Speed Estimation in Geared Wind Turbines Using the Maximum Correlation Coefficient
Skrimpas, Georgios Alexandros; Marhadi, Kun S.; Jensen, Bogi Bech;
2015-01-01
to overcome the above mentioned issues. The high speed stage shaft angular velocity is calculated based on the maximum correlation coefficient between the 1 st gear mesh frequency of the last gearbox stage and a pure sinus tone of known frequency and phase. The proposed algorithm utilizes vibration signals...
Rocco, Paolo; Cilurzo, Francesco; Minghetti, Paola; Vistoli, Giulio; Pedretti, Alessandro
2017-10-01
The data presented in this article are related to the article titled "Molecular Dynamics as a tool for in silico screening of skin permeability" (Rocco et al., 2017) [1]. Knowledge of the confidence interval and maximum theoretical value of the correlation coefficient r can prove useful to estimate the reliability of developed predictive models, in particular when there is great variability in compiled experimental datasets. In this Data in Brief article, data from purposely designed numerical simulations are presented to show how much the maximum r value is worsened by increasing the data uncertainty. The corresponding confidence interval of r is determined by using the Fisher r→Z transform.
Er, Hale Çolakoğlu; Erden, Ayşe; Küçük, N Özlem; Geçim, Ethem
2014-01-01
The aim of this study was to retrospectively assess the correlation between minimum apparent diffusion coefficient (ADCmin) values obtained from diffusion-weighted magnetic resonance imaging (MRI) and maximum standardized uptake values (SUVmax) obtained from positron emission tomography-computed tomography (PET-CT) in rectal cancer. Forty-one patients with pathologically confirmed rectal adenocarcinoma were included in this study. For preoperative staging, PET-CT and pelvic MRI with diffusion-weighted imaging were performed within one week (mean time interval, 3±1 day). For ADC measurements, the region of interest (ROI) was manually drawn along the border of each hyperintense tumor on b=1000 s/mm2 images. After repeating this procedure on each consecutive tumor-containing slice to cover the entire tumoral area, ROIs were copied to ADC maps. ADCmin was determined as the lowest ADC value among all ROIs in each tumor. For SUVmax measurements, whole-body images were assessed visually on transaxial, sagittal, and coronal images. ROIs were determined from the lesions observed on each slice, and SUVmax values were calculated automatically. The mean values of ADCmin and SUVmax were compared using Spearman's test. The mean ADCmin was 0.62±0.19×10-3 mm2/s (range, 0.368-1.227×10-3 mm2/s), the mean SUVmax was 20.07±9.3 (range, 4.3-49.5). A significant negative correlation was found between ADCmin and SUVmax (r=-0.347; P = 0.026). There was a significant negative correlation between the ADCmin and SUVmax values in rectal adenocarcinomas.
Modified Biserial Correlation Coefficients.
Kraemer, Helena Chmura
1981-01-01
Asymptotic distribution theory of Brogden's form of biserial correlation coefficient is derived and large sample estimates of its standard error obtained. Its relative efficiency to the biserial correlation coefficient is examined. Recommendations for choice of estimator of biserial correlation are presented. (Author/JKS)
Sürer Budak, Evrim; Toptaş, Tayfun; Aydın, Funda; Öner, Ali Ozan; Çevikol, Can; Şimşek, Tayup
2017-02-05
To explore the correlation of the primary tumor's maximum standardized uptake value (SUVmax) and minimum apparent diffusion coefficient (ADCmin) with clinicopathologic features, and to determine their predictive power in endometrial cancer (EC). A total of 45 patients who had undergone staging surgery after a preoperative evaluation with (18)F-fluorodeoxyglucose (FDG) positron emission tomography/computerized tomography (PET/CT) and diffusion-weighted magnetic resonance imaging (DW-MRI) were included in a prospective case-series study with planned data collection. Multiple linear regression analysis was used to determine the correlations between the study variables. The mean ADCmin and SUVmax values were determined as 0.72±0.22 and 16.54±8.73, respectively. A univariate analysis identified age, myometrial invasion (MI) and lymphovascular space involvement (LVSI) as the potential factors associated with ADCmin while it identified age, stage, tumor size, MI, LVSI and number of metastatic lymph nodes as the potential variables correlated to SUVmax. In multivariate analysis, on the other hand, MI was the only significant variable that correlated with ADCmin (p=0.007) and SUVmax (p=0.024). Deep MI was best predicted by an ADCmin cutoff value of ≤0.77 [93.7% sensitivity, 48.2% specificity, and 93.0% negative predictive value (NPV)] and SUVmax cutoff value of >20.5 (62.5% sensitivity, 86.2% specificity, and 81.0% NPV); however, the two diagnostic tests were not significantly different (p=0.266). Among clinicopathologic features, only MI was independently correlated with SUVmax and ADCmin. However, the routine use of (18)F-FDG PET/CT or DW-MRI cannot be recommended at the moment due to less than ideal predictive performances of both parameters.
Coefficient of Partial Correlation and Its Calculation
段全才; 张保法
1992-01-01
This thesis offers the general concept of coefficient of partial correlation.Starting with regres-sion analysis,the paper,by using samples,infers the general formula of expressing coefficient of partial correlation by way of simple correlation coefficient.
Correlation Degree and Correlation Coefficient of Multi- Output Functions
JU Gui-zhi; ZHAO Ya-qun
2005-01-01
We present definitions of the correlation degree and correlation coefficient of multi-output functions. Two relationships about the correlation degree of multi-output functions are proved. One is between the correlation degree and independency,the other is between the correlation degree and balance. Especially the paper discusses the correlation degree of affine multioutput functions. We demonstrate properties of the correlation coefficient of multi-output functions. One is the value range of the correlation coefficient, one is the relationship between the correlation coefficient and independency, and another is the sufficient and necessary condition that two multi-output functions are equivalent to each other.
Karan, Belgin; Pourbagher, Aysin; Torun, Nese
2016-06-01
To evaluate the correlations between the apparent diffusion coefficient (ADC) value and the standardized uptake value (SUV) with prognostic factors in breast cancer. Seventy women with invasive breast cancer (56 cases of invasive ductal carcinoma, four of mixed ductal and lobular invasive carcinoma, three of lobular invasive carcinoma, two of micropapillary carcinoma, and one each of mixed ductal and mucinous carcinoma, mucinous carcinoma, medullary carcinoma, metaplastic carcinoma, and tubular carcinoma) were included in this study. All patients underwent presurgical breast magnetic resonance imaging (MRI) with diffusion-weighted imaging (DWI) at 1.5T and whole-body (18) F-fluorodeoxyglucose ((18) F-FDG) positron emission tomography (PET) / computed tomography (CT). For all invasive breast cancers and invasive ductal carcinomas, we assessed the relationships among ADC, SUV, and pathological prognostic factors. Both the median ADC value and maximum SUV (SUVmax) were significantly associated with vascular invasion (P = 0.008 and P = 0.026, respectively). SUVmax was also significantly correlated with tumor size (P = 0.001), histological grade (P = 0.001), lymph node status (P = 0.0015), estrogen receptor status (P = 0.010), and human epidermal growth factor receptor 2 status (P = 0.020), whereas ADC values were not. The correlation between the ADC and SUVmax was not significant (P = 0.356; R = -0.112). Mucinous carcinoma showed high ADC and relatively low SUVmax. Medullary carcinoma showed low ADC and high SUVmax. When we evaluated the relationships among ADC, SUVmax, and prognostic factors in the 56 invasive ductal carcinomas, our statistical results were not significantly changed, except SUVmax was also significantly associated with progesterone receptor status (P = 0.034), but not lymph node status. SUVmax may be valuable for predicting the prognosis of breast cancer. Both ADC and SUVmax are useful to predict vascular invasion. J. Magn. Reson. Imaging 2016
Spatial correlation coefficient images for ultrasonic detection.
Cepel, Raina; Ho, K C; Rinker, Brett A; Palmer, Donald D; Lerch, Terrence P; Neal, Steven P
2007-09-01
In ultrasonics, image formation and detection are generally based on signal amplitude. In this paper, we introduce correlation coefficient images as a signal-amplitude independent approach for image formation. The correlation coefficients are calculated between A-scans digitized at adjacent measurement positions. In these images, defects are revealed as regions of high or low correlation relative to the background correlations associated with noise. Correlation coefficient and C-scan images are shown to demonstrate flat-bottom-hole detection in a stainless steel annular ring and crack detection in an aluminum aircraft structure.
Wavelet Correlation Coefficient of 'strongly correlated' financial time series
Ashok Razdan
2003-01-01
In this paper we use wavelet concepts to show that correlation coefficient between two financial data's is not constant but varies with scale from high correlation value to strongly anti-correlation value This studies is important because correlation coefficient is used to quantify degree of independence between two variables. In econophysics correlation coefficient forms important input to evolve hierarchial tree and minimum spanning tree of financial data.
Alternatives to Pearson's and Spearman's Correlation Coefficients
Smarandache, Florentin
2008-01-01
This article presents several alternatives to Pearson's correlation coefficient and many examples. In the samples where the rank in a discrete variable counts more than the variable values, the mixtures that we propose of Pearson's and Spearman's correlation coefficients give better results.
Estimation of the simple correlation coefficient.
Shieh, Gwowen
2010-11-01
This article investigates some unfamiliar properties of the Pearson product-moment correlation coefficient for the estimation of simple correlation coefficient. Although Pearson's r is biased, except for limited situations, and the minimum variance unbiased estimator has been proposed in the literature, researchers routinely employ the sample correlation coefficient in their practical applications, because of its simplicity and popularity. In order to support such practice, this study examines the mean squared errors of r and several prominent formulas. The results reveal specific situations in which the sample correlation coefficient performs better than the unbiased and nearly unbiased estimators, facilitating recommendation of r as an effect size index for the strength of linear association between two variables. In addition, related issues of estimating the squared simple correlation coefficient are also considered.
Evaluating maximum likelihood estimation methods to determine the hurst coefficients
Kendziorski, C. M.; Bassingthwaighte, J. B.; Tonellato, P. J.
1999-12-01
A maximum likelihood estimation method implemented in S-PLUS ( S-MLE) to estimate the Hurst coefficient ( H) is evaluated. The Hurst coefficient, with 0.5long memory time series by quantifying the rate of decay of the autocorrelation function. S-MLE was developed to estimate H for fractionally differenced (fd) processes. However, in practice it is difficult to distinguish between fd processes and fractional Gaussian noise (fGn) processes. Thus, the method is evaluated for estimating H for both fd and fGn processes. S-MLE gave biased results of H for fGn processes of any length and for fd processes of lengths less than 2 10. A modified method is proposed to correct for this bias. It gives reliable estimates of H for both fd and fGn processes of length greater than or equal to 2 11.
Concordance correlation coefficient applied to discrete data.
Carrasco, Josep L; Jover, Lluis
2005-12-30
In any field in which decisions are subject to measurements, interchangeability between the methods used to obtain these measurements is essential. To consider methods as interchangeable, a certain degree of agreement is needed between the measurements they provide. The concordance correlation coefficient is an index that assesses the strength of agreement and it has been widely applied in situations in which measurements are made on a continuous scale. Recently the concordance correlation coefficient has been defined as a specific intraclass correlation coefficient estimated by the variance components of a Normal-Normal mixed linear model. Although this coefficient was defined for the continuous scale case, it may also be used with a discrete scale. In this case the data are often transformed and normalized, and the concordance correlation is applied. This study discusses the expression of the concordance correlation coefficient for discrete Poisson data by means of the Poisson-Normal generalized linear mixed model. The behaviour of the concordance correlation coefficient estimate is assessed by means of a simulation study, in which the estimates were compared using four models: three Normal-Normal mixed models with raw data, log-transformed data and square-root transformed data, and the Poisson-Normal generalized linear mixed model. An example is provided in which two different methods are used to measure CD34+ cells.
Accurate structural correlations from maximum likelihood superpositions.
Douglas L Theobald
2008-02-01
Full Text Available The cores of globular proteins are densely packed, resulting in complicated networks of structural interactions. These interactions in turn give rise to dynamic structural correlations over a wide range of time scales. Accurate analysis of these complex correlations is crucial for understanding biomolecular mechanisms and for relating structure to function. Here we report a highly accurate technique for inferring the major modes of structural correlation in macromolecules using likelihood-based statistical analysis of sets of structures. This method is generally applicable to any ensemble of related molecules, including families of nuclear magnetic resonance (NMR models, different crystal forms of a protein, and structural alignments of homologous proteins, as well as molecular dynamics trajectories. Dominant modes of structural correlation are determined using principal components analysis (PCA of the maximum likelihood estimate of the correlation matrix. The correlations we identify are inherently independent of the statistical uncertainty and dynamic heterogeneity associated with the structural coordinates. We additionally present an easily interpretable method ("PCA plots" for displaying these positional correlations by color-coding them onto a macromolecular structure. Maximum likelihood PCA of structural superpositions, and the structural PCA plots that illustrate the results, will facilitate the accurate determination of dynamic structural correlations analyzed in diverse fields of structural biology.
Temporal correlation coefficient for directed networks.
Büttner, Kathrin; Salau, Jennifer; Krieter, Joachim
2016-01-01
Previous studies dealing with network theory focused mainly on the static aggregation of edges over specific time window lengths. Thus, most of the dynamic information gets lost. To assess the quality of such a static aggregation the temporal correlation coefficient can be calculated. It measures the overall possibility for an edge to persist between two consecutive snapshots. Up to now, this measure is only defined for undirected networks. Therefore, we introduce the adaption of the temporal correlation coefficient to directed networks. This new methodology enables the distinction between ingoing and outgoing edges. Besides a small example network presenting the single calculation steps, we also calculated the proposed measurements for a real pig trade network to emphasize the importance of considering the edge direction. The farm types at the beginning of the pork supply chain showed clearly higher values for the outgoing temporal correlation coefficient compared to the farm types at the end of the pork supply chain. These farm types showed higher values for the ingoing temporal correlation coefficient. The temporal correlation coefficient is a valuable tool to understand the structural dynamics of these systems, as it assesses the consistency of the edge configuration. The adaption of this measure for directed networks may help to preserve meaningful additional information about the investigated network that might get lost if the edge directions are ignored.
Correlation and prediction of gaseous diffusion coefficients.
Marrero, T. R.; Mason, E. A.
1973-01-01
A new correlation method for binary gaseous diffusion coefficients from very low temperatures to 10,000 K is proposed based on an extended principle of corresponding states, and having greater range and accuracy than previous correlations. There are two correlation parameters that are related to other physical quantities and that are predictable in the absence of diffusion measurements. Quantum effects and composition dependence are included, but high-pressure effects are not. The results are directly applicable to multicomponent mixtures.
Reymbaut, A.; Gagnon, A.-M.; Bergeron, D.; Tremblay, A.-M. S.
2017-03-01
The computation of transport coefficients, even in linear response, is a major challenge for theoretical methods that rely on analytic continuation of correlation functions obtained numerically in Matsubara space. While maximum entropy methods can be used for certain correlation functions, this is not possible in general, important examples being the Seebeck, Hall, Nernst, and Reggi-Leduc coefficients. Indeed, positivity of the spectral weight on the positive real-frequency axis is not guaranteed in these cases. The spectral weight can even be complex in the presence of broken time-reversal symmetry. Various workarounds, such as the neglect of vertex corrections or the study of the infinite frequency or Kelvin limits, have been proposed. Here, we show that one can define auxiliary response functions that allow one to extract the desired real-frequency susceptibilities from maximum entropy methods in the most general multiorbital cases with no particular symmetry. As a benchmark case, we study the longitudinal thermoelectric response and corresponding Onsager coefficient in the single-band two-dimensional Hubbard model treated with dynamical mean-field theory and continuous-time quantum Monte Carlo. We thereby extend the maximum entropy analytic continuation with auxiliary functions (MaxEntAux method), developed for the study of the superconducting pairing dynamics of correlated materials, to transport coefficients.
Clustering stocks using partial correlation coefficients
Jung, Sean S.; Chang, Woojin
2016-11-01
A partial correlation analysis is performed on the Korean stock market (KOSPI). The difference between Pearson correlation and the partial correlation is analyzed and it is found that when conditioned on the market return, Pearson correlation coefficients are generally greater than those of the partial correlation, which implies that the market return tends to drive up the correlation between stock returns. A clustering analysis is then performed to study the market structure given by the partial correlation analysis and the members of the clusters are compared with the Global Industry Classification Standard (GICS). The initial hypothesis is that the firms in the same GICS sector are clustered together since they are in a similar business and environment. However, the result is inconsistent with the hypothesis and most clusters are a mix of multiple sectors suggesting that the traditional approach of using sectors to determine the proximity between stocks may not be sufficient enough to diversify a portfolio.
The Evolution of Pearson's Correlation Coefficient
Kader, Gary D.; Franklin, Christine A.
2008-01-01
This article describes an activity for developing the notion of association between two quantitative variables. By exploring a collection of scatter plots, the authors propose a nonstandard "intuitive" measure of association; and by examining properties of this measure, they develop the more standard measure, Pearson's Correlation Coefficient. The…
Quantum Correlation Coefficients for Angular Coherent States
CHEN Wei; HE Yan; GUO Hao
2009-01-01
Quantum covariance and correlation coefficients of angular or SU(2) coherent states are directly calculated for all irreducible unitary representations.These results explicitly verify that the angular coherent states minimize the Robertson-Schrodinger uncertainty relation for all spins, which means that they are the so-called intelligent states.The same results can be obtained by the Schwinger representation approach.
Computer programs for the concordance correlation coefficient.
Crawford, Sara B; Kosinski, Andrzej S; Lin, Hung-Mo; Williamson, John M; Barnhart, Huiman X
2007-10-01
The CCC macro is presented for computation of the concordance correlation coefficient (CCC), a common measure of reproducibility. The macro has been produced in both SAS and R, and a detailed presentation of the macro input and output for the SAS program is included. The macro provides estimation of three versions of the CCC, as presented by Lin [L.I.-K. Lin, A concordance correlation coefficient to evaluate reproducibility, Biometrics 45 (1989) 255-268], Barnhart et al. [H.X. Barnhart, J.L. Haber, J.L. Song, Overall concordance correlation coefficient for evaluating agreement among multiple observers, Biometrics 58 (2002) 1020-1027], and Williamson et al. [J.M. Williamson, S.B. Crawford, H.M. Lin, Resampling dependent concordance correlation coefficients, J. Biopharm. Stat. 17 (2007) 685-696]. It also provides bootstrap confidence intervals for the CCC, as well as for the difference in CCCs for both independent and dependent samples. The macro is designed for balanced data only. Detailed explanation of the involved computations and macro variable definitions are provided in the text. Two biomedical examples are included to illustrate that the macro can be easily implemented.
The Evolution of Pearson's Correlation Coefficient
Kader, Gary D.; Franklin, Christine A.
2008-01-01
This article describes an activity for developing the notion of association between two quantitative variables. By exploring a collection of scatter plots, the authors propose a nonstandard "intuitive" measure of association; and by examining properties of this measure, they develop the more standard measure, Pearson's Correlation Coefficient. The…
Temporal Correlations of the Running Maximum of a Brownian Trajectory
Bénichou, Olivier; Krapivsky, P. L.; Mejía-Monasterio, Carlos; Oshanin, Gleb
2016-08-01
We study the correlations between the maxima m and M of a Brownian motion (BM) on the time intervals [0 ,t1] and [0 ,t2], with t2>t1. We determine the exact forms of the distribution functions P (m ,M ) and P (G =M -m ), and calculate the moments E {(M-m ) k} and the cross-moments E {mlMk} with arbitrary integers l and k . We show that correlations between m and M decay as √{t1/t2 } when t2/t1→∞ , revealing strong memory effects in the statistics of the BM maxima. We also compute the Pearson correlation coefficient ρ (m ,M ) and the power spectrum of Mt, and we discuss a possibility of extracting the ensemble-averaged diffusion coefficient in single-trajectory experiments using a single realization of the maximum process.
Design of wind turbine airfoils based on maximum power coefficient
Chen, Jin; Cheng, Jiangtao; Shen, Wenzhong;
2010-01-01
noise prediction model, the previously developed integrated design technique is further developed. The new code takes into account different airfoil requirements according to their local positions on a blade, such as sensitivity to leading edge roughness, design lift at off-design condition, stall......Based on the blade element momentum (BEM) theory, the power coefficient of a wind turbine can be expressed in function of local tip speed ratio and lift-drag ratio. By taking the power coefficient in a predefined range of angle of attack as the final design objective and combining with an airfoil...
Flash ADC data processing with correlation coefficients
Blyth, D.; Gibson, M.; Mcfarland, D.; Comfort, J.R., E-mail: Joseph.Comfort@asu.edu
2014-02-21
The large growth of flash ADC techniques for processing signals, especially in applications of streaming data, raises issues such as data flow through an acquisition system, long-term storage, and greater complexity in data analysis. In addition, experiments that push the limits of sensitivity need to distinguish legitimate signals from noise. The use of correlation coefficients is examined to address these issues. They are found to be quite successful well into the noise region. The methods can also be extended to Field Programmable Gate Array modules for compressing the data flow and greatly enhancing the event rate capabilities.
A comparison of two indices for the intraclass correlation coefficient.
Shieh, Gwowen
2012-12-01
In the present study, we examined the behavior of two indices for measuring the intraclass correlation in the one-way random effects model: the prevailing ICC(1) (Fisher, 1938) and the corrected eta-squared (Bliese & Halverson, 1998). These two procedures differ both in their methods of estimating the variance components that define the intraclass correlation coefficient and in their performance of bias and mean squared error in the estimation of the intraclass correlation coefficient. In contrast with the natural unbiased principle used to construct ICC(1), in the present study it was analytically shown that the corrected eta-squared estimator is identical to the maximum likelihood estimator and the pairwise estimator under equal group sizes. Moreover, the empirical results obtained from the present Monte Carlo simulation study across various group structures revealed the mutual dominance relationship between their truncated versions for negative values. The corrected eta-squared estimator performs better than the ICC(1) estimator when the underlying population intraclass correlation coefficient is small. Conversely, ICC(1) has a clear advantage over the corrected eta-squared for medium and large magnitudes of population intraclass correlation coefficient. The conceptual description and numerical investigation provide guidelines to help researchers choose between the two indices for more accurate reliability analysis in multilevel research.
Modeling Complex System Correlation Using Detrended Cross-Correlation Coefficient
Keqiang Dong
2014-01-01
Full Text Available The understanding of complex systems has become an area of active research for physicists because such systems exhibit interesting dynamical properties such as scale invariance, volatility correlation, heavy tails, and fractality. We here focus on traffic dynamic as an example of a complex system. By applying the detrended cross-correlation coefficient method to traffic time series, we find that the traffic fluctuation time series may exhibit cross-correlation characteristic. Further, we show that two traffic speed time series derived from adjacent sections exhibit much stronger cross-correlations than the two speed series derived from adjacent lanes. Similarly, we also demonstrate that the cross-correlation property between the traffic volume variables from two adjacent sections is stronger than the cross-correlation property between the volume variables of adjacent lanes.
The Attenuation of Correlation Coefficients: A Statistical Literacy Issue
Trafimow, David
2016-01-01
Much of the science reported in the media depends on correlation coefficients. But the size of correlation coefficients depends, in part, on the reliability with which the correlated variables are measured. Understanding this is a statistical literacy issue.
Adler, Jeremy; Parmryd, Ingela
2010-08-01
The Pearson correlation coefficient (PCC) and the Mander's overlap coefficient (MOC) are used to quantify the degree of colocalization between fluorophores. The MOC was introduced to overcome perceived problems with the PCC. The two coefficients are mathematically similar, differing in the use of either the absolute intensities (MOC) or of the deviation from the mean (PCC). A range of correlated datasets, which extend to the limits of the PCC, only evoked a limited response from the MOC. The PCC is unaffected by changes to the offset while the MOC increases when the offset is positive. Both coefficients are independent of gain. The MOC is a confusing hybrid measurement, that combines correlation with a heavily weighted form of co-occurrence, favors high intensity combinations, downplays combinations in which either or both intensities are low and ignores blank pixels. The PCC only measures correlation. A surprising finding was that the addition of a second uncorrelated population can substantially increase the measured correlation, demonstrating the importance of excluding background pixels. Overall, since the MOC is unresponsive to substantial changes in the data and is hard to interpret, it is neither an alternative to nor a useful substitute for the PCC. The MOC is not suitable for making measurements of colocalization either by correlation or co-occurrence.
Testing the Correlated Random Coefficient Model*
Heckman, James J.; Schmierer, Daniel; Urzua, Sergio
2010-01-01
The recent literature on instrumental variables (IV) features models in which agents sort into treatment status on the basis of gains from treatment as well as on baseline-pretreatment levels. Components of the gains known to the agents and acted on by them may not be known by the observing economist. Such models are called correlated random coe cient models. Sorting on unobserved components of gains complicates the interpretation of what IV estimates. This paper examines testable implications of the hypothesis that agents do not sort into treatment based on gains. In it, we develop new tests to gauge the empirical relevance of the correlated random coe cient model to examine whether the additional complications associated with it are required. We examine the power of the proposed tests. We derive a new representation of the variance of the instrumental variable estimator for the correlated random coefficient model. We apply the methods in this paper to the prototypical empirical problem of estimating the return to schooling and nd evidence of sorting into schooling based on unobserved components of gains. PMID:21057649
Tests of Hypotheses Arising In the Correlated Random Coefficient Model.
Heckman, James J; Schmierer, Daniel
2010-11-01
This paper examines the correlated random coefficient model. It extends the analysis of Swamy (1971), who pioneered the uncorrelated random coefficient model in economics. We develop the properties of the correlated random coefficient model and derive a new representation of the variance of the instrumental variable estimator for that model. We develop tests of the validity of the correlated random coefficient model against the null hypothesis of the uncorrelated random coefficient model.
On Estimation and Hypothesis Testing Problems for Correlation Coefficients
Kraemer, Helena Chmura
1975-01-01
A selection of statistical problems commonly encountered in psychological or psychiatric research concerning correlation coefficients are re-evaluated in the light of recently developed simplifications in the forms of the distribution theory of the intraclass correlation coefficient, of the product-moment correlation coefficient, and the Spearman…
Detection Performance of the Circular Correlation Coefficient Receiver,
of the squared modulus of the circular serial correlation coefficient is found when no signal is present, allowing computation of the detection...threshold. For small data records, as is typical in radar applications, the performance of the correlation coefficient detector is compared to a standard... Correlation Coefficient , Autoregressive, CFAR, Autocorrelation Estimation, Radar Receiver, and Digital Signal Processing.
A generalized concordance correlation coefficient for continuous and categorical data.
King, T S; Chinchilli, V M
2001-07-30
This paper discusses a generalized version of the concordance correlation coefficient for agreement data. The concordance correlation coefficient evaluates the accuracy and precision between two measures, and is based on the expected value of the squared function of distance. We have generalized this coefficient by applying alternative functions of distance to produce more robust versions of the concordance correlation coefficient. In this paper we extend the application of this class of estimators to categorical data as well, and demonstrate similarities to the kappa and weighted kappa statistics. We also introduce a stratified concordance correlation coefficient which adjusts for explanatory factors, and an extended concordance correlation coefficient which measures agreement among more than two responses. With these extensions, the generalized concordance correlation coefficient provides a unifying approach to assessing agreement among two or more measures that are either continuous or categorical in scale.
ON TESTING THE EQUALITY OF K MULTIPLEAND PARTIAL CORRELATION COEFFICIENTS
无
2001-01-01
Coutsourides (1980) derives an ad hoc nuisance parameter removal test for testing the equality of two multiple correlation coefficients of two independent p variate normal populations, under the assumption that a sample of size n is available from each population. He also extends his ad hoc nuisance parameter removal test to the testing of the equality of two multiple correlation matrices. This paper presents likelihood ratio tests for testing the equality of k multiple correlation coefficients, and also k partial correlation coefficients.
GUAN Hsin; WANG Bo; LU Pingping; XU Liang
2014-01-01
The identification of maximum road friction coefficient and optimal slip ratio is crucial to vehicle dynamics and control. However, it is always not easy to identify the maximum road friction coefficient with high robustness and good adaptability to various vehicle operating conditions. The existing investigations on robust identification of maximum road friction coefficient are unsatisfactory. In this paper, an identification approach based on road type recognition is proposed for the robust identification of maximum road friction coefficient and optimal slip ratio. The instantaneous road friction coefficient is estimated through the recursive least square with a forgetting factor method based on the single wheel model, and the estimated road friction coefficient and slip ratio are grouped in a set of samples in a small time interval before the current time, which are updated with time progressing. The current road type is recognized by comparing the samples of the estimated road friction coefficient with the standard road friction coefficient of each typical road, and the minimum statistical error is used as the recognition principle to improve identification robustness. Once the road type is recognized, the maximum road friction coefficient and optimal slip ratio are determined. The numerical simulation tests are conducted on two typical road friction conditions(single-friction and joint-friction) by using CarSim software. The test results show that there is little identification error between the identified maximum road friction coefficient and the pre-set value in CarSim. The proposed identification method has good robustness performance to external disturbances and good adaptability to various vehicle operating conditions and road variations, and the identification results can be used for the adjustment of vehicle active safety control strategies.
Modified Regression Correlation Coefficient for Poisson Regression Model
Kaengthong, Nattacha; Domthong, Uthumporn
2017-09-01
This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).
Spatial Correlation Coefficient Images for Ultrasonic Detection (Preprint)
2006-07-01
for image formation and detection based on the similarity of adjacent signals. Signal similarity is quantified in terms of the correlation coefficient calculated...between A-scans digitized at adjacent measurement positions. Correlation coefficient images are introduced for visualizing the similarity...beam field with the defect. Correlation coefficient and C-scan images are shown to demonstrate flat-bottom-hole detection in a stainless steel annular
Improvement of Similarity Measure： Pearson Product-Moment Correlation Coefficient
LIUYong-suo; MENGQing-hua; CHENRong; WANGJian-song; JIANGShu-min; HUYu-zhu
2004-01-01
Aim To study the reason of the insensitiveness of Pearson preduct-moment correlation coefficient as a similarity measure and the method to improve its sensitivity. Methods Experimental and simulated data sets were used. Results The distribution range of the data sets influences the sensitivity of Pearson product-moment correlation coefficient. Weighted Pearson product-moment correlation coefficient is more sensitive when the range of the data set is large. Conclusion Weighted Pearson product-moment correlation coefficient is necessary when the range of the data set is large.
Confidence intervals for intraclass correlation coefficients in variance components models
Demetrashvili, Nino; Wit, Ernst C; Van Den Heuvel, Edwin R.
2016-01-01
Confidence intervals for intraclass correlation coefficients in agreement studies with continuous outcomes are model-specific and no generic approach exists. This paper provides two generic approaches for intraclass correlation coefficients of the form -' q = 1 Q σ q 2 / (-' q = 1 Q σ q 2 + -' p = Q
A Note on the Correlated Random Coefficient Model
Kolodziejczyk, Christophe
In this note we derive the bias of the OLS estimator for a correlated random coefficient model with one random coefficient, but which is correlated with a binary variable. We provide set-identification to the parameters of interest of the model. We also show how to reduce the bias of the estimator...
Confidence intervals for intraclass correlation coefficients in variance components models
Demetrashvili, Nino; Wit, Ernst C; Van Den Heuvel, Edwin R.
2016-01-01
Confidence intervals for intraclass correlation coefficients in agreement studies with continuous outcomes are model-specific and no generic approach exists. This paper provides two generic approaches for intraclass correlation coefficients of the form -' q = 1 Q σ q 2 / (-' q = 1 Q σ q 2 + -' p = Q
Use of a Correlation Coefficient for Conditional Averaging.
1997-04-01
data. Selection of the sine function period and a correlation coefficient threshold are discussed. Also examined are the effects of the period and...threshold level on the number of ensembles captured for inclusion for conditional averaging. Both the selection of threshold correlation coefficient and the...A method of collecting ensembles for conditional averaging is presented that uses data collected from a plane mixing layer. The correlation
Diabetic Erythrocytes Test by Correlation Coefficient
Korol, A.M; Foresto, P; Darrigo, M; Rosso, O.A
2008-01-01
Even when a healthy individual is studied, his/her erythrocytes in capillaries continually change their shape in a synchronized erratic fashion. In this work, the problem of characterizing the cell behavior is studied from the perspective of bounded correlated random walk, based on the assumption that diffractometric data involves both deterministic and stochastic components. The photometric readings are obtained by ektacytometry over several millions of shear elongated cells, using a home-made device called Erythrodeformeter. We have only a scalar signal and no governing equations; therefore the complete behavior has to be reconstructed in an artificial phase space. To analyze dynamics we used the technique of time delay coordinates suggested by Takens, May algorithm, and Fourier transform. The results suggest that on random-walk approach the samples from healthy controls exhibit significant differences from those from diabetic patients and these could allow us to claim that we have linked mathematical nonlinear tools with clinical aspects of diabetic erythrocytes’ rheological properties. PMID:19415139
A correlation for heat transfer coefficients in food extruders.
Levine, L; Rockwood, J
1986-06-01
A dimensionless correlation of heat transfer coefficient for heat flow between the extruder barrel wall and extrudate is presented. The standard error of estimate of the correlation is 12.4%. The correlation is useful for the design and scale-up of food extruders and the design of associated temperature control systems.
[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.
Correlation between satellite vegetation indices and crop coefficients
Russo, A. L.; Simoniello, T.; Greco, M.; Squicciarrino, G.; Lanfredi, M.; Macchiato, M.
2010-05-01
Accurate estimations of plant evapotranspiration and its spatial distribution are fundamental for the evaluation of vegetation water stress. Satellite remote sensing techniques represent precious tools for the evapotranspiration estimations at large scale. Many studies are based on the use of thermal signals as inputs for energy balance equations that are solved to estimate evapotranspiration (e.g., Bastiaanssen et al., 1998; Ayenew, 2003). This approach requires many inputs and a detailed theoretical background knowledge. Other works (e.g., Calera at al., 2005; Gonzalez-Dugo and Mateos, 2008) explored a second approach based on the FAO method that estimates the plant evapotranspiration by weighting the reference evapotranspiration with a crop coefficient (Kc) derived from satellite based vegetation indices. Such studies mainly investigated the usefulness of high resolution satellite data, such as Quickbird, Ikonos, TM, that in spite of the high spatial sampling, are not suitable for a dense temporal sampling. In order to generate spatially distributed values of Kc that capture field-specific crop development, we investigated the usefulness of vegetation indices derived from a time series (2005-2008) of medium resolution MODIS data. We analyzed the spatial and temporal correlation of different indices (NDVI, EVI, and WDVI) with crop coefficients available in literature for different herbaceous and arboreal cultivations present in the study area (Basilicata region, southern Italy). To take into account the background of the cultivation covers, we weighted the Kc by considering the vegetation fraction within each the pixel. By evaluating altogether the cultivations, we found that the correlation increases during the growing season (R2 > 0.80) whereas it decreases during the winter period (R2 cultivation highlighted that NDVI provided quite high correlation for all the investigated cultivation with maximum values for wheat (R2 = 0.89) and vineyards (R2 = 0.83). For
Generalized Correlation Coefficient Based on Log Likelihood Ratio Test Statistic
Liu Hsiang-Chuan
2016-01-01
Full Text Available In this paper, I point out that both Joe’s and Ding’s strength statistics can only be used for testing the pair-wise independence, and I propose a novel G-square based strength statistic, called Liu’s generalized correlation coefficient, it can be used to detect and compare the strength of not only the pair-wise independence but also the mutual independence of any multivariate variables. Furthermore, I proved that only Liu’s generalized correlation coefficient is strictly increasing on its number of variables, it is more sensitive and useful than Cramer’s V coefficient, in other words, Liu generalized correlation coefficient is not only the G-square based strength statistic, but also an improved statistic for detecting and comparing the strengths of deferent associations of any two or more sets of multivariate variables, moreover, this new strength statistic can also be tested by G2.
Statistical Study of Turbulence: Spectral Functions and Correlation Coefficients
Frenkiel, Francois N.
1958-01-01
In reading the publications on turbulence of different authors, one often runs the risk of confusing the various correlation coefficients and turbulence spectra. We have made a point of defining, by appropriate concepts, the differences which exist between these functions. Besides, we introduce in the symbols a few new characteristics of turbulence. In the first chapter, we study some relations between the correlation coefficients and the different turbulence spectra. Certain relations are given by means of demonstrations which could be called intuitive rather than mathematical. In this way we demonstrate that the correlation coefficients between the simultaneous turbulent velocities at two points are identical, whether studied in Lagrange's or in Euler's systems. We then consider new spectra of turbulence, obtained by study of the simultaneous velocities along a straight line of given direction. We determine some relations between these spectra and the correlation coefficients. Examining the relation between the spectrum of the turbulence measured at a fixed point and the longitudinal-correlation curve given by G. I. Taylor, we find that this equation is exact only when the coefficient is very small.
Maximum-entropy closure of hydrodynamic moment hierarchies including correlations.
Hughes, Keith H; Burghardt, Irene
2012-06-07
Generalized hydrodynamic moment hierarchies are derived which explicitly include nonequilibrium two-particle and higher-order correlations. The approach is adapted to strongly correlated media and nonequilibrium processes on short time scales which necessitate an explicit treatment of time-evolving correlations. Closure conditions for the extended moment hierarchies are formulated by a maximum-entropy approach, generalizing related closure procedures for kinetic equations. A self-consistent set of nonperturbative dynamical equations are thus obtained for a chosen set of single-particle and two-particle (and possibly higher-order) moments. Analytical results are derived for generalized Gaussian closures including the dynamic pair distribution function and a two-particle correction to the current density. The maximum-entropy closure conditions are found to involve the Kirkwood superposition approximation.
Someswara Rao, Chinta; Viswanadha Raju, S
2016-03-01
In this paper, we consider correlation coefficient, rank correlation coefficient and cosine similarity measures for evaluating similarity between Homo sapiens and monkeys. We used DNA chromosomes of genome wide genes to determine the correlation between the chromosomal content and evolutionary relationship. The similarity among the H. sapiens and monkeys is measured for a total of 210 chromosomes related to 10 species. The similarity measures of these different species show the relationship between the H. sapiens and monkey. This similarity will be helpful at theft identification, maternity identification, disease identification, etc.
On the misinterpretation of the correlation coefficient in pharmaceutical sciences.
Sonnergaard, J M
2006-09-14
The correlation coefficient is often used and more often misused as a universal parameter expressing the quality in linear regression analysis. The popularity of this dimensionless quantity is evident as it is easy to communicate and considered to be unproblematic to comprehend. However, illustrative examples will demonstrate that the correlation coefficient is highly ineffective as a stand-alone quantity without reference to the number of observations, the pattern of the data and the slope of the regression line. Much more efficient quality methodologies are available where the correct technique depends on the purpose of the investigation. These relevant and precise methods in quality assurance of linear regression as alternative to the correlation coefficient are presented.
Distributing Correlation Coefficients of Linear Structure-Activity/Property Models
Sorana D. BOLBOACA
2011-12-01
Full Text Available Quantitative structure-activity/property relationships are mathematical relationships linking chemical structure and activity/property in a quantitative manner. These in silico approaches are frequently used to reduce animal testing and risk-assessment, as well as to increase time- and cost-effectiveness in characterization and identification of active compounds. The aim of our study was to investigate the pattern of correlation coefficients distribution associated to simple linear relationships linking the compounds structure with their activities. A set of the most common ordnance compounds found at naval facilities with a limited data set with a range of toxicities on aquatic ecosystem and a set of seven properties was studied. Statistically significant models were selected and investigated. The probability density function of the correlation coefficients was investigated using a series of possible continuous distribution laws. Almost 48% of the correlation coefficients proved fit Beta distribution, 40% fit Generalized Pareto distribution, and 12% fit Pert distribution.
Maximum-entropy distributions of correlated variables with prespecified marginals.
Larralde, Hernán
2012-12-01
The problem of determining the joint probability distributions for correlated random variables with prespecified marginals is considered. When the joint distribution satisfying all the required conditions is not unique, the "most unbiased" choice corresponds to the distribution of maximum entropy. The calculation of the maximum-entropy distribution requires the solution of rather complicated nonlinear coupled integral equations, exact solutions to which are obtained for the case of Gaussian marginals; otherwise, the solution can be expressed as a perturbation around the product of the marginals if the marginal moments exist.
Visualization of biological texture using correlation coefficient images.
Sviridov, Alexander P; Ulissi, Zachary; Chernomordik, Victor; Hassan, Moinuddin; Gandjbakhche, Amir H
2006-01-01
Subsurface structural features of biological tissue are visualized using polarized light images. The technique of Pearson correlation coefficient analysis is used to reduce blurring of these features by unpolarized backscattered light and to visualize the regions of high statistical similarities within the noisy tissue images. It is shown that under certain conditions, such correlation coefficient maps are determined by the textural character of tissues and not by the chosen region of interest, providing information on tissue structure. As an example, the subsurface texture of a demineralized tooth sample is enhanced from a noisy polarized light image.
Analysis of correlation coefficient filtering in elasticity imaging.
Huang, Sheng-Wen; Rubin, Jonathan M; Xie, Hua; Witte, Russell S; Jia, Congxian; Olafsson, Ragnar; O'Donnell, Matthew
2008-11-01
Correlation-based speckle tracking methods are commonly used in elasticity imaging to estimate displacements. In the presence of local strain, a larger window size results in larger displacement error. To reduce tracking error, we proposed a short correlation window followed by a correlation coefficient filter. Although simulation and experimental results demonstrated the efficacy of the method, it was not clear why correlation coefficient filtering reduces tracking error since tracking error increases if normalization before filtering is not applied. In this paper, we analyzed tracking errors by estimating phase variances of the cross-correlation function and the correlation coefficient at the true time lag based on statistical properties of these functions' real and imaginary parts. The role of normalization is clarified by identifying the effect of the cross-correlation function's amplitude fluctuation on the function's imaginary part. Furthermore, we present analytic forms for predicting axial displacement error as a function of strain, system parameters (signal-to-noise ratio, center frequency, and signal and noise bandwidths), and tracking parameters (window and filter sizes) for cases with and without normalization before filtering. Simulation results correspond to theory well for both noise-free cases and general cases with an empirical correction term included for strains up to 4%.
Minimum disturbance rewards with maximum possible classical correlations
Pande, Varad R., E-mail: varad_pande@yahoo.in [Department of Physics, Indian Institute of Science Education and Research Pune, 411008 (India); Shaji, Anil [School of Physics, Indian Institute of Science Education and Research Thiruvananthapuram, 695016 (India)
2017-07-12
Weak measurements done on a subsystem of a bipartite system having both classical and nonClassical correlations between its components can potentially reveal information about the other subsystem with minimal disturbance to the overall state. We use weak quantum discord and the fidelity between the initial bipartite state and the state after measurement to construct a cost function that accounts for both the amount of information revealed about the other system as well as the disturbance to the overall state. We investigate the behaviour of the cost function for families of two qubit states and show that there is an optimal choice that can be made for the strength of the weak measurement. - Highlights: • Weak measurements done on one part of a bipartite system with controlled strength. • Weak quantum discord & fidelity used to quantify all correlations and disturbance. • Cost function to probe the tradeoff between extracted correlations and disturbance. • Optimal measurement strength for maximum extraction of classical correlations.
A mixed relaxed singular maximum principle for linear SDEs with random coefficients
Andersson, Daniel
2008-01-01
We study singular stochastic control of a two dimensional stochastic differential equation, where the first component is linear with random and unbounded coefficients. We derive existence of an optimal relaxed control and necessary conditions for optimality in the form of a mixed relaxed-singular maximum principle in a global form. A motivating example is given in the form of an optimal investment and consumption problem with transaction costs, where we consider a portfolio with a continuum of bonds and where the portfolio weights are modeled as measure-valued processes on the set of times to maturity.
A Note on a Geometric Interpretation of the Correlation Coefficient.
Marks, Edmond
1982-01-01
An alternate geometric interpretation of the correlation coefficient to that given in most statistics texts for psychology and education is presented. This interpretation is considered to be more consistent with the statistical model for the data, and richer in geometric meaning. (Author)
Computer Map Typing - Optimizing the Correlation Coefficient Threshold,
the procedures which would be employed in the preparation of each catalog. This paper addresses only one of these questions; ’What correlation ... coefficient threshold provides the best of map types.’ The choice of an appropriate threshold value is, at best, a compromise. This paper shows that a
Highlighting material structure with transmission electron diffraction correlation coefficient maps.
Kiss, Ákos K; Rauch, Edgar F; Lábár, János L
2016-04-01
Correlation coefficient maps are constructed by computing the differences between neighboring diffraction patterns collected in a transmission electron microscope in scanning mode. The maps are shown to highlight material structural features like grain boundaries, second phase particles or dislocations. The inclination of the inner crystal interfaces are directly deduced from the resulting contrast.
Correlation Revelation: The Search for Meaning in Pearson's Coefficient
Huhn, Craig
2016-01-01
When the author was first charged with getting a group of students to understand the correlation coefficient, he did not anticipate the topic would challenge his own understanding, let alone cause him to eventually question the very nature of mathematics itself. On the surface, the idea seemed straightforward, one that millions of students across…
Modeling Concordance Correlation Coefficient for Longitudinal Study Data
Ma, Yan; Tang, Wan; Yu, Qin; Tu, X. M.
2010-01-01
Measures of agreement are used in a wide range of behavioral, biomedical, psychosocial, and health-care related research to assess reliability of diagnostic test, psychometric properties of instrument, fidelity of psychosocial intervention, and accuracy of proxy outcome. The concordance correlation coefficient (CCC) is a popular measure of…
On the misinterpretation of the correlation coefficient in pharmaceutical sciences
Sonnergaard, Jørn
2006-01-01
The correlation coefficient is often used and more often misused as a universal parameter expressing the quality in linear regression analysis. The popularity of this dimensionless quantity is evident as it is easy to communicate and considered to be unproblematic to comprehend. However, illustra...
Piretzidis, Dimitrios; Sra, Gurveer; Karantaidis, George; Sideris, Michael G.
2017-04-01
A new method for identifying correlated errors in Gravity Recovery and Climate Experiment (GRACE) monthly harmonic coefficients has been developed and tested. Correlated errors are present in the differences between monthly GRACE solutions, and can be suppressed using a de-correlation filter. In principle, the de-correlation filter should be implemented only on coefficient series with correlated errors to avoid losing useful geophysical information. In previous studies, two main methods of implementing the de-correlation filter have been utilized. In the first one, the de-correlation filter is implemented starting from a specific minimum order until the maximum order of the monthly solution examined. In the second one, the de-correlation filter is implemented only on specific coefficient series, the selection of which is based on statistical testing. The method proposed in the present study exploits the capabilities of supervised machine learning algorithms such as neural networks and support vector machines (SVMs). The pattern of correlated errors can be described by several numerical and geometric features of the harmonic coefficient series. The features of extreme cases of both correlated and uncorrelated coefficients are extracted and used for the training of the machine learning algorithms. The trained machine learning algorithms are later used to identify correlated errors and provide the probability of a coefficient series to be correlated. Regarding SVMs algorithms, an extensive study is performed with various kernel functions in order to find the optimal training model for prediction. The selection of the optimal training model is based on the classification accuracy of the trained SVM algorithm on the same samples used for training. Results show excellent performance of all algorithms with a classification accuracy of 97% - 100% on a pre-selected set of training samples, both in the validation stage of the training procedure and in the subsequent use of
Surov, Alexey; Meyer, Hans Jonas; Wienke, Andreas
2017-07-01
Diffusion-weighted imaging (DWI) is a magnetic resonance imaging (MRI) technique based on measure of water diffusion that can provide information about tissue microstructure, especially about cell count. Increase of cell density induces restriction of water diffusion and decreases apparent diffusion coefficient (ADC). ADC can be divided into three sub-parameters: ADC minimum or ADCmin, mean ADC or ADCmean and ADC maximum or ADCmax Some studies have suggested that ADCmin shows stronger correlations with cell count in comparison to other ADC fractions and may be used as a parameter for estimation of tumor cellularity. The aim of the present meta-analysis was to summarize correlation coefficients between ADCmin and cellularity in different tumors based on large patient data. For this analysis, MEDLINE database was screened for associations between ADC and cell count in different tumors up to September 2016. For this work, only data regarding ADCmin were included. Overall, 12 publications with 317 patients were identified. Spearman's correlation coefficient was used to analyze associations between ADCmin and cellularity. The reported Pearson correlation coefficients in some publications were converted into Spearman correlation coefficients. The pooled correlation coefficient for all included studies was ρ=-0.59 (95% confidence interval (CI)=-0.72 to -0.45), heterogeneity Tau(2)=0.04 (pcorrelated moderately with tumor cellularity. The calculated correlation coefficient is not stronger in comparison to the reported coefficient for ADCmean and, therefore, ADCmin does not represent a better means to reflect cellularity. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.
Maximum-likelihood analysis of the COBE angular correlation function
Seljak, Uros; Bertschinger, Edmund
1993-01-01
We have used maximum-likelihood estimation to determine the quadrupole amplitude Q(sub rms-PS) and the spectral index n of the density fluctuation power spectrum at recombination from the COBE DMR data. We find a strong correlation between the two parameters of the form Q(sub rms-PS) = (15.7 +/- 2.6) exp (0.46(1 - n)) microK for fixed n. Our result is slightly smaller than and has a smaller statistical uncertainty than the 1992 estimate of Smoot et al.
Estimating the generalized concordance correlation coefficient through variance components.
Carrasco, Josep L; Jover, Lluís
2003-12-01
The intraclass correlation coefficient (ICC) and the concordance correlation coefficient (CCC) are two of the most popular measures of agreement for variables measured on a continuous scale. Here, we demonstrate that ICC and CCC are the same measure of agreement estimated in two ways: by the variance components procedure and by the moment method. We propose estimating the CCC using variance components of a mixed effects model, instead of the common method of moments. With the variance components approach, the CCC can easily be extended to more than two observers, and adjusted using confounding covariates, by incorporating them in the mixed model. A simulation study is carried out to compare the variance components approach with the moment method. The importance of adjusting by confounding covariates is illustrated with a case example.
A short note on jackknifing the concordance correlation coefficient.
Feng, Dai; Baumgartner, Richard; Svetnik, Vladimir
2014-02-10
Lin's concordance correlation coefficient (CCC) is a very popular scaled index of agreement used in applied statistics. To obtain a confidence interval (CI) for the estimate of CCC, jackknifing was proposed and shown to perform well in simulation as well as in applications. However, a theoretical proof of the validity of the jackknife CI for the CCC has not been presented yet. In this note, we establish a sufficient condition for using the jackknife method to construct the CI for the CCC.
Xintao Xia
2013-07-01
Full Text Available This study proposed the bootstrap maximum-entropy method to evaluate the uncertainty of the starting torque of a slewing bearing. Addressing the variation coefficient of the slewing bearing starting torque under load, the probability density function, estimated true value and variation domain are obtained through experimental investigation of the slewing bearing starting torque under various loads. The probability density function is found to be characterized by variational figure, scale and location. In addition, the estimated true value and the variation domain vary from large to small along with increasing load, indicating better evolution of the stability and reliability of the starting friction torque. Finally, a sensitive spot exists where the estimated true value and the variation domain rise abnormally, showing a fluctuation in the immunity and a degenerative disorder in the stability and reliability of the starting friction torque.
Apparent diffusion coefficient correlation with oesophageal tumour stroma and angiogenesis
Aoyagi, Tomoyoshi; Shuto, Kiyohiko; Okazumi, Shinichi; Hayano, Kohichi; Satoh, Asami; Saitoh, Hiroshige; Shimada, Hideaki; Nabeya, Yoshihiro; Matsubara, Hisahiro [Chiba University, Department of Frontier Surgery, Graduate School of Medicine, Chiba (Japan); Kazama, Toshiki [Chiba University, Department of Radiology, Graduate School of Medicine, Chiba (Japan)
2012-06-15
Because diffusion-weighted imaging (DWI) can predict the prognosis of patients with oesophageal squamous cell carcinoma (ESCC), we hypothesised that apparent diffusion coefficient (ADC) values might be correlated with the collagen content and tumour angiogenesis. The purpose of this study was to determine the correlation between ADC values of ESCC before treatment and oesophageal tumour stroma and angiogenesis. Seventeen patients with ESCC were enrolled. The ADC values were calculated from the DWI score. Seventeen patients who had undergone oesophagectomy were analysed for tumour stroma, vascular endothelial growth factor (VEGF) and CD34. Tissue collagen was stained with azocarmine and aniline blue to quantitatively analyse the extracellular matrix in cancer stroma. Tissues were stained with VEGF and CD34 to analyse the angiogenesis. The ADC values decreased with stromal collagen growth. We found a negative correlation between the tumour ADC and the amount of stromal collagen (r = -0.729, P = 0.001), i.e. the ADC values decreased with growth of VEGF. We also found a negative correlation between the ADC of the tumours and the amount of VEGF (r = 0.538, P = 0.026). Our results indicated that the ADC value may be a novel prognostic factor and contribute to the treatment of oesophageal cancer. circle Magnetic resonance apparent diffusion coefficient values inversely indicate tumour stromal collagen circle There is also negative correlation between ADCs and vascular endothelial growth factor circle ADC values may contribute to the treatment of oesophageal cancer. (orig.)
Apparent diffusion coefficient correlation with oesophageal tumour stroma and angiogenesis.
Aoyagi, Tomoyoshi; Shuto, Kiyohiko; Okazumi, Shinichi; Hayano, Kohichi; Satoh, Asami; Saitoh, Hiroshige; Shimada, Hideaki; Nabeya, Yoshihiro; Kazama, Toshiki; Matsubara, Hisahiro
2012-06-01
Because diffusion-weighted imaging (DWI) can predict the prognosis of patients with oesophageal squamous cell carcinoma (ESCC), we hypothesised that apparent diffusion coefficient (ADC) values might be correlated with the collagen content and tumour angiogenesis. The purpose of this study was to determine the correlation between ADC values of ESCC before treatment and oesophageal tumour stroma and angiogenesis. Seventeen patients with ESCC were enrolled. The ADC values were calculated from the DWI score. Seventeen patients who had undergone oesophagectomy were analysed for tumour stroma, vascular endothelial growth factor (VEGF) and CD34. Tissue collagen was stained with azocarmine and aniline blue to quantitatively analyse the extracellular matrix in cancer stroma. Tissues were stained with VEGF and CD34 to analyse the angiogenesis. The ADC values decreased with stromal collagen growth. We found a negative correlation between the tumour ADC and the amount of stromal collagen (r = -0.729, P = 0.001), i.e. the ADC values decreased with growth of VEGF. We also found a negative correlation between the ADC of the tumours and the amount of VEGF (r = 0.538, P = 0.026). Our results indicated that the ADC value may be a novel prognostic factor and contribute to the treatment of oesophageal cancer. • Magnetic resonance apparent diffusion coefficient values inversely indicate tumour stromal collagen • There is also negative correlation between ADCs and vascular endothelial growth factor • ADC values may contribute to the treatment of oesophageal cancer.
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
Automatic speech segmentation using throat-acoustic correlation coefficients
Mussabayev, Rustam Rafikovich; Kalimoldayev, Maksat N.; Amirgaliyev, Yedilkhan N.; Mussabayev, Timur R.
2016-11-01
This work considers one of the approaches to the solution of the task of discrete speech signal automatic segmentation. The aim of this work is to construct such an algorithm which should meet the following requirements: segmentation of a signal into acoustically homogeneous segments, high accuracy and segmentation speed, unambiguity and reproducibility of segmentation results, lack of necessity of preliminary training with the use of a special set consisting of manually segmented signals. Development of the algorithm which corresponds to the given requirements was conditioned by the necessity of formation of automatically segmented speech databases that have a large volume. One of the new approaches to the solution of this task is viewed in this article. For this purpose we use the new type of informative features named TAC-coefficients (Throat-Acoustic Correlation coefficients) which provide sufficient segmentation accuracy and effi- ciency.
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.
Gene differential coexpression analysis based on biweight correlation and maximum clique.
Zheng, Chun-Hou; Yuan, Lin; Sha, Wen; Sun, Zhan-Li
2014-01-01
Differential coexpression analysis usually requires the definition of 'distance' or 'similarity' between measured datasets. Until now, the most common choice is Pearson correlation coefficient. However, Pearson correlation coefficient is sensitive to outliers. Biweight midcorrelation is considered to be a good alternative to Pearson correlation since it is more robust to outliers. In this paper, we introduce to use Biweight Midcorrelation to measure 'similarity' between gene expression profiles, and provide a new approach for gene differential coexpression analysis. Firstly, we calculate the biweight midcorrelation coefficients between all gene pairs. Then, we filter out non-informative correlation pairs using the 'half-thresholding' strategy and calculate the differential coexpression value of gene, The experimental results on simulated data show that the new approach performed better than three previously published differential coexpression analysis (DCEA) methods. Moreover, we use the maximum clique analysis to gene subset included genes identified by our approach and previously reported T2D-related genes, many additional discoveries can be found through our method.
Spatially varying cross-correlation coefficients in the presence of nugget effects
Kleiber, William
2012-11-29
We derive sufficient conditions for the cross-correlation coefficient of a multivariate spatial process to vary with location when the spatial model is augmented with nugget effects. The derived class is valid for any choice of covariance functions, and yields substantial flexibility between multiple processes. The key is to identify the cross-correlation coefficient matrix with a contraction matrix, which can be either diagonal, implying a parsimonious formulation, or a fully general contraction matrix, yielding greater flexibility but added model complexity. We illustrate the approach with a bivariate minimum and maximum temperature dataset in Colorado, allowing the two variables to be positively correlated at low elevations and nearly independent at high elevations, while still yielding a positive definite covariance matrix. © 2012 Biometrika Trust.
Matrix-based concordance correlation coefficient for repeated measures.
Hiriote, Sasiprapa; Chinchilli, Vernon M
2011-09-01
In many clinical studies, Lin's concordance correlation coefficient (CCC) is a common tool to assess the agreement of a continuous response measured by two raters or methods. However, the need for measures of agreement may arise for more complex situations, such as when the responses are measured on more than one occasion by each rater or method. In this work, we propose a new CCC in the presence of repeated measurements, called the matrix-based concordance correlation coefficient (MCCC) based on a matrix norm that possesses the properties needed to characterize the level of agreement between two p× 1 vectors of random variables. It can be shown that the MCCC reduces to Lin's CCC when p= 1. For inference, we propose an estimator for the MCCC based on U-statistics. Furthermore, we derive the asymptotic distribution of the estimator of the MCCC, which is proven to be normal. The simulation studies confirm that overall in terms of accuracy, precision, and coverage probability, the estimator of the MCCC works very well in general cases especially when n is greater than 40. Finally, we use real data from an Asthma Clinical Research Network (ACRN) study and the Penn State Young Women's Health Study for demonstration.
Overcoming multicollinearity in multiple regression using correlation coefficient
Zainodin, H. J.; Yap, S. J.
2013-09-01
Multicollinearity happens when there are high correlations among independent variables. In this case, it would be difficult to distinguish between the contributions of these independent variables to that of the dependent variable as they may compete to explain much of the similar variance. Besides, the problem of multicollinearity also violates the assumption of multiple regression: that there is no collinearity among the possible independent variables. Thus, an alternative approach is introduced in overcoming the multicollinearity problem in achieving a well represented model eventually. This approach is accomplished by removing the multicollinearity source variables on the basis of the correlation coefficient values based on full correlation matrix. Using the full correlation matrix can facilitate the implementation of Excel function in removing the multicollinearity source variables. It is found that this procedure is easier and time-saving especially when dealing with greater number of independent variables in a model and a large number of all possible models. Hence, in this paper detailed insight of the procedure is shown, compared and implemented.
A Novel Approach for Nonstationary Time Series Analysis with Time-Invariant Correlation Coefficient
Chengrui Liu
2014-01-01
Full Text Available We will concentrate on the modeling and analysis of a class of nonstationary time series, called correlation coefficient stationary series, which commonly exists in practical engineering. First, the concept and scope of correlation coefficient stationary series are discussed to get a better understanding. Second, a theorem is proposed to determine standard deviation function for correlation coefficient stationary series. Third, we propose a moving multiple-point average method to determine the function forms for mean and standard deviation, which can help to improve the analysis precision, especially in the context of limited sample size. Fourth, the conditional likelihood approach is utilized to estimate the model parameters. In addition, we discuss the correlation coefficient stationarity test method, which can contribute to the verification of modeling validity. Monte Carlo simulation study illustrates the authentication of the theorem and the validity of the established method. Empirical study shows that the approach can satisfactorily explain the nonstationary behavior of many practical data sets, including stock returns, maximum power load, China money supply, and foreign currency exchange rate. The effectiveness of these processes is addressed by forecasting performance.
Maximum key-profile correlation (MKC) as a measure of tonal structure in music.
Takeuchi, A H
1994-09-01
Tonal structure is musical organization on the basis of pitch, in which pitches vary in importance and rate of occurrence according to their relationship to a tonal center. Experiment 1 evaluated the maximum key-profile correlation (MKC), a product of Krumhansl and Schmuckler's key-finding algorithm (Krumhansl, 1990), as a measure of tonal structure. The MKC is the maximum correlation coefficient between the pitch class distribution in a musical sample and key profiles, which indicate the stability of pitches with respect to particular tonal centers. The MKC values of melodies correlated strongly with listeners' ratings of tonal structure. To measure the influence of the temporal order of pitches on perceived tonal structure, three measures (fifth span, semitone span, and pitch contour) taken from previous studies of melody perception were also correlated with tonal structure ratings. None of the temporal measures correlated as strongly or as consistently with tonal structure ratings as did the MKC, and nor did combining them with the MKC improve prediction of tonal structure ratings. In Experiment 2, the MKC did not correlate with recognition memory of melodies. However, melodies with very low MKC values were recognized less accurately than melodies with very high MKC values. Although it does not incorporate temporal, rhythmic, or harmonic factors that may influence perceived tonal structure, the MKC can be interpreted as a measure of tonal structure, at least for brief melodies.
Relative azimuth inversion by way of damped maximum correlation estimates
Ringler, A.T.; Edwards, J.D.; Hutt, C.R.; Shelly, F.
2012-01-01
Horizontal seismic data are utilized in a large number of Earth studies. Such work depends on the published orientations of the sensitive axes of seismic sensors relative to true North. These orientations can be estimated using a number of different techniques: SensOrLoc (Sensitivity, Orientation and Location), comparison to synthetics (Ekstrom and Busby, 2008), or by way of magnetic compass. Current methods for finding relative station azimuths are unable to do so with arbitrary precision quickly because of limitations in the algorithms (e.g. grid search methods). Furthermore, in order to determine instrument orientations during station visits, it is critical that any analysis software be easily run on a large number of different computer platforms and the results be obtained quickly while on site. We developed a new technique for estimating relative sensor azimuths by inverting for the orientation with the maximum correlation to a reference instrument, using a non-linear parameter estimation routine. By making use of overlapping windows, we are able to make multiple azimuth estimates, which helps to identify the confidence of our azimuth estimate, even when the signal-to-noise ratio (SNR) is low. Finally, our algorithm has been written as a stand-alone, platform independent, Java software package with a graphical user interface for reading and selecting data segments to be analyzed.
Akataki, K; Mita, K; Itoh, Y
1999-01-01
The within-day and between-day repeatability of the mechanomyogram (MMG) was assessed using the coefficient of variation (CV) and the intraclass correlation coefficient (ICC) and was compared with that of the electromyogram (EMG). The MMG and EMG were recorded simultaneously during isometric elbow flexion trials at different submaximal levels of 10% to 90% MVC. The testing session consisting of 9 submaximal trials was repeated 8 times on the same day for estimation of the within-day variation. In order to examine the between-day variation, the same testing session was also performed 8 times over 3 weeks with a 2-day rest interval between each session. The CVs within-day and between-day in both the MMG and EMG did not demonstrate any significant differences relating to the magnitude of force exerted. The CVs combined over all the force levels were approximately 10% within the same day and 25% between days for both the MMG and EMG. These corresponded to the within-day ICC of approximately 0.95 and the between-day ICC of 0.80. The repeatability of the MMG during submaximal isometric contractions of biceps brachii muscles is considered to be similar to that of the more established EMG.
A robust bayesian estimate of the concordance correlation coefficient.
Feng, Dai; Baumgartner, Richard; Svetnik, Vladimir
2015-01-01
A need for assessment of agreement arises in many situations including statistical biomarker qualification or assay or method validation. Concordance correlation coefficient (CCC) is one of the most popular scaled indices reported in evaluation of agreement. Robust methods for CCC estimation currently present an important statistical challenge. Here, we propose a novel Bayesian method of robust estimation of CCC based on multivariate Student's t-distribution and compare it with its alternatives. Furthermore, we extend the method to practically relevant settings, enabling incorporation of confounding covariates and replications. The superiority of the new approach is demonstrated using simulation as well as real datasets from biomarker application in electroencephalography (EEG). This biomarker is relevant in neuroscience for development of treatments for insomnia.
Correlation Coefficients: Mean Bias and Confidence Interval Distortions
Richard L. Gorsuch
2011-05-01
Full Text Available Non-zero correlation coefficients have non-normal distributions, affecting both means and standard deviations. Previous research suggests that z transformation may effectively correct mean bias for N's less than 30. In this study, simulations with small (20 and 30 and large (50 and 100 N's found that mean bias adjustments for larger N's are seldom needed. However, z transformations improved confidence intervals even for N = 100. The improvement was not in the estimated standard errors so much as in the asymmetrical CI's estimates based upon the z transformation. The resulting observed probabilities were generally accurate to within 1 point in the first non-zero digit. These issues are an order of magnitude less important for accuracy than design issues influencing the accuracy of the results, such as reliability, restriction of range, and N. DOI: 10.2458/azu_jmmss.v1i2.114
Bivariate correlation coefficients in family-type clustered studies.
Luo, Jingqin; D'Angela, Gina; Gao, Feng; Ding, Jimin; Xiong, Chengjie
2015-11-01
We propose a unified approach based on a bivariate linear mixed effects model to estimate three types of bivariate correlation coefficients (BCCs), as well as the associated variances between two quantitative variables in cross-sectional data from a family-type clustered design. These BCCs are defined at different levels of experimental units including clusters (e.g., families) and subjects within clusters and assess different aspects on the relationships between two variables. We study likelihood-based inferences for these BCCs, and provide easy implementation using standard software SAS. Unlike several existing BCC estimators in the literature on clustered data, our approach can seamlessly handle two major analytic challenges arising from a family-type clustered design: (1) many families may consist of only one single subject; (2) one of the paired measurements may be missing for some subjects. Hence, our approach maximizes the use of data from all subjects (even those missing one of the two variables to be correlated) from all families, regardless of family size. We also conduct extensive simulations to show that our estimators are superior to existing estimators in handling missing data or/and imbalanced family sizes and the proposed Wald test maintains good size and power for hypothesis testing. Finally, we analyze a real-world Alzheimer's disease dataset from a family clustered study to investigate the BCCs across different modalities of disease markers including cognitive tests, cerebrospinal fluid biomarkers, and neuroimaging biomarkers.
Statistical functions and relevant correlation coefficients of clearness index
Pavanello, Diego; Zaaiman, Willem; Colli, Alessandra; Heiser, John; Smith, Scott
2015-08-01
This article presents a statistical analysis of the sky conditions, during years from 2010 to 2012, for three different locations: the Joint Research Centre site in Ispra (Italy, European Solar Test Installation - ESTI laboratories), the site of National Renewable Energy Laboratory in Golden (Colorado, USA) and the site of Brookhaven National Laboratories in Upton (New York, USA). The key parameter is the clearness index kT, a dimensionless expression of the global irradiance impinging upon a horizontal surface at a given instant of time. In the first part, the sky conditions are characterized using daily averages, giving a general overview of the three sites. In the second part the analysis is performed using data sets with a short-term resolution of 1 sample per minute, demonstrating remarkable properties of the statistical distributions of the clearness index, reinforced by a proof using fuzzy logic methods. Successively some time-dependent correlations between different meteorological variables are presented in terms of Pearson and Spearman correlation coefficients, and introducing a new one.
Feng, Dai; Svetnik, Vladimir; Coimbra, Alexandre; Baumgartner, Richard
2014-01-01
The intraclass correlation coefficient (ICC) with fixed raters or, equivalently, the concordance correlation coefficient (CCC) for continuous outcomes is a widely accepted aggregate index of agreement in settings with small number of raters. Quantifying the precision of the CCC by constructing its confidence interval (CI) is important in early drug development applications, in particular in qualification of biomarker platforms. In recent years, there have been several new methods proposed for construction of CIs for the CCC, but their comprehensive comparison has not been attempted. The methods consisted of the delta method and jackknifing with and without Fisher's Z-transformation, respectively, and Bayesian methods with vague priors. In this study, we carried out a simulation study, with data simulated from multivariate normal as well as heavier tailed distribution (t-distribution with 5 degrees of freedom), to compare the state-of-the-art methods for assigning CI to the CCC. When the data are normally distributed, the jackknifing with Fisher's Z-transformation (JZ) tended to provide superior coverage and the difference between it and the closest competitor, the Bayesian method with the Jeffreys prior was in general minimal. For the nonnormal data, the jackknife methods, especially the JZ method, provided the coverage probabilities closest to the nominal in contrast to the others which yielded overly liberal coverage. Approaches based upon the delta method and Bayesian method with conjugate prior generally provided slightly narrower intervals and larger lower bounds than others, though this was offset by their poor coverage. Finally, we illustrated the utility of the CIs for the CCC in an example of a wake after sleep onset (WASO) biomarker, which is frequently used in clinical sleep studies of drugs for treatment of insomnia.
The Betz-Joukowsky limit for the maximum power coefficient of wind turbines
Okulov, Valery; van Kuik, G.A.M.
2009-01-01
The article addresses to a history of an important scientific result in wind energy. The maximum efficiency of an ideal wind turbine rotor is well known as the ‘Betz limit’, named after the German scientist that formulated this maximum in 1920. Also Lanchester, a British scientist, is associated...
Parametric image alignment using enhanced correlation coefficient maximization.
Evangelidis, Georgios D; Psarakis, Emmanouil Z
2008-10-01
In this work we propose the use of a modified version of the correlation coefficient as a performance criterion for the image alignment problem. The proposed modification has the desirable characteristic of being invariant with respect to photometric distortions. Since the resulting similarity measure is a nonlinear function of the warp parameters, we develop two iterative schemes for its maximization, one based on the forward additive approach and the second on the inverse compositional method. As it is customary in iterative optimization, in each iteration, the nonlinear objective function is approximated by an alternative expression for which the corresponding optimization is simple. In our case we propose an efficient approximation that leads to a closed-form solution (per iteration) which is of low computational complexity, the latter property being particularly strong in our inverse version. The proposed schemes are tested against the Forward Additive Lucas-Kanade and the Simultaneous Inverse Compositional (SIC) algorithm through simulations. Under noisy conditions and photometric distortions, our forward version achieves more accurate alignments and exhibits faster convergence whereas our inverse version has similar performance as the SIC algorithm but at a lower computational complexity.
Covariate-adjusted confidence interval for the intraclass correlation coefficient.
Shoukri, Mohamed M; Donner, Allan; El-Dali, Abdelmoneim
2013-09-01
A crucial step in designing a new study is to estimate the required sample size. For a design involving cluster sampling, the appropriate sample size depends on the so-called design effect, which is a function of the average cluster size and the intracluster correlation coefficient (ICC). It is well-known that under the framework of hierarchical and generalized linear models, a reduction in residual error may be achieved by including risk factors as covariates. In this paper we show that the covariate design, indicating whether the covariates are measured at the cluster level or at the within-cluster subject level affects the estimation of the ICC, and hence the design effect. Therefore, the distinction between these two types of covariates should be made at the design stage. In this paper we use the nested-bootstrap method to assess the accuracy of the estimated ICC for continuous and binary response variables under different covariate structures. The codes of two SAS macros are made available by the authors for interested readers to facilitate the construction of confidence intervals for the ICC. Moreover, using Monte Carlo simulations we evaluate the relative efficiency of the estimators and evaluate the accuracy of the coverage probabilities of a 95% confidence interval on the population ICC. The methodology is illustrated using a published data set of blood pressure measurements taken on family members.
Optimal classifier for imbalanced data using Matthews Correlation Coefficient metric.
Boughorbel, Sabri; Jarray, Fethi; El-Anbari, Mohammed
2017-01-01
Data imbalance is frequently encountered in biomedical applications. Resampling techniques can be used in binary classification to tackle this issue. However such solutions are not desired when the number of samples in the small class is limited. Moreover the use of inadequate performance metrics, such as accuracy, lead to poor generalization results because the classifiers tend to predict the largest size class. One of the good approaches to deal with this issue is to optimize performance metrics that are designed to handle data imbalance. Matthews Correlation Coefficient (MCC) is widely used in Bioinformatics as a performance metric. We are interested in developing a new classifier based on the MCC metric to handle imbalanced data. We derive an optimal Bayes classifier for the MCC metric using an approach based on Frechet derivative. We show that the proposed algorithm has the nice theoretical property of consistency. Using simulated data, we verify the correctness of our optimality result by searching in the space of all possible binary classifiers. The proposed classifier is evaluated on 64 datasets from a wide range data imbalance. We compare both classification performance and CPU efficiency for three classifiers: 1) the proposed algorithm (MCC-classifier), the Bayes classifier with a default threshold (MCC-base) and imbalanced SVM (SVM-imba). The experimental evaluation shows that MCC-classifier has a close performance to SVM-imba while being simpler and more efficient.
Bayesian Concordance Correlation Coefficient with Application to Repeatedly Measured Data
Atanu BHATTACHARJEE
2015-10-01
Full Text Available Objective: In medical research, Lin's classical concordance correlation coefficient (CCC is frequently applied to evaluate the similarity of the measurements produced by different raters or methods on the same subjects. It is particularly useful for continuous data. The objective of this paper is to propose the Bayesian counterpart to compute CCC for continuous data. Material and Methods: A total of 33 patients of astrocytoma brain treated in the Department of Radiation Oncology at Malabar Cancer Centre is enrolled in this work. It is a continuous data of tumor volume and tumor size repeatedly measured during baseline pretreatment workup and post surgery follow-ups for all patients. The tumor volume and tumor size are measured separately by MRI and CT scan. The agreement of measurement between MRI and CT scan is calculated through CCC. The statistical inference is performed through Markov Chain Monte Carlo (MCMC technique. Results: Bayesian CCC is found suitable to get prominent evidence for test statistics to explore the relation between concordance measurements. The posterior mean estimates and 95% credible interval of CCC on tumor size and tumor volume are observed with 0.96(0.87,0.99 and 0.98(0.95,0.99 respectively. Conclusion: The Bayesian inference is adopted for development of the computational algorithm. The approach illustrated in this work provides the researchers an opportunity to find out the most appropriate model for specific data and apply CCC to fulfill the desired hypothesis.
Shaw, A; Takács, I; Pagilla, K R; Murthy, S
2013-10-15
The Monod equation is often used to describe biological treatment processes and is the foundation for many activated sludge models. The Monod equation includes a "half-saturation coefficient" to describe the effect of substrate limitations on the process rate and it is customary to consider this parameter to be a constant for a given system. The purpose of this study was to develop a methodology, and its use to show that the half-saturation coefficient for denitrification is not constant but is in fact a function of the maximum denitrification rate. A 4-step procedure is developed to investigate the dependency of half-saturation coefficients on the maximum rate and two different models are used to describe this dependency: (a) an empirical linear model and (b) a deterministic model based on Fick's law of diffusion. Both models are proved better for describing denitrification kinetics than assuming a fixed K(NO3) at low nitrate concentrations. The empirical model is more utilitarian whereas the model based on Fick's law has a fundamental basis that enables the intrinsic K(NO3) to be estimated. In this study data was analyzed from 56 denitrification rate tests and it was found that the extant K(NO3) varied between 0.07 mgN/L and 1.47 mgN/L (5th and 95th percentile respectively) with an average of 0.47 mgN/L. In contrast to this, the intrinsic K(NO3) estimated for the diffusion model was 0.01 mgN/L which indicates that the extant K(NO3) is greatly influenced by, and mostly describes, diffusion limitations.
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
Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. This study shows that SCC is an alternative to the Pearson
Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient
Loraine Ann
2008-06-01
Full Text Available Abstract Background Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. Results In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC, that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. Conclusion
Correlation and path coefficient analysis in coconut (Cocos nucifera L.
S. Geethanjali, D. Rajkumar and N.Shoba
2014-12-01
Full Text Available A total of 43 coconut germplasm accessions were characterized for nut yield and fruit component traits. Correlation analysis showed that most of the fruit traits viz., fruit length, fruit breadth, fruit weight, nut weight, kernel weight and copra weight per nut were positively correlated with each other but showed significant negative correlation with the number of nuts produced per palm per annum. Shell thickness and husk thickness were not correlated with any of the fruit component traits. Path analysis revealed that nut yield and copra content per nut had positive direct effect on the total copra yield per palm. The results of this study showed that equal consideration should be given for both nut yield and copra content per nut while selecting elite genotypes for dual purpose viz., tender nut or culinary use and copra for oil extraction.
Korendijk, E.J.H.; Moerbeek, M.; Maas, C.J.M.
2010-01-01
In the case of trials with nested data, the optimal allocation of units depends on the budget, the costs, and the intracluster correlation coefficient. In general, the intracluster correlation coefficient is unknown in advance and an initial guess has to be made based on published values or subject
Correlation coefficient measurement of the mode-locked laser tones using four-wave mixing.
Anthur, Aravind P; Panapakkam, Vivek; Vujicic, Vidak; Merghem, Kamel; Lelarge, Francois; Ramdane, Abderrahim; Barry, Liam P
2016-06-01
We use four-wave mixing to measure the correlation coefficient of comb tones in a quantum-dash mode-locked laser under passive and active locked regimes. We study the uncertainty in the measurement of the correlation coefficient of the proposed method.
Wilson, Celia M.
2010-01-01
Research pertaining to the distortion of the squared canonical correlation coefficient has traditionally been limited to the effects of sampling error and associated correction formulas. The purpose of this study was to compare the degree of attenuation of the squared canonical correlation coefficient under varying conditions of score reliability.…
Korendijk, Elly J. H.; Moerbeek, Mirjam; Maas, Cora J. M.
2010-01-01
In the case of trials with nested data, the optimal allocation of units depends on the budget, the costs, and the intracluster correlation coefficient. In general, the intracluster correlation coefficient is unknown in advance and an initial guess has to be made based on published values or subject matter knowledge. This initial estimate is likely…
The concordance correlation coefficient for repeated measures estimated by variance components.
Carrasco, Josep L; King, Tonya S; Chinchilli, Vernon M
2009-01-01
The concordance correlation coefficient (CCC) is an index that is commonly used to assess the degree of agreement between observers on measuring a continuous characteristic. Here, a CCC for longitudinal repeated measurements is developed through the appropriate specification of the intraclass correlation coefficient from a variance components linear mixed model. A case example and the results of a simulation study are provided.
Korendijk, E.J.H.; Moerbeek, M.; Maas, C.J.M.
2010-01-01
In the case of trials with nested data, the optimal allocation of units depends on the budget, the costs, and the intracluster correlation coefficient. In general, the intracluster correlation coefficient is unknown in advance and an initial guess has to be made based on published values or
Korendijk, Elly J. H.; Moerbeek, Mirjam; Maas, Cora J. M.
2010-01-01
In the case of trials with nested data, the optimal allocation of units depends on the budget, the costs, and the intracluster correlation coefficient. In general, the intracluster correlation coefficient is unknown in advance and an initial guess has to be made based on published values or subject matter knowledge. This initial estimate is likely…
Wilson, Celia M.
2010-01-01
Research pertaining to the distortion of the squared canonical correlation coefficient has traditionally been limited to the effects of sampling error and associated correction formulas. The purpose of this study was to compare the degree of attenuation of the squared canonical correlation coefficient under varying conditions of score reliability.…
Tests of Fit Based on the Correlation Coefficient
1990-10-04
function. Regional Conference Series in Appl. Math., 9. Philadelphia: SIAM. 2. Gerlach, B., (1979). A consistent correlation-type goodness-of-fit test; with...the distribution of quadratic forms in normal variables. Biometrika, 48, 419-426. 4. Sarkadi, K., (1975). The consistency of the Shapiro- Francia test
Park, Sang Kyoo; Yang, Hei Cheon [Chonnam Nat’l Univ., Gwangju (Korea, Republic of)
2017-06-15
As stricter environmental regulation have led to an increase in the water treatment cost, it is necessary to quantitatively study the input power of the aeration process to improve the energy efficiency of the water treatment processes. The objective of this study is to propose the empirical correlations for the mass transfer coefficient with the gas hold-up and input power in order to investigate the mass transfer characteristics of the aeration process. It was found that as the input power increases, the mass transfer coefficient increases because of the decrease of gas hold-up and increase of Reynolds number, the penetration length, and dispersion of mixed flow. The correlations for the volumetric mass transfer coefficients with gas hold-up and input power were consistent with the experimental data, with the maximum deviation less than approximately ±10.0%.
Kilger, Robert; Stuke, Maik
2016-01-01
In this work we performed a detailed analysis on the calculation of 43 critical experiments from 6 experimental series all describing plutonium nitrate in aqueous solution contained in metal spheres. The underlying experimental data is taken from the handbook of the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Working Group. We present our modeling assumptions which were derived from the interpretation of the experimental data and discuss the resulting sensitivity analysis. Although the experiments share some components, the derived correlation coefficients are for many cases statistically not significant. Comparing our findings for the correlation coefficients with available data from the DICE Database we find an agreement for the correlation coefficients due to nuclear data. We also compare our results for the correlation coefficients due to experimental uncertainty. Our findings indicate that for the reliable Determination of correlation coefficients a detailed study of the underl...
Correlation of Cadmium Distribution Coefficients to Soil Characteristics
Holm, Peter Engelund; Rootzen, Helle; Borggaard, Ole K.;
2003-01-01
on whole soil samples have shown that pH is the main parameter controlling the distribution. To identify further the components that are important for Cd binding in soil we measured Cd distribution coefficients (K-d) at two fixed pH values and at low Cd loadings for 49 soils sampled in Denmark. The Kd...... that the organic carbon content was a significant variable at both pH values. Cation exchange capacity (CEC) and gibbsite were important at the low pH (5.3) while iron oxides also were important at the high pH (6.7). None of the other clay minerals present in the soils (illite, smectite, kaolinite, hydroxy......Cadmium (Cd) distribution between the soil solid phase and the soil solution is a key issue in assessing the environmental effect of Cd in the terrestrial environmental. Previous studies have shown that many individual minerals and other components found in soils can bind Cd, but most studies...
Empirical correlations for axial dispersion coefficient and Peclet number in fixed-bed columns.
Rastegar, Seyed Omid; Gu, Tingyue
2017-03-24
In this work, a new correlation for the axial dispersion coefficient was obtained using experimental data in the literature for axial dispersion in fixed-bed columns packed with particles. The Chung and Wen correlation, the De Ligny correlation are two popular empirical correlations. However, the former lacks the molecular diffusion term and the latter does not consider bed voidage. The new axial dispersion coefficient correlation in this work was based on additional experimental data in the literature by considering both molecular diffusion and bed voidage. It is more comprehensive and accurate. The Peclet number correlation from the new axial dispersion coefficient correlation on the average leads to 12% lower Peclet number values compared to the values from the Chung and Wen correlation, and in many cases much smaller than those from the De Ligny correlation. Copyright © 2017 Elsevier B.V. All rights reserved.
Shao, Y. F.; Song, F.; Jiang, C. P.; Xu, X. H.; Wei, J. C.; Zhou, Z. L.
2016-02-01
We study the difference in the maximum stress on a cylinder surface σmax using the measured surface heat transfer coefficient hm instead of its average value ha during quenching. In the quenching temperatures of 200, 300, 400, 500, 600 and 800°C, the maximum surface stress σmmax calculated by hm is always smaller than σamax calculated by ha, except in the case of 800°C; while the time to reach σmax calculated by hm (fmmax) is always earlier than that by ha (famax). It is inconsistent with the traditional view that σmax increases with increasing Biot number and the time to reach σmax decreases with increasing Biot number. Other temperature-dependent properties also have a small effect on the trend of their mutual ratios with quenching temperatures. Such a difference between the two maximum surface stresses is caused by the dramatic variation of hm with temperature, which needs to be considered in engineering analysis.
Diagnosing cysts with correlation coefficient images from 2-dimensional freehand elastography.
Booi, Rebecca C; Carson, Paul L; O'Donnell, Matthew; Richards, Michael S; Rubin, Jonathan M
2007-09-01
We compared the diagnostic potential of using correlation coefficient images versus elastograms from 2-dimensional (2D) freehand elastography to characterize breast cysts. In this preliminary study, which was approved by the Institutional Review Board and compliant with the Health Insurance Portability and Accountability Act, we imaged 4 consecutive human subjects (4 cysts, 1 biopsy-verified benign breast parenchyma) with freehand 2D elastography. Data were processed offline with conventional 2D phase-sensitive speckle-tracking algorithms. The correlation coefficient in the cyst and surrounding tissue was calculated, and appearances of the cysts in the correlation coefficient images and elastograms were compared. The correlation coefficient in the cysts was considerably lower (14%-37%) than in the surrounding tissue because of the lack of sufficient speckle in the cysts, as well as the prominence of random noise, reverberations, and clutter, which decorrelated quickly. Thus, the cysts were visible in all correlation coefficient images. In contrast, the elastograms associated with these cysts each had different elastographic patterns. The solid mass in this study did not have the same high decorrelation rate as the cysts, having a correlation coefficient only 2.1% lower than that of surrounding tissue. Correlation coefficient images may produce a more direct, reliable, and consistent method for characterizing cysts than elastograms.
Tool for Studying the Effects of Range Restriction in Correlation Coefficient Estimation
1990-07-01
AFHRL-TP-90-6 AIR FORCE TOOL FOR STUDYING THE EFFECTS OF RANGE RESTRICTION IN CORRELATION COEFFICIENT ESTIMATION H U Douglas E. JacksonM Eastern New...the Lftects of kange Restriction in Correlation Coefficient Estimation PE - 62703F PR - 7719 4. AUTHOR(S) TA - 18 Douglas E. Jackson WU - 46 Malcolm J...that one must try to estimate the correlation coefficient between two random variables X and Y in some population P using data taken f-om a
Comparing two K-category assignments by a K-category correlation coefficient
Gorodkin, Jan
2004-01-01
Predicted assignments of biological sequences are often evaluated by Matthews correlation coefficient. However, Matthews correlation coefficient applies only to cases where the assignments belong to two categories, and cases with more than two categories are often artificially forced into two...... categories by considering what belongs and what does not belong to one of the categories, leading to the loss of information. Here, an extended correlation coefficient that applies to K-categories is proposed, and this measure is shown to be highly applicable for evaluating prediction of RNA secondary...
Chu, De-Ren; Zhou, Qun; Yu, Lu; Sun, Su-Qin
2007-09-01
Based on the fingerprint infrared spectrum database, array of correlation coefficient has been first applied to identify traditional Chinese medicine slviae miltiorrhizae Bge. from different producing areas and growing environments. The result showed that the setting of high correlation coefficient in particular ranges of spectrum could differentiate the producing area of Slviae, while the setting of low correlation coefficient threshold of R5 to R7 ranges could identify wild or cultivated samples. This approach seems to be not only a simple but also an accurate method for identifying the character of different Slviae.
Statistics corner: A guide to appropriate use of correlation coefficient in medical research.
Mukaka, M M
2012-09-01
Correlation is a statistical method used to assess a possible linear association between two continuous variables. It is simple both to calculate and to interpret. However, misuse of correlation is so common among researchers that some statisticians have wished that the method had never been devised at all. The aim of this article is to provide a guide to appropriate use of correlation in medical research and to highlight some misuse. Examples of the applications of the correlation coefficient have been provided using data from statistical simulations as well as real data. Rule of thumb for interpreting size of a correlation coefficient has been provided.
KRIJNEN, WP
1994-01-01
De Vries (1993) discusses Pearson's product-moment correlation, Spearman's rank correlation, and Kendall's rank-correlation coefficient for assessing the association between the rows of two proximity matrices. For each of these he introduces a weighted average variant and a rowwise variant. In this
KRIJNEN, WP
De Vries (1993) discusses Pearson's product-moment correlation, Spearman's rank correlation, and Kendall's rank-correlation coefficient for assessing the association between the rows of two proximity matrices. For each of these he introduces a weighted average variant and a rowwise variant. In this
Beijeren, H. van; Kehr, K.W.
1986-01-01
The correlation factor, defined as the ratio between the tracer diffusion coefficient in lattice gases and the diffusion coefficient for a corresponding uncorrelated random walk, is known to assume a very simple form under certain conditions. A simple derivation of this is given with the aid of
Wang, Fang; Wang, Lin; Chen, Yuming
2017-08-31
In order to investigate the time-dependent cross-correlations of fine particulate (PM2.5) series among neighboring cities in Northern China, in this paper, we propose a new cross-correlation coefficient, the time-lagged q-L dependent height crosscorrelation coefficient (denoted by p q (τ, L)), which incorporates the time-lag factor and the fluctuation amplitude information into the analogous height cross-correlation analysis coefficient. Numerical tests are performed to illustrate that the newly proposed coefficient ρ q (τ, L) can be used to detect cross-correlations between two series with time lags and to identify different range of fluctuations at which two series possess cross-correlations. Applying the new coefficient to analyze the time-dependent cross-correlations of PM2.5 series between Beijing and the three neighboring cities of Tianjin, Zhangjiakou, and Baoding, we find that time lags between the PM2.5 series with larger fluctuations are longer than those between PM2.5 series withsmaller fluctuations. Our analysis also shows that cross-correlations between the PM2.5 series of two neighboring cities are significant and the time lags between two PM2.5 series of neighboring cities are significantly non-zero. These findings providenew scientific support on the view that air pollution in neighboring cities can affect one another not simultaneously but with a time lag.
Robustness of the Distribution Theory of the Product Moment Correlation Coefficient.
Kraemer, Helena Chmura
1980-01-01
The robustness of hypothesis tests for the correlation coefficient under varying conditions is discussed. The effects of violations of the assumptions of linearity, homoscedasticity, and kurtosis are examined. (JKS)
Crowell, Ed; Wang, Gufeng; Cox, Jason; Platz, Charles P; Geng, Lei
2005-03-01
Correlation coefficient mapping has been applied to intrinsic fluorescence spectra of colonic tissue for the purpose of cancer diagnosis. Fluorescence emission spectra were collected of 57 colonic tissue sites in a range of 4 physiological conditions: normal (29), hyperplastic (2), adenomatous (5), and cancerous tissues (21). The sample-sample correlation was used to examine the ability of correlation coefficient mapping to determine tissue disease state. The correlation coefficient map indicates two main categories of samples. These categories were found to relate to disease states of the tissue. Sensitivity, selectivity, predictive value positive, and predictive value negative for differentiation between normal tissue and all other categories were all above 92%. This was found to be similar to, or higher than, tissue classification using existing methods of data reduction. Wavelength-wavelength correlation among the samples highlights areas of importance for tissue classification. The two-dimensional correlation map reveals absorption by NADH and hemoglobin in the samples as negative correlation, an effect not obvious from the one-dimensional fluorescence spectra alone. The integrity of tissue was examined in a time series of spectra of a single tissue sample taken after tissue resection. The wavelength-wavelength correlation coefficient map shows the areas of significance for each fluorophore and their relation to each other. NADH displays negative correlation to collagen and FAD, from the absorption of emission or fluorescence resonance energy transfer. The wavelength-wavelength correlation map for the decay set also clearly shows that there are only three fluorophores of importance in the samples, by the well-defined pattern of the map. The sample-sample correlation coefficient map reveals the changes over time and their impact on tissue classification. Correlation coefficient mapping proves to be an effective method for sample classification and cancer
Observations of copolar correlation coefficient through a bright band at vertical incidence
Zrnic, D. S.; Raghavan, R.; Chandrasekar, V.
1994-01-01
This paper discusses an application of polarimetric measurements at vertical incidence. In particular, the correlation coefficients between linear copolar components are examined, and measurements obtained with the National Severe Storms Laboratory (NSSL)'s and National Center for Atmospheric Research (NCAR)'s polarimetric radars are presented. The data are from two well-defined bright bands. A sharp decrease of the correlation coefficient, confined to a height interval of a few hundred meters, marks the bottom of the bright band.
A Robust Multiple Correlation Coefficient for the Rank Analysis of Linear Models.
1983-09-01
A multiple correlation coefficient is discussed to measure the degree of association between a random variable Y and a set of random variables X sub...approach of analyzing linear models in a regression, prediction context. The population parameter equals the classical multiple correlation ... coefficient if the multivariate normal model holds but would be more robust for departures from this model. Some results are given on the consistency of the sample estimate and on a test for independence. (Author)
Provenzale, James M; Isaacson, Jared; Chen, Steven; Stinnett, Sandra; Liu, Chunlei
2010-12-01
The purpose of our study was to correlate decrease in apparent diffusion coefficient (ADC) and increase in fractional anisotropy (FA) in various white matter (WM) regions using diffusion tenor imaging (DTI) within the first year of life. We performed DTI on 53 infants and measured FA and ADC within 10 WM regions important in brain development. For each region, we calculated the slope of ADC as a function of FA, the correlation coefficient (r) and correlation of determination (r(2)). We performed a group analysis of r values and r(2)values for six WM regions primarily composed of crossing fibers and four regions primarily having parallel fibers. Upon finding that a strong correlation of FA with age existed, we adjusted for age and calculated partial correlation coefficients. Slopes of FA versus ADC ranged from -1.00711 to -1.67592 (p correlation coefficients ranged from -0.49 to 0.03 and r(2) values from 0.31 to 0.79. The highest partial correlation coefficients were then relatively equally distributed between the two types of WM regions. In various regions, FA and ADC evolved with differing degrees of correlation. We found a strong influence of age on the relationship between FA and ADC.
Du, Hongli; Hu, Haofu; Meng, Yuhuan; Zheng, Weihao; Ling, Fei; Wang, Jufang; Zhang, Xiquan; Nie, Qinghua; Wang, Xiaoning
2010-09-24
In this study, we present a new method for evaluating animal evolutionary relationships. We used the GC% levels of genome-wide genes to determine the correlation between the GC% content and evolutionary relationship. The correlation coefficients of the GC% content of the orthologous genes of the paired animal species were calculated for a total of 21 species, and the evolutionary branching dates of these 21 species were derived from fossil records. The correlation coefficient of the GC% content of the orthologous genes of the species pair under study served as an indicator of their evolutionary relationship. Moreover, there was a decreasing linear relationship between the correlation coefficient and evolutionary branching date (R(2)=0.930).
Zhuang, H; Savage, E M
2009-01-01
Measurements of texture properties related to tenderness at different locations within deboned broiler breast fillets have been used to validate techniques for texture analysis and establish correlations between different texture evaluation methods. However, it has been demonstrated that meat texture can vary from location to location within individual muscles. The objective of our study was to investigate the intramuscular variation and Pearson correlation coefficients of Warner-Bratzler (WB) shear force measurements within early deboned broiler breast fillets and the effect of deboning time and cold storage on the variation and correlation coefficients. Broiler breast fillets were removed from carcasses early postmortem (2 h) and later postmortem (24 h). Storage treatments of the 2 h samples included 0 d, 7 d at 3 degrees C, 7 d at -20 degrees C, and 6 d at -20 degrees C plus 1 d at 3 degrees C. The WB shears of cooked fillets were measured using a TA-XTPlus Texture Analyzer and a TA-7 WB shear type blade. Our results showed that although the average WB shear force values differed within the 0-d, 2-h fillets, compared with the variation among the fillets within the treatment, the difference within a fillet is still evidently small. The Pearson correlation coefficients were significant between the locations; however, values of the correlation coefficients depended on the paired locations. Location differences in the WB shear values and the correlation coefficient values between them changed with deboning time and cold storage. These results demonstrate that the variation of WB shear force measurements is substantial within early deboned broiler breast fillets and the Pearson correlation coefficient values of the measurements vary among the locations. Both the variation and the Pearson correlation coefficients can be affected by postmortem aging time and storage. The differences in the means between the locations in early deboned breasts are much smaller than the
Study on the Correlation Between Chlorophyll Maximum and Remote Sensing Data
XIU Peng; LIU Yuguang
2006-01-01
Based on the in situ optical measurements in the Bohai Sea of China, which belongs to a typical case-2 water area, we studied the characteristics of DCM (deep chlorophyll maximum) such as its spatial distribution, vertical profile,etc.We found that when the depth of the chlorophyll maximum is comparatively small, even in turbid coastal water regions,there is always a good correlation between the concentrations of chlorophyll maximum and the satellite-received signals in blue-green spectral bands; the correlation is even better than that between the surface chlorophyll concentrations and the satellite-received signals.The strong correlation existing even in turbid coastal water regions indicates that an ocean color model to retrieve the concentration of DCM can be constructed for coastal waters if a comprehensive knowledge of the vertical distribution of chlorophyll concentration in the Bohai Sea of China is available.
Cohen, S. C.
1980-01-01
A technique for fitting a straight line to a collection of data points is given. The relationships between the slopes and correlation coefficients, and between the corresponding standard deviations and correlation coefficient are given.
Reducing Bias and Error in the Correlation Coefficient Due to Nonnormality
Bishara, Anthony J.; Hittner, James B.
2015-01-01
It is more common for educational and psychological data to be nonnormal than to be approximately normal. This tendency may lead to bias and error in point estimates of the Pearson correlation coefficient. In a series of Monte Carlo simulations, the Pearson correlation was examined under conditions of normal and nonnormal data, and it was compared…
Reducing Bias and Error in the Correlation Coefficient Due to Nonnormality
Bishara, Anthony J.; Hittner, James B.
2015-01-01
It is more common for educational and psychological data to be nonnormal than to be approximately normal. This tendency may lead to bias and error in point estimates of the Pearson correlation coefficient. In a series of Monte Carlo simulations, the Pearson correlation was examined under conditions of normal and nonnormal data, and it was compared…
An empirical correlation of volumetric mass transfer coefficient was developed for a pilot scale internal-loop rectangular airlift bioreactor that was designed for biotechnology. The empirical correlation combines classic turbulence theory, Kolmogorov’s isotropic turbulence theory with Higbie’s pen...
Demetrashvili, Nino; Van den Heuvel, Edwin R
2015-06-01
This work is motivated by a meta-analysis case study on antipsychotic medications. The Michaelis-Menten curve is employed to model the nonlinear relationship between the dose and D2 receptor occupancy across multiple studies. An intraclass correlation coefficient (ICC) is used to quantify the heterogeneity across studies. To interpret the size of heterogeneity, an accurate estimate of ICC and its confidence interval is required. The goal is to apply a recently proposed generic beta-approach for construction the confidence intervals on ICCs for linear mixed effects models to nonlinear mixed effects models using four estimation methods. These estimation methods are the maximum likelihood, second-order generalized estimating equations and two two-step procedures. The beta-approach is compared with a large sample normal approximation (delta method) and bootstrapping. The confidence intervals based on the delta method and the nonparametric percentile bootstrap with various resampling strategies failed in our settings. The beta-approach demonstrates good coverages with both two-step estimation methods and consequently, it is recommended for the computation of confidence interval for ICCs in nonlinear mixed effects models for small studies.
Peters, Elisabeth; Stuke, Maik
2016-01-01
In this manuscript we study the modeling of experimental data and its impact on the resulting integral experimental covariance and correlation matrices. By investigating a set of three low enriched and water moderated UO2 fuel rod arrays we found that modeling the same set of data with different, yet reasonable assumptions concerning the fuel rod composition and its geometric properties leads to significantly different covariance matrices or correlation coefficients. Following a Monte Carlo sampling approach, we show for nine different modeling assumptions the corresponding correlation coefficients and sensitivity profiles for each pair of the effective neutron multiplication factor keff. Within the 95% confidence interval the correlation coefficients vary from 0 to 1, depending on the modeling assumptions. Our findings show that the choice of modeling can have a huge impact on integral experimental covariance matrices. When the latter are used in a validation procedure to derive a bias, this procedure can be...
Wheeler, David; Tiefelsdorf, Michael
2005-06-01
Present methodological research on geographically weighted regression (GWR) focuses primarily on extensions of the basic GWR model, while ignoring well-established diagnostics tests commonly used in standard global regression analysis. This paper investigates multicollinearity issues surrounding the local GWR coefficients at a single location and the overall correlation between GWR coefficients associated with two different exogenous variables. Results indicate that the local regression coefficients are potentially collinear even if the underlying exogenous variables in the data generating process are uncorrelated. Based on these findings, applied GWR research should practice caution in substantively interpreting the spatial patterns of local GWR coefficients. An empirical disease-mapping example is used to motivate the GWR multicollinearity problem. Controlled experiments are performed to systematically explore coefficient dependency issues in GWR. These experiments specify global models that use eigenvectors from a spatial link matrix as exogenous variables.
Shumanova M.V.
2015-03-01
Full Text Available The process fish salting has been studied by the method of photon correlation spectroscopy; the distribution of salt concentration in the solution and herring flesh with skin has been found, diffusion coefficients and salt concentrations used for creating a mathematical model of the salting technology have been worked out; the possibility of determination by this method the coefficient of dynamic viscosity of solutions and different media (minced meat etc. has been considered
Boesen, Lars; Chabanova, Elizaveta; Løgager, Vibeke
2015-01-01
PURPOSE: To evaluate the correlation between apparent diffusion coefficient measurements (ADCtumor and ADCratio ) and the Gleason score from radical prostatectomy specimens. MATERIALS AND METHODS: Seventy-one patients with clinically localized prostate cancer scheduled for radical prostatectomy...... correlated with the Gleason score from the prostatectomy specimens. RESULTS: The association between ADC measurements and Gleason score showed a significant negative correlation (P ... ) and 0.90 (ADCratio ) when discriminating Gleason score ≤7(3+4) from Gleason score ≥7(4+3). CONCLUSION: ADC measurements showed a significant correlation with tumor Gleason score at final pathology. The ADCratio demonstrated the best correlation compared to the ADCtumor value and radically improved...
A problem with the correlation coefficient as a measure of gene expression divergence.
Pereira, Vini; Waxman, David; Eyre-Walker, Adam
2009-12-01
The correlation coefficient is commonly used as a measure of the divergence of gene expression profiles between different species. Here we point out a potential problem with this statistic: if measurement error is large relative to the differences in expression, the correlation coefficient will tend to show high divergence for genes that have relatively uniform levels of expression across tissues or time points. We show that genes with a conserved uniform pattern of expression have significantly higher levels of expression divergence, when measured using the correlation coefficient, than other genes, in a data set from mouse, rat, and human. We also show that the Euclidean distance yields low estimates of expression divergence for genes with a conserved uniform pattern of expression.
Comparing two K-category assignments by a K-category correlation coefficient.
Gorodkin, J
2004-12-01
Predicted assignments of biological sequences are often evaluated by Matthews correlation coefficient. However, Matthews correlation coefficient applies only to cases where the assignments belong to two categories, and cases with more than two categories are often artificially forced into two categories by considering what belongs and what does not belong to one of the categories, leading to the loss of information. Here, an extended correlation coefficient that applies to K-categories is proposed, and this measure is shown to be highly applicable for evaluating prediction of RNA secondary structure in cases where some predicted pairs go into the category "unknown" due to lack of reliability in predicted pairs or unpaired residues. Hence, predicting base pairs of RNA secondary structure can be a three-category problem. The measure is further shown to be well in agreement with existing performance measures used for ranking protein secondary structure predictions. Server and software is available at http://rk.kvl.dk/.
Liu, An-Nuo; Wang, Lu-Lu; Li, Hui-Ping; Gong, Juan; Liu, Xiao-Hong
2016-11-22
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.
Quantized correlation coefficient for measuring reproducibility of ChIP-chip data.
Peng, Shouyong; Kuroda, Mitzi I; Park, Peter J
2010-07-27
Chromatin immunoprecipitation followed by microarray hybridization (ChIP-chip) is used to study protein-DNA interactions and histone modifications on a genome-scale. To ensure data quality, these experiments are usually performed in replicates, and a correlation coefficient between replicates is used often to assess reproducibility. However, the correlation coefficient can be misleading because it is affected not only by the reproducibility of the signal but also by the amount of binding signal present in the data. We develop the Quantized correlation coefficient (QCC) that is much less dependent on the amount of signal. This involves discretization of data into set of quantiles (quantization), a merging procedure to group the background probes, and recalculation of the Pearson correlation coefficient. This procedure reduces the influence of the background noise on the statistic, which then properly focuses more on the reproducibility of the signal. The performance of this procedure is tested in both simulated and real ChIP-chip data. For replicates with different levels of enrichment over background and coverage, we find that QCC reflects reproducibility more accurately and is more robust than the standard Pearson or Spearman correlation coefficients. The quantization and the merging procedure can also suggest a proper quantile threshold for separating signal from background for further analysis. To measure reproducibility of ChIP-chip data correctly, a correlation coefficient that is robust to the amount of signal present should be used. QCC is one such measure. The QCC statistic can also be applied in a variety of other contexts for measuring reproducibility, including analysis of array CGH data for DNA copy number and gene expression data.
Yue, Chen; Chen, Shaojie; Sair, Haris I; Airan, Raag; Caffo, Brian S
2015-09-01
Data reproducibility is a critical issue in all scientific experiments. In this manuscript, the problem of quantifying the reproducibility of graphical measurements is considered. The image intra-class correlation coefficient (I2C2) is generalized and the graphical intra-class correlation coefficient (GICC) is proposed for such purpose. The concept for GICC is based on multivariate probit-linear mixed effect models. A Markov Chain Monte Carlo EM (mcm-cEM) algorithm is used for estimating the GICC. Simulation results with varied settings are demonstrated and our method is applied to the KIRBY21 test-retest dataset.
Choosing the best index for the average score intraclass correlation coefficient.
Shieh, Gwowen
2016-09-01
The intraclass correlation coefficient (ICC)(2) index from a one-way random effects model is widely used to describe the reliability of mean ratings in behavioral, educational, and psychological research. Despite its apparent utility, the essential property of ICC(2) as a point estimator of the average score intraclass correlation coefficient is seldom mentioned. This article considers several potential measures and compares their performance with ICC(2). Analytical derivations and numerical examinations are presented to assess the bias and mean square error of the alternative estimators. The results suggest that more advantageous indices can be recommended over ICC(2) for their theoretical implication and computational ease.
Study of cross correlation coefficients of temperature fluctuations in a longitudinal magnetic field
Genin, L.G.; Manchkha, S.P.; Sviridov, V.G.
1977-01-01
An experimental study was made of the effect that a longitudinal magnetic field has on correlation coefficients of temperature fluctuations in a transverse direction. This effect on those fluctuations was shown to be small in comparison to its effect on the coefficients of longitudinal correlation. This indicates that the structure of the temperature field becomes more anisotropic so that there is an increase in the scale of turbulent disturbances in the direction of the magnetic field's force lines. 1 figure, 2 references.
Nakajo, Masatoyo [Nanpuh Hospital, Department of Radiology, Kagoshima (Japan); Kagoshima University, Department of Radiology, Graduate School of Medical and Dental Sciences, Kagoshima (Japan); Kajiya, Yoriko; Tani, Atsushi; Ueno, Masako [Nanpuh Hospital, Department of Radiology, Kagoshima (Japan); Kaneko, Tomoyo; Kaneko, Youichi [Kaneko Clinic, Department of Breast Surgery, Kagoshima (Japan); Takasaki, Takashi [Department of Pathology, Clinical Pathology Laboratory, Kagoshima (Japan); Koriyama, Chihaya [Kagoshima University, Department of Epidemiology and Preventive Medicine, Graduate School of Medical and Dental Sciences, Kagoshima (Japan); Nakajo, Masayuki [Kagoshima University, Department of Radiology, Graduate School of Medical and Dental Sciences, Kagoshima (Japan)
2010-11-15
To correlate both primary lesion {sup 18}F-fluorodeoxyglucose (FDG) maximum standardized uptake value (SUVmax) and diffusion-weighted imaging (DWI) apparent diffusion coefficient (ADC) with clinicopathological prognostic factors and compare the prognostic value of these indexes in breast cancer. The study population consisted of 44 patients with 44 breast cancers visible on both preoperative FDG PET/CT and DWI images. The breast cancers included 9 ductal carcinoma in situ (DCIS) and 35 invasive ductal carcinomas (IDC). The relationships between both SUVmax and ADC and clinicopathological prognostic factors were evaluated by univariate and multivariate regression analysis and the degree of correlation was determined by Spearman's rank test. The patients were divided into a better prognosis group (n = 24) and a worse prognosis group (n = 20) based upon invasiveness (DCIS or IDC) and upon their prognostic group (good, moderate or poor) determined from the modified Nottingham prognostic index. Their prognostic values were examined by receiver operating characteristic analysis. Both SUVmax and ADC were significantly associated (p<0.05) with histological grade (independently), nodal status and vascular invasion. Significant associations were also noted between SUVmax and tumour size (independently), oestrogen receptor status and human epidermal growth factor receptor-2 status, and between ADC and invasiveness. SUVmax and ADC were negatively correlated ({rho}=-0.486, p = 0.001) and positively and negatively associated with increasing of histological grade, respectively. The threshold values for predicting a worse prognosis were {>=}4.2 for SUVmax (with a sensitivity, specificity and accuracy of 80%, 75% and 77%, respectively) and {<=}0.98 for ADC (with a sensitivity, specificity and accuracy of 90%, 67% and 77%, respectively). SUVmax and ADC correlated with several of pathological prognostic factors and both indexes may have the same potential for predicting the
Aoki, T; Watanabe, A; Nitta, N; Numano, T; Fukushi, M; Niitsu, M
2012-09-01
Quantitative MR imaging techniques of degenerative cartilage have been reported as useful indicators of degenerative changes in cartilage extracellular matrix, which consists of proteoglycans, collagen, non-collagenous proteins, and water. Apparent diffusion coefficient (ADC) mapping of cartilage has been shown to correlate mainly with the water content of the cartilage. As the water content of the cartilage in turn correlates with its viscoelasticity, which directly affects the mechanical strength of articular cartilage, ADC can serve as a potentially useful indicator of the mechanical strength of cartilage. The aim of this study was to investigate the correlation between ADC and viscoelasticity as measured by indentation testing. Fresh porcine knee joints (n = 20, age 6 months) were obtained from a local abattoir. ADC of porcine knee cartilage was measured using a 3-Tesla MRI. Indentation testing was performed on an electromechanical precision-controlled system, and viscosity coefficient and relaxation time were measured as additional indicators of the viscoelasticity of cartilage. The relationship between ADC and viscosity coefficient as well as that between ADC and relaxation time were assessed. ADC was correlated with relaxation time and viscosity coefficient (R(2) = 0.75 and 0.69, respectively, p correlation between ADC and viscoelasticity in the superficial articular cartilage. Both molecular diffusion and viscoelasticity were higher in weight bearing than non-weight-bearing articular cartilage areas.
Liu Yanqiong; Chen Yingwu
2006-01-01
When analyze the uncertainty of the cost and the schedule of the spaceflight project, it is needed to know the value of the schedule-cost correlation coefficient. This paper deduces the schedule distribution, considering the effect of the cost, and proposes the estimation formula of the correlation coefficient between the ln(schedule) and the cost. On the basis of the fact and Taylor expansion, the relation expression between the schedule-cost correlation coefficient and the ln-schedule-cost correlation coefficient is put forward. By analyzing the value features of the estimation formula of the ln-schedule-cost correlation coefficient, the general rules are proposed to ascertain the value of the schedule-cost correlation coefficient. An example is given to demonstrate how to approximately amend the schedule-cost correlation coefficient based on the historical statistics, which reveals the traditional assigned value is inaccurate. The universality of this estimation method is analyzed.
Barlow, Andrew L; Macleod, Alasdair; Noppen, Samuel; Sanderson, Jeremy; Guérin, Christopher J
2010-12-01
One of the most routine uses of fluorescence microscopy is colocalization, i.e., the demonstration of a relationship between pairs of biological molecules. Frequently this is presented simplistically by the use of overlays of red and green images, with areas of yellow indicating colocalization of the molecules. Colocalization data are rarely quantified and can be misleading. Our results from both synthetic and biological datasets demonstrate that the generation of Pearson's correlation coefficient between pairs of images can overestimate positive correlation and fail to demonstrate negative correlation. We have demonstrated that the calculation of a thresholded Pearson's correlation coefficient using only intensity values over a determined threshold in both channels produces numerical values that more accurately describe both synthetic datasets and biological examples. Its use will bring clarity and accuracy to colocalization studies using fluorescent microscopy.
VARYING COEFFICIENT MODELS FOR DATA WITH AUTO-CORRELATED ERROR PROCESS.
Chen, Zhao; Li, Runze; Li, Yan
2015-04-01
Varying coefficient model has been popular in the literature. In this paper, we propose a profile least squares estimation procedure to its regression coefficients when its random error is an auto-regressive (AR) process. We further study the asymptotic properties of the proposed procedure, and establish the asymptotic normality for the resulting estimate. We show that the resulting estimate for the regression coefficients has the same asymptotic bias and variance as the local linear estimate for varying coefficient models with independent and identically distributed observations. We apply the SCAD variable selection procedure (Fan and Li, 2001) to reduce model complexity of the AR error process. Numerical comparison and finite sample performance of the resulting estimate are examined by Monte Carlo studies. Our simulation results demonstrate the proposed procedure is much more efficient than the one ignoring the error correlation. The proposed methodology is illustrated by a real data example.
Booi, Rebecca C; Carson, Paul L; O'Donnell, Matthew; Roubidoux, Marilyn A; Hall, Anne L; Rubin, Jonathan M
2008-01-01
Although simple cysts are easily identified using sonography, description and management of nonsimple cysts remains uncertain. This study evaluated whether the correlation coefficient differences between breast tissue and lesions, obtained from 2D breast elastography, could potentially distinguish nonsimple cysts from cancers and fibroadenomas. We hypothesized that correlation coefficients in cysts would be dramatically lower than surrounding tissue because noise, imaging artifacts, and particulate matter move randomly and decorrelate quickly under compression, compared with solid tissue. For this preliminary study, 18 breast lesions (7 nonsimple cysts, 4 cancers, and 7 fibroadenomas) underwent imaging with 2D elastography at 7.5 MHz through a TPX (a polymethyl pentene copolymer) 2.5 mm mammographic paddle. Breasts were compressed similar to mammographic positioning and then further compressed for elastography by 1 to 7%. Images were correlated using 2D phase-sensitive speckle tracking algorithms and displacement estimates were accumulated. Correlation coefficient means and standard deviations were measured in the lesion and adjacent tissue, and the differential correlation coefficient (DCC) was introduced as the difference between these values normalized to the correlation coefficient of adjacent tissue. Mean DCC values in nonsimple cysts were 24.2 +/- 11.6%, 5.7 +/- 6.3% for fibroadenomas, and 3.8 +/- 2.9 % for cancers (p < 0.05). Some of the cysts appeared smaller in DCC images than gray-scale images. These encouraging results demonstrate that characterization of nonsimple breast cysts may be improved by using DCC values from 2D elastography, which could potentially change management options of these cysts from intervention to imaging follow-up. A dedicated clinical trial to fully assess the efficacy of this technique is recommended.
Xuemei HU; Feng LIU; Zhizhong WANG
2009-01-01
The authors propose a V_(N,P) test statistic for testing finite-order serial correlation in a semiparametric varying coefficient partially linear errors-in-variables model. The test statistic is shown to have asymptotic normal distribution under the null hypothesis of no serial correlation. Some Monte Carlo experiments are conducted to examine the finite sample performance of the proposed V_(N,P) test statistic. Simulation results confirm that the proposed test performs satisfactorily in estimated size and power.
Taler, Dawid
2012-09-01
This paper presents a numerical method for determining heat transfer coefficients in cross-flow heat exchangers with extended heat exchange surfaces. Coefficients in the correlations defining heat transfer on the liquid- and air-side were determined using a nonlinear regression method. Correlation coefficients were determined from the condition that the sum of squared liquid and air temperature differences at the heat exchanger outlet, obtained by measurements and those calculated, achieved minimum. Minimum of the sum of the squares was found using the Levenberg-Marquardt method. The uncertainty in estimated parameters was determined using the error propagation rule by Gauss. The outlet temperature of the liquid and air leaving the heat exchanger was calculated using the analytical model of the heat exchanger.
The relation between Pearson’s correlation coefficient r and Salton’s cosine measure
Egghe, L.; Leydesdorff, L.
2009-01-01
The relation between Pearson's correlation coefficient and Salton's cosine measure is revealed based on the different possible values of the division of the L1-norm and the L2-norm of a vector. These different values yield a sheaf of increasingly straight lines which together form a cloud of points,
van de Wassenberg, Wilma J G; van der Hoeven, Johannes H; Leenders, Klaus L; Maurits, Natasha M
2008-06-01
Although large intersubject variability is reported for cortical somatosensory evoked potentials (SEPs), variability between hemispheres within one subject is thought to be small. Therefore, interhemispheric comparison of SEP waveforms might be clinically useful to detect unilateral abnormalities in cortical sensory processing. We developed and evaluated a new technique to quantify interhemispheric SEP symmetry that uses a time interval including multiple SEP components, measures similarity of SEP waveforms between both hemispheres and results in high symmetry values even in the presence of small interhemispheric anatomic differences. Median nerve SEPs were recorded in 50 healthy subjects (20-70 years) using 128-channel EEG. Symmetry was quantified by the intraclass correlation coefficient and correlation coefficient between global field power of left and right median nerve SEPs. In 74% of subjects left-right intraclass correlation coefficient was higher than 0.60, implying high SEP hemispheric symmetry in terms of shape and amplitude. Left-right intraclass correlation coefficients lower than 0.60 were due to differences in amplitude, unilateral absence of peaks, or shape differences. We quantified SEP waveform interhemispheric symmetry and found it to be high in most healthy subjects. This technique may therefore be useful for detection of unilateral abnormalities in cortical sensory processing.
Sample Size Calculation for Estimating or Testing a Nonzero Squared Multiple Correlation Coefficient
Krishnamoorthy, K.; Xia, Yanping
2008-01-01
The problems of hypothesis testing and interval estimation of the squared multiple correlation coefficient of a multivariate normal distribution are considered. It is shown that available one-sided tests are uniformly most powerful, and the one-sided confidence intervals are uniformly most accurate. An exact method of calculating sample size to…
LARGE DEVIATION FOR THE EMPIRICAL CORRELATION COEFFICIENT OF TWO GAUSSIAN RANDOM VARIABLES
Shen Si
2007-01-01
In this article, the author obtains the large deviation principles for the empirical correlation coefficient of two Gaussian random variables X and Y. Especially, when considering two independent Gaussian random variables X, Y with the means EX, EY(both known), wherein the author gives two kinds of different proofs and gets the same results.
A simple approximation to the bivariate normal distribution with large correlation coefficient
Albers, Willem; Kallenberg, Wilbert C.M.
1994-01-01
The bivariate normal distribution function is approximated with emphasis on situations where the correlation coefficient is large. The high accuracy of the approximation is illustrated by numerical examples. Moreover, exact upper and lower bounds are presented as well as asymptotic results on the er
Sample Size Calculation for Estimating or Testing a Nonzero Squared Multiple Correlation Coefficient
Krishnamoorthy, K.; Xia, Yanping
2008-01-01
The problems of hypothesis testing and interval estimation of the squared multiple correlation coefficient of a multivariate normal distribution are considered. It is shown that available one-sided tests are uniformly most powerful, and the one-sided confidence intervals are uniformly most accurate. An exact method of calculating sample size to…
The relation between Pearson’s correlation coefficient r and Salton’s cosine measure
Egghe, L.; Leydesdorff, L.
2009-01-01
The relation between Pearson's correlation coefficient and Salton's cosine measure is revealed based on the different possible values of the division of the L1-norm and the L2-norm of a vector. These different values yield a sheaf of increasingly straight lines which together form a cloud of points,
Raykov, Tenko
2011-01-01
Interval estimation of intraclass correlation coefficients in hierarchical designs is discussed within a latent variable modeling framework. A method accomplishing this aim is outlined, which is applicable in two-level studies where participants (or generally lower-order units) are clustered within higher-order units. The procedure can also be…
Demetrashvili, Nino; Van den Heuvel, Edwin R.
This work is motivated by a meta-analysis case study on antipsychotic medications. The Michaelis-Menten curve is employed to model the nonlinear relationship between the dose and D2 receptor occupancy across multiple studies. An intraclass correlation coefficient (ICC) is used to quantify the
Serge B. Provost
2015-07-01
Full Text Available This paper provides a simplified representation of the exact density function of R, the sample correlation coefficient. The odd and even moments of R are also obtained in closed forms. Being expressed in terms of generalized hypergeometric functions, the resulting representations are readily computable. Some numerical examples corroborate the validity of the results derived herein.
Demetrashvili, Nino; Van den Heuvel, Edwin R.
2015-01-01
This work is motivated by a meta-analysis case study on antipsychotic medications. The Michaelis-Menten curve is employed to model the nonlinear relationship between the dose and D2 receptor occupancy across multiple studies. An intraclass correlation coefficient (ICC) is used to quantify the hetero
A simple approximation to the bivariate normal distribution with large correlation coefficient
Albers, Willem/Wim; Kallenberg, W.C.M.
1994-01-01
The bivariate normal distribution function is approximated with emphasis on situations where the correlation coefficient is large. The high accuracy of the approximation is illustrated by numerical examples. Moreover, exact upper and lower bounds are presented as well as asymptotic results on the
Three dimensional winds: A maximum cross-correlation application to elastic lidar data
Buttler, William Tillman [Univ. of Texas, Austin, TX (United States)
1996-05-01
Maximum cross-correlation techniques have been used with satellite data to estimate winds and sea surface velocities for several years. Los Alamos National Laboratory (LANL) is currently using a variation of the basic maximum cross-correlation technique, coupled with a deterministic application of a vector median filter, to measure transverse winds as a function of range and altitude from incoherent elastic backscatter lidar (light detection and ranging) data taken throughout large volumes within the atmospheric boundary layer. Hourly representations of three-dimensional wind fields, derived from elastic lidar data taken during an air-quality study performed in a region of complex terrain near Sunland Park, New Mexico, are presented and compared with results from an Environmental Protection Agency (EPA) approved laser doppler velocimeter. The wind fields showed persistent large scale eddies as well as general terrain-following winds in the Rio Grande valley.
Reliability sensitivity-based correlation coefficient calculation in structural reliability analysis
Yang, Zhou; Zhang, Yimin; Zhang, Xufang; Huang, Xianzhen
2012-05-01
The correlation coefficients of random variables of mechanical structures are generally chosen with experience or even ignored, which cannot actually reflect the effects of parameter uncertainties on reliability. To discuss the selection problem of the correlation coefficients from the reliability-based sensitivity point of view, the theory principle of the problem is established based on the results of the reliability sensitivity, and the criterion of correlation among random variables is shown. The values of the correlation coefficients are obtained according to the proposed principle and the reliability sensitivity problem is discussed. Numerical studies have shown the following results: (1) If the sensitivity value of correlation coefficient ρ is less than (at what magnitude 0.000 01), then the correlation could be ignored, which could simplify the procedure without introducing additional error. (2) However, as the difference between ρ s, that is the most sensitive to the reliability, and ρ R , that is with the smallest reliability, is less than 0.001, ρ s is suggested to model the dependency of random variables. This could ensure the robust quality of system without the loss of safety requirement. (3) In the case of | E abs|>0.001 and also | E rel|>0.001, ρ R should be employed to quantify the correlation among random variables in order to ensure the accuracy of reliability analysis. Application of the proposed approach could provide a practical routine for mechanical design and manufactory to study the reliability and reliability-based sensitivity of basic design variables in mechanical reliability analysis and design.
Fiebig, H R
2002-01-01
We study various aspects of extracting spectral information from time correlation functions of lattice QCD by means of Bayesian inference with an entropic prior, the maximum entropy method (MEM). Correlator functions of a heavy-light meson-meson system serve as a repository for lattice data with diverse statistical quality. Attention is given to spectral mass density functions, inferred from the data, and their dependence on the parameters of the MEM. We propose to employ simulated annealing, or cooling, to solve the Bayesian inference problem, and discuss practical issues of the approach.
Strong Solar Control of Infrared Aurora on Jupiter: Correlation Since the Last Solar Maximum
Kostiuk, T.; Livengood, T. A.; Hewagama, T.
2009-01-01
Polar aurorae in Jupiter's atmosphere radiate throughout the electromagnetic spectrum from X ray through mid-infrared (mid-IR, 5 - 20 micron wavelength). Voyager IRIS data and ground-based spectroscopic measurements of Jupiter's northern mid-IR aurora, acquired since 1982, reveal a correlation between auroral brightness and solar activity that has not been observed in Jovian aurora at other wavelengths. Over nearly three solar cycles, Jupiter auroral ethane emission brightness and solar 10.7 cm radio flux and sunspot number are positively correlated with high confidence. Ethane line emission intensity varies over tenfold between low and high solar activity periods. Detailed measurements have been made using the GSFC HIPWAC spectrometer at the NASA IRTF since the last solar maximum, following the mid-IR emission through the declining phase toward solar minimum. An even more convincing correlation with solar activity is evident in these data. Current analyses of these results will be described, including planned measurements on polar ethane line emission scheduled through the rise of the next solar maximum beginning in 2009, with a steep gradient to a maximum in 2012. This work is relevant to the Juno mission and to the development of the Europa Jupiter System Mission. Results of observations at the Infrared Telescope Facility (IRTF) operated by the University of Hawaii under Cooperative Agreement no. NCC5-538 with the National Aeronautics and Space Administration, Science Mission Directorate, Planetary Astronomy Program. This work was supported by the NASA Planetary Astronomy Program.
Gender and Age Analyses of NIRS/STAI Pearson Correlation Coefficients at Resting State.
Matsumoto, T; Fuchita, Y; Ichikawa, K; Fukuda, Y; Takemura, N; Sakatani, K
2016-01-01
According to the valence asymmetry hypothesis, the left/right asymmetry of PFC activity is correlated with specific emotional responses to mental stress and personality traits. In a previous study we measured spontaneous oscillation of oxy-Hb concentrations in the bilateral PFC at rest in normal adults employing two-channel portable NIRS and computed the laterality index at rest (LIR). We investigated the Pearson correlation coefficient between the LIR and anxiety levels evaluated by the State-Trait Anxiety Inventory (STAI) test. We found that subjects with right-dominant activity at rest showed higher STAI scores, while those with left dominant oxy-Hb changes at rest showed lower STAI scores such that the Pearson correlation coefficient between LIR and STAI was positive. This study performed Bootstrap analysis on the data and showed the following statistics of the target correlation coefficient: mean=0.4925 and lower confidence limit=0.177 with confidence level 0.05. Using the KS-test, we demonstrated that the correlation did not depend on age, whereas it did depend on gender.
Evaluation of icing drag coefficient correlations applied to iced propeller performance prediction
Miller, Thomas L.; Shaw, R. J.; Korkan, K. D.
1987-01-01
Evaluation of three empirical icing drag coefficient correlations is accomplished through application to a set of propeller icing data. The various correlations represent the best means currently available for relating drag rise to various flight and atmospheric conditions for both fixed-wing and rotating airfoils, and the work presented here ilustrates and evaluates one such application of the latter case. The origins of each of the correlations are discussed, and their apparent capabilities and limitations are summarized. These correlations have been made to be an integral part of a computer code, ICEPERF, which has been designed to calculate iced propeller performance. Comparison with experimental propeller icing data shows generally good agreement, with the quality of the predicted results seen to be directly related to the radial icing extent of each case. The code's capability to properly predict thrust coefficient, power coefficient, and propeller efficiency is shown to be strongly dependent on the choice of correlation selected, as well as upon proper specificatioon of radial icing extent.
关于相关系数的探讨%Study of the Correlation Coefficients in Mathematical Statistics
张世强; 吕杰能; 蒋峥; 张雷
2009-01-01
讨论统计学中的线性相关系数和非线性相关系数,寻找其共性.对比研究与信息再利用.得到一个相关系数的通用公式.该公式适合于统计学中的各种数据处理.%To study the linear correlation coefficient and nonlinear correlation coefficient in statistics and find general character. To contrast the linear correlation coefficient with the nonlinear correlation coefficient in statistics and based information reused. A commonly used correlation coefficient is given. The commonly used correlation coefficient is suitable for all data analysis in statistics.
Wang, Yang; Li, Mingxing; Tu, Z. C.; Hernández, A. Calvo; Roco, J. M. M.
2012-07-01
The figure of merit for refrigerators performing finite-time Carnot-like cycles between two reservoirs at temperature Th and Tc (Carnot coefficient of performance for reversible refrigerators. These bounds can be reached for extremely asymmetric low-dissipation cases when the ratio between the dissipation constants of the processes in contact with the cold and hot reservoirs approaches to zero or infinity, respectively. The observed coefficients of performance for real refrigerators are located in the region between the lower and upper bounds, which is in good agreement with our theoretical estimation.
Wang, Yang; Li, Mingxing; Tu, Z C; Hernández, A Calvo; Roco, J M M
2012-07-01
The figure of merit for refrigerators performing finite-time Carnot-like cycles between two reservoirs at temperature T(h) and T(c) (Carnot coefficient of performance for reversible refrigerators. These bounds can be reached for extremely asymmetric low-dissipation cases when the ratio between the dissipation constants of the processes in contact with the cold and hot reservoirs approaches to zero or infinity, respectively. The observed coefficients of performance for real refrigerators are located in the region between the lower and upper bounds, which is in good agreement with our theoretical estimation.
Reddivenkatagari Subbarama Krishna Reddy
2013-06-01
Full Text Available One hundred germplasm lines of okra (Abelmoschus esculentus (L. Moench were evaluated in a randomized block design with two replications at the Vegetable Research Station, Rajendranagar, Hyderabad, Andhra Pradesh, India, during kharif, 2008. Correlation and path coefficient analysis were carried out to study the character association and contribution, respectively, for thirteen quantitative characters, namely plant height (cm, number of branches per plant, internodal length(cm, days to 50% flowering, first flowering node, first fruiting node, fruit length (cm, fruit width (cm, fruit weight (g, total number of fruits per plant, number of marketable fruits per plant, total yield per plant (g and marketable yield per plant (g for the identification of appropriate selection indices. Phenotypic and genotypic correlation coefficient analysis revealed that plant height, fruit length, fruit width, fruit weight, total number of fruits per plant, number of marketable fruits per plant and total yield per plant had significant positive correlation, while number of branches per plant, internodal length, days to 50% flowering, first flowering node and first fruiting node had significant negative correlation with marketable yield per plant.Genotypic path coefficient analysis revealed that fruit weight, total number of fruits per plant and number of marketable fruits per plant had positively high direct effect on marketable pod yield per plant. Correlation and path coefficient analyses revealed that fruit weight, total number of fruits per plant and number of marketable fruits per plant not only had positively significant association with marketable pod yield per plant, but also had positively high direct effect on marketable pod yield per plant and are regarded as the main determinants of marketable pod yield per plant. The improvement in marketable pod yield per plant will be efficient, if the selection is based on fruit weight, total number of fruits per
Herranz, J.; Bloxom, S.R.; Keeler, J.B.; Roth, S.R.
1975-12-17
In the proposed Molten Salt Breeder Reactor flowsheet, a fraction of the rare earth fission products is removed from the fuel salt in mass transfer cells. To obtain design parameters for this extraction, the effect of cell size, blade diameter, phase volume, and agitation rate on the mass transfer for a high density ratio system (mercury/water) in nondispersing square cross section contactors was determined. Aqueous side mass transfer coefficients were measured by polarography over a wide range of operating conditions. Correlations for the experimental mass transfer coefficients as functions of the operating parameters are presented. Several techniques for measuring mercury-side mass transfer coefficients were evaluated and a new one is recommended. (auth)
Liu, Yongsuo; Meng, Qinghua; Chen, Rong; Wang, Jiansong; Jiang, Shumin; Hu, Yuzhu
2004-01-01
The Pearson product-moment correlation coefficient is being used to evaluate the similarity of the high-performance liquid chromatographic fingerprints of traditional Chinese medicine (TCM) in China. It is confirmed that a large range of peak areas produced the wrong results. A new algorithm concerning weighted Pearson product-moment correlation coefficient is proposed in this article. The results for both real cases and simulated data sets show that the weighted Pearson product-moment correlation coefficients allow relatively larger differences for large values, smaller differences for small values, and more reliable results than the unweighted Pearson product-moment correlation coefficients. Weight selection depends on the specific scientific problem.
Sadjadi, Firooz A; Mahalanobis, Abhijit
2006-05-01
We report the development of a technique for adaptive selection of polarization ellipse tilt and ellipticity angles such that the target separation from clutter is maximized. From the radar scattering matrix [S] and its complex components, in phase and quadrature phase, the elements of the Mueller matrix are obtained. Then, by means of polarization synthesis, the radar cross section of the radar scatters are obtained at different transmitting and receiving polarization states. By designing a maximum average correlation height filter, we derive a target versus clutter distance measure as a function of four transmit and receive polarization state angles. The results of applying this method on real synthetic aperture radar imagery indicate a set of four transmit and receive angles that lead to maximum target versus clutter discrimination. These optimum angles are different for different targets. Hence, by adaptive control of the state of polarization of polarimetric radar, one can noticeably improve the discrimination of targets from clutter.
Estimation of the concordance correlation coefficient for repeated measures using SAS and R.
Carrasco, Josep L; Phillips, Brenda R; Puig-Martinez, Josep; King, Tonya S; Chinchilli, Vernon M
2013-03-01
The concordance correlation coefficient is one of the most common approaches used to assess agreement among different observers or instruments when the outcome of interest is a continuous variable. A SAS macro and R package are provided here to estimate the concordance correlation coefficient (CCC) where the design of the data involves repeated measurements by subject and observer. The CCC is estimated using U-statistics (UST) and variance components (VC) approaches. Confidence intervals and standard errors are reported along with the point estimate of the CCC. In the case of the VC approach, the linear mixed model output and variance components estimates are also provided. The performance of each function is shown by means of some examples with real data sets.
Ma, Rubao; Xu, Weichao; Zhang, Yun; Ye, Zhongfu
2014-01-01
This paper investigates the robustness properties of Pearson's rank-variate correlation coefficient (PRVCC) in scenarios where one channel is corrupted by impulsive noise and the other is impulsive noise-free. As shown in our previous work, these scenarios that frequently encountered in radar and/or sonar, can be well emulated by a particular bivariate contaminated Gaussian model (CGM). Under this CGM, we establish the asymptotic closed forms of the expectation and variance of PRVCC by means of the well known Delta method. To gain a deeper understanding, we also compare PRVCC with two other classical correlation coefficients, i.e., Spearman's rho (SR) and Kendall's tau (KT), in terms of the root mean squared error (RMSE). Monte Carlo simulations not only verify our theoretical findings, but also reveal the advantage of PRVCC by an example of estimating the time delay in the particular impulsive noise environment.
Bodryakov, V. Yu.; Bykov, A. A.
2016-05-01
The correlation between the volumetric thermal expansion coefficient β( T) and the heat capacity C( T) of aluminum is considered in detail. It is shown that a clear correlation is observed in a significantly wider temperature range, up to the melting temperature of the metal, along with the low-temperature range where it is linear. The significant deviation of dependence β( C) from the low-temperature linear behavior is observed up to the point where the heat capacity achieves the classical Dulong-Petit limit of 3 R ( R is the universal gas constant).
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.
Diagnosis method based on wavelet coefficient scale relativity correlation dimension for fault
2008-01-01
Correlation dimension as a tool to describe machinery condition is introduced.Vibration signals of the fan under different working conditions are analyzed using a threshold filtering algorithm based on the region relativity of the wavelet coefficients for reducing noise.The result shows that the characteristics of the signal could be preserved completely.The correlation dimension is able to identify conditions of the fan with faults compared with the normal condition,thereby providing an effective technology for condition monitoring and fault diagnosis of mechanical equipment.
Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data
Tan, Qihua; Thomassen, Mads; Burton, Mark
2017-01-01
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 Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data
Tan, Qihua; Thomassen, Mads; Burton, Mark
2017-01-01
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...
Ground reaction force analysed with correlation coefficient matrix in group of stroke patients.
Szczerbik, Ewa; Krawczyk, Maciej; Syczewska, Małgorzata
2014-01-01
Stroke is the third cause of death in contemporary society and causes many disorders. Clinical scales, ground reaction force (GRF) and objective gait analysis are used for assessment of patient's rehabilitation progress during treatment. The goal of this paper is to assess whether signal correlation coefficient matrix applied to GRF can be used for evaluation of the status of post-stroke patients. A group of patients underwent clinical assessment and instrumented gait analysis simultaneously three times. The difference between components of patient's GRF (vertical, fore/aft, med/lat) and normal ones (reference GRF of healthy subjects) was calculated as correlation coefficient. Patients were divided into two groups ("worse" and "better") based on the clinical functional scale tests done at the beginning of rehabilitation process. The results obtained by these two groups were compared using statistical analysis. An increase of median value of correlation coefficient is observed in all components of GRF, but only in non-paretic leg. Analysis of GRF signal can be helpful in assessment of post-stroke patients during rehabilitation. Improvement in stroke patients was observed in non-paretic leg of the "worse" group. GRF analysis should not be the only tool for objective validation of patient's improvement, but could be used as additional source of information.
Mikuni, Shintaro; Yamamoto, Johtaro; Horio, Takashi; Kinjo, Masataka
2017-08-25
The glucocorticoid receptor (GR) is a transcription factor, which interacts with DNA and other cofactors to regulate gene transcription. Binding to other partners in the cell nucleus alters the diffusion properties of GR. Raster image correlation spectroscopy (RICS) was applied to quantitatively characterize the diffusion properties of EGFP labeled human GR (EGFP-hGR) and its mutants in the cell nucleus. RICS is an image correlation technique that evaluates the spatial distribution of the diffusion coefficient as a diffusion map. Interestingly, we observed that the averaged diffusion coefficient of EGFP-hGR strongly and negatively correlated with its transcriptional activities in comparison to that of EGFP-hGR wild type and mutants with various transcriptional activities. This result suggests that the decreasing of the diffusion coefficient of hGR was reflected in the high-affinity binding to DNA. Moreover, the hyper-phosphorylation of hGR can enhance the transcriptional activity by reduction of the interaction between the hGR and the nuclear corepressors.
Moriya, Tomohisa; Saito, Kazuhiro; Tajima, Yu; Harada, Taiyo L; Araki, Yoichi; Sugimoto, Katsutoshi; Tokuuye, Koichi
2017-01-05
To evaluate the usefulness of differentiation of histological grade in hepatocellular carcinoma (HCC) using three-dimensional (3D) analysis of apparent diffusion coefficient (ADC) histograms retrospectively. The subjects consisted of 53 patients with 56 HCCs. The subjects included 12 well-differentiated, 35 moderately differentiated, and nine poorly differentiated HCCs. Diffusion-weighted imaging (b-values of 100 and 800 s/mm(2)) were obtained within 3 months before surgery. Regions of interest (ROIs) covered the entire tumor. The data acquired from each slice were summated to derive voxel-by-voxel ADCs for the entire tumor. The following parameters were derived from the ADC histogram: mean, standard deviation, minimum, maximum, mode, percentiles (5th, 10th, 25th, 50th, 75th, and 90th), skew, and kurtosis. These parameters were analyzed according to histological grade. After eliminating steatosis lesions, these parameters were re-analyzed. A weak correlation was observed in minimum ADC and 5th percentile for each histological grade (r = -0.340 and r = -0.268, respectively). The minimum ADCs of well, moderately, and poorly differentiated HCC were 585 ± 388, 411 ± 278, and 235 ± 102 × 10(-6) mm(2)/s, respectively. Minimum ADC showed significant differences among tumor histological grades (P = 0.009). The minimum ADC of poorly differentiated HCC and that of combined well and moderately differentiated HCC were 236 ± 102 and 437 ± 299 × 10(-6) mm(2)/s. The minimum ADC of poorly differentiated HCC was significantly lower than that of combined well and moderately differentiated HCC (P = 0.001). The sensitivity and specificity, when a minimum ADC of 400 × 10(-6) mm(2)/s or lower was considered to be poorly differentiated HCC, were 100 and 54%, respectively. After exclusion of the effect of steatosis, the sensitivity and specificity did not change, although the statistical differences became strong (P < 0
Mohammad Mizanur RAHMAN
2016-06-01
Full Text Available Digital terrestrial television (DTV covers an area with radius as large as 60 km. Federal Communications Commission (FCC and Office of Communications (Ofcom suggests detection of DTV signal at signal strength of as low as -114 dBm and -120 dBm respectively. Thus, detection of DTV signals in low signal-to-noise ratio (SNR is vital. Continual pilot (CP positions in all the DTV signals are fixed. Digital Video Broadcasting Terrestrial (DVB-T, a DTV standard, is followed by most of the countries of the world. In this paper we propose a correlation based CP detection which can detect a DVB-T signal at low SNR. One CP carrier was generated at the receiver which was correlated with the received orthogonal frequency division multiplexing (OFDM signal sequence. The correlation coefficient was then compared with a threshold correlation coefficient to identify the existence of the CP to detect the presence of a DVB-T signal and thereby spectrum hole. It was found from the simulation study for additive white Gaussian noise (AWGN channel that signal detection at low SNR is possible compared to the time domain symbol cross-correlation (TDSC method.
Dithering Digital Ripple Correlation Control for Photovoltaic Maximum Power Point Tracking
Barth, C; Pilawa-Podgurski, RCN
2015-08-01
This study demonstrates a new method for rapid and precise maximum power point tracking in photovoltaic (PV) applications using dithered PWM control. Constraints imposed by efficiency, cost, and component size limit the available PWM resolution of a power converter, and may in turn limit the MPP tracking efficiency of the PV system. In these scenarios, PWM dithering can be used to improve average PWM resolution. In this study, we present a control technique that uses ripple correlation control (RCC) on the dithering ripple, thereby achieving simultaneous fast tracking speed and high tracking accuracy. Moreover, the proposed method solves some of the practical challenges that have to date limited the effectiveness of RCC in solar PV applications. We present a theoretical derivation of the principles behind dithering digital ripple correlation control, as well as experimental results that show excellent tracking speed and accuracy with basic hardware requirements.
Zinchuk, Vadim; Wu, Yong; Grossenbacher-Zinchuk, Olga; Stefani, Enrico
2011-09-15
Interactions of proteins are examined by detecting their overlap using fluorescent markers. The observed overlap is then quantified to serve as a measure of spatial correlation. A major drawback of this approach is that it can produce false values because of the properties of the image background. To remedy this, we provide a protocol to reduce the contribution of image background and then apply a protein proximity index (PPI) and correlation coefficient to estimate colocalization. Background heterogeneity is reduced by the median filtering procedure, comprising two steps, to reduce random noise and background, respectively. Alternatively, background can be reduced by advanced thresholding. PPI provides separate values for each channel to characterize the contribution of each protein, whereas correlation coefficient determines the overall colocalization. The protocol is demonstrated using computer-simulated and real biological images. It minimizes human bias and can be universally applied to various cell types in which there is a need to understand protein-protein interactions. Background reductions require 3-5 min per image. Quantifications take <1 min. The entire procedure takes approximately 15-30 min.
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
Chen, Lihua; Liu, Min; Bao, Jing; Xia, Yunbao; Zhang, Jiuquan; Zhang, Lin; Huang, Xuequan; Wang, Jian
2013-01-01
To perform a meta-analysis exploring the correlation between the apparent diffusion coefficient (ADC) and tumor cellularity in patients. We searched medical and scientific literature databases for studies discussing the correlation between the ADC and tumor cellularity in patients. Only studies that were published in English or Chinese prior to November 2012 were considered for inclusion. Summary correlation coefficient (r) values were extracted from each study, and 95% confidence intervals (CIs) were calculated. Sensitivity and subgroup analyses were performed to investigate potential heterogeneity. Of 189 studies, 28 were included in the meta-analysis, comprising 729 patients. The pooled r for all studies was -0.57 (95% CI: -0.62, -0.52), indicating notable heterogeneity (Pcorrelation between the ADC and cellularity for brain tumors. There was no notable evidence of publication bias. There is a strong negative correlation between the ADC and tumor cellularity in patients, particularly in the brain. However, larger, prospective studies are warranted to validate these findings in other cancer types.
Ayatollahi, Majid R.; Moazzami, Mostafa
2017-03-01
The digital image correlation (DIC) method is used to obtain the coefficients of higher-order terms in the Williams expansion in a compact tension (CT) specimens made of polymethyl methacrylate (PMMA). The displacement field is determined by the correlation between reference image (i.e., before deformation) and deformed image. The part of displacements resulting from rigid body motion and rotation is eliminated from the displacement field. For a large number of points in the vicinity of the crack tip, an over-determined set of simultaneous linear equations is collected, and by using the fundamental concepts of the least-squares method, the coefficients of the Williams expansion are calculated for pure mode I conditions. The experimental results are then compared with the numerical results calculated by finite element method (FEM). Very good agreement is shown to exist between the DIC and FE results confirming the effectiveness of the DIC technique in obtaining the coefficients of higher order terms of Williams series expansion from the displacement field around the crack tip.
Correlation and path coefficient analysis for yield and its components in vegetable soybean
Teerawat Sarutayophat
2012-07-01
Full Text Available The associations of yield and its components offer important information in breeding plants. A study was conductedat the experimental field of the Faculty of Agricultural Technology, King Mongkut’s Institute of Technology Ladkrabang,Bangkok on 22 genotypes of the vegetable soybean to determine the association of yield and its components. The associationwas analyzed by correlation coefficient, and further subjected by path coefficient analysis to estimate direct and indirecteffects of each character on pod yield. Positive and significant correlation were found between the plant height and numberof marketable pods/plant (0.821**, plant height and marketable pod yield (0.520*, and number of marketable pods/plant andmarketable pod yield (0.822**. Negative and significance was determined between the plant height and green pod weight(-0.620**, and number of marketable pods/plant and green pod weight (-0.588**. Direct effects of the number of marketablepods/plant and green pod weight on marketable pod yield were positive and significant with path coefficients of 1.310** and0.707**, respectively. Indirect effect of the plant height on marketable pod yield through its association with number ofmarketable pods/plant was positive and significant (1.075**. The results of this study suggested that the number of marketablepods/plant, green pod weight and plant height were important characters that should be taken into account as selectioncriteria in improving marketable pod yield of the vegetable soybean.
Vahidi, B.; Ghaffarzadeh, N.; Hosseinian, S.H. [Dept. of Electrical Engineering, Amirkabir University of Technology, Tehran (Iran)
2010-09-15
In this paper a new method based on discrete wavelet transform and correlation coefficient is presented for digital differential protection. The algorithm includes offline and online operations. In offline operation, discrete wavelet transform is used to decompose typical three-phase differential currents for inrush current. Then an index is defined and computed. The index is based on the sum of the energy of detail coefficients at level 5 of three-phase differential currents at each half cycle. The online operation consists of capturing the three-phase differential currents using 10 kHz sampling rate, decomposing it by db1. Finally, the inrush current and internal fault is detected based on correlation coefficients of the computed index of pre-stored typical inrush current and a recorded indistinct signal. The effectiveness of the approach is tested using numerous inrush and internal fault currents. Simulations are used to confirm the aptness and the capability of the proposed method to discriminate inrush current from internal fault. (author)
Hladni Nada
2015-01-01
Full Text Available The most important criteria for introducing new confectionary hybrids into the production is high protein yield. Path coefficient analysis was used to obtain information on direct and indirect effects of studied traits (seed oil content, kernel oil content, seed yield, kernel protein content, mass of 1000 seeds, kernel ratio and hull ratio on protein yield. The research was conducted during three vegetation seasons, on 22 experimental confectionary sunflower hybrids created in the breeding program at the Institute of Field and Vegetable Crops. Strong and very strong correlations were found among the largest number of examined traits. A weak negative interdependence was determined between kernel oil content, kernel protein content, mass of 1000 seeds, hull ratio, and protein yield using the analysis of simple correlation coefficients. Positive but weak correlation was determined between protein yield and seed oil content, and kernel ratio. Very strong positive correlation was determined between protein yield and seed yield (0.468**. The seed oil content had a very strong direct negative effect on protein yield (DE=-0.734**. The mass of 1000 seeds had a weak negative direct effect on protein yield. Kernel protein content and kernel oil content demonstrated a weak direct positive effect on protein yield. Path coefficient analysis of protein yield showed a very strong positive direct effect of kernel ratio (DE=1.340**, seed yield (DE=0.657** and hull ratio (DE=0.992*. These findings confirm the effect of seed yield, kernel ratio, and hull ratio on protein yield, and their importance as the selection criteria in confectionary sunflower breeding. [Projekat Ministarstva nauke Republike Srbije, br. 31025: Development of new varieties and production technology improvement of oil crops for different purposes
Cao, Guangxi; He, Cuiting; Xu, Wei
2016-03-01
This study investigates the correlation between weather and agricultural futures markets on the basis of detrended cross-correlation analysis (DCCA) cross-correlation coefficients and q-dependent cross-correlation coefficients. In addition, detrended fluctuation analysis (DFA) is used to measure extreme weather and thus analyze further the effect of this condition on agricultural futures markets. Cross-correlation exists between weather and agricultural futures markets on certain time scales. There are some correlations between temperature and soybean return associated with medium amplitudes. Under extreme weather conditions, weather exerts different influences on different agricultural products; for instance, soybean return is greatly influenced by temperature, and weather variables exhibit no effect on corn return. Based on the detrending moving-average cross-correlation analysis (DMCA) coefficient and DFA regression results are similar to that of DCCA coefficient.
SPSS and SAS programs for comparing Pearson correlations and OLS regression coefficients.
Weaver, Bruce; Wuensch, Karl L
2013-09-01
Several procedures that use summary data to test hypotheses about Pearson correlations and ordinary least squares regression coefficients have been described in various books and articles. To our knowledge, however, no single resource describes all of the most common tests. Furthermore, many of these tests have not yet been implemented in popular statistical software packages such as SPSS and SAS. In this article, we describe all of the most common tests and provide SPSS and SAS programs to perform them. When they are applicable, our code also computes 100 × (1 - α)% confidence intervals corresponding to the tests. For testing hypotheses about independent regression coefficients, we demonstrate one method that uses summary data and another that uses raw data (i.e., Potthoff analysis). When the raw data are available, the latter method is preferred, because use of summary data entails some loss of precision due to rounding.
Dong, Shiqing; You, Minghai; Chen, Jianling; Zhou, Jie; Xie, Shusen; Yang, Hongqin
2017-06-01
The fluidity of proteins and lipids on cell membrane plays an important role in cell’s physiological functions. Fluorescence correlation spectroscopy (FCS) is an effective technique to detect the rapid dynamic behaviors of proteins and/or lipids in living cells. In this study, we used the rhodamine6G solution to optimize the FCS system. And, cholera toxin B subunit (CT-B) was used to label ganglioside on living Hela cell membranes. The diffusion time and coefficients of ganglioside can be obtained through fitting the autocorrelation curve based on the model of two-dimensional cell membrane. The results showed that the diffusion coefficients of ganglioside distributed within a wide range. It revealed the lateral diffusion of lipids on cell membrane was inhomogeneous, which was due to different microstructures of cytoplasmic membrane. The study provides a helpful method for further studying the dynamic characteristics of proteins and lipids molecules on living cell membrane.
Liu, Jian; Miller, William H.
2008-08-01
The maximum entropy analytic continuation (MEAC) method is used to extend the range of accuracy of the linearized semiclassical initial value representation (LSC-IVR)/classical Wigner approximation for real time correlation functions. The LSC-IVR provides a very effective 'prior' for the MEAC procedure since it is very good for short times, exact for all time and temperature for harmonic potentials (even for correlation functions of nonlinear operators), and becomes exact in the classical high temperature limit. This combined MEAC+LSC/IVR approach is applied here to two highly nonlinear dynamical systems, a pure quartic potential in one dimensional and liquid para-hydrogen at two thermal state points (25K and 14K under nearly zero external pressure). The former example shows the MEAC procedure to be a very significant enhancement of the LSC-IVR, for correlation functions of both linear and nonlinear operators, and especially at low temperature where semiclassical approximations are least accurate. For liquid para-hydrogen, the LSC-IVR is seen already to be excellent at T = 25K, but the MEAC procedure produces a significant correction at the lower temperature (T = 14K). Comparisons are also made to how the MEAC procedure is able to provide corrections for other trajectory-based dynamical approximations when used as priors.
Aliya, F; Begum, H; Reddy, M T; Sivaraj, N; Pandravada, S R; Narshimulu, G
2014-05-01
Fifty genotypes of spine gourd (Momordica dioica Roxb.) were evaluated in a randomized block design with two replications at the Vegetable Research Station, Rajendranagar, Hyderabad, Andhra Pradesh, India during kharif, 2012. Correlation and path coefficient analysis were carried out to study the character association and contribution, respectively for twelve quantitative characters namely vine length (m), number of stems per plant, days to first female flower appearance, first female flowering node, days to first fruit harvest, days to last fruit harvest, fruiting period (days), fruit length (cm), fruit width (cm), fruit weight (g), number of fruits per plant and fruit yield per plant (kg) for identification of the potential selection indices. Correlation and path coefficient analyses revealed that fruiting period and number of fruits per plant not only had positively significant correlation with fruit yield but also had positively high direct effect on it and are regarded as the main determinants of fruit yield. Days to first fruit harvest had positively moderate direct effect on fruit yield and its association was negatively significant, days to last fruit harvest had negatively high direct effect on fruit yield and its association was significant positively, hence restricted simultaneous selection can be made for days to first fruit harvest and days to last fruit harvest. The improvement in fruit yield can be effective if selection is based on days to first fruit harvest, days to last fruit harvest, fruiting period and number of fruits per plant.
Correlation coefficient based supervised locally linear embedding for pulmonary nodule recognition.
Wu, Panpan; Xia, Kewen; Yu, Hengyong
2016-11-01
Dimensionality reduction techniques are developed to suppress the negative effects of high dimensional feature space of lung CT images on classification performance in computer aided detection (CAD) systems for pulmonary nodule detection. An improved supervised locally linear embedding (SLLE) algorithm is proposed based on the concept of correlation coefficient. The Spearman's rank correlation coefficient is introduced to adjust the distance metric in the SLLE algorithm to ensure that more suitable neighborhood points could be identified, and thus to enhance the discriminating power of embedded data. The proposed Spearman's rank correlation coefficient based SLLE (SC(2)SLLE) is implemented and validated in our pilot CAD system using a clinical dataset collected from the publicly available lung image database consortium and image database resource initiative (LICD-IDRI). Particularly, a representative CAD system for solitary pulmonary nodule detection is designed and implemented. After a sequential medical image processing steps, 64 nodules and 140 non-nodules are extracted, and 34 representative features are calculated. The SC(2)SLLE, as well as SLLE and LLE algorithm, are applied to reduce the dimensionality. Several quantitative measurements are also used to evaluate and compare the performances. Using a 5-fold cross-validation methodology, the proposed algorithm achieves 87.65% accuracy, 79.23% sensitivity, 91.43% specificity, and 8.57% false positive rate, on average. Experimental results indicate that the proposed algorithm outperforms the original locally linear embedding and SLLE coupled with the support vector machine (SVM) classifier. Based on the preliminary results from a limited number of nodules in our dataset, this study demonstrates the great potential to improve the performance of a CAD system for nodule detection using the proposed SC(2)SLLE. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Frontal Face Detection using Haar Wavelet Coefficients and Local Histogram Correlation
Iwan Setyawan
2011-12-01
Full Text Available Face detection is the main building block on which all automatic systems dealing with human faces is built. For example, a face recognition system must rely on face detection to process an input image and determine which areas contain human faces. These areas then become the input for the face recognition system for further processing. This paper presents a face detection system designed to detect frontal faces. The system uses Haar wavelet coefficients and local histogram correlation as differentiating features. Our proposed system is trained using 100 training images. Our experiments show that the proposed system performed well during testing, achieving a detection rate of 91.5%.
Pradhan, Snigdhendubala; Boernick, Hilmar; Kumar, Pradeep; Mehrotra, Indu
2016-07-15
The correlation between octanol-water partition coefficient (KOW) and the transport of aqueous samples containing single organic compound is well documented. The concept of the KOW of river water containing the mixture of organics was evolved by Pradhan et al. (2015). The present study aims at determining the KOW and sorption parameters of synthetic aqueous samples and river water to finding out the correlation, if any. The laboratory scale columns packed with aquifer materials were fed with synthetic and river water samples. Under the operating conditions, the compounds in the samples did not separate, and all the samples that contain more than one organic compound yielded a single breakthrough curve. Breakthrough curves simulated from sorption isotherms were compared with those from the column runs. The sorption parameters such as retardation factor (Rf), height of mass transfer zone (HMTZ), rate of mass transfer zone (RMTZ), breakpoint column capacity (qb) and maximum column capacity (qx) estimated from column runs, sorption isotherms and models developed by Yoon-Nelson, Bohart-Adam and Thomas were in agreement. The empirical correlations were found between the KOW and sorption parameters. The transport of the organics measured as dissolved organic carbon (DOC) through the aquifer can be predicted from the KOW of the river water and other water samples. The novelty of the study is to measure KOW and to envisage the fate of the DOC of the river water, particularly during riverbank filtration. Statistical analysis of the results revealed a fair agreement between the observed and computed values.
Source Function Determined from HBT Correlations by the Maximum Entropy Principle
Yuan Fang Wei; Yuanfang, Wu; Heinz, Ulrich
1996-01-01
We study the reconstruction of the source function in space-time directly from the measured HBT correlation function using the Maximum Entropy Principle. We find that the problem is ill-defined without at least one additional theoretical constraint as input. Using the requirement of a finite source lifetime for the latter we find a new Gaussian parametrization of the source function directly in terms of the measured HBT radius parameters and its lifetime, where the latter is a free parameter which is not directly measurable by HBT. We discuss the implications of our results for the remaining freedom in building source models consistent with a given set of measured HBT radius parameters.
Source Function Determined from Hanbury-Brown/Twiss Correlations by the Maximum Entropy Principle
吴元芳; 刘连寿
2002-01-01
We study the reconstruction of the source function in space-time directly from the measured Hanbury-Brown/Twiss (HBT) correlation function using the maximum entropy principle. We find that the problem is ill-defined without at least one additional theoretical constraint as input. Using the requirement of a finite source lifetime for the problem we find a new Gaussian parametrization of the source function directly in terms of the measured HBT radius parameters and its lifetime, where the latter is a free parameter which is not directly measurable by HBT.We discuss the implications of our results for the remaining freedom in building source models consistent with a given set of measured HBT radius parameters.
Sun, Xuelian; Liu, Zixian
2016-02-01
In this paper, a new estimator of correlation matrix is proposed, which is composed of the detrended cross-correlation coefficients (DCCA coefficients), to improve portfolio optimization. In contrast to Pearson's correlation coefficients (PCC), DCCA coefficients acquired by the detrended cross-correlation analysis (DCCA) method can describe the nonlinear correlation between assets, and can be decomposed in different time scales. These properties of DCCA make it possible to improve the investment effect and more valuable to investigate the scale behaviors of portfolios. The minimum variance portfolio (MVP) model and the Mean-Variance (MV) model are used to evaluate the effectiveness of this improvement. Stability analysis shows the effect of two kinds of correlation matrices on the estimation error of portfolio weights. The observed scale behaviors are significant to risk management and could be used to optimize the portfolio selection.
Koral, Korgün; Mathis, Derek; Gimi, Barjor; Gargan, Lynn; Weprin, Bradley; Bowers, Daniel C; Margraf, Linda
2013-08-01
To test whether there is correlation between cell densities and apparent diffusion coefficient (ADC) metrics of common pediatric cerebellar tumors. This study was reviewed for issues of patient safety and confidentiality and was approved by the Institutional Review Board of the University of Texas Southwestern Medical Center and was compliant with HIPAA. The need for informed consent was waived. Ninety-five patients who had preoperative magnetic resonance imaging and surgical pathologic findings available between January 2003 and June 2011 were included. There were 37 pilocytic astrocytomas, 34 medulloblastomas (23 classic, eight desmoplastic-nodular, two large cell, one anaplastic), 17 ependymomas (13 World Health Organization [WHO] grade II, four WHO grade III), and seven atypical teratoid rhabdoid tumors. ADCs of solid tumor components and normal cerebellum were measured. Tumor-to-normal brain ADC ratios (hereafter, ADC ratio) were calculated. The medulloblastomas and ependymomas were subcategorized according to the latest WHO classification, and tumor cellularity was calculated. Correlation was sought between cell densities and mean tumor ADCs, minimum tumor ADCs, and ADC ratio. When all tumors were considered together, negative correlation was found between cellularity and mean tumor ADCs (ρ = -0.737, P correlation between cellularity and ADC ratio. Negative correlation was found between cellularity and minimum tumor ADC in atypical teratoid rhabdoid tumors (ρ = -0.786, P correlation was found between cellularity and mean tumor ADC and ADC ratio. There was no correlation between the ADC metrics and cellularity of the pilocytic astrocytomas, medulloblastomas, and ependymomas. Negative correlation was found between cellularity and ADC metrics of common pediatric cerebellar tumors. Although ADC metrics are useful in the preoperative diagnosis of common pediatric cerebellar tumors and this utility is generally attributed to differences in cellularity of tumors
Systematic bias of correlation coefficient may explain negative accuracy of genomic prediction.
Zhou, Yao; Vales, M Isabel; Wang, Aoxue; Zhang, Zhiwu
2017-09-01
Accuracy of genomic prediction is commonly calculated as the Pearson correlation coefficient between the predicted and observed phenotypes in the inference population by using cross-validation analysis. More frequently than expected, significant negative accuracies of genomic prediction have been reported in genomic selection studies. These negative values are surprising, given that the minimum value for prediction accuracy should hover around zero when randomly permuted data sets are analyzed. We reviewed the two common approaches for calculating the Pearson correlation and hypothesized that these negative accuracy values reflect potential bias owing to artifacts caused by the mathematical formulas used to calculate prediction accuracy. The first approach, Instant accuracy, calculates correlations for each fold and reports prediction accuracy as the mean of correlations across fold. The other approach, Hold accuracy, predicts all phenotypes in all fold and calculates correlation between the observed and predicted phenotypes at the end of the cross-validation process. Using simulated and real data, we demonstrated that our hypothesis is true. Both approaches are biased downward under certain conditions. The biases become larger when more fold are employed and when the expected accuracy is low. The bias of Instant accuracy can be corrected using a modified formula. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Dunning, David; Helzer, Erik G
2014-03-01
Zell and Krizan (2014, this issue) provide a comprehensive yet incomplete portrait of the factors influencing accurate self-assessment. This is no fault of their own. Much work on self-accuracy focuses on the correlation coefficient as the measure of accuracy, but it is not the only way self-accuracy can be measured. As such, its use can provide an incomplete and potentially misleading story. We urge researchers to explore measures of bias as well as correlation, because there are indirect hints that each respond to a different psychological dynamic. We further entreat researchers to develop other creative measures of accuracy and not to forget that self-accuracy may come not only from personal knowledge but also from insight about human nature more generally.
Correlation of apparent diffusion coefficient with Ki-67 proliferation index in grading meningioma.
Tang, Yi; Dundamadappa, Sathish K; Thangasamy, Senthur; Flood, Thomas; Moser, Richard; Smith, Thomas; Cauley, Keith; Takhtani, Deepak
2014-06-01
A noninvasive method to predict aggressiveness of high-grade meningiomas would be desirable because it would help anticipate tumor recurrence and improve tumor management and the treatment outcomes. The Ki-67 protein is a marker of tumor proliferation, and apparent diffusion coefficient (ADC) is related to tumor cellularity. Therefore, we sought to determine whether there is a statistically significant correlation between ADC and Ki-67 values in meningiomas and whether ADC values can differentiate various meningioma subtypes. MRI examinations and histopathology of 68 surgically treated meningiomas were retrospectively reviewed. Mean ADC values were derived from diffusion imaging. Correlation coefficients were calculated for mean ADC and Ki-67 proliferation index values using linear regression. An independent unpaired Student t test was used to compare the ADC and Ki-67 proliferation index values from low-grade and more aggressive meningiomas. A statistically significant inverse correlation was found between ADC and Ki-67 proliferation index for low-grade and aggressive meningiomas (r(2) = -0.33, p = 0.0039). ADC values (± SD) of low-grade meningiomas (0.84 ± 0.14 × 10(-3) mm(2)/s) and aggressive (atypical or anaplastic) meningiomas (0.75 ± 0.03 × 10(-3) mm(2)/s) were significantly different (p = 0.0495). Using an ADC cutoff value of 0.70 × 10(-3) mm(2)/s, the sensitivity for diagnosing aggressive meningiomas was 29%, specificity was 94%, positive predictive value was 67%, and negative predictive value was 75%. ADC values correlate inversely with Ki-67 proliferation index and help differentiate low-grade from aggressive meningiomas.
Chaumongkol, Y.
2001-11-01
Full Text Available A study of correlation, path coefficient analysis and heritablity for some agronomic characters of oil palm was investigated during February 1998 to January 2002. The oil palm population used in this experiment was derived from F1 tenera hybrids which were collected from various oil palm plantations in Southern Thailand. One good performance bunch (i.e., big bunch, thin shell was selected from each plantation and four to six seeds per selected bunch were used for cultivation. One thousand thirty eight plants were grown at Klong Hoi Khong Research Station, Faculty of Natural Resources, Prince of Songkla University, Songkhla, in 1989. Forty five palms consisted of Dura, Tenera and Pisifera types with 18, 18 and 9 plants respectively, were selected by randomization and tagged for investigation. The oil palm bunch yield and yield component characters were observed from individual palm for 4 years (February 1998 to January 2002. The bunch composition characters were analysed from a single bunch of each palm, sampled between June to October 1999. The results showed that in F2 plants of oil palm, the correlation and the path coefficient between characters relating to oil yield and %oil/bunch varied according to oil palm types (Dura, Tenera and Pisifera. In Dura and Tenera palms, the characters which gave highly positive correlation with a large direct and indirect positive effects on oil yield and %oil/bunch were total bunch weight, %oil/bunch, %fruit/bunch and %oil/fruit. In case of Pisifera palms, the characters which gave highly positive correlation with a large direct and indirect positive effects on oil yield and %oil/bunch were total bunch weight, number of bunches, single bunch weight, %oil/bunch and %fruit/bunch. However, from all investigated characters in F2 plants, only %mesocarp/fruit, %oil/fruit and %fruit/bunch showed the high values of broad sense heritabilities.
Yamanaka, Kota; Hirata, Shinnosuke; Hachiya, Hiroyuki
2016-07-01
Ultrasonic distance measurement for obstacles has been recently applied in automobiles. The pulse-echo method based on the transmission of an ultrasonic pulse and time-of-flight (TOF) determination of the reflected echo is one of the typical methods of ultrasonic distance measurement. Improvement of the signal-to-noise ratio (SNR) of the echo and the avoidance of crosstalk between ultrasonic sensors in the pulse-echo method are required in automotive measurement. The SNR of the reflected echo and the resolution of the TOF are improved by the employment of pulse compression using a maximum-length sequence (M-sequence), which is one of the binary pseudorandom sequences generated from a linear feedback shift register (LFSR). Crosstalk is avoided by using transmitted signals coded by different M-sequences generated from different LFSRs. In the case of lower-order M-sequences, however, the number of measurement channels corresponding to the pattern of the LFSR is not enough. In this paper, pulse compression using linear-frequency-modulated (LFM) signals coded by M-sequences has been proposed. The coding of LFM signals by the same M-sequence can produce different transmitted signals and increase the number of measurement channels. In the proposed method, however, the truncation noise in autocorrelation functions and the interference noise in cross-correlation functions degrade the SNRs of received echoes. Therefore, autocorrelation properties and cross-correlation properties in all patterns of combinations of coded LFM signals are evaluated.
Atefeh Goshvarpour
2012-04-01
Full Text Available Meditation is a practice of concentrated focus upon the breath in order to still the mind. In this paper we have investigated an algorithm to classify rest and meditation, by processing of electroencephalogram (EEG signals through the Wavelet and nonlinear methods. For this purpose, two types of EEG time series (before, and during meditation of 25 healthy women are collected in the meditation clinic in Mashhad. Correlation dimension and Wavelet coefficients at the forth decomposition level of EEG signals in Fz, Cz and Pz are extracted and used as an input of different classifiers. In order to evaluate performance of the classifiers, the classification accuracies and mean square error (MSE of the classifiers were examined. The results show that the Fisher discriminant and Parzen classifier trained on both composite features obtain higher accuracy than that of the others. The total classification accuracy of the Fisher discriminant and Parzen classifier applying Wavelet coefficients was 85.02% and 84.75%, respectively which is raised to 92.37% in both classifiers using Correlation dimensions.
Shou, H; Eloyan, A; Lee, S; Zipunnikov, V; Crainiceanu, A N; Nebel, N B; Caffo, B; Lindquist, M A; Crainiceanu, C M
2013-12-01
This article proposes the image intraclass correlation (I2C2) coefficient as a global measure of reliability for imaging studies. The I2C2 generalizes the classic intraclass correlation (ICC) coefficient to the case when the data of interest are images, thereby providing a measure that is both intuitive and convenient. Drawing a connection with classical measurement error models for replication experiments, the I2C2 can be computed quickly, even in high-dimensional imaging studies. A nonparametric bootstrap procedure is introduced to quantify the variability of the I2C2 estimator. Furthermore, a Monte Carlo permutation is utilized to test reproducibility versus a zero I2C2, representing complete lack of reproducibility. Methodologies are applied to three replication studies arising from different brain imaging modalities and settings: regional analysis of volumes in normalized space imaging for characterizing brain morphology, seed-voxel brain activation maps based on resting-state functional magnetic resonance imaging (fMRI), and fractional anisotropy in an area surrounding the corpus callosum via diffusion tensor imaging. Notably, resting-state fMRI brain activation maps are found to have low reliability, ranging from .2 to .4. Software and data are available to provide easy access to the proposed methods.
Cipolla, Valentina, E-mail: valentina.cipolla@yahoo.it [Department of Radiological Sciences, University of Rome “Sapienza”, Viale del Policlinico 155, 00161 Rome (Italy); Santucci, Domiziana; Guerrieri, Daniele; Drudi, Francesco Maria [Department of Radiological Sciences, University of Rome “Sapienza”, Viale del Policlinico 155, 00161 Rome (Italy); Meggiorini, Maria Letizia [Department of Gynaecological Sciences, University of Rome “Sapienza”, Viale del Policlinico 155, 00161 Rome (Italy); Felice, Carlo de [Department of Radiological Sciences, University of Rome “Sapienza”, Viale del Policlinico 155, 00161 Rome (Italy)
2014-12-15
Highlights: • Apparent diffusion coefficient is a quantitative parameter which reflects molecular water movement. • Grading is an independent prognostic factor which correlates with other histopathological features. • Apparent diffusion coefficient values were significantly different between G1 and G3 classes. - Abstract: Purpose: The aim of this study was to evaluate whether the apparent diffusion coefficient (ADC) provided by 3.0 T (3 T) magnetic resonance diffusion-weighted imaging (DWI) varied according to the grading of invasive breast carcinoma. Materials and methods: A total of 92 patients with 96 invasive breast cancer lesions were enrolled; all had undergone 3 T magnetic resonance imaging (MRI) for local staging. All lesions were confirmed by histological analysis, and tumor grade was established according to the Nottingham Grading System (NGS). MRI included both dynamic contrast-enhanced and DWI sequences, and ADC value was calculated for each lesion. ADC values were compared with NGS classification using the Mann–Whitney U and the Kruskal–Wallis H tests. Grading was considered as a comprehensive prognostic factor, and Rho Spearman test was performed to determine correlation between grading and tumor size, hormonal receptor status, HER2 expression and Ki67 index. Pearson's Chi square test was carried out to compare grading with the other prognostic factors. Results: ADC values were significantly higher in G1 than in G3 tumors. No significant difference was observed when G1 and G3 were compared with G2. Tumor size, hormonal receptor status, HER2 expression and Ki67 index correlated significantly with grading but there was a significant difference only between G1 and G3 related to the ER and PR status, HER2 expression and Ki67 index. There was no statistically significant difference in lesion size between the two groups. Conclusion: ADC values obtained on 3 T DWI correlated with low-grade (G1) and high-grade (G3) invasive breast carcinoma. 3
Edjabou, Maklawe Essonanawe; Martín-Fernández, Josep Antoni; Scheutz, Charlotte; Astrup, Thomas Fruergaard
2017-09-04
Data for fractional solid waste composition provide relative magnitudes of individual waste fractions, the percentages of which always sum to 100, thereby connecting them intrinsically. Due to this sum constraint, waste composition data represent closed data, and their interpretation and analysis require statistical methods, other than classical statistics that are suitable only for non-constrained data such as absolute values. However, the closed characteristics of waste composition data are often ignored when analysed. The results of this study showed, for example, that unavoidable animal-derived food waste amounted to 2.21±3.12% with a confidence interval of (-4.03; 8.45), which highlights the problem of the biased negative proportions. A Pearson's correlation test, applied to waste fraction generation (kg mass), indicated a positive correlation between avoidable vegetable food waste and plastic packaging. However, correlation tests applied to waste fraction compositions (percentage values) showed a negative association in this regard, thus demonstrating that statistical analyses applied to compositional waste fraction data, without addressing the closed characteristics of these data, have the potential to generate spurious or misleading results. Therefore, ¨compositional data should be transformed adequately prior to any statistical analysis, such as computing mean, standard deviation and correlation coefficients. Copyright © 2017 Elsevier Ltd. All rights reserved.
Khenouchi, H.; Smara, Y.; Migliaccio, M.; Nunziata, F.; Buono, A.
2016-08-01
Sea oil pollution is a matter of great concern since it affects both the environment and human health. Recent studies demonstrated that synthetic aperture radar (SAR) polarimetry is able to provide additional information useful for environmental applications, i. e., oil spill observation. In this context, different approaches based on polarimetric SARs were developed. In this study, a dual-polarimetric feature, namely the modulus of the complex correlation coefficient between the co-polarized channels, is used to discriminate between sea oil spill and weak-damping look-alikes.The proposed approach relies on the fact that high correlation between co-polarized channels is expected over sea surface and weak-damping look- alikes due to the dominant Bragg scattering, while significantly lower correlation is expected over strong-damping oil spills since they are characterized by a no-Bragg scattering behaviour. Experimental results show that the modulus of the complex correlation between the co-polarized chan- nels can be successfully exploited for both the observation of sea oil slicks and their discrimination from weak-damping look-alikes.
Miao, Yonghao; Zhao, Ming; Lin, Jing; Lei, Yaguo
2017-08-01
The extraction of periodic impulses, which are the important indicators of rolling bearing faults, from vibration signals is considerably significance for fault diagnosis. Maximum correlated kurtosis deconvolution (MCKD) developed from minimum entropy deconvolution (MED) has been proven as an efficient tool for enhancing the periodic impulses in the diagnosis of rolling element bearings and gearboxes. However, challenges still exist when MCKD is applied to the bearings operating under harsh working conditions. The difficulties mainly come from the rigorous requires for the multi-input parameters and the complicated resampling process. To overcome these limitations, an improved MCKD (IMCKD) is presented in this paper. The new method estimates the iterative period by calculating the autocorrelation of the envelope signal rather than relies on the provided prior period. Moreover, the iterative period will gradually approach to the true fault period through updating the iterative period after every iterative step. Since IMCKD is unaffected by the impulse signals with the high kurtosis value, the new method selects the maximum kurtosis filtered signal as the final choice from all candidates in the assigned iterative counts. Compared with MCKD, IMCKD has three advantages. First, without considering prior period and the choice of the order of shift, IMCKD is more efficient and has higher robustness. Second, the resampling process is not necessary for IMCKD, which is greatly convenient for the subsequent frequency spectrum analysis and envelope spectrum analysis without resetting the sampling rate. Third, IMCKD has a significant performance advantage in diagnosing the bearing compound-fault which expands the application range. Finally, the effectiveness and superiority of IMCKD are validated by a number of simulated bearing fault signals and applying to compound faults and single fault diagnosis of a locomotive bearing.
Kishimoto, Keiko; Tajima, Shinya; Maeda, Ichiro; Takagi, Masayuki; Ueno, Takahiko; Suzuki, Nao; Nakajima, Yasuo
2016-08-01
Diffusion-weighted imaging (DWI) and the apparent diffusion coefficient (ADC) are widely used for detecting uterine endometrial cancer. The relationships between ADC values and pathological features of endometrial cancer have not yet been established. To investigate whether ADC values of endometrial cancer vary according to histologic tumor cellularity and tumor grade. We retrospectively reviewed 30 pathologically confirmed endometrial cancers. All patients underwent conventional non-enhanced magnetic resonance imaging (MRI) and DWI procedures, and ADC values were calculated. Tumor cellularity was evaluated by counting cancer cells in three high-power ( × 400) fields. The correlation between ADC values and tumor cellularity was assessed using Pearson's correlation coefficient test for statistical analysis. The mean ± standard deviation (SD) ADC value ( ×10(-3) mm(2)/s) of endometrial cancer was 0.85 ± 0.22 (range, 0.55-1.71). The mean ± SD tumor cellularity was 528.36 ± 16.89 (range, 298.0-763.6). ADC values were significantly inversely correlated with tumor cellularity. No significant relationship was observed between ADC values and tumor grade (mean ADC values: G1, 0.88 ± 0.265 × 10(-3) mm(2)/s; G2, 0.80 ± 0.178 × 10(-3) mm(2)/s; G3, 0.81 ± 0.117 × 10(-3) mm(2)/s). There is a significant inverse relationship between ADC values and tumor cellularity in endometrial cancer. No significant differences in average ADC value were observed between G1, G2, and G3 tumors. However, the lower the tumor grade, the wider the SD. © The Foundation Acta Radiologica 2015.
Zhao, Qile; Guo, Jing; Hu, Zhigang; Shi, Chuang; Liu, Jingnan; Cai, Hua; Liu, Xianglin
2011-05-01
The GRACE (Gravity Recovery And Climate Experiment) monthly gravity models have been independently produced and published by several research institutions, such as Center for Space Research (CSR), GeoForschungsZentrum (GFZ), Jet Propulsion Laboratory (JPL), Centre National d’Etudes Spatiales (CNES) and Delft Institute of Earth Observation and Space Systems (DEOS). According to their processing standards, above institutions use the traditional variational approach except that the DEOS exploits the acceleration approach. The background force models employed are rather similar. The produced gravity field models generally agree with one another in the spatial pattern. However, there are some discrepancies in the gravity signal amplitude between solutions produced by different institutions. In particular, 10%-30% signal amplitude differences in some river basins can be observed. In this paper, we implemented a variant of the traditional variational approach and computed two sets of monthly gravity field solutions using the data from January 2005 to December 2006. The input data are K-band range-rates (KBRR) and kinematic orbits of GRACE satellites. The main difference in the production of our two types of models is how to deal with nuisance parameters. This type of parameters is necessary to absorb low-frequency errors in the data, which are mainly the aliasing and instrument errors. One way is to remove the nuisance parameters before estimating the geopotential coefficients, called NPARB approach in the paper. The other way is to estimate the nuisance parameters and geopotential coefficients simultaneously, called NPESS approach. These two types of solutions mainly differ in geopotential coefficients from degree 2 to 5. This can be explained by the fact that the nuisance parameters and the gravity field coefficients are highly correlated, particularly at low degrees. We compare these solutions with the official and published ones by means of spectral analysis. It is
Schaefer, Andreas; Wenzel, Friedemann
2017-04-01
Subduction zones are generally the sources of the earthquakes with the highest magnitudes. Not only in Japan or Chile, but also in Pakistan, the Solomon Islands or for the Lesser Antilles, subduction zones pose a significant hazard for the people. To understand the behavior of subduction zones, especially to identify their capabilities to produce maximum magnitude earthquakes, various physical models have been developed leading to a large number of various datasets, e.g. from geodesy, geomagnetics, structural geology, etc. There have been various studies to utilize this data for the compilation of a subduction zone parameters database, but mostly concentrating on only the major zones. Here, we compile the largest dataset of subduction zone parameters both in parameter diversity but also in the number of considered subduction zones. In total, more than 70 individual sources have been assessed and the aforementioned parametric data have been combined with seismological data and many more sources have been compiled leading to more than 60 individual parameters. Not all parameters have been resolved for each zone, since the data completeness depends on the data availability and quality for each source. In addition, the 3D down-dip geometry of a majority of the subduction zones has been resolved using historical earthquake hypocenter data and centroid moment tensors where available and additionally compared and verified with results from previous studies. With such a database, a statistical study has been undertaken to identify not only correlations between those parameters to estimate a parametric driven way to identify potentials for maximum possible magnitudes, but also to identify similarities between the sources themselves. This identification of similarities leads to a classification system for subduction zones. Here, it could be expected if two sources share enough common characteristics, other characteristics of interest may be similar as well. This concept
Raykov, Tenko; Marcoulides, George A.
2015-01-01
A latent variable modeling procedure that can be used to evaluate intraclass correlation coefficients in two-level settings with discrete response variables is discussed. The approach is readily applied when the purpose is to furnish confidence intervals at prespecified confidence levels for these coefficients in setups with binary or ordinal…
Zhou, Hong; Muellerleile, Paige; Ingram, Debra; Wong, Seok P.
2011-01-01
Intraclass correlation coefficients (ICCs) are commonly used in behavioral measurement and psychometrics when a researcher is interested in the relationship among variables of a common class. The formulas for deriving ICCs, or generalizability coefficients, vary depending on which models are specified. This article gives the equations for…
Zhou, Hong; Muellerleile, Paige; Ingram, Debra; Wong, Seok P.
2011-01-01
Intraclass correlation coefficients (ICCs) are commonly used in behavioral measurement and psychometrics when a researcher is interested in the relationship among variables of a common class. The formulas for deriving ICCs, or generalizability coefficients, vary depending on which models are specified. This article gives the equations for…
Improved efficiency of maximum likelihood analysis of time series with temporally correlated errors
Langbein, John O.
2017-01-01
Most time series of geophysical phenomena have temporally correlated errors. From these measurements, various parameters are estimated. For instance, from geodetic measurements of positions, the rates and changes in rates are often estimated and are used to model tectonic processes. Along with the estimates of the size of the parameters, the error in these parameters needs to be assessed. If temporal correlations are not taken into account, or each observation is assumed to be independent, it is likely that any estimate of the error of these parameters will be too low and the estimated value of the parameter will be biased. Inclusion of better estimates of uncertainties is limited by several factors, including selection of the correct model for the background noise and the computational requirements to estimate the parameters of the selected noise model for cases where there are numerous observations. Here, I address the second problem of computational efficiency using maximum likelihood estimates (MLE). Most geophysical time series have background noise processes that can be represented as a combination of white and power-law noise, 1/fα">1/fα1/fα with frequency, f. With missing data, standard spectral techniques involving FFTs are not appropriate. Instead, time domain techniques involving construction and inversion of large data covariance matrices are employed. Bos et al. (J Geod, 2013. doi:10.1007/s00190-012-0605-0) demonstrate one technique that substantially increases the efficiency of the MLE methods, yet is only an approximate solution for power-law indices >1.0 since they require the data covariance matrix to be Toeplitz. That restriction can be removed by simply forming a data filter that adds noise processes rather than combining them in quadrature. Consequently, the inversion of the data covariance matrix is simplified yet provides robust results for a wider range of power-law indices.
Improved efficiency of maximum likelihood analysis of time series with temporally correlated errors
Langbein, John
2017-02-01
Most time series of geophysical phenomena have temporally correlated errors. From these measurements, various parameters are estimated. For instance, from geodetic measurements of positions, the rates and changes in rates are often estimated and are used to model tectonic processes. Along with the estimates of the size of the parameters, the error in these parameters needs to be assessed. If temporal correlations are not taken into account, or each observation is assumed to be independent, it is likely that any estimate of the error of these parameters will be too low and the estimated value of the parameter will be biased. Inclusion of better estimates of uncertainties is limited by several factors, including selection of the correct model for the background noise and the computational requirements to estimate the parameters of the selected noise model for cases where there are numerous observations. Here, I address the second problem of computational efficiency using maximum likelihood estimates (MLE). Most geophysical time series have background noise processes that can be represented as a combination of white and power-law noise, 1/f^{α } with frequency, f. With missing data, standard spectral techniques involving FFTs are not appropriate. Instead, time domain techniques involving construction and inversion of large data covariance matrices are employed. Bos et al. (J Geod, 2013. doi: 10.1007/s00190-012-0605-0) demonstrate one technique that substantially increases the efficiency of the MLE methods, yet is only an approximate solution for power-law indices >1.0 since they require the data covariance matrix to be Toeplitz. That restriction can be removed by simply forming a data filter that adds noise processes rather than combining them in quadrature. Consequently, the inversion of the data covariance matrix is simplified yet provides robust results for a wider range of power-law indices.
Improved efficiency of maximum likelihood analysis of time series with temporally correlated errors
Langbein, John
2017-08-01
Most time series of geophysical phenomena have temporally correlated errors. From these measurements, various parameters are estimated. For instance, from geodetic measurements of positions, the rates and changes in rates are often estimated and are used to model tectonic processes. Along with the estimates of the size of the parameters, the error in these parameters needs to be assessed. If temporal correlations are not taken into account, or each observation is assumed to be independent, it is likely that any estimate of the error of these parameters will be too low and the estimated value of the parameter will be biased. Inclusion of better estimates of uncertainties is limited by several factors, including selection of the correct model for the background noise and the computational requirements to estimate the parameters of the selected noise model for cases where there are numerous observations. Here, I address the second problem of computational efficiency using maximum likelihood estimates (MLE). Most geophysical time series have background noise processes that can be represented as a combination of white and power-law noise, 1/f^{α } with frequency, f. With missing data, standard spectral techniques involving FFTs are not appropriate. Instead, time domain techniques involving construction and inversion of large data covariance matrices are employed. Bos et al. (J Geod, 2013. doi: 10.1007/s00190-012-0605-0) demonstrate one technique that substantially increases the efficiency of the MLE methods, yet is only an approximate solution for power-law indices >1.0 since they require the data covariance matrix to be Toeplitz. That restriction can be removed by simply forming a data filter that adds noise processes rather than combining them in quadrature. Consequently, the inversion of the data covariance matrix is simplified yet provides robust results for a wider range of power-law indices.
Trier, A.; Cabrini, N.; Ferrer, J. [Facultad de Ciencia, Universidad de Santiago de Chile, Santiago 2 (Chile); Olaeta, I. [SESMA, Santiago 1 (Chile)
1997-07-01
Total horizontal atmospheric light extinction coefficients as well as particle mass concentrations have been measured in downtown areas of Santiago de Chile, a heavily polluted city. Measurement campaigns were carried out in 1994 in 1995. Extinction measurements were made by a telephotometric technique in four wavelength bands; oscillating mass balance type instruments were used to measure PM2.5 and PM10 mass concentrations. The latter type instrument had not been available heretofore. The extensive continuous PM2.5 measurements are the first for this city. Strong and highly significant statistical correlations were found between extinction coefficients and mass concentrations, especially with the fine respirable or PM2.5 mass concentrations. Angstrom exponents and, in one case, mass extinction coefficients have been estimated. [Spanish] Se ha medido coeficientes atmosfericos totales horizontales de extincion de luz asi como concentraciones de masa de particulas atmosfericas en zonas centricas de Santiago de Chile, una ciudad altamente contaminada. Las campanas de medicion se han hecho en 1994 y en 1995. Las mediciones de extincion se han hecho por un metodo telefotometrico en cuatro bandas espectrales; las concentraciones de masa PM2.5 y PM10 se han medido con instrumentos del tipo de balanzas de masa oscilantes. Tales instrumentos no han estado disponibles durante trabajos anteriores. Las extensas mediciones continuas de concentraciones de masa PM2.5 son las primeras para Santiago de Chile. Se han encontrado fuertes correlaciones estadisticas, altamente significativas, entre coeficientes de extincion y concentraciones de masa, especialmente las concentraciones de particulas finas respirables PM2.5. Se han estimado tambien exponentes de Angstrom y, en un caso, coeficientes masicos de extincion.
Kim, Mimi; Kang, Tae Wook; Kim, Young Kon; Kim, Seong Hyun; Kwon, Wooil; Ha, Sang Yun; Ji, Sang A
2016-03-01
To evaluate the correlation between grade of pancreatic neuroendocrine tumours (pNETs) based on the 2010 World Health Organization (WHO) classification and the apparent diffusion coefficient (ADC), and to assess whether the ADC value and WHO classification can predict recurrence-free survival (RFS) after surgery for pNETs. This retrospective study was approved by the Institutional Review Board. The requirement for informed consent was waived. Between March 2009 and November 2014, forty-nine patients who underwent magnetic resonance (MR) imaging with diffusion-weighted image and subsequent surgery for single pNETs were included. Correlations among qualitative MR imaging findings, quantitative ADC values, and WHO classifications were assessed. An ordered logistic regression test was used to control for tumour size as a confounding factor. The association between ADC value (or WHO classification) and RFS was analysed. All tumors (n=49) were classified as low- (n=29, grade 1), intermediate- (n=17, grade 2), and high-grade (n=3, grade 3), respectively. The mean ADC of pNETs was moderately negatively correlated with WHO classification before and after adjustment for tumour size (ρ=-0.64, pcorrelated with WHO tumour grade, regardless of tumour size. However, the WHO tumour classification of pNET may be more suitable for predicting RFS than the ADC value. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Tao, Kai; Grand, Stephen P.; Niu, Fenglin
2017-09-01
In seismic full-waveform inversion (FWI), the choice of misfit function determines what information in data is used and ultimately affects the resolution of the inverted images of the Earth's structure. Misfit functions based on traveltime have been successfully applied in global and regional tomographic studies. However, wave propagation through the upper mantle results in multiple phases arriving at a given receiver in a narrow time interval resulting in complicated waveforms that evolve with distance. To extract waveform information as well as traveltime, we use a misfit function based on the normalized correlation coefficient (CC). This misfit function is able to capture the waveform complexities in both phase and relative amplitude within the measurement window. It is also insensitive to absolute amplitude differences between modeled and recorded data, which avoids problems due to uncertainties in source magnitude, radiation pattern, receiver site effects or even miscalibrated instruments. These features make the misfit function based on normalized CC a good candidate to achieve high-resolution images of complex geological structures when interfering phases coexist in the measurement window, such as triplication waveforms. From synthetic tests, we show the advantages of this misfit function over the cross-correlation traveltime misfit function. Preliminary inversion of data from an earthquake in Northeast China images a sharper and stronger amplitude slab stagnant in the middle of the transition zone than FWI of cross-correlation traveltime.
Testing Serial Correlation in Semiparametric Varying-Coefficient Partially Linear EV Models
Xue-mei Hu; Zhi-zhong Wang; Feng Liu
2008-01-01
This paper studies estimation and serial correlation test of a semiparametric varying-coefficient partially linear EV model of the form Y = Xτβ + Zτα(T) + ε,ξ = X + η with the identifying condition E[(ε,ητ)τ] = 0, Cov[(ε,ητ)τ] = σ2Iρ+1. The estimators of interested regression parameters β, and the model error variance σ2, as well as the nonparametric components α(T), are constructed. Under some regular conditions, we show that the estimators of the unknown vector β and the unknown parameter σ2 are strongly consistent and asymptotically normal and that the estimator of α(T) achieves the optimal strong convergence rate of the usual nonparametric regression. Based on these estimators and asymptotic properties, we propose the VN,p test statistic and empirical log-likelihood ratio statistic for testing serial correlation in the model. The proposed statistics are shown to have asymptotic normal or chi-square distributions under the null hypothesis of no serial correlation. Some simulation studies are conducted to illustrate the finite sample performance of the proposed tests.
Tsai, Miao-Yu
2017-04-15
The concordance correlation coefficient (CCC) is a commonly accepted measure of agreement between two observers for continuous responses. This paper proposes a generalized estimating equations (GEE) approach allowing dependency between repeated measurements over time to assess intra-agreement for each observer and inter- and total agreement among multiple observers simultaneously. Furthermore, the indices of intra-, inter-, and total agreement through variance components (VC) from an extended three-way linear mixed model (LMM) are also developed with consideration of the correlation structure of longitudinal repeated measurements. Simulation studies are conducted to compare the performance of the GEE and VC approaches for repeated measurements from longitudinal data. An application of optometric conformity study is used for illustration. In conclusion, the GEE approach allowing flexibility in model assumptions and correlation structures of repeated measurements gives satisfactory results with small mean square errors and nominal 95% coverage rates for large data sets, and when the assumption of the relationship between variances and covariances for the extended three-way LMM holds, the VC approach performs outstandingly well for all sample sizes. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
Spatial correlation in 3D MIMO channels using fourier coefficients of power spectrums
Nadeem, Qurrat-Ul-Ain
2015-03-01
In this paper, an exact closed-form expression for the Spatial Correlation Function (SCF) is derived for the standardized three-dimensional (3D) multiple-input multiple-output (MIMO) channel. This novel SCF is developed for a uniform linear array of antennas with non-isotropic antenna patterns. The proposed method resorts to the spherical harmonic expansion (SHE) of plane waves and the trigonometric expansion of Legendre and associated Legendre polynomials to obtain a closed-form expression for the SCF for arbitrary angular distributions and antenna patterns. The resulting expression depends on the underlying angular distributions and antenna patterns through the Fourier Series (FS) coefficients of power azimuth and elevation spectrums. The novelty of the proposed method lies in the SCF being valid for any 3D propagation environment. Numerical results validate the proposed analytical expression and study the impact of angular spreads on the correlation. The derived SCF will help evaluate the performance of correlated 3D MIMO channels in the future. © 2015 IEEE.
Jia, Feng; Lei, Yaguo; Shan, Hongkai; Lin, Jing
2015-01-01
The early fault characteristics of rolling element bearings carried by vibration signals are quite weak because the signals are generally masked by heavy background noise. To extract the weak fault characteristics of bearings from the signals, an improved spectral kurtosis (SK) method is proposed based on maximum correlated kurtosis deconvolution (MCKD). The proposed method combines the ability of MCKD in indicating the periodic fault transients and the ability of SK in locating these transients in the frequency domain. A simulation signal overwhelmed by heavy noise is used to demonstrate the effectiveness of the proposed method. The results show that MCKD is beneficial to clarify the periodic impulse components of the bearing signals, and the method is able to detect the resonant frequency band of the signal and extract its fault characteristic frequency. Through analyzing actual vibration signals collected from wind turbines and hot strip rolling mills, we confirm that by using the proposed method, it is possible to extract fault characteristics and diagnose early faults of rolling element bearings. Based on the comparisons with the SK method, it is verified that the proposed method is more suitable to diagnose early faults of rolling element bearings. PMID:26610501
The universal coefficient of the exact correlator of a large-$N$ matrix field theory
Katzav, Eytan
2016-01-01
Exact expressions have been proposed for correlation functions of the large-$N$ (planar) limit of the $(1+1)$-dimensional ${\\rm SU}(N)\\times {\\rm SU}(N)$ principal chiral sigma model. These were obtained with the form-factor bootstrap. The short-distance form of the two-point function of the scaling field $\\Phi(x)$, was found to be $N^{-1}\\langle {\\rm Tr}\\,\\Phi(0)^{\\dagger} \\Phi(x)\\rangle=C_{2}\\ln^{2}mx$, where $m$ is the mass gap, in agreement with the perturbative renormalization group. Here we point out that the universal coefficient $C_{2}$, is proportional to the mean first-passage time of a L\\'{e}vy flight in one dimension. This observation enables us to calculate $C_{2}=1/16\\pi$.
Big Macs and Eigenfactor Scores: Don't Let Correlation Coefficients Fool You
West, Jevin; Bergstrom, Carl
2009-01-01
The Eigenfactor Metrics provide an alternative way of evaluating scholarly journals based on an iterative ranking procedure analogous to Google's PageRank algorithm. These metrics have recently been adopted by Thomson-Reuters and are listed alongside the Impact Factor in the Journal Citation Reports. But do these metrics differ sufficiently so as to be a useful addition to the bibliometric toolbox? Davis (2008) has argued otherwise, based on his finding of a 0.95 correlation coefficient between Eigenfactor score and total citations for a sample of journals in the field of medicine. This conclusion is mistaken; here we illustrate the basic statistical fallacy to which Davis succumbed. We provide a complete analysis of the 2006 Journal Citation Reports and demonstrate that there are important differences between the information provided by the Eigenfactor Metrics and that provided by Impact Factor and Total Citations.
Jana Shafi
2016-09-01
Full Text Available In this paper, we discuss project scheduling with conflicting activity-resources. Several project activities require same resources but, may be scheduled with the certain lapse of time resulting in repeatedly using the same kind of resources for executing dissimilar activities. Due to the frequent usage of same resources multiple times, expenditure become more expensive and project duration extends. The problem is to find out such kind of activities which are developing implicit relations amid them. , we proposed a solution by introducing TVs (Transparent view of Scheduling model. First, we analyze and enlists activities according to required resources, categorize them and then we segregate dependent and independent activities by indicating a value. Performing Dependency test on activities by using Pearson's Correlation Coefficient (PCC to calculate the rate of relations among the ordered activities for similar resources. By using this model we can reschedule activities to avoid confusion and disordering of resources without consumption of time and capital.
Abe, Tomomi; Hashimoto, Shuji; Matsumoto, Mitsuharu
2010-02-01
epsilon-filter can reduce most kinds of noise from a single-channel noisy signal while preserving signals that vary drastically such as speech signals. It can reduce not only stationary noise but also nonstationary noise. However, it has some parameters whose values are set empirically. So far, there have been few studies to evaluate the appropriateness of the parameter settings for epsilon-filter. This paper employs the correlation coefficient of the filter output and the difference between the filter input and output as the evaluation function of the parameter setting. This paper also describes the algorithm to set the optimal parameter value of epsilon-filter automatically. To evaluate the adequateness of the obtained parameter, the mean absolute error is calculated. The experimental results show that the adequate parameter in epsilon-filter can be obtained automatically by using the proposed method.
Liu, Xuan; Ramella-Roman, Jessica C; Huang, Yong; Guo, Yuan; Kang, Jin U
2013-01-01
In this study, we propose a generic speckle simulation for optical coherence tomography (OCT) signal, by convolving the point-spread function (PSF) of the OCT system with the numerically synthesized random sample field. We validate our model and use the simulation method to study the statistical properties of cross-correlation coefficients between A-scans, which have been recently applied in transverse motion analysis by our group. The results of simulation show that oversampling is essential for accurate motion tracking; exponential decay of OCT signal leads to an underestimate of motion that can be corrected; lateral heterogeneity of sample leads to an overestimate of motion for a few pixels corresponding to the structural boundary.
Lesion area detection using source image correlation coefficient for CT perfusion imaging.
Fan Zhu; Rodriguez Gonzalez, David; Carpenter, Trevor; Atkinson, Malcolm; Wardlaw, Joanna
2013-09-01
Computer tomography (CT) perfusion imaging is widely used to calculate brain hemodynamic quantities such as cerebral blood flow, cerebral blood volume, and mean transit time that aid the diagnosis of acute stroke. Since perfusion source images contain more information than hemodynamic maps, good utilization of the source images can lead to better understanding than the hemodynamic maps alone. Correlation-coefficient tests are used in our approach to measure the similarity between healthy tissue time-concentration curves and unknown curves. This information is then used to differentiate penumbra and dead tissues from healthy tissues. The goal of the segmentation is to fully utilize information in the perfusion source images. Our method directly identifies suspected abnormal areas from perfusion source images and then delivers a suggested segmentation of healthy, penumbra, and dead tissue. This approach is designed to handle CT perfusion images, but it can also be used to detect lesion areas in magnetic resonance perfusion images.
Liang, Yunyun; Liu, Sanyang; Zhang, Shengli
2016-12-01
Apoptosis, or programed cell death, plays a central role in the development and homeostasis of an organism. Obtaining information on subcellular location of apoptosis proteins is very helpful for understanding the apoptosis mechanism. The prediction of subcellular localization of an apoptosis protein is still a challenging task, and existing methods mainly based on protein primary sequences. In this paper, we introduce a new position-specific scoring matrix (PSSM)-based method by using detrended cross-correlation (DCCA) coefficient of non-overlapping windows. Then a 190-dimensional (190D) feature vector is constructed on two widely used datasets: CL317 and ZD98, and support vector machine is adopted as classifier. To evaluate the proposed method, objective and rigorous jackknife cross-validation tests are performed on the two datasets. The results show that our approach offers a novel and reliable PSSM-based tool for prediction of apoptosis protein subcellular localization.
Haddad Samira M
2012-09-01
Full Text Available Abstract Background The purpose of the study was to evaluate intraclass correlation coefficients (ICC of variables concerning personal characteristics, structure, outcome and process in the Brazilian Network for Surveillance of Severe Maternal Morbidity study conducted to identify severe maternal morbidity/near miss cases using the World Health Organization criteria. Method It was a cross-sectional, multicenter study involving 27 hospitals providing care for pregnant women in Brazil. Cluster size and the mean size of the primary sampling unit were described. Estimated prevalence rates, ICC, their respective 95% confidence intervals, the design effect and the mean cluster size were presented for each variable. Results Overall, 9,555 cases of severe maternal morbidity (woman admitted with potentially life-threatening conditions, near miss events or death were included in the study. ICC ranged from Conclusions These results may be used to design new cluster trials in maternal and perinatal health and to help calculate sample sizes.
Ren, Da-Bing; Yang, Zhao-Hui; Liang, Yi-Zeng; Ding, Qiong; Chen, Chen; Ouyang, Mei-Lan
2013-08-02
Selection of a suitable solvent system is the first and foremost step for a successful counter-current chromatography (CCC) separation. In this paper, a thermodynamic model, nonrandom two-liquid segment activity coefficient model (NRTL-SAC) which uses four types of conceptual segments to describe the effective surface interactions for each solvent and solute molecule, was employed to correlate and predict the partition coefficients (K) of a given compound in a specific solvent system. Then a suitable solvent system was selected according to the predicted partition coefficients. Three solvent system families, heptane/methanol/water, heptane/ethyl acetate/methanol/water (Arizona) and hexane/ethyl acetate/methanol/water, and several solutes were selected to investigate the effectiveness of the NRTL-SAC model for predicting the partition coefficients. Comparison between experimental results and predicted results showed that the NRTL-SAC model is of potential for estimating the K value of a given compound. Also a practical separation case on magnolol and honokiol suggests the NRTL-SAC model is effective, reliable and practical for the purpose of predicting partition coefficients and selecting a suitable solvent system for CCC separation. Copyright © 2013. Published by Elsevier B.V.
Gang-Jin Wang
2013-05-01
Full Text Available We investigate the statistical properties of the foreign exchange (FX network at different time scales by two approaches, namely the methods of detrended cross-correlation coefficient (DCCA coefficient and minimum spanning tree (MST. The daily FX rates of 44 major currencies in the period of 2007–2012 are chosen as the empirical data. Based on the analysis of statistical properties of cross-correlation coefficients, we find that the cross-correlation coefficients of the FX market are fat-tailed. By examining three MSTs at three special time scales (i.e., the minimum, medium, and maximum scales, we come to some conclusions: USD and EUR are confirmed as the predominant world currencies; the Middle East cluster is very stable while the Asian cluster and the Latin America cluster are not stable in the MSTs; the Commonwealth cluster is also found in the MSTs. By studying four evaluation criteria, we find that the MSTs of the FX market present diverse topological and statistical properties at different time scales. The scale-free behavior is observed in the FX network at most of time scales. We also find that most of links in the FX network survive from one time scale to the next.
Inoue, Chie; Fujii, Shinya; Kaneda, Sachi; Fukunaga, Takeru; Kaminou, Toshio; Kigawa, Junzo; Harada, Tasuku; Ogawa, Toshihide
2015-01-01
To correlate the apparent diffusion coefficient (ADC) of endometrioid carcinoma with histological tumor grade and degree of myometrial invasion. 3T diffusion-weighted (DW) magnetic resonance (MR) images of 63 patients were retrospectively reviewed. Two readers measured tumor ADC according to a freehand region of interest (ROI) and a round ROI. Mean and minimum ADCs were correlated with prognostic parameters. The minimum ADC was 0.64 × 10(-3) mm(2)/s for grade 1 (G1, n = 42), 0.62 for grade 2 (G2, n = 14), 0.46 for grade 3 (G3, n = 7) on freehand ROI. There were significant differences between G1 and G3 (P = 0.007), and G2 and G3 (P = 0.038). No significant correlation was found between tumor grade and mean ADC (0.85 for G1, 0.82 for G2, and 0.72 for G3, P = 0.166). The minimum ADC was significantly lower for patients with deep (n = 21, 0.54) than for those with superficial (n = 39, 0.65) myometrial invasion. Conversely, mean ADC did not differ significantly (0.84 for superficial and 0.78 for deep myometrial invasion, P = 0.081). The same tendency was shown on round ROI. The minimum ADC correlates with prognostic parameters of endometrial carcinoma more strongly than mean ADC. Lower minimum ADC is associated with higher histological tumor grade and higher degree of myometrial invasion. © 2013 Wiley Periodicals, Inc.
Stella Crosara Lopes
2009-04-01
Full Text Available The purpose of this study was to evaluate the metal-ceramic bond strength (MCBS of 6 metal-ceramic pairs (2 Ni-Cr alloys and 1 Pd-Ag alloy with 2 dental ceramics and correlate the MCBS values with the differences between the coefficients of linear thermal expansion (CTEs of the metals and ceramics. Verabond (VB Ni-Cr-Be alloy, Verabond II (VB2, Ni-Cr alloy, Pors-on 4 (P, Pd-Ag alloy, and IPS (I and Duceram (D ceramics were used for the MCBS test and dilatometric test. Forty-eight ceramic rings were built around metallic rods (3.0 mm in diameter and 70.0 mm in length made from the evaluated alloys. The rods were subsequently embedded in gypsum cast in order to perform a tensile load test, which enabled calculating the CMBS. Five specimens (2.0 mm in diameter and 12.0 mm in length of each material were made for the dilatometric test. The chromel-alumel thermocouple required for the test was welded into the metal test specimens and inserted into the ceramics. ANOVA and Tukey's test revealed significant differences (p=0.01 for the MCBS test results (MPa, with PI showing higher MCBS (67.72 than the other pairs, which did not present any significant differences. The CTE (10-6 oC-1 differences were: VBI (0.54, VBD (1.33, VB2I (-0.14, VB2D (0.63, PI (1.84 and PD (2.62. Pearson's correlation test (r=0.17 was performed to evaluate of correlation between MCBS and CTE differences. Within the limitations of this study and based on the obtained results, there was no correlation between MCBS and CTE differences for the evaluated metal-ceramic pairs.
Grueneisen, Johannes; Beiderwellen, Karsten; Heusch, Philipp; Buderath, Paul; Aktas, Bahriye; Gratz, Marcel; Forsting, Michael; Lauenstein, Thomas; Ruhlmann, Verena; Umutlu, Lale
2014-01-01
To evaluate a potential correlation of the maximum standard uptake value (SUVmax) and the minimum apparent diffusion coefficient (ADCmin) in primary and recurrent cervical cancer based on integrated PET/MRI examinations. 19 consecutive patients (mean age 51.6 years; range 30-72 years) with histopathologically confirmed primary cervical cancer (n = 9) or suspected tumor recurrence (n = 10) were prospectively enrolled for an integrated PET/MRI examination. Two radiologists performed a consensus reading in random order, using a dedicated post-processing software. Polygonal regions of interest (ROI) covering the entire tumor lesions were drawn into PET/MR images to assess SUVmax and into ADC parameter maps to determine ADCmin values. Pearson's correlation coefficients were calculated to assess a potential correlation between the mean values of ADCmin and SUVmax. In 15 out of 19 patients cervical cancer lesions (n = 12) or lymph node metastases (n = 42) were detected. Mean SUVmax (12.5 ± 6.5) and ADCmin (644.5 ± 179.7 × 10(-5) mm2/s) values for all assessed tumor lesions showed a significant but weak inverse correlation (R = -0.342, p correlation between SUVmax and ADCmin (R = -0.692, p correlation. These initial results of this emerging hybrid imaging technique demonstrate the high diagnostic potential of simultaneous PET/MR imaging for the assessment of functional biomarkers, revealing a significant and strong correlation of tumor metabolism and higher cellularity in cervical cancer lesions.
Kunz, Cornelia U; Stallard, Nigel; Parsons, Nicholas; Todd, Susan; Friede, Tim
2017-03-01
Regulatory authorities require that the sample size of a confirmatory trial is calculated prior to the start of the trial. However, the sample size quite often depends on parameters that might not be known in advance of the study. Misspecification of these parameters can lead to under- or overestimation of the sample size. Both situations are unfavourable as the first one decreases the power and the latter one leads to a waste of resources. Hence, designs have been suggested that allow a re-assessment of the sample size in an ongoing trial. These methods usually focus on estimating the variance. However, for some methods the performance depends not only on the variance but also on the correlation between measurements. We develop and compare different methods for blinded estimation of the correlation coefficient that are less likely to introduce operational bias when the blinding is maintained. Their performance with respect to bias and standard error is compared to the unblinded estimator. We simulated two different settings: one assuming that all group means are the same and one assuming that different groups have different means. Simulation results show that the naïve (one-sample) estimator is only slightly biased and has a standard error comparable to that of the unblinded estimator. However, if the group means differ, other estimators have better performance depending on the sample size per group and the number of groups.
Nykolay Hristov Dyulgerov
2013-12-01
Full Text Available The aim of the present study was to generate information on interrelationships of some important productivity elements, direct and indirect effects of these characters on fruit yield of 1 plant in coriander. The study was conducted in the Institute of Agriculture - Karnobat, during the period 2006-2008 and included 81 coriander accessions. Phenotypic correlations of fruit weight per plant were highly significant and positive with number of branches per plant, number of umbels per plant, number of fruits per 1 umbel, fruit weight per umbel and 1000-fruits weight. Maximum direct contribution to fruit weight per plant was made by 1000-fruits weight, followed by fruit weight per umbel and number of umbels per plant. Therefore, these traits can be used as selection criteria to increase plant yield in coriander.
Cipolla, Valentina; Santucci, Domiziana; Guerrieri, Daniele; Drudi, Francesco Maria; Meggiorini, Maria Letizia; de Felice, Carlo
2014-12-01
The aim of this study was to evaluate whether the apparent diffusion coefficient (ADC) provided by 3.0T (3T) magnetic resonance diffusion-weighted imaging (DWI) varied according to the grading of invasive breast carcinoma. A total of 92 patients with 96 invasive breast cancer lesions were enrolled; all had undergone 3T magnetic resonance imaging (MRI) for local staging. All lesions were confirmed by histological analysis, and tumor grade was established according to the Nottingham Grading System (NGS). MRI included both dynamic contrast-enhanced and DWI sequences, and ADC value was calculated for each lesion. ADC values were compared with NGS classification using the Mann-Whitney U and the Kruskal-Wallis H tests. Grading was considered as a comprehensive prognostic factor, and Rho Spearman test was performed to determine correlation between grading and tumor size, hormonal receptor status, HER2 expression and Ki67 index. Pearson's Chi square test was carried out to compare grading with the other prognostic factors. ADC values were significantly higher in G1 than in G3 tumors. No significant difference was observed when G1 and G3 were compared with G2. Tumor size, hormonal receptor status, HER2 expression and Ki67 index correlated significantly with grading but there was a significant difference only between G1 and G3 related to the ER and PR status, HER2 expression and Ki67 index. There was no statistically significant difference in lesion size between the two groups. ADC values obtained on 3T DWI correlated with low-grade (G1) and high-grade (G3) invasive breast carcinoma. 3T ADC may be a helpful tool for identifying high-grade invasive breast carcinoma. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Sarafraz M.M.
2012-01-01
Full Text Available Pool boiling heat transfer coefficient of monoethylene glycol (MEG, diethylene glycol (DEG and water ternary mixtures has been experimentally measured up to heat flux 114 kW/m2 at various volumetric concentrations of MEG and DEG. As expected, heat transfer coefficient was strongly taken as a direct function of heat flux. Existing well-known correlations are shown to be unable to predict the acceptable values for the tested ternary mixtures, particularly at different concentrations of MEG and DEG. Furthermore, a new modified correlation is developed on the basis of the Stephan - Preußer correlation that predicts the values of heat transfer coefficients with absolute average error of about 7% that is reasonable and acceptable values in compare to other existing correlations.
Jun Ye
2013-03-01
Full Text Available A single valued neutrosophic set (SVNS, which is the subclass of a neutrosophic set, can be considered as a powerful tool to express the indeterminate and inconsistent information in the process of decision making. Then, correlation is one of the most broadly applied indices in many fields and also an important measure in data analysis and classification, pattern recognition, decision making and so on. Therefore, we propose another form of correlation coefficient between SVNSs and establish a multiple attribute decision making method using the correlation coefficient of SVNSs under single valued neutrosophic environment. Through the weighted correlation coefficient between each alternative and the ideal alternative, the ranking order of all alternatives can be determined and the best alternative can be easily identified as well. Finally, two illustrative examples are employed to illustrate the actual applications of the proposed decision-making approach.
Shih, I-Lun; Yen, Ruoh-Fang; Chen, Chi-An; Chen, Bang-Bin; Wei, Shwu-Yuan; Chang, Wen-Chun; Sheu, Bor-Ching; Cheng, Wen-Fang; Tseng, Yao-Hui; Chen, Xin-Jia; Chen, Chi-Hau; Wei, Lin-Hung; Chiang, Ying-Cheng; Torng, Pao-Ling; Yen, Men-Luh; Shih, Tiffany Ting-Fang
2015-12-01
To evaluate the correlation between maximum standardized uptake value (SUVmax ) and minimum apparent diffusion coefficient (ADCmin ) of endometrial cancer derived from an integrated positron emission tomography / magnetic resonance (PET/MR) system and to determine their correlation with pathological prognostic factors. This prospective study was approved by the Institutional Review Board of the hospital, and informed consent was obtained. Between April and December 2014, 47 consecutive patients with endometrial cancer were enrolled and underwent simultaneous PET/MR examinations before surgery. Thirty-six patients with measurable tumors on PET/MR were included for image analysis. Pearson's correlation coefficient was used to evaluate the correlation between SUVmax and ADCmin of the tumors. The Mann-Whitney U-test was utilized to evaluate relationships between these two imaging biomarkers and pathological prognostic factors. The mean SUVmax and ADCmin were 14.7 ± 7.1 and 0.48 ± 0.13 × 10(-3) mm(2) /s, respectively. A significant inverse correlation was found between SUVmax and ADCmin (r = -0.53; P = 0.001). SUVmax was significantly higher in tumors with advanced stage, deep myometrial invasion, cervical invasion, lymphovascular space involvement, and lymph node metastasis (P correlated and are associated with pathological prognostic factors. © 2015 Wiley Periodicals, Inc.
Turner, Rebecca M; Prevost, A Toby; Thompson, Simon G
2004-04-30
The sample size required for a cluster randomized trial depends on the magnitude of the intracluster correlation coefficient (ICC). The usual sample size calculation makes no allowance for the fact that the ICC is not known precisely in advance. We develop methods which allow for the uncertainty in a previously observed ICC, using a variety of distributional assumptions. Distributions for the power are derived, reflecting this uncertainty. Further, the observed ICC in a future study will not equal its true value, and we consider the impact of this on power. We implement calculations within a Bayesian simulation approach, and provide one simplification that can be performed using simple simulation within spreadsheet software. In our examples, recognizing the uncertainty in a previous ICC estimate decreases expected power, especially when the power calculated naively from the ICC estimate is high. To protect against the possibility of low power, sample sizes may need to be very substantially increased. Recognizing the variability in the future observed ICC has little effect if prior uncertainty has already been taken into account. We show how our method can be extended to the case in which multiple prior ICC estimates are available. The methods presented in this paper can be used by applied researchers to protect against loss of power, or to choose a design which reduces the impact of uncertainty in the ICC. Copyright 2004 John Wiley & Sons, Ltd.
Wang, Jifei; Sun, Meili; Liu, Dawei; Hu, Xiaoshu; Pui, Margaret H; Meng, Quanfei; Gao, Zhenhua
2017-08-01
Background Neoadjuvant chemotherapy has made limb-salvage surgery possible for the patients with osteosarcoma. Diffusion-weighted magnetic resonance imaging (DWI) has been used to monitor chemotherapy response. Purpose To correlate the apparent diffusion coefficient (ADC) values with histopathology subtypes of osteosarcoma after neoadjuvant chemotherapy. Material and Methods Twelve patients with osteoblastic (n = 7), chondroblastic (n = 4), and fibroblastic (n = 1) osteosarcomas underwent post-chemotherapy DWI before limb-salvage surgery. ADCs corresponding to 127 histological tissue samples from the 12 resected specimens were compared to histological features. Results The mean ADC value of non-cartilaginous viable tumor (38/91, ADC = 1.22 ± 0.03 × 10(-3 )mm(2)/s) was significantly ( P 0.05) different between viable cartilaginous tumor and cystic/hemorrhagic necrosis. Conclusion DWI allows assessment of tumor necrosis after neoadjuvant chemotherapy by ADC differences between viable tumor and necrosis in fibroblastic and osteoblastic osteosarcomas whereas viable chondroblastic osteosarcoma has high ADC and cannot be distinguished reliably from necrosis.
Wang, Jianji; Zheng, Nanning
2013-09-01
Fractal image compression (FIC) is an image coding technology based on the local similarity of image structure. It is widely used in many fields such as image retrieval, image denoising, image authentication, and encryption. FIC, however, suffers from the high computational complexity in encoding. Although many schemes are published to speed up encoding, they do not easily satisfy the encoding time or the reconstructed image quality requirements. In this paper, a new FIC scheme is proposed based on the fact that the affine similarity between two blocks in FIC is equivalent to the absolute value of Pearson's correlation coefficient (APCC) between them. First, all blocks in the range and domain pools are chosen and classified using an APCC-based block classification method to increase the matching probability. Second, by sorting the domain blocks with respect to APCCs between these domain blocks and a preset block in each class, the matching domain block for a range block can be searched in the selected domain set in which these APCCs are closer to APCC between the range block and the preset block. Experimental results show that the proposed scheme can significantly speed up the encoding process in FIC while preserving the reconstructed image quality well.
Measuring fMRI reliability with the intra-class correlation coefficient.
Caceres, Alejandro; Hall, Deanna L; Zelaya, Fernando O; Williams, Steven C R; Mehta, Mitul A
2009-04-15
The intra-class class correlation coefficient (ICC) is a prominent statistic to measure test-retest reliability of fMRI data. It can be used to address the question of whether regions of high group activation in a first scan session will show preserved subject differentiability in a second session. With this purpose, we present a method that extends voxel-wise ICC analysis. We show that voxels with high group activation have more probability of being reliable, if a subsequent session is performed, than typical voxels across the brain or across white matter. We also find that the existence of some voxels with high ICC but low group activation can be explained by stable signals across sessions that poorly fit the HRF model. At a region of interest level, we show that our voxel-wise ICC calculation is more robust than previous implementations under variations of smoothing and cluster size. The method also allows formal comparisons between the reliabilities of given brain regions; aimed at establishing which ROIs discriminate best between individuals. The method is applied to an auditory and a verbal working memory task. A reliability toolbox for SPM5 is provided at http://brainmap.co.uk.
Shi, Ming-Guang; Xia, Jun-Feng; Li, Xue-Ling; Huang, De-Shuang
2010-03-01
Identifying protein-protein interactions (PPIs) is critical for understanding the cellular function of the proteins and the machinery of a proteome. Data of PPIs derived from high-throughput technologies are often incomplete and noisy. Therefore, it is important to develop computational methods and high-quality interaction dataset for predicting PPIs. A sequence-based method is proposed by combining correlation coefficient (CC) transformation and support vector machine (SVM). CC transformation not only adequately considers the neighboring effect of protein sequence but describes the level of CC between two protein sequences. A gold standard positives (interacting) dataset MIPS Core and a gold standard negatives (non-interacting) dataset GO-NEG of yeast Saccharomyces cerevisiae were mined to objectively evaluate the above method and attenuate the bias. The SVM model combined with CC transformation yielded the best performance with a high accuracy of 87.94% using gold standard positives and gold standard negatives datasets. The source code of MATLAB and the datasets are available on request under smgsmg@mail.ustc.edu.cn.
Liang, Rong; Zhou, Shu-dong; Li, Li-xia; Zhang, Jun-guo; Gao, Yan-hui
2013-09-01
This paper aims to achieve Bootstraping in hierarchical data and to provide a method for the estimation on confidence interval(CI) of intraclass correlation coefficient(ICC).First, we utilize the mixed-effects model to estimate data from ICC of repeated measurement and from the two-stage sampling. Then, we use Bootstrap method to estimate CI from related ICCs. Finally, the influences of different Bootstraping strategies to ICC's CIs are compared. The repeated measurement instance show that the CI of cluster Bootsraping containing the true ICC value. However, when ignoring the hierarchy characteristics of data, the random Bootsraping method shows that it has the invalid CI. Result from the two-stage instance shows that bias observed between cluster Bootstraping's ICC means while the ICC of the original sample is the smallest, but with wide CI. It is necessary to consider the structure of data as important, when hierarchical data is being resampled. Bootstrapping seems to be better on the higher than that on lower levels.
A Bayesian estimate of the concordance correlation coefficient with skewed data.
Feng, Dai; Baumgartner, Richard; Svetnik, Vladimir
2015-01-01
Concordance correlation coefficient (CCC) is one of the most popular scaled indices used to evaluate agreement. Most commonly, it is used under the assumption that data is normally distributed. This assumption, however, does not apply to skewed data sets. While methods for the estimation of the CCC of skewed data sets have been introduced and studied, the Bayesian approach and its comparison with the previous methods has been lacking. In this study, we propose a Bayesian method for the estimation of the CCC of skewed data sets and compare it with the best method previously investigated. The proposed method has certain advantages. It tends to outperform the best method studied before when the variation of the data is mainly from the random subject effect instead of error. Furthermore, it allows for greater flexibility in application by enabling incorporation of missing data, confounding covariates, and replications, which was not considered previously. The superiority of this new approach is demonstrated using simulation as well as real-life biomarker data sets used in an electroencephalography clinical study. The implementation of the Bayesian method is accessible through the Comprehensive R Archive Network.
Aly, Sharif S; Zhao, Jianyang; Li, Ben; Jiang, Jiming
2014-01-01
The Intraclass Correlation Coefficient (ICC) is commonly used to estimate the similarity between quantitative measures obtained from different sources. Overdispersed data is traditionally transformed so that linear mixed model (LMM) based ICC can be estimated. A common transformation used is the natural logarithm. The reliability of environmental sampling of fecal slurry on freestall pens has been estimated for Mycobacterium avium subsp. paratuberculosis using the natural logarithm transformed culture results. Recently, the negative binomial ICC was defined based on a generalized linear mixed model for negative binomial distributed data. The current study reports on the negative binomial ICC estimate which includes fixed effects using culture results of environmental samples. Simulations using a wide variety of inputs and negative binomial distribution parameters (r; p) showed better performance of the new negative binomial ICC compared to the ICC based on LMM even when negative binomial data was logarithm, and square root transformed. A second comparison that targeted a wider range of ICC values showed that the mean of estimated ICC closely approximated the true ICC.
Sterling, Sarah M; Allgeyer, Edward S; Fick, Jörg; Prudovsky, Igor; Mason, Michael D; Neivandt, David J
2013-06-25
Model cellular membranes enable the study of biological processes in a controlled environment and reduce the traditional challenges associated with live or fixed cell studies. However, model membrane systems based on the air/water or oil/solution interface do not allow for incorporation of transmembrane proteins or for the study of protein transport mechanisms. Conversely, a phospholipid bilayer deposited via the Langmuir-Blodgett/Langmuir-Schaefer method on a hydrogel layer is potentially an effective mimic of the cross section of a biological membrane and facilitates both protein incorporation and transport studies. Prior to application, however, such membranes must be fully characterized, particularly with respect to the phospholipid bilayer phase transition temperature. Here we present a detailed characterization of the phase transition temperature of the inner and outer leaflets of a chitosan supported model membrane system. Specifically, the lateral diffusion coefficient of each individual leaflet has been determined as a function of temperature. Measurements were performed utilizing z-scan fluorescence correlation spectroscopy (FCS), a technique that yields calibration-free diffusion information. Analysis via the method of Wawrezinieck and co-workers revealed that phospholipid diffusion changes from raftlike to free diffusion as the temperature is increased-an insight into the dynamic behavior of hydrogel supported membranes not previously reported.
Mahapatra Rajendra
2011-06-01
Full Text Available Abstract Background Public health interventions are increasingly evaluated using cluster-randomised trials in which groups rather than individuals are allocated randomly to treatment and control arms. Outcomes for individuals within the same cluster are often more correlated than outcomes for individuals in different clusters. This needs to be taken into account in sample size estimations for planned trials, but most estimates of intracluster correlation for perinatal health outcomes come from hospital-based studies and may therefore not reflect outcomes in the community. In this study we report estimates for perinatal health outcomes from community-based trials to help researchers plan future evaluations. Methods We estimated the intracluster correlation and the coefficient of variation for a range of outcomes using data from five community-based cluster randomised controlled trials in three low-income countries: India, Bangladesh and Malawi. We also performed a simulation exercise to investigate the impact of cluster size and number of clusters on the reliability of estimates of the coefficient of variation for rare outcomes. Results Estimates of intracluster correlation for mortality outcomes were lower than those for process outcomes, with narrower confidence intervals throughout for trials with larger numbers of clusters. Estimates of intracluster correlation for maternal mortality were particularly variable with large confidence intervals. Stratified randomisation had the effect of reducing estimates of intracluster correlation. The simulation exercise showed that estimates of intracluster correlation are much less reliable for rare outcomes such as maternal mortality. The size of the cluster had a greater impact than the number of clusters on the reliability of estimates for rare outcomes. Conclusions The breadth of intracluster correlation estimates reported here in terms of outcomes and contexts will help researchers plan future
Wang, Fang
2016-06-01
In order to detect and quantify asymmetry of two time series, a novel cross-correlation coefficient is proposed based on recent asymmetric detrended cross-correlation analysis (A-DXA), which we called A-DXA coefficient. The A-DXA coefficient, as an important extension of DXA coefficient ρDXA, contains two directional asymmetric cross-correlated indexes, describing upwards and downwards asymmetric cross-correlations, respectively. By using the information of directional covariance function of two time series and directional variance function of each series itself instead of power-law between the covariance function and time scale, the proposed A-DXA coefficient can well detect asymmetry between the two series no matter whether the cross-correlation is significant or not. By means of the proposed A-DXA coefficient conducted over the asymmetry for California electricity market, we found that the asymmetry between the prices and loads is not significant for daily average data in 1999 yr market (before electricity crisis) but extremely significant for those in 2000 yr market (during the crisis). To further uncover the difference of asymmetry between the years 1999 and 2000, a modified H statistic (MH) and ΔMH statistic are proposed. One of the present contributions is that the high MH values calculated for hourly data exist in majority months in 2000 market. Another important conclusion is that the cross-correlation with downwards dominates over the whole 1999 yr in contrast to the cross-correlation with upwards dominates over the 2000 yr.
Wang, Fang
2016-06-01
In order to detect and quantify asymmetry of two time series, a novel cross-correlation coefficient is proposed based on recent asymmetric detrended cross-correlation analysis (A-DXA), which we called A-DXA coefficient. The A-DXA coefficient, as an important extension of DXA coefficient ρ D X A , contains two directional asymmetric cross-correlated indexes, describing upwards and downwards asymmetric cross-correlations, respectively. By using the information of directional covariance function of two time series and directional variance function of each series itself instead of power-law between the covariance function and time scale, the proposed A-DXA coefficient can well detect asymmetry between the two series no matter whether the cross-correlation is significant or not. By means of the proposed A-DXA coefficient conducted over the asymmetry for California electricity market, we found that the asymmetry between the prices and loads is not significant for daily average data in 1999 yr market (before electricity crisis) but extremely significant for those in 2000 yr market (during the crisis). To further uncover the difference of asymmetry between the years 1999 and 2000, a modified H statistic (MH) and ΔMH statistic are proposed. One of the present contributions is that the high MH values calculated for hourly data exist in majority months in 2000 market. Another important conclusion is that the cross-correlation with downwards dominates over the whole 1999 yr in contrast to the cross-correlation with upwards dominates over the 2000 yr.
Ma, Wanling; Li, Na; Zhao, Weiwei; Ren, Jing; Wei, Mengqi; Yang, Yong; Wang, Yingmei; Fu, Xin; Zhang, Zhuoli; Larson, Andrew C; Huan, Yi
2016-01-01
To clarify diffusion and perfusion abnormalities and evaluate correlation between apparent diffusion coefficient (ADC), MR perfusion and histopathologic parameters of pancreatic cancer (PC). Eighteen patients with PC underwent diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Parameters of DCE-MRI and ADC of cancer and non-cancerous tissue were compared. Correlation between the rate constant that represents transfer of contrast agent from the arterial blood into the extravascular extracellular space (K, volume of the extravascular extracellular space per unit volume of tissue (Ve), and ADC of PC and histopathologic parameters were analyzed. The rate constant that represents transfer of contrast agent from the extravascular extracellular space into blood plasma, K, tissue volume fraction occupied by vascular space, and ADC of PC were significantly lower than nontumoral pancreases. Ve of PC was significantly higher than that of nontumoral pancreas. Apparent diffusion coefficient and K values of PC were negatively correlated to fibrosis content and fibroblast activation protein staining score. Fibrosis content was positively correlated to Ve. Apparent diffusion coefficient values and parameters of DCE-MRI can differentiate PC from nontumoral pancreases. There are correlations between ADC, K, Ve, and fibrosis content of PC. Fibroblast activation protein staining score of PC is negatively correlated to ADC and K. Apparent diffusion coefficient, K, and Ve may be feasible to predict prognosis of PC.
İsmail Hakkı ERTEN
2008-10-01
Full Text Available This study aims to compare the appropriateness of two statistical procedures for measuring the effectiveness of vocabulary learning strategies: percentages and correlation coefficients. To do this a group of 20 learners of English were asked to study 12 words in a written list, with their pronunciations, dictionary definitions, and example sentences. Data was collected through introspection where students were asked to verbalize their mental processes as they studied the target words. A pre-test and post-test were given to measure the task achievement. The qualitative data was transcribed verbatim and content-analysed for tokens of strategy use as well as by noting whether each use of strategies led to successful recall of the words on which they were used. To calculate the strategy effectiveness, both simple percentage calculation and correlation coefficients were employed for comparison. The findings indicated that percentage calculation can give a more realistic picture of strategy effectiveness than correlation coefficients.
Tehsin, Sara; Rehman, Saad; Awan, Ahmad B.; Chaudry, Qaiser; Abbas, Muhammad; Young, Rupert; Asif, Afia
2016-04-01
Sensitivity to the variations in the reference image is a major concern when recognizing target objects. A combinational framework of correlation filters and logarithmic transformation has been previously reported to resolve this issue alongside catering for scale and rotation changes of the object in the presence of distortion and noise. In this paper, we have extended the work to include the influence of different logarithmic bases on the resultant correlation plane. The meaningful changes in correlation parameters along with contraction/expansion in the correlation plane peak have been identified under different scenarios. Based on our research, we propose some specific log bases to be used in logarithmically transformed correlation filters for achieving suitable tolerance to different variations. The study is based upon testing a range of logarithmic bases for different situations and finding an optimal logarithmic base for each particular set of distortions. Our results show improved correlation and target detection accuracies.
Bahman Navidshad
2012-02-01
Full Text Available The applications of conventional culture-dependent assays to quantify bacteria populations are limited by their dependence on the inconsistent success of the different culture-steps involved. In addition, some bacteria can be pathogenic or a source of endotoxins and pose a health risk to the researchers. Bacterial quantification based on the real-time PCR method can overcome the above-mentioned problems. However, the quantification of bacteria using this approach is commonly expressed as absolute quantities even though the composition of samples (like those of digesta can vary widely; thus, the final results may be affected if the samples are not properly homogenized, especially when multiple samples are to be pooled together before DNA extraction. The objective of this study was to determine the correlation coefficients between four different methods of expressing the output data of real-time PCR-based bacterial quantification. The four methods were: (i the common absolute method expressed as the cell number of specific bacteria per gram of digesta; (ii the Livak and Schmittgen, ΔΔCt method; (iii the Pfaffl equation; and (iv a simple relative method based on the ratio of cell number of specific bacteria to the total bacterial cells. Because of the effect on total bacteria population in the results obtained using ΔCt-based methods (ΔΔCt and Pfaffl, these methods lack the acceptable consistency to be used as valid and reliable methods in real-time PCR-based bacterial quantification studies. On the other hand, because of the variable compositions of digesta samples, a simple ratio of cell number of specific bacteria to the corresponding total bacterial cells of the same sample can be a more accurate method to quantify the population.
Cui, Wansong; Wang, Difeng; Gong, Fang; Bai, Yan; Zhang, Lin; Zhu, Qiankun; Chen, Peng
2016-10-01
The beam attenuation coefficient (c), an inherent optical property of water, can provide information about the particulate matter in the water. In this study, the vertical distribution of the particulate beam attenuation coefficient at 660 nm (cp(660)) and its correlation to the particulate organic carbon (POC) and chlorophyll a (Chl-a) concentrations in the north South China Sea (NSCS), was investigated based on the in situ data from two cruises covering the summer and autumn seasons during 2009-2010year. The results showed that in summer, the profiles of cp(660) at the near shore stations were generally well vertical mixed, except at the bottom layer where cp(660) sharply increased due to sediment resuspension. However, in the slope and basin, the profiles of cp(660) had the peak value in the subsurface layer, and the depth of maximum increased with the increasing of the water depth. The subsurface maximum of the cp(660) was corresponding to the subsurface maximum Chl-a in the shelf and basin in the NSCS in summer. In autumn, the depth profile of cp(660) was also well mixed in the near shore, similar as it in summer. In the basin, unlike the subsurface maximum in summer, cp(660) had the decreasing trend with the increasing of depth in most stations in autumn. The spatial distribution pattern of the surface cp(660) was similar in the two seasons, with high values in near shore and low values in the shelf and basin. This was mainly attributed to the river and terrigenous organic materials. There were good correlations between cp(660) and POC in both seasons, except some near shore stations with high sediment resuspension. That made the possibility of estimating the POC profile using the cp(660), and further calculating the vertical structure with satellite-derived surface POC.
Collett, B; Bateman, F; Bauder, W K; Byrne, J; Byron, W A; Chen, W; Darius, G; DeAngelis, C; Dewey, M S; Gentile, T R; Hassan, M T; Jones, G L; Komives, A; Laptev, A; Mendenhall, M P; Nico, J S; Noid, G; Park, H; Stephenson, E J; Stern, I; Stockton, K J S; Trull, C; Wietfeldt, F E; Yerozolimsky, B G
2017-08-01
We describe an apparatus used to measure the electron-antineutrino angular correlation coefficient in free neutron decay. The apparatus employs a novel measurement technique in which the angular correlation is converted into a proton time-of-flight asymmetry that is counted directly, avoiding the need for proton spectroscopy. Details of the method, apparatus, detectors, data acquisition, and data reduction scheme are presented, along with a discussion of the important systematic effects.
Collett, B.; Bateman, F.; Bauder, W. K.; Byrne, J.; Byron, W. A.; Chen, W.; Darius, G.; DeAngelis, C.; Dewey, M. S.; Gentile, T. R.; Hassan, M. T.; Jones, G. L.; Komives, A.; Laptev, A.; Mendenhall, M. P.; Nico, J. S.; Noid, G.; Park, H.; Stephenson, E. J.; Stern, I.; Stockton, K. J. S.; Trull, C.; Wietfeldt, F. E.; Yerozolimsky, B. G.
2017-08-01
We describe an apparatus used to measure the electron-antineutrino angular correlation coefficient in free neutron decay. The apparatus employs a novel measurement technique in which the angular correlation is converted into a proton time-of-flight asymmetry that is counted directly, avoiding the need for proton spectroscopy. Details of the method, apparatus, detectors, data acquisition, and data reduction scheme are presented, along with a discussion of the important systematic effects.
Christensen, Eva Arnspang; Koffman, Jennifer Skaarup; Marlar, Saw
2014-01-01
Lateral diffusion and compartmentalization of plasma membrane proteins are tightly regulated in cells and thus, studying these processes will reveal new insights to plasma membrane protein function and regulation. Recently, k-Space Image Correlation Spectroscopy (kICS)1 was developed to enable...... to the correlation function yields the diffusion coefficient. This paper provides a step-by-step guide to the image analysis and measurement of diffusion coefficients via kICS. First, a high frame rate image sequence of a fluorescently labeled plasma membrane protein is acquired using a fluorescence microscope Then...... routine measurements of diffusion coefficients directly from images of fluorescently tagged plasma membrane proteins, that avoided systematic biases introduced by probe photophysics. Although the theoretical basis for the analysis is complex, the method can be implemented by nonexperts using a freely...
Shengming Deng
2017-01-01
Full Text Available The objective of this meta-analysis is to explore the correlation between the apparent diffusion coefficient (ADC on diffusion-weighted MR and the standard uptake value (SUV of 18F-FDG on PET/CT in patients with cancer. Databases such as PubMed (MEDLINE included, EMBASE, and Cochrane Database of Systematic Review were searched for relevant original articles that explored the correlation between SUV and ADC in English. After applying Fisher’s r-to-z transformation, correlation coefficient (r values were extracted from each study and 95% confidence intervals (CIs were calculated. Sensitivity and subgroup analyses based on tumor type were performed to investigate the potential heterogeneity. Forty-nine studies were eligible for the meta-analysis, comprising 1927 patients. Pooled r for all studies was −0.35 (95% CI: −0.42–0.28 and exhibited a notable heterogeneity (I2 = 78.4%; P < 0.01. In terms of the cancer type subgroup analysis, combined correlation coefficients of ADC/SUV range from −0.12 (lymphoma, n = 5 to −0.59 (pancreatic cancer, n = 2. We concluded that there is an average negative correlation between ADC and SUV in patients with cancer. Higher correlations were found in the brain tumor, cervix carcinoma, and pancreas cancer. However, a larger, prospective study is warranted to validate these findings in different cancer types.
Pellis, E.P.M.; Franssen-Hal, van N.L.W.; Burema, J.; Keijer, J.
2003-01-01
We show that the intraclass correlation coefficient (ICC) can be used as a relatively simple statistical measure to assess methodological and biological variation in DNA microarray analysis. The ICC is a measure that determines the reproducibility of a variable, which can easily be calculated from a
Jiantian Wang
2012-01-01
This paper studies the relationship between Kendall's tau and Pearson correlation coefficient under the so-called bivariate homogeneous shock (BHS) model. We find Capéraà-Genest-type inequality may not hold for general BHS model. Computational simulations suggest that the Denials' inequality is likely to be true.
Huang, Jing; Ma, Jian-hua; Liu, Nan; Qian, Shan-shan
2010-10-01
We designed a weighted cross-correlation coefficient considering the "anchor" of the T cell epitopes, and used an evolutionary algorithm to search for an optimal weight vector. A SVM model with this new peptide similarity kernel was evaluated on a T-cell data set. The results demonstrated a good performance of this method.
1979-02-15
A simple approximate formula is shown to be remarkably accurate for the determination of the regions of the sequential test for the correlation ... coefficient , rho, when the variates follow a bivariate normal distribution. The approximate results are compared with the exact values and with an
A Maximum Entropy Fixed-Point Route Choice Model for Route Correlation
Louis de Grange
2014-06-01
Full Text Available In this paper we present a stochastic route choice model for transit networks that explicitly addresses route correlation due to overlapping alternatives. The model is based on a multi-objective mathematical programming problem, the optimality conditions of which generate an extension to the Multinomial Logit models. The proposed model considers a fixed point problem for treating correlations between routes, which can be solved iteratively. We estimated the new model on the Santiago (Chile Metro network and compared the results with other route choice models that can be found in the literature. The new model has better explanatory and predictive power that many other alternative models, correctly capturing the correlation factor. Our methodology can be extended to private transport networks.
A new maximum likelihood blood velocity estimator incorporating spatial and temporal correlation
Schlaikjer, Malene; Jensen, Jørgen Arendt
2001-01-01
The blood flow in the human cardiovascular system obeys the laws of fluid mechanics. Investigation of the flow properties reveals that a correlation exists between the velocity in time and space. The possible changes in velocity are limited, since the blood velocity has a continuous profile in time...... of the observations gives a probability measure of the correlation between the velocities. Both the MLE and the STC-MLE have been evaluated on simulated and in-vivo RF-data obtained from the carotid artery. Using the MLE 4.1% of the estimates deviate significantly from the true velocities, when the performance...
Bahrami Hamid Reza
2007-01-01
Full Text Available The ergodic capacity of MIMO frequency-flat and -selective channels depends greatly on the eigenvalue distribution of spatial correlation matrices. Knowing the eigenstructure of correlation matrices at the transmitter is very important to enhance the capacity of the system. This fact becomes of great importance in MIMO wireless systems where because of the fast changing nature of the underlying channel, full channel knowledge is difficult to obtain at the transmitter. In this paper, we first investigate the effect of eigenvalues distribution of spatial correlation matrices on the capacity of frequency-flat and -selective channels. Next, we introduce a practical scheme known as linear precoding that can enhance the ergodic capacity of the channel by changing the eigenstructure of the channel by applying a linear transformation. We derive the structures of precoders using eigenvalue decomposition and linear algebra techniques in both cases and show their similarities from an algebraic point of view. Simulations show the ability of this technique to change the eigenstructure of the channel, and hence enhance the ergodic capacity considerably.
Liao, Chen-Tuo; Lin, Chia-Ying; Liu, Jen-Pei
2007-01-01
Microarray is one of the breakthrough technologies in the twenty-first century. Despite of its great potential, transition and realization of microarray technology into the clinically useful commercial products have not been as rapid as the technology could promise. One of the primary reasons is lack of agreement and poor reproducibility of the intensity measurements on gene expression obtained from microarray experiments. Current practices often use the testing the hypothesis of zero Pearson correlation coefficient to assess the agreement of gene expression levels between the technical replicates from microarray experiments. However, Pearson correlation coefficient is to evaluate linear association between two variables and fail to take into account changes in accuracy and precision. Hence, it is not appropriate for evaluation of agreement of gene expression levels between technical replicates. Therefore, we propose to use the concordance correlation coefficient to assess agreement of gene expression levels between technical replicates. We also apply the Generalized Pivotal Quantities to obtain the exact confidence interval for concordance coefficient. In addition, based on the concept of noninferiority test, a one-sided (1 - alpha) lower confidence limit for concordance correlation coefficient is employed to test the hypothesis that the agreement of expression levels of the same genes between two technical replicates exceeds some minimal requirement of agreement. We conducted a simulation study, under various combinations of mean differences, variability, and sample size, to empirically compare the performance of different methods for assessment of agreement in terms of coverage probability, expected length, size, and power. Numerical data from published papers illustrate the application of the proposed methods.
Kok, S
2012-07-01
Full Text Available is considered in this paper, but the main result of Zimmermann [2] is disproved. 2 Kriging fundamentals A response y(x) is considered to consist of a deterministic contribution f(x) and a stochastic component Z(x), i.e. y(x) = f(x) + Z(x). (1...) and is symmetric by definition. In computer experiment applications, the Gaussian correlation function is particularly popular. In this case, R is given by R(xi, xj) = m? k=1 e??k|x i k?x j k|2 , (4) where m is the number of design variables (i.e...
Principle of Maximum Entanglement Entropy and Local Physics of Strongly Correlated Materials
Lanatà, Nicola [Rutgers University; Strand, Hugo U. R. [University of Gothenburg; Yao, Yongxin [Ames Laboratory; Kotliar, Gabriel [Rutgers University
2014-07-01
We argue that, because of quantum entanglement, the local physics of strongly correlated materials at zero temperature is described in a very good approximation by a simple generalized Gibbs distribution, which depends on a relatively small number of local quantum thermodynamical potentials. We demonstrate that our statement is exact in certain limits and present numerical calculations of the iron compounds FeSe and FeTe and of the elemental cerium by employing the Gutzwiller approximation that strongly support our theory in general.
Yang, Yi; Wang, Tianheng; Biswal, Nrusingh C.; Wang, Xiaohong; Sanders, Melinda; Brewer, Molly; Zhu, Quing
2011-09-01
Optical scattering coefficient from ex vivo unfixed normal and malignant ovarian tissue was quantitatively extracted by fitting optical coherence tomography (OCT) A-line signals to a single scattering model. 1097 average A-line measurements at a wavelength of 1310 nm were performed at 108 sites obtained from 18 ovaries. The average scattering coefficient obtained from the normal tissue group consisted of 833 measurements from 88 sites was 2.41 mm-1 (+/-0.59), while the average coefficient obtained from the malignant tissue group consisted of 264 measurements from 20 sites was 1.55 mm-1 (+/-0.46). The malignant ovarian tissue showed significant lower scattering than the normal group (p collagen within OCT imaging depth was analyzed from the tissue histological section stained with Sirius Red. The average collagen area fraction (CAF) obtained from the normal tissue group was 48.4% (+/-12.3%), while the average CAF obtained from the malignant tissue group was 11.4% (+/-4.7%). A statistical significance of the collagen content was found between the two groups (p < 0.001). These results demonstrated that quantitative measurements of optical scattering coefficient from OCT images could be a potential powerful method for ovarian cancer detection.
李伟; 朱自强
2002-01-01
The partition coefficients of baicalin were measured in ethylene oxide and propylene oxide(EOPO)/salt aqueous two-phase systems at 298.15K,It was found that most of baicalin partitioned into EOPO-rich phase.The partition coefficients of baicalin varied from 10 to 120.The effect of various factors,including tie-line lngth,salt composition,molecular weight of EOPO,and solution pH,on the partition behavior was investigated on EOPO/salt systems.Furthermore the partition coefficients of baicalin were correlated using the modified Diamond-Hsu model.Good agreement with experimental data is obtained.The average relative deviations are less than 5.0%.
Poddar, R; Sen, P; Andrews, J T
2008-01-01
Noninvasive, non-contact and \\textit{in vivo} monitoring of blood glucose is a long needed pathology tool for saving patients from recurring pain and hassle that can accompany conventional blood glucose testing methods. Optical coherence tomography known for its high axial resolution imaging modality is adopted in this article for monitoring glucose levels in tissue like media non-invasively. Making use of changes in reduced scattering coefficient due to the refractive-index mismatch between the extracellular fluid and the cellular membranes and armed with a theoretical model, we establish a correlation between the glucose concentration and reduced scattering coefficient. The scattering coefficients are extracted from the deconvoluted interference signal by using Monte-Carlo simulation with valid approximations. A program code using NI LabVIEW(^{TM}) is developed for automation of the experiment, data acquisition and analysis.
Pang, Hyunsoo; Shin, Young-Han; Ihm, Dongchul; Lee, Eok Kyun; Kum, Oyeon
2000-11-01
Molecular dynamics simulations were performed for soft- and hard-sphere systems, for number densities ranging from 0.5 to 1.0, and the Kolmogorov-Sinai entropy (KS entropy) and self-diffusion coefficients were calculated. It is found that the KS entropy, when expressed in terms of average collision frequency, is uniquely related to the self-diffusion coefficient by a simple scaling law. The dependence of the KS entropy on average collision frequency and number density was also explored. Numerical results show that the scaling laws proposed by Dzugutov, and by Beijeren, Dorfman, Posch, and Dellago, can be applied to both soft- and hard-sphere systems by changing to more generalized forms.
Discharge coefficient correlations for circular-arc venturi flowmeters at critical /sonic/ flow
Arnberg, B. T.; Britton, C. L.; Seidl, W. F.
1973-01-01
Experimental data are analyzed to support theoretical predictions for discharge coefficients in circular-arc venturi flow meters operating in the critical sonic flow regime at throat Reynolds numbers above 150 thousand. The data tend to verify the predicted 0.25% decrease in the discharge coefficient during transition from a laminar to turbulent boundary layer. Four different test gases and three flow measurement facilities were used in the experiments with 17 venturis with throat sizes from 0.15 to 1.37 in. and Beta ratios ranging from 0.014 to 0.25. Recommendations are given as to how the effectiveness of future studies in the field could be improved.
Discharge coefficient correlations for circular-arc venturi flowmeters at critical /sonic/ flow
Arnberg, B. T.; Britton, C. L.; Seidl, W. F.
1973-01-01
Experimental data are analyzed to support theoretical predictions for discharge coefficients in circular-arc venturi flow meters operating in the critical sonic flow regime at throat Reynolds numbers above 150 thousand. The data tend to verify the predicted 0.25% decrease in the discharge coefficient during transition from a laminar to turbulent boundary layer. Four different test gases and three flow measurement facilities were used in the experiments with 17 venturis with throat sizes from 0.15 to 1.37 in. and Beta ratios ranging from 0.014 to 0.25. Recommendations are given as to how the effectiveness of future studies in the field could be improved.
Drabik, Dominik; Przybyło, Magda; Sikorski, Aleksander; Langner, Marek
2016-03-01
Fluorescence Correlation Spectroscopy (FCS) is a technique, which allows determination of the diffusion coefficient and concentration of fluorescent objects suspended in the solution. The measured parameter is the fluctuation of the fluorescence signal emitted by diffusing molecules. When 100 nm DOPC vesicles labeled with various fluorescent dyes (Fluorescein-PE, NBD-PE, Atto488 DOPE or βBodipy FL) were measured, different values of diffusion coefficients have been obtained. These diffusion coefficients were different from the expected values measured using the dynamic light scattering method (DLS). The FCS was initially developed for solutions containing small fluorescent molecules therefore the observed inconsistency may result from the nature of vesicle suspension itself. The duration of the fluorescence signal may depend on the following factors: the exposure time of the labeled object to the excitation beam, the photo-physical properties (e.g., stability) of a fluorophore, the theoretical model used for the calculations of the diffusion coefficient and optical properties of the vesicle suspension. The diffusion coefficients determined for differently labeled liposomes show that its dependence on vesicle size and quantity of fluorescent probed used for labeling was significant demonstrating that the fluorescence properties of the fluorophore itself (bleaching and/or blinking) were critical factors for a correct outcome of FCS experiment. The new, based on combined FCS and DLS measurements, method for the determination of the focal volume prove itself to be useful for the evaluation of a fluorescence dye with respect to its applicability for FCS experiment.
Hladni Nada; Miklič Vladimir; Mijić Anto; Jocić Siniša; Miladinović Dragana
2015-01-01
The most important criteria for introducing new confectionary hybrids into the production is high protein yield. Path coefficient analysis was used to obtain information on direct and indirect effects of studied traits (seed oil content, kernel oil content, seed yield, kernel protein content, mass of 1000 seeds, kernel ratio and hull ratio) on protein yield. The research was conducted during three vegetation seasons, on 22 experimental confectionary sunflow...
Ibnal Asad, Khalid; Ahmed, Tanvir; Rahman, Md. Saiedur
2012-01-01
Abundance of movie data across the internet makes it an obvious candidate for machine learning and knowledge discovery. But most researches are directed towards bi-polar classification of movie or generation of a movie recommendation system based on reviews given by viewers on various internet si...... propose classification scheme of pre-release movie popularity based on inherent attributes using C4.S and PART classifier algorithm and define the relation between attributes of post release movies using correlation coefficient....
Rakheja, Rajan; Chandarana, Hersh; DeMello, Linda; Jackson, Kimberly; Geppert, Christian; Faul, David; Glielmi, Christopher; Friedman, Kent P
2013-11-01
The purpose of this study was to assess the correlation between standardized uptake value (SUV) and apparent diffusion coefficient (ADC) of neoplastic lesions in the use of a simultaneous PET/MRI hybrid system. Twenty-four patients with known primary malignancies underwent FDG PET/CT. They then underwent whole-body PET/MRI. Diffusion-weighted imaging was performed with free breathing and a single-shot spin-echo echo-planar imaging sequence with b values of 0, 350, and 750 s/mm(2). Regions of interest were manually drawn along the contours of neoplastic lesions larger than 1 cm, which were clearly identified on PET and diffusion-weighted images. Maximum SUV (SUVmax) on PET/MRI and PET/CT images, mean SUV (SUVmean), minimum ADC (ADCmin), and mean ADC (ADCmean) were recorded on PET/MR images for each FDG-avid neoplastic soft-tissue lesion with a maximum of three lesions per patient. Pearson correlation coefficient was used to asses the following relations: SUVmax versus ADCmin on PET/MR and PET/CT images, SUVmean versus ADCmean, and ratio of SUVmax to mean liver SUV (SUV ratio) versus ADCmin. A subanalysis of patients with progressive disease versus partial treatment response was performed with the ratio of SUVmax to ADCmin for the most metabolically active lesion. Sixty-nine neoplastic lesions (52 nonosseous lesions, 17 bone metastatic lesions) were evaluated. The mean SUVmax from PET/MRI was 7.0 ± 6.0; SUVmean, 5.6 ± 4.6; mean ADCmin, 1.10 ± 0.58; and mean ADCmean, 1.48 ± 0.72. A significant inverse Pearson correlation coefficient was found between PET/MRI SUVmax and ADCmin (r = -0.21, p = 0.04), between SUVmean and ADCmean (r = -0.18, p = 0.07), and between SUV ratio and ADCmin (r = -0.27, p = 0.01). A similar inverse Pearson correlation coefficient was found between the PET/CT SUVmax and ADCmin. Twenty of 24 patients had previously undergone PET/CT; five patients had a partial treatment response, and six had progressive disease according to Response Evaluation
Lipid–water partition coefficients and correlations with uptakes by algae of organic compounds
Hung, Wei-Nung [Green Energy and Environment Research Laboratories, Industrial Technology Research Institute, Hsinchu 30011, Taiwan (China); Chiou, Cary T., E-mail: carychio@mail.ncku.edu.tw [Department of Environmental Engineering and Sustainable Environment Research Laboratory, National Cheng Kung University, Tainan 70101, Taiwan (China); U.S. Geological Survey, Denver Federal Center, Denver, CO 80225 (United States); Lin, Tsair-Fuh, E-mail: tflin@mail.ncku.edu.tw [Department of Environmental Engineering and Sustainable Environment Research Laboratory, National Cheng Kung University, Tainan 70101, Taiwan (China)
2014-08-30
Graphical abstract: - Highlights: • Partition coefficients of contaminants with lipid triolein (K{sub tw}) are measured. • Measured K{sub tw} values are nearly the same as the respective K{sub ow}. • Sorption of the contaminants to a dry algal powder is similarly measured. • Algal uptake of a compound occurs primarily by partition into the algal lipid. - Abstract: In view of the scarcity of the lipid–water partition coefficients (K{sub tw}) for organic compounds, the log K{sub tw} values for many environmental contaminants were measured using ultra-pure triolein as the model lipid. Classes of compounds studied include alkyl benzenes, halogenated benzenes, short-chain chlorinated hydrocarbons, polycyclic aromatic hydrocarbons, polychlorinated biphenyls, and organochlorine pesticides. In addition to log K{sub tw} determination, the uptakes of these compounds from water by a dry algal species were measured to evaluate the lipid effect on the algal uptake. The measured log K{sub tw} are closely related to their respective log K{sub ow} (octanol–water), with log K{sub ow} = 1.9 to 6.5. A significant difference is observed between the present and early measured log K{sub tw} for compounds with log K{sub ow} > ∼5, which is attributed to the presence and absence of a triolein microemulsion in water affecting the solute partitioning. The observed lipid-normalized algae–water distribution coefficients (log K{sub aw/lipid}) are virtually identical to the respective log K{sub tw} values, which manifests the dominant lipid-partition effect of the compounds with algae.
Jameson, A. R.
1990-01-01
The relationship between the rainfall rate (R) obtained from radiometric brightness temperatures and the extinction coefficient (k sub e) is investigated by computing the values of k sub e over a wide range of rainfall rates, for frequencies from 3 to 25 GHz. The results show that the strength of the relation between the R and the k sub e values exhibits considerable variation for frequencies at this range. Practical suggestions are made concerning the selection of particular frequencies for rain measurements to minimize the error in R determinations.
Measurements of texture properties related to tenderness at different locations within deboned broiler breast fillets have been used to validate techniques for texture analysis and establish correlations between different texture evaluation methods. However, it has been demonstrated that meat text...
Correlation between intrinsic dipole moment and pyroelectric coefficient of Fe-Mg tourmaline
Chang-chun Zhao; Li-bing Liao; Jie Xing
2014-01-01
Single-crystal X-ray diffraction structural data of four Fe-Mg tourmalines with different Fe contents from Xinjiang, Sichuan, and Yunnan Provinces, China, were collected at room temperature and-100ºC. The intrinsic dipole moments of polyhedra and the total intrinsic dipole moment of the unit cell were calculated. By comparing the intrinsic electric dipole moments of the X, Y, Z, T, and B site polyhedra, it is found that the T site polyhedron makes the greatest contribution to the total intrinsic dipole moment. The pyroelectric coefficients of four Fe-Mg tourmalines were experimentally determined, and the influence of intrinsic dipole moments on their pyroelectric properties was inves-tigated. The experimental results show that, compared with the case at room temperature, the intrinsic dipole moments change with the total Fe content at-100ºC in a completely different way. With the decrease of temperature, the total intrinsic dipole moments of tourmaline de-crease. Over the same temperature interval, the pyroelectric coefficients increase with the increase in intrinsic dipole moment.
Kim, Eun Jeong; Kim, Sung Hun; Park, Ga Eun; Kang, Bong Joo; Song, Byung Joo; Kim, Yun Ju; Lee, Dongeon; Ahn, Hyunsoo; Kim, Inah; Son, Yo Han; Grimm, Robert
2015-12-01
To evaluate apparent diffusion coefficient (ADC) histogram parameters that show correlations with prognostic factors and subtypes of breast cancer. At 3.0T, various ADC histogram parameters were calculated including the entire tumor volume in 173 invasive ductal carcinomas: the minimum, 10th percentile, mean, median, 90th percentile, and maximum. ADC parameters were correlated with prognostic factors and subtype. The mean ADCmedian value was significantly higher in the group with lymph node metastasis, HER2 positivity, and a Ki-67 value correlation between ADCmedian and tumor size, histologic grade, estrogen receptor expression, and progesterone receptor expression (P = 0.272, 0.113, 0.261, and 0.181, respectively). For most ADC parameters except for ADCmin , the mean of variable ADC parameters of HER2-positive, luminal A, luminal B-HER2(+), triple-negative, and luminal B-HER2(-) diseases were arranged in descending order (1.175, 0.936, 0.863, 0.811, and 0.665 × 10(-3) mm(2) /s in ADCmedian , respectively) with statistical significant difference (P coefficient = -0.317). Various ADC parameters were correlated with prognostic factors and subtype, except for ADCmin . HER2 positivity showed high ADC values and high Ki-67 index revealed low ADC values. © 2015 Wiley Periodicals, Inc.
Mahdi Alajmi
2015-07-01
Full Text Available The correlation between the mechanical properties of Fillers/Epoxy composites and their tribological behavior was investigated. Tensile, hardness, wear, and friction tests were conducted for Neat Epoxy (NE, Graphite/Epoxy composites (GE, and Data Palm Fiber/Epoxy with or without Graphite composites (GFE and FE. The correlation was made between the tensile strength, the modulus of elasticity, elongation at the break, and the hardness, as an individual or a combined factor, with the specific wear rate (SWR and coefficient of friction (COF of composites. In general, graphite as an additive to polymeric composite has had an eclectic effect on mechanical properties, whereas it has led to a positive effect on tribological properties, whilst date palm fibers (DPFs, as reinforcement for polymeric composite, promoted a mechanical performance with a slight improvement to the tribological performance. Statistically, this study reveals that there is no strong confirmation of any marked correlation between the mechanical and the specific wear rate of filler/Epoxy composites. There is, however, a remarkable correlation between the mechanical properties and the friction coefficient of filler/Epoxy composites.
Yu, Xue; Lee, Elaine Yuen Phin; Lai, Vincent; Chan, Queenie
2014-07-01
To evaluate the correlation between standardized uptake value (SUV) (tissue metabolism) and apparent diffusion coefficient (ADC) (water diffusivity) in peritoneal metastases. Patients with peritoneal dissemination detected on (18)F-fluorodeoxyglucose positron emission tomography combined with computed tomography (FDG-PET/CT) were prospectively recruited for MRI examinations with informed consent and the study was approved by the local Institutional Review Board. FDG-PET/CT, diffusion-weighted imaging (DWI), MRI, and DWI/MRI images were independently reviewed by two radiologists based on visual analysis. SUVmax/SUVmean and ADCmin/ADCmean were obtained manually by drawing ROIs over the peritoneal metastases on FDG-PET/CT and DWI, respectively. Diagnostic characteristics of each technique were evaluated. Pearson's coefficient and McNemar and Kappa tests were used for statistical analysis. Eight patients were recruited for this prospective study and 34 peritoneal metastases were evaluated. ADCmean was significantly and negatively correlated with SUVmax (r = -0.528, P = 0.001) and SUVmean (r = -0.548, P = 0.001). ADCmin had similar correlation with SUVmax (r = -0.508, P = 0.002) and SUVmean (r = -0.513, P = 0.002). DWI/MRI had high diagnostic performance (accuracy = 98%) comparable to FDG-PET/CT, in peritoneal metastasis detection. Kappa values were excellent for all techniques. There was a significant inverse correlation between SUV and ADC. © 2013 Wiley Periodicals, Inc.
Alajmi, Mahdi; Shalwan, Abdullah
2015-07-08
The correlation between the mechanical properties of Fillers/Epoxy composites and their tribological behavior was investigated. Tensile, hardness, wear, and friction tests were conducted for Neat Epoxy (NE), Graphite/Epoxy composites (GE), and Data Palm Fiber/Epoxy with or without Graphite composites (GFE and FE). The correlation was made between the tensile strength, the modulus of elasticity, elongation at the break, and the hardness, as an individual or a combined factor, with the specific wear rate (SWR) and coefficient of friction (COF) of composites. In general, graphite as an additive to polymeric composite has had an eclectic effect on mechanical properties, whereas it has led to a positive effect on tribological properties, whilst date palm fibers (DPFs), as reinforcement for polymeric composite, promoted a mechanical performance with a slight improvement to the tribological performance. Statistically, this study reveals that there is no strong confirmation of any marked correlation between the mechanical and the specific wear rate of filler/Epoxy composites. There is, however, a remarkable correlation between the mechanical properties and the friction coefficient of filler/Epoxy composites.
Werner, Charles L.; Wegmueller, Urs; Small, David L.; Rosen, Paul A.
1994-01-01
Terrain slopes, which can be measured with Synthetic Aperture Radar (SAR) interferometry either from a height map or from the interferometric phase gradient, were used to calculate the local incidence angle and the correct pixel area. Both are required for correct thematic interpretation of SAR data. The interferometric correlation depends on the pixel area projected on a plane perpendicular to the look vector and requires correction for slope effects. Methods for normalization of the backscatter and interferometric correlation for ERS-1 SAR are presented.
A consistent local linear estimator of the covariate adjusted correlation coefficient.
Nguyen, Danh V; Sentürk, Damla
2009-08-01
Consider the correlation between two random variables (X, Y), both not directly observed. One only observes X̃ = φ(1)(U)X + φ(2)(U) and Ỹ = ψ(1)(U)Y + ψ(2)(U), where all four functions {φ(l)(·),ψ(l)(·), l = 1, 2} are unknown/unspecified smooth functions of an observable covariate U. We consider consistent estimation of the correlation between the unobserved variables X and Y, adjusted for the above general dual additive and multiplicative effects of U, based on the observed data (X̃, Ỹ, U).
Light vector correlator in medium: Wilson coefficients up to dimension 6 operators
Kim, HyungJoo; Gubler, Philipp; Lee, Su Houng
2017-09-01
As an improvement of the QCD sum rule method to study modifications of light vector mesons in nuclear matter and/or at finite temperature, we calculate the Wilson coefficients of all independent gluonic non-scalar operators up to dimension 6 in the operator product expansion (OPE) of the vector channel for light quarks. To obtain the gluon part of the light quark OPE from the heavy quark one, we also compute the heavy quark expansion of the relevant quark condensates. Together with the results for the quark operators that are already available in the literature, this completes the OPE of the vector channel in a hot or dense medium for operators up to dimension 6.
Navid Ghaffarzadeh
2013-03-01
Full Text Available In this paper a novel method based on discrete wavelet transform and correlation coefficient is presented for distinguishing between arcing and permanent faults. The algorithm includes offline and online processing. In the offline, discrete wavelet transform is used to decompose typical faulted phase voltage waveforms during arcing faults. An index is then defined and computed. The index is based on the normalised energy of detail coefficients at resolution levels 1 to 14. The online processing consists of capturing the faulted phase voltage waveform using a 20 kHz sampling rate, and decomposing it by db4. Finally, arcing faults are distinguished from permanent faults based on correlation coefficient of the computed index of the pre-stored typical arcing faults and a recorded indistinct signal. The effectiveness of the approach has been tested for numerous arcing and permanent fault conditions on a transmission line using the Electromagnetic transient Program (EMTP software tool. The simulation results show the capability of the proposed method in distinguishing between arcing faults from permanent faults.
de Winter, Joost C F; Gosling, Samuel D; Potter, Jeff
2016-09-01
The Pearson product–moment correlation coefficient (rp) and the Spearman rank correlation coefficient (rs) are widely used in psychological research. We compare rp and rs on 3 criteria: variability, bias with respect to the population value, and robustness to an outlier. Using simulations across low (N = 5) to high (N = 1,000) sample sizes we show that, for normally distributed variables, rp and rs have similar expected values but rs is more variable, especially when the correlation is strong. However, when the variables have high kurtosis, rp is more variable than rs. Next, we conducted a sampling study of a psychometric dataset featuring symmetrically distributed data with light tails, and of 2 Likert-type survey datasets, 1 with light-tailed and the other with heavy-tailed distributions. Consistent with the simulations, rp had lower variability than rs in the psychometric dataset. In the survey datasets with heavy-tailed variables in particular, rs had lower variability than rp, and often corresponded more accurately to the population Pearson correlation coefficient (Rp) than rp did. The simulations and the sampling studies showed that variability in terms of standard deviations can be reduced by about 20% by choosing rs instead of rp. In comparison, increasing the sample size by a factor of 2 results in a 41% reduction of the standard deviations of rs and rp. In conclusion, rp is suitable for light-tailed distributions, whereas rs is preferable when variables feature heavy-tailed distributions or when outliers are present, as is often the case in psychological research.
Sherwan E. Tofiq
2016-06-01
Full Text Available The present study was conducted at Agricultural Research Center of Bakrajo, Sulaimani, Iraq during three successive seasons 2011-2014. This research was conducted using seven faba bean cultivars namely (Zaina, Seher, Yieldiz, Civilla, Luz di Otono, Tanyari and local. The following measurements and observations were made: 100 seed weight, first node height, number of seeds/plant, number of seeds/pod, pod length, number of pods/plant and seed yield. The results indicated that highly significant and negative correlations were presented between 100 seed weight and seed yield, whereas, significant and positive correlations were presented between the numbers of seed/plant and seed yield at the second season. In addition, the results of the third season indicate that the number of seeds/plant correlated significantly and positively with seed yield, and the number of seeds/pod correlated significantly and negatively with seed yield, whereas, number of pods/plant correlated high significantly and positively with the seed yield. The character first node height showed maximum direct effect value in seed yield at the first season and the third season, while number of pods/plant showed maximum direct effect value in seed yield at the second season.
Hedge, Sh; Klimova, E Iu; Mande, Sh; Medvedeva, Iu A; Makeev, V Iu; Permina, E A
2011-01-01
We developed an approach for effective estimating the correlations in the noise component of gene expression data. An efficent noise reduction technique has been suggested. The resulting technique has been applied to E. coli microarray data and tested on SOS response modulated genes.
Barchard, Kimberly A.
2012-01-01
This article introduces new statistics for evaluating score consistency. Psychologists usually use correlations to measure the degree of linear relationship between 2 sets of scores, ignoring differences in means and standard deviations. In medicine, biology, chemistry, and physics, a more stringent criterion is often used: the extent to which…
Matrix correlations for high-dimensional data: The modified RV-coefficient
Smilde, A.K.; Kiers, H.A.L.; Bijlsma, S.; Rubingh, C.M.; Erk, M.J. van
2009-01-01
Motivation: Modern functional genomics generates high-dimensional datasets. It is often convenient to have a single simple number characterizing the relationship between pairs of such high-dimensional datasets in a comprehensive way. Matrix correlations are such numbers and are appealing since they
Matrix correlations for high-dimensional data : The modified RV-coefficient
Smilde, A. K.; Kiers, H. A. L.; Bijlsma, S.; Rubingh, C. M.; van Erk, M. J.
2009-01-01
Motivation: Modern functional genomics generates high-dimensional datasets. It is often convenient to have a single simple number characterizing the relationship between pairs of such high-dimensional datasets in a comprehensive way. Matrix correlations are such numbers and are appealing since they
Matrix correlations for high-dimensional data: the modified RV-coefficient
Smilde, A.K.; Kiers, H.A.L.; Bijlsma, S.; Rubingh, C.M.; van Erk, M.J.
2009-01-01
Motivation: Modern functional genomics generates high-dimensional datasets. It is often convenient to have a single simple number characterizing the relationship between pairs of such high-dimensional datasets in a comprehensive way. Matrix correlations are such numbers and are appealing since they
On the construction of bivariate exponential distributions with an arbitrary correlation coefficient
Bladt, Mogens; Nielsen, Bo Friis
In this paper we use a concept of multivariate phase-type distributions to define a class of bivariate exponential distributions. This class has the following three appealing properties. Firstly, we may construct a pair of exponentially distributed random variables with any feasible correlation...... the exponential random vectors....
On the Construction of Bivariate Exponential Distributions with an Arbitrary Correlation Coefficient
Bladt, Mogens; Nielsen, Bo Friis
2010-01-01
In this article we use the concept of multivariate phase-type distributions to define a class of bivariate exponential distributions. This class has the following three appealing properties. Firstly, we may construct a pair of exponentially distributed random variables with any feasible correlation...... the exponential random vectors....
Proposal for a Correction to the Temporal Correlation Coefficient Calculation for Temporal Networks
Pigott, Fiona
2014-01-01
Measuring the topological overlap of two graphs becomes important when assessing the changes between temporally adjacent graphs in a time-evolving network. Current methods depend on the fraction of nodes that have persisting edges. This breaks down when there are nodes with no edges, persisting or otherwise. The following outlines a proposed correction to ensure that correlation metrics have the expected behavior.
Younk, Patrick; Risse, Markus
2012-07-01
The composition of ultra-high energy cosmic rays is an important issue in astroparticle physics research, and additional experimental results are required for further progress. Here we investigate what can be learned from the statistical correlation factor r between the depth of shower maximum and the muon shower size, when these observables are measured simultaneously for a set of air showers. The correlation factor r contains the lowest-order moment of a two-dimensional distribution taking both observables into account, and it is independent of systematic uncertainties of the absolute scales of the two observables. We find that, assuming realistic measurement uncertainties, the value of r can provide a measure of the spread of masses in the primary beam. Particularly, one can differentiate between a well-mixed composition (i.e., a beam that contains large fractions of both light and heavy primaries) and a relatively pure composition (i.e., a beam that contains species all of a similar mass). The number of events required for a statistically significant differentiation is ˜200. This differentiation, though diluted, is maintained to a significant extent in the presence of uncertainties in the phenomenology of high energy hadronic interactions. Testing whether the beam is pure or well-mixed is well motivated by recent measurements of the depth of shower maximum.
Korcyl, Piotr
2016-01-01
We determine quark mass dependent order $a$ improvement terms of the form $b_J am$ for non-singlet scalar, pseudoscalar, vector and axialvector currents, using correlators in coordinate space. We use a set of CLS ensembles comprising non-perturbatively improved Wilson Fermions and the tree-level Luescher-Weisz gauge action at $\\beta=3.4,3.46,3.55$ and $\\beta=3.7$, corresponding to lattice spacings $a$ ranging from $0.05$ fm to $0.09$ fm. We report the values of the $b_J$ improvement coefficients which are proportional to non-singlet quark mass combinations and also discuss the possibility of determining the $\\bar{b}_J$ coefficients which are proportional to the trace of the quark mass matrix.
Receiver function estimated by maximum entropy deconvolution
吴庆举; 田小波; 张乃铃; 李卫平; 曾融生
2003-01-01
Maximum entropy deconvolution is presented to estimate receiver function, with the maximum entropy as the rule to determine auto-correlation and cross-correlation functions. The Toeplitz equation and Levinson algorithm are used to calculate the iterative formula of error-predicting filter, and receiver function is then estimated. During extrapolation, reflective coefficient is always less than 1, which keeps maximum entropy deconvolution stable. The maximum entropy of the data outside window increases the resolution of receiver function. Both synthetic and real seismograms show that maximum entropy deconvolution is an effective method to measure receiver function in time-domain.
Fyodorov, Yan V.; Doussal, Pierre Le
2016-07-01
We study three instances of log-correlated processes on the interval: the logarithm of the Gaussian unitary ensemble (GUE) characteristic polynomial, the Gaussian log-correlated potential in presence of edge charges, and the Fractional Brownian motion with Hurst index H → 0 (fBM0). In previous collaborations we obtained the probability distribution function (PDF) of the value of the global minimum (equivalently maximum) for the first two processes, using the freezing-duality conjecture (FDC). Here we study the PDF of the position of the maximum x_m through its moments. Using replica, this requires calculating moments of the density of eigenvalues in the β -Jacobi ensemble. Using Jack polynomials we obtain an exact and explicit expression for both positive and negative integer moments for arbitrary β >0 and positive integer n in terms of sums over partitions. For positive moments, this expression agrees with a very recent independent derivation by Mezzadri and Reynolds. We check our results against a contour integral formula derived recently by Borodin and Gorin (presented in the Appendix 1 from these authors). The duality necessary for the FDC to work is proved, and on our expressions, found to correspond to exchange of partitions with their dual. Performing the limit n → 0 and to negative Dyson index β → -2, we obtain the moments of x_m and give explicit expressions for the lowest ones. Numerical checks for the GUE polynomials, performed independently by N. Simm, indicate encouraging agreement. Some results are also obtained for moments in Laguerre, Hermite-Gaussian, as well as circular and related ensembles. The correlations of the position and the value of the field at the minimum are also analyzed.
Lu, Fengbin; Qiao, Han; Wang, Shouyang; Lai, Kin Keung; Li, Yuze
2017-01-01
This paper proposes a new time-varying coefficient vector autoregressions (VAR) model, in which the coefficient is a linear function of dynamic lagged correlation. The proposed model allows for flexibility in choices of dynamic correlation models (e.g. dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (GARCH) models, Markov-switching GARCH models and multivariate stochastic volatility models), which indicates that it can describe many types of time-varying causal effects. Time-varying causal relations between West Texas Intermediate (WTI) crude oil and the US Standard and Poor's 500 (S&P 500) stock markets are examined by the proposed model. The empirical results show that their causal relations evolve with time and display complex characters. Both positive and negative causal effects of the WTI on the S&P 500 in the subperiods have been found and confirmed by the traditional VAR models. Similar results have been obtained in the causal effects of S&P 500 on WTI. In addition, the proposed model outperforms the traditional VAR model. Copyright Â© 2016 Elsevier Ltd. All rights reserved.
Robin, M. J. L.; Sudicky, E. A.; Gillham, R. W.; Kachanoski, R. G.
1991-10-01
Distribution coefficients (Kd), defined as the ratio of the concentration of solute associated with the solids to the concentration in solution, are widely used in the prediction of reactive solute transport. With the advent of stochastic approaches to describe solute transport, there is a need to examine the spatial distribution of Kd, and its correlation with the hydraulic conductivity (K). Distribution coefficients were measured in triplicates for strontium on 1279 subsamples of cores from Canadian Forces Base Borden for which K measurements were available. The Kd values ranged from 4.4 to 29.8 mL/g, with a mean of 9.9 and standard deviation of 2.89 mL/g. The standard error on the triplicate means was 0.95 mL/g or approximately 10% of the mean. The spatial behavior of Kd and K (expressed as In (Kd) and ln (K)) was examined in three directions: horizontally along two orthogonal transects and vertically. The two variables each behaved nearly identically in the two horizontal directions, suggesting horizontal isotropy. Horizontally, ln (Kd) appeared as "white noise" suggesting that the horizontal spacing between cores (1 m) was too large to detect any self-correlation. The distribution coefficient displayed increasing power spectral density with increasing scale in the vertical direction, while In (K) showed these trends in all directions. Depending on the model used, the, correlation lengths obtained by least squares fits of the power spectra varied from 1 to 7.5 m horizontally and from 10 to 30 cm vertically for ln (K); and from 30 cm to 2 m horizontally and from 30 to 70 cm vertically for ln (Kd). The ln (Kd) values showed a significant but very weak negative overall correlation with ln (K) at the 99.95% confidence level. The cross-spectral and coherency analysis showed that the sign and degree of correlation between ln (Kd) and ln (K) depended on the scale and direction considered. The correlations in all directions and at all scales were weak, and could not
Lin, Yuning; Li, Hui; Chen, Ziqian; Ni, Ping; Zhong, Qun; Huang, Huijuan; Sandrasegaran, Kumar
2015-05-01
The purpose of this study was to investigate the application of histogram analysis of apparent diffusion coefficient (ADC) in characterizing pathologic features of cervical cancer and benign cervical lesions. This prospective study was approved by the institutional review board, and written informed consent was obtained. Seventy-three patients with cervical cancer (33-69 years old; 35 patients with International Federation of Gynecology and Obstetrics stage IB cervical cancer) and 38 patients (38-61 years old) with normal cervix or cervical benign lesions (control group) were enrolled. All patients underwent 3-T diffusion-weighted imaging (DWI) with b values of 0 and 800 s/mm(2). ADC values of the entire tumor in the patient group and the whole cervix volume in the control group were assessed. Mean ADC, median ADC, 25th and 75th percentiles of ADC, skewness, and kurtosis were calculated. Histogram parameters were compared between different pathologic features, as well as between stage IB cervical cancer and control groups. Mean ADC, median ADC, and 25th percentile of ADC were significantly higher for adenocarcinoma (p = 0.021, 0.006, and 0.004, respectively), and skewness was significantly higher for squamous cell carcinoma (p = 0.011). Median ADC was statistically significantly higher for well or moderately differentiated tumors (p = 0.044), and skewness was statistically significantly higher for poorly differentiated tumors (p = 0.004). No statistically significant difference of ADC histogram was observed between lymphovascular space invasion subgroups. All histogram parameters differed significantly between stage IB cervical cancer and control groups (p < 0.05). Distribution of ADCs characterized by histogram analysis may help to distinguish early-stage cervical cancer from normal cervix or cervical benign lesions and may be useful for evaluating the different pathologic features of cervical cancer.
Marcin Kozak
2012-12-01
Full Text Available This paper discusses a number of aspects concerning the analysis, interpretation and reporting of correlations in agricultural sciences. Various problems that one might encounter with these aspects are identified, and suggestions of how to overcome these problems are proposed. Some of the examples presented show how mistaken and even misleading the interpretation of correlation can be when one ignores simple rules of analysis.Este artigo discute uma série de aspectos relacionados a análise, interpretação e forma de relatar correlações em ciências Agrárias. São identificados vários problemas que podem ser encontrados, bem como feitas sugestões de como superá-los. Alguns dos exemplos apresentados mostram quão erradas e mesmo enganosas podem ser as interpretações de correlação quando regras simples de análise são ignoradas.
Shen, Guohua; Ma, Huan; Liu, Bin; Ren, Pengwei; Kuang, Anren
2017-09-06
Diffusion-weighted imaging and fluorine-18-fluorodeoxyglucose PET are increasingly being recognized as feasible oncological techniques. The apparent diffusion coefficient (ADC) measured by diffusion-weighted imaging and the standardized uptake value (SUV) from fluorine-18-fluorodeoxyglucose PET have similar clinical applications. The aim of this study was to assess the correlation between these two parameters in various cancers. Several major databases were searched for eligible studies. The correlation coefficient (ρ) values were pooled in a random-effects model. Begg's test was used to analyze the existence of publication bias and the sources of heterogeneity were explored in subgroup analyses on the basis of study design, diagnostic method, scanning modality, and tumor type. Thirty-five articles were accepted. The pooled ρ value of all of the accepted studies was -0.30 (95% confidence interval: -0.33 to -0.27), and notable heterogeneity was present (I=69.4%, Pcorrelation. The pooled ρ values were -0.26, -0.33, -0.32, and -0.33 for the SUVmax/ADCmean, SUVmax/ADCmin, SUVmean/ADCmean, and SUVmean/ADCmin relationships, respectively. The study design and diagnostic method were potential sources of heterogeneity. Lung cancer showed a stronger correlation (ρ=-0.42) than head and neck cancer (ρ=-0.27), cervical cancer (ρ=-0.21), and breast cancer (ρ=-0.23). A Begg's test indicated no significant publication bias among the accepted studies (P>0.05). The two functional parameters of ADC and SUV showed a very weak inverse correlation, which may contribute toward a sophisticated characterization of tumor biology. However, the findings require further validation with trials with large samples and different tumor types.
Ahn, Chul; Hu, Fan; Skinner, Celette Sugg; Ahn, Daniel
2009-07-01
In some cluster randomization trials, the number of clusters cannot exceed a specified maximum value due to cost constraints or other practical reasons. Donner and Klar [Donner A, and Klar N. Design and analysis of cluster randomization trials in health research. Oxford University Press 2000] provided the sample size formula for the number of subjects required per cluster when the number of clusters cannot exceed a specified maximum value. The sample size formula of Donner and Klar assumes that the number of subjects is the same in each cluster. In practical situations, the number of subjects may be different among clusters. We conducted simulation studies to investigate the effect of the cluster size variability (kappa) and the intracluster correlation coefficient (rho) on the power of the study in which the number of available clusters is fixed in advance. For the balanced case (kappa=1.0), i.e., equal cluster size among clusters, the sample size formula yielded empirical powers close to the nominal level even when the number of available clusters per group (k*) is as small as 10. The sample size formula yielded empirical powers close to the nominal level when the number of available clusters per group (k*) is at least 20 and the imbalance parameter (kappa) is at least 0.8. Empirical powers were close to the nominal level when (rho or =0.8, and k*=10) or (rho< or =0.02, kappa=0.8, and k*=20).
Schüürmann, Gerrit; Ebert, Ralf-Uwe; Chen, Jingwen; Wang, Bin; Kühne, Ralph
2008-11-01
The external prediction capability of quantitative structure-activity relationship (QSAR) models is often quantified using the predictive squared correlation coefficient, q (2). This index relates the predictive residual sum of squares, PRESS, to the activity sum of squares, SS, without postprocessing of the model output, the latter of which is automatically done when calculating the conventional squared correlation coefficient, r (2). According to the current OECD guidelines, q (2) for external validation should be calculated with SS referring to the training set activity mean. Our present findings including a mathematical proof demonstrate that this approach yields a systematic overestimation of the prediction capability that is triggered by the difference between the training and test set activity means. Example calculations with three regression models and data sets taken from literature show further that for external test sets, q (2) based on the training set activity mean may become even larger than r (2). As a consequence, we suggest to always use the test set activity mean when quantifying the external prediction capability through q (2) and to revise the respective OECD guidance document accordingly. The discussion includes a comparison between r (2) and q (2) value ranges and the q (2) statistics for cross-validation.
Daniel Paech
Full Text Available To explore the correlation between Nuclear Overhauser Enhancement (NOE-mediated signals and tumor cellularity in glioblastoma utilizing the apparent diffusion coefficient (ADC and cell density from histologic specimens. NOE is one type of chemical exchange saturation transfer (CEST that originates from mobile macromolecules such as proteins and might be associated with tumor cellularity via altered protein synthesis in proliferating cells.For 15 patients with newly diagnosed glioblastoma, NOE-mediated CEST-contrast was acquired at 7 Tesla (asymmetric magnetization transfer ratio (MTRasym at 3.3ppm, B1 = 0.7 μT. Contrast enhanced T1 (CE-T1, T2 and diffusion-weighted MRI (DWI were acquired at 3 Tesla and coregistered. The T2 edema and the CE-T1 tumor were segmented. ADC and MTRasym values within both regions of interest were correlated voxelwise yielding the correlation coefficient rSpearman (rSp. In three patients who underwent stereotactic biopsy, cell density of 12 specimens per patient was correlated with corresponding MTRasym and ADC values of the biopsy site.Eight of 15 patients showed a weak or moderate positive correlation of MTRasym and ADC within the T2 edema (0.16≤rSp≤0.53, p0.05, n = 4 or yielded rSp≈0 (p0.05, n = 6. The biopsy-analysis within CE-T1 tumor revealed a strong positive correlation between tumor cellularity and MTRasym values in two of the three patients (rSppatient3 = 0.69 and rSppatient15 = 0.87, p<0.05, while the correlation of ADC and cellularity was heterogeneous (rSppatient3 = 0.545 (p = 0.067, rSppatient4 = -0.021 (p = 0.948, rSppatient15 = -0.755 (p = 0.005.NOE-imaging is a new contrast promising insight into pathophysiologic processes in glioblastoma regarding cell density and protein content, setting itself apart from DWI. Future studies might be based on the assumption that NOE-mediated CEST visualizes cellularity more accurately than ADC, especially in the CE-T1 tumor region.
Duan, Yabo; Song, Chengtian
2016-10-01
Empirical mode decomposition (EMD) is a recently proposed nonlinear and nonstationary laser signal denoising method. A noisy signal is broken down using EMD into oscillatory components that are called intrinsic mode functions (IMFs). Thresholding-based denoising and correlation-based partial reconstruction of IMFs are the two main research directions for EMD-based denoising. Similar to other decomposition-based denoising approaches, EMD-based denoising methods require a reliable threshold to determine which IMFs are noise components and which IMFs are noise-free components. In this work, we propose a new approach in which each IMF is first denoised using EMD interval thresholding (EMD-IT), and then a robust thresholding process based on Spearman correlation coefficient is used for relevant modes selection. The proposed method tackles the problem using a thresholding-based denoising approach coupled with partial reconstruction of the relevant IMFs. Other traditional denoising methods, including correlation-based EMD partial reconstruction (EMD-Correlation), discrete Fourier transform and wavelet-based methods, are investigated to provide a comparison with the proposed technique. Simulation and test results demonstrate the superior performance of the proposed method when compared with the other methods.
Duan, Yabo; Song, Chengtian
2016-12-01
Empirical mode decomposition (EMD) is a recently proposed nonlinear and nonstationary laser signal denoising method. A noisy signal is broken down using EMD into oscillatory components that are called intrinsic mode functions (IMFs). Thresholding-based denoising and correlation-based partial reconstruction of IMFs are the two main research directions for EMD-based denoising. Similar to other decomposition-based denoising approaches, EMD-based denoising methods require a reliable threshold to determine which IMFs are noise components and which IMFs are noise-free components. In this work, we propose a new approach in which each IMF is first denoised using EMD interval thresholding (EMD-IT), and then a robust thresholding process based on Spearman correlation coefficient is used for relevant modes selection. The proposed method tackles the problem using a thresholding-based denoising approach coupled with partial reconstruction of the relevant IMFs. Other traditional denoising methods, including correlation-based EMD partial reconstruction (EMD-Correlation), discrete Fourier transform and wavelet-based methods, are investigated to provide a comparison with the proposed technique. Simulation and test results demonstrate the superior performance of the proposed method when compared with the other methods.
Paech, Daniel; Burth, Sina; Windschuh, Johannes; Meissner, Jan-Eric; Zaiss, Moritz; Eidel, Oliver; Kickingereder, Philipp; Nowosielski, Martha; Wiestler, Benedikt; Sahm, Felix; Floca, Ralf Omar; Neumann, Jan-Oliver; Wick, Wolfgang; Heiland, Sabine; Bendszus, Martin; Schlemmer, Heinz-Peter; Ladd, Mark Edward; Bachert, Peter; Radbruch, Alexander
2015-01-01
To explore the correlation between Nuclear Overhauser Enhancement (NOE)-mediated signals and tumor cellularity in glioblastoma utilizing the apparent diffusion coefficient (ADC) and cell density from histologic specimens. NOE is one type of chemical exchange saturation transfer (CEST) that originates from mobile macromolecules such as proteins and might be associated with tumor cellularity via altered protein synthesis in proliferating cells. For 15 patients with newly diagnosed glioblastoma, NOE-mediated CEST-contrast was acquired at 7 Tesla (asymmetric magnetization transfer ratio (MTRasym) at 3.3ppm, B1 = 0.7 μT). Contrast enhanced T1 (CE-T1), T2 and diffusion-weighted MRI (DWI) were acquired at 3 Tesla and coregistered. The T2 edema and the CE-T1 tumor were segmented. ADC and MTRasym values within both regions of interest were correlated voxelwise yielding the correlation coefficient rSpearman (rSp). In three patients who underwent stereotactic biopsy, cell density of 12 specimens per patient was correlated with corresponding MTRasym and ADC values of the biopsy site. Eight of 15 patients showed a weak or moderate positive correlation of MTRasym and ADC within the T2 edema (0.16≤rSp≤0.53, pcorrelations were statistically insignificant (p>0.05, n = 4) or yielded rSp≈0 (pcorrelation between MTRasym and ADC was found in CE-T1 tumor (-0.310.05, n = 6). The biopsy-analysis within CE-T1 tumor revealed a strong positive correlation between tumor cellularity and MTRasym values in two of the three patients (rSppatient3 = 0.69 and rSppatient15 = 0.87, pcorrelation of ADC and cellularity was heterogeneous (rSppatient3 = 0.545 (p = 0.067), rSppatient4 = -0.021 (p = 0.948), rSppatient15 = -0.755 (p = 0.005)). NOE-imaging is a new contrast promising insight into pathophysiologic processes in glioblastoma regarding cell density and protein content, setting itself apart from DWI. Future studies might be based on the assumption that NOE-mediated CEST visualizes
Jeong, Ju Hye [Dept. of Nuclear Medicine, Kyungpook National University Hospital, Daegu (Korea, Republic of); Cho, Ihn Ho; Chun, Kyung Ah; Kong, Eun Jung; Kwon, Sang Don; Kim, Jae Hwang [Yeungnam University Hospital, Daegu (Korea, Republic of)
2016-06-15
Fluorine-18-fluorodeoxyglucose ({sup 18}F-FDG) positron emission tomography (PET) and diffusion-weighted magnetic resonance imaging (DWI) share the same role in clinical oncology and it is feasible to obtain the standardized uptake value (SUV) and apparent diffusion coefficient (ADC) simultaneously by emerging the hybrid positron emission tomography/magnetic resonance (PET/MR). This study investigated the correlation between the ADCs of rectal cancer lesions and their SUVs derived from hybrid PET/MR. Nine patients with histologically proven rectal adenocarcinoma (5 men, 4 women; mean age, 70 ± 15.91 years) underwent torso {sup 18}F-FDG PET/CT and regional hybrid {sup 18}F-FDG PET/MR sequentially. A fixed threshold value of 40 % of maximum uptake was used to determine tumor volume of interest (VOI) on PET image; SUV{sub max}, SUV{sub peak}, and SUV{sub mean} were calculated automatically. A single freehand region of interest (ROI) was drawn on high b-value (b1000) DWI image and copied to corresponding ADC map to determine the ADCmean of rectal cancer lesion. Spearman'rank correlation coefficient (ρ) was calculated to determine the correlation between SUVs and ADC values. SUV{sub max}, SUV{sub peak}, and SUV{sub mean} derived by hybrid PET/MR were 12.35 ± 4.66 (mean ± standard deviation), 9.66 ± 3.15 and 7.41 ± 2.54, respectively. The ADCmean value of rectal cancer lesions was 1.02 ± 0.08 × 10{sup -3}mm{sup 2}/s. ADCmean was significantly and inversely correlated with SUV values (SUV{sub max}, ρ = -0.95, p < 0.001; SUV{sub peak}, ρ = -0.93, p < 0.001; SUV{sub mean}, ρ = -0.91, p = 0.001). This preliminary hybrid PET/MR study demonstrates a significant inverse correlation exists between metabolic activity on {sup 18}F-FDG PET and water diffusion on DWI in rectal cancer.
Ibrahim, E A; Ramadan, A Y
2013-07-01
Genotypic correlation and path analyses were carried out for growth, yield and fruit quality traits in 13 sweet melon genotypes collected from different places in Egypt. Seeds of these melon populations were sown under irrigated and drought stress conditions. The analysis of variance for the studied traits showed that the differences among genotypes were highly significant for all studied traits under irrigation and drought stress. Under irrigated conditions, total yield per plant was positively and significantly correlated with fruit weight, flesh fruit thickness and fruit length. Positive direct effects were exhibited for fruit weight, number of fruits per plant and stem length on total yield per plant, while maximum positive indirect effects on total yield per plant were exhibited by fruit length and flesh fruit thickness through fruit weight. In case of drought stress conditions, total yield per plant had the highest positive and significant correlation with fruit weight followed by flesh fruit thickness, fruit length and stem length. Fruit weight had the greatest positive direct effect on total yield per plant followed by number of fruits per plant, fruit length and total soluble solid content. Flesh fruit thickness and fruit length had high positive indirect effect on total yield per plant via fruit weight. The results obtained from correlation and path analyses showed that the efficiency in the selection for total yield per plant in sweet melon should increased through the selection of fruit weight under irrigated conditions and fruit weight and fruit length under drought conditions.
Nadeem, Qurrat-Ul-Ain
2015-05-07
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 by exploiting the channel’s degrees of freedom in the elevation, which necessitates the derivation and characterization of three-dimensional (3D) channels in the presence of spatial correlation. In this paper, an exact closed-form expression for the Spatial Correlation Function (SCF) is derived for 3D MIMO channels. This novel SCF is developed for a uniform linear array of antennas with nonisotropic antenna patterns. The proposed method resorts to the spherical harmonic expansion (SHE) of plane waves and the trigonometric expansion of Legendre and associated Legendre polynomials. The resulting expression depends on the underlying arbitrary angular distributions and antenna patterns through the Fourier Series (FS) coefficients of power azimuth and elevation spectrums. The novelty of the proposed method lies in the SCF being valid for any 3D propagation environment. The developed SCF determines the covariance matrices at the transmitter and the receiver that form the Kronecker channel model. In order to quantify the effects of correlation on the system performance, the information-theoretic deterministic equivalents of the MI for the Kronecker model are utilized in both mono-user and multi-user cases. Numerical results validate the proposed analytical expressions and elucidate the dependence of the system performance on azimuth and elevation angular spreads and antenna patterns. Some useful insights into the behaviour of MI as a function of downtilt angles are provided. The derived model will help evaluate the performance of correlated 3D MIMO channels in the future.
Liu, Song, E-mail: songliu532909756@gmail.com [Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008 (China); Guan, Wenxian, E-mail: wenxianguan123@126.com [Department of Gastrointestinal Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008 (China); Wang, Hao, E-mail: wanghao20140525@126.com [Department of Gastrointestinal Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008 (China); Pan, Liang, E-mail: panliang2014@126.com [Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008 (China); Zhou, Zhuping, E-mail: zhupingzhou@126.com [Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008 (China); Yu, Haiping, E-mail: haipingyu2012@126.com [Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008 (China); Liu, Tian, E-mail: tianliu2014@126.com [Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA 30322 (United States); Yang, Xiaofeng, E-mail: xiaofengyang2014@126.com [Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA 30322 (United States); He, Jian, E-mail: hjxueren@126.com [Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008 (China); Zhou, Zhengyang, E-mail: zyzhou@nju.edu.cn [Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008 (China)
2014-12-15
Highlights: • Gastric cancers’ ADC values were significantly lower than normal gastric wall. • Gastric adenocarcinomas with different differentiation had different ADC values. • Gastric adenocarcinomas’ ADC values correlated with histologic differentiations. • Gastric cancers’ ADC values correlated with Lauren classifications. • Mean ADC value was better than min ADC value in characterizing gastric cancers. - Abstract: Objective: The purpose of this study was to evaluate the correlations between histological differentiation and Lauren classification of gastric cancer and the apparent diffusion coefficient (ADC) value of diffusion weighted imaging (DWI). Materials and methods: Sixty-nine patients with gastric cancer lesions underwent preoperative magnetic resonance imaging (MRI) (3.0T) and surgical resection. DWI was obtained with a single-shot, echo-planar imaging sequence in the axial plane (b values: 0 and 1000 s/mm{sup 2}). Mean and minimum ADC values were obtained for each gastric cancer and normal gastric walls by two radiologists, who were blinded to the histological findings. Histological type, degree of differentiation and Lauren classification of each resected specimen were determined by one pathologist. Mean and minimum ADC values of gastric cancers with different histological types, degrees of differentiation and Lauren classifications were compared. Correlations between ADC values and histological differentiation and Lauren classification were analyzed. Results: The mean and minimum ADC values of gastric cancers, as a whole and separately, were significantly lower than those of normal gastric walls (all p values <0.001). There were significant differences in the mean and minimum ADC values among gastric cancers with different histological types, degrees of differentiation and Lauren classifications (p < 0.05). Mean and minimum ADC values correlated significantly (all p < 0.001) with histological differentiation (r = 0.564, 0.578) and
Rosner, Bernard; Glynn, Robert J
2007-02-10
The Spearman (rho(s)) and Kendall (tau) rank correlation coefficient are routinely used as measures of association between non-normally distributed random variables. However, confidence limits for rho(s) are only available under the assumption of bivariate normality and for tau under the assumption of asymptotic normality of tau. In this paper, we introduce another approach for obtaining confidence limits for rho(s) or tau based on the arcsin transformation of sample probit score correlations. This approach is shown to be applicable for an arbitrary bivariate distribution. The arcsin-based estimators for rho(s) and tau (denoted by rho(s,a), tau(a)) are shown to have asymptotic relative efficiency (ARE) of 9/pi2 compared with the usual estimators rho(s) and tau when rho(s) and tau are, respectively, 0. In some nutritional applications, the Spearman rank correlation between nutrient intake as assessed by a reference instrument versus nutrient intake as assessed by a surrogate instrument is used as a measure of validity of the surrogate instrument. However, if only a single replicate (or a few replicates) are available for the reference instrument, then the estimated Spearman rank correlation will be downwardly biased due to measurement error. In this paper, we use the probit transformation as a tool for specifying an ANOVA-type model for replicate ranked data resulting in a point and interval estimate of a measurement error corrected rank correlation. This extends previous work by Rosner and Willett for obtaining point and interval estimates of measurement error corrected Pearson correlations.
Zheng, Ping; He, Bin; Guo, Yijun; Zeng, Jingsong; Tong, Wusong
2015-07-01
The relationship between microstructural abnormality in patients with traumatic brain injury (TBI) and hormone-secreting status remains unknown. In this study, the authors aimed to identify the role of the apparent diffusion coefficient (ADC) using a diffusion-weighted imaging (DWI) technique and to evaluate the association of such changes with hypopituitarism in patients with TBI. Diffusion-weighted images were obtained in 164 consecutive patients with TBI within 2 weeks after injury to generate the pituitary ADC as a measure of microstructural change. Patients with TBI were further grouped into those with and those without hypopituitarism based on the secretion status of pituitary hormones at 6 months postinjury. Thirty healthy individuals were enrolled in the study and underwent MRI examinations for comparison. Mean ADC values were compared between this control group, the patients with TBI and hypopituitarism, and the patients with TBI without hypopituitarism; correlational studies were also performed. Neurological outcome was assessed with the Glasgow Outcome Scale (GOS) for all TBI patients 6 months postinjury. In the TBI group, 84 patients had hypopituitarism and 80 had normal pituitary function. The pituitary ADC in TBI patients was significantly less than that in controls (1.83 ± 0.16 vs 4.13 ± 0.33, p correlated with neurological outcome at 6 months following TBI (r = 0.602, p correlated with hormone-secreting status in TBI patients. The authors suggest that pituitary ADC may be a useful biomarker to predict pituitary function in patients with TBI.
Wu, X; Reinikainen, P; Vanhanen, A; Kapanen, M; Vierikko, T; Ryymin, P; Hyödynmaa, S; Kellokumpu-Lehtinen, P-L
2017-01-01
To investigate whether diffusion-weighted imaging (DWI) apparent diffusion coefficient (ADC) correlates with prostate cancer aggressiveness and further to compare the diagnostic performance of ADC and normalized ADC (nADC: normalized to non-tumor tissue). Thirty pre-treatment patients (mean age, 69years; range: 59-78years) with prostate cancer underwent magnetic resonance imaging (MRI) examination, including DWI with three b values: 50, 400, and 800s/mm(2). Both ADC and nADC were correlated with the Gleason score obtained through transrectal ultrasound-guided biopsy. The tumor minimum ADC (ADCmin: the lowest ADC value within tumor) had an inverse correlation with the Gleason score (r=-0.43, Pcorrelated with the Gleason score (r=-0.52 and r=-0.55, P<0.01; respectively), and they were lower in patients with Gleason score 3+4 than those with Gleason score 3+3 (P<0.01; respectively). Receiver operating characteristic (ROC) analysis showed that the area under the ROC curve was 0.765, 0.818, or 0.833 for the ADCmin, nADCmin, or nADCmean; respectively, in differentiating between Gleason score 3+4 and 3+3 tumors. Tumor ADCmin, nADCmin, and nADCmean are useful markers to predict the aggressiveness of prostate cancer. Copyright © 2016 Éditions françaises de radiologie. Published by Elsevier Masson SAS. All rights reserved.
Korcyl, Piotr
2016-01-01
We determine quark mass dependent order $a$ improvement terms of the form $b_Jam$ for non-singlet scalar, pseudoscalar, vector and axialvector currents using correlators in coordinate space on a set of CLS ensembles. These have been generated employing non-perturbatively improved Wilson Fermions and the tree-level L\\"uscher-Weisz gauge action at $\\beta = 3.4, 3.46, 3.55$ and $3.7$, corresponding to lattice spacings ranging from $a \\approx 0.085$ fm down to $0.05$ fm. In the $N_f=2+1$ flavour theory two types of improvement coefficients exist: $b_J$, proportional to non-singlet quark mass combinations, and $\\bar{b}_J$ (or $\\tilde{b}_J$), proportional to the trace of the quark mass matrix. Combining our non-perturbative determinations with perturbative results, we quote Pad\\'e approximants parameterizing the $b_J$ improvement coefficients within the above window of lattice spacings. We also give preliminary results for $\\tilde{b}_J$ at $\\beta=3.4$.
Kelley, Ken
2008-01-01
Methods of sample size planning are developed from the accuracy in parameter approach in the multiple regression context in order to obtain a sufficiently narrow confidence interval for the population squared multiple correlation coefficient when regressors are random. Approximate and exact methods are developed that provide necessary sample size so that the expected width of the confidence interval will be sufficiently narrow. Modifications of these methods are then developed so that necessary sample size will lead to sufficiently narrow confidence intervals with no less than some desired degree of assurance. Computer routines have been developed and are included within the MBESS R package so that the methods discussed in the article can be implemented. The methods and computer routines are demonstrated using an empirical example linking innovation in the health services industry with previous innovation, personality factors, and group climate characteristics.
Carrasco, Josep L
2010-09-01
The classical concordance correlation coefficient (CCC) to measure agreement among a set of observers assumes data to be distributed as normal and a linear relationship between the mean and the subject and observer effects. Here, the CCC is generalized to afford any distribution from the exponential family by means of the generalized linear mixed models (GLMMs) theory and applied to the case of overdispersed count data. An example of CD34+ cell count data is provided to show the applicability of the procedure. In the latter case, different CCCs are defined and applied to the data by changing the GLMM that fits the data. A simulation study is carried out to explore the behavior of the procedure with a small and moderate sample size.
Simson, Martin
2010-09-21
This thesis describes measurements with the retardation spectrometer aSPECT at the Institut Laue-Langevin in Grenoble. The goal of the measurement is to determine the angular correlation coefficient a from the form of the proton recoil spectrum in the decay of the free neutron in order to determine a precise value for the ratio of the weak axial vector and vector coupling constants of the nucleon. A big improvement was achieved with the use of a silicon drift detector which was used here for the first time to detect low energetic protons. A saturation effect of the electronics that was only discovered during the analysis of the data from neutron decay proved to be not correctable. The findings from analysis, simulations and test experiments gained in this work should allow a measurement of a with high precision in a future beamtime. (orig.)
Reza Azad
2013-11-01
Full Text Available Hand gesture recognition possesses extensive applications in virtual reality, sign language recognition, and computer games. The direct interface of hand gestures provides us a new way for communicating with the virtual environment. In this paper a novel and real-time approach for hand gesture recognition system is presented. In the suggested method, first, the hand gesture is extracted from the main image by the image segmentation and morphological operation and then is sent to feature extraction stage. In feature extraction stage the Cross-correlation coefficient is applied on the gesture to recognize it. In the result part, the proposed approach is applied on American Sign Language (ASL database and the accuracy rate obtained 98.34%.
Using the correlation coefficient
Krijnen, Wim
2015-01-01
De correlatie coeffcient wordt gedefinieerd en haar eigenschappen worden samengevat. Een tweetal andere coeffcienten worden gegeven voor het geval de metingen niet normaal verdeeld zijn. Met enkele voorbeelden wordt het gebruik toegelicht. In het kort wordt uitgelegd hoe onderzoekers een uitkomst we
Using the correlation coefficient
W.P. Krijnen
2015-01-01
De correlatie coeffcient wordt gedefinieerd en haar eigenschappen worden samengevat. Een tweetal andere coeffcienten worden gegeven voor het geval de metingen niet normaal verdeeld zijn. Met enkele voorbeelden wordt het gebruik toegelicht. In het kort wordt uitgelegd hoe onderzoekers een uitkomst
Heuzé, Céline; Eriksson, Leif; Carvajal, Gisela
2017-04-01
Using sea surface temperature from satellite images to retrieve sea surface currents is not a new idea, but so far its operational near-real time implementation has not been possible. Validation studies are too region-specific or uncertain, due to the errors induced by the images themselves. Moreover, the sensitivity of the most common retrieval method, the maximum cross correlation, to the three parameters that have to be set is unknown. Using model outputs instead of satellite images, biases induced by this method are assessed here, for four different seas of Western Europe, and the best of nine settings and eight temporal resolutions are determined. For all regions, tracking a small 5 km pattern from the first image over a large 30 km region around its original location on a second image, separated from the first image by 6 to 9 hours returned the most accurate results. Moreover, for all regions, the problem is not inaccurate results but missing results, where the velocity is too low to be picked by the retrieval. The results are consistent both with limitations caused by ocean surface current dynamics and with the available satellite technology, indicating that automated sea surface current retrieval from sea surface temperature images is feasible now, for search and rescue operations, pollution confinement or even for more energy efficient and comfortable ship navigation.
Driessen, Juliette P; van Bemmel, Alexander J M; van Kempen, Pauline M W; Janssen, Luuk M; Terhaard, Chris H J; Pameijer, Frank A; Willems, Stefan M; Stegeman, Inge; Grolman, Wilko; Philippens, Marielle E P
2016-04-01
Identification of prognostic patient characteristics in head and neck squamous cell carcinoma (HNSCC) is of great importance. Human papillomavirus (HPV)-positive HNSCCs have favorable response to (chemo)radiotherapy. Apparent diffusion coefficient, derived from diffusion-weighted MRI, has also shown to predict treatment response. The purpose of this study was to evaluate the correlation between HPV status and apparent diffusion coefficient. Seventy-three patients with histologically proven HNSCC were retrospectively analyzed. Mean pretreatment apparent diffusion coefficient was calculated by delineation of total tumor volume on diffusion-weighted MRI. HPV status was analyzed and correlated to apparent diffusion coefficient. Six HNSCCs were HPV-positive. HPV-positive HNSCC showed significantly lower apparent diffusion coefficient compared to HPV-negative. This correlation was independent of other patient characteristics. In HNSCC, positive HPV status correlates with low mean apparent diffusion coefficient. The favorable prognostic value of low pretreatment apparent diffusion coefficient might be partially attributed to patients with a positive HPV status. © 2015 Wiley Periodicals, Inc. Head Neck 38: E613-E618, 2016. © 2015 Wiley Periodicals, Inc.
Afacan, Onur; Gholipour, Ali; Mulkern, Robert V; Barnewolt, Carol E; Estroff, Judy A; Connolly, Susan A; Parad, Richard B; Bairdain, Sigrid; Warfield, Simon K
2016-12-01
To evaluate the feasibility of using diffusion-weighted magnetic resonance imaging (DW-MRI) to assess the fetal lung apparent diffusion coefficient (ADC) at 3 Tesla (T). Seventy-one pregnant women (32 second trimester, 39 third trimester) were scanned with a twice-refocused Echo-planar diffusion-weighted imaging sequence with 6 different b-values in 3 orthogonal diffusion orientations at 3T. After each scan, a region-of-interest (ROI) mask was drawn to select a region in the fetal lung and an automated robust maximum likelihood estimation algorithm was used to compute the ADC parameter. The amount of motion in each scan was visually rated. When scans with unacceptable levels of motion were eliminated, the lung ADC values showed a strong association with gestational age (P < 0.01), increasing dramatically between 16 and 27 weeks and then achieving a plateau around 27 weeks. We show that to get reliable estimates of ADC values of fetal lungs, a multiple b-value acquisition, where motion is either corrected or considered, can be performed. J. Magn. Reson. Imaging 2016;44:1650-1655. © 2016 International Society for Magnetic Resonance in Medicine.
IDA M FRIISBERG; LORENZO COSTIGLIOLA; JEPPE C DYRE
2017-07-01
This paper investigates the relation between the density-scaling exponent γ and the virial potential energy correlation coefficient R at several thermodynamic state points in three dimensions for the generalized (2n, n) Lennard-Jones (LJ) system for n = 4, 9, 12, 18, as well as for the standard n = 6 LJ system in two,three, and four dimensions. The state points studied include many low-density states at which the virial potential energy correlations are not strong. For these state points we find the roughly linear relation γ∼=3n R/d in d dimensions. This result is discussed in light of the approximate “extended inverse power law” description of generalized LJ potentials (Bailey N P et al. 2008 J. Chem. Phys. 129 184508). In the plot of γ versus R there is in all cases a transition around R ≈ 0.9, above which γ starts to decrease as R approaches unity. This is consistent with the fact that γ → 2n/d for R → 1, a limit that is approached at high densities and/or high temperatures at which the repulsive r−2n term dominates the physics.
Braschel, Melissa C; Svec, Ivana; Darlington, Gerarda A; Donner, Allan
2016-04-01
Many investigators rely on previously published point estimates of the intraclass correlation coefficient rather than on their associated confidence intervals to determine the required size of a newly planned cluster randomized trial. Although confidence interval methods for the intraclass correlation coefficient that can be applied to community-based trials have been developed for a continuous outcome variable, fewer methods exist for a binary outcome variable. The aim of this study is to evaluate confidence interval methods for the intraclass correlation coefficient applied to binary outcomes in community intervention trials enrolling a small number of large clusters. Existing methods for confidence interval construction are examined and compared to a new ad hoc approach based on dividing clusters into a large number of smaller sub-clusters and subsequently applying existing methods to the resulting data. Monte Carlo simulation is used to assess the width and coverage of confidence intervals for the intraclass correlation coefficient based on Smith's large sample approximation of the standard error of the one-way analysis of variance estimator, an inverted modified Wald test for the Fleiss-Cuzick estimator, and intervals constructed using a bootstrap-t applied to a variance-stabilizing transformation of the intraclass correlation coefficient estimate. In addition, a new approach is applied in which clusters are randomly divided into a large number of smaller sub-clusters with the same methods applied to these data (with the exception of the bootstrap-t interval, which assumes large cluster sizes). These methods are also applied to a cluster randomized trial on adolescent tobacco use for illustration. When applied to a binary outcome variable in a small number of large clusters, existing confidence interval methods for the intraclass correlation coefficient provide poor coverage. However, confidence intervals constructed using the new approach combined with Smith
Tegner, C.; Heilmann-Clausen, C.; Larsen, R. B.; Kent, A. J. R.
2012-04-01
Massive flood basalt volcanism in the NE Atlantic 56 million years ago can be related to the initial manifestation of the Iceland plume and ensuing continental rifting, and has been correlated with a short (c. 200,000 years) global warming period, the Paleocene-Eocene thermal maximum (PETM). A hypothesis is that magmatic sills emplaced into organic-rich sediments on the Norwegian margin triggered rapid release of greenhouse gases. However, the largest exposed volcanic succession in the region, the E Greenland flood basalts provide additional details. The alkaline Ash-17 provides regional correlation of continental volcanism and pertubation of the oceanic environment. In E Greenland Ash-17 is interbedded with the uppermost part of the flood basalt succession. In the marine sections of Denmark, Ash-17 postdates PETM, most likely by 3-400,000 years. While radiometric ages bracket the duration of the main flood basalt event to less than a million years, the subsidence history of the Skaergaard intrusion due to flood basalt emplacement indicates it took less than 300,000 years. It is therefore possible that the main flood basalts in E Greenland postdates PETM. This is supported by a scarcity of ash layers within the PETM interval. Continental flood basalt provinces represent some of the highest sustained volcanic outputs preserved within the geologic record. Recent studies have focused on estimating the atmospheric loading of volatile elements and have led to the suggestion that they may be associated with significant global climate changes and mass extinctions. Estimates suggest that c. 400,000 km3 of basaltic lava erupted in E Greenland and the Faeroe islands. Based on measurements of melt inclusions and solubility models, approximately 3000 Gt of SO2 and 220 Gt of HCl were released by these basalts. Calculated yearly fluxes approach 10 Mt/y SO2 and 0.7 Mt/y HCl. Refinements of these estimates, based largely on further melt inclusion measurements, are proceeding. Our
Mertin, D; Lippold, B C
1997-01-01
Penetration of homologous nicotinic acid esters through the human nail and a keratin membrane from bovine hooves was investigated by modified Franz diffusion cells in-vitro to study the transport mechanism. The partition coefficient octanol/water PCOct/W of the esters was over the range 7 to > 51,000. The permeability coefficient P of the nail plate as well as the hoof membrane did not increase with increasing partition coefficient or lipophilicity of the penetrating substance. This indicates that both barriers behave like hydrophilic gel membranes rather than lipophilic partition membranes as in the case of the stratum corneum. Penetration studies with the model compounds paracetamol and phenacetin showed that the maximum flux was first a function of the drug solubility in water or in the swollen keratin matrix. Dissociation hindered the diffusion of benzoic acid and pyridine through the hoof membrane. Since keratin, a protein with an isoelectric point of about 5, is also charged, this reduction can be attributed to an exclusion of the dissociating substance due to the Donnan equilibrium. Nevertheless, the simultaneous enhancement of the water solubility makes a distinct increase of the maximum flux possible. In order to screen drugs for potential topical application to the nail plate, attention has to be paid mainly to the water solubility of the compound. The bovine hoof membrane may serve as an appropriate model for the nail.
Taylor, J David; Fletcher, James P
2013-05-01
The 8-repetition maximum test has the potential to be a feasible, cost-effective method of measuring muscle strength for clinicians. The purpose of this study was to investigate the concurrent validity of the 8-repetition maximum test in the measurement of muscle strength by comparing the 8-repetition maximum test to the gold standard of isokinetic dynamometry. Thirty participants (15 males and 15 females, mean age = 23.2 years [standard deviation = 1.0]) underwent 8-repetition maximum testing and isokinetic dynamometry testing of the knee extensors (at 60, 120, and 240 degrees per second) on two separate sessions with 2-3 days between each mode of testing. Linear regression was used to assess the validity by comparing the findings between 8-repetition maximum testing and isokinetic dynamometry testing. Significant correlations were found between the 8-repetition maximum and isokinetic dynamometry peak torque at each testing velocity (r = 0.71-0.85). The highest correlations were between the 8-repetition maximum and isokinetic dynamometry peak torques at 60 (r = 0.85) and 120 (r = 0.85) degrees per second. The findings of this study provide supportive evidence for the use of 8-repetition maximum testing as a valid, alternative method for measuring muscle strength.
Cai, Chen-Bo; Xu, Lu; Han, Qing-Juan; Wu, Hai-Long; Nie, Jin-Fang; Fu, Hai-Yan; Yu, Ru-Qin
2010-05-15
The paper focuses on solving a common and important problem of NIR quantitative analysis in multi-component systems: how to significantly reduce the size of the calibration set while not impairing the predictive precision. To cope with the problem orthogonal discrete wavelet packet transform (WPT), the least correlation design and correlation coefficient test (r-test) have been combined together. As three examples, a two-component carbon tetrachloride system with 21 calibration samples, a two-component aqueous system with 21 calibration samples, and a two-component aqueous system with 41 calibration samples have been treated with the proposed strategy, respectively. In comparison with some previous methods based on much more calibration samples, the results out of the strategy showed that the predictive ability was not obviously decreased for the first system while being clearly strengthened for the second one, and the predictive precision out of the third one was even satisfactory enough for most cases of quantitative analysis. In addition, all important factors and parameters related to our strategy are discussed in detail.
Sarkar, Debdeep
2016-01-01
In this paper, the concept of cross-correlation Green's functions (CGF) is used in conjunction with the finite difference time domain (FDTD) technique for calculation of envelope correlation coefficient (ECC) of any arbitrary MIMO antenna system over wide frequency band. Both frequency-domain (FD) and time-domain (TD) post-processing techniques are proposed for possible application with this FDTD-CGF scheme. The FDTD-CGF time-domain (FDTD-CGF-TD) scheme utilizes time-domain signal processing methods and exhibits significant reduction in ECC computation time as compared to the FDTD-CGF frequency domain (FDTD-CGF-FD) scheme, for high frequency-resolution requirements. The proposed FDTD-CGF based schemes can be applied for accurate and fast prediction of wideband ECC response, instead of the conventional scattering parameter based techniques which have several limitations. Numerical examples of the proposed FDTD-CGF techniques are provided for two-element MIMO systems involving thin-wire half-wavelength dipoles ...
Sharifi Peyman
2014-01-01
Full Text Available Faba bean is a grain legume and grown for its high protein content in the seed. It is also serves as a rotational crop which play great role in controlling disease epidemics in areas were cereal mono-cropping is abundant. Yield in faba bean, similar to the other crops, is a complex trait and constitute by many of morphological and physiological traits. This study was carried out during 2011-12 and 2012-13 in two region of Iran including Guilan and Lorestan provinces. Field experiments were conducted in a randomized complete block design with three replications and ten genotypes. The results of combined analysis of variance indicated that the studied genotypes differed significantly for all of the studied traits. The results indicated also environment effect and environment × genotype interaction effects were significant or highly significant for all of the traits. The highest seed yield were determined for genotype 1 (3159.9 and 4016.9 kg ha-1 at 2012 and 2013, respectively in Guilan and genotype 5 (495.44 kg ha-1 in Lorestan. The results of correlation analysis indicated that there were positive significant correlation coefficients between seed yield and seed length (LS, seed width (WS, pod length (PL and hundred seed weight (HSW in Guilan province at two cropping season. Path coefficient analysis indicated that traits containing number of pod per plant, number of steam per plant, pod length, seed length/width ratio and hundred seed weight had the highest positive direct effects on dry seed yield in studied faba bean genotypes. Attention should be paid to some of characters such as pod length, hundred seed weight, number of pods per plant and number of stems per plant for augmentation of seed yield and these traits could be used as selection criteria in faba bean breeding programs. These findings indicate that selection for each or full of the above traits would be accompanied by high yielding ability under such conditions. It could be
Chiba Shigeru
2007-09-01
Full Text Available Abstract Background Computer graphics and virtual reality techniques are useful to develop automatic and effective rehabilitation systems. However, a kind of virtual environment including unstable visual images presented to wide field screen or a head mounted display tends to induce motion sickness. The motion sickness induced in using a rehabilitation system not only inhibits effective training but also may harm patients' health. There are few studies that have objectively evaluated the effects of the repetitive exposures to these stimuli on humans. The purpose of this study is to investigate the adaptation to visually induced motion sickness by physiological data. Methods An experiment was carried out in which the same video image was presented to human subjects three times. We evaluated changes of the intensity of motion sickness they suffered from by a subjective score and the physiological index ρmax, which is defined as the maximum cross-correlation coefficient between heart rate and pulse wave transmission time and is considered to reflect the autonomic nervous activity. Results The results showed adaptation to visually-induced motion sickness by the repetitive presentation of the same image both in the subjective and the objective indices. However, there were some subjects whose intensity of sickness increased. Thus, it was possible to know the part in the video image which related to motion sickness by analyzing changes in ρmax with time. Conclusion The physiological index, ρmax, will be a good index for assessing the adaptation process to visually induced motion sickness and may be useful in checking the safety of rehabilitation systems with new image technologies.
A Note about the Calculation of Partial Correlation Coefficient%关于偏相关系数的计算公式的一点注记
陈敏琼; 彭东海
2014-01-01
On the partial correlation coefficient ,the paper sums up the definitions and calculation meth-ods of commonly used and derives the method to calculate the partial correlation coefficient formula by the correlation coefficient matrix and covariance matrix inversion from the multivariate normal distribu-tion theory of the conclusion of conditional distribution .Then the method to calculate the partial corre-lation coefficient formula by the correlation coefficient matrix inversion is given a reasonable explana-tion .%首先对偏相关系数的常用的定义与计算方法作了归纳，然后从多元正态分布理论中的条件分布的结论出发，推导得出通过相关系数阵或协方差阵求逆的方法来计算偏相关系数的公式，从而对利用相关系数阵求逆方法计算偏相关系数的公式给出了合理的解释。
Oh, Ji-Won; Rha, Sung Eun; Oh, Soon Nam; Park, Michael Yong; Byun, Jae Young; Lee, Ahwon
2015-04-01
The purpose of this article is to correlate the apparent diffusion coefficient (ADC) values of epithelial ovarian cancers with histologic grade and surgical stage. We enrolled 43 patients with pathologically proven epithelial ovarian cancers for this retrospective study. All patients underwent preoperative pelvic magnetic resonance imaging (MRI) including diffusion-weighted images with b value of 0 and 1000 s/mm2 at 3.0-T unit. The mean ADC values of the solid portion of the tumor were measured and compared among different histologic grades and surgical stages. The mean ADC values of epithelial ovarian cancers differed significantly between grade 1 (well-differentiated) and grade 2 (moderately-differentiated) (P=0.013) as well as between grade 1 and grade 3 (poorly-differentiated) (P=0.01); however, no statistically significant difference existed between grade 2 and grade 3 (P=0.737). The receiver-operating characteristic analysis indicated that a cutoff ADC value of less than or equal to 1.09×10(-3)mm2/s was associated with 94.4% sensitivity and 85.7% specificity in distinguishing grade 1 and grade 2/3 cancer. The difference in mean ADC values was statistically significant for early stage (FIGO stage I) and advanced stage (FIGO stage II-IV) cancer (P=0.011). The interobserver agreement for the mean ADC values of epithelial ovarian cancers was excellent. The mean ADC values of the solid portion of epithelial ovarian cancers negatively correlated to histologic grade and surgical stage. The mean ADC values may be useful imaging biomarkers for assessment of tumor grade of epithelial ovarian cancer. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Mohamed Salleh, Faridah Hani; Arif, Shereena Mohd; Zainudin, Suhaila; Firdaus-Raih, Mohd
2015-12-01
A gene regulatory network (GRN) is a large and complex network consisting of interacting elements that, over time, affect each other's state. The dynamics of complex gene regulatory processes are difficult to understand using intuitive approaches alone. To overcome this problem, we propose an algorithm for inferring the regulatory interactions from knock-out data using a Gaussian model combines with Pearson Correlation Coefficient (PCC). There are several problems relating to GRN construction that have been outlined in this paper. We demonstrated the ability of our proposed method to (1) predict the presence of regulatory interactions between genes, (2) their directionality and (3) their states (activation or suppression). The algorithm was applied to network sizes of 10 and 50 genes from DREAM3 datasets and network sizes of 10 from DREAM4 datasets. The predicted networks were evaluated based on AUROC and AUPR. We discovered that high false positive values were generated by our GRN prediction methods because the indirect regulations have been wrongly predicted as true relationships. We achieved satisfactory results as the majority of sub-networks achieved AUROC values above 0.5.
Büttner, Kathrin; Salau, Jennifer; Krieter, Joachim
2016-01-01
The average topological overlap of two graphs of two consecutive time steps measures the amount of changes in the edge configuration between the two snapshots. This value has to be zero if the edge configuration changes completely and one if the two consecutive graphs are identical. Current methods depend on the number of nodes in the network or on the maximal number of connected nodes in the consecutive time steps. In the first case, this methodology breaks down if there are nodes with no edges. In the second case, it fails if the maximal number of active nodes is larger than the maximal number of connected nodes. In the following, an adaption of the calculation of the temporal correlation coefficient and of the topological overlap of the graph between two consecutive time steps is presented, which shows the expected behaviour mentioned above. The newly proposed adaption uses the maximal number of active nodes, i.e. the number of nodes with at least one edge, for the calculation of the topological overlap. The three methods were compared with the help of vivid example networks to reveal the differences between the proposed notations. Furthermore, these three calculation methods were applied to a real-world network of animal movements in order to detect influences of the network structure on the outcome of the different methods.
Yang, Yan; Kang, Bo-seon
2008-11-10
The feasibility and the accuracy of the correlation coefficient (CC) method for the determination of particle positions along the optical axis in digital particle holography were verified by validation experiments. A translation system capable of high precision was used to move the particle objects by exact known distances between several different positions. The particle positions along the optical axis were calculated by the CC method and compared with their exact values to obtain the errors of the focus plane determination. The tested particles were two-dimensional (2D) dots in a calibration target along with different-sized glass beads and droplets that reflected and caused a three-dimensional (3D) effect. The results show that the CC method can work well for both the 2D dots and the 3D particles. The effect of other particles on the focus plane determination was also investigated. The CC method can locate the focus plane of particles with high precision, regardless of the existence of other particles.
Wu, Sheng; Crespi, Catherine M; Wong, Weng Kee
2012-09-01
The intraclass correlation coefficient (ICC) is a fundamental parameter of interest in cluster randomized trials as it can greatly affect statistical power. We compare common methods of estimating the ICC in cluster randomized trials with binary outcomes, with a specific focus on their application to community-based cancer prevention trials with primary outcome of self-reported cancer screening. Using three real data sets from cancer screening intervention trials with different numbers and types of clusters and cluster sizes, we obtained point estimates and 95% confidence intervals for the ICC using five methods: the analysis of variance estimator, the Fleiss-Cuzick estimator, the Pearson estimator, an estimator based on generalized estimating equations and an estimator from a random intercept logistic regression model. We compared estimates of the ICC for the overall sample and by study condition. Our results show that ICC estimates from different methods can be quite different, although confidence intervals generally overlap. The ICC varied substantially by study condition in two studies, suggesting that the common practice of assuming a common ICC across all clusters in the trial is questionable. A simulation study confirmed pitfalls of erroneously assuming a common ICC. Investigators should consider using sample size and analysis methods that allow the ICC to vary by study condition.
Yang, Tao; Zhang, Feipeng; Yardimci, Galip Gurkan; Song, Fan; Hardison, Ross C; Noble, William Stafford; Yue, Feng; Li, Qunhua
2017-08-30
Hi-C is a powerful technology for studying genome-wide chromatin interactions. However, current methods for assessing Hi-C data reproducibility can produce misleading results because they ignore spatial features in Hi-C data, such as domain structure and distance dependence. We present HiCRep, a framework for assessing the reproducibility of Hi-C data that systematically accounts for these features. In particular, we introduce a novel similarity measure, the stratum adjusted correlation coefficient (SCC), for quantifying the similarity between Hi-C interaction matrices. Not only does it provide a statistically sound and reliable evaluation of reproducibility, SCC can also be used to quantify differences between Hi-C contact matrices and to determine the optimal sequencing depth for a desired resolution. The measure consistently shows higher accuracy than existing approaches in distinguishing subtle differences in reproducibility and depicting interrelationships of cell lineages. The proposed measure is straightforward to interpret and easy to compute, making it well-suited for providing standardized, interpretable, automatable, and scalable quality control. The freely available R package HiCRep implements our approach. Published by Cold Spring Harbor Laboratory Press.
Oh, Ji-Won, E-mail: fromentin@naver.com [Department of Radiology, Seoul St. Mary' s Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 137-701 (Korea, Republic of); Rha, Sung Eun, E-mail: serha@catholic.ac.kr [Department of Radiology, Seoul St. Mary' s Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 137-701 (Korea, Republic of); Oh, Soon Nam, E-mail: hiohsn@catholic.ac.kr [Department of Radiology, Seoul St. Mary' s Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 137-701 (Korea, Republic of); Park, Michael Yong, E-mail: digirave@kmle.com [Department of Radiology, Seoul St. Mary' s Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 137-701 (Korea, Republic of); Byun, Jae Young, E-mail: jybyun@catholic.ac.kr [Department of Radiology, Seoul St. Mary' s Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 137-701 (Korea, Republic of); Lee, Ahwon, E-mail: klee@catholic.ac.kr [Department of Hospital Pathology, Seoul St. Mary' s Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 137-701 (Korea, Republic of)
2015-04-15
Highlights: •The solid component of all invasive epithelial cancers showed high b{sub 1000} signal intensity. •ADCs can predict the histologic grade of epithelial ovarian cancer. •ADCs correlate negatively to the surgical stage of epithelial ovarian cancer. •ADCs may be useful imaging biomarkers to assess epithelial ovarian cancer. -- Abstract: Objective: The purpose of this article is to correlate the apparent diffusion coefficient (ADC) values of epithelial ovarian cancers with histologic grade and surgical stage. Materials and methods: We enrolled 43 patients with pathologically proven epithelial ovarian cancers for this retrospective study. All patients underwent preoperative pelvic magnetic resonance imaging (MRI) including diffusion-weighted images with b value of 0 and 1000 s/mm{sup 2} at 3.0-T unit. The mean ADC values of the solid portion of the tumor were measured and compared among different histologic grades and surgical stages. Results: The mean ADC values of epithelial ovarian cancers differed significantly between grade 1 (well-differentiated) and grade 2 (moderately-differentiated) (P = 0.013) as well as between grade 1 and grade 3 (poorly-differentiated) (P = 0.01); however, no statistically significant difference existed between grade 2 and grade 3 (P = 0.737). The receiver-operating characteristic analysis indicated that a cutoff ADC value of less than or equal to 1.09 × 10{sup −3} mm{sup 2}/s was associated with 94.4% sensitivity and 85.7% specificity in distinguishing grade 1 and grade 2/3 cancer. The difference in mean ADC values was statistically significant for early stage (FIGO stage I) and advanced stage (FIGO stage II-IV) cancer (P = 0.011). The interobserver agreement for the mean ADC values of epithelial ovarian cancers was excellent. Conclusion: The mean ADC values of the solid portion of epithelial ovarian cancers negatively correlated to histologic grade and surgical stage. The mean ADC values may be useful imaging
Jin, Ying; Myers, Nicholas D.; Ahn, Soyeon
2014-01-01
Previous research has demonstrated that differential item functioning (DIF) methods that do not account for multilevel data structure could result in too frequent rejection of the null hypothesis (i.e., no DIF) when the intraclass correlation coefficient (?) of the studied item was the same as the ? of the total score. The current study extended…
Improvement of Similarity Measure:Pearson Product-Moment Correlation Coefficient%相似度的评价指标相关系数的改进
刘永锁; 孟庆华; 陈蓉; 王健松; 蒋淑敏; 胡育筑
2004-01-01
Aim To study the reason of the insensitiveness of Pearson product-moment correlation coefficient as a similarity measure and the method to improve its sensitivity. Methods Experimental and simulated data sets were used. Results The distribution range of the data sets influences the sensitivity of Pearson product-moment correlation coefficient.Weighted Pearson product-moment correlation coefficient is more sensitive when the range of the data set is large. Conclusion Weighted Pearson product-moment correlation coefficient is necessary when the range of the data set is large.%目的研究相似度的评价指标:相关系数的灵敏度低的原因及其改进的方法.方法利用实验数据和模拟数据研究相关系数的灵敏度低的问题.结果相关系数的灵敏度受数据的分布范围的影响,在数据的分布范围宽时加权相关系数更灵敏.结论在数据的分布范围宽时有必要进行加权运算.
Jin, Ying; Myers, Nicholas D.; Ahn, Soyeon
2014-01-01
Previous research has demonstrated that differential item functioning (DIF) methods that do not account for multilevel data structure could result in too frequent rejection of the null hypothesis (i.e., no DIF) when the intraclass correlation coefficient (?) of the studied item was the same as the ? of the total score. The current study extended…
Franks, Peter J; Drake, Paul L; Beerling, David J
2009-01-01
.... However, using basic equations for gas diffusion through stomata of different sizes, we show that a negative correlation between S and D offers several advantages, including plasticity in gwmax...
Gray, Heewon Lee; Burgermaster, Marissa; Tipton, Elizabeth; Contento, Isobel R; Koch, Pamela A; Di Noia, Jennifer
2016-04-01
Sample size and statistical power calculation should consider clustering effects when schools are the unit of randomization in intervention studies. The objective of the current study was to investigate how student outcomes are clustered within schools in an obesity prevention trial. Baseline data from the Food, Health & Choices project were used. Participants were 9- to 13-year-old students enrolled in 20 New York City public schools (n= 1,387). Body mass index (BMI) was calculated based on measures of height and weight, and body fat percentage was measured with a Tanita® body composition analyzer (Model SC-331s). Energy balance-related behaviors were self-reported with a frequency questionnaire. To examine the cluster effects, intraclass correlation coefficients (ICCs) were calculated as school variance over total variance for outcome variables. School-level covariates, percentage students eligible for free and reduced-price lunch, percentage Black or Hispanic, and English language learners were added in the model to examine ICC changes. The ICCs for obesity indicators are: .026 for BMI-percentile, .031 for BMIz-score, .035 for percentage of overweight students, .037 for body fat percentage, and .041 for absolute BMI. The ICC range for the six energy balance-related behaviors are .008 to .044 for fruit and vegetables, .013 to .055 for physical activity, .031 to .052 for recreational screen time, .013 to .091 for sweetened beverages, .033 to .121 for processed packaged snacks, and .020 to .083 for fast food. When school-level covariates were included in the model, ICC changes varied from -95% to 85%. This is the first study reporting ICCs for obesity-related anthropometric and behavioral outcomes among New York City public schools. The results of the study may aid sample size estimation for future school-based cluster randomized controlled trials in similar urban setting and population. Additionally, identifying school-level covariates that can reduce cluster
Chirico, Nicola; Gramatica, Paola
2011-09-26
The main utility of QSAR models is their ability to predict activities/properties for new chemicals, and this external prediction ability is evaluated by means of various validation criteria. As a measure for such evaluation the OECD guidelines have proposed the predictive squared correlation coefficient Q(2)(F1) (Shi et al.). However, other validation criteria have been proposed by other authors: the Golbraikh-Tropsha method, r(2)(m) (Roy), Q(2)(F2) (Schüürmann et al.), Q(2)(F3) (Consonni et al.). In QSAR studies these measures are usually in accordance, though this is not always the case, thus doubts can arise when contradictory results are obtained. It is likely that none of the aforementioned criteria is the best in every situation, so a comparative study using simulated data sets is proposed here, using threshold values suggested by the proponents or those widely used in QSAR modeling. In addition, a different and simple external validation measure, the concordance correlation coefficient (CCC), is proposed and compared with other criteria. Huge data sets were used to study the general behavior of validation measures, and the concordance correlation coefficient was shown to be the most restrictive. On using simulated data sets of a more realistic size, it was found that CCC was broadly in agreement, about 96% of the time, with other validation measures in accepting models as predictive, and in almost all the examples it was the most precautionary. The proposed concordance correlation coefficient also works well on real data sets, where it seems to be more stable, and helps in making decisions when the validation measures are in conflict. Since it is conceptually simple, and given its stability and restrictiveness, we propose the concordance correlation coefficient as a complementary, or alternative, more prudent measure of a QSAR model to be externally predictive.
Klöckner, Wolf; Gacem, Riad; Anderlei, Tibor; Raven, Nicole; Schillberg, Stefan; Lattermann, Clemens; Büchs, Jochen
2013-12-02
Among disposable bioreactor systems, cylindrical orbitally shaken bioreactors show important advantages. They provide a well-defined hydrodynamic flow combined with excellent mixing and oxygen transfer for mammalian and plant cell cultivations. Since there is no known universal correlation between the volumetric mass transfer coefficient for oxygen kLa and relevant operating parameters in such bioreactor systems, the aim of this current study is to experimentally determine a universal kLa correlation. A Respiration Activity Monitoring System (RAMOS) was used to measure kLa values in cylindrical disposable shaken bioreactors and Buckingham's π-Theorem was applied to define a dimensionless equation for kLa. In this way, a scale- and volume-independent kLa correlation was developed and validated in bioreactors with volumes from 2 L to 200 L. The final correlation was used to calculate cultivation parameters at different scales to allow a sufficient oxygen supply of tobacco BY-2 cell suspension cultures. The resulting equation can be universally applied to calculate the mass transfer coefficient for any of seven relevant cultivation parameters such as the reactor diameter, the shaking frequency, the filling volume, the viscosity, the oxygen diffusion coefficient, the gravitational acceleration or the shaking diameter within an accuracy range of +/- 30%. To our knowledge, this is the first kLa correlation that has been defined and validated for the cited bioreactor system on a bench-to-pilot scale.
Hu, Hui; Lu, Hong; He, Zhanping; Han, Xiangjun; Chen, Jing; Tu, Rong
2012-07-25
To investigate the effects of mRNA interference on aquaporin-4 expression in swollen tissue of rats with ischemic cerebral edema, and diagnose the significance of diffusion-weighted MRI, we injected 5 μL shRNA- aquaporin-4 (control group) or siRNA- aquaporin-4 solution (1:800) (RNA interference group) into the rat right basal ganglia immediately before occlusion of the middle cerebral artery. At 0.25 hours after occlusion of the middle cerebral artery, diffusion-weighted MRI displayed a high signal; within 2 hours, the relative apparent diffusion coefficient decreased markedly, aquaporin-4 expression increased rapidly, and intracellular edema was obviously aggravated; at 4 and 6 hours, the relative apparent diffusion coefficient slowly returned to control levels, aquaporin-4 expression slightly increased, and angioedema was observed. In the RNA interference group, during 0.25-6 hours after injection of siRNA- aquaporin-4 solution, the relative apparent diffusion coefficient slightly fluctuated and aquaporin-4 expression was upregulated; during 0.5-4 hours, the relative apparent diffusion coefficient was significantly higher, while aquaporin-4 expression was significantly lower when compared with the control group, and intracellular edema was markedly reduced; at 0.25 and 6 hours, the relative apparent diffusion coefficient and aquaporin-4 expression were similar when compared with the control group; obvious angioedema remained at 6 hours. Pearson's correlation test results showed that aquaporin-4 expression was negatively correlated with the apparent diffusion coefficient (r = -0.806, P coefficient. Aquaporin-4 gene interference can effectively inhibit the upregulation of aquaporin-4 expression during the stage of intracellular edema with time-effectiveness. Moreover, diffusion-weighted MRI can accurately detect intracellular edema.
Hui Hu; Hong Lu; Zhanping He; Xiangjun Han; Jing Chen; Rong Tu
2012-01-01
To investigate the effects of mRNA interference on aquaporin-4 expression in swollen tissue of rats with ischemic cerebral edema, and diagnose the significance of diffusion-weighted MRI, we injected 5 μL shRNA- aquaporin-4 (control group) or siRNA- aquaporin-4 solution (1:800) (RNA interference group) into the rat right basal ganglia immediately before occlusion of the middle cerebral artery. At 0.25 hours after occlusion of the middle cerebral artery, diffusion-weighted MRI displayed a high signal; within 2 hours, the relative apparent diffusion coefficient decreased markedly, aquaporin-4 expression increased rapidly, and intracellular edema was obviously aggravated; at 4 and 6 hours, the relative apparent diffusion coefficient slowly returned to control levels, aquaporin-4 expression slightly increased, and angioedema was observed. In the RNA interference group, during 0.25- 6 hours after injection of siRNA- aquaporin-4 solution, the relative apparent diffusion coefficient slightly fluctuated and aquaporin-4 expression was upregulated; during 0.5-4 hours, the relative apparent diffusion coefficient was significantly higher, while aquaporin-4 expression was significantly lower when compared with the control group, and intracellular edema was markedly reduced; at 0.25 and 6 hours, the relative apparent diffusion coefficient and aquaporin-4 expression were similar when compared with the control group; obvious angioedema remained at 6 hours. Pearson's correlation test results showed that aquaporin-4 expression was negatively correlated with the apparent diffusion coefficient (r = -0.806, P < 0.01). These findings suggest that upregulated aquaporin-4 expression is likely to be the main molecular mechanism of intracellular edema and may be the molecular basis for decreased relative apparent diffusion coefficient. Aquaporin-4 gene interference can effectively inhibit the upregulation of aquaporin-4 expression during the stage of intracellular edema with time
Kong, Eunjung; Chun, Kyung Ah; Cho, Ihn Ho
2017-01-01
Metabolism and water diffusion may have a relationship or an effect on each other in the same tumor. Knowledge of their relationship could expand the understanding of tumor biology and serve the field of oncologic imaging. This study aimed to evaluate the relationship between metabolism and water diffusivity in hepatic tumors using a simultaneous positron emission tomography/magnetic resonance imaging (PET/MRI) system with F-18 fluorodeoxyglucose (FDG) and to reveal the metabolic and diffusional characteristics of each type of hepatic tumor. Forty-one patients (mean age 63 ± 13 years, 31 male) with hepatic tumors (18 hepatocellular carcinoma [HCC], six cholangiocarcinoma [CCC], 10 metastatic tumors, one neuroendocrine malignancy, and six benign lesions) underwent FDG PET/MRI before treatment. Maximum standard uptake (SUVmax) values from FDG PET and the apparent diffusion coefficient (ADC) from the diffusion-weighted images were obtained for the tumor and their relationships were examined. We also investigated the difference in SUVmax and ADC for each type of tumor. SUVmax showed a negative correlation with ADC (r = -0.404, p = 0.009). The median of SUVmax was 3.22 in HCC, 6.99 in CCC, 6.30 in metastatic tumors, and 1.82 in benign lesions. The median of ADC was 1.039 × 10-3 mm/s2 in HCC, 1.148 × 10-3 mm/s2 in CCC, 0.876 × 10-3 mm/s2 in metastatic tumors, and 1.323 × 10-3 mm/s2 in benign lesions. SUVmax was higher in metastatic tumors than in benign lesions (p = 0.023). Metastatic tumors had a lower ADC than CCC (p = 0.039) and benign lesions (p = 0.004). HCC had a lower ADC than benign lesions, with a suggestive trend (p = 0.06). Our results indicate that SUVmax is negatively correlated with ADC in hepatic tumors, and each group of tumors has different metabolic and water diffusivity characteristics. Evaluation of hepatic tumors by PET/MRI could be helpful in understanding tumor characteristics.
Consalvi, J. L.; Nmira, F.
2016-03-01
The main objective of this article is to quantify the influence of the soot absorption coefficient-Planck function correlation on radiative loss and flame structure in an oxygen-enhanced propane turbulent diffusion flame. Calculations were run with and without accounting for this correlation by using a standard k-ε model and the steady laminar flamelet model (SLF) coupled to a joint Probability Density Function (PDF) of mixture fraction, enthalpy defect, scalar dissipation rate, and soot quantities. The PDF transport equation is solved by using a Stochastic Eulerian Field (SEF) method. The modeling of soot production is carried out by using a flamelet-based semi-empirical acetylene/benzene soot model. Radiative heat transfer is modeled by using a wide band correlated-k model and turbulent radiation interactions (TRI) are accounted for by using the Optically-Thin Fluctuation Approximation (OTFA). Predicted soot volume fraction, radiant wall heat flux distribution and radiant fraction are in good agreement with the available experimental data. Model results show that soot absorption coefficient and Planck function are negatively correlated in the region of intense soot emission. Neglecting this correlation is found to increase significantly the radiative loss leading to a substantial impact on flame structure in terms of mean and rms values of temperature. In addition mean and rms values of soot volume fraction are found to be less sensitive to the correlation than temperature since soot formation occurs mainly in a region where its influence is low.
Larsen, Thomas; Kjeldsen, Peter; Christensen, Thomas Højlund
1992-01-01
area of the aquifer materials as a second regression parameter did not significantly improve the correlation. Estimated Koc values were up to 3 times higher than those predicted from regression equations based on the octanol-water partition coefficient. The reason for this is not known, but may...... by the distribution coefficient, Kd, since the isotherms were linear: Kd(benzene): 0.05–0.65, Kd(TCA): 0.04–0.55, and Kd(naphthalene): 0.1–15.7 ml/g. Correlating observed Kd values to the organic carbon content of the aquifer materials explained only 52–65 % of the variance in Kd. Introducing the specific surface...
Echavarría-Heras, Héctor; Leal-Ramírez, Cecilia; Villa-Diharce, Enrique; Castillo, Oscar
2014-01-01
Eelgrass is a cosmopolitan seagrass species that provides important ecological services in coastal and near-shore environments. Despite its relevance, loss of eelgrass habitats is noted worldwide. Restoration by replanting plays an important role, and accurate measurements of the standing crop and productivity of transplants are important for evaluating restoration of the ecological functions of natural populations. Traditional assessments are destructive, and although they do not harm natural populations, in transplants the destruction of shoots might cause undesirable alterations. Non-destructive assessments of the aforementioned variables are obtained through allometric proxies expressed in terms of measurements of the lengths or areas of leaves. Digital imagery could produce measurements of leaf attributes without the removal of shoots, but sediment attachments, damage infringed by drag forces or humidity contents induce noise-effects, reducing precision. Available techniques for dealing with noise caused by humidity contents on leaves use the concepts of adjacency, vicinity, connectivity and tolerance of similarity between pixels. Selection of an interval of tolerance of similarity for efficient measurements requires extended computational routines with tied statistical inferences making concomitant tasks complicated and time consuming. The present approach proposes a simplified and cost-effective alternative, and also a general tool aimed to deal with any sort of noise modifying eelgrass leaves images. Moreover, this selection criterion relies only on a single statistics; the calculation of the maximum value of the Concordance Correlation Coefficient for reproducibility of observed areas of leaves through proxies obtained from digital images. Available data reveals that the present method delivers simplified, consistent estimations of areas of eelgrass leaves taken from noisy digital images. Moreover, the proposed procedure is robust because both the optimal
Kuzuha, Yasuhisa; Sivapalan, Murugesu; Tomosugi, Kunio; Kishii, Tokuo; Komatsu, Yosuke
2006-04-01
Eagleson's classical regional flood frequency model is investigated. Our intention was not to improve the model, but to reveal previously unidentified important and dominant hydrological processes in it. The change of the coefficient of variation (CV) of annual maximum discharge with catchment area can be viewed as representing the spatial variance of floods in a homogeneous region. Several researchers have reported that the CV decreases as the catchment area increases, at least for large areas. On the other hand, Eagleson's classical studies have been known as pioneer efforts that combine the concept of similarity analysis (scaling) with the derived flood frequency approach. As we have shown, the classical model can reproduce the empirical relationship between the mean annual maximum discharge and catchment area, but it cannot reproduce the empirical decreasing CV-catchment area curve. Therefore, we postulate that previously unidentified hydrological processes would be revealed if the classical model were improved to reproduce the decreasing of CV with catchment area. First, we attempted to improve the classical model by introducing a channel network, but this was ineffective. However, the classical model was improved by introducing a two-parameter gamma distribution for rainfall intensity. What is important is not the gamma distribution itself, but those characteristics of spatial variability of rainfall intensity whose CV decreases with increasing catchment area. Introducing the variability of rainfall intensity into the hydrological simulations explains how the CV of rainfall intensity decreases with increasing catchment area. It is difficult to reflect the rainfall-runoff processes in the model while neglecting the characteristics of rainfall intensity from the viewpoint of annual flood discharge variances.
Mahdi Alajmi; Abdullah Shalwan
2015-01-01
The correlation between the mechanical properties of Fillers/Epoxy composites and their tribological behavior was investigated. Tensile, hardness, wear, and friction tests were conducted for Neat Epoxy (NE), Graphite/Epoxy composites (GE), and Data Palm Fiber/Epoxy with or without Graphite composites (GFE and FE). The correlation was made between the tensile strength, the modulus of elasticity, elongation at the break, and the hardness, as an individual or a combined factor, with the specific...
Mary Hokazono
Full Text Available CONTEXT AND OBJECTIVE: Transcranial Doppler (TCD detects stroke risk among children with sickle cell anemia (SCA. Our aim was to evaluate TCD findings in patients with different sickle cell disease (SCD genotypes and correlate the time-averaged maximum mean (TAMM velocity with hematological characteristics. DESIGN AND SETTING: Cross-sectional analytical study in the Pediatric Hematology sector, Universidade Federal de São Paulo. METHODS: 85 SCD patients of both sexes, aged 2-18 years, were evaluated, divided into: group I (62 patients with SCA/Sß0 thalassemia; and group II (23 patients with SC hemoglobinopathy/Sß+ thalassemia. TCD was performed and reviewed by a single investigator using Doppler ultrasonography with a 2 MHz transducer, in accordance with the Stroke Prevention Trial in Sickle Cell Anemia (STOP protocol. The hematological parameters evaluated were: hematocrit, hemoglobin, reticulocytes, leukocytes, platelets and fetal hemoglobin. Univariate analysis was performed and Pearson's coefficient was calculated for hematological parameters and TAMM velocities (P < 0.05. RESULTS: TAMM velocities were 137 ± 28 and 103 ± 19 cm/s in groups I and II, respectively, and correlated negatively with hematocrit and hemoglobin in group I. There was one abnormal result (1.6% and five conditional results (8.1% in group I. All results were normal in group II. Middle cerebral arteries were the only vessels affected. CONCLUSION: There was a low prevalence of abnormal Doppler results in patients with sickle-cell disease. Time-average maximum mean velocity was significantly different between the genotypes and correlated with hematological characteristics.
王凯; 冯晅; 刘财
2012-01-01
横波分裂是各向异性介质的重要特征,当横波或转换波穿过各向异性介质到达地面时,地面三分量检波器的x分量和y分量接收到的地震记录中都会同时存在快横波和慢横波.将快横波和慢横波进行分离,进而计算介质的各向异性参数是多分量数据处理中重要的一步.将数学中的Pearson相关系数引入到多分量地震勘探中,提出了Pearson相关系数法进行旋转角度识别,进而分离快、慢横波波场.相比于传统的互相关法,Pearson相关系数法从精度、抗噪性能和计算效率上都有提高.%Shear-wave splitting is an important characteristic of anisotropic media. Generally, when S or P-SV waves reach to the ground through anisotropic media, the seismic record received by x component and y component of three-component detector contains fast wave and slow wave simultaneously- Separating fast wave and slow wave and then calculating the anisotropic parameters of media are an important step in multi-component data processing. The authors introduce the Pearson correlation coefficients into multi-component seismic exploration and propose the Pearson correlation coefficients to detect the rotation angle and then separate the fast wave and slow wave. Compared with the traditional cross-correlation method, the Pearson correlation coefficient method is better in accuracy, noise immunity and computational efficiency.
Christensen, Eva Arnspang; Koffman, Jennifer Skaarup; Marlar, Saw
2014-01-01
Lateral diffusion and compartmentalization of plasma membrane proteins are tightly regulated in cells and thus, studying these processes will reveal new insights to plasma membrane protein function and regulation. Recently, k-Space Image Correlation Spectroscopy (kICS)1 was developed to enable ro...
Anwar Fitrianto
2014-01-01
Full Text Available When independent variables have high linear correlation in a multiple linear regression model, we can have wrong analysis. It happens if we do the multiple linear regression analysis based on common Ordinary Least Squares (OLS method. In this situation, we are suggested to use ridge regression estimator. We conduct some simulation study to compare the performance of ridge regression estimator and the OLS. We found that Hoerl and Kennard ridge regression estimation method has better performance than the other approaches.
Park, Eun Kyung; Cho, Kyu Ran; Seo, Bo Kyoung; Woo, Ok Hee; Cho, Sung Bum; Bae, Jeoung Won
2016-01-01
Breast cancer is a heterogeneous disease with diverse prognoses. The main prognostic determinants are lymph node status, tumor size, histological grade, and biological factors, such as hormone receptors, human epidermal growth factor receptor 2 (HER2), Ki-67 protein levels, and p53 expression. Diffusion-weighted imaging (DWI) can be used to measure the apparent diffusion coefficient (ADC) that provides information related to tumor cellularity and the integrity of the cell membranes. The goal of this study was to evaluate whether ADC measurements could provide information on the prognostic factors of breast cancer. A total of 71 women with invasive breast cancer, treated consecutively, who underwent preoperative breast MRIs with DWI at 3.0 Tesla and subsequent surgery, were prospectively included in this study. Each DWI was acquired with b values of 0 and 1000 s/mm(2). The mean ADC values of the lesions were measured, including the entire lesion on the three largest sections. We performed histopathological analyses for the tumor size, lymph node status, histological grade, hormone receptors, human epidermal growth factor receptor 2 (HER2), Ki-67, p53, and molecular subtypes. The associations with the ADC values and prognostic factors of breast cancer were evaluated using the independent-samples t test and the one-way analysis of variance (ANOVA). A low ADC value was associated with lymph node metastasis (P < 0.01) and with high Ki-67 protein levels (P = 0.03). There were no significant differences in the ADC values among the histological grade (P = 0.48), molecular subtype (P = 0.51), tumor size (P = 0.46), and p53 protein level (P = 0.62). The pre-operative use of the 3.0 Tesla DWI could provide information about the lymph node status and tumor proliferation for breast cancer patients, and could help determine the optimal treatment plan.
Petzoldt, G.
2007-08-29
In the four beam times we performed at the FRM-II, we were able to show that the spectrometer works in principle and that a determination of a with it is possible. A set of routines has been written for decoding and analyzing the raw data. The routines are written in C using the ROOT libraries and can be easily adapted or expanded. We have found a reliable way to extract the proton count rates from the data by building pulseheight spectra for each measurement, subtracting background measurements from those and fitting the resulting peak with a Gaussian. The background of the measurements was studied in detail. The background caused by electrons from neutron decay is very well understood and conforms quantitatively to our expectation. Due to the spatial resolution of our detector and the time resolution provided by our DAQ electronics, we were able to study correlated electron-proton pairs from one neutron decay event. They form a clearly visible peak in a time- and channel-distance spectrum, which can be shifted in the channel-dimension by varying the voltages applied to the lower and upper E x B electrodes. Performing a pulseheight analysis for both involved particles allowed us to obtain a fairly clean energy spectrum of the background caused by electrons from neutron decay in our detector. Using these correlations for data analysis may be of interest for future neutron decay experiments which use segmented detectors. (orig.)
Sigaut, Lorena; Villarruel, Cecilia; Ponce, María Laura; Ponce Dawson, Silvina
2017-06-01
Many cell signaling pathways involve the diffusion of messengers that bind and unbind to and from intracellular components. Quantifying their net transport rate under different conditions then requires having separate estimates of their free diffusion coefficient and binding or unbinding rates. In this paper, we show how performing sets of fluorescence correlation spectroscopy (FCS) experiments under different conditions, it is possible to quantify free diffusion coefficients and on and off rates of reaction-diffusion systems. We develop the theory and present a practical implementation for the case of the universal second messenger, calcium (Ca2 +) and single-wavelength dyes that increase their fluorescence upon Ca2 + binding. We validate the approach with experiments performed in aqueous solutions containing Ca2 + and Fluo4 dextran (both in its high and low affinity versions). Performing FCS experiments with tetramethylrhodamine-dextran in Xenopus laevis oocytes, we infer the corresponding free diffusion coefficients in the cytosol of these cells. Our approach can be extended to other physiologically relevant reaction-diffusion systems to quantify biophysical parameters that determine the dynamics of various variables of interest.
OU Xiaojuan; ZHOU Wei
2007-01-01
Global positioning system (GPS)common-view observation data were processed by using the multi-scale Kalman algorithm based on a correlative structure of the discrete wavelet coefficients.Suppose that the GPS common-view observation data has the 1/f fractal characteristic,the algorithm of wavelet transform was used to estimate the Hurst parameter H of GPS clock difference data.When 0＜H＜1,the 1/f fractal characteristic of the GPS clock difference data iS a Gaussian zero-mean and non-stationary stochastic process.Thus,the discrete wavelet coefficients can be discussed in the process of estimating multi-scale Kalman coefficients.Furthermore,the discrete clock difierence can be estimated.The single-channel and multi-channel common-view observation data were processed respectively.Comparisons were made between the results obtained and the Circular T data.Simulation results show that the algorithm discussed in this paper is both feasible and effective.
Guo, Yuan; Kong, Qing-Cong; Zhu, Ye-Qing; Liu, Zhen-Zhen; Peng, Ling-Rong; Tang, Wen-Jie; Yang, Rui-Meng; Xie, Jia-Jun; Liu, Chun-Ling
2017-06-22
To evaluate the utility of the whole-lesion histogram apparent diffusion coefficient (ADC) for characterizing the heterogeneity of mucinous breast carcinoma (MBC) and to determine which ADC metrics may help to best differentiate subtypes of MBC. This retrospective study involved 52 MBC patients, including 37 pure MBC (PMBC) and 15 mixed MBC (MMBC). The PMBC patients were subtyped into PMBC-A (20 cases) and PMBC-B (17 cases) groups. All patients underwent preoperative diffusion-weighted imaging (DWI) at 1.5T and the whole-lesion ADC assessments were generated. Histogram-derived ADC parameters were compared between PMBC vs. MMBC and PMBC-A vs. PMBC-B, and receiver operating characteristic (ROC) curve analysis was used to determine optimal histogram parameters for differentiating these groups. The PMBC group exhibited significantly higher ADC values for the mean (P = 0.004), 25(th) (P = 0.004), 50(th) (P = 0.004), 75(th) (P = 0.006), and 90(th) percentiles (P = 0.013) and skewness (P = 0.021) than did the MMBC group. The 25(th) percentile of ADC values achieved the highest area under the curve (AUC) (0.792), with a cutoff value of 1.345 × 10(-3) mm(2) /s, in distinguishing PMBC and MMBC. The PMBC-A group showed significantly higher ADC values for the mean (P = 0.049), 25(th) (P = 0.015), and 50(th) (P = 0.026) percentiles and skewness (P = 0.004) than did the PMBC-B group. The 25(th) percentile of the ADC cutoff value (1.476 × 10(-3) mm(2) /s) demonstrated the best AUC (0.837) among the ADC values for distinguishing PMBC-A and PMBC-B. Whole-lesion ADC histogram analysis enables comprehensive evaluation of an MBC in its entirety and differentiating subtypes of MBC. Thus, it may be a helpful and supportive tool for conventional MRI. 4 TECHNICAL EFFICACY: Stage 2 J. Magn. Reson. Imaging 2017. © 2017 International Society for Magnetic Resonance in Medicine.
Sun, Yangbo; Chen, Long; Huang, Bisheng; Chen, Keli
2017-07-01
As a mineral, the traditional Chinese medicine calamine has a similar shape to many other minerals. Investigations of commercially available calamine samples have shown that there are many fake and inferior calamine goods sold on the market. The conventional identification method for calamine is complicated, therefore as a result of the large scale of calamine samples, a rapid identification method is needed. To establish a qualitative model using near-infrared (NIR) spectroscopy for rapid identification of various calamine samples, large quantities of calamine samples including crude products, counterfeits and processed products were collected and correctly identified using the physicochemical and powder X-ray diffraction method. The NIR spectroscopy method was used to analyze these samples by combining the multi-reference correlation coefficient (MRCC) method and the error back propagation artificial neural network algorithm (BP-ANN), so as to realize the qualitative identification of calamine samples. The accuracy rate of the model based on NIR and MRCC methods was 85%; in addition, the model, which took comprehensive multiple factors into consideration, can be used to identify crude calamine products, its counterfeits and processed products. Furthermore, by in-putting the correlation coefficients of multiple references as the spectral feature data of samples into BP-ANN, a BP-ANN model of qualitative identification was established, of which the accuracy rate was increased to 95%. The MRCC method can be used as a NIR-based method in the process of BP-ANN modeling.
Climer, Sharlee; Yang, Wei; de las Fuentes, Lisa; Dávila-Román, Victor G; Gu, C Charles
2014-11-01
Complex diseases are often associated with sets of multiple interacting genetic factors and possibly with unique sets of the genetic factors in different groups of individuals (genetic heterogeneity). We introduce a novel concept of custom correlation coefficient (CCC) between single nucleotide polymorphisms (SNPs) that address genetic heterogeneity by measuring subset correlations autonomously. It is used to develop a 3-step process to identify candidate multi-SNP patterns: (1) pairwise (SNP-SNP) correlations are computed using CCC; (2) clusters of so-correlated SNPs identified; and (3) frequencies of these clusters in disease cases and controls compared to identify disease-associated multi-SNP patterns. This method identified 42 candidate multi-SNP associations with hypertensive heart disease (HHD), among which one cluster of 22 SNPs (six genes) included 13 in SLC8A1 (aka NCX1, an essential component of cardiac excitation-contraction coupling) and another of 32 SNPs had 29 from a different segment of SLC8A1. While allele frequencies show little difference between cases and controls, the cluster of 22 associated alleles were found in 20% of controls but no cases and the other in 3% of controls but 20% of cases. These suggest that both protective and risk effects on HHD could be exerted by combinations of variants in different regions of SLC8A1, modified by variants from other genes. The results demonstrate that this new correlation metric identifies disease-associated multi-SNP patterns overlooked by commonly used correlation measures. Furthermore, computation time using CCC is a small fraction of that required by other methods, thereby enabling the analyses of large GWAS datasets.
P Brandmaier
Full Text Available Previous non-simultaneous PET/MR studies have shown heterogeneous results about the correlation between standardized uptake values (SUVs and apparent diffusion coefficients (ADCs. The aim of this study was to investigate correlations in patients with primary and recurrent tumors using a simultaneous PET/MRI system which could lead to a better understanding of tumor biology and might play a role in early response assessment.We included 31 patients with histologically confirmed primary (n = 14 or recurrent cervical cancer (n = 17 who underwent simultaneous whole-body 18F-FDG-PET/MRI comprising DWI. Image analysis was performed by a radiologist and a nuclear physician who identified tumor margins and quantified ADC and SUV. Pearson correlations were calculated to investigate the association between ADC and SUV.92 lesions were detected. We found a significant inverse correlation between SUVmax and ADCmin (r = -0.532, p = 0.05 in primary tumors as well as in primary metastases (r = -0.362, p = 0.05 and between SUVmean and ADCmin (r = -0.403, p = 0.03. In recurrent local tumors we found correlations for SUVmax and ADCmin (r = -0.747, p = 0.002 and SUVmean and ADCmin (r = -0.773, p = 0.001. Associations for recurrent metastases were not significant (p>0.05.Our study demonstrates the feasibility of fast and reliable measurement of SUV and ADC with simultaneous PET/MRI. In patients with cervical cancer we found significant inverse correlations for SUV and ADC which could play a major role for further tumor characterization and therapy decisions.
Maximum phonation time: variability and reliability.
Speyer, Renée; Bogaardt, Hans C A; Passos, Valéria Lima; Roodenburg, Nel P H D; Zumach, Anne; Heijnen, Mariëlle A M; Baijens, Laura W J; Fleskens, Stijn J H M; Brunings, Jan W
2010-05-01
The objective of the study was to determine maximum phonation time reliability as a function of the number of trials, days, and raters in dysphonic and control subjects. Two groups of adult subjects participated in this reliability study: a group of outpatients with functional or organic dysphonia versus a group of healthy control subjects matched by age and gender. Over a period of maximally 6 weeks, three video recordings were made of five subjects' maximum phonation time trials. A panel of five experts were responsible for all measurements, including a repeated measurement of the subjects' first recordings. Patients showed significantly shorter maximum phonation times compared with healthy controls (on average, 6.6 seconds shorter). The averaged interclass correlation coefficient (ICC) over all raters per trial for the first day was 0.998. The averaged reliability coefficient per rater and per trial for repeated measurements of the first day's data was 0.997, indicating high intrarater reliability. The mean reliability coefficient per day for one trial was 0.939. When using five trials, the reliability increased to 0.987. The reliability over five trials for a single day was 0.836; for 2 days, 0.911; and for 3 days, 0.935. To conclude, the maximum phonation time has proven to be a highly reliable measure in voice assessment. A single rater is sufficient to provide highly reliable measurements.
Goi, Takanori; Nakazawa, Toshiyuki; Hirono, Yasuo; Yamaguchi, Akio
2015-10-06
The angiogenic proteins vascular endothelial growth factor (VEGF) and prokineticin1 (PROK1) proteins are considered important in colorectal cancer, the relationship between their simultaneous expression and prognosis was investigated in the present study. VEGF and PROK1 expression in 620 primary human colorectal cancer lesions was confirmed via immunohistochemical staining with anti-VEGF and anti-PROK1 antibodies, and the correlation between the expression of these 2 proteins and recurrence/prognosis were investigated. VEGF protein was expressed in 329 (53.1%) and PROK1 protein was expressed in 223 (36.0%). PROK1 and VEGF were simultaneously expressed in 116 (18.7%) of the 620 cases. The correlation coefficient between VEGF expression and PROK1 expression was r = 0.11, and therefore correlation was not observed. Clinical pathology revealed that substantially lymphnode matastasis, hematogenous metastasis, or TMN advanced-stage IV was significantly more prevalent in cases that expressed both VEGF and PROK1 than in the cases negative for both proteins or those positive for only 1 of the proteins. Also the cases positive for both proteins exhibited the worst recurrence and prognosis. In the Cox proportional hazards model, VEGF and PROK1 expression was an independent prognostic factor. The prognosis was poorer in colorectal cancers that expressed both PROK1 and VEGF relative to the cases that expressed only 1 protein, and the expression of both proteins was found to be an independent prognostic factor.
Vincze, Julianna; Valiskó, Mónika; Boda, Dezso
2010-10-21
We propose a simple model to explain the nonmonotonic concentration dependence of the mean activity coefficient of simple electrolytes without using any adjustable parameters. The primitive model of electrolytes is used to describe the interaction between ions computed by the adaptive grand canonical Monte Carlo method. For the dielectric constant of the electrolyte, we use experimental concentration dependent values. This is included through a solvation term in our treatment to describe the interaction between ions and water that changes as the dielectric constant changes with concentration. This term is computed by a Born-treatment fitted to experimental hydration energies. Our results for LiCl, NaCl, KCl, CsCl, NaBr, NaI, MgCl(2), CaCl(2), SrCl(2), and BaCl(2) demonstrate that the principal reason of the nonmonotonic behavior of the activity coefficient is a balance between the solvation and ion-ion correlation terms. This conclusion differs from previous studies that assumed that it is the balance of hard sphere repulsion and electrostatic attraction that produces the nonmonotonic behavior. Our results indicate that the earlier assumption that solvation can be taken into account by a larger, "solvated" ionic radius should be reconsidered. To explain second order effects (such as dependence on ionic size), we conclude that explicit water models are needed.
Mooney, Walter D.; Ritsema, Jeroen; Hwang, Yong Keun
2012-01-01
A joint analysis of global seismicity and seismic tomography indicates that the seismic potential of continental intraplate regions is correlated with the seismic properties of the lithosphere. Archean and Early Proterozoic cratons with cold, stable continental lithospheric roots have fewer crustal earthquakes and a lower maximum earthquake catalog moment magnitude (Mcmax). The geographic distribution of thick lithospheric roots is inferred from the global seismic model S40RTS that displays shear-velocity perturbations (δVS) relative to the Preliminary Reference Earth Model (PREM). We compare δVS at a depth of 175 km with the locations and moment magnitudes (Mw) of intraplate earthquakes in the crust (Schulte and Mooney, 2005). Many intraplate earthquakes concentrate around the pronounced lateral gradients in lithospheric thickness that surround the cratons and few earthquakes occur within cratonic interiors. Globally, 27% of stable continental lithosphere is underlain by δVS≥3.0%, yet only 6.5% of crustal earthquakes with Mw>4.5 occur above these regions with thick lithosphere. No earthquakes in our catalog with Mw>6 have occurred above mantle lithosphere with δVS>3.5%, although such lithosphere comprises 19% of stable continental regions. Thus, for cratonic interiors with seismically determined thick lithosphere (1) there is a significant decrease in the number of crustal earthquakes, and (2) the maximum moment magnitude found in the earthquake catalog is Mcmax=6.0. We attribute these observations to higher lithospheric strength beneath cratonic interiors due to lower temperatures and dehydration in both the lower crust and the highly depleted lithospheric root.
Demel, Anja; Feilke, Katharina; Wolf, Martin; Poets, Christian F.; Franz, Axel R.
2014-01-01
Near-infrared spectroscopy (NIRS) is increasingly used in neonatal intensive care. We investigated the impact of skin, bone, and cerebrospinal fluid (CSF) layer thickness in term and preterm infants on absorption-(μa) and/or reduced scattering coefficients (μs‧) measured by multidistance frequency-domain (FD)-NIRS. Transcranial ultrasound was performed to measure the layer thicknesses. Correlations were only statistically significant for μa at 692 nm with bone thickness and μs‧ at 834 nm with skin thickness. There is no evidence that skin, bone, or CSF thickness have an important effect on μa and μs‧. Layer thicknesses of skin, bone, and CSF in the range studied do not seem to affect cerebral oxygenation measurements by multidistance FD-NIRS significantly.
Benedikt Michael Schaarschmidt
Full Text Available To compare the apparent diffusion coefficient (ADC in lymph node metastases of non-small cell lung cancer (NSCLC patients with standardized uptake values (SUV derived from combined 18F-fluoro-deoxy-glucose-positron emission tomography/magnetic resonance imaging (18F-FDG PET/MRI.38 patients with histopathologically proven NSCLC (mean age 60.1 ± 9.5 y received whole-body PET/CT (Siemens mCT™ 60 min after injection of a mean dose of 280 ± 50 MBq 18F-FDG and subsequent PET/MRI (mean time after tracer injection: 139 ± 26 min, Siemens Biograph mMR. During PET acquisition, simultaneous diffusion-weighted imaging (DWI, b values: 0, 500, 1000 s/mm² was performed. A maximum of 10 lymph nodes per patient suspicious for malignancy were analyzed. Regions of interest (ROI were drawn covering the entire lymph node on the attenuation-corrected PET-image and the monoexponential ADC-map. According to histopathology or radiological follow-up, lymph nodes were classified as benign or malignant. Pearson's correlation coefficients were calculated for all lymph node metastases correlating SUVmax and SUVmean with ADCmean.A total of 146 suspicious lymph nodes were found in 25 patients. One hundred lymph nodes were eligible for final analysis. Ninety-one lymph nodes were classified as malignant and 9 as benign according to the reference standard. In malignant lesions, mean SUVmax was 9.1 ± 3.8 and mean SUVmean was 6.0 ± 2.5 while mean ADCmean was 877.0 ± 128.6 x10(-5 mm²/s in PET/MRI. For all malignant lymph nodes, a weak, inverse correlation between SUVmax and ADCmean as well as SUVmean and ADCmean (r = -0.30, p<0.05 and r = -0.36, p<0.05 existed.The present data show a weak inverse correlation between increased glucose-metabolism and cellularity in lymph node metastases of NSCLC patients. 18F-FDG-PET and DWI thus may offer complementary information for the evaluation of treatment response in lymph node metastases of NSCLC.
Cortesi, Nicola; Peña-Angulo, Dhais; Simolo, Claudia; Stepanek, Peter; Brunetti, Michele; Gonzalez-Hidalgo, José Carlos
2014-05-01
One of the key point in the develop of the MOTEDAS dataset (see Poster 1 MOTEDAS) in the framework of the HIDROCAES Project (Impactos Hidrológicos del Calentamiento Global en España, Spanish Ministery of Research CGL2011-27574-C02-01) is the reference series for which no generalized metadata exist. In this poster we present an analysis of spatial variability of monthly minimum and maximum temperatures in the conterminous land of Spain (Iberian Peninsula, IP), by using the Correlation Decay Distance function (CDD), with the aim of evaluating, at sub-regional level, the optimal threshold distance between neighbouring stations for producing the set of reference series used in the quality control (see MOTEDAS Poster 1) and the reconstruction (see MOREDAS Poster 3). The CDD analysis for Tmax and Tmin was performed calculating a correlation matrix at monthly scale between 1981-2010 among monthly mean values of maximum (Tmax) and minimum (Tmin) temperature series (with at least 90% of data), free of anomalous data and homogenized (see MOTEDAS Poster 1), obtained from AEMEt archives (National Spanish Meteorological Agency). Monthly anomalies (difference between data and mean 1981-2010) were used to prevent the dominant effect of annual cycle in the CDD annual estimation. For each station, and time scale, the common variance r2 (using the square of Pearson's correlation coefficient) was calculated between all neighbouring temperature series and the relation between r2 and distance was modelled according to the following equation (1): Log (r2ij) = b*°dij (1) being Log(rij2) the common variance between target (i) and neighbouring series (j), dij the distance between them and b the slope of the ordinary least-squares linear regression model applied taking into account only the surrounding stations within a starting radius of 50 km and with a minimum of 5 stations required. Finally, monthly, seasonal and annual CDD values were interpolated using the Ordinary Kriging with a
Kinkhabwala, Ali
2013-01-01
The most fundamental problem in statistics is the inference of an unknown probability distribution from a finite number of samples. For a specific observed data set, answers to the following questions would be desirable: (1) Estimation: Which candidate distribution provides the best fit to the observed data?, (2) Goodness-of-fit: How concordant is this distribution with the observed data?, and (3) Uncertainty: How concordant are other candidate distributions with the observed data? A simple unified approach for univariate data that addresses these traditionally distinct statistical notions is presented called "maximum fidelity". Maximum fidelity is a strict frequentist approach that is fundamentally based on model concordance with the observed data. The fidelity statistic is a general information measure based on the coordinate-independent cumulative distribution and critical yet previously neglected symmetry considerations. An approximation for the null distribution of the fidelity allows its direct conversi...
Zens, Joerg; Krauß, Lydia; Römer, Wolfgang; Klasen, Nicole; Pirson, Stéphane; Schulte, Philipp; Zeeden, Christian; Sirocko, Frank; Lehmkuhl, Frank
2016-04-01
The D1 project of the CRC 806 "Our way to Europe" focusses on Central Europe as a destination of modern human dispersal out of Africa. The paleo-environmental conditions along the migration areas are reconstructed by loess-paleosol sequences and lacustrine sediments. Stratigraphy and luminescence dating provide the chronological framework for the correlation of grain size and geochemical data to large-scale climate proxies like isotope ratios and dust content of Greenland ice cores. The reliability of correlations is improved by the development of precise age models of specific marker beds. In this study, we focus on the (terrestrial) Last Glacial Maximum of the Weichselian Upper Pleniglacial which is supposed to be dominated by high wind speeds and an increasing aridity. Especially in the Lower Rhine Embayment (LRE), this period is linked to an extensive erosion event. The disconformity is followed by an intensive cryosol formation. In order to support the stratigraphical observations from the field, luminescence dating and grain size analysis were applied on three loess-paleosol sequences along the northern European loess belt to develop a more reliable chronology and to reconstruct paleo-environmental dynamics. The loess sections were compared to newest results from heavy mineral and grain size analysis from the Dehner Maar core (Eifel Mountains) and correlated to NGRIP records. Volcanic minerals can be found in the Dehner Maar core from a visible tephra layer at 27.8 ka up to ~25 ka. They can be correlated to the Eltville Tephra found in loess section. New quartz luminescence ages from Romont (Belgium) surrounding the tephra dated the deposition between 25.0 + 2.3 ka and 25.8 + 2.4 ka. In the following, heavy minerals show an increasing importance of strong easterly winds during the second Greenland dust peak (~24 ka b2k) correlating with an extensive erosion event in the LRE. Luminescence dating on quartz bracketing the following soil formation yielded ages of
Iwasaki, Shingo; Kozawa, Junji; Fukui, Kenji; Iwahashi, Hiromi; Imagawa, Akihisa; Shimomura, Iichiro
2015-08-01
In type 1 diabetic patients, insulin secretory capacity, meals and physical activity correlate with glycemic variability. Autonomic function associated with gastrointestinal motility and counterregulatory hormone secretion is another candidate which correlates with glucose variability. The aim of this study is to clarify a new clinical parameter associated with glycemic variability in insulin-depleted patients with type 1 diabetes. We studied 31 inpatients with type 1 diabetes. We evaluated glycemic variability calculated by continuous glucose monitoring, clinical parameters and the coefficient of variation of R-R interval (CVR-R). Glycemic variability was also assessed during the daytime and nighttime. The CVR-R showed a significant negative correlation with the whole-day standard deviation (SD) (r = -0.50, p = 0.007), mean amplitude of glycemic excursions (MAGE) (r = -0.47, p=0.011), M-value (r = -0.38, p = 0.048) and mean of daily differences (MODD) (r = -0.59, p = 0.001). The CVR-R also showed a significant negative correlation with the nighttime SD (r = -0.59, p = 0.001), MAGE (r = -0.47, p=0.011), M-value (r = -0.53, p = 0.004) and MODD (r = -0.65, p = 0.0003). And furthermore, the CVR-R also showed a significant negative correlation with the daytime SD (r = -0.44, p = 0.019) and MAGE (r = -0.50, p = 0.006), but not with the daytime M-value or MODD. The nighttime SD was significantly higher in patients with diabetic polyneuropathy than in patients without it (p = 0.016), while the CVR-R was significantly lower in patients with polyneuropathy than in patients without it (p = 0.009). CVR-R is closely correlated with glycemic variability, especially during nighttime, in insulin-depleted patients with type 1 diabetes. Measuring CVR-R may help us to presume the degree of glycemic variability in those patients. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Inchingolo, Riccardo; De Gaetano, Anna Maria; Curione, Davide; Ciresa, Marzia; Miele, Luca; Pompili, Maurizio; Vecchio, Fabio Maria; Giuliante, Felice; Bonomo, Lorenzo
2015-04-01
To investigate the utility of diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC) and the correlation with hepatobiliary phase (delayed phase imaging, DPI) findings in the differentiation of cirrhotic hepatocellular nodules. Forty-three patients with 53 pathology-proven nodules (29 hepatocellular carcinomas (HCCs), 13 high-grade (HGDNs) and 11 low-grade dysplastic nodules (LGDNs); mean size 2.17 cm, range 1-4 cm), who underwent liver MRI with DWI and DPI sequences, were retrospectively reviewed. Lesions were classified as hypointense, isointense, or hyperintense relative to the adjacent liver parenchyma. ADC of each nodule, of the surrounding parenchyma, and lesion-to-liver ratio were calculated. Hyperintensity versus iso/hypointensity on DWI, hypointensity versus iso/hyperintensity on DPI, and the mean lesion-to-liver ratio showed a statistically significant difference both between HCCs versus DNs and between "HCCs + HGDNs" versus LGDNs (p Correlation of DWI with DPI improves differential diagnosis of cirrhotic nodules. • Characterization of atypically enhancing lesions becomes more confident.
Tian, Lixin [Jiangsu University, Energy Development and Environmental Protection Strategy Research Center, Zhenjiang, Jiangsu (China); Nanjing Normal University, School of Mathematical Sciences, Nanjing, Jiangsu (China); Ding, Zhenqi; Zhen, Zaili [Jiangsu University, Energy Development and Environmental Protection Strategy Research Center, Zhenjiang, Jiangsu (China); Wang, Minggang [Nanjing Normal University, School of Mathematical Sciences, Nanjing, Jiangsu (China)
2016-08-15
The international crude oil market plays a crucial role in economies, and the studies of the correlation, risk and synchronization of the international crude oil market have important implications for the security and stability of the country, avoidance of business risk and people's daily lives. We investigate the information and characteristics of the international crude oil market (1999-2015) based on the random matrix theory (RMT). Firstly, we identify richer information in the largest eigenvalues deviating from RMT predictions for the international crude oil market; the international crude oil market can be roughly divided into ten different periods by the methods of eigenvectors and characteristic combination, and the implied market information of the correlation coefficient matrix is advanced. Secondly, we study the characteristics of the international crude oil market by the methods of system risk entropy, dynamic synchronous ratio, dynamic non-synchronous ratio and dynamic clustering algorithm. The results show that the international crude oil market is full of risk. The synchronization of the international crude oil market is very strong, and WTI and Brent occupy a very important position in the international crude oil market. (orig.)
Zhan, Yuefu; Liang, Xianwen; Han, Xiangjun; Chen, Jianqiang; Zhang, Shufang; Tan, Shun; Li, Qun; Wang, Xiong; Liu, Fan
2017-02-28
To explore the correlation between the apparent diffusion coefficient (ADC) and mRNA expression of tissue inhibitor of metalloproteinase-1 (TIMP-1) in different stages of liver fibrosis in rats. Methods: A model of liver fibrosis in rats was established by intraperitoneal injection of high-fat diet combined with porcine serum. After drug administration for 4 weeks, 48 rats served as a model group and 12 rats served as a control group, then they underwent diffusion weighted imaging (DWI) scanning. The value of ADC was calculated at b value=800 s/mm2. The rats were sacrificed and carried out pathologic examination after DWI scanning immediately. The mRNA expression of TIMP-1 was detected by real time-polymerase chain reaction (RT-PCR). The rats of hepatic fibrosis were also divided into a S0 group (n=4), a S1 group (n=11), a S2 group (n=12), a S3 group (n=10), and a S4 group (n=9) according to their pathological stage. The value of ADC and the expression of TIMP-1 mRNA among the different stage groups of liver fibrosis were compared, and the correlation between ADC and the TIMP-1 mRNA were analyzed. Results: The ADC value and the TIMP-1 mRNA expression were significantly different between the control group and the liver fibrosis group (F=46.54 and 53.87, P0.05). For the comparison of TIMP-1 mRNA, there was no significant difference between the S1 group and the S2 group, the S3 group and the S4 group (both P>0.05). There were significant differences among the rest of the groups (all Pcorrelation analysis showed that there was a negative correlation between the ADC value and the TIMP-1 mRNA expression (r=-0.76, Pcorrelation between them.
Schaarschmidt, Benedikt Michael; Buchbender, Christian; Nensa, Felix; Grueneisen, Johannes; Grueneien, Johannes; Gomez, Benedikt; Köhler, Jens; Reis, Henning; Ruhlmann, Verena; Umutlu, Lale; Heusch, Philipp
2015-01-01
To compare the apparent diffusion coefficient (ADC) in lymph node metastases of non-small cell lung cancer (NSCLC) patients with standardized uptake values (SUV) derived from combined 18F-fluoro-deoxy-glucose-positron emission tomography/magnetic resonance imaging (18F-FDG PET/MRI). 38 patients with histopathologically proven NSCLC (mean age 60.1 ± 9.5 y) received whole-body PET/CT (Siemens mCT™) 60 min after injection of a mean dose of 280 ± 50 MBq 18F-FDG and subsequent PET/MRI (mean time after tracer injection: 139 ± 26 min, Siemens Biograph mMR). During PET acquisition, simultaneous diffusion-weighted imaging (DWI, b values: 0, 500, 1000 s/mm²) was performed. A maximum of 10 lymph nodes per patient suspicious for malignancy were analyzed. Regions of interest (ROI) were drawn covering the entire lymph node on the attenuation-corrected PET-image and the monoexponential ADC-map. According to histopathology or radiological follow-up, lymph nodes were classified as benign or malignant. Pearson's correlation coefficients were calculated for all lymph node metastases correlating SUVmax and SUVmean with ADCmean. A total of 146 suspicious lymph nodes were found in 25 patients. One hundred lymph nodes were eligible for final analysis. Ninety-one lymph nodes were classified as malignant and 9 as benign according to the reference standard. In malignant lesions, mean SUVmax was 9.1 ± 3.8 and mean SUVmean was 6.0 ± 2.5 while mean ADCmean was 877.0 ± 128.6 x10(-5) mm²/s in PET/MRI. For all malignant lymph nodes, a weak, inverse correlation between SUVmax and ADCmean as well as SUVmean and ADCmean (r = -0.30, pcorrelation between increased glucose-metabolism and cellularity in lymph node metastases of NSCLC patients. 18F-FDG-PET and DWI thus may offer complementary information for the evaluation of treatment response in lymph node metastases of NSCLC.
Parkash, Jai
2008-08-01
The immunological processes in type 1 diabetes and metabolic/inflammatory disorder in type 2 diabetes converge on common signaling pathway(s) leading to beta-cell death in these two diseases. The cytokine-mediated beta-cell death seems to be dependent on voltage-dependent calcium channel (VDCC)-mediated Ca2+ entry. The Ca2+ handling molecular networks control the homeostasis of [Ca2+]i in the beta-cell. The activity and membrane density of VDCC are regulated by several mechanisms including G protein-coupled receptors (GPCRs). CaR is a 123-kDa seven transmembrane extracellular Ca2+ sensing protein that belongs to GPCR family C. Tumor necrosis factor-alpha (TNF-alpha), is a cytokine widely known to activate nuclear factor-kappaB (NF-kappaB) transcription in beta-cells. To obtain a better understanding of TNF-alpha-induced molecular interactions between CaR and VDCC, confocal fluorescence measurements were performed on insulin-producing beta-cells exposed to varying concentrations of TNF-alpha and the results are discussed in the light of increased colocalization correlation coefficient. The insulin producing beta-cells were exposed to 5, 10, 20, 30, and 50 ng/ml TNF-alpha for 24 h at 37 degrees . The cells were then immunolabelled with antibodies directed against CaR, VDCC, and NF-kappaB. The confocal fluorescence imaging data showed enhancement in the colocalization correlation coefficient between CaR and VDCC in beta-cells exposed to TNF-alpha thereby indicating increased membrane delimited spatial interactions between these two membrane proteins. TNF-alpha-induced colocalization of VDCC with CaR was inhibited by nimodipine, an inhibitor of L-type VDCC thereby suggesting that VDCC activity is required for spatial interactions with CaR. The 3-D confocal fluorescence imaging data also demonstrated that addition of TNF-alpha to RIN cells led to the translocation of NF-kappaB from the cytoplasm to the nucleus. Such molecular interactions between CaR and VDCC in tissues
Warren, M. A.; Quartly, G. D.; Shutler, J. D.; Miller, P. I.; Yoshikawa, Y.
2016-09-01
Attempts to automatically estimate surface current velocities from satellite-derived thermal or visible imagery face the limitations of data occlusion due to cloud cover, the complex evolution of features and the degradation of their surface signature. The Geostationary Ocean Color Imager (GOCI) provides a chance to reappraise such techniques due to its multiyear record of hourly high-resolution visible spectrum data. Here we present the results of applying a Maximum Cross Correlation (MCC) technique to GOCI data. Using a combination of simulated and real data we derive suitable processing parameters and examine the robustness of different satellite products, those being water-leaving radiance and chlorophyll concentration. These estimates of surface currents are evaluated using High Frequency (HF) radar systems located in the Tsushima (Korea) Strait. We show the performance of the MCC approach varies depending on the amount of missing data and the presence of strong optical contrasts. Using simulated data it was found that patchy cloud cover occupying 25% of the image pair reduces the number of vectors by 20% compared to using perfect images. Root mean square errors between the MCC and HF radar velocities are of the order of 20 cm s-1. Performance varies depending on the wavelength of the data with the blue-green products out-performing the red and near infra-red products. Application of MCC to GOCI chlorophyll data results in similar performance to radiances in the blue-green bands. The technique has been demonstrated using specific examples of an eddy feature and tidal induced features in the region.
Li, Gui Dian; Liang, Ying Yin; Xu, Ping; Ling, Jian; Chen, Ying Ming
2016-04-01
The purpose of this study is to investigate the correlation of apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values with fatty infiltration in the thigh muscles of patients with Duchenne muscular dystrophy (DMD) using diffusion-tensor imaging (DTI). Twenty-one boys with DMD were recruited. The grade of fatty infiltration and the ADC and FA values of four thigh muscles (rectus femoris, semitendinosus, sartorius, and gracilis) were measured, and the FA and ADC values were compared with the grade of fatty infiltration. Twenty age-matched healthy boys were enrolled as the control group. The differences in the ADC and FA values of the thigh muscles between patients with DMD and the control group were compared. The patients with DMD showed lower FA values and higher ADC values in all measured muscles when compared with the control group. The FA and ADC values were correlated with the grade of fatty infiltration. For the rectus femoris muscle, r = -0.753 and p = 0.007 for FA, and r = 0.685 and p = 0.001 for ADC. For the semitendinosus muscle, r = -0.621 and p = 0.041 for FA, and r = 0.705 and p = 0.021 for ADC. For the sartorius muscle, r = -0.662 and p = 0.027 for FA, and r = 0.701 and p = 0.017 for ADC. For the gracilis muscle, r = -0.618 and p = 0.043 for FA, and r = 0.695 and p = 0.022 for ADC. Damage to the thigh muscles in patients with DMD can be detected by ADC and FA values using DTI. DTI can be used to assess the severity of the disease.
Yongbin Liu
2017-01-01
Full Text Available Envelope spectrum analysis is a simple, effective, and classic method for bearing fault identification. However, in the wayside acoustic health monitoring system, owing to the high relative moving speed between the railway vehicle and the wayside mounted microphone, the recorded signal is embedded with Doppler effect, which brings in shift and expansion of the bearing fault characteristic frequency (FCF. What is more, the background noise is relatively heavy, which makes it difficult to identify the FCF. To solve the two problems, this study introduces solutions for the wayside acoustic fault diagnosis of train bearing based on Doppler effect reduction using the improved time-domain interpolation resampling (TIR method and diagnosis-relevant information enhancement using Weighted-Correlation-Coefficient-Guided Stochastic Resonance (WCCSR method. First, the traditional TIR method is improved by incorporating the original method with kinematic parameter estimation based on time-frequency analysis and curve fitting. Based on the estimated parameters, the Doppler effect is removed using the TIR easily. Second, WCCSR is employed to enhance the diagnosis-relevant period signal component in the obtained Doppler-free signal. Finally, paved with the above two procedures, the local fault is identified using envelope spectrum analysis. Simulated and experimental cases have verified the effectiveness of the proposed method.
B. Thenkalvi
2014-01-01
Full Text Available Content Based Image Retrieval (CBIR is an evolving topic under image processing. Retrieval on medical images plays a vital role in saving mankind. Medical Content Based Image Retrieval (MCBIR does not stop its work in displaying similar images; it also goes one step further for diagnosis to decide the method of therapy by comparing the query image and database image. Hence we believe that, our work is a mile stone in the medical imaging research and will gain an appreciable amount of demand in automatic diagnosis done through artificial intelligence. While handling a large amount of data base, retrieval naturally reduces the search area. Many research works were conducted on CBIR systems to yield better performance on retrieval of medical images. Here we propose a modified integrated approach which extracts low level image features: Color, intensity, shape and texture using Certain Block based Difference of Inverse Probability (CBDIP and Certain Block based Variation of Local Correlation coefficients (CBVLC for pre-processed images. Consequently wavelet moments are calculated on derived CBDIP and CBVLC values that leads to mining on medical images only with 48 feature vectors. Thereby greatly reducing total number of feature vectors used for similarity comparison for retrieval of similar images. To know the retrieval accuracy, precision and recall values are calculated for the mined 1000 images. It has been examined that this integrated approach shows an improvement in retrieval accuracy and the time taken for similarity comparison.
Anigbogu, Chikodi N; Williams, Daniel T; Brown, David R; Silcox, Dennis L; Speakman, Richard O; Brown, Laura C; Karounos, Dennis G; Randall, David C
2011-01-01
Circadian changes in cardiovascular function during the progression of diabetes mellitus in the diabetes prone rat (BBDP) (n = 8) were studied. Age-matched diabetes-resistant rats (BBDR) served as controls. BP was recorded via telemetry in contiguous 4 hr time periods over 24 hours starting with 12 midnight to 4 am as period zero (P0). Prior to onset of diabetes BP was high at P0, peaked at P2, and then fell again at P3; BP and heart rate (HR) then increased gradually at P4 and leveled off at P5, thereby exhibiting a bipodal rhythm. These patterns changed during long-term diabetes. The cross-correlation coefficient of BP and HR was not significantly different across groups at onset, but it fell significantly at 9 months of duration of diabetes (BBDP: 0.39 ± 0.06; BBDR: 0.65 ± 0.03; P < .05). These results show that changes in circadian cardiovascular rhythms in diabetes mellitus became significant at the late stage of the disease.
Rights, Jason D; Sterba, Sonya K
2016-11-01
Multilevel data structures are common in the social sciences. Often, such nested data are analysed with multilevel models (MLMs) in which heterogeneity between clusters is modelled by continuously distributed random intercepts and/or slopes. Alternatively, the non-parametric multilevel regression mixture model (NPMM) can accommodate the same nested data structures through discrete latent class variation. The purpose of this article is to delineate analytic relationships between NPMM and MLM parameters that are useful for understanding the indirect interpretation of the NPMM as a non-parametric approximation of the MLM, with relaxed distributional assumptions. We define how seven standard and non-standard MLM specifications can be indirectly approximated by particular NPMM specifications. We provide formulas showing how the NPMM can serve as an approximation of the MLM in terms of intraclass correlation, random coefficient means and (co)variances, heteroscedasticity of residuals at level 1, and heteroscedasticity of residuals at level 2. Further, we discuss how these relationships can be useful in practice. The specific relationships are illustrated with simulated graphical demonstrations, and direct and indirect interpretations of NPMM classes are contrasted. We provide an R function to aid in implementing and visualizing an indirect interpretation of NPMM classes. An empirical example is presented and future directions are discussed. © 2016 The British Psychological Society.
Inchingolo, Riccardo; De Gaetano, Anna Maria; Curione, Davide; Ciresa, Marzia; Bonomo, Lorenzo [Catholic University of the Sacred Heart, Department of Bioimaging and Radiological Sciences, Institute of Radiology, ' ' Agostino Gemelli' ' Hospital, Rome (Italy); Miele, Luca; Pompili, Maurizio [Catholic University of the Sacred Heart, Department of Internal Medicine, ' ' Agostino Gemelli' ' Hospital, Rome (Italy); Vecchio, Fabio Maria [Catholic University of the Sacred Heart, Department of Anatomo-Pathology, ' ' Agostino Gemelli' ' Hospital, Rome (Italy); Giuliante, Felice [Catholic University of the Sacred Heart, Department of Surgery, ' ' Agostino Gemelli' ' Hospital, Rome (Italy)
2015-04-01
To investigate the utility of diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC) and the correlation with hepatobiliary phase (delayed phase imaging, DPI) findings in the differentiation of cirrhotic hepatocellular nodules. Forty-three patients with 53 pathology-proven nodules (29 hepatocellular carcinomas (HCCs), 13 high-grade (HGDNs) and 11 low-grade dysplastic nodules (LGDNs); mean size 2.17 cm, range 1-4 cm), who underwent liver MRI with DWI and DPI sequences, were retrospectively reviewed. Lesions were classified as hypointense, isointense, or hyperintense relative to the adjacent liver parenchyma. ADC of each nodule, of the surrounding parenchyma, and lesion-to-liver ratio were calculated. Hyperintensity versus iso/hypointensity on DWI, hypointensity versus iso/hyperintensity on DPI, and the mean lesion-to-liver ratio showed a statistically significant difference both between HCCs versus DNs and between ''HCCs + HGDNs'' versus LGDNs (p < 0.05); sensitivity, specificity, and accuracy for the diagnosis of ''HCCs + HGDNs'' were 96.8 %, 100 %, 97.4 % respectively when combining hyperintensity on DWI and hypointensity on DPI, and 90.9 %, 81.0 %, 83.6 % respectively when lesion-to-liver ratio was <0.95. Hyperintensity on DWI, especially in association with hypointensity on DPI, and low lesion-to-liver ratios should raise the suspicion of HCC, or at least of HGDN, thus helping the characterization of atypically enhancing lesions. (orig.)
Shimazaki, M; Kikuchi, K; Yamaji, I; Kobayakawa, H; Yamamoto, M; Kudo, C; Wada, A; Mukai, H; Iimura, O
1991-01-01
The relationship between changes in sympathetic nerve activity and those in parasympathetic tone with a change in position was investigated in patients with essential hypertension using the coefficient of variation of RR intervals on electrocardiograms (CVRR). Mean arterial pressure (MAP), heart rate (HR), plasma noradrenaline concentration (pNA) and CVRR were measured in a supine position at rest and 20 min after having the head tilted 60 degrees superiorly in 10 normotensives (NT: 51.9 +/- 3.0 yrs) and 7 essential hypertensive patients (EHT: 51.0 +/- 2.8 yrs). After changing the position, CVRR decreased significantly in the NT, but not in the EHT; whereas, significant increases of both HR and pNA without significant changes in MAP were shown in both groups. A significant negative correlation between percentage changes in CVRR (% delta CVRR) and pNA (% delta pNA) were observed in the NT, but not in the EHT. However, there was no relationship of % delta CVRR to % delta MAP or to % delta HR in either group. It was suggested from the changes in CVRR that suppression of the parasympathetic tone, which occurs in the NT group corresponding to sympathetic augmentation to present a decrease in blood pressure with a change in position, may be impaired in the EHT group.
李伟; 朱自强
2002-01-01
The partition coefficients of baicalin were measured in ethylene oxide and propylene oxide (EOPO)/salt aqueous two-phase systemsat 298.15K. It was found that most of baicalin partitioned into EOPO-rich phase. The partition coefficients of baicalin varied from 10 to 120.The effect of various factors, including tie-line length, salt composition, molecular weight of EOPO, and solution pH, on the partition behaviorwas investigated in EOPO/salt systems. Furthermore the partition coefficients of baicalin were correlated using the modified Diamond-Hsumodel. Good agreement with experimental data is obtained. The average relative deviations are less than 5.0%.
Razek, Ahmed Abdel Khalek Abdel; Nada, Nadia
2016-04-01
The aim of this study was to measure choline/creatine (Ch/Cr) levels through (1)H-MRS and apparent diffusion coefficient (ADC) values through diffusion-weighted MRI, and to correlate these values with the prognostic parameters of head and neck squamous cell carcinoma (HNSCC). The institutional review board approved this study and informed written consent was obtained from all study participants. A prospective study of 43 patients (31 men and 12 women; mean age, 65 years) with HNSCC was conducted. Single-voxel (1)H-MRS was performed at the tumor or metastatic cervical lymph node with point-resolved spectroscopy (PRESS) at TE = 135 ms. Diffusion-weighted MR images with b values of 0, 500 and 1000 s/mm(2) and contrast MRI of the head and neck were performed. The Ch/Cr levels and ADC values of HNSCC were calculated. The gross tumor volume (GTV) was also calculated. The degree of tumor differentiation was determined through pathological examination. The HNSCC Ch/Cr level was negatively correlated with the ADC value (r = -0.662, p = 0.001). There was a significant difference in the Ch/Cr and ADC values at different degrees of tumor differentiation (p = 0.003 and p = 0.001) and with different GTVs (p = 0.122 and p = 0.001). The following prognostic parameter categories were used: (i) poorly differentiated and undifferentiated versus well differentiated to moderately differentiated; and (ii) HNSCC with GTV 30 cm(3). The cut-off values for Cho/Cr and ADC for each category were 1.83, 0.95 and 1.94, 0.99, respectively, and the areas under the curve were 0.771, 0.967 and 0.726, 0.795, respectively, for each category. We conclude that the Ch/Cr levels determined using (1)H-MRS and the ADC values are well correlated with several prognostic parameters of HNSCC.
A viable method for goodness-of-fit test in maximum likelihood fit
ZHANG Feng; GAO Yuan-Ning; HUO Lei
2011-01-01
A test statistic is proposed to perform the goodness-of-fit test in the unbinned maximum likelihood fit. Without using a detailed expression of the efficiency function, the test statistic is found to be strongly correlated with the maximum likelihood function if the efficiency function varies smoothly. We point out that the correlation coefficient can be estimated by the Monte Carlo technique. With the established method, two examples are given to illustrate the performance of the test statistic.
Hanson, A A; Moon, R D; Wright, R J; Hunt, T E; Hutchison, W D
2015-08-01
Western bean cutworm, Striacosta albicosta (Smith) (Lepidoptera: Noctuidae), is a native, univoltine pest of corn and dry beans in North America. The current degree-day model for predicting a specified percentage of yearly moth flight involves heat unit accumulation above 10°C after 1 May. However, because the moth's observed range has expanded into the northern and eastern United States, there is concern that suitable temperatures before May could allow for significant S. albicosta development. Daily blacklight moth catch and temperature data from four Nebraska locations were used to construct degree-day models using simple or sine-wave methods, starting dates between 1 January and 1 May, and lower (-5 to 15°C) and upper (20 to 43.3°C) developmental thresholds. Predicted dates of flight from these models were compared with observed flight dates using independent datasets to assess model performance. Model performance was assessed with the concordance correlation coefficient to concurrently evaluate precision and accuracy. The best model for predicting timing of S. albicosta flight used simple degree-day calculations beginning on 1 March, a 3.3°C (38°F) lower threshold, and a 23.9°C (75°F) upper threshold. The revised cumulative flight model indicated field scouting to estimate moth egg density at the time of 25% flight should begin when 1,432 degree-days (2,577 degree-days °F) have accumulated. These results underscore the importance of assessing multiple parameters in phenological models and utilizing appropriate assessment methods, which in this case may allow for improved timing of field scouting for S. albicosta.
Woo, Sungmin; Cho, Jeong Yeon; Kim, Sang Youn; Kim, Seung Hyup
2014-12-01
Until now, several investigators have explored the value of diffusion-weighted magnetic resonance imaging (DWI) for the preoperative tumor grading of endometrial cancer. However, the diagnostic value of DWI with quantitative analysis of apparent diffusion coefficient (ADC) has been controversial. To explore the role of histogram analysis of ADC maps based on entire tumor volume in determining the grade of endometrial cancer. This study was IRB-approved with waiver of informed consent. Thirty-three patients with endometrial cancer underwent DWI (b = 0, 600, 1000 s/mm(2)), and corresponding ADC maps were acquired. Regions of interest (ROIs) were drawn on all slices of the ADC map in which the tumor was visualized including areas of necrosis to derive volume-based histographic ADC data. Histogram parameters (5th-95th percentiles, mean, standard deviation, skewness, kurtosis) were correlated with histological grade using one-way ANOVA with Tukey-Kramer test for post hoc comparisons, and were compared between high (grade 3) and low (grades 1/2) grade using Student t-test. ROC curve analysis was performed to determine the optimum threshold value for each parameter, and their corresponding sensitivity and specificity. The standard deviation, quartile, 75th, 90th, and 95th percentiles of ADC showed significant differences between grades (P ≤ 0.03 for all) and between high and low grades (P ≤ 0.024 for all). There were no significant correlations between tumor grade and other parameters. ROC curve analysis yielded sensitivities and specificities of 75% and 96%, 62.5% and 92%, 100% and 52%, 100% and 72%, and 100% and 88%, using standard deviation, quartile, 75th, 90th, and 95th percentiles for determining high grade with corresponding areas under the curve (AUCs) of 0.787, 0.792, 0.765, 0.880, and 0.925, respectively. Histogram analysis of ADC maps based on entire tumor volume can be useful for predicting the histological grade of endometrial cancer. The 90th and 95th
Kang, Yusuhn; Choi, Seung Hong; Kim, Young-Jae; Kim, Kwang Gi; Sohn, Chul-Ho; Kim, Ji-Hoon; Yun, Tae Jin; Chang, Kee-Hyun
2011-01-01
To explore the role of histogram analysis of apparent diffusion coefficient (ADC) maps based on entire tumor volume data in determining glioma grade and to evaluate the diagnostic performance of ADC maps at standard...
Pfrang, Christian; King, Martin D.; Braeckevelt, Mareike; Canosa-Mas, Carlos E.; Wayne, Richard P.
Experimental difficulties sometimes force modellers to use predicted rate coefficients for reactions of oxygenated volatile organic compounds (oVOCs). We examine here methods for making the predictions for reactions of atmospheric initiators of oxidation, NO 3, OH, O 3 and O( 3P), with unsaturated alcohols and ethers. Logarithmic correlations are found between measured rate coefficients and calculated orbital energies, and these correlations may be used directly to estimate rate coefficients for compounds where measurements have not been performed. To provide a shortcut that obviates the need to calculate orbital energies, structure-activity relations (SARs) are developed. Our SARs are tested for predictive power against compounds for which experimental rate coefficients exist, and their accuracy is discussed. Estimated atmospheric lifetimes for oVOCs are presented. The SARs for alkenols successfully predict key rate coefficients, and thus can be used to enhance the scope of atmospheric models incorporating detailed chemistry. SARs for the ethers have more limited applicability, but can still be useful in improving tropospheric models.
Geith, Tobias; Biffar, Andreas; Schmidt, Gerwin; Sourbron, Steven; Dietrich, Olaf; Reiser, Maximilian; Baur-Melnyk, Andrea
2015-01-01
To test the hypothesis that apparent diffusion coefficient (ADC) in vertebral bone marrow of benign and malignant fractures is related to the volume of the interstitial space, determined with dynamic contrast-enhanced (DCE) magnetic resonance imaging. Patients with acute benign (n = 24) and malignant (n = 19) vertebral body fractures were examined at 1.5 T. A diffusion-weighted single-shot turbo-spin-echo sequence (b = 100 to 600 s/mm) and DCE turbo-FLASH sequence were evaluated. Regions of interest were manually selected for each fracture. Apparent diffusion coefficient was determined with a monoexponential decay model. The DCE magnetic resonance imaging concentration-time curves were analyzed using a 2-compartment tracer-kinetic model. Apparent diffusion coefficient showed a significant positive correlation with interstitial volume in the whole study population (Pearson r = 0.66, P correlation between ADC and the permeability-surface area product could be observed when analyzing the whole study population (Spearman rs = 0.40, P = 0.008), but not when separately examining the subgroups. Plasma flow showed a significant correlation with ADC in benign fractures (Pearson r = 0.23, P = 0.03). Plasma volume did not show significant correlations with ADC. The results support the hypothesis that the ADC of a lesion is inversely correlated to its cellularity. This explains previous observations that ADC is reduced in more malignant lesions.
Berrocal T, Mariella J. [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia. Programa de Engenharia Nuclear]|[Universidad Nacional de Ingenieria, Lima (Peru); Roberty, Nilson C. [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia. Programa de Engenharia Nuclear; Silva Neto, Antonio J. [Universidade do Estado, Nova Friburgo, RJ (Brazil). Instituto Politecnico. Dept. de Engenharia Mecanica e Energia]|[Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia. Programa de Engenharia Nuclear
2002-07-01
The solution of inverse problems in participating media where there is emission, absorption and dispersion of the radiation possesses several applications in engineering and medicine. The objective of this work is to estimative the coefficients of absorption and dispersion in two-dimensional heterogeneous participating media, using in independent form the Generalized Maximum Entropy and Levenberg Marquardt methods. Both methods are based on the solution of the direct problem that is modeled by the Boltzmann equation in cartesian geometry. Some cases testes are presented. (author)
Driessen, Juliette P; van Bemmel, Xander; van Kempen, Pauline M. W.; Janssen, Luuk M; Terhaard, Chris H J; Pameijer, Frank A; Willems, Stefan M.; Stegeman, Inge; Grolman, Wilko; Philippens, Marielle E P
2016-01-01
Background Identification of prognostic patient characteristics in head and neck squamous cell carcinoma (HNSCC) is of great importance. Human papillomavirus (HPV)-positive HNSCCs have favorable response to (chemo)radiotherapy. Apparent diffusion coefficient, derived from diffusion-weighted MRI, has
Heethal Jaiprakash
2016-03-01
Full Text Available This paper is aimed at finding if there was a change of correlation between the written test score and tutors’ performance test scores in the assessment of medical students during a problem-based learning (PBL course in Malaysia. This is a cross-sectional observational study, conducted among 264 medical students in two groups from November 2010 to November 2012. The first group’s tutors did not receive tutor training; while the second group’s tutors were trained in the PBL process. Each group was divided into high, middle and low achievers based on their end-of-semester exam scores. PBL scores were taken which included written test scores and tutors’ performance test scores. Pearson correlation coefficient was calculated between the two kinds of scores in each group. The correlation coefficient between the written scores and tutors’ scores in group 1 was 0.099 (p<0.001 and for group 2 was 0.305 (p<0.001. The higher correlation coefficient in the group where tutors received the PBL training reinforces the importance of tutor training before their participation in the PBL course.
Liu, Wei; Lu, Jian; Leung, Lai-Yung R.; Xie, Shang-Ping; Liu, Zhengyu; Zhu, Jiang
2015-02-22
This paper investigates the changes of the Southern Westerly Winds (SWW) and Southern Ocean (SO) upwelling between the Last Glacial Maximum (LGM) and preindustrial (PI) in the PMIP3/CMIP5 simulations, highlighting the role of the Antarctic sea ice in modulating the wind stress effect on the ocean. Particularly, a discrepancy may occur between the changes in SWW and westerly wind stress, caused primarily by an equatorward expansion of winter Antarctic sea ice that undermines the wind stress in driving the liquid ocean. Such discrepancy may reflect the LGM condition in reality, in view of that the model simulates this condition has most credible simulation of modern SWW and Antarctic sea ice. The effect of wind stress on the SO upwelling is further explored via the wind-induced Ekman pumping, which is reduced under the LGM condition in all models, in part by the sea-ice “capping” effect present in the models.
陈敏伯
2011-01-01
本文旨在纠正一种在化学家中流传甚久的对统计数学中相关系数的错误理解.这种理解认为在数据拟合中单凭相关系数R大于某个人为指定值就可以判定数据拟合的优劣.%The misunderstanding in chemical community about the correlation coefficient R in statistical regression is pointed out and corrected. The misunderstanding has considered for a long time that the satisfactory of the linear regression can be judged by means of correlation coefficient solely.
Mishra, Manish Kumar; Mukherjee, Arijit; Ramamurty, Upadrasta; Desiraju, Gautam R
2015-11-01
A new monoclinic polymorph, form II (P21/c, Z = 4), has been isolated for 3,4-dimethoxycinnamic acid (DMCA). Its solid-state 2 + 2 photoreaction to the corresponding α-truxillic acid is different from that of the first polymorph, the triclinic form I ([Formula: see text], Z = 4) that was reported in 1984. The crystal structures of the two forms are rather different. The two polymorphs also exhibit different photomechanical properties. Form I exhibits photosalient behavior but this effect is absent in form II. These properties can be explained on the basis of the crystal packing in the two forms. The nanoindentation technique is used to shed further insights into these structure-property relationships. A faster photoreaction in form I and a higher yield in form II are rationalized on the basis of the mechanical properties of the individual crystal forms. It is suggested that both Schmidt-type and Kaupp-type topochemistry are applicable for the solid-state trans-cinnamic acid photodimerization reaction. Form I of DMCA is more plastic and seems to react under Kaupp-type conditions with maximum molecular movements. Form II is more brittle, and its interlocked structure seems to favor Schmidt-type topochemistry with minimum molecular movement.
王平
2015-01-01
研究高校各类课程之间的关联关系是信息化教学的手段之一，而分析课程成绩之间的相关性是研究高校课程关联关系的重要方法。针对传统的Pearson相关系数易于受到异常点影响的问题，提出一种基于鲁棒相关系数的成绩关联分析方法。该方法首先建立样本标准差的鲁棒估计器，在此基础上计算相关系数的鲁棒估计，最后将其用于不同课程成绩之间的相关性分析。%Study on the incidence relation among the various courses in colleges and universities is one of information⁃based teaching measures,and analysis of the correlation between course grades is one of the important methods of researching the incidence relation among courses. Aiming at the problem that the traditional Pearson correlation coefficient is influenced by outliers easily,a score correlation analytical method based on robust correlation coefficient is proposed. With the method,the ro⁃bust estimator of sample standard deviation is established. Based on this,the robust estimation of correlation coefficient is calcu⁃lated,which can be applied to correlation analysis between different courses.
2010-07-01
... 40 Protection of Environment 5 2010-07-01 2010-07-01 false Illustration of the Minimum Limits for Correlation Coefficient for PM2.5 and PM10â2.5 Class II and III Methods C Figure C-4 to Subpart C of Part 53... Methods and Reference Methods Pt. 53, Subpt. C, Fig. C-4 Figure C-4 to Subpart C of Part 53—Illustration...
Deary Ian J
2009-04-01
Full Text Available Abstract Background Brain size is associated with cognitive ability in adulthood (correlation ~ .3, but few studies have investigated the relationship in normal ageing, particularly beyond age 75 years. With age both brain size and fluid-type intelligence decline, and regional atrophy is often suggested as causing decline in specific cognitive abilities. However, an association between brain size and intelligence may be due to the persistence of this relationship from earlier life. Methods We recruited 107 community-dwelling volunteers (29% male aged 75–81 years for cognitive testing and neuroimaging. We used principal components analysis to derived a 'general cognitive factor' (g from tests of fluid-type ability. Using semi-automated analysis, we measured whole brain volume, intracranial area (ICA (an estimate of maximal brain volume, and volume of frontal and temporal lobes, amygdalo-hippocampal complex, and ventricles. Brain atrophy was estimated by correcting WBV for ICA. Results Whole brain volume (WBV correlated with general cognitive ability (g (r = .21, P Conclusion The association between brain regions and specific cognitive abilities in community dwelling people of older age is due to the life-long association between whole brain size and general cognitive ability, rather than atrophy of specific regions. Researchers and clinicians should therefore be cautious of interpreting global or regional brain atrophy on neuroimaging as contributing to cognitive status in older age without taking into account prior mental ability and brain size.
Jaiprakash, Heethal; Min, Aung Ko Ko; Ghosh, Sarmishtha
2016-03-01
This paper is aimed at finding if there was a change of correlation between the written test score and tutors' performance test scores in the assessment of medical students during a problem-based learning (PBL) course in Malaysia. This is a cross-sectional observational study, conducted among 264 medical students in two groups from November 2010 to November 2012. The first group's tutors did not receive tutor training; while the second group's tutors were trained in the PBL process. Each group was divided into high, middle and low achievers based on their end-of-semester exam scores. PBL scores were taken which included written test scores and tutors' performance test scores. Pearson correlation coefficient was calculated between the two kinds of scores in each group. The correlation coefficient between the written scores and tutors' scores in group 1 was 0.099 (pcorrelation coefficient in the group where tutors received the PBL training reinforces the importance of tutor training before their participation in the PBL course.
A hybrid solar panel maximum power point search method that uses light and temperature sensors
Ostrowski, Mariusz
2016-04-01
Solar cells have low efficiency and non-linear characteristics. To increase the output power solar cells are connected in more complex structures. Solar panels consist of series of connected solar cells with a few bypass diodes, to avoid negative effects of partial shading conditions. Solar panels are connected to special device named the maximum power point tracker. This device adapt output power from solar panels to load requirements and have also build in a special algorithm to track the maximum power point of solar panels. Bypass diodes may cause appearance of local maxima on power-voltage curve when the panel surface is illuminated irregularly. In this case traditional maximum power point tracking algorithms can find only a local maximum power point. In this article the hybrid maximum power point search algorithm is presented. The main goal of the proposed method is a combination of two algorithms: a method that use temperature sensors to track maximum power point in partial shading conditions and a method that use illumination sensor to track maximum power point in equal illumination conditions. In comparison to another methods, the proposed algorithm uses correlation functions to determinate the relationship between values of illumination and temperature sensors and the corresponding values of current and voltage in maximum power point. In partial shading condition the algorithm calculates local maximum power points bases on the value of temperature and the correlation function and after that measures the value of power on each of calculated point choose those with have biggest value, and on its base run the perturb and observe search algorithm. In case of equal illumination algorithm calculate the maximum power point bases on the illumination value and the correlation function and on its base run the perturb and observe algorithm. In addition, the proposed method uses a special coefficient modification of correlation functions algorithm. This sub
Hubbard, S. M.; Coutts, D. S.; Matthews, W.; Guest, B.; Bain, H.
2015-12-01
In basins adjacent to continually active arcs, detrital zircon geochronology can be used to establish a high-resolution chronostratigraphic framework for deep-time strata. Large-nU-Pb geochronological datasets can yield a statistically significant signature from the youngest sub-population of detrital zircons, which we deduce from maximum depositional age (MDA) calculations. MDA is determined through numerous methods such as the mean age of three or more overlapping grain ages at 2σ error, favored in this analysis. Positive identification of the youngest detrital zircon population in a rock is the limiting factor on precision and resolution. The Campanian-Paleogene Nanaimo Group of B.C., Canada, was deposited in a forearc basin, outboard of the Coast Mountain Batholith. The record of a deep-water sediment-routing system is exhumed at Denman and Hornby islands; sandstone- and conglomerate- dominated strata compose a composite sedimentary unit 20 km across and 1.5 km thick, in strike section. Volcanic ashes are absent from the succession, which has been constrained biostratigraphically. Eleven detrital zircon samples are analyzed to define stratigraphic architecture and provide insight into sedimentation rates. Our dataset (n=3081) constrains the overall duration of channelization to ~18 Ma. A series of at least five distinct composite channel fills 3-6 km wide and 400-600 m thick are identified. The MDA of these units are statistically distinct and constrained to better than 3% precision. Sedimentation rates amongst the channel fills increase upward, from 60-100 m/Ma to >500 m/Ma. This is likely linked to the tendency of a slope channel system to be dominated by sediment bypass early in its evolution, and later dominated by aggradation as large-scale levees develop. Channel processes were not continuous, with the longest hiatus ~6 Ma. The large-n detrital zircon dataset provides unprecedented insight into long-term sediment routing, evidence for which is
Mass transfer coefficients in a hanson mixer-settler extraction column
M. Torab-Mostaedi
2008-09-01
Full Text Available The volumetric overall mass transfer coefficients in a pilot plant Hanson mixer-settler extraction column of seven stages have been measured using toluene-acetone-water system. The effects of agitation speed and dispersed and continuous phases flow rates on volumetric overall mass transfer coefficients have been investigated. The results show that the volumetric overall mass transfer coefficient increases with increase in agitation speed and reaches a maximum. After having reached its maximum, it falls with further increase in agitation speed. It was found that the volumetric overall mass transfer coefficient increases with increase in dispersed phase flow rate, while it decreases with increase in continuous phase flow rate. By using interfacial area, the overall mass transfer coefficients for continuous and dispersed phases are determined from volumetric coefficients. An empirical correlation for prediction of the continuous phase overall mass transfer coefficient is proposed in terms of Sherwood and Reynolds numbers. Also the experimental data of the column investigated are compared with data for various extraction columns. Comparison between theoretical models and experimental results for the dispersed phase mass transfer coefficient shows that these models do not have enough accuracy for column design. Using effective diffusivity in the Gröber equation results in more accurate prediction of overall mass transfer coefficient. The prediction of overall mass transfer coefficients from the presented equations is in good agreement with experimental results.
Hayashi, R
2000-09-01
We studied the relationship between accuracy in the cognitive process and components of event-related potentials (P300) in 21 young and healthy subjects. Benzodiazepine was used to manipulate the cognitive state of the subjects. We recorded the serial changes in P300, choice reaction time (CRT), and error ratio (ER) before and after oral administration of 0.4 mg of alprazolam. After administration, the coefficient of variation of CRT tended to decrease in nine subjects (group I) and increase in 12 subjects (group II). Prolongation of the P300 latency was observed in all subjects after treatment; however, such change was more predominant in group II than in group I. In group I, there was no error and no significant difference in P300 amplitude before and after administration. In group II, alprazolam significantly reduced P300 amplitude and increased ER. Our results suggest that the accuracy and P300 amplitude were preserved when the central nerve system managed to reduce fluctuations in CRT but P300 amplitude diminished and the error ratio increased following deterioration of these processes.
Wu, Xia; Zhu, Jian-Cheng; Zhang, Yu; Li, Wei-Min; Rong, Xiang-Lu; Feng, Yi-Fan
2016-08-25
Potential impact of lipid research has been increasingly realized both in disease treatment and prevention. An effective metabolomics approach based on ultra-performance liquid chromatography/quadrupole-time-of-flight mass spectrometry (UPLC/Q-TOF-MS) along with multivariate statistic analysis has been applied for investigating the dynamic change of plasma phospholipids compositions in early type 2 diabetic rats after the treatment of an ancient prescription of Chinese Medicine Huang-Qi-San. The exported UPLC/Q-TOF-MS data of plasma samples were subjected to SIMCA-P and processed by bioMark, mixOmics, Rcomdr packages with R software. A clear score plots of plasma sample groups, including normal control group (NC), model group (MC), positive medicine control group (Flu) and Huang-Qi-San group (HQS), were achieved by principal-components analysis (PCA), partial least-squares discriminant analysis (PLS-DA) and orthogonal partial least-squares discriminant analysis (OPLS-DA). Biomarkers were screened out using student T test, principal component regression (PCR), partial least-squares regression (PLS) and important variable method (variable influence on projection, VIP). Structures of metabolites were identified and metabolic pathways were deduced by correlation coefficient. The relationship between compounds was explained by the correlation coefficient diagram, and the metabolic differences between similar compounds were illustrated. Based on KEGG database, the biological significances of identified biomarkers were described. The correlation coefficient was firstly applied to identify the structure and deduce the metabolic pathways of phospholipids metabolites, and the study provided a new methodological cue for further understanding the molecular mechanisms of metabolites in the process of regulating Huang-Qi-San for treating early type 2 diabetes.
米泽民; 李翠娥; 郝铁锁; 范百成; 刘艳花
2012-01-01
为了能够顺利地完成当地的测土配方施肥项目，通过进行“3414”常规5个处理的试验研究，了解测土配方施肥重要的参数，土壤养分的校正系数的数值以及它们之间与投肥之间的相互关系。结果表明，氮的校正系数与土壤中的碱解氮呈负相关关系，与土壤中的有效磷、速效钾以及在合理的范围内磷肥的投入、氮肥的利用率、缺钾区的相对产量呈正相关关系，与缺氮区的相对产量没有显著的相关关系；磷的校正系数与磷肥的利用率呈显著的正相关关系，与土壤养分含量的碱解氮、有效磷、速效钾以及氮、磷、钾肥的投入呈负相关关系，与氮肥利用率和缺磷区相对产量及缺钾区相对产量亦有显著的负相关关系；速效钾的校正系数除与速效钾呈负相关关系外，与氮肥和钾肥的利用率及缺磷区的相对产量呈正相关关系，而与缺钾区相对产量的关系则是以相对产量的85％为界，小于85％是正相关关系。大于85％呈负相关关系。%In order to finishing the project fertilizing proportion Based on soil test favorably, through the experiment of five treatments with ＇3414＇, know the important coefficient of researching of fertilizing proportion based on soil test, the relative relationship of soil nutrition correlation coefficient with putting fertilizer and different soil nutrition. Be cognizant of the soil nutrition correlation coefficient, it was negative relative relationship between soil nutrition correlation coefficient of nitrogen with quick results nitrogen, there were positive relative relationship with available phosphorus, the quick available kaliums, phosphoric fertilizer that had been fertilized and the rate of utilized nitric fertilizer ＆ relative output of kaliums be lacked, hut there was not relative relationship with Relative output of nitrogen be lacked. It is negative relative relationship between soil
Belteki, Gusztav; Lin, Benjamin; Morley, Colin J
2017-10-01
Carbon-dioxide elimination during high-frequency oscillatory ventilation (HFOV) is thought to be proportional to the carbon dioxide diffusion coefficient (DCO2 ) which is calculated as frequency x (tidal volume)(2) . DCO2 can be used to as an indicator of CO2 elimination but values obtained in different patients cannot be directly compared. To analyze the relationship between DCO2 , the weight-corrected DCO2 (DCO2 corr) and blood gas PCO2 values obtained from infants receiving HFOV. DCO2 data were obtained from 14 infants at 1/s sampling rate and the mean DCO2 was determined over 10 min periods preceding the time of the blood gas. DCO2 corr was calculated by dividing the DCO2 by the square of the body weight in kg. Weight-correction significantly reduced the inter-individual variability of DCO2 . When data from all the babies were combined, standard DCO2 showed no correlation with PCO2 but DCO2 corr showed a weak but statistically significant inverse correlation. The correlation was better when the endotracheal leak was 50 mL(2) /sec/kg(2) or VThf > 2.5 mL/kg was rarely needed to avoid hypercapnia. Weight-correction of DCO2 values improved its comparability between patients. Weight-corrected DCO2 correlated better with PCO2 than uncorrected DCO2 but the correlation was weak. © 2017 Wiley Periodicals, Inc.
Ip, Edward H; Wasserman, Richard; Barkin, Shari
2011-03-01
Designing cluster randomized trials in clinical studies often requires accurate estimates of intraclass correlation, which quantifies the strength of correlation between units, such as participants, within a cluster, such as a practice. Published ICC estimates, even when available, often suffer from the problem of wide confidence intervals. Using data from a national, randomized, controlled study concerning violence prevention for children--the Safety Check--we compare the ICC values derived from two approaches only baseline data and using both baseline and follow-up data. Using a variance component decomposition approach, the latter method allows flexibility in handling complex data sets. For example, it allows for shifts in the outcome variable over time and for an unbalanced cluster design. Furthermore, we evaluate the large-sample formula for ICC estimates and standard errors using the bootstrap method. Our findings suggest that ICC estimates range from 0.012 to 0.11 for providers within practice and range from 0.018 to 0.11 for families within provider. The estimates derived from the baseline-only and repeated-measurements approaches agree quite well except in cases in which variation over repeated measurements is large. The reductions in the widths of ICC confidence limits from using repeated measurement over baseline only are, respectively, 62% and 42% at the practice and provider levels. The contribution of this paper therefore includes two elements, which are a methodology for improving the accuracy of ICC, and the reporting of such quantities for pediatric and other researchers who are interested in designing clustered randomized trials similar to the current study.
Kotovich, D; Guedalia, J S B; Hoffmann, C; Sze, G; Eisenkraft, A; Yaniv, G
2017-07-01
Cytomegalovirus is the leading intrauterine infection. Fetal MR imaging is an accepted tool for fetal brain evaluation, yet it still lacks the ability to accurately predict the extent of the neurodevelopmental impairment, especially in fetal MR imaging scans with unremarkable findings. Our hypothesis was that intrauterine cytomegalovirus infection causes diffusional changes in fetal brains and that those changes may correlate with the severity of neurodevelopmental deficiencies. A retrospective analysis was performed on 90 fetal MR imaging scans of cytomegalovirus-infected fetuses with unremarkable results and compared with a matched gestational age control group of 68 fetal head MR imaging scans. ADC values were measured and averaged in the frontal, parietal, occipital, and temporal lobes; basal ganglia; thalamus; and pons. For neurocognitive assessment, the Vineland Adaptive Behavior Scales, Second Edition (VABS-II) was used on 58 children in the cytomegalovirus-infected group. ADC values were reduced for the cytomegalovirus-infected fetuses in most brain areas studied. The VABS-II showed no trend for the major domains or the composite score of the VABS-II for the cytomegalovirus-infected children compared with the healthy population distribution. Some subdomains showed an association between ADC values and VABS-II scores. Cytomegalovirus infection causes diffuse reduction in ADC values in the fetal brain even in unremarkable fetal MR imaging scans. Cytomegalovirus-infected children with unremarkable fetal MR imaging scans do not deviate from the healthy population in the VABS-II neurocognitive assessment. ADC values were not correlated with VABS-II scores. However, the lack of clinical findings, as seen in most cytomegalovirus-infected fetuses, does not eliminate the possibility of future neurodevelopmental pathology. © 2017 by American Journal of Neuroradiology.
利用相关系数改进的光束法平差相机检校%Camera Calibration of the Bundle Method Improved by Correlation Coefficient
孟丽媛; 孙黎明
2015-01-01
At present, the non-metric camera has become a major tool of close-range photogrammetry because it ’s economical and it’s easy to carry. Camera calibration is essential in photogrammetry. By solving the correlation coefficient between the stan⁃dard calibration image and the image taken by the measuring camera, the Lens distortion of the camera can be determined. Using the correlation coefficient as the iteration condition of the bundle adjustment, the adjustment results can be more precise and the camera distortion parameters can be more precise,too.%由于非量测相机价格便宜、易于携带等优点，它已成为近景摄影测量的主要工具。相机检校是摄影测量中至关重要的一步。通过求解标准检校影像与非量测相机所拍影像间的相关系数的大小，可以确定相机的镜头畸变严重程度。以相关系数作为光束法平差的迭代条件对其进行改进，可以提高光束法平差的精度，得到更为精确的相机畸变参数。
邵文权; 乔妮; 王建波
2015-01-01
The inrush current is the main factor that leads to misoperation for transformer differential current protection. This paper proposes a novel algorithm based on waveform cross correlation principle for distinguishing between magnetizing inrush current and internal fault currents. Either in the case of no-load switching or internal faults, a short sampling data-window is used to produce a normal sine wave as reference, and then calculate the normalized cross-correlation coefficient between the practical sampled waveform and the reference. In the condition of internal faults, the normalized cross-correlation coefficient is close to 1. But in the situation of inrush current, it is deviated from 1 and waves notably. Therefore, the calculated normalized cross-correlation coefficient is used to detect internal faults and inrush current. PACAD simulation results indicate that the proposed algorithm can identify inrush current and internal faults correctly and quickly, and it is helpful to supply theoretical basis for improving the performance of differential protection and optimizing protection scheme in transformers.%励磁涌流是导致变压器差动保护误动的主要因素。提出一种利用波形互相关系数特征的励磁涌流识别方法。利用空载合闸或内部故障后的短数据窗构造一标准正弦参考波，对采样波形与构造的标准正弦波两信号的相关性进行分析，计算归一化互相关系数进行内部故障和涌流识别。内部故障时波形互相关系数为接近1的稳定值，而励磁涌流时互相关系数偏离1且其值波动显著。最后PSCAD仿真计算分析结果表明：该方法能在一个周波内准确识别出励磁涌流与内部故障，为提高变压器差动保护性能和优化变压器保护配置提供了有益的理论依据。
Agbodemegbe, V.Y., E-mail: vincevalt@gmail.com [Karlsruhe Institute of Technology, Institute of Fusion and Reactor Technique, Kaiserstrasse 12, Karlsruhe (Germany); Cheng, Xu, E-mail: xu.cheng@kit.edu [Karlsruhe Institute of Technology, Institute of Fusion and Reactor Technique, Kaiserstrasse 12, Karlsruhe (Germany); Akaho, E.H.K, E-mail: akahoed@yahoo.com [School of Nuclear and Allied Sciences, University of Ghana, PO Box AE 1, Kwabenya, Accra (Ghana); Allotey, F.K.A, E-mail: fkallotey@gmail.com [Institute of Mathematical Sciences, PO Box LG 197, Legon, Accra (Ghana)
2015-04-15
Highlights: • Investigate spacer grid with split-type mixing vanes. • Extent of predictability of experimental data by STAR-CCM+. • Reliability of two equation turbulence models. • Resistance to cross-flow through gaps. - Abstract: Mass transfer by diversion cross-flow through gaps is an important inter-subchannel interaction in fuel bundle of power reactors. It is normally due to the lateral pressure difference between adjacent sub-channels. This phenomenon is augmented in the presence of flow deflectors and is referred to as, directed cross-flow. Diversion cross-flow carries the momentum and energy of flow and hence affects the velocity and temperature profile in the rod bundle. The resistance to cross-flow in the transverse momentum equations is specified by the cross-flow resistant coefficient which is the subject of concern in the present study. In order to obtain data to correlate cross-flow resistance coefficient, computational fluid dynamic simulation using STAR-CCM+ was performed for flow of water at the bundle Reynolds number of Re1 = 3.4×10{sup 4} through a 5 × 5 rod bundle geometry supported by spacer grid with split mixing vanes for which the rod to rod pitch to diameter ratio was 1.33 and the rod to wall pitch to diameter ratio was 0.74. The two layer k-epsilon turbulence model with an all y+ automatic wall treatment function in STAR-CCM+ were adopted for an isothermal single phase (water) flow through the geometry. The objectives were to primarily investigate the extent of predictability of the experimental data by the computational fluid dynamic (CFD) simulation as a measure of reliability on the CFD code employed and also apply the simulation data to develop correlations for determining resistance coefficient to cross-flow. Validation of simulation results with experimental data showed good correlation of mean flow parameters with experimental data whiles turbulent fluctuations deviated largely from experimental trends. Generally, the
张贤彪; 黄高明; 刘德志; 陶涛
2012-01-01
According to the problem that the independence criterion based on the minimization of mutual information is not normalized, a blind source separation(BSS) algorithm for post-nonlinear mixture(PNL) based on general correlation coefficient is introduced in this paper. Firstly, the PNL is taken as an indraft point to summarize this algorithm, which is the more practicable approximation to realism rather than linear model, meanwhile the independence criterion based on the generalized correlation coefficient is discussed. Then score function based on a Gram-Charlier expansion of densities is proposed. Finally, combined with the steepest descent method, the computations of regular matrix and parametric nonlinear mapping are given. The simulation results show that the proposed method is effective in BSS for the PNL and for the quantitative analysis of nonlinear correlation between variables.%基于互信息最小化的独立性测度对各分离信号间的非线性相关度度量没有归一化的问题,提出一种基于广义相关系数的肓信号分离(BSS)算法.首先选取后非线性混叠模型(PNL)分析基于广义相关系数的独立性测度；然后采用Gram-Charlier扩展形式估计输出参数并获取评价几率函数,结合最陡下降法求得分离矩阵和参数化可逆非线性映射的算法迭代公式.仿真结果表明,采用所提出的算法能够定量分析各分离信号间的非线性相关程度,有效分离后非线性混叠信号.
Fabián, Z. (Zdeněk)
2010-01-01
In this paper, we study a distribution-dependent correlation coefficient based on the concept of scalar score. This new measure of association of continuous random variables is compared by means of simulation experiments with the Pearson, Kendall and Spearman correlation coefficients.
刘圣波; 刘贺; 赵燕东
2013-01-01
为了提高光伏太阳能转换率，拓展传统纹波控制技术的应用，该文提出了离散时间纹波控制算法，通过对纹波控制技术的离散化处理，将最大功率点跟踪控制问题转换为离散采样-控制问题。以太阳能板输出电压为状态量，在其处于极大值和极小值时对系统进行采样；随后采取离散时间纹波控制算法使系统快速追踪到系统的最大功率点。该文在Simulink系统中对离散时间纹波控制算法进行了仿真。仿真结果表明，在1000和200 W/cm2，25℃的条件下，算法均可以快速准确地追踪到太阳能系统的最大功率点，追踪精度高达96%；在外部环境由1000变为200 W/cm2时，系统能够在0.1 s内准确地追踪到新的最大功率点。%Solar photovoltaic technology has been widely used in modern agriculture. Due to the volatility of solar power, it is hard to maximize the use of solar energy. In order to seek a way to improve the conversion rate of photovoltaic solar panels, this paper developed a new algorithm to utilize solar energy more efficiently. Since tracking solar maximum power point is a valid method to maintain the solar panel power output at a high level, at this paper, we choose ripple correlation control (RCC) to keep tracking the maximum power point of a solar photovoltaic (PV) system. Ripple correlation control is a real-time optimal method particularly suitable for power convertor control. The objective of RCC in solar PV system is to maximize the energy quantity. This paper extended the traditional analog RCC technique to the digital domain. With discretization and simplifications of math model, the RCC method can be transformed to a sampling problem. The control method shows that when the solar PV system reaches the maximum power point, power outputs at both maximum and minimum state should be nearly the same. Moreover, since voltage output of a system is easy to observe and directly related to power
Zukotynski, Katherine A; Vajapeyam, Sridhar; Fahey, Frederic H; Kocak, Mehmet; Brown, Douglas; Ricci, Kelsey I; Onar-Thomas, Arzu; Fouladi, Maryam; Poussaint, Tina Young
2017-08-01
The purpose of this study was to describe baseline (18)F-FDG PET voxel characteristics in pediatric diffuse intrinsic pontine glioma (DIPG) and to correlate these metrics with baseline MRI apparent diffusion coefficient (ADC) histogram metrics, progression-free survival (PFS), and overall survival. Methods: Baseline brain (18)F-FDG PET and MRI scans were obtained in 33 children from Pediatric Brain Tumor Consortium clinical DIPG trials. (18)F-FDG PET images, postgadolinium MR images, and ADC MR images were registered to baseline fluid attenuation inversion recovery MR images. Three-dimensional regions of interest on fluid attenuation inversion recovery MR images and postgadolinium MR images and (18)F-FDG PET and MR ADC histograms were generated. Metrics evaluated included peak number, skewness, and kurtosis. Correlation between PET and MR ADC histogram metrics was evaluated. PET pixel values within the region of interest for each tumor were plotted against MR ADC values. The association of these imaging markers with survival was described. Results: PET histograms were almost always unimodal (94%, vs. 6% bimodal). None of the PET histogram parameters (skewness or kurtosis) had a significant association with PFS, although a higher PET postgadolinium skewness tended toward a less favorable PFS (hazard ratio, 3.48; 95% confidence interval [CI], 0.75-16.28 [P = 0.11]). There was a significant association between higher MR ADC postgadolinium skewness and shorter PFS (hazard ratio, 2.56; 95% CI, 1.11-5.91 [P = 0.028]), and there was the suggestion that this also led to shorter overall survival (hazard ratio, 2.18; 95% CI, 0.95-5.04 [P = 0.067]). Higher MR ADC postgadolinium kurtosis tended toward shorter PFS (hazard ratio, 1.30; 95% CI, 0.98-1.74 [P = 0.073]). PET and MR ADC pixel values were negatively correlated using the Pearson correlation coefficient. Further, the level of PET and MR ADC correlation was significantly positively associated with PFS; tumors with higher
Heat transfer coefficient for boiling carbon dioxide
Knudsen, Hans Jørgen Høgaard; Jensen, Per Henrik
1998-01-01
Heat transfer coefficient and pressure drop for boiling carbon dioxide (R744) flowing in a horizontal pipe has been measured. The calculated heat transfer coeeficient has been compared with the Chart correlation of Shah. The Chart Correlation predits too low heat transfer coefficient but the ratio...
周塔
2014-01-01
收集了4个JDK版本相应的Java包JSCG特征数据，建立了相应的双层知识网络，对JDK双层网络的度相关性和集群系数相关性进行了详细分析，定量研究了物理层、功能层中度相关性函数以及集群系数相关性函数。研究发现：理论分析的结论和实证统计的结果非常接近，均呈现出正相关性，这表明在JDK双层网络中存在这样的相关性关系，进一步说明分析和实证是合理的。%The paper collects characteristic data in Java package of four JDK versions, structures the correspond-ing double knowledge networks, and makes an analysis of the correlations of the degree and the clustering coeffi-cients of the JDK double layered network, including a quantitative research on their correlation functions on the physical layer and functional layer, respectively.The analytical result is consistent with the empirical statistics, which indicates that there exists such correlations in the double layered network.
Maximum Autocorrelation Factorial Kriging
Nielsen, Allan Aasbjerg; Conradsen, Knut; Pedersen, John L.
2000-01-01
This paper describes maximum autocorrelation factor (MAF) analysis, maximum autocorrelation factorial kriging, and its application to irregularly sampled stream sediment geochemical data from South Greenland. Kriged MAF images are compared with kriged images of varimax rotated factors from...
李章安; 廖超平; 刘厚康
2015-01-01
Spearman秩相关系数法和湖泊（水库）综合营养状态指数法的计算公式应用非常普遍，用日常办公所用的Microsoft Office Excel电子表格以列表的方式来计算这两个公式，既简便、通俗，更能大大提高计算效率和结果的准确性。%Spearman rank correlation coefficient metho d and lakes (reservoirs) comprehensive nutrition state index method using formula is very common. Microsoft Office Excel spreadsheet used in the daily office was used to list to calculate the two formulas, which was simple,popular and can greatly improve the calculation efficiency and accuracy of the results.
Software for Computing the Tetrachoric Correlation Coefficient
Rubén Daniel Ledesma
2011-01-01
Full Text Available La correlación tetracórica es un caso particular de análisis de correlación entre variables continuas distribuidas normalmente pero que han sido medidas en formato dicotómico. En este artículo se presenta ViSta-Tetrachor, un software gratuito que emplea una aproximación al coeficiente de correlación tetracórica caracterizada por ser más fácil de computar que las ecuaciones originales, así como más eficiente que otras aproximaciones propuestas. ViSta-Tetrachor proporciona estimaciones puntuales e intervalos de confianza para el estadístico. También permite generar matrices de correlación tetracórica y aplicar un análisis factorial a estas matrices. Se presenta una breve descripción del programa junto con diversos ejemplos de aplicación.
Maximum flux density of the gyrosynchrotron spectrum in a nonuniform source
Ai-Hua Zhou; Rong-Chuan Wang; Cheng-Wen Shao
2009-01-01
The maximum flux density of a gyrosynchrotron radiation spectrum in a mag- netic dip|oe model with self absorption and gyroresonance is calculated. Our calculations show that the maximum flux density of the gyrosynchrotron spectrum increases with in- creasing low-energy cutoff, number density, input depth of energetic electrons, magnetic field strength and viewing angle, and with decreasing energy spectral index of energetic electrons, number density and temperature of thermal electrons. It is found that there are linear correlations between the logarithms of the maximum flux density and the above eight parameters with correlation coefficients higher than 0.91 and fit accuracies better than 10%. The maximum flux density could be a good indicator of the changes of these source parameters. In addition, we find that there are very good positive linear correla- tions between the logarithms of the maximum flux density and peak frequency when the above former five parameters vary respectively. Their linear correlation coefficients are higher than 0.90 and the fit accuracies are better than 0.5%.
Heat transfer coefficient for boiling carbon dioxide
Knudsen, Hans Jørgen Høgaard; Jensen, Per Henrik
1998-01-01
between the measured and the calculated heat transfer coefficient is nearly constant and equal 1.9. With this factor the correlation predicts the measured data within 14% (RMS). The pressure drop is of the same order as the measuring uncertainty and the pressure drop has not been compared with correlation's.......Heat transfer coefficient and pressure drop for boiling carbon dioxide (R744) flowing in a horizontal pipe has been measured. The calculated heat transfer coeeficient has been compared with the Chart correlation of Shah. The Chart Correlation predits too low heat transfer coefficient but the ratio...
Poulin, Patrick; Hop, Cornelis Eca; Salphati, Laurent; Liederer, Bianca M
2013-04-01
Understanding drug distribution and accumulation in tumors would be informative in the assessment of efficacy in targeted therapy; however, existing methods for predicting tissue drug distribution focus on normal tissues and do not incorporate tumors. The main objective of this study was to describe the relationships between tissue-plasma concentration ratios (Kp ) of normal tissues and those of subcutaneous xenograft tumors under nonsteady-state conditions, and establish regression equations that could potentially be used for the prediction of drug levels in several human tumor xenografts in mouse, based solely on a Kp value determined in a normal tissue (e.g., muscle). A dataset of 17 compounds was collected from the literature and from Genentech. Tissue and plasma concentration data in mouse were obtained following oral gavage or intraperitoneal administration. Linear regression analyses were performed between Kp values in several normal tissues (muscle, lung, liver, or brain) and those in human tumor xenografts (CL6, EBC-1, HT-29, PC3, U-87, MCF-7-neo-Her2, or BT474M1.1). The tissue-plasma ratios in normal tissues reasonably correlated with the tumor-plasma ratios in CL6, EBC-1, HT-29, U-87, BT474M1.1, and MCF-7-neo-Her2 xenografts (r(2) in the range 0.62-1) but not with the PC3 xenograft. In general, muscle and lung exhibited the strongest correlation with tumor xenografts, followed by liver. Regression coefficients from brain were low, except between brain and the glioblastoma U-87 xenograft (r(2) in the range 0.62-0.94). Furthermore, reasonably strong correlations were observed between muscle and lung and between muscle and liver (r(2) in the range 0.67-0.96). The slopes of the regressions differed depending on the class of drug (strong vs. weak base) and type of tissue (brain vs. other tissues and tumors). Overall, this study will contribute to our understanding of tissue-plasma partition coefficients for tumors and facilitate the use of physiologically
苑津莎; 尚海昆; 王瑜; 靳松
2013-01-01
针对变压器局部放电模式分类过程中特征参数维数过高的问题，提出了一种基于相关系数矩阵的参数降维方法。利用提取出的变压器局部放电信号的特征参数构造相关系数矩阵，通过分析放电信号18个特征参数间的相关性，删除具有相似分类能力的特征参数，之后引入分离度指标来衡量特征向量的分类能力大小，提取出6个具有较高分类能力的特征向量，最后通过概率神经网络进行模式识别。结果表明该降维方法有效降低了特征参数的维数，简化了分类器结构，在小样本情况下对于概率神经网络模式分类器具有较高的识别率，识别效果优于传统BP神经网络。%A new dimension reduction method based on correlation coefficient matrix is proposed aimed at the high-dimension of characteristic parameters in the process of pattern recognition for partial discharge in power transformer. The correlation coefficient matrix (CCM) is constructed using parameters extracted from partial discharge signal in power transformer. The parameters which have similar classification ability to each other are deleted with the help of correlation analysis among 18 characteristic parameters in CCM. Six parameters which have higher classification capabilities are extracted using the critical index and are used as the inputs for pattern classifiers of probabilistic neural networks. The results show that the parameter dimension is reduced and the classifier construction is simplified, and the recognition effect is better than that of the traditional back propagation neural network in the condition of small samples.
王振; 王中平; 郁群; 翁友法
2011-01-01
Since different detection methods of concrete permeability have both advantages and disadvantages, the study of the correlation between several permeability indexes has become a trend.This paper dicusses the correlation between the durability indexes of charge passed and air permeability coefficient of the mineral admixture modified concrete, and the relation between the amount of chloride-ion migration and charge passed by ASTM C1202 Method and Cembureau Method.The results indicate that: the linear correlations between charge passed and gas permeability coefficient, and the amount of chloride-ion migration were found to be significant.The chloride-ion migration amount (Decrement of chloride-ion in cathode cell, Increment of chloride-ion in anode cell, Chloride penetration depth) can be considered as one quantitative indexes of concrete permeability while it is not proper to directly measure the chloride permeability of concrete only by charge passed.In addition, the micro-crack induced by drying will cause the charge passed improved obviously.%由于混凝土渗透性能的不同检测方法各有优缺点,探讨几种渗透性能指标间的相关性已成为一种趋势.文章采用ASTM C1202直流电量法和Cembureau法探讨掺合料混凝土导电量与气体渗透系数两种耐久性指标间的相关性,并就电极溶液中氯离子的迁移量和导电量的关系进行讨论.结果表明:掺合料混凝土导电量与气体渗透系数之间存在线性相关性,其换算关系还需要更系统的实验来确立;在对以导电量直接评价混凝土抗氯离子渗透性能有所质疑时,可以考虑将实际的氯离子迁移量(阴极溶液氯离子减少量、阳极溶液氯离子增加量、氯离子渗透深度)作为评价混凝土抗氯离子渗透性能的一个辅助指标;干燥引发的微裂纹会导致混凝土导电量明显提高.
An eight-legged tactile sensor to estimate coefficient of static friction.
Wei Chen; Rodpongpun, Sura; Luo, William; Isaacson, Nathan; Kark, Lauren; Khamis, Heba; Redmond, Stephen J
2015-08-01
It is well known that a tangential force larger than the maximum static friction force is required to initiate the sliding motion between two objects, which is governed by a material constant called the coefficient of static friction. Therefore, knowing the coefficient of static friction is of great importance for robot grippers which wish to maintain a stable and precise grip on an object during various manipulation tasks. Importantly, it is most useful if grippers can estimate the coefficient of static friction without having to explicitly explore the object first, such as lifting the object and reducing the grip force until it slips. A novel eight-legged sensor, based on simplified theoretical principles of friction is presented here to estimate the coefficient of static friction between a planar surface and the prototype sensor. Each of the sensor's eight legs are straight and rigid, and oriented at a specified angle with respect to the vertical, allowing it to estimate one of five ranges (5 = 8/2 + 1) that the coefficient of static friction can occupy. The coefficient of friction can be estimated by determining whether the legs have slipped or not when pressed against a surface. The coefficients of static friction between the sensor and five different materials were estimated and compared to a measurement from traditional methods. A least-squares linear fit of the sensor estimated coefficient showed good correlation with the reference coefficient with a gradient close to one and an r(2) value greater than 0.9.
Auplish, Aashima; Clarke, Alison S; Van Zanten, Trent; Abel, Kate; Tham, Charmaine; Bhutia, Thinlay N; Wilks, Colin R; Stevenson, Mark A; Firestone, Simon M
2017-05-01
Educational initiatives targeting at-risk populations have long been recognized as a mainstay of ongoing rabies control efforts. Cluster-based studies are often utilized to assess levels of knowledge, attitudes and practices of a population in response to education campaigns. The design of cluster-based studies requires estimates of intra-cluster correlation coefficients obtained from previous studies. This study estimates the school-level intra-cluster correlation coefficient (ICC) for rabies knowledge change following an educational intervention program. A cross-sectional survey was conducted with 226 students from 7 schools in Sikkim, India, using cluster sampling. In order to assess knowledge uptake, rabies education sessions with pre- and post-session questionnaires were administered. Paired differences of proportions were estimated for questions answered correctly. A mixed effects logistic regression model was developed to estimate school-level and student-level ICCs and to test for associations between gender, age, school location and educational level. The school- and student-level ICCs for rabies knowledge and awareness were 0.04 (95% CI: 0.01, 0.19) and 0.05 (95% CI: 0.2, 0.09), respectively. These ICCs suggest design effect multipliers of 5.45 schools and 1.05 students per school, will be required when estimating sample sizes and designing future cluster randomized trials. There was a good baseline level of rabies knowledge (mean pre-session score 71%), however, key knowledge gaps were identified in understanding appropriate behavior around scared dogs, potential sources of rabies and how to correctly order post rabies exposure precaution steps. After adjusting for the effect of gender, age, school location and education level, school and individual post-session test scores improved by 19%, with similar performance amongst boys and girls attending schools in urban and rural regions. The proportion of participants that were able to correctly order post
IS THE SAMPLE COEFFICIENT OF VARIATION A GOOD ESTIMATOR FOR THE POPULATION COEFFICIENT OF VARIATION?
Mahmoudvand, Rahim; HASSANI, Hossein; Wilson, Rob
2007-01-01
In this paper, we obtain bounds for the population coefficient of variation (CV) in Bernoulli, Discrete Uniform, Normal and Exponential distributions. We also show that the sample coefficient of variation (cv) is not an accurate estimator of the population CV in the above indicated distributions. Finally we provide some suggestions based on the Maximum Likelihood Estimation to improve the population CV estimate.
Wave Reflection Coefficient Spectrum
俞聿修; 邵利民; 柳淑学
2003-01-01
The wave reflection coefficient frequency spectrum and directional spectrum for concrete face slope breakwaters and rubble mound breakwaters are investigated through physical model tests in the present study. The reflection coefficients of oblique irregular waves are analyzed by the Modified Two-Point Method (MTPM) proposed by the authors. The results show that the wave reflection coefficient decreases with increasing wave frequency and incident angle or decreasing structure slope. The reflection coefficient frequency spectrum and its variation with Iribarren number are given in this paper. The paper also suggests an empirical 3-dimensional reflection coefficient spectrum, i.e. reflection coefficient directional spectrum, which can be used to illustrate quantitatively the variation of reflection coefficient with the incident angle and the Iribarren number for oblique irregular waves.
Maximum Autocorrelation Factorial Kriging
Nielsen, Allan Aasbjerg; Conradsen, Knut; Pedersen, John L.; Steenfelt, Agnete
2000-01-01
This paper describes maximum autocorrelation factor (MAF) analysis, maximum autocorrelation factorial kriging, and its application to irregularly sampled stream sediment geochemical data from South Greenland. Kriged MAF images are compared with kriged images of varimax rotated factors from an ordinary non-spatial factor analysis, and they are interpreted in a geological context. It is demonstrated that MAF analysis contrary to ordinary non-spatial factor analysis gives an objective discrimina...
Interpretation of Standardized Regression Coefficients in Multiple Regression.
Thayer, Jerome D.
The extent to which standardized regression coefficients (beta values) can be used to determine the importance of a variable in an equation was explored. The beta value and the part correlation coefficient--also called the semi-partial correlation coefficient and reported in squared form as the incremental "r squared"--were compared for…
张宇镭; 党琰; 贺平安
2005-01-01
论文主要利用计算语言学中使用的统计学方法定量分析生物物种的亲缘关系.以包含生物体遗传信息的核酸序列为研究对象,采用计算语言学的思想和方法,将每一个生物体的核酸序列看作一篇很长的自然语言文本,抽取核酸序列的双核苷酸频率分布特征向量,用以表征其数字特征.而后采用Pearson Correlation Coefficient(Pearson相关系数)定量分析其亲缘关系的远近程度.将119个细菌的全基因组核酸序列进行两两比对,对所得的7 021个r值进行分析,得出的结论是:亲缘关系越相近的物种,其Pearson相关系数越大.取定0.985作为"属"的分界阈值时,得到召回率为75.824%,准确率为73.404%.论文对定量分析生物学核酸序列的相似性和对生物亲缘关系远近的建模有重要的实际意义.
An Efficient Approach for Computing Silhouette Coefficients
Moh'd B. Al- Zoubi
2008-01-01
Full Text Available One popular approach for finding the best number of clusters (K in a data set is through computing the silhouette coefficients. The silhouette coefficients for different values of K, are first found and then the maximum value of these coefficients is chosen. However, computing the silhouette coefficient for different Ks is a very time consuming process. This is due to the amount of CPU time spent on distance calculations. A proposed approach to compute the silhouette coefficient quickly had been presented. The approach was based on decreasing the number of addition operations when computing distances. The results were efficient and more than 50% of the CPU time was achieved when applied to different data sets.
Discharge coefficient of small sonic nozzles
Yin Zhao-Qin
2014-01-01
Full Text Available The purpose of this investigation is to understand flow characteristics in mini/micro sonic nozzles, in order to precisely measure and control miniscule flowrates. Experimental and numerical simulation methods have been used to study critical flow Venturi nozzles. The results show that the nozzle’s size and shape influence gas flow characteristics which leading the boundary layer thickness to change, and then impact on the discharge coefficient. With the diameter of sonic nozzle throat decreasing, the discharge coefficient reduces. The maximum discharge coefficient exits in the condition of the inlet surface radius being double the throat diameter. The longer the diffuser section, the smaller the discharge coefficient becomes. Diffuser angle affects the discharge coefficient slightly.
Maximum likely scale estimation
Loog, Marco; Pedersen, Kim Steenstrup; Markussen, Bo
2005-01-01
A maximum likelihood local scale estimation principle is presented. An actual implementation of the estimation principle uses second order moments of multiple measurements at a fixed location in the image. These measurements consist of Gaussian derivatives possibly taken at several scales and/or ...
A drying coefficient for building materials
Scheffler, Gregor Albrecht; Plagge, Rudolf
2009-01-01
The drying experiment is an important element of the hygrothermal characterisation of building materials. Contrary to other moisture transport experiments as the vapour diffusion and the water absorption test, it is until now not possible to derive a simple coefficient for the drying. However...... coefficient is defined which can be determined based on measured drying data. The correlation of this coefficient with the water absorption and the vapour diffusion coefficient is analyzed and its additional information content is critically challenged. As result, a drying coefficient has been derived...... and defined as a new and independent material parameter. It contains information about the moisture transport properties throughout the wide range of moisture contents from hygroscopic up to saturation. With this new and valuable coefficient, it is now possible to distinguish and select building materials...
兰兰; 郭明丽; 饶绍奇; 王秋菊; 韩东一; 史伟; 韩明鲲; 刘穹; 丁海娜; 陈之慧; 王大勇; 李善红
2008-01-01
Objective To estimate correlation between phonetically balanced maximum(PB max)and pure tone auditory threshold in auditory neuropathy(AN)patients.nethods 0ne hundred and six ANpatients were identified using multipie criteria including PB max,a metric for speech recognition,pure tone auditory threshold.acoustic emission test.distortion products otoacoustic emission(DPOAE) and auditory brainstem response(ABR).SPSS statistical software was used to estimate the Pearson's correlation between PB max and pure tone auditory threshold and to test whether pure tone auditory threshold,or auditory configuration had a significant impact on PB max.Results Even the patients had the same or similar values for pure tone auditory threshold or auditory configuration.varied values of PB max were found in two hundreds and twelve ears for 106 patients.Analysis of the data for 106 patients revealed a negative correlation(r=-0.602,P<0.01) between PB max and pure tone auditory threshold,i.e.hearing loss at a mild relates to a lower PB max.By using analysis of variance(ANOVA)method,it Was found that both pure tone auditory threshold and auditory configuration had a significant(P<0.01)impact on the patients' PB max.Conclusions This analysis implicated the promise and potential of pure tone auditory threshold and auditory configuration for predicting PB max of the AN patients,and improving the diagnosis of AN.%目的 分析听神经病患者最大言语识别率与纯音测听之间的相关性,探讨听神经病患者与言语识别率不成比例的临床意义.方法 对106例(212耳)经纯音测听、声导抗、畸变产物耳声发射、听件脑干反应测试确诊为听神经病的患者,行最大言语识别率测试,并与不同程度损失及不同类型听力曲线进行分类、分型比较.依据损失分出轻度、中度、中重度和重度;依据听力曲线分为平坦型、低频上升Ⅰ型、低频上升Ⅱ型、山型、谷型、不典型.统计数据应用SPSS 11.0
Maximum information photoelectron metrology
Hockett, P; Wollenhaupt, M; Baumert, T
2015-01-01
Photoelectron interferograms, manifested in photoelectron angular distributions (PADs), are a high-information, coherent observable. In order to obtain the maximum information from angle-resolved photoionization experiments it is desirable to record the full, 3D, photoelectron momentum distribution. Here we apply tomographic reconstruction techniques to obtain such 3D distributions from multiphoton ionization of potassium atoms, and fully analyse the energy and angular content of the 3D data. The PADs obtained as a function of energy indicate good agreement with previous 2D data and detailed analysis [Hockett et. al., Phys. Rev. Lett. 112, 223001 (2014)] over the main spectral features, but also indicate unexpected symmetry-breaking in certain regions of momentum space, thus revealing additional continuum interferences which cannot otherwise be observed. These observations reflect the presence of additional ionization pathways and, most generally, illustrate the power of maximum information measurements of th...
Transport Coefficients of Fluids
Eu, Byung Chan
2006-01-01
Until recently the formal statistical mechanical approach offered no practicable method for computing the transport coefficients of liquids, and so most practitioners had to resort to empirical fitting formulas. This has now changed, as demonstrated in this innovative monograph. The author presents and applies new methods based on statistical mechanics for calculating the transport coefficients of simple and complex liquids over wide ranges of density and temperature. These molecular theories enable the transport coefficients to be calculated in terms of equilibrium thermodynamic properties, and the results are shown to account satisfactorily for experimental observations, including even the non-Newtonian behavior of fluids far from equilibrium.
Predicting the solar maximum with the rising rate
Du, Z L
2011-01-01
The growth rate of solar activity in the early phase of a solar cycle has been known to be well correlated with the subsequent amplitude (solar maximum). It provides very useful information for a new solar cycle as its variation reflects the temporal evolution of the dynamic process of solar magnetic activities from the initial phase to the peak phase of the cycle. The correlation coefficient between the solar maximum (Rmax) and the rising rate ({\\beta}a) at {\\Delta}m months after the solar minimum (Rmin) is studied and shown to increase as the cycle progresses with an inflection point (r = 0.83) at about {\\Delta}m = 20 months. The prediction error of Rmax based on {\\beta}a is found within estimation at the 90% level of confidence and the relative prediction error will be less than 20% when {\\Delta}m \\geq 20. From the above relationship, the current cycle (24) is preliminarily predicted to peak around October 2013 with a size of Rmax =84 \\pm 33 at the 90% level of confidence.
Mery, A
2007-07-15
The central topic of this work is the study of the properties and the implementation of a Paul trap used for the measurement of the beta-neutrino angular correlation parameter in the decay of {sup 6}He. This coefficient provides a signature of the nature of the interactions involved in the weak interaction. The value of this coefficient can be deduced from the kinematical distribution of the decay events. An electromagnetic trap is used for the trapping of {sup 6}He{sup +} ions in a small volume. This trap has an open geometry that enables the detection in coincidence of the electron and the recoil ion emitted in the beta decay. A dedicated detection set up is used for the measurement of the electron energy, the ion time of flight and the position of the two particles for each event. A general description of the LPCTrap facility and of its performances is presented and shows that this set up is able to fulfill the proposed measurement. Especially, a comparison is made between the characteristics of the ion cloud obtained from Monte Carlo simulations and the experimental measurements with a good agreement. More than 100 000 coincident events have been recorded during the first experiment. A preliminary analysis of these results is shown. It includes a description of the different observables as well as a comparison between the experimental time of flight spectrum and the simulated spectrum. These data will allow a measurement of the angular correlation parameter with a statistical error smaller than 2 %. (author)
A stochastic maximum principle via Malliavin calculus
Øksendal, Bernt; Zhou, Xun Yu; Meyer-Brandis, Thilo
2008-01-01
This paper considers a controlled It\\^o-L\\'evy process where the information available to the controller is possibly less than the overall information. All the system coefficients and the objective performance functional are allowed to be random, possibly non-Markovian. Malliavin calculus is employed to derive a maximum principle for the optimal control of such a system where the adjoint process is explicitly expressed.
Comparison of Different Dough Rheological Measurement and Path Coefficient Analysis of Bread Quality
LIU Yan-ling; TIAN Ji-chun; DENG Zhi-ying; HAN Xiang-ming
2004-01-01
Farinograph, extensograph and mixograph are the special instruments used to determine dough rheological characteristics. In this study, twenty-seven wheat cultivars of different gluten strength were used to study the correlations among each rheological parameter determined by above instruments. Multiple linear regression analysis and path coefficient analysis were used to study the direct and indirect effects of 11 dough rheological characteristics on bread quality. The results showed significant correlations among the principal parameters. There were significantly or extremely significantly positive correlations among development time (DT), stability time (ST), farinograph quality number (FQN) of farinograph, area, maximum resistance (Rmax), viscoelastic ratio (Rmax/E)of extensograph and mixing time (MT), 8-minute-curve-tail (8MCT) of mixograph.These indexes affected bread-making quality either directly or indirectly. Of all the indexes, ST, maximum Rmax, MT and FQN were the most important ones.
Assessing reproducibility by the within-subject coefficient of variation with random effects models.
Quan, H; Shih, W J
1996-12-01
In this paper we consider the use of within-subject coefficient of variation (WCV) for assessing the reproducibility or reliability of a measurement. Application to assessing reproducibility of biochemical markers for measuring bone turnover is described and the comparison with intraclass correlation is discussed. Both maximum likelihood and moment confidence intervals of WCV are obtained through their corresponding asymptotic distributions. Normal and log-normal cases are considered. In general, WCV is preferred when the measurement scale bears intrinsic meaning and is not subject to arbitrary shifting. The intraclass correlation may be preferred when a fixed population of subjects can be well identified.
Maximum Likelihood Associative Memories
Gripon, Vincent; Rabbat, Michael
2013-01-01
Associative memories are structures that store data in such a way that it can later be retrieved given only a part of its content -- a sort-of error/erasure-resilience property. They are used in applications ranging from caches and memory management in CPUs to database engines. In this work we study associative memories built on the maximum likelihood principle. We derive minimum residual error rates when the data stored comes from a uniform binary source. Second, we determine the minimum amo...
Maximum likely scale estimation
Loog, Marco; Pedersen, Kim Steenstrup; Markussen, Bo
2005-01-01
A maximum likelihood local scale estimation principle is presented. An actual implementation of the estimation principle uses second order moments of multiple measurements at a fixed location in the image. These measurements consist of Gaussian derivatives possibly taken at several scales and....../or having different derivative orders. Although the principle is applicable to a wide variety of image models, the main focus here is on the Brownian model and its use for scale selection in natural images. Furthermore, in the examples provided, the simplifying assumption is made that the behavior...... of the measurements is completely characterized by all moments up to second order....
葛芳君; 赵磊; 刘俊; 周旻馨; 郭毅; 张庆军
2012-01-01
Objective To reflect the correlation between social support and mental health of the aged through the Pearson correlation coefficient. Methods Databases including PubMed, SpringerLink, EMbase, The Cochrane Library, VIP, WanFang Data and CNKI were searched from inception to October, 2011 to collect literature on the correlation between social support and mental health of the aged. The studies were screened according to the inclusion and exclusion criteria. After extracting data and assessing the quality of the included studies, meta-analysis was conducted using RevMan 5.0 software. Results Of the 2 396 identified studies, 4 studies were included. The results showed that 4 studies were not high in the overall quality. The total score of social support of the elderly and its three dimensions were related to mental health. Among 9 factors associated with mental health, somatization, depression and anxiety were weakly correlated to the objective support while the others were extremely weakly correlated. Anxiety and phobic anxiety were weakly correlated to the subjective support while the others were extremely weakly correlated. Phobic anxiety was weakly correlated to the utilizing degree while the others were extremely weakly correlated. Somatization, anxiety and phobic anxiety were weakly correlated to the total score of social support while the others were extremely weakly correlated. Conclusion Social support probably improves mental health of the aged to some extent.%目的 采用Meta分析的方法,评价基于Pearson相关系数的老年人社会支持与心理健康的相关性.方法 计算机检索PubMed、Springerlink、EMbase、the Cochrane Library、VIP、WanFang Data和CNKI数据库,检索时限均为从建库至2011年10月,查找关于老年人社会支持与心理健康相关性的文献.按照纳入排除标准筛选文献、提取资料并评价纳入研究的质量后,采用RevMan 5.0软件进行Meta分析.结果 共检出相关文献2 396
F. TopsÃƒÂ¸e
2001-09-01
Full Text Available Abstract: In its modern formulation, the Maximum Entropy Principle was promoted by E.T. Jaynes, starting in the mid-fifties. The principle dictates that one should look for a distribution, consistent with available information, which maximizes the entropy. However, this principle focuses only on distributions and it appears advantageous to bring information theoretical thinking more prominently into play by also focusing on the "observer" and on coding. This view was brought forward by the second named author in the late seventies and is the view we will follow-up on here. It leads to the consideration of a certain game, the Code Length Game and, via standard game theoretical thinking, to a principle of Game Theoretical Equilibrium. This principle is more basic than the Maximum Entropy Principle in the sense that the search for one type of optimal strategies in the Code Length Game translates directly into the search for distributions with maximum entropy. In the present paper we offer a self-contained and comprehensive treatment of fundamentals of both principles mentioned, based on a study of the Code Length Game. Though new concepts and results are presented, the reading should be instructional and accessible to a rather wide audience, at least if certain mathematical details are left aside at a rst reading. The most frequently studied instance of entropy maximization pertains to the Mean Energy Model which involves a moment constraint related to a given function, here taken to represent "energy". This type of application is very well known from the literature with hundreds of applications pertaining to several different elds and will also here serve as important illustration of the theory. But our approach reaches further, especially regarding the study of continuity properties of the entropy function, and this leads to new results which allow a discussion of models with so-called entropy loss. These results have tempted us to speculate over
Regularized maximum correntropy machine
Wang, Jim Jing-Yan
2015-02-12
In this paper we investigate the usage of regularized correntropy framework for learning of classifiers from noisy labels. The class label predictors learned by minimizing transitional loss functions are sensitive to the noisy and outlying labels of training samples, because the transitional loss functions are equally applied to all the samples. To solve this problem, we propose to learn the class label predictors by maximizing the correntropy between the predicted labels and the true labels of the training samples, under the regularized Maximum Correntropy Criteria (MCC) framework. Moreover, we regularize the predictor parameter to control the complexity of the predictor. The learning problem is formulated by an objective function considering the parameter regularization and MCC simultaneously. By optimizing the objective function alternately, we develop a novel predictor learning algorithm. The experiments on two challenging pattern classification tasks show that it significantly outperforms the machines with transitional loss functions.
NORMATIVE HEAT-TRANSFER COEFFICIENT OF THE RESIDENTIAL BUILDING
A. E. Piir
2015-01-01
Full Text Available The paper offers a simple but sufficiently accurate technique of the mid-normative heattransfer coefficient for any dwelling house applying the known dimensions, required thermalprotection level and specified facade-glazing portion. The authors present the ascertainment technique of the mid-normative heat-transfer coefficient for a dwelling house with the number of stories from 1 to 16 and the required level of thermal protection. They establish the theoretical dependence and parameters affecting the rate of heat-losses through the external building borders. The article considers the thermal-protection level effect on the heating load and the heating-season fuel consumption rate and finds the correlation between the regulatory requirements to the thermal resistance of certain elements of the building.The authors note the effect of the building geometrical characteristics on the heat-losses rate of the wall portion in the total area of the external borders and its relative quantity as compared with the floor-space of the heated accommodations. The comparison of the specific heat-losses computation results for buildings of 1-, 2-, 4-, 8and 16-storeys with the SNiP 23-02–2003 maximum permissible values show the computational results being less than the maximum values on average by 12 %. This permits recommending the normative heat-transfer coefficient of dwelling houses for evaluating heat-loses at the concept-design stage with the building external-borders engineering constructions being indeterminate or yet under development.
Multidimensional extremal dependence coefficients
2017-01-01
Extreme values modeling has attracting the attention of researchers in diverse areas such as the environment, engineering, or finance. Multivariate extreme value distributions are particularly suitable to model the tails of multidimensional phenomena. The analysis of the dependence among multivariate maxima is useful to evaluate risk. Here we present new multivariate extreme value models, as well as, coefficients to assess multivariate extremal dependence.
Assessing Reliability of a Multi-Dimensional Scale by Coefficient Alpha
Ivan Šerbetar
2016-04-01
Full Text Available The purpose of the study was to assess internal consistency by calculating coefficient alpha. It presents the variation in coefficient alpha, depending on questionnaire length and the homogeneity or heterogeneity of the questionnaire. The maximum possible value for coefficient alpha was also calculated by the item elimination method. The study included 99 children aged 10. The children completed The Athletic Coping Skills Inventory – 28 (ACSI-28; Smith et al., 1995, which contains seven constructs: coping with adversity, coachability, concentration, confidence and achievement motivation, goal setting and mental preparation, peaking under pressure and freedom from worry. The results confirmed that the values of the alpha coefficient vary depending on the number and composition of items and the sample size. In terms of item structure, homogeneous constructs yielded lower values for the alpha coefficient (in a range from .48 to .61 than the questionnaire with all the constructs (alpha = .79, despite higher inter-item correlations. In terms of the number of items, the longer test generated higher alpha coefficients (alpha = .79 than the shorter test (half-sets of items = .60, .73, .69, .70. A higher overall value (alpha = .83 can be achieved by item elimination.
Equalized near maximum likelihood detector
2012-01-01
This paper presents new detector that is used to mitigate intersymbol interference introduced by bandlimited channels. This detector is named equalized near maximum likelihood detector which combines nonlinear equalizer and near maximum likelihood detector. Simulation results show that the performance of equalized near maximum likelihood detector is better than the performance of nonlinear equalizer but worse than near maximum likelihood detector.
Cheeseman, Peter; Stutz, John
2005-01-01
A long standing mystery in using Maximum Entropy (MaxEnt) is how to deal with constraints whose values are uncertain. This situation arises when constraint values are estimated from data, because of finite sample sizes. One approach to this problem, advocated by E.T. Jaynes [1], is to ignore this uncertainty, and treat the empirically observed values as exact. We refer to this as the classic MaxEnt approach. Classic MaxEnt gives point probabilities (subject to the given constraints), rather than probability densities. We develop an alternative approach that assumes that the uncertain constraint values are represented by a probability density {e.g: a Gaussian), and this uncertainty yields a MaxEnt posterior probability density. That is, the classic MaxEnt point probabilities are regarded as a multidimensional function of the given constraint values, and uncertainty on these values is transmitted through the MaxEnt function to give uncertainty over the MaXEnt probabilities. We illustrate this approach by explicitly calculating the generalized MaxEnt density for a simple but common case, then show how this can be extended numerically to the general case. This paper expands the generalized MaxEnt concept introduced in a previous paper [3].
S Rahimi Moghaddam
2015-09-01
Full Text Available A field experiment was conducted at the research field of the University of Lorestan in 2011 as a randomized complete block design with three replications to estimate genetic coefficients of some maize (Zea mays L. cultivars. Treatments include six maize cultivars (T.V.C.767 and S.C.704 from late maturing group, T N.S640 and Maxima from mid-maturing group, and Koppany and D.C.370 from early maturing group. Results showed that there were significant differences among cultivars in terms of stem dry weight, maximum number of kernel per ear, thermal time from the flag leaf appearance to flowering, thermal time from flowering to maturity, phyllochron interval, grain weight, maximum plant height and minimum growth degree days during vegetative period. The highest (649.2 and lowest (350.6 maximum number of kernel per ear belonged to cultivars S.C.704 and D.C.370, respectively. Also, the highest and lowest stem dry weight, phyllochron interval and maximum plant height belonged to cultivars S.C.704 and D.C.370, respectively. Among genetic coefficients, the minimum growth degree days required for vegetative growth and the maximum number of kernel per ear had the greatest correlation with grain yield (r=0.72 and r=0.84, respectively. Overall, the results portrayed that the estimated genetic coefficients of the cultivars are not identical in different models and varied in a defined range.
Prestarlike functions with negative coefficients
H. Silverman
1979-01-01
Full Text Available The extreme points for prestarlike functions having negative coefficients are determined. Coefficient, distortion and radii of univalence, starlikeness, and convexity theorems are also obtained.
The Frictional Coefficient of Bovine Knee Articular Cartilage
Qian Shan-hua; Ge Shi-rong; Wang Qing-liang
2006-01-01
The normal displacement of articular cartilage was measured under load and in sliding, and the coefficient of friction during sliding was measured using a UMT-2 Multi-Specimen Test System. The maximum normal displacement under load and the start-up frictional coefficient have similar tendency of variation with loading time. The sliding speed does not significantly influence the frictional coefficient of articular cartilage.
Gorenstein Hilbert Coefficients
Khoury, Sabine El
2012-01-01
We prove upper and lower bounds for all the coefficients in the Hilbert Polynomial of a graded Gorenstein algebra $S=R/I$ with a quasi-pure resolution over $R$. The bounds are in terms of the minimal and the maximal shifts in the resolution of $R$ . These bounds are analogous to the bounds for the multiplicity found in \\cite{S} and are stronger than the bounds for the Cohen Macaulay algebras found in \\cite{HZ}.
Maximum a posteriori decoder for digital communications
Altes, Richard A. (Inventor)
1997-01-01
A system and method for decoding by identification of the most likely phase coded signal corresponding to received data. The present invention has particular application to communication with signals that experience spurious random phase perturbations. The generalized estimator-correlator uses a maximum a posteriori (MAP) estimator to generate phase estimates for correlation with incoming data samples and for correlation with mean phases indicative of unique hypothesized signals. The result is a MAP likelihood statistic for each hypothesized transmission, wherein the highest value statistic identifies the transmitted signal.
The Truth About Ballistic Coefficients
Courtney, Michael
2007-01-01
The ballistic coefficient of a bullet describes how it slows in flight due to air resistance. This article presents experimental determinations of ballistic coefficients showing that the majority of bullets tested have their previously published ballistic coefficients exaggerated from 5-25% by the bullet manufacturers. These exaggerated ballistic coefficients lead to inaccurate predictions of long range bullet drop, retained energy and wind drift.
Santra, Kalyan; Zhan, Jinchun; Song, Xueyu; Smith, Emily A; Vaswani, Namrata; Petrich, Jacob W
2016-03-10
The need for measuring fluorescence lifetimes of species in subdiffraction-limited volumes in, for example, stimulated emission depletion (STED) microscopy, entails the dual challenge of probing a small number of fluorophores and fitting the concomitant sparse data set to the appropriate excited-state decay function. This need has stimulated a further investigation into the relative merits of two fitting techniques commonly referred to as "residual minimization" (RM) and "maximum likelihood" (ML). Fluorescence decays of the well-characterized standard, rose bengal in methanol at room temperature (530 ± 10 ps), were acquired in a set of five experiments in which the total number of "photon counts" was approximately 20, 200, 1000, 3000, and 6000 and there were about 2-200 counts at the maxima of the respective decays. Each set of experiments was repeated 50 times to generate the appropriate statistics. Each of the 250 data sets was analyzed by ML and two different RM methods (differing in the weighting of residuals) using in-house routines and compared with a frequently used commercial RM routine. Convolution with a real instrument response function was always included in the fitting. While RM using Pearson's weighting of residuals can recover the correct mean result with a total number of counts of 1000 or more, ML distinguishes itself by yielding, in all cases, the same mean lifetime within 2% of the accepted value. For 200 total counts and greater, ML always provides a standard deviation of <10% of the mean lifetime, and even at 20 total counts there is only 20% error in the mean lifetime. The robustness of ML advocates its use for sparse data sets such as those acquired in some subdiffraction-limited microscopies, such as STED, and, more importantly, provides greater motivation for exploiting the time-resolved capacities of this technique to acquire and analyze fluorescence lifetime data.
6-hour maximum rain in Friuli Venezia Giulia: Climatology and ECMWF-based forecasts
Manzato, Agostino; Cicogna, Andrea; Pucillo, Arturo
2016-03-01
Friuli Venezia Giulia (FVG) is a region in Italy with very complex orography, having an annual rainfall amount that varies from about 900 mm on the coast to more than 3200 mm in the Julian Prealps. A network of 104 raingauges placed around the FVG territory was used to extract the absolute maximum rain accumulated every 6 h, during the period 16 February 2006 to 15 February 2015 (9 years). Interannual, annual, weekly and daily cycles of three classes of rain intensities are analyzed, finding that significant rainfalls (MaxRain > 5 mm) are more frequent in the May to mid-August period, while the heaviest rainfalls (> 40 mm) are more probable between May and the beginning of December, with a peak at the very beginning of November. ECMWF 6-h forecasts at 18 gridpoints (spaced at 0.25°) above the FVG region are studied for the same period, to find the maximum 6-h rain forecasted by the ECMWF model from + 6 to + 48 h and correlate it with the observed maximum rain of all the 104 raingauges. It is found that the correlation coefficient R is higher at 0000-0600 UTC and minimum at 1800-0000 UTC, while the BIAS is always negative (underestimation), varying between - 3.5 and - 6.9 mm. Looking at more homogeneous subareas, ECMWF has a much worse BIAS and RMSE for the Prealps zone, while its correlation coefficient is lower for the coastal and plains zones. For comparison, a similar exercise is repeated using a LAM model (ALADIN-ARSO), finding better BIAS and RMSE, but a lower skill for the mean correlation coefficient. Hence, a linear statistical method (multiregression with exhaustive input selection) for forecasting the maximum 6-h rain using as candidate predictors the direct model output (absolute values, anomalies, standardized values, plus mean, max and SD in time and space) is developed independently for four different sub-regions and two periods of the year starting from the ECMWF forecast. It is found that the strong BIAS in the Prealpine area can easily be removed
Modelling and Simulation of Seasonal Rainfall Using the Principle of Maximum Entropy
Jonathan Borwein
2014-02-01
Full Text Available We use the principle of maximum entropy to propose a parsimonious model for the generation of simulated rainfall during the wettest three-month season at a typical location on the east coast of Australia. The model uses a checkerboard copula of maximum entropy to model the joint probability distribution for total seasonal rainfall and a set of two-parameter gamma distributions to model each of the marginal monthly rainfall totals. The model allows us to match the grade correlation coefficients for the checkerboard copula to the observed Spearman rank correlation coefficients for the monthly rainfalls and, hence, provides a model that correctly describes the mean and variance for each of the monthly totals and also for the overall seasonal total. Thus, we avoid the need for a posteriori adjustment of simulated monthly totals in order to correctly simulate the observed seasonal statistics. Detailed results are presented for the modelling and simulation of seasonal rainfall in the town of Kempsey on the mid-north coast of New South Wales. Empirical evidence from extensive simulations is used to validate this application of the model. A similar analysis for Sydney is also described.