Attenuation of the Squared Canonical Correlation Coefficient under Varying Estimates of Score Reliability

ERIC Educational Resources Information Center

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.…

A method comparison of a food frequency questionnaire to measure folate, choline, betaine, vitamin C and carotenoids with 24-h dietary recalls in women of reproductive age.

PubMed

Coathup, V; Wheeler, S; Smith, L

2016-03-01

The objective of this study was to conduct a method comparison of a modified food frequency questionnaire (FFQ), designed to estimate usual dietary intake of selected micronutrients and antioxidants including folate, choline, betaine, vitamin C and carotenoids (α-carotene, β-carotene, lutein, lycopene and β-cryptoxanthin) with 24-h dietary recalls (24-HR) in women of reproductive age. Sixty-four British women of reproductive age (18-40 years) were recruited in Oxford, UK and provided complete dietary data for analysis. We compared micronutrient estimates from the FFQ against estimates derived from three multiple-pass, 24-HR interviews, by evaluating Pearson's correlation coefficients and Bland-Altman plots. Median intakes of most nutrients were higher when measured by FFQ compared with 24-HR. Strong correlation coefficients were observed for folate (r=0.80) and choline (r=0.68), whereas moderate correlation coefficients were observed for vitamin C (0.50) and lycopene (0.43). Weak correlation coefficients were observed for betaine (0.39) and other carotenoids (r=0.26-0.38). Bland-Altman plots indicated that there was a large amount of variability in the FFQ estimates of nutrient intakes compared to those using 24-HR, particularly for carotenoids. The findings indicate that this FFQ estimated higher mean intakes for most nutrients. Pearson's correlation coefficients were comparable with previous research; however, the Bland-Altman plots suggest a high variability in mean nutrient estimates between the FFQ and 24-h. We recommend further investigation of the validity of this FFQ before use.

Estimating a graphical intra-class correlation coefficient (GICC) using multivariate probit-linear mixed models.

PubMed

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.

Sample Size Calculation for Estimating or Testing a Nonzero Squared Multiple Correlation Coefficient

ERIC Educational Resources Information Center

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…

Estimation of Comfort/Disconfort Based on EEG in Massage by Use of Clustering according to Correration and Incremental Learning type NN

NASA Astrophysics Data System (ADS)

Teramae, Tatsuya; Kushida, Daisuke; Takemori, Fumiaki; Kitamura, Akira

Authors proposed the estimation method combining k-means algorithm and NN for evaluating massage. However, this estimation method has a problem that discrimination ratio is decreased to new user. There are two causes of this problem. One is that generalization of NN is bad. Another one is that clustering result by k-means algorithm has not high correlation coefficient in a class. Then, this research proposes k-means algorithm according to correlation coefficient and incremental learning for NN. The proposed k-means algorithm is method included evaluation function based on correlation coefficient. Incremental learning is method that NN is learned by new data and initialized weight based on the existing data. The effect of proposed methods are verified by estimation result using EEG data when testee is given massage.

Evaluation of estimation methods for organic carbon normalized sorption coefficients

USGS Publications Warehouse

Baker, James R.; Mihelcic, James R.; Luehrs, Dean C.; Hickey, James P.

1997-01-01

A critically evaluated set of 94 soil water partition coefficients normalized to soil organic carbon content (Koc) is presented for 11 classes of organic chemicals. This data set is used to develop and evaluate Koc estimation methods using three different descriptors. The three types of descriptors used in predicting Koc were octanol/water partition coefficient (Kow), molecular connectivity (mXt) and linear solvation energy relationships (LSERs). The best results were obtained estimating Koc from Kow, though a slight improvement in the correlation coefficient was obtained by using a two-parameter regression with Kow and the third order difference term from mXt. Molecular connectivity correlations seemed to be best suited for use with specific chemical classes. The LSER provided a better fit than mXt but not as good as the correlation with Koc. The correlation to predict Koc from Kow was developed for 72 chemicals; log Koc = 0.903* log Kow + 0.094. This correlation accounts for 91% of the variability in the data for chemicals with log Kow ranging from 1.7 to 7.0. The expression to determine the 95% confidence interval on the estimated Koc is provided along with an example for two chemicals of different hydrophobicity showing the confidence interval of the retardation factor determined from the estimated Koc. The data showed that Koc is not likely to be applicable for chemicals with log Kow < 1.7. Finally, the Koc correlation developed using Kow as a descriptor was compared with three nonclass-specific correlations and two 'commonly used' class-specific correlations to determine which method(s) are most suitable.

Correlation of ultrasound estimated placental volume and umbilical cord blood volume in term pregnancy.

PubMed

Pannopnut, Papinwit; Kitporntheranunt, Maethaphan; Paritakul, Panwara; Kongsomboon, Kittipong

2015-01-01

To investigate the correlation between ultrasound measured placental volume and collected umbilical cord blood (UCB) volume in term pregnancy. An observational cross-sectional study of term singleton pregnant women in the labor ward at Maha Chakri Sirindhorn Medical Center was conducted. Placental thickness, height, and width were measured using two-dimensional (2D) ultrasound and calculated for placental volume using the volumetric mathematic model. After the delivery of the baby, UCB was collected and measured for its volume immediately. Then, birth weight, placental weight, and the actual placental volume were analyzed. The Pearson's correlation was used to determine the correlation between each two variables. A total of 35 pregnant women were eligible for the study. The mean and standard deviation of estimated placental volume and actual placental volume were 534±180 mL and 575±118 mL, respectively. The median UCB volume was 140 mL (range 98-220 mL). The UCB volume did not have a statistically significant correlation with the estimated placental volume (correlation coefficient 0.15; p=0.37). However, the UCB volume was significantly correlated with the actual placental volume (correlation coefficient 0.62; p<0.001) and birth weight (correlation coefficient 0.38; p=0.02). The estimated placental volume by 2D ultrasound was not significantly correlated with the UCB volume. Further studies to establish the correlation between the UCB volume and the estimated placental volume using other types of placental imaging may be needed.

Choosing the best index for the average score intraclass correlation coefficient.

PubMed

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.

The effect of rare alleles on estimated genomic relationships from whole genome sequence data.

PubMed

Eynard, Sonia E; Windig, Jack J; Leroy, Grégoire; van Binsbergen, Rianne; Calus, Mario P L

2015-03-12

Relationships between individuals and inbreeding coefficients are commonly used for breeding decisions, but may be affected by the type of data used for their estimation. The proportion of variants with low Minor Allele Frequency (MAF) is larger in whole genome sequence (WGS) data compared to Single Nucleotide Polymorphism (SNP) chips. Therefore, WGS data provide true relationships between individuals and may influence breeding decisions and prioritisation for conservation of genetic diversity in livestock. This study identifies differences between relationships and inbreeding coefficients estimated using pedigree, SNP or WGS data for 118 Holstein bulls from the 1000 Bull genomes project. To determine the impact of rare alleles on the estimates we compared three scenarios of MAF restrictions: variants with a MAF higher than 5%, variants with a MAF higher than 1% and variants with a MAF between 1% and 5%. We observed significant differences between estimated relationships and, although less significantly, inbreeding coefficients from pedigree, SNP or WGS data, and between MAF restriction scenarios. Computed correlations between pedigree and genomic relationships, within groups with similar relationships, ranged from negative to moderate for both estimated relationships and inbreeding coefficients, but were high between estimates from SNP and WGS (0.49 to 0.99). Estimated relationships from genomic information exhibited higher variation than from pedigree. Inbreeding coefficients analysis showed that more complete pedigree records lead to higher correlation between inbreeding coefficients from pedigree and genomic data. Finally, estimates and correlations between additive genetic (A) and genomic (G) relationship matrices were lower, and variances of the relationships were larger when accounting for allele frequencies than without accounting for allele frequencies. Using pedigree data or genomic information, and including or excluding variants with a MAF below 5% showed significant differences in relationship and inbreeding coefficient estimates. Estimated relationships and inbreeding coefficients are the basis for selection decisions. Therefore, it can be expected that using WGS instead of SNP can affect selection decision. Inclusion of rare variants will give access to the variation they carry, which is of interest for conservation of genetic diversity.

A determinant-based criterion for working correlation structure selection in generalized estimating equations.

PubMed

Jaman, Ajmery; Latif, Mahbub A H M; Bari, Wasimul; Wahed, Abdus S

2016-05-20

In generalized estimating equations (GEE), the correlation between the repeated observations on a subject is specified with a working correlation matrix. Correct specification of the working correlation structure ensures efficient estimators of the regression coefficients. Among the criteria used, in practice, for selecting working correlation structure, Rotnitzky-Jewell, Quasi Information Criterion (QIC) and Correlation Information Criterion (CIC) are based on the fact that if the assumed working correlation structure is correct then the model-based (naive) and the sandwich (robust) covariance estimators of the regression coefficient estimators should be close to each other. The sandwich covariance estimator, used in defining the Rotnitzky-Jewell, QIC and CIC criteria, is biased downward and has a larger variability than the corresponding model-based covariance estimator. Motivated by this fact, a new criterion is proposed in this paper based on the bias-corrected sandwich covariance estimator for selecting an appropriate working correlation structure in GEE. A comparison of the proposed and the competing criteria is shown using simulation studies with correlated binary responses. The results revealed that the proposed criterion generally performs better than the competing criteria. An example of selecting the appropriate working correlation structure has also been shown using the data from Madras Schizophrenia Study. Copyright © 2015 John Wiley & Sons, Ltd.

p-capture reaction cycles in rotating massive stars and their impact on elemental abundances in globular cluster stars: A case study of O, Na and Al

NASA Astrophysics Data System (ADS)

Mahanta, Upakul; Goswami, Aruna; Duorah, Hiralal; Duorah, Kalpana

2017-08-01

Elemental abundance patterns of globular cluster stars can provide important clues for understanding cluster formation and early chemical evolution. The origin of the abundance patterns, however, still remains poorly understood. We have studied the impact of p-capture reaction cycles on the abundances of oxygen, sodium and aluminium considering nuclear reaction cycles of carbon-nitrogen-oxygen-fluorine, neon-sodium and magnesium-aluminium in massive stars in stellar conditions of temperature range 2×107 to 10×107 K and typical density of 102 gm cc-1. We have estimated abundances of oxygen, sodium and aluminium with respect to Fe, which are then assumed to be ejected from those stars because of rotation reaching a critical limit. These ejected abundances of elements are then compared with their counterparts that have been observed in some metal-poor evolved stars, mainly giants and red giants, of globular clusters M3, M4, M13 and NGC 6752. We observe an excellent agreement with [O/Fe] between the estimated and observed abundance values for globular clusters M3 and M4 with a correlation coefficient above 0.9 and a strong linear correlation for the remaining two clusters with a correlation coefficient above 0.7. The estimated [Na/Fe] is found to have a correlation coefficient above 0.7, thus implying a strong correlation for all four globular clusters. As far as [Al/Fe] is concerned, it also shows a strong correlation between the estimated abundance and the observed abundance for globular clusters M13 and NGC 6752, since here also the correlation coefficient is above 0.7 whereas for globular cluster M4 there is a moderate correlation found with a correlation coefficient above 0.6. Possible sources of these discrepancies are discussed.

Using beta coefficients to impute missing correlations in meta-analysis research: Reasons for caution.

PubMed

Roth, Philip L; Le, Huy; Oh, In-Sue; Van Iddekinge, Chad H; Bobko, Philip

2018-06-01

Meta-analysis has become a well-accepted method for synthesizing empirical research about a given phenomenon. Many meta-analyses focus on synthesizing correlations across primary studies, but some primary studies do not report correlations. Peterson and Brown (2005) suggested that researchers could use standardized regression weights (i.e., beta coefficients) to impute missing correlations. Indeed, their beta estimation procedures (BEPs) have been used in meta-analyses in a wide variety of fields. In this study, the authors evaluated the accuracy of BEPs in meta-analysis. We first examined how use of BEPs might affect results from a published meta-analysis. We then developed a series of Monte Carlo simulations that systematically compared the use of existing correlations (that were not missing) to data sets that incorporated BEPs (that impute missing correlations from corresponding beta coefficients). These simulations estimated ρ̄ (mean population correlation) and SDρ (true standard deviation) across a variety of meta-analytic conditions. Results from both the existing meta-analysis and the Monte Carlo simulations revealed that BEPs were associated with potentially large biases when estimating ρ̄ and even larger biases when estimating SDρ. Using only existing correlations often substantially outperformed use of BEPs and virtually never performed worse than BEPs. Overall, the authors urge a return to the standard practice of using only existing correlations in meta-analysis. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Comprehensive analysis of correlation coefficients estimated from pooling heterogeneous microarray data

PubMed Central

2013-01-01

Background The synthesis of information across microarray studies has been performed by combining statistical results of individual studies (as in a mosaic), or by combining data from multiple studies into a large pool to be analyzed as a single data set (as in a melting pot of data). Specific issues relating to data heterogeneity across microarray studies, such as differences within and between labs or differences among experimental conditions, could lead to equivocal results in a melting pot approach. Results We applied statistical theory to determine the specific effect of different means and heteroskedasticity across 19 groups of microarray data on the sign and magnitude of gene-to-gene Pearson correlation coefficients obtained from the pool of 19 groups. We quantified the biases of the pooled coefficients and compared them to the biases of correlations estimated by an effect-size model. Mean differences across the 19 groups were the main factor determining the magnitude and sign of the pooled coefficients, which showed largest values of bias as they approached ±1. Only heteroskedasticity across the pool of 19 groups resulted in less efficient estimations of correlations than did a classical meta-analysis approach of combining correlation coefficients. These results were corroborated by simulation studies involving either mean differences or heteroskedasticity across a pool of N > 2 groups. Conclusions The combination of statistical results is best suited for synthesizing the correlation between expression profiles of a gene pair across several microarray studies. PMID:23822712

Intraclass Correlation Coefficients in Hierarchical Design Studies with Discrete Response Variables: A Note on a Direct Interval Estimation Procedure

ERIC Educational Resources Information Center

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…

Estimation of instantaneous heat transfer coefficients for a direct-injection stratified-charge rotary engine

NASA Technical Reports Server (NTRS)

Lee, C. M.; Addy, H. E.; Bond, T. H.; Chun, K. S.; Lu, C. Y.

1987-01-01

The main objective of this report was to derive equations to estimate heat transfer coefficients in both the combustion chamber and coolant pasage of a rotary engine. This was accomplished by making detailed temperature and pressure measurements in a direct-injection stratified-charge rotary engine under a range of conditions. For each sppecific measurement point, the local physical properties of the fluids were calculated. Then an empirical correlation of the coefficients was derived by using a multiple regression program. This correlation expresses the Nusselt number as a function of the Prandtl number and Reynolds number.

Breast density estimation from high spectral and spatial resolution MRI

PubMed Central

Li, Hui; Weiss, William A.; Medved, Milica; Abe, Hiroyuki; Newstead, Gillian M.; Karczmar, Gregory S.; Giger, Maryellen L.

2016-01-01

Abstract. A three-dimensional breast density estimation method is presented for high spectral and spatial resolution (HiSS) MR imaging. Twenty-two patients were recruited (under an Institutional Review Board--approved Health Insurance Portability and Accountability Act-compliant protocol) for high-risk breast cancer screening. Each patient received standard-of-care clinical digital x-ray mammograms and MR scans, as well as HiSS scans. The algorithm for breast density estimation includes breast mask generating, breast skin removal, and breast percentage density calculation. The inter- and intra-user variabilities of the HiSS-based density estimation were determined using correlation analysis and limits of agreement. Correlation analysis was also performed between the HiSS-based density estimation and radiologists’ breast imaging-reporting and data system (BI-RADS) density ratings. A correlation coefficient of 0.91 (p<0.0001) was obtained between left and right breast density estimations. An interclass correlation coefficient of 0.99 (p<0.0001) indicated high reliability for the inter-user variability of the HiSS-based breast density estimations. A moderate correlation coefficient of 0.55 (p=0.0076) was observed between HiSS-based breast density estimations and radiologists’ BI-RADS. In summary, an objective density estimation method using HiSS spectral data from breast MRI was developed. The high reproducibility with low inter- and low intra-user variabilities shown in this preliminary study suggest that such a HiSS-based density metric may be potentially beneficial in programs requiring breast density such as in breast cancer risk assessment and monitoring effects of therapy. PMID:28042590

Reducing Bias and Error in the Correlation Coefficient Due to Nonnormality

ERIC Educational Resources Information Center

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…

Catching ghosts with a coarse net: use and abuse of spatial sampling data in detecting synchronization

PubMed Central

2017-01-01

Synchronization of population dynamics in different habitats is a frequently observed phenomenon. A common mathematical tool to reveal synchronization is the (cross)correlation coefficient between time courses of values of the population size of a given species where the population size is evaluated from spatial sampling data. The corresponding sampling net or grid is often coarse, i.e. it does not resolve all details of the spatial configuration, and the evaluation error—i.e. the difference between the true value of the population size and its estimated value—can be considerable. We show that this estimation error can make the value of the correlation coefficient very inaccurate or even irrelevant. We consider several population models to show that the value of the correlation coefficient calculated on a coarse sampling grid rarely exceeds 0.5, even if the true value is close to 1, so that the synchronization is effectively lost. We also observe ‘ghost synchronization’ when the correlation coefficient calculated on a coarse sampling grid is close to 1 but in reality the dynamics are not correlated. Finally, we suggest a simple test to check the sampling grid coarseness and hence to distinguish between the true and artifactual values of the correlation coefficient. PMID:28202589

Correlation Between the Field Line and Particle Diffusion Coefficients in the Stochastic Fields of a Tokamak

NASA Astrophysics Data System (ADS)

Calvin, Mark; Punjabi, Alkesh

1996-11-01

We use the method of quasi-magnetic surfaces to calculate the correlation between the field line and particle diffusion coefficients. The magnetic topology of a tokamak is perturbed by a spectrum of neighboring resonant resistive modes. The Hamiltonian equations of motion for the field line are integrated numerically. Poincare plots of the quasi-magnetic surfaces are generated initially and after the field line has traversed a considerable distance. From the areas of the quasi-magnetic surfaces and the field line distance, we estimate the field line diffusion coefficient. We start plasma particles on the initial quasi-surface, and calculate the particle diffusion coefficient from our Monte Carlo method (Punjabi A., Boozer A., Lam M., Kim H. and Burke K., J. Plasma Phys.), 44, 405 (1990). We then estimate the correlation between the particle and field diffusion as the strength of the resistive modes is varied.

Investigation of two-phase heat transfer coefficients of argon-freon cryogenic mixed refrigerants

NASA Astrophysics Data System (ADS)

Baek, Seungwhan; Lee, Cheonkyu; Jeong, Sangkwon

2014-11-01

Mixed refrigerant Joule Thomson refrigerators are widely used in various kinds of cryogenic systems these days. Although heat transfer coefficient estimation for a multi-phase and multi-component fluid in the cryogenic temperature range is necessarily required in the heat exchanger design of mixed refrigerant Joule Thomson refrigerators, it has been rarely discussed so far. In this paper, condensation and evaporation heat transfer coefficients of argon-freon mixed refrigerant are measured in a microchannel heat exchanger. A Printed Circuit Heat Exchanger (PCHE) with 340 μm hydraulic diameter has been developed as a compact microchannel heat exchanger and utilized in the experiment. Several two-phase heat transfer coefficient correlations are examined to discuss the experimental measurement results. The result of this paper shows that cryogenic two-phase mixed refrigerant heat transfer coefficients can be estimated by conventional two-phase heat transfer coefficient correlations.

Semimajor Axis Estimation Strategies

NASA Technical Reports Server (NTRS)

How, Jonathan P.; Alfriend, Kyle T.; Breger, Louis; Mitchell, Megan

2004-01-01

This paper extends previous analysis on the impact of sensing noise for the navigation and control aspects of formation flying spacecraft. We analyze the use of Carrier-phase Differential GPS (CDGPS) in relative navigation filters, with a particular focus on the filter correlation coefficient. This work was motivated by previous publications which suggested that a "good" navigation filter would have a strong correlation (i.e., coefficient near -1) to reduce the semimajor axis (SMA) error, and therefore, the overall fuel use. However, practical experience with CDGPS-based filters has shown this strong correlation seldom occurs (typical correlations approx. -0.1), even when the estimation accuracies are very good. We derive an analytic estimate of the filter correlation coefficient and demonstrate that, for the process and sensor noises levels expected with CDGPS, the expected value will be very low. It is also demonstrated that this correlation can be improved by increasing the time step of the discrete Kalman filter, but since the balance condition is not satisfied, the SMA error also increases. These observations are verified with several linear simulations. The combination of these simulations and analysis provide new insights on the crucial role of the process noise in determining the semimajor axis knowledge.

Body Adiposity Index Performance in Estimating Body Fat Percentage in Colombian College Students: Findings from the FUPRECOL-Adults Study.

PubMed

Ramírez-Vélez, Robinson; Correa-Bautista, Jorge Enrique; González-Ruíz, Katherine; Vivas, Andrés; Triana-Reina, Héctor Reynaldo; Martínez-Torres, Javier; Prieto-Benavides, Daniel Humberto; Carrillo, Hugo Alejandro; Ramos-Sepúlveda, Jeison Alexander; Villa-González, Emilio; García-Hermoso, Antonio

2017-01-17

Recently, a body adiposity index (BAI = (hip circumference)/((height)(1.5)) -18 ) was developed and validated in adult populations. The aim of this study was to evaluate the performance of BAI in estimating percentage body fat (BF%) in a sample of Colombian collegiate young adults. The participants were comprised of 903 volunteers (52% females, mean age = 21.4 years ± 3.3). We used the Lin's concordance correlation coefficient, linear regression, Bland-Altman's agreement analysis, concordance correlation coefficient ( ρc ) and the coefficient of determination ( R ²) between BAI, and BF%; by bioelectrical impedance analysis (BIA)). The correlation between the two methods of estimating BF% was R ² = 0.384, p < 0.001. A paired-sample t -test showed a difference between the methods (BIA BF% = 16.2 ± 3.1, BAI BF% = 30.0 ± 5.4%; p < 0.001). For BIA, bias value was 6.0 ± 6.2 BF% (95% confidence interval (CI) = -6.0 to 18.2), indicating that the BAI method overestimated BF% relative to the reference method. Lin's concordance correlation coefficient was poor ( ρc = 0.014, 95% CI = -0.124 to 0.135; p = 0.414). In Colombian college students, there was poor agreement between BAI- and BIA-based estimates of BF%, and so BAI is not accurate in people with low or high body fat percentage levels.

Sherwood correlation for dissolution of pooled NAPL in porous media

NASA Astrophysics Data System (ADS)

Aydin Sarikurt, Derya; Gokdemir, Cagri; Copty, Nadim K.

2017-11-01

The rate of interphase mass transfer from non-aqueous phase liquids (NAPLs) entrapped in the subsurface into the surrounding mobile aqueous phase is commonly expressed in terms of Sherwood (Sh) correlations that are expressed as a function of flow and porous media properties. Because of the lack of precise methods for the estimation of the interfacial area separating the NAPL and aqueous phases, most studies have opted to use modified Sherwood expressions that lump the interfacial area into the interphase mass transfer coefficient. To date, there are only two studies in the literature that have developed non-lumped Sherwood correlations; however, these correlations have undergone limited validation. In this paper controlled dissolution experiments from pooled NAPL were conducted. The immobile NAPL mass is placed at the bottom of a flow cell filled with porous media with water flowing horizontally on top. Effluent aqueous phase concentrations were measured for a wide range of aqueous phase velocities and for two different porous media. To interpret the experimental results, a two-dimensional pore network model of the NAPL dissolution kinetics and aqueous phase transport was developed. The observed effluent concentrations were then used to compute best-fit mass transfer coefficients. Comparison of the effluent concentrations computed with the two-dimensional pore network model to those estimated with one-dimensional analytical solutions indicates that the analytical model which ignores the transport in the lateral direction can lead to under-estimation of the mass transfer coefficient. Based on system parameters and the estimated mass transfer coefficients, non-lumped Sherwood correlations were developed and compared to previously published data. The developed correlations, which are a significant improvement over currently available correlations that are associated with large uncertainties, can be incorporated into future modeling studies requiring non-lumped Sh expressions.

Prediction of mass transfer coefficient in rotating bed contactor (Higee) using artificial neural network

NASA Astrophysics Data System (ADS)

Saha, Dipendu

2009-02-01

The feasibility of drastically reducing the contactor size in mass transfer processes utilizing centrifugal field has generated a lot of interest in rotating packed bed (Higee). Various investigators have proposed correlations to predict mass transfer coefficients in Higee, but, none of the correlations was more than 20-30% accurate. In this work, artificial neural network (ANN) is employed for predicting mass transfer coefficient data. Results show that ANN provides better estimation of mass transfer coefficient with accuracy 5-15%.

Solvation free energies and partition coefficients with the coarse-grained and hybrid all-atom/coarse-grained MARTINI models.

PubMed

Genheden, Samuel

2017-10-01

We present the estimation of solvation free energies of small solutes in water, n-octanol and hexane using molecular dynamics simulations with two MARTINI models at different resolutions, viz. the coarse-grained (CG) and the hybrid all-atom/coarse-grained (AA/CG) models. From these estimates, we also calculate the water/hexane and water/octanol partition coefficients. More than 150 small, organic molecules were selected from the Minnesota solvation database and parameterized in a semi-automatic fashion. Using either the CG or hybrid AA/CG models, we find considerable deviations between the estimated and experimental solvation free energies in all solvents with mean absolute deviations larger than 10 kJ/mol, although the correlation coefficient is between 0.55 and 0.75 and significant. There is also no difference between the results when using the non-polarizable and polarizable water model, although we identify some improvements when using the polarizable model with the AA/CG solutes. In contrast to the estimated solvation energies, the estimated partition coefficients are generally excellent with both the CG and hybrid AA/CG models, giving mean absolute deviations between 0.67 and 0.90 log units and correlation coefficients larger than 0.85. We analyze the error distribution further and suggest avenues for improvements.

Solvation free energies and partition coefficients with the coarse-grained and hybrid all-atom/coarse-grained MARTINI models

NASA Astrophysics Data System (ADS)

Genheden, Samuel

2017-10-01

We present the estimation of solvation free energies of small solutes in water, n-octanol and hexane using molecular dynamics simulations with two MARTINI models at different resolutions, viz. the coarse-grained (CG) and the hybrid all-atom/coarse-grained (AA/CG) models. From these estimates, we also calculate the water/hexane and water/octanol partition coefficients. More than 150 small, organic molecules were selected from the Minnesota solvation database and parameterized in a semi-automatic fashion. Using either the CG or hybrid AA/CG models, we find considerable deviations between the estimated and experimental solvation free energies in all solvents with mean absolute deviations larger than 10 kJ/mol, although the correlation coefficient is between 0.55 and 0.75 and significant. There is also no difference between the results when using the non-polarizable and polarizable water model, although we identify some improvements when using the polarizable model with the AA/CG solutes. In contrast to the estimated solvation energies, the estimated partition coefficients are generally excellent with both the CG and hybrid AA/CG models, giving mean absolute deviations between 0.67 and 0.90 log units and correlation coefficients larger than 0.85. We analyze the error distribution further and suggest avenues for improvements.

The Covariance Adjustment Approaches for Combining Incomparable Cox Regressions Caused by Unbalanced Covariates Adjustment: A Multivariate Meta-Analysis Study.

PubMed

Dehesh, Tania; Zare, Najaf; Ayatollahi, Seyyed Mohammad Taghi

2015-01-01

Univariate meta-analysis (UM) procedure, as a technique that provides a single overall result, has become increasingly popular. Neglecting the existence of other concomitant covariates in the models leads to loss of treatment efficiency. Our aim was proposing four new approximation approaches for the covariance matrix of the coefficients, which is not readily available for the multivariate generalized least square (MGLS) method as a multivariate meta-analysis approach. We evaluated the efficiency of four new approaches including zero correlation (ZC), common correlation (CC), estimated correlation (EC), and multivariate multilevel correlation (MMC) on the estimation bias, mean square error (MSE), and 95% probability coverage of the confidence interval (CI) in the synthesis of Cox proportional hazard models coefficients in a simulation study. Comparing the results of the simulation study on the MSE, bias, and CI of the estimated coefficients indicated that MMC approach was the most accurate procedure compared to EC, CC, and ZC procedures. The precision ranking of the four approaches according to all above settings was MMC ≥ EC ≥ CC ≥ ZC. This study highlights advantages of MGLS meta-analysis on UM approach. The results suggested the use of MMC procedure to overcome the lack of information for having a complete covariance matrix of the coefficients.

Distance correlation methods for discovering associations in large astrophysical databases

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

Martínez-Gómez, Elizabeth; Richards, Mercedes T.; Richards, Donald St. P., E-mail: elizabeth.martinez@itam.mx, E-mail: mrichards@astro.psu.edu, E-mail: richards@stat.psu.edu

2014-01-20

High-dimensional, large-sample astrophysical databases of galaxy clusters, such as the Chandra Deep Field South COMBO-17 database, provide measurements on many variables for thousands of galaxies and a range of redshifts. Current understanding of galaxy formation and evolution rests sensitively on relationships between different astrophysical variables; hence an ability to detect and verify associations or correlations between variables is important in astrophysical research. In this paper, we apply a recently defined statistical measure called the distance correlation coefficient, which can be used to identify new associations and correlations between astrophysical variables. The distance correlation coefficient applies to variables of any dimension,more » can be used to determine smaller sets of variables that provide equivalent astrophysical information, is zero only when variables are independent, and is capable of detecting nonlinear associations that are undetectable by the classical Pearson correlation coefficient. Hence, the distance correlation coefficient provides more information than the Pearson coefficient. We analyze numerous pairs of variables in the COMBO-17 database with the distance correlation method and with the maximal information coefficient. We show that the Pearson coefficient can be estimated with higher accuracy from the corresponding distance correlation coefficient than from the maximal information coefficient. For given values of the Pearson coefficient, the distance correlation method has a greater ability than the maximal information coefficient to resolve astrophysical data into highly concentrated horseshoe- or V-shapes, which enhances classification and pattern identification. These results are observed over a range of redshifts beyond the local universe and for galaxies from elliptical to spiral.« less

Comparison of Different Shrinkage Formulas in Estimating Population Multiple Correlation Coefficients.

ERIC Educational Resources Information Center

Carter, David S.

1979-01-01

There are a variety of formulas for reducing the positive bias which occurs in estimating R squared in multiple regression or correlation equations. Five different formulas are evaluated in a Monte Carlo study, and recommendations are made. (JKS)

Intraclass Correlation Coefficients in Hierarchical Designs: Evaluation Using Latent Variable Modeling

ERIC Educational Resources Information Center

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…

Body Adiposity Index Performance in Estimating Body Fat Percentage in Colombian College Students: Findings from the FUPRECOL—Adults Study

PubMed Central

Ramírez-Vélez, Robinson; Correa-Bautista, Jorge Enrique; González-Ruíz, Katherine; Vivas, Andrés; Triana-Reina, Héctor Reynaldo; Martínez-Torres, Javier; Prieto-Benavides, Daniel Humberto; Carrillo, Hugo Alejandro; Ramos-Sepúlveda, Jeison Alexander; Villa-González, Emilio; García-Hermoso, Antonio

2017-01-01

Recently, a body adiposity index (BAI = (hip circumference)/((height)(1.5))−18) was developed and validated in adult populations. The aim of this study was to evaluate the performance of BAI in estimating percentage body fat (BF%) in a sample of Colombian collegiate young adults. The participants were comprised of 903 volunteers (52% females, mean age = 21.4 years ± 3.3). We used the Lin’s concordance correlation coefficient, linear regression, Bland–Altman’s agreement analysis, concordance correlation coefficient (ρc) and the coefficient of determination (R2) between BAI, and BF%; by bioelectrical impedance analysis (BIA)). The correlation between the two methods of estimating BF% was R2 = 0.384, p < 0.001. A paired-sample t-test showed a difference between the methods (BIA BF% = 16.2 ± 3.1, BAI BF% = 30.0 ± 5.4%; p < 0.001). For BIA, bias value was 6.0 ± 6.2 BF% (95% confidence interval (CI) = −6.0 to 18.2), indicating that the BAI method overestimated BF% relative to the reference method. Lin’s concordance correlation coefficient was poor (ρc = 0.014, 95% CI = −0.124 to 0.135; p = 0.414). In Colombian college students, there was poor agreement between BAI- and BIA-based estimates of BF%, and so BAI is not accurate in people with low or high body fat percentage levels. PMID:28106719

Implementations of geographically weighted lasso in spatial data with multicollinearity (Case study: Poverty modeling of Java Island)

NASA Astrophysics Data System (ADS)

Setiyorini, Anis; Suprijadi, Jadi; Handoko, Budhi

2017-03-01

Geographically Weighted Regression (GWR) is a regression model that takes into account the spatial heterogeneity effect. In the application of the GWR, inference on regression coefficients is often of interest, as is estimation and prediction of the response variable. Empirical research and studies have demonstrated that local correlation between explanatory variables can lead to estimated regression coefficients in GWR that are strongly correlated, a condition named multicollinearity. It later results on a large standard error on estimated regression coefficients, and, hence, problematic for inference on relationships between variables. Geographically Weighted Lasso (GWL) is a method which capable to deal with spatial heterogeneity and local multicollinearity in spatial data sets. GWL is a further development of GWR method, which adds a LASSO (Least Absolute Shrinkage and Selection Operator) constraint in parameter estimation. In this study, GWL will be applied by using fixed exponential kernel weights matrix to establish a poverty modeling of Java Island, Indonesia. The results of applying the GWL to poverty datasets show that this method stabilizes regression coefficients in the presence of multicollinearity and produces lower prediction and estimation error of the response variable than GWR does.

Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient.

PubMed

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 correlation coefficient and the SD-weighted correlation coefficient, and is particularly useful for clustering replicated microarray data. This computational approach should be generally useful for proteomic data or other high-throughput analysis methodology.

Clustering Coefficients for Correlation Networks.

PubMed

Masuda, Naoki; Sakaki, Michiko; Ezaki, Takahiro; Watanabe, Takamitsu

2018-01-01

Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other) measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node) are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients were strongly correlated with and therefore may be confounded by the node's connectivity. The proposed methods are expected to help us to understand clustering and lack thereof in correlational brain networks, such as those derived from functional time series and across-participant correlation in neuroanatomical properties.

Clustering Coefficients for Correlation Networks

PubMed Central

Masuda, Naoki; Sakaki, Michiko; Ezaki, Takahiro; Watanabe, Takamitsu

2018-01-01

Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other) measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node) are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients were strongly correlated with and therefore may be confounded by the node's connectivity. The proposed methods are expected to help us to understand clustering and lack thereof in correlational brain networks, such as those derived from functional time series and across-participant correlation in neuroanatomical properties. PMID:29599714

Dietary intakes assessed by 24-h recalls in peri-urban African adolescents: validity of energy intake compared with estimated energy expenditure.

PubMed

Rankin, D; Ellis, S M; Macintyre, U E; Hanekom, S M; Wright, H H

2011-08-01

The objective of this study is to determine the relative validity of reported energy intake (EI) derived from multiple 24-h recalls against estimated energy expenditure (EE(est)). Basal metabolic rate (BMR) equations and physical activity factors were incorporated to calculate EE(est). This analysis was nested in the multidisciplinary PhysicaL Activity in the Young study with a prospective study design. Peri-urban black South African adolescents were investigated in a subsample of 131 learners (87 girls and 44 boys) from the parent study sample of 369 (211 girls and 158 boys) who had all measurements taken. Pearson correlation coefficients and Bland-Altman plots were calculated to identify the most accurate published equations to estimate BMR (P<0.05 statistically significant). EE(est) was estimated using BMR equations and estimated physical activity factors derived from Previous Day Physical Activity Recall questionnaires. After calculation of EE(est), the relative validity of reported energy intake (EI(rep)) derived from multiple 24-h recalls was tested for three data subsets using Pearson correlation coefficients. Goldberg's formula identified cut points (CPs) for under and over reporting of EI. Pearson correlation coefficients between calculated BMRs ranged from 0.97 to 0.99. Bland-Altman analyses showed acceptable agreement (two equations for each gender). One equation for each gender was used to calculate EE(est). Pearson correlation coefficients between EI(rep) and EE(est) for three data sets were weak, indicating poor agreement. CPs for physical activity groups showed under reporting in 87% boys and 95% girls. The 24-h recalls measured at five measurements over 2 years offered poor validity between EI(rep) and EE(est).

Linear unmixing of multidate hyperspectral imagery for crop yield estimation

USDA-ARS?s Scientific Manuscript database

In this paper, we have evaluated an unsupervised unmixing approach, vertex component analysis (VCA), for the application of crop yield estimation. The results show that abundance maps of the vegetation extracted by the approach are strongly correlated to the yield data (the correlation coefficients ...

Estimation of Rotary Stability Derivatives at Subsonic and Transonic Speeds

NASA Technical Reports Server (NTRS)

Tobak, Murray; Lessing, Henry C.

1961-01-01

The first part of this paper pertains to the estimation of subsonic rotary stability derivatives of wings. The unsteady potential flow problem is solved by a superposition of steady flow solutions. Numerical results for the damping coefficients of triangular wings are presented as functions of aspect ratio and Mach number, and are compared with experimental results over the Mach number range 0 to 1. In the second part, experimental results are used. to point out a close correlation between the nonlinear variations with angle of attack of the static pitching-moment curve slope and the damping-in-pitch coefficient. The underlying basis for the correlation is found as a result of an analysis in which the indicial function concept and. the principle of super-position are adapted to apply to the nonlinear problem. The form of the result suggests a method of estimating nonlinear damping coefficients from results of static wind-tunnel measurements.

Anisotropic diffusion of fluorescently labeled ATP in rat cardiomyocytes determined by raster image correlation spectroscopy

PubMed Central

Vendelin, Marko; Birkedal, Rikke

2008-01-01

A series of experimental data points to the existence of profound diffusion restrictions of ADP/ATP in rat cardiomyocytes. This assumption is required to explain the measurements of kinetics of respiration, sarcoplasmic reticulum loading with calcium, and kinetics of ATP-sensitive potassium channels. To be able to analyze and estimate the role of intracellular diffusion restrictions on bioenergetics, the intracellular diffusion coefficients of metabolites have to be determined. The aim of this work was to develop a practical method for determining diffusion coefficients in anisotropic medium and to estimate the overall diffusion coefficients of fluorescently labeled ATP in rat cardiomyocytes. For that, we have extended raster image correlation spectroscopy (RICS) protocols to be able to discriminate the anisotropy in the diffusion coefficient tensor. Using this extended protocol, we estimated diffusion coefficients of ATP labeled with the fluorescent conjugate Alexa Fluor 647 (Alexa-ATP). In the analysis, we assumed that the diffusion tensor can be described by two values: diffusion coefficient along the myofibril and that across it. The average diffusion coefficients found for Alexa-ATP were as follows: 83 ± 14 μm2/s in the longitudinal and 52 ± 16 μm2/s in the transverse directions (n = 8, mean ± SD). Those values are ∼2 (longitudinal) and ∼3.5 (transverse) times smaller than the diffusion coefficient value estimated for the surrounding solution. Such uneven reduction of average diffusion coefficient leads to anisotropic diffusion in rat cardiomyocytes. Although the source for such anisotropy is uncertain, we speculate that it may be induced by the ordered pattern of intracellular structures in rat cardiomyocytes. PMID:18815224

[Estimation of organic matter content of north fluvo-aquic soil based on the coupling model of wavelet transform and partial least squares].

PubMed

Wang, Yan-Cang; Yang, Gui-Jun; Zhu, Jin-Shan; Gu, Xiao-He; Xu, Peng; Liao, Qin-Hong

2014-07-01

For improving the estimation accuracy of soil organic matter content of the north fluvo-aquic soil, wavelet transform technology is introduced. The soil samples were collected from Tongzhou district and Shunyi district in Beijing city. And the data source is from soil hyperspectral data obtained under laboratory condition. First, discrete wavelet transform efficiently decomposes hyperspectral into approximate coefficients and detail coefficients. Then, the correlation between approximate coefficients, detail coefficients and organic matter content was analyzed, and the sensitive bands of the organic matter were screened. Finally, models were established to estimate the soil organic content by using the partial least squares regression (PLSR). Results show that the NIR bands made more contributions than the visible band in estimating organic matter content models; the ability of approximate coefficients to estimate organic matter content is better than that of detail coefficients; The estimation precision of the detail coefficients fir soil organic matter content decreases with the spectral resolution being lower; Compared with the commonly used three types of soil spectral reflectance transforms, the wavelet transform can improve the estimation ability of soil spectral fir organic content; The accuracy of the best model established by the approximate coefficients or detail coefficients is higher, and the coefficient of determination (R2) and the root mean square error (RMSE) of the best model for approximate coefficients are 0.722 and 0.221, respectively. The R2 and RMSE of the best model for detail coefficients are 0.670 and 0.255, respectively.

Evaluation of the influence of the definition of an isolated hip fracture as an exclusion criterion for trauma system benchmarking: a multicenter cohort study.

PubMed

Tiao, J; Moore, L; Porgo, T V; Belcaid, A

2016-06-01

To assess whether the definition of an IHF used as an exclusion criterion influences the results of trauma center benchmarking. We conducted a multicenter retrospective cohort study with data from an integrated Canadian trauma system. The study population included all patients admitted between 1999 and 2010 to any of the 57 adult trauma centers. Seven definitions of IHF based on diagnostic codes, age, mechanism of injury, and secondary injuries, identified in a systematic review, were used. Trauma centers were benchmarked using risk-adjusted mortality estimates generated using the Trauma Risk Adjustment Model. The agreement between benchmarking results generated under different IHF definitions was evaluated with correlation coefficients on adjusted mortality estimates. Correlation coefficients >0.95 were considered to convey acceptable agreement. The study population consisted of 172,872 patients before exclusion of IHF and between 128,094 and 139,588 patients after exclusion. Correlation coefficients between risk-adjusted mortality estimates generated in populations including and excluding IHF varied between 0.86 and 0.90. Correlation coefficients of estimates generated under different definitions of IHF varied between 0.97 and 0.99, even when analyses were restricted to patients aged ≥65 years. Although the exclusion of patients with IHF has an influence on the results of trauma center benchmarking based on mortality, the definition of IHF in terms of diagnostic codes, age, mechanism of injury and secondary injury has no significant impact on benchmarking results. Results suggest that there is no need to obtain formal consensus on the definition of IHF for benchmarking activities.

An eight-legged tactile sensor to estimate coefficient of static friction.

PubMed

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.

Investigating bias in squared regression structure coefficients

PubMed Central

Nimon, Kim F.; Zientek, Linda R.; Thompson, Bruce

2015-01-01

The importance of structure coefficients and analogs of regression weights for analysis within the general linear model (GLM) has been well-documented. The purpose of this study was to investigate bias in squared structure coefficients in the context of multiple regression and to determine if a formula that had been shown to correct for bias in squared Pearson correlation coefficients and coefficients of determination could be used to correct for bias in squared regression structure coefficients. Using data from a Monte Carlo simulation, this study found that squared regression structure coefficients corrected with Pratt's formula produced less biased estimates and might be more accurate and stable estimates of population squared regression structure coefficients than estimates with no such corrections. While our findings are in line with prior literature that identified multicollinearity as a predictor of bias in squared regression structure coefficients but not coefficients of determination, the findings from this study are unique in that the level of predictive power, number of predictors, and sample size were also observed to contribute bias in squared regression structure coefficients. PMID:26217273

Research and Development of Methods for Estimating Physicochemical Properties of Organic Compounds of Environmental Concern

DTIC Science & Technology

1979-02-01

coefficient (at equilibrium) when hysteresis is apparent. 6. Coefficient n in Freundlich equation for 1/n soil or sediment adsorption isotherms ýX - KC . 7...Biodegradation Chemical structures cal clasaes (e.g., Diffusion Correlations phenols). General Diffusion coefficients Equations terms for organic...OF THE FATE AND TRANSPORT OF ORGANIC CHEMICALS Adsorption coefficients: K, n* from Freundlich equation + Desorption coefficients: K’*, n’* from

GGOS and the EOP - the key role of SLR for a stable estimation of highly accurate Earth orientation parameters

NASA Astrophysics Data System (ADS)

Bloßfeld, Mathis; Panzetta, Francesca; Müller, Horst; Gerstl, Michael

2016-04-01

The GGOS vision is to integrate geometric and gravimetric observation techniques to estimate consistent geodetic-geophysical parameters. In order to reach this goal, the common estimation of station coordinates, Stokes coefficients and Earth Orientation Parameters (EOP) is necessary. Satellite Laser Ranging (SLR) provides the ability to study correlations between the different parameter groups since the observed satellite orbit dynamics are sensitive to the above mentioned geodetic parameters. To decrease the correlations, SLR observations to multiple satellites have to be combined. In this paper, we compare the estimated EOP of (i) single satellite SLR solutions and (ii) multi-satellite SLR solutions. Therefore, we jointly estimate station coordinates, EOP, Stokes coefficients and orbit parameters using different satellite constellations. A special focus in this investigation is put on the de-correlation of different geodetic parameter groups due to the combination of SLR observations. Besides SLR observations to spherical satellites (commonly used), we discuss the impact of SLR observations to non-spherical satellites such as, e.g., the JASON-2 satellite. The goal of this study is to discuss the existing parameter interactions and to present a strategy how to obtain reliable estimates of station coordinates, EOP, orbit parameter and Stokes coefficients in one common adjustment. Thereby, the benefits of a multi-satellite SLR solution are evaluated.

Identifying Bearing Rotodynamic Coefficients Using an Extended Kalman Filter

NASA Technical Reports Server (NTRS)

Miller, Brad A.; Howard, Samuel A.

2008-01-01

An Extended Kalman Filter is developed to estimate the linearized direct and indirect stiffness and damping force coefficients for bearings in rotor dynamic applications from noisy measurements of the shaft displacement in response to imbalance and impact excitation. The bearing properties are modeled as stochastic random variables using a Gauss-Markov model. Noise terms are introduced into the system model to account for all of the estimation error, including modeling errors and uncertainties and the propagation of measurement errors into the parameter estimates. The system model contains two user-defined parameters that can be tuned to improve the filter's performance; these parameters correspond to the covariance of the system and measurement noise variables. The filter is also strongly influenced by the initial values of the states and the error covariance matrix. The filter is demonstrated using numerically simulated data for a rotor bearing system with two identical bearings, which reduces the number of unknown linear dynamic coefficients to eight. The filter estimates for the direct damping coefficients and all four stiffness coefficients correlated well with actual values, whereas the estimates for the cross-coupled damping coefficients were the least accurate.

Estimating the Diffusion Coefficients of Sugars Using Diffusion Experiments in Agar-Gel and Computer Simulations.

PubMed

Miyamoto, Shuichi; Atsuyama, Kenji; Ekino, Keisuke; Shin, Takashi

2018-01-01

The isolation of useful microbes is one of the traditional approaches for the lead generation in drug discovery. As an effective technique for microbe isolation, we recently developed a multidimensional diffusion-based gradient culture system of microbes. In order to enhance the utility of the system, it is favorable to have diffusion coefficients of nutrients such as sugars in the culture medium beforehand. We have, therefore, built a simple and convenient experimental system that uses agar-gel to observe diffusion. Next, we performed computer simulations-based on random-walk concepts-of the experimental diffusion system and derived correlation formulas that relate observable diffusion data to diffusion coefficients. Finally, we applied these correlation formulas to our experimentally-determined diffusion data to estimate the diffusion coefficients of sugars. Our values for these coefficients agree reasonably well with values published in the literature. The effectiveness of our simple technique, which has elucidated the diffusion coefficients of some molecules which are rarely reported (e.g., galactose, trehalose, and glycerol) is demonstrated by the strong correspondence between the literature values and those obtained in our experiments.

Modification of the Sandwich Estimator in Generalized Estimating Equations with Correlated Binary Outcomes in Rare Event and Small Sample Settings

PubMed Central

Rogers, Paul; Stoner, Julie

2016-01-01

Regression models for correlated binary outcomes are commonly fit using a Generalized Estimating Equations (GEE) methodology. GEE uses the Liang and Zeger sandwich estimator to produce unbiased standard error estimators for regression coefficients in large sample settings even when the covariance structure is misspecified. The sandwich estimator performs optimally in balanced designs when the number of participants is large, and there are few repeated measurements. The sandwich estimator is not without drawbacks; its asymptotic properties do not hold in small sample settings. In these situations, the sandwich estimator is biased downwards, underestimating the variances. In this project, a modified form for the sandwich estimator is proposed to correct this deficiency. The performance of this new sandwich estimator is compared to the traditional Liang and Zeger estimator as well as alternative forms proposed by Morel, Pan and Mancl and DeRouen. The performance of each estimator was assessed with 95% coverage probabilities for the regression coefficient estimators using simulated data under various combinations of sample sizes and outcome prevalence values with an Independence (IND), Autoregressive (AR) and Compound Symmetry (CS) correlation structure. This research is motivated by investigations involving rare-event outcomes in aviation data. PMID:26998504

Assessing assay agreement estimation for multiple left-censored data: a multiple imputation approach.

PubMed

Lapidus, Nathanael; Chevret, Sylvie; Resche-Rigon, Matthieu

2014-12-30

Agreement between two assays is usually based on the concordance correlation coefficient (CCC), estimated from the means, standard deviations, and correlation coefficient of these assays. However, such data will often suffer from left-censoring because of lower limits of detection of these assays. To handle such data, we propose to extend a multiple imputation approach by chained equations (MICE) developed in a close setting of one left-censored assay. The performance of this two-step approach is compared with that of a previously published maximum likelihood estimation through a simulation study. Results show close estimates of the CCC by both methods, although the coverage is improved by our MICE proposal. An application to cytomegalovirus quantification data is provided. Copyright © 2014 John Wiley & Sons, Ltd.

Estimation of soil organic partition coefficients: from retention factors measured by soil column chromatography with water as eluent.

PubMed

Xu, Feng; Liang, Xinmiao; Lin, Bingcheng; Schramm, Karl-Werner; Kettrup, Antonius

2002-08-30

The retention factors (k) of 104 hydrophobic organic chemicals (HOCs) were measured in soil column chromatography (SCC) over columns filled with three naturally occurring reference soils and eluted with Milli-Q water. A novel method for the estimation of soil organic partition coefficient (Koc) was developed based on correlations with k in soil/water systems. Strong log Koc versus log k correlations (r>0.96) were found. The estimated Koc values were in accordance with the literature values with a maximum deviation of less than 0.4 log units. All estimated Koc values from three soils were consistent with each other. The SCC approach is promising for fast screening of a large number of chemicals in their environmental applications.

[Validating the Spanish version of the Nursing Activities Score].

PubMed

Sánchez-Sánchez, M M; Arias-Rivera, S; Fraile-Gamo, M P; Thuissard-Vasallo, I J; Frutos-Vivar, F

2015-01-01

Validating workload scores ensures that they are appropriate for the purpose for which they were developed. To validate the Nursing Activities Score (NAS) Spanish version. Observational and prospective study. 1,045 patients who were admitted to a medical-surgical unit and a serious burns unit in 2006 were included. The nurse in charge assessed patient workloads by Nine Equivalent of Nursing Manpower use Score and NAS. To assess the internal consistency of the measurements of NAS, item-test correlations, Cronbach's α and Cronbach's α corrected by omitting each of the items were calculated. The intraobserver and interobserver reliability were assessed with the intraclass correlation coefficient by viewing recordings and Kappa (interobserver reliability) was estimated. For the analysis of internal validity, a factorial principal components analysis was performed. Convergent validity was assessed using the Spearman correlation coefficient values obtained from the Nine Equivalent of Nursing Manpower use Score and Spanish-NAS scales. For internal consistency, 164 questionnaires were analysed and a Cronbach's α of 0.373 was calculated. The intraclass correlation coefficient for intraobserver reliability estimate was 0.837 (95% IC: 0.466-0.950) and 0.662 (95% IC: 0.033-0.882) for interobserver reliability. The estimated kappa was 0.371. For internal validity, exploratory factor analysis showed that the first item explained 58.9% of the variance of the questionnaire. For convergent validity 1006 questionnaires were included and a Spearman correlation coefficient of 0.746 was observed. The psychometric properties of Spanish-NAS are acceptable. Copyright © 2014 Elsevier España, S.L.U. y SEEIUC. All rights reserved.

Basal measures of insulin sensitivity and insulin secretion and simplified glucose tolerance tests in dogs.

PubMed

Verkest, K R; Fleeman, L M; Rand, J S; Morton, J M

2010-10-01

There is need for simple, inexpensive measures of glucose tolerance, insulin sensitivity, and insulin secretion in dogs. The aim of this study was to estimate the closeness of correlation between fasting and dynamic measures of insulin sensitivity and insulin secretion, the precision of fasting measures, and the agreement between results of standard and simplified glucose tolerance tests in dogs. A retrospective descriptive study using 6 naturally occurring obese and 6 lean dogs was conducted. Data from frequently sampled intravenous glucose tolerance tests (FSIGTTs) in 6 obese and 6 lean client-owned dogs were used to calculate HOMA, QUICKI, fasting glucose and insulin concentrations. Fasting measures of insulin sensitivity and secretion were compared with MINMOD analysis of FSIGTTs using Pearson correlation coefficients, and they were evaluated for precision by the discriminant ratio. Simplified sampling protocols were compared with standard FSIGTTs using Lin's concordance correlation coefficients, limits of agreement, and Pearson correlation coefficients. All fasting measures except fasting plasma glucose concentration were moderately correlated with MINMOD-estimated insulin sensitivity (|r| = 0.62-0.80; P < 0.03), and those that combined fasting insulin and glucose were moderately closely correlated with MINMOD-estimated insulin secretion (r = 0.60-0.79; P < 0.04). HOMA calculated using the nonlinear formulae had the closest estimated correlation (r = 0.77 and 0.74) and the best discrimination for insulin sensitivity and insulin secretion (discriminant ratio 4.4 and 3.4, respectively). Simplified sampling protocols with half as many samples collected over 3 h had close agreement with the full sampling protocol. Fasting measures and simplified intravenous glucose tolerance tests reflect insulin sensitivity and insulin secretion derived from frequently sampled glucose tolerance tests with MINMOD analysis in dogs. Copyright 2010 Elsevier Inc. All rights reserved.

Maximum Likelihood Estimation in Meta-Analytic Structural Equation Modeling

ERIC Educational Resources Information Center

Oort, Frans J.; Jak, Suzanne

2016-01-01

Meta-analytic structural equation modeling (MASEM) involves fitting models to a common population correlation matrix that is estimated on the basis of correlation coefficients that are reported by a number of independent studies. MASEM typically consist of two stages. The method that has been found to perform best in terms of statistical…

Correlation Between Minimum Apparent Diffusion Coefficient (ADCmin) and Tumor Cellularity: A Meta-analysis.

PubMed

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 ADC min , mean ADC or ADC mean and ADC maximum or ADC max Some studies have suggested that ADC min 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 ADC min 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 ADC min were included. Overall, 12 publications with 317 patients were identified. Spearman's correlation coefficient was used to analyze associations between ADC min 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 (p<0.0001), I 2 =73%, test for overall effect Z=8.67 (p<0.00001). ADC min correlated moderately with tumor cellularity. The calculated correlation coefficient is not stronger in comparison to the reported coefficient for ADC mean and, therefore, ADC min does not represent a better means to reflect cellularity. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Correlation Coefficients: Appropriate Use and Interpretation.

PubMed

Schober, Patrick; Boer, Christa; Schwarte, Lothar A

2018-05-01

Correlation in the broadest sense is a measure of an association between variables. In correlated data, the change in the magnitude of 1 variable is associated with a change in the magnitude of another variable, either in the same (positive correlation) or in the opposite (negative correlation) direction. Most often, the term correlation is used in the context of a linear relationship between 2 continuous variables and expressed as Pearson product-moment correlation. The Pearson correlation coefficient is typically used for jointly normally distributed data (data that follow a bivariate normal distribution). For nonnormally distributed continuous data, for ordinal data, or for data with relevant outliers, a Spearman rank correlation can be used as a measure of a monotonic association. Both correlation coefficients are scaled such that they range from -1 to +1, where 0 indicates that there is no linear or monotonic association, and the relationship gets stronger and ultimately approaches a straight line (Pearson correlation) or a constantly increasing or decreasing curve (Spearman correlation) as the coefficient approaches an absolute value of 1. Hypothesis tests and confidence intervals can be used to address the statistical significance of the results and to estimate the strength of the relationship in the population from which the data were sampled. The aim of this tutorial is to guide researchers and clinicians in the appropriate use and interpretation of correlation coefficients.

[Stature estimation for Sichuan Han nationality female based on X-ray technology with measurement of lumbar vertebrae].

PubMed

Qing, Si-han; Chang, Yun-feng; Dong, Xiao-ai; Li, Yuan; Chen, Xiao-gang; Shu, Yong-kang; Deng, Zhen-hua

2013-10-01

To establish the mathematical models of stature estimation for Sichuan Han female with measurement of lumbar vertebrae by X-ray to provide essential data for forensic anthropology research. The samples, 206 Sichuan Han females, were divided into three groups including group A, B and C according to the ages. Group A (206 samples) consisted of all ages, group B (116 samples) were 20-45 years old and 90 samples over 45 years old were group C. All the samples were examined lumbar vertebrae through CR technology, including the parameters of five centrums (L1-L5) as anterior border, posterior border and central heights (x1-x15), total central height of lumbar spine (x16), and the real height of every sample. The linear regression analysis was produced using the parameters to establish the mathematical models of stature estimation. Sixty-two trained subjects were tested to verify the accuracy of the mathematical models. The established mathematical models by hypothesis test of linear regression equation model were statistically significant (P<0.05). The standard errors of the equation were 2.982-5.004 cm, while correlation coefficients were 0.370-0.779 and multiple correlation coefficients were 0.533-0.834. The return tests of the highest correlation coefficient and multiple correlation coefficient of each group showed that the highest accuracy of the multiple regression equation, y = 100.33 + 1.489 x3 - 0.548 x6 + 0.772 x9 + 0.058 x12 + 0.645 x15, in group A were 80.6% (+/- lSE) and 100% (+/- 2SE). The established mathematical models in this study could be applied for the stature estimation for Sichuan Han females.

A robust bayesian estimate of the concordance correlation coefficient.

PubMed

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.

Remote Sensing of Groundwater Storage Changes in Illinois using the Gravity Recovery and Climate Experiment (GRACE)

NASA Technical Reports Server (NTRS)

Yeh, Pat J.-F.; Swenson, S. C.; Famiglietti, J. S.; Rodell, M.

2007-01-01

Regional groundwater storage changes in Illinois are estimated from monthly GRACE total water storage change (TWSC) data and in situ measurements of soil moisture for the period 2002-2005. Groundwater storage change estimates are compared to those derived from the soil moisture and available well level data. The seasonal pattern and amplitude of GRACE-estimated groundwater storage changes track those of the in situ measurements reasonably well, although substantial differences exist in month-to-month variations. The seasonal cycle of GRACE TWSC agrees well with observations (correlation coefficient = 0.83), while the seasonal cycle of GRACE-based estimates of groundwater storage changes beneath 2 m depth agrees with observations with a correlation coefficient of 0.63. We conclude that the GRACE-based method of estimating monthly to seasonal groundwater storage changes performs reasonably well at the 200,000 sq km scale of Illinois.

SCI model structure determination program (OSR) user's guide. [optimal subset regression

NASA Technical Reports Server (NTRS)

1979-01-01

The computer program, OSR (Optimal Subset Regression) which estimates models for rotorcraft body and rotor force and moment coefficients is described. The technique used is based on the subset regression algorithm. Given time histories of aerodynamic coefficients, aerodynamic variables, and control inputs, the program computes correlation between various time histories. The model structure determination is based on these correlations. Inputs and outputs of the program are given.

R package to estimate intracluster correlation coefficient with confidence interval for binary data.

PubMed

Chakraborty, Hrishikesh; Hossain, Akhtar

2018-03-01

The Intracluster Correlation Coefficient (ICC) is a major parameter of interest in cluster randomized trials that measures the degree to which responses within the same cluster are correlated. There are several types of ICC estimators and its confidence intervals (CI) suggested in the literature for binary data. Studies have compared relative weaknesses and advantages of ICC estimators as well as its CI for binary data and suggested situations where one is advantageous in practical research. The commonly used statistical computing systems currently facilitate estimation of only a very few variants of ICC and its CI. To address the limitations of current statistical packages, we developed an R package, ICCbin, to facilitate estimating ICC and its CI for binary responses using different methods. The ICCbin package is designed to provide estimates of ICC in 16 different ways including analysis of variance methods, moments based estimation, direct probabilistic methods, correlation based estimation, and resampling method. CI of ICC is estimated using 5 different methods. It also generates cluster binary data using exchangeable correlation structure. ICCbin package provides two functions for users. The function rcbin() generates cluster binary data and the function iccbin() estimates ICC and it's CI. The users can choose appropriate ICC and its CI estimate from the wide selection of estimates from the outputs. The R package ICCbin presents very flexible and easy to use ways to generate cluster binary data and to estimate ICC and it's CI for binary response using different methods. The package ICCbin is freely available for use with R from the CRAN repository (https://cran.r-project.org/package=ICCbin). We believe that this package can be a very useful tool for researchers to design cluster randomized trials with binary outcome. Copyright © 2017 Elsevier B.V. All rights reserved.

Streamflow simulation studies of the Hillsborough, Alafia, and Anclote Rivers, west-central Florida

USGS Publications Warehouse

Turner, J.F.

1979-01-01

A modified version of the Georgia Tech Watershed Model was applied for the purpose of flow simulation in three large river basins of west-central Florida. Calibrations were evaluated by comparing the following synthesized and observed data: annual hydrographs for the 1959, 1960, 1973 and 1974 water years, flood hydrographs (maximum daily discharge and flood volume), and long-term annual flood-peak discharges (1950-72). Annual hydrographs, excluding the 1973 water year, were compared using average absolute error in annual runoff and daily flows and correlation coefficients of monthly and daily flows. Correlations coefficients for simulated and observed maximum daily discharges and flood volumes used for calibrating range from 0.91 to 0.98 and average standard errors of estimate range from 18 to 45 percent. Correlation coefficients for simulated and observed annual flood-peak discharges range from 0.60 to 0.74 and average standard errors of estimate range from 33 to 44 percent. (Woodard-USGS)

Air sparging: Air-water mass transfer coefficients

NASA Astrophysics Data System (ADS)

Braida, Washington J.; Ong, Say Kee

1998-12-01

Experiments investigating the mass transfer of several dissolved volatile organic compounds (VOCs) across the air-water interface were conducted using a single-air- channel air-sparging system. Three different porous media were used in the study. Air velocities ranged from 0.2 cm s-1 to 2.5 cm s-1. The tortuosity factor for each porous medium and the air-water mass transfer coefficients were estimated by fitting experimental data to a one-dimensional diffusion model. The estimated mass transfer coefficients KG ranged from 1.79 × 10-3 cm min-1 to 3.85 × 10-2 cm min-1. The estimated lumped gas phase mass transfer coefficients KGa were found to be directly related to the air diffusivity of the VOC, air velocity, and particle size, and inversely related to the Henry's law constant of the VOCs. Of the four parameters investigated, the parameter that controlled or had a dominant effect on the lumped gas phase mass transfer coefficient was the air diffusivity of the VOC. Two empirical models were developed by correlating the Damkohler and the modified air phase Sherwood numbers with the air phase Peclet number, Henry's law constant, and the reduced mean particle size of porous media. The correlation developed in this study may be used to obtain better predictions of mass transfer fluxes for field conditions.

Identifying Bearing Rotordynamic Coefficients using an Extended Kalman Filter

NASA Technical Reports Server (NTRS)

Miller, Brad A.; Howard, Samuel A.

2008-01-01

An Extended Kalman Filter is developed to estimate the linearized direct and indirect stiffness and damping force coefficients for bearings in rotor-dynamic applications from noisy measurements of the shaft displacement in response to imbalance and impact excitation. The bearing properties are modeled as stochastic random variables using a Gauss-Markov model. Noise terms are introduced into the system model to account for all of the estimation error, including modeling errors and uncertainties and the propagation of measurement errors into the parameter estimates. The system model contains two user-defined parameters that can be tuned to improve the filter s performance; these parameters correspond to the covariance of the system and measurement noise variables. The filter is also strongly influenced by the initial values of the states and the error covariance matrix. The filter is demonstrated using numerically simulated data for a rotor-bearing system with two identical bearings, which reduces the number of unknown linear dynamic coefficients to eight. The filter estimates for the direct damping coefficients and all four stiffness coefficients correlated well with actual values, whereas the estimates for the cross-coupled damping coefficients were the least accurate.

Heritabilities and genetic correlations of economic traits in Iranian native fowl and estimated genetic trend and inbreeding coefficients.

PubMed

Kamali, M A; Ghorbani, S H; Sharbabak, M Moradi; Zamiri, M J

2007-08-01

1. Genetic parameters were estimated in a base population of a closed experimental strain of fowl. Data were obtained on 21 245 Iranian native hens (breeding centre for Fars province) subject to 8 successive generations of selection. This population had been selected for body weight at 12 weeks of age (BW12) and egg number during the first 12 weeks of the laying period (EN), mean egg weight (EW) at weeks 28, 30 and 32, and age at sexual maturity (ASM). 2. The method of multi-traits restricted maximum likelihood with an animal model was used to estimate genetic parameters. Resulting heritabilities for BW12, EN, EW and ASM were 0.68 +/- 0.02, 0.40 +/- 0.02, 0.64 +/- 0.02 and 0.49 +/- 0.02, respectively. 3. Genetic correlations between BW12 and EN, EW and ASM were 0.11 +/- 0.33, 0.54 +/- 0.21 and -0.12 +/- 0.03, respectively. Genetic correlations between EN and EW and ASM were -0.09 +/- 0.03 and -0.85 +/- 0.01, respectively, while between EW and ASM, it was 0.05 +/- 0.03. 4. The overall predicted genetic gains, after 7 generations of selection, estimated by the regression coefficients of the breeding value on generation number were equal to 22.7, 0.17, 0.04 and -1.38, for BW12, EN, EW and ASM, respectively. 5. A pedigree file of 21 245 female and male birds was used to calculate inbreeding coefficients and their influence on production and reproduction traits. Average inbreeding coefficients for all birds, inbred birds, female birds and male birds were 0.048, 0.673, 0.055 and 0.047%, respectively. Regression coefficients of BW12, ASM, EN and EW on inbreeding coefficient for all birds were equal to 0.51 +/- 0.001, 0.31 +/- 0.003, -0.51 +/- 0.003 and 0.03 +/- 0.001, respectively.

A Bayesian Framework for Estimating the Concordance Correlation Coefficient Using Skew-elliptical Distributions.

PubMed

Feng, Dai; Baumgartner, Richard; Svetnik, Vladimir

2018-04-05

The concordance correlation coefficient (CCC) is a widely used scaled index in the study of agreement. In this article, we propose estimating the CCC by a unified Bayesian framework that can (1) accommodate symmetric or asymmetric and light- or heavy-tailed data; (2) select model from several candidates; and (3) address other issues frequently encountered in practice such as confounding covariates and missing data. The performance of the proposal was studied and demonstrated using simulated as well as real-life biomarker data from a clinical study of an insomnia drug. The implementation of the proposal is accessible through a package in the Comprehensive R Archive Network.

Calcaneotalar ratio: a new concept in the estimation of the length of the calcaneus.

PubMed

David, Vikram; Stephens, Terry J; Kindl, Radek; Ang, Andy; Tay, Wei-Han; Asaid, Rafik; McCullough, Keith

2015-01-01

Maintaining the calcaneal length after calcaneal fractures is vital to restoring the normal biomechanics of the foot, because it acts as an important lever arm to the plantarflexors of the foot. However, estimation of the length of the calcaneus to be reconstructed in comminuted calcaneal fractures can be difficult. We propose a new method to reliably estimate the calcaneal length radiographically by defining the calcaneotalar length ratio. A total of 100 ankle radiographs with no fracture in the calcaneus or talus taken in skeletally mature patients were reviewed by 6 observers. The anteroposterior lengths of the calcaneus and talus were measured, and the calcaneotalar length ratio was determined. The ratio was then used to estimate the length of the calcaneus. Interobserver reliability was determined using Cronbach's α coefficient and Pearson's correlation coefficient. The mean length of the calcaneus was 75 ± 0.6 mm, and the mean length of the talus was 59 ± 0.5 mm. The calcaneotalar ratio was 1.3. Using this ratio and multiplying it by the talar length, the mean average estimated length of the calcaneus was within 0.7 mm of the known calcaneal length. Cronbach's α coefficient and Pearson's correlation coefficient showed excellent interobserver reliability. The proposed calcaneotalar ratio is a new and reliable method to radiographically estimate the normal length of the calcaneus when reconstructing the calcaneus. Copyright © 2015 American College of Foot and Ankle Surgeons. Published by Elsevier Inc. All rights reserved.

Radiation absorbed by a vertical cylinder in complex outdoor environments under clear sky conditions

NASA Astrophysics Data System (ADS)

Krys, S. A.; Brown, R. D.

1990-06-01

Research was conducted into the estimation of radiation absorbed by a vertical cylinder in complex outdoor environments under clear sky conditions. Two methods of estimation were employed: a cylindrical radiation thermometer (CRT) and model developed by Brown and Gillespie (1986), and the weather station model. The CRT produced an integrated temperature reading from which the radiant environment could be estimated successfully given simultaneous measurements of air temperature and wind speed. The CRT estimates compared to the measured radiation gave a correlation coefficient of 0.9499, SE=19.8 W/m2, α=99.9%. The physically-based equations (weather station model)require the inputs of data from a near by weather station and site characteristics to estimate radiation absorbed by a vertical cylinder. The correlation coefficient for the weather station model is 0.9529, SE=16.8 W/m2, α=99.9%. This model estimates short wave and long wave radiation separately; hence, this allowed further comparison to measured values. The short wave radiation was very successfully estimated: R=0.9865, SE=10.0 W/m2, α=99.9%. The long wave radiation estimates were also successful: R=0.8654, SE=15.7 W/m2, and α=99.9%. Though the correlation coefficient and standard error may suggest inaccuracy to the micrometeorologist, these estimation techniques would be extremely useful as predictors of human thermal comfort which is not a precise measure buut defined by a range. The reported methods require little specialized knowledge of micrometeorology and are vehicles for the designers of outdoor spaces to measure accurately the inherent radiant environment of outdoor spaces and provide a measurement technique to simulate or model the effect of various landscape elements on planned environments.

Distribution coefficients of rare earth ions in cubic zirconium dioxide

NASA Astrophysics Data System (ADS)

Romer, H.; Luther, K.-D.; Assmus, W.

1994-08-01

Cubic zirconium dioxide crystals are grown with the skull melting technique. The effective distribution coefficients for Nd(exp 3+), Sm(exp 3+) and Er(sup 3+) as dopants are determined experimentally as a function of the crystal growth velocity. With the Burton-Prim-Slichter theory, the equilibrium distribution coefficients can be calculated. The distribution coefficients of all other trivalent rare earth ions can be estimated by applying the correlation towards the ionic radii.

Genetic diversity of popcorn genotypes using molecular analysis.

PubMed

Resh, F S; Scapim, C A; Mangolin, C A; Machado, M F P S; do Amaral, A T; Ramos, H C C; Vivas, M

2015-08-19

In this study, we analyzed dominant molecular markers to estimate the genetic divergence of 26 popcorn genotypes and evaluate whether using various dissimilarity coefficients with these dominant markers influences the results of cluster analysis. Fifteen random amplification of polymorphic DNA primers produced 157 amplified fragments, of which 65 were monomorphic and 92 were polymorphic. To calculate the genetic distances among the 26 genotypes, the complements of the Jaccard, Dice, and Rogers and Tanimoto similarity coefficients were used. A matrix of Dij values (dissimilarity matrix) was constructed, from which the genetic distances among genotypes were represented in a more simplified manner as a dendrogram generated using the unweighted pair-group method with arithmetic average. Clusters determined by molecular analysis generally did not group material from the same parental origin together. The largest genetic distance was between varieties 17 (UNB-2) and 18 (PA-091). In the identification of genotypes with the smallest genetic distance, the 3 coefficients showed no agreement. The 3 dissimilarity coefficients showed no major differences among their grouping patterns because agreement in determining the genotypes with large, medium, and small genetic distances was high. The largest genetic distances were observed for the Rogers and Tanimoto dissimilarity coefficient (0.74), followed by the Jaccard coefficient (0.65) and the Dice coefficient (0.48). The 3 coefficients showed similar estimations for the cophenetic correlation coefficient. Correlations among the matrices generated using the 3 coefficients were positive and had high magnitudes, reflecting strong agreement among the results obtained using the 3 evaluated dissimilarity coefficients.

Estimating the total energy demand for supra-maximal exercise using the VO2-power regression from an incremental exercise test.

PubMed

Aisbett, B; Le Rossignol, P

2003-09-01

The VO2-power regression and estimated total energy demand for a 6-minute supra-maximal exercise test was predicted from a continuous incremental exercise test. Sub-maximal VO2-power co-ordinates were established from the last 40 seconds (s) of 150-second exercise stages. The precision of the estimated total energy demand was determined using the 95% confidence interval (95% CI) of the estimated total energy demand. The linearity of the individual VO2-power regression equations was determined using Pearson's correlation coefficient. The mean 95% CI of the estimated total energy demand was 5.9 +/- 2.5 mL O2 Eq x kg(-1) x min(-1), and the mean correlation coefficient was 0.9942 +/- 0.0042. The current study contends that the sub-maximal VO2-power co-ordinates from a continuous incremental exercise test can be used to estimate supra-maximal energy demand without compromising the precision of the accumulated oxygen deficit (AOD) method.

Estimation of alertness levels with changes in decibel scale wavelength of EEG during dual-task simulation of auditory sonar target detection.

PubMed

Arjunan, Sridhar P; Kumar, Dinesh K; Jung, Tzyy-Ping

2010-01-01

Changes in alertness levels can have dire consequences for people operating and controlling motorized equipment. Past research studies have shown the relationship of Electroencephalogram (EEG) with alertness of the person. This research reports the fractal analysis of EEG and estimation of the alertness levels of the individual based on the changes in the maximum fractal length (MFL) of EEG. The results indicate that MFL of only 2 channels of EEG can be used to identify the loss of alertness of the individual with mean (inverse) correlation coefficient = 0.82. This study has also reported that using the changes in MFL of EEG, the changes in alertness level of a person was estimated with a mean correlation coefficient = 0.69.

Estimation of PM2.5 and PM10 using ground-based AOD measurements during KORUS-AQ campaign

NASA Astrophysics Data System (ADS)

Koo, J. H.; Kim, J.; Kim, S.; Go, S.; Lee, S.; Lee, H.; Mok, J.; Hong, J.; Lee, J.; Eck, T. F.; Holben, B. N.

2017-12-01

During the KORUS-AQ campaign (2 May - 12 June, 2016), aerosol optical depth (AOD) was obtained at multiple channels using various ground-based instruments at Yonsei University, Seoul: AERONET sunphotometer, SKYNET skyradiometer, Brewer spectrophotometer, and multi-filter rotating shadowband radiometer (MFRSR). At the same location, planetary boundary layer (PBL) height and vertical profile of backscattering coefficients also can be obtained based on the celiometer measurements. Using celiometer products and various AODs, we try to estimate the amount of particular matter (PM2.5 and PM10) and validate with in-situ surface PM2.5 and PM10 measurements from AIRKOREA network. Direct comparison between PM2.5 and AOD reveals that the ultraviolet(UV) channel AOD has better correlations, due to the higher sensitivity of short wavelength to the fine-mode particle. In contrast, PM10 shows the highest correlation with the near-infrared(NIR) AOD. Next, we extract the boundary-layer portion of AOD using either PBL height or vertical profile of backscattering coefficients to compare with PM2.5 and PM10. Both results enhance the correlation, but consideration of weighting factor calculated from backscattering coefficients shows larger contribution to the correlation increase. Finally, we performed the multiple linear regression to estimate PM2.5 and PM10 using AODs. Consideration of meteorology (temperature, wind speed, and relative humidity) can enhance the correlation and also O3 and NO2 consideration highly contributes to the high correlation. This finding implies the importance to consider the ambient condition of secondary aerosol formation related to the PM2.5 variation. Multiple regression model finally finds the correlation 0.7-0.8, and diminishes the wavelength-dependent correlation patterns.

Improved estimation of subject-level functional connectivity using full and partial correlation with empirical Bayes shrinkage.

PubMed

Mejia, Amanda F; Nebel, Mary Beth; Barber, Anita D; Choe, Ann S; Pekar, James J; Caffo, Brian S; Lindquist, Martin A

2018-05-15

Reliability of subject-level resting-state functional connectivity (FC) is determined in part by the statistical techniques employed in its estimation. Methods that pool information across subjects to inform estimation of subject-level effects (e.g., Bayesian approaches) have been shown to enhance reliability of subject-level FC. However, fully Bayesian approaches are computationally demanding, while empirical Bayesian approaches typically rely on using repeated measures to estimate the variance components in the model. Here, we avoid the need for repeated measures by proposing a novel measurement error model for FC describing the different sources of variance and error, which we use to perform empirical Bayes shrinkage of subject-level FC towards the group average. In addition, since the traditional intra-class correlation coefficient (ICC) is inappropriate for biased estimates, we propose a new reliability measure denoted the mean squared error intra-class correlation coefficient (ICC MSE ) to properly assess the reliability of the resulting (biased) estimates. We apply the proposed techniques to test-retest resting-state fMRI data on 461 subjects from the Human Connectome Project to estimate connectivity between 100 regions identified through independent components analysis (ICA). We consider both correlation and partial correlation as the measure of FC and assess the benefit of shrinkage for each measure, as well as the effects of scan duration. We find that shrinkage estimates of subject-level FC exhibit substantially greater reliability than traditional estimates across various scan durations, even for the most reliable connections and regardless of connectivity measure. Additionally, we find partial correlation reliability to be highly sensitive to the choice of penalty term, and to be generally worse than that of full correlations except for certain connections and a narrow range of penalty values. This suggests that the penalty needs to be chosen carefully when using partial correlations. Copyright © 2018. Published by Elsevier Inc.

Assessing Performance of P-Band Backscattering Coefficients and TSAR in Hemi-Boreal Forest AGB Estimation

NASA Astrophysics Data System (ADS)

Li, Wenmei; Chen, Erxue; Li, Zengyuan; Feng, Qi

2014-11-01

To assess performance of P-band backscattering coefficients and TSAR for hemi-boreal forest AGB estimation, airborne P-band repeat-path Pol-InSAR data collected by ESAR in Ramingstorp test site during March and May 2007 are applied. The correlation coefficient (R) between P-band backscattering coefficients and in-situ biomass reaches 0.87 for HH polarization. Meanwhile, the R between P-band backscattering power at specific height and in-situ biomass are higher in VV polarization than that in HH and HV polarization. And R between P-band backscattering power and in-situ biomass reaches 0.70 at 5m and 10m height in VV polarization.

Assessing Performance of P-Band Backscattering Coefficients and TSAR in Hemi-Boreal Forest AGB Estimation

NASA Astrophysics Data System (ADS)

Li, Wenmei; Chen, Erxue; Li, Zengyuan; Feng, Qi

2014-11-01

To assess performance of P-band backscattering coefficients and TSAR for hemi-boreal forest AGB estimation, airborne P-band repeat-path Pol-InSAR data collected by ESAR in Ramingstorp test site during March and May 2007 are applied.The correlation coefficient (R) between P-band backscattering coefficients and in-situ biomass reaches 0.87 for HH polarization. Meanwhile, the R between P-band backscattering power at specific height and in-situ biomass are higher in VV polarization than that in HH and HV polarization. And R between P-band backscattering power and in-situ biomass reaches 0.70 at 5m and 10m height in VV polarization.

Triple collocation-based estimation of spatially correlated observation error covariance in remote sensing soil moisture data assimilation

NASA Astrophysics Data System (ADS)

Wu, Kai; Shu, Hong; Nie, Lei; Jiao, Zhenhang

2018-01-01

Spatially correlated errors are typically ignored in data assimilation, thus degenerating the observation error covariance R to a diagonal matrix. We argue that a nondiagonal R carries more observation information making assimilation results more accurate. A method, denoted TC_Cov, was proposed for soil moisture data assimilation to estimate spatially correlated observation error covariance based on triple collocation (TC). Assimilation experiments were carried out to test the performance of TC_Cov. AMSR-E soil moisture was assimilated with a diagonal R matrix computed using the TC and assimilated using a nondiagonal R matrix, as estimated by proposed TC_Cov. The ensemble Kalman filter was considered as the assimilation method. Our assimilation results were validated against climate change initiative data and ground-based soil moisture measurements using the Pearson correlation coefficient and unbiased root mean square difference metrics. These experiments confirmed that deterioration of diagonal R assimilation results occurred when model simulation is more accurate than observation data. Furthermore, nondiagonal R achieved higher correlation coefficient and lower ubRMSD values over diagonal R in experiments and demonstrated the effectiveness of TC_Cov to estimate richly structuralized R in data assimilation. In sum, compared with diagonal R, nondiagonal R may relieve the detrimental effects of assimilation when simulated model results outperform observation data.

Use of Empirical Estimates of Shrinkage in Multiple Regression: A Caution.

ERIC Educational Resources Information Center

Kromrey, Jeffrey D.; Hines, Constance V.

1995-01-01

The accuracy of four empirical techniques to estimate shrinkage in multiple regression was studied through Monte Carlo simulation. None of the techniques provided unbiased estimates of the population squared multiple correlation coefficient, but the normalized jackknife and bootstrap techniques demonstrated marginally acceptable performance with…

Development of a soy food frequency questionnaire to estimate isoflavone consumption in US adults.

PubMed

Kirk, P; Patterson, R E; Lampe, J

1999-05-01

To develop a dietary assessment instrument to measure soy food consumption and isoflavone intake and test it for reliability. A soy food frequency questionnaire, designed for use in this study, was administered twice to participants, separated by a 2-week interval. The questionnaire was tested for reproducibility of estimates of soy food consumption and isoflavone (genistein and daidzein) intake. A convenience sample of 51 faculty, staff, and students was recruited from a naturopathic university. Intraclass correlation coefficients were used to assess reproducibility of estimates of soy food intake and genistein and daidzein intake. Correlation coefficients comparing mean soy food servings per month between the 2 administrations of the questionnaire ranged from 0.50 for soy yogurt to 0.89 for tempeh. Correlation coefficients for genistein and daidzein intake estimated by the 2 administrations of the questionnaire were the same: 0.89. Mean intake (+/- standard deviation) of genistein and daidzein was 7 +/- 10 and 4 +/- 6 mg/day, respectively. Fifteen soy foods contributed 95% of the total genistein and daidzein intake: tofu, soy yogurt, tempeh, soy milk, low-fat tofu, soy flour, miso, soy protein isolate, low-fat soy milk, veggie soy burger, textured vegetable protein, miso soup, cooked soybeans, soy hot dogs, and natto (fermented soy beans). The soy food frequency questionnaire developed in this study provided highly reproducible estimates of soy food consumption and isoflavone intake. This instrument may be a useful tool in studies of the associations between isoflavone exposure and risk for chronic disease.

Comparison of the accuracy of kriging and IDW interpolations in estimating groundwater arsenic concentrations in Texas.

PubMed

Gong, Gordon; Mattevada, Sravan; O'Bryant, Sid E

2014-04-01

Exposure to arsenic causes many diseases. Most Americans in rural areas use groundwater for drinking, which may contain arsenic above the currently allowable level, 10µg/L. It is cost-effective to estimate groundwater arsenic levels based on data from wells with known arsenic concentrations. We compared the accuracy of several commonly used interpolation methods in estimating arsenic concentrations in >8000 wells in Texas by the leave-one-out-cross-validation technique. Correlation coefficient between measured and estimated arsenic levels was greater with inverse distance weighted (IDW) than kriging Gaussian, kriging spherical or cokriging interpolations when analyzing data from wells in the entire Texas (p<0.0001). Correlation coefficient was significantly lower with cokriging than any other methods (p<0.006) for wells in Texas, east Texas or the Edwards aquifer. Correlation coefficient was significantly greater for wells in southwestern Texas Panhandle than in east Texas, and was higher for wells in Ogallala aquifer than in Edwards aquifer (p<0.0001) regardless of interpolation methods. In regression analysis, the best models are when well depth and/or elevation were entered into the model as covariates regardless of area/aquifer or interpolation methods, and models with IDW are better than kriging in any area/aquifer. In conclusion, the accuracy in estimating groundwater arsenic level depends on both interpolation methods and wells' geographic distributions and characteristics in Texas. Taking well depth and elevation into regression analysis as covariates significantly increases the accuracy in estimating groundwater arsenic level in Texas with IDW in particular. Published by Elsevier Inc.

Estimating activity energy expenditure: how valid are physical activity questionnaires?

PubMed

Neilson, Heather K; Robson, Paula J; Friedenreich, Christine M; Csizmadi, Ilona

2008-02-01

Activity energy expenditure (AEE) is the modifiable component of total energy expenditure (TEE) derived from all activities, both volitional and nonvolitional. Because AEE may affect health, there is interest in its estimation in free-living people. Physical activity questionnaires (PAQs) could be a feasible approach to AEE estimation in large populations, but it is unclear whether or not any PAQ is valid for this purpose. Our aim was to explore the validity of existing PAQs for estimating usual AEE in adults, using doubly labeled water (DLW) as a criterion measure. We reviewed 20 publications that described PAQ-to-DLW comparisons, summarized study design factors, and appraised criterion validity using mean differences (AEE(PAQ) - AEE(DLW), or TEE(PAQ) - TEE(DLW)), 95% limits of agreement, and correlation coefficients (AEE(PAQ) versus AEE(DLW) or TEE(PAQ) versus TEE(DLW)). Only 2 of 23 PAQs assessed most types of activity over the past year and indicated acceptable criterion validity, with mean differences (TEE(PAQ) - TEE(DLW)) of 10% and 2% and correlation coefficients of 0.62 and 0.63, respectively. At the group level, neither overreporting nor underreporting was more prevalent across studies. We speculate that, aside from reporting error, discrepancies between PAQ and DLW estimates may be partly attributable to 1) PAQs not including key activities related to AEE, 2) PAQs and DLW ascertaining different time periods, or 3) inaccurate assignment of metabolic equivalents to self-reported activities. Small sample sizes, use of correlation coefficients, and limited information on individual validity were problematic. Future research should address these issues to clarify the true validity of PAQs for estimating AEE.

Shrinkage regression-based methods for microarray missing value imputation.

PubMed

Wang, Hsiuying; Chiu, Chia-Chun; Wu, Yi-Ching; Wu, Wei-Sheng

2013-01-01

Missing values commonly occur in the microarray data, which usually contain more than 5% missing values with up to 90% of genes affected. Inaccurate missing value estimation results in reducing the power of downstream microarray data analyses. Many types of methods have been developed to estimate missing values. Among them, the regression-based methods are very popular and have been shown to perform better than the other types of methods in many testing microarray datasets. To further improve the performances of the regression-based methods, we propose shrinkage regression-based methods. Our methods take the advantage of the correlation structure in the microarray data and select similar genes for the target gene by Pearson correlation coefficients. Besides, our methods incorporate the least squares principle, utilize a shrinkage estimation approach to adjust the coefficients of the regression model, and then use the new coefficients to estimate missing values. Simulation results show that the proposed methods provide more accurate missing value estimation in six testing microarray datasets than the existing regression-based methods do. Imputation of missing values is a very important aspect of microarray data analyses because most of the downstream analyses require a complete dataset. Therefore, exploring accurate and efficient methods for estimating missing values has become an essential issue. Since our proposed shrinkage regression-based methods can provide accurate missing value estimation, they are competitive alternatives to the existing regression-based methods.

Estimated Accuracy of Three Common Trajectory Statistical Methods

NASA Technical Reports Server (NTRS)

Kabashnikov, Vitaliy P.; Chaikovsky, Anatoli P.; Kucsera, Tom L.; Metelskaya, Natalia S.

2011-01-01

Three well-known trajectory statistical methods (TSMs), namely concentration field (CF), concentration weighted trajectory (CWT), and potential source contribution function (PSCF) methods were tested using known sources and artificially generated data sets to determine the ability of TSMs to reproduce spatial distribution of the sources. In the works by other authors, the accuracy of the trajectory statistical methods was estimated for particular species and at specified receptor locations. We have obtained a more general statistical estimation of the accuracy of source reconstruction and have found optimum conditions to reconstruct source distributions of atmospheric trace substances. Only virtual pollutants of the primary type were considered. In real world experiments, TSMs are intended for application to a priori unknown sources. Therefore, the accuracy of TSMs has to be tested with all possible spatial distributions of sources. An ensemble of geographical distributions of virtual sources was generated. Spearman s rank order correlation coefficient between spatial distributions of the known virtual and the reconstructed sources was taken to be a quantitative measure of the accuracy. Statistical estimates of the mean correlation coefficient and a range of the most probable values of correlation coefficients were obtained. All the TSMs that were considered here showed similar close results. The maximum of the ratio of the mean correlation to the width of the correlation interval containing the most probable correlation values determines the optimum conditions for reconstruction. An optimal geographical domain roughly coincides with the area supplying most of the substance to the receptor. The optimal domain s size is dependent on the substance decay time. Under optimum reconstruction conditions, the mean correlation coefficients can reach 0.70 0.75. The boundaries of the interval with the most probable correlation values are 0.6 0.9 for the decay time of 240 h and 0.5 0.95 for the decay time of 12 h. The best results of source reconstruction can be expected for the trace substances with a decay time on the order of several days. Although the methods considered in this paper do not guarantee high accuracy they are computationally simple and fast. Using the TSMs in optimum conditions and taking into account the range of uncertainties, one can obtain a first hint on potential source areas.

Wind-chill-equivalent temperatures: regarding the impact due to the variability of the environmental convective heat transfer coefficient.

PubMed

Shitzer, Avraham

2006-03-01

The wind-chill index (WCI), developed in Antarctica in the 1940s and recently updated by the weather services in the USA and Canada, expresses the enhancement of heat loss in cold climates from exposed body parts, e.g., face, due to wind. The index provides a simple and practical means for assessing the thermal effects of wind on humans outdoors. It is also used for indicating weather conditions that may pose adverse risks of freezing at subfreezing environmental temperatures. Values of the WCI depend on a number of parameters, i.e, temperatures, physical properties of the air, wind speed, etc., and on insolation and evaporation. This paper focuses on the effects of various empirical correlations used in the literature for calculating the convective heat transfer coefficients between humans and their environment. Insolation and evaporation are not included in the presentation. Large differences in calculated values among these correlations are demonstrated and quantified. Steady-state wind-chill-equivalent temperatures (WCETs) are estimated by a simple, one-dimensional heat-conducting hollow-cylindrical model using these empirical correlations. Partial comparison of these values with the published "new" WCETs is presented. The variability of the estimated WCETs, due to different correlations employed to calculate them, is clearly demonstrated. The results of this study clearly suggest the need for establishing a "gold standard" for estimating convective heat exchange between exposed body elements and the cold and windy environment. This should be done prior to the introduction and adoption of further modifications to WCETs and indices. Correlations to estimate the convective heat transfer coefficients between exposed body parts of humans in windy and cold environments influence the WCETs and need to be standardized.

Wind-chill-equivalent temperatures: regarding the impact due to the variability of the environmental convective heat transfer coefficient

NASA Astrophysics Data System (ADS)

Shitzer, Avraham

2006-03-01

The wind-chill index (WCI), developed in Antarctica in the 1940s and recently updated by the weather services in the USA and Canada, expresses the enhancement of heat loss in cold climates from exposed body parts, e.g., face, due to wind. The index provides a simple and practical means for assessing the thermal effects of wind on humans outdoors. It is also used for indicating weather conditions that may pose adverse risks of freezing at subfreezing environmental temperatures. Values of the WCI depend on a number of parameters, i.e, temperatures, physical properties of the air, wind speed, etc., and on insolation and evaporation. This paper focuses on the effects of various empirical correlations used in the literature for calculating the convective heat transfer coefficients between humans and their environment. Insolation and evaporation are not included in the presentation. Large differences in calculated values among these correlations are demonstrated and quantified. Steady-state wind-chill-equivalent temperatures (WCETs) are estimated by a simple, one-dimensional heat-conducting hollow-cylindrical model using these empirical correlations. Partial comparison of these values with the published “new” WCETs is presented. The variability of the estimated WCETs, due to different correlations employed to calculate them, is clearly demonstrated. The results of this study clearly suggest the need for establishing a “gold standard” for estimating convective heat exchange between exposed body elements and the cold and windy environment. This should be done prior to the introduction and adoption of further modifications to WCETs and indices. Correlations to estimate the convective heat transfer coefficients between exposed body parts of humans in windy and cold environments influence the WCETs and need to be standardized.

Strategic Use of Random Subsample Replication and a Coefficient of Factor Replicability

ERIC Educational Resources Information Center

Katzenmeyer, William G.; Stenner, A. Jackson

1975-01-01

The problem of demonstrating replicability of factor structure across random variables is addressed. Procedures are outlined which combine the use of random subsample replication strategies with the correlations between factor score estimates across replicate pairs to generate a coefficient of replicability and confidence intervals associated with…

Simulation data for an estimation of the maximum theoretical value and confidence interval for the correlation coefficient.

PubMed

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.

An Improved Internal Consistency Reliability Estimate.

ERIC Educational Resources Information Center

Cliff, Norman

1984-01-01

The proposed coefficient is derived by assuming that the average Goodman-Kruskal gamma between items of identical difficulty would be the same for items of different difficulty. An estimate of covariance between items of identical difficulty leads to an estimate of the correlation between two tests with identical distributions of difficulty.…

Translation, cross-cultural adaptation and validation of the Bulgarian version of the Dizziness Handicap Inventory.

PubMed

Georgieva-Zhostova, Spaska; Kolev, Ognyan I; Stambolieva, Katerina

2014-09-01

The aim of the present study was the translation, cross-cultural adaptation and validation of the Dizziness Handicap Inventory in Bulgarian language (DHI-BG). Ninety-seven vestibular patients (19 men and 78 women, mean age 45.08 ± 13.85 years) took part in the investigation. All participants were asked to fill in the DHI-BG. Internal consistency was estimated using Cronbach's alpha and item-total correlation, reproducibility by calculating Bland-Altman's limits of agreement and intraclass correlation coefficients (ICCs). Associations were estimated by Spearman's correlation coefficients. The Cronbach's alpha for the total score, functional, physical and emotional subscales of DHI-BG were 0.88, 0.75, 0.72 and 0.81. The floor and ceiling effects of the DHI-BG total scale were evaluated with respect to the limits of agreement which were ±9.4-14.53 points. Intraclass correlation coefficients (ICCs) for all scale and subscales were higher than the recommended value of 0.75 and determined good test-retest reliability. The range of items correlation for DHI-BG was from 0.27 (item 12) to 0.72 (item 3). No significant differences were observed in the Cronbach's alpha coefficients between the DHI-BG and the original version, the German and Italian versions of the questionnaire. The most significant difference was observed in comparison with the German version of DHI. Construct validity presented a moderate correlation between Romberg coefficients and DHI-BG scores and strong correlation between all scores of DHI and the self-perceived disability. The results suggest that DHI-BG scores show a good discriminative validity between groups with different levels of self-assessed disability. The Bulgarian version of the DHI is a reliable and valid tool in assessing the impact of dizziness on the quality of life in Bulgarian vestibular patients.

Accuracy of MRI skeletal age estimation for subjects 12-19. Potential use for subjects of unknown age.

PubMed

Serinelli, Serenella; Panebianco, Valeria; Martino, Milvia; Battisti, Sofia; Rodacki, Karina; Marinelli, Enrico; Zaccagna, Fulvio; Semelka, Richard C; Tomei, Ernesto

2015-05-01

In forensic practice, there is a growing need for accurate methods of age estimation, especially in the cases of young individuals of unknown age. Age can be estimated through somatic features that are universally considered associated with chronological age. Unfortunately, these features do not always coincide with the real chronological age: for these reasons that age determination is often very difficult. Our aim is to evaluate accuracy of skeletal age estimation using Tomei's MRI method in subjects between 12 and 19 years old for forensic purposes. Two investigators analyzed MRI images of the left hand and wrist of 77 male and 74 female caucasian subjects, without chronic diseases or developmental disorders, whose age ranged from 12 to 19 years. Skeletal maturation was determined by two operators, who analyzed all MRI images separately, in blinded fashion to the chronological age. Inter-rater agreement was measured with Pearson (R (2)) coefficient. One of the examiners repeated the evaluation after 6 months, and intraobserver variation was analyzed. Bland-Altman plots were used to determine mean differences between skeletal and chronological age. Inter-rater agreement Pearson coefficient showed a good linear correlation, respectively, 0.98 and 0.97 in males and females. Bland-Altman analysis demonstrated that the differences between chronological and skeletal age are not significant. Spearman's correlation coefficient showed good correlation between skeletal and chronological age both in females (R (2) = 0.96) and in males (R (2) = 0.94). Our results show that MRI skeletal age is a reproducible method and has good correlation with chronological age.

A non-linear regression method for CT brain perfusion analysis

NASA Astrophysics Data System (ADS)

Bennink, E.; Oosterbroek, J.; Viergever, M. A.; Velthuis, B. K.; de Jong, H. W. A. M.

2015-03-01

CT perfusion (CTP) imaging allows for rapid diagnosis of ischemic stroke. Generation of perfusion maps from CTP data usually involves deconvolution algorithms providing estimates for the impulse response function in the tissue. We propose the use of a fast non-linear regression (NLR) method that we postulate has similar performance to the current academic state-of-art method (bSVD), but that has some important advantages, including the estimation of vascular permeability, improved robustness to tracer-delay, and very few tuning parameters, that are all important in stroke assessment. The aim of this study is to evaluate the fast NLR method against bSVD and a commercial clinical state-of-art method. The three methods were tested against a published digital perfusion phantom earlier used to illustrate the superiority of bSVD. In addition, the NLR and clinical methods were also tested against bSVD on 20 clinical scans. Pearson correlation coefficients were calculated for each of the tested methods. All three methods showed high correlation coefficients (>0.9) with the ground truth in the phantom. With respect to the clinical scans, the NLR perfusion maps showed higher correlation with bSVD than the perfusion maps from the clinical method. Furthermore, the perfusion maps showed that the fast NLR estimates are robust to tracer-delay. In conclusion, the proposed fast NLR method provides a simple and flexible way of estimating perfusion parameters from CT perfusion scans, with high correlation coefficients. This suggests that it could be a better alternative to the current clinical and academic state-of-art methods.

Quantifying Abdominal Adipose Tissue and Thigh Muscle Volume and Hepatic Proton Density Fat Fraction: Repeatability and Accuracy of an MR Imaging-based, Semiautomated Analysis Method.

PubMed

Middleton, Michael S; Haufe, William; Hooker, Jonathan; Borga, Magnus; Dahlqvist Leinhard, Olof; Romu, Thobias; Tunón, Patrik; Hamilton, Gavin; Wolfson, Tanya; Gamst, Anthony; Loomba, Rohit; Sirlin, Claude B

2017-05-01

Purpose To determine the repeatability and accuracy of a commercially available magnetic resonance (MR) imaging-based, semiautomated method to quantify abdominal adipose tissue and thigh muscle volume and hepatic proton density fat fraction (PDFF). Materials and Methods This prospective study was institutional review board- approved and HIPAA compliant. All subjects provided written informed consent. Inclusion criteria were age of 18 years or older and willingness to participate. The exclusion criterion was contraindication to MR imaging. Three-dimensional T1-weighted dual-echo body-coil images were acquired three times. Source images were reconstructed to generate water and calibrated fat images. Abdominal adipose tissue and thigh muscle were segmented, and their volumes were estimated by using a semiautomated method and, as a reference standard, a manual method. Hepatic PDFF was estimated by using a confounder-corrected chemical shift-encoded MR imaging method with hybrid complex-magnitude reconstruction and, as a reference standard, MR spectroscopy. Tissue volume and hepatic PDFF intra- and interexamination repeatability were assessed by using intraclass correlation and coefficient of variation analysis. Tissue volume and hepatic PDFF accuracy were assessed by means of linear regression with the respective reference standards. Results Adipose and thigh muscle tissue volumes of 20 subjects (18 women; age range, 25-76 years; body mass index range, 19.3-43.9 kg/m 2 ) were estimated by using the semiautomated method. Intra- and interexamination intraclass correlation coefficients were 0.996-0.998 and coefficients of variation were 1.5%-3.6%. For hepatic MR imaging PDFF, intra- and interexamination intraclass correlation coefficients were greater than or equal to 0.994 and coefficients of variation were less than or equal to 7.3%. In the regression analyses of manual versus semiautomated volume and spectroscopy versus MR imaging, PDFF slopes and intercepts were close to the identity line, and correlations of determination at multivariate analysis (R 2 ) ranged from 0.744 to 0.994. Conclusion This MR imaging-based, semiautomated method provides high repeatability and accuracy for estimating abdominal adipose tissue and thigh muscle volumes and hepatic PDFF. © RSNA, 2017.

Summary of retrospective asbestos and welding fume exposure estimates for a nuclear naval shipyard and their correlation with radiation exposure estimates.

PubMed

Zaebst, D D; Seel, E A; Yiin, J H; Nowlin, S J; Chen, P

2009-07-01

In support of a nested case-control study at a U.S. naval shipyard, the results of the reconstruction of historical exposures were summarized, and an analysis was undertaken to determine the impact of historical exposures to potential chemical confounders. The nested case-control study (N = 4388) primarily assessed the relationship between lung cancer and external ionizing radiation. Chemical confounders considered important were asbestos and welding fume (as iron oxide fume), and the chromium and nickel content of welding fume. Exposures to the potential confounders were estimated by an expert panel based on a set of quantitatively defined categories of exposure. Distributions of the estimated exposures and trends in exposures over time were examined for the study population. Scatter plots and Spearman rank correlation coefficients were used to assess the degree of association between the estimates of exposure to asbestos, welding fume, and ionizing radiation. Correlation coefficients were calculated separately for 0-, 15-, 20-, and 25-year time-lagged cumulative exposures, total radiation dose (which included medical X-ray dose) and occupational radiation dose. Exposed workers' estimated cumulative exposures to asbestos ranged from 0.01 fiber-days/cm(3) to just under 20,000 fiber-days/cm(3), with a median of 29.0 fiber-days/cm(3). Estimated cumulative exposures to welding fume ranged from 0.16 mg-days/m(3) to just over 30,000 mg-days/m(3), with a median of 603 mg-days/m(3). Spearman correlation coefficients between cumulative radiation dose and cumulative asbestos exposures ranged from 0.09 (occupational dose) to 0.47 (total radiation dose), and those between radiation and welding fume from 0.14 to 0.47. The estimates of relative risk for ionizing radiation and lung cancer were unchanged when lowest and highest estimates of asbestos and welding fume were considered. These results suggest a fairly large proportion of study population workers were exposed to asbestos and welding fume, that the absolute level of confounding exposure did not affect the risk estimates, and that weak relationships existed between monitored lifetime cumulative occupational radiation dose and asbestos or welding fume.

The Association Between Self-Rated Fitness and Cardiorespiratory Fitness in Adults.

PubMed

Jensen, Karina Gregersen; Rosthøj, Susanne; Linneberg, Allan; Aadahl, Mette

2018-06-01

To assess criterion validity of a single item question on self-rated physical fitness against objectively measured cardiorespiratory fitness. From the Health2008 study 749 men and women between 30 and 60 years of age rated their fitness as excellent, very good, good, fair or poor. Cardiorespiratory fitness was estimated with the watt-max test. Agreement between self-rated and objectively measured physical fitness was assessed by Cohen's weighted kappa coefficient. Correlation was determined by Goodman & Kruskal's gamma correlation coefficient. All analyses were stratified according to gender. Data from 323 men and 426 women were analysed. There was a slight agreement between self-rated and objectively measured fitness in men (weighted kappa: 0.18, [95%CI: 0.13;0.23]) and a fair agreement in women (weighted kappa: 0.27, [95%CI: 0.22;0.32]). In both genders, self-rated fitness was positively correlated with objectively measured fitness (moderate correlation; gamma correlation coefficient for men: 0.63 [95%CI: 0.54;0.72] and women: 0.67 [95%CI: 0.59;0.75]). There was a slight to fair agreement and moderate, positive correlations between self-rated physical fitness and watt-max estimated cardiorespiratory fitness. Hence, a single-item question on physical fitness may be a cost-effective method of assessing fitness in large population studies, but is not valid for individual assessments. © Georg Thieme Verlag KG Stuttgart · New York.

Reliability of the ecSatter Inventory as a tool to measure eating competence.

PubMed

Stotts, Jodi L; Lohse, Barbara

2007-01-01

To examine the reliability of the ecSatter Inventory (ecSI), a measure of eating competence. Self-report questionnaires were administered in person or by mail. Retesting occurred 2 to 6 weeks after completion of the first questionnaire. Both administrations of the questionnaire were completed by 259 participants who were mostly food secure, white females with some college education; mean age was 26.9 +/- 10.4 years. Test-retest reliability and internal consistency. Spearman's rank correlation coefficients to estimate test-retest reliability and Cronbach alpha coefficients to estimate internal consistency. Spearman's rank correlation coefficient for ecSI total score was 0.68; subscale coefficients were 0.70 for eating attitudes, 0.70 for contextual skills, 0.65 for food acceptance, and 0.52 for internal regulation. Cronbach alpha coefficient for ecSI total score was 0.77. Subscale alphas coefficients were 0.80 for eating attitudes, 0.69 for contextual skills, 0.68 for food acceptance, and 0.66 for internal regulation. This study provides psychometric evidence about the reliability of ecSI as a measure of eating competence in this sample. Although some ecSI items may require revision, results suggest that the instrument may be used to evaluate nutrition education designed to improve eating competence.

An interrater reliability study of the Braden scale in two nursing homes.

PubMed

Kottner, Jan; Dassen, Theo

2008-10-01

Adequate risk assessment is essential in pressure ulcer prevention. Assessment scales were designed to support practitioners in identifying persons at pressure ulcer risk. The Braden scale is one of the most extensively studied risk assessment instruments, although the majority of studies focused on validity rather than reliability. The first aim was to measure the interrater reliability of the Braden scale and its individual items. The second aim was to study different statistical approaches regarding interrater reliability estimation. An interrater reliability study was conducted in two German nursing homes. Residents (n = 152) from 8 units were assessed twice. The raters were trained nurses with a work experience ranging from 0.5 to 30 years. Data were analysed using an overall percentage of agreement, weighted and unweighted kappa and the intraclass correlation coefficient. Differences between nurses rating the overall Braden score ranged from 0 up to 9 points. Interrater reliability expressed by the intraclass correlation coefficient ranged from 0.73 (95% CI 0.26 - 0.91) to 0.95 (95% CI 0.87 - 0.98). Calculated intraclass correlation coefficients for individual items ranged from 0.06 (95% CI -0.31 to 0.48) to 0.97 (95% CI 0.93-0.99) with the lowest values being measured for the items "sensory perception" and "nutrition". There was no association between work experience and the level of interrater reliability. With two exceptions, simple kappa-values were always lower than weighted kappa-values and intraclass correlation coefficients. Although the calculated interrater reliability coefficients for the total Braden score were high in some cases, several clinically relevant differences occurred between the nurses. Due to interrater reliability being very low for the items "sensory perception" and "nutrition", it is doubtful if their assessment contributes to any valid results. The calculation of weighted kappa or intraclass correlation coefficients is the most appropriate interrater reliability estimates.

Estimation of positive semidefinite correlation matrices by using convex quadratic semidefinite programming.

PubMed

Fushiki, Tadayoshi

2009-07-01

The correlation matrix is a fundamental statistic that is used in many fields. For example, GroupLens, a collaborative filtering system, uses the correlation between users for predictive purposes. Since the correlation is a natural similarity measure between users, the correlation matrix may be used in the Gram matrix in kernel methods. However, the estimated correlation matrix sometimes has a serious defect: although the correlation matrix is originally positive semidefinite, the estimated one may not be positive semidefinite when not all ratings are observed. To obtain a positive semidefinite correlation matrix, the nearest correlation matrix problem has recently been studied in the fields of numerical analysis and optimization. However, statistical properties are not explicitly used in such studies. To obtain a positive semidefinite correlation matrix, we assume the approximate model. By using the model, an estimate is obtained as the optimal point of an optimization problem formulated with information on the variances of the estimated correlation coefficients. The problem is solved by a convex quadratic semidefinite program. A penalized likelihood approach is also examined. The MovieLens data set is used to test our approach.

Model for the partition of neutral compounds between n-heptane and formamide.

PubMed

Karunasekara, Thushara; Poole, Colin F

2010-04-01

Partition coefficients for 84 varied compounds were determined for n-heptane-formamide biphasic partition system and used to derive a model for the distribution of neutral compounds between the n-heptane-rich and formamide-rich layers. The partition coefficients, log K(p), were correlated through the solvation parameter model giving log K(p)=0.083+0.559E-2.244S-3.250A-1.614B+2.387V with a multiple correlation coefficient of 0.996, standard error of the estimate 0.139, and Fisher statistic 1791. In the model, the solute descriptors are excess molar refraction, E, dipolarity/polarizability, S, overall hydrogen-bond acidity, A, overall hydrogen-bond basicity, B, and McGowan's characteristic volume, V. The model is expected to be able to estimate further values of the partition coefficient to about 0.13 log units for the same descriptor space covered by the calibration compounds (E=-0.26-2.29, S=0-1.93, A=0-1.25, B=0.02-1.58, and V=0.78-2.50). The n-heptane-formamide partition system is shown to have different selectivity to other totally organic biphasic systems and to be suitable for estimating descriptor values for compounds of low water solubility and/or stability.

Effective gaseous diffusion coefficients of select ultra-fine, super-fine and medium grain nuclear graphite

DOE PAGES

Kane, Joshua J.; Matthews, Austin C.; Orme, Christopher J.; ...

2018-05-05

Understanding “Where?” and “How much?” oxidation has occurred in a nuclear graphite component is critical to predicting any deleterious effects to physical, mechanical, and thermal properties. A key factor in answering these questions is characterizing the effective mass transport rates of gas species in nuclear graphites. Effective gas diffusion coefficients were determined for twenty-six graphite specimens spanning six modern grades of nuclear graphite. A correlation was established for the majority of grades examined allowing a reasonable estimate of the effective diffusion coefficient to be determined purely from an estimate of total porosity. The importance of Knudsen diffusion to the measuredmore » diffusion coefficients is also shown for modern grades. Furthermore, Knudsen diffusion has not historically been considered to contribute to measured diffusion coefficients of nuclear graphite.« less

Effective gaseous diffusion coefficients of select ultra-fine, super-fine and medium grain nuclear graphite

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

Kane, Joshua J.; Matthews, Austin C.; Orme, Christopher J.

Understanding “Where?” and “How much?” oxidation has occurred in a nuclear graphite component is critical to predicting any deleterious effects to physical, mechanical, and thermal properties. A key factor in answering these questions is characterizing the effective mass transport rates of gas species in nuclear graphites. Effective gas diffusion coefficients were determined for twenty-six graphite specimens spanning six modern grades of nuclear graphite. A correlation was established for the majority of grades examined allowing a reasonable estimate of the effective diffusion coefficient to be determined purely from an estimate of total porosity. The importance of Knudsen diffusion to the measuredmore » diffusion coefficients is also shown for modern grades. Furthermore, Knudsen diffusion has not historically been considered to contribute to measured diffusion coefficients of nuclear graphite.« less

Development of reliable predictive heat transfer correlations for low-rank coal-fired fluid bed combustors. Final report

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

Grewal, N.S.

(1) The proposed correlation of Equation (5) is recommended to predict the maximum value of heat transfer coefficient between a horzontal tube and a gas-solid fluidized bed of small particles under the conditions given. For high temperature applications (T/sub B/ > 600/sup 0/C), the radiative component is important and was estimated following Baskakov et al. (2) The proposed correlation of Equation (8) was found reliable to predict the existing data on the maximum value of heat transfer coefficient between a horizontal tube bundle and a gas-solid fluidized bed of small particles under the conditions given. At high temperatures, the radiativemore » component was estimated from the experimental data of Baskakov et al. (3) The correlation of Equation (8) predicted the GFETC data taken during the combustion of low-rank coal very well, when the contribution due to radiation was estimated following Baskakov et al. (4) The correlations proposed by Grewal and Bansal et al. were found to predict the data taken during low-rank coal combustion within +-25%, when the contribution due to radiation was included and estimated following Baskakov et al. (5) Finally, the correlations for large particles (anti d/sub p/ > 1mm) as proposed by Glicksman and Decker, Catipovic et al., Xavier and Davidson, and Zabrodsky et al. also predicted the data for low-rank coal fluidized bed combustor quite well, when the radiative component was estimated from the data of Baskakov et al. 64 references, 19 figures, 10 tables.« less

Estimation of population mean under systematic sampling

NASA Astrophysics Data System (ADS)

Noor-ul-amin, Muhammad; Javaid, Amjad

2017-11-01

In this study we propose a generalized ratio estimator under non-response for systematic random sampling. We also generate a class of estimators through special cases of generalized estimator using different combinations of coefficients of correlation, kurtosis and variation. The mean square errors and mathematical conditions are also derived to prove the efficiency of proposed estimators. Numerical illustration is included using three populations to support the results.

Rapid Contour-based Segmentation for 18F-FDG PET Imaging of Lung Tumors by Using ITK-SNAP: Comparison to Expert-based Segmentation.

PubMed

Besson, Florent L; Henry, Théophraste; Meyer, Céline; Chevance, Virgile; Roblot, Victoire; Blanchet, Elise; Arnould, Victor; Grimon, Gilles; Chekroun, Malika; Mabille, Laurence; Parent, Florence; Seferian, Andrei; Bulifon, Sophie; Montani, David; Humbert, Marc; Chaumet-Riffaud, Philippe; Lebon, Vincent; Durand, Emmanuel

2018-04-03

Purpose To assess the performance of the ITK-SNAP software for fluorodeoxyglucose (FDG) positron emission tomography (PET) segmentation of complex-shaped lung tumors compared with an optimized, expert-based manual reference standard. Materials and Methods Seventy-six FDG PET images of thoracic lesions were retrospectively segmented by using ITK-SNAP software. Each tumor was manually segmented by six raters to generate an optimized reference standard by using the simultaneous truth and performance level estimate algorithm. Four raters segmented 76 FDG PET images of lung tumors twice by using ITK-SNAP active contour algorithm. Accuracy of ITK-SNAP procedure was assessed by using Dice coefficient and Hausdorff metric. Interrater and intrarater reliability were estimated by using intraclass correlation coefficients of output volumes. Finally, the ITK-SNAP procedure was compared with currently recommended PET tumor delineation methods on the basis of thresholding at 41% volume of interest (VOI; VOI 41 ) and 50% VOI (VOI 50 ) of the tumor's maximal metabolism intensity. Results Accuracy estimates for the ITK-SNAP procedure indicated a Dice coefficient of 0.83 (95% confidence interval: 0.77, 0.89) and a Hausdorff distance of 12.6 mm (95% confidence interval: 9.82, 15.32). Interrater reliability was an intraclass correlation coefficient of 0.94 (95% confidence interval: 0.91, 0.96). The intrarater reliabilities were intraclass correlation coefficients above 0.97. Finally, VOI 41 and VOI 50 accuracy metrics were as follows: Dice coefficient, 0.48 (95% confidence interval: 0.44, 0.51) and 0.34 (95% confidence interval: 0.30, 0.38), respectively, and Hausdorff distance, 25.6 mm (95% confidence interval: 21.7, 31.4) and 31.3 mm (95% confidence interval: 26.8, 38.4), respectively. Conclusion ITK-SNAP is accurate and reliable for active-contour-based segmentation of heterogeneous thoracic PET tumors. ITK-SNAP surpassed the recommended PET methods compared with ground truth manual segmentation. © RSNA, 2018.

Robust spectral-domain optical coherence tomography speckle model and its cross-correlation coefficient analysis

PubMed Central

Liu, Xuan; Ramella-Roman, Jessica C.; Huang, Yong; Guo, Yuan; Kang, Jin U.

2013-01-01

In this study, we proposed 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 validated our model and used the simulation method to study the statistical properties of cross-correlation coefficients (XCC) between Ascans which have been recently applied in transverse motion analysis by our group. The results of simulation show that over sampling is essential for accurate motion tracking; exponential decay of OCT signal leads to an under estimate of motion which can be corrected; lateral heterogeneity of sample leads to an over estimate of motion for a few pixels corresponding to the structural boundary. PMID:23456001

Determination of suitable drying curve model for bread moisture loss during baking

NASA Astrophysics Data System (ADS)

Soleimani Pour-Damanab, A. R.; Jafary, A.; Rafiee, S.

2013-03-01

This study presents mathematical modelling of bread moisture loss or drying during baking in a conventional bread baking process. In order to estimate and select the appropriate moisture loss curve equation, 11 different models, semi-theoretical and empirical, were applied to the experimental data and compared according to their correlation coefficients, chi-squared test and root mean square error which were predicted by nonlinear regression analysis. Consequently, of all the drying models, a Page model was selected as the best one, according to the correlation coefficients, chi-squared test, and root mean square error values and its simplicity. Mean absolute estimation error of the proposed model by linear regression analysis for natural and forced convection modes was 2.43, 4.74%, respectively.

Assessment of the reliability of protein-protein interactions and protein function prediction.

PubMed

Deng, Minghua; Sun, Fengzhu; Chen, Ting

2003-01-01

As more and more high-throughput protein-protein interaction data are collected, the task of estimating the reliability of different data sets becomes increasingly important. In this paper, we present our study of two groups of protein-protein interaction data, the physical interaction data and the protein complex data, and estimate the reliability of these data sets using three different measurements: (1) the distribution of gene expression correlation coefficients, (2) the reliability based on gene expression correlation coefficients, and (3) the accuracy of protein function predictions. We develop a maximum likelihood method to estimate the reliability of protein interaction data sets according to the distribution of correlation coefficients of gene expression profiles of putative interacting protein pairs. The results of the three measurements are consistent with each other. The MIPS protein complex data have the highest mean gene expression correlation coefficients (0.256) and the highest accuracy in predicting protein functions (70% sensitivity and specificity), while Ito's Yeast two-hybrid data have the lowest mean (0.041) and the lowest accuracy (15% sensitivity and specificity). Uetz's data are more reliable than Ito's data in all three measurements, and the TAP protein complex data are more reliable than the HMS-PCI data in all three measurements as well. The complex data sets generally perform better in function predictions than do the physical interaction data sets. Proteins in complexes are shown to be more highly correlated in gene expression. The results confirm that the components of a protein complex can be assigned to functions that the complex carries out within a cell. There are three interaction data sets different from the above two groups: the genetic interaction data, the in-silico data and the syn-express data. Their capability of predicting protein functions generally falls between that of the Y2H data and that of the MIPS protein complex data. The supplementary information is available at the following Web site: http://www-hto.usc.edu/-msms/AssessInteraction/.

Relative validity of an FFQ to estimate daily food and nutrient intakes for Chilean adults.

PubMed

Dehghan, Mahshid; Martinez, Solange; Zhang, Xiaohe; Seron, Pamela; Lanas, Fernando; Islam, Shofiqul; Merchant, Anwar T

2013-10-01

FFQ are commonly used to rank individuals by their food and nutrient intakes in large epidemiological studies. The purpose of the present study was to develop and validate an FFQ to rank individuals participating in an ongoing Prospective Urban and Rural Epidemiological (PURE) study in Chile. An FFQ and four 24 h dietary recalls were completed over 1 year. Pearson correlation coefficients, energy-adjusted and de-attenuated correlations and weighted kappa were computed between the dietary recalls and the FFQ. The level of agreement between the two dietary assessment methods was evaluated by Bland-Altman analysis. Temuco, Chile. Overall, 166 women and men enrolled in the present study. One hundred men and women participated in FFQ development and sixty-six individuals participated in FFQ validation. The FFQ consisted of 109 food items. For nutrients, the crude correlation coefficients between the dietary recalls and FFQ varied from 0.14 (protein) to 0.44 (fat). Energy adjustment and de-attenuation improved correlation coefficients and almost all correlation coefficients exceeded 0.40. Similar correlation coefficients were observed for food groups; the highest de-attenuated energy adjusted correlation coefficient was found for margarine and butter (0.75) and the lowest for potatoes (0.12). The FFQ showed moderate to high agreement for most nutrients and food groups, and can be used to rank individuals based on energy, nutrient and food intakes. The validation study was conducted in a unique setting and indicated that the tool is valid for use by adults in Chile.

The Yale-Brown Obsessive Compulsive Scale: A Reliability Generalization Meta-Analysis.

PubMed

López-Pina, José Antonio; Sánchez-Meca, Julio; López-López, José Antonio; Marín-Martínez, Fulgencio; Núñez-Núñez, Rosa Maria; Rosa-Alcázar, Ana I; Gómez-Conesa, Antonia; Ferrer-Requena, Josefa

2015-10-01

The Yale-Brown Obsessive Compulsive Scale (Y-BOCS) is the most frequently applied test to assess obsessive compulsive symptoms. We conducted a reliability generalization meta-analysis on the Y-BOCS to estimate the average reliability, examine the variability among the reliability estimates, search for moderators, and propose a predictive model that researchers and clinicians can use to estimate the expected reliability of the Y-BOCS. We included studies where the Y-BOCS was applied to a sample of adults and reliability estimate was reported. Out of the 11,490 references located, 144 studies met the selection criteria. For the total scale, the mean reliability was 0.866 for coefficients alpha, 0.848 for test-retest correlations, and 0.922 for intraclass correlations. The moderator analyses led to a predictive model where the standard deviation of the total test and the target population (clinical vs. nonclinical) explained 38.6% of the total variability among coefficients alpha. Finally, clinical implications of the results are discussed. © The Author(s) 2014.

Manure sampling procedures and nutrient estimation by the hydrometer method for gestation pigs.

PubMed

Zhu, Jun; Ndegwa, Pius M; Zhang, Zhijian

2004-05-01

Three manure agitation procedures were examined in this study (vertical mixing, horizontal mixing, and no mixing) to determine the efficacy of producing a representative manure sample. The total solids content for manure from gestation pigs was found to be well correlated with the total nitrogen (TN) and total phosphorus (TP) concentrations in the manure, with highly significant correlation coefficients of 0.988 and 0.994, respectively. Linear correlations were observed between the TN and TP contents and the manure specific gravity (correlation coefficients: 0.991 and 0.987, respectively). Therefore, it may be inferred that the nutrients in pig manure can be estimated with reasonable accuracy by measuring the liquid manure specific gravity. A rapid testing method for manure nutrient contents (TN and TP) using a soil hydrometer was also evaluated. The results showed that the estimating error increased from +/-10% to +/-30% with the decrease in TN (from 1000 to 100 ppm) and TP (from 700 to 50 ppm) concentrations in the manure. Data also showed that the hydrometer readings had to be taken within 10 s after mixing to avoid reading drift in specific gravity due to the settling of manure solids.

MO-E-17A-08: Attenuation-Based Size Adjusted, Scanner-Independent Organ Dose Estimates for Head CT Exams: TG 204 for Head CT

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

McMillan, K; Bostani, M; Cagnon, C

Purpose: AAPM Task Group 204 described size specific dose estimates (SSDE) for body scans. The purpose of this work is to use a similar approach to develop patient-specific, scanner-independent organ dose estimates for head CT exams using an attenuation-based size metric. Methods: For eight patient models from the GSF family of voxelized phantoms, dose to brain and lens of the eye was estimated using Monte Carlo simulations of contiguous axial scans for 64-slice MDCT scanners from four major manufacturers. Organ doses were normalized by scannerspecific 16 cm CTDIvol values and averaged across all scanners to obtain scanner-independent CTDIvol-to-organ-dose conversion coefficientsmore » for each patient model. Head size was measured at the first slice superior to the eyes; patient perimeter and effective diameter (ED) were measured directly from the GSF data. Because the GSF models use organ identification codes instead of Hounsfield units, water equivalent diameter (WED) was estimated indirectly. Using the image data from 42 patients ranging from 2 weeks old to adult, the perimeter, ED and WED size metrics were obtained and correlations between each metric were established. Applying these correlations to the GSF perimeter and ED measurements, WED was calculated for each model. The relationship between the various patient size metrics and CTDIvol-to-organ-dose conversion coefficients was then described. Results: The analysis of patient images demonstrated the correlation between WED and ED across a wide range of patient sizes. When applied to the GSF patient models, an exponential relationship between CTDIvol-to-organ-dose conversion coefficients and the WED size metric was observed with correlation coefficients of 0.93 and 0.77 for the brain and lens of the eye, respectively. Conclusion: Strong correlation exists between CTDIvol normalized brain dose and WED. For the lens of the eye, a lower correlation is observed, primarily due to surface dose variations. Funding Support: Siemens-UCLA Radiology Master Research Agreement; Disclosures - Michael McNitt-Gray: Institutional Research Agreement, Siemens AG; Research Support, Siemens AG; Consultant, Flaherty Sensabaugh Bonasso PLLC; Consultant, Fulbright and Jaworski.« less

The Evolution of Human Intelligence and the Coefficient of Additive Genetic Variance in Human Brain Size

ERIC Educational Resources Information Center

Miller, Geoffrey F.; Penke, Lars

2007-01-01

Most theories of human mental evolution assume that selection favored higher intelligence and larger brains, which should have reduced genetic variance in both. However, adult human intelligence remains highly heritable, and is genetically correlated with brain size. This conflict might be resolved by estimating the coefficient of additive genetic…

Assessment of Thematic Mapper Band-to-band Registration by the Block Correlation Method

NASA Technical Reports Server (NTRS)

Card, D. H.; Wrigley, R. C.; Mertz, F. C.; Hall, J. R.

1984-01-01

The design of the Thematic Mapper (TM) multispectral radiometer makes it susceptible to band-to-band misregistration. To estimate band-to-band misregistration a block correlation method is employed. This method is chosen over other possible techniques (band differencing and flickering) because quantitative results are produced. The method correlates rectangular blocks of pixels from one band against blocks centered on identical pixels from a second band. The block pairs are shifted in pixel increments both vertically and horizontally with respect to each other and the correlation coefficient for each shift position is computed. The displacement corresponding to the maximum correlation is taken as the best estimate of registration error for each block pair. Subpixel shifts are estimated by a bi-quadratic interpolation of the correlation values surrounding the maximum correlation. To obtain statistical summaries for each band combination post processing of the block correlation results performed. The method results in estimates of registration error that are consistent with expectations.

More accurate, calibrated bootstrap confidence intervals for correlating two autocorrelated climate time series

NASA Astrophysics Data System (ADS)

Olafsdottir, Kristin B.; Mudelsee, Manfred

2013-04-01

Estimation of the Pearson's correlation coefficient between two time series to evaluate the influences of one time depended variable on another is one of the most often used statistical method in climate sciences. Various methods are used to estimate confidence interval to support the correlation point estimate. Many of them make strong mathematical assumptions regarding distributional shape and serial correlation, which are rarely met. More robust statistical methods are needed to increase the accuracy of the confidence intervals. Bootstrap confidence intervals are estimated in the Fortran 90 program PearsonT (Mudelsee, 2003), where the main intention was to get an accurate confidence interval for correlation coefficient between two time series by taking the serial dependence of the process that generated the data into account. However, Monte Carlo experiments show that the coverage accuracy for smaller data sizes can be improved. Here we adapt the PearsonT program into a new version called PearsonT3, by calibrating the confidence interval to increase the coverage accuracy. Calibration is a bootstrap resampling technique, which basically performs a second bootstrap loop or resamples from the bootstrap resamples. It offers, like the non-calibrated bootstrap confidence intervals, robustness against the data distribution. Pairwise moving block bootstrap is used to preserve the serial correlation of both time series. The calibration is applied to standard error based bootstrap Student's t confidence intervals. The performances of the calibrated confidence intervals are examined with Monte Carlo simulations, and compared with the performances of confidence intervals without calibration, that is, PearsonT. The coverage accuracy is evidently better for the calibrated confidence intervals where the coverage error is acceptably small (i.e., within a few percentage points) already for data sizes as small as 20. One form of climate time series is output from numerical models which simulate the climate system. The method is applied to model data from the high resolution ocean model, INALT01 where the relationship between the Agulhas Leakage and the North Brazil Current is evaluated. Preliminary results show significant correlation between the two variables when there is 10 year lag between them, which is more or less the time that takes the Agulhas Leakage water to reach the North Brazil Current. Mudelsee, M., 2003. Estimating Pearson's correlation coefficient with bootstrap confidence interval from serially dependent time series. Mathematical Geology 35, 651-665.

Comparison between uroflowmetry and sonouroflowmetry in recording of urinary flow in healthy men.

PubMed

Krhut, Jan; Gärtner, Marcel; Sýkora, Radek; Hurtík, Petr; Burda, Michal; Luňáček, Libor; Zvarová, Katarína; Zvara, Peter

2015-08-01

To evaluate the accuracy of sonouroflowmetry in recording urinary flow parameters and voided volume. A total of 25 healthy male volunteers (age 18-63 years) were included in the study. All participants were asked to carry out uroflowmetry synchronous with recording of the sound generated by the urine stream hitting the water level in the urine collection receptacle, using a dedicated cell phone. From 188 recordings, 34 were excluded, because of voided volume <150 mL or technical problems during recording. Sonouroflowmetry recording was visualized in a form of a trace, representing sound intensity over time. Subsequently, the matching datasets of uroflowmetry and sonouroflowmetry were compared with respect to flow time, voided volume, maximum flow rate and average flow rate. Pearson's correlation coefficient was used to compare parameters recorded by uroflowmetry with those calculated based on sonouroflowmetry recordings. The flow pattern recorded by sonouroflowmetry showed a good correlation with the uroflowmetry trace. A strong correlation (Pearson's correlation coefficient 0.87) was documented between uroflowmetry-recorded flow time and duration of the sound signal recorded with sonouroflowmetry. A moderate correlation was observed in voided volume (Pearson's correlation coefficient 0.68) and average flow rate (Pearson's correlation coefficient 0.57). A weak correlation (Pearson's correlation coefficient 0.38) between maximum flow rate recorded using uroflowmetry and sonouroflowmetry-recorded peak sound intensity was documented. The present study shows that the basic concept utilizing sound analysis for estimation of urinary flow parameters and voided volume is valid. However, further development of this technology and standardization of recording algorithm are required. © 2015 The Japanese Urological Association.

Reliability of environmental sampling culture results using the negative binomial intraclass correlation coefficient.

PubMed

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.

Cavitation in liquid cryogens. 3: Ogives

NASA Technical Reports Server (NTRS)

Hord, J.

1973-01-01

Experimental results for three, scaled, quarter-caliber ogives are given. Both desinent and developed cavity data, using liquid hydrogen and liquid nitrogen, are reported. The desinent data do not exhibit a consistent ogive size effect, but the developed cavity data were consistently influenced by ogive size; B-factor increases with increasing ogive diameter. The developed cavity data indicated that stable thermodynamic equilibrium exists throughout the vaporous cavities. These data were correlated by using the extended theory derived in NASA-CR-2156 (volume II of this report series). The new correlating parameter MTWO, improves data correlation for the ogives, hydrofoil, and venturi and appears attractive for future predictive applications. The cavitation coefficient and equipment size effects are shown to vary with specific equipment-fluid combinations. A method of estimating cavitation coefficient from knowledge of the noncavitating pressure coefficient is suggested.

A quantitative property-property relationship for the internal diffusion coefficients of organic compounds in solid materials.

PubMed

Huang, L; Fantke, P; Ernstoff, A; Jolliet, O

2017-11-01

Indoor releases of organic chemicals encapsulated in solid materials are major contributors to human exposures and are directly related to the internal diffusion coefficient in solid materials. Existing correlations to estimate the diffusion coefficient are only valid for a limited number of chemical-material combinations. This paper develops and evaluates a quantitative property-property relationship (QPPR) to predict diffusion coefficients for a wide range of organic chemicals and materials. We first compiled a training dataset of 1103 measured diffusion coefficients for 158 chemicals in 32 consolidated material types. Following a detailed analysis of the temperature influence, we developed a multiple linear regression model to predict diffusion coefficients as a function of chemical molecular weight (MW), temperature, and material type (adjusted R 2 of .93). The internal validations showed the model to be robust, stable and not a result of chance correlation. The external validation against two separate prediction datasets demonstrated the model has good predicting ability within its applicability domain (Rext2>.8), namely MW between 30 and 1178 g/mol and temperature between 4 and 180°C. By covering a much wider range of organic chemicals and materials, this QPPR facilitates high-throughput estimates of human exposures for chemicals encapsulated in solid materials. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Validity of gestational age estimates by last menstrual period and neonatal examination compared to ultrasound in Vietnam.

PubMed

Deputy, Nicholas P; Nguyen, Phuong H; Pham, Hoa; Nguyen, Son; Neufeld, Lynnette; Martorell, Reynaldo; Ramakrishnan, Usha

2017-01-11

Accurate estimation of gestational age is important for both clinical and public health purposes. Estimates of gestational age using fetal ultrasound measurements are considered most accurate but are frequently unavailable in low- and middle-income countries. The objective of this study was to assess the validity of last menstrual period and Farr neonatal examination estimates of gestational age, compared to ultrasound estimates, in a large cohort of women in Vietnam. Data for this analysis come from a randomized, placebo-controlled micronutrient supplementation trial in Vietnam. We analyzed 912 women with ultrasound and prospectively-collected last menstrual period estimates of gestational age and 685 women with ultrasound and Farr estimates of gestational age. We used the Wilcoxon signed rank sum test to assess differences in gestational age estimated by last menstrual period or Farr examination compared to ultrasound and computed the intraclass correlation coefficient (ICC) and concordance correlation coefficient (CCC) to quantify agreement between methods. We computed the Kappa coefficient (κ) to quantify agreement in preterm, term and post-term classification. The median gestational age estimated by ultrasound was 273.9 days. Gestational age was slightly overestimated by last menstrual period (median 276.0 days, P < 0.001) and more greatly overestimated by Farr examination (median 286.7 days, P < 0.001). Gestational age estimates by last menstrual period and ultrasound were moderately correlated (ICC = 0.78) and concordant (CCC = 0.63), whereas gestational age estimates by Farr examination and ultrasound were weakly correlated (ICC = 0.26) and concordant (CCC = 0.05). Last menstrual period and ultrasound estimates of gestational age were within ± 14 days for 88.4% of women; Farr and ultrasound estimates were within ± 14 days for 55.8% of women. Last menstrual period and ultrasound estimates of gestational age had higher agreement in term classification (κ = 0.41) than Farr and ultrasound (κ = 0.05). In this study of women in Vietnam, we found last menstrual period provided a more accurate estimate of gestational age than the Farr examination when compared to ultrasound. These findings provide useful information about the utility and accuracy of different methods to estimate gestational age and suggest last menstrual period may be preferred over Farr examination in settings where ultrasound is unavailable. The trial was registered at ClinicalTrials.Gov as NCT01665378 on August 13, 2012.

A short note on jackknifing the concordance correlation coefficient.

PubMed

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. Copyright © 2013 John Wiley & Sons, Ltd.

Prediction of Partition Coefficients of Organic Compounds between SPME/PDMS and Aqueous Solution

PubMed Central

Chao, Keh-Ping; Lu, Yu-Ting; Yang, Hsiu-Wen

2014-01-01

Polydimethylsiloxane (PDMS) is commonly used as the coated polymer in the solid phase microextraction (SPME) technique. In this study, the partition coefficients of organic compounds between SPME/PDMS and the aqueous solution were compiled from the literature sources. The correlation analysis for partition coefficients was conducted to interpret the effect of their physicochemical properties and descriptors on the partitioning process. The PDMS-water partition coefficients were significantly correlated to the polarizability of organic compounds (r = 0.977, p < 0.05). An empirical model, consisting of the polarizability, the molecular connectivity index, and an indicator variable, was developed to appropriately predict the partition coefficients of 61 organic compounds for the training set. The predictive ability of the empirical model was demonstrated by using it on a test set of 26 chemicals not included in the training set. The empirical model, applying the straightforward calculated molecular descriptors, for estimating the PDMS-water partition coefficient will contribute to the practical applications of the SPME technique. PMID:24534804

Prediction of random-regression coefficient for daily milk yield after 305 days in milk by using the regression-coefficient estimates from the first 305 days.

PubMed

Yamazaki, Takeshi; Takeda, Hisato; Hagiya, Koichi; Yamaguchi, Satoshi; Sasaki, Osamu

2018-03-13

Because lactation periods in dairy cows lengthen with increasing total milk production, it is important to predict individual productivities after 305 days in milk (DIM) to determine the optimal lactation period. We therefore examined whether the random regression (RR) coefficient from 306 to 450 DIM (M2) can be predicted from those during the first 305 DIM (M1) by using a random regression model. We analyzed test-day milk records from 85690 Holstein cows in their first lactations and 131727 cows in their later (second to fifth) lactations. Data in M1 and M2 were analyzed separately by using different single-trait RR animal models. We then performed a multiple regression analysis of the RR coefficients of M2 on those of M1 during the first and later lactations. The first-order Legendre polynomials were practical covariates of random regression for the milk yields of M2. All RR coefficients for the additive genetic (AG) effect and the intercept for the permanent environmental (PE) effect of M2 had moderate to strong correlations with the intercept for the AG effect of M1. The coefficients of determination for multiple regression of the combined intercepts for the AG and PE effects of M2 on the coefficients for the AG effect of M1 were moderate to high. The daily milk yields of M2 predicted by using the RR coefficients for the AG effect of M1 were highly correlated with those obtained by using the coefficients of M2. Milk production after 305 DIM can be predicted by using the RR coefficient estimates of the AG effect during the first 305 DIM.

Laboratory Experiments and Modeling of Pooled NAPL Dissolution in Porous Media

NASA Astrophysics Data System (ADS)

Copty, N. K.; Sarikurt, D. A.; Gokdemir, C.

2017-12-01

The dissolution of non-aqueous phase liquids (NAPLs) entrapped in porous media is commonly modeled at the continuum scale as the product of a chemical potential and an interphase mass transfer coefficient, the latter expressed in terms of Sherwood correlations that are related to flow and porous media properties. Because of the lack of precise estimates of the interface area separating the NAPL and aqueous phase, numerous studies have lumped the interfacial area into the interphase mass transfer coefficient. In this paper controlled dissolution experiments from a pooled NAPL were conducted. The immobile NAPL mass is placed at the bottom of a flow cell filled with porous media with water flowing on top. Effluent aqueous phase concentrations were measured for a wide range of aqueous phase velocities and for two types of porous media. To interpret the experimental results, a two-dimensional pore network model of the NAPL dissolution was developed. The well-defined geometry of the NAPL-water interface and the observed effluent concentrations were used to compute best-fit mass transfer coefficients and non-lumped Sherwood correlations. Comparing the concentrations predicted with the pore network model to simple previously used one-dimensional analytic solutions indicates that the analytic model which ignores the transverse dispersion can lead to over-estimation of the mass transfer coefficient. The predicted Sherwood correlations are also compared to previously published data and implications on NAPL remediation strategies are discussed.

Comparative analysis of the 1-mile run test evaluation formulae: assessment of aerobic capacity in male law enforcement officers aged 20-23 years.

PubMed

Kayihan, Gürhan; Özkan, Ali; Köklü, Yusuf; Eyuboğlu, Ender; Akça, Firat; Koz, Mitat; Ersöz, Gülfem

2014-04-01

The purpose of this study was to compare values of aerobic performance in the 1-mile run test (1-MRT) using different formulae. Aerobic capacities of 351 male volunteers working for the Turkish National Police within the age range of 20-23 years were evaluated by the 1-MRT and the 20-metre shuttle run (20-MST). VO2max values were estimated by the prediction equations developed by George et al. (1993), Cureton et al. (1995) and Kline et al. (1987) for the 1-MRT and by Leger and Lambert (1982) for the 20-MST. The difference between the results of the different formulae was significant (p = 0.000). The correlation coefficient between the estimated VO2max using Cureton's equation, George's equation, Kline's equation and the 20-MST were 0.691 (p < 0.001), 0.486 (p < 0.001) and 0.608 (p < 0.001), respectively. The highest correlation coefficient was between the VO2max estimated by the 20-MST and Cureton's equation. Similarly, the highest correlation coefficient (r = -0.779) was between the 1-mile run time and the VO2max estimated by Cureton's equation. When analysing more vigorous exercise than sub-maximal exercise, we suggest that Cureton's equation be used to predict the VO2max from 1-mile run/walk performance in large numbers of healthy individuals with high VO2max. This research compares the use of 3 different formulae to estimate VO2max from 1-mile run/walk performance in male law enforcement officers aged 20-23 years for the first time and reports the most accurate formula to use when evaluating aerobic capacities of large numbers of healthy individuals.

[Estimators of internal consistency in health research: the use of the alpha coefficient].

PubMed

da Silva, Franciele Cascaes; Gonçalves, Elizandra; Arancibia, Beatriz Angélica Valdivia; Bento, Gisele Graziele; Castro, Thiago Luis da Silva; Hernandez, Salma Stephany Soleman; da Silva, Rudney

2015-01-01

Academic production has increased in the area of health, increasingly demanding high quality in publications of great impact. One of the ways to consider quality is through methods that increase the consistency of data analysis, such as reliability which, depending on the type of data, can be evaluated by different coefficients, especially the alpha coefficient. Based on this, the present review systematically gathers scientific articles produced in the last five years, which in a methodological manner gave the α coefficient psychometric use as an estimator of internal consistency and reliability in the processes of construction, adaptation and validation of instruments. The identification of the studies was conducted systematically in the databases BioMed Central Journals, Web of Science, Wiley Online Library, Medline, SciELO, Scopus, Journals@Ovid, BMJ and Springer, using inclusion and exclusion criteria. Data analyses were performed by means of triangulation, content analysis and descriptive analysis. It was found that most studies were conducted in Iran (f=3), Spain (f=2) and Brazil (f=2). These studies aimed to test the psychometric properties of instruments, with eight studies using the α coefficient to assess reliability and nine for assessing internal consistency. All studies were classified as methodological research when their objectives were analyzed. In addition, four studies were also classified as correlational and one as descriptive-correlational. It can be concluded that though the α coefficient is widely used as one of the main parameters for assessing internal consistency of questionnaires in health sciences, its use as an estimator of trust of the methodology used and internal consistency has some critiques that should be considered.

Application of lag-k autocorrelation coefficient and the TGA signals approach to detecting and quantifying adulterations of extra virgin olive oil with inferior edible oils.

PubMed

Torrecilla, José S; García, Julián; García, Silvia; Rodríguez, Francisco

2011-03-04

The combination of lag-k autocorrelation coefficients (LCCs) and thermogravimetric analyzer (TGA) equipment is defined here as a tool to detect and quantify adulterations of extra virgin olive oil (EVOO) with refined olive (ROO), refined olive pomace (ROPO), sunflower (SO) or corn (CO) oils, when the adulterating agents concentration are less than 14%. The LCC is calculated from TGA scans of adulterated EVOO samples. Then, the standardized skewness of this coefficient has been applied to classify pure and adulterated samples of EVOO. In addition, this chaotic parameter has also been used to quantify the concentration of adulterant agents, by using successful linear correlation of LCCs and ROO, ROPO, SO or CO in 462 EVOO adulterated samples. In the case of detection, more than 82% of adulterated samples have been correctly classified. In the case of quantification of adulterant concentration, by an external validation process, the LCC/TGA approach estimates the adulterant agents concentration with a mean correlation coefficient (estimated versus real adulterant agent concentration) greater than 0.90 and a mean square error less than 4.9%. Copyright © 2011 Elsevier B.V. All rights reserved.

Epidural Catheter Placement in Morbidly Obese Parturients with the Use of an Epidural Depth Equation prior to Ultrasound Visualization

PubMed Central

Singh, Sukhdip; Wirth, Keith M.; Phelps, Amy L.; Badve, Manasi H.; Shah, Tanmay H.; Vallejo, Manuel C.

2013-01-01

Background. Previously, Balki determined the Pearson correlation coefficient with the use of ultrasound (US) was 0.85 in morbidly obese parturients. We aimed to determine if the use of the epidural depth equation (EDE) in conjunction with US can provide better clinical correlation in estimating the distance from the skin to the epidural space in morbidly obese parturients. Methods. One hundred sixty morbidly obese (≥40 kg/m2) parturients requesting labor epidural analgesia were enrolled. Before epidural catheter placement, EDE was used to estimate depth to the epidural space. This estimation was used to help visualize the epidural space with the transverse and midline longitudinal US views and to measure depth to epidural space. The measured epidural depth was made available to the resident trainee before needle insertion. Actual needle depth (ND) to the epidural space was recorded. Results. Pearson's correlation coefficients comparing actual (ND) versus US estimated depth to the epidural space in the longitudinal median and transverse planes were 0.905 (95% CI: 0.873 to 0.929) and 0.899 (95% CI: 0.865 to 0.925), respectively. Conclusion. Use of the epidural depth equation (EDE) in conjunction with the longitudinal and transverse US views results in better clinical correlation than with the use of US alone. PMID:23983645

Validation of the Regicor Short Physical Activity Questionnaire for the Adult Population

PubMed Central

Molina, Luis; Sarmiento, Manuel; Peñafiel, Judith; Donaire, David; Garcia-Aymerich, Judith; Gomez, Miquel; Ble, Mireia; Ruiz, Sonia; Frances, Albert; Schröder, Helmut; Marrugat, Jaume; Elosua, Roberto

2017-01-01

Objective To develop and validate a short questionnaire to estimate physical activity (PA) practice and sedentary behavior for the adult population. Methods The short questionnaire was developed using data from a cross-sectional population-based survey (n = 6352) that included the Minnesota leisure-time PA questionnaire. Activities that explained a significant proportion of the variability of population PA practice were identified. Validation of the short questionnaire included a cross-sectional component to assess validity with respect to the data collected by accelerometers and a longitudinal component to assess reliability and sensitivity to detect changes (n = 114, aged 35 to 74 years). Results Six types of activities that accounted for 87% of population variability in PA estimated with the Minnesota questionnaire were selected. The short questionnaire estimates energy expenditure in total PA and by intensity (light, moderate, vigorous), and includes 2 questions about sedentary behavior and a question about occupational PA. The short questionnaire showed high reliability, with intraclass correlation coefficients ranging between 0.79 to 0.95. The Spearman correlation coefficients between estimated energy expenditure obtained with the questionnaire and the number of steps detected by the accelerometer were as follows: 0.36 for total PA, 0.40 for moderate intensity, and 0.26 for vigorous intensity. The questionnaire was sensitive to detect changes in moderate and vigorous PA (correlation coefficients ranging from 0.26 to 0.34). Conclusion The REGICOR short questionnaire is reliable, valid, and sensitive to detect changes in moderate and vigorous PA. This questionnaire could be used in daily clinical practice and epidemiological studies. PMID:28085886

Gaussian graphical modeling reconstructs pathway reactions from high-throughput metabolomics data

PubMed Central

2011-01-01

Background With the advent of high-throughput targeted metabolic profiling techniques, the question of how to interpret and analyze the resulting vast amount of data becomes more and more important. In this work we address the reconstruction of metabolic reactions from cross-sectional metabolomics data, that is without the requirement for time-resolved measurements or specific system perturbations. Previous studies in this area mainly focused on Pearson correlation coefficients, which however are generally incapable of distinguishing between direct and indirect metabolic interactions. Results In our new approach we propose the application of a Gaussian graphical model (GGM), an undirected probabilistic graphical model estimating the conditional dependence between variables. GGMs are based on partial correlation coefficients, that is pairwise Pearson correlation coefficients conditioned against the correlation with all other metabolites. We first demonstrate the general validity of the method and its advantages over regular correlation networks with computer-simulated reaction systems. Then we estimate a GGM on data from a large human population cohort, covering 1020 fasting blood serum samples with 151 quantified metabolites. The GGM is much sparser than the correlation network, shows a modular structure with respect to metabolite classes, and is stable to the choice of samples in the data set. On the example of human fatty acid metabolism, we demonstrate for the first time that high partial correlation coefficients generally correspond to known metabolic reactions. This feature is evaluated both manually by investigating specific pairs of high-scoring metabolites, and then systematically on a literature-curated model of fatty acid synthesis and degradation. Our method detects many known reactions along with possibly novel pathway interactions, representing candidates for further experimental examination. Conclusions In summary, we demonstrate strong signatures of intracellular pathways in blood serum data, and provide a valuable tool for the unbiased reconstruction of metabolic reactions from large-scale metabolomics data sets. PMID:21281499

The Free-Free Absorption Coefficients of the Negative Helium Ion

NASA Astrophysics Data System (ADS)

John, T. L.

1994-08-01

Free-free absorption coefficients of the negative helium ion are calculated by a phaseshift approximation, using continuum data that accurately account for electron-atom correlation and polarization. The approximation is considered to yield results within a few per cent of numerical values for wavelengths greater than 1 m, over the temperature range 1400-10080 K. These coefficients are expected to give the best current estimates of He - continuous absorption. Key words: atomic data - atomic processes - stars: atmospheres - infrared: general.

Blinded versus unblinded estimation of a correlation coefficient to inform interim design adaptations.

PubMed

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. © 2016 The Authors. Biometrical Journal Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Blinded versus unblinded estimation of a correlation coefficient to inform interim design adaptations

PubMed Central

Stallard, Nigel; Parsons, Nicholas; Todd, Susan; Friede, Tim

2016-01-01

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. PMID:27886393

Statistical methods for astronomical data with upper limits. II - Correlation and regression

NASA Technical Reports Server (NTRS)

Isobe, T.; Feigelson, E. D.; Nelson, P. I.

1986-01-01

Statistical methods for calculating correlations and regressions in bivariate censored data where the dependent variable can have upper or lower limits are presented. Cox's regression and the generalization of Kendall's rank correlation coefficient provide significant levels of correlations, and the EM algorithm, under the assumption of normally distributed errors, and its nonparametric analog using the Kaplan-Meier estimator, give estimates for the slope of a regression line. Monte Carlo simulations demonstrate that survival analysis is reliable in determining correlations between luminosities at different bands. Survival analysis is applied to CO emission in infrared galaxies, X-ray emission in radio galaxies, H-alpha emission in cooling cluster cores, and radio emission in Seyfert galaxies.

Determining the K coefficient to leaf area index estimations in a tropical dry forest

NASA Astrophysics Data System (ADS)

Magalhães, Sarah Freitas; Calvo-Rodriguez, Sofia; do Espírito Santo, Mário Marcos; Sánchez Azofeifa, Gerardo Arturo

2018-03-01

Vegetation indices are useful tools to remotely estimate several important parameters related to ecosystem functioning. However, improving and validating estimations for a wide range of vegetation types are necessary. In this study, we provide a methodology for the estimation of the leaf area index (LAI) in a tropical dry forest (TDF) using the light diffusion through the canopy as a function of the successional stage. For this purpose, we estimated the K coefficient, a parameter that relates the normalized difference vegetation index (NDVI) to LAI, based on photosynthetically active radiation (PAR) and solar radiation. The study was conducted in the Mata Seca State Park, in southeastern Brazil, from 2012 to 2013. We defined four successional stages (very early, early, intermediate, and late) and established one optical phenology tower at one plot of 20 × 20 m per stage. Towers measured the incoming and reflected solar radiation and PAR for NDVI calculation. For each plot, we established 24 points for LAI sampling through hemispherical photographs. Because leaf cover is highly seasonal in TDFs, we determined ΔK (leaf growth phase) and K max (leaf maturity phase). We detected a strong correlation between NDVI and LAI, which is necessary for a reliable determination of the K coefficient. Both NDVI and LAI varied significantly between successional stages, indicating sensitivity to structural changes in forest regeneration. Furthermore, the K values differed between successional stages and correlated significantly with other environmental variables such as air temperature and humidity, fraction of absorbed PAR, and soil moisture. Thus, we established a model based on spectral properties of the vegetation coupled with biophysical characteristics in a TDF that makes possible to estimate LAI from NDVI values. The application of the K coefficient can improve remote estimations of forest primary productivity and gases and energy exchanges between vegetation and atmosphere. This model can be applied to distinguish different successional stages of TDFs, supporting environmental monitoring and conservation policies towards this biome.

Soil clay content controls the turnover of slow soil carbon across Chinese cropland

NASA Astrophysics Data System (ADS)

Feng, W.; Jiang, J.; Li, J.

2017-12-01

Improving the prediction of changes in global soil organic carbon (SOC) lies in accurate estimate of C inputs to soils and SOC turnover time. Since C inputs to soils in cropland can be estimated due to well documented data of crop yields, SOC turnover rate becomes critical for accurate prediction of changes in SOC. The laboratory incubation is widely used but cannot well represent the turnover of slow soil C that accounts for the majority of total SOC, while the long-term observation of temporal changes in SOC stock offers an opportunity to estimate the turnover of slow soil C. Using time series data of SOC stock of twenty long-term agricultural trials that have initiated since 1990 in China, we estimated SOC turnover rates based on changes in soil C pool size and aimed to identify the dominant controls on SOC turnover rate across Chinese cropland. We used the two-pool first-order kinetic soil C model and the inverse modeling with Markov chain the Monte Carlo algorithm, and estimated humification coefficient (h) of C inputs to soils, turnover rates of fast and slow soil C pools, and the transfer coefficient between these two soil C pools. The preliminary results show that the turnover rate of slow soil C is positively correlated with climate (i.e. mean annual temperature and precipitation) but negatively correlated with the clay content, demonstrating that the clay content is important in regulating SOC turnover rates. The ratio of humification coefficient to C turnover rate (h/k) that indicates soil C sequestration efficiency, is negatively correlated with climate and positively correlated with the clay content. In addition, the quantity of C inputs is correlated with h/k and the turnover rate of slow soil C, suggesting that the quantity of C inputs plays an important role in mediating C sequestration efficiency. Further results will inform us the main controls on SOC turnover in Chinese cropland. Keywords: SOC; turnover; long-term trial; temporal change; clay content; inverse modeling

An improved method based on wavelet coefficient correlation to filter noise in Doppler ultrasound blood flow signals

NASA Astrophysics Data System (ADS)

Wan, Renzhi; Zu, Yunxiao; Shao, Lin

2018-04-01

The blood echo signal maintained through Medical ultrasound Doppler devices would always include vascular wall pulsation signal .The traditional method to de-noise wall signal is using high-pass filter, which will also remove the lowfrequency part of the blood flow signal. Some scholars put forward a method based on region selective reduction, which at first estimates of the wall pulsation signals and then removes the wall signal from the mixed signal. Apparently, this method uses the correlation between wavelet coefficients to distinguish blood signal from wall signal, but in fact it is a kind of wavelet threshold de-noising method, whose effect is not so much ideal. In order to maintain a better effect, this paper proposes an improved method based on wavelet coefficient correlation to separate blood signal and wall signal, and simulates the algorithm by computer to verify its validity.

Asymptotic properties of Pearson's rank-variate correlation coefficient under contaminated Gaussian model.

PubMed

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.

Progression of Mortality due to Diseases of the Circulatory System and Human Development Index in Rio de Janeiro Municipalities

PubMed Central

Soares, Gabriel Porto; Klein, Carlos Henrique; Silva, Nelson Albuquerque de Souza e; de Oliveira, Glaucia Maria Moraes

2016-01-01

Background Diseases of the circulatory system (DCS) are the major cause of death in Brazil and worldwide. Objective To correlate the compensated and adjusted mortality rates due to DCS in the Rio de Janeiro State municipalities between 1979 and 2010 with the Human Development Index (HDI) from 1970 onwards. Methods Population and death data were obtained in DATASUS/MS database. Mortality rates due to ischemic heart diseases (IHD), cerebrovascular diseases (CBVD) and DCS adjusted by using the direct method and compensated for ill-defined causes. The HDI data were obtained at the Brazilian Institute of Applied Research in Economics. The mortality rates and HDI values were correlated by estimating Pearson linear coefficients. The correlation coefficients between the mortality rates of census years 1991, 2000 and 2010 and HDI data of census years 1970, 1980 and 1991 were calculated with discrepancy of two demographic censuses. The linear regression coefficients were estimated with disease as the dependent variable and HDI as the independent variable. Results In recent decades, there was a reduction in mortality due to DCS in all Rio de Janeiro State municipalities, mainly because of the decline in mortality due to CBVD, which was preceded by an elevation in HDI. There was a strong correlation between the socioeconomic indicator and mortality rates. Conclusion The HDI progression showed a strong correlation with the decline in mortality due to DCS, signaling to the relevance of improvements in life conditions. PMID:27849263

Progression of Mortality due to Diseases of the Circulatory System and Human Development Index in Rio de Janeiro Municipalities.

PubMed

Soares, Gabriel Porto; Klein, Carlos Henrique; Silva, Nelson Albuquerque de Souza E; Oliveira, Glaucia Maria Moraes de

2016-10-01

Diseases of the circulatory system (DCS) are the major cause of death in Brazil and worldwide. To correlate the compensated and adjusted mortality rates due to DCS in the Rio de Janeiro State municipalities between 1979 and 2010 with the Human Development Index (HDI) from 1970 onwards. Population and death data were obtained in DATASUS/MS database. Mortality rates due to ischemic heart diseases (IHD), cerebrovascular diseases (CBVD) and DCS adjusted by using the direct method and compensated for ill-defined causes. The HDI data were obtained at the Brazilian Institute of Applied Research in Economics. The mortality rates and HDI values were correlated by estimating Pearson linear coefficients. The correlation coefficients between the mortality rates of census years 1991, 2000 and 2010 and HDI data of census years 1970, 1980 and 1991 were calculated with discrepancy of two demographic censuses. The linear regression coefficients were estimated with disease as the dependent variable and HDI as the independent variable. In recent decades, there was a reduction in mortality due to DCS in all Rio de Janeiro State municipalities, mainly because of the decline in mortality due to CBVD, which was preceded by an elevation in HDI. There was a strong correlation between the socioeconomic indicator and mortality rates. The HDI progression showed a strong correlation with the decline in mortality due to DCS, signaling to the relevance of improvements in life conditions.

Suppressor Variables: The Difference between "Is" versus "Acting As"

ERIC Educational Resources Information Center

Ludlow, Larry; Klein, Kelsey

2014-01-01

Correlated predictors in regression models are a fact of life in applied social science research. The extent to which they are correlated will influence the estimates and statistics associated with the other variables they are modeled along with. These effects, for example, may include enhanced regression coefficients for the other variables--a…

Exact Interval Estimation, Power Calculation, and Sample Size Determination in Normal Correlation Analysis

ERIC Educational Resources Information Center

Shieh, Gwowen

2006-01-01

This paper considers the problem of analysis of correlation coefficients from a multivariate normal population. A unified theorem is derived for the regression model with normally distributed explanatory variables and the general results are employed to provide useful expressions for the distributions of simple, multiple, and partial-multiple…

In vitro burn model illustrating heat conduction patterns using compressed thermal papers.

PubMed

Lee, Jun Yong; Jung, Sung-No; Kwon, Ho

2015-01-01

To date, heat conduction from heat sources to tissue has been estimated by complex mathematical modeling. In the present study, we developed an intuitive in vitro skin burn model that illustrates heat conduction patterns inside the skin. This was composed of tightly compressed thermal papers with compression frames. Heat flow through the model left a trace by changing the color of thermal papers. These were digitized and three-dimensionally reconstituted to reproduce the heat conduction patterns in the skin. For standardization, we validated K91HG-CE thermal paper using a printout test and bivariate correlation analysis. We measured the papers' physical properties and calculated the estimated depth of heat conduction using Fourier's equation. Through contact burns of 5, 10, 15, 20, and 30 seconds on porcine skin and our burn model using a heated brass comb, and comparing the burn wound and heat conduction trace, we validated our model. The heat conduction pattern correlation analysis (intraclass correlation coefficient: 0.846, p < 0.001) and the heat conduction depth correlation analysis (intraclass correlation coefficient: 0.93, p < 0.001) showed statistically significant high correlations between the porcine burn wound and our model. Our model showed good correlation with porcine skin burn injury and replicated its heat conduction patterns. © 2014 by the Wound Healing Society.

Parameter identification of thermophilic anaerobic degradation of valerate.

PubMed

Flotats, Xavier; Ahring, Birgitte K; Angelidaki, Irini

2003-01-01

The considered mathematical model of the decomposition of valerate presents three unknown kinetic parameters, two unknown stoichiometric coefficients, and three unknown initial concentrations for biomass. Applying a structural identifiability study, we concluded that it is necessary to perform simultaneous batch experiments with different initial conditions for estimating these parameters. Four simultaneous batch experiments were conducted at 55 degrees C, characterized by four different initial acetate concentrations. Product inhibition of valerate degradation by acetate was considered. Practical identification was done optimizing the sum of the multiple determination coefficients for all measured state variables and for all experiments simultaneously. The estimated values of kinetic parameters and stoichiometric coefficients were characterized by the parameter correlation matrix, the confidence interval, and the student's t-test at 5% significance level with positive results except for the saturation constant, for which more experiments for improving its identifiability should be conducted. In this article, we discuss kinetic parameter estimation methods.

A technique for estimating time of concentration and storage coefficient values for Illinois streams

USGS Publications Warehouse

Graf, Julia B.; Garklavs, George; Oberg, Kevin A.

1982-01-01

Values of the unit hydrograph parameters time of concentration (TC) and storage coefficient (R) can be estimated for streams in Illinois by a two-step technique developed from data for 98 gaged basins in the State. The sum of TC and R is related to stream length (L) and main channel slope (S) by the relation (TC + R)e = 35.2L0.39S-0.78. The variable R/(TC + R) is not significantly correlated with drainage area, slope, or length, but does exhibit a regional trend. Regional values of R/(TC + R) are used with the computed values of (TC + R)e to solve for estimated values of time of concentration (TCe) and storage coefficient (Re). The use of the variable R/(TC + R) is thought to account for variations in unit hydrograph parameters caused by physiographic variables such as basin topography, flood-plain development, and basin storage characteristics. (USGS)

Correlation diagrams in 40 Ar/39Ar dating: is there a correct choice?

USGS Publications Warehouse

Dalrymple, G.B.; Lanphere, M.A.; Pringle, M.S.

1988-01-01

Contrary to published assertions, the 2 types of correlation diagrams used in the interpretation of 40Ar/39Ar incremental-heating data yield the same information provided the correct mathematics are used for estimating correlation coefficients and for the least squares fit. The choice is simply between 2 illustrative, graphical displays, neither of which is fundamentally superior to the other. -Authors

Using pedometers to estimate ambulatory physical activity in Vietnam.

PubMed

Thuy, Au Bich; Blizzard, Leigh; Schmidt, Michael; Magnussen, Costan; Hansen, Emily; Dwyer, Terence

2011-01-01

Pedometer measurement of physical activity (PA) has been shown to be reliable and valid in industrialized populations, but its applicability in economically developing Vietnam remains untested. This study assessed the feasibility, stability and validity of pedometer estimates of PA in Vietnam. 250 adults from a population-based survey were randomly selected to wear Yamax pedometers and record activities for 7 consecutive days. Stability and concurrent validity were assessed using intraclass correlation coefficients (ICC) and Spearman correlation coefficients. Overall, 97.6% of participants provided at least 1 day of usable recordings, and 76.2% wore pedometers for all 7 days. Only 5.2% of the sample participants were involved in work activities not measurable by pedometer. The number of steps increased with hours of wear. There was no significant difference between weekday and weekend in number of steps, and at least 3 days of recordings were required (ICC of the 3 days of recordings: men 0.96, women 0.97). Steps per hour were moderately correlated (men r = .42, women r = .26) with record estimates of total PA. It is feasible to use pedometers to estimate PA in Vietnam. The measure should involve at least 3 days of recording irrespective of day of the week. ©2011 Human Kinetics, Inc.

Designing Large-Scale Multisite and Cluster-Randomized Studies of Professional Development

ERIC Educational Resources Information Center

Kelcey, Ben; Spybrook, Jessaca; Phelps, Geoffrey; Jones, Nathan; Zhang, Jiaqi

2017-01-01

We develop a theoretical and empirical basis for the design of teacher professional development studies. We build on previous work by (a) developing estimates of intraclass correlation coefficients for teacher outcomes using two- and three-level data structures, (b) developing estimates of the variance explained by covariates, and (c) modifying…

Impact of measurement invariance on construct correlations, mean differences, and relations with external correlates: an illustrative example using Big Five and RIASEC measures.

PubMed

Schmitt, Neal; Golubovich, Juliya; Leong, Frederick T L

2011-12-01

The impact of measurement invariance and the provision for partial invariance in confirmatory factor analytic models on factor intercorrelations, latent mean differences, and estimates of relations with external variables is investigated for measures of two sets of widely assessed constructs: Big Five personality and the six Holland interests (RIASEC). In comparing models that include provisions for partial invariance with models that do not, the results indicate quite small differences in parameter estimates involving the relations between factors, one relatively large standardized mean difference in factors between the subgroups compared and relatively small differences in the regression coefficients when the factors are used to predict external variables. The results provide support for the use of partially invariant models, but there does not seem to be a great deal of difference between structural coefficients when the measurement model does or does not include separate estimates of subgroup parameters that differ across subgroups. Future research should include simulations in which the impact of various factors related to invariance is estimated.

Relationship of crop radiance to alfalfa agronomic values

NASA Technical Reports Server (NTRS)

Tucker, C. J.; Elgin, J. H., Jr.; Mcmurtrey, J. E., III

1980-01-01

Red and photographic infrared spectral data of alfalfa were collected at the time of the third and fourth cuttings using a hand-held radiometer for the earlier alfalfa cutting. Significant linear and non-linear correlation coefficients were found between the spectral variables and plant height, biomass, forage water content, and estimated canopy cover. For the alfalfa of the later cutting, which had experienced a period of severe drought stress which limited growth, the spectral variables were found to be highly correlated with the estimated drought scores.

Quantitative genetics and sex-specific selection on sexually dimorphic traits in bighorn sheep

PubMed Central

Poissant, Jocelyn; Wilson, Alastair J; Festa-Bianchet, Marco; Hogg, John T; Coltman, David W

2008-01-01

Sexual conflict at loci influencing traits shared between the sexes occurs when sex-specific selection pressures are antagonistic relative to the genetic correlation between the sexes. To assess whether there is sexual conflict over shared traits, we estimated heritability and intersexual genetic correlations for highly sexually dimorphic traits (horn volume and body mass) in a wild population of bighorn sheep (Ovis canadensis) and quantified sex-specific selection using estimates of longevity and lifetime reproductive success. Body mass and horn volume showed significant additive genetic variance in both sexes, and intersexual genetic correlations were 0.24±0.28 for horn volume and 0.63±0.30 for body mass. For horn volume, selection coefficients did not significantly differ from zero in either sex. For body weight, selection coefficients were positive in females but did not differ from zero in males. The absence of detectable sexually antagonistic selection suggests that currently there are no sexual conflicts at loci influencing horn volume and body mass. PMID:18211870

Genetic diversity of dog breeds: within-breed diversity comparing genealogical and molecular data.

PubMed

Leroy, G; Verrier, E; Meriaux, J C; Rognon, X

2009-06-01

The genetic diversity of 61 dog breeds raised in France was investigated. Genealogical analyses were performed on the pedigree file of the French kennel club. A total of 1514 dogs were also genotyped using 21 microsatellite markers. For animals born from 2001 to 2005, the average coefficient of inbreeding ranged from 0.2% to 8.8% and the effective number of ancestors ranged from 9 to 209, according to the breed. The mean value of heterozygosity was 0.62 over all breeds (range 0.37-0.77). At the breed level, few correlations were found between genealogical and molecular parameters. Kinship coefficients and individual similarity estimators were, however, significantly correlated, with the best mean correlation being found for the Lynch & Ritland estimator (r = 0.43). According to both approaches, it was concluded that special efforts should be made to maintain diversity for three breeds, namely the Berger des Pyrénées, Braque Saint-Germain and Bull Terrier.

An efficient sensitivity analysis method for modified geometry of Macpherson suspension based on Pearson correlation coefficient

NASA Astrophysics Data System (ADS)

Shojaeefard, Mohammad Hasan; Khalkhali, Abolfazl; Yarmohammadisatri, Sadegh

2017-06-01

The main purpose of this paper is to propose a new method for designing Macpherson suspension, based on the Sobol indices in terms of Pearson correlation which determines the importance of each member on the behaviour of vehicle suspension. The formulation of dynamic analysis of Macpherson suspension system is developed using the suspension members as the modified links in order to achieve the desired kinematic behaviour. The mechanical system is replaced with an equivalent constrained links and then kinematic laws are utilised to obtain a new modified geometry of Macpherson suspension. The equivalent mechanism of Macpherson suspension increased the speed of analysis and reduced its complexity. The ADAMS/CAR software is utilised to simulate a full vehicle, Renault Logan car, in order to analyse the accuracy of modified geometry model. An experimental 4-poster test rig is considered for validating both ADAMS/CAR simulation and analytical geometry model. Pearson correlation coefficient is applied to analyse the sensitivity of each suspension member according to vehicle objective functions such as sprung mass acceleration, etc. Besides this matter, the estimation of Pearson correlation coefficient between variables is analysed in this method. It is understood that the Pearson correlation coefficient is an efficient method for analysing the vehicle suspension which leads to a better design of Macpherson suspension system.

Incorporation of diffusion-weighted magnetic resonance imaging data into a simple mathematical model of tumor growth

NASA Astrophysics Data System (ADS)

Atuegwu, N. C.; Colvin, D. C.; Loveless, M. E.; Xu, L.; Gore, J. C.; Yankeelov, T. E.

2012-01-01

We build on previous work to show how serial diffusion-weighted MRI (DW-MRI) data can be used to estimate proliferation rates in a rat model of brain cancer. Thirteen rats were inoculated intracranially with 9L tumor cells; eight rats were treated with the chemotherapeutic drug 1,3-bis(2-chloroethyl)-1-nitrosourea and five rats were untreated controls. All animals underwent DW-MRI immediately before, one day and three days after treatment. Values of the apparent diffusion coefficient (ADC) were calculated from the DW-MRI data and then used to estimate the number of cells in each voxel and also for whole tumor regions of interest. The data from the first two imaging time points were then used to estimate the proliferation rate of each tumor. The proliferation rates were used to predict the number of tumor cells at day three, and this was correlated with the corresponding experimental data. The voxel-by-voxel analysis yielded Pearson's correlation coefficients ranging from -0.06 to 0.65, whereas the region of interest analysis provided Pearson's and concordance correlation coefficients of 0.88 and 0.80, respectively. Additionally, the ratio of positive to negative proliferation values was used to separate the treated and control animals (p <0.05) at an earlier point than the mean ADC values. These results further illustrate how quantitative measurements of tumor state obtained non-invasively by imaging can be incorporated into mathematical models that predict tumor growth.

Validation of Pooled Whole-Genome Re-Sequencing in Arabidopsis lyrata.

PubMed

Fracassetti, Marco; Griffin, Philippa C; Willi, Yvonne

2015-01-01

Sequencing pooled DNA of multiple individuals from a population instead of sequencing individuals separately has become popular due to its cost-effectiveness and simple wet-lab protocol, although some criticism of this approach remains. Here we validated a protocol for pooled whole-genome re-sequencing (Pool-seq) of Arabidopsis lyrata libraries prepared with low amounts of DNA (1.6 ng per individual). The validation was based on comparing single nucleotide polymorphism (SNP) frequencies obtained by pooling with those obtained by individual-based Genotyping By Sequencing (GBS). Furthermore, we investigated the effect of sample number, sequencing depth per individual and variant caller on population SNP frequency estimates. For Pool-seq data, we compared frequency estimates from two SNP callers, VarScan and Snape; the former employs a frequentist SNP calling approach while the latter uses a Bayesian approach. Results revealed concordance correlation coefficients well above 0.8, confirming that Pool-seq is a valid method for acquiring population-level SNP frequency data. Higher accuracy was achieved by pooling more samples (25 compared to 14) and working with higher sequencing depth (4.1× per individual compared to 1.4× per individual), which increased the concordance correlation coefficient to 0.955. The Bayesian-based SNP caller produced somewhat higher concordance correlation coefficients, particularly at low sequencing depth. We recommend pooling at least 25 individuals combined with sequencing at a depth of 100× to produce satisfactory frequency estimates for common SNPs (minor allele frequency above 0.05).

Histogram analysis parameters of apparent diffusion coefficient reflect tumor cellularity and proliferation activity in head and neck squamous cell carcinoma

PubMed Central

Winter, Karsten; Richter, Cindy; Hoehn, Anna-Kathrin

2018-01-01

Our purpose was to analyze associations between apparent diffusion coefficient (ADC) histogram analysis parameters and histopathologicalfeatures in head and neck squamous cell carcinoma (HNSCC). The study involved 32 patients with primary HNSCC. For every tumor, the following histogram analysis parameters were calculated: ADCmean, ADCmax, ADCmin, ADCmedian, ADCmode, P10, P25, P75, P90, kurtosis, skewness, and entropy. Furthermore, proliferation index KI 67, cell count, total and average nucleic areas were estimated. Spearman's correlation coefficient (p) was used to analyze associations between investigated parameters. In overall sample, all ADC values showed moderate inverse correlations with KI 67. All ADC values except ADCmax correlated inversely with tumor cellularity. Slightly correlations were identified between total/average nucleic area and ADCmean, ADCmin, ADCmedian, and P25. In G1/2 tumors, only ADCmode correlated well with Ki67. No statistically significant correlations between ADC parameters and cellularity were found. In G3 tumors, Ki 67 correlated with all ADC parameters except ADCmode. Cell count correlated well with all ADC parameters except ADCmax. Total nucleic area correlated inversely with ADCmean, ADCmin, ADCmedian, P25, and P90. ADC histogram parameters reflect proliferation potential and cellularity in HNSCC. The associations between histopathology and imaging depend on tumor grading. PMID:29805759

Classical Wigner method with an effective quantum force: application to reaction rates.

PubMed

Poulsen, Jens Aage; Li, Huaqing; Nyman, Gunnar

2009-07-14

We construct an effective "quantum force" to be used in the classical molecular dynamics part of the classical Wigner method when determining correlation functions. The quantum force is obtained by estimating the most important short time separation of the Feynman paths that enter into the expression for the correlation function. The evaluation of the force is then as easy as classical potential energy evaluations. The ideas are tested on three reaction rate problems. The resulting transmission coefficients are in much better agreement with accurate results than transmission coefficients from the ordinary classical Wigner method.

A B-B-G-K-Y framework for fluid turbulence

NASA Technical Reports Server (NTRS)

Montgomery, D.

1975-01-01

A kinetic theory for fluid turbulence is developed from the Liouville equation and the associated BBGKY hierarchy. Real and imaginary parts of Fourier coefficients of fluid variables play the roles of particles. Closure is achieved by the assumption of negligible five-coefficient correlation functions and probability distributions of Fourier coefficients are the basic variables of the theory. An additional approximation leads to a closed-moment description similar to the so-called eddy-damped Markovian approximation. A kinetic equation is derived for which conservation laws and an H-theorem can be rigorously established, the H-theorem implying relaxation of the absolute equilibrium of Kraichnan. The equation can be cast in the Fokker-Planck form, and relaxation times estimated from its friction and diffusion coefficients. An undetermined parameter in the theory is the free decay time for triplet correlations. Some attention is given to the inclusion of viscous damping and external driving forces.

Simple Estimation of the Endolymphatic Volume Ratio after Intravenous Administration of a Single-dose of Gadolinium Contrast

PubMed Central

NAGANAWA, Shinji; KANOU, Mai; OHASHI, Toshio; KUNO, Kayao; SONE, Michihiko

2016-01-01

Purpose: To evaluate the feasibility of a simple estimation for the endolymphatic volume ratio (endolymph volume/total lymph volume = %ELvolume) from an area ratio obtained from only one slice (%EL1slice) or from three slices (%EL3slices). The %ELvolume, calculated from a time-consuming measurement on all magnetic resonance (MR) slices, was compared to the %EL1slice and the %EL3slices. Methods: In 40 ears of 20 patients with a clinical suspicion of endolymphatic hydrops, MR imaging was performed 4 hours after intravenous administration of a single dose of gadolinium-based contrast material (IV-SD-GBCM). Using previously reported HYDROPS2-Mi2 MR imaging, the %ELvolume values in the cochlea and the vestibule were measured separately by two observers. The correlations between the %EL1slice or the %EL3slices and the %ELvolume values were evaluated. Results: A strong linear correlation was observed between the %ELvolume and the %EL3slices or the %EL1slice in the cochlea. The Pearson correlation coefficient (r) was 0.968 (3 slices) and 0.965 (1 slice) for observer A, and 0.968 (3 slices) and 0.964 (1 slice) for observer B (P < 0.001, for all). A strong linear correlation was also observed between the %ELvolume and the %EL3slices or the %EL1slice in the vestibule. The Pearson correlation coefficient (r) was 0.980 (3 slices) and 0.953 (1 slice) for observer A, and 0.979 (3 slices) and 0.952 (1 slice) for observer B (P < 0.001, for all). The high intra-class correlation coefficients (0.991–0.997) between the endolymph volume ratios by two observers were observed in both the cochlea and the vestibule for values of the %ELvolume, the %EL3slices and the %EL1slice. Conclusion: The %ELvolume might be easily estimated from the %EL3slices or the %EL1slice. PMID:27001396

Simple Estimation of the Endolymphatic Volume Ratio after Intravenous Administration of a Single-dose of Gadolinium Contrast.

PubMed

Naganawa, Shinji; Kanou, Mai; Ohashi, Toshio; Kuno, Kayao; Sone, Michihiko

2016-10-11

To evaluate the feasibility of a simple estimation for the endolymphatic volume ratio (endolymph volume/total lymph volume = %EL volume ) from an area ratio obtained from only one slice (%EL 1slice ) or from three slices (%EL 3slices ). The %EL volume, calculated from a time-consuming measurement on all magnetic resonance (MR) slices, was compared to the %EL 1slice and the %EL 3slices . In 40 ears of 20 patients with a clinical suspicion of endolymphatic hydrops, MR imaging was performed 4 hours after intravenous administration of a single dose of gadolinium-based contrast material (IV-SD-GBCM). Using previously reported HYDROPS2-Mi2 MR imaging, the %EL volume values in the cochlea and the vestibule were measured separately by two observers. The correlations between the %EL 1slice or the %EL 3slices and the %EL volume values were evaluated. A strong linear correlation was observed between the %EL volume and the %EL 3slices or the %EL 1slice in the cochlea. The Pearson correlation coefficient (r) was 0.968 (3 slices) and 0.965 (1 slice) for observer A, and 0.968 (3 slices) and 0.964 (1 slice) for observer B (P < 0.001, for all). A strong linear correlation was also observed between the %EL volume and the %EL 3slices or the %EL 1slice in the vestibule. The Pearson correlation coefficient (r) was 0.980 (3 slices) and 0.953 (1 slice) for observer A, and 0.979 (3 slices) and 0.952 (1 slice) for observer B (P < 0.001, for all). The high intra-class correlation coefficients (0.991-0.997) between the endolymph volume ratios by two observers were observed in both the cochlea and the vestibule for values of the %EL volume , the %EL 3slices and the %EL 1slice . The %EL volume might be easily estimated from the %EL 3slices or the %EL 1slice .

Settling characteristics of nursery pig manure and nutrient estimation by the hydrometer method.

PubMed

Zhu, Jun; Ndegwa, Pius M; Zhang, Zhijian

2003-05-01

The hydrometer method to measure manure specific gravity and subsequently relate it to manure nutrient contents was examined in this study. It was found that this method might be improved in estimation accuracy if only manure from a single growth stage of pigs was used (e.g., nursery pig manure used here). The total solids (TS) content of the test manure was well correlated with the total nitrogen (TN) and total phosphorus (TP) concentrations in the manure, with highly significant correlation coefficients of 0.9944 and 0.9873, respectively. Also observed were good linear correlations between the TN and TP contents and the manure specific gravity (correlation coefficients: 0.9836 and 0.9843, respectively). These correlations were much better than those reported by past researchers, in which lumped data for pigs at different growing stages were used. It may therefore be inferred that developing different linear equations for pigs at different ages should improve the accuracy in manure nutrient estimation using a hydrometer. Also, the error of using the hydrometer method to estimate manure TN and TP was found to increase, from +/- 10% to +/- 50%, with the decrease in TN (from 700 ppm to 100 ppm) and TP (from 130 ppm to 30 ppm) concentrations in the manure. The estimation errors for TN and TP may be larger than 50% if the total solids content is below 0.5%. In addition, the rapid settling of solids has long been considered characteristic of swine manure; however, in this study, the solids settling property appeared to be quite poor for nursery pig manure in that no conspicuous settling occurred after the manure was left statically for 5 hours. This information has not been reported elsewhere in the literature and may need further research to verify.

Estimation of interfacial area in a packed cross-flow cascade with distillation of ethanol-water, methanol-water, and hexane-heptane

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

Velaga, A.

1986-01-01

Packed cross-flow internals consisting of four and ten stages including the samplers for liquid and vapor were fabricated to fit into the existing distillation column. Experiments were conducted using methanol-water, ethanol-water and hexane-heptane binary mixtures. The experimental data were collected for compositions of inlet and exist streams of cross-flow stages. The overall gas phase height transfer units (H/sub og/) were estimated using the experimental data. H/sub og/ values were compared to those of counter current conditions. The individual mass transfer coefficients in the liquid and vapor phases were estimated using the collected experimental data for degree of separation, flow ratesmore » and physical properties of the binary system used. The physical properties were estimated at an average temperature of the specific cross-flow stage. The mass transfer coefficients were evaluated using three different correlations proposed by Shulman. Onda and Hayashi respectively. The interfacial areas were estimated using the evaluated mass transfer coefficients and the experimental data at each stage of the column for different runs and compared.« less

Estimation of stature using hand and foot dimensions in Slovak adults.

PubMed

Uhrová, Petra; Beňuš, Radoslav; Masnicová, Soňa; Obertová, Zuzana; Kramárová, Daniela; Kyselicová, Klaudia; Dörnhöferová, Michaela; Bodoriková, Silvia; Neščáková, Eva

2015-03-01

Hand and foot dimensions used for stature estimation help to formulate a biological profile in the process of personal identification. Morphological variability of hands and feet shows the importance of generating population-specific equations to estimate stature. The stature, hand length, hand breadth, foot length and foot breadth of 250 young Slovak males and females, aged 18-24 years, were measured according to standard anthropometric procedures. The data were statistically analyzed using independent t-test for sex and bilateral differences. Pearson correlation coefficient was used for assessing relationship between stature and hand/foot parameters, and subsequently linear regression analysis was used to estimate stature. The results revealed significant sex differences in hand and foot dimensions as well as in stature (p<0.05). There was a positive and statistically significant correlation between stature and all measurements in both sexes (p<0.01). The highest correlation coefficient was found for foot length in males (r=0.71) as well as in females (r=0.63). Regression equations were computed separately for each sex. The accuracy of stature prediction ranged from ±4.6 to ±6.1cm. The results of this study indicate that hand and foot dimension can be used to estimate stature for Slovak for the purpose of forensic field. The regression equations can be of use for stature estimation particularly in cases of dismembered bodies. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Identifying Optimal Temporal Scale for the Correlation of AOD and Ground Measurements of PM2.5 to Improve the Modeling Performance in a Real-Time Air Quality Estimation System

NASA Technical Reports Server (NTRS)

Li,Hui; Faruque, Fazlay; Williams, Worth; Al-Hamdan, Mohammad; Luvall, Jeffrey; Crosson, William; Rickman, Douglas; Limaye, Ashutosh

2008-01-01

Aerosol optical depth (AOD), derived from satellite measurements using Moderate Resolution Imaging Spectrometer (MODIS), offers indirect estimates of particle matter. Research shows a significant positive correlation between satellite-based measurements of AOD and ground-based measurements of particulate matter with aerodynamic diameter less than or equal to 2.5 micrometers (PM2.5). In addition, satellite observations have also shown great promise in improving estimates of PM2.5 air quality surface. Research shows that correlations between AOD and ground PM2.5 are affected by a combination of many factors such as inherent characteristics of satellite observations, terrain, cloud cover, height of the mixing layer, and weather conditions, and thus might vary widely in different regions, different seasons, and even different days in a same location. Analysis of correlating AOD with ground measured PM2.5 on a day-to-day basis suggests the temporal scale, a number of immediate latest days for a given run's day, for their correlations needs to be considered to improve air quality surface estimates, especially when satellite observations are used in a real-time pollution system. The second reason is that correlation coefficients between AOD and ground PM2.5 cannot be predetermined and needs to be calculated for each day's run for a real-time system because the coefficients can vary over space and time. Few studies have been conducted to explore the optimal way to apply AOD data to improve model accuracies of PM2.5 surface estimation in a real-time air quality system. This paper discusses the best temporal scale to calculate the correlation of AOD and ground particle matter data to improve the results of pollution models in real-time system.

Centroid estimation for a Shack-Hartmann wavefront sensor based on stream processing.

PubMed

Kong, Fanpeng; Polo, Manuel Cegarra; Lambert, Andrew

2017-08-10

Using center of gravity to estimate the centroid of the spot in a Shack-Hartmann wavefront sensor, the measurement corrupts with photon and detector noise. Parameters, like window size, often require careful optimization to balance the noise error, dynamic range, and linearity of the response coefficient under different photon flux. It also needs to be substituted by the correlation method for extended sources. We propose a centroid estimator based on stream processing, where the center of gravity calculation window floats with the incoming pixel from the detector. In comparison with conventional methods, we show that the proposed estimator simplifies the choice of optimized parameters, provides a unit linear coefficient response, and reduces the influence of background and noise. It is shown that the stream-based centroid estimator also works well for limited size extended sources. A hardware implementation of the proposed estimator is discussed.

A new method to estimate average hourly global solar radiation on the horizontal surface

NASA Astrophysics Data System (ADS)

Pandey, Pramod K.; Soupir, Michelle L.

2012-10-01

A new model, Global Solar Radiation on Horizontal Surface (GSRHS), was developed to estimate the average hourly global solar radiation on the horizontal surfaces (Gh). The GSRHS model uses the transmission function (Tf,ij), which was developed to control hourly global solar radiation, for predicting solar radiation. The inputs of the model were: hour of day, day (Julian) of year, optimized parameter values, solar constant (H0), latitude, and longitude of the location of interest. The parameter values used in the model were optimized at a location (Albuquerque, NM), and these values were applied into the model for predicting average hourly global solar radiations at four different locations (Austin, TX; El Paso, TX; Desert Rock, NV; Seattle, WA) of the United States. The model performance was assessed using correlation coefficient (r), Mean Absolute Bias Error (MABE), Root Mean Square Error (RMSE), and coefficient of determinations (R2). The sensitivities of parameter to prediction were estimated. Results show that the model performed very well. The correlation coefficients (r) range from 0.96 to 0.99, while coefficients of determination (R2) range from 0.92 to 0.98. For daily and monthly prediction, error percentages (i.e. MABE and RMSE) were less than 20%. The approach we proposed here can be potentially useful for predicting average hourly global solar radiation on the horizontal surface for different locations, with the use of readily available data (i.e. latitude and longitude of the location) as inputs.

Testing a single regression coefficient in high dimensional linear models

PubMed Central

Zhong, Ping-Shou; Li, Runze; Wang, Hansheng; Tsai, Chih-Ling

2017-01-01

In linear regression models with high dimensional data, the classical z-test (or t-test) for testing the significance of each single regression coefficient is no longer applicable. This is mainly because the number of covariates exceeds the sample size. In this paper, we propose a simple and novel alternative by introducing the Correlated Predictors Screening (CPS) method to control for predictors that are highly correlated with the target covariate. Accordingly, the classical ordinary least squares approach can be employed to estimate the regression coefficient associated with the target covariate. In addition, we demonstrate that the resulting estimator is consistent and asymptotically normal even if the random errors are heteroscedastic. This enables us to apply the z-test to assess the significance of each covariate. Based on the p-value obtained from testing the significance of each covariate, we further conduct multiple hypothesis testing by controlling the false discovery rate at the nominal level. Then, we show that the multiple hypothesis testing achieves consistent model selection. Simulation studies and empirical examples are presented to illustrate the finite sample performance and the usefulness of the proposed method, respectively. PMID:28663668

Testing a single regression coefficient in high dimensional linear models.

PubMed

Lan, Wei; Zhong, Ping-Shou; Li, Runze; Wang, Hansheng; Tsai, Chih-Ling

2016-11-01

In linear regression models with high dimensional data, the classical z -test (or t -test) for testing the significance of each single regression coefficient is no longer applicable. This is mainly because the number of covariates exceeds the sample size. In this paper, we propose a simple and novel alternative by introducing the Correlated Predictors Screening (CPS) method to control for predictors that are highly correlated with the target covariate. Accordingly, the classical ordinary least squares approach can be employed to estimate the regression coefficient associated with the target covariate. In addition, we demonstrate that the resulting estimator is consistent and asymptotically normal even if the random errors are heteroscedastic. This enables us to apply the z -test to assess the significance of each covariate. Based on the p -value obtained from testing the significance of each covariate, we further conduct multiple hypothesis testing by controlling the false discovery rate at the nominal level. Then, we show that the multiple hypothesis testing achieves consistent model selection. Simulation studies and empirical examples are presented to illustrate the finite sample performance and the usefulness of the proposed method, respectively.

The geographic location (latitude) of studies evaluating protective effect of BCG vaccine and it's efficacy/effectiveness against tuberculosis.

PubMed

Zodpey, Sanjay P; Shrikhande, Sunanda N

2007-01-01

To study association between the geographic location (latitude) of studies evaluating protective effect of BCG vaccine and it's efficacy / effectiveness against tuberculosis. A comprehensive literature search was carried out to identify relevant studies. Data extraction from these studies included place of study (geographic latitude), study design and reported point estimate of protective effect of BCG vaccine against tuberculosis. Information on latitude was obtained from Oxford School Atlas for World Geography. A spearman rank correlation coefficient was estimated to study the association between the latitude of studies and protective effect of BCG vaccine. The Spearman's rank correlation coefficient was significant for all studies grouped together & trials and marginally non-significant for other observational studies. However it was not statistically significant for case-control studies and cohort studies. Overall rho (for 80 studies) between latitude and protective effect of BCG was calculated to be 0.3853 (p = 0.0004). The results thus demonstrated that, in general BCG appeared to provide greater protection at higher latitudes. Thus a correlation coefficient of 0.3853 between latitude and protective effect would indicate that (0.3853)(2) or 15% of the variance in protective effect was accounted for by latitude. The study recognized an association between geographic locations of studies and reported protective effects of BCG vaccine against tuberculosis.

Prediction of blood-brain partitioning: a model based on molecular electronegativity distance vector descriptors.

PubMed

Zhang, Yong-Hong; Xia, Zhi-Ning; Qin, Li-Tang; Liu, Shu-Shen

2010-09-01

The objective of this paper is to build a reliable model based on the molecular electronegativity distance vector (MEDV) descriptors for predicting the blood-brain barrier (BBB) permeability and to reveal the effects of the molecular structural segments on the BBB permeability. Using 70 structurally diverse compounds, the partial least squares regression (PLSR) models between the BBB permeability and the MEDV descriptors were developed and validated by the variable selection and modeling based on prediction (VSMP) technique. The estimation ability, stability, and predictive power of a model are evaluated by the estimated correlation coefficient (r), leave-one-out (LOO) cross-validation correlation coefficient (q), and predictive correlation coefficient (R(p)). It has been found that PLSR model has good quality, r=0.9202, q=0.7956, and R(p)=0.6649 for M1 model based on the training set of 57 samples. To search the most important structural factors affecting the BBB permeability of compounds, we performed the values of the variable importance in projection (VIP) analysis for MEDV descriptors. It was found that some structural fragments in compounds, such as -CH(3), -CH(2)-, =CH-, =C, triple bond C-, -CH<, =C<, =N-, -NH-, =O, and -OH, are the most important factors affecting the BBB permeability. (c) 2010. Published by Elsevier Inc.

Calculating sediment discharge from a highway construction site in central Pennsylvania

USGS Publications Warehouse

Reed, L.A.; Ward, J.R.; Wetzel, K.L.

1985-01-01

The Pennsylvania Department of Transportation, the Federal Highway Administration, and the U.S. Geological Survey have cooperated in a study to evaluate two methods of predicting sediment yields during highway construction. Sediment yields were calculated using the Universal Soil Loss and the Younkin Sediment Prediction Equations. Results were compared to the actual measured values, and standard errors and coefficients of correlation were calculated. Sediment discharge from the construction area was determined for storms that occurred during construction of Interstate 81 in a 0.38-square mile basin near Harrisburg, Pennsylvania. Precipitation data tabulated included total rainfall, maximum 30-minute rainfall, kinetic energy, and the erosive index of the precipitation. Highway construction data tabulated included the area disturbed by clearing and grubbing, the area in cuts and fills, the average depths of cuts and fills, the area seeded and mulched, and the area paved. Using the Universal Soil Loss Equation, sediment discharge from the construction area was calculated for storms. The standard error of estimate was 0.40 (about 105 percent), and the coefficient of correlation was 0.79. Sediment discharge from the construction area was also calculated using the Younkin Equation. The standard error of estimate of 0.42 (about 110 percent), and the coefficient of correlation of 0.77 are comparable to those from the Universal Soil Loss Equation.

Revisiting crash spatial heterogeneity: A Bayesian spatially varying coefficients approach.

PubMed

Xu, Pengpeng; Huang, Helai; Dong, Ni; Wong, S C

2017-01-01

This study was performed to investigate the spatially varying relationships between crash frequency and related risk factors. A Bayesian spatially varying coefficients model was elaborately introduced as a methodological alternative to simultaneously account for the unstructured and spatially structured heterogeneity of the regression coefficients in predicting crash frequencies. The proposed method was appealing in that the parameters were modeled via a conditional autoregressive prior distribution, which involved a single set of random effects and a spatial correlation parameter with extreme values corresponding to pure unstructured or pure spatially correlated random effects. A case study using a three-year crash dataset from the Hillsborough County, Florida, was conducted to illustrate the proposed model. Empirical analysis confirmed the presence of both unstructured and spatially correlated variations in the effects of contributory factors on severe crash occurrences. The findings also suggested that ignoring spatially structured heterogeneity may result in biased parameter estimates and incorrect inferences, while assuming the regression coefficients to be spatially clustered only is probably subject to the issue of over-smoothness. Copyright © 2016 Elsevier Ltd. All rights reserved.

Inversion of multi-frequency electromagnetic induction data for 3D characterization of hydraulic conductivity

USGS Publications Warehouse

Brosten, Troy R.; Day-Lewis, Frederick D.; Schultz, Gregory M.; Curtis, Gary P.; Lane, John W.

2011-01-01

Electromagnetic induction (EMI) instruments provide rapid, noninvasive, and spatially dense data for characterization of soil and groundwater properties. Data from multi-frequency EMI tools can be inverted to provide quantitative electrical conductivity estimates as a function of depth. In this study, multi-frequency EMI data collected across an abandoned uranium mill site near Naturita, Colorado, USA, are inverted to produce vertical distribution of electrical conductivity (EC) across the site. The relation between measured apparent electrical conductivity (ECa) and hydraulic conductivity (K) is weak (correlation coefficient of 0.20), whereas the correlation between the depth dependent EC obtained from the inversions, and K is sufficiently strong to be used for hydrologic estimation (correlation coefficient of − 0.62). Depth-specific EC values were correlated with co-located K measurements to develop a site-specific ln(EC)–ln(K) relation. This petrophysical relation was applied to produce a spatially detailed map of K across the study area. A synthetic example based on ECa values at the site was used to assess model resolution and correlation loss given variations in depth and/or measurement error. Results from synthetic modeling indicate that optimum correlation with K occurs at ~ 0.5 m followed by a gradual correlation loss of 90% at 2.3 m. These results are consistent with an analysis of depth of investigation (DOI) given the range of frequencies, transmitter–receiver separation, and measurement errors for the field data. DOIs were estimated at 2.0 ± 0.5 m depending on the soil conductivities. A 4-layer model, with varying thicknesses, was used to invert the ECa to maximize available information within the aquifer region for improved correlations with K. Results show improved correlation between K and the corresponding inverted EC at similar depths, underscoring the importance of inversion in using multi-frequency EMI data for hydrologic estimation.

Inversion of multi-frequency electromagnetic induction data for 3D characterization of hydraulic conductivity

USGS Publications Warehouse

Brosten, T.R.; Day-Lewis, F. D.; Schultz, G.M.; Curtis, G.P.; Lane, J.W.

2011-01-01

Electromagnetic induction (EMI) instruments provide rapid, noninvasive, and spatially dense data for characterization of soil and groundwater properties. Data from multi-frequency EMI tools can be inverted to provide quantitative electrical conductivity estimates as a function of depth. In this study, multi-frequency EMI data collected across an abandoned uranium mill site near Naturita, Colorado, USA, are inverted to produce vertical distribution of electrical conductivity (EC) across the site. The relation between measured apparent electrical conductivity (ECa) and hydraulic conductivity (K) is weak (correlation coefficient of 0.20), whereas the correlation between the depth dependent EC obtained from the inversions, and K is sufficiently strong to be used for hydrologic estimation (correlation coefficient of -0.62). Depth-specific EC values were correlated with co-located K measurements to develop a site-specific ln(EC)-ln(K) relation. This petrophysical relation was applied to produce a spatially detailed map of K across the study area. A synthetic example based on ECa values at the site was used to assess model resolution and correlation loss given variations in depth and/or measurement error. Results from synthetic modeling indicate that optimum correlation with K occurs at ~0.5m followed by a gradual correlation loss of 90% at 2.3m. These results are consistent with an analysis of depth of investigation (DOI) given the range of frequencies, transmitter-receiver separation, and measurement errors for the field data. DOIs were estimated at 2.0??0.5m depending on the soil conductivities. A 4-layer model, with varying thicknesses, was used to invert the ECa to maximize available information within the aquifer region for improved correlations with K. Results show improved correlation between K and the corresponding inverted EC at similar depths, underscoring the importance of inversion in using multi-frequency EMI data for hydrologic estimation. ?? 2011.

Efficient Strategies for Estimating the Spatial Coherence of Backscatter

PubMed Central

Hyun, Dongwoon; Crowley, Anna Lisa C.; Dahl, Jeremy J.

2017-01-01

The spatial coherence of ultrasound backscatter has been proposed to reduce clutter in medical imaging, to measure the anisotropy of the scattering source, and to improve the detection of blood flow. These techniques rely on correlation estimates that are obtained using computationally expensive strategies. In this study, we assess existing spatial coherence estimation methods and propose three computationally efficient modifications: a reduced kernel, a downsampled receive aperture, and the use of an ensemble correlation coefficient. The proposed methods are implemented in simulation and in vivo studies. Reducing the kernel to a single sample improved computational throughput and improved axial resolution. Downsampling the receive aperture was found to have negligible effect on estimator variance, and improved computational throughput by an order of magnitude for a downsample factor of 4. The ensemble correlation estimator demonstrated lower variance than the currently used average correlation. Combining the three methods, the throughput was improved 105-fold in simulation with a downsample factor of 4 and 20-fold in vivo with a downsample factor of 2. PMID:27913342

Patient-specific radiation dose and cancer risk estimation in pediatric chest CT: a study in 30 patients

NASA Astrophysics Data System (ADS)

Li, Xiang; Samei, Ehsan; Segars, W. Paul; Sturgeon, Gregory M.; Colsher, James G.; Frush, Donald P.

2010-04-01

Radiation-dose awareness and optimization in CT can greatly benefit from a dosereporting system that provides radiation dose and cancer risk estimates specific to each patient and each CT examination. Recently, we reported a method for estimating patientspecific dose from pediatric chest CT. The purpose of this study is to extend that effort to patient-specific risk estimation and to a population of pediatric CT patients. Our study included thirty pediatric CT patients (16 males and 14 females; 0-16 years old), for whom full-body computer models were recently created based on the patients' clinical CT data. Using a validated Monte Carlo program, organ dose received by the thirty patients from a chest scan protocol (LightSpeed VCT, 120 kVp, 1.375 pitch, 40-mm collimation, pediatric body scan field-of-view) was simulated and used to estimate patient-specific effective dose. Risks of cancer incidence were calculated for radiosensitive organs using gender-, age-, and tissue-specific risk coefficients and were used to derive patientspecific effective risk. The thirty patients had normalized effective dose of 3.7-10.4 mSv/100 mAs and normalized effective risk of 0.5-5.8 cases/1000 exposed persons/100 mAs. Normalized lung dose and risk of lung cancer correlated strongly with average chest diameter (correlation coefficient: r = -0.98 to -0.99). Normalized effective risk also correlated strongly with average chest diameter (r = -0.97 to -0.98). These strong correlations can be used to estimate patient-specific dose and risk prior to or after an imaging study to potentially guide healthcare providers in justifying CT examinations and to guide individualized protocol design and optimization.

Efficiency of including first-generation information in second-generation ranking and selection: results of computer simulation.

Treesearch

T.Z. Ye; K.J.S. Jayawickrama; G.R. Johnson

2006-01-01

Using computer simulation, we evaluated the impact of using first-generation information to increase selection efficiency in a second-generation breeding program. Selection efficiency was compared in terms of increase in rank correlation between estimated and true breeding values (i.e., ranking accuracy), reduction in coefficient of variation of correlation...

Introduction and application of the multiscale coefficient of variation analysis.

PubMed

Abney, Drew H; Kello, Christopher T; Balasubramaniam, Ramesh

2017-10-01

Quantifying how patterns of behavior relate across multiple levels of measurement typically requires long time series for reliable parameter estimation. We describe a novel analysis that estimates patterns of variability across multiple scales of analysis suitable for time series of short duration. The multiscale coefficient of variation (MSCV) measures the distance between local coefficient of variation estimates within particular time windows and the overall coefficient of variation across all time samples. We first describe the MSCV analysis and provide an example analytical protocol with corresponding MATLAB implementation and code. Next, we present a simulation study testing the new analysis using time series generated by ARFIMA models that span white noise, short-term and long-term correlations. The MSCV analysis was observed to be sensitive to specific parameters of ARFIMA models varying in the type of temporal structure and time series length. We then apply the MSCV analysis to short time series of speech phrases and musical themes to show commonalities in multiscale structure. The simulation and application studies provide evidence that the MSCV analysis can discriminate between time series varying in multiscale structure and length.

Reliability of the Brazilian version of the Physical Activity Checklist Interview in children.

PubMed

Adami, Fernando; Cruciani, Fernanda; Douek, Michelle; Sewell, Carolina Dumit; Mariath, Aline Brandão; Hinnig, Patrícia de Fragas; Freaza, Silvia Rafaela Mascarenhas; Bergamaschi, Denise Pimentel

2011-04-01

To assess the reliability of the Lista de Atividades Físicas (Brazilian version of the Physical Activity Checklist Interview) in children. The study is part of a cross-cultural adaptation of the Physical Activity Checklist Interview, conducted with 83 school children aged between seven and ten years, enrolled between the 2nd and 5th grades of primary education in the city of São Paulo, Southeastern Brazil, in 2008. The questionnaire was responded by children through individual interviews. It is comprised of a list of 21 moderate to vigorous physical activities performed on the previous day, it is divided into periods (before, during and after school) and it has a section for interview assessment. This questionnaire enables the quantification of time spent in physical and sedentary activities and the total and weighed metabolic costs. Reliability was assessed by comparing two interviews conducted with a mean interval of three hours. For the interview assessment, data from the first interview and those from an external evaluator were compared. Bland-Altman's proposal, the intraclass correlation coefficient and Lin's concordance correlation coefficient were used to assess reliability. The intraclass correlation coefficient lower limits for the outcomes analyzed varied from 0.84 to 0.96. Precision and agreement varied between 0.83 and 0.97 and between 0.99 and 1, respectively. The line estimated from the pairs of values obtained in both interviews indicates high data precision. The interview item showing the poorest result was the ability to estimate time (fair in 27.7% of interviews). Interview assessment items showed intraclass correlation coefficients between 0.60 and 0.70, except for level of cooperation (0.46). The Brazilian version of the Physical Activity Checklist Interview shows high reliability to assess physical and sedentary activity on the previous day in children.

Effective record length for the T-year event

USGS Publications Warehouse

Tasker, Gary D.

1983-01-01

The effect of serial dependence on the reliability of an estimate of the T-yr. event is of importance in hydrology because design decisions are based upon the estimate. In this paper the reliability of estimates of the T-yr. event from two common distributions is given as a function of number of observations and lag-one serial correlation coefficient for T = 2, 10, 20, 50, and 100 yr. A lag-one autoregressive model is assumed with either a normal or Pearson Type-III disturbance term. Results indicate that, if observations are serially correlated, the effective record length should be used to estimate the discharge associated with the expected exceedance probability. ?? 1983.

Genotypic gain with simultaneous selection of production, nutrition, and culinary traits in cowpea crosses and backcrosses using mixed models.

PubMed

Oliveira, D G; Rocha, M M; Damasceno-Silva, K J; Sá, F V; Lima, L R L; Resende, M D V

2017-08-17

The aim of this study was to estimate the genotypic gain with simultaneous selection of production, nutrition, and culinary traits in cowpea crosses and backcrosses and to compare different selection indexes. Eleven cowpea populations were evaluated in a randomized complete block design with four replications. Fourteen traits were evaluated, and the following parameters were estimated: genotypic variation coefficient, genotypic determination coefficient, experimental quality indicator and selection reliability, estimated genotypic values ​​- BLUE, genotypic correlation coefficient among traits, and genotypic gain with simultaneous selection of all traits. The genotypic gain was estimated based on tree selection indexes: classical, multiplicative, and the sum of ranks. The genotypic variation coefficient was higher than the environmental variation coefficient for the number of days to start flowering, plant type, the weight of one hundred grains, grain index, and protein concentration. The majority of the traits presented genotypic determination coefficient from medium to high magnitude. The identification of increases in the production components is associated with decreases in protein concentration, and the increase in precocity leads to decreases in protein concentration and cooking time. The index based on the sum of ranks was the best alternative for simultaneous selection of traits in the cowpea segregating populations resulting from the crosses and backcrosses evaluated, with emphasis on the F 4 BC 12 , F 4 C 21 , and F 4 C 12 populations, which had the highest genotypic gains.

Importance of Preserving Cross-correlation in developing Statistically Downscaled Climate Forcings and in estimating Land-surface Fluxes and States

NASA Astrophysics Data System (ADS)

Das Bhowmik, R.; Arumugam, S.

2015-12-01

Multivariate downscaling techniques exhibited superiority over univariate regression schemes in terms of preserving cross-correlations between multiple variables- precipitation and temperature - from GCMs. This study focuses on two aspects: (a) develop an analytical solutions on estimating biases in cross-correlations from univariate downscaling approaches and (b) quantify the uncertainty in land-surface states and fluxes due to biases in cross-correlations in downscaled climate forcings. Both these aspects are evaluated using climate forcings available from both historical climate simulations and CMIP5 hindcasts over the entire US. The analytical solution basically relates the univariate regression parameters, co-efficient of determination of regression and the co-variance ratio between GCM and downscaled values. The analytical solutions are compared with the downscaled univariate forcings by choosing the desired p-value (Type-1 error) in preserving the observed cross-correlation. . For quantifying the impacts of biases on cross-correlation on estimating streamflow and groundwater, we corrupt the downscaled climate forcings with different cross-correlation structure.

Estimating leaf nitrogen accumulation in maize based on canopy hyperspectrum data

NASA Astrophysics Data System (ADS)

Gu, Xiaohe; Wang, Lizhi; Song, Xiaoyu; Xu, Xingang

2016-10-01

Leaf nitrogen accumulation (LNA) has important influence on the formation of crop yield and grain protein. Monitoring leaf nitrogen accumulation of crop canopy quantitively and real-timely is helpful for mastering crop nutrition status, diagnosing group growth and managing fertilization precisely. The study aimed to develop a universal method to monitor LNA of maize by hyperspectrum data, which could provide mechanism support for mapping LNA of maize at county scale. The correlations between LNA and hyperspectrum reflectivity and its mathematical transformations were analyzed. Then the feature bands and its transformations were screened to develop the optimal model of estimating LNA based on multiple linear regression method. The in-situ samples were used to evaluate the accuracy of the estimating model. Results showed that the estimating model with one differential logarithmic transformation (lgP') of reflectivity could reach highest correlation coefficient (0.889) with lowest RMSE (0.646 g·m-2), which was considered as the optimal model for estimating LNA in maize. The determination coefficient (R2) of testing samples was 0.831, while the RMSE was 1.901 g·m-2. It indicated that the one differential logarithmic transformation of hyperspectrum had good response with LNA of maize. Based on this transformation, the optimal estimating model of LNA could reach good accuracy with high stability.

Reproducibility of food consumption frequencies derived from the Children's Eating Habits Questionnaire used in the IDEFICS study.

PubMed

Lanfer, A; Hebestreit, A; Ahrens, W; Krogh, V; Sieri, S; Lissner, L; Eiben, G; Siani, A; Huybrechts, I; Loit, H-M; Papoutsou, S; Kovács, E; Pala, V

2011-04-01

To investigate the reproducibility of food consumption frequencies derived from the food frequency section of the Children's Eating Habits Questionnaire (CEHQ-FFQ) that was developed and used in the IDEFICS (Identification and prevention of dietary- and lifestyle-induced health effects in children and infants) project to assess food habits in 2- to 9-year-old European children. From a subsample of 258 children who participated in the IDEFICS baseline examination, parental questionnaires of the CEHQ were collected twice to assess reproducibility of questionnaire results from 0 to 354 days after the first examination. Weighted Cohen's kappa coefficients (κ) and Spearman's correlation coefficients (r) were calculated to assess agreement between the first and second questionnaires for each food item of the CEHQ-FFQ. Stratification was performed for sex, age group, geographical region and length of period between the first and second administrations. Fisher's Z transformation was applied to test correlation coefficients for significant differences between strata. For all food items analysed, weighted Cohen's kappa coefficients (κ) and Spearman's correlation coefficients (r) were significant and positive (P<0.001). Reproducibility was lowest for diet soft drinks (κ=0.23, r=0.32) and highest for sweetened milk (κ=0.68, r=0.76). Correlation coefficients were comparable to those of previous studies on FFQ reproducibility in children and adults. Stratification did not reveal systematic differences in reproducibility by sex and age group. Spearman's correlation coefficients differed significantly between northern and southern European countries for 10 food items. In nine of them, the lower respective coefficient was still high enough to conclude acceptable reproducibility. As expected, longer time (>128 days) between the first and second administrations resulted in a generally lower, yet still acceptable, reproducibility. Results indicate that the CEHQ-FFQ gives reproducible estimates of the consumption frequency of 43 food items from 14 food groups in European children.

[Estimation of rice LAI by using NDVI at different spectral bandwidths].

PubMed

Wang, Fu-min; Huang, Jing-feng; Tang, Yan-lin; Wang, Xiu-zhen

2007-11-01

The canopy hyperspectral reflectance data of rice at its different development stages were collected from field measurement, and the corresponding NDVIs as well as the correlation coefficients of NDVIs and LAI were computed at extending bandwidth of TM red and near-infrared (NIR) spectra. According to the variation characteristics of best fitted R2 with spectral bandwidth, the optimal bandwidth was determined. The results showed that the correlation coefficients of LAI and ND-VI and the maximum R2 of the best fitted functions at different spectral bandwidths had the same variation trend, i.e., decreased with increasing bandwidth when the bandwidth was less than 60 nm. However, when the bandwidth was beyond 60 nm, the maximum R2 somewhat fluctuated due to the effect of NIR. The analysis of R2 variation with bandwidth indicated that 15 nm was the optimal bandwidth for the estimation of rice LAI by using NDVI.

CORRELATED AND ZONAL ERRORS OF GLOBAL ASTROMETRIC MISSIONS: A SPHERICAL HARMONIC SOLUTION

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

Makarov, V. V.; Dorland, B. N.; Gaume, R. A.

We propose a computer-efficient and accurate method of estimating spatially correlated errors in astrometric positions, parallaxes, and proper motions obtained by space- and ground-based astrometry missions. In our method, the simulated observational equations are set up and solved for the coefficients of scalar and vector spherical harmonics representing the output errors rather than for individual objects in the output catalog. Both accidental and systematic correlated errors of astrometric parameters can be accurately estimated. The method is demonstrated on the example of the JMAPS mission, but can be used for other projects in space astrometry, such as SIM or JASMINE.

Correlated and Zonal Errors of Global Astrometric Missions: A Spherical Harmonic Solution

NASA Astrophysics Data System (ADS)

Makarov, V. V.; Dorland, B. N.; Gaume, R. A.; Hennessy, G. S.; Berghea, C. T.; Dudik, R. P.; Schmitt, H. R.

2012-07-01

We propose a computer-efficient and accurate method of estimating spatially correlated errors in astrometric positions, parallaxes, and proper motions obtained by space- and ground-based astrometry missions. In our method, the simulated observational equations are set up and solved for the coefficients of scalar and vector spherical harmonics representing the output errors rather than for individual objects in the output catalog. Both accidental and systematic correlated errors of astrometric parameters can be accurately estimated. The method is demonstrated on the example of the JMAPS mission, but can be used for other projects in space astrometry, such as SIM or JASMINE.

Tmax Determined Using a Bayesian Estimation Deconvolution Algorithm Applied to Bolus Tracking Perfusion Imaging: A Digital Phantom Validation Study.

PubMed

Uwano, Ikuko; Sasaki, Makoto; Kudo, Kohsuke; Boutelier, Timothé; Kameda, Hiroyuki; Mori, Futoshi; Yamashita, Fumio

2017-01-10

The Bayesian estimation algorithm improves the precision of bolus tracking perfusion imaging. However, this algorithm cannot directly calculate Tmax, the time scale widely used to identify ischemic penumbra, because Tmax is a non-physiological, artificial index that reflects the tracer arrival delay (TD) and other parameters. We calculated Tmax from the TD and mean transit time (MTT) obtained by the Bayesian algorithm and determined its accuracy in comparison with Tmax obtained by singular value decomposition (SVD) algorithms. The TD and MTT maps were generated by the Bayesian algorithm applied to digital phantoms with time-concentration curves that reflected a range of values for various perfusion metrics using a global arterial input function. Tmax was calculated from the TD and MTT using constants obtained by a linear least-squares fit to Tmax obtained from the two SVD algorithms that showed the best benchmarks in a previous study. Correlations between the Tmax values obtained by the Bayesian and SVD methods were examined. The Bayesian algorithm yielded accurate TD and MTT values relative to the true values of the digital phantom. Tmax calculated from the TD and MTT values with the least-squares fit constants showed excellent correlation (Pearson's correlation coefficient = 0.99) and agreement (intraclass correlation coefficient = 0.99) with Tmax obtained from SVD algorithms. Quantitative analyses of Tmax values calculated from Bayesian-estimation algorithm-derived TD and MTT from a digital phantom correlated and agreed well with Tmax values determined using SVD algorithms.

Estimation of vegetation parameters such as Leaf Area Index from polarimetric SAR data

NASA Astrophysics Data System (ADS)

Hetz, Marina; Blumberg, Dan G.; Rotman, Stanley R.

2010-05-01

This work presents the analysis of the capability to use the radar backscatter coefficient in semi-arid zones to estimate the vegetation crown in terms of Leaf Area Index (LAI). The research area is characterized by the presence of a pine forest with shrubs as an underlying vegetation layer (understory), olive trees, natural grove areas and eucalyptus trees. The research area was imaged by an airborne RADAR system in L-band during February 2009. The imagery includes multi-look radar images. All the images were fully polarized i.e., HH, VV, HV polarizations. For this research we used the central azimuth angle (113° ). We measured LAI using the ?T Sun Scan Canopy Analysis System. Verification was done by analytic calculations and digital methods for the leaf's and needle's surface area. In addition, we estimated the radar extinction coefficient of the vegetation volume by comparing point calibration targets (trihedral corner reflectors with 150cm side length) within and without the canopy. The radar extinction in co- polarized images was ~26dB and ~24dB for pines and olives respectively, compared to the same calibration target outside the vegetation. We used smaller trihedral corner reflectors (41cm side length) and covered them with vegetation to measure the correlation between vegetation density, LAI and radar backscatter coefficient for pines and olives under known conditions. An inverse correlation between the radar backscatter coefficient of the trihedral corner reflectors covered by olive branches and the LAI of those branches was observed. The correlation between LAI and the optical transmittance was derived using the Beer-Lambert law. In addition, comparing this law's principle to the principle of the radar backscatter coefficient production, we derived the equation that connects between the radar backscatter coefficient and LAI. After extracting the radar backscatter coefficient of forested areas, all the vegetation parameters were used as inputs for the MIMICS model that simulates the radar backscatter coefficient of pines. The model results show a backscatter of -18dB in HV polarization which is 13dB higher than the mean pines backscatter in the radar images, whereas the co-polarized images revealed a backscatter of -10dB which is 23dB higher than the actual backscatter value deriver from the radar images. Therefore, next step in the research will incorporate other vegetation parameters and attempt to understand the discrepancies between the simulation and the actual data.

Relationship of red and photographic infrared spectral radiances to alfalfa biomass, forage water content, percentage canopy cover, and severity of drought stress

NASA Technical Reports Server (NTRS)

Tucker, C. J.; Elgin, J. H., Jr.; Mcmurtrey, J. E., III

1979-01-01

Red and photographic infrared spectral data were collected using a handheld radiometer for two cuttings of alfalfa. Significant linear and non-linear correlation coefficients were found between the spectral variables and plant height, biomass, forage water content, and estimated canopy cover for the earlier alfalfa cutting. The alfalfa of later cutting experienced a period of severe drought stress which limited growth. The spectral variables were found to be highly correlated with the estimated drought scores for this alfalfa cutting.

Comparison of body mass index (BMI) with the CUN-BAE body adiposity estimator in the prediction of hypertension and type 2 diabetes.

PubMed

Martín, Vicente; Dávila-Batista, Verónica; Castilla, Jesús; Godoy, Pere; Delgado-Rodríguez, Miguel; Soldevila, Nuria; Molina, Antonio J; Fernandez-Villa, Tania; Astray, Jenaro; Castro, Ady; González-Candelas, Fernando; Mayoral, José María; Quintana, José María; Domínguez, Angela

2016-01-27

Obesity is a world-wide epidemic whose prevalence is underestimated by BMI measurements, but CUN-BAE (Clínica Universidad de Navarra - Body Adiposity Estimator) estimates the percentage of body fat (BF) while incorporating information on sex and age, thus giving a better match. Our aim is to compare the BMI and CUN-BAE in determining the population attributable fraction (AFp) for obesity as a cause of chronic diseases. We calculated the Pearson correlation coefficient between BMI and CUN-BAE, the Kappa index and the internal validity of the BMI. The risks of arterial hypertension (AHT) and diabetes mellitus (DM) and the AFp for obesity were assessed using both the BMI and CUN-BAE. 3888 white subjects were investigated. The overall correlation between BMI and CUN-BAE was R(2) = 0.48, which improved when sex and age were taken into account (R(2) > 0.90). The Kappa coefficient for diagnosis of obesity was low (28.7 %). The AFp was 50 % higher for DM and double for AHT when CUN-BAE was used. The overall correlation between BMI and CUN-BAE was not good. The AFp of obesity for AHT and DM may be underestimated if assessed using the BMI, as may the prevalence of obesity when estimated from the percentage of BF.

Histogram analysis parameters of apparent diffusion coefficient reflect tumor cellularity and proliferation activity in head and neck squamous cell carcinoma.

PubMed

Surov, Alexey; Meyer, Hans Jonas; Winter, Karsten; Richter, Cindy; Hoehn, Anna-Kathrin

2018-05-04

Our purpose was to analyze associations between apparent diffusion coefficient (ADC) histogram analysis parameters and histopathologicalfeatures in head and neck squamous cell carcinoma (HNSCC). The study involved 32 patients with primary HNSCC. For every tumor, the following histogram analysis parameters were calculated: ADCmean, ADCmax, ADC min , ADC median , ADC mode , P10, P25, P75, P90, kurtosis, skewness, and entropy. Furthermore, proliferation index KI 67, cell count, total and average nucleic areas were estimated. Spearman's correlation coefficient (p) was used to analyze associations between investigated parameters. In overall sample, all ADC values showed moderate inverse correlations with KI 67. All ADC values except ADCmax correlated inversely with tumor cellularity. Slightly correlations were identified between total/average nucleic area and ADC mean , ADC min , ADC median , and P25. In G1/2 tumors, only ADCmode correlated well with Ki67. No statistically significant correlations between ADC parameters and cellularity were found. In G3 tumors, Ki 67 correlated with all ADC parameters except ADCmode. Cell count correlated well with all ADC parameters except ADCmax. Total nucleic area correlated inversely with ADC mean , ADC min , ADC median , P25, and P90. ADC histogram parameters reflect proliferation potential and cellularity in HNSCC. The associations between histopathology and imaging depend on tumor grading.

Estimation of Rank Correlation for Clustered Data

PubMed Central

Rosner, Bernard; Glynn, Robert

2017-01-01

It is well known that the sample correlation coefficient (Rxy) is the maximum likelihood estimator (MLE) of the Pearson correlation (ρxy) for i.i.d. bivariate normal data. However, this is not true for ophthalmologic data where X (e.g., visual acuity) and Y (e.g., visual field) are available for each eye and there is positive intraclass correlation for both X and Y in fellow eyes. In this paper, we provide a regression-based approach for obtaining the MLE of ρxy for clustered data, which can be implemented using standard mixed effects model software. This method is also extended to allow for estimation of partial correlation by controlling both X and Y for a vector U of other covariates. In addition, these methods can be extended to allow for estimation of rank correlation for clustered data by (a) converting ranks of both X and Y to the probit scale, (b) estimating the Pearson correlation between probit scores for X and Y, and (c) using the relationship between Pearson and rank correlation for bivariate normally distributed data. The validity of the methods in finite-sized samples is supported by simulation studies. Finally, two examples from ophthalmology and analgesic abuse are used to illustrate the methods. PMID:28399615

A simple method to estimate restoration volume as a possible predictor for tooth fracture.

PubMed

Sturdevant, J R; Bader, J D; Shugars, D A; Steet, T C

2003-08-01

Many dentists cite the fracture risk posed by a large existing restoration as a primary reason for their decision to place a full-coverage restoration. However, there is poor agreement among dentists as to when restoration placement is necessary because of the inability to make objective measurements of restoration size. The purpose of this study was to compare a new method to estimate restoration volumes in posterior teeth with analytically determined volumes. True restoration volume proportion (RVP) was determined for 96 melamine typodont teeth: 24 each of maxillary second premolar, mandibular second premolar, maxillary first molar, and mandibular first molar. Each group of 24 was subdivided into 3 groups to receive an O, MO, or MOD amalgam preparation design. Each preparation design was further subdivided into 4 groups of increasingly larger size. The density of amalgam used was calculated according to ANSI/ADA Specification 1. The teeth were weighed before and after restoration with amalgam. Restoration weight was calculated, and the density of amalgam was used to calculate restoration volume. A liquid pycnometer was used to calculate coronal volume after sectioning the anatomic crown from the root horizontally at the cementoenamel junction. True RVP was calculated by dividing restoration volume by coronal volume. An occlusal photograph and a bitewing radiograph were made of each restored tooth to provide 2 perpendicular views. Each image was digitized, and software was used to measure the percentage of the anatomic crown restored with amalgam. Estimated RVP was calculated by multiplying the percentage of the anatomic crown restored from the 2 views together. Pearson correlation coefficients were used to compare estimated RVP with true RVP. The Pearson correlation coefficient of true RVP with estimated RVP was 0.97 overall (P

High inter-rater reliability, agreement, and convergent validity of Constant score in patients with clavicle fractures.

PubMed

Ban, Ilija; Troelsen, Anders; Kristensen, Morten Tange

2016-10-01

The Constant score (CS) has been the primary endpoint in most studies on clavicle fractures. However, the CS was not developed to assess patients with clavicle fractures. Our aim was to examine inter-rater reliability and agreement of the CS in patients with clavicle fractures. The secondary aim was to estimate the correlation between the CS and the Disabilities of the Arm, Shoulder and Hand score and the internal consistency of the 2 scores. On the basis of sample sizing, 36 patients (31 male and 5 female patients; mean age, 41.3 years) with clavicle fractures underwent standardized CS assessment at a mean of 6.8 weeks (SD, 1.0 weeks) after injury. Reliability and agreement of the CS were determined by 2 raters. The interclass correlation coefficient (ICC2,1), standard error of measurement, minimal detectable change, Cronbach α coefficient, and Pearson correlation coefficient were estimated. Inter-rater reliability of the total CS was excellent (interclass correlation coefficient, 0.94; 95% confidence interval, 0.88-0.97), with no systematic difference between the 2 raters (P = .75). The standard error of measurement (measurement error at the group level) was 4.9, whereas the minimal detectable change (smallest change needed to indicate a real change for an individual) was 13.6 CS points. The internal consistency of the 10 CS items was good, with a Cronbach α of .85, and we found a strong correlation (r = -0.92) between the CS and Disabilities of the Arm, Shoulder and Hand score. The CS was found to be reliable for assessing patients with clavicle fractures, especially at the group level. With high inter-rater reliability and agreement, in addition to good internal consistency, the standardized CS used in this study can be used for comparison of results from different settings. Copyright © 2016 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

Improving Assessment of Lifetime Solar Ultraviolet Radiation Exposure in Epidemiologic Studies: Comparison of Ultraviolet Exposure Assessment Methods in a Nationwide United States Occupational Cohort.

PubMed

Little, Mark P; Tatalovich, Zaria; Linet, Martha S; Fang, Michelle; Kendall, Gerald M; Kimlin, Michael G

2018-06-13

Solar ultraviolet radiation is the primary risk factor for skin cancers and sun-related eye disorders. Estimates of individual ambient ultraviolet irradiance derived from ground-based solar measurements and from satellite measurements have rarely been compared. Using self-reported residential history from 67,189 persons in a nationwide occupational US radiologic technologists cohort, we estimated ambient solar irradiance using data from ground-based meters and noontime satellite measurements. The mean distance-moved from city of longest residence in childhood increased from 137.6 km at ages 13-19 to 870.3 km at ages ≥65, with corresponding increases in absolute latitude-difference moved. At ages 20/40/60/80, the Pearson/Spearman correlation coefficients of ground-based and satellite-derived solar potential ultraviolet exposure, using irradiance and cumulative radiant-exposure metrics, were high (=0.87-0.92). There was also moderate correlation (Pearson/Spearman correlation coefficients=0.51-0.60) between irradiance at birth and at last-known address, for ground-based and satellite data. Satellite-based lifetime estimates of ultraviolet radiation were generally 14-15% lower than ground-based estimates, albeit with substantial uncertainties, possibly because ground-based estimates incorporate fluctuations in cloud and ozone, which are incompletely incorporated in the single noontime satellite-overpass ultraviolet value. If confirmed elsewhere, the findings suggest that ground-based estimates may improve exposure-assessment accuracy and potentially provide new insights into ultraviolet-radiation-disease relationships in epidemiologic studies. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Estimating endogenous changes in task performance from EEG

PubMed Central

Touryan, Jon; Apker, Gregory; Lance, Brent J.; Kerick, Scott E.; Ries, Anthony J.; McDowell, Kaleb

2014-01-01

Brain wave activity is known to correlate with decrements in behavioral performance as individuals enter states of fatigue, boredom, or low alertness.Many BCI technologies are adversely affected by these changes in user state, limiting their application and constraining their use to relatively short temporal epochs where behavioral performance is likely to be stable. Incorporating a passive BCI that detects when the user is performing poorly at a primary task, and adapts accordingly may prove to increase overall user performance. Here, we explore the potential for extending an established method to generate continuous estimates of behavioral performance from ongoing neural activity; evaluating the extended method by applying it to the original task domain, simulated driving; and generalizing the method by applying it to a BCI-relevant perceptual discrimination task. Specifically, we used EEG log power spectra and sequential forward floating selection (SFFS) to estimate endogenous changes in behavior in both a simulated driving task and a perceptual discrimination task. For the driving task the average correlation coefficient between the actual and estimated lane deviation was 0.37 ± 0.22 (μ ± σ). For the perceptual discrimination task we generated estimates of accuracy, reaction time, and button press duration for each participant. The correlation coefficients between the actual and estimated behavior were similar for these three metrics (accuracy = 0.25 ± 0.37, reaction time = 0.33 ± 0.23, button press duration = 0.36 ± 0.30). These findings illustrate the potential for modeling time-on-task decrements in performance from concurrent measures of neural activity. PMID:24994968

Estimating biomass of shrubs and forbs in central Washington Douglas-fir stands.

Treesearch

Craig M. Olson; Robert E. Martin

1981-01-01

Understory plants in closed 70-year-old even-aged Douglas-fir stands in north central Washington were destructively sampled to determine the relationship of ground cover and height to dry weight. Weight of plant material can be estimated from the product of plant height and percentage of ground cover on 50- x 100-centimeter (cm) quadrats. Correlation coefficients for...

Estimates of Intraclass Correlation Coefficients from Longitudinal Group-Randomized Trials of Adolescent HIV/STI/Pregnancy Prevention Programs

ERIC Educational Resources Information Center

Glassman, Jill R.; Potter, Susan C.; Baumler, Elizabeth R.; Coyle, Karin K.

2015-01-01

Introduction: Group-randomized trials (GRTs) are one of the most rigorous methods for evaluating the effectiveness of group-based health risk prevention programs. Efficiently designing GRTs with a sample size that is sufficient for meeting the trial's power and precision goals while not wasting resources exceeding them requires estimates of the…

Estimation of rank correlation for clustered data.

PubMed

Rosner, Bernard; Glynn, Robert J

2017-06-30

It is well known that the sample correlation coefficient (R xy ) is the maximum likelihood estimator of the Pearson correlation (ρ xy ) for independent and identically distributed (i.i.d.) bivariate normal data. However, this is not true for ophthalmologic data where X (e.g., visual acuity) and Y (e.g., visual field) are available for each eye and there is positive intraclass correlation for both X and Y in fellow eyes. In this paper, we provide a regression-based approach for obtaining the maximum likelihood estimator of ρ xy for clustered data, which can be implemented using standard mixed effects model software. This method is also extended to allow for estimation of partial correlation by controlling both X and Y for a vector U_ of other covariates. In addition, these methods can be extended to allow for estimation of rank correlation for clustered data by (i) converting ranks of both X and Y to the probit scale, (ii) estimating the Pearson correlation between probit scores for X and Y, and (iii) using the relationship between Pearson and rank correlation for bivariate normally distributed data. The validity of the methods in finite-sized samples is supported by simulation studies. Finally, two examples from ophthalmology and analgesic abuse are used to illustrate the methods. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

The Stayhealthy bioelectrical impedance analyzer predicts body fat in children and adults.

PubMed

Erceg, David N; Dieli-Conwright, Christina M; Rossuello, Amerigo E; Jensky, Nicole E; Sun, Stephanie; Schroeder, E Todd

2010-05-01

Bioelectrical impedance analysis (BIA) is a time-efficient and cost-effective method for estimating body composition. We hypothesized that there would be no significant difference between the Stayhealthy BC1 BIA and the selected reference methods when determining body composition. Thus, the purpose of the present study was to determine the validity of estimating percent body fat (%BF) using the Stayhealthy BIA with its most recently updated algorithms compared to the reference methods of dual-energy x-ray absorptiometry for adults and hydrostatic weighing for children. We measured %BF in 245 adults aged 18 to 80 years and 115 children aged 10 to 17 years. Body fat by BIA was determined using a single 50 kHz frequency handheld impedance device and proprietary software. Agreement between BIA and reference methods was assessed by Bland and Altman plots. Bland and Altman analysis for men, women, and children revealed good agreement between the reference methods and BIA. There was no significant difference by t tests between mean %BF by BIA for men, women, or children when compared to the respective reference method. Significant correlation values between BIA, and reference methods for all men, women, and children were 0.85, 0.88, and 0.79, respectively. Reliability (test-retest) was assessed by intraclass correlation coefficient and coefficient of variation. Intraclass correlation coefficient values were greater than 0.99 (P < .001) for men, women, and children with coefficient of variation values 3.3%, 1.8%, and 1.7%, respectively. The Stayhealthy BIA device demonstrated good agreement between reference methods using Bland and Altman analyses. Copyright 2010 Elsevier Inc. All rights reserved.

Income inequality, disinvestment in health care and use of dental services.

PubMed

Bhandari, Bishal; Newton, Jonathan T; Bernabé, Eduardo

2015-01-01

To explore the interrelationships between income inequality, disinvestment in health care, and use of dental services at country level. This study pooled national estimates for use of dental services among adults aged 18 years or older from the 70 countries that participated in the World Health Survey from 2002 to 2004, together with aggregate data on national income (GDP per capita), income inequality (Gini coefficient), and disinvestment in health care (total health expenditure and dentist-to-population ratio) from various international sources. Use of dental services was defined as having had dental problems in the last 12 months and having received any treatment to address those needs. Associations between variables were explored using Pearson correlation coefficients and linear regression. Data from 63 countries representing the six WHO regions were analyzed. Use of dental services was negatively correlated with Gini coefficient (Pearson correlation coefficient -0.48, P < 0.001) and positively correlated with GDP per capita (0.40, P < 0.05), total health expenditure (0.45, P < 0.001), and dentist-to-population ratio (0.67, P < 0.001). The association between Gini coefficient and use of dental services was attenuated but remained significant after adjustments for GDP per capita, total health expenditure, and dentist-to-population ratio (regression coefficient -0.36; 95% CI -0.57, -0.15). This study shows an inverse relationship between income inequality and use of dental services. Of the two indicators of disinvestment in health care assessed, only dentist-to-population ratio was associated with income inequality and use of dental services. © 2014 American Association of Public Health Dentistry.

Validity of a food frequency questionnaire to estimate long-chain polyunsaturated fatty acid intake among Japanese women in early and late pregnancy.

PubMed

Kobayashi, Minatsu; Jwa, Seung Chik; Ogawa, Kohei; Morisaki, Naho; Fujiwara, Takeo

2017-01-01

The relative validity of food frequency questionnaires for estimating long-chain polyunsaturated fatty acid (LC-PUFA) intake among pregnant Japanese women is currently unclear. The aim of this study was to verify the external validity of a food frequency questionnaire, originally developed for non-pregnant adults, to assess the dietary intake of LC-PUFA using dietary records and serum phospholipid levels among Japanese women in early and late pregnancy. A validation study involving 188 participants in early pregnancy and 169 participants in late pregnancy was conducted. Intake LC-PUFA was estimated using a food frequency questionnaire and evaluated using a 3-day dietary record and serum phospholipid concentrations in both early and late pregnancy. The food frequency questionnaire provided estimates of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) intake with higher precision than dietary records in both early and late pregnancy. Significant correlations were observed for LC-PUFA intake estimated using dietary records in both early and late pregnancy, particularly for EPA and DHA (correlation coefficients ranged from 0.34 to 0.40, p < 0.0001). Similarly, high correlations for EPA and DHA in serum phospholipid composition were also observed in both early and late pregnancy (correlation coefficients ranged 0.27 to 0.34, p < 0.0001). Our findings suggest that the food frequency questionnaire, which was originally designed for non-pregnant adults and was evaluated in this study against dietary records and biological markers, has good validity for assessing LC-PUFA intake, especially EPA and DHA intake, among Japanese women in early and late pregnancy. Copyright © 2016 The Authors. Production and hosting by Elsevier B.V. All rights reserved.

Estimation of old field ecosystem biomass using low altitude imagery

NASA Technical Reports Server (NTRS)

Nor, S. M.; Safir, G.; Burton, T. M.; Hook, J. E.; Schultink, G.

1977-01-01

Color-infrared photography was used to evaluate the biomass of experimental plots in an old-field ecosystem that was treated with different levels of waste water from a sewage treatment facility. Cibachrome prints at a scale of approximately 1:1,600 produced from 35 mm color infrared slides were used to analyze density patterns using prepared tonal density scales and multicell grids registered to ground panels shown on the photograph. Correlation analyses between tonal density and vegetation biomass obtained from ground samples and harvests were carried out. Correlations between mean tonal density and harvest biomass data gave consistently high coefficients ranging from 0.530 to 0.896 at the 0.001 significance level. Corresponding multiple regression analysis resulted in higher correlation coefficients. The results of this study indicate that aerial infrared photography can be used to estimate standing crop biomass on waste water irrigated old field ecosystems. Combined with minimal ground truth data, this technique could enable managers of wastewater irrigation projects to precisely time harvest of such systems for maximal removal of nutrients in harvested biomass.

Detection of tissue coagulation by decorrelation of ultrasonic echo signals in cavitation-enhanced high-intensity focused ultrasound treatment.

PubMed

Yoshizawa, Shin; Matsuura, Keiko; Takagi, Ryo; Yamamoto, Mariko; Umemura, Shin-Ichiro

2016-01-01

A noninvasive technique to monitor thermal lesion formation is necessary to ensure the accuracy and safety of high-intensity focused ultrasound (HIFU) treatment. The purpose of this study is to ultrasonically detect the tissue change due to thermal coagulation in the HIFU treatment enhanced by cavitation microbubbles. An ultrasound imaging probe transmitted plane waves at a center frequency of 4.5 MHz. Ultrasonic radio-frequency (RF) echo signals during HIFU exposure at a frequency of 1.2 MHz were acquired. Cross-correlation coefficients were calculated between in-phase and quadrature (IQ) data of two B-mode images with an interval time of 50 and 500 ms for the estimation of the region of cavitation and coagulation, respectively. Pathological examination of the coagulated tissue was also performed to compare with the corresponding ultrasonically detected coagulation region. The distribution of minimum hold cross-correlation coefficient between two sets of IQ data with 50-ms intervals was compared with a pulse inversion (PI) image. The regions with low cross-correlation coefficients approximately corresponded to those with high brightness in the PI image. The regions with low cross-correlation coefficients in 500-ms intervals showed a good agreement with those with significant change in histology. The results show that the regions of coagulation and cavitation could be ultrasonically detected as those with low cross-correlation coefficients between RF frames with certain intervals. This method will contribute to improve the safety and accuracy of the HIFU treatment enhanced by cavitation microbubbles.

[Correlation analysis of major agronomic characters and the polysaccharide contents in Dendrobium officinale].

PubMed

Zhang, Lei; Zheng, Xi-Long; Qiu, Dao-Shou; Cai, Shi-Ke; Luo, Huan-Ming; Deng, Rui-Yun; Liu, Xiao-Jin

2013-10-01

In order to provide theoretical and technological basis for the germplasm innovation and variety breeding in Dendrobium officinale, a study of the correlation between polysaccharide content and agronomic characters was conducted. Based on the polysaccharide content determination and the agronomic characters investigation of 30 copies (110 individual plants) of Dendrobium officinale germplasm resources, the correlation between polysaccharide content and agronomic characters was analyzed via path and correlation analysis. Correlation analysis results showed that there was a significant negative correlation between average spacing and polysaccharide content, the correlation coefficient was -0.695. And the blade thickness was positively correlated with the polysaccharide content, but the correlation was not significant. The path analysis results showed that the stem length was the maximum influence factor to the polysaccharide, and it was positive effect, the direct path coefficient was 1.568. According to thess results, the polysaccharide content can be easily and intuitively estimated by the agronomic characters investigating data in the germpalsm resources screening and variety breeding. Therefore, it is a visual and practical technology guidance in quality variety breeding of Dendrobium officinale.

Above-ground biomass and carbon estimates of Shorea robusta and Tectona grandis forests using QuadPOL ALOS PALSAR data

NASA Astrophysics Data System (ADS)

Behera, M. D.; Tripathi, P.; Mishra, B.; Kumar, Shashi; Chitale, V. S.; Behera, Soumit K.

2016-01-01

Mechanisms to mitigate climate change in tropical countries such as India require information on forest structural components i.e., biomass and carbon for conservation steps to be implemented successfully. The present study focuses on investigating the potential use of a one time, QuadPOL ALOS PALSAR L-band 25 m data to estimate above-ground biomass (AGB) using a water cloud model (WCM) in a wildlife sanctuary in India. A significant correlation was obtained between the SAR-derived backscatter coefficient (σ°) and the field measured AGB, with the maximum coefficient of determination for cross-polarized (HV) σ° for Shorea robusta, and the weakest correlation was observed with co-polarized (HH) σ° for Tectona grandis forests. The biomass of S. robusta and that of T. grandis were estimated on the basis of field-measured data at 444.7 ± 170.4 Mg/ha and 451 ± 179.4 Mg/ha respectively. The mean biomass values estimated using the WCM varied between 562 and 660 Mg/ha for S. robusta; between 590 and 710 Mg/ha for T. grandis using various polarized data. Our results highlighted the efficacy of one time, fully polarized PALSAR data for biomass and carbon estimate in a dense forest.

Estimation of the prevalence of adverse drug reactions from social media.

PubMed

Nguyen, Thin; Larsen, Mark E; O'Dea, Bridianne; Phung, Dinh; Venkatesh, Svetha; Christensen, Helen

2017-06-01

This work aims to estimate the degree of adverse drug reactions (ADR) for psychiatric medications from social media, including Twitter, Reddit, and LiveJournal. Advances in lightning-fast cluster computing was employed to process large scale data, consisting of 6.4 terabytes of data containing 3.8 billion records from all the media. Rates of ADR were quantified using the SIDER database of drugs and side-effects, and an estimated ADR rate was based on the prevalence of discussion in the social media corpora. Agreement between these measures for a sample of ten popular psychiatric drugs was evaluated using the Pearson correlation coefficient, r, with values between 0.08 and 0.50. Word2vec, a novel neural learning framework, was utilized to improve the coverage of variants of ADR terms in the unstructured text by identifying syntactically or semantically similar terms. Improved correlation coefficients, between 0.29 and 0.59, demonstrates the capability of advanced techniques in machine learning to aid in the discovery of meaningful patterns from medical data, and social media data, at scale. Copyright © 2017 Elsevier B.V. All rights reserved.

On the frequency spectra of the core magnetic field Gauss coefficients

NASA Astrophysics Data System (ADS)

Lesur, Vincent; Wardinski, Ingo; Baerenzung, Julien; Holschneider, Matthias

2018-03-01

From monthly mean observatory data spanning 1957-2014, geomagnetic field secular variation values were calculated by annual differences. Estimates of the spherical harmonic Gauss coefficients of the core field secular variation were then derived by applying a correlation based modelling. Finally, a Fourier transform was applied to the time series of the Gauss coefficients. This process led to reliable temporal spectra of the Gauss coefficients up to spherical harmonic degree 5 or 6, and down to periods as short as 1 or 2 years depending on the coefficient. We observed that a k-2 slope, where k is the frequency, is an acceptable approximation for these spectra, with possibly an exception for the dipole field. The monthly estimates of the core field secular variation at the observatory sites also show that large and rapid variations of the latter happen. This is an indication that geomagnetic jerks are frequent phenomena and that significant secular variation signals at short time scales - i.e. less than 2 years, could still be extracted from data to reveal an unexplored part of the core dynamics.

PyLDTk: Python toolkit for calculating stellar limb darkening profiles and model-specific coefficients for arbitrary filters

NASA Astrophysics Data System (ADS)

Parviainen, Hannu

2015-10-01

PyLDTk automates the calculation of custom stellar limb darkening (LD) profiles and model-specific limb darkening coefficients (LDC) using the library of PHOENIX-generated specific intensity spectra by Husser et al. (2013). It facilitates exoplanet transit light curve modeling, especially transmission spectroscopy where the modeling is carried out for custom narrow passbands. PyLDTk construct model-specific priors on the limb darkening coefficients prior to the transit light curve modeling. It can also be directly integrated into the log posterior computation of any pre-existing transit modeling code with minimal modifications to constrain the LD model parameter space directly by the LD profile, allowing for the marginalization over the whole parameter space that can explain the profile without the need to approximate this constraint by a prior distribution. This is useful when using a high-order limb darkening model where the coefficients are often correlated, and the priors estimated from the tabulated values usually fail to include these correlations.

A comparison of maximum likelihood and other estimators of eigenvalues from several correlated Monte Carlo samples

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

Beer, M.

1980-12-01

The maximum likelihood method for the multivariate normal distribution is applied to the case of several individual eigenvalues. Correlated Monte Carlo estimates of the eigenvalue are assumed to follow this prescription and aspects of the assumption are examined. Monte Carlo cell calculations using the SAM-CE and VIM codes for the TRX-1 and TRX-2 benchmark reactors, and SAM-CE full core results are analyzed with this method. Variance reductions of a few percent to a factor of 2 are obtained from maximum likelihood estimation as compared with the simple average and the minimum variance individual eigenvalue. The numerical results verify that themore » use of sample variances and correlation coefficients in place of the corresponding population statistics still leads to nearly minimum variance estimation for a sufficient number of histories and aggregates.« less

Development of a Plantar Load Estimation Algorithm for Evaluation of Forefoot Load of Diabetic Patients during Daily Walks Using a Foot Motion Sensor

PubMed Central

Noguchi, Hiroshi; Sanada, Hiromi

2017-01-01

Forefoot load (FL) contributes to callus formation, which is one of the pathways to diabetic foot ulcers (DFU). In this study, we hypothesized that excessive FL, which cannot be detected by plantar load measurements within laboratory settings, occurs in daily walks. To demonstrate this, we created a FL estimation algorithm using foot motion data. Acceleration and angular velocity data were obtained from a motion sensor attached to each shoe of the subjects. The accuracy of the estimated FL was validated by correlation with the FL measured by force sensors on the metatarsal heads, which was assessed using the Pearson correlation coefficient. The mean of correlation coefficients of all the subjects was 0.63 at a level corridor, while it showed an intersubject difference at a slope and stairs. We conducted daily walk measurements in two diabetic patients, and additionally, we verified the safety of daily walk measurement using a wearable motion sensor attached to each shoe. We found that excessive FL occurred during their daily walks for approximately three hours in total, when any adverse event was not observed. This study indicated that FL evaluation method using wearable motion sensors was one of the promising ways to prevent DFUs. PMID:28840130

Development of a Plantar Load Estimation Algorithm for Evaluation of Forefoot Load of Diabetic Patients during Daily Walks Using a Foot Motion Sensor.

PubMed

Watanabe, Ayano; Noguchi, Hiroshi; Oe, Makoto; Sanada, Hiromi; Mori, Taketoshi

2017-01-01

Forefoot load (FL) contributes to callus formation, which is one of the pathways to diabetic foot ulcers (DFU). In this study, we hypothesized that excessive FL, which cannot be detected by plantar load measurements within laboratory settings, occurs in daily walks. To demonstrate this, we created a FL estimation algorithm using foot motion data. Acceleration and angular velocity data were obtained from a motion sensor attached to each shoe of the subjects. The accuracy of the estimated FL was validated by correlation with the FL measured by force sensors on the metatarsal heads, which was assessed using the Pearson correlation coefficient. The mean of correlation coefficients of all the subjects was 0.63 at a level corridor, while it showed an intersubject difference at a slope and stairs. We conducted daily walk measurements in two diabetic patients, and additionally, we verified the safety of daily walk measurement using a wearable motion sensor attached to each shoe. We found that excessive FL occurred during their daily walks for approximately three hours in total, when any adverse event was not observed. This study indicated that FL evaluation method using wearable motion sensors was one of the promising ways to prevent DFUs.

Restoration of acidic mine spoils with sewage sludge: II measurement of solids applied

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

Stucky, D.J.; Zoeller, A.L.

1980-01-01

Sewage sludge was incorporated in acidic strip mine spoils at rates equivalent to 0, 224, 336, and 448 dry metric tons (dmt)/ha and placed in pots in a greenhouse. Spoil parameters were determined 48 hours after sludge incorporation, Time Planting (P), and five months after orchardgrass (Dactylis glomerata L.) was planted, Time Harvest (H), in the pots. Parameters measured were: pH, organic matter content (OM), cation exchange capacity (CEC), electrical conductivity (EC) and yield. Values for each parameter were significantly different at the two sampling times. Correlation coefficient values were calculated for all parameters versus rates of applied sewage sludgemore » and all parameters versus each other. Multiple regressions were performed, stepwise, for all parameters versus rates of applied sewage sludge. Equations to predict amounts of sewage sludge incorporated in spoils were derived for individual and multiple parameters. Generally, measurements made at Time P achieved the highest correlation coefficient and multiple correlation coefficient values; therefore, the authors concluded data from Time P had the greatest predictability value. The most important value measured to predict rate of applied sewage sludge was pH and some additional accuracy was obtained by including CEC in equation. This experiment indicated that soil properties can be used to estimate amounts of sewage sludge solids required to reclaim acidic mine spoils and to estimate quantities incorporated.« less

Preliminary quantification of the permeability, solubility and diffusion coefficients of major aroma compounds present in herbs through various plastic packaging materials.

PubMed

Leelaphiwat, Pattarin; Auras, Rafael A; Burgess, Gary J; Harte, Janice B; Chonhenchob, Vanee

2018-03-01

Aroma permeation through packaging material is an important factor when designing a package for food products. The masses of aroma compounds permeating through films over time were measured at 25 °C using a quasi-isostatic system. A model was proposed for estimating the permeability coefficients (P) of key aroma compounds present in fresh herbs (i.e. eucalyptol, estragole, linalool and citral) through major plastic films used by the food industry [i.e. low-density polyethylene (LDPE), polypropylene (PP), nylon (Nylon), polyethylene terephthalate (PET), metalised-polyethylene terephthalate (MPET) and poly(lactic acid) (PLA)]. Solubility coefficients (S) were estimated from the amount of aroma compound sorbed in the films. Diffusion coefficients (D) were estimated following from the relation P = D*S. P and D for all four aroma compounds were highest in LDPE, except for eucalyptol, which P was slightly higher in PLA. The solubility coefficients and contact angles were highest in PLA suggesting the highest affinity of PLA to these aroma compounds. The theoretical solubility parameters were correlated with the solubility coefficients for estragole and citral, but not for eucalyptol and linalool. The preliminary P, D and S of eucalyptol, estragole, linalool and citral through LDPE, PP, Nylon, PET, MPET and PLA can be useful in selecting the proper packaging material for preserving these specific aroma compounds in food products and can potentially be used for estimating the shelf life of food products based on aroma loss. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Estimating EQ-5D values from the Neck Disability Index and numeric rating scales for neck and arm pain.

PubMed

Carreon, Leah Y; Bratcher, Kelly R; Das, Nandita; Nienhuis, Jacob B; Glassman, Steven D

2014-09-01

The Neck Disability Index (NDI) and numeric rating scales (0 to 10) for neck pain and arm pain are widely used cervical spine disease-specific measures. Recent studies have shown that there is a strong relationship between the SF-6D and the NDI such that using a simple linear regression allows for the estimation of an SF-6D value from the NDI alone. Due to ease of administration and scoring, the EQ-5D is increasingly being used as a measure of utility in the clinical setting. The purpose of this study is to determine if the EQ-5D values can be estimated from commonly available cervical spine disease-specific health-related quality of life measures, much like the SF-6D. The EQ-5D, NDI, neck pain score, and arm pain score were prospectively collected in 3732 patients who presented to the authors' clinic with degenerative cervical spine disorders. Correlation coefficients for paired observations from multiple time points between the NDI, neck pain and arm pain scores, and EQ-5D were determined. Regression models were built to estimate the EQ-5D values from the NDI, neck pain, and arm pain scores. The mean age of the 3732 patients was 53.3 ± 12.2 years, and 43% were male. Correlations between the EQ-5D and the NDI, neck pain score, and arm pain score were statistically significant (p < 0.0001), with correlation coefficients of -0.77, -0.62, and -0.50, respectively. The regression equation 0.98947 + (-0.00705 × NDI) + (-0.00875 × arm pain score) + (-0.00877 × neck pain score) to predict EQ-5D had an R-square of 0.62 and a root mean square error (RMSE) of 0.146. The model using NDI alone had an R-square of 0.59 and a RMSE of 0.150. The model using the individual NDI items had an R-square of 0.46 and an RMSE of 0.172. The correlation coefficient between the observed and estimated EQ-5D scores was 0.79. There was no statistically significant difference between the actual EQ-5D score (0.603 ± 0.235) and the estimated EQ-5D score (0.603 ± 0.185) using the NDI, neck pain score, and arm pain score regression model. However, rounding off the coefficients to fewer than 5 decimal places produced less accurate results. The regression model estimating the EQ-5D from the NDI, neck pain score, and arm pain score accounted for 60% of the variability of the EQ-5D with a relatively large RMSE. This regression model may not be sufficient to accurately or reliably estimate actual EQ-5D values.

Estimating lifetime risk from spot biomarker data and intra‐class correlation coefficients (ICC)

EPA Science Inventory

Human biomarker measurements in tissues including blood, breath, and urine can serve as efficient surrogates for environmental monitoring because a single biological sample integrates personal exposure across all environmental media and uptake pathways. However, biomarkers repres...

Calculation of Drug Solubilities by Pharmacy Students.

ERIC Educational Resources Information Center

Cates, Lindley A.

1981-01-01

A method of estimating the solubilities of drugs in water is reported that is based on a principle applied in quantitative structure-activity relationships. This procedure involves correlation of partition coefficient values using the octanol/water system and aqueous solubility. (Author/MLW)

Use of the Method of Triads in the Validation of Sodium and Potassium Intake in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil)

PubMed Central

Pereira, Taísa Sabrina Silva; Cade, Nágela Valadão; Mill, José Geraldo; Sichieri, Rosely; Molina, Maria del Carmen Bisi

2016-01-01

Introduction Biomarkers are a good choice to be used in the validation of food frequency questionnaire due to the independence of their random errors. Objective To assess the validity of the potassium and sodium intake estimated using the Food Frequency Questionnaire ELSA-Brasil. Subjects/Methods A subsample of participants in the ELSA-Brasil cohort was included in this study in 2009. Sodium and potassium intake were estimated using three methods: Semi-quantitative food frequency questionnaire, 12-hour nocturnal urinary excretion and three 24-hour food records. Correlation coefficients were calculated between the methods, and the validity coefficient was calculated using the method of triads. The 95% confidence intervals for the validity coefficient were estimated using bootstrap sampling. Exact and adjacent agreement and disagreement of the estimated sodium and potassium intake quintiles were compared among three methods. Results The sample consisted of 246 participants, aged 53±8 years, 52% of women. Validity coefficient for sodium were considered weak (рfood frequency questionnaire actual intake = 0.37 and рbiomarker actual intake = 0.21) and moderate (рfood records actual intake 0.56). The validity coefficient were higher for potassium (рfood frequency questionnaire actual intake = 0.60; рbiomarker actual intake = 0.42; рfood records actual intake = 0.79). Conclusions: The Food Frequency Questionnaire ELSA-Brasil showed good validity in estimating potassium intake in epidemiological studies. For sodium validity was weak, likely due to the non-quantification of the added salt to prepared food. PMID:28030625

Use of the Method of Triads in the Validation of Sodium and Potassium Intake in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil).

PubMed

Pereira, Taísa Sabrina Silva; Cade, Nágela Valadão; Mill, José Geraldo; Sichieri, Rosely; Molina, Maria Del Carmen Bisi

2016-01-01

Biomarkers are a good choice to be used in the validation of food frequency questionnaire due to the independence of their random errors. To assess the validity of the potassium and sodium intake estimated using the Food Frequency Questionnaire ELSA-Brasil. A subsample of participants in the ELSA-Brasil cohort was included in this study in 2009. Sodium and potassium intake were estimated using three methods: Semi-quantitative food frequency questionnaire, 12-hour nocturnal urinary excretion and three 24-hour food records. Correlation coefficients were calculated between the methods, and the validity coefficient was calculated using the method of triads. The 95% confidence intervals for the validity coefficient were estimated using bootstrap sampling. Exact and adjacent agreement and disagreement of the estimated sodium and potassium intake quintiles were compared among three methods. The sample consisted of 246 participants, aged 53±8 years, 52% of women. Validity coefficient for sodium were considered weak (рfood frequency questionnaire actual intake = 0.37 and рbiomarker actual intake = 0.21) and moderate (рfood records actual intake 0.56). The validity coefficient were higher for potassium (рfood frequency questionnaire actual intake = 0.60; рbiomarker actual intake = 0.42; рfood records actual intake = 0.79). Conclusions: The Food Frequency Questionnaire ELSA-Brasil showed good validity in estimating potassium intake in epidemiological studies. For sodium validity was weak, likely due to the non-quantification of the added salt to prepared food.

Numerical and analytical assessment of radon diffusion in various media and potential of charcoal as radon detector

NASA Astrophysics Data System (ADS)

Rybalkin, Andrey

Numerical assessments of radon diffusion together with analytical estimates for short-time and long-time exposure were the first objective of this thesis with the goal to demonstrate how radon propagates in various media. Theoretical predictions were compared to numerical simulations, and obtained values of total radon activities inside each material match quite well with the analytical estimates. These estimates, for activated and nonactivated charcoal, were then used to evaluate the possibility of designing a charcoal system to be used as a radon detector. Another objective was to use nonactivated charcoal samples and measure the level of radon accumulation, and use these data to estimate radon diffusion and adsorption coefficients. The analytical approach was developed to estimate these values. Radon adsorption coefficient in nonactivated charcoal was found to be from 0.2 to 0.4 m3/kg. Radon diffusion coefficient for nonactivated charcoal is in the range of 1.2×10-11 to 5.1×10-10 m2/s in comparison to activated charcoal with adsorption coefficient of 4 m3/kg and diffusion coefficient of 1.43×10-9 m2/s. The third objective was to use GEANT4 numerical code to simulate decay of 238U series and 222Rn in an arbitrary soil sample. Based on that model, the goal was to provide a guideline for merging GEANT4 radioactive decay modeling with the diffusion of radon in a soil sample. It is known that radon can be used as an earthquake predictor by measuring its concentration in groundwater, or if possible, along the faults. Numerical simulations of radon migration by diffusion only were made to estimate how fast and how far radon can move along the fault strands. Among the known cases of successful correlations between radon concentration anomalies and earthquake are the 1966 Tashkent and 1976 Songpan-Pingwu earthquakes. Thus, an idea of radon monitoring along the Wasatch Fault, using system of activated/nonactivated charcoals together with solid state radon detectors is suggested in the thesis. Also, the use of neutron activation analysis for soil samples, collected along and away from Wasatch Fault, and looking for the trace elements can result in correlation with earthquakes, occurred in the past. This approach can be used for earthquake prediction in future.

MRI-based intelligence quotient (IQ) estimation with sparse learning.

PubMed

Wang, Liye; Wee, Chong-Yaw; Suk, Heung-Il; Tang, Xiaoying; Shen, Dinggang

2015-01-01

In this paper, we propose a novel framework for IQ estimation using Magnetic Resonance Imaging (MRI) data. In particular, we devise a new feature selection method based on an extended dirty model for jointly considering both element-wise sparsity and group-wise sparsity. Meanwhile, due to the absence of large dataset with consistent scanning protocols for the IQ estimation, we integrate multiple datasets scanned from different sites with different scanning parameters and protocols. In this way, there is large variability in these different datasets. To address this issue, we design a two-step procedure for 1) first identifying the possible scanning site for each testing subject and 2) then estimating the testing subject's IQ by using a specific estimator designed for that scanning site. We perform two experiments to test the performance of our method by using the MRI data collected from 164 typically developing children between 6 and 15 years old. In the first experiment, we use a multi-kernel Support Vector Regression (SVR) for estimating IQ values, and obtain an average correlation coefficient of 0.718 and also an average root mean square error of 8.695 between the true IQs and the estimated ones. In the second experiment, we use a single-kernel SVR for IQ estimation, and achieve an average correlation coefficient of 0.684 and an average root mean square error of 9.166. All these results show the effectiveness of using imaging data for IQ prediction, which is rarely done in the field according to our knowledge.

Estimates of Intraclass Correlation for Variables Related to Behavioral HIV/STD Prevention in a Predominantly African American and Hispanic Sample of Young Women

ERIC Educational Resources Information Center

Pals, Sherri L.; Beaty, Brenda L.; Posner, Samuel F.; Bull, Sheana S.

2009-01-01

Studies designed to evaluate HIV and STD prevention interventions often involve random assignment of groups such as neighborhoods or communities to study conditions (e.g., to intervention or control). Investigators who design group-randomized trials (GRTs) must take the expected intraclass correlation coefficient (ICC) into account in sample size…

The coefficient of determination R2 and intra-class correlation coefficient from generalized linear mixed-effects models revisited and expanded.

PubMed

Nakagawa, Shinichi; Johnson, Paul C D; Schielzeth, Holger

2017-09-01

The coefficient of determination R 2 quantifies the proportion of variance explained by a statistical model and is an important summary statistic of biological interest. However, estimating R 2 for generalized linear mixed models (GLMMs) remains challenging. We have previously introduced a version of R 2 that we called [Formula: see text] for Poisson and binomial GLMMs, but not for other distributional families. Similarly, we earlier discussed how to estimate intra-class correlation coefficients (ICCs) using Poisson and binomial GLMMs. In this paper, we generalize our methods to all other non-Gaussian distributions, in particular to negative binomial and gamma distributions that are commonly used for modelling biological data. While expanding our approach, we highlight two useful concepts for biologists, Jensen's inequality and the delta method, both of which help us in understanding the properties of GLMMs. Jensen's inequality has important implications for biologically meaningful interpretation of GLMMs, whereas the delta method allows a general derivation of variance associated with non-Gaussian distributions. We also discuss some special considerations for binomial GLMMs with binary or proportion data. We illustrate the implementation of our extension by worked examples from the field of ecology and evolution in the R environment. However, our method can be used across disciplines and regardless of statistical environments. © 2017 The Author(s).

Iodine intake by adult residents of a farming area in Iwate Prefecture, Japan, and the accuracy of estimated iodine intake calculated using the Standard Tables of Food Composition in Japan.

PubMed

Nakatsuka, Haruo; Chiba, Keiko; Watanabe, Takao; Sawatari, Hideyuki; Seki, Takako

2016-11-01

Iodine intake by adults in farming districts in Northeastern Japan was evaluated by two methods: (1) government-approved food composition tables based calculation and (2) instrumental measurement. The correlation between these two values and a regression model for the calibration of calculated values was presented. Iodine intake was calculated, using the values in the Japan Standard Tables of Food Composition (FCT), through the analysis of duplicate samples of complete 24-h food consumption for 90 adult subjects. In cases where the value for iodine content was not available in the FCT, it was assumed to be zero for that food item (calculated values). Iodine content was also measured by ICP-MS (measured values). Calculated and measured values rendered geometric means (GM) of 336 and 279 μg/day, respectively. There was no statistically significant (p > 0.05) difference between calculated and measured values. The correlation coefficient was 0.646 (p < 0.05). With this high correlation coefficient, a simple regression line can be applied to estimate measured value from calculated value. A survey of the literature suggests that the values in this study were similar to values that have been reported to date for Japan, and higher than those for other countries in Asia. Iodine intake of Japanese adults was 336 μg/day (GM, calculated) and 279 μg/day (GM, measured). Both values correlated so well, with a correlation coefficient of 0.646, that a regression model (Y = 130.8 + 1.9479X, where X and Y are measured and calculated values, respectively) could be used to calibrate calculated values.

Effective diffusion coefficients of DNAPL waste components in saturated low permeability soil materials

NASA Astrophysics Data System (ADS)

Ayral-Cinar, Derya; Demond, Avery H.

2017-12-01

Diffusion is regarded as the dominant transport mechanism into and out of low permeable subsurface lenses and layers in the subsurface. But, some reports of mass storage in such zones are higher than what might be attributable to diffusion, based on estimated diffusion coefficients. Despite the importance of diffusion to efforts to estimate the quantity of residual contamination in the subsurface, relatively few studies present measured diffusion coefficients of organic solutes in saturated low permeability soils. This study reports the diffusion coefficients of a trichloroethylene (TCE), and an anionic surfactant, Aerosol OT (AOT), in water-saturated silt and a silt-montmorillonite (25:75) mixture, obtained using steady-state experiments. The relative diffusivity ranged from 0.11 to 0.17 for all three compounds for the silt and the silt-clay mixture that was allowed to expand. In the case in which the swelling was constrained, the relative diffusivity was about 0.07. In addition, the relative diffusivity of 13C-labeled TCE through a water saturated silt-clay mixture that had contacted a field dense non-aqueous phase liquid (DNAPL) for 18 months was measured and equaled 0.001. These experimental results were compared with the estimates generated using common correlations, and it was found that, in all cases, the measured diffusion coefficients were significantly lower than the estimated. Thus, the discrepancy between mass accumulations observed in the field and the mass storage that can attributable to diffusion may be greater than previously believed.

Correlations between the Various Methods of Estimating Prostate Volume: Transabdominal, Transrectal, and Three-Dimensional US

PubMed Central

Kim, Seung Hyup

2008-01-01

Objective To evaluate the correlations between prostate volumes estimated by transabdominal, transrectal, and three-dimensional US and the factors affecting the differences. Materials and Methods The prostate volumes of 94 consecutive patients were measured by both transabdominal and transrectal US. Next, the prostate volumes of 58 other patients was measured by both transrectal and three-dimensional US. We evaluated the degree of correlation and mean difference in each comparison. We also analyzed possible factors affecting the differences, such as the experiences of examiners in transrectal US, bladder volume, and prostate volume. Results In the comparison of transabdominal and transrectal US methods, the mean difference was 8.4 ± 10.5 mL and correlation coefficient (r) was 0.775 (p < 0.01). The experienced examiner for the transrectal US method had the highest correlation (r = 0.967) and the significantly smallest difference (5.4 ± 3.9 mL) compared to the other examiners (the beginner and the trained; p < 0.05). Prostate volume measured by transrectal US showed a weak correlation with the difference (r = 0.360, p < 0.05). Bladder volume did not show significant correlation with the difference (r = -0.043, p > 0.05). The comparison between the transrectal and three-dimensional US methods revealed a mean difference of 3.7 ± 3.4 mL and the correlation coefficient was 0.924 for the experienced examiner. Furthermore, no significant difference existed between examiners (p > 0.05). Prostate volume measured by transrectal US showed a positive correlation with the difference for the beginner only (r = 0.405, p < 0.05). Conclusion In the prostate volume estimation by US, experience in transrectal US is important in the correlation with transabdominal US, but not with three-dimensional US. Also, less experienced examiners' assessment of the prostate volume can be affected by prostate volume itself. PMID:18385560

A Comparison between Discrimination Indices and Item-Response Theory Using the Rasch Model in a Clinical Course Written Examination of a Medical School.

PubMed

Park, Jong Cook; Kim, Kwang Sig

2012-03-01

The reliability of test is determined by each items' characteristics. Item analysis is achieved by classical test theory and item response theory. The purpose of the study was to compare the discrimination indices with item response theory using the Rasch model. Thirty-one 4th-year medical school students participated in the clinical course written examination, which included 22 A-type items and 3 R-type items. Point biserial correlation coefficient (C(pbs)) was compared to method of extreme group (D), biserial correlation coefficient (C(bs)), item-total correlation coefficient (C(it)), and corrected item-total correlation coeffcient (C(cit)). Rasch model was applied to estimate item difficulty and examinee's ability and to calculate item fit statistics using joint maximum likelihood. Explanatory power (r2) of Cpbs is decreased in the following order: C(cit) (1.00), C(it) (0.99), C(bs) (0.94), and D (0.45). The ranges of difficulty logit and standard error and ability logit and standard error were -0.82 to 0.80 and 0.37 to 0.76, -3.69 to 3.19 and 0.45 to 1.03, respectively. Item 9 and 23 have outfit > or =1.3. Student 1, 5, 7, 18, 26, 30, and 32 have fit > or =1.3. C(pbs), C(cit), and C(it) are good discrimination parameters. Rasch model can estimate item difficulty parameter and examinee's ability parameter with standard error. The fit statistics can identify bad items and unpredictable examinee's responses.

Validity of a self-administered food frequency questionnaire in the estimation of heterocyclic aromatic amines.

PubMed

Iwasaki, Motoki; Mukai, Tomomi; Takachi, Ribeka; Ishihara, Junko; Totsuka, Yukari; Tsugane, Shoichiro

2014-08-01

Clarification of the putative etiologic role of heterocyclic aromatic amines (HAAs) in the development of cancer requires a validated assessment tool for dietary HAAs. This study primarily aimed to evaluate the validity of a food frequency questionnaire (FFQ) in estimating HAA intake, using 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) level in human hair as the reference method. We first updated analytical methods of PhIP using liquid chromatography-electrospray ionization/tandem mass spectrometry (LC-ESI/MS/MS) and measured 44 fur samples from nine rats from a feeding study as part-verification of the quantitative performance of LC-ESI/MS/MS. We next measured PhIP level in human hair samples from a validation study of the FFQ (n = 65). HAA intake from the FFQ was estimated using information on intake from six fish items and seven meat items and data on HAA content in each food item. Correlation coefficients between PhIP level in human hair and HAA intake from the FFQ were calculated. The animal feeding study of PhIP found a significant dose-response relationship between dosage and PhIP in rat fur. Mean level was 53.8 pg/g hair among subjects with values over the limit of detection (LOD) (n = 57). We found significant positive correlation coefficients between PhIP in human hair and HAA intake from the FFQ, with Spearman rank correlation coefficients of 0.35 for all subjects, 0.21 for subjects with over LOD values, and 0.34 for subjects with over limit of quantification. Findings from the validation study suggest that the FFQ is reasonably valid for the assessment of HAA intake.

Improving Spleen Volume Estimation via Computer Assisted Segmentation on Clinically Acquired CT Scans

PubMed Central

Xu, Zhoubing; Gertz, Adam L.; Burke, Ryan P.; Bansal, Neil; Kang, Hakmook; Landman, Bennett A.; Abramson, Richard G.

2016-01-01

OBJECTIVES Multi-atlas fusion is a promising approach for computer-assisted segmentation of anatomical structures. The purpose of this study was to evaluate the accuracy and time efficiency of multi-atlas segmentation for estimating spleen volumes on clinically-acquired CT scans. MATERIALS AND METHODS Under IRB approval, we obtained 294 deidentified (HIPAA-compliant) abdominal CT scans on 78 subjects from a recent clinical trial. We compared five pipelines for obtaining splenic volumes: Pipeline 1–manual segmentation of all scans, Pipeline 2–automated segmentation of all scans, Pipeline 3–automated segmentation of all scans with manual segmentation for outliers on a rudimentary visual quality check, Pipelines 4 and 5–volumes derived from a unidimensional measurement of craniocaudal spleen length and three-dimensional splenic index measurements, respectively. Using Pipeline 1 results as ground truth, the accuracy of Pipelines 2–5 (Dice similarity coefficient [DSC], Pearson correlation, R-squared, and percent and absolute deviation of volume from ground truth) were compared for point estimates of splenic volume and for change in splenic volume over time. Time cost was also compared for Pipelines 1–5. RESULTS Pipeline 3 was dominant in terms of both accuracy and time cost. With a Pearson correlation coefficient of 0.99, average absolute volume deviation 23.7 cm3, and 1 minute per scan, Pipeline 3 yielded the best results. The second-best approach was Pipeline 5, with a Pearson correlation coefficient 0.98, absolute deviation 46.92 cm3, and 1 minute 30 seconds per scan. Manual segmentation (Pipeline 1) required 11 minutes per scan. CONCLUSION A computer-automated segmentation approach with manual correction of outliers generated accurate splenic volumes with reasonable time efficiency. PMID:27519156

The correlation between preoperative volumetry and real graft weight: comparison of two volumetry programs.

PubMed

Mussin, Nadiar; Sumo, Marco; Lee, Kwang-Woong; Choi, YoungRok; Choi, Jin Yong; Ahn, Sung-Woo; Yoon, Kyung Chul; Kim, Hyo-Sin; Hong, Suk Kyun; Yi, Nam-Joon; Suh, Kyung-Suk

2017-04-01

Liver volumetry is a vital component in living donor liver transplantation to determine an adequate graft volume that meets the metabolic demands of the recipient and at the same time ensures donor safety. Most institutions use preoperative contrast-enhanced CT image-based software programs to estimate graft volume. The objective of this study was to evaluate the accuracy of 2 liver volumetry programs (Rapidia vs . Dr. Liver) in preoperative right liver graft estimation compared with real graft weight. Data from 215 consecutive right lobe living donors between October 2013 and August 2015 were retrospectively reviewed. One hundred seven patients were enrolled in Rapidia group and 108 patients were included in the Dr. Liver group. Estimated graft volumes generated by both software programs were compared with real graft weight measured during surgery, and further classified into minimal difference (≤15%) and big difference (>15%). Correlation coefficients and degree of difference were determined. Linear regressions were calculated and results depicted as scatterplots. Minimal difference was observed in 69.4% of cases from Dr. Liver group and big difference was seen in 44.9% of cases from Rapidia group (P = 0.035). Linear regression analysis showed positive correlation in both groups (P < 0.01). However, the correlation coefficient was better for the Dr. Liver group (R 2 = 0.719), than for the Rapidia group (R 2 = 0.688). Dr. Liver can accurately predict right liver graft size better and faster than Rapidia, and can facilitate preoperative planning in living donor liver transplantation.

A Lagrangian Subgridscale Model for Particle Transport Improvement and Application in the Adriatic Sea Using the Navy Coastal Ocean Model

DTIC Science & Technology

2006-12-01

based on input statistical parameters , such as the turbulent velocity fluc- tuation and correlation time scale, without the need of an underlying...8217mVr) 2 + (ar, r- ;m Vm) 2 (8) Tr + Tm which is zero if the model and real parameters coincide. The correlation coefficient rmc between the...well correlated with the latter. The parameters estimated from the corrected velocity, Real(top), Model(mid), Corrected(bottom), Tm=1.5, Gm=l 0, Tr

Applying new Magee equations for predicting the Oncotype Dx recurrence score.

PubMed

Sughayer, Maher; Alaaraj, Rolla; Alsughayer, Ahmad

2018-04-24

Breast cancer is one of the most prevalent cancers in women. Oncotype Dx is a multi-gene assay frequently used to predict the recurrence risk for estrogen receptor-positive early breast cancer, with values < 18 considered low risk; ≥ 18 and ≤ 30, intermediate risk; and > 30, high risk. Patients at a high risk for recurrence are more likely to benefit from chemotherapy treatment. In this study, clinicopathological parameters for 37 cases of early breast cancer with available Oncotype Dx results were used to estimate the recurrence score using the three new Magee equations. Correlation studies with Oncotype Dx results were performed. Applying the same cutoff points as Oncotype Dx, patients were categorized into low-, intermediate- and high-risk groups according to their estimated recurrence scores. Pearson correlation coefficient (R) values between estimated and actual recurrence score were 0.73, 0.66, and 0.70 for Magee equations 1, 2 and 3, respectively. The concordance values between actual and estimated recurrence scores were 57.6%, 52.9%, and 57.6% for Magee equations 1, 2 and 3, respectively. Using standard pathologic measures and immunohistochemistry scores in these three linear Magee equations, most low and high recurrence risk cases can be predicted with a strong positive correlation coefficient, high concordance and negligible two-step discordance. Magee equations are user-friendly and can be used to predict the recurrence score in early breast cancer cases.

On the estimation of intracluster correlation for time-to-event outcomes in cluster randomized trials.

PubMed

Kalia, Sumeet; Klar, Neil; Donner, Allan

2016-12-30

Cluster randomized trials (CRTs) involve the random assignment of intact social units rather than independent subjects to intervention groups. Time-to-event outcomes often are endpoints in CRTs. Analyses of such data need to account for the correlation among cluster members. The intracluster correlation coefficient (ICC) is used to assess the similarity among binary and continuous outcomes that belong to the same cluster. However, estimating the ICC in CRTs with time-to-event outcomes is a challenge because of the presence of censored observations. The literature suggests that the ICC may be estimated using either censoring indicators or observed event times. A simulation study explores the effect of administrative censoring on estimating the ICC. Results show that ICC estimators derived from censoring indicators or observed event times are negatively biased. Analytic work further supports these results. Observed event times are preferred to estimate the ICC under minimum frequency of administrative censoring. To our knowledge, the existing literature provides no practical guidance on the estimation of ICC when substantial amount of administrative censoring is present. The results from this study corroborate the need for further methodological research on estimating the ICC for correlated time-to-event outcomes. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

A holistic approach to age estimation in refugee children.

PubMed

Sypek, Scott A; Benson, Jill; Spanner, Kate A; Williams, Jan L

2016-06-01

Many refugee children arriving in Australia have an inaccurately documented date of birth (DOB). A medical assessment of a child's age is often requested when there is a concern that their documented DOB is incorrect. This study's aim was to assess the accuracy a holistic age assessment tool (AAT) in estimating the age of refugee children newly settled in Australia. A holistic AAT that combines medical and non-medical approaches was used to estimate the ages of 60 refugee children with a known DOB. The tool used four components to assess age: an oral narrative, developmental assessment, anthropometric measures and pubertal assessment. Assessors were blinded to the true age of the child. Correlation coefficients for the actual and estimated age were calculated for the tool overall and individual components. The correlation coefficient between the actual and estimated age from the AAT was very strong at 0.9802 (boys 0.9748, girls 0.9876). The oral narrative component of the tool performed best (R = 0.9603). Overall, 86.7% of age estimates were within 1 year of the true age. The range of differences was -1.43 to 3.92 years with a standard deviation of 0.77 years (9.24 months). The AAT is a holistic, simple and safe instrument that can be used to estimate age in refugee children with results comparable with radiological methods currently used. © 2016 Paediatrics and Child Health Division (The Royal Australasian College of Physicians).

Copula based prediction models: an application to an aortic regurgitation study

PubMed Central

Kumar, Pranesh; Shoukri, Mohamed M

2007-01-01

Background: An important issue in prediction modeling of multivariate data is the measure of dependence structure. The use of Pearson's correlation as a dependence measure has several pitfalls and hence application of regression prediction models based on this correlation may not be an appropriate methodology. As an alternative, a copula based methodology for prediction modeling and an algorithm to simulate data are proposed. Methods: The method consists of introducing copulas as an alternative to the correlation coefficient commonly used as a measure of dependence. An algorithm based on the marginal distributions of random variables is applied to construct the Archimedean copulas. Monte Carlo simulations are carried out to replicate datasets, estimate prediction model parameters and validate them using Lin's concordance measure. Results: We have carried out a correlation-based regression analysis on data from 20 patients aged 17–82 years on pre-operative and post-operative ejection fractions after surgery and estimated the prediction model: Post-operative ejection fraction = - 0.0658 + 0.8403 (Pre-operative ejection fraction); p = 0.0008; 95% confidence interval of the slope coefficient (0.3998, 1.2808). From the exploratory data analysis, it is noted that both the pre-operative and post-operative ejection fractions measurements have slight departures from symmetry and are skewed to the left. It is also noted that the measurements tend to be widely spread and have shorter tails compared to normal distribution. Therefore predictions made from the correlation-based model corresponding to the pre-operative ejection fraction measurements in the lower range may not be accurate. Further it is found that the best approximated marginal distributions of pre-operative and post-operative ejection fractions (using q-q plots) are gamma distributions. The copula based prediction model is estimated as: Post -operative ejection fraction = - 0.0933 + 0.8907 × (Pre-operative ejection fraction); p = 0.00008 ; 95% confidence interval for slope coefficient (0.4810, 1.3003). For both models differences in the predicted post-operative ejection fractions in the lower range of pre-operative ejection measurements are considerably different and prediction errors due to copula model are smaller. To validate the copula methodology we have re-sampled with replacement fifty independent bootstrap samples and have estimated concordance statistics 0.7722 (p = 0.0224) for the copula model and 0.7237 (p = 0.0604) for the correlation model. The predicted and observed measurements are concordant for both models. The estimates of accuracy components are 0.9233 and 0.8654 for copula and correlation models respectively. Conclusion: Copula-based prediction modeling is demonstrated to be an appropriate alternative to the conventional correlation-based prediction modeling since the correlation-based prediction models are not appropriate to model the dependence in populations with asymmetrical tails. Proposed copula-based prediction model has been validated using the independent bootstrap samples. PMID:17573974

Reliability of a self-report Italian version of the AUDIT-C questionnaire, used to estimate alcohol consumption by pregnant women in an obstetric setting.

PubMed

Bazzo, Stefania; Battistella, Giuseppe; Riscica, Patrizia; Moino, Giuliana; Dal Pozzo, Giuseppe; Bottarel, Mery; Geromel, Mariasole; Czerwinsky, Loredana

2015-01-01

Alcohol consumption during pregnancy can result in a range of harmful effects on the developing foetus and newborn, called Fetal Alcohol Spectrum Disorders (FASD). The identification of pregnant women who use alcohol enables to provide information, support and treatment for women and the surveillance of their children. The AUDIT-C (the shortened consumption version of the Alcohol Use Disorders Identification Test) is used for investigating risky drinking with different populations, and has been applied to estimate alcohol use and risky drinking also in antenatal clinics. The aim of the study was to investigate the reliability of a self-report Italian version of the AUDIT-C questionnaire to detect alcohol consumption during pregnancy, regardless of its use as a screening tool. The questionnaire was filled in by two independent consecutive series of pregnant women at the 38th gestation week visit in the two birth locations of the Local Health Authority of Treviso (Italy), during the years 2010 and 2011 (n=220 and n=239). Reliability analysis was performed using internal consistency, item-total score correlations, and inter-item correlations. The "discriminatory power" of the test was also evaluated. Results. Overall, about one third of women recalled alcohol consumption at least once during the current pregnancy. The questionnaire had an internal consistency of 0.565 for the group of the year 2010, of 0.516 for the year 2011, and of 0.542 for the overall group. The highest item total correlations' coefficient was 0.687 and the highest inter-item correlations' coefficient was 0.675. As for the discriminatory power of the questionnaire, the highest Ferguson's delta coefficient was 0.623. These findings suggest that the Italian self-report version of the AUDIT-C possesses unsatisfactory reliability to estimate alcohol consumption during pregnancy when used as self-report questionnaire in an obstetric setting.

Estimation and analysis of interannual variations in tropical oceanic rainfall using data from SSM/I

NASA Technical Reports Server (NTRS)

Berg, Wesley

1992-01-01

Rainfall over tropical ocean regions, particularly in the tropical Pacific, is estimated using Special Sensor Microwave/Imager (SSM/I) data. Instantaneous rainfall estimates are derived from brightness temperature values obtained from the satellite data using the Hughes D-Matrix algorithm. Comparisons with other satellite techniques are made to validate the SSM/I results for the tropical Pacific. The correlation coefficients are relatively high for the three data sets investigated, especially for the annual case.

HARBO, a simple computer-aided observation method for recording work postures.

PubMed

Wiktorin, C; Mortimer, M; Ekenvall, L; Kilbom, A; Hjelm, E W

1995-12-01

The aim of the study was to present an observation method focusing on the positions of the hands relative to the body and to evaluate whether this simple observation technique gives a reliable estimate of the total time spent in each of five work postures during one workday. In the first part of the study the interobserver reliability of the observation method was tested with eight blue-collar workers. In the second part the observed time spent with work above the shoulder level was tested in relation to an upper-arm position analyzer, and observed time spent in work below knuckle level was tested in relation to a trunk flexion analyzer, both with 72 blue-collar workers. The interobserver reliability for full-day registrations was high. The intraclass correlation coefficients ranged from 0.99 to 1.00. The observed duration of work with hands above shoulder level correlated well with the measured duration of pronounced arm elevation (> 75 degrees). The product moment correlation coefficient was 0.97. The observed duration of work with hands below knuckle level correlated well with the measured duration of pronounced trunk flexion angles (> 40 degrees). The product moment correlation coefficient was 0.98. The present observation method, designed to make postural observations continuously for several hours, is easy to learn and seems reliable.

Evaluation of AUC(0-4) predictive methods for cyclosporine in kidney transplant patients.

PubMed

Aoyama, Takahiko; Matsumoto, Yoshiaki; Shimizu, Makiko; Fukuoka, Masamichi; Kimura, Toshimi; Kokubun, Hideya; Yoshida, Kazunari; Yago, Kazuo

2005-05-01

Cyclosporine (CyA) is the most commonly used immunosuppressive agent in patients who undergo kidney transplantation. Dosage adjustment of CyA is usually based on trough levels. Recently, trough levels have been replacing the area under the concentration-time curve during the first 4 h after CyA administration (AUC(0-4)). The aim of this study was to compare the predictive values obtained using three different methods of AUC(0-4) monitoring. AUC(0-4) was calculated from 0 to 4 h in early and stable renal transplant patients using the trapezoidal rule. The predicted AUC(0-4) was calculated using three different methods: the multiple regression equation reported by Uchida et al.; Bayesian estimation for modified population pharmacokinetic parameters reported by Yoshida et al.; and modified population pharmacokinetic parameters reported by Cremers et al. The predicted AUC(0-4) was assessed on the basis of predictive bias, precision, and correlation coefficient. The predicted AUC(0-4) values obtained using three methods through measurement of three blood samples showed small differences in predictive bias, precision, and correlation coefficient. In the prediction of AUC(0-4) measurement of one blood sample from stable renal transplant patients, the performance of the regression equation reported by Uchida depended on sampling time. On the other hand, the performance of Bayesian estimation with modified pharmacokinetic parameters reported by Yoshida through measurement of one blood sample, which is not dependent on sampling time, showed a small difference in the correlation coefficient. The prediction of AUC(0-4) using a regression equation required accurate sampling time. In this study, the prediction of AUC(0-4) using Bayesian estimation did not require accurate sampling time in the AUC(0-4) monitoring of CyA. Thus Bayesian estimation is assumed to be clinically useful in the dosage adjustment of CyA.

Continuous opacity from Ne^-

NASA Astrophysics Data System (ADS)

John, T. L.

1996-04-01

Free-free absorption coefficients of the negative neon ion are calculated by the phase-shift approximation based on multiconfiguration Hartree-Fock continuum wave functions. These wave functions accurately account for electron-neon correlation and polarization, and yield scattering cross-sections in excellent agreement with the latest experimental values. The coefficients are expected to give the best current estimates of Ne^- continuous absorption. We find that Ne^- makes only a small contribution (less than 0.3 per cent) to stellar opacities, including hydrogen-deficient stars with enhanced Ne abundances.

Non-Markovian Effects in Turbulent Diffusion in Magnetized Plasmas

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

Zagorodny, Anatoly; Weiland, Jan

2009-10-08

The derivation of the kinetic equations for inhomogeneous plasma in an external magnetic field is presented. The Fokker-Planck-type equations with the non-Markovian kinetic coefficients are proposed. In the time-local limit (small correlation times with respect to the distribution function relaxation time) the relations obtained recover the results known from the appropriate quasilinear theory and the Dupree-Weinstock theory of plasma turbulence. The equations proposed are used to describe zonal flow generation and to estimate the diffusion coefficient for saturated turbulence.

Estimation of old field ecosystem biomass using low altitude imagery

NASA Technical Reports Server (NTRS)

Nor, S. M.; Safir, G.; Burton, T. M.; Hook, J. E.; Schultink, G.

1977-01-01

Color-infrared photography was used to evaluate the biomass of experimental plots in an old-field ecosystem that was treated with different levels of waste water from a sewage treatment facility. Cibachrome prints at a scale of approximately 1:1,600 produced from 35 mm color infrared slides were used to analyze density patterns using prepared tonal density scales and multicell grids registered to ground panels shown on the photograph. Correlations between mean tonal density and harvest biomass data gave consistently high coefficients ranging from 0.530 to 0.896 at the 0.001 significance level. Corresponding multiple regression analysis resulted in higher correlation coefficients. The results indicate that aerial infrared photography can be used to estimate standing crop biomass on waste water irrigated old field ecosystems. Combined with minimal ground truth data, this technique could enable managers of waste water irrigation projects to precisely time harvest of such systems for maximal removal of nutrients in harvested biomass.

Adaptive Waveform Correlation Detectors for Arrays: Algorithms for Autonomous Calibration

DTIC Science & Technology

2007-09-01

March 17, 2005. The seismic signals from both master and detected events are followed by infrasound arrivals. Note the long duration of the...correlation coefficient traces with a significant array -gain. A detected event that is co-located with the master event will record the same time-difference...estimating the detection threshold reduction for a range of highly repeating seismic sources using arrays of different configurations and at different

Comparison of Nimbus-7 SMMR and GOES-1 VISSR Atmospheric Liquid Water Content.

NASA Astrophysics Data System (ADS)

Lojou, Jean-Yves; Frouin, Robert; Bernard, René

1991-02-01

Vertically integrated atmospheric liquid water content derived from Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) brightness temperatures and from GOES-1 Visible and Infrared Spin-Scan Radiometer (VISSR) radiances in the visible are compared over the Indian Ocean during MONEX (monsoon experiment). In the retrieval procedure, Wilheit and Chang' algorithm and Stephens' parameterization schemes are applied to the SMMR and VISSR data, respectively. The results indicate that in the 0-100 mg cm2 range of liquid water content considered, the correlation coefficient between the two types of estimates is 0.83 (0.81- 0.85 at the 99 percent confidence level). The Wilheit and Chang algorithm, however, yields values lower than those obtained with Stephens's schemes by 24.5 mg cm2 on the average, and occasionally the SMMR-based values are negative. Alternative algorithms are proposed for use with SMMR data, which eliminate the bias, augment the correlation coefficient, and reduce the rms difference. These algorithms include using the Witheit and Chang formula with modified coefficients (multilinear regression), the Wilheit and Chang formula with the same coefficients but different equivalent atmospheric temperatures for each channel (temperature bias adjustment), and a second-order polynomial in brightness temperatures at 18, 21, and 37 GHz (polynomial development). When applied to a dataset excluded from the regressionn dataset, the multilinear regression algorithm provides the best results, namely a 0.91 correlation coefficient, a 5.2 mg cm2 (residual) difference, and a 2.9 mg cm2 bias. Simply shifting the liquid water content predicted by the Wilheit and Chang algorithm does not yield as good comparison statistics, indicating that the occasional negative values are not due only to a bias. The more accurate SMMR-derived liquid water content allows one to better evaluate cloud transmittance in the solar spectrum, at least in the area and during the period analyzed. Combining this cloud transmittance with a clear sky model would provide ocean surface insulation estimates from SMMR data alone.

Development and validation of two equations based on anthropometry, estimating body fat for the Greek adult population.

PubMed

Kanellakis, Spyridon; Skoufas, Efstathios; Khudokonenko, Vladlena; Apostolidou, Eftychia; Gerakiti, Loukia; Andrioti, Maria-Chrysi; Bountouvi, Evangelia; Manios, Yannis

2017-02-01

To validate anthropometric equations in the current literature predicting body fat percentage (%BF) in the Greek population, to develop and validate two anthropometric equations estimating %BF, and to compare them with the retrieved equations. Anthropometric data from 642 Greek adults were incorporated. Dual-energy X-ray absorptiometry was used as reference method. The comparison with other equations was made using Bland-Altman analysis, intraclass correlation coefficient, and Lin's concordance correlation coefficient. Nine of the thirty-one retrieved equations had no statistically significant bias. However, all of them had wide limits of agreement (±8.3 to ±16%BF). The equations accrued were: BF% = -0.615-10.948 × sex + 0.321 × waist circumference + 0.502 × hips circumference-0.39 × forearm circumference - 19.768 × height (m) and BF% = -27.787-5.515 × sex-8.419 × height + 0.145 × waist circumference + 0.270 × hips circumference + 7.509 × log of thigh skinfold + 20.090 × log of sum of skinfolds (bicep + tricep + suprailiac + subscapular)-0.445 × forearm circumference. Bland-Altman's reliability analysis showed no significant bias of -0.058 and -0.148%BF and limits of agreement ±8.100 and ±6.056%BF; the intraclass correlation coefficient was 0.955 and 0.976; and Lin's concordance correlation coefficient was 0.914 and 0.951, respectively. Literature equations performed moderately on this study's population. Therefore, two equations were designed and validated. The first one was simple and easily applicable, with measures obtained from a measuring tape, and the second one more complicated yet more accurate and reliable. Both were found to be reliable for the assessment of body composition in the Greek population. © 2017 The Obesity Society.

Second-degree Stokes coefficients from multi-satellite SLR

NASA Astrophysics Data System (ADS)

Bloßfeld, Mathis; Müller, Horst; Gerstl, Michael; Štefka, Vojtěch; Bouman, Johannes; Göttl, Franziska; Horwath, Martin

2015-09-01

The long wavelength part of the Earth's gravity field can be determined, with varying accuracy, from satellite laser ranging (SLR). In this study, we investigate the combination of up to ten geodetic SLR satellites using iterative variance component estimation. SLR observations to different satellites are combined in order to identify the impact of each satellite on the estimated Stokes coefficients. The combination of satellite-specific weekly or monthly arcs allows to reduce parameter correlations of the single-satellite solutions and leads to alternative estimates of the second-degree Stokes coefficients. This alternative time series might be helpful for assessing the uncertainty in the impact of the low-degree Stokes coefficients on geophysical investigations. In order to validate the obtained time series of second-degree Stokes coefficients, a comparison with the SLR RL05 time series of the Center of Space Research (CSR) is done. This investigation shows that all time series are comparable to the CSR time series. The precision of the weekly/monthly and coefficients is analyzed by comparing mass-related equatorial excitation functions with geophysical model results and reduced geodetic excitation functions. In case of , the annual amplitude and phase of the DGFI solution agrees better with three of four geophysical model combinations than other time series. In case of , all time series agree very well to each other. The impact of on the ice mass trend estimates for Antarctica are compared based on CSR GRACE RL05 solutions, in which different monthly time series are used for replacing. We found differences in the long-term Antarctic ice loss of Gt/year between the GRACE solutions induced by the different SLR time series of CSR and DGFI, which is about 13 % of the total ice loss of Antarctica. This result shows that Antarctic ice mass loss quantifications must be carefully interpreted.

Statistical inference for Hardy-Weinberg proportions in the presence of missing genotype information.

PubMed

Graffelman, Jan; Sánchez, Milagros; Cook, Samantha; Moreno, Victor

2013-01-01

In genetic association studies, tests for Hardy-Weinberg proportions are often employed as a quality control checking procedure. Missing genotypes are typically discarded prior to testing. In this paper we show that inference for Hardy-Weinberg proportions can be biased when missing values are discarded. We propose to use multiple imputation of missing values in order to improve inference for Hardy-Weinberg proportions. For imputation we employ a multinomial logit model that uses information from allele intensities and/or neighbouring markers. Analysis of an empirical data set of single nucleotide polymorphisms possibly related to colon cancer reveals that missing genotypes are not missing completely at random. Deviation from Hardy-Weinberg proportions is mostly due to a lack of heterozygotes. Inbreeding coefficients estimated by multiple imputation of the missings are typically lowered with respect to inbreeding coefficients estimated by discarding the missings. Accounting for missings by multiple imputation qualitatively changed the results of 10 to 17% of the statistical tests performed. Estimates of inbreeding coefficients obtained by multiple imputation showed high correlation with estimates obtained by single imputation using an external reference panel. Our conclusion is that imputation of missing data leads to improved statistical inference for Hardy-Weinberg proportions.

Application of the two-film model to the volatilization of acetone and t-butyl alcohol from water as a function of temperature

USGS Publications Warehouse

Rathbun, R.E.; Tai, D.Y.

1988-01-01

The two-film model is often used to describe the volatilization of organic substances from water. This model assumes uniformly mixed water and air phases separated by thin films of water and air in which mass transfer is by molecular diffusion. Mass-transfer coefficients for the films, commonly called film coefficients, are related through the Henry's law constant and the model equation to the overall mass-transfer coefficient for volatilization. The films are modeled as two resistances in series, resulting in additive resistances. The two-film model and the concept of additivity of resistances were applied to experimental data for acetone and t-butyl alcohol. Overall mass-transfer coefficients for the volatilization of acetone and t-butyl alcohol from water were measured in the laboratory in a stirred constant-temperature bath. Measurements were completed for six water temperatures, each at three water mixing conditions. Wind-speed was constant at about 0.1 meter per second for all experiments. Oxygen absorption coefficients were measured simultaneously with the measurement of the acetone and t-butyl alcohol mass-transfer coefficients. Gas-film coefficients for acetone, t-butyl alcohol, and water were determined by measuring the volatilization fluxes of the pure substances over a range of temperatures. Henry's law constants were estimated from data from the literature. The combination of high resistance in the gas film for solutes with low values of the Henry's law constants has not been studied previously. Calculation of the liquid-film coefficients for acetone and t-butyl alcohol from measured overall mass-transfer and gas-film coefficients, estimated Henry's law constants, and the two-film model equation resulted in physically unrealistic, negative liquid-film coefficients for most of the experiments at the medium and high water mixing conditions. An analysis of the two-film model equation showed that when the percentage resistance in the gas film is large and the gas-film resistance approaches the overall resistance in value, the calculated liquid-film coefficient becomes extremely sensitive to errors in the Henry's law constant. The negative coefficients were attributed to this sensitivity and to errors in the estimated Henry's law constants. Liquid-film coefficients for the absorption of oxygen were correlated with the stirrer Reynolds number and the Schmidt number. Application of this correlation with the experimental conditions and a molecular-diffusion coefficient adjustment resulted in values of the liquid-film coefficients for both acetone and t-butyl alcohol within the range expected for all three mixing conditions. Comparison of Henry's law constants calculated from these film coefficients and the experimental data with the constants calculated from literature data showed that the differences were small relative to the errors reported in the literature as typical for the measurement or estimation of Henry's law constants for hydrophilic compounds such as ketones and alcohols. Temperature dependence of the mass-transfer coefficients was expressed in two forms. The first, based on thermodynamics, assumed the coefficients varied as the exponential of the reciprocal absolute temperature. The second empirical approach assumed the coefficients varied as the exponential of the absolute temperature. Both of these forms predicted the temperature dependence of the experimental mass-transfer coefficients with little error for most of the water temperature range likely to be found in streams and rivers. Liquid-film and gas-film coefficients for acetone and t-butyl alcohol were similar in value. However, depending on water mixing conditions, overall mass-transfer coefficients for acetone were from two to four times larger than the coefficients for t-butyl alcohol. This difference in behavior of the coefficients resulted because the Henry's law constant for acetone was about three times larger than that of

Reliability of plasma polar metabolite concentrations in a large-scale cohort study using capillary electrophoresis-mass spectrometry.

PubMed

Harada, Sei; Hirayama, Akiyoshi; Chan, Queenie; Kurihara, Ayako; Fukai, Kota; Iida, Miho; Kato, Suzuka; Sugiyama, Daisuke; Kuwabara, Kazuyo; Takeuchi, Ayano; Akiyama, Miki; Okamura, Tomonori; Ebbels, Timothy M D; Elliott, Paul; Tomita, Masaru; Sato, Asako; Suzuki, Chizuru; Sugimoto, Masahiro; Soga, Tomoyoshi; Takebayashi, Toru

2018-01-01

Cohort studies with metabolomics data are becoming more widespread, however, large-scale studies involving 10,000s of participants are still limited, especially in Asian populations. Therefore, we started the Tsuruoka Metabolomics Cohort Study enrolling 11,002 community-dwelling adults in Japan, and using capillary electrophoresis-mass spectrometry (CE-MS) and liquid chromatography-mass spectrometry. The CE-MS method is highly amenable to absolute quantification of polar metabolites, however, its reliability for large-scale measurement is unclear. The aim of this study is to examine reproducibility and validity of large-scale CE-MS measurements. In addition, the study presents absolute concentrations of polar metabolites in human plasma, which can be used in future as reference ranges in a Japanese population. Metabolomic profiling of 8,413 fasting plasma samples were completed using CE-MS, and 94 polar metabolites were structurally identified and quantified. Quality control (QC) samples were injected every ten samples and assessed throughout the analysis. Inter- and intra-batch coefficients of variation of QC and participant samples, and technical intraclass correlation coefficients were estimated. Passing-Bablok regression of plasma concentrations by CE-MS on serum concentrations by standard clinical chemistry assays was conducted for creatinine and uric acid. In QC samples, coefficient of variation was less than 20% for 64 metabolites, and less than 30% for 80 metabolites out of the 94 metabolites. Inter-batch coefficient of variation was less than 20% for 81 metabolites. Estimated technical intraclass correlation coefficient was above 0.75 for 67 metabolites. The slope of Passing-Bablok regression was estimated as 0.97 (95% confidence interval: 0.95, 0.98) for creatinine and 0.95 (0.92, 0.96) for uric acid. Compared to published data from other large cohort measurement platforms, reproducibility of metabolites common to the platforms was similar to or better than in the other studies. These results show that our CE-MS platform is suitable for conducting large-scale epidemiological studies.

A 3D analysis of oxygen transfer in a low-cost micro-bioreactor for animal cell suspension culture.

PubMed

Yu, P; Lee, T S; Zeng, Y; Low, H T

2007-01-01

A 3D numerical model was developed to study the flow field and oxygen transport in a micro-bioreactor with a rotating magnetic bar on the bottom to mix the culture medium. The Reynolds number (Re) was kept in the range of 100-716 to ensure laminar environment for animal cell culture. The volumetric oxygen transfer coefficient (k(L)a) was determined from the oxygen concentration distribution. It was found that the effect of the cell consumption on k(L)a could be negligible. A correlation was proposed to predict the liquid-phase oxygen transfer coefficient (k(Lm)) as a function of Re. The overall oxygen transfer coefficient (k(L)) was obtained by the two-resistance model. Another correlation, within an error of 15%, was proposed to estimate the minimum oxygen concentration to avoid cell hypoxia. By combination of the correlations, the maximum cell density, which the present micro-bioreactor could support, was predicted to be in the order of 10(12) cells m(-3). The results are comparable with typical values reported for animal cell growth in mechanically stirred bioreactors.

Upscaling of nanoparticle transport in porous media under unfavorable conditions: Pore scale to Darcy scale

NASA Astrophysics Data System (ADS)

Seetha, N.; Raoof, Amir; Mohan Kumar, M. S.; Majid Hassanizadeh, S.

2017-05-01

Transport and deposition of nanoparticles in porous media is a multi-scale problem governed by several pore-scale processes, and hence, it is critical to link the processes at pore scale to the Darcy-scale behavior. In this study, using pore network modeling, we develop correlation equations for deposition rate coefficients for nanoparticle transport under unfavorable conditions at the Darcy scale based on pore-scale mechanisms. The upscaling tool is a multi-directional pore-network model consisting of an interconnected network of pores with variable connectivities. Correlation equations describing the pore-averaged deposition rate coefficients under unfavorable conditions in a cylindrical pore, developed in our earlier studies, are employed for each pore element. Pore-network simulations are performed for a wide range of parameter values to obtain the breakthrough curves of nanoparticle concentration. The latter is fitted with macroscopic 1-D advection-dispersion equation with a two-site linear reversible deposition accounting for both equilibrium and kinetic sorption. This leads to the estimation of three Darcy-scale deposition coefficients: distribution coefficient, kinetic rate constant, and the fraction of equilibrium sites. The correlation equations for the Darcy-scale deposition coefficients, under unfavorable conditions, are provided as a function of measurable Darcy-scale parameters, including: porosity, mean pore throat radius, mean pore water velocity, nanoparticle radius, ionic strength, dielectric constant, viscosity, temperature, and surface potentials of the particle and grain surfaces. The correlation equations are found to be consistent with the available experimental results, and in qualitative agreement with Colloid Filtration Theory for all parameters, except for the mean pore water velocity and nanoparticle radius.

Discrepancies between leg-to-leg bioelectrical Impedance analysis and computerized tomography in abdominal visceral fat measurement.

PubMed

Lu, Hsueh-Kuan; Chen, Yu-Yawn; Yeh, Chinagwen; Chuang, Chih-Lin; Chiang, Li-Ming; Lai, Chung-Liang; Casebolt, Kevin M; Huang, Ai-Chun; Lin, Wen-Long; Hsieh, Kuen-Chang

2017-08-22

The aim of this study was to evaluate leg-to-leg bioelectrical impedance analysis (LBIA) using a four-contact electrode system for measuring abdominal visceral fat area (VFA). The present study recruited 381 (240 male and 141 female) Chinese participants to compare VFA measurements estimated by a standing LBIA system (VFALBIA) with computerized tomography (CT) scanned at the L4-L5 vertebrae (VFA CT ). The total mean body mass index (BMI) was 24.7 ± 4.2 kg/m 2 . Correlation analysis, regression analysis, Bland-Altman plot, and paired sample t-tests were used to analyze the accuracy of the VFA LBIA . For the total subjects, the regression line was VFA LBIA  = 0.698 VFA CT  + 29.521, (correlation coefficient (r) = 0.789, standard estimate of error (SEE) = 24.470 cm 2 , p < 0.001), Lin's correlation coefficient (CCC) was 0.785; and the limit of agreement (LOA; mean difference ±2 standard deviation) ranged from -43.950 to 67.951 cm 2 , LOA% (given as a percentage of mean value measured by the CT) was 48.2%. VFA LBIA and VFA CT showed significant difference (p < 0.001). Collectively, the current study indicates that LBIA has limited potential to accurately estimate visceral fat in a clinical setting.

A Correlation Study of DHA Intake Estimated by a FFQ and Concentrations in Plasma and Erythrocytes in Mid- and Late Pregnancy

PubMed Central

Zhou, Yu-Bo; Li, Hong-Tian; Trasande, Leonardo; Wang, Lin-Lin; Zhang, Ya-Li; Si, Ke-Yi; Bai, Man-Xi; Liu, Jian-Meng

2017-01-01

Adequate docosahexaenoic acid (DHA) is essential for the optimal growth and development of the fetus. Maternal DHA content fluctuates during pregnancy. The correlation of DHA content with dietary intake might be varied over the course of pregnancy. We aimed to compare the dietary DHA intake, estimated by a DHA-specific semiquantitative food frequency questionnaire (FFQ) against its blood content, among mid- and late-term pregnant women. A total of 804 Chinese pregnant women completed the tailored FFQ and provided fasting venous blood samples. Dietary DHA intake (mg/day) in the previous month was calculated from the FFQ using Chinese Food Composition Table. DHA concentrations (weight percent of total fatty acids) in plasma and erythrocytes were measured by capillary gas chromatography. Spearman correlation coefficients (rs) between DHA intake and its relative concentrations were calculated. After adjustment for maternal age, pre-pregnancy body mass index, stage of pregnancy, parity, education level, ethnicity, and annual family income per capita, the correlation coefficients of DHA intake with its concentrations in plasma and erythrocytes were 0.35 and 0.33, respectively (p < 0.001). The correlations were relatively stronger among women in late pregnancy (rs = 0.44 in plasma and 0.39 in erythrocytes) than those in mid-pregnancy (rs = 0.25 and 0.26). The significant correlations were consistently observed in subgroups stratified by regions, except for erythrocytes in women living in a coastland area. Multiple regression analyses also indicated significant positive linear correlations between DHA intake and its plasma or erythrocytes concentrations (p < 0.001). In conclusion, dietary DHA intake, estimated by the FFQ, was positively correlated with its concentrations in plasma and erythrocytes in Chinese pregnant women, especially for women in late pregnancy, with the exception of the erythrocytes of those living in a coastland area. PMID:29144430

A Correlation Study of DHA Intake Estimated by a FFQ and Concentrations in Plasma and Erythrocytes in Mid- and Late Pregnancy.

PubMed

Zhou, Yu-Bo; Li, Hong-Tian; Trasande, Leonardo; Wang, Lin-Lin; Zhang, Ya-Li; Si, Ke-Yi; Bai, Man-Xi; Liu, Jian-Meng

2017-11-16

Adequate docosahexaenoic acid (DHA) is essential for the optimal growth and development of the fetus. Maternal DHA content fluctuates during pregnancy. The correlation of DHA content with dietary intake might be varied over the course of pregnancy. We aimed to compare the dietary DHA intake, estimated by a DHA-specific semiquantitative food frequency questionnaire (FFQ) against its blood content, among mid- and late-term pregnant women. A total of 804 Chinese pregnant women completed the tailored FFQ and provided fasting venous blood samples. Dietary DHA intake (mg/day) in the previous month was calculated from the FFQ using Chinese Food Composition Table. DHA concentrations (weight percent of total fatty acids) in plasma and erythrocytes were measured by capillary gas chromatography. Spearman correlation coefficients ( r s ) between DHA intake and its relative concentrations were calculated. After adjustment for maternal age, pre-pregnancy body mass index, stage of pregnancy, parity, education level, ethnicity, and annual family income per capita, the correlation coefficients of DHA intake with its concentrations in plasma and erythrocytes were 0.35 and 0.33, respectively ( p < 0.001). The correlations were relatively stronger among women in late pregnancy ( r s = 0.44 in plasma and 0.39 in erythrocytes) than those in mid-pregnancy ( r s = 0.25 and 0.26). The significant correlations were consistently observed in subgroups stratified by regions, except for erythrocytes in women living in a coastland area. Multiple regression analyses also indicated significant positive linear correlations between DHA intake and its plasma or erythrocytes concentrations ( p < 0.001). In conclusion, dietary DHA intake, estimated by the FFQ, was positively correlated with its concentrations in plasma and erythrocytes in Chinese pregnant women, especially for women in late pregnancy, with the exception of the erythrocytes of those living in a coastland area.

Impact of Autocorrelation on Functional Connectivity

PubMed Central

Arbabshirani, Mohammad R.; Damaraju, Eswar; Phlypo, Ronald; Plis, Sergey; Allen, Elena; Ma, Sai; Mathalon, Daniel; Preda, Adrian; Vaidya, Jatin G.; Adali, Tülay; Calhoun, Vince D.

2014-01-01

Although the impact of serial correlation (autocorrelation) in residuals of general linear models for fMRI time-series has been studied extensively, the effect of autocorrelation on functional connectivity studies has been largely neglected until recently. Some recent studies based on results from economics have questioned the conventional estimation of functional connectivity and argue that not correcting for autocorrelation in fMRI time-series results in “spurious” correlation coefficients. In this paper, first we assess the effect of autocorrelation on Pearson correlation coefficient through theoretical approximation and simulation. Then we present this effect on real fMRI data. To our knowledge this is the first work comprehensively investigating the effect of autocorrelation on functional connectivity estimates. Our results show that although FC values are altered, even following correction for autocorrelation, results of hypothesis testing on FC values remain very similar to those before correction. In real data we show this is true for main effects and also for group difference testing between healthy controls and schizophrenia patients. We further discuss model order selection in the context of autoregressive processes, effects of frequency filtering and propose a preprocessing pipeline for connectivity studies. PMID:25072392

Estimating the intra-cluster correlation coefficient for evaluating an educational intervention program to improve rabies awareness and dog bite prevention among children in Sikkim, India: A pilot study.

PubMed

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-exposure precautionary steps following educational intervention increased by 87%. The ICC estimates presented in this study will aid in designing cluster-based studies evaluating educational interventions as part of disease control programs. This study demonstrates the likely benefits of educational intervention incorporating bite prevention and rabies education. Copyright © 2017 Elsevier B.V. All rights reserved.

MRI-Based Intelligence Quotient (IQ) Estimation with Sparse Learning

PubMed Central

Wang, Liye; Wee, Chong-Yaw; Suk, Heung-Il; Tang, Xiaoying; Shen, Dinggang

2015-01-01

In this paper, we propose a novel framework for IQ estimation using Magnetic Resonance Imaging (MRI) data. In particular, we devise a new feature selection method based on an extended dirty model for jointly considering both element-wise sparsity and group-wise sparsity. Meanwhile, due to the absence of large dataset with consistent scanning protocols for the IQ estimation, we integrate multiple datasets scanned from different sites with different scanning parameters and protocols. In this way, there is large variability in these different datasets. To address this issue, we design a two-step procedure for 1) first identifying the possible scanning site for each testing subject and 2) then estimating the testing subject’s IQ by using a specific estimator designed for that scanning site. We perform two experiments to test the performance of our method by using the MRI data collected from 164 typically developing children between 6 and 15 years old. In the first experiment, we use a multi-kernel Support Vector Regression (SVR) for estimating IQ values, and obtain an average correlation coefficient of 0.718 and also an average root mean square error of 8.695 between the true IQs and the estimated ones. In the second experiment, we use a single-kernel SVR for IQ estimation, and achieve an average correlation coefficient of 0.684 and an average root mean square error of 9.166. All these results show the effectiveness of using imaging data for IQ prediction, which is rarely done in the field according to our knowledge. PMID:25822851

Estimating EQ-5D values from the Oswestry Disability Index and numeric rating scales for back and leg pain.

PubMed

Carreon, Leah Y; Bratcher, Kelly R; Das, Nandita; Nienhuis, Jacob B; Glassman, Steven D

2014-04-15

Cross-sectional cohort. The purpose of this study is to determine whether the EuroQOL-5D (EQ-5D) can be derived from commonly available low back disease-specific health-related quality of life measures. The Oswestry Disability Index (ODI) and numeric rating scales (0-10) for back pain (BP) and leg pain (LP) are widely used disease-specific measures in patients with lumbar degenerative disorders. Increasingly, the EQ-5D is being used as a measure of utility due to ease of administration and scoring. The EQ-5D, ODI, BP, and LP were prospectively collected in 14,544 patients seen in clinic for lumbar degenerative disorders. Pearson correlation coefficients for paired observations from multiple time points between ODI, BP, LP, and EQ-5D were determined. Regression modeling was done to compute the EQ-5D score from the ODI, BP, and LP. The mean age was 53.3 ± 16.4 years and 41% were male. Correlations between the EQ-5D and the ODI, BP, and LP were statistically significant (P < 0.0001) with correlation coefficients of -0.77, -0.50, and -0.57, respectively. The regression equation: [0.97711 + (-0.00687 × ODI) + (-0.01488 × LP) + (-0.01008 × BP)] to predict EQ-5D, had an R2 of 0.61 and a root mean square error of 0.149. The model using ODI alone had an R2 of 0.57 and a root mean square error of 0.156. The model using the individual ODI items had an R2 of 0.64 and a root mean square error of 0.143. The correlation coefficient between the observed and estimated EQ-5D score was 0.78. There was no statistically significant difference between the actual EQ-5D (0.553 ± 0.238) and the estimated EQ-5D score (0.553 ± 0.186) using the ODI, BP, and LP regression model. However, rounding off the coefficients to less than 5 decimal places produced less accurate results. Unlike previous studies showing a robust relationship between low back-specific measures and the Short Form-6D, a similar relationship was not seen between the ODI, BP, LP, and the EQ-5D. Thus, the EQ-5D cannot be accurately estimated from the ODI, BP, and LP. 2.

A Bayesian estimate of the concordance correlation coefficient with skewed data.

PubMed

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. Copyright © 2015 John Wiley & Sons, Ltd.

Using CO2:CO Correlations to Improve Inverse Analyses of Carbon Fluxes

NASA Technical Reports Server (NTRS)

Palmer, Paul I.; Suntharalingam, Parvadha; Jones, Dylan B. A.; Jacob, Daniel J.; Streets, David G.; Fu, Qingyan; Vay, Stephanie A.; Sachse, Glen W.

2006-01-01

Observed correlations between atmospheric concentrations of CO2 and CO represent potentially powerful information for improving CO2 surface flux estimates through coupled CO2-CO inverse analyses. We explore the value of these correlations in improving estimates of regional CO2 fluxes in east Asia by using aircraft observations of CO2 and CO from the TRACE-P campaign over the NW Pacific in March 2001. Our inverse model uses regional CO2 and CO surface fluxes as the state vector, separating biospheric and combustion contributions to CO2. CO2-CO error correlation coefficients are included in the inversion as off-diagonal entries in the a priori and observation error covariance matrices. We derive error correlations in a priori combustion source estimates of CO2 and CO by propagating error estimates of fuel consumption rates and emission factors. However, we find that these correlations are weak because CO source uncertainties are mostly determined by emission factors. Observed correlations between atmospheric CO2 and CO concentrations imply corresponding error correlations in the chemical transport model used as the forward model for the inversion. These error correlations in excess of 0.7, as derived from the TRACE-P data, enable a coupled CO2-CO inversion to achieve significant improvement over a CO2-only inversion for quantifying regional fluxes of CO2.

Effective diffusion coefficients of DNAPL waste components in saturated low permeability soil materials.

PubMed

Ayral-Cinar, Derya; Demond, Avery H

2017-12-01

Diffusion is regarded as the dominant transport mechanism into and out of low permeable subsurface lenses and layers in the subsurface. But, some reports of mass storage in such zones are higher than what might be attributable to diffusion, based on estimated diffusion coefficients. Despite the importance of diffusion to efforts to estimate the quantity of residual contamination in the subsurface, relatively few studies present measured diffusion coefficients of organic solutes in saturated low permeability soils. This study reports the diffusion coefficients of a trichloroethylene (TCE), and an anionic surfactant, Aerosol OT (AOT), in water-saturated silt and a silt-montmorillonite (25:75) mixture, obtained using steady-state experiments. The relative diffusivity ranged from 0.11 to 0.17 for all three compounds for the silt and the silt-clay mixture that was allowed to expand. In the case in which the swelling was constrained, the relative diffusivity was about 0.07. In addition, the relative diffusivity of 13 C-labeled TCE through a water saturated silt-clay mixture that had contacted a field dense non-aqueous phase liquid (DNAPL) for 18months was measured and equaled 0.001. These experimental results were compared with the estimates generated using common correlations, and it was found that, in all cases, the measured diffusion coefficients were significantly lower than the estimated. Thus, the discrepancy between mass accumulations observed in the field and the mass storage that can attributable to diffusion may be greater than previously believed. Copyright © 2017. Published by Elsevier B.V.

Weather adjustment using seemingly unrelated regression

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

Noll, T.A.

1995-05-01

Seemingly unrelated regression (SUR) is a system estimation technique that accounts for time-contemporaneous correlation between individual equations within a system of equations. SUR is suited to weather adjustment estimations when the estimation is: (1) composed of a system of equations and (2) the system of equations represents either different weather stations, different sales sectors or a combination of different weather stations and different sales sectors. SUR utilizes the cross-equation error values to develop more accurate estimates of the system coefficients than are obtained using ordinary least-squares (OLS) estimation. SUR estimates can be generated using a variety of statistical software packagesmore » including MicroTSP and SAS.« less

Estimating parameter of influenza transmission using regularized least square

NASA Astrophysics Data System (ADS)

Nuraini, N.; Syukriah, Y.; Indratno, S. W.

2014-02-01

Transmission process of influenza can be presented in a mathematical model as a non-linear differential equations system. In this model the transmission of influenza is determined by the parameter of contact rate of the infected host and susceptible host. This parameter will be estimated using a regularized least square method where the Finite Element Method and Euler Method are used for approximating the solution of the SIR differential equation. The new infected data of influenza from CDC is used to see the effectiveness of the method. The estimated parameter represents the contact rate proportion of transmission probability in a day which can influence the number of infected people by the influenza. Relation between the estimated parameter and the number of infected people by the influenza is measured by coefficient of correlation. The numerical results show positive correlation between the estimated parameters and the infected people.

Effects of calcium leaching on diffusion properties of hardened and altered cement pastes

NASA Astrophysics Data System (ADS)

Kurumisawa, Kiyofumi; Haga, Kazuko; Hayashi, Daisuke; Owada, Hitoshi

2017-06-01

It is very important to predict alterations in the concrete used for fabricating disposal containers for radioactive waste. Therefore, it is necessary to understand the alteration of cementitious materials caused by calcium leaching when they are in contact with ground water in the long term. To evaluate the long-term transport characteristics of cementitious materials, the microstructural behavior of these materials should be considered. However, many predictive models of transport characteristics focus on the pore structure, while only few such models consider both, the spatial distribution of calcium silicate hydrate (C-S-H), portlandite, and the pore spaces. This study focused on the spatial distribution of these cement phases. The auto-correlation function of each phase of cementitious materials was calculated from two-dimensional backscattered electron imaging, and the three-dimensional spatial image of the cementitious material was produced using these auto-correlation functions. An attempt was made to estimate the diffusion coefficient of chloride from the three-dimensional spatial image. The estimated diffusion coefficient of the altered sample from the three-dimensional spatial image was found to be comparable to the measured value. This demonstrated that it is possible to predict the diffusion coefficient of the altered cement paste by using the proposed model.

Developing a Danish version of the "Impact on Participation and Autonomy Questionnaire".

PubMed

Ghaziani, Emma; Krogh, Anne Grethe; Lund, Hans

2013-05-01

To translate the "Impact on Participation and Autonomy Questionnaire" into Danish (IPAQ-DK), and estimate its internal consistency and test-retest reliability in order to promote participation-based interventions and research. Translation and two successive reliability assessments through test-retest. 137 adults with varying degrees of impairment; of these, 67 participated in the final reliability assessment. The translation followed guidelines set forth by the "European Group for Quality of Life Assessment and Health Measurement". Internal consistency for subscales was estimated by Chronbach's alpha. Weighted kappa coefficients and intraclass correlation coefficients were calculated to assess the test-retest reliability at item and subscale level, respectively. A preliminary reliability assessment revealed residual issues regarding the translation and cultural adaptation of the instrument. The revised version (IPAQ-DK) was subsequently subjected to a similar assessment demonstrating Chronbach's alpha values from 0.698 to 0.817. Weighted kappa ranged from 0.370 to 0.880; 78% of these values were higher than 0.600. The intraclass correlation coefficient covered values from 0.701 to 0.818. IPAQ-DK is a useful instrument for identifying person-perceived participation restrictions and satisfaction with participation. Further studies of IPAQ-DK's floor/ceiling effects and responsiveness to change are recommended, and whether there is a need for further linguistic improvement of certain items.

Development of a Method to Observe Preschoolers' Packed Lunches in Early Care and Education Centers.

PubMed

Sweitzer, Sara J; Byrd-Williams, Courtney E; Ranjit, Nalini; Romo-Palafox, Maria Jose; Briley, Margaret E; Roberts-Gray, Cynthia R; Hoelscher, Deanna M

2015-08-01

As early childhood education (ECE) centers become a more common setting for nutrition interventions, a variety of data collection methods are required, based on the center foodservice. ECE centers that require parents to send in meals and/or snacks from home present a unique challenge for accurate nutrition estimation and data collection. We present an observational methodology for recording the contents and temperature of preschool-aged children's lunchboxes and data to support a 2-day vs a 3-day collection period. Lunchbox observers were trained in visual estimation of foods based on Child and Adult Care Food Program and MyPlate servings and household recommended measures. Trainees weighed and measured foods commonly found in preschool-aged children's lunchboxes and practiced recording accurate descriptions and food temperatures. Training included test assessments of whole-grain bread products, mixed dishes such as macaroni and cheese, and a variety of sandwich preparations. Validity of the estimation method was tested by comparing estimated to actual amounts for several distinct food types. Reliability was assessed by computing the intraclass correlation coefficient for each observer as well as an interrater reliability coefficient across observers. To compare 2- and 3-day observations, 2 of the 3 days of observations were randomly selected for each child and analyzed as a separate dataset. Linear model estimated mean and standard error of whole grains, fruits and vegetables, and amounts of energy, carbohydrates, protein, total fat, saturated fat, dietary fiber, thiamin, riboflavin, niacin, vitamins A and C, calcium, iron, sodium, and dietary fiber per lunch were compared across the 2- and 3-day observation datasets. The mean estimated amounts across 11 observers were statistically indistinguishable from the measured portion size for each of the 41 test foods, implying that the visual estimation measurement method was valid: intraobserver intraclass correlation coefficients ranged from 0.951 (95% CI 0.91 to 0.97) to 1.0. Across observers, the interrater reliability correlation coefficient was estimated at 0.979 (95% CI 0.957 to 0.993). Comparison of servings of fruits, vegetables, and whole grains showed no significant differences for serving size or mean energy and nutrient content between 2- and 3-day lunch observations. The methodology is a valid and reliable option for use in research and practice that requires observing and assessing the contents and portion sizes of food items in preschool-aged children's lunchboxes in an ECE setting. The use of visual observation and estimation with Child and Adult Care Food Program and MyPlate serving sizes and household measures over 2 random days of data collection enables food handling to be minimized while obtaining an accurate record of the variety and quantities of foods that young children are exposed to at lunch time. Copyright © 2015 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

Temporal behavior of the effective diffusion coefficients for transport in heterogeneous saturated aquifers

NASA Astrophysics Data System (ADS)

Suciu, N.; Vamos, C.; Vereecken, H.; Vanderborght, J.; Hardelauf, H.

2003-04-01

When the small scale transport is modeled by a Wiener process and the large scale heterogeneity by a random velocity field, the effective coefficients, Deff, can be decomposed as sums between the local coefficient, D, a contribution of the random advection, Dadv, and a contribution of the randomness of the trajectory of plume center of mass, Dcm: Deff=D+Dadv-Dcm. The coefficient Dadv is similar to that introduced by Taylor in 1921, and more recent works associate it with the thermodynamic equilibrium. The ``ergodic hypothesis'' says that over large time intervals Dcm vanishes and the effect of the heterogeneity is described by Dadv=Deff-D. In this work we investigate numerically the long time behavior of the effective coefficients as well as the validity of the ergodic hypothesis. The transport in every realization of the velocity field is modeled with the Global Random Walk Algorithm, which is able to track as many particles as necessary to achieve a statistically reliable simulation of the process. Averages over realizations are further used to estimate mean coefficients and standard deviations. In order to remain in the frame of most of the theoretical approaches, the velocity field was generated in a linear approximation and the logarithm of the hydraulic conductivity was taken to be exponential decaying correlated with variance equal to 0.1. Our results show that even in these idealized conditions, the effective coefficients tend to asymptotic constant values only when the plume travels thousands of correlations lengths (while the first order theories usually predict Fickian behavior after tens of correlations lengths) and that the ergodicity conditions are still far from being met.

Rip Channels, Megacusps, and Shoreline Change: Measurements and Modeling

DTIC Science & Technology

2010-06-01

and October 2007 with correlation coefficients (r) and slopes (m) in upper left corner. While the correlation of CDIP - and ADCP-predicted rms wave...about ±5º). In spite of this, CDIP -model- based predictions of offshore radiation stress, Syx,s, and sediment transport rates, qs, in the surf zone...73 Figure 12. Wave roses showing mean wave directions and frequencies at 15 m depth, offshore of Stilwell site, as estimated by CDIP

Forecasting F10.7 with Solar Magnetic Flux Transport Modeling (Postprint)

DTIC Science & Technology

2012-04-03

Charles N. Arge Joel B. Mozer Project Manager, RVBXS Chief, RVB This report is published in the interest of...within 6 hours of the F10.7 measurements during the years 1993 through 2010, the Spearman correlation coefficient, rs, for an empirical model of...estimation of the Earth-side solar magnetic field distribution used to forecast F10.7. Spearman correlation values of approximately 0.97, 0.95, and 0.93 are

Accuracy of contrast-enhanced spectral mammography for estimating residual tumor size after neoadjuvant chemotherapy in patients with breast cancer: a feasibility study.

PubMed

Barra, Filipe Ramos; de Souza, Fernanda Freire; Camelo, Rosimara Eva Ferreira Almeida; Ribeiro, Andrea Campos de Oliveira; Farage, Luciano

2017-01-01

To assess the feasibility of contrast-enhanced spectral mammography (CESM) of the breast for assessing the size of residual tumors after neoadjuvant chemotherapy (NAC). In breast cancer patients who underwent NAC between 2011 and 2013, we evaluated residual tumor measurements obtained with CESM and full-field digital mammography (FFDM). We determined the concordance between the methods, as well as their level of agreement with the pathology. Three radiologists analyzed eight CESM and FFDM measurements separately, considering the size of the residual tumor at its largest diameter and correlating it with that determined in the pathological analysis. Interobserver agreement was also evaluated. The sensitivity, specificity, positive predictive value, and negative predictive value were higher for CESM than for FFDM (83.33%, 100%, 100%, and 66% vs. 50%, 50%, 50%, and 25%, respectively). The CESM measurements showed a strong, consistent correlation with the pathological findings (correlation coefficient = 0.76-0.92; intraclass correlation coefficient = 0.692-0.886). The correlation between the FFDM measurements and the pathological findings was not statistically significant, with questionable consistency (intraclass correlation coefficient = 0.488-0.598). Agreement with the pathological findings was narrower for CESM measurements than for FFDM measurements. Interobserver agreement was higher for CESM than for FFDM (0.94 vs. 0.88). CESM is a feasible means of evaluating residual tumor size after NAC, showing a good correlation and good agreement with pathological findings. For CESM measurements, the interobserver agreement was excellent.

[VALIDATION OF PREDICTIVE EQUATIONS FOR WEIGHT AND HEIGHT USING BODY CIRCUMFERENCES IN MEXICAN ELDERLYS].

PubMed

Osuna-Padilla, Iván Armando; Borja-Magno, Angélica Irais; Leal-Escobar, Gabriela; Verdugo-Hernández, Sonia

2015-12-01

weight and height measurements are important data for the nutritional assessment of elderly people and the implementation of the nutritional care process. Malnutrition is common in this population, who has high rates of disability that difficult to measurement this variables. evaluate the validity of predictive equations for weight and height that include body circumferences created for brazilian population, in mexican elderly people. this is a comparative, observational, prospective and cross-sectional study, 61 elderly were evaluated. Body weight, height, half span, calf, arm and abdominal circumferences were determinated. Weight and height were estimated with de predictive equations published by Rabito et al. Bland-Altman analysis and Intraclass Correlation Coefficient were used to assess the levels of agreement between the estimated and the measured values. The level of statistical significance was p < 0.05. the age mean was 78.7 ± 8.7 and 55.7% were females. The weight mean was 61.9 ± 14.1 kg, height mean was 155.4 ± 9.5 cm and Body Mass Index (BMI) mean corresponded to 25.5 ± 5.1 kg/m. The Bland-Altman plots indicated that the 95% confidence interval (95% IC) limits for the difference between real and estimated weight ranged from -14.3 kg to 8.1 kg, the mean of the difference or systematic error (SE) was -3.1 kg, we observed an statistically significant coefficient of 0.12 (p < 0.03). The 95% IC limits for the difference between real and estimated height ranged from -11.1 to 15.9 cm, the diffe rence mean or SE of 2.4 cm, we observed a coefficient of -0.04 (p = 0.67) . Intraclass Correlation Coefficient of 0.72 (p < 0.00) and 0.88 (p < 0.00) were obtained for weight and height, respectively. the equations developed by Rabito showed a good agreement when compared with the actual weight and height of elderly people. We observed variations in the estimated weight in obesity elderlys. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

Patient-specific dose estimation for pediatric abdomen-pelvis CT

NASA Astrophysics Data System (ADS)

Li, Xiang; Samei, Ehsan; Segars, W. Paul; Sturgeon, Gregory M.; Colsher, James G.; Frush, Donald P.

2009-02-01

The purpose of this study is to develop a method for estimating patient-specific dose from abdomen-pelvis CT examinations and to investigate dose variation across patients in the same weight group. Our study consisted of seven pediatric patients in the same weight/protocol group, for whom full-body computer models were previously created based on the patients' CT data obtained for clinical indications. Organ and effective dose of these patients from an abdomen-pelvis scan protocol (LightSpeed VCT scanner, 120-kVp, 85-90 mA, 0.4-s gantry rotation period, 1.375-pitch, 40-mm beam collimation, and small body scan field-of-view) was calculated using a Monte Carlo program previously developed and validated for the same CT system. The seven patients had effective dose of 2.4-2.8 mSv, corresponding to normalized effective dose of 6.6-8.3 mSv/100mAs (coefficient of variation: 7.6%). Dose variations across the patients were small for large organs in the scan coverage (mean: 6.6%; range: 4.9%-9.2%), larger for small organs in the scan coverage (mean: 10.3%; range: 1.4%-15.6%), and the largest for organs partially or completely outside the scan coverage (mean: 14.8%; range: 5.7%-27.7%). Normalized effective dose correlated strongly with body weight (correlation coefficient: r = -0.94). Normalized dose to the kidney and the adrenal gland correlated strongly with mid-liver equivalent diameter (kidney: r = -0.97; adrenal glands: r = -0.98). Normalized dose to the small intestine correlated strongly with mid-intestine equivalent diameter (r = -0.97). These strong correlations suggest that patient-specific dose may be estimated for any other child in the same size group who undergoes the abdomen-pelvis scan.

Kinetic evolution and correlation of fluctuations in an expanding quark gluon plasma

NASA Astrophysics Data System (ADS)

Sarwar, Golam; Alam, Jan-E.

2018-03-01

Evolution of spatially anisotropic perturbation created in the system formed after Relativistic Heavy Ion Collisions has been studied. The microscopic evolution of the fluctuations has been examined within the ambit of Boltzmann Transport Equation (BTE) in a hydrodynamically expanding background. The expansion of the background composed of quark gluon plasma (QGP) is treated within the framework of relativistic hydrodynamics. Spatial anisotropic fluctuations with different geometries have been evolved through Boltzmann equation. It is observed that the trace of such fluctuation survives the evolution. Within the relaxation time approximation, analytical results have been obtained for the evolution of these anisotropies. Explicit relations between fluctuations and transport coefficients have been derived. The mixing of various Fourier (or k) modes of the perturbations during the evolution of the system has been explicitly demonstrated. This study is very useful in understanding the presumption that the measured anisotropies in the data from heavy ion collisions at relativistic energies imitate the initial state effects. The evolution of correlation function for the perturbation in pressure has been studied and shows that the initial correlation between two neighbouring points in real space evolves to a constant value at later time which gives rise to Dirac delta function for the correlation function in Fourier space. The power spectrum of the fluctuation in thermodynamic quantities (like temperature estimated in this work) can be connected to the fluctuation in transverse momentum of the thermal hadrons measured experimentally. The bulk viscous coefficient of the QGP has been estimated by using correlations of pressure fluctuation with the help of Green-Kubo relation. Angular power spectrum of the anisotropies has been estimated in the appendix.

Plasma fluctuations as Markovian noise.

PubMed

Li, B; Hazeltine, R D; Gentle, K W

2007-12-01

Noise theory is used to study the correlations of stationary Markovian fluctuations that are homogeneous and isotropic in space. The relaxation of the fluctuations is modeled by the diffusion equation. The spatial correlations of random fluctuations are modeled by the exponential decay. Based on these models, the temporal correlations of random fluctuations, such as the correlation function and the power spectrum, are calculated. We find that the diffusion process can give rise to the decay of the correlation function and a broad frequency spectrum of random fluctuations. We also find that the transport coefficients may be estimated by the correlation length and the correlation time. The theoretical results are compared with the observed plasma density fluctuations from the tokamak and helimak experiments.

Translation, cross-cultural adaptation and reliability of the german version of the dizziness handicap inventory.

PubMed

Kurre, Annette; van Gool, Christel J A W; Bastiaenen, Caroline H G; Gloor-Juzi, Thomas; Straumann, Dominik; de Bruin, Eling D

2009-04-01

To translate the Dizziness Handicap Inventory into German (DHI-G) and investigate reliability, assess the association between selected items of the University of California Los Angeles Dizziness Questionnaire and the DHI-G, and compare the scores of patients and healthy participants. Cross-sectional design. Tertiary center for vertigo, dizziness, or balance disorders. One hundred forty-one patients with vertigo, dizziness, and unsteadiness associated with a vestibular disorder, with a mean age (standard deviation) of 51.5 (13.2) years, and 52 healthy individuals participated. Fourteen patients participated in the cognitive debriefing; 127 patients completed the questionnaires once or twice within 1 week. The DHI-G assesses disability caused by dizziness and unsteadiness; the items of the University of California Los Angeles Dizziness Questionnaire assess dizziness and impact on everyday activities. Internal consistency was estimated using Cronbach alpha, reproducibility by calculating Bland-Altman limits of agreement and intraclass correlation coefficients. Associations were estimated by Spearman correlation coefficients. Patients filled out the DHI-G without problem and found that their self-perceived disabilities were mostly included. Cronbach alpha values for the DHI-G and the functional, physical, and emotional subscales were 0.90, 0.80, 0.71, and 0.82, respectively. The limits of agreement were +/-12.4 points for the total scale (maximum, 100 points). Intraclass correlation coefficients ranged from 0.90 to 0.95. The DHI-G correlated moderately with the question assessing functional disability (0.56) and fairly with the questions quantifying dizziness (0.43, 0.35). The DHI-G discriminated significantly between healthy participants and patients. The DHI-G demonstrated good reliability and is recommended as a measure of disability in patients with dizziness and unsteadiness.

Predictive Validity of the Body Adiposity Index in Overweight and Obese Adults Using Dual-Energy X-ray Absorptiometry

PubMed Central

Ramírez-Vélez, Robinson; Correa-Bautista, Jorge Enrique; González-Ruíz, Katherine; Vivas, Andrés; García-Hermoso, Antonio; Triana-Reina, Hector Reynaldo

2016-01-01

The body adiposity index (BAI) is a recent anthropometric measure proven to be valid in predicting body fat percentage (BF%) in some populations. However, the results have been inconsistent across populations. This study was designed to verify the validity of BAI in predicting BF% in a sample of overweight/obese adults, using dual-energy X-ray absorptiometry (DEXA) as the reference method. A cross-sectional study was conducted in 48 participants (54% women, mean age 41.0 ± 7.3 years old). DEXA was used as the “gold standard” to determine BF%. Pearson’s correlation coefficient was used to evaluate the association between BAI and BF%, as assessed by DEXA. A paired sample t-test was used to test differences in mean BF% obtained with BAI and DEXA methods. To evaluate the concordance between BF% as measured by DEXA and as estimated by BAI, we used Lin’s concordance correlation coefficient and Bland–Altman agreement analysis. The correlation between BF% obtained by DEXA and that estimated by BAI was r = 0.844, p < 0.001. Paired t-test showed a significant mean difference in BF% between methods (BAI = 33.3 ± 6.2 vs. DEXA 39.0 ± 6.1; p < 0.001). The bias of the BAI was −6.0 ± 3.0 BF% (95% CI = −12.0 to 1.0), indicating that the BAI method significantly underestimated the BF% compared to the reference method. Lin’s concordance correlation coefficient was considered stronger (ρc = 0.923, 95% CI = 0.862 to 0.957). In obese adults, BAI presented low agreement with BF% measured by DEXA; therefore, BAI is not recommended for BF% prediction in this overweight/obese sample studied. PMID:27916871

Investigations on the links between rain intensity or reflectivity structures estimated from radar and drop size distributions

NASA Astrophysics Data System (ADS)

Hachani, Sahar; Boudevillain, Brice; Bargaoui, Zoubeida; Delrieu, Guy

2015-04-01

During the first Special Observation Period (SOP) of the Hydrological cycle in the Mediterranean Experiment (HyMeX, www.hymex.org) held in fall 2012 in the Northwestern Mediterranean region, an observation network dedicated to rain studies was implemented in the Cévennes region, France. It was mainly constituted by weather radars, micro rain radars, disdrometers and rain gauges. Observations are performed by a network of 25 OTT Parsivel optical disdrometers distributed with inter-distances ranging from a few meters up to about one hundred kilometers. This presentation focuses on the comparison of one optical disdrometer observations located at Villeneuve-de-berg to observations using weather Météo-France / ARAMIS radar located at Bollène which is in a neighborhood of 60 km from the disdrometer.The period from September to November 2012 is studied. To analyze the structure of the rain observed by radar, a window of investigation centered on the disdrometer was selected and the mean spatial values, standard deviation, gradients, and intermittency of radar reflectivity or rainfall intensity were computed for a time step of 5 minutes.Four different windowsizes were analyzed: 1 km², 25 km², 100 km² and 400 km². On the other hand, the total concentration of drops Nt, the characteristic diameter of drops Dc, and a Gamma distribution shape parameter µ were estimated. Gamma distribution for the DSD related to disdrometer observations was estimated according to the modeling framework proposed by Yu et al. (2014). Correlation coefficient between intensity R obtained by the disdrometer and windowaverage R estimated using radar data is nearly 0.70 whatever the window. The highest value is found for the window 25 km² (0.74). Correlation coefficients between Dc and window average R vary from 0.35 for the window 1 km² to 0.4 for the window 400 km². So, they areweak and not sensitive to the choice of the window. Contrarily, formean radar reflectivityZ, correlation coefficients with Dc, Nt and µ vary to some extent from the window size 1 km² to the window size 100 km². The most sensitive is the correlation coefficient between Z and Nt. However it presents the smallest correlations while the highest correlations are found for Dc (respectively 0.80 and 0.74). The overall of relations between the rainfall structure variables and DSD parameters will be presented in the communication with a special attention to the weather and/or rainfall types (orographic, stratiform, and convective). References: Yu, N., Delrieu, G., Boudevillain, B., Hazenberg, P., and Uijlenhoet, R., 2014: Unified formulation of single and multi-moment normalizations of the raindrop size distribution based on the gamma probability density function. Journal of Applied Meteorology and Climatology, 53, pp 166-179.

Drag Coefficient Estimation in Orbit Determination

NASA Astrophysics Data System (ADS)

McLaughlin, Craig A.; Manee, Steve; Lichtenberg, Travis

2011-07-01

Drag modeling is the greatest uncertainty in the dynamics of low Earth satellite orbits where ballistic coefficient and density errors dominate drag errors. This paper examines fitted drag coefficients found as part of a precision orbit determination process for Stella, Starlette, and the GEOSAT Follow-On satellites from 2000 to 2005. The drag coefficients for the spherical Stella and Starlette satellites are assumed to be highly correlated with density model error. The results using MSIS-86, NRLMSISE-00, and NRLMSISE-00 with dynamic calibration of the atmosphere (DCA) density corrections are compared. The DCA corrections were formulated for altitudes of 200-600 km and are found to be inappropriate when applied at 800 km. The yearly mean fitted drag coefficients are calculated for each satellite for each year studied. The yearly mean drag coefficients are higher for Starlette than Stella, where Starlette is at a higher altitude. The yearly mean fitted drag coefficients for all three satellites decrease as solar activity decreases after solar maximum.

Mapping the spatial pattern of temperate forest above ground biomass by integrating airborne lidar with Radarsat-2 imagery via geostatistical models

NASA Astrophysics Data System (ADS)

Li, Wang; Niu, Zheng; Gao, Shuai; Wang, Cheng

2014-11-01

Light Detection and Ranging (LiDAR) and Synthetic Aperture Radar (SAR) are two competitive active remote sensing techniques in forest above ground biomass estimation, which is important for forest management and global climate change study. This study aims to further explore their capabilities in temperate forest above ground biomass (AGB) estimation by emphasizing the spatial auto-correlation of variables obtained from these two remote sensing tools, which is a usually overlooked aspect in remote sensing applications to vegetation studies. Remote sensing variables including airborne LiDAR metrics, backscattering coefficient for different SAR polarizations and their ratio variables for Radarsat-2 imagery were calculated. First, simple linear regression models (SLR) was established between the field-estimated above ground biomass and the remote sensing variables. Pearson's correlation coefficient (R2) was used to find which LiDAR metric showed the most significant correlation with the regression residuals and could be selected as co-variable in regression co-kriging (RCoKrig). Second, regression co-kriging was conducted by choosing the regression residuals as dependent variable and the LiDAR metric (Hmean) with highest R2 as co-variable. Third, above ground biomass over the study area was estimated using SLR model and RCoKrig model, respectively. The results for these two models were validated using the same ground points. Results showed that both of these two methods achieved satisfactory prediction accuracy, while regression co-kriging showed the lower estimation error. It is proved that regression co-kriging model is feasible and effective in mapping the spatial pattern of AGB in the temperate forest using Radarsat-2 data calibrated by airborne LiDAR metrics.

Coherent Power Analysis in Multilevel Studies Using Parameters from Surveys

ERIC Educational Resources Information Center

Rhoads, Christopher

2017-01-01

Researchers designing multisite and cluster randomized trials of educational interventions will usually conduct a power analysis in the planning stage of the study. To conduct the power analysis, researchers often use estimates of intracluster correlation coefficients and effect sizes derived from an analysis of survey data. When there is…

Comparative analysis of microarray data in Arabidopsis transcriptome during compatible interactions with plant viruses

USDA-ARS?s Scientific Manuscript database

To analyze transcriptome response to virus infection, we have assembled currently available microarray data on changes in gene expression levels in compatible Arabidopsis-virus interactions. We used the mean r (Pearson’s correlation coefficient) for neighboring pairs to estimate pairwise local simil...

Comparative Analysis of 2-D Versus 3-D Ultrasound Estimation of the Fetal Adrenal Gland Volume and Prediction of Preterm Birth

PubMed Central

Turan, Ozhan M.; Turan, Sifa; Buhimschi, Irina A.; Funai, Edmund F.; Campbell, Katherine H.; Bahtiyar, Ozan M.; Harman, Chris R.; Copel, Joshua A.; Baschat, Ahmet A; Buhimschi, Catalin S.

2013-01-01

Objective We aim to test the hypothesis that 2D fetal AGV measurements offer similar volume estimates as volume calculations based on 3D technique Methods Fetal AGV was estimated by 3D ultrasound (VOCAL) in 93 women with signs/symptoms of preterm labor and 73 controls. Fetal AGV was calculated using an ellipsoid formula derived from 2D measurements of the same blocks (0.523× length × width × depth). Comparisons were performed by intra-class correlation coefficient (ICC), coefficient of repeatability, and Bland-Altman method. The cAGV (AGV/fetal weight) was calculated for both methods and compared for prediction of PTB within 7 days. Results Among 168 volumes, there was a significant correlation between 3D and 2D methods (ICC=0.979[95%CI: 0.971-0.984]). The coefficient of repeatability for the 3D was superior to the 2D method (Intra-observer 3D: 30.8, 2D:57.6; inter-observer 3D: 12.2, 2D: 15.6). Based on 2D calculations, a cAGV≥433mm3/kg, was best for prediction of PTB (sensitivity: 75%(95%CI=59-87); specificity: 89%(95%CI=82-94). Sensitivity and specificity for the 3D cAGV (cut-off ≥420mm3/kg) was 85%(95%CI=70-94) and 95%(95%CI=90-98), respectively. In receiver-operating-curve curve analysis, 3D cAGV was superior to 2D cAGV for prediction of PTB (z=1.99, p=0.047). Conclusion 2D volume estimation of fetal adrenal gland using ellipsoid formula cannot replace 3D AGV calculations for prediction of PTB. PMID:22644825

The correlation between preoperative volumetry and real graft weight: comparison of two volumetry programs

PubMed Central

Mussin, Nadiar; Sumo, Marco; Choi, YoungRok; Choi, Jin Yong; Ahn, Sung-Woo; Yoon, Kyung Chul; Kim, Hyo-Sin; Hong, Suk Kyun; Yi, Nam-Joon; Suh, Kyung-Suk

2017-01-01

Purpose Liver volumetry is a vital component in living donor liver transplantation to determine an adequate graft volume that meets the metabolic demands of the recipient and at the same time ensures donor safety. Most institutions use preoperative contrast-enhanced CT image-based software programs to estimate graft volume. The objective of this study was to evaluate the accuracy of 2 liver volumetry programs (Rapidia vs. Dr. Liver) in preoperative right liver graft estimation compared with real graft weight. Methods Data from 215 consecutive right lobe living donors between October 2013 and August 2015 were retrospectively reviewed. One hundred seven patients were enrolled in Rapidia group and 108 patients were included in the Dr. Liver group. Estimated graft volumes generated by both software programs were compared with real graft weight measured during surgery, and further classified into minimal difference (≤15%) and big difference (>15%). Correlation coefficients and degree of difference were determined. Linear regressions were calculated and results depicted as scatterplots. Results Minimal difference was observed in 69.4% of cases from Dr. Liver group and big difference was seen in 44.9% of cases from Rapidia group (P = 0.035). Linear regression analysis showed positive correlation in both groups (P < 0.01). However, the correlation coefficient was better for the Dr. Liver group (R2 = 0.719), than for the Rapidia group (R2 = 0.688). Conclusion Dr. Liver can accurately predict right liver graft size better and faster than Rapidia, and can facilitate preoperative planning in living donor liver transplantation. PMID:28382294

Consistent Partial Least Squares Path Modeling via Regularization.

PubMed

Jung, Sunho; Park, JaeHong

2018-01-01

Partial least squares (PLS) path modeling is a component-based structural equation modeling that has been adopted in social and psychological research due to its data-analytic capability and flexibility. A recent methodological advance is consistent PLS (PLSc), designed to produce consistent estimates of path coefficients in structural models involving common factors. In practice, however, PLSc may frequently encounter multicollinearity in part because it takes a strategy of estimating path coefficients based on consistent correlations among independent latent variables. PLSc has yet no remedy for this multicollinearity problem, which can cause loss of statistical power and accuracy in parameter estimation. Thus, a ridge type of regularization is incorporated into PLSc, creating a new technique called regularized PLSc. A comprehensive simulation study is conducted to evaluate the performance of regularized PLSc as compared to its non-regularized counterpart in terms of power and accuracy. The results show that our regularized PLSc is recommended for use when serious multicollinearity is present.

Rapid estimation of the electron correlation energy for van der Waals complexes RgX (Rg = Kr, Xe, X = Br, I)

NASA Astrophysics Data System (ADS)

Xinying, Li; Yongfang, Zhao; Xiaogong, Jing; Fengli, Liu; Fengyou, Hao

2006-01-01

We present the rules of electron correlation energies for RgX (Rg = Kr, Xe, X = Br, I) van der Waals (vdW) complex systems at CCSD(T) theoretical level with SDB-cc-pVQZ basis set by the Gaussian 98 program. A new method to derive the dispersion coefficient C6 by fitting the intermonomer electron correlation energies to C6R-6 function is introduced. The present C6 values are compared with the corresponding theoretical ones.

Applicability of Cameriere's and Drusini's age estimation methods to a sample of Turkish adults.

PubMed

Hatice, Boyacioglu Dogru; Nihal, Avcu; Nursel, Akkaya; Humeyra Ozge, Yilanci; Goksuluk, Dincer

2017-10-01

The aim of this study was to investigate the applicability of Drusini's and Cameriere's methods to a sample of Turkish people. Panoramic images of 200 individuals were allocated into two groups as study and test groups and examined by two observers. Tooth coronal indexes (TCI), which is the ratio between coronal pulp cavity height and crown height, were calculated in the mandibular first and second premolars and molars. Pulp/tooth area ratios (ARs) were calculated in the maxillary and mandibular canine teeth. Study group measurements were used to derive a regression model. Test group measurements were used to evaluate the accuracy of the regression model. Pearson's correlation coefficients and regression analysis were used. The correlations between TCIs and age were -0.230, -0.301, -0.344 and -0.257 for mandibular first premolar, second premolar, first molar and second molar, respectively. Those for the maxillary canine (MX) and mandibular canine (MN) ARs were -0.716 and -0.514, respectively. The MX ARs were used to build the linear regression model that explained 51.2% of the total variation, with a standard error of 9.23 years. The mean error of the estimates in test group was 8 years and age of 64% of the individuals were estimated with an error of <±10 years which is acceptable in forensic age prediction. The low correlation coefficients between age and TCI indicate that Drusini's method was not applicable to the estimation of age in a Turkish population. Using Cameriere's method, we derived a regression model.

The development of an estimation model for energy expenditure during water walking by acceleration and walking speed.

PubMed

Kaneda, Koichi; Ohgi, Yuji; Tanaka, Chiaki; Burkett, Brendan

2014-01-01

The aim of this study was to develop an estimation equation for energy expenditure during water walking based on the acceleration and walking speed. Cross-validation study. Fifty participants, males (n=29, age: 27-73) and females (n=21, age: 33-70) volunteered for this study. Based on their physical condition water walking was conducted at three self-selected walking speeds from a range of: 20, 25, 30, 35 and 40 m/min. Energy expenditure during each trial was calculated. During water walking, an accelerometer was attached to the occipital region and recorded three-dimensional accelerations at 100 Hz. A stopwatch was used for timing the participant's walking speed. The estimation model for energy expenditure included three components; (i) resting metabolic rate, (ii) internal energy expenditure for moving participants' body, and (iii) external energy expenditure due to water drag force. When comparing the measured and estimated energy expenditure with the acceleration data being the third component of the estimation model, high correlation coefficients were found in both male (r=0.73) and female (r=0.77) groups. When walking speeds were applied to the third component of the model, higher correlation coefficients were found (r=0.82 in male and r=0.88 in female). Good agreements of the developed estimation model were found in both methods, regardless of gender. This study developed a valid estimation model for energy expenditure during water walking by using head acceleration and walking speed. Copyright © 2013 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

An investigation of spectral change as influenced by irrigation and evapotranspiration volume estimation in western Nebraska

USGS Publications Warehouse

Seevers, P.M.; Sadowski, F.C.; Lauer, D.T.

1990-01-01

Retrospective satellite image data were evaluated for their ability to demonstrate the influence of center-pivot irrigation development in western Nebraska on spectral change and climate-related factors for the region. Periodic images of an albedo index and a normalized difference vegetation index (NDVI) were generated from calibrated Landsat multispectral scanner (MSS) data and used to monitor spectral changes associated with irrigation development from 1972 through 1986. The albedo index was not useful for monitoring irrigation development. For the NDVI, it was found that proportions of counties in irrigated agriculture, as discriminated by a threshold, were more highly correlated with reported ground estimates of irrigated agriculture than were county mean greenness values. A similar result was achieved when using coarse resolution Advanced Very High Resolution Radiometer (AVHRR) image data for estimating irrigated agriculture. The NDVI images were used to evaluate a procedure for making areal estimates of actual evapotranspiration (ET) volumes. Estimates of ET volumes for test counties, using reported ground acreages and corresponding standard crop coefficients, were correlated with the estimates of ET volume using crop coefficients scaled to NDVI values and pixel counts of crop areas. These county estimates were made under the assumption that soil water availability was unlimited. For nonirrigated vegetation, this may result in over-estimation of ET volumes. Ground information regarding crop types and acreages are required to derive the NDVI scaling factor. Potential ET, estimated with the Jensen-Haise model, is common to both methods. These results, achieved with both MSS and AVHRR data, show promise for providing climatologically important land surface information for regional and global climate models. ?? 1990 Kluwer Academic Publishers.

Wechsler Adult Intelligence Scale-IV Dyads for Estimating Global Intelligence.

PubMed

Girard, Todd A; Axelrod, Bradley N; Patel, Ronak; Crawford, John R

2015-08-01

All possible two-subtest combinations of the core Wechsler Adult Intelligence Scale-IV (WAIS-IV) subtests were evaluated as possible viable short forms for estimating full-scale IQ (FSIQ). Validity of the dyads was evaluated relative to FSIQ in a large clinical sample (N = 482) referred for neuropsychological assessment. Sample validity measures included correlations, mean discrepancies, and levels of agreement between dyad estimates and FSIQ scores. In addition, reliability and validity coefficients were derived from WAIS-IV standardization data. The Coding + Information dyad had the strongest combination of reliability and validity data. However, several other dyads yielded comparable psychometric performance, albeit with some variability in their particular strengths. We also observed heterogeneity between validity coefficients from the clinical and standardization-based estimates for several dyads. Thus, readers are encouraged to also consider the individual psychometric attributes, their clinical or research goals, and client or sample characteristics when selecting among the dyadic short forms. © The Author(s) 2014.

Non-Markovian renormalization of kinetic coefficients for drift-type turbulence in magnetized plasmas

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

Zagorodny, A.; Weiland, J.

2009-05-15

The problem of derivation of the kinetic equations for inhomogeneous plasma in an external magnetic field is considered. The Fokker-Planck-type equations with the non-Markovian kinetic coefficients are proposed. In the time-local limit (small correlation times with respect to the distribution function relaxation time) the relations obtained recover the results known from the appropriate quasilinear theory and the Dupree-Weinstock theory of plasma turbulence. Kinetic calculations of the dielectric response function are also performed with regard to the influence of turbulent fields on particle motion. The equations proposed are used to describe zonal flow generation and to estimate the diffusion coefficient formore » saturated turbulence.« less

Comparing land use regression and dispersion modelling to assess residential exposure to ambient air pollution for epidemiological studies.

PubMed

de Hoogh, Kees; Korek, Michal; Vienneau, Danielle; Keuken, Menno; Kukkonen, Jaakko; Nieuwenhuijsen, Mark J; Badaloni, Chiara; Beelen, Rob; Bolignano, Andrea; Cesaroni, Giulia; Pradas, Marta Cirach; Cyrys, Josef; Douros, John; Eeftens, Marloes; Forastiere, Francesco; Forsberg, Bertil; Fuks, Kateryna; Gehring, Ulrike; Gryparis, Alexandros; Gulliver, John; Hansell, Anna L; Hoffmann, Barbara; Johansson, Christer; Jonkers, Sander; Kangas, Leena; Katsouyanni, Klea; Künzli, Nino; Lanki, Timo; Memmesheimer, Michael; Moussiopoulos, Nicolas; Modig, Lars; Pershagen, Göran; Probst-Hensch, Nicole; Schindler, Christian; Schikowski, Tamara; Sugiri, Dorothee; Teixidó, Oriol; Tsai, Ming-Yi; Yli-Tuomi, Tarja; Brunekreef, Bert; Hoek, Gerard; Bellander, Tom

2014-12-01

Land-use regression (LUR) and dispersion models (DM) are commonly used for estimating individual air pollution exposure in population studies. Few comparisons have however been made of the performance of these methods. Within the European Study of Cohorts for Air Pollution Effects (ESCAPE) we explored the differences between LUR and DM estimates for NO2, PM10 and PM2.5. The ESCAPE study developed LUR models for outdoor air pollution levels based on a harmonised monitoring campaign. In thirteen ESCAPE study areas we further applied dispersion models. We compared LUR and DM estimates at the residential addresses of participants in 13 cohorts for NO2; 7 for PM10 and 4 for PM2.5. Additionally, we compared the DM estimates with measured concentrations at the 20-40 ESCAPE monitoring sites in each area. The median Pearson R (range) correlation coefficients between LUR and DM estimates for the annual average concentrations of NO2, PM10 and PM2.5 were 0.75 (0.19-0.89), 0.39 (0.23-0.66) and 0.29 (0.22-0.81) for 112,971 (13 study areas), 69,591 (7) and 28,519 (4) addresses respectively. The median Pearson R correlation coefficients (range) between DM estimates and ESCAPE measurements were of 0.74 (0.09-0.86) for NO2; 0.58 (0.36-0.88) for PM10 and 0.58 (0.39-0.66) for PM2.5. LUR and dispersion model estimates correlated on average well for NO2 but only moderately for PM10 and PM2.5, with large variability across areas. DM predicted a moderate to large proportion of the measured variation for NO2 but less for PM10 and PM2.5. Copyright © 2014 Elsevier Ltd. All rights reserved.

The estimation method on diffusion spot energy concentration of the detection system

NASA Astrophysics Data System (ADS)

Gao, Wei; Song, Zongxi; Liu, Feng; Dan, Lijun; Sun, Zhonghan; Du, Yunfei

2016-09-01

We propose a method to estimate the diffusion spot energy of the detection system. We do outdoor observation experiments in Xinglong Observatory, by using a detection system which diffusion spot energy concentration is estimated (the correlation coefficient is approximate 0.9926).The aperture of system is 300mm and limiting magnitude of system is 14.15Mv. Observation experiments show that the highest detecting magnitude of estimated system is 13.96Mv, and the average detecting magnitude of estimated system is about 13.5Mv. The results indicate that this method can be used to evaluate the energy diffusion spot concentration level of detection system efficiently.

Surgical management of congenital heart disease: correlation between hospital costs and the Aristotle complexity score.

PubMed

Sinzobahamvya, N; Kopp, T; Photiadis, J; Arenz, C; Schindler, E; Haun, C; Hraska, V; Asfour, B

2010-09-01

Hospital costs are expected to correlate with clinical complexity. Do costs for congenital heart surgery correlate with Aristotle complexity scores? 442 inpatient stays in 2008 were evaluated. Aristotle scores and levels were determined. Costs were estimated according to the German Institute for Hospital Reimbursement system. Pearson and Spearman R correlation coefficients and corresponding goodness-of-fit regression coefficients R2 were calculated. Mean basic and comprehensive Aristotle scores were 7.60 +/- 2.74 and 9.23 +/- 2.94 points, respectively. Mean expenses per hospital stay amounted to 29,369 +/- 30,823 Euros. Aristotle basic and comprehensive scores and levels were positively correlated with hospital costs. With a Spearman R of 1 and related R2 of 0.9436, scores of the 6 Aristotle comprehensive levels correlated best. Mean hospital reimbursement was 26,412 +/- 17,962 Euros. Compensation was higher than expenses for patients in comprehensive levels 1 to 3, but much lower for those in levels 4 to 6. Aristotle comprehensive complexity scores were highly correlated with hospital costs. The Aristotle score could be used as a scale to establish the correct reimbursement after congenital heart surgery. Georg Thieme Verlag KG Stuttgart, New York.

Chronologic age and skeletal maturation of the cervical vertebrae and hand-wrist: is there a relationship?

PubMed

Uysal, Tancan; Ramoglu, Sabri Ilhan; Basciftci, Faruk Ayhan; Sari, Zafer

2006-11-01

The aims of this study were (1) to investigate the relationship between chronologic age and maturation of cervical vertebrae, (2) to identify the relationship between chronologic age and maturation stage evaluated by hand-wrist radiographs, and (3) to determine whether the maturation of cervical vertebrae correlates with maturation indicated by hand-wrist radiographs in a Turkish population. The samples were derived from lateral cephalometric and hand-wrist radiographs of 503 subjects (213 male, 290 female; ages, 5.3-24.1 years). Cervical vertebral development was evaluated by the method of Hassel and Farman. Skeletal maturation of each hand-wrist radiograph was determined according to the method described by Björk and Grave, and Brown's system. The Spearman rank-order correlation coefficients were estimated separately for males and females to measure the relationships among chronologic age, cervical vertebral maturation, and the skeletal maturation measured at the hand-wrist. The Spearman correlation coefficients were 0.72 (P <.001) between chronologic age and cervical vertebrae skeletal maturation, and 0.79 (P < .001) between chronologic age and maturation via hand-wrist radiographs. The correlation coefficient between hand-wrist and cervical-vertebrae maturation was 0.86 (P <.001). The cervical-vertebrae maturation stages are clinically useful maturity indicators of the pubertal growth period Turkish subjects.

Electronic transport coefficients from ab initio simulations and application to dense liquid hydrogen

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

Holst, Bastian; French, Martin; Redmer, Ronald

2011-06-15

Using Kubo's linear response theory, we derive expressions for the frequency-dependent electrical conductivity (Kubo-Greenwood formula), thermopower, and thermal conductivity in a strongly correlated electron system. These are evaluated within ab initio molecular dynamics simulations in order to study the thermoelectric transport coefficients in dense liquid hydrogen, especially near the nonmetal-to-metal transition region. We also observe significant deviations from the widely used Wiedemann-Franz law, which is strictly valid only for degenerate systems, and give an estimate for its valid scope of application toward lower densities.

Random diffusion and leverage effect in financial markets.

PubMed

Perelló, Josep; Masoliver, Jaume

2003-03-01

We prove that Brownian market models with random diffusion coefficients provide an exact measure of the leverage effect [J-P. Bouchaud et al., Phys. Rev. Lett. 87, 228701 (2001)]. This empirical fact asserts that past returns are anticorrelated with future diffusion coefficient. Several models with random diffusion have been suggested but without a quantitative study of the leverage effect. Our analysis lets us to fully estimate all parameters involved and allows a deeper study of correlated random diffusion models that may have practical implications for many aspects of financial markets.

Messages Do Diffuse Faster than Messengers: Reconciling Disparate Estimates of the Morphogen Bicoid Diffusion Coefficient

PubMed Central

Sigaut, Lorena; Pearson, John E.; Colman-Lerner, Alejandro; Ponce Dawson, Silvina

2014-01-01

The gradient of Bicoid (Bcd) is key for the establishment of the anterior-posterior axis in Drosophila embryos. The gradient properties are compatible with the SDD model in which Bcd is synthesized at the anterior pole and then diffuses into the embryo and is degraded with a characteristic time. Within this model, the Bcd diffusion coefficient is critical to set the timescale of gradient formation. This coefficient has been measured using two optical techniques, Fluorescence Recovery After Photobleaching (FRAP) and Fluorescence Correlation Spectroscopy (FCS), obtaining estimates in which the FCS value is an order of magnitude larger than the FRAP one. This discrepancy raises the following questions: which estimate is "correct''; what is the reason for the disparity; and can the SDD model explain Bcd gradient formation within the experimentally observed times? In this paper, we use a simple biophysical model in which Bcd diffuses and interacts with binding sites to show that both the FRAP and the FCS estimates may be correct and compatible with the observed timescale of gradient formation. The discrepancy arises from the fact that FCS and FRAP report on different effective (concentration dependent) diffusion coefficients, one of which describes the spreading rate of the individual Bcd molecules (the messengers) and the other one that of their concentration (the message). The latter is the one that is more relevant for the gradient establishment and is compatible with its formation within the experimentally observed times. PMID:24901638

Messages do diffuse faster than messengers: reconciling disparate estimates of the morphogen bicoid diffusion coefficient.

PubMed

Sigaut, Lorena; Pearson, John E; Colman-Lerner, Alejandro; Ponce Dawson, Silvina

2014-06-01

The gradient of Bicoid (Bcd) is key for the establishment of the anterior-posterior axis in Drosophila embryos. The gradient properties are compatible with the SDD model in which Bcd is synthesized at the anterior pole and then diffuses into the embryo and is degraded with a characteristic time. Within this model, the Bcd diffusion coefficient is critical to set the timescale of gradient formation. This coefficient has been measured using two optical techniques, Fluorescence Recovery After Photobleaching (FRAP) and Fluorescence Correlation Spectroscopy (FCS), obtaining estimates in which the FCS value is an order of magnitude larger than the FRAP one. This discrepancy raises the following questions: which estimate is "correct''; what is the reason for the disparity; and can the SDD model explain Bcd gradient formation within the experimentally observed times? In this paper, we use a simple biophysical model in which Bcd diffuses and interacts with binding sites to show that both the FRAP and the FCS estimates may be correct and compatible with the observed timescale of gradient formation. The discrepancy arises from the fact that FCS and FRAP report on different effective (concentration dependent) diffusion coefficients, one of which describes the spreading rate of the individual Bcd molecules (the messengers) and the other one that of their concentration (the message). The latter is the one that is more relevant for the gradient establishment and is compatible with its formation within the experimentally observed times.

Model for estimating enteric methane emissions from United States dairy and feedlot cattle.

PubMed

Kebreab, E; Johnson, K A; Archibeque, S L; Pape, D; Wirth, T

2008-10-01

Methane production from enteric fermentation in cattle is one of the major sources of anthropogenic greenhouse gas emission in the United States and worldwide. National estimates of methane emissions rely on mathematical models such as the one recommended by the Intergovernmental Panel for Climate Change (IPCC). Models used for prediction of methane emissions from cattle range from empirical to mechanistic with varying input requirements. Two empirical and 2 mechanistic models (COWPOLL and MOLLY) were evaluated for their prediction ability using individual cattle measurements. Model selection was based on mean square prediction error (MSPE), concordance correlation coefficient, and residuals vs. predicted values analyses. In dairy cattle, COWPOLL had the lowest root MSPE and greatest accuracy and precision of predicting methane emissions (correlation coefficient estimate = 0.75). The model simulated differences in diet more accurately than the other models, and the residuals vs. predicted value analysis showed no mean bias (P = 0.71). In feedlot cattle, MOLLY had the lowest root MSPE with almost all errors from random sources (correlation coefficient estimate = 0.69). The IPCC model also had good agreement with observed values, and no significant mean (P = 0.74) or linear bias (P = 0.11) was detected when residuals were plotted against predicted values. A fixed methane conversion factor (Ym) might be an easier alternative to diet-dependent variable Ym. Based on the results, the 2 mechanistic models were used to simulate methane emissions from representative US diets and were compared with the IPCC model. The average Ym in dairy cows was 5.63% of GE (range 3.78 to 7.43%) compared with 6.5% +/- 1% recommended by IPCC. In feedlot cattle, the average Ym was 3.88% (range 3.36 to 4.56%) compared with 3% +/- 1% recommended by IPCC. Based on our simulations, using IPCC values can result in an overestimate of about 12.5% and underestimate of emissions by about 9.8% for dairy and feedlot cattle, respectively. In addition to providing improved estimates of emissions based on diets, mechanistic models can be used to assess mitigation options such as changing source of carbohydrate or addition of fat to decrease methane, which is not possible with empirical models. We recommend national inventories use diet-specific Ym values predicted by mechanistic models to estimate methane emissions from cattle.

Computer-assisted stereology and automated image analysis for quantification of tumor infiltrating lymphocytes in colon cancer.

PubMed

Eriksen, Ann C; Andersen, Johnnie B; Kristensson, Martin; dePont Christensen, René; Hansen, Torben F; Kjær-Frifeldt, Sanne; Sørensen, Flemming B

2017-08-29

Precise prognostic and predictive variables allowing improved post-operative treatment stratification are missing in patients treated for stage II colon cancer (CC). Investigation of tumor infiltrating lymphocytes (TILs) may be rewarding, but the lack of a standardized analytic technique is a major concern. Manual stereological counting is considered the gold standard, but digital pathology with image analysis is preferred due to time efficiency. The purpose of this study was to compare manual stereological estimates of TILs with automatic counts obtained by image analysis, and at the same time investigate the heterogeneity of TILs. From 43 patients treated for stage II CC in 2002 three paraffin embedded, tumor containing tissue blocks were selected one of them representing the deepest invasive tumor front. Serial sections from each of the 129 blocks were immunohistochemically stained for CD3 and CD8, and the slides were scanned. Stereological estimates of the numerical density and area fraction of TILs were obtained using the computer-assisted newCAST stereology system. For the image analysis approach an app-based algorithm was developed using Visiopharm Integrator System software. For both methods the tumor areas of interest (invasive front and central area) were manually delineated by the observer. Based on all sections, the Spearman's correlation coefficients for density estimates varied from 0.9457 to 0.9638 (p < 0.0001), whereas the coefficients for area fraction estimates ranged from 0.9400 to 0.9603 (P < 0.0001). Regarding heterogeneity, intra-class correlation coefficients (ICC) for CD3+ TILs varied from 0.615 to 0.746 in the central area, and from 0.686 to 0.746 in the invasive area. ICC for CD8+ TILs varied from 0.724 to 0.775 in the central area, and from 0.746 to 0.765 in the invasive area. Exact objective and time efficient estimates of numerical densities and area fractions of CD3+ and CD8+ TILs in stage II colon cancer can be obtained by image analysis and are highly correlated to the corresponding estimates obtained by the gold standard based on stereology. Since the intra-tumoral heterogeneity was low, this method may be recommended for quantifying TILs in only one histological section representing the deepest invasive tumor front.

Five radiographic methods for assessing skeletal maturity in a Spanish population: is there a correlation?

PubMed

Camacho-Basallo, Paula; Yáñez-Vico, Rosa-María; Solano-Reina, Enrique; Iglesias-Linares, Alejandro

2017-03-01

The need for accurate techniques of estimating age has sharply increased in line with the rise in illegal migration and the political, economic and socio-demographic problems that this poses in developed countries today. The methods routinely employed for determining chronological age are mainly based on determining skeletal maturation using radiological techniques. The objective of this study was to correlate five different methods for assessing skeletal maturation. 606 radiographs of growing patients were analyzed, and each patient was classified according to two cervical vertebral-based methods, two hand-wrist-based methods and one tooth-based method. Spearman's rank-order correlation coefficient was applied to assess the relationship between chronological age and the five methods of assessing maturation, as well as correlations between the five methods (p < 0.05). Spearman's rank correlation coefficients for chronological age and cervical vertebral maturation stage using both methods were 0.656/0.693 (p < 0.001), respectively, for males. For females, the correlation was stronger for both methods. The correlation coefficients for chronological age against the two hand-wrist assessment methods were statistically significant only for Fishman's method, 0.722 (p < 0.001) and 0.839 (p < 0.001), respectively for males and females. The cervical vertebral, hand-wrist and dental maturation methods of assessment were all found to correlate strongly with each other, irrespective of gender, except for Grave and Brown's method. The results found the strongest correlation between the second molars and females, and the second premolar and males. This study sheds light on and correlates with the five radiographic methods most commonly used for assessing skeletal maturation in a Spanish population in southern Europe.

Study on Hyperspectral Estimation Model of Total Nitrogen Content in Soil of Shaanxi Province

NASA Astrophysics Data System (ADS)

Liu, Jinbao; Dong, Zhenyu; Chen, Xi

2018-01-01

The development of hyperspectral remote sensing technology has been widely used in soil nutrient prediction. The soil is the representative soil type in Shaanxi Province. In this study, the soil total nitrogen content in Shaanxi soil was used as the research target, and the soil samples were measured by reflectance spectroscopy using ASD method. Pre-treatment, the first order differential, second order differential and reflectance logarithmic transformation of the reflected spectrum after pre-treatment, and the hyperspectral estimation model is established by using the least squares regression method and the principal component regression method. The results show that the correlation between the reflectance spectrum and the total nitrogen content of the soil is significantly improved. The correlation coefficient between the original reflectance and soil total nitrogen content is in the range of 350 ~ 2500nm. The correlation coefficient of soil total nitrogen content and first deviation of reflectance is more than 0.5 at 142nm, 1963nm, 2204nm and 2307nm, the second deviation has a significant positive correlation at 1114nm, 1470nm, 1967nm, 2372nm and 2402nm, respectively. After the reciprocal logarithmic transformation of the reflectance with the total nitrogen content of the correlation analysis found that the effect is not obvious. Rc2 = 0.7102, RMSEC = 0.0788; Rv2 = 0.8480, RMSEP = 0.0663, which can achieve the rapid prediction of the total nitrogen content in the region. The results show that the principal component regression model is the best.

Ultrasonographic assessment of splenic volume and its correlation with body parameters in a Jordanian population.

PubMed

Badran, Darwish H; Kalbouneh, Heba M; Al-Hadidi, Maher T; Shatarat, Amjad T; Tarawneh, Emad S; Hadidy, Azmy M; Mahafza, Waleed S

2015-08-01

To estimate normal linear dimensions and volume of spleen in Jordanians using ultrasonography, and to correlate splenic volume with age and body parameters: height, weight, body surface area (BSA), and body mass index (BMI). A prospective pilot study was conducted on 205 volunteers (115 males and 90 females) not known to have any conditions likely to be associated with splenomegaly. The study was performed at the Radiology Department, Jordanian University Hospital, Amman, Jordan, between December 2013 and August 2014. All linear dimensions of spleen were measured, and splenic volume (index) was calculated using the standard prolate ellipsoid formula (length × width × depth × 0.523). The splenic volume was then analyzed with age and body parameters using the Pearson's correlation coefficient. The mean (± SD) splenic dimensions were 10.72±1.37 cm in length, 7.40±1.52 cm in width, 4.40±1.47 cm in depth, and 184.15±79.56 cm3 in volume. Men had larger spleens than women (p less than 0.0001). Age had no significant effect on spleen volume (r=0.11, p=0.12). There was a significant moderate positive correlation (p less than 0.0001), using Pearson's correlation coefficient, between the spleen volume, and other parameters (height, weight, BSA, and BMI), with correlation coefficients exceeding 0.3. A local reference of spleen dimensions was established with a different range of values reported previously.

Estimating correlation of prevalence at two locations in the farm-to-table continuum using qualitative test data.

PubMed

Williams, Michael S; Ebel, Eric D

2017-03-20

The presence or absence of contaminants in food samples changes as a commodity moves along the farm-to-table continuum. Interest lies in the degree to which the prevalence (i.e., infected animals or contaminated sample units) at one location in the continuum, as measured by the proportion of test-positive samples, is correlated with the prevalence at a location later in the continuum. If prevalence of a contaminant at one location in the continuum is strongly correlated with the prevalence of the contaminant later in the continuum, then the effect of changes in contamination on overall food safety can be better understood. Pearson's correlation coefficient is one of the simplest metrics of association between two measurements of prevalence but it is biased when data consisting of presence/absence testing results are used to directly estimate the correlation. This study demonstrates the potential magnitude of this bias and explores the utility of three methods for unbiased estimation of the degree of correlation in prevalence. An example, based on testing broiler chicken carcasses for Salmonella at re-hang and post-chill, is used to demonstrate the methods. Published by Elsevier B.V.

Estimating groundwater levels using system identification models in Nzhelele and Luvuvhu areas, Limpopo Province, South Africa

NASA Astrophysics Data System (ADS)

Makungo, Rachel; Odiyo, John O.

2017-08-01

This study was focused on testing the ability of a coupled linear and non-linear system identification model in estimating groundwater levels. System identification provides an alternative approach for estimating groundwater levels in areas that lack data required by physically-based models. It also overcomes the limitations of physically-based models due to approximations, assumptions and simplifications. Daily groundwater levels for 4 boreholes, rainfall and evaporation data covering the period 2005-2014 were used in the study. Seventy and thirty percent of the data were used to calibrate and validate the model, respectively. Correlation coefficient (R), coefficient of determination (R2), root mean square error (RMSE), percent bias (PBIAS), Nash Sutcliffe coefficient of efficiency (NSE) and graphical fits were used to evaluate the model performance. Values for R, R2, RMSE, PBIAS and NSE ranged from 0.8 to 0.99, 0.63 to 0.99, 0.01-2.06 m, -7.18 to 1.16 and 0.68 to 0.99, respectively. Comparisons of observed and simulated groundwater levels for calibration and validation runs showed close agreements. The model performance mostly varied from satisfactory, good, very good and excellent. Thus, the model is able to estimate groundwater levels. The calibrated models can reasonably capture description between input and output variables and can, thus be used to estimate long term groundwater levels.

Measurements of experimental precision for trials with cowpea (Vigna unguiculata L. Walp.) genotypes.

PubMed

Teodoro, P E; Torres, F E; Santos, A D; Corrêa, A M; Nascimento, M; Barroso, L M A; Ceccon, G

2016-05-09

The aim of this study was to evaluate the suitability of statistics as experimental precision degree measures for trials with cowpea (Vigna unguiculata L. Walp.) genotypes. Cowpea genotype yields were evaluated in 29 trials conducted in Brazil between 2005 and 2012. The genotypes were evaluated with a randomized block design with four replications. Ten statistics that were estimated for each trial were compared using descriptive statistics, Pearson correlations, and path analysis. According to the class limits established, selective accuracy and F-test values for genotype, heritability, and the coefficient of determination adequately estimated the degree of experimental precision. Using these statistics, 86.21% of the trials had adequate experimental precision. Selective accuracy and the F-test values for genotype, heritability, and the coefficient of determination were directly related to each other, and were more suitable than the coefficient of variation and the least significant difference (by the Tukey test) to evaluate experimental precision in trials with cowpea genotypes.

A comparison of individual and population-derived vascular input functions for quantitative DCE-MRI in rats.

PubMed

Hormuth, David A; Skinner, Jack T; Does, Mark D; Yankeelov, Thomas E

2014-05-01

Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) can quantitatively and qualitatively assess physiological characteristics of tissue. Quantitative DCE-MRI requires an estimate of the time rate of change of the concentration of the contrast agent in the blood plasma, the vascular input function (VIF). Measuring the VIF in small animals is notoriously difficult as it requires high temporal resolution images limiting the achievable number of slices, field-of-view, spatial resolution, and signal-to-noise. Alternatively, a population-averaged VIF could be used to mitigate the acquisition demands in studies aimed to investigate, for example, tumor vascular characteristics. Thus, the overall goal of this manuscript is to determine how the kinetic parameters estimated by a population based VIF differ from those estimated by an individual VIF. Eight rats bearing gliomas were imaged before, during, and after an injection of Gd-DTPA. K(trans), ve, and vp were extracted from signal-time curves of tumor tissue using both individual and population-averaged VIFs. Extended model voxel estimates of K(trans) and ve in all animals had concordance correlation coefficients (CCC) ranging from 0.69 to 0.98 and Pearson correlation coefficients (PCC) ranging from 0.70 to 0.99. Additionally, standard model estimates resulted in CCCs ranging from 0.81 to 0.99 and PCCs ranging from 0.98 to 1.00, supporting the use of a population based VIF if an individual VIF is not available. Copyright © 2014 Elsevier Inc. All rights reserved.

Assessment of the reliability and consistency of the "malnutrition inflammation score" (MIS) in Mexican adults with chronic kidney disease for diagnosis of protein-energy wasting syndrome (PEW).

PubMed

González-Ortiz, Ailema Janeth; Arce-Santander, Celene Viridiana; Vega-Vega, Olynka; Correa-Rotter, Ricardo; Espinosa-Cuevas, María de Los Angeles

2014-10-04

The protein-energy wasting syndrome (PEW) is a condition of malnutrition, inflammation, anorexia and wasting of body reserves resulting from inflammatory and non-inflammatory conditions in patients with chronic kidney disease (CKD).One way of assessing PEW, extensively described in the literature, is using the Malnutrition Inflammation Score (MIS). To assess the reliability and consistency of MIS for diagnosis of PEW in Mexican adults with CKD on hemodialysis (HD). Study of diagnostic tests. A sample of 45 adults with CKD on HD were analyzed during the period June-July 2014.The instrument was applied on 2 occasions; the test-retest reliability was calculated using the Intraclass Correlation Coefficient (ICC); the internal consistency of the questionnaire was analyzed using Cronbach's αcoefficient. A weighted Kappa test was used to estimate the validity of the instrument; the result was subsequently compared with the Bilbrey nutritional index (BNI). The reliability of the questionnaires, evaluated in the patient sample, was ICC=0.829.The agreement between MIS observations was considered adequate, k= 0.585 (p <0.001); when comparing it with BNI, a value of k = 0.114 was obtained (p <0.001).In order to estimate the tendency, a correlation test was performed. The r² correlation coefficient was 0.488 (P <0.001). MIS has adequate reliability and validity for diagnosing PEW in the population with chronic kidney disease on HD. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

FIBER AND INTEGRAL OPTICS: Mode composition of radiation in graded-index waveguides with random microbending of the axis

NASA Astrophysics Data System (ADS)

Valyaev, A. B.; Krivoshlykov, S. G.

1989-06-01

It is shown that the problem of investigating the mode composition of a partly coherent radiation beam in a randomly inhomogeneous medium can be reduced to a study of evolution of the energy of individual modes and of the coefficients of correlations between the modes. General expressions are obtained for the coupling coefficients of modes in a parabolic waveguide with a random microbending of the axis and an analysis is made of their evolution as a function of the excitation conditions. An estimate is obtained of the distance in which a steady-state energy distribution between the modes is established. Explicit expressions are obtained for the correlation function in the case when a waveguide is excited by off-axial Gaussian beams or Gauss-Hermite modes.

Empirical analysis on future-cash arbitrage risk with portfolio VaR

NASA Astrophysics Data System (ADS)

Chen, Rongda; Li, Cong; Wang, Weijin; Wang, Ze

2014-03-01

This paper constructs the positive arbitrage position by alternating the spot index with Chinese Exchange Traded Fund (ETF) portfolio and estimating the arbitrage-free interval of futures with the latest trade data. Then, an improved Delta-normal method was used, which replaces the simple linear correlation coefficient with tail dependence correlation coefficient, to measure VaR (Value-at-risk) of the arbitrage position. Analysis of VaR implies that the risk of future-cash arbitrage is less than that of investing completely in either futures or spot market. Then according to the compositional VaR and the marginal VaR, we should increase the futures position and decrease the spot position appropriately to minimize the VaR, which can minimize risk subject to certain revenues.

A study of the coherence length of ULF waves in the earth's foreshock

NASA Technical Reports Server (NTRS)

Le, G.; Russell, C. T.

1990-01-01

High-time-resolution magnetic-field data for different separations of ISEE 1 and 2 in the earth's ion foreshock region are examined to study the coherence length of upstream ULF waves. Examining the correlation coefficients of the low-frequency waves as a function of separation distance shows that the correlation coefficient depends mainly on the separation distance of ISEE 1 and 2 transverse to the solar-wind flow. It drops to about 0.5 when the transverse separation is about 1 earth radius, a distance much larger than the proton thermal gyroradius in the solar wind. Thus the coherence length of the low-frequency waves is about one earth radius, which is of the order of the wavelength, and is consistent with that estimated from the bandwidth of the waves.

Effect of Correlated Precision Errors on Uncertainty of a Subsonic Venturi Calibration

NASA Technical Reports Server (NTRS)

Hudson, S. T.; Bordelon, W. J., Jr.; Coleman, H. W.

1996-01-01

An uncertainty analysis performed in conjunction with the calibration of a subsonic venturi for use in a turbine test facility produced some unanticipated results that may have a significant impact in a variety of test situations. Precision uncertainty estimates using the preferred propagation techniques in the applicable American National Standards Institute/American Society of Mechanical Engineers standards were an order of magnitude larger than precision uncertainty estimates calculated directly from a sample of results (discharge coefficient) obtained at the same experimental set point. The differences were attributable to the effect of correlated precision errors, which previously have been considered negligible. An analysis explaining this phenomenon is presented. The article is not meant to document the venturi calibration, but rather to give a real example of results where correlated precision terms are important. The significance of the correlated precision terms could apply to many test situations.

Multivariate poisson lognormal modeling of crashes by type and severity on rural two lane highways.

PubMed

Wang, Kai; Ivan, John N; Ravishanker, Nalini; Jackson, Eric

2017-02-01

In an effort to improve traffic safety, there has been considerable interest in estimating crash prediction models and identifying factors contributing to crashes. To account for crash frequency variations among crash types and severities, crash prediction models have been estimated by type and severity. The univariate crash count models have been used by researchers to estimate crashes by crash type or severity, in which the crash counts by type or severity are assumed to be independent of one another and modelled separately. When considering crash types and severities simultaneously, this may neglect the potential correlations between crash counts due to the presence of shared unobserved factors across crash types or severities for a specific roadway intersection or segment, and might lead to biased parameter estimation and reduce model accuracy. The focus on this study is to estimate crashes by both crash type and crash severity using the Integrated Nested Laplace Approximation (INLA) Multivariate Poisson Lognormal (MVPLN) model, and identify the different effects of contributing factors on different crash type and severity counts on rural two-lane highways. The INLA MVPLN model can simultaneously model crash counts by crash type and crash severity by accounting for the potential correlations among them and significantly decreases the computational time compared with a fully Bayesian fitting of the MVPLN model using Markov Chain Monte Carlo (MCMC) method. This paper describes estimation of MVPLN models for three-way stop controlled (3ST) intersections, four-way stop controlled (4ST) intersections, four-way signalized (4SG) intersections, and roadway segments on rural two-lane highways. Annual Average Daily traffic (AADT) and variables describing roadway conditions (including presence of lighting, presence of left-turn/right-turn lane, lane width and shoulder width) were used as predictors. A Univariate Poisson Lognormal (UPLN) was estimated by crash type and severity for each highway facility, and their prediction results are compared with the MVPLN model based on the Average Predicted Mean Absolute Error (APMAE) statistic. A UPLN model for total crashes was also estimated to compare the coefficients of contributing factors with the models that estimate crashes by crash type and severity. The model coefficient estimates show that the signs of coefficients for presence of left-turn lane, presence of right-turn lane, land width and speed limit are different across crash type or severity counts, which suggest that estimating crashes by crash type or severity might be more helpful in identifying crash contributing factors. The standard errors of covariates in the MVPLN model are slightly lower than the UPLN model when the covariates are statistically significant, and the crash counts by crash type and severity are significantly correlated. The model prediction comparisons illustrate that the MVPLN model outperforms the UPLN model in prediction accuracy. Therefore, when predicting crash counts by crash type and crash severity for rural two-lane highways, the MVPLN model should be considered to avoid estimation error and to account for the potential correlations among crash type counts and crash severity counts. Copyright © 2016 Elsevier Ltd. All rights reserved.

The association between hospital outcomes and diagnostic imaging: early findings.

PubMed

Lee, David W; Foster, David A

2009-11-01

Resource use variation across the United States prompts the important question of whether "more is better" when it comes to health care services. The aim of this study was to examine correlations between the use of 4 common imaging modalities (CT, MR, ultrasound, and radiography) and in-hospital mortality and costs. Using clinical and utilization data for 1.1 million inpatient admissions at 102 US hospitals during 2007, two hospital-specific, risk-adjusted imaging utilization measures for each modality were constructed that controlled for patients' demographic and clinical characteristics and for hospital characteristics were constructed for each modality. First, logistic regression was used to estimate the odds that each type of imaging service would be provided during an admission. Second, the mean number of services per admission was estimated using output from a two-part ordinary least squares model. Hospital-specific, risk-adjusted inpatient mortality and total hospital costs were also computed, and correlations between the imaging utilization measures and the mortality and cost outcome measures were then assessed using Pearson's correlation coefficients (P < .05). The correlation analyses were weighted by hospital admission volume. Hospitals in which patients were more likely to receive imaging services during admissions had lower mortality, even after controlling for potential confounders. Correlation coefficients were -0.2 for all modalities (P = .02-.05). Weaker correlations existed between mean services per admission and mortality, while costs trended insignificantly higher with greater utilization. This study lays the foundation for further exploration of the relationship between resource use and the clinical and economic outcomes associated with imaging utilization.

Quantifying expert diagnosis variability when grading tumor-infiltrating lymphocytes

NASA Astrophysics Data System (ADS)

Toro, Paula; Corredor, Germán.; Wang, Xiangxue; Arias, Viviana; Velcheti, Vamsidhar; Madabhushi, Anant; Romero, Eduardo

2017-11-01

Tumor-infiltrating lymphocytes (TILs) have proved to play an important role in predicting prognosis, survival, and response to treatment in patients with a variety of solid tumors. Unfortunately, currently, there are not a standardized methodology to quantify the infiltration grade. The aim of this work is to evaluate variability among the reports of TILs given by a group of pathologists who examined a set of digitized Non-Small Cell Lung Cancer samples (n=60). 28 pathologists answered a different number of histopathological images. The agreement among pathologists was evaluated by computing the Kappa index coefficient and the standard deviation of their estimations. Furthermore, TILs reports were correlated with patient's prognosis and survival using the Pearson's correlation coefficient. General results show that the agreement among experts grading TILs in the dataset is low since Kappa values remain below 0.4 and the standard deviation values demonstrate that in none of the images there was a full consensus. Finally, the correlation coefficient for each pathologist also reveals a low association between the pathologists' predictions and the prognosis/survival data. Results suggest the need of defining standardized, objective, and effective strategies to evaluate TILs, so they could be used as a biomarker in the daily routine.

Uncertainty for calculating transport on Titan: A probabilistic description of bimolecular diffusion parameters

NASA Astrophysics Data System (ADS)

Plessis, S.; McDougall, D.; Mandt, K.; Greathouse, T.; Luspay-Kuti, A.

2015-11-01

Bimolecular diffusion coefficients are important parameters used by atmospheric models to calculate altitude profiles of minor constituents in an atmosphere. Unfortunately, laboratory measurements of these coefficients were never conducted at temperature conditions relevant to the atmosphere of Titan. Here we conduct a detailed uncertainty analysis of the bimolecular diffusion coefficient parameters as applied to Titan's upper atmosphere to provide a better understanding of the impact of uncertainty for this parameter on models. Because temperature and pressure conditions are much lower than the laboratory conditions in which bimolecular diffusion parameters were measured, we apply a Bayesian framework, a problem-agnostic framework, to determine parameter estimates and associated uncertainties. We solve the Bayesian calibration problem using the open-source QUESO library which also performs a propagation of uncertainties in the calibrated parameters to temperature and pressure conditions observed in Titan's upper atmosphere. Our results show that, after propagating uncertainty through the Massman model, the uncertainty in molecular diffusion is highly correlated to temperature and we observe no noticeable correlation with pressure. We propagate the calibrated molecular diffusion estimate and associated uncertainty to obtain an estimate with uncertainty due to bimolecular diffusion for the methane molar fraction as a function of altitude. Results show that the uncertainty in methane abundance due to molecular diffusion is in general small compared to eddy diffusion and the chemical kinetics description. However, methane abundance is most sensitive to uncertainty in molecular diffusion above 1200 km where the errors are nontrivial and could have important implications for scientific research based on diffusion models in this altitude range.

Diffusion and solubility coefficients determined by permeation and immersion experiments for organic solvents in HDPE geomembrane.

PubMed

Chao, Keh-Ping; Wang, Ping; Wang, Ya-Ting

2007-04-02

The chemical resistance of eight organic solvents in high density polyethylene (HDPE) geomembrane has been investigated using the ASTM F739 permeation method and the immersion test at different temperatures. The diffusion of the experimental organic solvents in HDPE geomembrane was non-Fickian kinetic, and the solubility coefficients can be consistent with the solubility parameter theory. The diffusion coefficients and solubility coefficients determined by the ASTM F739 method were significantly correlated to the immersion tests (p<0.001). The steady state permeation rates also showed a good agreement between ASTM F739 and immersion experiments (r(2)=0.973, p<0.001). Using a one-dimensional diffusion equation based on Fick's second law, the diffusion and solubility coefficients obtained by immersion test resulted in over estimates of the ASTM F739 permeation results. The modeling results indicated that the diffusion and solubility coefficients should be obtained using ASTM F739 method which closely simulates the practical application of HDPE as barriers in the field.

Analysis of Manning’s and Drag Coefficients for Flexible Submerged Vegetation

NASA Astrophysics Data System (ADS)

Yusof, Khamaruzaman Wan; Mujahid Muhammad, Muhammad; Mustafa, Muhammad Raza Ul; Azazi Zakaria, Nor; Gahani, Aminuddin Ab.

2017-06-01

Accurate determination of flow resistance is of great significance in modelling of open channels that will convey water efficiently. Although, resistance or drag induced by vegetation have been systematically studied for several decades, estimating of the resistance remain as a challenge. This is because most of previous studies use artificial vegetation to investigate flow - vegetation interactions. To overcome this, the present study evaluates the vegetation resistance in terms of Manning’s roughness coefficient and drag coefficient using a natural flexible vegetation (cow grass) under submerged condition. From the experimental result obtained, it was observed that the Manning’s and drag coefficients decreased with the increasing in average velocity. Also, graphical relationship between Manning’s coefficient, n and drag coefficient, CD has been developed with R2 = 0.9465, which indicate that there exist a strong correlation between n and CD, and one can use the proposed graphical model to predict the n - values corresponding to the CD - values.

RESPONSE FUNCTIONS FOR COMPUTING ABSORBED DOSE TO SKELETAL TISSUES FROM NEUTRON IRRADIATION

PubMed Central

Bahadori, Amir A.; Johnson, Perry; Jokisch, Derek W.; Eckerman, Keith F.; Bolch, Wesley E.

2016-01-01

Spongiosa in the adult human skeleton consists of three tissues - active marrow (AM), inactive marrow (IM), and trabecularized mineral bone (TB). Active marrow is considered to be the target tissue for assessment of both long-term leukemia risk and acute marrow toxicity following radiation exposure. The total shallow marrow (TM50), defined as all tissues laying within the first 50 μm the bone surfaces, is considered to be the radiation target tissue of relevance for radiogenic bone cancer induction. For irradiation by sources external to the body, kerma to homogeneous spongiosa has been used as a surrogate for absorbed dose to both of these tissues, as direct dose calculations are not possible using computational phantoms with homogenized spongiosa. Recent microCT imaging of a 40-year-old male cadaver has allowed for the accurate modeling of the fine microscopic structure of spongiosa in many regions of the adult skeleton [Hough et al PMB (2011)]. This microstructure, along with associated masses and tissue compositions, was used to compute specific absorbed fractions (SAF) values for protons originating in axial and appendicular bone sites [Jokisch et al PMB (submitted)]. These proton SAFs, bone masses, tissue compositions, and proton production cross-sections, were subsequently used to construct neutron dose response functions (DRFs) for both AM and TM50 targets in each bone of the reference adult male. Kerma conditions were assumed for other resultant charged particles. For comparison, active marrow, total shallow marrow, and spongiosa kerma coefficients were also calculated. At low incident neutron energies, AM kerma coefficients for neutrons correlate well with values of the AM DRF, while total marrow (TM) kerma coefficients correlate well with values of the TM50 DRF. At high incident neutron energies, all kerma coefficients and DRFs tend to converge as charged particle equilibrium (CPE) is established across the bone site. In the range of 10 eV to 100 MeV, substantial differences are observed among the kerma coefficients and DRF. As a result, it is recommended that the AM kerma coefficient be used to estimate the AM DRF, and that the TM kerma coefficient be used to estimate the TM50 DRF below 10 eV. Between 10 eV and 100 MeV, the appropriate DRF should be used as presented in this study. Above 100 MeV, spongiosa kerma coefficients apply well for estimating skeletal tissue doses. DRF values for each bone site as a function of energy are provided in an electronic annex to this article. PMID:21983525

Sample Size Estimation in Cluster Randomized Educational Trials: An Empirical Bayes Approach

ERIC Educational Resources Information Center

Rotondi, Michael A.; Donner, Allan

2009-01-01

The educational field has now accumulated an extensive literature reporting on values of the intraclass correlation coefficient, a parameter essential to determining the required size of a planned cluster randomized trial. We propose here a simple simulation-based approach including all relevant information that can facilitate this task. An…

Do sampling methods differ in their utility for ecological monitoring? Comparison of line-point intercept, grid-point intercept, and ocular estimate methods

USDA-ARS?s Scientific Manuscript database

This study compared the utility of three sampling methods for ecological monitoring based on: interchangeability of data (rank correlations), precision (coefficient of variation), cost (minutes/transect), and potential of each method to generate multiple indicators. Species richness and foliar cover...

A satellite snow depth multi-year average derived from SSM/I for the high latitude regions

USGS Publications Warehouse

Biancamaria, S.; Mognard, N.M.; Boone, A.; Grippa, M.; Josberger, E.G.

2008-01-01

The hydrological cycle for high latitude regions is inherently linked with the seasonal snowpack. Thus, accurately monitoring the snow depth and the associated aerial coverage are critical issues for monitoring the global climate system. Passive microwave satellite measurements provide an optimal means to monitor the snowpack over the arctic region. While the temporal evolution of snow extent can be observed globally from microwave radiometers, the determination of the corresponding snow depth is more difficult. A dynamic algorithm that accounts for the dependence of the microwave scattering on the snow grain size has been developed to estimate snow depth from Special Sensor Microwave/Imager (SSM/I) brightness temperatures and was validated over the U.S. Great Plains and Western Siberia. The purpose of this study is to assess the dynamic algorithm performance over the entire high latitude (land) region by computing a snow depth multi-year field for the time period 1987-1995. This multi-year average is compared to the Global Soil Wetness Project-Phase2 (GSWP2) snow depth computed from several state-of-the-art land surface schemes and averaged over the same time period. The multi-year average obtained by the dynamic algorithm is in good agreement with the GSWP2 snow depth field (the correlation coefficient for January is 0.55). The static algorithm, which assumes a constant snow grain size in space and time does not correlate with the GSWP2 snow depth field (the correlation coefficient with GSWP2 data for January is - 0.03), but exhibits a very high anti-correlation with the NCEP average January air temperature field (correlation coefficient - 0.77), the deepest satellite snow pack being located in the coldest regions, where the snow grain size may be significantly larger than the average value used in the static algorithm. The dynamic algorithm performs better over Eurasia (with a correlation coefficient with GSWP2 snow depth equal to 0.65) than over North America (where the correlation coefficient decreases to 0.29). ?? 2007 Elsevier Inc. All rights reserved.

Internal and temporal reliability estimates for informant ratings of personality using the NEO PI-R and IAS. NEO Personality Inventory. Interpersonal Adjective Scales.

PubMed

Kurtz, J E; Lee, P A; Sherker, J L

1999-06-01

This study examines the internal consistency and temporal stability of informant ratings from two widely used instruments for normal personality assessment, the revised NEO Personality Inventory (NEO PI-R) and the Interpersonal Adjective Scales (IAS). Well-known adult targets were selected by 109 undergraduate students and rated on two occasions separated by a 6-month interval. With few exceptions, estimates of internal consistency are adequate to good for both instruments. NEO PI-R domain scores yield coefficient alphas ranging from .89 to .96, with a median of .80 for the 30 facet scales. IAS octant scales show coefficient alphas ranging from .83 to .92. Retest Pearson correlations are above .70 for each of the NEO PI-R domain scores and both IAS axis coordinates, and intraclass correlations are above .60 for all scales from both instruments. Score changes were small but statistically significant for three of the five NEO PI-R domains at retest. The retest stability of IAS type classifications varies as a function of the extremity of the associated octant scores.

A novel method to quantify the adulteration of extra virgin olive oil with low-grade olive oils by UV-vis.

PubMed

Torrecilla, José S; Rojo, Ester; Domínguez, Juan C; Rodríguez, Francisco

2010-02-10

A simple and novel method to quantify adulterations of extra virgin olive oil (EVOO) with refined olive oil (ROO) and refined olive-pomace oil (ROPO) is described here. This method consists of calculating chaotic parameters (Lyapunov exponent, autocorrelation coefficients, and two fractal dimensions, CPs) from UV-vis scans of adulterated EVOO samples. These parameters have been successfully linearly correlated with the ROO or ROPO concentrations in 396 EVOO adulterated samples. By an external validation process, when the adulterating agent concentration is less than 10%, the integrated CPs/UV-vis model estimates the adulterant agent concentration with a mean correlation coefficient (estimated versus real concentration of low grade olive oil) greater than 0.97 and a mean square error of less than 1%. In light of these results, this detector is suitable not only to detect adulterations but also to measure impurities when, for instance, a higher grade olive oil is transferred to another storage tank in which lower grade olive oil was stored that had not been adequately cleaned.

[Rapid prediction of annual ring density of Paulownia elongate standing tress using near infrared spectroscopy].

PubMed

Jiang, Ze-Hui; Wang, Yu-Rong; Fei, Ben-Hua; Fu, Feng; Hse, Chung-Yun

2007-06-01

Rapid prediction of annual ring density of Paulownia elongate standing trees using near infrared spectroscopy was studied. It was non-destructive to collect the samples for trees, that is, the wood cores 5 mm in diameter were unthreaded at the breast height of standing trees instead of fallen trees. Then the spectra data were collected by autoscan method of NIR. The annual ring density was determined by mercury immersion. And the models were made and analyzed by the partial least square (PLS) and full cross validation in the 350-2 500 nm wavelength range. The results showed that high coefficients were obtained between the annual ring and the NIR fitted data. The correlation coefficient of prediction model was 0.88 and 0.91 in the middle diameter and bigger diameter, respectively. Moreover, high coefficients of correlation were also obtained between annual ring density laboratory-determined and the NIR fitted data in the middle diameter of Paulownia elongate standing trees, the correlation coefficient of calibration model and prediction model were 0.90 and 0.83, and the standard errors of calibration (SEC) and standard errors of prediction(SEP) were 0.012 and 0.016, respectively. The method can simply, rapidly and non-destructively estimate the annual ring density of the Paulownia elongate standing trees close to the cutting age.

Genetic parameters for stayability to consecutive calvings in Zebu cattle.

PubMed

Silva, D O; Santana, M L; Ayres, D R; Menezes, G R O; Silva, L O C; Nobre, P R C; Pereira, R J

2017-12-22

Longer-lived cows tend to be more profitable and the stayability trait is a selection criterion correlated to longevity. An alternative to the traditional approach to evaluate stayability is its definition based on consecutive calvings, whose main advantage is the more accurate evaluation of young bulls. However, no study using this alternative approach has been conducted for Zebu breeds. Therefore, the objective of this study was to compare linear random regression models to fit stayability to consecutive calvings of Guzerá, Nelore and Tabapuã cows and to estimate genetic parameters for this trait in the respective breeds. Data up to the eighth calving were used. The models included the fixed effects of age at first calving and year-season of birth of the cow and the random effects of contemporary group, additive genetic, permanent environmental and residual. Random regressions were modeled by orthogonal Legendre polynomials of order 1 to 4 (2 to 5 coefficients) for contemporary group, additive genetic and permanent environmental effects. Using Deviance Information Criterion as the selection criterion, the model with 4 regression coefficients for each effect was the most adequate for the Nelore and Tabapuã breeds and the model with 5 coefficients is recommended for the Guzerá breed. For Guzerá, heritabilities ranged from 0.05 to 0.08, showing a quadratic trend with a peak between the fourth and sixth calving. For the Nelore and Tabapuã breeds, the estimates ranged from 0.03 to 0.07 and from 0.03 to 0.08, respectively, and increased with increasing calving number. The additive genetic correlations exhibited a similar trend among breeds and were higher for stayability between closer calvings. Even between more distant calvings (second v. eighth), stayability showed a moderate to high genetic correlation, which was 0.77, 0.57 and 0.79 for the Guzerá, Nelore and Tabapuã breeds, respectively. For Guzerá, when the models with 4 or 5 regression coefficients were compared, the rank correlations between predicted breeding values for the intercept were always higher than 0.99, indicating the possibility of practical application of the least parameterized model. In conclusion, the model with 4 random regression coefficients is recommended for the genetic evaluation of stayability to consecutive calvings in Zebu cattle.

Correlation analysis of respiratory signals by using parallel coordinate plots.

PubMed

Saatci, Esra

2018-01-01

The understanding of the bonds and the relationships between the respiratory signals, i.e. the airflow, the mouth pressure, the relative temperature and the relative humidity during breathing may provide the improvement on the measurement methods of respiratory mechanics and sensor designs or the exploration of the several possible applications in the analysis of respiratory disorders. Therefore, the main objective of this study was to propose a new combination of methods in order to determine the relationship between respiratory signals as a multidimensional data. In order to reveal the coupling between the processes two very different methods were used: the well-known statistical correlation analysis (i.e. Pearson's correlation and cross-correlation coefficient) and parallel coordinate plots (PCPs). Curve bundling with the number intersections for the correlation analysis, Least Mean Square Time Delay Estimator (LMS-TDE) for the point delay detection and visual metrics for the recognition of the visual structures were proposed and utilized in PCP. The number of intersections was increased when the correlation coefficient changed from high positive to high negative correlation between the respiratory signals, especially if whole breath was processed. LMS-TDE coefficients plotted in PCP indicated well-matched point delay results to the findings in the correlation analysis. Visual inspection of PCB by visual metrics showed range, dispersions, entropy comparisons and linear and sinusoidal-like relationships between the respiratory signals. It is demonstrated that the basic correlation analysis together with the parallel coordinate plots perceptually motivates the visual metrics in the display and thus can be considered as an aid to the user analysis by providing meaningful views of the data. Copyright © 2017 Elsevier B.V. All rights reserved.

Estimation of premorbid general fluid intelligence using traditional Chinese reading performance in Taiwanese samples.

PubMed

Chen, Ying-Jen; Ho, Meng-Yang; Chen, Kwan-Ju; Hsu, Chia-Fen; Ryu, Shan-Jin

2009-08-01

The aims of the present study were to (i) investigate if traditional Chinese word reading ability can be used for estimating premorbid general intelligence; and (ii) to provide multiple regression equations for estimating premorbid performance on Raven's Standard Progressive Matrices (RSPM), using age, years of education and Chinese Graded Word Reading Test (CGWRT) scores as predictor variables. Four hundred and twenty-six healthy volunteers (201 male, 225 female), aged 16-93 years (mean +/- SD, 41.92 +/- 18.19 years) undertook the tests individually under supervised conditions. Seventy percent of subjects were randomly allocated to the derivation group (n = 296), and the rest to the validation group (n = 130). RSPM score was positively correlated with CGWRT score and years of education. RSPM and CGWRT scores and years of education were also inversely correlated with age, but the declining trend for RSPM performance against age was steeper than that for CGWRT performance. Separate multiple regression equations were derived for estimating RSPM scores using different combinations of age, years of education, and CGWRT score for both groups. The multiple regression coefficient of each equation ranged from 0.71 to 0.80 with the standard error of estimate between 7 and 8 RSPM points. When fitting the data of one group to the equations derived from its counterpart group, the cross-validation multiple regression coefficients ranged from 0.71 to 0.79. There were no significant differences in the 'predicted-obtained' RSPM discrepancies between any equations. The regression equations derived in the present study may provide a basis for estimating premorbid RSPM performance.

Noninvasive measurement of beat-to-beat arterial blood pressure by the Korotkoff sound delay time.

PubMed

Xiang, Haiyan; Liu, Yanyong; Li, Yinhua; Qin, Yufei; Yu, Mengsun

2012-02-01

To propose a novel noninvasive beat-to-beat arterial blood pressure measurement method based on the Korotkoff sound delay time (KDT) and evaluate its accuracy in preliminary experiments. KDT decreases as the cuff pressure P deflates, which can be described by a function KDT=f (P). Actually, KDT is a function of arterial transmural pressure. Therefore, the variation in blood pressure can be obtained by the transmural pressure, which is estimated by the KDT. Holding the cuff pressure at an approximate constant pressure between systolic pressure and diastolic pressure, the variation in blood pressure ΔEBP between successive heartbeats can be estimated according to KDT and f'(p), which represents the variation of KDT corresponding to unit pressure. Then the blood pressure for each heartbeat can be obtained by accumulating the ΔEBP. Invasive and noninvasive blood pressure values of six participants were measured simultaneously to evaluate the method. The average of the correlation coefficients between the invasive mean arterial pressure (MAP) and the KDT for six participants was -0.91. The average of the correlation coefficients between the invasive MAP and the estimated mean blood pressure (EBP) was 0.92. The mean difference between EBP and MAP was 0.51 mmHg, and the SD was 2.65 mmHg. The mean blood pressure estimated by the KDT is consistent with the invasive MAP. The beat-to-beat blood pressure estimated by KDT provides an accurate estimate of MAP in the preliminary experiments and represents a potential acceptable alternative to invasive blood pressure monitoring during laboratory studies.

Measuring dental fear using the CFSS-DS. Do children and parents agree?

PubMed

Krikken, Janneke B; van Wijk, Arjen J; ten Cate, Jacob M; Veerkamp, Jaap S J

2013-03-01

In most studies, the parental version of the CFSS-DS is used; however, no information is available concerning the extent to which parents are able to report dental fear on behalf of their children. This study aims to assess whether parents are accurate reporters of their child's dental fear. The CFSS-DS was filled out by 326 children in a classroom setting and by 167 parents (mostly mothers) at home on behalf of their child. Intraclass correlation coefficients were used as a measure of agreement between both CFSS-DS versions, and reasons for nonagreement were assessed. Mean CFSS-DS for children was 21.15 (SD = 6.4) and for parents 23.26 (SD = 6.7). The intraclass correlation coefficient was 0.57. After selection of the 73.1% most accurate reporting parents, the ICC was 0.90. In general, parents estimate the dental fear of their children higher than their children do (P ≤ 0.001), whereas parents of high anxious children (HAC) estimate this fear lower, and parents of low anxious children (LAC) estimate this fear higher. Anxious parents (AP) estimate the dental fear of their children significantly higher than nonanxious parents (NAP) (P ≤ 0.001), but the children of AP do not estimate their own dental fear higher than children of NAP. In general, parents tend to estimate the dental fear of their children slightly higher than their children. © 2012 The Authors. International Journal of Paediatric Dentistry © 2012 BSPD, IAPD and Blackwell Publishing Ltd.

Accuracy of contrast-enhanced spectral mammography for estimating residual tumor size after neoadjuvant chemotherapy in patients with breast cancer: a feasibility study

PubMed Central

Barra, Filipe Ramos; de Souza, Fernanda Freire; Camelo, Rosimara Eva Ferreira Almeida; Ribeiro, Andrea Campos de Oliveira; Farage, Luciano

2017-01-01

Objective To assess the feasibility of contrast-enhanced spectral mammography (CESM) of the breast for assessing the size of residual tumors after neoadjuvant chemotherapy (NAC). Materials and methods In breast cancer patients who underwent NAC between 2011 and 2013, we evaluated residual tumor measurements obtained with CESM and full-field digital mammography (FFDM). We determined the concordance between the methods, as well as their level of agreement with the pathology. Three radiologists analyzed eight CESM and FFDM measurements separately, considering the size of the residual tumor at its largest diameter and correlating it with that determined in the pathological analysis. Interobserver agreement was also evaluated. Results The sensitivity, specificity, positive predictive value, and negative predictive value were higher for CESM than for FFDM (83.33%, 100%, 100%, and 66% vs. 50%, 50%, 50%, and 25%, respectively). The CESM measurements showed a strong, consistent correlation with the pathological findings (correlation coefficient = 0.76-0.92; intraclass correlation coefficient = 0.692-0.886). The correlation between the FFDM measurements and the pathological findings was not statistically significant, with questionable consistency (intraclass correlation coefficient = 0.488-0.598). Agreement with the pathological findings was narrower for CESM measurements than for FFDM measurements. Interobserver agreement was higher for CESM than for FFDM (0.94 vs. 0.88). Conclusion CESM is a feasible means of evaluating residual tumor size after NAC, showing a good correlation and good agreement with pathological findings. For CESM measurements, the interobserver agreement was excellent. PMID:28894329

Estimating chlorophyll content of spartina alterniflora at leaf level using hyper-spectral data

NASA Astrophysics Data System (ADS)

Wang, Jiapeng; Shi, Runhe; Liu, Pudong; Zhang, Chao; Chen, Maosi

2017-09-01

Spartina alterniflora, one of most successful invasive species in the world, was firstly introduced to China in 1979 to accelerate sedimentation and land formation via so-called "ecological engineering", and it is now widely distributed in coastal saltmarshes in China. A key question is how to retrieve chlorophyll content to reflect growth status, which has important implication of potential invasiveness. In this work, an estimation model of chlorophyll content of S. alterniflora was developed based on hyper-spectral data in the Dongtan Wetland, Yangtze Estuary, China. The spectral reflectance of S. alterniflora leaves and their corresponding chlorophyll contents were measured, and then the correlation analysis and regression (i.e., linear, logarithmic, quadratic, power and exponential regression) method were established. The spectral reflectance was transformed and the feature parameters (i.e., "san bian", "lv feng" and "hong gu") were extracted to retrieve the chlorophyll content of S. alterniflora . The results showed that these parameters had a large correlation coefficient with chlorophyll content. On the basis of the correlation coefficient, mathematical models were established, and the models of power and exponential based on SDb had the least RMSE and larger R2 , which had a good performance regarding the inversion of chlorophyll content of S. alterniflora.

Stability-Indicating HPTLC Method for Simultaneous Estimation of Flurbiprofen and Chloramphenicol in Ophthalmic Solution.

PubMed

Sadakwala, Vaishnavi M; Chauhan, Renu S; Shah, Shailesh A; Shah, Dinesh R

2016-01-01

A specific, accurate and reproducible stability-indicating high performance thin layer chromatography (HPTLC) method was developed for the estimation of flurbiprofen and chloramphenicol in the presence of their degradation products. Degradation studies of both the drugs were carried out in acidic, alkaline, neutral, oxidative, photolytic and thermal stress conditions. Separation was performed on thin layer chromatography plate precoated with silica gel 60 F254 using ethyl acetate : n-hexane : methanol : tri-ethyl amine (5 : 4 : 2 : 0.5, v/v/v/v). Spots at retention factor 0.29 and 0.62 were recognized as flurbiprofen and chloramphenicol, respectively, and were quantified through densitometric measurements at wavelength 267 nm. Method was found to be linear over the concentration range 12-60 ng/spot with correlation coefficient of 0.9997 for flurbiprofen and 200-1,000 ng/spot with correlation coefficient of 0.9977 for chloramphenicol. The proposed method was applied to the estimation of flurbiprofen and chloramphenicol in commercial ophthalmic formulation. The developed HPTLC method can be applied for routine analysis of flurbiprofen and chloramphenicol in the presence of their degradation products in their individual as well as combined pharmaceutical formulations. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Relative Validity and Reproducibility of an Interviewer Administered 14-Item FFQ to Estimate Flavonoid Intake Among Older Adults with Mild-Moderate Dementia.

PubMed

Kent, Katherine; Charlton, Karen

2017-01-01

There is a large burden on researchers and participants when attempting to accurately measure dietary flavonoid intake using dietary assessment. Minimizing participant and researcher burden when collecting dietary data may improve the validity of the results, especially in older adults with cognitive impairment. A short 14-item food frequency questionnaire (FFQ) to measure flavonoid intake, and flavonoid subclasses (anthocyanins, flavan-3-ols, flavones, flavonols, and flavanones) was developed and assessed for validity and reproducibility against a 24-hour recall. Older adults with mild-moderate dementia (n = 49) attended two interviews 12 weeks apart. With the assistance of a family carer, a 24-h recall was collected at the first interview, and the flavonoid FFQ was interviewer-administered at both time-points. Validity and reproducibility was assessed using the Wilcoxon signed-rank sum test, Spearman's correlation coefficient, Bland-Altman Plots, and Cohen's kappa. Mean flavonoid intake was determined (FFQ1 = 795 ± 492.7 mg/day, 24-h recall = 515.6 ± 384.3 mg/day). Tests of validity indicated the FFQ was better at estimating total flavonoid intake than individual flavonoid subclasses compared with the 24-h recall. There was a significant difference in total flavonoid intake estimates between the FFQ and the 24-h recall (Wilcoxon signed-rank sum p < 0.001; Bland-Altman plots indicated large bias and wide limits of agreement), but they were well correlated (Spearman's correlation coefficient r = 0.74, p < 0.001; Cohen's kappa κ = 0.292, p < 0.001). The FFQ showed good reproducibility, with a small mean percentage difference (12.6%). The Wilcoxon signed-rank sum test showed no significant difference, Spearman's correlation coefficient indicated excellent reliability (r = 0.75, p < 0.001), Bland-Altman plots visually showed small, nonsignificant bias and wide limits of agreement, and Cohen's kappa indicated fair agreement (κ = 0.429, p < 0.001). A 14-item FFQ developed to easily measure flavonoid intake in older adults with dementia demonstrates fair validity against a 24-h recall and good reproducibility.

Estimates of bottom roughness length and bottom shear stress in South San Francisco Bay, California

USGS Publications Warehouse

Cheng, R.T.; Ling, C.-H.; Gartner, J.W.; Wang, P.-F.

1999-01-01

A field investigation of the hydrodynamics and the resuspension and transport of participate matter in a bottom boundary layer was carried out in South San Francisco Bay (South Bay), California, during March-April 1995. Using broadband acoustic Doppler current profilers, detailed measurements of turbulent mean velocity distribution within 1.5 m above bed have been obtained. A global method of data analysis was used for estimating bottom roughness length zo and bottom shear stress (or friction velocities u*). Field data have been examined by dividing the time series of velocity profiles into 24-hour periods and independently analyzing the velocity profile time series by flooding and ebbing periods. The global method of solution gives consistent properties of bottom roughness length zo and bottom shear stress values (or friction velocities u*) in South Bay. Estimated mean values of zo and u* for flooding and ebbing cycles are different. The differences in mean zo and u* are shown to be caused by tidal current flood-ebb inequality, rather than the flooding or ebbing of tidal currents. The bed shear stress correlates well with a reference velocity; the slope of the correlation defines a drag coefficient. Forty-three days of field data in South Bay show two regimes of zo (and drag coefficient) as a function of a reference velocity. When the mean velocity is >25-30 cm s-1, the ln zo (and thus the drag coefficient) is inversely proportional to the reference velocity. The cause for the reduction of roughness length is hypothesized as sediment erosion due to intensifying tidal currents thereby reducing bed roughness. When the mean velocity is <25-30 cm s-1, the correlation between zo and the reference velocity is less clear. A plausible explanation of scattered values of zo under this condition may be sediment deposition. Measured sediment data were inadequate to support this hypothesis, but the proposed hypothesis warrants further field investigation.

Fluorescence correlation spectroscopy experiments to quantify free diffusion coefficients in reaction-diffusion systems: The case of Ca2 + and its dyes

NASA Astrophysics Data System (ADS)

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.

Validity and Calibration of Food Frequency Questionnaires used with African American Adults in the Jackson Heart Study

PubMed Central

Carithers, Teresa C.; Talegawkar, Sameera A.; Rowser, Marjuyua L.; Henry, Olivia R.; Dubbert, Patricia M.; Bogle, Margaret L; Taylor, Herman A.

2009-01-01

Objective To examine the relative validity of two Food Frequency Questionnaires (FFQs) developed for use in investigating diet and disease relationships within the adult African American population in the southern United States. Design Cross-sectional analyses of dietary nutrient intake data, comparing four 24-hour dietary recalls with a FFQ developed by the Lower Mississippi Delta Nutrition Intervention Research Initiative (Delta NIRI), and its shorter version adapted for use in the Jackson Heart Study (JHS). Subjects A representative subset of participants (n=499, 35-81 y) from the baseline JHS cohort (N=5,302) was selected for this study. Data collection took place between winter of 2000 and spring of 2004. Statistical Analyses Pearson's correlation coefficients (energy adjusted and de-attenuated) for 26 nutrients estimates from each of the FFQs, comparing them with the mean of four 24-hour dietary recalls. The ability of the FFQs to rank individuals based on nutrient intakes was compared to that of the mean of four 24-hour dietary recalls and attenuation coefficients were also calculated. Results Median nutrient intake estimates tended to be higher on the long and lower on the short FFQ compared to the median for the mean of four 24-hour dietary recalls. Energy adjusted and de-attenuated correlations of FFQ intake estimates with recalls ranged from 0.20 for sodium to 0.70 for carbohydrate for the short FFQ and from 0.23 for polyunsaturated fat to 0.75 for dietary fiber and magnesium for the long. Attenuation coefficients for men on average were 0.42 for the short and 0.49 for the long FFQ. For women, these were 0.31 for the short and 0.42 for the long FFQ. Conclusions Both FFQs appear to be reasonably valid for assessment of dietary intake of adult African Americans in the South. The Delta NIRI FFQ exhibited higher intake estimates and stronger correlations with recalls than the JHS FFQ for most nutrients analyzed, more so for women than men. PMID:19559135

QSPR study of polychlorinated diphenyl ethers by molecular electronegativity distance vector (MEDV-4).

PubMed

Sun, Lili; Zhou, Liping; Yu, Yu; Lan, Yukun; Li, Zhiliang

2007-01-01

Polychlorinated diphenyl ethers (PCDEs) have received more and more concerns as a group of ubiquitous potential persistent organic pollutants (POPs). By using molecular electronegativity distance vector (MEDV-4), multiple linear regression (MLR) models are developed for sub-cooled liquid vapor pressures (P(L)), n-octanol/water partition coefficients (K(OW)) and sub-cooled liquid water solubilities (S(W,L)) of 209 PCDEs and diphenyl ether. The correlation coefficients (R) and the leave-one-out cross-validation (LOO) correlation coefficients (R(CV)) of all the 6-descriptor models for logP(L), logK(OW) and logS(W,L) are more than 0.98. By using stepwise multiple regression (SMR), the descriptors are selected and the resulting models are 5-descriptor model for logP(L), 4-descriptor model for logK(OW), and 6-descriptor model for logS(W,L), respectively. All these models exhibit excellent estimate capabilities for internal sample set and good predictive capabilities for external samples set. The consistency between observed and estimated/predicted values for logP(L) is the best (R=0.996, R(CV)=0.996), followed by logK(OW) (R=0.992, R(CV)=0.992) and logS(W,L) (R=0.983, R(CV)=0.980). By using MEDV-4 descriptors, the QSPR models can be used for prediction and the model predictions can hence extend the current database of experimental values.

Use of a W-band polarimeter to measure microphysical characteristics of clouds

NASA Astrophysics Data System (ADS)

Galloway, John Charles

1997-08-01

This dissertation presents W-Band measurements of the copolar correlation co-efficient and Doppler spectrum taken from the University of Wyoming King Air research airplane. These measurements demonstrate the utility of making W-Band polarimetric and Doppler spectrum measurements from an airborne platform in investigations of cloud microphysical properties. Comparison of copolar correlation coefficient measurements with aircraft in situ probe measurements verifies that polarimetric measurements indicate phase transitions, and hydrometeor alignment in ice clouds. Melting layers in clouds were measured by the W-Band system on board the King Air during 1992 and 1994. Both measurements established the use of the linear depolarization ratio, LDR, to locate the melting layer using an airborne W-Band system. The measurement during 1994 allowed direct comparison of the magnitude of the copolar correlation coefficient with the values of LDR. The relation between the measurements corresponds with a predicted relationship between the two parameters for observation of particles exhibiting isotropy in the plane of polarization. Measurements of needle crystals at horizontal and vertical incidence provided further evidence that the copolar correlation coefficient values agreed with the expected response from hydrometeors possessing a preferred alignment for the side looking case, and hydrometeors without a preferred alignment for the vertical incidence case. Observation of significant specific differential phase at vertical incidence, the first reported at W-Band, corresponded to a significant increase in differential reflectivity overhead, which was most likely produced by hydrometeor alignment driven by cloud electrification. Comparison of the drop size distributions estimated using the Doppler spectra with those measured by the wingtip probes on the King Air reveals that the radar system is better suited under some liquid cloud conditions to provide microphysical measurements of the cloud or precipitation than the probes. The radiometric calibration of the radar system determines the accuracy of the drop size distribution estimate. The results presented here indicate that the procedure used to absolutely calibrate the W-Band radar system successfully characterized the reflectivity measurements to the extent required to obtain close correspondence between the radar and probe measurements of the drop size distribution.

A new correlation coefficient for bivariate time-series data

NASA Astrophysics Data System (ADS)

Erdem, Orhan; Ceyhan, Elvan; Varli, Yusuf

2014-11-01

The correlation in time series has received considerable attention in the literature. Its use has attained an important role in the social sciences and finance. For example, pair trading in finance is concerned with the correlation between stock prices, returns, etc. In general, Pearson’s correlation coefficient is employed in these areas although it has many underlying assumptions which restrict its use. Here, we introduce a new correlation coefficient which takes into account the lag difference of data points. We investigate the properties of this new correlation coefficient. We demonstrate that it is more appropriate for showing the direction of the covariation of the two variables over time. We also compare the performance of the new correlation coefficient with Pearson’s correlation coefficient and Detrended Cross-Correlation Analysis (DCCA) via simulated examples.

Development and testing of the Test of Functional Health Literacy in Dentistry (TOFHLiD).

PubMed

Gong, Debra A; Lee, Jessica Y; Rozier, R Gary; Pahel, Bhavna T; Richman, Julia A; Vann, William F

2007-01-01

This study aims to evaluate the reliability and validity of the Test of Functional Health Literacy in Dentistry (TOFHLiD), a new instrument to measure functional oral health literacy. TOFHLiD uses text passages and prompts related to fluoride use and access to care to assess reading comprehension and numerical ability. Parents of pediatric dental patients (n = 102) were administered TOFHLiD, a medical literacy comprehension test (TOFHLA), and two word recognition tests [Rapid Estimate of Adult Literacy in Dentistry (REALD), Rapid Estimate of Adult Literacy in Medicine (REALM)]. This design provided assessments of dental and medical health literacy by all subjects, both measured with two different methods (reading/numeracy ability and word recognition). Construct validity of TOFHLiD was assessed by entering the correlation coefficients for all pairwise comparisons of literacy instruments into a multitrait-multimethod matrix. Internal reliability of TOFHLiD was assessed with Cronbach's alpha. Criterion-related predictive validity was tested by associations between the TOFHLiD scores and the three measures of oral health in multivariate regression analyses. The correlation coefficient for TOFHLiD and REALD-99 scores (monotrait-heteromethod) was high (r = 0.82, P < 0.05). Coefficients between TOFHLiD and TOFHLA (heterotrait-monomethod: r = 0.52) and REALM (heterotrait-heteromethod: r = 0.53) were smaller than coefficients for convergent validity Cronbach's alpha for TOFHLiD was 0.63. TOFHLiD was positively correlated with OHIP-14 (P < 0.05), but not with parent or child oral health. TOFHLA was not related to dental outcomes. TOFHLiD demonstrates good convergent validity but only moderate ability to discriminate between dental and medical health literacy. Its predictive validity is only partially established, and internal consistency just meets the threshold for acceptability. Results provide solid support for more research, but not widespread use in clinical or public health practice.

Accuracy and reliability testing of two methods to measure internal rotation of the glenohumeral joint.

PubMed

Hall, Justin M; Azar, Frederick M; Miller, Robert H; Smith, Richard; Throckmorton, Thomas W

2014-09-01

We compared accuracy and reliability of a traditional method of measurement (most cephalad vertebral spinous process that can be reached by a patient with the extended thumb) to estimates made with the shoulder in abduction to determine if there were differences between the two methods. Six physicians with fellowship training in sports medicine or shoulder surgery estimated measurements in 48 healthy volunteers. Three were randomly chosen to make estimates of both internal rotation measurements for each volunteer. An independent observer made objective measurements on lateral scoliosis films (spinous process method) or with a goniometer (abduction method). Examiners were blinded to objective measurements as well as to previous estimates. Intraclass coefficients for interobserver reliability for the traditional method averaged 0.75, indicating good agreement among observers. The difference in vertebral level estimated by the examiner and the actual radiographic level averaged 1.8 levels. The intraclass coefficient for interobserver reliability for the abduction method averaged 0.81 for all examiners, indicating near-perfect agreement. Confidence intervals indicated that estimates were an average of 8° different from the objective goniometer measurements. Pearson correlation coefficients of intraobserver reliability for the abduction method averaged 0.94, indicating near-perfect agreement within observers. Confidence intervals demonstrated repeated estimates between 5° and 10° of the original. Internal rotation estimates made with the shoulder abducted demonstrated interobserver reliability superior to that of spinous process estimates, and reproducibility was high. On the basis of this finding, we now take glenohumeral internal rotation measurements with the shoulder in abduction and use a goniometer to maximize accuracy and objectivity. Copyright © 2014 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Mosby, Inc. All rights reserved.

Structured penalties for functional linear models-partially empirical eigenvectors for regression.

PubMed

Randolph, Timothy W; Harezlak, Jaroslaw; Feng, Ziding

2012-01-01

One of the challenges with functional data is incorporating geometric structure, or local correlation, into the analysis. This structure is inherent in the output from an increasing number of biomedical technologies, and a functional linear model is often used to estimate the relationship between the predictor functions and scalar responses. Common approaches to the problem of estimating a coefficient function typically involve two stages: regularization and estimation. Regularization is usually done via dimension reduction, projecting onto a predefined span of basis functions or a reduced set of eigenvectors (principal components). In contrast, we present a unified approach that directly incorporates geometric structure into the estimation process by exploiting the joint eigenproperties of the predictors and a linear penalty operator. In this sense, the components in the regression are 'partially empirical' and the framework is provided by the generalized singular value decomposition (GSVD). The form of the penalized estimation is not new, but the GSVD clarifies the process and informs the choice of penalty by making explicit the joint influence of the penalty and predictors on the bias, variance and performance of the estimated coefficient function. Laboratory spectroscopy data and simulations are used to illustrate the concepts.

Estimating absorption coefficients of colored dissolved organic matter (CDOM) using a semi-analytical algorithm for Southern Beaufort Sea (Canadian Arctic) waters: application to deriving concentrations of dissolved organic carbon from space

NASA Astrophysics Data System (ADS)

Matsuoka, A.; Hooker, S. B.; Bricaud, A.; Gentili, B.; Babin, M.

2012-10-01

A series of papers have suggested that freshwater discharge, including a large amount of dissolved organic matter (DOM), has increased since the middle of the 20th century. In this study, a semi-analytical algorithm for estimating light absorption coefficients of the colored fraction of DOM (CDOM) was developed for Southern Beaufort Sea waters using remote sensing reflectance at six wavelengths in the visible spectral domain corresponding to MODIS ocean color sensor. This algorithm allows to separate colored detrital matter (CDM) into CDOM and non-algal particles (NAP) by determining NAP absorption using an empirical relationship between NAP absorption and particle backscattering coefficients. Evaluation using independent datasets, that were not used for developing the algorithm, showed that CDOM absorption can be estimated accurately to within an uncertainty of 35% and 50% for oceanic and turbid waters, respectively. In situ measurements showed that dissolved organic carbon (DOC) concentrations were tightly correlated with CDOM absorption (r2 = 0.97). By combining the CDOM absorption algorithm together with the DOC versus CDOM relationship, it is now possible to estimate DOC concentrations in the near-surface layer of the Southern Beaufort Sea using satellite ocean color data. DOC concentrations in the surface waters were estimated using MODIS ocean color data, and the estimates showed reasonable values compared to in situ measurements. We propose a routine and near real-time method for deriving DOC concentrations from space, which may open the way to an estimate of DOC budgets for Arctic coastal waters.

Preliminary statistical studies concerning the Campos RJ sugar cane area, using LANDSAT imagery and aerial photographs

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Costa, S. R. X.; Paiao, L. B. F.; Mendonca, F. J.; Shimabukuro, Y. E.; Duarte, V.

1983-01-01

The two phase sampling technique was applied to estimate the area cultivated with sugar cane in an approximately 984 sq km pilot region of Campos. Correlation between existing aerial photography and LANDSAT data was used. The two phase sampling technique corresponded to 99.6% of the results obtained by aerial photography, taken as ground truth. This estimate has a standard deviation of 225 ha, which constitutes a coefficient of variation of 0.6%.

Estimating glomerular filtration rate in black South Africans by use of the modification of diet in renal disease and Cockcroft-Gault equations.

PubMed

van Deventer, Hendrick E; George, Jaya A; Paiker, Janice E; Becker, Piet J; Katz, Ivor J

2008-07-01

The 4-variable Modification of Diet in Renal Disease (4-v MDRD) and Cockcroft-Gault (CG) equations are commonly used for estimating glomerular filtration rate (GFR); however, neither of these equations has been validated in an indigenous African population. The aim of this study was to evaluate the performance of the 4-v MDRD and CG equations for estimating GFR in black South Africans against measured GFR and to assess the appropriateness for the local population of the ethnicity factor established for African Americans in the 4-v MDRD equation. We enrolled 100 patients in the study. The plasma clearance of chromium-51-EDTA ((51)Cr-EDTA) was used to measure GFR, and serum creatinine was measured using an isotope dilution mass spectrometry (IDMS) traceable assay. We estimated GFR using both the reexpressed 4-v MDRD and CG equations and compared it to measured GFR using 4 modalities: correlation coefficient, weighted Deming regression analysis, percentage bias, and proportion of estimated GFR within 30% of measured GFR (P(30)). The Spearman correlation coefficient between measured and estimated GFR for both equations was similar (4-v MDRD R(2) = 0.80 and CG R(2) = 0.79). Using the 4-v MDRD equation with the ethnicity factor of 1.212 as established for African Americans resulted in a median positive bias of 13.1 (95% CI 5.5 to 18.3) mL/min/1.73 m(2). Without the ethnicity factor, median bias was 1.9 (95% CI -0.8 to 4.5) mL/min/1.73 m(2). The 4-v MDRD equation, without the ethnicity factor of 1.212, can be used for estimating GFR in black South Africans.

Remotely sensing wheat maturation with radar

NASA Technical Reports Server (NTRS)

Bush, T. F.; Ulaby, F. T.

1975-01-01

The scattering properties of wheat were studied in the 8-18 GHz band as a function of frequency, polarization, incidence angle, and crop maturity. Supporting ground truth was collected at the time of measurement. The data indicate that the radar backscattering coefficient is sensitive to both radar system parameters and crop characteristics particularly at incidence angles near nadir. Linear regression analyses of the radar backscattering coefficient on both time and plant moisture content result in rather good correlation. Furthermore, by calculating the average time rate of change of the radar backscattering coefficient it is found that it undergoes rapid variations shortly before and after the wheat is harvested. Both of these analyses suggest methods for estimating wheat maturity and for monitoring the progress of harvest.

Impact of pesticide exposure misclassification on estimates of relative risks in the Agricultural Health Study.

PubMed

Blair, Aaron; Thomas, Kent; Coble, Joseph; Sandler, Dale P; Hines, Cynthia J; Lynch, Charles F; Knott, Charles; Purdue, Mark P; Zahm, Shelia Hoar; Alavanja, Michael C R; Dosemeci, Mustafa; Kamel, Freya; Hoppin, Jane A; Freeman, Laura Beane; Lubin, Jay H

2011-07-01

The Agricultural Health Study (AHS) is a prospective study of licensed pesticide applicators and their spouses in Iowa and North Carolina. We evaluate the impact of occupational pesticide exposure misclassification on relative risks using data from the cohort and the AHS Pesticide Exposure Study (AHS/PES). We assessed the impact of exposure misclassification on relative risks using the range of correlation coefficients observed between measured post-application urinary levels of 2,4-dichlorophenoxyacetic acid (2,4-D) and a chlorpyrifos metabolite and exposure estimates based on an algorithm from 83 AHS pesticide applications. Correlations between urinary levels of 2,4-D and a chlorpyrifos metabolite and algorithm estimated intensity scores were about 0.4 for 2,4-D (n=64), 0.8 for liquid chlorpyrifos (n=4) and 0.6 for granular chlorpyrifos (n=12). Correlations of urinary levels with kilograms of active ingredient used, duration of application, or number of acres treated were lower and ranged from -0.36 to 0.19. These findings indicate that a priori expert-derived algorithm scores were more closely related to measured urinary levels than individual exposure determinants evaluated here. Estimates of potential bias in relative risks based on the correlations from the AHS/PES indicate that non-differential misclassification of exposure using the algorithm would bias estimates towards the null, but less than that from individual exposure determinants. Although correlations between algorithm scores and urinary levels were quite good (ie, correlations between 0.4 and 0.8), exposure misclassification would still bias relative risk estimates in the AHS towards the null and diminish study power.

Estimating Premorbid Cognitive Abilities in Low-Educated Populations

PubMed Central

Apolinario, Daniel; Brucki, Sonia Maria Dozzi; Ferretti, Renata Eloah de Lucena; Farfel, José Marcelo; Magaldi, Regina Miksian; Busse, Alexandre Leopold; Jacob-Filho, Wilson

2013-01-01

Objective To develop an informant-based instrument that would provide a valid estimate of premorbid cognitive abilities in low-educated populations. Methods A questionnaire was drafted by focusing on the premorbid period with a 10-year time frame. The initial pool of items was submitted to classical test theory and a factorial analysis. The resulting instrument, named the Premorbid Cognitive Abilities Scale (PCAS), is composed of questions addressing educational attainment, major lifetime occupation, reading abilities, reading habits, writing abilities, calculation abilities, use of widely available technology, and the ability to search for specific information. The validation sample was composed of 132 older Brazilian adults from the following three demographically matched groups: normal cognitive aging (n = 72), mild cognitive impairment (n = 33), and mild dementia (n = 27). The scores of a reading test and a neuropsychological battery were adopted as construct criteria. Post-mortem inter-informant reliability was tested in a sub-study with two relatives from each deceased individual. Results All items presented good discriminative power, with corrected item-total correlation varying from 0.35 to 0.74. The summed score of the instrument presented high correlation coefficients with global cognitive function (r = 0.73) and reading skills (r = 0.82). Cronbach's alpha was 0.90, showing optimal internal consistency without redundancy. The scores did not decrease across the progressive levels of cognitive impairment, suggesting that the goal of evaluating the premorbid state was achieved. The intraclass correlation coefficient was 0.96, indicating excellent inter-informant reliability. Conclusion The instrument developed in this study has shown good properties and can be used as a valid estimate of premorbid cognitive abilities in low-educated populations. The applicability of the PCAS, both as an estimate of premorbid intelligence and cognitive reserve, is discussed. PMID:23555894

Environmental and Genetic Factors Explain Differences in Intraocular Scattering.

PubMed

Benito, Antonio; Hervella, Lucía; Tabernero, Juan; Pennos, Alexandros; Ginis, Harilaos; Sánchez-Romera, Juan F; Ordoñana, Juan R; Ruiz-Sánchez, Marcos; Marín, José M; Artal, Pablo

2016-01-01

To study the relative impact of genetic and environmental factors on the variability of intraocular scattering within a classical twin study. A total of 64 twin pairs, 32 monozygotic (MZ) (mean age: 54.9 ± 6.3 years) and 32 dizygotic (DZ) (mean age: 56.4 ± 7.0 years), were measured after a complete ophthalmologic exam had been performed to exclude all ocular pathologies that increase intraocular scatter as cataracts. Intraocular scattering was evaluated by using two different techniques based on a straylight parameter log(S) estimation: a compact optical instrument based in the principle of optical integration and a psychophysical measurement. Intraclass correlation coefficients (ICC) were used as descriptive statistics of twin resemblance, and genetic models were fitted to estimate heritability. No statistically significant difference was found for MZ and DZ groups for age (P = 0.203), best-corrected visual acuity (P = 0.626), cataract gradation (P = 0.701), sex (P = 0.941), optical log(S) (P = 0.386), or psychophysical log(S) (P = 0.568), with only a minor difference in equivalent sphere (P = 0.008). Intraclass correlation coefficients between siblings were similar for scatter parameters: 0.676 in MZ and 0.471 in DZ twins for optical log(S); 0.533 in MZ twins and 0.475 in DZ twins for psychophysical log(S). For equivalent sphere, ICCs were 0.767 in MZ and 0.228 in DZ twins. Conservative estimates of heritability for the measured scattering parameters were 0.39 and 0.20, respectively. Correlations of intraocular scatter (straylight) parameters in the groups of identical and nonidentical twins were similar. Heritability estimates were of limited magnitude, suggesting that genetic and environmental factors determine the variance of ocular straylight in healthy middle-aged adults.

Estimation of the Arrival Time and Duration of a Radio Signal with Unknown Amplitude and Initial Phase

NASA Astrophysics Data System (ADS)

Trifonov, A. P.; Korchagin, Yu. E.; Korol'kov, S. V.

2018-05-01

We synthesize the quasi-likelihood, maximum-likelihood, and quasioptimal algorithms for estimating the arrival time and duration of a radio signal with unknown amplitude and initial phase. The discrepancies between the hardware and software realizations of the estimation algorithm are shown. The characteristics of the synthesized-algorithm operation efficiency are obtained. Asymptotic expressions for the biases, variances, and the correlation coefficient of the arrival-time and duration estimates, which hold true for large signal-to-noise ratios, are derived. The accuracy losses of the estimates of the radio-signal arrival time and duration because of the a priori ignorance of the amplitude and initial phase are determined.

Estimating correlation between multivariate longitudinal data in the presence of heterogeneity.

PubMed

Gao, Feng; Philip Miller, J; Xiong, Chengjie; Luo, Jingqin; Beiser, Julia A; Chen, Ling; Gordon, Mae O

2017-08-17

Estimating correlation coefficients among outcomes is one of the most important analytical tasks in epidemiological and clinical research. Availability of multivariate longitudinal data presents a unique opportunity to assess joint evolution of outcomes over time. Bivariate linear mixed model (BLMM) provides a versatile tool with regard to assessing correlation. However, BLMMs often assume that all individuals are drawn from a single homogenous population where the individual trajectories are distributed smoothly around population average. Using longitudinal mean deviation (MD) and visual acuity (VA) from the Ocular Hypertension Treatment Study (OHTS), we demonstrated strategies to better understand the correlation between multivariate longitudinal data in the presence of potential heterogeneity. Conditional correlation (i.e., marginal correlation given random effects) was calculated to describe how the association between longitudinal outcomes evolved over time within specific subpopulation. The impact of heterogeneity on correlation was also assessed by simulated data. There was a significant positive correlation in both random intercepts (ρ = 0.278, 95% CI: 0.121-0.420) and random slopes (ρ = 0.579, 95% CI: 0.349-0.810) between longitudinal MD and VA, and the strength of correlation constantly increased over time. However, conditional correlation and simulation studies revealed that the correlation was induced primarily by participants with rapid deteriorating MD who only accounted for a small fraction of total samples. Conditional correlation given random effects provides a robust estimate to describe the correlation between multivariate longitudinal data in the presence of unobserved heterogeneity (NCT00000125).

Leverage effect and its causality in the Korea composite stock price index

NASA Astrophysics Data System (ADS)

Lee, Chang-Yong

2012-02-01

In this paper, we investigate the leverage effect and its causality in the time series of the Korea Composite Stock Price Index from November of 1997 to September of 2010. The leverage effect, which can be quantitatively expressed as a negative correlation between past return and future volatility, is measured by using the cross-correlation coefficient of different time lags between the two time series of the return and the volatility. We find that past return and future volatility are negatively correlated and that the cross correlation is moderate and decays over 60 trading days. We also carry out a partial correlation analysis in order to confirm that the negative correlation between past return and future volatility is neither an artifact nor influenced by the traded volume. To determine the causality of the leverage effect within the decay time, we additionally estimate the cross correlation between past volatility and future return. With the estimate, we perform a statistical hypothesis test to demonstrate that the causal relation is in favor of the return influencing the volatility rather than the other way around.

Estimating GATE rainfall with geosynchronous satellite images

NASA Technical Reports Server (NTRS)

Stout, J. E.; Martin, D. W.; Sikdar, D. N.

1979-01-01

A method of estimating GATE rainfall from either visible or infrared images of geosynchronous satellites is described. Rain is estimated from cumulonimbus cloud area by the equation R = a sub 0 A + a sub 1 dA/dt, where R is volumetric rainfall, A cloud area, t time, and a sub 0 and a sub 1 are constants. Rainfall, calculated from 5.3 cm ship radar, and cloud area are measured from clouds in the tropical North Atlantic. The constants a sub 0 and a sub 1 are fit to these measurements by the least-squares method. Hourly estimates by the infrared version of this technique correlate well (correlation coefficient of 0.84) with rain totals derived from composited radar for an area of 100,000 sq km. The accuracy of this method is described and compared to that of another technique using geosynchronous satellite images. It is concluded that this technique provides useful estimates of tropical oceanic rainfall on a convective scale.

Molecular modeling of diffusion coefficient and ionic conductivity of CO2 in aqueous ionic solutions.

PubMed

Garcia-Ratés, Miquel; de Hemptinne, Jean-Charles; Bonet Avalos, Josep; Nieto-Draghi, Carlos

2012-03-08

Mass diffusion coefficients of CO(2)/brine mixtures under thermodynamic conditions of deep saline aquifers have been investigated by molecular simulation. The objective of this work is to provide estimates of the diffusion coefficient of CO(2) in salty water to compensate the lack of experimental data on this property. We analyzed the influence of temperature, CO(2) concentration,and salinity on the diffusion coefficient, the rotational diffusion, as well as the electrical conductivity. We observe an increase of the mass diffusion coefficient with the temperature, but no clear dependence is identified with the salinity or with the CO(2) mole fraction, if the system is overall dilute. In this case, we notice an important dispersion on the values of the diffusion coefficient which impairs any conclusive statement about the effect of the gas concentration on the mobility of CO(2) molecules. Rotational relaxation times for water and CO(2) increase by decreasing temperature or increasing the salt concentration. We propose a correlation for the self-diffusion coefficient of CO(2) in terms of the rotational relaxation time which can ultimately be used to estimate the mutual diffusion coefficient of CO(2) in brine. The electrical conductivity of the CO(2)-brine mixtures was also calculated under different thermodynamic conditions. Electrical conductivity tends to increase with the temperature and salt concentration. However, we do not observe any influence of this property with the CO(2) concentration at the studied regimes. Our results give a first evaluation of the variation of the CO(2)-brine mass diffusion coefficient, rotational relaxation times, and electrical conductivity under the thermodynamic conditions typically encountered in deep saline aquifers.

Conformal perturbation of off-critical correlators in the 3D Ising universality class

NASA Astrophysics Data System (ADS)

Caselle, M.; Costagliola, G.; Magnoli, N.

2016-07-01

Thanks to the impressive progress of conformal bootstrap methods we have now very precise estimates of both scaling dimensions and operator product expansion coefficients for several 3D universality classes. We show how to use this information to obtain similarly precise estimates for off-critical correlators using conformal perturbation. We discuss in particular the ⟨σ (r )σ (0 )⟩ , ⟨ɛ (r )ɛ (0 )⟩ and ⟨σ (r )ɛ (0 )⟩ two-point functions in the high and low temperature regimes of the 3D Ising model and evaluate the leading and next to leading terms in the s =trΔt expansion, where t is the reduced temperature. Our results for ⟨σ (r )σ (0 )⟩ agree both with Monte Carlo simulations and with a set of experimental estimates of the critical scattering function.

Statistical interpretation of pollution data from satellites. [for levels distribution over metropolitan area

NASA Technical Reports Server (NTRS)

Smith, G. L.; Green, R. N.; Young, G. R.

1974-01-01

The NIMBUS-G environmental monitoring satellite has an instrument (a gas correlation spectrometer) onboard for measuring the mass of a given pollutant within a gas volume. The present paper treats the problem: How can this type measurement be used to estimate the distribution of pollutant levels in a metropolitan area. Estimation methods are used to develop this distribution. The pollution concentration caused by a point source is modeled as a Gaussian plume. The uncertainty in the measurements is used to determine the accuracy of estimating the source strength, the wind velocity, diffusion coefficients and source location.

Criterion validity of the Physical Activity Questionnaire for Schoolchildren (PAQ-S) in assessing physical activity levels: the Healthy Growth Study.

PubMed

Manios, Y; Androutsos, O; Moschonis, G; Birbilis, M; Maragkopoulou, K; Giannopoulou, A; Argyri, E; Kourlaba, G

2013-10-01

The aim of this paper was to evaluate the criterion validity of the Physical Activity Questionnaire for Schoolchildren (PAQ-S). The current study is a subcohort of the Healthy Growth Study, a large-scale cross-sectional study. 202 schoolchildren aged 9-13 years from Greece completed the PAQ-S and wore an accelerometer for 4 consecutive days. Time spent moderate (MPA), moderate to vigorous (MVPA) and vigorous (VPA) physical activity was calculated based on PAQ-S and accelerometer data. The average time spent on MPA and MVPA as derived from PAQ-S and from accelerometers were significantly moderately correlated (r=0.462, P<0.001 and r=0.483, P<0.001, respectively). No significant correlation was detected between PAQ-S and accelerometer-measured time spent performing VPA (rho=0.150, P=0.057). Intraclass Correlation Coefficient (ICC) indicated a moderate agreement between PAQ-S and accelerometer in estimating MPA (ICC=0.592, P<0.001) and MVPA (ICC=0.581, P<0.001). Bland-Altman analysis revealed a small mean difference (the "bias"), between the two methods, in estimating MPA, although this difference was found to be significantly higher than zero ("bias"=27.4% of the accelerometer-measured mean score, P=0.006). On the other hand, Bland-Altman analysis revealed a large mean difference in estimating MVPA and VPA ("bias"=84.2% and 357% of the accelerometer-measured mean score for MVPA and VPA, respectively and P<0.001). The high correlation coefficient between the average and difference values between all physical activity scores derived from accelerometers and PAQ-S, indicate a systematic overestimation of physical activity time with increasing physical activity for PAQ-S. The validity of PAQ-S for the estimation of MPA and MVPA was found to be slightly similar self-reported measures for schoolchildren. Therefore, this questionnaire could be used as a tool for physical activity assessment in large population studies.

Estimating 24-h urinary sodium/potassium ratio from casual ('spot') urinary sodium/potassium ratio: the INTERSALT Study.

PubMed

Iwahori, Toshiyuki; Miura, Katsuyuki; Ueshima, Hirotsugu; Chan, Queenie; Dyer, Alan R; Elliott, Paul; Stamler, Jeremiah

2017-10-01

Association between casual and 24-h urinary sodium-to-potassium (Na/K) ratio is well recognized, although it has not been validated in diverse demographic groups. Our aim was to assess utility across and within populations of casual urine to estimate 24-h urinary Na/K ratio using data from the INTERSALT Study. The INTERSALT Study collected cross-sectional standardized data on casual urinary sodium and potassium and also on timed 24-h urinary sodium and potassium for 10 065 individuals from 52 population samples in 32 countries (1985-87). Pearson correlation coefficients and agreement were computed for Na/K ratio of casual urine against 24-h urinary Na/K ratio both at population and individual levels. Pearson correlation coefficients relating means of 24-h urine and casual urine Na/K ratio were r = 0.96 and r = 0.69 in analyses across populations and individuals, respectively. Correlations of casual urine Na/creatinine and K/creatinine ratios with 24-h urinary Na and K excretion, respectively, were lower than correlation of casual and 24-h urinary Na/K ratio in analyses across populations and individuals. The bias estimate with the Bland-Altman method, defined as the difference between Na/K ratio of 24-h urine and casual urine, was approximately 0.4 across both populations and individuals. Spread around, the mean bias was higher for individuals than populations. With appropriate bias correction, casual urine Na/K ratio may be a useful, low-burden alternative method to 24-h urine for estimation of population urinary Na/K ratio. It may also be applicable for assessment of the urinary Na/K ratio of individuals, with use of repeated measurements to reduce measurement error and increase precision. © The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association

Collinear Latent Variables in Multilevel Confirmatory Factor Analysis: A Comparison of Maximum Likelihood and Bayesian Estimations.

PubMed

Can, Seda; van de Schoot, Rens; Hox, Joop

2015-06-01

Because variables may be correlated in the social and behavioral sciences, multicollinearity might be problematic. This study investigates the effect of collinearity manipulated in within and between levels of a two-level confirmatory factor analysis by Monte Carlo simulation. Furthermore, the influence of the size of the intraclass correlation coefficient (ICC) and estimation method; maximum likelihood estimation with robust chi-squares and standard errors and Bayesian estimation, on the convergence rate are investigated. The other variables of interest were rate of inadmissible solutions and the relative parameter and standard error bias on the between level. The results showed that inadmissible solutions were obtained when there was between level collinearity and the estimation method was maximum likelihood. In the within level multicollinearity condition, all of the solutions were admissible but the bias values were higher compared with the between level collinearity condition. Bayesian estimation appeared to be robust in obtaining admissible parameters but the relative bias was higher than for maximum likelihood estimation. Finally, as expected, high ICC produced less biased results compared to medium ICC conditions.

Utility of Fite-Faraco stain for both mast cell count and bacillary index in skin biopsies of leprosy patients.

PubMed

Chatura, K R; Sangeetha, S

2012-01-01

To assess the utility of a single stain for both mast cell count and bacillary index (BI), 50 skin-biopsie patients were stained with Fite-Faraco (FF) stain, viewed under oil immersion and BI calculated using the Ridley's logarithmic scale, and mast cells counted as the number of cells per mm2. Mean mast cell count per mm2 at the tuberculoid pole was lowest in TT 7.9 and highest in BT 14.23. At the lepromatous end, it was highest in BL 9.21, while in LL it was 8.23. Highest counts were seen in the borderline types overall. The correlation coefficient between histopathological diagnosis and BI is 0.822 which is a positive correlation to a significant degree. The correlation coefficient between histopathological diagnosis and mast cell count was found to be -0.17, which is a negative correlation but not to a significant degree. FF stain was utilised to visualise both bacilli for estimation of BI and mast cells for mast cell count, a seldom attempted feature in literature.

Dealing with Item Nonresponse in Large-Scale Cognitive Assessments: The Impact of Missing Data Methods on Estimated Explanatory Relationships

ERIC Educational Resources Information Center

Köhler, Carmen; Pohl, Steffi; Carstensen, Claus H.

2017-01-01

Competence data from low-stakes educational large-scale assessment studies allow for evaluating relationships between competencies and other variables. The impact of item-level nonresponse has not been investigated with regard to statistics that determine the size of these relationships (e.g., correlations, regression coefficients). Classical…

Iterative Ellipsoidal Trimming.

DTIC Science & Technology

1980-02-11

to above. Iterative ellipsoidal trimming has been investigated before by other statisticians, most notably by Gnanadesikan and his coworkers...J., Gnanadesikan R., and Kettenring, J. R. (1975). "Robust estimation and outlier detection with correlation coefficients." Biometrika. 62, 531-45. [6...Duda, Richard, and Hart, Peter (1973). Pattern Classification and Scene Analysis. Wiley, New York. [7] Gnanadesikan , R. (1977). Methods for

Bayesian power spectrum inference with foreground and target contamination treatment

NASA Astrophysics Data System (ADS)

Jasche, J.; Lavaux, G.

2017-10-01

This work presents a joint and self-consistent Bayesian treatment of various foreground and target contaminations when inferring cosmological power spectra and three-dimensional density fields from galaxy redshift surveys. This is achieved by introducing additional block-sampling procedures for unknown coefficients of foreground and target contamination templates to the previously presented ARES framework for Bayesian large-scale structure analyses. As a result, the method infers jointly and fully self-consistently three-dimensional density fields, cosmological power spectra, luminosity-dependent galaxy biases, noise levels of the respective galaxy distributions, and coefficients for a set of a priori specified foreground templates. In addition, this fully Bayesian approach permits detailed quantification of correlated uncertainties amongst all inferred quantities and correctly marginalizes over observational systematic effects. We demonstrate the validity and efficiency of our approach in obtaining unbiased estimates of power spectra via applications to realistic mock galaxy observations that are subject to stellar contamination and dust extinction. While simultaneously accounting for galaxy biases and unknown noise levels, our method reliably and robustly infers three-dimensional density fields and corresponding cosmological power spectra from deep galaxy surveys. Furthermore, our approach correctly accounts for joint and correlated uncertainties between unknown coefficients of foreground templates and the amplitudes of the power spectrum. This effect amounts to correlations and anti-correlations of up to 10 per cent across wide ranges in Fourier space.

Development of estimation method for crop yield using MODIS satellite imagery data and process-based model for corn and soybean in US Corn-Belt region

NASA Astrophysics Data System (ADS)

Lee, J.; Kang, S.; Jang, K.; Ko, J.; Hong, S.

2012-12-01

Crop productivity is associated with the food security and hence, several models have been developed to estimate crop yield by combining remote sensing data with carbon cycle processes. In present study, we attempted to estimate crop GPP and NPP using algorithm based on the LUE model and a simplified respiration model. The state of Iowa and Illinois was chosen as the study site for estimating the crop yield for a period covering the 5 years (2006-2010), as it is the main Corn-Belt area in US. Present study focuses on developing crop-specific parameters for corn and soybean to estimate crop productivity and yield mapping using satellite remote sensing data. We utilized a 10 km spatial resolution daily meteorological data from WRF to provide cloudy-day meteorological variables but in clear-say days, MODIS-based meteorological data were utilized to estimate daily GPP, NPP, and biomass. County-level statistics on yield, area harvested, and productions were used to test model predicted crop yield. The estimated input meteorological variables from MODIS and WRF showed with good agreements with the ground observations from 6 Ameriflux tower sites in 2006. For examples, correlation coefficients ranged from 0.93 to 0.98 for Tmin and Tavg ; from 0.68 to 0.85 for daytime mean VPD; from 0.85 to 0.96 for daily shortwave radiation, respectively. We developed county-specific crop conversion coefficient, i.e. ratio of yield to biomass on 260 DOY and then, validated the estimated county-level crop yield with the statistical yield data. The estimated corn and soybean yields at the county level ranged from 671 gm-2 y-1 to 1393 gm-2 y-1 and from 213 gm-2 y-1 to 421 gm-2 y-1, respectively. The county-specific yield estimation mostly showed errors less than 10%. Furthermore, we estimated crop yields at the state level which were validated against the statistics data and showed errors less than 1%. Further analysis for crop conversion coefficient was conducted for 200 DOY and 280 DOY. For the case of 280 DOY, Crop yield estimation showed better accuracy for soybean at county level. Though the case of 200 DOY resulted in less accuracy (i.e. 20% mean bias), it provides a useful tool for early forecasting of crop yield. We improved the spatial accuracy of estimated crop yield at county level by developing county-specific crop conversion coefficient. Our results indicate that the aboveground crop biomass can be estimated successfully with the simple LUE and respiration models combined with MODIS data and then, county-specific conversion coefficient can be different with each other across different counties. Hence, applying region-specific conversion coefficient is necessary to estimate crop yield with better accuracy.

Correlation between pre-pregnancy body mass index and maternal visceral adiposity with fetal biometry during the second trimester.

PubMed

Lopes, Karina R M; Souza, Alex Sandro R; Figueiroa, José N; Alves, João Guilherme B

2017-08-01

To determine the correlation between pre-pregnancy body mass index (BMI) and maternal visceral adiposity with fetal biometry during the second trimester. A cross-sectional observational study was conducted among pregnant women who received prenatal care at a center in Recife, Brazil, between October 3, 2011, and September 27, 2013. Pre-pregnancy BMI was determined at the first prenatal care visit. Maternal visceral adiposity and fetal biometry were measured at the same ultrasonography session. The associations between maternal and fetal variables were evaluated using the Pearson correlation coefficient (R). The Student t test was used to test the null hypothesis of adjusted correlation coefficients. Overall, 740 women were included. No correlation was found between pre-pregnancy BMI and any of the fetal biometric variables assessed. By contrast, maternal visceral adiposity positively correlated with fetal abdominal circumference (R=0.529), estimated fetal weight (R=0.524), head circumference (R=0.521), femur length (R=0.521), and biparietal diameter (R=0.524; P<0.001 for all fetal variables). These findings remained statistically significant after controlling for pregnancy length. Maternal visceral adiposity, but not pre-pregnancy BMI, positively correlated with fetal biometry during the second trimester. © 2017 International Federation of Gynecology and Obstetrics.

A Study of Correlation of Various Growth Indicators with Chronological Age.

PubMed

Singh, Sarabjeet; Sandhu, Navreet; Puri, Taruna; Gulati, Ritika; Kashyap, Rita

2015-01-01

The aim of this study was to assess the relationship of chronological age with cervical vertebrae skeletal maturation, frontal sinus width and antegonial notch depth and a correlation, if any, among the three variables. The samples were derived from lateral cephalometric radiographs of 80 subjects (40 males, 40 females; age range: 10 to 19 years). Cervical vertebral development was evaluated by the method of Hassel and Farman, frontal sinus width was measured by the method described by Ertürk and antegonial notch depth as described by Singer et al. The Pearson's correlation coefficients were estimated to assess the relationship of chronological age with cervical vertebrae skeletal maturation, frontal sinus width and antegonial notch depth. The Pearson's correlation coefficient were 0.855 (p < 0.001) between chronological age and cervical vertebrae skeletal maturation, and 0.333 (p < 0.001) between chronological age and frontal sinus width. A highly significant positive correlation was found between chronological age and cervical vertebrae skeletal maturation, and between chronological age and frontal sinus width. Nonsignificant correlation was found between chronological age and antegonial notch depth. How to cite this article: Singh S, Sandhu N, Puri T, Gulati R, Kashyap R. A Study of Correlation of Various Growth Indicators with Chronological Age. Int J Clin Pediatr Dent 2015;8(3): 190-195.

Regressed relations for forced convection heat transfer in a direct injection stratified charge rotary engine

NASA Technical Reports Server (NTRS)

Lee, Chi M.; Schock, Harold J.

1988-01-01

Currently, the heat transfer equation used in the rotary combustion engine (RCE) simulation model is taken from piston engine studies. These relations have been empirically developed by the experimental input coming from piston engines whose geometry differs considerably from that of the RCE. The objective of this work was to derive equations to estimate heat transfer coefficients in the combustion chamber of an RCE. This was accomplished by making detailed temperature and pressure measurements in a direct injection stratified charge (DISC) RCE under a range of conditions. For each specific measurement point, the local gas velocity was assumed equal to the local rotor tip speed. Local physical properties of the fluids were then calculated. Two types of correlation equations were derived and are described in this paper. The first correlation expresses the Nusselt number as a function of the Prandtl number, Reynolds number, and characteristic temperature ratio; the second correlation expresses the forced convection heat transfer coefficient as a function of fluid temperature, pressure and velocity.

Sample size requirements for the design of reliability studies: precision consideration.

PubMed

Shieh, Gwowen

2014-09-01

In multilevel modeling, the intraclass correlation coefficient based on the one-way random-effects model is routinely employed to measure the reliability or degree of resemblance among group members. To facilitate the advocated practice of reporting confidence intervals in future reliability studies, this article presents exact sample size procedures for precise interval estimation of the intraclass correlation coefficient under various allocation and cost structures. Although the suggested approaches do not admit explicit sample size formulas and require special algorithms for carrying out iterative computations, they are more accurate than the closed-form formulas constructed from large-sample approximations with respect to the expected width and assurance probability criteria. This investigation notes the deficiency of existing methods and expands the sample size methodology for the design of reliability studies that have not previously been discussed in the literature.

Performance Analysis of Occurrences January 1, 2011-December 31, 2011

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

Ludwig, M

2012-03-16

This report documents the analysis of the occurrences during the period January 1, 2011 through December 31, 2011. The report compares LLNL occurrences by reporting criteria and significance category to see if LLNL is reporting occurrences along similar percentages as other DOE sites. The three-year trends are analyzed. It does not include the analysis of the causes or the lessons learned from the occurrences, as they are analyzed separately. The number and types of occurrences that LLNL reports to DOE varies over time. This variation can be attributed to normally occurring changes in frequency; DOE's or LLNL's heightened interest inmore » a particular subject area; changes in LLNL processes; or emerging problems. Since all of the DOE sites use the same reporting criteria, it is helpful to understand if LLNL is consistent with or diverging from reporting at other sites. This section compares the normalized number of occurrences reported by LLNL and other DOE sites. In order to compare LLNL occurrence reports to occurrence reports from other DOE sites, we normalized (or standardized) the data from the sites. DOE sites vary widely in their budgets, populations, and scope of work and these variations may affect reporting frequency. In addition, reports are required for a wide range of occurrence types, some of which may not be applicable to all DOE sites. For example, one occurrence reporting group is Group 3, Nuclear Safety Basis, and not all sites have nuclear operations. Because limited information is available for all sites, the sites were normalized based on best available information. Site effort hours were extracted from the DOE Computerized Accident Incident Reporting System (CAIRS) and used to normalize (or standardize) the number of occurrences by site. Effort hours are those hours that employees normally work and do not include vacation, holiday hours etc. Sites are responsible for calculating their effort hours and ensuring entry into CAIRS. Out of the 30 DOE sites that reported occurrences into ORPS during January 2011 through December 2011, 28 had effort hours available in CAIRS. Two sites had not submitted effort hours data to CAIRS as of the time data was pulled for this report. In those two cases, third quarter data was used as an estimate of fourth quarter data. The use of estimated data may introduce minor errors in the average, median, and Pearson calculations. Using the effort hours and the frequency of occurrences by site, a rate of occurrence frequency per 100 FTE workers was calculated. This rate is similar to the injury/illness frequency rate: the number of injury/illness cases per 100 FTE workers. To validate that this rate was appropriate to use, we compared the effort hours and the frequency of occurrences by site to determine if a relationship exists between the two, e.g. the more effort hours a site has, the more occurrences they tend to have. This hypothesis was tested using the Pearson Correlation Coefficient Test. The correlation coefficient measures the strength of the linear relationship between effort hours and occurrence frequency. The Pearson Correlation Coefficient Test will determine if the true correlation coefficient is equal to zero (no relationship exists), or if the correlation coefficient is not equal to zero (a relationship exists). Values approaching 1.00 show a more positive correlation. Simple linear regression was also used to display a trend line and to test if a one-way relationship exists between effort hours predicting the number of occurrences a site will have. Using the Pearson Correlation test, for the NNSA sites, effort hours and the number of occurrences are significantly and positively correlated with a correlation coefficient of 0.90, as was also seen in the previous report (correlation coefficient of 0.67). All DOE sites are positively correlated with a coefficient of 0.85. As the effort hours increase, so does the number of occurrences and vice versa. Based on the results of the simple linear regression, effort hours were found to predict the number of occurrences.« less

Reliability Estimation of Aero-engine Based on Mixed Weibull Distribution Model

NASA Astrophysics Data System (ADS)

Yuan, Zhongda; Deng, Junxiang; Wang, Dawei

2018-02-01

Aero-engine is a complex mechanical electronic system, based on analysis of reliability of mechanical electronic system, Weibull distribution model has an irreplaceable role. Till now, only two-parameter Weibull distribution model and three-parameter Weibull distribution are widely used. Due to diversity of engine failure modes, there is a big error with single Weibull distribution model. By contrast, a variety of engine failure modes can be taken into account with mixed Weibull distribution model, so it is a good statistical analysis model. Except the concept of dynamic weight coefficient, in order to make reliability estimation result more accurately, three-parameter correlation coefficient optimization method is applied to enhance Weibull distribution model, thus precision of mixed distribution reliability model is improved greatly. All of these are advantageous to popularize Weibull distribution model in engineering applications.

Global and system-specific resting-state fMRI fluctuations are uncorrelated: principal component analysis reveals anti-correlated networks.

PubMed

Carbonell, Felix; Bellec, Pierre; Shmuel, Amir

2011-01-01

The influence of the global average signal (GAS) on functional-magnetic resonance imaging (fMRI)-based resting-state functional connectivity is a matter of ongoing debate. The global average fluctuations increase the correlation between functional systems beyond the correlation that reflects their specific functional connectivity. Hence, removal of the GAS is a common practice for facilitating the observation of network-specific functional connectivity. This strategy relies on the implicit assumption of a linear-additive model according to which global fluctuations, irrespective of their origin, and network-specific fluctuations are super-positioned. However, removal of the GAS introduces spurious negative correlations between functional systems, bringing into question the validity of previous findings of negative correlations between fluctuations in the default-mode and the task-positive networks. Here we present an alternative method for estimating global fluctuations, immune to the complications associated with the GAS. Principal components analysis was applied to resting-state fMRI time-series. A global-signal effect estimator was defined as the principal component (PC) that correlated best with the GAS. The mean correlation coefficient between our proposed PC-based global effect estimator and the GAS was 0.97±0.05, demonstrating that our estimator successfully approximated the GAS. In 66 out of 68 runs, the PC that showed the highest correlation with the GAS was the first PC. Since PCs are orthogonal, our method provides an estimator of the global fluctuations, which is uncorrelated to the remaining, network-specific fluctuations. Moreover, unlike the regression of the GAS, the regression of the PC-based global effect estimator does not introduce spurious anti-correlations beyond the decrease in seed-based correlation values allowed by the assumed additive model. After regressing this PC-based estimator out of the original time-series, we observed robust anti-correlations between resting-state fluctuations in the default-mode and the task-positive networks. We conclude that resting-state global fluctuations and network-specific fluctuations are uncorrelated, supporting a Resting-State Linear-Additive Model. In addition, we conclude that the network-specific resting-state fluctuations of the default-mode and task-positive networks show artifact-free anti-correlations.

A linear least squares approach for evaluation of crack tip stress field parameters using DIC

NASA Astrophysics Data System (ADS)

Harilal, R.; Vyasarayani, C. P.; Ramji, M.

2015-12-01

In the present work, an experimental study is carried out to estimate the mixed-mode stress intensity factors (SIF) for different cracked specimen configurations using digital image correlation (DIC) technique. For the estimation of mixed-mode SIF's using DIC, a new algorithm is proposed for the extraction of crack tip location and coefficients in the multi-parameter displacement field equations. From those estimated coefficients, SIF could be extracted. The required displacement data surrounding the crack tip has been obtained using 2D-DIC technique. An open source 2D DIC software Ncorr is used for the displacement field extraction. The presented methodology has been used to extract mixed-mode SIF's for specimen configurations like single edge notch (SEN) specimen and centre slant crack (CSC) specimens made out of Al 2014-T6 alloy. The experimental results have been compared with the analytical values and they are found to be in good agreement, thereby confirming the accuracy of the algorithm being proposed.

Consistent Partial Least Squares Path Modeling via Regularization

PubMed Central

Jung, Sunho; Park, JaeHong

2018-01-01

Partial least squares (PLS) path modeling is a component-based structural equation modeling that has been adopted in social and psychological research due to its data-analytic capability and flexibility. A recent methodological advance is consistent PLS (PLSc), designed to produce consistent estimates of path coefficients in structural models involving common factors. In practice, however, PLSc may frequently encounter multicollinearity in part because it takes a strategy of estimating path coefficients based on consistent correlations among independent latent variables. PLSc has yet no remedy for this multicollinearity problem, which can cause loss of statistical power and accuracy in parameter estimation. Thus, a ridge type of regularization is incorporated into PLSc, creating a new technique called regularized PLSc. A comprehensive simulation study is conducted to evaluate the performance of regularized PLSc as compared to its non-regularized counterpart in terms of power and accuracy. The results show that our regularized PLSc is recommended for use when serious multicollinearity is present. PMID:29515491

Modified Regression Correlation Coefficient for Poisson Regression Model

NASA Astrophysics Data System (ADS)

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).

Molecular radiotherapy: the NUKFIT software for calculating the time-integrated activity coefficient.

PubMed

Kletting, P; Schimmel, S; Kestler, H A; Hänscheid, H; Luster, M; Fernández, M; Bröer, J H; Nosske, D; Lassmann, M; Glatting, G

2013-10-01

Calculation of the time-integrated activity coefficient (residence time) is a crucial step in dosimetry for molecular radiotherapy. However, available software is deficient in that it is either not tailored for the use in molecular radiotherapy and/or does not include all required estimation methods. The aim of this work was therefore the development and programming of an algorithm which allows for an objective and reproducible determination of the time-integrated activity coefficient and its standard error. The algorithm includes the selection of a set of fitting functions from predefined sums of exponentials and the choice of an error model for the used data. To estimate the values of the adjustable parameters an objective function, depending on the data, the parameters of the error model, the fitting function and (if required and available) Bayesian information, is minimized. To increase reproducibility and user-friendliness the starting values are automatically determined using a combination of curve stripping and random search. Visual inspection, the coefficient of determination, the standard error of the fitted parameters, and the correlation matrix are provided to evaluate the quality of the fit. The functions which are most supported by the data are determined using the corrected Akaike information criterion. The time-integrated activity coefficient is estimated by analytically integrating the fitted functions. Its standard error is determined assuming Gaussian error propagation. The software was implemented using MATLAB. To validate the proper implementation of the objective function and the fit functions, the results of NUKFIT and SAAM numerical, a commercially available software tool, were compared. The automatic search for starting values was successfully tested for reproducibility. The quality criteria applied in conjunction with the Akaike information criterion allowed the selection of suitable functions. Function fit parameters and their standard error estimated by using SAAM numerical and NUKFIT showed differences of <1%. The differences for the time-integrated activity coefficients were also <1% (standard error between 0.4% and 3%). In general, the application of the software is user-friendly and the results are mathematically correct and reproducible. An application of NUKFIT is presented for three different clinical examples. The software tool with its underlying methodology can be employed to objectively and reproducibly estimate the time integrated activity coefficient and its standard error for most time activity data in molecular radiotherapy.

Blood Pressure Estimation Using Pulse Transit Time From Bioimpedance and Continuous Wave Radar.

PubMed

Buxi, Dilpreet; Redout, Jean-Michel; Yuce, Mehmet Rasit

2017-04-01

We have developed and tested a new architecture for pulse transit time (PTT) estimation at the central arteries using electrical bioimpedance, electrocardiogram, and continuous wave radar to estimate cuffless blood pressure. A transmitter and receiver antenna are placed at the sternum to acquire the arterial pulsation at the aortic arch. A four-electrode arrangement across the shoulders acquires arterial pulse across the carotid and subclavian arteries from bioimpedance as well as a bipolar lead I electrocardiogram. The PTT and pulse arrival times (PATs) are measured on six healthy male subjects during exercise on a bicycle ergometer. Using linear regression, the estimated PAT and PTT values are calibrated to the systolic and mean as well as diastolic blood pressure from an oscillometric device. For all subjects, the Pearson correlation coefficients for PAT-SBP and PTT-SBP are -0.66 (p = 0.001) and -0.48 (p = 0.0029), respectively. Correlation coefficients for individual subjects ranged from -0.54 to -0.9 and -0.37 to -0.95, respectively. The proposed system architecture is promising in estimating cuffless arterial blood pressure at the central, proximal arteries, which obey the Moens-Korteweg equation more closely when compared to peripheral arteries. An important advantage of PTT from the carotid and subclavian arteries is that the PTT over the central elastic arteries is measured instead of the peripheral arteries, which potentially reduces the changes in PTT due to vasomotion. Furthermore, the sensors can be completely hidden under a patients clothes, making them more acceptable by the patient for ambulatory monitoring.

Clinical and Pathological Staging Validation in the Eighth Edition of the TNM Classification for Lung Cancer: Correlation between Solid Size on Thin-Section Computed Tomography and Invasive Size in Pathological Findings in the New T Classification.

PubMed

Aokage, Keiju; Miyoshi, Tomohiro; Ishii, Genichiro; Kusumoto, Masahiro; Nomura, Shogo; Katsumata, Shinya; Sekihara, Keigo; Hishida, Tomoyuki; Tsuboi, Masahiro

2017-09-01

The aim of this study was to validate the new eighth edition of the TNM classification and to elucidate whether radiological solid size corresponds to pathological invasive size incorporated in this T factor. We analyzed the data on 1792 patients who underwent complete resection from 2003 to 2011 at the National Cancer Center Hospital East, Japan. We reevaluated preoperative thin-section computed tomography (TSCT) to determine solid size and pathological invasive size using the fourth edition of the WHO classification and reclassified them according to the new TNM classification. The discriminative power of survival curves by the seventh edition was compared with that by the eighth edition by using concordance probability estimates and Akaike's information criteria calculated using a univariable Cox regression model. Pearson's correlation coefficient was calculated to elucidate the correlation between radiological solid size using TSCT and pathological invasive size. The overall survival curves in the eighth edition were well distinct at each clinical and pathological stage. The 5-year survival rates of patients with clinical and pathological stage 0 newly defined were both 100%. The concordance probability estimate and Akaike's information criterion values of the eighth edition were higher than those of the seventh edition in discriminatory power for overall survival. Solid size on TSCT scan and pathological invasive size showed a positive linear relationship, and Pearson's correlation coefficient was calculated as 0.83, which indicated strong correlation. This TNM classification will be feasible regarding patient survival, and radiological solid size correlates significantly with pathological invasive size as a new T factor. Copyright © 2017 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

Overton's Rule Helps To Estimate the Penetration of Anti-Infectives into Patients' Cerebrospinal Fluid

PubMed Central

Djukic, Marija; Munz, Martin; Sörgel, Fritz; Holzgrabe, Ulrike; Eiffert, Helmut

2012-01-01

In 1900, Ernst Overton found that the entry of anilin dyes through the cell membranes of living cells depended on the lipophilicity of the dyes. The brain is surrounded by barriers consisting of lipid layers that possess several inward and outward active transport systems. In the absence of meningeal inflammation, the cerebrospinal fluid (CSF) penetration of anti-infectives in humans estimated by the ratio of the area under the concentration-time curve (AUC) in CSF (AUCCSF) to that in serum (AUCCSF/AUCS) correlated positively with the lipid-water partition coefficient at pH 7.0 (log D) (Spearman's rank correlation coefficient rS = 0.40; P = 0.01) and negatively with the molecular mass (MM) (rS = −0.33; P = 0.04). The ratio of AUCCSF to the AUC of the fraction in serum that was not bound (AUCCSF/AUCS,free) strongly correlated with log D (rS = 0.67; P < 0.0001). In the presence of meningeal inflammation, AUCCSF/AUCS also correlated positively with log D (rS = 0.46; P = 0.002) and negatively with the MM (rS = −0.37; P = 0.01). The correlation of AUCCSF/AUCS,free with log D (rS = 0.66; P < 0.0001) was as strong as in the absence of meningeal inflammation. Despite these clear correlations, Overton's rule was able to explain only part of the differences in CSF penetration of the individual compounds. The site of CSF withdrawal (lumbar versus ventricular CSF), age of the patients, underlying diseases, active transport, and alterations in the pharmacokinetics by comedications also appeared to strongly influence the CSF penetration of the drugs studied. PMID:22106225

Validation of a simplified food frequency questionnaire for the assessment of dietary habits in Iranian adults: Isfahan Healthy Heart Program, Iran.

PubMed

Mohammadifard, Noushin; Sajjadi, Firouzeh; Maghroun, Maryam; Alikhasi, Hassan; Nilforoushzadeh, Farzaneh; Sarrafzadegan, Nizal

2015-03-01

Dietary assessment is the first step of dietary modification in community-based interventional programs. This study was performed to validate a simple food frequency questionnaire (SFFQ) for assessment of selected food items in epidemiological studies with a large sample size as well as community trails. This validation study was carried out on 264 healthy adults aged ≥ 41 years old living in 3 district central of Iran, including Isfahan, Najafabad, and Arak. Selected food intakes were assessed using a 48-item food frequency questionnaire (FFQ). The FFQ was interviewer-administered, which was completed twice; at the beginning of the study and 2 weeks thereafter. The validity of this SFFQ was examined compared to estimated amount by single 24 h dietary recall and 2 days dietary record. Validation of the FFQ was determined using Spearman correlation coefficients between daily frequency consumption of food groups as assessed by the FFQ and the qualitative amount of daily food groups intake accessed by dietary reference method was applied to evaluate validity. Intraclass correlation coefficients (ICC) were used to determine the reproducibility. Spearman correlation coefficient between the estimated amount of food groups intake by examined and reference methods ranged from 0.105 (P = 0.378) in pickles to 0.48 (P < 0.001) in plant protein. ICC for reproducibility of FFQ were between 0.47-0.69 in different food groups (P < 0.001). The designed SFFQ has a good relative validity and reproducibility for assessment of selected food groups intake. Thus, it can serve as a valid tool in epidemiological studies and clinical trial with large participants.

[Correlation coefficient-based classification method of hydrological dependence variability: With auto-regression model as example].

PubMed

Zhao, Yu Xi; Xie, Ping; Sang, Yan Fang; Wu, Zi Yi

2018-04-01

Hydrological process evaluation is temporal dependent. Hydrological time series including dependence components do not meet the data consistency assumption for hydrological computation. Both of those factors cause great difficulty for water researches. Given the existence of hydrological dependence variability, we proposed a correlationcoefficient-based method for significance evaluation of hydrological dependence based on auto-regression model. By calculating the correlation coefficient between the original series and its dependence component and selecting reasonable thresholds of correlation coefficient, this method divided significance degree of dependence into no variability, weak variability, mid variability, strong variability, and drastic variability. By deducing the relationship between correlation coefficient and auto-correlation coefficient in each order of series, we found that the correlation coefficient was mainly determined by the magnitude of auto-correlation coefficient from the 1 order to p order, which clarified the theoretical basis of this method. With the first-order and second-order auto-regression models as examples, the reasonability of the deduced formula was verified through Monte-Carlo experiments to classify the relationship between correlation coefficient and auto-correlation coefficient. This method was used to analyze three observed hydrological time series. The results indicated the coexistence of stochastic and dependence characteristics in hydrological process.

Are Tornadoes Getting Stronger?

NASA Astrophysics Data System (ADS)

Elsner, J.; Jagger, T.

2013-12-01

A cumulative logistic model for tornado damage category is developed and examined. Damage path length and width are significantly correlated to the odds of a tornado receiving the next highest damage category. Given values for the cube root of path length and square root of path width, the model predicts a probability for each category. The length and width coefficients are insensitive to the switch to the Enhanced Fujita (EF) scale and to distance from nearest city although these variables are statistically significant in the model. The width coefficient is sensitive to whether or not the tornado caused at least one fatality. This is likely due to the fact that the dimensions and characteristics of the damage path for such events are always based on ground surveys. The model predicted probabilities across the categories are then multiplied by the center wind speed from the categorical EF scale to obtain an estimate of the highest tornado wind speed on a continuous scale in units of meters per second. The estimated wind speeds correlate at a level of .82 (.46, .95) [95% confidence interval] to wind speeds estimated independently from a doppler radar calibration. The estimated wind speeds allow analyses to be done on the tornado database that are not possible with the categorical scale. The modeled intensities can be used in climatology and in environmental and engineering applications. More work needs to be done to understand the upward trends in path length and width. The increases lead to an apparent increase in tornado intensity across all EF categories.

Validation of multi-frequency bioelectrical impedance analysis versus dual-energy X-ray absorptiometry to measure body fat percentage in overweight/obese Colombian adults.

PubMed

Ramírez-Vélez, Robinson; Tordecilla-Sanders, Alejandra; Correa-Bautista, Jorge Enrique; González-Ruíz, Katherine; González-Jiménez, Emilio; Triana-Reina, Hector Reynaldo; García-Hermoso, Antonio; Schmidt-RioValle, Jacqueline

2018-01-01

To verify the validity of multi-frequency bioelectrical impedance analysis (mBCA) for predicting body fat percentage (BF%) in overweight/obese adults using dual-energy X-ray absorptiometry (DXA) as the reference method. Forty-eight adults participated (54% women, mean age = 41.0 ± 7.3 years old). The Pearson's correlation coefficient was used to evaluate the correlation between BIA and BF% assessed by DXA. The concordance between BF% measured by both methods was obtained with Lin's concordance correlation coefficient and Bland-Altman difference plots. Measures of BF% were estimated as 39.0 (SD = 6.1) and 38.3 (SD = 6.5) using DXA and mBCA, respectively. The Pearson's correlation coefficient reflected a strong correlation (r =.921, P = .001). The paired t-test showed a significant mean difference between these methods for obese men BF% of -0.6 [(SD 1.95; 95% CI = -4.0 to 3.0), P =.037]. Overall, the bias of the mBCA was -0.6 [(SD 2.2; 95% CI = -5.0 to 3.7), P =.041], which indicated that the mBCA method significantly underestimated BF% in comparison to the reference method. Finally, in both genders, Lin's concordance correlation coefficient showed a strong agreement. More specifically the DXA value was ρc = 0.943 (95% CI = 0.775 to 0.950) and the mBCA value was ρc = 0.948 (95% CI = 0.778 to 0.978). Our analysis showed a strong agreement between the two methods as reflected in the range of BF%. These results show that mBCA and DXA are comparable methods for measuring body composition with higher body fat percentages. However, due to broad limits of agreement, we can only recommend mBCA for groups of populations. © 2017 Wiley Periodicals, Inc.

Improving Global Models of Remotely Sensed Ocean Chlorophyll Content Using Partial Least Squares and Geographically Weighted Regression

NASA Astrophysics Data System (ADS)

Gholizadeh, H.; Robeson, S. M.

2015-12-01

Empirical models have been widely used to estimate global chlorophyll content from remotely sensed data. Here, we focus on the standard NASA empirical models that use blue-green band ratios. These band ratio ocean color (OC) algorithms are in the form of fourth-order polynomials and the parameters of these polynomials (i.e. coefficients) are estimated from the NASA bio-Optical Marine Algorithm Data set (NOMAD). Most of the points in this data set have been sampled from tropical and temperate regions. However, polynomial coefficients obtained from this data set are used to estimate chlorophyll content in all ocean regions with different properties such as sea-surface temperature, salinity, and downwelling/upwelling patterns. Further, the polynomial terms in these models are highly correlated. In sum, the limitations of these empirical models are as follows: 1) the independent variables within the empirical models, in their current form, are correlated (multicollinear), and 2) current algorithms are global approaches and are based on the spatial stationarity assumption, so they are independent of location. Multicollinearity problem is resolved by using partial least squares (PLS). PLS, which transforms the data into a set of independent components, can be considered as a combined form of principal component regression (PCR) and multiple regression. Geographically weighted regression (GWR) is also used to investigate the validity of spatial stationarity assumption. GWR solves a regression model over each sample point by using the observations within its neighbourhood. PLS results show that the empirical method underestimates chlorophyll content in high latitudes, including the Southern Ocean region, when compared to PLS (see Figure 1). Cluster analysis of GWR coefficients also shows that the spatial stationarity assumption in empirical models is not likely a valid assumption.

Salting-out effect in aqueous NaCl solutions: trends with size and polarity of solute molecules.

PubMed

Endo, Satoshi; Pfennigsdorff, Andrea; Goss, Kai-Uwe

2012-02-07

Salting-out in aqueous NaCl solutions is relevant for the environmental behavior of organic contaminants. In this study, Setschenow (or salting-out) coefficients (K(s) [M(-1)]) for 43 diverse neutral compounds in NaCl solutions were measured using a shared headspace passive dosing method and a negligible depletion solid phase microextraction technique. The results were used to calibrate and evaluate estimation models for K(s). The molar volume of the solute correlated only moderately with K(s) (R(2) = 0.49, SD = 0.052). The polyparameter linear free energy relationship (pp-LFER) model that uses five compound descriptors resulted in a more accurate fit to our data (R(2) = 0.83, SD = 0.031). The pp-LFER analysis revealed that Na(+) and Cl(-) in aqueous solutions increase the cavity formation energy cost and the polar interaction energies toward neutral organic solutes. Accordingly, the salting-out effect increases with the size and decreases with the polarity of the solute molecule. COSMO-RS, a quantum mechanics-based fully predictive model, generally overpredicted the experimental K(s), but the predicted values were moderately correlated with the experimental values (R(2) = 0.66, SD = 0.042). Literature data (n = 93) were predicted by the calibrated pp-LFER and COSMO-RS models with root mean squared errors of 0.047 and 0.050, respectively. This study offers prediction models to estimate K(s), allowing implementation of the salting-out effect in contaminant fate models, linkage of various partition coefficients (such as air-water, sediment-water, and extraction phase-water partition coefficients) measured for fresh water and seawater, and estimation of enhancement of extraction efficiency in analytical procedures.

Global estimation of long-term persistence in annual river runoff

NASA Astrophysics Data System (ADS)

Markonis, Y.; Moustakis, Y.; Nasika, C.; Sychova, P.; Dimitriadis, P.; Hanel, M.; Máca, P.; Papalexiou, S. M.

2018-03-01

Long-term persistence (LTP) of annual river runoff is a topic of ongoing hydrological research, due to its implications to water resources management. Here, we estimate its strength, measured by the Hurst coefficient H, in 696 annual, globally distributed, streamflow records with at least 80 years of data. We use three estimation methods (maximum likelihood estimator, Whittle estimator and least squares variance) resulting in similar mean values of H close to 0.65. Subsequently, we explore potential factors influencing H by two linear (Spearman's rank correlation, multiple linear regression) and two non-linear (self-organizing maps, random forests) techniques. Catchment area is found to be crucial for medium to larger watersheds, while climatic controls, such as aridity index, have higher impact to smaller ones. Our findings indicate that long-term persistence is weaker than found in other studies, suggesting that enhanced LTP is encountered in large-catchment rivers, were the effect of spatial aggregation is more intense. However, we also show that the estimated values of H can be reproduced by a short-term persistence stochastic model such as an auto-regressive AR(1) process. A direct consequence is that some of the most common methods for the estimation of H coefficient, might not be suitable for discriminating short- and long-term persistence even in long observational records.

Pixel-By Estimation of Scene Motion in Video

NASA Astrophysics Data System (ADS)

Tashlinskii, A. G.; Smirnov, P. V.; Tsaryov, M. G.

2017-05-01

The paper considers the effectiveness of motion estimation in video using pixel-by-pixel recurrent algorithms. The algorithms use stochastic gradient decent to find inter-frame shifts of all pixels of a frame. These vectors form shift vectors' field. As estimated parameters of the vectors the paper studies their projections and polar parameters. It considers two methods for estimating shift vectors' field. The first method uses stochastic gradient descent algorithm to sequentially process all nodes of the image row-by-row. It processes each row bidirectionally i.e. from the left to the right and from the right to the left. Subsequent joint processing of the results allows compensating inertia of the recursive estimation. The second method uses correlation between rows to increase processing efficiency. It processes rows one after the other with the change in direction after each row and uses obtained values to form resulting estimate. The paper studies two criteria of its formation: gradient estimation minimum and correlation coefficient maximum. The paper gives examples of experimental results of pixel-by-pixel estimation for a video with a moving object and estimation of a moving object trajectory using shift vectors' field.

Estimating time-varying conditional correlations between stock and foreign exchange markets

NASA Astrophysics Data System (ADS)

Tastan, Hüseyin

2006-02-01

This study explores the dynamic interaction between stock market returns and changes in nominal exchange rates. Many financial variables are known to exhibit fat tails and autoregressive variance structure. It is well-known that unconditional covariance and correlation coefficients also vary significantly over time and multivariate generalized autoregressive model (MGARCH) is able to capture the time-varying variance-covariance matrix for stock market returns and changes in exchange rates. The model is applied to daily Euro-Dollar exchange rates and two stock market indexes from the US economy: Dow-Jones Industrial Average Index and S&P500 Index. The news impact surfaces are also drawn based on the model estimates to see the effects of idiosyncratic shocks in respective markets.

Optimal Extraction of Tropospheric Ozone Column by Simultaneous Use of OMI and TES Data and the Surface Temperature

NASA Astrophysics Data System (ADS)

Mobasheri, M. R.; Shirazi, H.

2015-12-01

This article aims to increase the accuracy of Ozone data from tropospheric column (TOC) of the OMI and TES satellite instruments. To validate the estimated amount of satellite data, Ozonesonde data is used. The vertical resolution in both instruments in the tropospheric atmosphere decreases so that the degree of freedom signals (DOFS) on the average for TES is reduced to 2 and for OMI is reduced to1. But this decline in accuracy in estimation of tropospheric ozone is more obvious in urban areas so that estimated ozone in both instruments alone in non-urban areas show a high correlation with Ozonesonde. But in urban areas this correlation is significantly reduced, due to the ozone pre-structures and consequently an increase on surface-level ozone in urban areas. In order to improve the accuracy of satellite data, the average tropospheric ozone data from the two instruments were used. The aim is to increase the vertical resolution of ozone profile and the results clearly indicate an increase in correlations, but nevertheless the satellite data have a positive bias towards the earth data. To reduce the bias, with the solar flux and nitrogen dioxide values and surface temperatures are calculated as factors of ozone production on the earth's surface and formation of mathematical equations based on coefficients for each of the mentioned values and multiplication of these coefficients by satellite data and repeated comparison with the values of Ozonesonde, the results showed that bias in urban areas is greatly reduced.

The Sedentary Time and Activity Reporting Questionnaire (STAR-Q): Reliability and Validity Against Doubly Labeled Water and 7-Day Activity Diaries

PubMed Central

Csizmadi, Ilona; Neilson, Heather K.; Kopciuk, Karen A.; Khandwala, Farah; Liu, Andrew; Friedenreich, Christine M.; Yasui, Yutaka; Rabasa-Lhoret, Rémi; Bryant, Heather E.; Lau, David C. W.; Robson, Paula J.

2014-01-01

We determined measurement properties of the Sedentary Time and Activity Reporting Questionnaire (STAR-Q), which was designed to estimate past-month activity energy expenditure (AEE). STAR-Q validity and reliability were assessed in 102 adults in Alberta, Canada (2009–2011), who completed 14-day doubly labeled water (DLW) protocols, 7-day activity diaries on day 15, and the STAR-Q on day 14 and again at 3 and 6 months. Three-month reliability was substantial for total energy expenditure (TEE) and AEE (intraclass correlation coefficients of 0.84 and 0.73, respectively), while 6-month reliability was moderate. STAR-Q-derived TEE and AEE were moderately correlated with DLW estimates (Spearman's ρs of 0.53 and 0.40, respectively; P < 0.001), and on average, the STAR-Q overestimated TEE and AEE (median differences were 367 kcal/day and 293 kcal/day, respectively). Body mass index-, age-, sex-, and season-adjusted concordance correlation coefficients (CCCs) were 0.24 (95% confidence interval (CI): 0.07, 0.36) and 0.21 (95% CI: 0.11, 0.32) for STAR-Q-derived versus DLW-derived TEE and AEE, respectively. Agreement between the diaries and STAR-Q (metabolic equivalent-hours/day) was strongest for occupational sedentary time (adjusted CCC = 0.76, 95% CI: 0.64, 0.85) and overall strenuous activity (adjusted CCC = 0.64, 95% CI: 0.49, 0.76). The STAR-Q demonstrated substantial validity for estimating occupational sedentary time and strenuous activity and fair validity for ranking individuals by AEE. PMID:25038920

Measurement errors when estimating the vertical jump height with flight time using photocell devices: the example of Optojump.

PubMed

Attia, A; Dhahbi, W; Chaouachi, A; Padulo, J; Wong, D P; Chamari, K

2017-03-01

Common methods to estimate vertical jump height (VJH) are based on the measurements of flight time (FT) or vertical reaction force. This study aimed to assess the measurement errors when estimating the VJH with flight time using photocell devices in comparison with the gold standard jump height measured by a force plate (FP). The second purpose was to determine the intrinsic reliability of the Optojump photoelectric cells in estimating VJH. For this aim, 20 subjects (age: 22.50±1.24 years) performed maximal vertical jumps in three modalities in randomized order: the squat jump (SJ), counter-movement jump (CMJ), and CMJ with arm swing (CMJarm). Each trial was simultaneously recorded by the FP and Optojump devices. High intra-class correlation coefficients (ICCs) for validity (0.98-0.99) and low limits of agreement (less than 1.4 cm) were found; even a systematic difference in jump height was consistently observed between FT and double integration of force methods (-31% to -27%; p<0.001) and a large effect size (Cohen's d >1.2). Intra-session reliability of Optojump was excellent, with ICCs ranging from 0.98 to 0.99, low coefficients of variation (3.98%), and low standard errors of measurement (0.8 cm). It was concluded that there was a high correlation between the two methods to estimate the vertical jump height, but the FT method cannot replace the gold standard, due to the large systematic bias. According to our results, the equations of each of the three jump modalities were presented in order to obtain a better estimation of the jump height.

Tracking variable sedimentation rates in orbitally forced paleoclimate proxy series

NASA Astrophysics Data System (ADS)

Li, M.; Kump, L. R.; Hinnov, L.

2017-12-01

This study addresses two fundamental issues in cyclostratigraphy: quantitative testing of orbital forcing in cyclic sedimentary sequences and tracking variable sedimentation rates. The methodology proposed here addresses these issues as an inverse problem, and estimates the product-moment correlation coefficient between the frequency spectra of orbital solutions and paleoclimate proxy series over a range of "test" sedimentation rates. It is inspired by the ASM method (1). The number of orbital parameters involved in the estimation is also considered. The method relies on the hypothesis that orbital forcing had a significant impact on the paleoclimate proxy variations, and thus is also tested. The null hypothesis of no astronomical forcing is evaluated using the Beta distribution, for which the shape parameters are estimated using a Monte Carlo simulation approach. We introduce a metric to estimate the most likely sedimentation rate using the product-moment correlation coefficient, H0 significance level, and the number of contributing orbital parameters, i.e., the CHO value. The CHO metric is applied with a sliding window to track variable sedimentation rates along the paleoclimate proxy series. Two forward models with uniform and variable sedimentation rates are evaluated to demonstrate the robustness of the method. The CHO method is applied to the classical Late Triassic Newark depth rank series; the estimated sedimentation rates match closely with previously published sedimentation rates and provide a more highly time-resolved estimate (2,3). References: (1) Meyers, S.R., Sageman, B.B., Amer. J. Sci., 307, 773-792, 2007; (2) Kent, D.V., Olsen, P.E., Muttoni, G., Earth-Sci. Rev.166, 153-180, 2017; (3) Li, M., Zhang, Y., Huang, C., Ogg, J., Hinnov, L., Wang, Y., Zou, Z., Li, L., 2017. Earth Plant. Sc. Lett. doi:10.1016/j.epsl.2017.07.015

Estimation of the Length of Day (LOD) from DORIS observations

NASA Astrophysics Data System (ADS)

Štěpánek, Petr; Hugentobler, Urs; Buday, Michal; Filler, Vratislav

2018-07-01

The paper is devoted to the estimation of the Length of the Day (LOD) from DORIS observations and summarizes the first successful experiment with LOD estimation at the level of geodetic precision. This result is confirmed by 9 years of DORIS data (2006.0-2015.0). The mean difference of the non smoothed LOD series with respect to the IERS C04 model reaches a value of tens μs and a standard deviation around 120 μs for the last years of the campaign 2012.0-2015.0. However, the mean difference with respect to the reference model varies over time, reaching negative values from -60 to -20 μs for the years 2006-2011 and positive values from 80 to 120 μs for the years 2012-2014. The time variable mean difference with respect to the changes in DORIS satellite constellation is discussed, as well as the possibility of the bias reduction applying the long-term averages of the cross-track harmonics or adjustment of the geopotential coefficient C20. Moreover, the possibility of LOD adjustment in the standard DORIS solution is discussed with focus on the station coordinates estimation. In addition, the power spectrum of the difference between estimated LOD and the reference model was performed, showing the domination of the annual signal. Also LOD estimated from single-satellite DORIS solutions was analyzed to identify satellite-specific issues. The paper includes a correlation analysis of the orbit parameters, Earth rotation parameters and the geopotential coefficient C20, based on covariance matrices from weekly solutions. High correlation around 0.96 was found for LOD and the sine amplitude of the cross-track harmonic empirical acceleration, which was also confirmed analytically.

Measurement errors when estimating the vertical jump height with flight time using photocell devices: the example of Optojump

PubMed Central

Attia, A; Chaouachi, A; Padulo, J; Wong, DP; Chamari, K

2016-01-01

Common methods to estimate vertical jump height (VJH) are based on the measurements of flight time (FT) or vertical reaction force. This study aimed to assess the measurement errors when estimating the VJH with flight time using photocell devices in comparison with the gold standard jump height measured by a force plate (FP). The second purpose was to determine the intrinsic reliability of the Optojump photoelectric cells in estimating VJH. For this aim, 20 subjects (age: 22.50±1.24 years) performed maximal vertical jumps in three modalities in randomized order: the squat jump (SJ), counter-movement jump (CMJ), and CMJ with arm swing (CMJarm). Each trial was simultaneously recorded by the FP and Optojump devices. High intra-class correlation coefficients (ICCs) for validity (0.98-0.99) and low limits of agreement (less than 1.4 cm) were found; even a systematic difference in jump height was consistently observed between FT and double integration of force methods (-31% to -27%; p<0.001) and a large effect size (Cohen’s d>1.2). Intra-session reliability of Optojump was excellent, with ICCs ranging from 0.98 to 0.99, low coefficients of variation (3.98%), and low standard errors of measurement (0.8 cm). It was concluded that there was a high correlation between the two methods to estimate the vertical jump height, but the FT method cannot replace the gold standard, due to the large systematic bias. According to our results, the equations of each of the three jump modalities were presented in order to obtain a better estimation of the jump height. PMID:28416900

Evaluation of the pulse-contour method of determining stroke volume in man.

NASA Technical Reports Server (NTRS)

Alderman, E. L.; Branzi, A.; Sanders, W.; Brown, B. W.; Harrison, D. C.

1972-01-01

The pulse-contour method for determining stroke volume has been employed as a continuous rapid method of monitoring the cardiovascular status of patients. Twenty-one patients with ischemic heart disease and 21 patients with mitral valve disease were subjected to a variety of hemodynamic interventions. The pulse-contour estimations, using three different formulas derived by Warner, Kouchoukos, and Herd, were compared with indicator-dilution outputs. A comparison of the results of the two methods for determining stroke volume yielded correlation coefficients ranging from 0.59 to 0.84. The better performing Warner formula yielded a coefficient of variation of about 20%. The type of hemodynamic interventions employed did not significantly affect the results using the pulse-contour method. Although the correlation of the pulse-contour and indicator-dilution stroke volumes is high, the coefficient of variation is such that small changes in stroke volume cannot be accurately assessed by the pulse-contour method. However, the simplicity and rapidity of this method compared to determination of cardiac output by Fick or indicator-dilution methods makes it a potentially useful adjunct for monitoring critically ill patients.

Use of the mouse jumping test for estimating antagonistic potencies of morphine antagonists.

PubMed

Cowan, A

1976-03-01

The potencies of 19 reference morphine antagonists have been compared in a modified version of the mouse jumping test. Mice were each implanted subcutaneously with one 75 mg pellet of morphine. Antagonist challenge took place 72 h later and the incidence of repetitive vertical-jumping was monitored over 1 h. A high Pearson correlation coefficient (r = 0.997) was found between quantitative assays based on the total number of jumps per mouse and quantal assays based on mice jumping at least 6 times. A comparison of relative potencies obtained with the mouse test and with non-withdrawn morphine-dependent monkeys gave a Spearman rank order coefficient of 0.91 while a similar comparison with values obtained with the guinea-pig isolated ileum preparation also gave a high correlation coefficient (r= 0.92). Whereas it is difficult to assess the antagonistic component of buprenorphine and cyclorphan with the ileum preparation, both compounds can be satisfactorily assayed in the mouse jumping test. The reported antagonistic properties of ketocyclazocine and profadol could not be confirmed in the mouse model.

Estimating Isometric Tension of Finger Muscle Using Needle EMG Signals and the Twitch Contraction Model

NASA Astrophysics Data System (ADS)

Tachibana, Hideyuki; Suzuki, Takafumi; Mabuchi, Kunihiko

We address an estimation method of isometric muscle tension of fingers, as fundamental research for a neural signal-based prosthesis of fingers. We utilize needle electromyogram (EMG) signals, which have approximately equivalent information to peripheral neural signals. The estimating algorithm comprised two convolution operations. The first convolution is between normal distribution and a spike array, which is detected by needle EMG signals. The convolution estimates the probability density of spike-invoking time in the muscle. In this convolution, we hypothesize that each motor unit in a muscle activates spikes independently based on a same probability density function. The second convolution is between the result of the previous convolution and isometric twitch, viz., the impulse response of the motor unit. The result of the calculation is the sum of all estimated tensions of whole muscle fibers, i.e., muscle tension. We confirmed that there is good correlation between the estimated tension of the muscle and the actual tension, with >0.9 correlation coefficients at 59%, and >0.8 at 89% of all trials.

Collinear Latent Variables in Multilevel Confirmatory Factor Analysis

PubMed Central

van de Schoot, Rens; Hox, Joop

2014-01-01

Because variables may be correlated in the social and behavioral sciences, multicollinearity might be problematic. This study investigates the effect of collinearity manipulated in within and between levels of a two-level confirmatory factor analysis by Monte Carlo simulation. Furthermore, the influence of the size of the intraclass correlation coefficient (ICC) and estimation method; maximum likelihood estimation with robust chi-squares and standard errors and Bayesian estimation, on the convergence rate are investigated. The other variables of interest were rate of inadmissible solutions and the relative parameter and standard error bias on the between level. The results showed that inadmissible solutions were obtained when there was between level collinearity and the estimation method was maximum likelihood. In the within level multicollinearity condition, all of the solutions were admissible but the bias values were higher compared with the between level collinearity condition. Bayesian estimation appeared to be robust in obtaining admissible parameters but the relative bias was higher than for maximum likelihood estimation. Finally, as expected, high ICC produced less biased results compared to medium ICC conditions. PMID:29795827

Molecular electronegativity distance vector model for the prediction of bioconcentration factors in fish.

PubMed

Liu, Shu-Shen; Qin, Li-Tang; Liu, Hai-Ling; Yin, Da-Qiang

2008-02-01

Molecular electronegativity distance vector (MEDV) derived directly from the molecular topological structures was used to describe the structures of 122 nonionic organic compounds (NOCs) and a quantitative relationship between the MEDV descriptors and the bioconcentration factors (BCF) of NOCs in fish was developed using the variable selection and modeling based on prediction (VSMP). It was found that some main structural factors influencing the BCFs of NOCs are the substructures expressed by four atomic types of nos. 2, 3, 5, and 13, i.e., atom groups -CH(2)- or =CH-, -CH< or =C<, -NH(2), and -Cl or -Br where the former two groups exist in the molecular skeleton of NOC and the latter three groups are related closely to the substituting groups on a benzene ring. The best 5-variable model, with the correlation coefficient (r(2)) of 0.9500 and the leave-one-out cross-validation correlation coefficient (q(2)) of 0.9428, was built by multiple linear regressions, which shows a good estimation ability and stability. A predictive power for the external samples was tested by the model from the training set of 80 NOCs and the predictive correlation coefficient (u(2)) for the 42 external samples in the test set was 0.9028.

Performance of chromatographic systems to model soil-water sorption.

PubMed

Hidalgo-Rodríguez, Marta; Fuguet, Elisabet; Ràfols, Clara; Rosés, Martí

2012-08-24

A systematic approach for evaluating the goodness of chromatographic systems to model the sorption of neutral organic compounds by soil from water is presented in this work. It is based on the examination of the three sources of error that determine the overall variance obtained when soil-water partition coefficients are correlated against chromatographic retention factors: the variance of the soil-water sorption data, the variance of the chromatographic data, and the variance attributed to the dissimilarity between the two systems. These contributions of variance are easily predicted through the characterization of the systems by the solvation parameter model. According to this method, several chromatographic systems besides the reference octanol-water partition system have been selected to test their performance in the emulation of soil-water sorption. The results from the experimental correlations agree with the predicted variances. The high-performance liquid chromatography system based on an immobilized artificial membrane and the micellar electrokinetic chromatography systems of sodium dodecylsulfate and sodium taurocholate provide the most precise correlation models. They have shown to predict well soil-water sorption coefficients of several tested herbicides. Octanol-water partitions and high-performance liquid chromatography measurements using C18 columns are less suited for the estimation of soil-water partition coefficients. Copyright © 2012 Elsevier B.V. All rights reserved.

Seismicity of the North Atlantic as measured by the International Data Centre using waveform cross correlation

NASA Astrophysics Data System (ADS)

Given, J. W.; Bobrov, D.; Kitov, I. O.; Spiliopoulos, S.

2012-12-01

The Technical Secretariat (TS) of the Comprehensive Nuclear Test-Ban Treaty Organization (CTBTO) will carry out the verification of the CTBT which obligates each State Party not to carry out any nuclear explosions, independently of their size and purpose. The International Data Centre (IDC) receives, collects, processes, analyses, reports on and archives data from the International Monitoring System(IMS). The IDC is responsible for automatic and interactive processing of the IMS data and for standard IDC products. The IDC is also required by the Treaty to progressively enhance its technical capabilities. In this study, we use waveform cross correlation as a technique to improve the detection capability and reliability of the seismic part of the IMS. In order to quantitatively estimate the gain obtained by cross correlation on the current sensitivity of automatic and interactive processing we compared seismic bulletins built for the North Atlantic (NA), which is an isolated region with earthquakes concentrating around the Mid-Atlantic Ridge. This avoids the influence of adjacent seismic regions on the final bulletins: the Reviewed Event Bulletin (REB) issued by the International Data Centre and the cross correlation Standard Event List (XSEL). We have cross correlated waveforms from ~1500 events reported in the REB since 2009. The resulting cross correlation matrix revealed the best candidates for master events. High-quality signals (SNR>5.0) recorded at eighteen array stations from approximately 50 master events evenly distributed over the seismically active zone in the NA were selected as templates. These templates are used for a continuous calculation of cross correlation coefficients since 2011. All detections obtained by cross-correlation are then used to build events according to the current IDC definition, i.e. at least three primary stations with accurate arrival times, azimuth and slowness estimates. The qualified event hypotheses populated the XSEL. In order to confirm the XSEL events not found in the REB, a portion of the newly built events was reviewed interactively by experienced analysts. The influence of all defining parameters (cross correlation coefficient threshold and SNR, F-statistics and fk-analysis, azimuth and slowness estimates, relative magnitude, etc.) on the final XSEL has been studied using the relevant frequency distributions for all detections vs only for those which were associated with the XSEL events. These distributions are also station and master dependent. This allows estimating the thresholds for all defining parameters, which may be adjusted to balance the rate of missed events and false alarms.

Measurement properties of the WOMAC LK 3.1 pain scale.

PubMed

Stratford, P W; Kennedy, D M; Woodhouse, L J; Spadoni, G F

2007-03-01

The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) is applied extensively to patients with osteoarthritis of the hip or knee. Previous work has challenged the validity of its physical function scale however an extensive evaluation of its pain scale has not been reported. Our purpose was to estimate internal consistency, factorial validity, test-retest reliability, and the standard error of measurement (SEM) of the WOMAC LK 3.1 pain scale. Four hundred and seventy-four patients with osteoarthritis of the hip or knee awaiting arthroplasty were administered the WOMAC. Estimates of internal consistency (coefficient alpha), factorial validity (confirmatory factor analysis), and the SEM based on internal consistency (SEM(IC)) were obtained. Test-retest reliability [Type 2,1 intraclass correlation coefficients (ICC)] and a corresponding SEM(TRT) were estimated on a subsample of 36 patients. Our estimates were: internal consistency alpha=0.84; SEM(IC)=1.48; Type 2,1 ICC=0.77; SEM(TRT)=1.69. Confirmatory factor analysis failed to support a single factor structure of the pain scale with uncorrelated error terms. Two comparable models provided excellent fit: (1) a model with correlated error terms between the walking and stairs items, and between night and sit items (chi2=0.18, P=0.98); (2) a two factor model with walking and stairs items loading on one factor, night and sit items loading on a second factor, and the standing item loading on both factors (chi2=0.18, P=0.98). Our examination of the factorial structure of the WOMAC pain scale failed to support a single factor and internal consistency analysis yielded a coefficient less than optimal for individual patient use. An alternate strategy to summing the five-item responses when considering individual patient application would be to interpret item responses separately or to sum only those items which display homogeneity.

Link prediction with node clustering coefficient

NASA Astrophysics Data System (ADS)

Wu, Zhihao; Lin, Youfang; Wang, Jing; Gregory, Steve

2016-06-01

Predicting missing links in incomplete complex networks efficiently and accurately is still a challenging problem. The recently proposed Cannistrai-Alanis-Ravai (CAR) index shows the power of local link/triangle information in improving link-prediction accuracy. Inspired by the idea of employing local link/triangle information, we propose a new similarity index with more local structure information. In our method, local link/triangle structure information can be conveyed by clustering coefficient of common-neighbors directly. The reason why clustering coefficient has good effectiveness in estimating the contribution of a common-neighbor is that it employs links existing between neighbors of a common-neighbor and these links have the same structural position with the candidate link to this common-neighbor. In our experiments, three estimators: precision, AUP and AUC are used to evaluate the accuracy of link prediction algorithms. Experimental results on ten tested networks drawn from various fields show that our new index is more effective in predicting missing links than CAR index, especially for networks with low correlation between number of common-neighbors and number of links between common-neighbors.

Novel SVM-based technique to improve rainfall estimation over the Mediterranean region (north of Algeria) using the multispectral MSG SEVIRI imagery

NASA Astrophysics Data System (ADS)

Sehad, Mounir; Lazri, Mourad; Ameur, Soltane

2017-03-01

In this work, a new rainfall estimation technique based on the high spatial and temporal resolution of the Spinning Enhanced Visible and Infra Red Imager (SEVIRI) aboard the Meteosat Second Generation (MSG) is presented. This work proposes efficient scheme rainfall estimation based on two multiclass support vector machine (SVM) algorithms: SVM_D for daytime and SVM_N for night time rainfall estimations. Both SVM models are trained using relevant rainfall parameters based on optical, microphysical and textural cloud proprieties. The cloud parameters are derived from the Spectral channels of the SEVIRI MSG radiometer. The 3-hourly and daily accumulated rainfall are derived from the 15 min-rainfall estimation given by the SVM classifiers for each MSG observation image pixel. The SVMs were trained with ground meteorological radar precipitation scenes recorded from November 2006 to March 2007 over the north of Algeria located in the Mediterranean region. Further, the SVM_D and SVM_N models were used to estimate 3-hourly and daily rainfall using data set gathered from November 2010 to March 2011 over north Algeria. The results were validated against collocated rainfall observed by rain gauge network. Indeed, the statistical scores given by correlation coefficient, bias, root mean square error and mean absolute error, showed good accuracy of rainfall estimates by the present technique. Moreover, rainfall estimates of our technique were compared with two high accuracy rainfall estimates methods based on MSG SEVIRI imagery namely: random forests (RF) based approach and an artificial neural network (ANN) based technique. The findings of the present technique indicate higher correlation coefficient (3-hourly: 0.78; daily: 0.94), and lower mean absolute error and root mean square error values. The results show that the new technique assign 3-hourly and daily rainfall with good and better accuracy than ANN technique and (RF) model.

Parameters estimation of sandwich beam model with rigid polyurethane foam core

NASA Astrophysics Data System (ADS)

Barbieri, Nilson; Barbieri, Renato; Winikes, Luiz Carlos

2010-02-01

In this work, the physical parameters of sandwich beams made with the association of hot-rolled steel, Polyurethane rigid foam and High Impact Polystyrene, used for the assembly of household refrigerators and food freezers are estimated using measured and numeric frequency response functions (FRFs). The mathematical models are obtained using the finite element method (FEM) and the Timoshenko beam theory. The physical parameters are estimated using the amplitude correlation coefficient and genetic algorithm (GA). The experimental data are obtained using the impact hammer and four accelerometers displaced along the sample (cantilevered beam). The parameters estimated are Young's modulus and the loss factor of the Polyurethane rigid foam and the High Impact Polystyrene.

Utility of Penman-Monteith, Priestley-Taylor, reference evapotranspiration, and pan evaporation methods to estimate pasture evapotranspiration

USGS Publications Warehouse

Sumner, D.M.; Jacobs, J.M.

2005-01-01

Actual evapotranspiration (ETa) was measured at 30-min resolution over a 19-month period (September 28, 2000-April 23, 2002) from a nonirrigated pasture site in Florida, USA, using eddy correlation methods. The relative magnitude of measured ETa (about 66% of long-term annual precipitation at the study site) indicates the importance of accurate ET a estimates for water resources planning. The time and cost associated with direct measurements of ETa and the rarity of historical measurements of ETa make the use of methods relying on more easily obtainable data desirable. Several such methods (Penman-Monteith (PM), modified Priestley-Taylor (PT), reference evapotranspiration (ET 0), and pan evaporation (Ep)) were related to measured ETa using regression methods to estimate PM bulk surface conductance, PT ??, ET0 vegetation coefficient, and Ep pan coefficient. The PT method, where the PT ?? is a function of green-leaf area index (LAI) and solar radiation, provided the best relation with ET a (standard error (SE) for daily ETa of 0.11 mm). The PM method, in which the bulk surface conductance was a function of net radiation and vapor-pressure deficit, was slightly less effective (SE=0.15 mm) than the PT method. Vegetation coefficients for the ET0 method (SE=0.29 mm) were found to be a simple function of LAI. Pan coefficients for the Ep method (SE=0.40 mm) were found to be a function of LAI and Ep. Historical or future meteorological, LAI, and pan evaporation data from the study site could be used, along with the relations developed within this study, to provide estimates of ETa in the absence of direct measurements of ETa. Additionally, relations among PM, PT, and ET0 methods and ETa can provide estimates of ETa in other, environmentally similar, pasture settings for which meteorological and LAI data can be obtained or estimated. ?? 2004 Elsevier B.V. All rights reserved.

Predicting missing links via correlation between nodes

NASA Astrophysics Data System (ADS)

Liao, Hao; Zeng, An; Zhang, Yi-Cheng

2015-10-01

As a fundamental problem in many different fields, link prediction aims to estimate the likelihood of an existing link between two nodes based on the observed information. Since this problem is related to many applications ranging from uncovering missing data to predicting the evolution of networks, link prediction has been intensively investigated recently and many methods have been proposed so far. The essential challenge of link prediction is to estimate the similarity between nodes. Most of the existing methods are based on the common neighbor index and its variants. In this paper, we propose to calculate the similarity between nodes by the Pearson correlation coefficient. This method is found to be very effective when applied to calculate similarity based on high order paths. We finally fuse the correlation-based method with the resource allocation method, and find that the combined method can substantially outperform the existing methods, especially in sparse networks.

Non-Gaussian diffusion in static disordered media

NASA Astrophysics Data System (ADS)

Luo, Liang; Yi, Ming

2018-04-01

Non-Gaussian diffusion is commonly considered as a result of fluctuating diffusivity, which is correlated in time or in space or both. In this work, we investigate the non-Gaussian diffusion in static disordered media via a quenched trap model, where the diffusivity is spatially correlated. Several unique effects due to quenched disorder are reported. We analytically estimate the diffusion coefficient Ddis and its fluctuation over samples of finite size. We show a mechanism of population splitting in the non-Gaussian diffusion. It results in a sharp peak in the distribution of displacement P (x ,t ) around x =0 , that has frequently been observed in experiments. We examine the fidelity of the coarse-grained diffusion map, which is reconstructed from particle trajectories. Finally, we propose a procedure to estimate the correlation length in static disordered environments, where the information stored in the sample-to-sample fluctuation has been utilized.

Response functions for computing absorbed dose to skeletal tissues from neutron irradiation

NASA Astrophysics Data System (ADS)

Bahadori, Amir A.; Johnson, Perry; Jokisch, Derek W.; Eckerman, Keith F.; Bolch, Wesley E.

2011-11-01

Spongiosa in the adult human skeleton consists of three tissues—active marrow (AM), inactive marrow (IM) and trabecularized mineral bone (TB). AM is considered to be the target tissue for assessment of both long-term leukemia risk and acute marrow toxicity following radiation exposure. The total shallow marrow (TM50), defined as all tissues lying within the first 50 µm of the bone surfaces, is considered to be the radiation target tissue of relevance for radiogenic bone cancer induction. For irradiation by sources external to the body, kerma to homogeneous spongiosa has been used as a surrogate for absorbed dose to both of these tissues, as direct dose calculations are not possible using computational phantoms with homogenized spongiosa. Recent micro-CT imaging of a 40 year old male cadaver has allowed for the accurate modeling of the fine microscopic structure of spongiosa in many regions of the adult skeleton (Hough et al 2011 Phys. Med. Biol. 56 2309-46). This microstructure, along with associated masses and tissue compositions, was used to compute specific absorbed fraction (SAF) values for protons originating in axial and appendicular bone sites (Jokisch et al 2011 Phys. Med. Biol. 56 6857-72). These proton SAFs, bone masses, tissue compositions and proton production cross sections, were subsequently used to construct neutron dose-response functions (DRFs) for both AM and TM50 targets in each bone of the reference adult male. Kerma conditions were assumed for other resultant charged particles. For comparison, AM, TM50 and spongiosa kerma coefficients were also calculated. At low incident neutron energies, AM kerma coefficients for neutrons correlate well with values of the AM DRF, while total marrow (TM) kerma coefficients correlate well with values of the TM50 DRF. At high incident neutron energies, all kerma coefficients and DRFs tend to converge as charged-particle equilibrium is established across the bone site. In the range of 10 eV to 100 MeV, substantial differences are observed among the kerma coefficients and DRF. As a result, it is recommended that the AM kerma coefficient be used to estimate the AM DRF, and that the TM kerma coefficient be used to estimate the TM50 DRF below 10 eV. Between 10 eV and 100 MeV, the appropriate DRF should be used as presented in this study. Above 100 MeV, spongiosa kerma coefficients apply well for estimating skeletal tissue doses. DRF values for each bone site as a function of energy are provided in an electronic annex to this article available at http://stacks.iop.org/0031-9155/56/6873/mmedia.

Response functions for computing absorbed dose to skeletal tissues from neutron irradiation.

PubMed

Bahadori, Amir A; Johnson, Perry; Jokisch, Derek W; Eckerman, Keith F; Bolch, Wesley E

2011-11-07

Spongiosa in the adult human skeleton consists of three tissues-active marrow (AM), inactive marrow (IM) and trabecularized mineral bone (TB). AM is considered to be the target tissue for assessment of both long-term leukemia risk and acute marrow toxicity following radiation exposure. The total shallow marrow (TM(50)), defined as all tissues lying within the first 50 µm of the bone surfaces, is considered to be the radiation target tissue of relevance for radiogenic bone cancer induction. For irradiation by sources external to the body, kerma to homogeneous spongiosa has been used as a surrogate for absorbed dose to both of these tissues, as direct dose calculations are not possible using computational phantoms with homogenized spongiosa. Recent micro-CT imaging of a 40 year old male cadaver has allowed for the accurate modeling of the fine microscopic structure of spongiosa in many regions of the adult skeleton (Hough et al 2011 Phys. Med. Biol. 56 2309-46). This microstructure, along with associated masses and tissue compositions, was used to compute specific absorbed fraction (SAF) values for protons originating in axial and appendicular bone sites (Jokisch et al 2011 Phys. Med. Biol. 56 6857-72). These proton SAFs, bone masses, tissue compositions and proton production cross sections, were subsequently used to construct neutron dose-response functions (DRFs) for both AM and TM(50) targets in each bone of the reference adult male. Kerma conditions were assumed for other resultant charged particles. For comparison, AM, TM(50) and spongiosa kerma coefficients were also calculated. At low incident neutron energies, AM kerma coefficients for neutrons correlate well with values of the AM DRF, while total marrow (TM) kerma coefficients correlate well with values of the TM(50) DRF. At high incident neutron energies, all kerma coefficients and DRFs tend to converge as charged-particle equilibrium is established across the bone site. In the range of 10 eV to 100 MeV, substantial differences are observed among the kerma coefficients and DRF. As a result, it is recommended that the AM kerma coefficient be used to estimate the AM DRF, and that the TM kerma coefficient be used to estimate the TM(50) DRF below 10 eV. Between 10 eV and 100 MeV, the appropriate DRF should be used as presented in this study. Above 100 MeV, spongiosa kerma coefficients apply well for estimating skeletal tissue doses. DRF values for each bone site as a function of energy are provided in an electronic annex to this article available at http://stacks.iop.org/0031-9155/56/6873/mmedia.

Development and Evaluation of a Manganese and Iron Food Frequency Questionnaire for Pediatrics

PubMed Central

Zipkin, Frida B; Falciglia, Grace A; Kuhnell, Pierce; Haynes, Erin N

2017-01-01

Manganese (Mn) is an essential nutrient, but overexposure can lead to neurotoxicity. Given the essentiality of Mn in the diet, particularly during children’s growth and development, it is imperative to quantify dietary Mn intake in populations that may be exposed to industrial sources of Mn. Dietary absorption of Mn is inversely associated with iron (Fe) stores, yet there is currently no food frequency questionnaire (FFQ) to assess dietary Mn and Fe intake. The study objective was to develop and evaluate the validity of a FFQ to measure dietary Mn and Fe intake in pediatrics by comparing the estimated intakes of Mn and Fe with biomarkers: Mn in blood and hair and Fe in serum. This study utilized a subset of the Communities Actively Researching Exposure Study (CARES) population residing in Guernsey County, Ohio. Dietary Mn was not correlated with either blood or hair Mn; however, dietary Mn and serum ferritin were significantly correlated, with a correlation coefficient of 0.51, p < 0.01. Moreover, dietary Fe and serum ferritin were also significantly correlated, with a correlation coefficient of 0.51, p < 0.01. This FFQ is a valid measurement tool for Fe intake as measured by serum ferritin; however, Mn intake did not correlate with either blood or hair Mn. PMID:28906436

Development and Evaluation of a Manganese and Iron Food Frequency Questionnaire for Pediatrics.

PubMed

Zipkin, Frida B; Falciglia, Grace A; Kuhnell, Pierce; Haynes, Erin N

2017-09-14

Manganese (Mn) is an essential nutrient, but overexposure can lead to neurotoxicity. Given the essentiality of Mn in the diet, particularly during children's growth and development, it is imperative to quantify dietary Mn intake in populations that may be exposed to industrial sources of Mn. Dietary absorption of Mn is inversely associated with iron (Fe) stores, yet there is currently no food frequency questionnaire (FFQ) to assess dietary Mn and Fe intake. The study objective was to develop and evaluate the validity of a FFQ to measure dietary Mn and Fe intake in pediatrics by comparing the estimated intakes of Mn and Fe with biomarkers: Mn in blood and hair and Fe in serum. This study utilized a subset of the Communities Actively Researching Exposure Study (CARES) population residing in Guernsey County, Ohio. Dietary Mn was not correlated with either blood or hair Mn; however, dietary Mn and serum ferritin were significantly correlated, with a correlation coefficient of 0.51, p < 0.01. Moreover, dietary Fe and serum ferritin were also significantly correlated, with a correlation coefficient of 0.51, p < 0.01. This FFQ is a valid measurement tool for Fe intake as measured by serum ferritin; however, Mn intake did not correlate with either blood or hair Mn.

Estimating absorption coefficients of colored dissolved organic matter (CDOM) using a semi-analytical algorithm for southern Beaufort Sea waters: application to deriving concentrations of dissolved organic carbon from space

NASA Astrophysics Data System (ADS)

Matsuoka, A.; Hooker, S. B.; Bricaud, A.; Gentili, B.; Babin, M.

2013-02-01

A series of papers have suggested that freshwater discharge, including a large amount of dissolved organic matter (DOM), has increased since the middle of the 20th century. In this study, a semi-analytical algorithm for estimating light absorption coefficients of the colored fraction of DOM (CDOM) was developed for southern Beaufort Sea waters using remote sensing reflectance at six wavelengths in the visible spectral domain corresponding to MODIS ocean color sensor. This algorithm allows the separation of colored detrital matter (CDM) into CDOM and non-algal particles (NAP) through the determination of NAP absorption using an empirical relationship between NAP absorption and particle backscattering coefficients. Evaluation using independent datasets, which were not used for developing the algorithm, showed that CDOM absorption can be estimated accurately to within an uncertainty of 35% and 50% for oceanic and coastal waters, respectively. A previous paper (Matsuoka et al., 2012) showed that dissolved organic carbon (DOC) concentrations were tightly correlated with CDOM absorption in our study area (r2 = 0.97). By combining the CDOM absorption algorithm together with the DOC versus CDOM relationship, it is now possible to estimate DOC concentrations in the near-surface layer of the southern Beaufort Sea using satellite ocean color data. DOC concentrations in the surface waters were estimated using MODIS ocean color data, and the estimates showed reasonable values compared to in situ measurements. We propose a routine and near real-time method for deriving DOC concentrations from space, which may open the way to an estimate of DOC budgets for Arctic coastal waters.

The efficiency of parameter estimation of latent path analysis using summated rating scale (SRS) and method of successive interval (MSI) for transformation of score to scale

NASA Astrophysics Data System (ADS)

Solimun, Fernandes, Adji Achmad Rinaldo; Arisoesilaningsih, Endang

2017-12-01

Research in various fields generally investigates systems and involves latent variables. One method to analyze the model representing the system is path analysis. The data of latent variables measured using questionnaires by applying attitude scale model yields data in the form of score, before analyzed should be transformation so that it becomes data of scale. Path coefficient, is parameter estimator, calculated from scale data using method of successive interval (MSI) and summated rating scale (SRS). In this research will be identifying which data transformation method is better. Path coefficients have smaller varieties are said to be more efficient. The transformation method that produces scaled data and used in path analysis capable of producing path coefficients (parameter estimators) with smaller varieties is said to be better. The result of analysis using real data shows that on the influence of Attitude variable to Intention Entrepreneurship, has relative efficiency (ER) = 1, where it shows that the result of analysis using data transformation of MSI and SRS as efficient. On the other hand, for simulation data, at high correlation between items (0.7-0.9), MSI method is more efficient 1.3 times better than SRS method.

Three-gene identity coefficients demonstrate that clonal reproduction promotes inbreeding and spatial relatedness in yellow-cedar, Callitropsis nootkatensis.

PubMed

Thompson, Stacey Lee; Bérubé, Yanik; Bruneau, Anne; Ritland, Kermit

2008-10-01

Asexual reproduction has the potential to promote population structuring through matings between clones as well as through limited dispersal of related progeny. Here we present an application of three-gene identity coefficients that tests whether clonal reproduction promotes inbreeding and spatial relatedness within populations. With this method, the first two genes are sampled to estimate pairwise relatedness or inbreeding, whereas the third gene is sampled from either a clone or a sexually derived individual. If three-gene coefficients are significantly greater for clones than nonclones, then clonality contributes excessively to genetic structure. First, we describe an estimator of three-gene identity and briefly evaluate its properties. We then use this estimator to test the effect of clonality on the genetic structure within populations of yellow-cedar (Callitropsis nootkatensis) using a molecular marker survey. Five microsatellite loci were genotyped for 485 trees sampled from nine populations. Our three-gene analyses show that clonal ramets promote inbreeding and spatial structure in most populations. Among-population correlations between clonal extent and genetic structure generally support these trends, yet with less statistical significance. Clones appear to contribute to genetic structure through the limited dispersal of offspring from replicated ramets of the same clonal genet, whereas this structure is likely maintained by mating among these relatives.

Correlation between benzene and testosterone in workers exposed to urban pollution.

PubMed

Rosati, M V; Sancini, A; Tomei, F; Sacco, C; Traversini, V; De Vita, A; De Cesare, D P; Giammichele, G; De Marco, F; Pagliara, F; Massoni, F; Ricci, L; Tomei, G; Ricci, S

2017-01-01

Many studies have examined the effects of benzene on testosterone. The purpose of this study was to evaluate the possible correlation between the blood levels of benzene and the levels of testosterone. The study involved a group of 148 subjects. For every worker have been made out a blood sample for the evaluation of benzene and testosterone levels and an urine analysis for the evaluation of the levels of trans, trans-muconic acid and S-phenylmercapturic acid. We estimated the Pearson correlation coefficient between the variables in the sample and the urinary metabolites, age, length of service, gender, BMI. For the analysis of the major confounding factors it was performed a multiple linear regression. The Pearson correlation coefficiet showed: 1. a significant inverse correlation between the S-phenyl mercapturic acid and free testosterone; 2. a significant direct correlation between trans-trans muconic acid and BMI. After dividing the sample according to the median of blood benzene (161.0 ng / L), Pearson correlation coefficient showed a significant inverse correlation between the S-phenyl mercapturic acid and free testosterone in the group with values below this median. Our results, to be considered preliminary, suggest that occupational exposure to low levels of benzene, present in urban pollution, affect the blood levels of testosterone. These results need to be confirmed in future studies, with the eventual possibility of including more specific fertility tests.

Validation of TRMM precipitation radar monthly rainfall estimates over Brazil

NASA Astrophysics Data System (ADS)

Franchito, Sergio H.; Rao, V. Brahmananda; Vasques, Ana C.; Santo, Clovis M. E.; Conforte, Jorge C.

2009-01-01

In an attempt to validate the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) over Brazil, TRMM PR estimates are compared with rain gauge station data from Agência Nacional de Energia Elétrica (ANEEL). The analysis is conducted on a seasonal basis and considers five geographic regions with different precipitation regimes. The results showed that TRMM PR seasonal rainfall is well correlated with ANEEL rainfall (correlation coefficients are significant at the 99% confidence level) over most of Brazil. The random and systematic errors of TRMM PR are sensitive to seasonal and regional differences. During December to February and March to May, TRMM PR rainfall is reliable over Brazil. In June to August (September to November) TRMM PR estimates are only reliable in the Amazonian and southern (Amazonian and southeastern) regions. In the other regions the relative RMS errors are larger than 50%, indicating that the random errors are high.

Estimates of genetic and environmental (co)variances for first lactation on milk yield, survival, and calving interval.

PubMed

Dong, M C; van Vleck, L D

1989-03-01

Variance and covariance components for milk yield, survival to second freshening, calving interval in first lactation were estimated by REML with the expectation and maximization algorithm for an animal model which included herd-year-season effects. Cows without calving interval but with milk yield were included. Each of the four data sets of 15 herds included about 3000 Holstein cows. Relationships across herds were ignored to enable inversion of the coefficient matrix of mixed model equations. Quadratics and their expectations were accumulated herd by herd. Heritability of milk yield (.32) agrees with reports by same methods. Heritabilities of survival (.11) and calving interval(.15) are slightly larger and genetic correlations smaller than results from different methods of estimation. Genetic correlation between milk yield and calving interval (.09) indicates genetic ability to produce more milk is lightly associated with decreased fertility.

The Attenuation of Correlation Coefficients: A Statistical Literacy Issue

ERIC Educational Resources Information Center

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.

Prevalence and risk factors of mucous retention cysts in a Brazilian population.

PubMed

Rodrigues, C D; Freire, G F; Silva, L B; Fonseca da Silveira, M M; Estrela, C

2009-10-01

The aim of this study was to estimate the prevalence and analyse the risk factors of mucous retention cysts (MRCs) of the maxillary sinus. From November 2002 to May 2007, 6293 panoramic radiographs were taken and retrospectively reviewed to estimate the prevalence of MRCs and to analyse risk factors (month, relative air humidity and mean temperature). The months in which MRCs occurred were recorded and analysed. The Spearman rank correlation coefficient was used to correlate MRCs with relative air humidity, environmental temperature and month (significance level R(2)>0.85). Of the 6293 radiographs analysed, 201 (3.19%) images were suggestive of MRCs. No significant correlation was found between MRCs and relative humidity (R(2) = 0.15) of the air or temperature (R(2) = 0.40). The months with the highest numbers of MRC cases were September, October and November. The prevalence of MRCs was low, and no statistical correlation was found between MRCs and relative humidity of the air, mean temperature or month.

Validation of a food frequency questionnaire for Japanese pregnant women with and without nausea and vomiting in early pregnancy.

PubMed

Ogawa, Kohei; Jwa, Seung-Chik; Kobayashi, Minatsu; Morisaki, Naho; Sago, Haruhiko; Fujiwara, Takeo

2017-05-01

No previous study has shown the validity of a food frequency questionnaire (FFQ) in early pregnancy with consideration of nausea and vomiting during pregnancy (NVP). The aim of this study was to evaluate the validity of a FFQ in early pregnancy for Japanese pregnant women. We included 188 women before 15 weeks of gestation and compared estimated nutrient intake and food group intake based on a modified FFQ with that based on 3-day dietary records (DRs). Spearman's rank correlation coefficients, adjusting energy intake and attenuating within-person error, were calculated. Subgroup analysis for those with and without NVP was conducted. We also examined the degree of appropriate classification across categories between FFQ and DRs through division of consumption of nutrients and food groups into quintiles. Crude Spearman's correlation coefficients of nutrients ranged from 0.098 (sodium) to 0.401 (vitamin C), and all of the 36 nutrients were statistically significant. In 27 food groups, correlation coefficients ranged from -0.015 (alcohol) to 0.572 (yogurt), and 81% were statistically significant. In subgroup analysis, correlation coefficients in 89% of nutrients and 70% of food groups in women with NVP and 97% of nutrients and 74% of food groups in women without NVP were statistically significant. On average, 63.7% of nutrients and 60.4% of food groups were classified into same or adjacent quintiles according to the FFQ and DRs. The FFQ is a useful instrument, regardless of NVP, for assessing the diet of women in early pregnancy in Japan. Copyright © 2016 The Authors. Production and hosting by Elsevier B.V. All rights reserved.

Statistical analysis and digital processing of the Mössbauer spectra

NASA Astrophysics Data System (ADS)

Prochazka, Roman; Tucek, Pavel; Tucek, Jiri; Marek, Jaroslav; Mashlan, Miroslav; Pechousek, Jiri

2010-02-01

This work is focused on using the statistical methods and development of the filtration procedures for signal processing in Mössbauer spectroscopy. Statistical tools for noise filtering in the measured spectra are used in many scientific areas. The use of a pure statistical approach in accumulated Mössbauer spectra filtration is described. In Mössbauer spectroscopy, the noise can be considered as a Poisson statistical process with a Gaussian distribution for high numbers of observations. This noise is a superposition of the non-resonant photons counting with electronic noise (from γ-ray detection and discrimination units), and the velocity system quality that can be characterized by the velocity nonlinearities. The possibility of a noise-reducing process using a new design of statistical filter procedure is described. This mathematical procedure improves the signal-to-noise ratio and thus makes it easier to determine the hyperfine parameters of the given Mössbauer spectra. The filter procedure is based on a periodogram method that makes it possible to assign the statistically important components in the spectral domain. The significance level for these components is then feedback-controlled using the correlation coefficient test results. The estimation of the theoretical correlation coefficient level which corresponds to the spectrum resolution is performed. Correlation coefficient test is based on comparison of the theoretical and the experimental correlation coefficients given by the Spearman method. The correctness of this solution was analyzed by a series of statistical tests and confirmed by many spectra measured with increasing statistical quality for a given sample (absorber). The effect of this filter procedure depends on the signal-to-noise ratio and the applicability of this method has binding conditions.

Validation of the French version of the Burn Specific Health Scale-Brief (BSHS-B) questionnaire.

PubMed

Gandolfi, S; Auquit-Auckbur, I; Panunzi, S; Mici, E; Grolleau, J-L; Chaput, B

2016-11-01

The Burn Specific Health Scale-Brief questionnaire is a widely validated tool for estimating the health related quality of life and for assessing the best multidisciplinary management of burn patients. The aim of this study was to translate the BSHS-B into French and to investigate its reliability and validity. According to the procedure proposed by the Scientific Advisory Committee of the Medical Outcomes Trust, the Burn Specific Health Scale-Brief (BSHS-B) was translated from the English version into French. In order to test the reliability of the French version of the BSHS-B, 53 burn patients French speakers completed the BSHS-B and SF-36 questionnaires from two to four years after burn. Ten of them have been re-tested at 6 months after the first evaluation. To evaluate clinical utility of the BSHS-F, internal consistency, construct validity (using SF-36) and stability in time were assessed using Cronbach's alpha statistic, Spearman rank test, and intra-class correlation coefficient respectively. The French version of the BSHS-B Cronbach's alpha coefficient was 0.93 and was >0.80 for all the sub-domains. French version of the BSHS-B and the SF-36 were positively correlated, all the associations were statistically significant (p<0.01). Intra-class correlation coefficients for test-retest ranged between 0.95 and 0.99 for the sub-domains. The intra-class correlation coefficient (ICC) for the total score was 0.98. The French version of the BSHS-B shows a robust rate of internal consistency, construct validity and stability in time, supporting its application in routine clinical practice as well as in international studies. Copyright © 2016 Elsevier Ltd and ISBI. All rights reserved.

Association Between Masticatory Function and Oral Health-Related Quality of Life in Partial Maxillectomy Patients.

PubMed

Said, Mohamed Moustafa; Otomaru, Takafumi; Aimaijiang, Yiliyaer; Li, Na; Taniguchi, Hisashi

The aim of this study was to investigate associations between objectively and subjectively measured masticatory function and oral health-related quality of life (OHRQoL) in partial maxillectomy patients wearing dentomaxillary prostheses. A sample of 32 consecutively treated patients who had undergone a partial maxillectomy were enrolled. Masticatory function was assessed using two objective measures and one subjective measure. The objective measures were masticatory performance (MP), which was estimated by measuring the glucose extracted from gummy jelly, and food mixing ability (a*), which was assessed using color-changeable chewing gum. The subjective measure was perceived chewing ability, rated as masticatory score (MS) based on the patient's responses to a food intake questionnaire. OHRQoL was assessed using the Geriatric Oral Health Assessment Index (GOHAI). Relationships between the masticatory function measures and OHRQoL were analyzed using Spearman rank correlation coefficient. The correlation coefficients (r) obtained were 0.57 (P = .001) for MS and GOHAI, 0.247 (P = .173) for MP and GOHAI, -0.173 (P = .343) for a* and GOHAI, 0.517 (P = .002) for MP and a*, 0.199 (P = .257) for MP and MS, and 0.019 (P = .919) for a* and MS. Subjective MS showed a significant positive correlation with GOHAI score, suggesting that perceived chewing ability could be an important factor in the estimation of OHRQoL in partial maxillectomy patients.

Determination of oleanolic acid in human plasma and its association with olive oil intake in healthy Spanish adults within the EPIC Spain cohort study.

PubMed

Buckland, Genevieve; Pastor, Antoni; Lujan-Barroso, Leila; Gonzalez, Carlos Alberto; Travier, Noemie; Amiano, Pilar; Huerta, José María; Agudo, Antonio; Navarro, Carmen; Chirlaque, María Dolores; Sánchez, Maria-José; Rodríguez-Barranco, Miguel; Barricarte, Aurelio; Ardanaz, Eva; Dorronsoro, Miren; Molinuevo, Amaia; Quirós, José Ramón; de la Torre, Rafael

2017-08-01

Oleanolic acid (OA) is an important triterpenic compound found in olive oil, however little is known about its concentrations in human plasma. We aimed to determine plasma OA levels in a healthy Spanish population and compare them with estimates of dietary olive oil intake. The final study sample included 141 individuals randomly selected from the European Prospective Investigation into Cancer and Nutrition Spanish cohort. Dietary olive oil intake was estimated using validated dietary history questionnaires. OA concentrations were determined in plasma (from the participants' stored blood samples) using a HPLC-MS method. Correlation coefficients between OA and olive oil intake were calculated, adjusting for center; sex; age; consumption of olives, apples, grapes, and red wine; and fasting state. The mean OA concentration in olive oil nonconsumers was 0.72 ng/mL (SD 0.82), while in the high olive oil intake group it was 1.32 ng/mL (SD 1.14). The fully adjusted partial Spearman correlations coefficients reached 0.36 (p-value < 0.001) overall, varying minimally by sex and fasting state. This is the first study providing steady-state concentrations of triterpenes in humans. The results show that there was low-to-moderate correlation between OA concentrations and olive oil intake in this population. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Prediction of soil frost penetration depth in northwest of Iran using air freezing indices

NASA Astrophysics Data System (ADS)

Mohammadi, H.; Moghbel, M.; Ranjbar, F.

2016-11-01

Information about soil frost penetration depth can be effective in finding appropriate solutions to reduce the agricultural crop damage, transportations, and building facilities. Amongst proper methods to achieve this information are the statistical and empirical models capable of estimating soil frost penetration depth. Therefore, the main objective of this research is to calculate soil frost penetration depth in northwest of Iran during the year 2007-2008 to validate two different models accuracy. To do so, the relationship between air and soil temperature in different depths (5-10-20-30-50-100 cm) at three times of the day (3, 9, and 15 GMT) for 14 weather stations over 7 provinces was analyzed using linear regression. Then, two different air freezing indices (AFIs) including Norwegian and Finn AFI was implemented. Finally, the frost penetration depth was calculated by McKeown method and the accuracy of models determined by actual soil frost penetration depth. The results demonstrated that there is a significant correlation between air and soil depth temperature in all studied stations up to the 30 cm under the surface. Also, according to the results, Norwegian index can be effectively used for determination of soil frost depth penetration and the correlation coefficient between actual and estimated soil frost penetration depth is r = 0.92 while the Finn index overestimates the frost depth in all stations with correlation coefficient r = 0.70.

Trends in frequency of type 2 diabetes in Mexico and its relationship to dietary patterns and contextual factors.

PubMed

Soto-Estrada, Guadalupe; Moreno Altamirano, Laura; García-García, Juan José; Ochoa Moreno, Iván; Silberman, Martín

To analyse the evolution of the frequency of type 2 diabetes (T2D) and its relationship to eating patterns in Mexico from 1961 to 2013, and the Gini coefficient, Human Development Index (HDI) and Gross Domestic Product (GDP). Mexico ranked sixth in world prevalence of diabetes in 2015 with an estimated 11.4 million Mexicans affected. Using data from the Balance Sheets Food published by the Food and Agriculture Organization of the United Nations (FAO), the means of apparent food consumption (kcal/person/day) were grouped by decades. Data for mortality rate for diabetes were obtained from 1990 until 2015. Spearman's correlation coefficient was calculated between the diabetes mellitus mortality rate and all food groups. Pearson's correlation explored the relationship between socio economic indicators and the prevalence of T2D diabetes. The mortality rate for T2D has increased over the last decades. An increase of 647.9kcal/person/day in apparent food consumption was observed. Cereal and legume consumption decreased, while apparent sugar, animal food and animal fat and vegetable oil consumption increased substantially. HDI and GDP showed a directly proportional relationship to diabetes. Spearman's correlation coefficient was statistically significant only for sugar. The Gini coefficient suggests that in lower inequalities there is an increased frequency of diabetes. The increase in the mortality rate of type 2 diabetes was constant during the study period, which coincides with the increase in energy density of Mexican eating patterns from 1961 to 2013. The higher the Gini coefficient, HDI and GDP, the higher the mortality observed for diabetes. Copyright © 2017 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

Intraherd correlation coefficients and design effects for bovine viral diarrhoea, infectious bovine rhinotracheitis, leptospirosis and neosporosis in cow-calf system herds in North-eastern Mexico.

PubMed

Segura-Correa, J C; Domínguez-Díaz, D; Avalos-Ramírez, R; Argaez-Sosa, J

2010-09-01

Knowledge of the intraherd correlation coefficient (ICC) and design (D) effect for infectious diseases could be of interest in sample size calculation and to provide the correct standard errors of prevalence estimates in cluster or two-stage samplings surveys. Information on 813 animals from 48 non-vaccinated cow-calf herds from North-eastern Mexico was used. The ICC for the bovine viral diarrhoea (BVD), infectious bovine rhinotracheitis (IBR), leptospirosis and neosporosis diseases were calculated using a Bayesian approach adjusting for the sensitivity and specificity of the diagnostic tests. The ICC and D values for BVD, IBR, leptospirosis and neosporosis were 0.31 and 5.91, 0.18 and 3.88, 0.22 and 4.53, and 0.11 and 2.68, respectively. The ICC and D values were different from 0 and D greater than 1, therefore large sample sizes are required to obtain the same precision in prevalence estimates than for a random simple sampling design. The report of ICC and D values is of great help in planning and designing two-stage sampling studies. 2010 Elsevier B.V. All rights reserved.

[Association between inequality and suicide rate in Colombia (1994-2013)].

PubMed

Campo-Arias, Adalberto; Herazo, Edwin

2015-01-01

Income inequality is directly related to the mental health of the population. However, the relationship between income inequality and suicide rates in Colombia has still not been explored. To estimate the relationship between inequality and suicide rates in Colombia from 1994 to 2013. An ecological study was conducted, in which the correlation was estimated (Spearman) between inequality (Gini coefficient) and suicide rate between 1994 and 2013, according to official information available from the National Administrative Department of Statistics (DANE), and the National Institute of Forensic Science and Forensic Medicine. A Gini coefficient between 0.53 and 0.60 (median, 0.65 [interquartile range, 0.54-0.57]) was observed, and suicide rates were between 3.84 and 5.26 (median, 4.20 [4.08-4.86]). The correlation between inequality and suicide rates was positive and statistically significant (r=.70; p<.001). There is a positive association between economic inequality and suicide rate in Colombia. It is important to achieve greater equity in the distribution of income to reduce suicide rate in the country. Copyright © 2014 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.

Unraveling spurious properties of interaction networks with tailored random networks.

PubMed

Bialonski, Stephan; Wendler, Martin; Lehnertz, Klaus

2011-01-01

We investigate interaction networks that we derive from multivariate time series with methods frequently employed in diverse scientific fields such as biology, quantitative finance, physics, earth and climate sciences, and the neurosciences. Mimicking experimental situations, we generate time series with finite length and varying frequency content but from independent stochastic processes. Using the correlation coefficient and the maximum cross-correlation, we estimate interdependencies between these time series. With clustering coefficient and average shortest path length, we observe unweighted interaction networks, derived via thresholding the values of interdependence, to possess non-trivial topologies as compared to Erdös-Rényi networks, which would indicate small-world characteristics. These topologies reflect the mostly unavoidable finiteness of the data, which limits the reliability of typically used estimators of signal interdependence. We propose random networks that are tailored to the way interaction networks are derived from empirical data. Through an exemplary investigation of multichannel electroencephalographic recordings of epileptic seizures--known for their complex spatial and temporal dynamics--we show that such random networks help to distinguish network properties of interdependence structures related to seizure dynamics from those spuriously induced by the applied methods of analysis.

Unraveling Spurious Properties of Interaction Networks with Tailored Random Networks

PubMed Central

Bialonski, Stephan; Wendler, Martin; Lehnertz, Klaus

2011-01-01

We investigate interaction networks that we derive from multivariate time series with methods frequently employed in diverse scientific fields such as biology, quantitative finance, physics, earth and climate sciences, and the neurosciences. Mimicking experimental situations, we generate time series with finite length and varying frequency content but from independent stochastic processes. Using the correlation coefficient and the maximum cross-correlation, we estimate interdependencies between these time series. With clustering coefficient and average shortest path length, we observe unweighted interaction networks, derived via thresholding the values of interdependence, to possess non-trivial topologies as compared to Erdös-Rényi networks, which would indicate small-world characteristics. These topologies reflect the mostly unavoidable finiteness of the data, which limits the reliability of typically used estimators of signal interdependence. We propose random networks that are tailored to the way interaction networks are derived from empirical data. Through an exemplary investigation of multichannel electroencephalographic recordings of epileptic seizures – known for their complex spatial and temporal dynamics – we show that such random networks help to distinguish network properties of interdependence structures related to seizure dynamics from those spuriously induced by the applied methods of analysis. PMID:21850239

A study comparison of two system model performance in estimated lifted index over Indonesia.

NASA Astrophysics Data System (ADS)

lestari, Juliana tri; Wandala, Agie

2018-05-01

Lifted index (LI) is one of atmospheric stability indices that used for thunderstorm forecasting. Numerical weather Prediction Models are essential for accurate weather forecast these day. This study has completed the attempt to compare the two NWP models these are Weather Research Forecasting (WRF) model and Global Forecasting System (GFS) model in estimates LI at 20 locations over Indonesia and verified the result with observation. Taylor diagram was used to comparing the models skill with shown the value of standard deviation, coefficient correlation and Root mean square error (RMSE). This study using the dataset on 00.00 UTC and 12.00 UTC during mid-March to Mid-April 2017. From the sample of LI distributions, both models have a tendency to overestimated LI value in almost all region in Indonesia while the WRF models has the better ability to catch the LI pattern distribution with observation than GFS model has. The verification result shows how both WRF and GFS model have such a weak relationship with observation except Eltari meteorologi station that its coefficient correlation reach almost 0.6 with the low RMSE value. Mean while WRF model have a better performance than GFS model. This study suggest that estimated LI of WRF model can provide the good performance for Thunderstorm forecasting over Indonesia in the future. However unsufficient relation between output models and observation in the certain location need a further investigation.

Comparison of body adiposity index (BAI) and air displacement plethysmograph with estimations of % body fat in adults with Down's syndrome.

PubMed

Rossato, M; Dellagrana, R A; de Souza Bezerra, E; da Costa, R M; Dos Santos, J O L; Silva, D A S; Diefenthaeler, F

2017-11-01

The aim of this study was to verify the agreement between body fat percentage (%BF) values evaluated by air displacement plethysmograph (ADP) and body adiposity index (BAI) in adults with Down's syndrome (DS). Forty-five adults with DS volunteered to participate in this study (19 women; age 28.7±8.5 years and 26 men; age 29.1±8.8 years). The %BF was measured by ADP (%BF ADP ) and estimated by anthropometric measures [%BF=(hip circumference/height) 1.5 -18] (%BF BAI ). Agreement between methods was evaluated by paired t-test, Pearson's correlation coefficient and Bland-Altman analysis. Although high correlation coefficients were found between %BF ADP and %BF BAI for women (r=0.78, P<0.05) and men (r=0.87, P<0.05), significant differences were observed between methods for both sexes (38.9±8.9 vs 42.5±8.5% for women, and 25.8±11.3 vs 32.6±5.4% for men in %BF ADP and %BF BAI , respectively). Moreover, Bland-Altman analysis showed that the mean error estimate was +3.6 (95%CI, -7.59 to 14.79) in women and +6.74 (95%CI, -7.25 to 20.72) in men. The results indicate that BAI seems to be a limited method to evaluate %BF in women and in men with DS.

The best alternative for estimating reference crop evapotranspiration in different sub-regions of mainland China.

PubMed

Peng, Lingling; Li, Yi; Feng, Hao

2017-07-14

Reference crop evapotranspiration (ET o ) is a critically important parameter for climatological, hydrological and agricultural management. The FAO56 Penman-Monteith (PM) equation has been recommended as the standardized ET o (ET o,s ) equation, but it has a high requirements of climatic data. There is a practical need for finding a best alternative method to estimate ET o in the regions where full climatic data are lacking. A comprehensive comparison for the spatiotemporal variations, relative errors, standard deviations and Nash-Sutcliffe efficacy coefficients of monthly or annual ET o,s and ET o,i (i = 1, 2, …, 10) values estimated by 10 selected methods (i.e., Irmak et al., Makkink, Priestley-Taylor, Hargreaves-Samani, Droogers-Allen, Berti et al., Doorenbos-Pruitt, Wright and Valiantzas, respectively) using data at 552 sites over 1961-2013 in mainland China. The method proposed by Berti et al. (2014) was selected as the best alternative of FAO56-PM because it was simple in computation process, only utilized temperature data, had generally good accuracy in describing spatiotemporal characteristics of ET o,s in different sub-regions and mainland China, and correlated linearly to the FAO56-PM method very well. The parameters of the linear correlations between ET o of the two methods are calibrated for each site with the smallest determination of coefficient being 0.87.

Weak data do not make a free lunch, only a cheap meal

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

Luo, Zhipu; Rajashankar, Kanagalaghatta; Dauter, Zbigniew

2014-01-17

Four data sets were processed at resolutions significantly exceeding the criteria traditionally used for estimating the diffraction data resolution limit. The analysis of these data and the corresponding model-quality indicators suggests that the criteria of resolution limits widely adopted in the past may be somewhat conservative. Various parameters, such asR mergeandI/σ(I), optical resolution and the correlation coefficients CC 1/2and CC*, can be used for judging the internal data quality, whereas the reliability factorsRandR freeas well as the maximum-likelihood target values and real-space map correlation coefficients can be used to estimate the agreement between the data and the refined model. However,more » none of these criteria provide a reliable estimate of the data resolution cutoff limit. The analysis suggests that extension of the maximum resolution by about 0.2 Å beyond the currently adopted limit where theI/σ(I) value drops to 2.0 does not degrade the quality of the refined structural models, but may sometimes be advantageous. Such an extension may be particularly beneficial for significantly anisotropic diffraction. Extension of the maximum resolution at the stage of data collection and structure refinement is cheap in terms of the required effort and is definitely more advisable than accepting a too conservative resolution cutoff, which is unfortunately quite frequent among the crystal structures deposited in the Protein Data Bank.« less

The Effectiveness of Using Limited Gauge Measurements for Bias Adjustment of Satellite-Based Precipitation Estimation over Saudi Arabia

NASA Astrophysics Data System (ADS)

Alharbi, Raied; Hsu, Kuolin; Sorooshian, Soroosh; Braithwaite, Dan

2018-01-01

Precipitation is a key input variable for hydrological and climate studies. Rain gauges are capable of providing reliable precipitation measurements at point scale. However, the uncertainty of rain measurements increases when the rain gauge network is sparse. Satellite -based precipitation estimations appear to be an alternative source of precipitation measurements, but they are influenced by systematic bias. In this study, a method for removing the bias from the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) over a region where the rain gauge is sparse is investigated. The method consists of monthly empirical quantile mapping, climate classification, and inverse-weighted distance method. Daily PERSIANN-CCS is selected to test the capability of the method for removing the bias over Saudi Arabia during the period of 2010 to 2016. The first six years (2010 - 2015) are calibrated years and 2016 is used for validation. The results show that the yearly correlation coefficient was enhanced by 12%, the yearly mean bias was reduced by 93% during validated year. Root mean square error was reduced by 73% during validated year. The correlation coefficient, the mean bias, and the root mean square error show that the proposed method removes the bias on PERSIANN-CCS effectively that the method can be applied to other regions where the rain gauge network is sparse.

Sex Estimation from Human Cranium: Forensic and Anthropological Interest of Maxillary Sinus Volumes.

PubMed

Radulesco, Thomas; Michel, Justin; Mancini, Julien; Dessi, Patrick; Adalian, Pascal

2018-05-01

Sex estimation is a key objective of forensic science. We aimed to establish whether maxillary sinus volumes (MSV) could assist in estimating an individual's sex. One hundred and three CT scans were included. MSV were determined using three-dimensional reconstructions. Two observers performed three-dimensional MSV reconstructions using the same methods. Intra- and interobserver reproducibility were statistically compared using the intraclass correlation coefficient (ICC) (α = 5%). Both intra- and interobserver reproducibility were perfect regarding MSV; both ICCs were 100%. There were no significant differences between right and left MSV (p = 0.083). No correlation was found between age and MSV (p > 0.05). We demonstrated the existence of sexual dimorphism in MSV (p < 0.001) and showed that MSV measurements gave a 68% rate of correct allocations to sex group. MSV measurements could be useful to support sex estimation in forensic medicine. © 2017 American Academy of Forensic Sciences.

Parameter Estimation for the Four Parameter Beta Distribution.

DTIC Science & Technology

1983-12-01

060 1,000 ,033 -,027 -+046 -. 047 .042 1,000 ITERATIONS FCN2 USED FCN4 USED DIVERGED 4,9260 0.0000 . 4640 o0460 SAMPLE SIZE+ 10 ESTIMATOR: MME1 SEED ; 1...903 .278 1.000 -. 271 .882 .538 1.000 -. 078 -. 202 .038 -� 1.000 .050 .228 -o050 .086 .019 1.000 ITERATIONS FCN2 USED FCN4 USED DIVERGED...5.6575 33.2908 .0507 1.1332 .0002 .0000 .0000 .0007 CORRELATION COEFFICIENTS: 1.000 -. 058 1.000 -.914 . 262 1.000 -. 270 .895 .534 1.000 .021 .030 -,045

Numerical determination of lateral loss coefficients for subchannel analysis in nuclear fuel bundles

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

Sin Kim; Goon-Cherl Park

1995-09-01

An accurate prediction of cross-flow based on detailed knowledge of the velocity field in subchannels of a nuclear fuel assembly is of importance in nuclear fuel performance analysis. In this study, the low-Reynolds number {kappa}-{epsilon} turbulence model has been adopted in two adjacent subchannels with cross-flow. The secondary flow is estimated accurately by the anisotropic algebraic Reynolds stress model. This model was numerically calculated by the finite element method and has been verified successfully through comparison with existing experimental data. Finally, with the numerical analysis of the velocity field in such subchannel domain, an analytical correlation of the lateral lossmore » coefficient is obtained to predict the cross-flow rate in subchannel analysis codes. The correlation is expressed as a function of the ratio of the lateral flow velocity to the donor subchannel axial velocity, recipient channel Reynolds number and pitch-to-diameter.« less

Fixed-bed column studies of total organic carbon removal from industrial wastewater by use of diatomite decorated with polyethylenimine-functionalized pyroxene nanoparticles.

PubMed

Hethnawi, Afif; Manasrah, Abdallah D; Vitale, Gerardo; Nassar, Nashaat N

2018-03-01

In this study, a fixed-bed column adsorption process was employed to remove organic pollutants from a real industrial wastewater effluent using polyethylenimine-functionalized pyroxene nanoparticles (PEI-PY) embedded into Diatomite at very low mass percentage. Various dynamic parameters (e.g., inlet concentration, inlet flow rate, bed height, and PEI-nanoparticle concentration in Diatomite, (%nps)) were investigated to determine the breakthrough behavior. The obtained breakthrough curves were fit with a convection-dispersion model to determine the characteristic parameters based on mass transfer phenomena. The axial dispersion coefficient (D L ) and group of dimensionless numbers; including Renold number (Re), Schmidt number (Sc), and Sherwood number (Sh) were all determined and correlated by Wilson-Geankoplis correlation that was used to estimate the external film diffusion coefficients (Kc) at 0.0015 < Re<55. Copyright © 2017 Elsevier Inc. All rights reserved.

Body temperature measurements in pigs during general anaesthesia.

PubMed

Musk, G C; Costa, R S; Tuke, J

2016-04-01

The aim was to compare rectal, pharyngeal and oesophageal temperature measurements in anaesthetized pigs. Data were compared using the Bland-Altman method, and correlation coefficients and error measures were calculated. Sixty-six sets of data were collected from 16 pigs weighing 16.2 ± 4.2 kg. The bias (and 95% limit of agreement) for rectal and pharyngeal compared with oesophageal temperature were 0.69 (-1.18 to 2.57) ℃ and 0.22 (-0.84 to 1.28) ℃, respectively. The correlation coefficients for rectal and pharyngeal compared with oesophageal temperature were 0.47 and 0.87, respectively. The absolute error for rectal and pharyngeal compared with oesophageal temperature was 0.7 ± 0.9℃ and 0.2 ± 0.5℃, respectively. Pharyngeal temperature measurement may be more suitable than rectal temperature measurement for estimation of oesophageal temperature during general anaesthesia of pigs. © The Author(s) 2015.

Partial Roc Reveals Superiority of Mutual Rank of Pearson's Correlation Coefficient as a Coexpression Measure to Elucidate Functional Association of Genes

NASA Astrophysics Data System (ADS)

Obayashi, Takeshi; Kinoshita, Kengo

2013-01-01

Gene coexpression analysis is a powerful approach to elucidate gene function. We have established and developed this approach using vast amount of publicly available gene expression data measured by microarray techniques. The coexpressed genes are used to estimate gene function of the guide gene or to construct gene coexpression networks. In the case to construct gene networks, researchers should introduce an arbitrary threshold of gene coexpression, because gene coexpression value is continuous value. In the viewpoint to introduce common threshold of gene coexpression, we previously reported rank of Pearson's correlation coefficient (PCC) is more useful than the original PCC value. In this manuscript, we re-assessed the measure of gene coexpression to construct gene coexpression network, and found that mutual rank (MR) of PCC showed better performance than rank of PCC and the original PCC in low false positive rate.

Three-parameter modeling of the soil sorption of acetanilide and triazine herbicide derivatives.

PubMed

Freitas, Mirlaine R; Matias, Stella V B G; Macedo, Renato L G; Freitas, Matheus P; Venturin, Nelson

2014-02-01

Herbicides have widely variable toxicity and many of them are persistent soil contaminants. Acetanilide and triazine family of herbicides have widespread use, but increasing interest for the development of new herbicides has been rising to increase their effectiveness and to diminish environmental hazard. The environmental risk of new herbicides can be accessed by estimating their soil sorption (logKoc), which is usually correlated to the octanol/water partition coefficient (logKow). However, earlier findings have shown that this correlation is not valid for some acetanilide and triazine herbicides. Thus, easily accessible quantitative structure-property relationship models are required to predict logKoc of analogues of the these compounds. Octanol/water partition coefficient, molecular weight and volume were calculated and then regressed against logKoc for two series of acetanilide and triazine herbicides using multiple linear regression, resulting in predictive and validated models.

Absolute binding free energies between T4 lysozyme and 141 small molecules: calculations based on multiple rigid receptor configurations

PubMed Central

Xie, Bing; Nguyen, Trung Hai; Minh, David D. L.

2017-01-01

We demonstrate the feasibility of estimating protein-ligand binding free energies using multiple rigid receptor configurations. Based on T4 lysozyme snapshots extracted from six alchemical binding free energy calculations with a flexible receptor, binding free energies were estimated for a total of 141 ligands. For 24 ligands, the calculations reproduced flexible-receptor estimates with a correlation coefficient of 0.90 and a root mean square error of 1.59 kcal/mol. The accuracy of calculations based on Poisson-Boltzmann/Surface Area implicit solvent was comparable to previously reported free energy calculations. PMID:28430432

Harmonic regression of Landsat time series for modeling attributes from national forest inventory data

NASA Astrophysics Data System (ADS)

Wilson, Barry T.; Knight, Joseph F.; McRoberts, Ronald E.

2018-03-01

Imagery from the Landsat Program has been used frequently as a source of auxiliary data for modeling land cover, as well as a variety of attributes associated with tree cover. With ready access to all scenes in the archive since 2008 due to the USGS Landsat Data Policy, new approaches to deriving such auxiliary data from dense Landsat time series are required. Several methods have previously been developed for use with finer temporal resolution imagery (e.g. AVHRR and MODIS), including image compositing and harmonic regression using Fourier series. The manuscript presents a study, using Minnesota, USA during the years 2009-2013 as the study area and timeframe. The study examined the relative predictive power of land cover models, in particular those related to tree cover, using predictor variables based solely on composite imagery versus those using estimated harmonic regression coefficients. The study used two common non-parametric modeling approaches (i.e. k-nearest neighbors and random forests) for fitting classification and regression models of multiple attributes measured on USFS Forest Inventory and Analysis plots using all available Landsat imagery for the study area and timeframe. The estimated Fourier coefficients developed by harmonic regression of tasseled cap transformation time series data were shown to be correlated with land cover, including tree cover. Regression models using estimated Fourier coefficients as predictor variables showed a two- to threefold increase in explained variance for a small set of continuous response variables, relative to comparable models using monthly image composites. Similarly, the overall accuracies of classification models using the estimated Fourier coefficients were approximately 10-20 percentage points higher than the models using the image composites, with corresponding individual class accuracies between six and 45 percentage points higher.

Identification of Correlated GRACE Monthly Harmonic Coefficients Using Pattern Recognition and Neural Networks

NASA Astrophysics Data System (ADS)

Piretzidis, D.; Sra, G.; Sideris, M. G.

2016-12-01

This study explores new methods for identifying correlation errors in harmonic coefficients derived from monthly solutions of the Gravity Recovery and Climate Experiment (GRACE) satellite mission using pattern recognition and neural network algorithms. These correlation errors are evidenced in the differences between monthly solutions and can be suppressed using a de-correlation filter. In all studies so far, the implementation of the de-correlation filter starts from a specific minimum order (i.e., 11 for RL04 and 38 for RL05) until the maximum order of the monthly solution examined. This implementation method has two disadvantages, namely, the omission of filtering correlated coefficients of order less than the minimum order and the filtering of uncorrelated coefficients of order higher than the minimum order. In the first case, the filtered solution is not completely free of correlated errors, whereas the second case results in a monthly solution that suffers from loss of geophysical signal. In the present study, a new method of implementing the de-correlation filter is suggested, by identifying and filtering only the coefficients that show indications of high correlation. Several numerical and geometric properties of the harmonic coefficient series of all orders are examined. Extreme cases of both correlated and uncorrelated coefficients are selected, and their corresponding properties are used to train a two-layer feed-forward neural network. The objective of the neural network is to identify and quantify the correlation by providing the probability of an order of coefficients to be correlated. Results show good performance of the neural network, both in the validation stage of the training procedure and in the subsequent use of the trained network to classify independent coefficients. The neural network is also capable of identifying correlated coefficients even when a small number of training samples and neurons are used (e.g.,100 and 10, respectively).

Quantitative differentiation of breast lesions at 3T diffusion-weighted imaging (DWI) using the ratio of distributed diffusion coefficient (DDC).

PubMed

Ertas, Gokhan; Onaygil, Can; Akin, Yasin; Kaya, Handan; Aribal, Erkin

2016-12-01

To investigate the accuracy of diffusion coefficients and diffusion coefficient ratios of breast lesions and of glandular breast tissue from mono- and stretched-exponential models for quantitative diagnosis in diffusion-weighted magnetic resonance imaging (MRI). We analyzed pathologically confirmed 170 lesions (85 benign and 85 malignant) imaged using a 3.0T MR scanner. Small regions of interest (ROIs) focusing on the highest signal intensity for lesions and also for glandular tissue of contralateral breast were obtained. Apparent diffusion coefficient (ADC) and distributed diffusion coefficient (DDC) were estimated by performing nonlinear fittings using mono- and stretched-exponential models, respectively. Coefficient ratios were calculated by dividing the lesion coefficient by the glandular tissue coefficient. A stretched exponential model provides significantly better fits then the monoexponential model (P < 0.001): 65% of the better fits for glandular tissue and 71% of the better fits for lesion. High correlation was found in diffusion coefficients (0.99-0.81 and coefficient ratios (0.94) between the models. The highest diagnostic accuracy was found by the DDC ratio (area under the curve [AUC] = 0.93) when compared with lesion DDC, ADC ratio, and lesion ADC (AUC = 0.91, 0.90, 0.90) but with no statistically significant difference (P > 0.05). At optimal thresholds, the DDC ratio achieves 93% sensitivity, 80% specificity, and 87% overall diagnostic accuracy, while ADC ratio leads to 89% sensitivity, 78% specificity, and 83% overall diagnostic accuracy. The stretched exponential model fits better with signal intensity measurements from both lesion and glandular tissue ROIs. Although the DDC ratio estimated by using the model shows a higher diagnostic accuracy than the ADC ratio, lesion DDC, and ADC, it is not statistically significant. J. Magn. Reson. Imaging 2016;44:1633-1641. © 2016 International Society for Magnetic Resonance in Medicine.

Anthropometry for design for the elderly.

PubMed

Kothiyal, K; Tettey, S

2001-01-01

This paper presents anthropometric data on elderly people in Australia. Data were collected in the metropolitan city of Sydney, NSW, Australia. In all 171 elderly people (males and females, aged 65 years and above) took part in the study. Mean values, standard deviations, medians, range, and coefficients of variation for the various body dimensions were estimated. Correlation coefficients were also calculated to determine the relationship between different body dimensions for the elderly population. The mean stature of elderly Australian males and females were compared with populations from other countries. The paper discusses design implications for elderly people and provides several examples of application of the anthropometric data.

Measuring Perceived Educational Impact of a Resident-Led Research Newsletter.

PubMed

Aftab, Awais; Lackamp, Jeanne; Cerny, Cathleen

2017-06-01

To determine the perceived educational impact of a resident-led psychiatry research newsletter ('Research Watch') on the psychiatry residents at the authors' residency program. An anonymous, voluntary paper questionnaire was distributed to all psychiatry residents at the program. The survey inquired about the degree of exposure (quantified as 'exposure index') and contribution to the newsletter. A set of questions asked residents to estimate how much of the improvement they attributed to the influence of the newsletter, rating the attribution between 0 and 100%, in the areas of interest in scholarly activities/research, knowledge of current psychiatric research, and participation in scholarly activities/research. The survey also inquired if the newsletter had any impact on their clinical practice. Of 29 residents in the program who received the survey, 27 (93%) responded. The percentage of residents reporting perceived non-zero impact of the newsletter on specific areas of improvement was as follows: interest in scholarly activities/research (44%), knowledge of current psychiatric research (48%), participation in scholarly activities/research (40%), and clinical practice (40%). Exposure index significantly and positively correlated with self-reported percentage attribution for knowledge (correlation coefficient 0.422, p value 0.028) and self-reported impact on clinical practice (correlation coefficient 0.660, p value 0.000), and degree of contribution significantly and positively correlated with self-reported percentage attribution for knowledge (correlation coefficient 0.488, p value 0.010). A resident-led research newsletter can have a positive perceived impact on the residents' interest, knowledge, and participation in research, as well as a positive perceived impact on clinical practice.

Correlation between lung to thorax transverse area ratio and observed/expected lung area to head circumference ratio in fetuses with left-sided diaphragmatic hernia.

PubMed

Hidaka, Nobuhiro; Murata, Masaharu; Sasahara, Jun; Ishii, Keisuke; Mitsuda, Nobuaki

2015-05-01

Observed/expected lung area to head circumference ratio (o/e LHR) and lung to thorax transverse area ratio (LTR) are the sonographic indicators of postnatal outcome in fetuses with congenital diaphragmatic hernia (CDH), and they are not influenced by gestational age. We aimed to evaluate the relationship between these two parameters in the same subjects with fetal left-sided CDH. Fetuses with left-sided CDH managed between 2005 and 2012 were included. Data of LTR and o/e LHR values measured on the same day prior to 33 weeks' gestation in target fetuses were retrospectively collected. The correlation between the two parameters was estimated using the Spearman's rank-correlation coefficient, and linear regression analysis was used to assess the relationship between them. Data on 61 measurements from 36 CDH fetuses were analyzed to obtain a Spearman's rank-correlation coefficient of 0.74 with the following linear equation: LTR = 0.002 × (o/e LHR) + 0.005. The determination coefficient of this linear equation was sufficiently high at 0.712, and the prediction accuracy obtained with this regression formula was considered satisfactory. A good linear correlation between the LTR and the o/e LHR was obtained, suggesting that we can translate the predictive parameters for each other. This information is expected to be useful to improve our understanding of different investigations focusing on LTR or o/e LHR as a predictor of postnatal outcome in CDH. © 2014 Japanese Teratology Society.

Meteorological adjustment of yearly mean values for air pollutant concentration comparison

NASA Technical Reports Server (NTRS)

Sidik, S. M.; Neustadter, H. E.

1976-01-01

Using multiple linear regression analysis, models which estimate mean concentrations of Total Suspended Particulate (TSP), sulfur dioxide, and nitrogen dioxide as a function of several meteorologic variables, two rough economic indicators, and a simple trend in time are studied. Meteorologic data were obtained and do not include inversion heights. The goodness of fit of the estimated models is partially reflected by the squared coefficient of multiple correlation which indicates that, at the various sampling stations, the models accounted for about 23 to 47 percent of the total variance of the observed TSP concentrations. If the resulting model equations are used in place of simple overall means of the observed concentrations, there is about a 20 percent improvement in either: (1) predicting mean concentrations for specified meteorological conditions; or (2) adjusting successive yearly averages to allow for comparisons devoid of meteorological effects. An application to source identification is presented using regression coefficients of wind velocity predictor variables.

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

Shirazi, M.A.; Davis, L.R.

To obtain improved prediction of heated plume characteristics from a surface jet, an integral analysis computer model was modified and a comprehensive set of field and laboratory data available from the literature was gathered, analyzed, and correlated for estimating the magnitude of certain coefficients that are normally introduced in these analyses to achieve closure. The parameters so estimated include the coefficients for entrainment, turbulent exchange, drag, and shear. Since there appeared considerable scatter in the data, even after appropriate subgrouping to narrow the influence of various flow conditions on the data, only statistical procedures could be applied to find themore » best fit. This and other analyses of its type have been widely used in industry and government for the prediction of thermal plumes from steam power plants. Although the present model has many shortcomings, a recent independent and exhaustive assessment of such predictions revealed that in comparison with other analyses of its type the present analysis predicts the field situations more successfully.« less

Estimation of Koc values for deuterated benzene, toluene, and ethylbenzene, and application to ground water contamination studies.

PubMed

Poulson, S R; Drever, J I; Colberg, P J

1997-11-01

Sorption partition coefficients between water and organic carbon (Koc) for deuterated benzene, toluene, and ethylbenzene have been estimated by measuring values of the octanol-water partition coefficient (Kow) and HPLC retention factors (k1), which correlate closely to values of Koc. Measured values of log Kow for non-deuterated and deuterated toluene are 2.77 (+/- 0.02) and 2.78 (+/- 0.04), respectively, indicating that within experimental error, log Koc for deuterated and non-deuterated toluene are the same. The HPLC method provides greater precision, and yields values of delta log Koc (= log Koc [deuterated]-log Koc [non-deuterated]) of -0.021 (+/- 0.001) for benzene, -0.028 (+/- 0.002) for toluene, and -0.035 (+/- 0.003) for ethylbenzene. The small values of delta log Koc demonstrates that deuterated compounds are excellent tracers for the hydrologic behavior of ground water contaminants.

Multivariate space - time analysis of PRE-STORM precipitation

NASA Technical Reports Server (NTRS)

Polyak, Ilya; North, Gerald R.; Valdes, Juan B.

1994-01-01

This paper presents the methodologies and results of the multivariate modeling and two-dimensional spectral and correlation analysis of PRE-STORM rainfall gauge data. Estimated parameters of the models for the specific spatial averages clearly indicate the eastward and southeastward wave propagation of rainfall fluctuations. A relationship between the coefficients of the diffusion equation and the parameters of the stochastic model of rainfall fluctuations is derived that leads directly to the exclusive use of rainfall data to estimate advection speed (about 12 m/s) as well as other coefficients of the diffusion equation of the corresponding fields. The statistical methodology developed here can be used for confirmation of physical models by comparison of the corresponding second-moment statistics of the observed and simulated data, for generating multiple samples of any size, for solving the inverse problem of the hydrodynamic equations, and for application in some other areas of meteorological and climatological data analysis and modeling.

Predicting SF-6D utility scores from the Oswestry disability index and numeric rating scales for back and leg pain.

PubMed

Carreon, Leah Y; Glassman, Steven D; McDonough, Christine M; Rampersaud, Raja; Berven, Sigurd; Shainline, Michael

2009-09-01

Cross-sectional cohort. The purpose of this study is to provide a model to allow estimation of utility from the Short Form (SF)-6D using data from the Oswestry Disability Index (ODI), Back Pain Numeric Rating Scale (BPNRS), and the Leg Pain Numeric Rating Scale (LPNRS). Cost-utility analysis provides important information about the relative value of interventions and requires a measure of utility not often available from clinical trial data. The ODI and numeric rating scales for back (BPNRS) and leg pain (LPNRS), are widely used disease-specific measures for health-related quality of life in patients with lumbar degenerative disorders. The purpose of this study is to provide a model to allow estimation of utility from the SF-6D using data from the ODI, BPNRS, and the LPNRS. SF-36, ODI, BPNRS, and LPNRS were prospectively collected before surgery, at 12 and 24 months after surgery in 2640 patients undergoing lumbar fusion for degenerative disorders. Spearman correlation coefficients for paired observations from multiple time points between ODI, BPNRS, and LPNRS, and SF-6D utility scores were determined. Regression modeling was done to compute the SF-6D score from the ODI, BPNRS, and LPNRS. Using a separate, independent dataset of 2174 patients in which actual SF-6D and ODI scores were available, the SF-6D was estimated for each subject and compared to their actual SF-6D. In the development sample, the mean age was 52.5 +/- 15 years and 34% were male. In the validation sample, the mean age was 52.9 +/- 14.2 years and 44% were male. Correlations between the SF-6D and the ODI, BPNRS, and LPNRS were statistically significant (P < 0.0001) with correlation coefficients of 0.82, 0.78, and 0.72, respectively. The regression equation using ODI, BPNRS,and LPNRS to predict SF-6D had an R of 0.69 and a root mean square error of 0.076. The model using ODI alone had an R of 0.67 and a root mean square error of 0.078. The correlation coefficient between the observed and estimated SF-6D score was 0.80. In the validation analysis, there was no statistically significant difference (P = 0.11) between actual mean SF-6D (0.55 +/- 0.12) and the estimated mean SF-6D score (0.55 +/- 0.10) using the ODI regression model. This regression-based algorithm may be used to predict SF-6D scores in studies of lumbar degenerative disease that have collected ODI but not utility scores.

Predicting SF-6D utility scores from the Oswestry Disability Index and Numeric Rating Scales for Back and Leg Pain

PubMed Central

Carreon, Leah Y.; Glassman, Steven D.; McDonough, Christine M.; Rampersaud, Raja; Berven, Sigurd; Shainline, Michael

2012-01-01

Study Design Cross-sectional cohort Objective The purpose of this study is to provide a model to allow estimation of utility from the SF-6D using data from the ODI, BPNRS, and the LPNRS. Summary of Background Data Cost-utility analysis provides important information about the relative value of interventions and requires a measure of utility not often available from clinical trial data. The Oswestry Disability Index (ODI) and numeric rating scales for back (BPNRS) and leg pain (LPNRS), are widely used disease-specific measures for health-related quality of life in patients with lumbar degenerative disorders. The purpose of this study is to provide a model to allow estimation of utility from the SF-6D using data from the ODI, BPNRS, and the LPNRS. Methods SF-36, ODI, BPNRS and LPNRS were prospectively collected pre-operatively, at 12 and 24 months post-operatively in 2640 patients undergoing lumbar fusion for degenerative disorders. Spearman correlation coefficients for paired observations from multiple time points between ODI, BPNRS and LPNRS and SF-6D utility scores were determined. Regression modeling was done to compute the SF-6D score from the ODI, BPNRS and LPNRS. Using a separate, independent dataset of 2174 patients in which actual SF-6D and ODI scores were available, the SF-6D was estimated for each subject and compared to their actual SF-6D. Results In the development sample, the mean age was 52.5 ± 15 years and 34% were male. In the validation sample the mean age was 52.9 ± 14.2 years and 44% were male. Correlations between the SF-6D and the ODI, BPNRS and LPNRS were statistically significant (p<0.0001) with correlation coefficients of 0.82, 0.78, and 0.72 respectively. The regression equation using ODI, BPNRS and LPNRS to predict SF-6D had an R2 of 0.69 and a root mean square error (RMSE) of 0.076. The model using ODI alone had an R2 of 0.67 and a RMSE of 0.078. The correlation coefficient between the observed and estimated SF-6D score was 0.80. In the validation analysis, there was no statistically significant difference (p=0.11) between actual mean SF-6D (0.55 ± 0.12) and the estimated mean SF-6D score (0.55 ± 0.10) using the ODI regression model. Conclusion This regression-based algorithm may be used to predict SF-6D scores in studies of lumbar degenerative disease that have collected ODI but not utility scores. PMID:19730215

Extracting near-surface QL between 1-4 Hz from higher-order noise correlations in the Euroseistest area, Greece

NASA Astrophysics Data System (ADS)

Haendel, A.; Ohrnberger, M.; Krüger, F.

2016-11-01

Knowledge of the quality factor of near-surface materials is of fundamental interest in various applications. Attenuation can be very strong close to the surface and thus needs to be properly assessed. In recent years, several researchers have studied the retrieval of attenuation coefficients from the cross correlation of ambient seismic noise. Yet, the determination of exact amplitude information from noise-correlation functions is, in contrast to the extraction of traveltimes, not trivial. Most of the studies estimated attenuation coefficients on the regional scale and within the microseism band. In this paper, we investigate the possibility to derive attenuation coefficients from seismic noise at much shallower depths and higher frequencies (>1 Hz). The Euroseistest area in northern Greece offers ideal conditions to study quality factor retrieval from ambient noise for different rock types. Correlations are computed between the stations of a small scale array experiment (station spacings <2 km) that was carried out in the Euroseistest area in 2011. We employ the correlation of the coda of the correlation (C3) method instead of simple cross correlations to mitigate the effect of uneven noise source distributions on the correlation amplitude. Transient removal and temporal flattening are applied instead of 1-bit normalization in order to retain relative amplitudes. The C3 method leads to improved correlation results (higher signal-to-noise ratio and improved time symmetry) compared to simple cross correlations. The C3 functions are rotated from the ZNE to the ZRT system and we focus on Love wave arrivals on the transverse component and on Love wave quality factors QL. The analysis is performed for selected stations being either situated on soft soil or on weathered rock. Phase slowness is extracted using a slant-stack method. Attenuation parameters are inferred by inspecting the relative amplitude decay of Love waves with increasing interstation distance. We observe that the attenuation coefficient γ and QL can be reliably extracted for stations situated on soft soil whereas the derivation of attenuation parameters is more problematic for stations that are located on weathered rock. The results are in acceptable conformance with theoretical Love wave attenuation curves that were computed using 1-D shear wave velocity and quality factor profiles from the Euroseistest area.

Estimation of heat transfer coefficients for biomass particles by direct numerical simulation using microstructured particle models in the Laminar regime

DOE PAGES

Pecha, M. Brennan; Garcia-Perez, Manuel; Foust, Thomas D.; ...

2016-11-08

Here, direct numerical simulation of convective heat transfer from hot gas to isolated biomass particle models with realistic morphology and explicit microstructure was performed over a range of conditions with laminar flow of hot gas (500 degrees C). Steady-state results demonstrated that convective interfacial heat transfer is dependent on the wood species. The computed heat transfer coefficients were shown to vary between the pine and aspen models by nearly 20%. These differences are attributed to the species-specific variations in the exterior surface morphology of the biomass particles. We also quantify variations in heat transfer experienced by the particle when positionedmore » in different orientations with respect to the direction of fluid flow. These results are compared to previously reported heat transfer coefficient correlations in the range of 0.1 < Pr < 1.5 and 10 < Re < 500. Comparison of these simulation results to correlations commonly used in the literature (Gunn, Ranz-Marshall, and Bird-Stewart-Lightfoot) shows that the Ranz-Marshall (sphere) correlation gave the closest h values to our steady-state simulations for both wood species, though no existing correlation was within 20% of both species at all conditions studied. In general, this work exemplifies the fact that all biomass feedstocks are not created equal, and that their species-specific characteristics must be appreciated in order to facilitate accurate simulations of conversion processes.« less

Estimation of heat transfer coefficients for biomass particles by direct numerical simulation using microstructured particle models in the Laminar regime

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

Pecha, M. Brennan; Garcia-Perez, Manuel; Foust, Thomas D.

Here, direct numerical simulation of convective heat transfer from hot gas to isolated biomass particle models with realistic morphology and explicit microstructure was performed over a range of conditions with laminar flow of hot gas (500 degrees C). Steady-state results demonstrated that convective interfacial heat transfer is dependent on the wood species. The computed heat transfer coefficients were shown to vary between the pine and aspen models by nearly 20%. These differences are attributed to the species-specific variations in the exterior surface morphology of the biomass particles. We also quantify variations in heat transfer experienced by the particle when positionedmore » in different orientations with respect to the direction of fluid flow. These results are compared to previously reported heat transfer coefficient correlations in the range of 0.1 < Pr < 1.5 and 10 < Re < 500. Comparison of these simulation results to correlations commonly used in the literature (Gunn, Ranz-Marshall, and Bird-Stewart-Lightfoot) shows that the Ranz-Marshall (sphere) correlation gave the closest h values to our steady-state simulations for both wood species, though no existing correlation was within 20% of both species at all conditions studied. In general, this work exemplifies the fact that all biomass feedstocks are not created equal, and that their species-specific characteristics must be appreciated in order to facilitate accurate simulations of conversion processes.« less

Genotypic character relationship and phenotypic path coefficient analysis in chili pepper genotypes grown under tropical condition.

PubMed

Usman, Magaji G; Rafii, Mohd Y; Martini, Mohammad Y; Oladosu, Yusuff; Kashiani, Pedram

2017-03-01

Studies on genotypic and phenotypic correlations among characters of crop plants are useful in planning, evaluating and setting selection criteria for the desired characters in a breeding program. The present study aimed to estimate the phenotypic correlation coefficients among yield and yield attributed characters and to work out the direct and indirect effects of yield-related characters on yield per plant using path coefficient analysis. Twenty-six genotypes of chili pepper were laid out in a randomized complete block design with three replications. Yield per plant showed positive and highly significant (P ≤ 0.01) correlations with most of the characters studied at both the phenotypic and genotypic levels. By contrast, disease incidence and days to flowering showed a significant negative association with yield. Fruit weight and number of fruits exerted positive direct effect on yield and also had a positive and significant (P ≤ 0.01) correlation with yield per plant. However, fruit length showed a low negative direct effect with a strong and positive indirect effect through fruit weight on yield and had a positive and significant association with yield. Longer fruits, heavy fruits and a high number of fruits are variables that are related to higher yields of chili pepper under tropical conditions and hence could be used as a reliable indicator in indirect selection for yield. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Correlation of Hip Fracture with Other Fracture Types: Toward a Rational Composite Hip Fracture Endpoint

PubMed Central

Colón-Emeric, Cathleen; Pieper, Carl F.; Grubber, Janet; Van Scoyoc, Lynn; Schnell, Merritt L; Van Houtven, Courtney Harold; Pearson, Megan; Lafleur, Joanne; Lyles, Kenneth W.; Adler, Robert A.

2016-01-01

Purpose With ethical requirements to the enrollment of lower risk subjects, osteoporosis trials are underpowered to detect reduction in hip fractures. Different skeletal sites have different levels of fracture risk and response to treatment. We sought to identify fracture sites which cluster with hip fracture at higher than expected frequency; if these sites respond to treatment similarly, then a composite fracture endpoint could provide a better estimate of hip fracture reduction. Methods Cohort study using Veterans Affairs and Medicare administrative data. Male Veterans (n=5,036,536) aged 50-99 years receiving VA primary care between1999-2009 were included. Fractures were ascertained using ICD9 and CPT codes and classified by skeletal site. Pearson correlation coefficients, logistic regression and kappa statistics, were used to describe the correlation between each fracture type and hip fracture within individuals, without regards to the timing of the events. Results 595,579 (11.8%) men suffered 1 or more fractures and 179,597 (3.6%) suffered 2 or more fractures during the time under study. Of those with one or more fractures, rib was the most common site (29%), followed by spine (22%), hip (21%) and femur (20%). The fracture types most highly correlated with hip fracture were pelvic/acetabular (Pearson correlation coefficient 0.25, p<0.0001), femur (0.15, p<0.0001), and shoulder (0.11, p<0.0001). Conclusions Pelvic, acetabular, femur, and shoulder fractures cluster with hip fractures within individuals at greater than expected frequency. If we observe similar treatment risk reductions within that cluster, subsequent trials could consider use of a composite endpoint to better estimate hip fracture risk. PMID:26151123

Regression analysis and categorical agreement of fluconazole disk zone diameters and minimum inhibitory concentration by broth microdilution of clinical isolates of Candida.

PubMed

Aggarwal, P; Kashyap, B

2017-06-01

Rampant use of fluconazole in Candida infections has led to predominance of less susceptible non-albicans Candida over Candida albicans. The aim of the study was to determine if zone diameters around fluconazole disk can be used to estimate the minimum inhibitory concentration (MIC) for clinical isolates of Candida species and vice versa. Categorical agreement between the Clinical & Laboratory Standards Institute (CLSI) recommended disk diffusion and CLSI broth microdilution method was sought for. Antifungal susceptibility testing by disk diffusion and Broth microdilution was done as per CLSI document M44-S3 and CLSI document M27-S4 for Candida isolates respectively. Regression analysis correlating zone diameters to MIC value was done. Pearson's correlation coefficient was calculated to determine correlation between disk zone diameters and MICs. Candida albicans (33.3%) was clearly outnumbered by other non-albicans species predominantly Candida tropicalis (42.5%) and Candida glabrata (18.4%). Ten percent of the strains were resistant to fluconazole by disk diffusion and 13% by broth microdilution. MIC range for Candida albicans and Candida tropicalis ranged from≤0.25-64μg/ml while that of Candida glabrata ranged from≤0.25-128μg/ml. Categorical agreement between disk diffusion and broth microdilution was 86.8%. Pearson's coefficient of correlation was -0.5975 indicating moderate negative correlation between the two variables. Zone sizes can be used to estimate the MIC values, although with limited accuracy. There should be a constant effort to upgrade the guidelines in view of new clinical data, and laboratories should make an active effort to incorporate them. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Comparison of tricuspid annular plane systolic excursion with fractional area change for the evaluation of right ventricular systolic function: a meta-analysis

PubMed Central

Low, See-Wei; Pasha, Ahmed K; Howe, Carol L; Lee, Kwan S; Suryanarayana, Prakash G

2018-01-01

Background Accurate determination of right ventricular ejection fraction (RVEF) is challenging because of the unique geometry of the right ventricle. Tricuspidannular plane systolic excursion (TAPSE) and fractional area change (FAC) are commonly used echocardiographic quantitative estimates of RV function. Cardiac MRI (CMRI) has emerged as the gold standard for assessment of RVEF. We sought to summarise the available data on correlation of TAPSE and FAC with CMRI-derived RVEF and to compare their accuracy. Methods We searched PubMed, EMBASE, Web of Science, CINAHL, ClinicalTrials.gov and the Cochrane Library databases for studies that assessed the correlation of TAPSE or FAC with CMRI-derived RVEF. Data from each study selected were pooled and analysed to compare the correlation coefficient of TAPSE and FAC with CMRI-derived RVEF. Subgroup analysis was performed on patients with pulmonary hypertension. Results Analysis of data from 17 studies with a total of 1280 patients revealed that FAC had a higher correlation with CMRI-derived RVEF compared with TAPSE (0.56vs0.40, P=0.018). In patients with pulmonary hypertension, there was no statistical difference in the mean correlation coefficient of FAC and TAPSE to CMR (0.57vs0.46, P=0.16). Conclusions FAC provides a more accurate estimate of RV systolic function (RVSF) compared with TAPSE. Adoption of FAC as a routine tool for the assessment of RVSF should be considered, especially since it is also an independent predictor of morbidity and mortality. Further studies will be needed to compare other methods of echocardiographic measurement of RV function. PMID:29387425

Reconstructing for joint angles on the shoulder and elbow from non-invasive electroencephalographic signals through electromyography

PubMed Central

Choi, Kyuwan

2013-01-01

In this study, first the cortical activities over 2240 vertexes on the brain were estimated from 64 channels electroencephalography (EEG) signals using the Hierarchical Bayesian estimation while 5 subjects did continuous arm reaching movements. From the estimated cortical activities, a sparse linear regression method selected only useful features in reconstructing the electromyography (EMG) signals and estimated the EMG signals of 9 arm muscles. Then, a modular artificial neural network was used to estimate four joint angles from the estimated EMG signals of 9 muscles: one for movement control and the other for posture control. The estimated joint angles using this method have the correlation coefficient (CC) of 0.807 (±0.10) and the normalized root-mean-square error (nRMSE) of 0.176 (±0.29) with the actual joint angles. PMID:24167469

Correlation between dental maturity and cervical vertebral maturity.

PubMed

Chen, Jianwei; Hu, Haikun; Guo, Jing; Liu, Zeping; Liu, Renkai; Li, Fan; Zou, Shujuan

2010-12-01

The aim of this study was to investigate the association between dental and skeletal maturity. Digital panoramic radiographs and lateral skull cephalograms of 302 patients (134 boys and 168 girls, ranging from 8 to 16 years of age) were examined. Dental maturity was assessed by calcification stages of the mandibular canines, first and second premolars, and second molars, whereas skeletal maturity was estimated by the cervical vertebral maturation (CVM) stages. The Spearman rank-order correlation coefficient was used to measure the association between CVM stage and dental calcification stage of individual teeth. The mean chronologic age of girls was significantly lower than that of boys in each CVM stage. The Spearman rank-order correlation coefficients between dental maturity and cervical vertebral maturity ranged from 0.391 to 0.582 for girls and from 0.464 to 0.496 for boys (P < 0.05). In girls, the mandibular second molar had the highest and the canine the lowest correlation. In boys, the canine had the highest and the first premolar the lowest correlation. Tooth calcification stage was significantly correlated with cervical vertebral maturation stage. The development of the mandibular second molar in females and that of the mandibular canine in males had the strongest correlations with cervical vertebral maturity. Therefore, it is practical to consider the relationship between dental and skeletal maturity when planning orthodontic treatment. Copyright © 2010 Mosby, Inc. All rights reserved.

Dietary quality varies according to data collection instrument: a comparison between a food frequency questionnaire and 24-hour recall.

PubMed

Rodrigues, Paulo Rogério Melo; de Souza, Rita Adriana Gomes; De Cnop, Mara Lima; Monteiro, Luana Silva; Coura, Camila Pinheiro; Brito, Alessandra Page; Pereira, Rosangela Alves

2016-02-01

The objective of this study was to assess the agreement between the Brazilian Healthy Eating Index - Revised (BHEI-R), estimated by a food frequency questionnaire (FFQ) and multiple 24-hour recalls (24h-R). The Wilcoxon paired test, partial correlations (PC), intraclass correlation coefficient (ICC), and Bland-Altman method were used. The total BHEI-R scores and its components ("total fruits", "whole fruits", "total vegetables", "integral cereals", "saturated fat", "sodium", and "energy intake derived from solid fat, added sugar, and alcoholic beverages") were statistically different, with the ICC and PC indicating poor concordance and correlation. The mean concordance estimated for the total BHEI-R and its components varied from 68% for "integral cereals" to 147% for "whole fruits". The suitable concordance limits were violated for most of the components of the BHEI-R. Poor concordance was observed between the BHEI-R estimated by the FFQ and by multiple 24h-R, which indicated a strong reliability of the BHEI-R on the instrument used to collect information on food consumption.

Analyzing Spatial and Temporal Variation in Precipitation Estimates in a Coupled Model

NASA Astrophysics Data System (ADS)

Tomkins, C. D.; Springer, E. P.; Costigan, K. R.

2001-12-01

Integrated modeling efforts at the Los Alamos National Laboratory aim to simulate the hydrologic cycle and study the impacts of climate variability and land use changes on water resources and ecosystem function at the regional scale. The integrated model couples three existing models independently responsible for addressing the atmospheric, land surface, and ground water components: the Regional Atmospheric Model System (RAMS), the Los Alamos Distributed Hydrologic System (LADHS), and the Finite Element and Heat Mass (FEHM). The upper Rio Grande Basin, extending 92,000 km2 over northern New Mexico and southern Colorado, serves as the test site for this model. RAMS uses nested grids to simulate meteorological variables, with the smallest grid over the Rio Grande having 5-km horizontal grid spacing. As LADHS grid spacing is 100 m, a downscaling approach is needed to estimate meteorological variables from the 5km RAMS grid for input into LADHS. This study presents daily and cumulative precipitation predictions, in the month of October for water year 1993, and an approach to compare LADHS downscaled precipitation to RAMS-simulated precipitation. The downscaling algorithm is based on kriging, using topography as a covariate to distribute the precipitation and thereby incorporating the topographical resolution achieved at the 100m-grid resolution in LADHS. The results of the downscaling are analyzed in terms of the level of variance introduced into the model, mean simulated precipitation, and the correlation between the LADHS and RAMS estimates. Previous work presented a comparison of RAMS-simulated and observed precipitation recorded at COOP and SNOTEL sites. The effects of downscaling the RAMS precipitation were evaluated using Spearman and linear correlations and by examining the variance of both populations. The study focuses on determining how the downscaling changes the distribution of precipitation compared to the RAMS estimates. Spearman correlations computed for the LADHS and RAMS cumulative precipitation reveal a disassociation over time, with R equal to 0.74 at day eight and R equal to 0.52 at day 31. Linear correlation coefficients (Pearson) returned a stronger initial correlation of 0.97, decreasing to 0.68. The standard deviations for the 2500 LADHS cells underlying each 5km RAMS cell range from 8 mm to 695 mm in the Sangre de Cristo Mountains and 2 mm to 112 mm in the San Luis Valley. Comparatively, the standard deviations of the RAMS estimates in these regions are 247 mm and 30 mm respectively. The LADHS standard deviations provide a measure of the variability introduced through the downscaling routine, which exceeds RAMS regional variability by a factor of 2 to 4. The coefficient of variation for the average LADHS grid cell values and the RAMS cell values in the Sangre de Cristo Mountains are 0.66 and 0.27, respectively, and 0.79 and 0.75 in the San Luis Valley. The coefficients of variation evidence the uniformity of the higher precipitation estimates in the mountains, especially for RAMS, and also the lower means and variability found in the valley. Additionally, Kolmogorov-Smirnov tests indicate clear spatial and temporal differences in mean simulated precipitation across the grid.

Diagnosing cysts with correlation coefficient images from 2-dimensional freehand elastography.

PubMed

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.

Evaluation of an eddy resolving global model at the Bermuda Atlantic Time-series Study site

NASA Astrophysics Data System (ADS)

Hiron, L.; Goncalves Neto, A.; Bates, N. R.; Johnson, R. J.

2016-02-01

The Bermuda Atlantic Time-series Study (BATS) commenced monthly sampling in 1988 and thus provides an invaluable 27 years of ocean temperature and salinity profiles for inferring climate relevant processes. However, the passage of mesoscale eddies through this site complicates the local heat and salinity budgets due to inadequate spatial and temporal sampling of these eddy systems. Thus, application of high resolution operational numerical models potentially offers a framework for estimating the horizontal transport due to mesoscale processes. The goal of this research was to analyze the accuracy of the MERCATOR operational 1/12° global ocean model at the BATS site by comparing temperature, salinity and heat budgets for years 2008 - 2015. Overall agreement in the upper 540m for temperature and salinity is found to be very encouraging with significant (P< 0.01) correlations at all depths for both fields. The highest value of correlation coefficient for the temperature field is 0.98 at the surface which decreases to 0.66 at 150m and then reaches a minimum of 0.50 at 320 to 540m. Similarly, the highest correlation coefficient for salinity is found at the surface, with a value of 0.83 and then decreases to a minimum of 0.25 in the subtropical mode water though then increases to 0.5 at 540m. Mixing in the MERCATOR model is also very well captured with a mixed layer depth (MLD) correlation coefficient of 0.92 for the seven year period. Finally, the total heat budget (0-540m) from MERCATOR varies coherently with the BATS observations as shown by a high correlation coefficient of 0.84 (P < 0.01). According to these analyses, daily output from the MERCATOR model represents accurately the temperature, salinity, heat budget and MLD at the BATS site. We propose this model can be used in future research at the BATS site by providing information about mesoscale structure and importantly, advective fluxes at this site.

Estimation of the absorption coefficients of two-layered media by a simple method using spatially and time-resolved reflectances

NASA Astrophysics Data System (ADS)

Shimada, M.; Sato, C.; Hoshi, Y.; Yamada, Y.

2009-08-01

Our newly developed method using spatially and time-resolved reflectances can easily estimate the absorption coefficients of each layer in a two-layered medium if the thickness of the upper layer and the reduced scattering coefficients of the two layers are known a priori. We experimentally validated this method using phantoms and examined its possibility of estimating the absorption coefficients of the tissues in human heads. In the case of a homogeneous plastic phantom (polyacetal block), the absorption coefficient estimated by our method agreed well with that obtained by a conventional method. Also, in the case of two-layered phantoms, our method successfully estimated the absorption coefficients of the two layers. Furthermore, the absorption coefficients of the extracerebral and cerebral tissue inside human foreheads were estimated under the assumption that the human heads were two-layered media. It was found that the absorption coefficients of the cerebral tissues were larger than those of the extracerebral tissues.

Systematic effects in LOD from SLR observations

NASA Astrophysics Data System (ADS)

Bloßfeld, Mathis; Gerstl, Michael; Hugentobler, Urs; Angermann, Detlef; Müller, Horst

2014-09-01

Beside the estimation of station coordinates and the Earth’s gravity field, laser ranging observations to near-Earth satellites can be used to determine the rotation of the Earth. One parameter of this rotation is ΔLOD (excess Length Of Day) which describes the excess revolution time of the Earth w.r.t. 86,400 s. Due to correlations among the different parameter groups, it is difficult to obtain reliable estimates for all parameters. In the official ΔLOD products of the International Earth Rotation and Reference Systems Service (IERS), the ΔLOD information determined from laser ranging observations is excluded from the processing. In this paper, we study the existing correlations between ΔLOD, the orbital node Ω, the even zonal gravity field coefficients, cross-track empirical accelerations and relativistic accelerations caused by the Lense-Thirring and deSitter effect in detail using first order Gaussian perturbation equations. We found discrepancies due to different a priories by using different gravity field models of up to 1.0 ms for polar orbits at an altitude of 500 km and up to 40.0 ms, if the gravity field coefficients are estimated using only observations to LAGEOS 1. If observations to LAGEOS 2 are included, reliable ΔLOD estimates can be achieved. Nevertheless, an impact of the a priori gravity field even on the multi-satellite ΔLOD estimates can be clearly identified. Furthermore, we investigate the effect of empirical cross-track accelerations and the effect of relativistic accelerations of near-Earth satellites on ΔLOD. A total effect of 0.0088 ms is caused by not modeled Lense-Thirring and deSitter terms. The partial derivatives of these accelerations w.r.t. the position and velocity of the satellite cause very small variations (0.1 μs) on ΔLOD.

On the choice of the functional form of the aftershocks decay equation

NASA Astrophysics Data System (ADS)

Gasperini, P.; Lolli, B.

2003-04-01

To infer the optimal form of the rate equation describing the decay of aftershock sequences, we analyzed the correlation among parameter estimates made for New Zealand (Eberhard-Phillips, 1998) and Italy (Lolli and Gasperini, 2003), for the simple model proposed by Reasenberg and Jones (1989) λ(t)=10a+b(Mm-Mmin)over(t+c)^p} We found significant correlations between the sequence productivity parameter a and all other ones (p, c and b) and between p and c. At odd with previous findings (Guo and Ogata, 1995; 1997) we did not find instead correlation between b and p. We verified that the explicit inclusion in the formula of the time decay normalization integral removes the correlation of a with both parameters p and c. We also found, separately for both regions, that assuming the linear coefficient of main shock magnitude M_m about 2/3b makes parameter a also independent of b. The a parameter of the resulting rate equation λ(t)= 10a+2/3bMm-bMmin/ (t+c)^pint_ST(t+c)-pdt being almost independent of the other ones, can be reliably considered the expressions of a peculiar property of the seismogenic process. Thus we can infer that the new equation could be more appropriate than the previous one to predict sequence behavior in different areas. This formulation has also been applied to more sophisticated models of the epidemic type (ETAS), letting the coefficient of the main shock magnitude to vary freely. Some preliminary experiments give estimates close to 1/2b for this parameter.

HBsAg level and hepatitis B viral load correlation with focus on pregnancy

PubMed Central

Belopolskaya, Maria; Avrutin, Viktor; Firsov, Sergey; Yakovlev, Alexey

2015-01-01

Background Viral load measurement is necessary to estimate mother-to-child transmission risk for women with chronic hepatitis B (CHB), however, it is expensive. The present study aimed to investigate the relationship between HBsAg and hepatitis B virus (HBV) DNA levels, and to determine potential applications of HBsAg level monitoring for estimating viral load. Methods 85 patients with CHB (31 pregnant women, 26 non-pregnant women, 28 men) were included in the study. HBV DNA level was measured by real-time PCR, and HBsAg level by chemiluminescent immunoassay method. Dependency between viral load and HBsAg level was determined by Spearman correlation coefficient ρ. Results The correlation between HBsAg and HBV DNA levels was significant for all patients [ρ=0.3762 (P<0.0005; n=85)]. In the group of pregnant women, a low (unmeasurable) HBV DNA level led to a decrease in the Spearman coefficient ρ. In almost all cases a low level of the HBsAg corresponded to a low HBV DNA level. Only 2 patients had a low level of HBsAg and a relatively high viral load. By contrast, a high HBsAg level was observed in patients both with high and low viral load. Conclusions Correlation between HBsAg and HBV DNA levels is significant. In most cases, a low level of HBsAg indicates a low HBV DNA level, whereas a high HBsAg level does not always correspond to a high viral load. The measurement of HBV DNA level is necessary for pregnant women with a high HBsAg level. PMID:26127004

Voxel-based statistical analysis of uncertainties associated with deformable image registration

NASA Astrophysics Data System (ADS)

Li, Shunshan; Glide-Hurst, Carri; Lu, Mei; Kim, Jinkoo; Wen, Ning; Adams, Jeffrey N.; Gordon, James; Chetty, Indrin J.; Zhong, Hualiang

2013-09-01

Deformable image registration (DIR) algorithms have inherent uncertainties in their displacement vector fields (DVFs).The purpose of this study is to develop an optimal metric to estimate DIR uncertainties. Six computational phantoms have been developed from the CT images of lung cancer patients using a finite element method (FEM). The FEM generated DVFs were used as a standard for registrations performed on each of these phantoms. A mechanics-based metric, unbalanced energy (UE), was developed to evaluate these registration DVFs. The potential correlation between UE and DIR errors was explored using multivariate analysis, and the results were validated by landmark approach and compared with two other error metrics: DVF inverse consistency (IC) and image intensity difference (ID). Landmark-based validation was performed using the POPI-model. The results show that the Pearson correlation coefficient between UE and DIR error is rUE-error = 0.50. This is higher than rIC-error = 0.29 for IC and DIR error and rID-error = 0.37 for ID and DIR error. The Pearson correlation coefficient between UE and the product of the DIR displacements and errors is rUE-error × DVF = 0.62 for the six patients and rUE-error × DVF = 0.73 for the POPI-model data. It has been demonstrated that UE has a strong correlation with DIR errors, and the UE metric outperforms the IC and ID metrics in estimating DIR uncertainties. The quantified UE metric can be a useful tool for adaptive treatment strategies, including probability-based adaptive treatment planning.

The Correlation Between Atmospheric Dust Deposition to the Surface Ocean and SeaWiFS Ocean Color: A Global Satellite-Based Analysis

NASA Technical Reports Server (NTRS)

Erickson, D. J., III; Hernandez, J.; Ginoux, P.; Gregg, W.; Kawa, R.; Behrenfeld, M.; Esaias, W.; Einaudi, Franco (Technical Monitor)

2000-01-01

Since the atmospheric deposition of iron has been linked to primary productivity in various oceanic regions, we have conducted an objective study of the correlation of dust deposition and satellite remotely sensed surface ocean chlorophyll concentrations. We present a global analysis of the correlation between atmospheric dust deposition derived from a satellite-based 3-D atmospheric transport model and SeaWiFs estimates of ocean color. We use the monthly mean dust deposition fields of Ginoux et al. which are based on a global model of dust generation and transport. This model is driven by atmospheric circulation from the Data Assimilation Office (DAO) for the period 1995-1998. This global dust model is constrained by several satellite estimates of standard circulation characteristics. We then perform an analysis of the correlation between the dust deposition and the 1998 SeaWIFS ocean color data for each 2.0 deg x 2.5 deg lat/long grid point, for each month of the year. The results are surprisingly robust. The region between 40 S and 60 S has correlation coefficients from 0.6 to 0.95, statistically significant at the 0.05 level. There are swaths of high correlation at the edges of some major ocean current systems. We interpret these correlations as reflecting areas that have shear related turbulence bringing nitrogen and phosphorus from depth into the surface ocean, and the atmospheric supply of iron provides the limiting nutrient and the correlation between iron deposition and surface ocean chlorophyll is high. There is a region in the western North Pacific with high correlation, reflecting the input of Asian dust to that region. The southern hemisphere has an average correlation coefficient of 0.72 compared that in the northern hemisphere of 0.42 consistent with present conceptual models of where atmospheric iron deposition may play a role in surface ocean biogeochemical cycles. The spatial structure of the correlation fields will be discussed within the context of guiding the design of field programs.

Estimating individual glomerular volume in the human kidney: clinical perspectives.

PubMed

Puelles, Victor G; Zimanyi, Monika A; Samuel, Terence; Hughson, Michael D; Douglas-Denton, Rebecca N; Bertram, John F; Armitage, James A

2012-05-01

Measurement of individual glomerular volumes (IGV) has allowed the identification of drivers of glomerular hypertrophy in subjects without overt renal pathology. This study aims to highlight the relevance of IGV measurements with possible clinical implications and determine how many profiles must be measured in order to achieve stable size distribution estimates. We re-analysed 2250 IGV estimates obtained using the disector/Cavalieri method in 41 African and 34 Caucasian Americans. Pooled IGV analysis of mean and variance was conducted. Monte-Carlo (Jackknife) simulations determined the effect of the number of sampled glomeruli on mean IGV. Lin's concordance coefficient (R(C)), coefficient of variation (CV) and coefficient of error (CE) measured reliability. IGV mean and variance increased with overweight and hypertensive status. Superficial glomeruli were significantly smaller than juxtamedullary glomeruli in all subjects (P < 0.01), by race (P < 0.05) and in obese individuals (P < 0.01). Subjects with multiple chronic kidney disease (CKD) comorbidities showed significant increases in IGV mean and variability. Overall, mean IGV was particularly reliable with nine or more sampled glomeruli (R(C) > 0.95, <5% difference in CV and CE). These observations were not affected by a reduced sample size and did not disrupt the inverse linear correlation between mean IGV and estimated total glomerular number. Multiple comorbidities for CKD are associated with increased IGV mean and variance within subjects, including overweight, obesity and hypertension. Zonal selection and the number of sampled glomeruli do not represent drawbacks for future longitudinal biopsy-based studies of glomerular size and distribution.

A New Methodology of Spatial Cross-Correlation Analysis

PubMed Central

Chen, Yanguang

2015-01-01

Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran’s index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson’s correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China’s urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes. PMID:25993120

A new methodology of spatial cross-correlation analysis.

PubMed

Chen, Yanguang

2015-01-01

Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran's index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson's correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China's urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes.

Age Band 1 of the Movement Assessment Battery for Children-Second Edition: Exploring Its Usefulness in Mainland China

ERIC Educational Resources Information Center

Hua, Jing; Gu, Guixiong; Meng, Wei; Wu, Zhuochun

2013-01-01

The aim of this paper was to examine the validity and reliability of age band 1 of the Movement Assessment Battery for Children-Second Edition (MABC-2) in preparation for its standardization in mainland China. Interrater and test-retest reliability of the MABC-2 was estimated using Intraclass Correlation Coefficient (ICC). Cronbach's alpha for…

Random matrix theory analysis of cross-correlations in the US stock market: Evidence from Pearson’s correlation coefficient and detrended cross-correlation coefficient

NASA Astrophysics Data System (ADS)

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.

The predictive value of hunger score on gastric evacuation after oral intake of carbohydrate solution.

PubMed

Weiji, Qiu; Shitong, Li; Yu, Luo; Tianfang, Hua; Ning, Kong; Lina, Zhang

2018-01-12

Surgical patients are asked to fast for a sufficient duration to ensure that the amount of residual liquid in the stomach is within the safe range, thereby reducing the risk of gastric reflux perioperatively. The authors hypothesized that subjective hunger numerical rating scale (NRS) score could also help assess the process of gastric emptying and determine the amount of fluid remaining in the stomach. The current study consisted of healthy volunteers recruited by advertisement and mutual introduction. Participants were asked to rate their subjective hunger feeling every 30 min after oral administration of 8 mL/kg carbohydrate nutrient solution that contained 10% maltodextrin and 2.5% sucrose. Consecutively, the gastric residual fluid was measured by magnetic resonance imagining (MRI). The Spearman's correlation coefficient, the ROC curves and the stepwise regression were used to analyze the predictive value of NRS for the gastric emptying process. The cohort consisted of 29 healthy volunteers enrolled in this study. The area under ROC curves estimated by the NRS score for the gastric residual volume of 2 mL/kg, 1 mL/kg, and 0.5 mL/kg were AUC 2.0  = 0.78, AUC 1.0  = 0.76, and AUC 0.5  = 0.72, respectively. The correlation coefficient between the NRS score and the residual liquid in the stomach was -0.57 (P < 0.01). The correlation coefficient between the increase of the NRS score and the decrease of gastric liquid residual volume was 0.46 (P < 0.01). The standardized estimate of NRS score for the residual volume was -0.18 (P < 0.01) and the standardized estimate of fasting time was -0.73 (P < 0.01). The subjective hunger NRS score can not accurately predict the gastric residual volume, but it can provide a reference for clinicians to judge the gastric emptying process and it should be used as a second check after oral intake of clear fluids before surgery according to the new fasting protocol.

A Psychometric Analysis of Quality of Life Tools in Lung Cancer Patients Who Smoke

PubMed Central

Browning, Kristine K.; Ferketich, Amy K.; Otterson, Gregory A.; Reynolds, Nancy R.; Wewers, Mary Ellen

2009-01-01

Lung cancer is the leading cause of cancer death for both men and women in the United States. Patient quality of life (QOL) prior to cancer treatment is known to be a strong predictor of survival and toleration of treatment toxicities. A lung cancer patient’s self-assessment of QOL is highly valued among clinicians as it guides treatment-related decisions and impacts clinical outcomes. Smokers are known to report a lower QOL. Limited research has been conducted on QOL outcomes in lung cancer patients who continue to smoke. To assess QOL, a reliable and valid QOL measure specific to lung cancer is required. The Functional Assessment of Cancer Therapy-Lung Cancer (FACT-L) and Lung Cancer Symptom Scale (LCSS) are instruments that specifically examine QOL among lung cancer patients. The LCSS is a focused QOL instrument that includes physical and functional domains of QOL and disease symptomatology. The FACT-L is a broader QOL instrument that includes physical, functional, social and emotional domains and disease symptomatology. Both are psychometrically valid and are widely used in the literature, but have not been exclusively evaluated in smokers. Furthermore, there is no ‘gold standard’ instrument since there has never been a correlation study to compare estimates of reliability and validity between these instruments. The purpose of this study is to report the internal consistency and convergence validity of the FACT-L and the LCSS among newly diagnosed lung cancer patients who smoke. This data were collected and analyzed from a larger study examining smoking behavior among newly diagnosed lung cancer patients (n=51). Descriptive statistics were calculated on the FACT-L and LCSS scores, internal consistency was assessed by estimating Cronbach’s alpha coefficients, and Pearson correlation coefficients were estimated between the two scales. Internal consistency coefficients demonstrated good reliability for both scales, and the two instruments demonstrated a strong correlation, suggesting good convergence validity. Either of these instruments are appropriate measures for QOL in lung cancer patients who smoke. Given the conceptual difference between the two instruments, it is important to carefully consider the research aims when selecting the appropriate QOL measurement instrument. PMID:19181418