mir with a Shuttle docked. A total of 45 test sessions were performed including: Shuttle and Mir thruster firings, Shuttle-Mir and Progress-Mir dockings, crew exercise and pushoffs, and ambient noise during night-to-day and day-to-night orbital transitions. Test data were recorded with a variety of existing and new instrumentation systems that included: the MiSDE Mir Auxiliary Sensor Unit (MASU), the Space Acceleration Measurement System (SAMS), the Russian Mir Structural Dynamic Measurement System (SDMS), the Mir and Shuttle Inertial Measurement Units (IMUs), and the Shuttle payload bay video cameras. Modal analysis was performed on the collected test data to extract modal parameters, i.e. frequencies, damping factors, and mode shapes. A special time-domain modal identification procedure was used on free-decay structural responses. The results from this study show that modal testing and analysis of large space structures is feasible within operational constraints. Model refinements were performed on both the Mir alone and the Shuttle-Mir mated configurations. The design sensitivity approach was used for refinement, which adjusts structural properties in order to match analytical and test modal parameters. To verify the refinement results, the analytical responses calculated using
Multigroup Moderation Test in Generalized Structured Component Analysis
Angga Dwi Mulyanto
2016-05-01
Full Text Available Generalized Structured Component Analysis (GSCA is an alternative method in structural modeling using alternating least squares. GSCA can be used for the complex analysis including multigroup. GSCA can be run with a free software called GeSCA, but in GeSCA there is no multigroup moderation test to compare the effect between groups. In this research we propose to use the T test in PLS for testing moderation Multigroup on GSCA. T test only requires sample size, estimate path coefficient, and standard error of each group that are already available on the output of GeSCA and the formula is simple so the user does not need a long time for analysis.
Asymmetric correlation matrices: an analysis of financial data
Livan, G.; Rebecchi, L.
2012-06-01
We analyse the spectral properties of correlation matrices between distinct statistical systems. Such matrices are intrinsically non-symmetric, and lend themselves to extend the spectral analyses usually performed on standard Pearson correlation matrices to the realm of complex eigenvalues. We employ some recent random matrix theory results on the average eigenvalue density of this type of matrix to distinguish between noise and non-trivial correlation structures, and we focus on financial data as a case study. Namely, we employ daily prices of stocks belonging to the American and British stock exchanges, and look for the emergence of correlations between two such markets in the eigenvalue spectrum of their non-symmetric correlation matrix. We find several non trivial results when considering time-lagged correlations over short lags, and we corroborate our findings by additionally studying the asymmetric correlation matrix of the principal components of our datasets.
Richman, J A; Rospenda, K M; Nawyn, S J; Flaherty, J A; Fendrich, M; Drum, M L; Johnson, T P
1999-03-01
This study hypothesized that interpersonal workplace stressors involving sexual harassment and generalized workplace abuse are highly prevalent and significantly linked with mental health outcomes including symptomatic distress, the use and abuse of alcohol, and other drug use. Employees in 4 university occupational groups (faculty, student, clerical, and service workers; n = 2492) were surveyed by means of a mailed self-report instrument. Cross-tabular and ordinary least squares and logistic regression analyses examined the prevalence of harassment and abuse and their association with mental health status. The data show high rates of harassment and abuse. Among faculty, females were subjected to higher rates; among clerical and service workers, males were subjected to higher rates. Male and female clerical and service workers experienced higher levels of particularly severe mistreatment. Generalized abuse was more prevalent than harassment for all groups. Both harassment and abuse were significantly linked to most mental health outcomes for men and women. Interpersonally abusive workplace dynamics constitute a significant public health problem that merits increased intervention and prevention strategies.
Nonlinear analysis of generalized cross-field current instability
Yoon, P.H.; Lui, A.T.Y.
1993-01-01
Analysis of the generalized cross-field current instability is carried out in which cross-field drift of both the ions and electrons and their temperatures are permitted to vary in time. The unstable mode under consideration is the electromagnetic generalization of the classical modified-two-stream instability. The generalized instability is made of the modified-two-stream and ion-Weibel modes. The relative importance of the features associated with the ion-Weibel mode and those of the modified-two-stream mode is assessed. Specific applications are made to the Earth's neutral sheet prior to substorm onset and to the Earth's bow shock. The numerical solution indicates that the ion-Weibel mode dominates in the Earth's neutral sheet environment. In contrast, the situation for the bow shock is dominated by the modified-two-stream mode. Notable differences are found between the present calculation and previous results on ion-Weibel mode which restrict the analysis to only parallel propagating waves. However, in the case of Earth's bow shock for which the ion-Weibel mode plays no important role, the inclusion of the electromagnetic ion response is found to differ little from the previous results which treats ions responding only to the electrostatic component of the excited waves
Hansen, Tobias
2015-07-01
This thesis covers two main topics: the tensorial structure of quantum field theory correlators in general spacetime dimensions and a method for computing string theory scattering amplitudes directly in target space. In the first part tensor structures in generic bosonic CFT correlators and scattering amplitudes are studied. To this end arbitrary irreducible tensor representations of SO(d) (traceless mixed-symmetry tensors) are encoded in group invariant polynomials, by contracting with sets of commuting and anticommuting polarization vectors which implement the index symmetries of the tensors. The tensor structures appearing in CFT d correlators can then be inferred by studying these polynomials in a d + 2 dimensional embedding space. It is shown with an example how these correlators can be used to compute general conformal blocks describing the exchange of mixed-symmetry tensors in four-point functions, which are crucial for advancing the conformal bootstrap program to correlators of operators with spin. Bosonic string theory lends itself as an ideal example for applying the same methods to scattering amplitudes, due to its particle spectrum of arbitrary mixed-symmetry tensors. This allows in principle the definition of on-shell recursion relations for string theory amplitudes. A further chapter introduces a different target space definition of string scattering amplitudes. As in the case of on-shell recursion relations, the amplitudes are expressed in terms of their residues via BCFW shifts. The new idea here is that the residues are determined by use of the monodromy relations for open string theory, avoiding the infinite sums over the spectrum arising in on-shell recursion relations. Several checks of the method are presented, including a derivation of the Koba-Nielsen amplitude in the bosonic string. It is argued that this method provides a target space definition of the complete S-matrix of string theory at tree-level in a at background in terms of a small
Dutta, Srimonti; Ghosh, Dipak; Chatterjee, Sucharita
2016-12-01
The manuscript studies autocorrelation and cross correlation of SENSEX fluctuations and Forex Exchange Rate in respect to Indian scenario. Multifractal detrended fluctuation analysis (MFDFA) and multifractal detrended cross correlation analysis (MFDXA) were employed to study the correlation between the two series. It was observed that the two series are strongly cross correlated. The change of degree of cross correlation with time was studied and the results are interpreted qualitatively.
Recovering Intrinsic Fragmental Vibrations Using the Generalized Subsystem Vibrational Analysis.
Tao, Yunwen; Tian, Chuan; Verma, Niraj; Zou, Wenli; Wang, Chao; Cremer, Dieter; Kraka, Elfi
2018-05-08
Normal vibrational modes are generally delocalized over the molecular system, which makes it difficult to assign certain vibrations to specific fragments or functional groups. We introduce a new approach, the Generalized Subsystem Vibrational Analysis (GSVA), to extract the intrinsic fragmental vibrations of any fragment/subsystem from the whole system via the evaluation of the corresponding effective Hessian matrix. The retention of the curvature information with regard to the potential energy surface for the effective Hessian matrix endows our approach with a concrete physical basis and enables the normal vibrational modes of different molecular systems to be legitimately comparable. Furthermore, the intrinsic fragmental vibrations act as a new link between the Konkoli-Cremer local vibrational modes and the normal vibrational modes.
Analysis of General Power Counting Rules in Effective Field Theory
Gavela, B M; Manohar, A V; Merlo, L
2016-01-01
We derive the general counting rules for a quantum effective field theory (EFT) in $\\mathsf{d}$ dimensions. The rules are valid for strongly and weakly coupled theories, and predict that all kinetic energy terms are canonically normalized. They determine the energy dependence of scattering cross sections in the range of validity of the EFT expansion. The size of cross sections is controlled by the $\\Lambda$ power counting of EFT, not by chiral counting, even for chiral perturbation theory ($\\chi$PT). The relation between $\\Lambda$ and $f$ is generalized to $\\mathsf{d}$ dimensions. We show that the naive dimensional analysis $4\\pi$ counting is related to $\\hbar$ counting. The EFT counting rules are applied to $\\chi$PT, to Standard Model EFT and to the non-trivial case of Higgs EFT, which combines the $\\Lambda$ and chiral counting rules within a single theory.
Computer code for general analysis of radon risks (GARR)
Ginevan, M.
1984-09-01
This document presents a computer model for general analysis of radon risks that allow the user to specify a large number of possible models with a small number of simple commands. The model is written in a version of BASIC which conforms closely to the American National Standards Institute (ANSI) definition for minimal BASIC and thus is readily modified for use on a wide variety of computers and, in particular, microcomputers. Model capabilities include generation of single-year life tables from 5-year abridged data, calculation of multiple-decrement life tables for lung cancer for the general population, smokers, and nonsmokers, and a cohort lung cancer risk calculation that allows specification of level and duration of radon exposure, the form of the risk model, and the specific population assumed at risk. 36 references, 8 figures, 7 tables
Mookerjee, A.; Prasad, R.
1993-09-01
We present a method for calculating the electronic structure of disordered alloys with short range order (SRO) which guarantees positive density of states for all values of the SRO parameter. The method is based on the generalized augmented space theorem which is valid for alloys with SRO. This theorem is applied to alloys with SRO in the tight-binding linear muffin-tin orbital (TB-LMTO) framework. This is done by using the augmented space formulation of Mookerjee and cluster coherent potential approximation. As an illustration, the method is applied to a single band mode TB-LMTO Hamiltonian. We find that the SRO can induce substantial changes in the density of states. (author). 22 refs, 2 figs
Gupta, M.J.; Freeman, A.B.
1976-01-01
The generalized susceptibility, chi(q), of both NbC and TaC determined from APW energy band calculations show large maxima to occur at precisely those q/sub max/ values at which soft phonon modes were observed by Smith. Maxima in chi(q) are predicted for other directions. The locus of these q/sub max/ values can be represented by a warped cube of dimension approximately 1.2(2π/a) in momentum space--in striking agreement with the soft mode surface proposed phenomenologically by Weber. In sharp contrast, the chi(q) calculated for both ZrC and HfC--for which no phonon anomalies have been observed--fall off in all symmetry directions away from the zone center. The phonon anomalies in the transition metal carbides are thus interpreted as due to an ''overscreening'' effect resulting from an anomalous increase of the response function of the conduction electrons
The high vaginal swab in general practice: clinical correlates of possible pathogens.
Dykhuizen, R S; Harvey, G; Gould, I M
1995-06-01
Clinical features, diagnosis and treatment of 286 women whose high vaginal swabs (HVS) submitted by their general practitioners showed pure, heavy growth of Staphylococcus aureus, beta haemolytic streptococci groups A, C or G, Streptococcus milleri, Streptococcus pneumoniae or Haemophilus influenzae were analysed. Women with group A, C and G streptococci frequently had clinical vulvovaginitis and although the numbers were too small for statistical confirmation, S. pneumoniae and H. influenzae appeared to cause clinical disease as well. The association of S. aureus or S. milleri with clinical vulvovaginitis was much less convincing. It seems relevant for laboratories to report sensitivities for group A, C and G streptococci. Further research is needed to determine the pathogenicity of S. pneumoniae and H. influenzae.
Generalized correlation integral vectors: A distance concept for chaotic dynamical systems
Haario, Heikki, E-mail: heikki.haario@lut.fi [School of Engineering Science, Lappeenranta University of Technology, Lappeenranta (Finland); Kalachev, Leonid, E-mail: KalachevL@mso.umt.edu [Department of Mathematical Sciences, University of Montana, Missoula, Montana 59812-0864 (United States); Hakkarainen, Janne [Earth Observation Unit, Finnish Meteorological Institute, Helsinki (Finland)
2015-06-15
Several concepts of fractal dimension have been developed to characterise properties of attractors of chaotic dynamical systems. Numerical approximations of them must be calculated by finite samples of simulated trajectories. In principle, the quantities should not depend on the choice of the trajectory, as long as it provides properly distributed samples of the underlying attractor. In practice, however, the trajectories are sensitive with respect to varying initial values, small changes of the model parameters, to the choice of a solver, numeric tolerances, etc. The purpose of this paper is to present a statistically sound approach to quantify this variability. We modify the concept of correlation integral to produce a vector that summarises the variability at all selected scales. The distribution of this stochastic vector can be estimated, and it provides a statistical distance concept between trajectories. Here, we demonstrate the use of the distance for the purpose of estimating model parameters of a chaotic dynamic model. The methodology is illustrated using computational examples for the Lorenz 63 and Lorenz 95 systems, together with a framework for Markov chain Monte Carlo sampling to produce posterior distributions of model parameters.
Colombeau's generalized functions and non-standard analysis
Todorov, T.D.
1987-10-01
Using some methods of the Non-Standard Analysis we modify one of Colombeau's classes of generalized functions. As a result we define a class ε-circumflex of the so-called meta-functions which possesses all good properties of Colombeau's generalized functions, i.e. (i) ε-circumflex is an associative and commutative algebra over the system of the so-called complex meta-numbers C-circumflex; (ii) Every meta-function has partial derivatives of any order (which are meta-functions again); (iii) Every meta-function is integrable on any compact set of R n and the integral is a number from C-circumflex; (iv) ε-circumflex contains all tempered distributions S', i.e. S' is contained in ε' isomorphically with respect to all linear operations (including the differentiation). Thus, within the class ε-circumflex the problem of multiplication of the tempered distributions is satisfactorily solved (every two distributions in S' have a well-defined product in ε-circumflex). The crucial point is that C-circumflex is a field in contrast to the system of Colombeau's generalized numbers C-bar which is a ring only (C-bar is the counterpart of C-circumflex in Colombeau's theory). In this way we simplify and improve slightly the properties of the integral and notion of ''values of the meta-functions'' as well as the properties of the whole class ε-circumflex itself if compared with the original Colombeau theory. And, what is maybe more important, we clarify the connection between the Non-Standard Analysis and Colombeau's theory of new generalized functions in the framework of which the problem of multiplication of distributions was recently solved. (author). 14 refs
Liu, An-Nuo; Wang, Lu-Lu; Li, Hui-Ping; Gong, Juan; Liu, Xiao-Hong
2017-05-01
The literature on posttraumatic growth (PTG) is burgeoning, with the inconsistencies in the literature of the relationship between PTG and posttraumatic stress disorder (PTSD) symptoms becoming a focal point of attention. Thus, this meta-analysis aims to explore the relationship between PTG and PTSD symptoms through the Pearson correlation coefficient. A systematic search of the literature from January 1996 to November 2015 was completed. We retrieved reports on 63 studies that involved 26,951 patients. The weighted correlation coefficient revealed an effect size of 0.22 with a 95% confidence interval of 0.18 to 0.25. Meta-analysis provides evidence that PTG may be positively correlated with PTSD symptoms and that this correlation may be modified by age, trauma type, and time since trauma. Accordingly, people with high levels of PTG should not be ignored, but rather, they should continue to receive help to alleviate their PTSD symptoms.
Druzhinina, O V; Shestakov, A A
2002-01-01
A generalized direct Lyapunov method is put forward for the study of stability and attraction in general time systems of the following types: the classical dynamical system in the sense of Birkhoff, the general system in the sense of Zubov, the general system in the sense of Seibert, the general system with delay, and the general 'input-output' system. For such systems, with the help of generalized Lyapunov functions with respect to two filters, two quasifilters, or two filter bases, necessary and sufficient conditions for stability and attraction are obtained under minimal assumptions about the mathematical structure of the general system
Engineering Properties and Correlation Analysis of Fiber Cementitious Materials
Wei-Ting Lin
2014-11-01
Full Text Available This study focuses on the effect of the amount of silica fume addition and volume fraction of steel fiber on the engineering properties of cementitious materials. Test variables include dosage of silica fume (5% and 10%, water/cement ratio (0.35 and 0.55 and steel fiber dosage (0.5%, 1.0% and 2.0%. The experimental results included: compressive strength, direct tensile strength, splitting tensile strength, surface abrasion and drop-weight test, which were collected to carry out the analysis of variance to realize the relevancy and significance between material parameters and those mechanical properties. Test results illustrate that the splitting tensile strength, direct tensile strength, strain capacity and ability of crack-arresting increase with increasing steel fiber and silica fume dosages, as well as the optimum mixture of the fiber cementitious materials is 5% replacement silica fume and 2% fiber dosage. In addition, the Pearson correlation coefficient was conducted to evaluate the influence of the material variables and corresponds to the experiment result.
Applications of temporal kernel canonical correlation analysis in adherence studies.
John, Majnu; Lencz, Todd; Ferbinteanu, Janina; Gallego, Juan A; Robinson, Delbert G
2017-10-01
Adherence to medication is often measured as a continuous outcome but analyzed as a dichotomous outcome due to lack of appropriate tools. In this paper, we illustrate the use of the temporal kernel canonical correlation analysis (tkCCA) as a method to analyze adherence measurements and symptom levels on a continuous scale. The tkCCA is a novel method developed for studying the relationship between neural signals and hemodynamic response detected by functional MRI during spontaneous activity. Although the tkCCA is a powerful tool, it has not been utilized outside the application that it was originally developed for. In this paper, we simulate time series of symptoms and adherence levels for patients with a hypothetical brain disorder and show how the tkCCA can be used to understand the relationship between them. We also examine, via simulations, the behavior of the tkCCA under various missing value mechanisms and imputation methods. Finally, we apply the tkCCA to a real data example of psychotic symptoms and adherence levels obtained from a study based on subjects with a first episode of schizophrenia, schizophreniform or schizoaffective disorder.
Charlene C Lew
2006-04-01
Full Text Available This study investigated the relationships between the scales of the Adult Career Concerns Inventory (ACCI and those of the Career Attitudes and Strategies Inventory (CASI. The scores of 202 South African adults for the two inventories were subjected to a canonical correlation analysis. Two canonical variates made statistically significant contributions to the explanation of the relationships between the two sets of variables. Inspection of the correlations of the original variables with the first canonical variate suggested that a high level of career concerns in general, as measured by the ACCI, is associated with high levels of career worries, more geographical barriers, a low risk-taking style and a non-dominant interpersonal style, as measured by the CASI. The second canonical variate suggested that concerns with career exploration and advancement of one’s career is associated with low job satisfaction, low family commitment, high work involvement, and a dominant style at work.
An analysis of correlation between occlusion classification and skeletal pattern
Lu Xinhua; Cai Bin; Wang Dawei; Wu Liping
2003-01-01
Objective: To study the correlation between dental relationship and skeletal pattern of individuals. Methods: 194 cases were selected and classified by angle classification, incisor relationship and skeletal pattern respectively. The correlation of angle classification and incisor relationship to skeletal pattern was analyzed with SPSS 10.0. Results: The values of correlation index (Kappa) were 0.379 and 0.494 respectively. Conclusion: The incisor relationship is more consistent with skeletal pattern than angle classification
Asset correlations and credit portfolio risk: an empirical analysis
Düllmann, Klaus; Scheicher, Martin; Schmieder, Christian
2007-01-01
In credit risk modelling, the correlation of unobservable asset returns is a crucial component for the measurement of portfolio risk. In this paper, we estimate asset correlations from monthly time series of Moody's KMV asset values for around 2,000 European firms from 1996 to 2004. We compare correlation and value-atrisk (VaR) estimates in a one-factor or market model and a multi-factor or sector model. Our main finding is a complex interaction of credit risk correlations and default probabi...
Singh, Aakanksha; Mattoo, Surendra K.; Grover, Sandeep
2016-01-01
Background: Very few studies from India have studied stigma experienced by patients with schizophrenia. Aim of the Study: To study stigma in patients with schizophrenia (in the form of internalized stigma, perceived stigma and social-participation-restriction stigma) and its relationship with specified demographic and clinical variables (demographic variables, clinical profile, level of psychopathology, knowledge about illness, and insight). Materials and Methods: Selected by purposive random sampling, 100 patients with schizophrenia in remission were evaluated on internalized stigma of mental illness scale (ISMIS), explanatory model interview catalog stigma scale, participation scale (P-scale), positive and negative syndrome scale for schizophrenia, global assessment of functioning scale, scale to assess unawareness of mental disorder, and knowledge of mental illness scale. Results: On ISMIS scale, 81% patients experienced alienation and 45% exhibited stigma resistance. Stereotype endorsement was seen in 26% patients, discrimination experience was faced by 21% patients, and only 16% patients had social withdrawal. Overall, 29% participants had internalized stigma when total ISMIS score was taken into consideration. On P-scale, 67% patients experienced significant restriction, with a majority reporting moderate to mild restriction. In terms of associations between stigma and sociodemographic variables, no consistent correlations emerged, except for those who were not on paid job, had higher participation restriction. Of the clinical variables, level of functioning was the only consistent predictor of stigma. While better knowledge about the disorder was associated with lower level of stigma, there was no association between stigma and insight. Conclusion: Significant proportion of patients with schizophrenia experience stigma and stigma is associated with lower level of functioning and better knowledge about illness is associated with lower level of stigma. PMID
Generalized Multi-Edge Analysis for K-Edge Densitometry
Collins, M.
1998-01-01
In K-edge densitometry (KED), a continuous-energy x-ray beam is transmitted through a liquid sample. The actinide content of the sample can be measured through analysis of the transmitted portion of the x-ray beam. Traditional methods for KED analysis allow the simultaneous calculation of, at most, two actinide concentrations. A generalized multi-edge KED analytical method is presented, allowing up to six actinide concentrations to be calculated simultaneously. Applications of this method for hybrid KED/x-ray fluorescence (HKED) systems are discussed. Current HKED systems require the operator to know the approximate actinide content of each sample, and manually select the proper analysis mode. The new multi-edge KED technique allows rapid identification of the major actinide components in a sample, independent of actinide content. The proper HKED analysis mode can be selected automatically, without requiring sample content information from the user. Automatic HKED analysis would be especially useful in an analytical laboratory setting, where samples with truly unknown characteristics are encountered. Because this technique requires no hardware modifications, several facilities that use HKED may eventually benefit from this approach
Correlations between human mobility and social interaction reveal general activity patterns.
Mollgaard, Anders; Lehmann, Sune; Mathiesen, Joachim
2017-01-01
A day in the life of a person involves a broad range of activities which are common across many people. Going beyond diurnal cycles, a central question is: to what extent do individuals act according to patterns shared across an entire population? Here we investigate the interplay between different activity types, namely communication, motion, and physical proximity by analyzing data collected from smartphones distributed among 638 individuals. We explore two central questions: Which underlying principles govern the formation of the activity patterns? Are the patterns specific to each individual or shared across the entire population? We find that statistics of the entire population allows us to successfully predict 71% of the activity and 85% of the inactivity involved in communication, mobility, and physical proximity. Surprisingly, individual level statistics only result in marginally better predictions, indicating that a majority of activity patterns are shared across our sample population. Finally, we predict short-term activity patterns using a generalized linear model, which suggests that a simple linear description might be sufficient to explain a wide range of actions, whether they be of social or of physical character.
Gupta, M.; Freeman, A.J.
1976-01-01
The generalized susceptibility, chi(q vector), of both NbC and TaC determined from APW energy band calculations show large maxima to occur at precisely those q vector/sub max/ values at which soft phonon modes were observed by Smith. Maxima in chi (q vector) are predicted for other directions. The locus of these q vector/sub max/ values can be represented by a warped cube of dimension approximately 1.2 (2π/a) in momentum space, in striking agreement with the soft mode surface proposed phenomenologically by Weber. In sharp contrast, the chi(q vector) calculated for both ZrC and HfC (for which no phonon anomalies have been observed) fall off in all symmetry directions away from the zone center. The phonon anomalies in the transition metal carbides are interpreted as due to an ''overscreening'' effect resulting from an anomalous increase of the response function of the conduction electrons. 8 figures, 41 references
LI Rui; WANG Liqun; MA Chunxia; MA Lixian
2016-01-01
Objective To explore the personality characteristics of children with tic disorders and their relationship with family factors.Methods Sixty cases of children with tic disorders diagnosed in our hospital were selected as the case group and 65 cases of normal children were selected as the control group.The children of two groups were assessed using Eysenck Personality Questionnaire (EPQ),Family Environment Scale (FES-CV) and general situation questionnaire of family (GSQ),respectively.The scores of EPQ personality characteristics,FES-CV and GSQ scores were compared for the children in the two groups.The Person correlation analysis method was used to analyze the correlation between personality scores of children in case group and family environment factors.Results The general situation questionnaire results showed that there was significant statistically difference in parenting style,parental education level and family types of the children between case group and control group (P ＜ 0.05);EPQ results showed that the neuroticism and psychoticism scores of children in the case group were significantly higher than those in the control group (P＜ 0.05) and the lying degree scores in the control group were significantly higher than those in the case group (P＜ 0.05);FES-CV results showed that the family cohesion scores of the case group were significantly lower than those of the control group (P＜0.05),and the family conflict scores in the case group were significantly higher than those in the control group (P＜0.05).The Person correlation analysis results indicated that the psychoticism score was negatively correlated with the score of family cohesion (P＜0.05),and positively correlated with family conflict (P＜0.05),while the neuroticism score was positively correlated with family conflict score (P＜0.05).Conclusion The children with tic disorders have significant personality deviation compared to the normal children,and the personality deviation degree is
Smith, C.
2009-01-01
The objective of the study was to evaluate rainfall and water table elevation data in search of a correlation that could be used to understand and predict water elevation changes. This information will be useful in placing screen zones for future monitoring wells and operations of groundwater treatment units. Fifteen wells in the General Separations Area (GSA) at Savannah River Site were evaluated from 1986 through 2001. The study revealed that the water table does respond to rainfall with minimal delay. (Water level information was available monthly, which restricted the ability to evaluate a shorter delay period.) Water elevations were found to be related to the cumulative sum (Q-Delta Sum) of the difference between the average rainfall for a specific month and the actual rainfall for that month, calculated from an arbitrary starting point. Water table elevations could also be correlated between wells, but using the right well for correlation was very important. The strongest correlation utilized a quadratic equation that takes into account the rainfall in a specific area and the rainfall from an adjacent area that contributes through a horizontal flow. Specific values vary from well to well as a result of geometry and underground variations. R2's for the best models ranged up to 0.96. The data in the report references only GSA wells but other wells (including confined water tables) on the site have been observed to return similar water level fluctuation patterns
A κ-generalized statistical mechanics approach to income analysis
Clementi, F; Gallegati, M; Kaniadakis, G
2009-01-01
This paper proposes a statistical mechanics approach to the analysis of income distribution and inequality. A new distribution function, having its roots in the framework of κ-generalized statistics, is derived that is particularly suitable for describing the whole spectrum of incomes, from the low–middle income region up to the high income Pareto power-law regime. Analytical expressions for the shape, moments and some other basic statistical properties are given. Furthermore, several well-known econometric tools for measuring inequality, which all exist in a closed form, are considered. A method for parameter estimation is also discussed. The model is shown to fit remarkably well the data on personal income for the United States, and the analysis of inequality performed in terms of its parameters is revealed as very powerful
A κ-generalized statistical mechanics approach to income analysis
Clementi, F.; Gallegati, M.; Kaniadakis, G.
2009-02-01
This paper proposes a statistical mechanics approach to the analysis of income distribution and inequality. A new distribution function, having its roots in the framework of κ-generalized statistics, is derived that is particularly suitable for describing the whole spectrum of incomes, from the low-middle income region up to the high income Pareto power-law regime. Analytical expressions for the shape, moments and some other basic statistical properties are given. Furthermore, several well-known econometric tools for measuring inequality, which all exist in a closed form, are considered. A method for parameter estimation is also discussed. The model is shown to fit remarkably well the data on personal income for the United States, and the analysis of inequality performed in terms of its parameters is revealed as very powerful.
Tang You-Fu; Liu Shu-Lin; Jiang Rui-Hong; Liu Ying-Hui
2013-01-01
We study the correlation between detrended fluctuation analysis (DFA) and the Lempel-Ziv complexity (LZC) in nonlinear time series analysis in this paper. Typical dynamic systems including a logistic map and a Duffing model are investigated. Moreover, the influence of Gaussian random noise on both the DFA and LZC are analyzed. The results show a high correlation between the DFA and LZC, which can quantify the non-stationarity and the nonlinearity of the time series, respectively. With the enhancement of the random component, the exponent a and the normalized complexity index C show increasing trends. In addition, C is found to be more sensitive to the fluctuation in the nonlinear time series than α. Finally, the correlation between the DFA and LZC is applied to the extraction of vibration signals for a reciprocating compressor gas valve, and an effective fault diagnosis result is obtained
Numata, Shinya; Yasuda, Masatoshi; Suzuki, Ryo O.; Hosaka, Tetsuro; Noor, Nur Supardi Md.; Fletcher, Christine D.; Hashim, Mazlan
2013-01-01
In South-East Asian dipterocarp forests, many trees synchronize their reproduction at the community level, but irregularly, in a phenomenon known as general flowering (GF). Several proximate cues have been proposed as triggers for the synchronization of Southeast Asian GF, but the debate continues, as many studies have not considered geographical variation in climate and flora. We hypothesized that the spatial pattern of GF forests is explained by previously proposed climatic cues if there are common cues for GF among regions. During the study, GF episodes occurred every year, but the spatial occurrence varied considerably from just a few forests to the whole of Peninsular Malaysia. In 2001, 2002 and 2005, minor and major GF occurred widely throughout Peninsular Malaysia (GF2001, GF2002, and GF2005), and the geographical patterns of GF varied between the episodes. In the three regional-scale GF episodes, most major events occurred in regions where prolonged drought (PD) had been recorded prior, and significant associations between GF scores and PD were found in GF2001 and GF2002. However, the frequency of PD was higher than that of GF throughout the peninsula. In contrast, low temperature (LT) was observed during the study period only before GF2002 and GF2005, but there was no clear spatial relationship between GF and LT in the regional-scale episodes. There was also no evidence that last GF condition influenced the magnitude of GF. Thus, our results suggest that PD would be essential to trigger regional-scale GF in the peninsula, but also that PD does not fully explain the spatial and temporal patterns of GF. The coarse relationships between GF and the proposed climatic cues may be due to the geographical variation in proximate cues for GF, and the climatic and floristic geographical variations should be considered to understand the proximate factors of GF. PMID:24260159
Self-perceived smoking motives and their correlates in a general population sample.
Fidler, Jennifer A; West, Robert
2009-10-01
Understanding motivation to continue smoking may help the development of smoking cessation interventions. However, little information exists on the prevalence of specific motives for smoking in representative samples of smokers. This study examined smokers' reports of their motives for continued smoking in an English general population sample. A total of 2,133 smokers participating in monthly cross-sectional surveys (the Smoking Toolkit Study) identified which, if any, of the following motives they believed were important in keeping them smoking: enjoyment, stress relief, weight control, boredom relief, aid to concentration, aid to socializing, pain relief, liking being a smoker, and feeling bad when not smoking. Associations between these motives and gender, age, social grade, Fagerström Test for Nicotine Dependence, and quit attempts in the last year were examined using logistic regression. Enjoyment and stress relief were the most commonly reported motives (51% and 47%, respectively). Women reported stress relief and weight control more often than men, whereas men were more likely to report enjoyment and liking being a smoker. Older smokers reported enjoying smoking and liking being a smoker more than younger smokers but were less likely to report socializing and stress relief as important motives. Not having made a quit attempt in the last year was associated with enjoying smoking and liking being a smoker. Higher dependence was associated with a greater number of reported motives. While smoking for stress relief is common, perceptions of enjoyment of smoking and positive smoker identity may be the key motives that inhibit attempts at cessation.
Moore, S.E.; Moffat, D.G.
2007-01-01
A general theory for the construction of best-fit correlation equations for multi-dimensioned sets of numerical data is presented. This new theory is based on the mathematics of n-dimensional surfaces and goodness-of-fit statistics. It is shown that orthogonal best-fit analytical trend lines for each of the independent parameters of the data can be used to construct an overall best-fit correlation equation that satisfies both physical boundary conditions and best-of-fit statistical measurements. Application of the theory is illustrated by fitting a three-parameter set of numerical finite-element maximum-stress data obtained earlier by Dr. Moffat for pressure vessel nozzles and/or piping system branch connections
Linear analysis of degree correlations in complex networks
Many real-world networks such as the protein–protein interaction networks and metabolic networks often display nontrivial correlations between degrees of vertices connected by edges. Here, we analyse the statistical methods used usually to describe the degree correlation in the networks, and analytically give linear ...
Generalization in the XCSF classifier system: analysis, improvement, and extension.
Lanzi, Pier Luca; Loiacono, Daniele; Wilson, Stewart W; Goldberg, David E
2007-01-01
We analyze generalization in XCSF and introduce three improvements. We begin by showing that the types of generalizations evolved by XCSF can be influenced by the input range. To explain these results we present a theoretical analysis of the convergence of classifier weights in XCSF which highlights a broader issue. In XCSF, because of the mathematical properties of the Widrow-Hoff update, the convergence of classifier weights in a given subspace can be slow when the spread of the eigenvalues of the autocorrelation matrix associated with each classifier is large. As a major consequence, the system's accuracy pressure may act before classifier weights are adequately updated, so that XCSF may evolve piecewise constant approximations, instead of the intended, and more efficient, piecewise linear ones. We propose three different ways to update classifier weights in XCSF so as to increase the generalization capabilities of XCSF: one based on a condition-based normalization of the inputs, one based on linear least squares, and one based on the recursive version of linear least squares. Through a series of experiments we show that while all three approaches significantly improve XCSF, least squares approaches appear to be best performing and most robust. Finally we show how XCSF can be extended to include polynomial approximations.
Made Wiryana
2016-06-01
Full Text Available Background: A cell injury from surgical stress in a trauma or a non-trauma case will induce a hyper metabolic response in which the protein degradation increases, the somatic protein synthesis decreases and the amino acid catabolism increases. Thus, the pyper metabolic response contributes to nitrogen loss in urine. This response, without an adequate nutrition, will lead an iatrogenic malnutrition and deterioration. A balance nitrogen formula through urinary urea nitrogen is one of many nutrition evaluation methods. This method aids in evaluating the daily nutrition status and it can be the baseline data for daily intake. Objective: To find a correlation between the protein intake and the nitrogen balance of the surgical patients in anesthesiology and intensive care installation, Sanglah General Hospital, Denpasar, Bali. Methods: Fifty-one surgical patients with trauma and non-trauma cases were observed for their protein intake for 2-3 days continuously. Moreover, they were evaluated for their nitrogen balance based on the urinary urea nitrogen per 24 hours for 2-3 days. For statistical analysis, we utilized Shapiro-Francia, Shapiro-Wilk, Spearman Frank correlation, two-sample t test, and multivariate regression analysis in Strata SE 12.1. Results: The correlation between the protein intake and the nitrogen balance on the first day was ra=0.50 (p<0.05, on the second day ra=0.70 (p<0,05, and on the third day ra=0.740 (p<0,05. Conclusions: There is a correlation between the protein intake and the nitrogen balance of surgical patients in Anesthesiology and Intensive Care Installation Sanglah General Hospital Denpasar.
Mutational analysis and clinical correlation of metastatic colorectal cancer.
Russo, Andrea L; Borger, Darrell R; Szymonifka, Jackie; Ryan, David P; Wo, Jennifer Y; Blaszkowsky, Lawrence S; Kwak, Eunice L; Allen, Jill N; Wadlow, Raymond C; Zhu, Andrew X; Murphy, Janet E; Faris, Jason E; Dias-Santagata, Dora; Haigis, Kevin M; Ellisen, Leif W; Iafrate, Anthony J; Hong, Theodore S
2014-05-15
Early identification of mutations may guide patients with metastatic colorectal cancer toward targeted therapies that may be life prolonging. The authors assessed tumor genotype correlations with clinical characteristics to determine whether mutational profiling can account for clinical similarities, differences, and outcomes. Under Institutional Review Board approval, 222 patients with metastatic colon adenocarcinoma (n = 158) and rectal adenocarcinoma (n = 64) who underwent clinical tumor genotyping were reviewed. Multiplexed tumor genotyping screened for >150 mutations across 15 commonly mutated cancer genes. The chi-square test was used to assess genotype frequency by tumor site and additional clinical characteristics. Cox multivariate analysis was used to assess the impact of genotype on overall survival. Broad-based tumor genotyping revealed clinical and anatomic differences that could be linked to gene mutations. NRAS mutations were associated with rectal cancer versus colon cancer (12.5% vs 0.6%; P colon cancer (13% vs 3%; P = .024) and older age (15.8% vs 4.6%; P = .006). TP53 mutations were associated with rectal cancer (30% vs 18%; P = .048), younger age (14% vs 28.7%; P = .007), and men (26.4% vs 14%; P = .03). Lung metastases were associated with PIK3CA mutations (23% vs 8.7%; P = .004). Only mutations in BRAF were independently associated with decreased overall survival (hazard ratio, 2.4; 95% confidence interval, 1.09-5.27; P = .029). The current study suggests that underlying molecular profiles can differ between colon and rectal cancers. Further investigation is warranted to assess whether the differences identified are important in determining the optimal treatment course for these patients. © 2014 American Cancer Society.
Wang, Gang-Jin; Xie, Chi; Chen, Shou; Yang, Jiao-Jiao; Yang, Ming-Yan
2013-09-01
In this study, we first build two empirical cross-correlation matrices in the US stock market by two different methods, namely the Pearson’s correlation coefficient and the detrended cross-correlation coefficient (DCCA coefficient). Then, combining the two matrices with the method of random matrix theory (RMT), we mainly investigate the statistical properties of cross-correlations in the US stock market. We choose the daily closing prices of 462 constituent stocks of S&P 500 index as the research objects and select the sample data from January 3, 2005 to August 31, 2012. In the empirical analysis, we examine the statistical properties of cross-correlation coefficients, the distribution of eigenvalues, the distribution of eigenvector components, and the inverse participation ratio. From the two methods, we find some new results of the cross-correlations in the US stock market in our study, which are different from the conclusions reached by previous studies. The empirical cross-correlation matrices constructed by the DCCA coefficient show several interesting properties at different time scales in the US stock market, which are useful to the risk management and optimal portfolio selection, especially to the diversity of the asset portfolio. It will be an interesting and meaningful work to find the theoretical eigenvalue distribution of a completely random matrix R for the DCCA coefficient because it does not obey the Marčenko-Pastur distribution.
Cost analysis of robotic versus laparoscopic general surgery procedures.
Higgins, Rana M; Frelich, Matthew J; Bosler, Matthew E; Gould, Jon C
2017-01-01
Robotic surgical systems have been used at a rapidly increasing rate in general surgery. Many of these procedures have been performed laparoscopically for years. In a surgical encounter, a significant portion of the total costs is associated with consumable supplies. Our hospital system has invested in a software program that can track the costs of consumable surgical supplies. We sought to determine the differences in cost of consumables with elective laparoscopic and robotic procedures for our health care organization. De-identified procedural cost and equipment utilization data were collected from the Surgical Profitability Compass Procedure Cost Manager System (The Advisory Board Company, Washington, DC) for our health care system for laparoscopic and robotic cholecystectomy, fundoplication, and inguinal hernia between the years 2013 and 2015. Outcomes were length of stay, case duration, and supply cost. Statistical analysis was performed using a t-test for continuous variables, and statistical significance was defined as p robotic procedures. Length of stay did not differ for fundoplication or cholecystectomy. Length of stay was greater for robotic inguinal hernia repair. Case duration was similar for cholecystectomy (84.3 robotic and 75.5 min laparoscopic, p = 0.08), but significantly longer for robotic fundoplication (197.2 robotic and 162.1 min laparoscopic, p = 0.01) and inguinal hernia repair (124.0 robotic and 84.4 min laparoscopic, p = ≪0.01). We found a significantly increased cost of general surgery procedures for our health care system when cases commonly performed laparoscopically are instead performed robotically. Our analysis is limited by the fact that we only included costs associated with consumable surgical supplies. The initial acquisition cost (over $1 million for robotic surgical system), depreciation, and service contract for the robotic and laparoscopic systems were not included in this analysis.
Carvalhana, Sofia; Leitão, Jorge; Alves, Ana C; Bourbon, Mafalda; Cortez-Pinto, Helena
2014-07-01
Liver steatosis measurement by controlled attenuation parameter (CAP) is a non-invasive method for diagnosing steatosis, based on transient elastography. Its usefulness as screening procedure for hepatic steatosis in general population has not been previously evaluated. The aim of this study was to evaluate the diagnostic accuracy of CAP and fatty liver index (FLI) for detection and quantification of steatosis in general population. Recruitment was done from a prospective epidemiological study of the general adult population. Steatosis was evaluated using CAP, FLI and ultrasound (US). Steatosis scored according to Hamaguchi's US scoring, from 0 (S0) to 6 (S6) points. Hepatic steatosis defined by score ≥2 (S≥2) and moderate/severe steatosis by score ≥4 (S≥4). Performance of CAP and FLI for diagnosing steatosis compared with US was assessed using areas under receiver operating characteristic curves (AUROC). From 219 consecutive individuals studied, 13 (5.9%) excluded because of failure/unreliable liver stiffness measurements. Steatosis prevalence: S≥2 38.4% and S≥4 12.1%. CAP significantly correlated with steatosis (ρ = 0.73, P steatosis score (ρ = 0.76; P steatosis quantification in the general population. Larger studies are needed for validation. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Correlation Function Analysis of Fiber Networks: Implications for Thermal Conductivity
Martinez-Garcia, Jorge; Braginsky, Leonid; Shklover, Valery; Lawson, John W.
2011-01-01
The heat transport in highly porous fiber structures is investigated. The fibers are supposed to be thin, but long, so that the number of the inter-fiber connections along each fiber is large. We show that the effective conductivity of such structures can be found from the correlation length of the two-point correlation function of the local conductivities. Estimation of the parameters, determining the conductivity, from the 2D images of the structures is analyzed.
Approximation generation for correlations in thermal-hydraulic analysis codes
Pereira, Luiz C.M.; Carmo, Eduardo G.D. do
1997-01-01
A fast and precise evaluation of fluid thermodynamic and transport properties is needed for the efficient mass, energy and momentum transport phenomena simulation related to nuclear plant power generation. A fully automatic code capable to generate suitable approximation for correlations with one or two independent variables is presented. Comparison in terms of access speed and precision with original correlations currently used shows the adequacy of the approximation obtained. (author). 4 refs., 8 figs., 1 tab
Generalized causal mediation and path analysis: Extensions and practical considerations.
Albert, Jeffrey M; Cho, Jang Ik; Liu, Yiying; Nelson, Suchitra
2018-01-01
Causal mediation analysis seeks to decompose the effect of a treatment or exposure among multiple possible paths and provide casually interpretable path-specific effect estimates. Recent advances have extended causal mediation analysis to situations with a sequence of mediators or multiple contemporaneous mediators. However, available methods still have limitations, and computational and other challenges remain. The present paper provides an extended causal mediation and path analysis methodology. The new method, implemented in the new R package, gmediation (described in a companion paper), accommodates both a sequence (two stages) of mediators and multiple mediators at each stage, and allows for multiple types of outcomes following generalized linear models. The methodology can also handle unsaturated models and clustered data. Addressing other practical issues, we provide new guidelines for the choice of a decomposition, and for the choice of a reference group multiplier for the reduction of Monte Carlo error in mediation formula computations. The new method is applied to data from a cohort study to illuminate the contribution of alternative biological and behavioral paths in the effect of socioeconomic status on dental caries in adolescence.
Vehicle technology under CO2 constraint: a general equilibrium analysis
Schaefer, Andreas; Jacoby, Henry D.
2006-01-01
A study is presented of the rates of penetration of different transport technologies under policy constraints on CO 2 emissions. The response of this sector is analyzed within an overall national level of restriction, with a focus on automobiles, light trucks, and heavy freight trucks. Using the US as an example, a linked set of three models is used to carry out the analysis: a multi-sector computable general equilibrium model of the economy, a MARKAL-type model of vehicle and fuel supply technology, and a model simulating the split of personal and freight transport among modes. Results highlight the importance of incremental improvements in conventional internal combustion engine technology, and, in the absence of policies to overcome observed consumer discount rates, the very long time horizons before radical alternatives like the internal combustion engine hybrid drive train vehicle are likely to take substantial market share
Stability analysis of embedded nonlinear predictor neural generalized predictive controller
Hesham F. Abdel Ghaffar
2014-03-01
Full Text Available Nonlinear Predictor-Neural Generalized Predictive Controller (NGPC is one of the most advanced control techniques that are used with severe nonlinear processes. In this paper, a hybrid solution from NGPC and Internal Model Principle (IMP is implemented to stabilize nonlinear, non-minimum phase, variable dead time processes under high disturbance values over wide range of operation. Also, the superiority of NGPC over linear predictive controllers, like GPC, is proved for severe nonlinear processes over wide range of operation. The necessary conditions required to stabilize NGPC is derived using Lyapunov stability analysis for nonlinear processes. The NGPC stability conditions and improvement in disturbance suppression are verified by both simulation using Duffing’s nonlinear equation and real-time using continuous stirred tank reactor. Up to our knowledge, the paper offers the first hardware embedded Neural GPC which has been utilized to verify NGPC–IMP improvement in realtime.
General analysis of slab lasers using geometrical optics.
Chung, Te-yuan; Bass, Michael
2007-02-01
A thorough and general geometrical optics analysis of a slab-shaped laser gain medium is presented. The length and thickness ratio is critical if one is to achieve the maximum utilization of absorbed pump power by the laser light in such a medium; e.g., the fill factor inside the slab is to be maximized. We point out that the conditions for a fill factor equal to 1, laser light entering and exiting parallel to the length of the slab, and Brewster angle incidence on the entrance and exit faces cannot all be satisfied at the same time. Deformed slabs are also studied. Deformation along the width direction of the largest surfaces is shown to significantly reduce the fill factor that is possible.
Inverse dynamic analysis of general n-link robot manipulators
Yih, T.C.; Wang, T.Y.; Burks, B.L.; Babcock, S.M.
1996-01-01
In this paper, a generalized matrix approach is derived to analyze the dynamic forces and moments (torques) required by the joint actuators. This method is general enough to solve the problems of any n-link open-chain robot manipulators with joint combinations of R(revolute), P(prismatic), and S(spherical). On the other hand, the proposed matrix solution is applicable to both nonredundant and redundant robotic systems. The matrix notation is formulated based on the Newton-Euler equations under the condition of quasi-static equilibrium. The 4 x 4 homogeneous cylindrical coordinates-Bryant angles (C-B) notation is applied to model the robotic systems. Displacements, velocities, and accelerations of each joint and link center of gravity (CG) are calculated through kinematic analysis. The resultant external forces and moments exerted on the CG of each link are considered as known inputs. Subsequently, a 6n x 6n displacement coefficient matrix and a 6n x 1 external force/moment vector can be established. At last, the joint forces and moments needed for the joint actuators to control the robotic system are determined through matrix inversion. Numerical examples will be illustrated for the nonredundant industrial robots: Bendix AA/CNC (RRP/RRR) and Unimate 2000 spherical (SP/RRR) robots; and the redundant light duty utility arm (LDUA), modified LDUA, and tank waste retrieval manipulator system
On the Analysis of Case-Control Studies in Cluster-correlated Data Settings.
Haneuse, Sebastien; Rivera-Rodriguez, Claudia
2018-01-01
In resource-limited settings, long-term evaluation of national antiretroviral treatment (ART) programs often relies on aggregated data, the analysis of which may be subject to ecological bias. As researchers and policy makers consider evaluating individual-level outcomes such as treatment adherence or mortality, the well-known case-control design is appealing in that it provides efficiency gains over random sampling. In the context that motivates this article, valid estimation and inference requires acknowledging any clustering, although, to our knowledge, no statistical methods have been published for the analysis of case-control data for which the underlying population exhibits clustering. Furthermore, in the specific context of an ongoing collaboration in Malawi, rather than performing case-control sampling across all clinics, case-control sampling within clinics has been suggested as a more practical strategy. To our knowledge, although similar outcome-dependent sampling schemes have been described in the literature, a case-control design specific to correlated data settings is new. In this article, we describe this design, discuss balanced versus unbalanced sampling techniques, and provide a general approach to analyzing case-control studies in cluster-correlated settings based on inverse probability-weighted generalized estimating equations. Inference is based on a robust sandwich estimator with correlation parameters estimated to ensure appropriate accounting of the outcome-dependent sampling scheme. We conduct comprehensive simulations, based in part on real data on a sample of N = 78,155 program registrants in Malawi between 2005 and 2007, to evaluate small-sample operating characteristics and potential trade-offs associated with standard case-control sampling or when case-control sampling is performed within clusters.
AN ANALYSIS OF MALIGNANCIES PRESENTING AS ACUTE GENERAL SURGICAL EMERGENCIES
Kannan Ross
2017-02-01
Full Text Available BACKGROUND Malignancies in the setting of acute general surgical emergencies are rare to present. The commonly presenting malignancies to the general surgeon in emergency conditions are perforation, obstruction, haemorrhage or urinary retention. Though their incidence when compared to benign conditions presenting with same clinical presentations are rare, they should never be neglected. The general surgeon must be aware of such presentations and hereby decide the management and follow up according to the malignancy he encounters on the operation theatre. The management should aim at radical procedures and regular follow up if needed with chemotherapy or radiotherapy and also should be well informed of the morbidity and mortality following intervention considering the malignancy grade, age of patient, duration of presentation and co-morbid conditions. MATERIALS AND METHODS In this study, we consider all patients taken up in emergency operative procedures, study their findings on operation theatre, correlate with their biopsy report for any malignancy and follow up during their immediate postop up to <30 days and also late post beyond the procedure and bring about the incidence, common modes of presentation, malignancies encountered, age and sex distribution and the perioperative morbidity and mortality rates of the those malignancies. RESULTS The incidence of malignancies presenting as acute abdominal emergencies in this study was found to be around 8.27%. The number of males who presented with such malignancies outnumbered females in a significant manner in the ratio 1.6:1. Among the malignancies, gastric (25% and colonic malignancies (59.38% were the most common. Perforation was the only presentation as acute emergency in carcinoma stomach. Incidence of malignancy in gastric perforation was 57.14% when compared to that reported by Emer Ergul et al that about 10-16% of all gastric perforations are caused by gastric carcinoma. 11 Perioperative
Analysis of factors correlating with medical radiological examination frequencies
Jahnen, A.; Jaervinen, H.; Bly, R.; Olerud, H.; Vassilieva, J.; Vogiatzi, S.; Shannoun, F.
2015-01-01
The European Commission (EC) funded project Dose Datamed 2 (DDM2) had two objectives: to collect available data on patient doses from the radiodiagnostic procedures (X-ray and nuclear medicine) in Europe, and to facilitate the implementation of the Radiation Protection 154 Guidelines (RP154). Besides the collection of frequency and dose data, two questionnaires were issued to gather information about medical radiological imaging. This article analyses a possible correlation between the collected frequency data, selected variables from the results of the detailed questionnaire and national economic data. Based on a 35 countries dataset, there is no correlation between the gross domestic product (GDP) and the total number of X-ray examinations in a country. However, there is a significant correlation ( p < 0.01) between the GDP and the overall CT examination frequency. High income countries perform more CT examinations per inhabitant. That suggests that planar X-ray examinations are replaced by CT examinations. (authors)
Thermodynamic correlations for the accident analysis of HTR's
Rehm, W.; Jahn, W.; Finken, R.
1976-12-01
The thermal properties of Helium and for the case of a depressurized primary circuit, various mixtures of primary cooling gas were taken into consideration. The temperature dependence of the correlations for the thermal properties of the graphite components in the core and for the structural materials in the primary circuit are extrapolated about normal operation conditions. Furthermore the correlations for the effective thermal conductivity, the heat transfer and pressure drop are described for pebble bed HTR's. In addition some important heat transfer data of the steam generator are included. With these correlations, for example accident sequences with failure of the afterheat removal systems are discussed for pebble bed HTR's. It is concluded that the transient temperature behaviour demonstrates the inherent safety features of the HTR in extreme accidents. (orig.) [de
Gerald: a general environment for radiation analysis and design
Boyle, Ch.; Oliveira, P.I.E. de; Oliveira, C.R.E. de; Adams, M.L.; Galan, J.M.
2005-01-01
Full text of publication follows: This paper describes the status of the GERALD interactive workbench for the analysis of radiation transport problems. GERALD basically guides the user through the various steps that are necessary to solve a radiation transport problem, and is aimed at education, research and industry. The advantages of such workbench are many: quality assurance of problem setup, interaction of the user with problem solution, preservation of theory and legacy research codes, and rapid proto-typing and testing of new methods. The environment is of general applicability catering for analytical, deterministic and stochastic analysis of the radiation problem and is not tied to one specific solution method or code. However, GERALD is being developed as a portable, modular, open source framework which renders itself quite naturally to the coupling of existing computational tools through specifically developed plug-ins. By offering a common route for setting up, solving and analyzing radiation transport problems GERALD offers the possibility of methods intercomparison and validation. Such flexible radiation transport environment will also facilitate the coupling of radiation physics methods to other physical phenomena and their application to other areas of application such as medical physics and the environment. (authors)
Generalization error analysis: deep convolutional neural network in mammography
Richter, Caleb D.; Samala, Ravi K.; Chan, Heang-Ping; Hadjiiski, Lubomir; Cha, Kenny
2018-02-01
We conducted a study to gain understanding of the generalizability of deep convolutional neural networks (DCNNs) given their inherent capability to memorize data. We examined empirically a specific DCNN trained for classification of masses on mammograms. Using a data set of 2,454 lesions from 2,242 mammographic views, a DCNN was trained to classify masses into malignant and benign classes using transfer learning from ImageNet LSVRC-2010. We performed experiments with varying amounts of label corruption and types of pixel randomization to analyze the generalization error for the DCNN. Performance was evaluated using the area under the receiver operating characteristic curve (AUC) with an N-fold cross validation. Comparisons were made between the convergence times, the inference AUCs for both the training set and the test set of the original image patches without corruption, and the root-mean-squared difference (RMSD) in the layer weights of the DCNN trained with different amounts and methods of corruption. Our experiments observed trends which revealed that the DCNN overfitted by memorizing corrupted data. More importantly, this study improved our understanding of DCNN weight updates when learning new patterns or new labels. Although we used a specific classification task with the ImageNet as example, similar methods may be useful for analysis of the DCNN learning processes, especially those that employ transfer learning for medical image analysis where sample size is limited and overfitting risk is high.
Refined generalized multiscale entropy analysis for physiological signals
Liu, Yunxiao; Lin, Youfang; Wang, Jing; Shang, Pengjian
2018-01-01
Multiscale entropy analysis has become a prevalent complexity measurement and been successfully applied in various fields. However, it only takes into account the information of mean values (first moment) in coarse-graining procedure. Then generalized multiscale entropy (MSEn) considering higher moments to coarse-grain a time series was proposed and MSEσ2 has been implemented. However, the MSEσ2 sometimes may yield an imprecise estimation of entropy or undefined entropy, and reduce statistical reliability of sample entropy estimation as scale factor increases. For this purpose, we developed the refined model, RMSEσ2, to improve MSEσ2. Simulations on both white noise and 1 / f noise show that RMSEσ2 provides higher entropy reliability and reduces the occurrence of undefined entropy, especially suitable for short time series. Besides, we discuss the effect on RMSEσ2 analysis from outliers, data loss and other concepts in signal processing. We apply the proposed model to evaluate the complexity of heartbeat interval time series derived from healthy young and elderly subjects, patients with congestive heart failure and patients with atrial fibrillation respectively, compared to several popular complexity metrics. The results demonstrate that RMSEσ2 measured complexity (a) decreases with aging and diseases, and (b) gives significant discrimination between different physiological/pathological states, which may facilitate clinical application.
General metabolism of Laribacter hongkongensis: a genome-wide analysis
Curreem Shirly O
2011-04-01
Full Text Available Abstract Background Laribacter hongkongensis is associated with community-acquired gastroenteritis and traveler's diarrhea. In this study, we performed an in-depth annotation of the genes and pathways of the general metabolism of L. hongkongensis and correlated them with its phenotypic characteristics. Results The L. hongkongensis genome possesses the pentose phosphate and gluconeogenesis pathways and tricarboxylic acid and glyoxylate cycles, but incomplete Embden-Meyerhof-Parnas and Entner-Doudoroff pathways, in agreement with its asaccharolytic phenotype. It contains enzymes for biosynthesis and β-oxidation of saturated fatty acids, biosynthesis of all 20 universal amino acids and selenocysteine, the latter not observed in Neisseria gonorrhoeae, Neisseria meningitidis and Chromobacterium violaceum. The genome contains a variety of dehydrogenases, enabling it to utilize different substrates as electron donors. It encodes three terminal cytochrome oxidases for respiration using oxygen as the electron acceptor under aerobic and microaerophilic conditions and four reductases for respiration with alternative electron acceptors under anaerobic conditions. The presence of complete tetrathionate reductase operon may confer survival advantage in mammalian host in association with diarrhea. The genome contains CDSs for incorporating sulfur and nitrogen by sulfate assimilation, ammonia assimilation and nitrate reduction. The existence of both glutamate dehydrogenase and glutamine synthetase/glutamate synthase pathways suggests an importance of ammonia metabolism in the living environments that it may encounter. Conclusions The L. hongkongensis genome possesses a variety of genes and pathways for carbohydrate, amino acid and lipid metabolism, respiratory chain and sulfur and nitrogen metabolism. These allow the bacterium to utilize various substrates for energy production and survive in different environmental niches.
Variability, correlation and path coefficient analysis of seedling traits ...
use
2011-12-12
Dec 12, 2011 ... Indirect selection is a useful means for improving yield in cotton crop. The objective of the present study was to determine the genetic variability, broad sense heritability, genetic advance and correlation among the six seedling traits and their direct and indirect effects on cotton yield by using path coefficient ...
Correlation of energy balance method to dynamic pipe rupture analysis
Kuo, H.H.; Durkee, M.
1983-01-01
When using an energy balance approach in the design of pipe rupture restraints for nuclear power plants, the NRC specifies in its Standard Review Plan 3.6.2 that the input energy to the system must be multiplied by a factor of 1.1 unless a lower value can be justified. Since the energy balance method is already quite conservative, an across-the-board use of 1.1 to amplify the energy input appears unneccessary. The paper's purpose is to show that this 'correlation factor' could be substantially less than unity if certain design parameters are met. In this paper, result of nonlinear dynamic analyses were compared to the results of the corresponding analyses based on the energy balance method which assumes constant blowdown forces and rigid plastic material properties. The appropriate correlation factors required to match the energy balance results with the dynamic analyses results were correlated to design parameters such as restraint location from the break, yield strength of the energy absorbing component, and the restraint gap. It is shown that the correlation factor is related to a single nondimensional design parameter and can be limited to a value below unity if appropriate design parameters are chosen. It is also shown that the deformation of the restraints can be related to dimensionless system parameters. This, therefore, allows the maximum restraint deformation to be evaluated directly for design purposes. (orig.)
Correlation Analysis of some Growth, Yield, Yield Components and ...
three critical growth stages which was imposed by withholding water (at ... November, 5th December, 19th December and 2nd January) laid out in a split ... Simple correlation coefficient ® of different crop parameters and grain yield ... The husk bran and germ are rich sources of ..... heat in 2009/2010 dry season at Fadam a ...
Linear analysis of degree correlations in complex networks
2016-11-02
Nov 2, 2016 ... 4College of Science, Qi Lu University of Technology, Jinan 250353, Shandong, China ... cal methods used usually to describe the degree correlation in the ... Most social networks show assorta- .... a clear but only qualitative description of the degree ... is difficult to give quantitative relation between DCC.
Correlational Analysis of Servant Leadership and School Climate
Black, Glenda Lee
2010-01-01
The purpose of this mixed-method research study was to determine the extent that servant leadership was correlated with perceptions of school climate to identify whether there was a relationship between principals' and teachers' perceived practice of servant leadership and of school climate. The study employed a mixed-method approach by first…
Analysis of Current HT9 Creep Correlations and Modification
Lee, Cheol Min; Sohn, Dongseong; Cheon, Jin Sik
2014-01-01
It has high thermal conductivity, high mechanical strength and low irradiation induced swelling. However high temperature creep of HT9 has always been a life limiting factor. Above 600 .deg. C, the dislocation density in HT9 is decreased and the M 23 C 6 precipitates coarsen, these processes are accelerated if there is irradiation. Finally microstructural changes at high temperature lead to lower creep strength and large creep strain. For HT9 to be used as a future cladding, creep behavior of the HT9 should be predicted accurately based on the physical understanding of the creep phenomenon. Most of the creep correlations are composed of irradiation creep and thermal creep terms. However, it is certain that in-pile thermal creep and out-of-pile thermal creep are different because of the microstructure changes induced from neutron irradiation. To explain creep behavior more accurately, thermal creep contributions other than neutron irradiation should be discriminated in a creep correlation. To perform this work, existing HT9 creep correlations are analyzed, and the results are used to develop more accurate thermal creep correlation. Then, the differences between in-pile thermal creep and out-of-pile thermal creep are examined
Murase, Kimihiko; Tabara, Yasuharu; Takahashi, Yoshimitsu; Muro, Shigeo; Yamada, Ryo; Setoh, Kazuya; Kawaguchi, Takahisa; Kadotani, Hiroshi; Kosugi, Shinji; Sekine, Akihiro; Nakayama, Takeo; Mishima, Michiaki; Chiba, Tsutomu; Chin, Kazuo; Matsuda, Fumihiko
2014-11-01
To examine relationships among gastroesophageal reflux disease (GERD) symptoms, dietary behaviors, and sleep duration in the general population. Cross-sectional. Community-based. There were 9,643 participants selected from the general population (54 ± 13 y). None. Sleep duration, sleep habits, and unfavorable dietary behaviors of each participant were assessed with a structured questionnaire. Participants were categorized into five groups according to their sleep duration: less than 5 h, 5 to less than 6 h, 6 to less than 7 h, 7 to less than 8 h, and 8 or more h per day. GERD was evaluated using the Frequency Scale for the Symptoms of GERD (FSSG) and participants having an FSSG score of 8 or more or those under treatment of GERD were defined as having GERD. Trend analysis showed that both the FSSG score and the number of unfavorable dietary habits increased with decreasing sleep duration. Further, multiple logistic regression analysis showed that both the presence of GERD (odds ratio = 1.19, 95% confidence interval (CI) = 1.07-1.32) and the number of unfavorable dietary behaviors (odds ratio = 1.19, 95% CI = 1.13-1.26) were independent and potent factors to identify participants with short sleep duration even after controlling for other confounding factors. The current study showed that both GERD symptoms and unfavorable dietary behaviors were significant correlates of short sleep duration independently of each other in a large sample from the general population.
SNAP: A General Purpose Network Analysis and Graph Mining Library.
Leskovec, Jure; Sosič, Rok
2016-10-01
Large networks are becoming a widely used abstraction for studying complex systems in a broad set of disciplines, ranging from social network analysis to molecular biology and neuroscience. Despite an increasing need to analyze and manipulate large networks, only a limited number of tools are available for this task. Here, we describe Stanford Network Analysis Platform (SNAP), a general-purpose, high-performance system that provides easy to use, high-level operations for analysis and manipulation of large networks. We present SNAP functionality, describe its implementational details, and give performance benchmarks. SNAP has been developed for single big-memory machines and it balances the trade-off between maximum performance, compact in-memory graph representation, and the ability to handle dynamic graphs where nodes and edges are being added or removed over time. SNAP can process massive networks with hundreds of millions of nodes and billions of edges. SNAP offers over 140 different graph algorithms that can efficiently manipulate large graphs, calculate structural properties, generate regular and random graphs, and handle attributes and meta-data on nodes and edges. Besides being able to handle large graphs, an additional strength of SNAP is that networks and their attributes are fully dynamic, they can be modified during the computation at low cost. SNAP is provided as an open source library in C++ as well as a module in Python. We also describe the Stanford Large Network Dataset, a set of social and information real-world networks and datasets, which we make publicly available. The collection is a complementary resource to our SNAP software and is widely used for development and benchmarking of graph analytics algorithms.
General tensor discriminant analysis and gabor features for gait recognition.
Tao, Dacheng; Li, Xuelong; Wu, Xindong; Maybank, Stephen J
2007-10-01
The traditional image representations are not suited to conventional classification methods, such as the linear discriminant analysis (LDA), because of the under sample problem (USP): the dimensionality of the feature space is much higher than the number of training samples. Motivated by the successes of the two dimensional LDA (2DLDA) for face recognition, we develop a general tensor discriminant analysis (GTDA) as a preprocessing step for LDA. The benefits of GTDA compared with existing preprocessing methods, e.g., principal component analysis (PCA) and 2DLDA, include 1) the USP is reduced in subsequent classification by, for example, LDA; 2) the discriminative information in the training tensors is preserved; and 3) GTDA provides stable recognition rates because the alternating projection optimization algorithm to obtain a solution of GTDA converges, while that of 2DLDA does not. We use human gait recognition to validate the proposed GTDA. The averaged gait images are utilized for gait representation. Given the popularity of Gabor function based image decompositions for image understanding and object recognition, we develop three different Gabor function based image representations: 1) the GaborD representation is the sum of Gabor filter responses over directions, 2) GaborS is the sum of Gabor filter responses over scales, and 3) GaborSD is the sum of Gabor filter responses over scales and directions. The GaborD, GaborS and GaborSD representations are applied to the problem of recognizing people from their averaged gait images.A large number of experiments were carried out to evaluate the effectiveness (recognition rate) of gait recognition based on first obtaining a Gabor, GaborD, GaborS or GaborSD image representation, then using GDTA to extract features and finally using LDA for classification. The proposed methods achieved good performance for gait recognition based on image sequences from the USF HumanID Database. Experimental comparisons are made with nine
A sensory analysis of butter cookies: An application of generalized procrustes analysis
Juhl, Hans Jørn
1994-01-01
Executive Summary: 1. A sensory analysis is one of the first steps in product development in the food industry. A thorough analysis of the results from such an analysis may give important input to the development process. 2. A sensory analysis on butter cookies is conducted in order to evaluate...... if some butter may be replaced by vegetable fat without a significant change in the sensory profile. The conclusion is that the replacement is possible without a considerable change in the sensory profile. 3. Generalized Procrustes Analysis is used to analyze the results. It is a relatively new technique...
Approximate models for the analysis of laser velocimetry correlation functions
Robinson, D.P.
1981-01-01
Velocity distributions in the subchannels of an eleven pin test section representing a slice through a Fast Reactor sub-assembly were measured with a dual beam laser velocimeter system using a Malvern K 7023 digital photon correlator for signal processing. Two techniques were used for data reduction of the correlation function to obtain velocity and turbulence values. Whilst both techniques were in excellent agreement on the velocity, marked discrepancies were apparent in the turbulence levels. As a consequence of this the turbulence data were not reported. Subsequent investigation has shown that the approximate technique used as the basis of Malvern's Data Processor 7023V is restricted in its range of application. In this note alternative approximate models are described and evaluated. The objective of this investigation was to develop an approximate model which could be used for on-line determination of the turbulence level. (author)
Clifton, P.M.
1985-03-01
This study examines the sensitivity of the travel time distribution predicted by a reference case model to (1) scale of representation of the model parameters, (2) size of the model domain, (3) correlation range of log-transmissivity, and (4) cross correlations between transmissivity and effective thickness. The basis for the reference model is the preliminary stochastic travel time model previously documented by the Basalt Waste Isolation Project. Results of this study show the following. The variability of the predicted travel times can be adequately represented when the ratio between the size of the zones used to represent the model parameters and the log-transmissivity correlation range is less than about one-fifth. The size of the model domain and the types of boundary conditions can have a strong impact on the distribution of travel times. Longer log-transmissivity correlation ranges cause larger variability in the predicted travel times. Positive cross correlation between transmissivity and effective thickness causes a decrease in the travel time variability. These results demonstrate the need for a sound conceptual model prior to conducting a stochastic travel time analysis
Dynamics of market correlations: taxonomy and portfolio analysis.
Onnela, J-P; Chakraborti, A; Kaski, K; Kertész, J; Kanto, A
2003-11-01
The time dependence of the recently introduced minimum spanning tree description of correlations between stocks, called the "asset tree" has been studied in order to reflect the financial market taxonomy. The nodes of the tree are identified with stocks and the distance between them is a unique function of the corresponding element of the correlation matrix. By using the concept of a central vertex, chosen as the most strongly connected node of the tree, an important characteristic is defined by the mean occupation layer. During crashes, due to the strong global correlation in the market, the tree shrinks topologically, and this is shown by a low value of the mean occupation layer. The tree seems to have a scale-free structure where the scaling exponent of the degree distribution is different for "business as usual" and "crash" periods. The basic structure of the tree topology is very robust with respect to time. We also point out that the diversification aspect of portfolio optimization results in the fact that the assets of the classic Markowitz portfolio are always located on the outer leaves of the tree. Technical aspects such as the window size dependence of the investigated quantities are also discussed.
Comparison and Correlation Analysis of Different Swine Breeds Meat Quality
Y. X. Li
2013-07-01
Full Text Available This study was performed to determine the influence of pig breed and gender on the ultimate pH and physicochemical properties of pork. The correlations between pH and pork quality traits directly related to carcass grade, and consumer’s preference were also evaluated. The pH and meat grading scores for cold carcasses of 215 purebred pigs (Duroc, Landrace, and Yorkshire from four different farms were obtained. Meat quality parameters of the pork loin were analyzed. Duroc and female animals were more affected compared to other breeds and male pigs. Duroc animals had the highest ultimate pH, carcass back fat thickness, marbling scores, yellowness, and fat content (p<0.05. Landrace pigs had the highest color lightness and cooking loss values (p<0.05. Among all trait parameters, marbling scores showed the highest significant differences when evaluating the impact of breed and gender on meat quality characteristics (p<0.001. Ultimate pH was positively correlated with carcass weight (0.20, back fat thickness (0.19, marbling score (0.17, and color score (0.16 while negatively correlated with cooking loss (−0.24 and shear force (−0.20. Therefore, pork samples with lower ultimate pH had lower cooking loss, higher lightness, and higher shear force values irrespective of breed.
Dynamics of market correlations: Taxonomy and portfolio analysis
Onnela, J.-P.; Chakraborti, A.; Kaski, K.; Kertész, J.; Kanto, A.
2003-11-01
The time dependence of the recently introduced minimum spanning tree description of correlations between stocks, called the “asset tree” has been studied in order to reflect the financial market taxonomy. The nodes of the tree are identified with stocks and the distance between them is a unique function of the corresponding element of the correlation matrix. By using the concept of a central vertex, chosen as the most strongly connected node of the tree, an important characteristic is defined by the mean occupation layer. During crashes, due to the strong global correlation in the market, the tree shrinks topologically, and this is shown by a low value of the mean occupation layer. The tree seems to have a scale-free structure where the scaling exponent of the degree distribution is different for “business as usual” and “crash” periods. The basic structure of the tree topology is very robust with respect to time. We also point out that the diversification aspect of portfolio optimization results in the fact that the assets of the classic Markowitz portfolio are always located on the outer leaves of the tree. Technical aspects such as the window size dependence of the investigated quantities are also discussed.
Correlation analysis on alpha attenuation and nasal skin temperature
Nozawa, Akio; Tacano, Munecazu
2009-01-01
Some serious accidents caused by declines in arousal level, such as traffic accidents and mechanical control mistakes, have become issues of social concern. The physiological index obtained by human body measurement is expected to offer a leading tool for evaluating arousal level as an objective indicator. In this study, declines in temporal arousal levels were evaluated by nasal skin temperature. As arousal level declines, sympathetic nervous activity is decreased and blood flow in peripheral vessels is increased. Since peripheral vessels exist just under the skin on the fingers and nose, the psychophysiological state can be judged from the displacement of skin temperature caused by changing blood flow volume. Declining arousal level is expected to be observable as a temperature rise in peripheral parts of the body. The objective of this experiment was to obtain assessment criteria for judging declines in arousal level by nasal skin temperature using the alpha attenuation coefficient (AAC) of electroencephalography (EEG) as a reference benchmark. Furthermore, a psychophysical index of sleepiness was also measured using a visual analogue scale (VAS). Correlations between nasal skin temperature index and EEG index were analyzed. AAC and maximum displacement of nasal skin temperature displayed a clear negative correlation, with a correlation coefficient of −0.55
Feynman-α correlation analysis by prompt-photon detection
Hashimoto, Kengo; Yamada, Sumasu; Hasegawa, Yasuhiro; Horiguchi, Tetsuo
1998-01-01
Two-detector Feynman-α measurements were carried out using the UTR-KINKI reactor, a light-water-moderated and graphite-reflected reactor, by detecting high-energy, prompt gamma rays. For comparison, the conventional measurements by detecting neutrons were also performed. These measurements were carried out in the subcriticality range from 0 to $1.8. The gate-time dependence of the variance-and covariance-to-mean ratios measured by gamma-ray detection were nearly identical with those obtained using standard neutron-detection techniques. Consequently, the prompt-neutron decay constants inferred from the gamma-ray correlation data agreed with those from the neutron data. Furthermore, the correlated-to-uncorrelated amplitude ratios obtained by gamma-ray detection significantly depended on the low-energy discriminator level of the single-channel analyzer. The discriminator level was determined as optimum for obtaining a maximum value of the amplitude ratio. The maximum amplitude ratio was much larger than that obtained by neutron detection. The subcriticality dependence of the decay constant obtained by gamma-ray detection was consistent with that obtained by neutron detection and followed the linear relation based on the one-point kinetic model in the vicinity of delayed critical. These experimental results suggest that the gamma-ray correlation technique can be applied to measure reactor kinetic parameters more efficiently
Thanatophoric dysplasia. Correlation among bone X-ray morphometry, histopathology, and gene analysis
Pazzaglia, Ugo E.; Donzelli, Carla M.; Izzi, Claudia; Baldi, Maurizia; Di Gaetano, Giuseppe; Bondioni, MariaPia
2014-01-01
Documentation through X-ray morphometry and histology of the steady phenotype expressed by FGFR3 gene mutation and interpolation of mechanical factors on spine and long bones dysmorphism. Long bones and spine of eight thanatophoric dysplasia and three age-matched controls without skeletal dysplasia were studied after pregnancy termination between the 18th and the 22nd week with X-ray morphometry, histology, and molecular analysis. Statistical analysis with comparison between TD cases and controls and intraobserver/interobserver variation were applied to X-ray morphometric data. Generalized shortening of long bones was observed in TD. A variable distribution of axial deformities was correlated with chondrocyte proliferation inhibition, defective seriate cell columns organization, and final formation of the primary metaphyseal trabeculae. The periosteal longitudinal growth was not equally inhibited, so that decoupling with the cartilage growth pattern produced the typical lateral spurs around the metaphyseal growth plates. In spine, platyspondyly was due to a reduced height of the vertebral body anterior ossification center, while its enlargement in the transversal plane was not restricted. The peculiar radiographic and histopathological features of TD bones support the hypothesis of interpolation of mechanical factors with FGFR3 gene mutations. The correlated observations of X-ray morphometry, histopathology, and gene analysis prompted the following diagnostic workup for TD: (1) prenatal sonography suspicion of skeletal dysplasia; (2) post-mortem X-ray morphometry for provisional diagnosis; (3) confirmation by genetic tests (hot-spot exons 7, 10, 15, and 19 analysis with 80-90 % sensibility); (4) in negative cases if histopathology confirms TD diagnosis, research of rare mutations through sequential analysis of FGFR3 gene. (orig.)
Thanatophoric dysplasia. Correlation among bone X-ray morphometry, histopathology, and gene analysis
Pazzaglia, Ugo E. [University of Brescia, Orthopaedic Clinic, Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, Brescia (Italy); Donzelli, Carla M. [Spedali Civili di Brescia, Morbid Anatomy Department, Brescia (Italy); Izzi, Claudia [University of Brescia, Prenatal Diagnosis Unit, Department of Obstetrics and Gynaecology, Brescia (Italy); Baldi, Maurizia [Hospital Galliera, Human Genetic Laboratory, Genova (Italy); Di Gaetano, Giuseppe; Bondioni, MariaPia [University of Brescia, Paediatric Radiology, Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, Brescia (Italy)
2014-09-15
Documentation through X-ray morphometry and histology of the steady phenotype expressed by FGFR3 gene mutation and interpolation of mechanical factors on spine and long bones dysmorphism. Long bones and spine of eight thanatophoric dysplasia and three age-matched controls without skeletal dysplasia were studied after pregnancy termination between the 18th and the 22nd week with X-ray morphometry, histology, and molecular analysis. Statistical analysis with comparison between TD cases and controls and intraobserver/interobserver variation were applied to X-ray morphometric data. Generalized shortening of long bones was observed in TD. A variable distribution of axial deformities was correlated with chondrocyte proliferation inhibition, defective seriate cell columns organization, and final formation of the primary metaphyseal trabeculae. The periosteal longitudinal growth was not equally inhibited, so that decoupling with the cartilage growth pattern produced the typical lateral spurs around the metaphyseal growth plates. In spine, platyspondyly was due to a reduced height of the vertebral body anterior ossification center, while its enlargement in the transversal plane was not restricted. The peculiar radiographic and histopathological features of TD bones support the hypothesis of interpolation of mechanical factors with FGFR3 gene mutations. The correlated observations of X-ray morphometry, histopathology, and gene analysis prompted the following diagnostic workup for TD: (1) prenatal sonography suspicion of skeletal dysplasia; (2) post-mortem X-ray morphometry for provisional diagnosis; (3) confirmation by genetic tests (hot-spot exons 7, 10, 15, and 19 analysis with 80-90 % sensibility); (4) in negative cases if histopathology confirms TD diagnosis, research of rare mutations through sequential analysis of FGFR3 gene. (orig.)
Creating Lasting Behavioral Change through the Generalization Analysis Worksheet
Brady, John; Kotkin, Ron
2011-01-01
The goal of any behavioral program is to facilitate lasting change. A significant criticism of behavioral programs is that they work in the clinical setting but do not generalize once the clinical program is stopped. The authors suggest that behavioral programs often do not generalize because clinicians fail to plan for generalization to occur…
Delignières, Didier; Marmelat, Vivien
2014-01-01
In this paper, we analyze empirical data, accounting for coordination processes between complex systems (bimanual coordination, interpersonal coordination, and synchronization with a fractal metronome), by using a recently proposed method: detrended cross-correlation analysis (DCCA). This work is motivated by the strong anticipation hypothesis, which supposes that coordination between complex systems is not achieved on the basis of local adaptations (i.e., correction, predictions), but results from a more global matching of complexity properties. Indeed, recent experiments have evidenced a very close correlation between the scaling properties of the series produced by two coordinated systems, despite a quite weak local synchronization. We hypothesized that strong anticipation should result in the presence of long-range cross-correlations between the series produced by the two systems. Results allow a detailed analysis of the effects of coordination on the fluctuations of the series produced by the two systems. In the long term, series tend to present similar scaling properties, with clear evidence of long-range cross-correlation. Short-term results strongly depend on the nature of the task. Simulation studies allow disentangling the respective effects of noise and short-term coupling processes on DCCA results, and suggest that the matching of long-term fluctuations could be the result of short-term coupling processes.
Felleki, M; Lee, D; Lee, Y; Gilmour, A R; Rönnegård, L
2012-12-01
The possibility of breeding for uniform individuals by selecting animals expressing a small response to environment has been studied extensively in animal breeding. Bayesian methods for fitting models with genetic components in the residual variance have been developed for this purpose, but have limitations due to the computational demands. We use the hierarchical (h)-likelihood from the theory of double hierarchical generalized linear models (DHGLM) to derive an estimation algorithm that is computationally feasible for large datasets. Random effects for both the mean and residual variance parts of the model are estimated together with their variance/covariance components. An important feature of the algorithm is that it can fit a correlation between the random effects for mean and variance. An h-likelihood estimator is implemented in the R software and an iterative reweighted least square (IRWLS) approximation of the h-likelihood is implemented using ASReml. The difference in variance component estimates between the two implementations is investigated, as well as the potential bias of the methods, using simulations. IRWLS gives the same results as h-likelihood in simple cases with no severe indication of bias. For more complex cases, only IRWLS could be used, and bias did appear. The IRWLS is applied on the pig litter size data previously analysed by Sorensen & Waagepetersen (2003) using Bayesian methodology. The estimates we obtained by using IRWLS are similar to theirs, with the estimated correlation between the random genetic effects being -0·52 for IRWLS and -0·62 in Sorensen & Waagepetersen (2003).
Wolf, David R.
2004-01-01
The topic of this paper is a hierarchy of information-like functions, here named the information correlation functions, where each function of the hierarchy may be thought of as the information between the variables it depends upon. The information correlation functions are particularly suited to the description of the emergence of complex behaviors due to many- body or many-agent processes. They are particularly well suited to the quantification of the decomposition of the information carried among a set of variables or agents, and its subsets. In more graphical language, they provide the information theoretic basis for understanding the synergistic and non-synergistic components of a system, and as such should serve as a forceful toolkit for the analysis of the complexity structure of complex many agent systems. The information correlation functions are the natural generalization to an arbitrary number of sets of variables of the sequence starting with the entropy function (one set of variables) and the mutual information function (two sets). We start by describing the traditional measures of information (entropy) and mutual information.
Sampling in forests for radionuclide analysis. General and practical guidance
Aro, Lasse (Finnish Forest Research Inst. (METLA) (Finland)); Plamboeck, Agneta H. (Swedish Defence Research Agency (FOI) (Sweden)); Rantavaara, Aino; Vetikko, Virve (Radiation and Nuclear Safety Authority (STUK) (Finland)); Straalberg, Elisabeth (Inst. Energy Technology (IFE) (Norway))
2009-01-15
The NKS project FOREST was established to prepare a guide for sampling in forest ecosystems for radionuclide analysis. The aim of this guide is to improve the reliability of datasets generated in future studies by promoting the use of consistent, recommended practices, thorough documentation of field sampling regimes and robust preparation of samples from the forest ecosystem. The guide covers general aims of sampling, the description of major compartments of the forest ecosystem and outlines key factors to consider when planning sampling campaigns for radioecological field studies in forests. Recommended and known sampling methods for various sample types are also compiled and presented. The guide focuses on sampling practices that are applicable in various types of boreal forests, robust descriptions of sampling sites, and documentation of the origin and details of individual samples. The guide is intended for scientists, students, forestry experts and technicians who appreciate the need to use sound sampling procedures in forest radioecological projects. The guide will hopefully encourage readers to participate in field studies and sampling campaigns, using robust techniques, thereby fostering competence in sampling. (au)
Sampling in forests for radionuclide analysis. General and practical guidance
Aro, Lasse; Plamboeck, Agneta H.; Rantavaara, Aino; Vetikko, Virve; Straelberg, Elisabeth
2009-01-01
The NKS project FOREST was established to prepare a guide for sampling in forest ecosystems for radionuclide analysis. The aim of this guide is to improve the reliability of datasets generated in future studies by promoting the use of consistent, recommended practices, thorough documentation of field sampling regimes and robust preparation of samples from the forest ecosystem. The guide covers general aims of sampling, the description of major compartments of the forest ecosystem and outlines key factors to consider when planning sampling campaigns for radioecological field studies in forests. Recommended and known sampling methods for various sample types are also compiled and presented. The guide focuses on sampling practices that are applicable in various types of boreal forests, robust descriptions of sampling sites, and documentation of the origin and details of individual samples. The guide is intended for scientists, students, forestry experts and technicians who appreciate the need to use sound sampling procedures in forest radioecological projects. The guide will hopefully encourage readers to participate in field studies and sampling campaigns, using robust techniques, thereby fostering competence in sampling. (au)
Yixiong Feng
2017-03-01
Full Text Available The problem of large amounts of carbon emissions causes wide concern across the world, and it has become a serious threat to the sustainable development of the manufacturing industry. The intensive research into technologies and methodologies for green product design has significant theoretical meaning and practical value in reducing the emissions of the manufacturing industry. Therefore, a low carbon-oriented product reliability optimal design model is proposed in this paper: (1 The related expert evaluation information was prepared in interval numbers; (2 An improved product failure analysis considering the uncertain carbon emissions of the subsystem was performed to obtain the subsystem weight taking the carbon emissions into consideration. The interval grey correlation analysis was conducted to obtain the subsystem weight taking the uncertain correlations inside the product into consideration. Using the above two kinds of subsystem weights and different caution indicators of the decision maker, a series of product reliability design schemes is available; (3 The interval-valued intuitionistic fuzzy sets (IVIFSs were employed to select the optimal reliability and optimal design scheme based on three attributes, namely, low carbon, correlation and functions, and economic cost. The case study of a vertical CNC lathe proves the superiority and rationality of the proposed method.
Admixture analysis of age of onset in generalized anxiety disorder.
Rhebergen, Didi; Aderka, Idan M; van der Steenstraten, Ira M; van Balkom, Anton J L M; van Oppen, Patricia; Stek, Max L; Comijs, Hannie C; Batelaan, Neeltje M
2017-08-01
Age of onset is a marker of clinically relevant subtypes in various medical and psychiatric disorders. Past research has also reported that age of onset in generalized anxiety disorder (GAD) is clinically significant; but, in research to date, arbitrary cut-off ages have been used. In the present study, admixture analysis was used to determine the best fitting model for age of onset distribution in GAD. Data were derived from 459 adults with a diagnosis of GAD who took part in the Netherlands Study of Depression and Anxiety (NESDA). Associations between age of onset subtypes, identified by admixture analysis, and sociodemographic, clinical, and vulnerability factors were examined using univariate tests and multivariate logistic regression analyses. Two age of onset distributions were identified: an early-onset group (24 years of age and younger) and a late-onset group (greater than 24 years of age). Multivariate analysis revealed that early-onset GAD was associated with female gender (OR 2.1 (95%CI 1.4-3.2)), higher education (OR 1.1 (95%CI 1.0-1.2)), and higher neuroticism (OR 1.4 (95%CI 1.1-1.7)), while late-onset GAD was associated with physical illnesses (OR 1.3 (95%CI 1.1-1.7)). Study limitations include the possibility of recall bias given that age of onset was assessed retrospectively, and an inability to detect a possible very-late-onset GAD subtype. Collectively, the results of the study indicate that GAD is characterized by a bimodal age of onset distribution with an objectively determined early cut-off at 24 years of age. Early-onset GAD is associated with unique factors that may contribute to its aetiology; but, it does not constitute a more severe subtype compared to late-onset GAD. Future research should use 24 years of age as the cut-off for early-onset GAD to when examining the clinical relevance of age of onset for treatment efficacy and illness course. Copyright © 2017 Elsevier Ltd. All rights reserved.
Harrington, Peter DEB.; Zheng, Peng
1995-01-01
Ion Mobility Spectrometry (IMS) is a powerful technique for trace organic analysis in the gas phase. Quantitative measurements are difficult, because IMS has a limited linear range. Factors that may affect the instrument response are pressure, temperature, and humidity. Nonlinear calibration methods, such as neural networks, may be ideally suited for IMS. Neural networks have the capability of modeling complex systems. Many neural networks suffer from long training times and overfitting. Cascade correlation neural networks train at very fast rates. They also build their own topology, that is a number of layers and number of units in each layer. By controlling the decay parameter in training neural networks, reproducible and general models may be obtained.
S-matrix analysis of the baryon electric charge correlation
Lo, Pok Man; Friman, Bengt; Redlich, Krzysztof; Sasaki, Chihiro
2018-03-01
We compute the correlation of the net baryon number with the electric charge (χBQ) for an interacting hadron gas using the S-matrix formulation of statistical mechanics. The observable χBQ is particularly sensitive to the details of the pion-nucleon interaction, which are consistently incorporated in the current scheme via the empirical scattering phase shifts. Comparing to the recent lattice QCD studies in the (2 + 1)-flavor system, we find that the natural implementation of interactions and the proper treatment of resonances in the S-matrix approach lead to an improved description of the lattice data over that obtained in the hadron resonance gas model.
The Asian crisis contagion: A dynamic correlation approach analysis
Essaadi Essahbi
2009-01-01
Full Text Available In this paper we are testing for contagion caused by the Thai baht collapse of July 1997. In line with earlier work, shift-contagion is defined as a structural change within the international propagation mechanisms of financial shocks. We adopt Bai and Perron's (1998 structural break approach in order to detect the endogenous break points of the pair-wise time-varying correlations between Thailand and seven Asian stock market returns. Our approach enables us to solve the misspecification problem of the crisis window. Our results illustrate the existence of shift-contagion in the Asian crisis caused by the crisis in Thailand.
Re-analysis of correlations among four impulsivity scales.
Gallardo-Pujol, David; Andrés-Pueyo, Antonio
2006-08-01
Impulsivity plays a key role in normal and pathological behavior. Although there is some consensus about its conceptualization, there have been many attempts to build a multidimensional tool due to the lack of agreement in how to measure it. A recent study claimed support for a three-dimensional structure of impulsivity, however with weak empirical support. By re-analysing those data, a four-factor structure was found to describe the correlation matrix much better. The debate remains open and further research is needed to clarify the factor structure. The desirability of constructing new measures, perhaps analogously to the Wechsler Intelligence Scale, is emphasized.
Correlation Analysis between Nominal and Real Convergence. The Romanian Case
Marius-Corneliu Marinas
2006-05-01
Full Text Available This study aims to analyze the sources of the correlation between the nominal and real convergence, as well as the impact of the macroeconomic politics on it. The perspective of Euro adoption will impose stricter management of monetary and budgetary politics, which will affect negatively the catching up process of the economic delays given the lack of higher economic flexibility. This enables a more rapid adjustment of the economy to some persistent shocks as a result of applying growth aggregate supply politics.
Correlation Analysis between Nominal and Real Convergence. The Romanian Case
Marius-Corneliu Marinas
2006-03-01
Full Text Available This study aims to analyze the sources of the correlation between the nominal and real convergence, as well as the impact of the macroeconomic politics on it. The perspective of Euro adoption will impose stricter management of monetary and budgetary politics, which will affect negatively the catching up process of the economic delays given the lack of higher economic flexibility. This enables a more rapid adjustment of the economy to some persistent shocks as a result of applying growth aggregate supply politics.
Prevalence and correlates of adult overweight in the Muslim world: analysis of 46 countries.
Kahan, D
2015-04-01
The primary objectives of the study were to calculate overweight prevalence (body mass index ≥ 25.0) and simple correlations between 10 demographic, social welfare and behavioural variables and overweight prevalence for Muslim countries (populations >50% Muslim; N = 46). Overweight data for a country's total, male and female populations were extracted from the World Health Organization's (WHO) STEPwise country reports and relevant publications. Country-level data for potential correlates were extracted from multiple sources: Central Intelligence Agency (literacy), Gallup Poll (religiosity), United Nations (agricultural employment, food supply, gender inequality, human development), World Bank (automobile ownership, Internet, labour force) and WHO (physical inactivity). The overall, male and female overweight prevalence was 37.4, 33.0 and 42.1%, respectively. Prevalence estimates significantly differed by economic classification, gender and ethnicity. Middle- and upper income countries were 1.54-7.76 (95% confidence interval [CI]: 1.49-8.07) times more likely overweight than low-income countries, females were 1.48 (CI: 1.45-1.50) times more likely overweight than males and Arab countries were 2.92 (CI: 2.86-2.97) times more likely overweight than non-Arab countries. All 10 of the potential correlates were significantly associated with overweight for at least one permutation (total, economic classification, gender, ethnicity). The greater percentage of poorer countries among non-Arab Muslim countries, which compared with Arab countries have not as rapidly been transformed by globalization, nutrition transition and urbanization, may partially explain prevalence differences. Evaluation of correlational data generally followed associations seen in non-Muslim countries but more complex analysis of subnational data is needed. Arab women are a particularly vulnerable subgroup and governments should act within religious and cultural parameters to provide
Cumulative trauma, hyperarousal, and suicidality in the general population: a path analysis.
Briere, John; Godbout, Natacha; Dias, Colin
2015-01-01
Although trauma exposure and posttraumatic stress disorder (PTSD) both have been linked to suicidal thoughts and behavior, the underlying basis for this relationship is not clear. In a sample of 357 trauma-exposed individuals from the general population, younger participant age, cumulative trauma exposure, and all three Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, PTSD clusters (reexperiencing, avoidance, and hyperarousal) were correlated with clinical levels of suicidality. However, logistic regression analysis indicated that when all PTSD clusters were considered simultaneously, only hyperarousal continued to be predictive. A path analysis confirmed that posttraumatic hyperarousal (but not other components of PTSD) fully mediated the relationship between extent of trauma exposure and degree of suicidal thoughts and behaviors.
[Determination and correlation analysis of trace elements in Boletus tomentipes].
Li, Tao; Wang, Yuan-zhong; Zhang, Ji; Zhao, Yan-li; Liu, Hong-gao
2011-07-01
The contents of eleven trace elements in Boletus tomentipes were determined by inductively coupled plasma atomic emission spectroscopy (ICP-AES). The results showed that the fruiting bodies of B. tomentipes were very rich in Mg and Fe (>100 mg x kg(-1)) and rich in Mn, Zn and Cu (>10 mg x kg(-1)). Cr, Pb, Ni, Cd, and As were relatively minor contents (0.1-10.0 mg x kg(-1)) of this species, while Hg occurred at the smallest content (< 0.1 mg x kg(-1)). Among the determined 11 trace elements, Zn-Cu had significantly positive correlation (r = 0.659, P < 0.05), whereas, Hg-As, Ni-Fe, and Zn-Mg had significantly negative correlation (r = -0.672, -0.610, -0.617, P < 0.05). This paper presented the trace elements properties of B. tomentipes, and is expected to be useful for exploitation and quality evaluation of this species.
Partitioning Water Vapor and Carbon Dioxide Fluxes using Correlation Analysis
Scanlon, T. M.
2008-12-01
A variety of methods are currently available to partition water vapor fluxes (into components of transpiration and direct evaporation) and carbon dioxide fluxes (into components of photosynthesis and respiration), using chambers, isotopes, and regression modeling approaches. Here, a methodology is presented that accounts for correlations between high-frequency measurements of water vapor (q) and carbon dioxide (c) concentrations being influenced by their non-identical source-sink distributions and the relative magnitude of their constituent fluxes. Flux-variance similarity assumptions are applied separately to the stomatal and the non-stomatal exchange, and the flux components are identified by considering the q-c correlation. Water use efficiency for the vegetation, and how it varies with respect to vapor pressure deficit, is the only input needed for this approach that uses standard eddy covariance measurements. The method is demonstrated using data collected over a corn field throughout a growing season. In particular, the research focuses on the partitioning of the water flux with the aim of improving how direct evaporation is handled in soil-vegetation- atmosphere transfer models over the course of wetting and dry-down cycles.
Auto-correlation analysis of wave heights in the Bay of Bengal
Time series observations of significant wave heights in the Bay of Bengal were subjected to auto- correlation analysis to determine temporal variability scale. The analysis indicates an exponen- tial fall of auto-correlation in the first few hours with a decorrelation time scale of about six hours. A similar figure was found earlier ...
correlation studies and path coefficient analysis for seed yield
Prof. Adipala Ekwamu
African Crop Science Journal, Vol. 21, No. 1, pp. 51 - 59 ... Yield being a quantitative trait has complex inheritance, which is ... Analysis for seed yield and yield components in Ethiopian coriander. 53 ..... The financial assistance of Canadian.
The effects of common risk factors on stock returns: A detrended cross-correlation analysis
Ruan, Qingsong; Yang, Bingchan
2017-10-01
In this paper, we investigate the cross-correlations between Fama and French three factors and the return of American industries on the basis of cross-correlation statistic test and multifractal detrended cross-correlation analysis (MF-DCCA). Qualitatively, we find that the return series of Fama and French three factors and American industries were overall significantly cross-correlated based on the analysis of a statistic. Quantitatively, we find that the cross-correlations between three factors and the return of American industries were strongly multifractal, and applying MF-DCCA we also investigate the cross-correlation of industry returns and residuals. We find that there exists multifractality of industry returns and residuals. The result of correlation coefficients we can verify that there exist other factors which influence the industry returns except Fama three factors.
Jacobsen, Martin; Martinussen, Torben
2016-01-01
Pseudo-values have proven very useful in censored data analysis in complex settings such as multi-state models. It was originally suggested by Andersen et al., Biometrika, 90, 2003, 335 who also suggested to estimate standard errors using classical generalized estimating equation results. These r......Pseudo-values have proven very useful in censored data analysis in complex settings such as multi-state models. It was originally suggested by Andersen et al., Biometrika, 90, 2003, 335 who also suggested to estimate standard errors using classical generalized estimating equation results....... These results were studied more formally in Graw et al., Lifetime Data Anal., 15, 2009, 241 that derived some key results based on a second-order von Mises expansion. However, results concerning large sample properties of estimates based on regression models for pseudo-values still seem unclear. In this paper......, we study these large sample properties in the simple setting of survival probabilities and show that the estimating function can be written as a U-statistic of second order giving rise to an additional term that does not vanish asymptotically. We further show that previously advocated standard error...
Closure and ratio correlation analysis of lunar chemical and grain size data
Butler, J. C.
1976-01-01
Major element and major element plus trace element analyses were selected from the lunar data base for Apollo 11, 12 and 15 basalt and regolith samples. Summary statistics for each of the six data sets were compiled, and the effects of closure on the Pearson product moment correlation coefficient were investigated using the Chayes and Kruskal approximation procedure. In general, there are two types of closure effects evident in these data sets: negative correlations of intermediate size which are solely the result of closure, and correlations of small absolute value which depart significantly from their expected closure correlations which are of intermediate size. It is shown that a positive closure correlation will arise only when the product of the coefficients of variation is very small (less than 0.01 for most data sets) and, in general, trace elements in the lunar data sets exhibit relatively large coefficients of variation.
Correlation analysis of milk production traits across three ...
The relationship between milk production traits over whole lactations was evaluated across three generations of Simmental cows (between daughters, dams and granddams) by a corelation analysis with whole lactation traits in the daughter generation being used as the dependent variables (x1), and those in ...
Kenett, Dror Y; Tumminello, Michele; Madi, Asaf; Gur-Gershgoren, Gitit; Mantegna, Rosario N; Ben-Jacob, Eshel
2010-12-20
What are the dominant stocks which drive the correlations present among stocks traded in a stock market? Can a correlation analysis provide an answer to this question? In the past, correlation based networks have been proposed as a tool to uncover the underlying backbone of the market. Correlation based networks represent the stocks and their relationships, which are then investigated using different network theory methodologies. Here we introduce a new concept to tackle the above question--the partial correlation network. Partial correlation is a measure of how the correlation between two variables, e.g., stock returns, is affected by a third variable. By using it we define a proxy of stock influence, which is then used to construct partial correlation networks. The empirical part of this study is performed on a specific financial system, namely the set of 300 highly capitalized stocks traded at the New York Stock Exchange, in the time period 2001-2003. By constructing the partial correlation network, unlike the case of standard correlation based networks, we find that stocks belonging to the financial sector and, in particular, to the investment services sub-sector, are the most influential stocks affecting the correlation profile of the system. Using a moving window analysis, we find that the strong influence of the financial stocks is conserved across time for the investigated trading period. Our findings shed a new light on the underlying mechanisms and driving forces controlling the correlation profile observed in a financial market.
Clifton, P.M.
1984-12-01
The deep basalt formations beneath the Hanford Site are being investigated for the Department of Energy (DOE) to assess their suitability as a host medium for a high level nuclear waste repository. Predicted performance of the proposed repository is an important part of the investigation. One of the performance measures being used to gauge the suitability of the host medium is pre-waste-emplacement groundwater travel times to the accessible environment. Many deterministic analyses of groundwater travel times have been completed by Rockwell and other independent organizations. Recently, Rockwell has completed a preliminary stochastic analysis of groundwater travel times. This document presents analyses that show the sensitivity of the results from the previous stochastic travel time study to: (1) scale of representation of model parameters, (2) size of the model domain, (3) correlation range of log-transmissivity, and (4) cross-correlation between transmissivity and effective thickness. 40 refs., 29 figs., 6 tabs
Data analysis of backscattering LIDAR system correlated with meteorological data
Uehara, Sandro Toshio
2009-01-01
In these last years, we had an increase in the interest in the monitoring of the effect of the human activity being on the atmosphere and the climate in the planet. The remote sensing techniques has been used in many studies, also related the global changes. A backscattering LIDAR system, the first of this kind in Brazil, has been used to provide the vertical profile of the aerosol backscatter coefficient at 532 nm up to an altitude of 4-6 km above sea level. In this study, data has was collected in the year of 2005. These data had been correlated with data of solar photometer CIMEL and also with meteorological data. The main results had indicated to exist a standard in the behavior of these meteorological data and the vertical distribution of the extinction coefficient gotten through LIDAR. In favorable periods of atmospheric dispersion, that is, rise of the temperature of associated air the fall of relative humidity, increase of the atmospheric pressure and low ventilation tax, was possible to determine with good precision the height of the Planetary Boundary Layer, as much through the vertical profile of the extinction coefficient how much through the technique of the vertical profile of the potential temperature. The technique LIDAR showed to be an important tool in the determination of the thermodynamic structure of the atmosphere, assisting to characterize the evolution of the CLP throughout the day, which had its good space and secular resolution. (author)
Analysis of three particle correlations with the INDRA detector
Rahmani, A.; Eudes, Ph.; Lautridou, P.; Lebrun, C.; Reposeur, T.
1997-01-01
In the framework of the study of light particle production with the INDRA detector, we have analysed the invariant mass distribution of three particles produced in the Xe + Sn collisions at 50 A.MeV making use of an original interferometric method which offers the possibilities to access the intrinsic parameters of intermediate 'resonances' created during the nuclear collisions. By analyzing the correlations of (α,α,α) it was possible to make evident a signal equivalent to that from 12 C. The study of this signal allows: - to estimate the production rate of αs coming from the 12 C * decay; - accordingly, to introduce a correction for α multiplicity measured by INDRA; - to extract the temperature of the emitting fragment ( 12 C * ); to establish the sequential or direct decay mode of the emitting fragments ( 12 C * → α + 8 Be → α + α + α or 12 C * → α + α + α). Thus, the measured signal is an apparent consequence of the occurrence of the intermediate fragments excited in a metastable state from which the particles are emitted. The emission rate of the α particles coming from the decay of these fragments is estimated to several percents (< 10 %)
Sugawara, Y.; Sugiyama, T.; Kobayashi, T.; Yamaya, H.; Kitamura, E.
1995-01-01
The correlation analysis for a forced vibration test of a 1/4-scale containment SSI test model constructed in Hualien, Taiwan was carried out for the case of after backfilling. Prior to this correlation analysis, the structural properties were revised to adjust the calculated fundamental frequency in the fixed base condition to that derived from the test results. A correlation analysis was carried out using the Lattice Model which was able to estimate the soil-structure effects with embedment. The analysis results coincide well with test results and it is concluded that the mathematical soil-structure interaction model established by the correlation analysis is efficient in estimating the dynamic soil-structure interaction effect with embedment. This mathematical model will be applied as a basic model for simulation analysis of earthquake observation records. (author). 3 refs., 12 figs., 2 tabs
NDVI and Panchromatic Image Correlation Using Texture Analysis
2010-03-01
6 Figure 5. Spectral reflectance of vegetation and soil from 0.4 to 1.1 mm (From Perry...should help the classification methods to be able to classify kelp. Figure 5. Spectral reflectance of vegetation and soil from 0.4 to 1.1 mm...1988). Image processing software for imaging spectrometry analysis. Remote Sensing of Enviroment , 24: 201–210. Perry, C., & Lautenschlager, L. F
Rissing, Steven W
2013-01-01
Most American colleges and universities offer gateway biology courses to meet the needs of three undergraduate audiences: biology and related science majors, many of whom will become biomedical researchers; premedical students meeting medical school requirements and preparing for the Medical College Admissions Test (MCAT); and students completing general education (GE) graduation requirements. Biology textbooks for these three audiences present a topic scope and sequence that correlates with the topic scope and importance ratings of the biology content specifications for the MCAT regardless of the intended audience. Texts for "nonmajors," GE courses appear derived directly from their publisher's majors text. Topic scope and sequence of GE texts reflect those of "their" majors text and, indirectly, the MCAT. MCAT term density of GE texts equals or exceeds that of their corresponding majors text. Most American universities require a GE curriculum to promote a core level of academic understanding among their graduates. This includes civic scientific literacy, recognized as an essential competence for the development of public policies in an increasingly scientific and technological world. Deriving GE biology and related science texts from majors texts designed to meet very different learning objectives may defeat the scientific literacy goals of most schools' GE curricula.
Rethlefsen, Melissa L; Farrell, Ann M; Osterhaus Trzasko, Leah C; Brigham, Tara J
2015-06-01
To determine whether librarian and information specialist authorship was associated with better reported systematic review (SR) search quality. SRs from high-impact general internal medicine journals were reviewed for search quality characteristics and reporting quality by independent reviewers using three instruments, including a checklist of Institute of Medicine Recommended Standards for the Search Process and a scored modification of the Peer Review of Electronic Search Strategies instrument. The level of librarian and information specialist participation was significantly associated with search reproducibility from reported search strategies (Χ(2) = 23.5; P Librarian co-authored SRs had significantly higher odds of meeting 8 of 13 analyzed search standards than those with no librarian participation and six more than those with mentioned librarian participation. One-way ANOVA showed that differences in total search quality scores between all three groups were statistically significant (F2,267 = 10.1233; P librarian or information specialist co-authors are correlated with significantly higher quality reported search strategies. To minimize bias in SRs, authors and editors could encourage librarian engagement in SRs including authorship as a potential way to help improve documentation of the search strategy. Copyright © 2015 Elsevier Inc. All rights reserved.
Rissing, Steven W.
2013-01-01
Most American colleges and universities offer gateway biology courses to meet the needs of three undergraduate audiences: biology and related science majors, many of whom will become biomedical researchers; premedical students meeting medical school requirements and preparing for the Medical College Admissions Test (MCAT); and students completing general education (GE) graduation requirements. Biology textbooks for these three audiences present a topic scope and sequence that correlates with the topic scope and importance ratings of the biology content specifications for the MCAT regardless of the intended audience. Texts for “nonmajors,” GE courses appear derived directly from their publisher's majors text. Topic scope and sequence of GE texts reflect those of “their” majors text and, indirectly, the MCAT. MCAT term density of GE texts equals or exceeds that of their corresponding majors text. Most American universities require a GE curriculum to promote a core level of academic understanding among their graduates. This includes civic scientific literacy, recognized as an essential competence for the development of public policies in an increasingly scientific and technological world. Deriving GE biology and related science texts from majors texts designed to meet very different learning objectives may defeat the scientific literacy goals of most schools’ GE curricula. PMID:24006392
Subiakto Soekarno
2012-01-01
Full Text Available Insurance industry stands as a service business that plays a significant role in Indonesiaeconomical condition. The development of insurance industry in Indonesia, both of generalinsurance and life insurance, has increased very fast. The general insurance industry itselfdivided into two major players which are local private company and Joint Venture Company.Lately, the use of statistical techniques and financial ratios models to asses financial institutionsuch as insurance company have been used as one of the appropriate combination inpredicting the performance of an industry. This research aims to distinguish between JointVenture General Insurance Companies that have a good performance and those who are lessperforming well using Discriminant Analysis. Further, the findings led that DiscriminantAnalysis is able to distinguish Joint Venture General Insurance Companies that have a goodperformance and those who are not performing well. There are also six ratios which are RBC,Technical Reserve to Investment Ratio, Debt Ratio, Return on Equity, Loss Ratio, and ExpenseRatio that stand as the most influential ratios to distinguish the performance of joint venturegeneral insurance companies. In addition, the result suggest business people to be concernedtoward those six ratios, to increase their companies’ performance.Key words: general insurance, financial ratio, discriminant analysis
Analysis of the irradiation data for A302B and A533B correlation monitor materials
Wang, J.A.
1996-04-01
The results of Charpy V-notch impact tests for A302B and A533B-1 Correlation Monitor Materials (CMM) listed in the surveillance power reactor data base (PR-EDB) and material test reactor data base (TR-EDB) are analyzed. The shift of the transition temperature at 30 ft-lb (T 30 ) is considered as the primary measure of radiation embrittlement in this report. The hyperbolic tangent fitting model and uncertainty of the fitting parameters for Charpy impact tests are presented in this report. For the surveillance CMM data, the transition temperature shifts at 30 ft-lb (ΔT 30 ) generally follow the predictions provided by Revision 2 of Regulatory Guide 1.99 (R.G. 1.99). Difference in capsule temperatures is a likely explanation for large deviations from R.G. 1.99 predictions. Deviations from the R.G. 1.99 predictions are correlated to similar deviations for the accompanying materials in the same capsules, but large random fluctuations prevent precise quantitative determination. Significant scatter is noted in the surveillance data, some of which may be attributed to variations from one specimen set to another, or inherent in Charpy V-notch testing. The major contributions to the uncertainty of the R.G. 1.99 prediction model, and the overall data scatter are from mechanical test results, chemical analysis, irradiation environments, fluence evaluation, and inhomogeneous material properties. Thus in order to improve the prediction model, control of the above-mentioned error sources needs to be improved. In general the embrittlement behavior of both the A302B and A533B-1 plate materials is similar. There is evidence for a fluence-rate effect in the CMM data irradiated in test reactors; thus its implication on power reactor surveillance programs deserves special attention
Xu, Weifeng; Cai, Jiejin; Liu, Shichang; Tang, Qi
2015-01-01
Highlights: • Different thermal correlations for supercritical water are summarized. • Influences of thermal correlations on neutronic–thermohydraulic coupling calculation are analyzed. • Sensitivity analysis has been done for the thermal correlations. - Abstract: The neutronic–thermohydraulic coupling (N–T coupling) calculation is important on core design, security and stability analysis of supercritical water-coolant reactor (SCWR), and a suitable thermal correlation is also necessary for the N–T coupling calculation. In this paper, the scheme of the U.S. SCWR design and the process of the N–T coupling will be introduced as well as some of different thermal correlations firstly. Then, based on the N–T coupling system ARNT, the U.S. SCWR design is simulated to analyze the influences of thermal correlations on N–T coupling calculation of SCWR so as to find out which correlation is best. The result shows that all thermal correlations are suitable. However, using different correlations for calculation leads to a great difference in safety margin of SCWR. What's more, the Bishop and Jackson correlations are more suitable and conservative, but the Griem correlation is not very precise. And the effect of buoyancy lift makes little influence on the calculation of heat transfer of SCWR. This research is also of great significance for the further study of N–T coupling of SCWR
Gersh, Elon; Hallford, David J; Rice, Simon M; Kazantzis, Nikolaos; Gersh, Hannah; Gersh, Benji; McCarty, Carolyn A
2017-12-01
Despite being a relatively prevalent and debilitating disorder, Generalized Anxiety Disorder (GAD) is the second least studied anxiety disorder and among the most difficult to treat. Dropout from psychotherapy is concerning as it is associated with poorer outcomes, leads to service inefficiencies and can disproportionately affect disadvantaged populations. No study to date has calculated a weighted mean dropout rate for GAD and explored associated correlates. A systematic review was conducted using PsycINFO, Medline and Embase databases, identifying studies investigating individual psychotherapies for adults with GAD. Forty-five studies, involving 2224 participants, were identified for meta-analysis. The weighted mean dropout rate was 16.99% (95% confidence interval 14.42%-19.91%). The Q-statistic indicated significant heterogeneity among studies. Moderator analysis and meta-regressions indicated no statistically significant effect of client age, sex, symptom severity, comorbidity, treatment type, study type (randomized trial or not), study quality, number of sessions or therapist experience. In research investigating psychotherapy for GAD, approximately one in six clients can be expected to drop out of treatment. Dropout rate was not significantly moderated by the client, therapist or treatment variables investigated. Future research should specify the definition of dropout, reasons for dropout and associated correlates to assist the field's progression. Copyright © 2017 Elsevier Ltd. All rights reserved.
Empirical mode decomposition and long-range correlation analysis of sunspot time series
Zhou, Yu; Leung, Yee
2010-01-01
Sunspots, which are the best known and most variable features of the solar surface, affect our planet in many ways. The number of sunspots during a period of time is highly variable and arouses strong research interest. When multifractal detrended fluctuation analysis (MF-DFA) is employed to study the fractal properties and long-range correlation of the sunspot series, some spurious crossover points might appear because of the periodic and quasi-periodic trends in the series. However many cycles of solar activities can be reflected by the sunspot time series. The 11-year cycle is perhaps the most famous cycle of the sunspot activity. These cycles pose problems for the investigation of the scaling behavior of sunspot time series. Using different methods to handle the 11-year cycle generally creates totally different results. Using MF-DFA, Movahed and co-workers employed Fourier truncation to deal with the 11-year cycle and found that the series is long-range anti-correlated with a Hurst exponent, H, of about 0.12. However, Hu and co-workers proposed an adaptive detrending method for the MF-DFA and discovered long-range correlation characterized by H≈0.74. In an attempt to get to the bottom of the problem in the present paper, empirical mode decomposition (EMD), a data-driven adaptive method, is applied to first extract the components with different dominant frequencies. MF-DFA is then employed to study the long-range correlation of the sunspot time series under the influence of these components. On removing the effects of these periods, the natural long-range correlation of the sunspot time series can be revealed. With the removal of the 11-year cycle, a crossover point located at around 60 months is discovered to be a reasonable point separating two different time scale ranges, H≈0.72 and H≈1.49. And on removing all cycles longer than 11 years, we have H≈0.69 and H≈0.28. The three cycle-removing methods—Fourier truncation, adaptive detrending and the
Roth, Philip L; Le, Huy; Oh, In-Sue; Van Iddekinge, Chad H; Bobko, Philip
2018-06-01
Meta-analysis has become a well-accepted method for synthesizing empirical research about a given phenomenon. Many meta-analyses focus on synthesizing correlations across primary studies, but some primary studies do not report correlations. Peterson and Brown (2005) suggested that researchers could use standardized regression weights (i.e., beta coefficients) to impute missing correlations. Indeed, their beta estimation procedures (BEPs) have been used in meta-analyses in a wide variety of fields. In this study, the authors evaluated the accuracy of BEPs in meta-analysis. We first examined how use of BEPs might affect results from a published meta-analysis. We then developed a series of Monte Carlo simulations that systematically compared the use of existing correlations (that were not missing) to data sets that incorporated BEPs (that impute missing correlations from corresponding beta coefficients). These simulations estimated ρ̄ (mean population correlation) and SDρ (true standard deviation) across a variety of meta-analytic conditions. Results from both the existing meta-analysis and the Monte Carlo simulations revealed that BEPs were associated with potentially large biases when estimating ρ̄ and even larger biases when estimating SDρ. Using only existing correlations often substantially outperformed use of BEPs and virtually never performed worse than BEPs. Overall, the authors urge a return to the standard practice of using only existing correlations in meta-analysis. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Analysis of generalized Schwarz alternating procedure for domain decomposition
Engquist, B.; Zhao, Hongkai [Univ. of California, Los Angeles, CA (United States)
1996-12-31
The Schwartz alternating method(SAM) is the theoretical basis for domain decomposition which itself is a powerful tool both for parallel computation and for computing in complicated domains. The convergence rate of the classical SAM is very sensitive to the overlapping size between each subdomain, which is not desirable for most applications. We propose a generalized SAM procedure which is an extension of the modified SAM proposed by P.-L. Lions. Instead of using only Dirichlet data at the artificial boundary between subdomains, we take a convex combination of u and {partial_derivative}u/{partial_derivative}n, i.e. {partial_derivative}u/{partial_derivative}n + {Lambda}u, where {Lambda} is some {open_quotes}positive{close_quotes} operator. Convergence of the modified SAM without overlapping in a quite general setting has been proven by P.-L.Lions using delicate energy estimates. The important questions remain for the generalized SAM. (1) What is the most essential mechanism for convergence without overlapping? (2) Given the partial differential equation, what is the best choice for the positive operator {Lambda}? (3) In the overlapping case, is the generalized SAM superior to the classical SAM? (4) What is the convergence rate and what does it depend on? (5) Numerically can we obtain an easy to implement operator {Lambda} such that the convergence is independent of the mesh size. To analyze the convergence of the generalized SAM we focus, for simplicity, on the Poisson equation for two typical geometry in two subdomain case.
Jacques, J
2005-12-15
Two topics are studied in this thesis: sensitivity analysis and generalized discriminant analysis. Global sensitivity analysis of a mathematical model studies how the output variables of this last react to variations of its inputs. The methods based on the study of the variance quantify the part of variance of the response of the model due to each input variable and each subset of input variables. The first subject of this thesis is the impact of a model uncertainty on results of a sensitivity analysis. Two particular forms of uncertainty are studied: that due to a change of the model of reference, and that due to the use of a simplified model with the place of the model of reference. A second problem was studied during this thesis, that of models with correlated inputs. Indeed, classical sensitivity indices not having significance (from an interpretation point of view) in the presence of correlation of the inputs, we propose a multidimensional approach consisting in expressing the sensitivity of the output of the model to groups of correlated variables. Applications in the field of nuclear engineering illustrate this work. Generalized discriminant analysis consists in classifying the individuals of a test sample in groups, by using information contained in a training sample, when these two samples do not come from the same population. This work extends existing methods in a Gaussian context to the case of binary data. An application in public health illustrates the utility of generalized discrimination models thus defined. (author)
Jacques, J
2005-12-15
Two topics are studied in this thesis: sensitivity analysis and generalized discriminant analysis. Global sensitivity analysis of a mathematical model studies how the output variables of this last react to variations of its inputs. The methods based on the study of the variance quantify the part of variance of the response of the model due to each input variable and each subset of input variables. The first subject of this thesis is the impact of a model uncertainty on results of a sensitivity analysis. Two particular forms of uncertainty are studied: that due to a change of the model of reference, and that due to the use of a simplified model with the place of the model of reference. A second problem was studied during this thesis, that of models with correlated inputs. Indeed, classical sensitivity indices not having significance (from an interpretation point of view) in the presence of correlation of the inputs, we propose a multidimensional approach consisting in expressing the sensitivity of the output of the model to groups of correlated variables. Applications in the field of nuclear engineering illustrate this work. Generalized discriminant analysis consists in classifying the individuals of a test sample in groups, by using information contained in a training sample, when these two samples do not come from the same population. This work extends existing methods in a Gaussian context to the case of binary data. An application in public health illustrates the utility of generalized discrimination models thus defined. (author)
DNA microarray data and contextual analysis of correlation graphs
Hingamp Pascal
2003-04-01
Full Text Available Abstract Background DNA microarrays are used to produce large sets of expression measurements from which specific biological information is sought. Their analysis requires efficient and reliable algorithms for dimensional reduction, classification and annotation. Results We study networks of co-expressed genes obtained from DNA microarray experiments. The mathematical concept of curvature on graphs is used to group genes or samples into clusters to which relevant gene or sample annotations are automatically assigned. Application to publicly available yeast and human lymphoma data demonstrates the reliability of the method in spite of its simplicity, especially with respect to the small number of parameters involved. Conclusions We provide a method for automatically determining relevant gene clusters among the many genes monitored with microarrays. The automatic annotations and the graphical interface improve the readability of the data. A C++ implementation, called Trixy, is available from http://tagc.univ-mrs.fr/bioinformatics/trixy.html.
Nadorff, Michael R; Porter, Ben; Rhoades, Howard M; Greisinger, Anthony J; Kunik, Mark E; Stanley, Melinda A
2014-01-01
This study investigated the relation between generalized anxiety disorder (GAD) and frequency of bad dreams in older adults. A secondary analysis from a randomized clinical trial comparing cognitive behavioral therapy (CBT) for anxiety to enhanced usual care (EUC) assessed bad dream frequency at baseline, post treatment (3 months), and at 6, 9, 12, and 15 months. Of 227 participants (mean age = 67.4), 134 met GAD diagnostic criteria (CBT = 70, EUC = 64), with the remaining 93 serving as a comparison group. Patients with GAD had significantly more bad dreams than those without, and bad dream frequency was significantly associated with depression, anxiety, worry, and poor quality of life. CBT for anxiety significantly reduced bad dream frequency at post treatment and throughout follow up compared to EUC.
Nadorff, Michael R.; Porter, Ben; Rhoades, Howard M.; Greisinger, Anthony J.; Kunik, Mark E.; Stanley, Melinda A.
2012-01-01
This study investigated the relation between generalized anxiety disorder (GAD) and frequency of bad dreams in older adults. A secondary analysis from a randomized clinical trial comparing cognitive behavioral therapy for anxiety (CBT) to enhanced usual care (EUC), it assessed bad dream frequency at baseline, post-treatment (3 months), and 6, 9, 12 and 15 months. Of 227 participants (mean age = 67.4), 134 met GAD diagnostic criteria (CBT = 70, EUC = 64), with the remaining 93 serving as a comparison group. Patients with GAD had significantly more bad dreams than those without, and bad dream frequency was significantly associated with depression, anxiety, worry, and poor quality of life. CBT for anxiety significantly reduced bad dream frequency at post-treatment and throughout follow-up compared to EUC. PMID:23470116
Pavan K. Sharma
2012-01-01
Full Text Available In water-cooled nuclear power reactors, significant quantities of steam and hydrogen could be produced within the primary containment following the postulated design basis accidents (DBA or beyond design basis accidents (BDBA. For accurate calculation of the temperature/pressure rise and hydrogen transport calculation in nuclear reactor containment due to such scenarios, wall condensation heat transfer coefficient (HTC is used. In the present work, the adaptation of a commercial CFD code with the implementation of models for steam condensation on wall surfaces in presence of noncondensable gases is explained. Steam condensation has been modeled using the empirical average HTC, which was originally developed to be used for “lumped-parameter” (volume-averaged modeling of steam condensation in the presence of noncondensable gases. The present paper suggests a generalized HTC based on curve fitting of most of the reported semiempirical condensation models, which are valid for specific wall conditions. The present methodology has been validated against limited reported experimental data from the COPAIN experimental facility. This is the first step towards the CFD-based generalized analysis procedure for condensation modeling applicable for containment wall surfaces that is being evolved further for specific wall surfaces within the multicompartment containment atmosphere.
Shen, Lanxiao; Chen, Shan; Zhu, Xiaoyang; Han, Ce; Zheng, Xiaomin; Deng, Zhenxiang; Zhou, Yongqiang; Gong, Changfei; Xie, Congying; Jin, Xiance
2018-03-01
A multidimensional exploratory statistical method, canonical correlation analysis (CCA), was applied to evaluate the impact of complexity parameters on the plan quality and deliverability of volumetric-modulated arc therapy (VMAT) and to determine parameters in the generation of an ideal VMAT plan. Canonical correlations among complexity, quality and deliverability parameters of VMAT, as well as the contribution weights of different parameters were investigated with 71 two-arc VMAT nasopharyngeal cancer (NPC) patients, and further verified with 28 one-arc VMAT prostate cancer patients. The average MU and MU per control point (MU/CP) for two-arc VMAT plans were 702.6 ± 55.7 and 3.9 ± 0.3 versus 504.6 ± 99.2 and 5.6 ± 1.1 for one-arc VMAT plans, respectively. The individual volume-based 3D gamma passing rates of clinical target volume (γCTV) and planning target volume (γPTV) for NPC and prostate cancer patients were 85.7% ± 9.0% vs 92.6% ± 7.8%, and 88.0% ± 7.6% vs 91.2% ± 7.7%, respectively. Plan complexity parameters of NPC patients were correlated with plan quality (P = 0.047) and individual volume-based 3D gamma indices γ(IV) (P = 0.01), in which, MU/CP and segment area (SA) per control point (SA/CP) were weighted highly in correlation with γ(IV) , and SA/CP, percentage of CPs with SA plan quality with coefficients of 0.98, 0.68 and -0.99, respectively. Further verification with one-arc VMAT plans demonstrated similar results. In conclusion, MU, SA-related parameters and PTV volume were found to have strong effects on the plan quality and deliverability.
Comparative analysis of general characteristics of ischemic stroke of BAD and non-BAD CISS subtypes.
Mei, Bin; Liu, Guang-zhi; Yang, Yang; Liu, Yu-min; Cao, Jiang-hui; Zhang, Jun-jian
2015-12-01
Based on the recently proposed Chinese ischemic stroke subclassification (CISS) system, intracranial branch atheromatous disease (BAD) is divided into large artery atherosclerosis (LAA) and penetrating artery disease (PAD). In the current retrospective analysis, we compared the general characteristics of BAD-LAA with BAD-PAD, BAD-LAA with non-BAD-LAA and BAD-PAD with non-BAD-PAD. The study included a total of 80 cases, including 45 cases of BAD and 35 cases of non-BAD. Subjects were classified using CISS system: BAD-LAA, BAD-PAD, non-BAD-LAA and non-BAD-PAD. In addition to analysis of general characteristics, the correlation between the factors and the two subtypes of BAD was evaluated. The number of cases included in the analysis was: 32 cases of BAD-LAA, 13 cases of BAD-PAD, 21 cases of non-BAD-LAA, and 14 cases of non-BAD-PAD. Diabetes mellitus affected more non-BAD-LAA patients than BAD-LAA patients (P=0.035). In comparison with non-BAD-PAD, patients with BAD-PAD were younger (P=0.040), had higher initial NIHSS score (PBAD, the PAD subtype was associated with smoking (OR=0.043; P=0.011), higher low-density lipoprotein (OR=5.339; P=0.029), ischemic heart disease (OR=9.383; P=0.047) and diabetes mellitus (OR=12.59; P=0.020). It was concluded that large artery atherosclerosis was the primary mechanism of BAD. The general characteristics showed no significant differences between the CISS subtypes of LAA and PAD within BAD, as well as between the BAD and non-BAD within LAA subtype. Several differences between PAD subtypes of BAD and non-BAD were revealed.
Authentication of reprocessing plant safeguards data through correlation analysis
Burr, T.L.; Wangen, L.E.; Mullen, M.F.
1995-04-01
This report investigates the feasibility and benefits of two new approaches to the analysis of safeguards data from reprocessing plants. Both approaches involve some level of plant modeling. All models involve some form of mass balance, either applied in the usual way that leads to material balances for individual process vessels at discrete times or applied by accounting for pipe flow rates that leads to material balances for individual process vessels at continuous times. In the first case, material balances are computed after each tank-to-tank transfer. In the second case, material balances can be computed at any desired time. The two approaches can be described as follows. The first approach considers the application of a new multivariate sequential test. The test statistic is a scalar, but the monitored residual is a vector. The second approach considers the application of recent nonlinear time series methods for the purpose of empirically building a model for the expected magnitude of a material balance or other scalar variable. Although the report restricts attention to monitoring scalar time series, the methodology can be extended to vector time series
Correlation between videogame mechanics and executive functions through EEG analysis.
Mondéjar, Tania; Hervás, Ramón; Johnson, Esperanza; Gutierrez, Carlos; Latorre, José Miguel
2016-10-01
This paper addresses a different point of view of videogames, specifically serious games for health. This paper contributes to that area with a multidisciplinary perspective focus on neurosciences and computation. The experiment population has been pre-adolescents between the ages of 8 and 12 without any cognitive issues. The experiment consisted in users playing videogames as well as performing traditional psychological assessments; during these tasks the frontal brain activity was evaluated. The main goal was to analyse how the frontal lobe of the brain (executive function) works in terms of prominent cognitive skills during five types of game mechanics widely used in commercial videogames. The analysis was made by collecting brain signals during the two phases of the experiment, where the signals were analysed with an electroencephalogram neuroheadset. The validated hypotheses were whether videogames can develop executive functioning and if it was possible to identify which kind of cognitive skills are developed during each kind of typical videogame mechanic. The results contribute to the design of serious games for health purposes on a conceptual level, particularly in support of the diagnosis and treatment of cognitive-related pathologies. Copyright © 2016 Elsevier Inc. All rights reserved.
An applied general equilibrium model for Dutch agribusiness policy analysis
Peerlings, J.
1993-01-01
The purpose of this thesis was to develop a basic static applied general equilibrium (AGE) model to analyse the effects of agricultural policy changes on Dutch agribusiness. In particular the effects on inter-industry transactions, factor demand, income, and trade are of
Municipal solid waste management problems: an applied general equilibrium analysis
Bartelings, H.
2003-01-01
Keywords: Environmental policy; General equilibrium modeling; Negishi format; Waste management policies; Market distortions.
About 40% of the entire budget spent on environmental problems in the
Specific Cooperative Analysis and Design in General Hypermedia Development
Grønbæk, Kaj; Mogensen, Preben Holst
1994-01-01
activities. We demonstrate how these activities informed the general hypermedia framework and application design. Use scenarios and prototypes with example data from the users’ daily work were used as sources both to trigger design ideas and new insights regarding work practice. Mutual challenging...
Analysis and design of generalized BICM-T system
Malik, Muhammad Talha; Hossain, Md Jahangir; Alouini, Mohamed-Slim
2014-01-01
-T). In this paper, we analyze a generalized BICM-T system that uses a nonequally spaced signal constellation in conjunction with a bit-level multiplexer in an additive white Gaussian noise (AWGN) channel. As such, one can exploit the full benefit of BICM
Time-correlated neutron analysis of a multiplying HEU source
Miller, E.C.; Kalter, J.M.; Lavelle, C.M.; Watson, S.M.; Kinlaw, M.T.; Chichester, D.L.; Noonan, W.A.
2015-01-01
The ability to quickly identify and characterize special nuclear material remains a national security challenge. In counter-proliferation applications, identifying the neutron multiplication of a sample can be a good indication of the level of threat. Currently neutron multiplicity measurements are performed with moderated 3 He proportional counters. These systems rely on the detection of thermalized neutrons, a process which obscures both energy and time information from the source. Fast neutron detectors, such as liquid scintillators, have the ability to detect events on nanosecond time scales, providing more information on the temporal structure of the arriving signal, and provide an alternative method for extracting information from the source. To explore this possibility, a series of measurements were performed on the Idaho National Laboratory's MARVEL assembly, a configurable HEU source. The source assembly was measured in a variety of different HEU configurations and with different reflectors, covering a range of neutron multiplications from 2 to 8. The data was collected with liquid scintillator detectors and digitized for offline analysis. A gap based approach for identifying the bursts of detected neutrons associated with the same fission chain was used. Using this approach, we are able to study various statistical properties of individual fission chains. One of these properties is the distribution of neutron arrival times within a given burst. We have observed two interesting empirical trends. First, this distribution exhibits a weak, but definite, dependence on source multiplication. Second, there are distinctive differences in the distribution depending on the presence and type of reflector. Both of these phenomena might prove to be useful when assessing an unknown source. The physical origins of these phenomena can be illuminated with help of MCNPX-PoliMi simulations
Time-correlated neutron analysis of a multiplying HEU source
Miller, E.C., E-mail: Eric.Miller@jhuapl.edu [Johns Hopkins University Applied Physics Laboratory, Laurel, MD (United States); Kalter, J.M.; Lavelle, C.M. [Johns Hopkins University Applied Physics Laboratory, Laurel, MD (United States); Watson, S.M.; Kinlaw, M.T.; Chichester, D.L. [Idaho National Laboratory, Idaho Falls, ID (United States); Noonan, W.A. [Johns Hopkins University Applied Physics Laboratory, Laurel, MD (United States)
2015-06-01
The ability to quickly identify and characterize special nuclear material remains a national security challenge. In counter-proliferation applications, identifying the neutron multiplication of a sample can be a good indication of the level of threat. Currently neutron multiplicity measurements are performed with moderated {sup 3}He proportional counters. These systems rely on the detection of thermalized neutrons, a process which obscures both energy and time information from the source. Fast neutron detectors, such as liquid scintillators, have the ability to detect events on nanosecond time scales, providing more information on the temporal structure of the arriving signal, and provide an alternative method for extracting information from the source. To explore this possibility, a series of measurements were performed on the Idaho National Laboratory's MARVEL assembly, a configurable HEU source. The source assembly was measured in a variety of different HEU configurations and with different reflectors, covering a range of neutron multiplications from 2 to 8. The data was collected with liquid scintillator detectors and digitized for offline analysis. A gap based approach for identifying the bursts of detected neutrons associated with the same fission chain was used. Using this approach, we are able to study various statistical properties of individual fission chains. One of these properties is the distribution of neutron arrival times within a given burst. We have observed two interesting empirical trends. First, this distribution exhibits a weak, but definite, dependence on source multiplication. Second, there are distinctive differences in the distribution depending on the presence and type of reflector. Both of these phenomena might prove to be useful when assessing an unknown source. The physical origins of these phenomena can be illuminated with help of MCNPX-PoliMi simulations.
Time-correlated neutron analysis of a multiplying HEU source
Miller, E. C.; Kalter, J. M.; Lavelle, C. M.; Watson, S. M.; Kinlaw, M. T.; Chichester, D. L.; Noonan, W. A.
2015-06-01
The ability to quickly identify and characterize special nuclear material remains a national security challenge. In counter-proliferation applications, identifying the neutron multiplication of a sample can be a good indication of the level of threat. Currently neutron multiplicity measurements are performed with moderated 3He proportional counters. These systems rely on the detection of thermalized neutrons, a process which obscures both energy and time information from the source. Fast neutron detectors, such as liquid scintillators, have the ability to detect events on nanosecond time scales, providing more information on the temporal structure of the arriving signal, and provide an alternative method for extracting information from the source. To explore this possibility, a series of measurements were performed on the Idaho National Laboratory's MARVEL assembly, a configurable HEU source. The source assembly was measured in a variety of different HEU configurations and with different reflectors, covering a range of neutron multiplications from 2 to 8. The data was collected with liquid scintillator detectors and digitized for offline analysis. A gap based approach for identifying the bursts of detected neutrons associated with the same fission chain was used. Using this approach, we are able to study various statistical properties of individual fission chains. One of these properties is the distribution of neutron arrival times within a given burst. We have observed two interesting empirical trends. First, this distribution exhibits a weak, but definite, dependence on source multiplication. Second, there are distinctive differences in the distribution depending on the presence and type of reflector. Both of these phenomena might prove to be useful when assessing an unknown source. The physical origins of these phenomena can be illuminated with help of MCNPX-PoliMi simulations.
Macmann, Gregg M.; Barnett, David W.
1994-01-01
Describes exploratory and confirmatory analyses of verbal-performance procedures to illustrate concepts and procedures for analysis of correlated factors. Argues that, based on convergent and discriminant validity criteria, factors should have higher correlations with variables that they purport to measure than with other variables. Discusses…
L2 Reading Comprehension and Its Correlates: A Meta-Analysis
Jeon, Eun Hee; Yamashita, Junko
2014-01-01
The present meta-analysis examined the overall average correlation (weighted for sample size and corrected for measurement error) between passage-level second language (L2) reading comprehension and 10 key reading component variables investigated in the research domain. Four high-evidence correlates (with 18 or more accumulated effect sizes: L2…
Chen, Jun; Bushman, Frederic D; Lewis, James D; Wu, Gary D; Li, Hongzhe
2013-04-01
Motivated by studying the association between nutrient intake and human gut microbiome composition, we developed a method for structure-constrained sparse canonical correlation analysis (ssCCA) in a high-dimensional setting. ssCCA takes into account the phylogenetic relationships among bacteria, which provides important prior knowledge on evolutionary relationships among bacterial taxa. Our ssCCA formulation utilizes a phylogenetic structure-constrained penalty function to impose certain smoothness on the linear coefficients according to the phylogenetic relationships among the taxa. An efficient coordinate descent algorithm is developed for optimization. A human gut microbiome data set is used to illustrate this method. Both simulations and real data applications show that ssCCA performs better than the standard sparse CCA in identifying meaningful variables when there are structures in the data.
Meta-analysis in a nutshell: Techniques and general findings
Paldam, Martin
2015-01-01
The purpose of this article is to introduce the technique and main findings of meta-analysis to the reader, who is unfamiliar with the field and has the usual objections. A meta-analysis is a quantitative survey of a literature reporting estimates of the same parameter. The funnel showing...
40 CFR 265.13 - General waste analysis.
2010-07-01
... 265.13 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SOLID WASTES (CONTINUED... waste analysis requirements for specific waste management methods as specified in §§ 265.200, 265.225... analysis of test data; and, (iii) The annual removal of residues which are not delisted under § 260.22 -of...
Scalable Kernel Methods and Algorithms for General Sequence Analysis
Kuksa, Pavel
2011-01-01
Analysis of large-scale sequential data has become an important task in machine learning and pattern recognition, inspired in part by numerous scientific and technological applications such as the document and text classification or the analysis of biological sequences. However, current computational methods for sequence comparison still lack…
National Oceanic and Atmospheric Administration, Department of Commerce — The Ensemble Canonical Correlation Analysis (ECCA) precipitation forecast is a 90-day (seasonal) outlook of US surface precipitation anomalies. The ECCA uses...
Study of relationship between MUF correlation and detection sensitivity of statistical analysis
Tamura, Toshiaki; Ihara, Hitoshi; Yamamoto, Yoichi; Ikawa, Koji
1989-11-01
Various kinds of statistical analysis are proposed to NRTA (Near Real Time Materials Accountancy) which was devised to satisfy the timeliness goal of one of the detection goals of IAEA. It will be presumed that different statistical analysis results will occur between the case of considered rigorous error propagation (with MUF correlation) and the case of simplified error propagation (without MUF correlation). Therefore, measurement simulation and decision analysis were done using flow simulation of 800 MTHM/Y model reprocessing plant, and relationship between MUF correlation and detection sensitivity and false alarm of statistical analysis was studied. Specific character of material accountancy for 800 MTHM/Y model reprocessing plant was grasped by this simulation. It also became clear that MUF correlation decreases not only false alarm but also detection probability for protracted loss in case of CUMUF test and Page's test applied to NRTA. (author)
Climate Prediction Center(CPC)Ensemble Canonical Correlation Analysis Forecast of Temperature
National Oceanic and Atmospheric Administration, Department of Commerce — The Ensemble Canonical Correlation Analysis (ECCA) temperature forecast is a 90-day (seasonal) outlook of US surface temperature anomalies. The ECCA uses Canonical...
Serum adiponectin levels are inversely correlated with leukemia: A meta-analysis
Jun-Jie Ma
2016-01-01
Conclusion: Our meta-analysis suggested that serum ADPN levels may be inversely correlated with leukemia, and ADPN levels can be used as an effective biologic marker in early diagnosis and therapeutic monitoring of leukemia.
Practical likelihood analysis for spatial generalized linear mixed models
Bonat, W. H.; Ribeiro, Paulo Justiniano
2016-01-01
We investigate an algorithm for maximum likelihood estimation of spatial generalized linear mixed models based on the Laplace approximation. We compare our algorithm with a set of alternative approaches for two datasets from the literature. The Rhizoctonia root rot and the Rongelap are......, respectively, examples of binomial and count datasets modeled by spatial generalized linear mixed models. Our results show that the Laplace approximation provides similar estimates to Markov Chain Monte Carlo likelihood, Monte Carlo expectation maximization, and modified Laplace approximation. Some advantages...... of Laplace approximation include the computation of the maximized log-likelihood value, which can be used for model selection and tests, and the possibility to obtain realistic confidence intervals for model parameters based on profile likelihoods. The Laplace approximation also avoids the tuning...
[Robotics in general surgery: personal experience, critical analysis and prospectives].
Fracastoro, Gerolamo; Borzellino, Giuseppe; Castelli, Annalisa; Fiorini, Paolo
2005-01-01
Today mini invasive surgery has the chance to be enhanced with sophisticated informative systems (Computer Assisted Surgery, CAS) like robotics, tele-mentoring and tele-presence. ZEUS and da Vinci, present in more than 120 Centres in the world, have been used in many fields of surgery and have been tested in some general surgical procedures. Since the end of 2003, we have performed 70 experimental procedures and 24 operations of general surgery with ZEUS robotic system, after having properly trained 3 surgeons and the operating room staff. Apart from the robot set-up, the mean operative time of the robotic operations was similar to the laparoscopic ones; no complications due to robotic technique occurred. The Authors report benefits and disadvantages related to robots' utilization, problems still to be solved and the possibility to make use of them with tele-surgery, training and virtual surgery.
World Oil Price and Biofuels : A General Equilibrium Analysis
Timilsina, Govinda R.; Mevel, Simon; Shrestha, Ashish
2011-01-01
The price of oil could play a significant role in influencing the expansion of biofuels. However, this issue has not been fully investigated yet in the literature. Using a global computable general equilibrium model, this study analyzes the impact of oil price on biofuel expansion, and subsequently, on food supply. The study shows that a 65 percent increase in oil price in 2020 from the 20...
Within-Subject Correlation Analysis to Detect Functional Areas Associated With Response Inhibition
Tomoko Yamasaki
2018-05-01
Full Text Available Functional areas in fMRI studies are often detected by brain-behavior correlation, calculating across-subject correlation between the behavioral index and the brain activity related to a function of interest. Within-subject correlation analysis is also employed in a single subject level, which utilizes cognitive fluctuations in a shorter time period by correlating the behavioral index with the brain activity across trials. In the present study, the within-subject analysis was applied to the stop-signal task, a standard task to probe response inhibition, where efficiency of response inhibition can be evaluated by the stop-signal reaction time (SSRT. Since the SSRT is estimated, by definition, not in a trial basis but from pooled trials, the correlation across runs was calculated between the SSRT and the brain activity related to response inhibition. The within-subject correlation revealed negative correlations in the anterior cingulate cortex and the cerebellum. Moreover, the dissociation pattern was observed in the within-subject analysis when earlier vs. later parts of the runs were analyzed: negative correlation was dominant in earlier runs, whereas positive correlation was dominant in later runs. Regions of interest analyses revealed that the negative correlation in the anterior cingulate cortex, but not in the cerebellum, was dominant in earlier runs, suggesting multiple mechanisms associated with inhibitory processes that fluctuate on a run-by-run basis. These results indicate that the within-subject analysis compliments the across-subject analysis by highlighting different aspects of cognitive/affective processes related to response inhibition.
The correlation of social support with mental health: A meta-analysis.
Harandi, Tayebeh Fasihi; Taghinasab, Maryam Mohammad; Nayeri, Tayebeh Dehghan
2017-09-01
Social support is an important factor that can affect mental health. In recent decades, many studies have been done on the impact of social support on mental health. The purpose of the present study is to investigate the effect size of the relationship between social support and mental health in studies in Iran. This meta-analysis was carried out in studies that were performed from 1996 through 2015. Databases included SID and Magiran, the comprehensive portal of human sciences, Noor specialized magazine databases, IRANDOC, Proquest, PubMed, Scopus, ERIC, Iranmedex and Google Scholar. The keywords used to search these websites included "mental health or general health," and "Iran" and "social support." In total, 64 studies had inclusion criteria meta-analysis. In order to collect data used from a meta-analysis worksheet that was made by the researcher and for data analysis software, CMA-2 was used. The mean of effect size of the 64 studies in the fixed-effect model and random-effect model was obtained respectively as 0.356 and 0.330, which indicated the moderate effect size of social support on mental health. The studies did not have publication bias, and enjoyed a heterogeneous effect size. The target population and social support questionnaire were moderator variables, but sex, sampling method, and mental health questionnaire were not moderator variables. Regarding relatively high effect size of the correlation between social support and mental health, it is necessary to predispose higher social support, especially for women, the elderly, patients, workers, and students.
The correlation of social support with mental health: A meta-analysis
Harandi, Tayebeh Fasihi; Taghinasab, Maryam Mohammad; Nayeri, Tayebeh Dehghan
2017-01-01
Background and aim Social support is an important factor that can affect mental health. In recent decades, many studies have been done on the impact of social support on mental health. The purpose of the present study is to investigate the effect size of the relationship between social support and mental health in studies in Iran. Methods This meta-analysis was carried out in studies that were performed from 1996 through 2015. Databases included SID and Magiran, the comprehensive portal of human sciences, Noor specialized magazine databases, IRANDOC, Proquest, PubMed, Scopus, ERIC, Iranmedex and Google Scholar. The keywords used to search these websites included “mental health or general health,” and “Iran” and “social support.” In total, 64 studies had inclusion criteria meta-analysis. In order to collect data used from a meta-analysis worksheet that was made by the researcher and for data analysis software, CMA-2 was used. Results The mean of effect size of the 64 studies in the fixed-effect model and random-effect model was obtained respectively as 0.356 and 0.330, which indicated the moderate effect size of social support on mental health. The studies did not have publication bias, and enjoyed a heterogeneous effect size. The target population and social support questionnaire were moderator variables, but sex, sampling method, and mental health questionnaire were not moderator variables. Conclusion Regarding relatively high effect size of the correlation between social support and mental health, it is necessary to predispose higher social support, especially for women, the elderly, patients, workers, and students. PMID:29038699
Ole E. Barndorff-Nielsen; Neil Shephard
2002-01-01
This paper analyses multivariate high frequency financial data using realised covariation. We provide a new asymptotic distribution theory for standard methods such as regression, correlation analysis and covariance. It will be based on a fixed interval of time (e.g. a day or week), allowing the number of high frequency returns during this period to go to infinity. Our analysis allows us to study how high frequency correlations, regressions and covariances change through time. In particular w...
Umar, Efrizon
1995-01-01
In nuclear fuel fabrication, welding plays a very important role to join the end cap to the tube. In order to determine the welding current in TIG welding process for various materials, weld geometries and welding rates, the correlation between the welding current and the other parameters are needed. This paper presents the correlation of those parameters mentioned above. The proposed correlation was tested and produced satisfactory results. (author). 8 refs., 2 tabs., 2 figs
Feng, Jinchao; Lansford, Joshua; Mironenko, Alexander; Pourkargar, Davood Babaei; Vlachos, Dionisios G.; Katsoulakis, Markos A.
2018-03-01
We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data). The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.
Jinchao Feng
2018-03-01
Full Text Available We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data. The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.
Non-linear canonical correlation for joint analysis of MEG signals from two subjects
Cristina eCampi
2013-06-01
Full Text Available We consider the problem of analysing magnetoencephalography (MEG data measured from two persons undergoing the same experiment, and we propose a method that searches for sources with maximally correlated energies. Our method is based on canonical correlation analysis (CCA, which provides linear transformations, one for each subject, such that the correlation between the transformed MEG signals is maximized. Here, we present a nonlinear version of CCA which measures the correlation of energies. Furthermore, we introduce a delay parameter in the modelto analyse, e.g., leader-follower changes in experiments where the two subjects are engaged in social interaction.
Generalized Aliasing as a Basis for Program Analysis Tools
O'Callahan, Robert
2000-01-01
.... This dissertation describes the design of a system, Ajax, that addresses this problem by using semantics-based program analysis as the basis for a number of different tools to aid Java programmers...
Zhang, Lei; Zheng, Xi-Long; Qiu, Dao-Shou; Cai, Shi-Ke; Luo, Huan-Ming; Deng, Rui-Yun; Liu, Xiao-Jin
2013-10-01
In order to provide theoretical and technological basis for the germplasm innovation and variety breeding in Dendrobium officinale, a study of the correlation between polysaccharide content and agronomic characters was conducted. Based on the polysaccharide content determination and the agronomic characters investigation of 30 copies (110 individual plants) of Dendrobium officinale germplasm resources, the correlation between polysaccharide content and agronomic characters was analyzed via path and correlation analysis. Correlation analysis results showed that there was a significant negative correlation between average spacing and polysaccharide content, the correlation coefficient was -0.695. And the blade thickness was positively correlated with the polysaccharide content, but the correlation was not significant. The path analysis results showed that the stem length was the maximum influence factor to the polysaccharide, and it was positive effect, the direct path coefficient was 1.568. According to thess results, the polysaccharide content can be easily and intuitively estimated by the agronomic characters investigating data in the germpalsm resources screening and variety breeding. Therefore, it is a visual and practical technology guidance in quality variety breeding of Dendrobium officinale.
Hsu, C.T.; Keshock, E.G.; McGill, R.N.
1983-01-01
A flag type electrical impedance probe has been developed at the Oak Ridge National Lab (ORNL) to measure liquid- and vapor-phase velocities in steam-water mixtures flowing through rod bundles. Measurements are made by utilizing the probes in pairs, installed in line, parallel to the flow direction, and extending out into the flow channel. The present study addresses performance difficulties by examining from a fundamental point of view the two-phase flow system which the impedance probes typically operate in. Specifically, the governing equations (continuity, momentum, energy) were formulated for both air-water and steam-water systems, and then subjected to a scaling analysis. The scaling analysis yielded the appropriate dimensionless parameters of significance in both kinds of systems. Additionally, with the aid of experimental data obtained at ORNL, those parameters of significant magnitude were established. As a result, a generalized correlation was developed for liquid and vapor phase velocities that makes it possible to employ the impedance probe velocity measurement technique in a wide variety of test configurations and fluid combinations
Detrended cross-correlation analysis on RMB exchange rate and Hang Seng China Enterprises Index
Ruan, Qingsong; Yang, Bingchan; Ma, Guofeng
2017-02-01
In this paper, we investigate the cross-correlations between the Hang Seng China Enterprises Index and RMB exchange markets on the basis of a cross-correlation statistic test and multifractal detrended cross-correlation analysis (MF-DCCA). MF-DCCA has, at best, serious limitations for most of the signals describing complex natural processes and often indicates multifractal cross-correlations when there are none. In order to prevent these false multifractal cross-correlations, we apply MFCCA to verify the cross-correlations. Qualitatively, we find that the return series of the Hang Seng China Enterprises Index and RMB exchange markets were, overall, significantly cross-correlated based on the statistical analysis. Quantitatively, we find that the cross-correlations between the stock index and RMB exchange markets were strongly multifractal, and the multifractal degree of the onshore RMB exchange markets was somewhat larger than the offshore RMB exchange markets. Moreover, we use the absolute return series to investigate and confirm the fact of multifractality. The results from the rolling windows show that the short-term cross-correlations between volatility series remain high.
Irregular Liesegang-type patterns in gas phase revisited. II. Statistical correlation analysis
Torres-Guzmán, José C.; Martínez-Mekler, Gustavo; Müller, Markus F.
2016-05-01
We present a statistical analysis of Liesegang-type patterns formed in a gaseous HCl-NH3 system by ammonium chloride precipitation along glass tubes, as described in Paper I [J. C. Torres-Guzmán et al., J. Chem. Phys. 144, 174701 (2016)] of this work. We focus on the detection and characterization of short and long-range correlations within the non-stationary sequence of apparently irregular precipitation bands. To this end we applied several techniques to estimate spatial correlations stemming from different fields, namely, linear auto-correlation via the power spectral density, detrended fluctuation analysis (DFA), and methods developed in the context of random matrix theory (RMT). In particular RMT methods disclose well pronounced long-range correlations over at least 40 bands in terms of both, band positions and intensity values. By using a variant of the DFA we furnish proof of the nonlinear nature of the detected long-range correlations.
Probabilistic structural analysis using a general purpose finite element program
Riha, D. S.; Millwater, H. R.; Thacker, B. H.
1992-07-01
This paper presents an accurate and efficient method to predict the probabilistic response for structural response quantities, such as stress, displacement, natural frequencies, and buckling loads, by combining the capabilities of MSC/NASTRAN, including design sensitivity analysis and fast probability integration. Two probabilistic structural analysis examples have been performed and verified by comparison with Monte Carlo simulation of the analytical solution. The first example consists of a cantilevered plate with several point loads. The second example is a probabilistic buckling analysis of a simply supported composite plate under in-plane loading. The coupling of MSC/NASTRAN and fast probability integration is shown to be orders of magnitude more efficient than Monte Carlo simulation with excellent accuracy.
CORRELATIONS BETWEEN FINDINGS OF OCCLUSAL AND MANUAL ANALYSIS IN TMD-PATIENTS
Mariana Dimova
2016-08-01
Full Text Available The aim of this study was to investigate and analyze the possible correlations between findings by manual functional analysis and clinical occlusal analysis in TMD-patients. Material and methods: Material of this study are 111 TMD-patients selected after visual diagnostics, functional brief review under Ahlers Jakstatt, intraoral examination and taking periodontal status. In the period September 2014 - March 2016 all patients were subjected to manual functional analysis and clinical occlusal analysis. 17 people (10 women and 7 men underwent imaging with cone-beam computed tomography. Results: There were found many statistically significant correlations between tests of the structural analysis that indicate the relationships between findings. Conclusion: The presence of statistically significant correlations between occlusal relationships, freedom in the centric and condition of the muscle complex of masticatory system and TMJ confirm the relationship between the state of occlusal components and TMD.
Cross-correlation time-of-flight analysis of molecular beam scattering
Nowikow, C.V.; Grice, R.
1979-01-01
The theory of the cross-correlation method of time-of-flight analysis is presented in a form which highlights its formal similarity to the conventional method. A time-of-flight system for the analysis of crossed molecular beam scattering is described, which is based on a minicomputer interface and can operate in both the cross-correlation and conventional modes. The interface maintains the synchronisation of chopper disc rotation and channel advance indefinitely in the cross-correlation method and can acquire data in phase with the beam modulation in both methods. The shutter function of the cross-correlation method is determined and the deconvolution analysis of the data is discussed. (author)
ADC histogram analysis of muscle lymphoma - Correlation with histopathology in a rare entity.
Meyer, Hans-Jonas; Pazaitis, Nikolaos; Surov, Alexey
2018-06-21
Diffusion weighted imaging (DWI) is able to reflect histopathology architecture. A novel imaging approach, namely histogram analysis, is used to further characterize lesion on MRI. The purpose of this study is to correlate histogram parameters derived from apparent diffusion coefficient- (ADC) maps with histopathology parameters in muscle lymphoma. Eight patients (mean age 64.8 years, range 45-72 years) with histopathologically confirmed muscle lymphoma were retrospectively identified. Cell count, total nucleic and average nucleic areas were estimated using ImageJ. Additionally, Ki67-index was calculated. DWI was obtained on a 1.5T scanner by using the b values of 0 and 1000 s/mm2. Histogram analysis was performed as a whole lesion measurement by using a custom-made Matlabbased application. The correlation analysis revealed statistically significant correlation between cell count and ADCmean (p=-0.76, P=0.03) as well with ADCp75 (p=-0.79, P=0.02). Kurtosis and entropy correlated with average nucleic area (p=-0.81, P=0.02, p=0.88, P=0.007, respectively). None of the analyzed ADC parameters correlated with total nucleic area and with Ki67-index. This study identified significant correlations between cellularity and histogram parameters derived from ADC maps in muscle lymphoma. Thus, histogram analysis parameters reflect histopathology in muscle tumors. Advances in knowledge: Whole lesion ADC histogram analysis is able to reflect histopathology parameters in muscle lymphomas.
40 CFR 264.13 - General waste analysis.
2010-07-01
... 264.13 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SOLID WASTES (CONTINUED... waste management methods as specified in §§ 264.17, 264.314, 264.341, 264.1034(d), 264.1063(d), 264.1083... analysis of test data; and, (iii) The annual removal of residues which are not delisted under § 260.22 of...
Seismic risk analysis for General Electric Plutonium Facility, Pleasanton, California
1978-01-01
This report presents the results of a seismic risk analysis that focuses on all possible sources of seismic activity, with the exception of the postulated Verona Fault. The best estimate curve indicates that the Vallecitos facility will experience 30% g with a return period of roughly 130 years and 60% g with a return period of roughly 700 years
A GENERALIZATION OF TRADITIONAL KANO MODEL FOR CUSTOMER REQUIREMENTS ANALYSIS
Renáta Turisová
2015-07-01
Full Text Available Purpose: The theory of attractiveness determines the relationship between the technically achieved and customer perceived quality of product attributes. The most frequently used approach in the theory of attractiveness is the implementation of Kano‘s model. There exist a lot of generalizations of that model which take into consideration various aspects and approaches focused on understanding the customer preferences and identification of his priorities for a selling product. The aim of this article is to outline another possible generalization of Kano‘s model.Methodology/Approach: The traditional Kano’s model captures the nonlinear relationship between reached attributes of quality and customer requirements. The individual attributes of quality are divided into three main categories: must-be, one-dimensional, attractive quality and into two side categories: indifferent and reverse quality. The well selling product has to contain the must-be attribute. It should contain as many one-dimensional attributes as possible. If there are also supplementary attractive attributes, it means that attractiveness of the entire product, from the viewpoint of the customer, nonlinearly sharply rises what has a direct positive impact on a decision of potential customer when purchasing the product. In this article, we show that inclusion of individual quality attributes of a product to the mentioned categories depends, among other things, also on costs on life cycle of the product, respectively on a price of the product on the market.Findings: In practice, we are often encountering the inclusion of products into different price categories: lower, middle and upper class. For a certain type of products the category is either directly declared by a producer (especially in automotive industry, or is determined by a customer by means of assessment of available market prices. To each of those groups of a products different customer expectations can be assigned
A meta-analysis of the relationship between general mental ability and nontask performance.
Gonzalez-Mulé, Erik; Mount, Michael K; Oh, In-Sue
2014-11-01
Although one of the most well-established research findings in industrial-organizational psychology is that general mental ability (GMA) is a strong and generalizable predictor of job performance, this meta-analytically derived conclusion is based largely on measures of task or overall performance. The primary purpose of this study is to address a void in the research literature by conducting a meta-analysis to determine the direction and magnitude of the correlation of GMA with 2 dimensions of nontask performance: counterproductive work behaviors (CWB) and organizational citizenship behaviors (OCB). Overall, the results show that the true-score correlation between GMA and CWB is essentially 0 (-.02, k = 35), although rating source of CWB moderates this relationship. The true-score correlation between GMA and OCB is positive but modest in magnitude (.23, k = 43). The 2nd purpose of this study is to conduct meta-analytic relative weight analyses to determine the relative importance of GMA and the five-factor model (FFM) of personality traits in predicting nontask and task performance criteria. Results indicate that, collectively, the FFM traits are substantially more important for CWB than GMA, that the FFM traits are roughly equal in importance to GMA for OCB, and that GMA is substantially more important for task and overall job performance than the FFM traits. Implications of these findings for the development of optimal selection systems and the development of comprehensive theories of job performance are discussed along with study limitation and future research directions. (PsycINFO Database Record (c) 2014 APA, all rights reserved).
Patterns of stigma toward schizophrenia among the general population: a latent profile analysis.
Loch, Alexandre A; Wang, Yuan-Pang; Guarniero, Francisco B; Lawson, Fabio L; Hengartner, Michael P; Rössler, Wulf; Gattaz, Wagner F
2014-09-01
Our purpose was to assess stigma toward schizophrenia in a representative sample of the Brazilian general population. The sample consisted of 1015 individuals interviewed by telephone. A vignette describing someone with schizophrenia was read, and four stigma aspects regarding this hypothetical individual were assessed: stereotypes, restrictions, perceived prejudice and social distance. Latent profile analysis searched for stigma profiles among the sample. Multinomial logistic regression was used to find correlates of each class. Four stigma profiles were found; 'no stigma' individuals (n = 251) mostly displayed positive opinions. 'Labelers' (n = 222) scored high on social distance; they more often had familial contact with mental illness and more often labeled the vignette's disorder as schizophrenia. 'Discriminators', the group with the majority of individuals (n = 302), showed high levels of stigmatizing beliefs in all dimensions; discriminators were significantly older. 'Unobtrusive stigma' individuals (n = 240) seemed to demonstrate uncertainty or low commitment since they mostly answered items with the middle/impartial option. Some findings from the international literature were replicated; however, familial contact increased stigma, possibly denoting a locally modulated determinant. Hereby, our study also adds important cross-cultural data by showing that stigma toward schizophrenia is high in a Latin-American setting. We highlight the importance of analyzing the general population as a heterogeneous group, aiming to better elaborate anti-stigma campaigns. © The Author(s) 2013.
Geal: A general program for the analysis of alpha spectra
Garcia-Torano, E.; Acena Barrenechea, M.L.
1978-01-01
A computing program for analysis and representation of alpha spectra obtained with surface barrier detectors is described. Several methods for fitting spectra are studied. A monoenergetic line or a doublet previously fitted has been used as a standard for the analyses of all kind of spectra. Some examples of application as well as a list of the program are shown. The program has been written in Fortran V language. (author)
Gang-Jin Wang
2014-01-01
Full Text Available We supply a new perspective to describe and understand the behavior of cross-correlations between energy and emissions markets. Namely, we investigate cross-correlations between oil and gas (Oil-Gas, oil and CO2 (Oil-CO2, and gas and CO2 (Gas-CO2 based on fractal and multifractal analysis. We focus our study on returns of the oil, gas, and CO2 during the period of April 22, 2005–April 30, 2013. In the empirical analysis, by using the detrended cross-correlation analysis (DCCA method, we find that cross-correlations for Oil-Gas, Oil-CO2, and Gas-CO2 obey a power-law and are weakly persistent. Then, we adopt the method of DCCA cross-correlation coefficient to quantify cross-correlations between energy and emissions markets. The results show that their cross-correlations are diverse at different time scales. Next, based on the multifractal DCCA method, we find that cross-correlated markets have the nonlinear and multifractal nature and that the multifractality strength for three cross-correlated markets is arranged in the order of Gas-CO2 > Oil-Gas > Oil-CO2. Finally, by employing the rolling windows method, which can be used to investigate time-varying cross-correlation scaling exponents, we analyze short-term and long-term market dynamics and find that the recent global financial crisis has a notable influence on short-term and long-term market dynamics.
Stürmer, Morgana; Busanello, Marcos; Velho, João Pedro; Heck, Vanessa Isabel; Haygert-Velho, Ione Maria Pereira
2018-06-04
A number of studies have addressed the relations between climatic variables and milk composition, but these works used univariate statistical approaches. In our study, we used a multivariate approach (canonical correlation) to study the impact of climatic variables on milk composition, price, and monthly milk production at a dairy farm using bulk tank milk data. Data on milk composition, price, and monthly milk production were obtained from a dairy company that purchased the milk from the farm, while climatic variable data were obtained from the National Institute of Meteorology (INMET). The data are from January 2014 to December 2016. Univariate correlation analysis and canonical correlation analysis were performed. Few correlations between the climatic variables and milk composition were found using a univariate approach. However, using canonical correlation analysis, we found a strong and significant correlation (r c = 0.95, p value = 0.0029). Lactose, ambient temperature measures (mean, minimum, and maximum), and temperature-humidity index (THI) were found to be the most important variables for the canonical correlation. Our study indicated that 10.2% of the variation in milk composition, pricing, and monthly milk production can be explained by climatic variables. Ambient temperature variables, together with THI, seem to have the most influence on variation in milk composition.
Correlations between MRI and Information Processing Speed in MS: A Meta-Analysis
S. M. Rao
2014-01-01
Full Text Available Objectives. To examine relationships between conventional MRI measures and the paced auditory serial addition test (PASAT and symbol digit modalities test (SDMT. Methods. A systematic literature review was conducted. Included studies had ≥30 multiple sclerosis (MS patients, administered the SDMT or PASAT, and measured T2LV or brain atrophy. Meta-analysis of MRI/information processing speed (IPS correlations, analysis of MRI/IPS significance tests to account for reporting bias, and binomial testing to detect trends when comparing correlation strengths of SDMT versus PASAT and T2LV versus atrophy were conducted. Results. The 39 studies identified frequently reported only significant correlations, suggesting reporting bias. Direct meta-analysis was only feasible for correlations between SDMT and T2LV (r=-0.45, P<0.001 and atrophy in patients with mixed-MS subtypes (r=-0.54, P<0.001. Familywise Holm-Bonferroni testing found that selective reporting was not the source of at least half of significant results reported. Binomial tests (P=0.006 favored SDMT over PASAT in strength of MRI correlations. Conclusions. A moderate-to-strong correlation exists between impaired IPS and MRI in mixed MS populations. Correlations with MRI were stronger for SDMT than for PASAT. Neither heterogeneity among populations nor reporting bias appeared to be responsible for these findings.
Rees, Terry F.
1990-01-01
Colloidal materials, dispersed phases with dimensions between 0.001 and 1 μm, are potential transport media for a variety of contaminants in surface and ground water. Characterization of these colloids, and identification of the parameters that control their movement, are necessary before transport simulations can be attempted. Two techniques that can be used to determine the particle-size distribution of colloidal materials suspended in natural waters are compared. Photon correlation Spectroscopy (PCS) utilizes the Doppler frequency shift of photons scattered off particles undergoing Brownian motion to determine the size of colloids suspended in water. Photosedimentation analysis (PSA) measures the time-dependent change in optical density of a suspension of colloidal particles undergoing centrifugation. A description of both techniques, important underlying assumptions, and limitations are given. Results for a series of river water samples show that the colloid-size distribution means are statistically identical as determined by both techniques. This also is true of the mass median diameter (MMD), even though MMD values determined by PSA are consistently smaller than those determined by PCS. Because of this small negative bias, the skew parameters for the distributions are generally smaller for the PCS-determined distributions than for the PSA-determined distributions. Smaller polydispersity indices for the distributions are also determined by PCS.
Cai, Jia; Tang, Yi
2018-02-01
Canonical correlation analysis (CCA) is a powerful statistical tool for detecting the linear relationship between two sets of multivariate variables. Kernel generalization of it, namely, kernel CCA is proposed to describe nonlinear relationship between two variables. Although kernel CCA can achieve dimensionality reduction results for high-dimensional data feature selection problem, it also yields the so called over-fitting phenomenon. In this paper, we consider a new kernel CCA algorithm via randomized Kaczmarz method. The main contributions of the paper are: (1) A new kernel CCA algorithm is developed, (2) theoretical convergence of the proposed algorithm is addressed by means of scaled condition number, (3) a lower bound which addresses the minimum number of iterations is presented. We test on both synthetic dataset and several real-world datasets in cross-language document retrieval and content-based image retrieval to demonstrate the effectiveness of the proposed algorithm. Numerical results imply the performance and efficiency of the new algorithm, which is competitive with several state-of-the-art kernel CCA methods. Copyright © 2017 Elsevier Ltd. All rights reserved.
Multivariate Meta-Analysis of Brain-Mass Correlations in Eutherian Mammals
Charlene Steinhausen
2016-09-01
Full Text Available The general assumption that brain size differences are an adequate proxy for subtler differences in brain organization turned neurobiologists towards the question why some groups of mammals such as primates, elephants, and whales have such remarkably large brains. In this meta-analysis, an extensive sample of eutherian mammals (115 species distributed in 14 orders provided data about several different biological traits and measures of brain size such as absolute brain mass (AB, relative brain mass (RB; quotient from AB and body mass, and encephalization quotient (EQ. These data were analyzed by established multivariate statistics without taking specific phylogenetic information into account. Species with high AB tend to (1 feed on protein-rich nutrition, (2 have a long lifespan, (3 delay sexual maturity, and (4 have long and rare pregnancies with small litter sizes. Animals with high RB usually have (1 a short life span, (2 reach sexual maturity early, and (3 have short and frequent gestations. Moreover males of species with high RB also have few potential sexual partners. In contrast, animals with high EQs have (1 a high number of potential sexual partners, (2 delayed sexual maturity, and (3 rare gestations with small litter sizes. Based on these correlations, we conclude that Eutheria with either high AB or high EQ occupy high positions in the network of food chains (high trophic levels. Eutheria of low trophic levels can develop a high RB only if they have small body masses.
General gastroscopy of gastroesophageal reflux disease: Analysis of 4086 cases
Zhi-wei HU
2018-04-01
Full Text Available Objective To analyze the characteristics of gastroesophageal reflux disease (GERD under general gastroscope. Methods The detection rates of GERD related abnormalities such as esophagitis, Barrett esophagus and hiatal hernia under the first gastroscopy of the adult GERD patients from January 2013 to January 2017 in our center and the statistical relationship between the abnormal findings were analyzed retrospectively. Results A total of 4086 GERD patients, 2004 males and 2082 females, were included in this study, and the age was 18-89(50.4±13.3 years old. The detection rate of non erosive GERD was 78.7%, esophagitis 21.3%; non Barrett esophagus 87.7%, suspected Barrett esophagus 8.3%, Barrett esophagus 3.9%; generally normal cardia 61.4%, short segment hiatus hernia 20.4%, and long segment hiatal hernia 18.2%. The detection rates of esophagitis showed statistically significant differences (P0.013. Comparing the three age groups of 18-39, 40-59 and ≥60 years old, the detection rate of hiatal hernia was significantly higher in the group of ≥60 years old than in the 18-39 and 40-59 years old groups (P=0.007, while there was no significant difference (P>0.013 between the 18-39 and 40-59 years old groups. The detection rate of esophagitis was significantly higher in ≥60 years old group than in 18-39 and 40-59 years old groups (P=0.004, P=0.008, while no significant statistically difference (P>0.013 was found between the later two groups. Conclusions Gastroscopy can be used as a basic examination means for GERD; short segment hiatal hernia can be regarded as an early form of hiatal hernia, and is of importantreference value for the diagnosis and treatment of GERD; more serious hiatal hernia and esophagitis could be found in elderly GERD patients. DOI: 10.11855/j.issn.0577-7402.2018.01.08
Gruber, Jan
2011-01-01
Roč. 56, č. 2 (2011), s. 185-205 ISSN 0001-7043 Institutional research plan: CEZ:AV0Z20570509 Keywords : correlation dimension * time-embeddings * chaos Subject RIV: BL - Plasma and Gas Discharge Physics
Quantum correlations between each two-level system in a pair of atoms and general coherent fields
S. Abdel-Khalek
Full Text Available The quantitative description of the quantum correlations between each two-level system in a two-atom system and the coherent fields initially defined in a coherent state in the framework of power-law potentials (PLPCSs is considered. Specifically, we consider two atoms locally interacting with PLPCSs and take into account the different terms of interactions, the entanglement and quantum discord are studied including the time-dependent coupling and photon transition effects. Using the monogamic relation between the entanglement of formation and quantum discord in tripartite systems, we show that the control and preservation of the different kinds of quantum correlations greatly benefit from the combination of the choice of the physical quantities. Finally, we explore the link between the dynamical behavior of quantum correlations and nonclassicality of the fields with and without atomic motion effect. Keywords: Quantum correlations, Monogamic relation, Coherent states, Power-law potentials, Wehrl entropy
Nadeem, Qurrat-Ul-Ain; Kammoun, Abla; Debbah, Merouane; Alouini, Mohamed-Slim
2015-01-01
Previous studies have confirmed the adverse impact of fading correlation on the mutual information (MI) of two-dimensional (2D) multiple-input multiple-output (MIMO) systems. More recently, the trend is to enhance the system performance
Fouladi, Rachel T.
2000-01-01
Provides an overview of standard and modified normal theory and asymptotically distribution-free covariance and correlation structure analysis techniques and details Monte Carlo simulation results on Type I and Type II error control. Demonstrates through the simulation that robustness and nonrobustness of structure analysis techniques vary as a…
Hu, Shunren; Chen, Weimin; Liu, Lin; Gao, Xiaoxia
2010-03-01
Bridge structural health monitoring system is a typical multi-sensor measurement system due to the multi-parameters of bridge structure collected from the monitoring sites on the river-spanning bridges. Bridge structure monitored by multi-sensors is an entity, when subjected to external action; there will be different performances to different bridge structure parameters. Therefore, the data acquired by each sensor should exist countless correlation relation. However, complexity of the correlation relation is decided by complexity of bridge structure. Traditionally correlation analysis among monitoring sites is mainly considered from physical locations. unfortunately, this method is so simple that it cannot describe the correlation in detail. The paper analyzes the correlation among the bridge monitoring sites according to the bridge structural data, defines the correlation of bridge monitoring sites and describes its several forms, then integrating the correlative theory of data mining and signal system to establish the correlation model to describe the correlation among the bridge monitoring sites quantificationally. Finally, The Chongqing Mashangxi Yangtze river bridge health measurement system is regards as research object to diagnosis sensors fault, and simulation results verify the effectiveness of the designed method and theoretical discussions.
CFD and thermal analysis applications at General Motors
Johnson, J.P.
2002-01-01
The presentation will include a brief history of the growth of CFD and thermal analysis in GM's vehicle program divisions. Its relationship to the underlying computer infrastructure will be sketched. Application results will be presented for calculations in aerodynamics, flow through heat exchangers, engine compartment thermal studies, HVAC systems and others. Current technical challenges will be outlined including grid generation, turbulence modeling, heat transfer, and solution algorithms. The introduction of CFD and heat transfer results into Virtual Vehicle Reviews, and its potential impact on a company's CAE infrastructure will be noted. Finally, some broad comments will be made on the management of CFD and heat transfer technology across a global corporate enterprise. (author)
Analysis and design of generalized BICM-T system
Malik, Muhammad Talha
2014-09-01
The performance of bit-interleaved coded modulation (BICM) using convolutional codes in nonfading channels can be significantly improved if the coded bits are not interleaved at all. This particular BICM system is referred to as BICM trivial (BICM-T). In this paper, we analyze a generalized BICM-T system that uses a nonequally spaced signal constellation in conjunction with a bit-level multiplexer in an additive white Gaussian noise (AWGN) channel. As such, one can exploit the full benefit of BICM-T by jointly optimizing different system modules to further improve its performance. We also investigate the performance of the considered BICM-T system in the Gaussian mixture noise (GMN) channel because of its practical importance. The presented numerical results show that an optimized BICM-T system can offer gains up to 1.5 dB over a non-optimized BICM-T system in the AWGN channel for a target bit error rate of $10^{-6}$. The presented results for the GMN channel interestingly reveal that if the strength of the impulsive noise component, i.e., the noise component due to some ambient phenomenon in the GMN, is below a certain threshold level, then the BICM-T system performs significantly better as compared to traditional BICM system.
Quaternion analysis of generalized electromagnetic fields in chiral media
Bisht, P. S. . Email. ps_bisht123@rediffmail.com
2007-01-01
The time dependent Maxwell's equations in presence of electric and magnetic charges has been developed in chiral media and the solutions for the classical problem are obtained in unique, simple and consistent manner. The quaternionic reformulation of generalized electromagnetic fields in chiral media has also been developed in compact and consistent way. Simulation of neutron backscattering process applied to organic material detection. Forero Martinez, Nancy Carolina; Cristancho, Fernando (Nuclear Physics Group, Universidad Nacional de Colombia, Bogota D.C. (Colombia)) Abstract Atomic and nuclear physics based sensors might offer new possibilities in de-mining. There is a particular interest in the possibility of using neutrons for the non-intrusive detection of hidden contraband, explosives or illicit drugs. The Neutron Backscattering Technique, based on the detection of the produced thermal neutrons, is known to be a useful tool to detect hidden explosives which present an elevated concentration of light elements (H, C, N, O). In this way we present the simulated results using the program package Geant4. Different variables were modified including the soil composition and the studied materials. (Author)
Analysis of general specifications for nuclear facilities environmental monitoring vehicles
Xu Xiaowei
2014-01-01
At present, with the nuclear energy more increasingly extensive application, the continuous stable radiation monitoring has become the focus of the public attention. The main purpose of the environmental monitoring vehicle for the continuous monitoring of the environmental radiation dose rate and the radionuclides concentration in the medium around nuclear facilities is that the environmental radiation level and the radioactive nuclides activity in the environment medium are measured. The radioactive pollution levels, the scope contaminated and the trends of the pollution accumulation are found out. The change trends for the pollution are observed and the monitoring results are explained. The domestic demand of the environmental monitoring for the nuclear facilities is shown in this report. The changes and demands of the routine environmental monitoring and the nuclear emergency monitoring are researched. The revision opinions for EJ/T 981-1995 General specifications for nuclear facilities environmental monitoring vehicles are put forward. The purpose is to regulate domestic environmental monitoring vehicle technical criterion. The criterion makes it better able to adapt and serve the environmental monitoring for nuclear facilities. The technical guarantee is provided for the environmental monitoring of the nuclear facilities. (authors)
Analysis of a convenient information bound for general quantum channels
O'Loan, C J
2007-01-01
Open questions from Sarovar and Milburn (2006 J. Phys. A: Math. Gen. 39 8487) are answered. Sarovar and Milburn derived a convenient upper bound for the Fisher information of a one-parameter quantum channel. They showed that for quasi-classical models their bound is achievable and they gave a necessary and sufficient condition for positive operator-valued measures (POVMs) attaining this bound. They asked (i) whether their bound is attainable more generally (ii) whether explicit expressions for optimal POVMs can be derived from the attainability condition. We show that the symmetric logarithmic derivative (SLD) quantum information is less than or equal to the SM bound, i.e., H(θ) ≤ C Y (θ) and we find conditions for equality. As the Fisher information is less than or equal to the SLD quantum information, i.e., F M (θ) ≤ H(θ), we can deduce when equality holds in F M (θ) ≤ C Y (θ). Equality does not hold for all channels. As a consequence, the attainability condition cannot be used to test for optimal POVMs for all channels. These results are extended to multi-parameter channels
Munoz-Diosdado, A
2005-01-01
We analyzed databases with gait time series of adults and persons with Parkinson, Huntington and amyotrophic lateral sclerosis (ALS) diseases. We obtained the staircase graphs of accumulated events that can be bounded by a straight line whose slope can be used to distinguish between gait time series from healthy and ill persons. The global Hurst exponent of these series do not show tendencies, we intend that this is because some gait time series have monofractal behavior and others have multifractal behavior so they cannot be characterized with a single Hurst exponent. We calculated the multifractal spectra, obtained the spectra width and found that the spectra of the healthy young persons are almost monofractal. The spectra of ill persons are wider than the spectra of healthy persons. In opposition to the interbeat time series where the pathology implies loss of multifractality, in the gait time series the multifractal behavior emerges with the pathology. Data were collected from healthy and ill subjects as they walked in a roughly circular path and they have sensors in both feet, so we have one time series for the left foot and other for the right foot. First, we analyzed these time series separately, and then we compared both results, with direct comparison and with a cross correlation analysis. We tried to find differences in both time series that can be used as indicators of equilibrium problems
Munoz-Diosdado, A [Department of Mathematics, Unidad Profesional Interdisciplinaria de Biotecnologia, Instituto Politecnico Nacional, Av. Acueducto s/n, 07340, Mexico City (Mexico)
2005-01-01
We analyzed databases with gait time series of adults and persons with Parkinson, Huntington and amyotrophic lateral sclerosis (ALS) diseases. We obtained the staircase graphs of accumulated events that can be bounded by a straight line whose slope can be used to distinguish between gait time series from healthy and ill persons. The global Hurst exponent of these series do not show tendencies, we intend that this is because some gait time series have monofractal behavior and others have multifractal behavior so they cannot be characterized with a single Hurst exponent. We calculated the multifractal spectra, obtained the spectra width and found that the spectra of the healthy young persons are almost monofractal. The spectra of ill persons are wider than the spectra of healthy persons. In opposition to the interbeat time series where the pathology implies loss of multifractality, in the gait time series the multifractal behavior emerges with the pathology. Data were collected from healthy and ill subjects as they walked in a roughly circular path and they have sensors in both feet, so we have one time series for the left foot and other for the right foot. First, we analyzed these time series separately, and then we compared both results, with direct comparison and with a cross correlation analysis. We tried to find differences in both time series that can be used as indicators of equilibrium problems.
Flerchuk Viktor Viktorovich
2011-09-01
Full Text Available Correlation connections of tests are certain to on general physical preparation with indexes morphological possibilities of sportsmen. 15 sportsmen took part in research. Propensity of sportsmen is set to certain distances in competition activity. Directions of selection and orientation of sportsmen are recommended to work of different orientation.
Analysis and optimization of bellows with general shape
Koh, B.K.; Park, G.J.
1998-01-01
Bellows are commonly used in piping systems to absorb expansion and contraction in order to reduce stress. They have widespread applications which include industrial and chemical plants, fossil and nuclear power systems, heating and cooling systems, and vehicle exhaust systems. A bellows is a component in piping systems which absorbs mechanical deformation with flexibility. Its geometry is an axially symmetric shell which consists of two toroidal shells and one annular plate or conical shell. In order to analyze the bellows, this study presents the finite element analysis using a conical frustum shell element. A finite element analysis program is developed to analyze various bellows. The formula for calculating the natural frequency of bellows is made by the simple beam theory. The formula for fatigue life is also derived by experiments. A shape optimal design problem is formulated using multiple objective optimization. The multiple objective functions are transformed to a scalar function with weighting factors. The stiffness, strength, and specified stiffness are considered as the multiple objective function. The formulation has inequality constraints imposed on the natural frequencies, the fatigue limit, and the manufacturing conditions. Geometric parameters of bellows are the design variables. The recursive quadratic programming algorithm is utilized to solve the problem
Han, Xixuan; Clemmensen, Line Katrine Harder
2015-01-01
We propose a general technique for obtaining sparse solutions to generalized eigenvalue problems, and call it Regularized Generalized Eigen-Decomposition (RGED). For decades, Fisher's discriminant criterion has been applied in supervised feature extraction and discriminant analysis, and it is for...
Zhang Weigang
2000-01-01
Based on the concept of correlative degree, a new method of high-order collective-flow measurement is constructed, with which azimuthal correlations, correlations of final state transverse momentum magnitude and transverse correlations can be inspected respectively. Using the new method the contributions of the azimuthal correlations of particles distribution and the correlations of transverse momentum magnitude of final state particles to high-order collective-flow correlations are analyzed respectively with 4π experimental events for 1.2 A GeV Ar + BaI 2 collisions at the Bevalac stream chamber. Comparing with the correlations of transverse momentum magnitude, the azimuthal correlations of final state particles distribution dominate high-order collective-flow correlations in experimental samples. The contributions of correlations of transverse momentum magnitude of final state particles not only enhance the strength of the high-order correlations of particle group, but also provide important information for the measurement of the collectivity of collective flow within the more constraint district
On minimizing the influence of the noise tail of correlation functions in operational modal analysis
Tarpø, Marius; Olsen, Peter; Amador, Sandro
2017-01-01
on the identification results (random errors) when the noise tail is included in the identification. On the other hand, if the correlation function is truncated too much, then important information is lost. In other to minimize this error, a suitable truncation based on manual inspection of the correlation function......In operational modal analysis (OMA) correlation functions are used by all classical time-domain modal identification techniques that uses the impulse response function (free decays) as primary data. However, the main difference between the impulse response and the correlation functions estimated...... from the operational responses is that the latter present a higher noise level. This is due to statistical errors in the estimation of the correlation function and it causes random noise in the end of the function and this is called the noise tail. This noise might have significant influence...
Seljogi, D; Wolff, A P; Scheffer, G J; van Geffen, G J; Bruhn, J
2016-01-01
BACKGROUND: Failed spinal anesthesia for cesarean sections may require conversion to general anesthesia. The aim of this study was to determine whether the administered spinal bupivacaine dose for performing a cesarean section under spinal anesthesia was related to the conversion rate to general
Development of a general method for photovoltaic system analysis
Nolay, P
1987-01-01
The photovoltaic conversion for energetic applications is now widely used, but its development still needs the resolution of many problems for the sizing and for the real working of the installations. The precise analysis of the components and whole system behaviour has led to the development of accurate models for the simulation of such systems. From this modelling phase, a simulation code has been built. The validation of this software has been achieved from experimental test measurements. Since the quality of the software depends on the precision of the input data, an original method of determination of component characteristics, by means of model identification, has been developed. These tools permit the prediction of system behaviour and the dynamic simulation of systems under real conditions. Used for the study of photovoltaic system sizing, this software has allowed the definition of new concepts which will serve as a basis for the development of a sizing method.
Generalized modal analysis for closed-loop piezoelectric devices
Giraud-Audine, Christophe; Giraud, Frédéric; Amberg, Michel; Lemaire-Semail, Betty
2015-01-01
Stress in a piezoelectric material can be controlled by imposing an electrical field. Thanks to feedback, this electrical field can be a function of some strain-related measurement so as to confer on the piezoelectric device a closed-loop macroscopic behaviour. In this paper we address the modelling of such a system by extending the modal decomposition methods to account for the closed loop. To do so, the boundary conditions are modified to include the electrical feedback circuit, hence allowing a closed-loop modal analysis. A case study is used to illustrate the theory and to validate it. The main advantage of the method is that design issues such as the coupling factor of the device and closed-loop stability are simultaneously captured. (paper)
A Generalized Lanczos-QR Technique for Structural Analysis
Vissing, S.
systems with very special properties. Due to the finite discretization the matrices are sparse and a relatively large number of problems also has real and symmetric matrices. The matrix equation for an undamped vibration contains two matrices describing tangent stiffness and mass distributions......Within the field of solid mechanics such as structural dynamics and linearized as well as non-linear stability, the eigenvalue problem plays an important role. In the class of finite element and finite difference discretized problems these engineering problems are characterized by large matrix....... Alternatively, in a stability analysis, tangent stiffness and geometric stiffness matrices are introduced into an eigenvalue problem used to determine possible bifurcation points. The common basis for these types of problems is that the matrix equation describing the problem contains two real, symmetric...
A Generalized Framework for Non-Stationary Extreme Value Analysis
Ragno, E.; Cheng, L.; Sadegh, M.; AghaKouchak, A.
2017-12-01
Empirical trends in climate variables including precipitation, temperature, snow-water equivalent at regional to continental scales are evidence of changes in climate over time. The evolving climate conditions and human activity-related factors such as urbanization and population growth can exert further changes in weather and climate extremes. As a result, the scientific community faces an increasing demand for updated appraisal of the time-varying climate extremes. The purpose of this study is to offer a robust and flexible statistical tool for non-stationary extreme value analysis which can better characterize the severity and likelihood of extreme climatic variables. This is critical to ensure a more resilient environment in a changing climate. Following the positive feedback on the first version of Non-Stationary Extreme Value Analysis (NEVA) Toolbox by Cheng at al. 2014, we present an improved version, i.e. NEVA2.0. The upgraded version herein builds upon a newly-developed hybrid evolution Markov Chain Monte Carlo (MCMC) approach for numerical parameters estimation and uncertainty assessment. This addition leads to a more robust uncertainty estimates of return levels, return periods, and risks of climatic extremes under both stationary and non-stationary assumptions. Moreover, NEVA2.0 is flexible in incorporating any user-specified covariate other than the default time-covariate (e.g., CO2 emissions, large scale climatic oscillation patterns). The new feature will allow users to examine non-stationarity of extremes induced by physical conditions that underlie the extreme events (e.g. antecedent soil moisture deficit, large-scale climatic teleconnections, urbanization). In addition, the new version offers an option to generate stationary and/or non-stationary rainfall Intensity - Duration - Frequency (IDF) curves that are widely used for risk assessment and infrastructure design. Finally, a Graphical User Interface (GUI) of the package is provided, making NEVA
V. L. Kozlov
2018-01-01
Full Text Available To solve the problem of increasing the accuracy of restoring a three-dimensional picture of space using two-dimensional digital images, it is necessary to use new effective techniques and algorithms for processing and correlation analysis of digital images. Actively developed tools that allow you to reduce the time costs for processing stereo images, improve the quality of the depth maps construction and automate their construction. The aim of the work is to investigate the possibilities of using various techniques for processing digital images to improve the measurements accuracy of the rangefinder based on the correlation analysis of the stereo image. The results of studies of the influence of color channel mixing techniques on the distance measurements accuracy for various functions realizing correlation processing of images are presented. Studies on the analysis of the possibility of using integral representation of images to reduce the time cost in constructing a depth map areproposed. The results of studies of the possibility of using images prefiltration before correlation processing when distance measuring by stereo imaging areproposed.It is obtained that using of uniform mixing of channels leads to minimization of the total number of measurement errors, and using of brightness extraction according to the sRGB standard leads to an increase of errors number for all of the considered correlation processing techniques. Integral representation of the image makes it possible to accelerate the correlation processing, but this method is useful for depth map calculating in images no more than 0.5 megapixels. Using of image filtration before correlation processing can provide, depending on the filter parameters, either an increasing of the correlation function value, which is useful for analyzing noisy images, or compression of the correlation function.
s-core network decomposition: A generalization of k-core analysis to weighted networks
Eidsaa, Marius; Almaas, Eivind
2013-12-01
A broad range of systems spanning biology, technology, and social phenomena may be represented and analyzed as complex networks. Recent studies of such networks using k-core decomposition have uncovered groups of nodes that play important roles. Here, we present s-core analysis, a generalization of k-core (or k-shell) analysis to complex networks where the links have different strengths or weights. We demonstrate the s-core decomposition approach on two random networks (ER and configuration model with scale-free degree distribution) where the link weights are (i) random, (ii) correlated, and (iii) anticorrelated with the node degrees. Finally, we apply the s-core decomposition approach to the protein-interaction network of the yeast Saccharomyces cerevisiae in the context of two gene-expression experiments: oxidative stress in response to cumene hydroperoxide (CHP), and fermentation stress response (FSR). We find that the innermost s-cores are (i) different from innermost k-cores, (ii) different for the two stress conditions CHP and FSR, and (iii) enriched with proteins whose biological functions give insight into how yeast manages these specific stresses.
Interactive general-purpose function minimization for the analysis of neutron scattering data
Abel, W.
1981-12-01
An on-line graphic display facility has been employed mainly for the peak analysis of time-of-flight spectra measured by inelastic scattering of thermal neutrons. But it is useful also for the analysis of spectra measured with triple axis spectrometers and of diffraction patterns. The spectral lines may be fitted by the following analytical shape functions: (i) a Gaussian, (ii) a Lorentzian, or (iii) a convolution of a Lorentzian with a Gaussian, plus a background continuum. Data reduction or correction may be invoked optionally. For more general applications in analysing of numerical data there is also the possibility to define the analytical shape functions by the user. Three different minimization methods are available which may be used alone or in combination. The parameters of the shape functions may be kept fixed or variable during the minimization steps. The width of variation may be restricted. Global correlation coefficients, parameter errors and the chi 2 are displayed to inform the user about the quality of the fit. A detailed description of the program operations is given. The programs are written in FORTRAN IV and use an IBM/2250-1 graphic display unit. (orig.) [de
Kinnebrock, Silja; Podolskij, Mark
This paper introduces a new estimator to measure the ex-post covariation between high-frequency financial time series under market microstructure noise. We provide an asymptotic limit theory (including feasible central limit theorems) for standard methods such as regression, correlation analysis...... process can be relaxed and how our method can be applied to non-synchronous observations. We also present an empirical study of how high-frequency correlations, regressions and covariances change through time....
Co-occurrence correlations of heavy metals in sediments revealed using network analysis.
Liu, Lili; Wang, Zhiping; Ju, Feng; Zhang, Tong
2015-01-01
In this study, the correlation-based study was used to identify the co-occurrence correlations among metals in marine sediment of Hong Kong, based on the long-term (from 1991 to 2011) temporal and spatial monitoring data. 14 stations out of the total 45 marine sediment monitoring stations were selected from three representative areas, including Deep Bay, Victoria Harbour and Mirs Bay. Firstly, Spearman's rank correlation-based network analysis was conducted as the first step to identify the co-occurrence correlations of metals from raw metadata, and then for further analysis using the normalized metadata. The correlations patterns obtained by network were consistent with those obtained by the other statistic normalization methods, including annual ratios, R-squared coefficient and Pearson correlation coefficient. Both Deep Bay and Victoria Harbour have been polluted by heavy metals, especially for Pb and Cu, which showed strong co-occurrence with other heavy metals (e.g. Cr, Ni, Zn and etc.) and little correlations with the reference parameters (Fe or Al). For Mirs Bay, which has better marine sediment quality compared with Deep Bay and Victoria Harbour, the co-occurrence patterns revealed by network analysis indicated that the metals in sediment dominantly followed the natural geography process. Besides the wide applications in biology, sociology and informatics, it is the first time to apply network analysis in the researches of environment pollutions. This study demonstrated its powerful application for revealing the co-occurrence correlations among heavy metals in marine sediments, which could be further applied for other pollutants in various environment systems. Copyright © 2014 Elsevier Ltd. All rights reserved.
Fujiwara, Shigeyasu; Sakata, Fumihiko
2003-01-01
The quantum level fluctuation in various systems has been shown to be characterized by the random matrix theory, and to be related to a regular-to-chaos transition in classical system. We present a new qualitative analysis of quantum and classical fluctuation properties by exploiting correlation coefficients and variances. It is shown that the correlation coefficient of quantum level density is inversely proportional to the variance of consecutive phase-space point spacings on the Poincare section plane. (author)
Shimizu, Ryosuke; Edamatsu, Keiichi; Itoh, Tadashi
2006-01-01
We present one- and two-photon diffraction and interference experiments involving parametric down-converted photon pairs. By controlling the divergence of the pump beam in parametric down-conversion, the diffraction-interference pattern produced by an object changes from a quantum (perfectly correlated) case to a classical (uncorrelated) one. The observed diffraction and interference patterns are accurately reproduced by Fourier-optical analysis taking into account the quantum spatial correlation. We show that the relation between the spatial correlation and the object size plays a crucial role in the formation of both one- and two-photon diffraction-interference patterns
Balint-Kurti, Gabriel G; Vasyutinskii, Oleg S
2009-12-31
A general reactive collision of the type A + B --> C + D is considered where both the collision partners (A and B) or the products (C and D) may possess internal, i.e., spin, orbital or rotational, angular momenta. Compact expressions are derived using a rigorous quantum mechanical analysis for the angular momentum anisotropy of either of the products (C or D) arising from an initially polarized distribution of the reactant angular momentum. The angular momentum distribution of the product is expressed in terms of canonical spherical tensors multiplied by anisotropy-transforming coefficients c(K(i)q(k))(K)(K(r),L). These coefficients act as transformation coefficients between the angular momentum anisotropy of the reactants and that of the product. They are independent of scattering angle but depend on the details of the scattering dynamics. The relationship between the coefficients c(K(i)q(k))(K)(K(r),L) and the body-fixed scattering S matrix is given and the methodology for the quantum mechanical calculation of the anisotropy-transforming coefficients is clearly laid out. The anisotropy-transforming coefficients are amenable to direct experimental measurement in a similar manner to vector correlation and alignment parameters in photodissociation processes. A key aspect of the theory is the use of projections of both reactant and product angular momenta onto the product recoil vector direction. An important new conservation rule is revealed through the analysis, namely that if the state multipole for reactant angular momentum distribution has a projection q(k) onto the product recoil vector the state multipoles for the product angular momentum distribution all have this same projection. Expressions are also presented for the distribution of the product angular momentum when its components are evaluated relative to the space-fixed Z-axis. Notes with detailed derivations of all the formulas are available as Supporting Information.
Yang, Xiaojing; Xiong, Xuewu; Cao, Ji; Luan, Baolei; Liu, Yongjun; Liu, Guozhu; Zhang, Lei
2015-01-30
Matrix interference, which can lead to false positive/negative results, contamination of injector or separation column, incompatibility between sample solution and the selected analytical instrument, and response inhibition or even quenching, is commonly suffered for the analysis of trace level toxic impurities in drug substance. In this study, a simple matrix precipitation strategy is proposed to eliminate or minimize the above stated matrix interference problems. Generally, a sample of active pharmaceutical ingredients (APIs) is dissolved in an appropriate solvent to achieve the desired high concentration and then an anti-solvent is added to precipitate the matrix substance. As a result, the target analyte is extracted into the mixed solution with very less residual of APIs. This strategy has the characteristics of simple manipulation, high recovery and excellent anti-interference capability. It was found that the precipitation ratio (R, representing the ability to remove matrix substance) and the proportion of solvent (the one used to dissolve APIs) in final solution (P, affecting R and also affecting the method sensitivity) are two important factors of the precipitation process. The correlation between R and P was investigated by performing precipitation with various APIs in different solvent/anti-solvent systems. After a detailed mathematical reasoning process, P=20% was proved to be an effective and robust condition to perform the precipitation strategy. The precipitation method with P=20% can be used as a general strategy for toxic impurity analysis in APIs. Finally, several typical examples are described in this article, where the challenging matrix interference issues have been resolved successfully. Copyright © 2014 Elsevier B.V. All rights reserved.
Zhuang, Xiaoyang; Wei, Yu; Ma, Feng
2015-07-01
In this paper, the multifractality and efficiency degrees of ten important Chinese sectoral indices are evaluated using the methods of MF-DFA and generalized Hurst exponents. The study also scrutinizes the dynamics of the efficiency of Chinese sectoral stock market by the rolling window approach. The overall empirical findings revealed that all the sectoral indices of Chinese stock market exist different degrees of multifractality. The results of different efficiency measures have agreed on that the 300 Materials index is the least efficient index. However, they have a slight diffidence on the most efficient one. The 300 Information Technology, 300 Telecommunication Services and 300 Health Care indices are comparatively efficient. We also investigate the cross-correlations between the ten sectoral indices and WTI crude oil price based on Multifractal Detrended Cross-correlation Analysis. At last, some relevant discussions and implications of the empirical results are presented.
Kanno, Shoichi; Matsuo, Yutaka; Shiba, Shotaro
2010-01-01
We give some evidences of the Alday-Gaiotto-Tachikawa-Wyllard relation between SU(3) quiver gauge theories and A 2 Toda theory. In particular, we derive the explicit form of 5-point correlation functions in the lower orders and confirm the agreement with Nekrasov's partition function for SU(3)xSU(3) quiver gauge theory. The algorithm to derive the correlation functions can be applied to a general n-point function in A 2 Toda theory, which will be useful to establish the relation for more generic quivers. Partial analysis is also given for the SU(3)xSU(2) case, and we comment on some technical issues that need clarification before establishing the relation.
Ma, Chuang; Wang, Xiangfeng
2012-09-01
One of the computational challenges in plant systems biology is to accurately infer transcriptional regulation relationships based on correlation analyses of gene expression patterns. Despite several correlation methods that are applied in biology to analyze microarray data, concerns regarding the compatibility of these methods with the gene expression data profiled by high-throughput RNA transcriptome sequencing (RNA-Seq) technology have been raised. These concerns are mainly due to the fact that the distribution of read counts in RNA-Seq experiments is different from that of fluorescence intensities in microarray experiments. Therefore, a comprehensive evaluation of the existing correlation methods and, if necessary, introduction of novel methods into biology is appropriate. In this study, we compared four existing correlation methods used in microarray analysis and one novel method called the Gini correlation coefficient on previously published microarray-based and sequencing-based gene expression data in Arabidopsis (Arabidopsis thaliana) and maize (Zea mays). The comparisons were performed on more than 11,000 regulatory relationships in Arabidopsis, including 8,929 pairs of transcription factors and target genes. Our analyses pinpointed the strengths and weaknesses of each method and indicated that the Gini correlation can compensate for the shortcomings of the Pearson correlation, the Spearman correlation, the Kendall correlation, and the Tukey's biweight correlation. The Gini correlation method, with the other four evaluated methods in this study, was implemented as an R package named rsgcc that can be utilized as an alternative option for biologists to perform clustering analyses of gene expression patterns or transcriptional network analyses.
Ma, Chuang; Wang, Xiangfeng
2012-01-01
One of the computational challenges in plant systems biology is to accurately infer transcriptional regulation relationships based on correlation analyses of gene expression patterns. Despite several correlation methods that are applied in biology to analyze microarray data, concerns regarding the compatibility of these methods with the gene expression data profiled by high-throughput RNA transcriptome sequencing (RNA-Seq) technology have been raised. These concerns are mainly due to the fact that the distribution of read counts in RNA-Seq experiments is different from that of fluorescence intensities in microarray experiments. Therefore, a comprehensive evaluation of the existing correlation methods and, if necessary, introduction of novel methods into biology is appropriate. In this study, we compared four existing correlation methods used in microarray analysis and one novel method called the Gini correlation coefficient on previously published microarray-based and sequencing-based gene expression data in Arabidopsis (Arabidopsis thaliana) and maize (Zea mays). The comparisons were performed on more than 11,000 regulatory relationships in Arabidopsis, including 8,929 pairs of transcription factors and target genes. Our analyses pinpointed the strengths and weaknesses of each method and indicated that the Gini correlation can compensate for the shortcomings of the Pearson correlation, the Spearman correlation, the Kendall correlation, and the Tukey’s biweight correlation. The Gini correlation method, with the other four evaluated methods in this study, was implemented as an R package named rsgcc that can be utilized as an alternative option for biologists to perform clustering analyses of gene expression patterns or transcriptional network analyses. PMID:22797655
Estimation of the biserial correlation and its sampling variance for use in meta-analysis.
Jacobs, Perke; Viechtbauer, Wolfgang
2017-06-01
Meta-analyses are often used to synthesize the findings of studies examining the correlational relationship between two continuous variables. When only dichotomous measurements are available for one of the two variables, the biserial correlation coefficient can be used to estimate the product-moment correlation between the two underlying continuous variables. Unlike the point-biserial correlation coefficient, biserial correlation coefficients can therefore be integrated with product-moment correlation coefficients in the same meta-analysis. The present article describes the estimation of the biserial correlation coefficient for meta-analytic purposes and reports simulation results comparing different methods for estimating the coefficient's sampling variance. The findings indicate that commonly employed methods yield inconsistent estimates of the sampling variance across a broad range of research situations. In contrast, consistent estimates can be obtained using two methods that appear to be unknown in the meta-analytic literature. A variance-stabilizing transformation for the biserial correlation coefficient is described that allows for the construction of confidence intervals for individual coefficients with close to nominal coverage probabilities in most of the examined conditions. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Briassouli Alexia
2004-01-01
Full Text Available A novel technique is proposed for watermarking of MPEG-1 and MPEG-2 compressed video streams. The proposed scheme is applied directly in the domain of MPEG-1 system streams and MPEG-2 program streams (multiplexed streams. Perceptual models are used during the embedding process in order to avoid degradation of the video quality. The watermark is detected without the use of the original video sequence. A modified correlation-based detector is introduced that applies nonlinear preprocessing before correlation. Experimental evaluation demonstrates that the proposed scheme is able to withstand several common attacks. The resulting watermarking system is very fast and therefore suitable for copyright protection of compressed video.
Python tools for rapid development, calibration, and analysis of generalized groundwater-flow models
Starn, J. J.; Belitz, K.
2014-12-01
National-scale water-quality data sets for the United States have been available for several decades; however, groundwater models to interpret these data are available for only a small percentage of the country. Generalized models may be adequate to explain and project groundwater-quality trends at the national scale by using regional scale models (defined as watersheds at or between the HUC-6 and HUC-8 levels). Coast-to-coast data such as the National Hydrologic Dataset Plus (NHD+) make it possible to extract the basic building blocks for a model anywhere in the country. IPython notebooks have been developed to automate the creation of generalized groundwater-flow models from the NHD+. The notebook format allows rapid testing of methods for model creation, calibration, and analysis. Capabilities within the Python ecosystem greatly speed up the development and testing of algorithms. GeoPandas is used for very efficient geospatial processing. Raster processing includes the Geospatial Data Abstraction Library and image processing tools. Model creation is made possible through Flopy, a versatile input and output writer for several MODFLOW-based flow and transport model codes. Interpolation, integration, and map plotting included in the standard Python tool stack also are used, making the notebook a comprehensive platform within on to build and evaluate general models. Models with alternative boundary conditions, number of layers, and cell spacing can be tested against one another and evaluated by using water-quality data. Novel calibration criteria were developed by comparing modeled heads to land-surface and surface-water elevations. Information, such as predicted age distributions, can be extracted from general models and tested for its ability to explain water-quality trends. Groundwater ages then can be correlated with horizontal and vertical hydrologic position, a relation that can be used for statistical assessment of likely groundwater-quality conditions
Langenbucher, Frieder
2002-01-01
Most computations in the field of in vitro/in vivo correlations can be handled directly by Excel worksheets, without the need for specialized software. Following a summary of Excel features, applications are illustrated for numerical computation of AUC and Mean, Wagner-Nelson and Loo-Riegelman absorption plots, and polyexponential curve fitting.