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

NASA Astrophysics Data System (ADS)

Joachimi, B.; Taylor, A. N.

2011-09-01

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

On the statistical distribution in a deformed solid

NASA Astrophysics Data System (ADS)

Gorobei, N. N.; Luk'yanenko, A. S.

2017-09-01

A modification of the Gibbs distribution in a thermally insulated mechanically deformed solid, where its linear dimensions (shape parameters) are excluded from statistical averaging and included among the macroscopic parameters of state alongside with the temperature, is proposed. Formally, this modification is reduced to corresponding additional conditions when calculating the statistical sum. The shape parameters and the temperature themselves are found from the conditions of mechanical and thermal equilibria of a body, and their change is determined using the first law of thermodynamics. Known thermodynamic phenomena are analyzed for the simple model of a solid, i.e., an ensemble of anharmonic oscillators, within the proposed formalism with an accuracy of up to the first order by the anharmonicity constant. The distribution modification is considered for the classic and quantum temperature regions apart.

Coherent Doppler lidar signal covariance including wind shear and wind turbulence

NASA Technical Reports Server (NTRS)

Frehlich, R. G.

1993-01-01

The performance of coherent Doppler lidar is determined by the statistics of the coherent Doppler signal. The derivation and calculation of the covariance of the Doppler lidar signal is presented for random atmospheric wind fields with wind shear. The random component is described by a Kolmogorov turbulence spectrum. The signal parameters are clarified for a general coherent Doppler lidar system. There are two distinct physical regimes: one where the transmitted pulse determines the signal statistics and the other where the wind field dominates the signal statistics. The Doppler shift of the signal is identified in terms of the wind field and system parameters.

A design methodology for nonlinear systems containing parameter uncertainty

NASA Technical Reports Server (NTRS)

Young, G. E.; Auslander, D. M.

1983-01-01

In the present design methodology for nonlinear systems containing parameter uncertainty, a generalized sensitivity analysis is incorporated which employs parameter space sampling and statistical inference. For the case of a system with j adjustable and k nonadjustable parameters, this methodology (which includes an adaptive random search strategy) is used to determine the combination of j adjustable parameter values which maximize the probability of those performance indices which simultaneously satisfy design criteria in spite of the uncertainty due to k nonadjustable parameters.

The Effect of Folate and Folate Plus Zinc Supplementation on Endocrine Parameters and Sperm Characteristics in Sub-Fertile Men: A Systematic Review and Meta-Analysis.

PubMed

Irani, Morvarid; Amirian, Malihe; Sadeghi, Ramin; Lez, Justine Le; Latifnejad Roudsari, Robab

2017-08-29

To evaluate the effect of folate and folate plus zinc supplementation on endocrine parameters and sperm characteristics in sub fertile men. We conducted a systematic review and meta-analysis. Electronic databases of Medline, Scopus , Google scholar and Persian databases (SID, Iran medex, Magiran, Medlib, Iran doc) were searched from 1966 to December 2016 using a set of relevant keywords including "folate or folic acid AND (infertility, infertile, sterility)".All available randomized controlled trials (RCTs), conducted on a sample of sub fertile men with semen analyses, who took oral folic acid or folate plus zinc, were included. Data collected included endocrine parameters and sperm characteristics. Statistical analyses were done by Comprehensive Meta-analysis Version 2. In total, seven studies were included. Six studies had sufficient data for meta-analysis. "Sperm concentration was statistically higher in men supplemented with folate than with placebo (P < .001)". However, folate supplementation alone did not seem to be more effective than the placebo on the morphology (P = .056) and motility of the sperms (P = .652). Folate plus zinc supplementation did not show any statistically different effect on serum testosterone (P = .86), inhibin B (P = .84), FSH (P = .054), and sperm motility (P = .169) as compared to the placebo. Yet, folate plus zinc showed statistically higher effect on the sperm concentration (P < .001), morphology (P < .001), and serum folate level (P < .001) as compared to placebo. Folate plus zinc supplementation has a positive effect on sperm characteristics in sub fertile men. However, these results should be interpreted with caution due to the important heterogeneity of the studies included in this meta-analysis. Further trials are still needed to confirm the current findings.

Calculation of Weibull strength parameters, Batdorf flaw density constants and related statistical quantities using PC-CARES

NASA Technical Reports Server (NTRS)

Szatmary, Steven A.; Gyekenyesi, John P.; Nemeth, Noel N.

1990-01-01

This manual describes the operation and theory of the PC-CARES (Personal Computer-Ceramic Analysis and Reliability Evaluation of Structures) computer program for the IBM PC and compatibles running PC-DOS/MS-DOR OR IBM/MS-OS/2 (version 1.1 or higher) operating systems. The primary purpose of this code is to estimate Weibull material strength parameters, the Batdorf crack density coefficient, and other related statistical quantities. Included in the manual is the description of the calculation of shape and scale parameters of the two-parameter Weibull distribution using the least-squares analysis and maximum likelihood methods for volume- and surface-flaw-induced fracture in ceramics with complete and censored samples. The methods for detecting outliers and for calculating the Kolmogorov-Smirnov and the Anderson-Darling goodness-of-fit statistics and 90 percent confidence bands about the Weibull line, as well as the techniques for calculating the Batdorf flaw-density constants are also described.

Machine Learning Predictions of a Multiresolution Climate Model Ensemble

NASA Astrophysics Data System (ADS)

Anderson, Gemma J.; Lucas, Donald D.

2018-05-01

Statistical models of high-resolution climate models are useful for many purposes, including sensitivity and uncertainty analyses, but building them can be computationally prohibitive. We generated a unique multiresolution perturbed parameter ensemble of a global climate model. We use a novel application of a machine learning technique known as random forests to train a statistical model on the ensemble to make high-resolution model predictions of two important quantities: global mean top-of-atmosphere energy flux and precipitation. The random forests leverage cheaper low-resolution simulations, greatly reducing the number of high-resolution simulations required to train the statistical model. We demonstrate that high-resolution predictions of these quantities can be obtained by training on an ensemble that includes only a small number of high-resolution simulations. We also find that global annually averaged precipitation is more sensitive to resolution changes than to any of the model parameters considered.

Reporting of various methodological and statistical parameters in negative studies published in prominent Indian Medical Journals: a systematic review.

PubMed

Charan, J; Saxena, D

2014-01-01

Biased negative studies not only reflect poor research effort but also have an impact on 'patient care' as they prevent further research with similar objectives, leading to potential research areas remaining unexplored. Hence, published 'negative studies' should be methodologically strong. All parameters that may help a reader to judge validity of results and conclusions should be reported in published negative studies. There is a paucity of data on reporting of statistical and methodological parameters in negative studies published in Indian Medical Journals. The present systematic review was designed with an aim to critically evaluate negative studies published in prominent Indian Medical Journals for reporting of statistical and methodological parameters. Systematic review. All negative studies published in 15 Science Citation Indexed (SCI) medical journals published from India were included in present study. Investigators involved in the study evaluated all negative studies for the reporting of various parameters. Primary endpoints were reporting of "power" and "confidence interval." Power was reported in 11.8% studies. Confidence interval was reported in 15.7% studies. Majority of parameters like sample size calculation (13.2%), type of sampling method (50.8%), name of statistical tests (49.1%), adjustment of multiple endpoints (1%), post hoc power calculation (2.1%) were reported poorly. Frequency of reporting was more in clinical trials as compared to other study designs and in journals having impact factor more than 1 as compared to journals having impact factor less than 1. Negative studies published in prominent Indian medical journals do not report statistical and methodological parameters adequately and this may create problems in the critical appraisal of findings reported in these journals by its readers.

Parametric study of the swimming performance of a fish robot propelled by a flexible caudal fin.

PubMed

Low, K H; Chong, C W

2010-12-01

In this paper, we aim to study the swimming performance of fish robots by using a statistical approach. A fish robot employing a carangiform swimming mode had been used as an experimental platform for the performance study. The experiments conducted aim to investigate the effect of various design parameters on the thrust capability of the fish robot with a flexible caudal fin. The controllable parameters associated with the fin include frequency, amplitude of oscillation, aspect ratio and the rigidity of the caudal fin. The significance of these parameters was determined in the first set of experiments by using a statistical approach. A more detailed parametric experimental study was then conducted with only those significant parameters. As a result, the parametric study could be completed with a reduced number of experiments and time spent. With the obtained experimental result, we were able to understand the relationship between various parameters and a possible adjustment of parameters to obtain a higher thrust. The proposed statistical method for experimentation provides an objective and thorough analysis of the effects of individual or combinations of parameters on the swimming performance. Such an efficient experimental design helps to optimize the process and determine factors that influence variability.

The Effects of Measurement Error on Statistical Models for Analyzing Change. Final Report.

ERIC Educational Resources Information Center

Dunivant, Noel

The results of six major projects are discussed including a comprehensive mathematical and statistical analysis of the problems caused by errors of measurement in linear models for assessing change. In a general matrix representation of the problem, several new analytic results are proved concerning the parameters which affect bias in…

Dose-escalation designs in oncology: ADEPT and the CRM.

PubMed

Shu, Jianfen; O'Quigley, John

2008-11-20

The ADEPT software package is not a statistical method in its own right as implied by Gerke and Siedentop (Statist. Med. 2008; DOI: 10.1002/sim.3037). ADEPT implements two-parameter CRM models as described in O'Quigley et al. (Biometrics 1990; 46(1):33-48). All of the basic ideas (use of a two-parameter logistic model, use of a two-dimensional prior for the unknown slope and intercept parameters, sequential estimation and subsequent patient allocation based on minimization of some loss function, flexibility to use cohorts instead of one by one inclusion) are strictly identical. The only, and quite trivial, difference arises in the setting of the prior. O'Quigley et al. (Biometrics 1990; 46(1):33-48) used priors having an analytic expression whereas Whitehead and Brunier (Statist. Med. 1995; 14:33-48) use pseudo-data to play the role of the prior. The question of interest is whether two-parameter CRM works as well, or better, than the one-parameter CRM recommended in O'Quigley et al. (Biometrics 1990; 46(1):33-48). Gerke and Siedentop argue that it does. The published literature suggests otherwise. The conclusions of Gerke and Siedentop stem from three highly particular, and somewhat contrived, situations. Unlike one-parameter CRM (Biometrika 1996; 83:395-405; J. Statist. Plann. Inference 2006; 136:1765-1780; Biometrika 2005; 92:863-873), no statistical properties appear to have been studied for two-parameter CRM. In particular, for two-parameter CRM, the parameter estimates are inconsistent. This ought to be a source of major concern to those proposing its use. Worse still, for finite samples the behavior of estimates can be quite wild despite having incorporated the kind of dampening priors discussed by Gerke and Siedentop. An example in which we illustrate this behavior describes a single patient included at level 1 of 6 levels and experiencing a dose limiting toxicity. The subsequent recommendation is to experiment at level 6! Such problematic behavior is not common. Even so, we show that the allocation behavior of two-parameter CRM is very much less stable than that of one-parameter CRM.

MODFLOW-2000, the U.S. Geological Survey modular ground-water model; user guide to the observation, sensitivity, and parameter-estimation processes and three post-processing programs

USGS Publications Warehouse

Hill, Mary C.; Banta, E.R.; Harbaugh, A.W.; Anderman, E.R.

2000-01-01

This report documents the Observation, Sensitivity, and Parameter-Estimation Processes of the ground-water modeling computer program MODFLOW-2000. The Observation Process generates model-calculated values for comparison with measured, or observed, quantities. A variety of statistics is calculated to quantify this comparison, including a weighted least-squares objective function. In addition, a number of files are produced that can be used to compare the values graphically. The Sensitivity Process calculates the sensitivity of hydraulic heads throughout the model with respect to specified parameters using the accurate sensitivity-equation method. These are called grid sensitivities. If the Observation Process is active, it uses the grid sensitivities to calculate sensitivities for the simulated values associated with the observations. These are called observation sensitivities. Observation sensitivities are used to calculate a number of statistics that can be used (1) to diagnose inadequate data, (2) to identify parameters that probably cannot be estimated by regression using the available observations, and (3) to evaluate the utility of proposed new data. The Parameter-Estimation Process uses a modified Gauss-Newton method to adjust values of user-selected input parameters in an iterative procedure to minimize the value of the weighted least-squares objective function. Statistics produced by the Parameter-Estimation Process can be used to evaluate estimated parameter values; statistics produced by the Observation Process and post-processing program RESAN-2000 can be used to evaluate how accurately the model represents the actual processes; statistics produced by post-processing program YCINT-2000 can be used to quantify the uncertainty of model simulated values. Parameters are defined in the Ground-Water Flow Process input files and can be used to calculate most model inputs, such as: for explicitly defined model layers, horizontal hydraulic conductivity, horizontal anisotropy, vertical hydraulic conductivity or vertical anisotropy, specific storage, and specific yield; and, for implicitly represented layers, vertical hydraulic conductivity. In addition, parameters can be defined to calculate the hydraulic conductance of the River, General-Head Boundary, and Drain Packages; areal recharge rates of the Recharge Package; maximum evapotranspiration of the Evapotranspiration Package; pumpage or the rate of flow at defined-flux boundaries of the Well Package; and the hydraulic head at constant-head boundaries. The spatial variation of model inputs produced using defined parameters is very flexible, including interpolated distributions that require the summation of contributions from different parameters. Observations can include measured hydraulic heads or temporal changes in hydraulic heads, measured gains and losses along head-dependent boundaries (such as streams), flows through constant-head boundaries, and advective transport through the system, which generally would be inferred from measured concentrations. MODFLOW-2000 is intended for use on any computer operating system. The program consists of algorithms programmed in Fortran 90, which efficiently performs numerical calculations and is fully compatible with the newer Fortran 95. The code is easily modified to be compatible with FORTRAN 77. Coordination for multiple processors is accommodated using Message Passing Interface (MPI) commands. The program is designed in a modular fashion that is intended to support inclusion of new capabilities.

Surface flaw reliability analysis of ceramic components with the SCARE finite element postprocessor program

NASA Technical Reports Server (NTRS)

Gyekenyesi, John P.; Nemeth, Noel N.

1987-01-01

The SCARE (Structural Ceramics Analysis and Reliability Evaluation) computer program on statistical fast fracture reliability analysis with quadratic elements for volume distributed imperfections is enhanced to include the use of linear finite elements and the capability of designing against concurrent surface flaw induced ceramic component failure. The SCARE code is presently coupled as a postprocessor to the MSC/NASTRAN general purpose, finite element analysis program. The improved version now includes the Weibull and Batdorf statistical failure theories for both surface and volume flaw based reliability analysis. The program uses the two-parameter Weibull fracture strength cumulative failure probability distribution model with the principle of independent action for poly-axial stress states, and Batdorf's shear-sensitive as well as shear-insensitive statistical theories. The shear-sensitive surface crack configurations include the Griffith crack and Griffith notch geometries, using the total critical coplanar strain energy release rate criterion to predict mixed-mode fracture. Weibull material parameters based on both surface and volume flaw induced fracture can also be calculated from modulus of rupture bar tests, using the least squares method with known specimen geometry and grouped fracture data. The statistical fast fracture theories for surface flaw induced failure, along with selected input and output formats and options, are summarized. An example problem to demonstrate various features of the program is included.

Statistical properties of filtered pseudorandom digital sequences formed from the sum of maximum-length sequences

NASA Technical Reports Server (NTRS)

Wallace, G. R.; Weathers, G. D.; Graf, E. R.

1973-01-01

The statistics of filtered pseudorandom digital sequences called hybrid-sum sequences, formed from the modulo-two sum of several maximum-length sequences, are analyzed. The results indicate that a relation exists between the statistics of the filtered sequence and the characteristic polynomials of the component maximum length sequences. An analysis procedure is developed for identifying a large group of sequences with good statistical properties for applications requiring the generation of analog pseudorandom noise. By use of the analysis approach, the filtering process is approximated by the convolution of the sequence with a sum of unit step functions. A parameter reflecting the overall statistical properties of filtered pseudorandom sequences is derived. This parameter is called the statistical quality factor. A computer algorithm to calculate the statistical quality factor for the filtered sequences is presented, and the results for two examples of sequence combinations are included. The analysis reveals that the statistics of the signals generated with the hybrid-sum generator are potentially superior to the statistics of signals generated with maximum-length generators. Furthermore, fewer calculations are required to evaluate the statistics of a large group of hybrid-sum generators than are required to evaluate the statistics of the same size group of approximately equivalent maximum-length sequences.

Introduction to Sample Size Choice for Confidence Intervals Based on "t" Statistics

ERIC Educational Resources Information Center

Liu, Xiaofeng Steven; Loudermilk, Brandon; Simpson, Thomas

2014-01-01

Sample size can be chosen to achieve a specified width in a confidence interval. The probability of obtaining a narrow width given that the confidence interval includes the population parameter is defined as the power of the confidence interval, a concept unfamiliar to many practitioners. This article shows how to utilize the Statistical Analysis…

Leads Detection Using Mixture Statistical Distribution Based CRF Algorithm from Sentinel-1 Dual Polarization SAR Imagery

NASA Astrophysics Data System (ADS)

Zhang, Yu; Li, Fei; Zhang, Shengkai; Zhu, Tingting

2017-04-01

Synthetic Aperture Radar (SAR) is significantly important for polar remote sensing since it can provide continuous observations in all days and all weather. SAR can be used for extracting the surface roughness information characterized by the variance of dielectric properties and different polarization channels, which make it possible to observe different ice types and surface structure for deformation analysis. In November, 2016, Chinese National Antarctic Research Expedition (CHINARE) 33rd cruise has set sails in sea ice zone in Antarctic. Accurate leads spatial distribution in sea ice zone for routine planning of ship navigation is essential. In this study, the semantic relationship between leads and sea ice categories has been described by the Conditional Random Fields (CRF) model, and leads characteristics have been modeled by statistical distributions in SAR imagery. In the proposed algorithm, a mixture statistical distribution based CRF is developed by considering the contexture information and the statistical characteristics of sea ice for improving leads detection in Sentinel-1A dual polarization SAR imagery. The unary potential and pairwise potential in CRF model is constructed by integrating the posteriori probability estimated from statistical distributions. For mixture statistical distribution parameter estimation, Method of Logarithmic Cumulants (MoLC) is exploited for single statistical distribution parameters estimation. The iteration based Expectation Maximal (EM) algorithm is investigated to calculate the parameters in mixture statistical distribution based CRF model. In the posteriori probability inference, graph-cut energy minimization method is adopted in the initial leads detection. The post-processing procedures including aspect ratio constrain and spatial smoothing approaches are utilized to improve the visual result. The proposed method is validated on Sentinel-1A SAR C-band Extra Wide Swath (EW) Ground Range Detected (GRD) imagery with a pixel spacing of 40 meters near Prydz Bay area, East Antarctica. Main work is listed as follows: 1) A mixture statistical distribution based CRF algorithm has been developed for leads detection from Sentinel-1A dual polarization images. 2) The assessment of the proposed mixture statistical distribution based CRF method and single distribution based CRF algorithm has been presented. 3) The preferable parameters sets including statistical distributions, the aspect ratio threshold and spatial smoothing window size have been provided. In the future, the proposed algorithm will be developed for the operational Sentinel series data sets processing due to its less time consuming cost and high accuracy in leads detection.

Development of a statistical model for cervical cancer cell death with irreversible electroporation in vitro.

PubMed

Yang, Yongji; Moser, Michael A J; Zhang, Edwin; Zhang, Wenjun; Zhang, Bing

2018-01-01

The aim of this study was to develop a statistical model for cell death by irreversible electroporation (IRE) and to show that the statistic model is more accurate than the electric field threshold model in the literature using cervical cancer cells in vitro. HeLa cell line was cultured and treated with different IRE protocols in order to obtain data for modeling the statistical relationship between the cell death and pulse-setting parameters. In total, 340 in vitro experiments were performed with a commercial IRE pulse system, including a pulse generator and an electric cuvette. Trypan blue staining technique was used to evaluate cell death after 4 hours of incubation following IRE treatment. Peleg-Fermi model was used in the study to build the statistical relationship using the cell viability data obtained from the in vitro experiments. A finite element model of IRE for the electric field distribution was also built. Comparison of ablation zones between the statistical model and electric threshold model (drawn from the finite element model) was used to show the accuracy of the proposed statistical model in the description of the ablation zone and its applicability in different pulse-setting parameters. The statistical models describing the relationships between HeLa cell death and pulse length and the number of pulses, respectively, were built. The values of the curve fitting parameters were obtained using the Peleg-Fermi model for the treatment of cervical cancer with IRE. The difference in the ablation zone between the statistical model and the electric threshold model was also illustrated to show the accuracy of the proposed statistical model in the representation of ablation zone in IRE. This study concluded that: (1) the proposed statistical model accurately described the ablation zone of IRE with cervical cancer cells, and was more accurate compared with the electric field model; (2) the proposed statistical model was able to estimate the value of electric field threshold for the computer simulation of IRE in the treatment of cervical cancer; and (3) the proposed statistical model was able to express the change in ablation zone with the change in pulse-setting parameters.

Global Sensitivity Analysis of Environmental Systems via Multiple Indices based on Statistical Moments of Model Outputs

NASA Astrophysics Data System (ADS)

Guadagnini, A.; Riva, M.; Dell'Oca, A.

2017-12-01

We propose to ground sensitivity of uncertain parameters of environmental models on a set of indices based on the main (statistical) moments, i.e., mean, variance, skewness and kurtosis, of the probability density function (pdf) of a target model output. This enables us to perform Global Sensitivity Analysis (GSA) of a model in terms of multiple statistical moments and yields a quantification of the impact of model parameters on features driving the shape of the pdf of model output. Our GSA approach includes the possibility of being coupled with the construction of a reduced complexity model that allows approximating the full model response at a reduced computational cost. We demonstrate our approach through a variety of test cases. These include a commonly used analytical benchmark, a simplified model representing pumping in a coastal aquifer, a laboratory-scale tracer experiment, and the migration of fracturing fluid through a naturally fractured reservoir (source) to reach an overlying formation (target). Our strategy allows discriminating the relative importance of model parameters to the four statistical moments considered. We also provide an appraisal of the error associated with the evaluation of our sensitivity metrics by replacing the original system model through the selected surrogate model. Our results suggest that one might need to construct a surrogate model with increasing level of accuracy depending on the statistical moment considered in the GSA. The methodological framework we propose can assist the development of analysis techniques targeted to model calibration, design of experiment, uncertainty quantification and risk assessment.

Directional statistics-based reflectance model for isotropic bidirectional reflectance distribution functions.

PubMed

Nishino, Ko; Lombardi, Stephen

2011-01-01

We introduce a novel parametric bidirectional reflectance distribution function (BRDF) model that can accurately encode a wide variety of real-world isotropic BRDFs with a small number of parameters. The key observation we make is that a BRDF may be viewed as a statistical distribution on a unit hemisphere. We derive a novel directional statistics distribution, which we refer to as the hemispherical exponential power distribution, and model real-world isotropic BRDFs as mixtures of it. We derive a canonical probabilistic method for estimating the parameters, including the number of components, of this novel directional statistics BRDF model. We show that the model captures the full spectrum of real-world isotropic BRDFs with high accuracy, but a small footprint. We also demonstrate the advantages of the novel BRDF model by showing its use for reflection component separation and for exploring the space of isotropic BRDFs.

42 CFR 493.1256 - Standard: Control procedures.

Code of Federal Regulations, 2010 CFR

2010-10-01

... for having control procedures that monitor the accuracy and precision of the complete analytic process..., include two control materials, including one that is capable of detecting errors in the extraction process... control materials having previously determined statistical parameters. (e) For reagent, media, and supply...

A computer program (MODFLOWP) for estimating parameters of a transient, three-dimensional ground-water flow model using nonlinear regression

USGS Publications Warehouse

Hill, Mary Catherine

1992-01-01

This report documents a new version of the U.S. Geological Survey modular, three-dimensional, finite-difference, ground-water flow model (MODFLOW) which, with the new Parameter-Estimation Package that also is documented in this report, can be used to estimate parameters by nonlinear regression. The new version of MODFLOW is called MODFLOWP (pronounced MOD-FLOW*P), and functions nearly identically to MODFLOW when the ParameterEstimation Package is not used. Parameters are estimated by minimizing a weighted least-squares objective function by the modified Gauss-Newton method or by a conjugate-direction method. Parameters used to calculate the following MODFLOW model inputs can be estimated: Transmissivity and storage coefficient of confined layers; hydraulic conductivity and specific yield of unconfined layers; vertical leakance; vertical anisotropy (used to calculate vertical leakance); horizontal anisotropy; hydraulic conductance of the River, Streamflow-Routing, General-Head Boundary, and Drain Packages; areal recharge rates; maximum evapotranspiration; pumpage rates; and the hydraulic head at constant-head boundaries. Any spatial variation in parameters can be defined by the user. Data used to estimate parameters can include existing independent estimates of parameter values, observed hydraulic heads or temporal changes in hydraulic heads, and observed gains and losses along head-dependent boundaries (such as streams). Model output includes statistics for analyzing the parameter estimates and the model; these statistics can be used to quantify the reliability of the resulting model, to suggest changes in model construction, and to compare results of models constructed in different ways.

The community pharmacist's role in reducing CVD risk factors in Lebanon: a cross-sectional longitudinal study.

PubMed

Fahs, Iqbal; Hallit, Souheil; Rahal, Mohamad; Malaeb, Diana

2018-06-13

To assess the role of pharmacist in modifying CVDs risk factors among Lebanese adults in urban and rural areas.
Materials (Subjects) and Methods
In a prospective survey, 865 out of 1000 participants aged ≥ 45, previously interviewed, agreed to be followed at 1 and 2 year time points. Parameters including blood pressure, lipid profile, blood glucose, average number of risk factors, and atherosclerotic cardiovascular disease (ASCVD) risk were assessed and evaluated at the beginning of the study, then after 1 and 2 years.
Results:
After patient's education and during both follow ups, the mean average body mass index (BMI) and systolic blood pressure (SBP) statistically decreased significantly. The lipid profile as well statistically improved significantly during both follow-ups. to around 9%. Further statistically significant improvements in ASCVD risk occurred during the second follow-up to around 8%. Monitoring parameters revealed statistical significant improvements as well.
Conclusion:
This study showed that a plan that includes pharmacists, who regularly monitor and follow-up patients, could improve CVD prevention through reduction of risk factors.
. ©2018The Author(s). Published by S. Karger AG, Basel.

Effects of foot reflexology on anxiety and physiological parameters in patients undergoing coronary artery bypass graft surgery: A clinical trial.

PubMed

Abbaszadeh, Yaser; Allahbakhshian, Atefeh; Seyyedrasooli, Alehe; Sarbakhsh, Parvin; Goljarian, Sakineh; Safaei, Naser

2018-05-01

This study aimed to investigate the effect of foot reflexology on anxiety and physiological parameters in patients after CABG surgery. This was a single-blind, three-arm, parallel-group, randomized controlled trial with three groups of 40 male patients undergoing CABG. Participants were placed in three groups, named intervention, placebo, and control. Physiological parameters were measured including systolic and diastolic blood pressure, mean arterial pressure, heart rate, respiratory rate, percutaneous oxygen saturation, and anxiety of participants. Results showed a statistically significant difference between intervention and control groups in terms of the level of anxiety (p < 0.05). Also, results showed a statistically significant effect on all physiological parameters except heart rate (p < 0.05). This study indicated that foot reflexology may be used by nurses as an adjunct to standard ICU care to reduce anxiety and stabilize physiological parameters such as systolic, diastolic, mean arterial pressure, and heart rate. Copyright © 2018 Elsevier Ltd. All rights reserved.

Corneal endothelial cell density and morphology in Phramongkutklao Hospital

PubMed Central

Sopapornamorn, Narumon; Lekskul, Manapon; Panichkul, Suthee

2008-01-01

Objective To describe the corneal endothelial density and morphology in patients of Phramongkutklao Hospital and the relationship between endothelial cell parameters and other factors. Methods Four hundred and four eyes of 202 volunteers were included. Noncontact specular microscopy was performed after taking a history and testing the visual acuity, intraocular pressure measurement, Schirmer’s test and routine eye examination by slit lamp microscope. The studied parameters included mean endothelial cell density (MCD), coefficient of variation (CV), and percentage of hexagonality. Results The mean age of volunteers was 45.73 years; the range being 20 to 80 years old. Their MCD (SD), mean percentage of CV (SD) and mean (SD) percentage of hexagonality were 2623.49(325) cell/mm2, 39.43(8.23)% and 51.50(10.99)%, respectively. Statistically, MCD decreased significantly with age (p < 0.01). There was a significant difference in the percentage of CV between genders. There was no statistical significance between parameters and other factors. Conclusion The normative data of the corneal endothelium of Thai eyes indicated that, statistically, MCD decreased significantly with age. Previous studies have reported no difference in MCD, percentage of CV, and percentage of hexagonality between gender. Nevertheless, significantly different percentages of CV between genders were presented in this study. PMID:19668398

Phase-Angle Dependence of Determinations of Diameter, Albedo, and Taxonomy: A Case Study of NEO 3691 Bede

NASA Technical Reports Server (NTRS)

Wooden, Diane H.; Lederer, Susan M.; Jehin, Emmanuel; Howell, Ellen S.; Fernandez, Yan; Harker, David E.; Ryan, Erin; Lovell, Amy; Woodward, Charles E.; Benner, Lance A.

2015-01-01

Parameters important for NEO risk assessment and mitigation include Near-Earth Object diameter and taxonomic classification, which translates to surface composition. Diameters of NEOs are derived from the thermal fluxes measured by WISE, NEOWISE, Spitzer Warm Mission and ground-based telescopes including the IRTF and UKIRT. Diameter and its coupled parameters Albedo and IR beaming parameter (a proxy for thermal inertia and/or surface roughness) are dependent upon the phase angle, which is the Sun-target-observer angle. Orbit geometries of NEOs, however, typically provide for observations at phase angles greater than 20 degrees. At higher phase angles, the observed thermal emission is sampling both the day and night sides of the NEO. We compare thermal models for NEOs that exclude (NEATM) and include (NESTM) night-side emission. We present a case study of NEO 3691 Bede, which is a higher albedo object, X (Ec) or Cgh taxonomy, to highlight the range of H magnitudes for this object (depending on the albedo and phase function slope parameter G), and to examine at different phase angles the taxonomy and thermal model fits for this NEO. Observations of 3691 Bede include our observations with IRTF+SpeX and with the 10 micrometer UKIRT+Michelle instrument, as well as WISE and Spitzer Warm mission data. By examining 3691 Bede as a case study, we highlight the interplay between the derivation of basic physical parameters and observing geometry, and we discuss the uncertainties in H magnitude, taxonomy assignment amongst the X-class (P, M, E), and diameter determinations. Systematic dependencies in the derivation of basic characterization parameters of H-magnitude, diameter, albedo and taxonomy with observing geometry are important to understand. These basic characterization parameters affect the statistical assessments of the NEO population, which in turn, affects the assignment of statistically-assessed basic parameters to discovered but yet-to-be-fully-characterized NEOs.

TRACKING FRESHWATER DIVERSIONS AND ALGAL BLOOMS THAT IMPACT THE NEW ORLEANS STANDARD METROPOLITAN STATISTICAL AREA -

EPA Science Inventory

This project will monitor selected water quality parameters, including water temperature, turbidity, salinity, and algal blooms to assess the impacts of freshwater diversions for several selected areas within the New Orleans metropolitan area. The specific areas of study include ...

The use of heart rate turbulence and heart rate variability in the assessment of autonomic regulation and circadian rhythm in patients with systemic lupus erythematosus without apparent heart disease.

PubMed

Poliwczak, A R; Waszczykowska, E; Dziankowska-Bartkowiak, B; Koziróg, M; Dworniak, K

2018-03-01

Background Systemic lupus erythematosus is a progressive autoimmune disease. There are reports suggesting that patients even without overt signs of cardiovascular complications have impaired autonomic function. The aim of this study was to assess autonomic function using heart rate turbulence and heart rate variability parameters indicated in 24-hour ECG Holter monitoring. Methods Twenty-six women with systemic lupus erythematosus and 30 healthy women were included. Twenty-four hour ambulatory ECG-Holter was performed in home conditions. The basic parameters of heart rate turbulence and heart rate variability were calculated. The analyses were performed for the entire day and separately for daytime activity and night time rest. Results There were no statistically significant differences in the basic anthropometric parameters. The mean duration of disease was 11.52 ± 7.42. There was a statistically significant higher turbulence onset (To) value in patients with systemic lupus erythematosus, median To = -0.17% (minimum -1.47, maximum 3.0) versus To = -1.36% (minimum -4.53, maximum -0.41), P < 0.001. There were no such differences for turbulence slope (Ts). In the 24-hour analysis almost all heart rate variability parameters were significantly lower in the systemic lupus erythematosus group than in the healthy controls, including SDANN and r-MSSD and p50NN. Concerning the morning activity and night resting periods, the results were similar as for the whole day. In the control group, higher values in morning activity were noted for parameters that characterise sympathetic activity, especially SDANN, and were significantly lower for parasympathetic parameters, including r-MSSD and p50NN, which prevailed at night. There were no statistically significant changes for systemic lupus erythematosus patients for p50NN and low and very low frequency. There was a positive correlation between disease duration and SDNN, R = 0.417; P < 0.05 and SDANN, R = 0.464; P < 0.05, a negative correlation between low/high frequency ratio and r-MSSD, R = -0.454; P < 0.05; p50NN, R = -0.435; P < 0.05 and high frequency, R = -0.478; P < 0.05. In contrast, there was no statistically significant correlation between heart rate turbulence and other variables evaluated, including disease duration and the type of autoantibodies. Our study confirms the presence of autonomic disorders with respect to both heart rate variability and heart rate turbulence parameters and the presence of diurnal disturbances of sympathetic-parasympathetic balance. Further studies are required.

The Impact of Model Misspecification on Parameter Estimation and Item-Fit Assessment in Log-Linear Diagnostic Classification Models

ERIC Educational Resources Information Center

Kunina-Habenicht, Olga; Rupp, Andre A.; Wilhelm, Oliver

2012-01-01

Using a complex simulation study we investigated parameter recovery, classification accuracy, and performance of two item-fit statistics for correct and misspecified diagnostic classification models within a log-linear modeling framework. The basic manipulated test design factors included the number of respondents (1,000 vs. 10,000), attributes (3…

PROUCL 4.0 SOFTWARE

EPA Science Inventory

Statistical inference, including both estimation and hypotheses testing approaches, is routinely used to: estimate environmental parameters of interest, such as exposure point concentration (EPC) terms, not-to-exceed values, and background level threshold values (BTVs) for contam...

Surface defect detection in tiling Industries using digital image processing methods: analysis and evaluation.

PubMed

Karimi, Mohammad H; Asemani, Davud

2014-05-01

Ceramic and tile industries should indispensably include a grading stage to quantify the quality of products. Actually, human control systems are often used for grading purposes. An automatic grading system is essential to enhance the quality control and marketing of the products. Since there generally exist six different types of defects originating from various stages of tile manufacturing lines with distinct textures and morphologies, many image processing techniques have been proposed for defect detection. In this paper, a survey has been made on the pattern recognition and image processing algorithms which have been used to detect surface defects. Each method appears to be limited for detecting some subgroup of defects. The detection techniques may be divided into three main groups: statistical pattern recognition, feature vector extraction and texture/image classification. The methods such as wavelet transform, filtering, morphology and contourlet transform are more effective for pre-processing tasks. Others including statistical methods, neural networks and model-based algorithms can be applied to extract the surface defects. Although, statistical methods are often appropriate for identification of large defects such as Spots, but techniques such as wavelet processing provide an acceptable response for detection of small defects such as Pinhole. A thorough survey is made in this paper on the existing algorithms in each subgroup. Also, the evaluation parameters are discussed including supervised and unsupervised parameters. Using various performance parameters, different defect detection algorithms are compared and evaluated. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Computer programs for computing particle-size statistics of fluvial sediments

USGS Publications Warehouse

Stevens, H.H.; Hubbell, D.W.

1986-01-01

Two versions of computer programs for inputing data and computing particle-size statistics of fluvial sediments are presented. The FORTRAN 77 language versions are for use on the Prime computer, and the BASIC language versions are for use on microcomputers. The size-statistics program compute Inman, Trask , and Folk statistical parameters from phi values and sizes determined for 10 specified percent-finer values from inputed size and percent-finer data. The program also determines the percentage gravel, sand, silt, and clay, and the Meyer-Peter effective diameter. Documentation and listings for both versions of the programs are included. (Author 's abstract)

Characterizing Uncertainty and Variability in PBPK Models ...

EPA Pesticide Factsheets

Mode-of-action based risk and safety assessments can rely upon tissue dosimetry estimates in animals and humans obtained from physiologically-based pharmacokinetic (PBPK) modeling. However, risk assessment also increasingly requires characterization of uncertainty and variability; such characterization for PBPK model predictions represents a continuing challenge to both modelers and users. Current practices show significant progress in specifying deterministic biological models and the non-deterministic (often statistical) models, estimating their parameters using diverse data sets from multiple sources, and using them to make predictions and characterize uncertainty and variability. The International Workshop on Uncertainty and Variability in PBPK Models, held Oct 31-Nov 2, 2006, sought to identify the state-of-the-science in this area and recommend priorities for research and changes in practice and implementation. For the short term, these include: (1) multidisciplinary teams to integrate deterministic and non-deterministic/statistical models; (2) broader use of sensitivity analyses, including for structural and global (rather than local) parameter changes; and (3) enhanced transparency and reproducibility through more complete documentation of the model structure(s) and parameter values, the results of sensitivity and other analyses, and supporting, discrepant, or excluded data. Longer-term needs include: (1) theoretic and practical methodological impro

An audit of the statistics and the comparison with the parameter in the population

NASA Astrophysics Data System (ADS)

Bujang, Mohamad Adam; Sa'at, Nadiah; Joys, A. Reena; Ali, Mariana Mohamad

2015-10-01

The sufficient sample size that is needed to closely estimate the statistics for particular parameters are use to be an issue. Although sample size might had been calculated referring to objective of the study, however, it is difficult to confirm whether the statistics are closed with the parameter for a particular population. All these while, guideline that uses a p-value less than 0.05 is widely used as inferential evidence. Therefore, this study had audited results that were analyzed from various sub sample and statistical analyses and had compared the results with the parameters in three different populations. Eight types of statistical analysis and eight sub samples for each statistical analysis were analyzed. Results found that the statistics were consistent and were closed to the parameters when the sample study covered at least 15% to 35% of population. Larger sample size is needed to estimate parameter that involve with categorical variables compared with numerical variables. Sample sizes with 300 to 500 are sufficient to estimate the parameters for medium size of population.

Characterizing uncertainty and variability in physiologically based pharmacokinetic models: state of the science and needs for research and implementation.

PubMed

Barton, Hugh A; Chiu, Weihsueh A; Setzer, R Woodrow; Andersen, Melvin E; Bailer, A John; Bois, Frédéric Y; Dewoskin, Robert S; Hays, Sean; Johanson, Gunnar; Jones, Nancy; Loizou, George; Macphail, Robert C; Portier, Christopher J; Spendiff, Martin; Tan, Yu-Mei

2007-10-01

Physiologically based pharmacokinetic (PBPK) models are used in mode-of-action based risk and safety assessments to estimate internal dosimetry in animals and humans. When used in risk assessment, these models can provide a basis for extrapolating between species, doses, and exposure routes or for justifying nondefault values for uncertainty factors. Characterization of uncertainty and variability is increasingly recognized as important for risk assessment; this represents a continuing challenge for both PBPK modelers and users. Current practices show significant progress in specifying deterministic biological models and nondeterministic (often statistical) models, estimating parameters using diverse data sets from multiple sources, using them to make predictions, and characterizing uncertainty and variability of model parameters and predictions. The International Workshop on Uncertainty and Variability in PBPK Models, held 31 Oct-2 Nov 2006, identified the state-of-the-science, needed changes in practice and implementation, and research priorities. For the short term, these include (1) multidisciplinary teams to integrate deterministic and nondeterministic/statistical models; (2) broader use of sensitivity analyses, including for structural and global (rather than local) parameter changes; and (3) enhanced transparency and reproducibility through improved documentation of model structure(s), parameter values, sensitivity and other analyses, and supporting, discrepant, or excluded data. Longer-term needs include (1) theoretical and practical methodological improvements for nondeterministic/statistical modeling; (2) better methods for evaluating alternative model structures; (3) peer-reviewed databases of parameters and covariates, and their distributions; (4) expanded coverage of PBPK models across chemicals with different properties; and (5) training and reference materials, such as cases studies, bibliographies/glossaries, model repositories, and enhanced software. The multidisciplinary dialogue initiated by this Workshop will foster the collaboration, research, data collection, and training necessary to make characterizing uncertainty and variability a standard practice in PBPK modeling and risk assessment.

Efficient Moment-Based Inference of Admixture Parameters and Sources of Gene Flow

PubMed Central

Levin, Alex; Reich, David; Patterson, Nick; Berger, Bonnie

2013-01-01

The recent explosion in available genetic data has led to significant advances in understanding the demographic histories of and relationships among human populations. It is still a challenge, however, to infer reliable parameter values for complicated models involving many populations. Here, we present MixMapper, an efficient, interactive method for constructing phylogenetic trees including admixture events using single nucleotide polymorphism (SNP) genotype data. MixMapper implements a novel two-phase approach to admixture inference using moment statistics, first building an unadmixed scaffold tree and then adding admixed populations by solving systems of equations that express allele frequency divergences in terms of mixture parameters. Importantly, all features of the model, including topology, sources of gene flow, branch lengths, and mixture proportions, are optimized automatically from the data and include estimates of statistical uncertainty. MixMapper also uses a new method to express branch lengths in easily interpretable drift units. We apply MixMapper to recently published data for Human Genome Diversity Cell Line Panel individuals genotyped on a SNP array designed especially for use in population genetics studies, obtaining confident results for 30 populations, 20 of them admixed. Notably, we confirm a signal of ancient admixture in European populations—including previously undetected admixture in Sardinians and Basques—involving a proportion of 20–40% ancient northern Eurasian ancestry. PMID:23709261

Hybrid Gibbs Sampling and MCMC for CMB Analysis at Small Angular Scales

NASA Technical Reports Server (NTRS)

Jewell, Jeffrey B.; Eriksen, H. K.; Wandelt, B. D.; Gorski, K. M.; Huey, G.; O'Dwyer, I. J.; Dickinson, C.; Banday, A. J.; Lawrence, C. R.

2008-01-01

A) Gibbs Sampling has now been validated as an efficient, statistically exact, and practically useful method for "low-L" (as demonstrated on WMAP temperature polarization data). B) We are extending Gibbs sampling to directly propagate uncertainties in both foreground and instrument models to total uncertainty in cosmological parameters for the entire range of angular scales relevant for Planck. C) Made possible by inclusion of foreground model parameters in Gibbs sampling and hybrid MCMC and Gibbs sampling for the low signal to noise (high-L) regime. D) Future items to be included in the Bayesian framework include: 1) Integration with Hybrid Likelihood (or posterior) code for cosmological parameters; 2) Include other uncertainties in instrumental systematics? (I.e. beam uncertainties, noise estimation, calibration errors, other).

Statistical modeling of space shuttle environmental data

NASA Technical Reports Server (NTRS)

Tubbs, J. D.; Brewer, D. W.

1983-01-01

Statistical models which use a class of bivariate gamma distribution are examined. Topics discussed include: (1) the ratio of positively correlated gamma varieties; (2) a method to determine if unequal shape parameters are necessary in bivariate gamma distribution; (3) differential equations for modal location of a family of bivariate gamma distribution; and (4) analysis of some wind gust data using the analytical results developed for modeling application.

Markov chain Monte Carlo estimation of quantum states

NASA Astrophysics Data System (ADS)

Diguglielmo, James; Messenger, Chris; Fiurášek, Jaromír; Hage, Boris; Samblowski, Aiko; Schmidt, Tabea; Schnabel, Roman

2009-03-01

We apply a Bayesian data analysis scheme known as the Markov chain Monte Carlo to the tomographic reconstruction of quantum states. This method yields a vector, known as the Markov chain, which contains the full statistical information concerning all reconstruction parameters including their statistical correlations with no a priori assumptions as to the form of the distribution from which it has been obtained. From this vector we can derive, e.g., the marginal distributions and uncertainties of all model parameters, and also of other quantities such as the purity of the reconstructed state. We demonstrate the utility of this scheme by reconstructing the Wigner function of phase-diffused squeezed states. These states possess non-Gaussian statistics and therefore represent a nontrivial case of tomographic reconstruction. We compare our results to those obtained through pure maximum-likelihood and Fisher information approaches.

Correlation between the different therapeutic properties of Chinese medicinal herbs and delayed luminescence.

PubMed

Pang, Jingxiang; Fu, Jialei; Yang, Meina; Zhao, Xiaolei; van Wijk, Eduard; Wang, Mei; Fan, Hua; Han, Jinxiang

2016-03-01

In the practice and principle of Chinese medicine, herbal materials are classified according to their therapeutic properties. 'Cold' and 'heat' are the most important classes of Chinese medicinal herbs according to the theory of traditional Chinese medicine (TCM). In this work, delayed luminescence (DL) was measured for different samples of Chinese medicinal herbs using a sensitive photon multiplier detection system. A comparison of DL parameters, including mean intensity and statistic entropy, was undertaken to discriminate between the 'cold' and 'heat' properties of Chinese medicinal herbs. The results suggest that there are significant differences in mean intensity and statistic entropy and using this method combined with statistical analysis may provide novel parameters for the characterization of Chinese medicinal herbs in relation to their energetic properties. Copyright © 2015 John Wiley & Sons, Ltd.

Statistical Mechanics of Node-perturbation Learning with Noisy Baseline

NASA Astrophysics Data System (ADS)

Hara, Kazuyuki; Katahira, Kentaro; Okada, Masato

2017-02-01

Node-perturbation learning is a type of statistical gradient descent algorithm that can be applied to problems where the objective function is not explicitly formulated, including reinforcement learning. It estimates the gradient of an objective function by using the change in the object function in response to the perturbation. The value of the objective function for an unperturbed output is called a baseline. Cho et al. proposed node-perturbation learning with a noisy baseline. In this paper, we report on building the statistical mechanics of Cho's model and on deriving coupled differential equations of order parameters that depict learning dynamics. We also show how to derive the generalization error by solving the differential equations of order parameters. On the basis of the results, we show that Cho's results are also apply in general cases and show some general performances of Cho's model.

The landscape of W± and Z bosons produced in pp collisions up to LHC energies

NASA Astrophysics Data System (ADS)

Basso, Eduardo; Bourrely, Claude; Pasechnik, Roman; Soffer, Jacques

2017-10-01

We consider a selection of recent experimental results on electroweak W± , Z gauge boson production in pp collisions at BNL RHIC and CERN LHC energies in comparison to prediction of perturbative QCD calculations based on different sets of NLO parton distribution functions including the statistical PDF model known from fits to the DIS data. We show that the current statistical PDF parametrization (fitted to the DIS data only) underestimates the LHC data on W± , Z gauge boson production cross sections at the NLO by about 20%. This suggests that there is a need to refit the parameters of the statistical PDF including the latest LHC data.

Voice analysis before and after vocal rehabilitation in patients following open surgery on vocal cords.

PubMed

Bunijevac, Mila; Petrović-Lazić, Mirjana; Jovanović-Simić, Nadica; Vuković, Mile

2016-02-01

The major role of larynx in speech, respiration and swallowing makes carcinomas of this region and their treatment very influential for patients' life quality. The aim of this study was to assess the importance of voice therapy in patients after open surgery on vocal cords. This study included 21 male patients and the control group of 19 subjects. The vowel (A) was recorded and analyzed for each examinee. All the patients were recorded twice: firstly, when they contacted the clinic and secondly, after a three-month vocal therapy, which was held twiceper week on an outpatient basis. The voice analysis was carried out in the Ear, Nose and Throat (ENT) Clinic, Clinical Hospital Center "Zvezdara" in Belgrade. The values of the acoustic parameters in the patients submitted to open surgery on the vocal cords before vocal rehabilitation and the control group subjects were significantly different in all specified parameters. These results suggest that the voice of the patients was damaged before vocal rehabilitation. The results of the acoustic parameters of the vowel (A) before and after vocal rehabilitation of the patients with open surgery on vocal cords were statistically significantly different. Among the parameters--Jitter (%), Shimmer (%)--the observed difference was highly statistically significant (p < 0.01). The voice turbulence index and the noise/harmonic ratio were also notably improved, and the observed difference was statistically significant (p < 0.05). The analysis of the tremor intensity index showed no significant improvement and the observed difference was not statistically significant (p > 0.05 ). CONCLUSION. There was a significant improvement of the acoustic parameters of the vowel (A) in the study subjects three months following vocal therapy. Only one out of five representative parameters showed no significant improvement.

Choosing an Appropriate Modelling Framework for Analysing Multispecies Co-culture Cell Biology Experiments.

PubMed

Markham, Deborah C; Simpson, Matthew J; Baker, Ruth E

2015-04-01

In vitro cell biology assays play a crucial role in informing our understanding of the migratory, proliferative and invasive properties of many cell types in different biological contexts. While mono-culture assays involve the study of a population of cells composed of a single cell type, co-culture assays study a population of cells composed of multiple cell types (or subpopulations of cells). Such co-culture assays can provide more realistic insights into many biological processes including tissue repair, tissue regeneration and malignant spreading. Typically, system parameters, such as motility and proliferation rates, are estimated by calibrating a mathematical or computational model to the observed experimental data. However, parameter estimates can be highly sensitive to the choice of model and modelling framework. This observation motivates us to consider the fundamental question of how we can best choose a model to facilitate accurate parameter estimation for a particular assay. In this work we describe three mathematical models of mono-culture and co-culture assays that include different levels of spatial detail. We study various spatial summary statistics to explore if they can be used to distinguish between the suitability of each model over a range of parameter space. Our results for mono-culture experiments are promising, in that we suggest two spatial statistics that can be used to direct model choice. However, co-culture experiments are far more challenging: we show that these same spatial statistics which provide useful insight into mono-culture systems are insufficient for co-culture systems. Therefore, we conclude that great care ought to be exercised when estimating the parameters of co-culture assays.

Use of ocean color scanner data in water quality mapping

NASA Technical Reports Server (NTRS)

Khorram, S.

1981-01-01

Remotely sensed data, in combination with in situ data, are used in assessing water quality parameters within the San Francisco Bay-Delta. The parameters include suspended solids, chlorophyll, and turbidity. Regression models are developed between each of the water quality parameter measurements and the Ocean Color Scanner (OCS) data. The models are then extended to the entire study area for mapping water quality parameters. The results include a series of color-coded maps, each pertaining to one of the water quality parameters, and the statistical analysis of the OCS data and regression models. It is found that concurrently collected OCS data and surface truth measurements are highly useful in mapping the selected water quality parameters and locating areas having relatively high biological activity. In addition, it is found to be virtually impossible, at least within this test site, to locate such areas on U-2 color and color-infrared photography.

Investigation of Polarization Phase Difference Related to Forest Fields Characterizations

NASA Astrophysics Data System (ADS)

Majidi, M.; Maghsoudi, Y.

2013-09-01

The information content of Synthetic Aperture Radar (SAR) data significantly included in the radiometric polarization channels, hence polarimetric SAR data should be analyzed in relation with target structure. The importance of the phase difference between two co-polarized scattered signals due to the possible association between the biophysical parameters and the measured Polarization Phase Difference (PPD) statistics of the backscattered signal recorded components has been recognized in geophysical remote sensing. This paper examines two Radarsat-2 images statistics of the phase difference to describe the feasibility of relationship with the physical properties of scattering targets and tries to understand relevance of PPD statistics with various types of forest fields. As well as variation of incidence angle due to affecting on PPD statistics is investigated. The experimental forest pieces that are used in this research are characterized white pine (Pinus strobus L.), red pine (Pinus resinosa Ait.), jack pine (Pinus banksiana Lamb.), white spruce (Picea glauca (Moench Voss), black spruce (Picea mariana (Mill) B.S.P.), poplar (Populus L.), red oak (Quercus rubra L.) , aspen and ground vegetation. The experimental results show that despite of biophysical parameters have a wide diversity, PPD statistics are almost the same. Forest fields distributions as distributed targets have close to zero means regardless of the incidence angle. Also, The PPD distribution are function of both target and sensor parameters, but for more appropriate examination related to PPD statistics the observations should made in the leaf-off season or in bands with lower frequencies.

Statistical analysis of NaOH pretreatment effects on sweet sorghum bagasse characteristics

NASA Astrophysics Data System (ADS)

Putri, Ary Mauliva Hada; Wahyuni, Eka Tri; Sudiyani, Yanni

2017-01-01

We analyze the behavior of sweet sorghum bagasse characteristics before and after NaOH pretreatments by statistical analysis. These characteristics include the percentages of lignocellulosic materials and the degree of crystallinity. We use the chi-square method to get the values of fitted parameters, and then deploy student's t-test to check whether they are significantly different from zero at 99.73% confidence level (C.L.). We obtain, in the cases of hemicellulose and lignin, that their percentages after pretreatment decrease statistically. On the other hand, crystallinity does not possess similar behavior as the data proves that all fitted parameters in this case might be consistent with zero. Our statistical result is then cross examined with the observations from X-ray diffraction (XRD) and Fourier Transform Infrared (FTIR) Spectroscopy, showing pretty good agreement. This result may indicate that the 10% NaOH pretreatment might not be sufficient in changing the crystallinity index of the sweet sorghum bagasse.

On the Relationship Between Transfer Function-derived Response Times and Hydrograph Analysis Timing Parameters: Are there Similarities?

NASA Astrophysics Data System (ADS)

Bansah, S.; Ali, G.; Haque, M. A.; Tang, V.

2017-12-01

The proportion of precipitation that becomes streamflow is a function of internal catchment characteristics - which include geology, landscape characteristics and vegetation - and influence overall storage dynamics. The timing and quantity of water discharged by a catchment are indeed embedded in event hydrographs. Event hydrograph timing parameters, such as the response lag and time of concentration, are important descriptors of how long it takes the catchment to respond to input precipitation and how long it takes the latter to filter through the catchment. However, the extent to which hydrograph timing parameters relate to average response times derived from fitting transfer functions to annual hydrographs is unknown. In this study, we used a gamma transfer function to determine catchment average response times as well as event-specific hydrograph parameters across a network of eight nested watersheds ranging from 0.19 km2 to 74.6 km2 prairie catchments located in south central Manitoba (Canada). Various statistical analyses were then performed to correlate average response times - estimated using the parameters of the fitted gamma transfer function - to event-specific hydrograph parameters. Preliminary results show significant interannual variations in response times and hydrograph timing parameters: the former were in the order of a few hours to days, while the latter ranged from a few days to weeks. Some statistically significant relationships were detected between response times and event-specific hydrograph parameters. Future analyses will involve the comparison of statistical distributions of event-specific hydrograph parameters with that of runoff response times and baseflow transit times in order to quantity catchment storage dynamics across a range of temporal scales.

Effects of Intra-Family Parameters: Educative Style and Academic Knowledge of Parents and Their Economic Conditions on Teenagers' Personality and Behavior

ERIC Educational Resources Information Center

Bakhtavar, Mohammad; Bayova, Rana

2015-01-01

The present study aims to investigate the effects of intra-family parameters; educative styles and academic knowledge of parents and their economic condition on teenagers' personality and behavior. The present study is a descriptive survey. The statistical sample of the study included 166 teenage students from Baku, Azerbaijan and 332 of their…

Trans-dimensional matched-field geoacoustic inversion with hierarchical error models and interacting Markov chains.

PubMed

Dettmer, Jan; Dosso, Stan E

2012-10-01

This paper develops a trans-dimensional approach to matched-field geoacoustic inversion, including interacting Markov chains to improve efficiency and an autoregressive model to account for correlated errors. The trans-dimensional approach and hierarchical seabed model allows inversion without assuming any particular parametrization by relaxing model specification to a range of plausible seabed models (e.g., in this case, the number of sediment layers is an unknown parameter). Data errors are addressed by sampling statistical error-distribution parameters, including correlated errors (covariance), by applying a hierarchical autoregressive error model. The well-known difficulty of low acceptance rates for trans-dimensional jumps is addressed with interacting Markov chains, resulting in a substantial increase in efficiency. The trans-dimensional seabed model and the hierarchical error model relax the degree of prior assumptions required in the inversion, resulting in substantially improved (more realistic) uncertainty estimates and a more automated algorithm. In particular, the approach gives seabed parameter uncertainty estimates that account for uncertainty due to prior model choice (layering and data error statistics). The approach is applied to data measured on a vertical array in the Mediterranean Sea.

THE Role OF Anisotropy AND Intermittency IN Solar Wind/Magnetosphere Coupling

NASA Astrophysics Data System (ADS)

Jankovicova, D.; Voros, Z.

2006-12-01

Turbulent fluctuations are common in the solar wind as well as in the Earth's magnetosphere. The fluctuations of both magnetic field and plasma parameters exhibit non-Gaussian statistics. Neither the amplitude of these fluctuations nor their spectral characteristics can provide a full statistical description of multi-scale features in turbulence. It substantiates a statistical approach including the estimation of experimentally accessible statistical moments. In this contribution, we will directly estimate the third (skewness) and the fourth (kurtosis) statistical moments from the available time series of magnetic measurements in the solar wind (ACE and WIND spacecraft) and in the Earth's magnetosphere (SYM-H index). Then we evaluate how the statistical moments change during strong and weak solar wind/magnetosphere coupling intervals.

Space-weather Parameters for 1,000 Active Regions Observed by SDO/HMI

NASA Astrophysics Data System (ADS)

Bobra, M.; Liu, Y.; Hoeksema, J. T.; Sun, X.

2013-12-01

We present statistical studies of several space-weather parameters, derived from observations of the photospheric vector magnetic field by the Helioseismic and Magnetic Imager (HMI) aboard the Solar Dynamics Observatory, for a thousand active regions. Each active region has been observed every twelve minutes during the entirety of its disk passage. Some of these parameters, such as energy density and shear angle, indicate the deviation of the photospheric magnetic field from that of a potential field. Other parameters include flux, helicity, field gradients, polarity inversion line properties, and measures of complexity. We show that some of these parameters are useful for event prediction.

[Correlations of 18F-Fluorodeoxyglucose Positron Emission Tomography/Magnetic Resonance Imaging Parameters with the Pathological Differentiation of Head and Neck Squamous Cell Carcinoma and Their Diagnostic Efficiencies].

PubMed

Dang, Hao Dan; Chen, Yu; Shi, Xiao Hua; Hou, Bo; Xing, Hai Qun; Zhang, Tao; Chen, Xing Ming; Zhang, Zhu Hua; Xue, Hua Dan; Jin, Zheng Yu

2018-04-28

Objective To evaluate the correlation of the positron emission tomography/magnetic resonance imaging (PET/MR) parameters with the pathological differentiation of head and neck squamous cell carcinoma(HNSCC) and the diagnostic efficiencies of PET/MR parameters. Methods Patients with clinical suspicion of HNSCC were included and underwent PET/MR scan. HNSCC was pathologically confirmed in all these patients. The PET/MR examination included PET and MR sequences of diffusion-weighted imaging (DWI) and T2-and T1-weighted imaging. The multiple parameters of PET/MR included the mean values of apparent diffusion coefficient(ADC mean ) and the maximum and mean values of standardized uptake value (SUV max and SUV mean ) were measured and estimated. The correlations of all the parameters and distribution between the different tumor differentiation groups were analyzed. Logistic regression was utilized to build the model as the PET/MR combined parameter for predicting the differentiation by multiple parameters of PET/MR. The receiver operating characteristic curve was calculated for each parameter and the combination. Results Totally 23 patients were included in this study:9 patients (9 males and 0 female) had well-differentiated tumor,with an average age of (61.0±6.8)years;14 cases had moderately-differentiated (n=10) or poorly-differentiated tumors (n=4),with an average age of (62.0±9.1) years. All the patients were males. There was statistical correlation between SUV mean and SUV max (P<0.001);however,ADC mean showed no statistical correlation with SUV max and with SUV mean (P=0.42,P=0.13). ADC mean and SUV mean showed significant difference between well-differentiated group and moderately-poorly-differentiated group (P=0.005,P=0.007). Compared with the individual parameters,the combination of PET/MR parameters with SUV mean and ADC mean had higher efficacy in predicting tumor differentiation,with an area under curve of 0.84. Conclusions The distributions of ADC mean ,SUV max and SUV mean differ among HNSCC with different pathological differentiation. Compared with the individual parameters,the combination of the PET/MR parameters has higher efficiency in predicting tumor differentiation.

Transmission overhaul and replacement predictions using Weibull and renewel theory

NASA Technical Reports Server (NTRS)

Savage, M.; Lewicki, D. G.

1989-01-01

A method to estimate the frequency of transmission overhauls is presented. This method is based on the two-parameter Weibull statistical distribution for component life. A second method is presented to estimate the number of replacement components needed to support the transmission overhaul pattern. The second method is based on renewal theory. Confidence statistics are applied with both methods to improve the statistical estimate of sample behavior. A transmission example is also presented to illustrate the use of the methods. Transmission overhaul frequency and component replacement calculations are included in the example.

Bayesian approach to inverse statistical mechanics.

PubMed

Habeck, Michael

2014-05-01

Inverse statistical mechanics aims to determine particle interactions from ensemble properties. This article looks at this inverse problem from a Bayesian perspective and discusses several statistical estimators to solve it. In addition, a sequential Monte Carlo algorithm is proposed that draws the interaction parameters from their posterior probability distribution. The posterior probability involves an intractable partition function that is estimated along with the interactions. The method is illustrated for inverse problems of varying complexity, including the estimation of a temperature, the inverse Ising problem, maximum entropy fitting, and the reconstruction of molecular interaction potentials.

Bayesian approach to inverse statistical mechanics

NASA Astrophysics Data System (ADS)

Habeck, Michael

2014-05-01

Inverse statistical mechanics aims to determine particle interactions from ensemble properties. This article looks at this inverse problem from a Bayesian perspective and discusses several statistical estimators to solve it. In addition, a sequential Monte Carlo algorithm is proposed that draws the interaction parameters from their posterior probability distribution. The posterior probability involves an intractable partition function that is estimated along with the interactions. The method is illustrated for inverse problems of varying complexity, including the estimation of a temperature, the inverse Ising problem, maximum entropy fitting, and the reconstruction of molecular interaction potentials.

Moments of inclination error distribution computer program

NASA Technical Reports Server (NTRS)

Myler, T. R.

1981-01-01

A FORTRAN coded computer program is described which calculates orbital inclination error statistics using a closed-form solution. This solution uses a data base of trajectory errors from actual flights to predict the orbital inclination error statistics. The Scott flight history data base consists of orbit insertion errors in the trajectory parameters - altitude, velocity, flight path angle, flight azimuth, latitude and longitude. The methods used to generate the error statistics are of general interest since they have other applications. Program theory, user instructions, output definitions, subroutine descriptions and detailed FORTRAN coding information are included.

ProUCL Version 4.0 Technical Guide

EPA Science Inventory

Statistical inference, including both estimation and hypotheses testing approaches, is routinely used to: estimate environmental parameters of interest, such as exposure point concentration (EPC) terms, not-to-exceed values, and background level threshold values (BTVs) for contam...

[Vulnerability to atmospheric and geomagnetic factors of the body functions in healthy male dwellers of the Russian North].

PubMed

Markov, A L; Zenchenko, T A; Solonin, Iu G; Boĭko, E R

2013-01-01

In April 2009 through to November 2011, a Mars-500 satellite study of Russian Northerners (Syktyvkar citizens) was performed using the standard ECOSAN-2007 procedure evaluating the atmospheric and geomagnetic susceptibility of the main body functional parameters. Seventeen essentially healthy men at the age of 25 to 46 years were investigated. Statistical data treatment included correlation and single-factor analysis of variance. Comparison of the number of statistical correlations of the sum of all functional parameters for participants showed that most often they were sensitive to atmospheric pressure, temperature, relative humidity and oxygen partial pressure (29-35 %), and geomagnetic activity (28 %). Dependence of the functional parameters on the rate of temperature and pressure change was weak and comparable with random coincidence (11 %). Among the hemodynamic parameters, systolic pressure was particularly sensitive to space and terrestrial weather variations (29 %); sensitivity of heart rate and diastolic pressure were determined in 25 % and 21 % of participants, respectively. Among the heart rate variability parameters (HRV) the largest number of statistically reliable correlations was determined for the centralization index (32 %) and high-frequency HRV spectrum (31 %); index of the regulatory systems activity was least dependable (19 %). Life index, maximal breath-holding and Ckibinskaya's cardiorespiratory index are also susceptible. Individual responses of the functional parameters to terrestrial and space weather changes varied with partidpants which points to the necessity of individual approach to evaluation of person's reactions to environmental changes.

Estimation of trabecular bone parameters in children from multisequence MRI using texture-based regression

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

Lekadir, Karim, E-mail: karim.lekadir@upf.edu; Hoogendoorn, Corné; Armitage, Paul

Purpose: This paper presents a statistical approach for the prediction of trabecular bone parameters from low-resolution multisequence magnetic resonance imaging (MRI) in children, thus addressing the limitations of high-resolution modalities such as HR-pQCT, including the significant exposure of young patients to radiation and the limited applicability of such modalities to peripheral bones in vivo. Methods: A statistical predictive model is constructed from a database of MRI and HR-pQCT datasets, to relate the low-resolution MRI appearance in the cancellous bone to the trabecular parameters extracted from the high-resolution images. The description of the MRI appearance is achieved between subjects by usingmore » a collection of feature descriptors, which describe the texture properties inside the cancellous bone, and which are invariant to the geometry and size of the trabecular areas. The predictive model is built by fitting to the training data a nonlinear partial least square regression between the input MRI features and the output trabecular parameters. Results: Detailed validation based on a sample of 96 datasets shows correlations >0.7 between the trabecular parameters predicted from low-resolution multisequence MRI based on the proposed statistical model and the values extracted from high-resolution HRp-QCT. Conclusions: The obtained results indicate the promise of the proposed predictive technique for the estimation of trabecular parameters in children from multisequence MRI, thus reducing the need for high-resolution radiation-based scans for a fragile population that is under development and growth.« less

Testing alternative ground water models using cross-validation and other methods

USGS Publications Warehouse

Foglia, L.; Mehl, S.W.; Hill, M.C.; Perona, P.; Burlando, P.

2007-01-01

Many methods can be used to test alternative ground water models. Of concern in this work are methods able to (1) rank alternative models (also called model discrimination) and (2) identify observations important to parameter estimates and predictions (equivalent to the purpose served by some types of sensitivity analysis). Some of the measures investigated are computationally efficient; others are computationally demanding. The latter are generally needed to account for model nonlinearity. The efficient model discrimination methods investigated include the information criteria: the corrected Akaike information criterion, Bayesian information criterion, and generalized cross-validation. The efficient sensitivity analysis measures used are dimensionless scaled sensitivity (DSS), composite scaled sensitivity, and parameter correlation coefficient (PCC); the other statistics are DFBETAS, Cook's D, and observation-prediction statistic. Acronyms are explained in the introduction. Cross-validation (CV) is a computationally intensive nonlinear method that is used for both model discrimination and sensitivity analysis. The methods are tested using up to five alternative parsimoniously constructed models of the ground water system of the Maggia Valley in southern Switzerland. The alternative models differ in their representation of hydraulic conductivity. A new method for graphically representing CV and sensitivity analysis results for complex models is presented and used to evaluate the utility of the efficient statistics. The results indicate that for model selection, the information criteria produce similar results at much smaller computational cost than CV. For identifying important observations, the only obviously inferior linear measure is DSS; the poor performance was expected because DSS does not include the effects of parameter correlation and PCC reveals large parameter correlations. ?? 2007 National Ground Water Association.

Spatial trends in Pearson Type III statistical parameters

USGS Publications Warehouse

Lichty, R.W.; Karlinger, M.R.

1995-01-01

Spatial trends in the statistical parameters (mean, standard deviation, and skewness coefficient) of a Pearson Type III distribution of the logarithms of annual flood peaks for small rural basins (less than 90 km2) are delineated using a climate factor CT, (T=2-, 25-, and 100-yr recurrence intervals), which quantifies the effects of long-term climatic data (rainfall and pan evaporation) on observed T-yr floods. Maps showing trends in average parameter values demonstrate the geographically varying influence of climate on the magnitude of Pearson Type III statistical parameters. The spatial trends in variability of the parameter values characterize the sensitivity of statistical parameters to the interaction of basin-runoff characteristics (hydrology) and climate. -from Authors

Ultrasound biomicroscopy and iris pigment dispersion: a case--control study.

PubMed

Mora, P; Sangermani, C; Ghirardini, S; Carta, A; Ungaro, N; Gandolfi, Sa

2010-04-01

The study involved eyes affected by pigment dispersion syndrome (PDS) or pigmentary glaucoma (PG) investigated by ultrasound biomicroscopy (UBM). Different irido-corneal parameters were assessed and compared with those from healthy controls. The aim was to investigate the capacity of the UBM in differentiating the cases and, potentially, in confirming the pathogenic mechanisms. Patients with a first diagnosis of PDS or PG were included. A cohort of healthy volunteers matched for sex, age and refractive errors was recruited. All underwent UBM examination: the following parameters were assessed in relaxed and stimulated accommodative state in one eye: iris-lens contact (ILC), irido-corneal angle (ICA) and iris concavity (IC). A receiver operating characteristic (ROC) analysis assessed the ability of UBM to discriminate between subjects with and without PDS/PG. There were 24 eyes in the case group: four diagnosed as PG and the remaining 20 as PDS. There were 25 eyes in the control group. The two groups were statistically superimposable except for baseline intraocular pressure, which was higher in the case group (p=0.0001). All UBM parameters were statistically different between the two groups. ICA in near vision was the best-performing parameter, reaching a sensitivity (=specificity) of 0.875 with a cut-off at 53.0 degrees . The second most sensitive parameter was IC, still in near vision. All UBM parameters examined were statistically different between the two groups. ROC analysis showed ICA and IC in near vision to be the most discriminatory parameters. This evidence confirms the importance of iris movements in inducing the particular features of PDS/PG.

Analysis of Acoustic Emission Parameters from Corrosion of AST Bottom Plate in Field Testing

NASA Astrophysics Data System (ADS)

Jomdecha, C.; Jirarungsatian, C.; Suwansin, W.

Field testing of aboveground storage tank (AST) to monitor corrosion of the bottom plate is presented in this chapter. AE testing data of the ten AST with different sizes, materials, and products were employed to monitor the bottom plate condition. AE sensors of 30 and 150 kHz were used to monitor the corrosion activity of up to 24 channels including guard sensors. Acoustic emission (AE) parameters were analyzed to explore the AE parameter patterns of occurring corrosion compared to the laboratory results. Amplitude, count, duration, and energy were main parameters of analysis. Pattern recognition technique with statistical was implemented to eliminate the electrical and environmental noises. The results showed the specific AE patterns of corrosion activities related to the empirical results. In addition, plane algorithm was utilized to locate the significant AE events from corrosion. Both results of parameter patterns and AE event locations can be used to interpret and locate the corrosion activities. Finally, basic statistical grading technique was used to evaluate the bottom plate condition of the AST.

Finding Mass Constraints Through Third Neutrino Mass Eigenstate Decay

NASA Astrophysics Data System (ADS)

Gangolli, Nakul; de Gouvêa, André; Kelly, Kevin

2018-01-01

In this paper we aim to constrain the decay parameter for the third neutrino mass utilizing already accepted constraints on the other mixing parameters from the Pontecorvo-Maki-Nakagawa-Sakata matrix (PMNS). The main purpose of this project is to determine the parameters that will allow the Jiangmen Underground Neutrino Observatory (JUNO) to observe a decay parameter with some statistical significance. Another goal is to determine the parameters that JUNO could detect in the case that the third neutrino mass is lighter than the first two neutrino species. We also replicate the results that were found in the JUNO Conceptual Design Report (CDR). By utilizing Χ2-squared analysis constraints have been put on the mixing angles, mass squared differences, and the third neutrino decay parameter. These statistical tests take into account background noise and normalization corrections and thus the finalized bounds are a good approximation for the true bounds that JUNO can detect. If the decay parameter is not included in our models, the 99% confidence interval lies within The bounds 0s to 2.80x10-12s. However, if we account for a decay parameter of 3x10-5 ev2, then 99% confidence interval lies within 8.73x10-12s to 8.73x10-11s.

Statistical Inference for Data Adaptive Target Parameters.

PubMed

Hubbard, Alan E; Kherad-Pajouh, Sara; van der Laan, Mark J

2016-05-01

Consider one observes n i.i.d. copies of a random variable with a probability distribution that is known to be an element of a particular statistical model. In order to define our statistical target we partition the sample in V equal size sub-samples, and use this partitioning to define V splits in an estimation sample (one of the V subsamples) and corresponding complementary parameter-generating sample. For each of the V parameter-generating samples, we apply an algorithm that maps the sample to a statistical target parameter. We define our sample-split data adaptive statistical target parameter as the average of these V-sample specific target parameters. We present an estimator (and corresponding central limit theorem) of this type of data adaptive target parameter. This general methodology for generating data adaptive target parameters is demonstrated with a number of practical examples that highlight new opportunities for statistical learning from data. This new framework provides a rigorous statistical methodology for both exploratory and confirmatory analysis within the same data. Given that more research is becoming "data-driven", the theory developed within this paper provides a new impetus for a greater involvement of statistical inference into problems that are being increasingly addressed by clever, yet ad hoc pattern finding methods. To suggest such potential, and to verify the predictions of the theory, extensive simulation studies, along with a data analysis based on adaptively determined intervention rules are shown and give insight into how to structure such an approach. The results show that the data adaptive target parameter approach provides a general framework and resulting methodology for data-driven science.

Application of Statistically Derived CPAS Parachute Parameters

NASA Technical Reports Server (NTRS)

Romero, Leah M.; Ray, Eric S.

2013-01-01

The Capsule Parachute Assembly System (CPAS) Analysis Team is responsible for determining parachute inflation parameters and dispersions that are ultimately used in verifying system requirements. A model memo is internally released semi-annually documenting parachute inflation and other key parameters reconstructed from flight test data. Dispersion probability distributions published in previous versions of the model memo were uniform because insufficient data were available for determination of statistical based distributions. Uniform distributions do not accurately represent the expected distributions since extreme parameter values are just as likely to occur as the nominal value. CPAS has taken incremental steps to move away from uniform distributions. Model Memo version 9 (MMv9) made the first use of non-uniform dispersions, but only for the reefing cutter timing, for which a large number of sample was available. In order to maximize the utility of the available flight test data, clusters of parachutes were reconstructed individually starting with Model Memo version 10. This allowed for statistical assessment for steady-state drag area (CDS) and parachute inflation parameters such as the canopy fill distance (n), profile shape exponent (expopen), over-inflation factor (C(sub k)), and ramp-down time (t(sub k)) distributions. Built-in MATLAB distributions were applied to the histograms, and parameters such as scale (sigma) and location (mu) were output. Engineering judgment was used to determine the "best fit" distribution based on the test data. Results include normal, log normal, and uniform (where available data remains insufficient) fits of nominal and failure (loss of parachute and skipped stage) cases for all CPAS parachutes. This paper discusses the uniform methodology that was previously used, the process and result of the statistical assessment, how the dispersions were incorporated into Monte Carlo analyses, and the application of the distributions in trajectory benchmark testing assessments with parachute inflation parameters, drag area, and reefing cutter timing used by CPAS.

A range of complex probabilistic models for RNA secondary structure prediction that includes the nearest-neighbor model and more.

PubMed

Rivas, Elena; Lang, Raymond; Eddy, Sean R

2012-02-01

The standard approach for single-sequence RNA secondary structure prediction uses a nearest-neighbor thermodynamic model with several thousand experimentally determined energy parameters. An attractive alternative is to use statistical approaches with parameters estimated from growing databases of structural RNAs. Good results have been reported for discriminative statistical methods using complex nearest-neighbor models, including CONTRAfold, Simfold, and ContextFold. Little work has been reported on generative probabilistic models (stochastic context-free grammars [SCFGs]) of comparable complexity, although probabilistic models are generally easier to train and to use. To explore a range of probabilistic models of increasing complexity, and to directly compare probabilistic, thermodynamic, and discriminative approaches, we created TORNADO, a computational tool that can parse a wide spectrum of RNA grammar architectures (including the standard nearest-neighbor model and more) using a generalized super-grammar that can be parameterized with probabilities, energies, or arbitrary scores. By using TORNADO, we find that probabilistic nearest-neighbor models perform comparably to (but not significantly better than) discriminative methods. We find that complex statistical models are prone to overfitting RNA structure and that evaluations should use structurally nonhomologous training and test data sets. Overfitting has affected at least one published method (ContextFold). The most important barrier to improving statistical approaches for RNA secondary structure prediction is the lack of diversity of well-curated single-sequence RNA secondary structures in current RNA databases.

A range of complex probabilistic models for RNA secondary structure prediction that includes the nearest-neighbor model and more

PubMed Central

Rivas, Elena; Lang, Raymond; Eddy, Sean R.

2012-01-01

The standard approach for single-sequence RNA secondary structure prediction uses a nearest-neighbor thermodynamic model with several thousand experimentally determined energy parameters. An attractive alternative is to use statistical approaches with parameters estimated from growing databases of structural RNAs. Good results have been reported for discriminative statistical methods using complex nearest-neighbor models, including CONTRAfold, Simfold, and ContextFold. Little work has been reported on generative probabilistic models (stochastic context-free grammars [SCFGs]) of comparable complexity, although probabilistic models are generally easier to train and to use. To explore a range of probabilistic models of increasing complexity, and to directly compare probabilistic, thermodynamic, and discriminative approaches, we created TORNADO, a computational tool that can parse a wide spectrum of RNA grammar architectures (including the standard nearest-neighbor model and more) using a generalized super-grammar that can be parameterized with probabilities, energies, or arbitrary scores. By using TORNADO, we find that probabilistic nearest-neighbor models perform comparably to (but not significantly better than) discriminative methods. We find that complex statistical models are prone to overfitting RNA structure and that evaluations should use structurally nonhomologous training and test data sets. Overfitting has affected at least one published method (ContextFold). The most important barrier to improving statistical approaches for RNA secondary structure prediction is the lack of diversity of well-curated single-sequence RNA secondary structures in current RNA databases. PMID:22194308

Calculation of evapotranspiration using color-infrared photography. [remote sensing in Arizona

NASA Technical Reports Server (NTRS)

Jones, J. E.

1977-01-01

Data from 38 color-infrared photographic missions flown during a five year period over the Gila River Phreatophyte Project in southeastern Arizona were analyzed to determine the possibility of identifying and measuring vegetative parameters and their associated hydrologic variables by spectral analysis of the photographs. The derived spectra equations are discussed, and a table of 24 statistical parameters describing the spectral and hydrologic variables is included.

Determination of polarimetric parameters of honey by near-infrared transflectance spectroscopy.

PubMed

García-Alvarez, M; Ceresuela, S; Huidobro, J F; Hermida, M; Rodríguez-Otero, J L

2002-01-30

NIR transflectance spectroscopy was used to determine polarimetric parameters (direct polarization, polarization after inversion, specific rotation in dry matter, and polarization due to nonmonosaccharides) and sucrose in honey. In total, 156 honey samples were collected during 1992 (45 samples), 1995 (56 samples), and 1996 (55 samples). Samples were analyzed by NIR spectroscopy and polarimetric methods. Calibration (118 samples) and validation (38 samples) sets were made up; honeys from the three years were included in both sets. Calibrations were performed by modified partial least-squares regression and scatter correction by standard normal variation and detrend methods. For direct polarization, polarization after inversion, specific rotation in dry matter, and polarization due to nonmonosaccharides, good statistics (bias, SEV, and R(2)) were obtained for the validation set, and no statistically (p = 0.05) significant differences were found between instrumental and polarimetric methods for these parameters. Statistical data for sucrose were not as good as those of the other parameters. Therefore, NIR spectroscopy is not an effective method for quantitative analysis of sucrose in these honey samples. However, NIR spectroscopy may be an acceptable method for semiquantitative evaluation of sucrose for honeys, such as those in our study, containing up to 3% of sucrose. Further work is necessary to validate the uncertainty at higher levels.

SU-C-BRD-03: Analysis of Accelerator Generated Text Logs for Preemptive Maintenance

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

Able, CM; Baydush, AH; Nguyen, C

2014-06-15

Purpose: To develop a model to analyze medical accelerator generated parameter and performance data that will provide an early warning of performance degradation and impending component failure. Methods: A robust 6 MV VMAT quality assurance treatment delivery was used to test the constancy of accelerator performance. The generated text log files were decoded and analyzed using statistical process control (SPC) methodology. The text file data is a single snapshot of energy specific and overall systems parameters. A total of 36 system parameters were monitored which include RF generation, electron gun control, energy control, beam uniformity control, DC voltage generation, andmore » cooling systems. The parameters were analyzed using Individual and Moving Range (I/MR) charts. The chart limits were calculated using a hybrid technique that included the use of the standard 3σ limits and the parameter/system specification. Synthetic errors/changes were introduced to determine the initial effectiveness of I/MR charts in detecting relevant changes in operating parameters. The magnitude of the synthetic errors/changes was based on: the value of 1 standard deviation from the mean operating parameter of 483 TB systems, a small fraction (≤ 5%) of the operating range, or a fraction of the minor fault deviation. Results: There were 34 parameters in which synthetic errors were introduced. There were 2 parameters (radial position steering coil, and positive 24V DC) in which the errors did not exceed the limit of the I/MR chart. The I chart limit was exceeded for all of the remaining parameters (94.2%). The MR chart limit was exceeded in 29 of the 32 parameters (85.3%) in which the I chart limit was exceeded. Conclusion: Statistical process control I/MR evaluation of text log file parameters may be effective in providing an early warning of performance degradation or component failure for digital medical accelerator systems. Research is Supported by Varian Medical Systems, Inc.« less

Treatment of automotive industry oily wastewater by electrocoagulation: statistical optimization of the operational parameters.

PubMed

GilPavas, Edison; Molina-Tirado, Kevin; Gómez-García, Miguel Angel

2009-01-01

An electrocoagulation process was used for the treatment of oily wastewater generated from an automotive industry in Medellín (Colombia). An electrochemical cell consisting of four parallel electrodes (Fe and Al) in bipolar configuration was implemented. A multifactorial experimental design was used for evaluating the influence of several parameters including: type and arrangement of electrodes, pH, and current density. Oil and grease removal was defined as the response variable for the statistical analysis. Additionally, the BOD(5), COD, and TOC were monitored during the treatment process. According to the results, at the optimum parameter values (current density = 4.3 mA/cm(2), distance between electrodes = 1.5 cm, Fe as anode, and pH = 12) it was possible to reach a c.a. 95% oils removal, COD and mineralization of 87.4% and 70.6%, respectively. A final biodegradability (BOD(5)/COD) of 0.54 was reached.

Quantum Space Charge Waves in a Waveguide Filled with Fermi-Dirac Plasmas Including Relativistic Wake Field and Quantum Statistical Pressure Effects

NASA Astrophysics Data System (ADS)

Hong, Woo-Pyo; Jung, Young-Dae

2018-03-01

The effects of quantum statistical degeneracy pressure on the propagation of the quantum space charge wave are investigated in a cylindrically bounded plasma waveguide filled with relativistically degenerate quantum Fermi-Dirac plasmas and the relativistic ion wake field. The results show that the domain of the degenerate parameter for the resonant beam instability significantly increases with an increase of the scaled beam velocity. It is found that the instability domain of the wave number increases with an increase of the degenerate parameter. It is also found that the growth rate for the resonant beam instability decreases with an increase of the degenerate parameter. In addition, it is shown that the lowest harmonic mode provides the maximum value of the growth rates. Moreover, it is shown that the instability domain of the wave number decreases with an increase of the beam velocity.

RAD-ADAPT: Software for modelling clonogenic assay data in radiation biology.

PubMed

Zhang, Yaping; Hu, Kaiqiang; Beumer, Jan H; Bakkenist, Christopher J; D'Argenio, David Z

2017-04-01

We present a comprehensive software program, RAD-ADAPT, for the quantitative analysis of clonogenic assays in radiation biology. Two commonly used models for clonogenic assay analysis, the linear-quadratic model and single-hit multi-target model, are included in the software. RAD-ADAPT uses maximum likelihood estimation method to obtain parameter estimates with the assumption that cell colony count data follow a Poisson distribution. The program has an intuitive interface, generates model prediction plots, tabulates model parameter estimates, and allows automatic statistical comparison of parameters between different groups. The RAD-ADAPT interface is written using the statistical software R and the underlying computations are accomplished by the ADAPT software system for pharmacokinetic/pharmacodynamic systems analysis. The use of RAD-ADAPT is demonstrated using an example that examines the impact of pharmacologic ATM and ATR kinase inhibition on human lung cancer cell line A549 after ionizing radiation. Copyright © 2017 Elsevier B.V. All rights reserved.

Interrelationships Between 3 Keratoconic Cone Parameters.

PubMed

Tu, Kyaw L; Tourkmani, Abdo K; Srinivas, Singaram

2017-09-01

To find out the interrelationships between 3 parameters of the keratoconic cone. A total of 101 keratoconic eyes of 58 patients were included in this retrospective case series study. A complete eye examination was performed. Kmax (K) and pachymetry at the thinnest point (T) were obtained from the Pentacam tomographer. The vertex to thinnest pachymetry distance (D for decentration) was calculated using trigonometry. Pearson correlation coefficients between T and D, between T and K, and between D and K were calculated. There is a statistically significant positive correlation between thinnest point pachymetry and decentration (R = 0.366, P = 0.0002) and also statistically significant negative correlation between thinnest point pachymetry and Kmax (R = -0.719, P < 0.00001) and decentration and Kmax (R = -0.281, P = 0.0044). The interrelationships between the 3 keratoconic cone parameters suggest that the thinner cones are largely central, that is, decenter less, but show greater steepening.

Calculating background levels for ecological risk parameters in toxic harbor sediment

USGS Publications Warehouse

Leadon, C.J.; McDonnell, T.R.; Lear, J.; Barclift, D.

2007-01-01

Establishing background levels for biological parameters is necessary in assessing the ecological risks from harbor sediment contaminated with toxic chemicals. For chemicals in sediment, the term contaminated is defined as having concentrations above background and significant human health or ecological risk levels. For biological parameters, a site could be considered contaminated if levels of the parameter are either more or less than the background level, depending on the specific parameter. Biological parameters can include tissue chemical concentrations in ecological receptors, bioassay responses, bioaccumulation levels, and benthic community metrics. Chemical parameters can include sediment concentrations of a variety of potentially toxic chemicals. Indirectly, contaminated harbor sediment can impact shellfish, fish, birds, and marine mammals, and human populations. This paper summarizes the methods used to define background levels for chemical and biological parameters from a survey of ecological risk investigations of marine harbor sediment at California Navy bases. Background levels for regional biological indices used to quantify ecological risks for benthic communities are also described. Generally, background stations are positioned in relatively clean areas exhibiting the same physical and general chemical characteristics as nearby areas with contaminated harbor sediment. The number of background stations and the number of sample replicates per background station depend on the statistical design of the sediment ecological risk investigation, developed through the data quality objective (DQO) process. Biological data from the background stations can be compared to data from a contaminated site by using minimum or maximum background levels or comparative statistics. In Navy ecological risk assessments (ERA's), calculated background levels and appropriate ecological risk screening criteria are used to identify sampling stations and sites with contaminated sediments.

TU-FG-201-03: Automatic Pre-Delivery Verification Using Statistical Analysis of Consistencies in Treatment Plan Parameters by the Treatment Site and Modality

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

Liu, S; Wu, Y; Chang, X

Purpose: A novel computer software system, namely APDV (Automatic Pre-Delivery Verification), has been developed for verifying patient treatment plan parameters right prior to treatment deliveries in order to automatically detect and prevent catastrophic errors. Methods: APDV is designed to continuously monitor new DICOM plan files on the TMS computer at the treatment console. When new plans to be delivered are detected, APDV checks the consistencies of plan parameters and high-level plan statistics using underlying rules and statistical properties based on given treatment site, technique and modality. These rules were quantitatively derived by retrospectively analyzing all the EBRT treatment plans ofmore » the past 8 years at authors’ institution. Therapists and physicists will be notified with a warning message displayed on the TMS computer if any critical errors are detected, and check results, confirmation, together with dismissal actions will be saved into database for further review. Results: APDV was implemented as a stand-alone program using C# to ensure required real time performance. Mean values and standard deviations were quantitatively derived for various plan parameters including MLC usage, MU/cGy radio, beam SSD, beam weighting, and the beam gantry angles (only for lateral targets) per treatment site, technique and modality. 2D-based rules of combined MU/cGy ratio and averaged SSD values were also derived using joint probabilities of confidence error ellipses. The statistics of these major treatment plan parameters quantitatively evaluate the consistency of any treatment plans which facilitates automatic APDV checking procedures. Conclusion: APDV could be useful in detecting and preventing catastrophic errors immediately before treatment deliveries. Future plan including automatic patient identify and patient setup checks after patient daily images are acquired by the machine and become available on the TMS computer. This project is supported by the Agency for Healthcare Research and Quality (AHRQ) under award 1R01HS0222888. The senior author received research grants from ViewRay Inc. and Varian Medical System.« less

Equations for normal-mode statistics of sound scattering by a rough elastic boundary in an underwater waveguide, including backscattering.

PubMed

Morozov, Andrey K; Colosi, John A

2017-09-01

Underwater sound scattering by a rough sea surface, ice, or a rough elastic bottom is studied. The study includes both the scattering from the rough boundary and the elastic effects in the solid layer. A coupled mode matrix is approximated by a linear function of one random perturbation parameter such as the ice-thickness or a perturbation of the surface position. A full two-way coupled mode solution is used to derive the stochastic differential equation for the second order statistics in a Markov approximation.

Parameter Estimation and Model Validation of Nonlinear Dynamical Networks

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

Abarbanel, Henry; Gill, Philip

In the performance period of this work under a DOE contract, the co-PIs, Philip Gill and Henry Abarbanel, developed new methods for statistical data assimilation for problems of DOE interest, including geophysical and biological problems. This included numerical optimization algorithms for variational principles, new parallel processing Monte Carlo routines for performing the path integrals of statistical data assimilation. These results have been summarized in the monograph: “Predicting the Future: Completing Models of Observed Complex Systems” by Henry Abarbanel, published by Spring-Verlag in June 2013. Additional results and details have appeared in the peer reviewed literature.

SPIPS: Spectro-Photo-Interferometry of Pulsating Stars

NASA Astrophysics Data System (ADS)

Mérand, Antoine

2017-10-01

SPIPS (Spectro-Photo-Interferometry of Pulsating Stars) combines radial velocimetry, interferometry, and photometry to estimate physical parameters of pulsating stars, including presence of infrared excess, color excess, Teff, and ratio distance/p-factor. The global model-based parallax-of-pulsation method is implemented in Python. Derived parameters have a high level of confidence; statistical precision is improved (compared to other methods) due to the large number of data taken into account, accuracy is improved by using consistent physical modeling and reliability of the derived parameters is strengthened by redundancy in the data.

Validating an Air Traffic Management Concept of Operation Using Statistical Modeling

NASA Technical Reports Server (NTRS)

He, Yuning; Davies, Misty Dawn

2013-01-01

Validating a concept of operation for a complex, safety-critical system (like the National Airspace System) is challenging because of the high dimensionality of the controllable parameters and the infinite number of states of the system. In this paper, we use statistical modeling techniques to explore the behavior of a conflict detection and resolution algorithm designed for the terminal airspace. These techniques predict the robustness of the system simulation to both nominal and off-nominal behaviors within the overall airspace. They also can be used to evaluate the output of the simulation against recorded airspace data. Additionally, the techniques carry with them a mathematical value of the worth of each prediction-a statistical uncertainty for any robustness estimate. Uncertainty Quantification (UQ) is the process of quantitative characterization and ultimately a reduction of uncertainties in complex systems. UQ is important for understanding the influence of uncertainties on the behavior of a system and therefore is valuable for design, analysis, and verification and validation. In this paper, we apply advanced statistical modeling methodologies and techniques on an advanced air traffic management system, namely the Terminal Tactical Separation Assured Flight Environment (T-TSAFE). We show initial results for a parameter analysis and safety boundary (envelope) detection in the high-dimensional parameter space. For our boundary analysis, we developed a new sequential approach based upon the design of computer experiments, allowing us to incorporate knowledge from domain experts into our modeling and to determine the most likely boundary shapes and its parameters. We carried out the analysis on system parameters and describe an initial approach that will allow us to include time-series inputs, such as the radar track data, into the analysis

A Handbook of Sound and Vibration Parameters

DTIC Science & Technology

1978-09-18

fixed in space. (Reference 1.) no motion atay node Static Divergence: (See Divergence.) Statistical Energy Analysis (SEA): Statistical energy analysis is...parameters of the circuits come from statistics of the vibrational characteristics of the structure. Statistical energy analysis is uniquely successful

Emulating Simulations of Cosmic Dawn for 21 cm Power Spectrum Constraints on Cosmology, Reionization, and X-Ray Heating

NASA Astrophysics Data System (ADS)

Kern, Nicholas S.; Liu, Adrian; Parsons, Aaron R.; Mesinger, Andrei; Greig, Bradley

2017-10-01

Current and upcoming radio interferometric experiments are aiming to make a statistical characterization of the high-redshift 21 cm fluctuation signal spanning the hydrogen reionization and X-ray heating epochs of the universe. However, connecting 21 cm statistics to the underlying physical parameters is complicated by the theoretical challenge of modeling the relevant physics at computational speeds quick enough to enable exploration of the high-dimensional and weakly constrained parameter space. In this work, we use machine learning algorithms to build a fast emulator that can accurately mimic an expensive simulation of the 21 cm signal across a wide parameter space. We embed our emulator within a Markov Chain Monte Carlo framework in order to perform Bayesian parameter constraints over a large number of model parameters, including those that govern the Epoch of Reionization, the Epoch of X-ray Heating, and cosmology. As a worked example, we use our emulator to present an updated parameter constraint forecast for the Hydrogen Epoch of Reionization Array experiment, showing that its characterization of a fiducial 21 cm power spectrum will considerably narrow the allowed parameter space of reionization and heating parameters, and could help strengthen Planck's constraints on {σ }8. We provide both our generalized emulator code and its implementation specifically for 21 cm parameter constraints as publicly available software.

Revised Planning Methodology For Signalized Intersections And Operational Analysis Of Exclusive Left-Turn Lanes, Part-II: Models And Procedures (Final Report)

DOT National Transportation Integrated Search

1996-04-01

THIS REPORT ALSO DESCRIBES THE PROCEDURES FOR DIRECT ESTIMATION OF INTERSECTION CAPACITY WITH SIMULATION, INCLUDING A SET OF RIGOROUS STATISTICAL TESTS FOR SIMULATION PARAMETER CALIBRATION FROM FIELD DATA.

Interpolative modeling of GaAs FET S-parameter data bases for use in Monte Carlo simulations

NASA Technical Reports Server (NTRS)

Campbell, L.; Purviance, J.

1992-01-01

A statistical interpolation technique is presented for modeling GaAs FET S-parameter measurements for use in the statistical analysis and design of circuits. This is accomplished by interpolating among the measurements in a GaAs FET S-parameter data base in a statistically valid manner.

Uncertainty Analysis of Seebeck Coefficient and Electrical Resistivity Characterization

NASA Technical Reports Server (NTRS)

Mackey, Jon; Sehirlioglu, Alp; Dynys, Fred

2014-01-01

In order to provide a complete description of a materials thermoelectric power factor, in addition to the measured nominal value, an uncertainty interval is required. The uncertainty may contain sources of measurement error including systematic bias error and precision error of a statistical nature. The work focuses specifically on the popular ZEM-3 (Ulvac Technologies) measurement system, but the methods apply to any measurement system. The analysis accounts for sources of systematic error including sample preparation tolerance, measurement probe placement, thermocouple cold-finger effect, and measurement parameters; in addition to including uncertainty of a statistical nature. Complete uncertainty analysis of a measurement system allows for more reliable comparison of measurement data between laboratories.

The effects of platelet apheresis on blood saving and coagulation in bilateral total hip replacement: A prospective study on 60 patients.

PubMed

Qu, Zhijun; Wang, Geng; Xu, Chengshi; Zhang, Dazhi; Qu, Xiangdong; Zhou, Haibin; Ma, Jun

2016-10-01

Preoperative platelet rich plasma (PRP) harvest has been used in cardiopulmonary surgery for more than 10 years. There is no previous study dealing with PRP in bilateral total hip replacement. This study was to investigate the effects of PRP on blood saving and blood coagulation function in patients with bilateral total hip replacement. A prospective, randomized, clinical trial was conducted. Sixty patients were enrolled, including 30 patients undergoing PRP in the PRP group and 30 controls. The surgery time, total transfusion volume, blood loss, allogenic blood transfusion, autologous blood transfusion, urine volume, drainage volume, some blood parameters (including Fibrinogen, D-dimer, Prothrombin time, international normalizedratio, activated partial thromboplastin time, Platelet, Haemoglobin B), thrombelastogram (TEG) and blood-gas parameters were studied in the perioperative stage. The measurement data were analyzed statistically. There was no statistical difference between the two groups in baseline characteristics, surgery time, total transfusion volume, blood loss, autologous blood transfusion, etc. Allogenic blood transfusion in the PRP group was less than the control group with statistical difference (p = 0.024). Fibrinogen in the PRP group was higher than the control group (p = 0.008). Among the TEG indicators, activated clotting time and coagulation time K in the PRP group were less than the control group. Clotting rate and maximum amplitude in the PRP group were higher. The blood-gas parameters presented no statistical difference. The results suggested that PRP probably played a positive role in blood coagulation function as well as blood saving in patients with bilateral total hip replacement. Copyright © 2016 IJS Publishing Group Ltd. Published by Elsevier Ltd. All rights reserved.

Multivariate Meta-Analysis of Heterogeneous Studies Using Only Summary Statistics: Efficiency and Robustness

PubMed Central

Liu, Dungang; Liu, Regina; Xie, Minge

2014-01-01

Meta-analysis has been widely used to synthesize evidence from multiple studies for common hypotheses or parameters of interest. However, it has not yet been fully developed for incorporating heterogeneous studies, which arise often in applications due to different study designs, populations or outcomes. For heterogeneous studies, the parameter of interest may not be estimable for certain studies, and in such a case, these studies are typically excluded from conventional meta-analysis. The exclusion of part of the studies can lead to a non-negligible loss of information. This paper introduces a metaanalysis for heterogeneous studies by combining the confidence density functions derived from the summary statistics of individual studies, hence referred to as the CD approach. It includes all the studies in the analysis and makes use of all information, direct as well as indirect. Under a general likelihood inference framework, this new approach is shown to have several desirable properties, including: i) it is asymptotically as efficient as the maximum likelihood approach using individual participant data (IPD) from all studies; ii) unlike the IPD analysis, it suffices to use summary statistics to carry out the CD approach. Individual-level data are not required; and iii) it is robust against misspecification of the working covariance structure of the parameter estimates. Besides its own theoretical significance, the last property also substantially broadens the applicability of the CD approach. All the properties of the CD approach are further confirmed by data simulated from a randomized clinical trials setting as well as by real data on aircraft landing performance. Overall, one obtains an unifying approach for combining summary statistics, subsuming many of the existing meta-analysis methods as special cases. PMID:26190875

A new statistical method for characterizing the atmospheres of extrasolar planets

NASA Astrophysics Data System (ADS)

Henderson, Cassandra S.; Skemer, Andrew J.; Morley, Caroline V.; Fortney, Jonathan J.

2017-10-01

By detecting light from extrasolar planets, we can measure their compositions and bulk physical properties. The technologies used to make these measurements are still in their infancy, and a lack of self-consistency suggests that previous observations have underestimated their systemic errors. We demonstrate a statistical method, newly applied to exoplanet characterization, which uses a Bayesian formalism to account for underestimated errorbars. We use this method to compare photometry of a substellar companion, GJ 758b, with custom atmospheric models. Our method produces a probability distribution of atmospheric model parameters including temperature, gravity, cloud model (fsed) and chemical abundance for GJ 758b. This distribution is less sensitive to highly variant data and appropriately reflects a greater uncertainty on parameter fits.

Correlations of fatty acid supplementation, aeroallergens, shampoo, and ear cleanser with multiple parameters in pruritic dogs.

PubMed

Nesbitt, Gene H; Freeman, Lisa M; Hannah, Steven S

2004-01-01

Seventy-two pruritic dogs were fed one of four diets controlled for n-6:n-3 fatty acid ratios and total dietary intake of fatty acids. Multiple parameters were evaluated, including clinical and cytological findings, aeroallergen testing, microbial sampling techniques, and effects of an anti-fungal/antibacterial shampoo and ear cleanser. Significant correlations were observed between many clinical parameters, anatomical sampling sites, and microbial counts when data from the diet groups was combined. There were no statistically significant differences between individual diets for any of the clinical parameters. The importance of total clinical management in the control of pruritus was demonstrated.

Selecting Summary Statistics in Approximate Bayesian Computation for Calibrating Stochastic Models

PubMed Central

Burr, Tom

2013-01-01

Approximate Bayesian computation (ABC) is an approach for using measurement data to calibrate stochastic computer models, which are common in biology applications. ABC is becoming the “go-to” option when the data and/or parameter dimension is large because it relies on user-chosen summary statistics rather than the full data and is therefore computationally feasible. One technical challenge with ABC is that the quality of the approximation to the posterior distribution of model parameters depends on the user-chosen summary statistics. In this paper, the user requirement to choose effective summary statistics in order to accurately estimate the posterior distribution of model parameters is investigated and illustrated by example, using a model and corresponding real data of mitochondrial DNA population dynamics. We show that for some choices of summary statistics, the posterior distribution of model parameters is closely approximated and for other choices of summary statistics, the posterior distribution is not closely approximated. A strategy to choose effective summary statistics is suggested in cases where the stochastic computer model can be run at many trial parameter settings, as in the example. PMID:24288668

Selecting summary statistics in approximate Bayesian computation for calibrating stochastic models.

PubMed

Burr, Tom; Skurikhin, Alexei

2013-01-01

Approximate Bayesian computation (ABC) is an approach for using measurement data to calibrate stochastic computer models, which are common in biology applications. ABC is becoming the "go-to" option when the data and/or parameter dimension is large because it relies on user-chosen summary statistics rather than the full data and is therefore computationally feasible. One technical challenge with ABC is that the quality of the approximation to the posterior distribution of model parameters depends on the user-chosen summary statistics. In this paper, the user requirement to choose effective summary statistics in order to accurately estimate the posterior distribution of model parameters is investigated and illustrated by example, using a model and corresponding real data of mitochondrial DNA population dynamics. We show that for some choices of summary statistics, the posterior distribution of model parameters is closely approximated and for other choices of summary statistics, the posterior distribution is not closely approximated. A strategy to choose effective summary statistics is suggested in cases where the stochastic computer model can be run at many trial parameter settings, as in the example.

Phase 1 of the near term hybrid passenger vehicle development program, appendix A. Mission analysis and performance specification studies. Volume 2: Appendices

NASA Technical Reports Server (NTRS)

Traversi, M.; Barbarek, L. A. C.

1979-01-01

A handy reference for JPL minimum requirements and guidelines is presented as well as information on the use of the fundamental information source represented by the Nationwide Personal Transportation Survey. Data on U.S. demographic statistics and highway speeds are included along with methodology for normal parameters evaluation, synthesis of daily distance distributions, and projection of car ownership distributions. The synthesis of tentative mission quantification results, of intermediate mission quantification results, and of mission quantification parameters are considered and 1985 in place fleet fuel economy data are included.

Characteristics of quantitative perfusion parameters on dynamic contrast‐enhanced MRI in mammographically occult breast cancer

PubMed Central

Ryu, Jung Kyu; Rhee, Sun Jung; Song, Jeong Yoon; Cho, Soo Hyun

2016-01-01

The purpose of this study was to compare the characteristics of quantitative perfusion parameters obtained from dynamic contrast‐enhanced (DCE) magnetic resonance imaging (MRI) in patients with mammographically occult (MO) breast cancers and those with mammographically visible (MV) breast cancers. Quantitative parameters (AUC, Ktrans,kep,ve,vp, and wi) from 13 MO breast cancers and 16 MV breast cancers were mapped after the DCE‐MRI data were acquired. Various prognostic factors, including axillary nodal status, estrogen receptor (ER), progesterone receptor (PR), Ki‐67, p53, E‐cadherin, and human epidermal growth factor receptor 2 (HER2) were obtained in each group. Fisher's exact test was used to compare any differences of the various prognostic factors between the two groups. The Mann‐Whitney U test was applied to compare the quantitative parameters between these two groups. Finally, Spearman's correlation was used to investigate the relationships between perfusion indices and four factors — age, tumor size, Ki‐67, and p53 — for each group. Although age, tumor size, and the prognostic factors were not statistically different between the two groups, the mean values of the quantitative parameters, except wi in the MV group, were higher than those in the MO group without statistical significance (p=0.219). The kep value was significantly different between the two groups (p=0.048), but the other parameters were not. In the MO group, vp with size, ve with p53, and Ktrans and vp with Ki‐67 had significant correlations (p<0.05). However, in the MV group, only kep showed significant correlation with age. The kep value was only the perfusion parameter of statistical significance between MO and MV breast cancers. PACS number(s): 87.19.U‐, 87.61.‐c PMID:27685105

Uncertainty Analysis of Inertial Model Attitude Sensor Calibration and Application with a Recommended New Calibration Method

NASA Technical Reports Server (NTRS)

Tripp, John S.; Tcheng, Ping

1999-01-01

Statistical tools, previously developed for nonlinear least-squares estimation of multivariate sensor calibration parameters and the associated calibration uncertainty analysis, have been applied to single- and multiple-axis inertial model attitude sensors used in wind tunnel testing to measure angle of attack and roll angle. The analysis provides confidence and prediction intervals of calibrated sensor measurement uncertainty as functions of applied input pitch and roll angles. A comparative performance study of various experimental designs for inertial sensor calibration is presented along with corroborating experimental data. The importance of replicated calibrations over extended time periods has been emphasized; replication provides independent estimates of calibration precision and bias uncertainties, statistical tests for calibration or modeling bias uncertainty, and statistical tests for sensor parameter drift over time. A set of recommendations for a new standardized model attitude sensor calibration method and usage procedures is included. The statistical information provided by these procedures is necessary for the uncertainty analysis of aerospace test results now required by users of industrial wind tunnel test facilities.

Large ensemble modeling of the last deglacial retreat of the West Antarctic Ice Sheet: comparison of simple and advanced statistical techniques

NASA Astrophysics Data System (ADS)

Pollard, David; Chang, Won; Haran, Murali; Applegate, Patrick; DeConto, Robert

2016-05-01

A 3-D hybrid ice-sheet model is applied to the last deglacial retreat of the West Antarctic Ice Sheet over the last ˜ 20 000 yr. A large ensemble of 625 model runs is used to calibrate the model to modern and geologic data, including reconstructed grounding lines, relative sea-level records, elevation-age data and uplift rates, with an aggregate score computed for each run that measures overall model-data misfit. Two types of statistical methods are used to analyze the large-ensemble results: simple averaging weighted by the aggregate score, and more advanced Bayesian techniques involving Gaussian process-based emulation and calibration, and Markov chain Monte Carlo. The analyses provide sea-level-rise envelopes with well-defined parametric uncertainty bounds, but the simple averaging method only provides robust results with full-factorial parameter sampling in the large ensemble. Results for best-fit parameter ranges and envelopes of equivalent sea-level rise with the simple averaging method agree well with the more advanced techniques. Best-fit parameter ranges confirm earlier values expected from prior model tuning, including large basal sliding coefficients on modern ocean beds.

ANESTHETIC INDUCTION AND RECOVERY PARAMETERS IN BEARDED DRAGONS (POGONA VITTICEPS): COMPARISON OF ISOFLURANE DELIVERED IN 100% OXYGEN VERSUS 21% OXYGEN.

PubMed

O, Odette; Churgin, Sarah M; Sladky, Kurt K; Smith, Lesley J

2015-09-01

Inland bearded dragons (Pogona vitticeps, n=6) were anesthetized for 1 hr using isoflurane in either 100% oxygen or 21% oxygen (FI 21; medical-grade room air). Parameters of anesthetic depth were recorded throughout both induction and recovery by an observer blinded to the fraction of inspired oxygen (FiO2), including the loss and return of withdrawal and righting reflexes, muscle tone, ability to intubate or extubate, and return to spontaneous respiration. Physiologic data were recorded every 5 min throughout the anesthetic procedures, including heart rate, body temperature, end-tidal CO2, hemoglobin oxygen saturation (SpO2), and percent expired isoflurane. Lizards were subjected to application of a noxious stimulus (needle stick) at 0, 30, and 60 min, and responses recorded. Following a minimum 7-day washout period, the experiment was repeated with each lizard subjected to the other protocol in a randomized, complete crossover design. The only statistically significant difference was a lower mean SpO2 in the group inspiring 21% oxygen (P<0.0020). No statistically significant differences were detected in any parameters during induction or recovery; however, all values were uniformly shorter for the FI 21 group, indicating a possible clinically significant difference. A larger sample size may have detected statistically significant differences. Further studies are needed to evaluate these effects in other reptile species and with the concurrent use of injectable anesthetic and analgesic drugs.

SCARE: A post-processor program to MSC/NASTRAN for the reliability analysis of structural ceramic components

NASA Technical Reports Server (NTRS)

Gyekenyesi, J. P.

1985-01-01

A computer program was developed for calculating the statistical fast fracture reliability and failure probability of ceramic components. The program includes the two-parameter Weibull material fracture strength distribution model, using the principle of independent action for polyaxial stress states and Batdorf's shear-sensitive as well as shear-insensitive crack theories, all for volume distributed flaws in macroscopically isotropic solids. Both penny-shaped cracks and Griffith cracks are included in the Batdorf shear-sensitive crack response calculations, using Griffith's maximum tensile stress or critical coplanar strain energy release rate criteria to predict mixed mode fracture. Weibull material parameters can also be calculated from modulus of rupture bar tests, using the least squares method with known specimen geometry and fracture data. The reliability prediction analysis uses MSC/NASTRAN stress, temperature and volume output, obtained from the use of three-dimensional, quadratic, isoparametric, or axisymmetric finite elements. The statistical fast fracture theories employed, along with selected input and output formats and options, are summarized. An example problem to demonstrate various features of the program is included.

OPEN PROBLEM: Orbits' statistics in chaotic dynamical systems

NASA Astrophysics Data System (ADS)

Arnold, V.

2008-07-01

This paper shows how the measurement of the stochasticity degree of a finite sequence of real numbers, published by Kolmogorov in Italian in a journal of insurances' statistics, can be usefully applied to measure the objective stochasticity degree of sequences, originating from dynamical systems theory and from number theory. Namely, whenever the value of Kolmogorov's stochasticity parameter of a given sequence of numbers is too small (or too big), one may conclude that the conjecture describing this sequence as a sample of independent values of a random variables is highly improbable. Kolmogorov used this strategy fighting (in a paper in 'Doklady', 1940) against Lysenko, who had tried to disprove the classical genetics' law of Mendel experimentally. Calculating his stochasticity parameter value for the numbers from Lysenko's experiment reports, Kolmogorov deduced, that, while these numbers were different from the exact fulfilment of Mendel's 3 : 1 law, any smaller deviation would be a manifestation of the report's number falsification. The calculation of the values of the stochasticity parameter would be useful for many other generators of pseudorandom numbers and for many other chaotically looking statistics, including even the prime numbers distribution (discussed in this paper as an example).

New insights into time series analysis. II - Non-correlated observations

NASA Astrophysics Data System (ADS)

Ferreira Lopes, C. E.; Cross, N. J. G.

2017-08-01

Context. Statistical parameters are used to draw conclusions in a vast number of fields such as finance, weather, industrial, and science. These parameters are also used to identify variability patterns on photometric data to select non-stochastic variations that are indicative of astrophysical effects. New, more efficient, selection methods are mandatory to analyze the huge amount of astronomical data. Aims: We seek to improve the current methods used to select non-stochastic variations on non-correlated data. Methods: We used standard and new data-mining parameters to analyze non-correlated data to find the best way to discriminate between stochastic and non-stochastic variations. A new approach that includes a modified Strateva function was performed to select non-stochastic variations. Monte Carlo simulations and public time-domain data were used to estimate its accuracy and performance. Results: We introduce 16 modified statistical parameters covering different features of statistical distribution such as average, dispersion, and shape parameters. Many dispersion and shape parameters are unbound parameters, I.e. equations that do not require the calculation of average. Unbound parameters are computed with single loop and hence decreasing running time. Moreover, the majority of these parameters have lower errors than previous parameters, which is mainly observed for distributions with few measurements. A set of non-correlated variability indices, sample size corrections, and a new noise model along with tests of different apertures and cut-offs on the data (BAS approach) are introduced. The number of mis-selections are reduced by about 520% using a single waveband and 1200% combining all wavebands. On the other hand, the even-mean also improves the correlated indices introduced in Paper I. The mis-selection rate is reduced by about 18% if the even-mean is used instead of the mean to compute the correlated indices in the WFCAM database. Even-statistics allows us to improve the effectiveness of both correlated and non-correlated indices. Conclusions: The selection of non-stochastic variations is improved by non-correlated indices. The even-averages provide a better estimation of mean and median for almost all statistical distributions analyzed. The correlated variability indices, which are proposed in the first paper of this series, are also improved if the even-mean is used. The even-parameters will also be useful for classifying light curves in the last step of this project. We consider that the first step of this project, where we set new techniques and methods that provide a huge improvement on the efficiency of selection of variable stars, is now complete. Many of these techniques may be useful for a large number of fields. Next, we will commence a new step of this project regarding the analysis of period search methods.

Estimation of Quasi-Stiffness and Propulsive Work of the Human Ankle in the Stance Phase of Walking

PubMed Central

Shamaei, Kamran; Sawicki, Gregory S.; Dollar, Aaron M.

2013-01-01

Characterizing the quasi-stiffness and work of lower extremity joints is critical for evaluating human locomotion and designing assistive devices such as prostheses and orthoses intended to emulate the biological behavior of human legs. This work aims to establish statistical models that allow us to predict the ankle quasi-stiffness and net mechanical work for adults walking on level ground. During the stance phase of walking, the ankle joint propels the body through three distinctive phases of nearly constant stiffness known as the quasi-stiffness of each phase. Using a generic equation for the ankle moment obtained through an inverse dynamics analysis, we identify key independent parameters needed to predict ankle quasi-stiffness and propulsive work and also the functional form of each correlation. These parameters include gait speed, ankle excursion, and subject height and weight. Based on the identified form of the correlation and key variables, we applied linear regression on experimental walking data for 216 gait trials across 26 subjects (speeds from 0.75–2.63 m/s) to obtain statistical models of varying complexity. The most general forms of the statistical models include all the key parameters and have an R2 of 75% to 81% in the prediction of the ankle quasi-stiffnesses and propulsive work. The most specific models include only subject height and weight and could predict the ankle quasi-stiffnesses and work for optimal walking speed with average error of 13% to 30%. We discuss how these models provide a useful framework and foundation for designing subject- and gait-specific prosthetic and exoskeletal devices designed to emulate biological ankle function during level ground walking. PMID:23555839

PMMA/PS coaxial electrospinning: a statistical analysis on processing parameters

NASA Astrophysics Data System (ADS)

Rahmani, Shahrzad; Arefazar, Ahmad; Latifi, Masoud

2017-08-01

Coaxial electrospinning, as a versatile method for producing core-shell fibers, is known to be very sensitive to two classes of influential factors including material and processing parameters. Although coaxial electrospinning has been the focus of many studies, the effects of processing parameters on the outcomes of this method have not yet been well investigated. A good knowledge of the impacts of processing parameters and their interactions on coaxial electrospinning can make it possible to better control and optimize this process. Hence, in this study, the statistical technique of response surface method (RSM) using the design of experiments on four processing factors of voltage, distance, core and shell flow rates was applied. Transmission electron microscopy (TEM), scanning electron microscopy (SEM), oil immersion and Fluorescent microscopy were used to characterize fiber morphology. The core and shell diameters of fibers were measured and the effects of all factors and their interactions were discussed. Two polynomial models with acceptable R-squares were proposed to describe the core and shell diameters as functions of the processing parameters. Voltage and distance were recognized as the most significant and influential factors on shell diameter, while core diameter was mainly under the influence of core and shell flow rates besides the voltage.

Statistical Study of ICMEs and Their Sheaths During Solar Cycle 23 (1996 - 2008)

NASA Astrophysics Data System (ADS)

Mitsakou, E.; Moussas, X.

2014-08-01

We have created a new catalog of 325 interplanetary coronal mass ejections (ICMEs) using their in-situ plasma signatures from 1996 to 2008; this time period includes Solar Cycle 23. The data set came from the OMNI near-Earth database. The one-minute resolution data that we used include magnetic-field strength, solar-wind speed, proton density, proton temperature, and plasma β. We compared this new catalog with other published catalogs. For every event, we indicated the presence of an ICME-driven shock. We identified the boundaries of ICMEs and their sheaths, and examined the statistical properties of characteristic parameters. We derived the duration and radial width of ICMEs and sheaths in the region near Earth. The statistical analysis of all events shows that, on average, sheaths travel faster than ICMEs, which indicates the expansion of CMEs in the interplanetary medium. They have higher mean magnetic-field strength values than ICMEs, and they are denser. They have higher mean proton temperature and plasma β than ICMEs, but they are smaller than ICMEs and last for a shorter time. The events were divided into different categories according to whether they included a shock and according to the phase of Solar Cycle 23 in which they are observed, i.e. ascending, maximum, or descending phase. We compared the different categories. We present a catalog of events available to the scientific community that studies ICMEs, and show the distribution and statistical properties of various parameters during these phenomena that govern the solar wind, the interplanetary medium, and space weather.

Sequential Markov chain Monte Carlo filter with simultaneous model selection for electrocardiogram signal modeling.

PubMed

Edla, Shwetha; Kovvali, Narayan; Papandreou-Suppappola, Antonia

2012-01-01

Constructing statistical models of electrocardiogram (ECG) signals, whose parameters can be used for automated disease classification, is of great importance in precluding manual annotation and providing prompt diagnosis of cardiac diseases. ECG signals consist of several segments with different morphologies (namely the P wave, QRS complex and the T wave) in a single heart beat, which can vary across individuals and diseases. Also, existing statistical ECG models exhibit a reliance upon obtaining a priori information from the ECG data by using preprocessing algorithms to initialize the filter parameters, or to define the user-specified model parameters. In this paper, we propose an ECG modeling technique using the sequential Markov chain Monte Carlo (SMCMC) filter that can perform simultaneous model selection, by adaptively choosing from different representations depending upon the nature of the data. Our results demonstrate the ability of the algorithm to track various types of ECG morphologies, including intermittently occurring ECG beats. In addition, we use the estimated model parameters as the feature set to classify between ECG signals with normal sinus rhythm and four different types of arrhythmia.

Establishment and Assessment of Plasma Disruption and Warning Databases from EAST

NASA Astrophysics Data System (ADS)

Wang, Bo; Robert, Granetz; Xiao, Bingjia; Li, Jiangang; Yang, Fei; Li, Junjun; Chen, Dalong

2016-12-01

Disruption database and disruption warning database of the EAST tokamak had been established by a disruption research group. The disruption database, based on Structured Query Language (SQL), comprises 41 disruption parameters, which include current quench characteristics, EFIT equilibrium characteristics, kinetic parameters, halo currents, and vertical motion. Presently most disruption databases are based on plasma experiments of non-superconducting tokamak devices. The purposes of the EAST database are to find disruption characteristics and disruption statistics to the fully superconducting tokamak EAST, to elucidate the physics underlying tokamak disruptions, to explore the influence of disruption on superconducting magnets and to extrapolate toward future burning plasma devices. In order to quantitatively assess the usefulness of various plasma parameters for predicting disruptions, a similar SQL database to Alcator C-Mod for EAST has been created by compiling values for a number of proposed disruption-relevant parameters sampled from all plasma discharges in the 2015 campaign. The detailed statistic results and analysis of two databases on the EAST tokamak are presented. supported by the National Magnetic Confinement Fusion Science Program of China (No. 2014GB103000)

Pattern statistics on Markov chains and sensitivity to parameter estimation

PubMed Central

Nuel, Grégory

2006-01-01

Background: In order to compute pattern statistics in computational biology a Markov model is commonly used to take into account the sequence composition. Usually its parameter must be estimated. The aim of this paper is to determine how sensitive these statistics are to parameter estimation, and what are the consequences of this variability on pattern studies (finding the most over-represented words in a genome, the most significant common words to a set of sequences,...). Results: In the particular case where pattern statistics (overlap counting only) computed through binomial approximations we use the delta-method to give an explicit expression of σ, the standard deviation of a pattern statistic. This result is validated using simulations and a simple pattern study is also considered. Conclusion: We establish that the use of high order Markov model could easily lead to major mistakes due to the high sensitivity of pattern statistics to parameter estimation. PMID:17044916

Pattern statistics on Markov chains and sensitivity to parameter estimation.

PubMed

Nuel, Grégory

2006-10-17

In order to compute pattern statistics in computational biology a Markov model is commonly used to take into account the sequence composition. Usually its parameter must be estimated. The aim of this paper is to determine how sensitive these statistics are to parameter estimation, and what are the consequences of this variability on pattern studies (finding the most over-represented words in a genome, the most significant common words to a set of sequences,...). In the particular case where pattern statistics (overlap counting only) computed through binomial approximations we use the delta-method to give an explicit expression of sigma, the standard deviation of a pattern statistic. This result is validated using simulations and a simple pattern study is also considered. We establish that the use of high order Markov model could easily lead to major mistakes due to the high sensitivity of pattern statistics to parameter estimation.

Parameter estimation techniques based on optimizing goodness-of-fit statistics for structural reliability

NASA Technical Reports Server (NTRS)

Starlinger, Alois; Duffy, Stephen F.; Palko, Joseph L.

1993-01-01

New methods are presented that utilize the optimization of goodness-of-fit statistics in order to estimate Weibull parameters from failure data. It is assumed that the underlying population is characterized by a three-parameter Weibull distribution. Goodness-of-fit tests are based on the empirical distribution function (EDF). The EDF is a step function, calculated using failure data, and represents an approximation of the cumulative distribution function for the underlying population. Statistics (such as the Kolmogorov-Smirnov statistic and the Anderson-Darling statistic) measure the discrepancy between the EDF and the cumulative distribution function (CDF). These statistics are minimized with respect to the three Weibull parameters. Due to nonlinearities encountered in the minimization process, Powell's numerical optimization procedure is applied to obtain the optimum value of the EDF. Numerical examples show the applicability of these new estimation methods. The results are compared to the estimates obtained with Cooper's nonlinear regression algorithm.

Surveillance of industrial processes with correlated parameters

DOEpatents

White, Andrew M.; Gross, Kenny C.; Kubic, William L.; Wigeland, Roald A.

1996-01-01

A system and method for surveillance of an industrial process. The system and method includes a plurality of sensors monitoring industrial process parameters, devices to convert the sensed data to computer compatible information and a computer which executes computer software directed to analyzing the sensor data to discern statistically reliable alarm conditions. The computer software is executed to remove serial correlation information and then calculate Mahalanobis distribution data to carry out a probability ratio test to determine alarm conditions.

Multivariable Parametric Cost Model for Ground Optical Telescope Assembly

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Rowell, Ginger Holmes; Reese, Gayle; Byberg, Alicia

2005-01-01

A parametric cost model for ground-based telescopes is developed using multivariable statistical analysis of both engineering and performance parameters. While diameter continues to be the dominant cost driver, diffraction-limited wavelength is found to be a secondary driver. Other parameters such as radius of curvature are examined. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e., multi-telescope phased-array systems). Additionally, single variable models Based on aperture diameter are derived.

Progress in Turbulence Detection via GNSS Occultation Data

NASA Technical Reports Server (NTRS)

Cornman, L. B.; Goodrich, R. K.; Axelrad, P.; Barlow, E.

2012-01-01

The increased availability of radio occultation (RO) data offers the ability to detect and study turbulence in the Earth's atmosphere. An analysis of how RO data can be used to determine the strength and location of turbulent regions is presented. This includes the derivation of a model for the power spectrum of the log-amplitude and phase fluctuations of the permittivity (or index of refraction) field. The bulk of the paper is then concerned with the estimation of the model parameters. Parameter estimators are introduced and some of their statistical properties are studied. These estimators are then applied to simulated log-amplitude RO signals. This includes the analysis of global statistics derived from a large number of realizations, as well as case studies that illustrate various specific aspects of the problem. Improvements to the basic estimation methods are discussed, and their beneficial properties are illustrated. The estimation techniques are then applied to real occultation data. Only two cases are presented, but they illustrate some of the salient features inherent in real data.

The effects of DRIE operational parameters on vertically aligned micropillar arrays

NASA Astrophysics Data System (ADS)

Miller, Kane; Li, Mingxiao; Walsh, Kevin M.; Fu, Xiao-An

2013-03-01

Vertically aligned silicon micropillar arrays have been created by deep reactive ion etching (DRIE) and used for a number of microfabricated devices including microfluidic devices, micropreconcentrators and photovoltaic cells. This paper delineates an experimental design performed on the Bosch process of DRIE of micropillar arrays. The arrays are fabricated with direct-write optical lithography without photomask, and the effects of DRIE process parameters, including etch cycle time, passivation cycle time, platen power and coil power on profile angle, scallop depth and scallop peak-to-peak distance are studied by statistical design of experiments. Scanning electron microscope images are used for measuring the resultant profile angles and characterizing the scalloping effect on the pillar sidewalls. The experimental results indicate the effects of the determining factors, etch cycle time, passivation cycle time and platen power, on the micropillar profile angles and scallop depths. An optimized DRIE process recipe for creating nearly 90° and smooth surface (invisible scalloping) has been obtained as a result of the statistical design of experiments.

Probabilistic evaluation of damage potential in earthquake-induced liquefaction in a 3-D soil deposit

NASA Astrophysics Data System (ADS)

Halder, A.; Miller, F. J.

1982-03-01

A probabilistic model to evaluate the risk of liquefaction at a site and to limit or eliminate damage during earthquake induced liquefaction is proposed. The model is extended to consider three dimensional nonhomogeneous soil properties. The parameters relevant to the liquefaction phenomenon are identified, including: (1) soil parameters; (2) parameters required to consider laboratory test and sampling effects; and (3) loading parameters. The fundamentals of risk based design concepts pertient to liquefaction are reviewed. A detailed statistical evaluation of the soil parameters in the proposed liquefaction model is provided and the uncertainty associated with the estimation of in situ relative density is evaluated for both direct and indirect methods. It is found that the liquefaction potential the uncertainties in the load parameters could be higher than those in the resistance parameters.

A multimodal wave spectrum-based approach for statistical downscaling of local wave climate

USGS Publications Warehouse

Hegermiller, Christie; Antolinez, Jose A A; Rueda, Ana C.; Camus, Paula; Perez, Jorge; Erikson, Li; Barnard, Patrick; Mendez, Fernando J.

2017-01-01

Characterization of wave climate by bulk wave parameters is insufficient for many coastal studies, including those focused on assessing coastal hazards and long-term wave climate influences on coastal evolution. This issue is particularly relevant for studies using statistical downscaling of atmospheric fields to local wave conditions, which are often multimodal in large ocean basins (e.g. the Pacific). Swell may be generated in vastly different wave generation regions, yielding complex wave spectra that are inadequately represented by a single set of bulk wave parameters. Furthermore, the relationship between atmospheric systems and local wave conditions is complicated by variations in arrival time of wave groups from different parts of the basin. Here, we address these two challenges by improving upon the spatiotemporal definition of the atmospheric predictor used in statistical downscaling of local wave climate. The improved methodology separates the local wave spectrum into “wave families,” defined by spectral peaks and discrete generation regions, and relates atmospheric conditions in distant regions of the ocean basin to local wave conditions by incorporating travel times computed from effective energy flux across the ocean basin. When applied to locations with multimodal wave spectra, including Southern California and Trujillo, Peru, the new methodology improves the ability of the statistical model to project significant wave height, peak period, and direction for each wave family, retaining more information from the full wave spectrum. This work is the base of statistical downscaling by weather types, which has recently been applied to coastal flooding and morphodynamic applications.

Software for Statistical Analysis of Weibull Distributions with Application to Gear Fatigue Data: User Manual with Verification

NASA Technical Reports Server (NTRS)

Krantz, Timothy L.

2002-01-01

The Weibull distribution has been widely adopted for the statistical description and inference of fatigue data. This document provides user instructions, examples, and verification for software to analyze gear fatigue test data. The software was developed presuming the data are adequately modeled using a two-parameter Weibull distribution. The calculations are based on likelihood methods, and the approach taken is valid for data that include type 1 censoring. The software was verified by reproducing results published by others.

Software for Statistical Analysis of Weibull Distributions with Application to Gear Fatigue Data: User Manual with Verification

NASA Technical Reports Server (NTRS)

Kranz, Timothy L.

2002-01-01

The Weibull distribution has been widely adopted for the statistical description and inference of fatigue data. This document provides user instructions, examples, and verification for software to analyze gear fatigue test data. The software was developed presuming the data are adequately modeled using a two-parameter Weibull distribution. The calculations are based on likelihood methods, and the approach taken is valid for data that include type I censoring. The software was verified by reproducing results published by others.

SEDIDAT: A BASIC program for the collection and statistical analysis of particle settling velocity data

NASA Astrophysics Data System (ADS)

Wright, Robyn; Thornberg, Steven M.

SEDIDAT is a series of compiled IBM-BASIC (version 2.0) programs that direct the collection, statistical calculation, and graphic presentation of particle settling velocity and equivalent spherical diameter for samples analyzed using the settling tube technique. The programs follow a menu-driven format that is understood easily by students and scientists with little previous computer experience. Settling velocity is measured directly (cm,sec) and also converted into Chi units. Equivalent spherical diameter (reported in Phi units) is calculated using a modified Gibbs equation for different particle densities. Input parameters, such as water temperature, settling distance, particle density, run time, and Phi;Chi interval are changed easily at operator discretion. Optional output to a dot-matrix printer includes a summary of moment and graphic statistical parameters, a tabulation of individual and cumulative weight percents, a listing of major distribution modes, and cumulative and histogram plots of a raw time, settling velocity. Chi and Phi data.

Predictive Model for the Design of Zwitterionic Polymer Brushes: A Statistical Design of Experiments Approach.

PubMed

Kumar, Ramya; Lahann, Joerg

2016-07-06

The performance of polymer interfaces in biology is governed by a wide spectrum of interfacial properties. With the ultimate goal of identifying design parameters for stem cell culture coatings, we developed a statistical model that describes the dependence of brush properties on surface-initiated polymerization (SIP) parameters. Employing a design of experiments (DOE) approach, we identified operating boundaries within which four gel architecture regimes can be realized, including a new regime of associated brushes in thin films. Our statistical model can accurately predict the brush thickness and the degree of intermolecular association of poly[{2-(methacryloyloxy) ethyl} dimethyl-(3-sulfopropyl) ammonium hydroxide] (PMEDSAH), a previously reported synthetic substrate for feeder-free and xeno-free culture of human embryonic stem cells. DOE-based multifunctional predictions offer a powerful quantitative framework for designing polymer interfaces. For example, model predictions can be used to decrease the critical thickness at which the wettability transition occurs by simply increasing the catalyst quantity from 1 to 3 mol %.

Verification of Eulerian-Eulerian and Eulerian-Lagrangian simulations for turbulent fluid-particle flows

DOE PAGES

Patel, Ravi G.; Desjardins, Olivier; Kong, Bo; ...

2017-09-01

Here, we present a verification study of three simulation techniques for fluid–particle flows, including an Euler–Lagrange approach (EL) inspired by Jackson's seminal work on fluidized particles, a quadrature–based moment method based on the anisotropic Gaussian closure (AG), and the traditional two-fluid model. We perform simulations of two problems: particles in frozen homogeneous isotropic turbulence (HIT) and cluster-induced turbulence (CIT). For verification, we evaluate various techniques for extracting statistics from EL and study the convergence properties of the three methods under grid refinement. The convergence is found to depend on the simulation method and on the problem, with CIT simulations posingmore » fewer difficulties than HIT. Specifically, EL converges under refinement for both HIT and CIT, but statistics exhibit dependence on the postprocessing parameters. For CIT, AG produces similar results to EL. For HIT, converging both TFM and AG poses challenges. Overall, extracting converged, parameter-independent Eulerian statistics remains a challenge for all methods.« less

Conditions, interventions, and outcomes in nursing research: a comparative analysis of North American and European/International journals. (1981-1990).

PubMed

Abraham, I L; Chalifoux, Z L; Evers, G C; De Geest, S

1995-04-01

This study compared the conceptual foci and methodological characteristics of research projects which tested the effects of nursing interventions, published in four general nursing research journals with predominantly North American, and two with predominantly European/International authorship and readership. Dimensions and variables of comparison included: nature of subjects, design issues, statistical methodology, statistical power, and types of interventions and outcomes. Although some differences emerged, the most striking and consistent finding was that there were no statistically significant differences (and thus similarities) in the content foci and methodological parameters of the intervention studies published in both groups of journals. We conclude that European/International and North American nursing intervention studies, as reported in major general nursing research journals, are highly similar in the parameters studied, yet in need of overall improvement. Certainly, there is no empirical support for the common (explicit or implicit) ethnocentric American bias that leadership in nursing intervention research resides with and in the United States of America.

Verification of Eulerian-Eulerian and Eulerian-Lagrangian simulations for turbulent fluid-particle flows

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

Patel, Ravi G.; Desjardins, Olivier; Kong, Bo

Here, we present a verification study of three simulation techniques for fluid–particle flows, including an Euler–Lagrange approach (EL) inspired by Jackson's seminal work on fluidized particles, a quadrature–based moment method based on the anisotropic Gaussian closure (AG), and the traditional two-fluid model. We perform simulations of two problems: particles in frozen homogeneous isotropic turbulence (HIT) and cluster-induced turbulence (CIT). For verification, we evaluate various techniques for extracting statistics from EL and study the convergence properties of the three methods under grid refinement. The convergence is found to depend on the simulation method and on the problem, with CIT simulations posingmore » fewer difficulties than HIT. Specifically, EL converges under refinement for both HIT and CIT, but statistics exhibit dependence on the postprocessing parameters. For CIT, AG produces similar results to EL. For HIT, converging both TFM and AG poses challenges. Overall, extracting converged, parameter-independent Eulerian statistics remains a challenge for all methods.« less

Comparison of Sperm Parameters in Patients with Infertility Induced by Genital Infection versus Varicocele

PubMed Central

Pajovic, Bogdan; Dimitrovski, Antonio; Radojevic, Nemanja; Vukovic, Marko

2015-01-01

Background: Male infertility is a common and complex problem and, despite much research in this field, the major cause of infertility unfortunately remains unknown. Genital infection and varicocele are important causes of infertility. Aims: To compare the influence of genital infection and varicocele individually on male infertility based on semen analysis. Study Design: Cross-sectional study. Methods: The study included 120 infertile patients divided into two groups according to the presence of genital infection or varicocele. The first group included 60 examinees with proven genital infection, but without varicocele formation. The second included 60 patients with varicocele, regardless of the varicocele grade, but without genital infection. The fertile parameters were compared and an assessment was performed on the impact on quality of spermatogenesis due to infection and varicocele. Results: There is a statistically significant difference regarding abnormal forms of spermatozoids (45.94±9.79 vs. 25.27±6.54) and progressive motility (8.15±1.24 vs. 24.95±7.2), between two groups of patients. However, acidity of ejaculates, minimum sperm concentration, total spermatozoid motility and ejaculate volume showed no statistically significant difference. Conclusion: The study showed a stronger negative influence of genital infection on fertile parameters over varicocele. The significance of our study is the lack of contemporary researches comparing varicocele and genital infection influence on male infertility individually. PMID:26185712

Comparison of Sperm Parameters in Patients with Infertility Induced by Genital Infection versus Varicocele.

PubMed

Pajovic, Bogdan; Dimitrovski, Antonio; Radojevic, Nemanja; Vukovic, Marko

2015-07-01

Male infertility is a common and complex problem and, despite much research in this field, the major cause of infertility unfortunately remains unknown. Genital infection and varicocele are important causes of infertility. To compare the influence of genital infection and varicocele individually on male infertility based on semen analysis. Cross-sectional study. The study included 120 infertile patients divided into two groups according to the presence of genital infection or varicocele. The first group included 60 examinees with proven genital infection, but without varicocele formation. The second included 60 patients with varicocele, regardless of the varicocele grade, but without genital infection. The fertile parameters were compared and an assessment was performed on the impact on quality of spermatogenesis due to infection and varicocele. There is a statistically significant difference regarding abnormal forms of spermatozoids (45.94±9.79 vs. 25.27±6.54) and progressive motility (8.15±1.24 vs. 24.95±7.2), between two groups of patients. However, acidity of ejaculates, minimum sperm concentration, total spermatozoid motility and ejaculate volume showed no statistically significant difference. The study showed a stronger negative influence of genital infection on fertile parameters over varicocele. The significance of our study is the lack of contemporary researches comparing varicocele and genital infection influence on male infertility individually.

Improving the efficiency of the cardiac catheterization laboratories through understanding the stochastic behavior of the scheduled procedures.

PubMed

Stepaniak, Pieter S; Soliman Hamad, Mohamed A; Dekker, Lukas R C; Koolen, Jacques J

2014-01-01

In this study, we sought to analyze the stochastic behavior of Catherization Laboratories (Cath Labs) procedures in our institution. Statistical models may help to improve estimated case durations to support management in the cost-effective use of expensive surgical resources. We retrospectively analyzed all the procedures performed in the Cath Labs in 2012. The duration of procedures is strictly positive (larger than zero) and has mostly a large minimum duration. Because of the strictly positive character of the Cath Lab procedures, a fit of a lognormal model may be desirable. Having a minimum duration requires an estimate of the threshold (shift) parameter of the lognormal model. Therefore, the 3-parameter lognormal model is interesting. To avoid heterogeneous groups of observations, we tested every group-cardiologist-procedure combination for the normal, 2- and 3-parameter lognormal distribution. The total number of elective and emergency procedures performed was 6,393 (8,186 h). The final analysis included 6,135 procedures (7,779 h). Electrophysiology (intervention) procedures fit the 3-parameter lognormal model 86.1% (80.1%). Using Friedman test statistics, we conclude that the 3-parameter lognormal model is superior to the 2-parameter lognormal model. Furthermore, the 2-parameter lognormal is superior to the normal model. Cath Lab procedures are well-modelled by lognormal models. This information helps to improve and to refine Cath Lab schedules and hence their efficient use.

Principle of maximum entropy for reliability analysis in the design of machine components

NASA Astrophysics Data System (ADS)

Zhang, Yimin

2018-03-01

We studied the reliability of machine components with parameters that follow an arbitrary statistical distribution using the principle of maximum entropy (PME). We used PME to select the statistical distribution that best fits the available information. We also established a probability density function (PDF) and a failure probability model for the parameters of mechanical components using the concept of entropy and the PME. We obtained the first four moments of the state function for reliability analysis and design. Furthermore, we attained an estimate of the PDF with the fewest human bias factors using the PME. This function was used to calculate the reliability of the machine components, including a connecting rod, a vehicle half-shaft, a front axle, a rear axle housing, and a leaf spring, which have parameters that typically follow a non-normal distribution. Simulations were conducted for comparison. This study provides a design methodology for the reliability of mechanical components for practical engineering projects.

A perceptual space of local image statistics.

PubMed

Victor, Jonathan D; Thengone, Daniel J; Rizvi, Syed M; Conte, Mary M

2015-12-01

Local image statistics are important for visual analysis of textures, surfaces, and form. There are many kinds of local statistics, including those that capture luminance distributions, spatial contrast, oriented segments, and corners. While sensitivity to each of these kinds of statistics have been well-studied, much less is known about visual processing when multiple kinds of statistics are relevant, in large part because the dimensionality of the problem is high and different kinds of statistics interact. To approach this problem, we focused on binary images on a square lattice - a reduced set of stimuli which nevertheless taps many kinds of local statistics. In this 10-parameter space, we determined psychophysical thresholds to each kind of statistic (16 observers) and all of their pairwise combinations (4 observers). Sensitivities and isodiscrimination contours were consistent across observers. Isodiscrimination contours were elliptical, implying a quadratic interaction rule, which in turn determined ellipsoidal isodiscrimination surfaces in the full 10-dimensional space, and made predictions for sensitivities to complex combinations of statistics. These predictions, including the prediction of a combination of statistics that was metameric to random, were verified experimentally. Finally, check size had only a mild effect on sensitivities over the range from 2.8 to 14min, but sensitivities to second- and higher-order statistics was substantially lower at 1.4min. In sum, local image statistics form a perceptual space that is highly stereotyped across observers, in which different kinds of statistics interact according to simple rules. Copyright © 2015 Elsevier Ltd. All rights reserved.

A perceptual space of local image statistics

PubMed Central

Victor, Jonathan D.; Thengone, Daniel J.; Rizvi, Syed M.; Conte, Mary M.

2015-01-01

Local image statistics are important for visual analysis of textures, surfaces, and form. There are many kinds of local statistics, including those that capture luminance distributions, spatial contrast, oriented segments, and corners. While sensitivity to each of these kinds of statistics have been well-studied, much less is known about visual processing when multiple kinds of statistics are relevant, in large part because the dimensionality of the problem is high and different kinds of statistics interact. To approach this problem, we focused on binary images on a square lattice – a reduced set of stimuli which nevertheless taps many kinds of local statistics. In this 10-parameter space, we determined psychophysical thresholds to each kind of statistic (16 observers) and all of their pairwise combinations (4 observers). Sensitivities and isodiscrimination contours were consistent across observers. Isodiscrimination contours were elliptical, implying a quadratic interaction rule, which in turn determined ellipsoidal isodiscrimination surfaces in the full 10-dimensional space, and made predictions for sensitivities to complex combinations of statistics. These predictions, including the prediction of a combination of statistics that was metameric to random, were verified experimentally. Finally, check size had only a mild effect on sensitivities over the range from 2.8 to 14 min, but sensitivities to second- and higher-order statistics was substantially lower at 1.4 min. In sum, local image statistics forms a perceptual space that is highly stereotyped across observers, in which different kinds of statistics interact according to simple rules. PMID:26130606

A practical approach for the scale-up of roller compaction process.

PubMed

Shi, Weixian; Sprockel, Omar L

2016-09-01

An alternative approach for the scale-up of ribbon formation during roller compaction was investigated, which required only one batch at the commercial scale to set the operational conditions. The scale-up of ribbon formation was based on a probability method. It was sufficient in describing the mechanism of ribbon formation at both scales. In this method, a statistical relationship between roller compaction parameters and ribbon attributes (thickness and density) was first defined with DoE using a pilot Alexanderwerk WP120 roller compactor. While the milling speed was included in the design, it has no practical effect on granule properties within the study range despite its statistical significance. The statistical relationship was then adapted to a commercial Alexanderwerk WP200 roller compactor with one experimental run. The experimental run served as a calibration of the statistical model parameters. The proposed transfer method was then confirmed by conducting a mapping study on the Alexanderwerk WP200 using a factorial DoE, which showed a match between the predictions and the verification experiments. The study demonstrates the applicability of the roller compaction transfer method using the statistical model from the development scale calibrated with one experiment point at the commercial scale. Copyright © 2016 Elsevier B.V. All rights reserved.

Instantaneous polarization statistic property of EM waves incident on time-varying reentry plasma

NASA Astrophysics Data System (ADS)

Bai, Bowen; Liu, Yanming; Li, Xiaoping; Yao, Bo; Shi, Lei

2018-06-01

An analytical method is proposed in this paper to study the effect of time-varying reentry plasma sheath on the instantaneous polarization statistic property of electromagnetic (EM) waves. Based on the disturbance property of the hypersonic fluid, the spatial-temporal model of the time-varying reentry plasma sheath is established. An analytical technique referred to as transmission line analogy is developed to calculate the instantaneous transmission coefficient of EM wave propagation in time-varying plasma. Then, the instantaneous polarization statistic theory of EM wave propagation in the time-varying plasma sheath is developed. Taking the S-band telemetry right hand circularly polarized wave as an example, effects of incident angle and plasma parameters, including the electron density and the collision frequency on the EM wave's polarization statistic property are studied systematically. Statistical results indicate that the lower the collision frequency and the larger the electron density and incident angle is, the worse the deterioration of the polarization property is. Meanwhile, in conditions of critical parameters of certain electron density, collision frequency, and incident angle, the transmitted waves have both the right and left hand polarization mode, and the polarization mode will reverse. The calculation results could provide useful information for adaptive polarization receiving of the spacecraft's reentry communication.

Surveillance of industrial processes with correlated parameters

DOEpatents

White, A.M.; Gross, K.C.; Kubic, W.L.; Wigeland, R.A.

1996-12-17

A system and method for surveillance of an industrial process are disclosed. The system and method includes a plurality of sensors monitoring industrial process parameters, devices to convert the sensed data to computer compatible information and a computer which executes computer software directed to analyzing the sensor data to discern statistically reliable alarm conditions. The computer software is executed to remove serial correlation information and then calculate Mahalanobis distribution data to carry out a probability ratio test to determine alarm conditions. 10 figs.

A Situational-Awareness System For Networked Infantry Including An Accelerometer-Based Shot-Identification Algorithm For Direct-Fire Weapons

DTIC Science & Technology

2016-09-01

noise density and temperature sensitivity of these devices are all on the same order of magnitude. Even the worst- case noise density of the GCDC...accelerations from a handgun firing were distinct from other impulsive events on the wrist, such as using a hammer. Loeffler first identified potential shots by...spikes, taking various statistical parameters. He used a logistic regression model on these parameters and was able to classify 98.9% of shots

Multivariable Parametric Cost Model for Ground Optical: Telescope Assembly

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Rowell, Ginger Holmes; Reese, Gayle; Byberg, Alicia

2004-01-01

A parametric cost model for ground-based telescopes is developed using multi-variable statistical analysis of both engineering and performance parameters. While diameter continues to be the dominant cost driver, diffraction limited wavelength is found to be a secondary driver. Other parameters such as radius of curvature were examined. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e. multi-telescope phased-array systems). Additionally, single variable models based on aperture diameter were derived.

Statistical Parameter Study of the Time Interval Distribution for Nonparalyzable, Paralyzable, and Hybrid Dead Time Models

NASA Astrophysics Data System (ADS)

Syam, Nur Syamsi; Maeng, Seongjin; Kim, Myo Gwang; Lim, Soo Yeon; Lee, Sang Hoon

2018-05-01

A large dead time of a Geiger Mueller (GM) detector may cause a large count loss in radiation measurements and consequently may cause distortion of the Poisson statistic of radiation events into a new distribution. The new distribution will have different statistical parameters compared to the original distribution. Therefore, the variance, skewness, and excess kurtosis in association with the observed count rate of the time interval distribution for well-known nonparalyzable, paralyzable, and nonparalyzable-paralyzable hybrid dead time models of a Geiger Mueller detector were studied using Monte Carlo simulation (GMSIM). These parameters were then compared with the statistical parameters of a perfect detector to observe the change in the distribution. The results show that the behaviors of the statistical parameters for the three dead time models were different. The values of the skewness and the excess kurtosis of the nonparalyzable model are equal or very close to those of the perfect detector, which are ≅2 for skewness, and ≅6 for excess kurtosis, while the statistical parameters in the paralyzable and hybrid model obtain minimum values that occur around the maximum observed count rates. The different trends of the three models resulting from the GMSIM simulation can be used to distinguish the dead time behavior of a GM counter; i.e. whether the GM counter can be described best by using the nonparalyzable, paralyzable, or hybrid model. In a future study, these statistical parameters need to be analyzed further to determine the possibility of using them to determine a dead time for each model, particularly for paralyzable and hybrid models.

High-temperature behavior of a deformed Fermi gas obeying interpolating statistics.

PubMed

Algin, Abdullah; Senay, Mustafa

2012-04-01

An outstanding idea originally introduced by Greenberg is to investigate whether there is equivalence between intermediate statistics, which may be different from anyonic statistics, and q-deformed particle algebra. Also, a model to be studied for addressing such an idea could possibly provide us some new consequences about the interactions of particles as well as their internal structures. Motivated mainly by this idea, in this work, we consider a q-deformed Fermi gas model whose statistical properties enable us to effectively study interpolating statistics. Starting with a generalized Fermi-Dirac distribution function, we derive several thermostatistical functions of a gas of these deformed fermions in the thermodynamical limit. We study the high-temperature behavior of the system by analyzing the effects of q deformation on the most important thermostatistical characteristics of the system such as the entropy, specific heat, and equation of state. It is shown that such a deformed fermion model in two and three spatial dimensions exhibits the interpolating statistics in a specific interval of the model deformation parameter 0 < q < 1. In particular, for two and three spatial dimensions, it is found from the behavior of the third virial coefficient of the model that the deformation parameter q interpolates completely between attractive and repulsive systems, including the free boson and fermion cases. From the results obtained in this work, we conclude that such a model could provide much physical insight into some interacting theories of fermions, and could be useful to further study the particle systems with intermediate statistics.

The power and robustness of maximum LOD score statistics.

PubMed

Yoo, Y J; Mendell, N R

2008-07-01

The maximum LOD score statistic is extremely powerful for gene mapping when calculated using the correct genetic parameter value. When the mode of genetic transmission is unknown, the maximum of the LOD scores obtained using several genetic parameter values is reported. This latter statistic requires higher critical value than the maximum LOD score statistic calculated from a single genetic parameter value. In this paper, we compare the power of maximum LOD scores based on three fixed sets of genetic parameter values with the power of the LOD score obtained after maximizing over the entire range of genetic parameter values. We simulate family data under nine generating models. For generating models with non-zero phenocopy rates, LOD scores maximized over the entire range of genetic parameters yielded greater power than maximum LOD scores for fixed sets of parameter values with zero phenocopy rates. No maximum LOD score was consistently more powerful than the others for generating models with a zero phenocopy rate. The power loss of the LOD score maximized over the entire range of genetic parameters, relative to the maximum LOD score calculated using the correct genetic parameter value, appeared to be robust to the generating models.

ZERODUR: deterministic approach for strength design

NASA Astrophysics Data System (ADS)

Hartmann, Peter

2012-12-01

There is an increasing request for zero expansion glass ceramic ZERODUR substrates being capable of enduring higher operational static loads or accelerations. The integrity of structures such as optical or mechanical elements for satellites surviving rocket launches, filigree lightweight mirrors, wobbling mirrors, and reticle and wafer stages in microlithography must be guaranteed with low failure probability. Their design requires statistically relevant strength data. The traditional approach using the statistical two-parameter Weibull distribution suffered from two problems. The data sets were too small to obtain distribution parameters with sufficient accuracy and also too small to decide on the validity of the model. This holds especially for the low failure probability levels that are required for reliable applications. Extrapolation to 0.1% failure probability and below led to design strengths so low that higher load applications seemed to be not feasible. New data have been collected with numbers per set large enough to enable tests on the applicability of the three-parameter Weibull distribution. This distribution revealed to provide much better fitting of the data. Moreover it delivers a lower threshold value, which means a minimum value for breakage stress, allowing of removing statistical uncertainty by introducing a deterministic method to calculate design strength. Considerations taken from the theory of fracture mechanics as have been proven to be reliable with proof test qualifications of delicate structures made from brittle materials enable including fatigue due to stress corrosion in a straight forward way. With the formulae derived, either lifetime can be calculated from given stress or allowable stress from minimum required lifetime. The data, distributions, and design strength calculations for several practically relevant surface conditions of ZERODUR are given. The values obtained are significantly higher than those resulting from the two-parameter Weibull distribution approach and no longer subject to statistical uncertainty.

Cine phase-contrast MRI evaluation of normal aqueductal cerebrospinal fluid flow according to sex and age.

PubMed

Unal, Ozkan; Kartum, Alp; Avcu, Serhat; Etlik, Omer; Arslan, Halil; Bora, Aydin

2009-12-01

The aim of this study was cerebrospinal flow quantification in the cerebral aqueduct using cine phase-contrast magnetic resonance imaging (MRI) technique in both sexes and five different age groups to provide normative data. Sixty subjects with no cerebral pathology were included in this study. Subjects were divided into five age groups: < or =14 years, 15-24 years, 25-34 years, 35-44 years, and > or =45 years. Phase, rephase, and magnitude images were acquired by 1.5 T MR unit at the level of cerebral aqueduct with spoiled gradient echo through-plane, which is a cine phase-contrast sequence. At this level, peak flow velocity (cm/s), average flow rate (cm/ s), average flow (L/min), volumes in cranial and caudal directions (mL), and net volumes (mL) were studied. There was a statistically significant difference in peak flow between the age group of < or =14 years and the older age groups. There were no statistically significant differences in average velocity, cranial and caudal volume, net volume, and average flow parameters among different age groups. Statistically significant differences were not detected in flow parameters between sexes. When using cine-phase contrast MRI in the cerebral aqueduct, only the peak velocity showed a statistically significant difference between age groups; it was higher in subjects aged < or =14 years than those in older age groups. When performing age-dependent clinical studies including adolescents, this should be taken into consideration.

Intrinsic factor antibody negative atrophic gastritis; is it different from pernicious anaemia?

PubMed

Amarapurkar, D N; Amarapurkar, A D

2010-01-01

H. pylori gastritis and autoimmune gastritis are the two main types of chronic atrophic gastritis. Parietal cell antibody (PCA) and intrinsic factor antibody (IFA) are characteristic of autoimmune gastritis, of which IFA is more specific. Patients who are IFA negative are considered under the category of chronic atrophic gastritis. To differentiate IFA positive from IFA negative chronic atrophic gastritis. Fifty consecutive patients of biopsy proven chronic atrophic gastritis were included in this study. All patients underwent haematological and biochemical tests including serum LDH, vitamin B12 and fasting serum gastrin levels. PCA and IFA antibodies were tested in all patients. Multiple gastric biopsies from body and antrum of the stomach were taken and evaluated for presence of intestinal metaplasia, endocrine cell hyperplasia, carcinoid and H. pylori infection. Patients were grouped as group A (IFA positive) and group B (IFA negative). The mean laboratory values and histological parameters were compared between the two groups using appropriate statistical methods. Eighteen patients were in group A (mean age 55.5 +/- 13 years, male: female = 16:2) and thirty-two in group B (mean age 49.7 +/- 13 years, male: female = 25:7). There was no statistically significant difference between median values of haemoglobin, MCV, LDH, Vitamin B12 and serum gastrin in both the groups. None of the histological parameters showed any significant difference. There was no statistically significant difference in haematological, biochemical and histological parameters in IFA positive and negative gastritis. These may be the spectrum of the same disease, where H. pylori may be responsible for initiating the process.

Evaluation of body weight, body mass index, and body fat percentage changes in early stages of fixed orthodontic therapy.

PubMed

Sandeep, K Sai; Singaraju, Gowri Sankar; Reddy, V Karunakar; Mandava, Prasad; Bhavikati, Venkata N; Reddy, Rohit

2016-01-01

The aim of this study was to evaluate and compare the changes in body weight, body mass index (BMI), and body fat percentage (BFP) during the initial stages of fixed orthodontic treatment. The sample for this observational prospective study included 68 individuals with fixed orthodontic appliance in the age group of 18-25 years of both the sexes (25 males and 43 females). The control group consisted of 60 individuals (24 males and 36 females). The weight, BMI, and BFP were measured using a Body Composition Monitor at three points of time "T1" initial; "T2" after 1 month; and "T2" after 3 months. The results were tabulated and analyzed with the Statistical Package for the Social Sciences software. The mean changes between different parameters in both the study and control groups and between males and females in the study group was compared by using two-tailed unpaired student's t-test. The statistical significance is set atP ≤ 0.05. There was an overall decrease in the body weight, BMI, and BFP after 1 month in the study cohort, which was statistically significant compared to the control group (P < 0.0001). This was followed by an increase in the parameters after the end of the 3(rd) month. Comparison of the parameters between the study and control group at the start of the treatment and at the end of the 3(rd) month had no statistical significance. There was a marked variation in the changes of these parameters between males and females of the study group, which is statistically significant (<0.0001). There is a definite reduction in the weight, BMP, and BMI at the end of the first month followed by a gain of weight, but not at the initial point by the end of the 3(rd) month.

An Economic Impact Study: How and Why To Do One.

ERIC Educational Resources Information Center

Graefe, Martin; Wells, Matt

1996-01-01

An economic impact study tells the community about a camp's contribution, and is good advertising. Describes an economic impact study and its benefits. Uses Concordia Language Villages' study to illustrate features of an impact study, including goals and scope, parameters and assumptions, statistical information, research methodology, review…

A New Look at Bias in Aptitude Tests.

ERIC Educational Resources Information Center

Scheuneman, Janice Dowd

1981-01-01

Statistical bias in measurement and ethnic-group bias in testing are discussed, reviewing predictive and construct validity studies. Item bias is reconceptualized to include distance of item content from respondent's experience. Differing values of mean and standard deviation for bias parameter are analyzed in a simulation. References are…

A new test statistic for climate models that includes field and spatial dependencies using Gaussian Markov random fields

DOE PAGES

Nosedal-Sanchez, Alvaro; Jackson, Charles S.; Huerta, Gabriel

2016-07-20

A new test statistic for climate model evaluation has been developed that potentially mitigates some of the limitations that exist for observing and representing field and space dependencies of climate phenomena. Traditionally such dependencies have been ignored when climate models have been evaluated against observational data, which makes it difficult to assess whether any given model is simulating observed climate for the right reasons. The new statistic uses Gaussian Markov random fields for estimating field and space dependencies within a first-order grid point neighborhood structure. We illustrate the ability of Gaussian Markov random fields to represent empirical estimates of fieldmore » and space covariances using "witch hat" graphs. We further use the new statistic to evaluate the tropical response of a climate model (CAM3.1) to changes in two parameters important to its representation of cloud and precipitation physics. Overall, the inclusion of dependency information did not alter significantly the recognition of those regions of parameter space that best approximated observations. However, there were some qualitative differences in the shape of the response surface that suggest how such a measure could affect estimates of model uncertainty.« less

Characterizing microstructural features of biomedical samples by statistical analysis of Mueller matrix images

NASA Astrophysics Data System (ADS)

He, Honghui; Dong, Yang; Zhou, Jialing; Ma, Hui

2017-03-01

As one of the salient features of light, polarization contains abundant structural and optical information of media. Recently, as a comprehensive description of polarization property, the Mueller matrix polarimetry has been applied to various biomedical studies such as cancerous tissues detections. In previous works, it has been found that the structural information encoded in the 2D Mueller matrix images can be presented by other transformed parameters with more explicit relationship to certain microstructural features. In this paper, we present a statistical analyzing method to transform the 2D Mueller matrix images into frequency distribution histograms (FDHs) and their central moments to reveal the dominant structural features of samples quantitatively. The experimental results of porcine heart, intestine, stomach, and liver tissues demonstrate that the transformation parameters and central moments based on the statistical analysis of Mueller matrix elements have simple relationships to the dominant microstructural properties of biomedical samples, including the density and orientation of fibrous structures, the depolarization power, diattenuation and absorption abilities. It is shown in this paper that the statistical analysis of 2D images of Mueller matrix elements may provide quantitative or semi-quantitative criteria for biomedical diagnosis.

A new test statistic for climate models that includes field and spatial dependencies using Gaussian Markov random fields

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

Nosedal-Sanchez, Alvaro; Jackson, Charles S.; Huerta, Gabriel

A new test statistic for climate model evaluation has been developed that potentially mitigates some of the limitations that exist for observing and representing field and space dependencies of climate phenomena. Traditionally such dependencies have been ignored when climate models have been evaluated against observational data, which makes it difficult to assess whether any given model is simulating observed climate for the right reasons. The new statistic uses Gaussian Markov random fields for estimating field and space dependencies within a first-order grid point neighborhood structure. We illustrate the ability of Gaussian Markov random fields to represent empirical estimates of fieldmore » and space covariances using "witch hat" graphs. We further use the new statistic to evaluate the tropical response of a climate model (CAM3.1) to changes in two parameters important to its representation of cloud and precipitation physics. Overall, the inclusion of dependency information did not alter significantly the recognition of those regions of parameter space that best approximated observations. However, there were some qualitative differences in the shape of the response surface that suggest how such a measure could affect estimates of model uncertainty.« less

Probability distributions of the electroencephalogram envelope of preterm infants.

PubMed

Saji, Ryoya; Hirasawa, Kyoko; Ito, Masako; Kusuda, Satoshi; Konishi, Yukuo; Taga, Gentaro

2015-06-01

To determine the stationary characteristics of electroencephalogram (EEG) envelopes for prematurely born (preterm) infants and investigate the intrinsic characteristics of early brain development in preterm infants. Twenty neurologically normal sets of EEGs recorded in infants with a post-conceptional age (PCA) range of 26-44 weeks (mean 37.5 ± 5.0 weeks) were analyzed. Hilbert transform was applied to extract the envelope. We determined the suitable probability distribution of the envelope and performed a statistical analysis. It was found that (i) the probability distributions for preterm EEG envelopes were best fitted by lognormal distributions at 38 weeks PCA or less, and by gamma distributions at 44 weeks PCA; (ii) the scale parameter of the lognormal distribution had positive correlations with PCA as well as a strong negative correlation with the percentage of low-voltage activity; (iii) the shape parameter of the lognormal distribution had significant positive correlations with PCA; (iv) the statistics of mode showed significant linear relationships with PCA, and, therefore, it was considered a useful index in PCA prediction. These statistics, including the scale parameter of the lognormal distribution and the skewness and mode derived from a suitable probability distribution, may be good indexes for estimating stationary nature in developing brain activity in preterm infants. The stationary characteristics, such as discontinuity, asymmetry, and unimodality, of preterm EEGs are well indicated by the statistics estimated from the probability distribution of the preterm EEG envelopes. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Chemical freezeout parameters within generic nonextensive statistics

NASA Astrophysics Data System (ADS)

Tawfik, Abdel; Yassin, Hayam; Abo Elyazeed, Eman R.

2018-06-01

The particle production in relativistic heavy-ion collisions seems to be created in a dynamically disordered system which can be best described by an extended exponential entropy. In distinguishing between the applicability of this and Boltzmann-Gibbs (BG) in generating various particle-ratios, generic (non)extensive statistics is introduced to the hadron resonance gas model. Accordingly, the degree of (non)extensivity is determined by the possible modifications in the phase space. Both BG extensivity and Tsallis nonextensivity are included as very special cases defined by specific values of the equivalence classes (c, d). We found that the particle ratios at energies ranging between 3.8 and 2760 GeV are best reproduced by nonextensive statistics, where c and d range between ˜ 0.9 and ˜ 1 . The present work aims at illustrating that the proposed approach is well capable to manifest the statistical nature of the system on interest. We don't aim at highlighting deeper physical insights. In other words, while the resulting nonextensivity is neither BG nor Tsallis, the freezeout parameters are found very compatible with BG and accordingly with the well-known freezeout phase-diagram, which is in an excellent agreement with recent lattice calculations. We conclude that the particle production is nonextensive but should not necessarily be accompanied by a radical change in the intensive or extensive thermodynamic quantities, such as internal energy and temperature. Only, the two critical exponents defining the equivalence classes (c, d) are the physical parameters characterizing the (non)extensivity.

General displaced SU(1, 1) number states: Revisited

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

Dehghani, A., E-mail: alireza.dehghani@gmail.com, E-mail: a-dehghani@tabrizu.ac.ir

2014-04-15

The most general displaced number states, based on the bosonic and an irreducible representation of the Lie algebra symmetry of su(1, 1) and associated with the Calogero-Sutherland model are introduced. Here, we utilize the Barut-Girardello displacement operator instead of the Klauder-Perelomov counterpart, to construct new kind of the displaced number states which can be classified in nonlinear coherent states regime, too, with special nonlinearity functions. They depend on two parameters, and can be converted into the well-known Barut-Girardello coherent and number states, respectively, depending on which of the parameters equal to zero. A discussion of the statistical properties of thesemore » states is included. Significant are their squeezing properties and anti-bunching effects which can be raised by increasing the energy quantum number. Depending on the particular choice of the parameters of the above scenario, we are able to determine the status of compliance with flexible statistics. Major parts of the issue is spent on something that these states, in fact, should be considered as new kind of photon-added coherent states, too. Which can be reproduced through an iterated action of a creation operator on new nonlinear Barut-Girardello coherent states. Where the latter carry, also, outstanding statistical features.« less

Performance evaluation of spectral vegetation indices using a statistical sensitivity function

USGS Publications Warehouse

Ji, Lei; Peters, Albert J.

2007-01-01

A great number of spectral vegetation indices (VIs) have been developed to estimate biophysical parameters of vegetation. Traditional techniques for evaluating the performance of VIs are regression-based statistics, such as the coefficient of determination and root mean square error. These statistics, however, are not capable of quantifying the detailed relationship between VIs and biophysical parameters because the sensitivity of a VI is usually a function of the biophysical parameter instead of a constant. To better quantify this relationship, we developed a “sensitivity function” for measuring the sensitivity of a VI to biophysical parameters. The sensitivity function is defined as the first derivative of the regression function, divided by the standard error of the dependent variable prediction. The function elucidates the change in sensitivity over the range of the biophysical parameter. The Student's t- or z-statistic can be used to test the significance of VI sensitivity. Additionally, we developed a “relative sensitivity function” that compares the sensitivities of two VIs when the biophysical parameters are unavailable.

VizieR Online Data Catalog: The ESO DIBs Large Exploration Survey (Cox+, 2017)

NASA Astrophysics Data System (ADS)

Cox, N. L. J.; Cami, J.; Farhang, A.; Smoker, J.; Monreal-Ibero, A.; Lallement, R.; Sarre, P. J.; Marshall, C. C. M.; Smith, K. T.; Evans, C. J.; Royer, P.; Linnartz, H.; Cordiner, M. A.; Joblin, C.; van Loon, J. T.; Foing, B. H.; Bhatt, N. H.; Bron, E.; Elyajouri, M.; de Koter, A.; Ehrenfreund, P.; Javadi, A.; Kaper, L.; Khosroshadi, H. G.; Laverick, M.; Le Petit, F.; Mulas, G.; Roueff, E.; Salama, F.; Spaans, M.

2018-01-01

We constructed a statistically representative survey sample that probes a wide range of interstellar environment parameters including reddening E(B-V), visual extinction AV, total-to-selective extinction ratio RV, and molecular hydrogen fraction fH2. EDIBLES provides the community with optical (~305-1042nm) spectra at high spectral resolution (R~70000 in the blue arm and 100000 in the red arm) and high signal-to-noise (S/N; median value ~500-1000), for a statistically significant sample of interstellar sightlines. Many of the >100 sightlines included in the survey already have auxiliary available ultraviolet, infrared and/or polarisation data on the dust and gas components. (2 data files).

SU-E-T-79: Comparison of Doses Received by the Hippocampus in Patients Treated with Single Vs Multiple Isocenter Based Stereotactic Radiation Therapy to the Brain for Multiple Brain Metastases

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

Algan, O; Giem, J; Young, J

Purpose: To investigate the doses received by the hippocampus and normal brain tissue during a course of stereotactic radiotherapy utilizing a single isocenter (SI) versus multiple isocenter (MI) in patients with multiple intracranial metastases. Methods: Seven patients imaged with MRI including SPGR sequence and diagnosed with 2–3 brain metastases were included in this retrospective study. Two sets of stereotactic IMRT treatment plans, (MI vs SI), were generated. The hippocampus was contoured on SPGR sequences and doses received by the hippocampus and whole brain were calculated. The prescribed dose was 25Gy in 5 fractions. The two groups were compared using t-testmore » analysis. Results: There were 17 lesions in 7 patients. The median tumor, right hippocampus, left hippocampus and brain volumes were: 3.37cc, 2.56cc, 3.28cc, and 1417cc respectively. In comparing the two treatment plans, there was no difference in the PTV coverage except in the tail of the DVH curve. All tumors had V95 > 99.5%. The only statistically significant parameter was the V100 (72% vs 45%, p=0.002, favoring MI). All other evaluated parameters including the V95 and V98 did not reveal any statistically significant differences. None of the evaluated dosimetric parameters for the hippocampus (V100, V80, V60, V40, V20, V10, D100, D90, D70, D50, D30, D10) revealed any statistically significant differences (all p-values > 0.31) between MI and SI plans. The total brain dose was slightly higher in the SI plans, especially in the lower dose regions, although this difference was not statistically significant. Utilizing brain-sub-PTV volumes did not change these results. Conclusion: The use of SI treatment planning for patients with up to 3 brain metastases produces similar PTV coverage and similar normal tissue doses to the hippocampus and the brain compared to MI plans. SI treatment planning should be considered in patients with multiple brain metastases undergoing stereotactic treatment.« less

Electromagnetic wave scattering from rough terrain

NASA Astrophysics Data System (ADS)

Papa, R. J.; Lennon, J. F.; Taylor, R. L.

1980-09-01

This report presents two aspects of a program designed to calculate electromagnetic scattering from rough terrain: (1) the use of statistical estimation techniques to determine topographic parameters and (2) the results of a single-roughness-scale scattering calculation based on those parameters, including comparison with experimental data. In the statistical part of the present calculation, digitized topographic maps are used to generate data bases for the required scattering cells. The application of estimation theory to the data leads to the specification of statistical parameters for each cell. The estimated parameters are then used in a hypothesis test to decide on a probability density function (PDF) that represents the height distribution in the cell. Initially, the formulation uses a single observation of the multivariate data. A subsequent approach involves multiple observations of the heights on a bivariate basis, and further refinements are being considered. The electromagnetic scattering analysis, the second topic, calculates the amount of specular and diffuse multipath power reaching a monopulse receiver from a pulsed beacon positioned over a rough Earth. The program allows for spatial inhomogeneities and multiple specular reflection points. The analysis of shadowing by the rough surface has been extended to the case where the surface heights are distributed exponentially. The calculated loss of boresight pointing accuracy attributable to diffuse multipath is then compared with the experimental results. The extent of the specular region, the use of localized height variations, and the effect of the azimuthal variation in power pattern are all assessed.

The statistical analysis of energy release in small-scale coronal structures

NASA Astrophysics Data System (ADS)

Ulyanov, Artyom; Kuzin, Sergey; Bogachev, Sergey

We present the results of statistical analysis of impulsive flare-like brightenings, which numerously occur in the quiet regions of solar corona. For our study, we utilized high-cadence observations performed with two EUV-telescopes - TESIS/Coronas-Photon and AIA/SDO. In total, we processed 6 sequences of images, registered throughout the period between 2009 and 2013, covering the rising phase of the 24th solar cycle. Based on high-speed DEM estimation method, we developed a new technique to evaluate the main parameters of detected events (geometrical sizes, duration, temperature and thermal energy). We then obtained the statistical distributions of these parameters and examined their variations depending on the level of solar activity. The results imply that near the minimum of the solar cycle the energy release in quiet corona is mainly provided by small-scale events (nanoflares), whereas larger events (microflares) prevail on the peak of activity. Furthermore, we investigated the coronal conditions that had specified the formation and triggering of registered flares. By means of photospheric magnetograms obtained with MDI/SoHO and HMI/SDO instruments, we examined the topology of local magnetic fields at different stages: the pre-flare phase, the peak of intensity and the ending phase. To do so, we introduced a number of topological parameters including the total magnetic flux, the distance between magnetic sources and their mutual arrangement. The found correlation between the change of these parameters and the formation of flares may offer an important tool for application of flare forecasting.

A multibody knee model with discrete cartilage prediction of tibio-femoral contact mechanics.

PubMed

Guess, Trent M; Liu, Hongzeng; Bhashyam, Sampath; Thiagarajan, Ganesh

2013-01-01

Combining musculoskeletal simulations with anatomical joint models capable of predicting cartilage contact mechanics would provide a valuable tool for studying the relationships between muscle force and cartilage loading. As a step towards producing multibody musculoskeletal models that include representation of cartilage tissue mechanics, this research developed a subject-specific multibody knee model that represented the tibia plateau cartilage as discrete rigid bodies that interacted with the femur through deformable contacts. Parameters for the compliant contact law were derived using three methods: (1) simplified Hertzian contact theory, (2) simplified elastic foundation contact theory and (3) parameter optimisation from a finite element (FE) solution. The contact parameters and contact friction were evaluated during a simulated walk in a virtual dynamic knee simulator, and the resulting kinematics were compared with measured in vitro kinematics. The effects on predicted contact pressures and cartilage-bone interface shear forces during the simulated walk were also evaluated. The compliant contact stiffness parameters had a statistically significant effect on predicted contact pressures as well as all tibio-femoral motions except flexion-extension. The contact friction was not statistically significant to contact pressures, but was statistically significant to medial-lateral translation and all rotations except flexion-extension. The magnitude of kinematic differences between model formulations was relatively small, but contact pressure predictions were sensitive to model formulation. The developed multibody knee model was computationally efficient and had a computation time 283 times faster than a FE simulation using the same geometries and boundary conditions.

Reference charts for fetal biometric parameters in twin pregnancies according to chorionicity.

PubMed

Araujo Júnior, Edward; Ruano, Rodrigo; Javadian, Pouya; Martins, Wellington P; Elito, Julio; Pires, Claudio Rodrigues; Zanforlin Filho, Sebastião Marques

2014-04-01

The objective of this article is to determine reference values for fetal biometric parameters in twin pregnancies and to compare these values between monochorionic and dichorionic pregnancies. A retrospective cross-sectional study was conducted among 157 monochorionic and 176 dichorionic twin pregnancies between 14 and 38 weeks of gestation. Biometric measurements included the biparietal diameter (BPD), abdominal circumference (AC), femurs length (FL) and estimated fetal weight (EFW). To evaluate the correlation between biometric parameters and gestational age, polynomial regression models were created, with adjustments using the coefficient of determination (R(2) ). Comparison between monochorionic and dichorionic pregnancies was performed using analysis of covariance. The mean BPD, AC, FL and EFW for the dichorionic pregnancies were 56.16 mm, 191.1 mm, 41.08 mm and 816.1 g, respectively. The mean BPD, AC, FL and EFW for the monochorionic pregnancies were 57.14 mm, 184.2 mm, 39.29 mm and 723.4 g, respectively. There was a statistical difference between mono and dichorionic pregnancies for all the biometric parameters (BPD p = 0.012; AC p = 0.047; FL p = 0.007; EFW p = 0.011). Reference curves of biometric parameters in twin pregnancies were determined. Biometric parameters were statistically different between monochorionic and dichorionic pregnancies. © 2014 John Wiley & Sons, Ltd.

Disaster Metrics: Evaluation of de Boer's Disaster Severity Scale (DSS) Applied to Earthquakes.

PubMed

Bayram, Jamil D; Zuabi, Shawki; McCord, Caitlin M; Sherak, Raphael A G; Hsu, Edberdt B; Kelen, Gabor D

2015-02-01

Quantitative measurement of the medical severity following multiple-casualty events (MCEs) is an important goal in disaster medicine. In 1990, de Boer proposed a 13-point, 7-parameter scale called the Disaster Severity Scale (DSS). Parameters include cause, duration, radius, number of casualties, nature of injuries, rescue time, and effect on surrounding community. Hypothesis This study aimed to examine the reliability and dimensionality (number of salient themes) of de Boer's DSS scale through its application to 144 discrete earthquake events. A search for earthquake events was conducted via National Oceanic and Atmospheric Administration (NOAA) and US Geological Survey (USGS) databases. Two experts in the field of disaster medicine independently reviewed and assigned scores for parameters that had no data readily available (nature of injuries, rescue time, and effect on surrounding community), and differences were reconciled via consensus. Principle Component Analysis was performed using SPSS Statistics for Windows Version 22.0 (IBM Corp; Armonk, New York USA) to evaluate the reliability and dimensionality of the DSS. A total of 144 individual earthquakes from 2003 through 2013 were identified and scored. Of 13 points possible, the mean score was 6.04, the mode = 5, minimum = 4, maximum = 11, and standard deviation = 2.23. Three parameters in the DSS had zero variance (ie, the parameter received the same score in all 144 earthquakes). Because of the zero contribution to variance, these three parameters (cause, duration, and radius) were removed to run the statistical analysis. Cronbach's alpha score, a coefficient of internal consistency, for the remaining four parameters was found to be robust at 0.89. Principle Component Analysis showed uni-dimensional characteristics with only one component having an eigenvalue greater than one at 3.17. The 4-parameter DSS, however, suffered from restriction of scoring range on both parameter and scale levels. Jan de Boer's DSS in its 7-parameter format fails to hold statistically in a dataset of 144 earthquakes subjected to analysis. A modified 4-parameter scale was found to quantitatively assess medical severity more directly, but remains flawed due to range restriction on both individual parameter and scale levels. Further research is needed in the field of disaster metrics to develop a scale that is reliable in its complete set of parameters, capable of better fine discrimination, and uni-dimensional in measurement of the medical severity of MCEs.

Using the MCNP Taylor series perturbation feature (efficiently) for shielding problems

NASA Astrophysics Data System (ADS)

Favorite, Jeffrey

2017-09-01

The Taylor series or differential operator perturbation method, implemented in MCNP and invoked using the PERT card, can be used for efficient parameter studies in shielding problems. This paper shows how only two PERT cards are needed to generate an entire parameter study, including statistical uncertainty estimates (an additional three PERT cards can be used to give exact statistical uncertainties). One realistic example problem involves a detailed helium-3 neutron detector model and its efficiency as a function of the density of its high-density polyethylene moderator. The MCNP differential operator perturbation capability is extremely accurate for this problem. A second problem involves the density of the polyethylene reflector of the BeRP ball and is an example of first-order sensitivity analysis using the PERT capability. A third problem is an analytic verification of the PERT capability.

Algorithmic detectability threshold of the stochastic block model

NASA Astrophysics Data System (ADS)

Kawamoto, Tatsuro

2018-03-01

The assumption that the values of model parameters are known or correctly learned, i.e., the Nishimori condition, is one of the requirements for the detectability analysis of the stochastic block model in statistical inference. In practice, however, there is no example demonstrating that we can know the model parameters beforehand, and there is no guarantee that the model parameters can be learned accurately. In this study, we consider the expectation-maximization (EM) algorithm with belief propagation (BP) and derive its algorithmic detectability threshold. Our analysis is not restricted to the community structure but includes general modular structures. Because the algorithm cannot always learn the planted model parameters correctly, the algorithmic detectability threshold is qualitatively different from the one with the Nishimori condition.

LANDSAT menhaden and thread herring resources investigation. [Gulf of Mexico

NASA Technical Reports Server (NTRS)

Kemmerer, A. J. (Principal Investigator); Brucks, J. T.; Butler, J. A.; Faller, K. H.; Holley, H. J.; Leming, T. D.; Savastano, K. J.; Vanselous, T. M.

1977-01-01

The author has identified the following significant results. The relationship between the distribution of menhaden and selected oceanographic parameters (water color, turbidity, and possibly chlorophyll concentrations) was established. Similar relationships for thread herring were not established nor were relationships relating to the abundance of either species. Use of aircraft and LANDSAT remote sensing instruments to measure or infer a set of basic oceanographic parameters was evaluated. Parameters which could be accurately inferred included surface water temperature, salinity, and color. Water turbidity (Secchi disk) was evaluated as marginally inferrable from the LANDSAT MSS data and chlorophyll-a concentrations as less than marginal. These evaluations considered the parameters only as experienced in the two test areas using available sensors and statistical techniques.

Selection and Reporting of Statistical Methods to Assess Reliability of a Diagnostic Test: Conformity to Recommended Methods in a Peer-Reviewed Journal

PubMed Central

Park, Ji Eun; Han, Kyunghwa; Sung, Yu Sub; Chung, Mi Sun; Koo, Hyun Jung; Yoon, Hee Mang; Choi, Young Jun; Lee, Seung Soo; Kim, Kyung Won; Shin, Youngbin; An, Suah; Cho, Hyo-Min

2017-01-01

Objective To evaluate the frequency and adequacy of statistical analyses in a general radiology journal when reporting a reliability analysis for a diagnostic test. Materials and Methods Sixty-three studies of diagnostic test accuracy (DTA) and 36 studies reporting reliability analyses published in the Korean Journal of Radiology between 2012 and 2016 were analyzed. Studies were judged using the methodological guidelines of the Radiological Society of North America-Quantitative Imaging Biomarkers Alliance (RSNA-QIBA), and COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) initiative. DTA studies were evaluated by nine editorial board members of the journal. Reliability studies were evaluated by study reviewers experienced with reliability analysis. Results Thirty-one (49.2%) of the 63 DTA studies did not include a reliability analysis when deemed necessary. Among the 36 reliability studies, proper statistical methods were used in all (5/5) studies dealing with dichotomous/nominal data, 46.7% (7/15) of studies dealing with ordinal data, and 95.2% (20/21) of studies dealing with continuous data. Statistical methods were described in sufficient detail regarding weighted kappa in 28.6% (2/7) of studies and regarding the model and assumptions of intraclass correlation coefficient in 35.3% (6/17) and 29.4% (5/17) of studies, respectively. Reliability parameters were used as if they were agreement parameters in 23.1% (3/13) of studies. Reproducibility and repeatability were used incorrectly in 20% (3/15) of studies. Conclusion Greater attention to the importance of reporting reliability, thorough description of the related statistical methods, efforts not to neglect agreement parameters, and better use of relevant terminology is necessary. PMID:29089821

Impact of spurious shear on cosmological parameter estimates from weak lensing observables

DOE PAGES

Petri, Andrea; May, Morgan; Haiman, Zoltán; ...

2014-12-30

We research, residual errors in shear measurements, after corrections for instrument systematics and atmospheric effects, can impact cosmological parameters derived from weak lensing observations. Here we combine convergence maps from our suite of ray-tracing simulations with random realizations of spurious shear. This allows us to quantify the errors and biases of the triplet (Ω m,w,σ 8) derived from the power spectrum (PS), as well as from three different sets of non-Gaussian statistics of the lensing convergence field: Minkowski functionals (MFs), low-order moments (LMs), and peak counts (PKs). Our main results are as follows: (i) We find an order of magnitudemore » smaller biases from the PS than in previous work. (ii) The PS and LM yield biases much smaller than the morphological statistics (MF, PK). (iii) For strictly Gaussian spurious shear with integrated amplitude as low as its current estimate of σ sys 2 ≈ 10 -7, biases from the PS and LM would be unimportant even for a survey with the statistical power of Large Synoptic Survey Telescope. However, we find that for surveys larger than ≈ 100 deg 2, non-Gaussianity in the noise (not included in our analysis) will likely be important and must be quantified to assess the biases. (iv) The morphological statistics (MF, PK) introduce important biases even for Gaussian noise, which must be corrected in large surveys. The biases are in different directions in (Ωm,w,σ8) parameter space, allowing self-calibration by combining multiple statistics. Our results warrant follow-up studies with more extensive lensing simulations and more accurate spurious shear estimates.« less

Statistical analysis of multivariate atmospheric variables. [cloud cover

NASA Technical Reports Server (NTRS)

Tubbs, J. D.

1979-01-01

Topics covered include: (1) estimation in discrete multivariate distributions; (2) a procedure to predict cloud cover frequencies in the bivariate case; (3) a program to compute conditional bivariate normal parameters; (4) the transformation of nonnormal multivariate to near-normal; (5) test of fit for the extreme value distribution based upon the generalized minimum chi-square; (6) test of fit for continuous distributions based upon the generalized minimum chi-square; (7) effect of correlated observations on confidence sets based upon chi-square statistics; and (8) generation of random variates from specified distributions.

PyEvolve: a toolkit for statistical modelling of molecular evolution.

PubMed

Butterfield, Andrew; Vedagiri, Vivek; Lang, Edward; Lawrence, Cath; Wakefield, Matthew J; Isaev, Alexander; Huttley, Gavin A

2004-01-05

Examining the distribution of variation has proven an extremely profitable technique in the effort to identify sequences of biological significance. Most approaches in the field, however, evaluate only the conserved portions of sequences - ignoring the biological significance of sequence differences. A suite of sophisticated likelihood based statistical models from the field of molecular evolution provides the basis for extracting the information from the full distribution of sequence variation. The number of different problems to which phylogeny-based maximum likelihood calculations can be applied is extensive. Available software packages that can perform likelihood calculations suffer from a lack of flexibility and scalability, or employ error-prone approaches to model parameterisation. Here we describe the implementation of PyEvolve, a toolkit for the application of existing, and development of new, statistical methods for molecular evolution. We present the object architecture and design schema of PyEvolve, which includes an adaptable multi-level parallelisation schema. The approach for defining new methods is illustrated by implementing a novel dinucleotide model of substitution that includes a parameter for mutation of methylated CpG's, which required 8 lines of standard Python code to define. Benchmarking was performed using either a dinucleotide or codon substitution model applied to an alignment of BRCA1 sequences from 20 mammals, or a 10 species subset. Up to five-fold parallel performance gains over serial were recorded. Compared to leading alternative software, PyEvolve exhibited significantly better real world performance for parameter rich models with a large data set, reducing the time required for optimisation from approximately 10 days to approximately 6 hours. PyEvolve provides flexible functionality that can be used either for statistical modelling of molecular evolution, or the development of new methods in the field. The toolkit can be used interactively or by writing and executing scripts. The toolkit uses efficient processes for specifying the parameterisation of statistical models, and implements numerous optimisations that make highly parameter rich likelihood functions solvable within hours on multi-cpu hardware. PyEvolve can be readily adapted in response to changing computational demands and hardware configurations to maximise performance. PyEvolve is released under the GPL and can be downloaded from http://cbis.anu.edu.au/software.

OPTESIM, a Versatile Toolbox for Numerical Simulation of Electron Spin Echo Envelope Modulation (ESEEM) that Features Hybrid Optimization and Statistical Assessment of Parameters

PubMed Central

Sun, Li; Hernandez-Guzman, Jessica; Warncke, Kurt

2009-01-01

Electron spin echo envelope modulation (ESEEM) is a technique of pulsed-electron paramagnetic resonance (EPR) spectroscopy. The analyis of ESEEM data to extract information about the nuclear and electronic structure of a disordered (powder) paramagnetic system requires accurate and efficient numerical simulations. A single coupled nucleus of known nuclear g value (gN) and spin I=1 can have up to eight adjustable parameters in the nuclear part of the spin Hamiltonian. We have developed OPTESIM, an ESEEM simulation toolbox, for automated numerical simulation of powder two- and three-pulse one-dimensional ESEEM for arbitrary number (N) and type (I, gN) of coupled nuclei, and arbitrary mutual orientations of the hyperfine tensor principal axis systems for N>1. OPTESIM is based in the Matlab environment, and includes the following features: (1) a fast algorithm for translation of the spin Hamiltonian into simulated ESEEM, (2) different optimization methods that can be hybridized to achieve an efficient coarse-to-fine grained search of the parameter space and convergence to a global minimum, (3) statistical analysis of the simulation parameters, which allows the identification of simultaneous confidence regions at specific confidence levels. OPTESIM also includes a geometry-preserving spherical averaging algorithm as default for N>1, and global optimization over multiple experimental conditions, such as the dephasing time ( ) for three-pulse ESEEM, and external magnetic field values. Application examples for simulation of 14N coupling (N=1, N=2) in biological and chemical model paramagnets are included. Automated, optimized simulations by using OPTESIM lead to a convergence on dramatically shorter time scales, relative to manual simulations. PMID:19553148

The use and misuse of statistical analyses. [in geophysics and space physics

NASA Technical Reports Server (NTRS)

Reiff, P. H.

1983-01-01

The statistical techniques most often used in space physics include Fourier analysis, linear correlation, auto- and cross-correlation, power spectral density, and superposed epoch analysis. Tests are presented which can evaluate the significance of the results obtained through each of these. Data presented without some form of error analysis are frequently useless, since they offer no way of assessing whether a bump on a spectrum or on a superposed epoch analysis is real or merely a statistical fluctuation. Among many of the published linear correlations, for instance, the uncertainty in the intercept and slope is not given, so that the significance of the fitted parameters cannot be assessed.

Statistical Analysis of speckle noise reduction techniques for echocardiographic Images

NASA Astrophysics Data System (ADS)

Saini, Kalpana; Dewal, M. L.; Rohit, Manojkumar

2011-12-01

Echocardiography is the safe, easy and fast technology for diagnosing the cardiac diseases. As in other ultrasound images these images also contain speckle noise. In some cases this speckle noise is useful such as in motion detection. But in general noise removal is required for better analysis of the image and proper diagnosis. Different Adaptive and anisotropic filters are included for statistical analysis. Statistical parameters such as Signal-to-Noise Ratio (SNR), Peak Signal-to-Noise Ratio (PSNR), and Root Mean Square Error (RMSE) calculated for performance measurement. One more important aspect that there may be blurring during speckle noise removal. So it is prefered that filter should be able to enhance edges during noise removal.

Maps on statistical manifolds exactly reduced from the Perron-Frobenius equations for solvable chaotic maps

NASA Astrophysics Data System (ADS)

Goto, Shin-itiro; Umeno, Ken

2018-03-01

Maps on a parameter space for expressing distribution functions are exactly derived from the Perron-Frobenius equations for a generalized Boole transform family. Here the generalized Boole transform family is a one-parameter family of maps, where it is defined on a subset of the real line and its probability distribution function is the Cauchy distribution with some parameters. With this reduction, some relations between the statistical picture and the orbital one are shown. From the viewpoint of information geometry, the parameter space can be identified with a statistical manifold, and then it is shown that the derived maps can be characterized. Also, with an induced symplectic structure from a statistical structure, symplectic and information geometric aspects of the derived maps are discussed.

A growing social network model in geographical space

NASA Astrophysics Data System (ADS)

Antonioni, Alberto; Tomassini, Marco

2017-09-01

In this work we propose a new model for the generation of social networks that includes their often ignored spatial aspects. The model is a growing one and links are created either taking space into account, or disregarding space and only considering the degree of target nodes. These two effects can be mixed linearly in arbitrary proportions through a parameter. We numerically show that for a given range of the combination parameter, and for given mean degree, the generated network class shares many important statistical features with those observed in actual social networks, including the spatial dependence of connections. Moreover, we show that the model provides a good qualitative fit to some measured social networks.

On the Response of the Special Sensor Microwave/Imager to the Marine Environment: Implications for Atmospheric Parameter Retrievals. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Petty, Grant W.

1990-01-01

A reasonably rigorous basis for understanding and extracting the physical information content of Special Sensor Microwave/Imager (SSM/I) satellite images of the marine environment is provided. To this end, a comprehensive algebraic parameterization is developed for the response of the SSM/I to a set of nine atmospheric and ocean surface parameters. The brightness temperature model includes a closed-form approximation to microwave radiative transfer in a non-scattering atmosphere and fitted models for surface emission and scattering based on geometric optics calculations for the roughened sea surface. The combined model is empirically tuned using suitable sets of SSM/I data and coincident surface observations. The brightness temperature model is then used to examine the sensitivity of the SSM/I to realistic variations in the scene being observed and to evaluate the theoretical maximum precision of global SSM/I retrievals of integrated water vapor, integrated cloud liquid water, and surface wind speed. A general minimum-variance method for optimally retrieving geophysical parameters from multichannel brightness temperature measurements is outlined, and several global statistical constraints of the type required by this method are computed. Finally, a unified set of efficient statistical and semi-physical algorithms is presented for obtaining fields of surface wind speed, integrated water vapor, cloud liquid water, and precipitation from SSM/I brightness temperature data. Features include: a semi-physical method for retrieving integrated cloud liquid water at 15 km resolution and with rms errors as small as approximately 0.02 kg/sq m; a 3-channel statistical algorithm for integrated water vapor which was constructed so as to have improved linear response to water vapor and reduced sensitivity to precipitation; and two complementary indices of precipitation activity (based on 37 GHz attenuation and 85 GHz scattering, respectively), each of which are relatively insensitive to variations in other environmental parameters.

The Vertical Flux Method (VFM) for regional estimates of temporally and spatially varying nitrate fluxes in unsaturated zone and groundwater

NASA Astrophysics Data System (ADS)

Green, C. T.; Liao, L.; Nolan, B. T.; Juckem, P. F.; Ransom, K.; Harter, T.

2017-12-01

Process-based modeling of regional NO3- fluxes to groundwater is critical for understanding and managing water quality. Measurements of atmospheric tracers of groundwater age and dissolved-gas indicators of denitrification progress have potential to improve estimates of NO3- reactive transport processes. This presentation introduces a regionalized version of a vertical flux method (VFM) that uses simple mathematical estimates of advective-dispersive reactive transport with regularization procedures to calibrate estimated tracer concentrations to observed equivalents. The calibrated VFM provides estimates of chemical, hydrologic and reaction parameters (source concentration time series, recharge, effective porosity, dispersivity, reaction rate coefficients) and derived values (e.g. mean unsaturated zone travel time, eventual depth of the NO3- front) for individual wells. Statistical learning methods are used to extrapolate parameters and predictions from wells to continuous areas. The regional VFM was applied to 473 well samples in central-eastern Wisconsin. Chemical measurements included O2, NO3-, N2 from denitrification, and atmospheric tracers of groundwater age including carbon-14, chlorofluorocarbons, tritium, and triogiogenic helium. VFM results were consistent with observed chemistry, and calibrated parameters were in-line with independent estimates. Results indicated that (1) unsaturated zone travel times were a substantial portion of the transit time to wells and streams (2) fractions of N leached to groundwater have changed over time, with increasing fractions from manure and decreasing fractions from fertilizer, and (3) under current practices and conditions, 60% of the shallow aquifer will eventually be affected by NO3- contamination. Based on GIS coverages of variables related to soils, land use and hydrology, the VFM results at individual wells were extrapolated regionally using boosted regression trees, a statistical learning approach, that related the GIS variables to the VFM parameters and predictions. Future work will explore applications at larger scales with direct integration of the statistical prediction model with the mechanistic VFM.

Minnesota State Grant Statistics Over Time. 2003 Edition.

ERIC Educational Resources Information Center

Minnesota Higher Education Services Office, 2004

2004-01-01

This report contains data on the number and dollar amounts of Minnesota State Grants received by Minnesota undergraduates for Fiscal Years 1978 through 2003. Combined federal Pell and State Grant awards are also reported. The report includes a table showing the parameters used in the State Grant Program from Fiscal Year 1984 through 2003. The…

A Case Study to Examine Peer Grouping and Aspirant Selection. Professional File. Article 132, Fall 2013

ERIC Educational Resources Information Center

D'Allegro, Mary Lou; Zhou, Kai

2013-01-01

Peer selection based on the similarity of a couple of institutional parameters, by itself, is insufficient. Several other considerations, including clarity of purpose, alignment of institutional information to that purpose, identification of appropriate statistical procedures, review of preliminary peer sets, and the application of additional…

Determining fundamental properties of matter created in ultrarelativistic heavy-ion collisions

NASA Astrophysics Data System (ADS)

Novak, J.; Novak, K.; Pratt, S.; Vredevoogd, J.; Coleman-Smith, C. E.; Wolpert, R. L.

2014-03-01

Posterior distributions for physical parameters describing relativistic heavy-ion collisions, such as the viscosity of the quark-gluon plasma, are extracted through a comparison of hydrodynamic-based transport models to experimental results from 100AGeV+100AGeV Au +Au collisions at the Relativistic Heavy Ion Collider. By simultaneously varying six parameters and by evaluating several classes of observables, we are able to explore the complex intertwined dependencies of observables on model parameters. The methods provide a full multidimensional posterior distribution for the model output, including a range of acceptable values for each parameter, and reveal correlations between them. The breadth of observables and the number of parameters considered here go beyond previous studies in this field. The statistical tools, which are based upon Gaussian process emulators, are tested in detail and should be extendable to larger data sets and a higher number of parameters.

Statistical Aspects of North Atlantic Basin Tropical Cyclones During the Weather Satellite Era, 1960-2013. Part 2

NASA Technical Reports Server (NTRS)

Wilson, Robert M.

2014-01-01

This Technical Publication (TP) is part 2 of a two-part study of the North Atlantic basin tropical cyclones that occurred during the weather satellite era, 1960-2013. In particular, this TP examines the inferred statistical relationships between 25 tropical cyclone parameters and 9 specific climate-related factors, including the (1) Oceanic Niño Index (ONI), (2) Southern Oscillation Index (SOI), (3) Atlantic Multidecadal Oscillation (AMO) index, (4) Quasi-Biennial Oscillation (QBO) index, (5) North Atlantic Oscillation (NAO) index of the Climate Prediction Center (CPC), (6) NAO index of the Climate Research Unit (CRU), (7) Armagh surface air temperature (ASAT), (8) Global Land-Ocean Temperature Index (GLOTI), and (9) Mauna Loa carbon dioxide (CO2) (MLCO2) index. Part 1 of this two-part study examined the statistical aspects of the 25 tropical cyclone parameters (e.g., frequencies, peak wind speed (PWS), accumulated cyclone energy (ACE), etc.) and provided the results of statistical testing (i.e., runs-testing, the t-statistic for independent samples, and Poisson distributions). Also, the study gave predictions for the frequencies of the number of tropical cyclones (NTC), number of hurricanes (NH), number of major hurricanes (NMH), and number of United States land-falling hurricanes (NUSLFH) expected for the 2014 season, based on the statistics of the overall interval 1960-2013, the subinterval 1995-2013, and whether the year 2014 would be either an El Niño year (ENY) or a non-El Niño year (NENY).

Photospheric Magnetic Field Properties of Flaring versus Flare-quiet Active Regions. II. Discriminant Analysis

NASA Astrophysics Data System (ADS)

Leka, K. D.; Barnes, G.

2003-10-01

We apply statistical tests based on discriminant analysis to the wide range of photospheric magnetic parameters described in a companion paper by Leka & Barnes, with the goal of identifying those properties that are important for the production of energetic events such as solar flares. The photospheric vector magnetic field data from the University of Hawai'i Imaging Vector Magnetograph are well sampled both temporally and spatially, and we include here data covering 24 flare-event and flare-quiet epochs taken from seven active regions. The mean value and rate of change of each magnetic parameter are treated as separate variables, thus evaluating both the parameter's state and its evolution, to determine which properties are associated with flaring. Considering single variables first, Hotelling's T2-tests show small statistical differences between flare-producing and flare-quiet epochs. Even pairs of variables considered simultaneously, which do show a statistical difference for a number of properties, have high error rates, implying a large degree of overlap of the samples. To better distinguish between flare-producing and flare-quiet populations, larger numbers of variables are simultaneously considered; lower error rates result, but no unique combination of variables is clearly the best discriminator. The sample size is too small to directly compare the predictive power of large numbers of variables simultaneously. Instead, we rank all possible four-variable permutations based on Hotelling's T2-test and look for the most frequently appearing variables in the best permutations, with the interpretation that they are most likely to be associated with flaring. These variables include an increasing kurtosis of the twist parameter and a larger standard deviation of the twist parameter, but a smaller standard deviation of the distribution of the horizontal shear angle and a horizontal field that has a smaller standard deviation but a larger kurtosis. To support the ``sorting all permutations'' method of selecting the most frequently occurring variables, we show that the results of a single 10-variable discriminant analysis are consistent with the ranking. We demonstrate that individually, the variables considered here have little ability to differentiate between flaring and flare-quiet populations, but with multivariable combinations, the populations may be distinguished.

Trans-dimensional inversion of microtremor array dispersion data with hierarchical autoregressive error models

NASA Astrophysics Data System (ADS)

Dettmer, Jan; Molnar, Sheri; Steininger, Gavin; Dosso, Stan E.; Cassidy, John F.

2012-02-01

This paper applies a general trans-dimensional Bayesian inference methodology and hierarchical autoregressive data-error models to the inversion of microtremor array dispersion data for shear wave velocity (vs) structure. This approach accounts for the limited knowledge of the optimal earth model parametrization (e.g. the number of layers in the vs profile) and of the data-error statistics in the resulting vs parameter uncertainty estimates. The assumed earth model parametrization influences estimates of parameter values and uncertainties due to different parametrizations leading to different ranges of data predictions. The support of the data for a particular model is often non-unique and several parametrizations may be supported. A trans-dimensional formulation accounts for this non-uniqueness by including a model-indexing parameter as an unknown so that groups of models (identified by the indexing parameter) are considered in the results. The earth model is parametrized in terms of a partition model with interfaces given over a depth-range of interest. In this work, the number of interfaces (layers) in the partition model represents the trans-dimensional model indexing. In addition, serial data-error correlations are addressed by augmenting the geophysical forward model with a hierarchical autoregressive error model that can account for a wide range of error processes with a small number of parameters. Hence, the limited knowledge about the true statistical distribution of data errors is also accounted for in the earth model parameter estimates, resulting in more realistic uncertainties and parameter values. Hierarchical autoregressive error models do not rely on point estimates of the model vector to estimate data-error statistics, and have no requirement for computing the inverse or determinant of a data-error covariance matrix. This approach is particularly useful for trans-dimensional inverse problems, as point estimates may not be representative of the state space that spans multiple subspaces of different dimensionalities. The order of the autoregressive process required to fit the data is determined here by posterior residual-sample examination and statistical tests. Inference for earth model parameters is carried out on the trans-dimensional posterior probability distribution by considering ensembles of parameter vectors. In particular, vs uncertainty estimates are obtained by marginalizing the trans-dimensional posterior distribution in terms of vs-profile marginal distributions. The methodology is applied to microtremor array dispersion data collected at two sites with significantly different geology in British Columbia, Canada. At both sites, results show excellent agreement with estimates from invasive measurements.

StatisticAl Characteristics of Cloud over Beijing, China Obtained FRom Ka band Doppler Radar Observation

NASA Astrophysics Data System (ADS)

LIU, J.; Bi, Y.; Duan, S.; Lu, D.

2017-12-01

It is well-known that cloud characteristics, such as top and base heights and their layering structure of micro-physical parameters, spatial coverage and temporal duration are very important factors influencing both radiation budget and its vertical partitioning as well as hydrological cycle through precipitation data. Also, cloud structure and their statistical distribution and typical values will have respective characteristics with geographical and seasonal variation. Ka band radar is a powerful tool to obtain above parameters around the world, such as ARM cloud radar at the Oklahoma US, Since 2006, Cloudsat is one of NASA's A-Train satellite constellation, continuously observe the cloud structure with global coverage, but only twice a day it monitor clouds over same local site at same local time.By using IAP Ka band Doppler radar which has been operating continuously since early 2013 over the roof of IAP building in Beijing, we obtained the statistical characteristic of clouds, including cloud layering, cloud top and base heights, as well as the thickness of each cloud layer and their distribution, and were analyzed monthly and seasonal and diurnal variation, statistical analysis of cloud reflectivity profiles is also made. The analysis covers both non-precipitating clouds and precipitating clouds. Also, some preliminary comparison of the results with Cloudsat/Calipso products for same period and same area are made.

[Value influence of different compatibilities of main active parts in yangyintongnao granule on pharmacokinetics parameters in rats with cerebral ischemia reperfusion injury by total amount statistic moment method].

PubMed

Guo, Ying; Yang, Jiehong; Znang, Hengyi; Fu, Xuchun; Zhnag, Yuyan; Wan, Haitong

2010-02-01

To study the influence of the different combinations of the main active parts in Yangyintongnao granule on the pharmacokinetics parameters of the two active components--ligustrazine and puerarin using the method of total amount statistic moment for pharmacokinetics. Combinations were formed according to the dosages of the four active parts (alkaloid, flavone, saponin, naphtha) by orthogonal experiment L9 (3(4)). Blood concentrations of ligustrazine and puerarin were determinated by HPLC at different time. Zero rank moment (AUC) and one rank moment (MRT, mean residence time) of ligustrazine and puerarin have been worked out to calculate the total amount statistic moment parameters was analyzed of Yangyintongnao granule by the method of the total amount statistic moment. The influence of different compatibilities on the pharmacokinetics parameters was analyzed by orthogonal test. Flavone has the strongest effect than saponin on the total AUC. Ligustrazine has the strongest effect on the total MRT. Saponin has little effect on the two parameters, but naphtha has more effect on both of them. It indicates that naphtha may promote metabolism of ligustrazine and puerarin in rat. Total amount statistic moment parameters can be used to guide for compatibilities of TCM.

Phenomenon of statistical instability of the third type systems—complexity

NASA Astrophysics Data System (ADS)

Eskov, V. V.; Gavrilenko, T. V.; Eskov, V. M.; Vokhmina, Yu. V.

2017-11-01

The problem of the existence and special properties of third type systems has been formulated within the new chaos-self-organization theory. In fact, a global problem of the possibility of the existence of steady-state regimes for homeostatic systems has been considered. These systems include not only medical and biological systems, but also the dynamics of meteorological parameters, as well as the ambient parameters of the environment in which humans are located. The new approach has been used to give a new definition for homeostatic systems (complexity).

Using sensitivity analysis in model calibration efforts

USGS Publications Warehouse

Tiedeman, Claire; Hill, Mary C.

2003-01-01

In models of natural and engineered systems, sensitivity analysis can be used to assess relations among system state observations, model parameters, and model predictions. The model itself links these three entities, and model sensitivities can be used to quantify the links. Sensitivities are defined as the derivatives of simulated quantities (such as simulated equivalents of observations, or model predictions) with respect to model parameters. We present four measures calculated from model sensitivities that quantify the observation-parameter-prediction links and that are especially useful during the calibration and prediction phases of modeling. These four measures are composite scaled sensitivities (CSS), prediction scaled sensitivities (PSS), the value of improved information (VOII) statistic, and the observation prediction (OPR) statistic. These measures can be used to help guide initial calibration of models, collection of field data beneficial to model predictions, and recalibration of models updated with new field information. Once model sensitivities have been calculated, each of the four measures requires minimal computational effort. We apply the four measures to a three-layer MODFLOW-2000 (Harbaugh et al., 2000; Hill et al., 2000) model of the Death Valley regional ground-water flow system (DVRFS), located in southern Nevada and California. D’Agnese et al. (1997, 1999) developed and calibrated the model using nonlinear regression methods. Figure 1 shows some of the observations, parameters, and predictions for the DVRFS model. Observed quantities include hydraulic heads and spring flows. The 23 defined model parameters include hydraulic conductivities, vertical anisotropies, recharge rates, evapotranspiration rates, and pumpage. Predictions of interest for this regional-scale model are advective transport paths from potential contamination sites underlying the Nevada Test Site and Yucca Mountain.

GENASIS Basics: Object-oriented utilitarian functionality for large-scale physics simulations (Version 2)

NASA Astrophysics Data System (ADS)

Cardall, Christian Y.; Budiardja, Reuben D.

2017-05-01

GenASiS Basics provides Fortran 2003 classes furnishing extensible object-oriented utilitarian functionality for large-scale physics simulations on distributed memory supercomputers. This functionality includes physical units and constants; display to the screen or standard output device; message passing; I/O to disk; and runtime parameter management and usage statistics. This revision -Version 2 of Basics - makes mostly minor additions to functionality and includes some simplifying name changes.

Estimating urban ground-level PM10 using MODIS 3km AOD product and meteorological parameters from WRF model

NASA Astrophysics Data System (ADS)

Ghotbi, Saba; Sotoudeheian, Saeed; Arhami, Mohammad

2016-09-01

Satellite remote sensing products of AOD from MODIS along with appropriate meteorological parameters were used to develop statistical models and estimate ground-level PM10. Most of previous studies obtained meteorological data from synoptic weather stations, with rather sparse spatial distribution, and used it along with 10 km AOD product to develop statistical models, applicable for PM variations in regional scale (resolution of ≥10 km). In the current study, meteorological parameters were simulated with 3 km resolution using WRF model and used along with the rather new 3 km AOD product (launched in 2014). The resulting PM statistical models were assessed for a polluted and largely variable urban area, Tehran, Iran. Despite the critical particulate pollution problem, very few PM studies were conducted in this area. The issue of rather poor direct PM-AOD associations existed, due to different factors such as variations in particles optical properties, in addition to bright background issue for satellite data, as the studied area located in the semi-arid areas of Middle East. Statistical approach of linear mixed effect (LME) was used, and three types of statistical models including single variable LME model (using AOD as independent variable) and multiple variables LME model by using meteorological data from two sources, WRF model and synoptic stations, were examined. Meteorological simulations were performed using a multiscale approach and creating an appropriate physic for the studied region, and the results showed rather good agreements with recordings of the synoptic stations. The single variable LME model was able to explain about 61%-73% of daily PM10 variations, reflecting a rather acceptable performance. Statistical models performance improved through using multivariable LME and incorporating meteorological data as auxiliary variables, particularly by using fine resolution outputs from WRF (R2 = 0.73-0.81). In addition, rather fine resolution for PM estimates was mapped for the studied city, and resulting concentration maps were consistent with PM recordings at the existing stations.

A statistical approach to quasi-extinction forecasting.

PubMed

Holmes, Elizabeth Eli; Sabo, John L; Viscido, Steven Vincent; Fagan, William Fredric

2007-12-01

Forecasting population decline to a certain critical threshold (the quasi-extinction risk) is one of the central objectives of population viability analysis (PVA), and such predictions figure prominently in the decisions of major conservation organizations. In this paper, we argue that accurate forecasting of a population's quasi-extinction risk does not necessarily require knowledge of the underlying biological mechanisms. Because of the stochastic and multiplicative nature of population growth, the ensemble behaviour of population trajectories converges to common statistical forms across a wide variety of stochastic population processes. This paper provides a theoretical basis for this argument. We show that the quasi-extinction surfaces of a variety of complex stochastic population processes (including age-structured, density-dependent and spatially structured populations) can be modelled by a simple stochastic approximation: the stochastic exponential growth process overlaid with Gaussian errors. Using simulated and real data, we show that this model can be estimated with 20-30 years of data and can provide relatively unbiased quasi-extinction risk with confidence intervals considerably smaller than (0,1). This was found to be true even for simulated data derived from some of the noisiest population processes (density-dependent feedback, species interactions and strong age-structure cycling). A key advantage of statistical models is that their parameters and the uncertainty of those parameters can be estimated from time series data using standard statistical methods. In contrast for most species of conservation concern, biologically realistic models must often be specified rather than estimated because of the limited data available for all the various parameters. Biologically realistic models will always have a prominent place in PVA for evaluating specific management options which affect a single segment of a population, a single demographic rate, or different geographic areas. However, for forecasting quasi-extinction risk, statistical models that are based on the convergent statistical properties of population processes offer many advantages over biologically realistic models.

Measuring the statistical validity of summary meta-analysis and meta-regression results for use in clinical practice.

PubMed

Willis, Brian H; Riley, Richard D

2017-09-20

An important question for clinicians appraising a meta-analysis is: are the findings likely to be valid in their own practice-does the reported effect accurately represent the effect that would occur in their own clinical population? To this end we advance the concept of statistical validity-where the parameter being estimated equals the corresponding parameter for a new independent study. Using a simple ('leave-one-out') cross-validation technique, we demonstrate how we may test meta-analysis estimates for statistical validity using a new validation statistic, Vn, and derive its distribution. We compare this with the usual approach of investigating heterogeneity in meta-analyses and demonstrate the link between statistical validity and homogeneity. Using a simulation study, the properties of Vn and the Q statistic are compared for univariate random effects meta-analysis and a tailored meta-regression model, where information from the setting (included as model covariates) is used to calibrate the summary estimate to the setting of application. Their properties are found to be similar when there are 50 studies or more, but for fewer studies Vn has greater power but a higher type 1 error rate than Q. The power and type 1 error rate of Vn are also shown to depend on the within-study variance, between-study variance, study sample size, and the number of studies in the meta-analysis. Finally, we apply Vn to two published meta-analyses and conclude that it usefully augments standard methods when deciding upon the likely validity of summary meta-analysis estimates in clinical practice. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Orthotopic bladder substitution in men revisited: identification of continence predictors.

PubMed

Koraitim, M M; Atta, M A; Foda, M K

2006-11-01

We determined the impact of the functional characteristics of the neobladder and urethral sphincter on continence results, and determined the most significant predictors of continence. A total of 88 male patients 29 to 70 years old underwent orthotopic bladder substitution with tubularized ileocecal segment (40) and detubularized sigmoid (25) or ileum (23). Uroflowmetry, cystometry and urethral pressure profilometry were performed at 13 to 36 months (mean 19) postoperatively. The correlation between urinary continence and 28 urodynamic variables was assessed. Parameters that correlated significantly with continence were entered into a multivariate analysis using a logistic regression model to determine the most significant predictors of continence. Maximum urethral closure pressure was the only parameter that showed a statistically significant correlation with diurnal continence. Nocturnal continence had not only a statistically significant positive correlation with maximum urethral closure pressure, but also statistically significant negative correlations with maximum contraction amplitude, and baseline pressure at mid and maximum capacity. Three of these 4 parameters, including maximum urethral closure pressure, maximum contraction amplitude and baseline pressure at mid capacity, proved to be significant predictors of continence on multivariate analysis. While daytime continence is determined by maximum urethral closure pressure, during the night it is the net result of 2 forces that have about equal influence but in opposite directions, that is maximum urethral closure pressure vs maximum contraction amplitude plus baseline pressure at mid capacity. Two equations were derived from the logistic regression model to predict the probability of continence after orthotopic bladder substitution, including Z1 (diurnal) = 0.605 + 0.0085 maximum urethral closure pressure and Z2 (nocturnal) = 0.841 + 0.01 [maximum urethral closure pressure - (maximum contraction amplitude + baseline pressure at mid capacity)].

An initial-abstraction, constant-loss model for unit hydrograph modeling for applicable watersheds in Texas

USGS Publications Warehouse

Asquith, William H.; Roussel, Meghan C.

2007-01-01

Estimation of representative hydrographs from design storms, which are known as design hydrographs, provides for cost-effective, riskmitigated design of drainage structures such as bridges, culverts, roadways, and other infrastructure. During 2001?07, the U.S. Geological Survey (USGS), in cooperation with the Texas Department of Transportation, investigated runoff hydrographs, design storms, unit hydrographs,and watershed-loss models to enhance design hydrograph estimation in Texas. Design hydrographs ideally should mimic the general volume, peak, and shape of observed runoff hydrographs. Design hydrographs commonly are estimated in part by unit hydrographs. A unit hydrograph is defined as the runoff hydrograph that results from a unit pulse of excess rainfall uniformly distributed over the watershed at a constant rate for a specific duration. A time-distributed, watershed-loss model is required for modeling by unit hydrographs. This report develops a specific time-distributed, watershed-loss model known as an initial-abstraction, constant-loss model. For this watershed-loss model, a watershed is conceptualized to have the capacity to store or abstract an absolute depth of rainfall at and near the beginning of a storm. Depths of total rainfall less than this initial abstraction do not produce runoff. The watershed also is conceptualized to have the capacity to remove rainfall at a constant rate (loss) after the initial abstraction is satisfied. Additional rainfall inputs after the initial abstraction is satisfied contribute to runoff if the rainfall rate (intensity) is larger than the constant loss. The initial abstraction, constant-loss model thus is a two-parameter model. The initial-abstraction, constant-loss model is investigated through detailed computational and statistical analysis of observed rainfall and runoff data for 92 USGS streamflow-gaging stations (watersheds) in Texas with contributing drainage areas from 0.26 to 166 square miles. The analysis is limited to a previously described, watershed-specific, gamma distribution model of the unit hydrograph. In particular, the initial-abstraction, constant-loss model is tuned to the gamma distribution model of the unit hydrograph. A complex computational analysis of observed rainfall and runoff for the 92 watersheds was done to determine, by storm, optimal values of initial abstraction and constant loss. Optimal parameter values for a given storm were defined as those values that produced a modeled runoff hydrograph with volume equal to the observed runoff hydrograph and also minimized the residual sum of squares of the two hydrographs. Subsequently, the means of the optimal parameters were computed on a watershed-specific basis. These means for each watershed are considered the most representative, are tabulated, and are used in further statistical analyses. Statistical analyses of watershed-specific, initial abstraction and constant loss include documentation of the distribution of each parameter using the generalized lambda distribution. The analyses show that watershed development has substantial influence on initial abstraction and limited influence on constant loss. The means and medians of the 92 watershed-specific parameters are tabulated with respect to watershed development; although they have considerable uncertainty, these parameters can be used for parameter prediction for ungaged watersheds. The statistical analyses of watershed-specific, initial abstraction and constant loss also include development of predictive procedures for estimation of each parameter for ungaged watersheds. Both regression equations and regression trees for estimation of initial abstraction and constant loss are provided. The watershed characteristics included in the regression analyses are (1) main-channel length, (2) a binary factor representing watershed development, (3) a binary factor representing watersheds with an abundance of rocky and thin-soiled terrain, and (4) curve numb

Quons, an interpolation between Bose and Fermi oscillators

NASA Technical Reports Server (NTRS)

Greenberg, O. W.

1993-01-01

After a brief mention of Bose and Fermi oscillators and of particles which obey other types of statistics, including intermediate statistics, parastatistics, paronic statistics, anyon statistics, and infinite statistics, I discuss the statistics of 'quons' (pronounced to rhyme with muons), particles whose annihilation and creation operators obey the q-deformed commutation relation (the quon algebra or q-mutator) which interpolates between fermions and bosons. I emphasize that the operator for interaction with an external source must be an effective Bose operator in all cases. To accomplish this for parabose, parafermi and quon operators, I introduce parabose, parafermi, and quon Grassmann numbers, respectively. I also discuss interactions of non-relativistic quons, quantization of quon fields with antiparticles, calculation of vacuum matrix elements of relativistic quon fields, demonstration of the TCP theorem, cluster decomposition, and Wick's theorem for relativistic quon fields, and the failure of local commutativity of observables for relativistic quon fields. I conclude with the bound on the parameter q for electrons due to the Ramberg-Snow experiment.

A Parameter Subset Selection Algorithm for Mixed-Effects Models

DOE PAGES

Schmidt, Kathleen L.; Smith, Ralph C.

2016-01-01

Mixed-effects models are commonly used to statistically model phenomena that include attributes associated with a population or general underlying mechanism as well as effects specific to individuals or components of the general mechanism. This can include individual effects associated with data from multiple experiments. However, the parameterizations used to incorporate the population and individual effects are often unidentifiable in the sense that parameters are not uniquely specified by the data. As a result, the current literature focuses on model selection, by which insensitive parameters are fixed or removed from the model. Model selection methods that employ information criteria are applicablemore » to both linear and nonlinear mixed-effects models, but such techniques are limited in that they are computationally prohibitive for large problems due to the number of possible models that must be tested. To limit the scope of possible models for model selection via information criteria, we introduce a parameter subset selection (PSS) algorithm for mixed-effects models, which orders the parameters by their significance. In conclusion, we provide examples to verify the effectiveness of the PSS algorithm and to test the performance of mixed-effects model selection that makes use of parameter subset selection.« less

Temperature and Voltage Offsets in High- ZT Thermoelectrics

NASA Astrophysics Data System (ADS)

Levy, George S.

2018-06-01

Thermodynamic temperature can take on different meanings. Kinetic temperature is an expectation value and a function of the kinetic energy distribution. Statistical temperature is a parameter of the distribution. Kinetic temperature and statistical temperature, identical in Maxwell-Boltzmann statistics, can differ in other statistics such as those of Fermi-Dirac or Bose-Einstein when a field is present. Thermal equilibrium corresponds to zero statistical temperature gradient, not zero kinetic temperature gradient. Since heat carriers in thermoelectrics are fermions, the difference between these two temperatures may explain voltage and temperature offsets observed during meticulous Seebeck measurements in which the temperature-voltage curve does not go through the origin. In conventional semiconductors, temperature offsets produced by fermionic electrical carriers are not observable because they are shorted by heat phonons in the lattice. In high- ZT materials, however, these offsets have been detected but attributed to faulty laboratory procedures. Additional supporting evidence for spontaneous voltages and temperature gradients includes data collected in epistatic experiments and in the plasma Q-machine. Device fabrication guidelines for testing the hypothesis are suggested including using unipolar junctions stacked in a superlattice, alternating n/ n + and p/ p + junctions, selecting appropriate dimensions, doping, and loading.

Temperature and Voltage Offsets in High-ZT Thermoelectrics

NASA Astrophysics Data System (ADS)

Levy, George S.

2017-10-01

Thermodynamic temperature can take on different meanings. Kinetic temperature is an expectation value and a function of the kinetic energy distribution. Statistical temperature is a parameter of the distribution. Kinetic temperature and statistical temperature, identical in Maxwell-Boltzmann statistics, can differ in other statistics such as those of Fermi-Dirac or Bose-Einstein when a field is present. Thermal equilibrium corresponds to zero statistical temperature gradient, not zero kinetic temperature gradient. Since heat carriers in thermoelectrics are fermions, the difference between these two temperatures may explain voltage and temperature offsets observed during meticulous Seebeck measurements in which the temperature-voltage curve does not go through the origin. In conventional semiconductors, temperature offsets produced by fermionic electrical carriers are not observable because they are shorted by heat phonons in the lattice. In high-ZT materials, however, these offsets have been detected but attributed to faulty laboratory procedures. Additional supporting evidence for spontaneous voltages and temperature gradients includes data collected in epistatic experiments and in the plasma Q-machine. Device fabrication guidelines for testing the hypothesis are suggested including using unipolar junctions stacked in a superlattice, alternating n/n + and p/p + junctions, selecting appropriate dimensions, doping, and loading.

Statistical characteristics of trajectories of diamagnetic unicellular organisms in a magnetic field.

PubMed

Gorobets, Yu I; Gorobets, O Yu

2015-01-01

The statistical model is proposed in this paper for description of orientation of trajectories of unicellular diamagnetic organisms in a magnetic field. The statistical parameter such as the effective energy is calculated on basis of this model. The resulting effective energy is the statistical characteristics of trajectories of diamagnetic microorganisms in a magnetic field connected with their metabolism. The statistical model is applicable for the case when the energy of the thermal motion of bacteria is negligible in comparison with their energy in a magnetic field and the bacteria manifest the significant "active random movement", i.e. there is the randomizing motion of the bacteria of non thermal nature, for example, movement of bacteria by means of flagellum. The energy of the randomizing active self-motion of bacteria is characterized by the new statistical parameter for biological objects. The parameter replaces the energy of the randomizing thermal motion in calculation of the statistical distribution. Copyright © 2014 Elsevier Ltd. All rights reserved.

Dissolution comparisons using a Multivariate Statistical Distance (MSD) test and a comparison of various approaches for calculating the measurements of dissolution profile comparison.

PubMed

Cardot, J-M; Roudier, B; Schütz, H

2017-07-01

The f 2 test is generally used for comparing dissolution profiles. In cases of high variability, the f 2 test is not applicable, and the Multivariate Statistical Distance (MSD) test is frequently proposed as an alternative by the FDA and EMA. The guidelines provide only general recommendations. MSD tests can be performed either on raw data with or without time as a variable or on parameters of models. In addition, data can be limited-as in the case of the f 2 test-to dissolutions of up to 85% or to all available data. In the context of the present paper, the recommended calculation included all raw dissolution data up to the first point greater than 85% as a variable-without the various times as parameters. The proposed MSD overcomes several drawbacks found in other methods.

A Backscatter-Lidar Forward-Operator

NASA Astrophysics Data System (ADS)

Geisinger, Armin; Behrendt, Andreas; Wulfmeyer, Volker; Vogel, Bernhard; Mattis, Ina; Flentje, Harald; Förstner, Jochen; Potthast, Roland

2015-04-01

We have developed a forward-operator which is capable of calculating virtual lidar profiles from atmospheric state simulations. The operator allows us to compare lidar measurements and model simulations based on the same measurement parameter: the lidar backscatter profile. This method simplifies qualitative comparisons and also makes quantitative comparisons possible, including statistical error quantification. Implemented into an aerosol-capable model system, the operator will act as a component to assimilate backscatter-lidar measurements. As many weather services maintain already networks of backscatter-lidars, such data are acquired already in an operational manner. To estimate and quantify errors due to missing or uncertain aerosol information, we started sensitivity studies about several scattering parameters such as the aerosol size and both the real and imaginary part of the complex index of refraction. Furthermore, quantitative and statistical comparisons between measurements and virtual measurements are shown in this study, i.e. applying the backscatter-lidar forward-operator on model output.

Quantum-statistical theory of microwave detection using superconducting tunnel junctions

NASA Astrophysics Data System (ADS)

Deviatov, I. A.; Kuzmin, L. S.; Likharev, K. K.; Migulin, V. V.; Zorin, A. B.

1986-09-01

A quantum-statistical theory of microwave and millimeter-wave detection using superconducting tunnel junctions is developed, with a rigorous account of quantum, thermal, and shot noise arising from fluctuation sources associated with the junctions, signal source, and matching circuits. The problem of the noise characterization in the quantum sensitivity range is considered and a general noise parameter Theta(N) is introduced. This parameter is shown to be an adequate figure of merit for most receivers of interest while some devices can require a more complex characterization. Analytical expressions and/or numerically calculated plots for Theta(N) are presented for the most promising detection modes including the parametric amplification, heterodyne mixing, and quadratic videodetection, using both the quasiparticle-current and the Cooper-pair-current nonlinearities. Ultimate minimum values of Theta(N) for each detection mode are compared and found to be in agreement with limitations imposed by the quantum-mechanical uncertainty principle.

Remote sensing-aided systems for snow qualification, evapotranspiration estimation, and their application in hydrologic models

NASA Technical Reports Server (NTRS)

Korram, S.

1977-01-01

The design of general remote sensing-aided methodologies was studied to provide the estimates of several important inputs to water yield forecast models. These input parameters are snow area extent, snow water content, and evapotranspiration. The study area is Feather River Watershed (780,000 hectares), Northern California. The general approach involved a stepwise sequence of identification of the required information, sample design, measurement/estimation, and evaluation of results. All the relevent and available information types needed in the estimation process are being defined. These include Landsat, meteorological satellite, and aircraft imagery, topographic and geologic data, ground truth data, and climatic data from ground stations. A cost-effective multistage sampling approach was employed in quantification of all the required parameters. The physical and statistical models for both snow quantification and evapotranspiration estimation was developed. These models use the information obtained by aerial and ground data through appropriate statistical sampling design.

A new item response theory model to adjust data allowing examinee choice

PubMed Central

Costa, Marcelo Azevedo; Braga Oliveira, Rivert Paulo

2018-01-01

In a typical questionnaire testing situation, examinees are not allowed to choose which items they answer because of a technical issue in obtaining satisfactory statistical estimates of examinee ability and item difficulty. This paper introduces a new item response theory (IRT) model that incorporates information from a novel representation of questionnaire data using network analysis. Three scenarios in which examinees select a subset of items were simulated. In the first scenario, the assumptions required to apply the standard Rasch model are met, thus establishing a reference for parameter accuracy. The second and third scenarios include five increasing levels of violating those assumptions. The results show substantial improvements over the standard model in item parameter recovery. Furthermore, the accuracy was closer to the reference in almost every evaluated scenario. To the best of our knowledge, this is the first proposal to obtain satisfactory IRT statistical estimates in the last two scenarios. PMID:29389996

Anisotropic analysis of trabecular architecture in human femur bone radiographs using quaternion wavelet transforms.

PubMed

Sangeetha, S; Sujatha, C M; Manamalli, D

2014-01-01

In this work, anisotropy of compressive and tensile strength regions of femur trabecular bone are analysed using quaternion wavelet transforms. The normal and abnormal femur trabecular bone radiographic images are considered for this study. The sub-anatomic regions, which include compressive and tensile regions, are delineated using pre-processing procedures. These delineated regions are subjected to quaternion wavelet transforms and statistical parameters are derived from the transformed images. These parameters are correlated with apparent porosity, which is derived from the strength regions. Further, anisotropy is also calculated from the transformed images and is analyzed. Results show that the anisotropy values derived from second and third phase components of quaternion wavelet transform are found to be distinct for normal and abnormal samples with high statistical significance for both compressive and tensile regions. These investigations demonstrate that architectural anisotropy derived from QWT analysis is able to differentiate normal and abnormal samples.

Static shape control for flexible structures

NASA Technical Reports Server (NTRS)

Rodriguez, G.; Scheid, R. E., Jr.

1986-01-01

An integrated methodology is described for defining static shape control laws for large flexible structures. The techniques include modeling, identifying and estimating the control laws of distributed systems characterized in terms of infinite dimensional state and parameter spaces. The models are expressed as interconnected elliptic partial differential equations governing a range of static loads, with the capability of analyzing electromagnetic fields around antenna systems. A second-order analysis is carried out for statistical errors, and model parameters are determined by maximizing an appropriate defined likelihood functional which adjusts the model to observational data. The parameter estimates are derived from the conditional mean of the observational data, resulting in a least squares superposition of shape functions obtained from the structural model.

A new statistical method for design and analyses of component tolerance

NASA Astrophysics Data System (ADS)

Movahedi, Mohammad Mehdi; Khounsiavash, Mohsen; Otadi, Mahmood; Mosleh, Maryam

2017-03-01

Tolerancing conducted by design engineers to meet customers' needs is a prerequisite for producing high-quality products. Engineers use handbooks to conduct tolerancing. While use of statistical methods for tolerancing is not something new, engineers often use known distributions, including the normal distribution. Yet, if the statistical distribution of the given variable is unknown, a new statistical method will be employed to design tolerance. In this paper, we use generalized lambda distribution for design and analyses component tolerance. We use percentile method (PM) to estimate the distribution parameters. The findings indicated that, when the distribution of the component data is unknown, the proposed method can be used to expedite the design of component tolerance. Moreover, in the case of assembled sets, more extensive tolerance for each component with the same target performance can be utilized.

THE MEASUREMENT OF BONE QUALITY USING GRAY LEVEL CO-OCCURRENCE MATRIX TEXTURAL FEATURES.

PubMed

Shirvaikar, Mukul; Huang, Ning; Dong, Xuanliang Neil

2016-10-01

In this paper, statistical methods for the estimation of bone quality to predict the risk of fracture are reported. Bone mineral density and bone architecture properties are the main contributors of bone quality. Dual-energy X-ray Absorptiometry (DXA) is the traditional clinical measurement technique for bone mineral density, but does not include architectural information to enhance the prediction of bone fragility. Other modalities are not practical due to cost and access considerations. This study investigates statistical parameters based on the Gray Level Co-occurrence Matrix (GLCM) extracted from two-dimensional projection images and explores links with architectural properties and bone mechanics. Data analysis was conducted on Micro-CT images of 13 trabecular bones (with an in-plane spatial resolution of about 50μm). Ground truth data for bone volume fraction (BV/TV), bone strength and modulus were available based on complex 3D analysis and mechanical tests. Correlation between the statistical parameters and biomechanical test results was studied using regression analysis. The results showed Cluster-Shade was strongly correlated with the microarchitecture of the trabecular bone and related to mechanical properties. Once the principle thesis of utilizing second-order statistics is established, it can be extended to other modalities, providing cost and convenience advantages for patients and doctors.

THE MEASUREMENT OF BONE QUALITY USING GRAY LEVEL CO-OCCURRENCE MATRIX TEXTURAL FEATURES

PubMed Central

Shirvaikar, Mukul; Huang, Ning; Dong, Xuanliang Neil

2016-01-01

In this paper, statistical methods for the estimation of bone quality to predict the risk of fracture are reported. Bone mineral density and bone architecture properties are the main contributors of bone quality. Dual-energy X-ray Absorptiometry (DXA) is the traditional clinical measurement technique for bone mineral density, but does not include architectural information to enhance the prediction of bone fragility. Other modalities are not practical due to cost and access considerations. This study investigates statistical parameters based on the Gray Level Co-occurrence Matrix (GLCM) extracted from two-dimensional projection images and explores links with architectural properties and bone mechanics. Data analysis was conducted on Micro-CT images of 13 trabecular bones (with an in-plane spatial resolution of about 50μm). Ground truth data for bone volume fraction (BV/TV), bone strength and modulus were available based on complex 3D analysis and mechanical tests. Correlation between the statistical parameters and biomechanical test results was studied using regression analysis. The results showed Cluster-Shade was strongly correlated with the microarchitecture of the trabecular bone and related to mechanical properties. Once the principle thesis of utilizing second-order statistics is established, it can be extended to other modalities, providing cost and convenience advantages for patients and doctors. PMID:28042512

The effect of the dynamic wet troposphere on radio interferometric measurements

NASA Technical Reports Server (NTRS)

Treuhaft, R. N.; Lanyi, G. E.

1987-01-01

A statistical model of water vapor fluctuations is used to describe the effect of the dynamic wet troposphere on radio interferometric measurements. It is assumed that the spatial structure of refractivity is approximated by Kolmogorov turbulence theory, and that the temporal fluctuations are caused by spatial patterns moved over a site by the wind, and these assumptions are examined for the VLBI delay and delay rate observables. The results suggest that the delay rate measurement error is usually dominated by water vapor fluctuations, and water vapor induced VLBI parameter errors and correlations are determined as a function of the delay observable errors. A method is proposed for including the water vapor fluctuations in the parameter estimation method to obtain improved parameter estimates and parameter covariances.

Statistical inference involving binomial and negative binomial parameters.

PubMed

García-Pérez, Miguel A; Núñez-Antón, Vicente

2009-05-01

Statistical inference about two binomial parameters implies that they are both estimated by binomial sampling. There are occasions in which one aims at testing the equality of two binomial parameters before and after the occurrence of the first success along a sequence of Bernoulli trials. In these cases, the binomial parameter before the first success is estimated by negative binomial sampling whereas that after the first success is estimated by binomial sampling, and both estimates are related. This paper derives statistical tools to test two hypotheses, namely, that both binomial parameters equal some specified value and that both parameters are equal though unknown. Simulation studies are used to show that in small samples both tests are accurate in keeping the nominal Type-I error rates, and also to determine sample size requirements to detect large, medium, and small effects with adequate power. Additional simulations also show that the tests are sufficiently robust to certain violations of their assumptions.

Boosting Bayesian parameter inference of nonlinear stochastic differential equation models by Hamiltonian scale separation.

PubMed

Albert, Carlo; Ulzega, Simone; Stoop, Ruedi

2016-04-01

Parameter inference is a fundamental problem in data-driven modeling. Given observed data that is believed to be a realization of some parameterized model, the aim is to find parameter values that are able to explain the observed data. In many situations, the dominant sources of uncertainty must be included into the model for making reliable predictions. This naturally leads to stochastic models. Stochastic models render parameter inference much harder, as the aim then is to find a distribution of likely parameter values. In Bayesian statistics, which is a consistent framework for data-driven learning, this so-called posterior distribution can be used to make probabilistic predictions. We propose a novel, exact, and very efficient approach for generating posterior parameter distributions for stochastic differential equation models calibrated to measured time series. The algorithm is inspired by reinterpreting the posterior distribution as a statistical mechanics partition function of an object akin to a polymer, where the measurements are mapped on heavier beads compared to those of the simulated data. To arrive at distribution samples, we employ a Hamiltonian Monte Carlo approach combined with a multiple time-scale integration. A separation of time scales naturally arises if either the number of measurement points or the number of simulation points becomes large. Furthermore, at least for one-dimensional problems, we can decouple the harmonic modes between measurement points and solve the fastest part of their dynamics analytically. Our approach is applicable to a wide range of inference problems and is highly parallelizable.

EFFECTS OF AROMATHERAPY MASSAGE ON THE SLEEP QUALITY AND PHYSIOLOGICAL PARAMETERS OF PATIENTS IN A SURGICAL INTENSIVE CARE UNIT.

PubMed

Özlü, Zeynep Karaman; Bilican, Pınar

2017-01-01

Surgical pain is experienced by inpatients with clinical, disease-related concerns, unknown encounters after surgery, quality of sleep, restrictions in position after surgery is known to be serious. The study was conducted to determine the effect of aromatherapy massage on quality of sleep and physiological parameters in surgical intensive care patients. This is an experimental study. The sample of this study consisted of 60 patients who were divided into two groups as experimental group and control group including 30 patients in each one. The participants were postoperative patients, absent complications, who were unconscious and extubated. A data collection form on personal characteristics of the patients, a registration form on their physical parameters and the Richards-Campbell Sleep Scale (RCSQ) were used to collect the data of the study. The Richards-Campbell Sleep Scale indicated that while the experimental group had a mean score of 53.80 ± 13.20, the control group had a mean score of 29.08 ± 9.71 and there was a statistically significant difference between mean scores of the groups. In a comparison of physiologic parameters, only diastolic blood pressure measuring between parameters in favor of an assembly as a statistically significant difference was detected. Results of the study showed that aromatherapy massage enhanced the sleep quality of patients in a surgical intensive care unit and resulted in some positive changes in their physiological parameters.

EFFECTS OF AROMATHERAPY MASSAGE ON THE SLEEP QUALITY AND PHYSIOLOGICAL PARAMETERS OF PATIENTS IN A SURGICAL INTENSIVE CARE UNIT

PubMed Central

Özlü, Zeynep Karaman; Bilican, Pınar

2017-01-01

Background: Surgical pain is experienced by inpatients with clinical, disease-related concerns, unknown encounters after surgery, quality of sleep, restrictions in position after surgery is known to be serious. The study was conducted to determine the effect of aromatherapy massage on quality of sleep and physiological parameters in surgical intensive care patients. Materials and Methods: This is an experimental study. The sample of this study consisted of 60 patients who were divided into two groups as experimental group and control group including 30 patients in each one. The participants were postoperative patients, absent complications, who were unconscious and extubated. A data collection form on personal characteristics of the patients, a registration form on their physical parameters and the Richards-Campbell Sleep Scale (RCSQ) were used to collect the data of the study. Results: The Richards-Campbell Sleep Scale indicated that while the experimental group had a mean score of 53.80 ± 13.20, the control group had a mean score of 29.08 ± 9.71 and there was a statistically significant difference between mean scores of the groups. In a comparison of physiologic parameters, only diastolic blood pressure measuring between parameters in favor of an assembly as a statistically significant difference was detected. Conclusions: Results of the study showed that aromatherapy massage enhanced the sleep quality of patients in a surgical intensive care unit and resulted in some positive changes in their physiological parameters. PMID:28480419

Using Perturbed Physics Ensembles and Machine Learning to Select Parameters for Reducing Regional Biases in a Global Climate Model

NASA Astrophysics Data System (ADS)

Li, S.; Rupp, D. E.; Hawkins, L.; Mote, P.; McNeall, D. J.; Sarah, S.; Wallom, D.; Betts, R. A.

2017-12-01

This study investigates the potential to reduce known summer hot/dry biases over Pacific Northwest in the UK Met Office's atmospheric model (HadAM3P) by simultaneously varying multiple model parameters. The bias-reduction process is done through a series of steps: 1) Generation of perturbed physics ensemble (PPE) through the volunteer computing network weather@home; 2) Using machine learning to train "cheap" and fast statistical emulators of climate model, to rule out regions of parameter spaces that lead to model variants that do not satisfy observational constraints, where the observational constraints (e.g., top-of-atmosphere energy flux, magnitude of annual temperature cycle, summer/winter temperature and precipitation) are introduced sequentially; 3) Designing a new PPE by "pre-filtering" using the emulator results. Steps 1) through 3) are repeated until results are considered to be satisfactory (3 times in our case). The process includes a sensitivity analysis to find dominant parameters for various model output metrics, which reduces the number of parameters to be perturbed with each new PPE. Relative to observational uncertainty, we achieve regional improvements without introducing large biases in other parts of the globe. Our results illustrate the potential of using machine learning to train cheap and fast statistical emulators of climate model, in combination with PPEs in systematic model improvement.

Inverse and forward modeling under uncertainty using MRE-based Bayesian approach

NASA Astrophysics Data System (ADS)

Hou, Z.; Rubin, Y.

2004-12-01

A stochastic inverse approach for subsurface characterization is proposed and applied to shallow vadose zone at a winery field site in north California and to a gas reservoir at the Ormen Lange field site in the North Sea. The approach is formulated in a Bayesian-stochastic framework, whereby the unknown parameters are identified in terms of their statistical moments or their probabilities. Instead of the traditional single-valued estimation /prediction provided by deterministic methods, the approach gives a probability distribution for an unknown parameter. This allows calculating the mean, the mode, and the confidence interval, which is useful for a rational treatment of uncertainty and its consequences. The approach also allows incorporating data of various types and different error levels, including measurements of state variables as well as information such as bounds on or statistical moments of the unknown parameters, which may represent prior information. To obtain minimally subjective prior probabilities required for the Bayesian approach, the principle of Minimum Relative Entropy (MRE) is employed. The approach is tested in field sites for flow parameters identification and soil moisture estimation in the vadose zone and for gas saturation estimation at great depth below the ocean floor. Results indicate the potential of coupling various types of field data within a MRE-based Bayesian formalism for improving the estimation of the parameters of interest.

Large ensemble modeling of last deglacial retreat of the West Antarctic Ice Sheet: comparison of simple and advanced statistical techniques

NASA Astrophysics Data System (ADS)

Pollard, D.; Chang, W.; Haran, M.; Applegate, P.; DeConto, R.

2015-11-01

A 3-D hybrid ice-sheet model is applied to the last deglacial retreat of the West Antarctic Ice Sheet over the last ~ 20 000 years. A large ensemble of 625 model runs is used to calibrate the model to modern and geologic data, including reconstructed grounding lines, relative sea-level records, elevation-age data and uplift rates, with an aggregate score computed for each run that measures overall model-data misfit. Two types of statistical methods are used to analyze the large-ensemble results: simple averaging weighted by the aggregate score, and more advanced Bayesian techniques involving Gaussian process-based emulation and calibration, and Markov chain Monte Carlo. Results for best-fit parameter ranges and envelopes of equivalent sea-level rise with the simple averaging method agree quite well with the more advanced techniques, but only for a large ensemble with full factorial parameter sampling. Best-fit parameter ranges confirm earlier values expected from prior model tuning, including large basal sliding coefficients on modern ocean beds. Each run is extended 5000 years into the "future" with idealized ramped climate warming. In the majority of runs with reasonable scores, this produces grounding-line retreat deep into the West Antarctic interior, and the analysis provides sea-level-rise envelopes with well defined parametric uncertainty bounds.

Combined Uncertainty and A-Posteriori Error Bound Estimates for General CFD Calculations: Theory and Software Implementation

NASA Technical Reports Server (NTRS)

Barth, Timothy J.

2014-01-01

This workshop presentation discusses the design and implementation of numerical methods for the quantification of statistical uncertainty, including a-posteriori error bounds, for output quantities computed using CFD methods. Hydrodynamic realizations often contain numerical error arising from finite-dimensional approximation (e.g. numerical methods using grids, basis functions, particles) and statistical uncertainty arising from incomplete information and/or statistical characterization of model parameters and random fields. The first task at hand is to derive formal error bounds for statistics given realizations containing finite-dimensional numerical error [1]. The error in computed output statistics contains contributions from both realization error and the error resulting from the calculation of statistics integrals using a numerical method. A second task is to devise computable a-posteriori error bounds by numerically approximating all terms arising in the error bound estimates. For the same reason that CFD calculations including error bounds but omitting uncertainty modeling are only of limited value, CFD calculations including uncertainty modeling but omitting error bounds are only of limited value. To gain maximum value from CFD calculations, a general software package for uncertainty quantification with quantified error bounds has been developed at NASA. The package provides implementations for a suite of numerical methods used in uncertainty quantification: Dense tensorization basis methods [3] and a subscale recovery variant [1] for non-smooth data, Sparse tensorization methods[2] utilizing node-nested hierarchies, Sampling methods[4] for high-dimensional random variable spaces.

Statistical mechanics of two-dimensional shuffled foams: prediction of the correlation between geometry and topology.

PubMed

Durand, Marc; Käfer, Jos; Quilliet, Catherine; Cox, Simon; Talebi, Shirin Ataei; Graner, François

2011-10-14

We propose an analytical model for the statistical mechanics of shuffled two-dimensional foams with moderate bubble size polydispersity. It predicts without any adjustable parameters the correlations between the number of sides n of the bubbles (topology) and their areas A (geometry) observed in experiments and numerical simulations of shuffled foams. Detailed statistics show that in shuffled cellular patterns n correlates better with √A (as claimed by Desch and Feltham) than with A (as claimed by Lewis and widely assumed in the literature). At the level of the whole foam, standard deviations Δn and ΔA are in proportion. Possible applications include correlations of the detailed distributions of n and A, three-dimensional foams, and biological tissues.

Effects of the magnetic field direction on the Tsallis statistic

NASA Astrophysics Data System (ADS)

González-Casanova, Diego F.; Lazarian, A.; Cho, J.

2018-04-01

We extend the use of the Tsallis statistic to measure the differences in gas dynamics relative to the mean magnetic field present from natural eddy-type motions existing in magnetohydrodynamical (MHD) turbulence. The variation in gas dynamics was estimated using the Tsallis parameters on the incremental probability distribution function of the observables (intensity and velocity centroid) obtained from compressible MHD simulations. We find that the Tsallis statistic is susceptible to the anisotropy produced by the magnetic field, even when anisotropy is present the Tsallis statistic can be used to determine MHD parameters such as the Sonic Mach number. We quantize the goodness of the Tsallis parameters using the coefficient of determination to measure the differences in the gas dynamics. These parameters also determine the level of magnetization and compressibility of the medium. To further simulate realistic spectroscopic observational data, we introduced smoothing, noise, and cloud boundaries to the MHD simulations.

Statistical Signal Process in R Language in the Pharmacovigilance Programme of India.

PubMed

Kumar, Aman; Ahuja, Jitin; Shrivastava, Tarani Prakash; Kumar, Vipin; Kalaiselvan, Vivekanandan

2018-05-01

The Ministry of Health & Family Welfare, Government of India, initiated the Pharmacovigilance Programme of India (PvPI) in July 2010. The purpose of the PvPI is to collect data on adverse reactions due to medications, analyze it, and use the reference to recommend informed regulatory intervention, besides communicating the risk to health care professionals and the public. The goal of the present study was to apply statistical tools to find the relationship between drugs and ADRs for signal detection by R programming. Four statistical parameters were proposed for quantitative signal detection. These 4 parameters are IC 025 , PRR and PRR lb , chi-square, and N 11 ; we calculated these 4 values using R programming. We analyzed 78,983 drug-ADR combinations, and the total count of drug-ADR combination was 4,20,060. During the calculation of the statistical parameter, we use 3 variables: (1) N 11 (number of counts), (2) N 1. (Drug margin), and (3) N .1 (ADR margin). The structure and calculation of these 4 statistical parameters in R language are easily understandable. On the basis of the IC value (IC value >0), out of the 78,983 drug-ADR combination (drug-ADR combination), we found the 8,667 combinations to be significantly associated. The calculation of statistical parameters in R language is time saving and allows to easily identify new signals in the Indian ICSR (Individual Case Safety Reports) database.

Comparative Evaluation of Platelet-Rich Fibrin Biomaterial and Open Flap Debridement in the Treatment of Two and Three Wall Intrabony Defects

PubMed Central

Ajwani, Himanshu; Shetty, Sharath; Gopalakrishnan, Dharmarajan; Kathariya, Rahul; Kulloli, Anita; Dolas, R S; Pradeep, A R

2015-01-01

Background: Platelet-rich concentrates are the most widely used regenerative biomaterials. Stimulation and acceleration of soft and hard tissue healing are due to local and continuous delivery of growth factors and proteins, mimicking the needs of the physiological wound healing and reparative tissue processes. This article aims to evaluate the clinical efficacy of open flap debridement (OFD) with or without platelet-rich fibrin (PRF) in the treatment of intrabony defects. Materials and Methods: Twenty subjects with forty intrabony defects were treated with either autologous PRF with open-flap debridement (test, n = 20) or open-flap debridement alone (control, n = 20). Soft tissue parameters included: Plaque index, sulcus bleeding index, probing depth, relative attachment level and gingival marginal level (GML). The hard tissue parameters included-distances from: Cement enamel junction to the base of the defect (CEJ-BOD): Alveolar crest to the base of the defect (AC-BOD): And CEJ to AC. The parameters were recorded at baseline and at 9 months postoperatively calculated using standardized radiographs by image-analysis software. Results: Statistically significant (0.005*) intragroup improvements were seen with all the hard and soft parameters in both test and control groups, except for GML. Statistically significant improvements were seen with the mean defect fill (CEJ-BOD and AC-BOD) (P = 0.003*) when intergroup comparisons were made. Conclusions: Adjunctive use of PRF with OFD significantly improves defect fill when compared to OFD alone. PRF has consistently been showing regenerative potential; it is simple, easy and inexpensive biomaterial compared with bone grafts. PMID:25954068

Parameter estimation method that directly compares gravitational wave observations to numerical relativity

NASA Astrophysics Data System (ADS)

Lange, J.; O'Shaughnessy, R.; Boyle, M.; Calderón Bustillo, J.; Campanelli, M.; Chu, T.; Clark, J. A.; Demos, N.; Fong, H.; Healy, J.; Hemberger, D. A.; Hinder, I.; Jani, K.; Khamesra, B.; Kidder, L. E.; Kumar, P.; Laguna, P.; Lousto, C. O.; Lovelace, G.; Ossokine, S.; Pfeiffer, H.; Scheel, M. A.; Shoemaker, D. M.; Szilagyi, B.; Teukolsky, S.; Zlochower, Y.

2017-11-01

We present and assess a Bayesian method to interpret gravitational wave signals from binary black holes. Our method directly compares gravitational wave data to numerical relativity (NR) simulations. In this study, we present a detailed investigation of the systematic and statistical parameter estimation errors of this method. This procedure bypasses approximations used in semianalytical models for compact binary coalescence. In this work, we use the full posterior parameter distribution for only generic nonprecessing binaries, drawing inferences away from the set of NR simulations used, via interpolation of a single scalar quantity (the marginalized log likelihood, ln L ) evaluated by comparing data to nonprecessing binary black hole simulations. We also compare the data to generic simulations, and discuss the effectiveness of this procedure for generic sources. We specifically assess the impact of higher order modes, repeating our interpretation with both l ≤2 as well as l ≤3 harmonic modes. Using the l ≤3 higher modes, we gain more information from the signal and can better constrain the parameters of the gravitational wave signal. We assess and quantify several sources of systematic error that our procedure could introduce, including simulation resolution and duration; most are negligible. We show through examples that our method can recover the parameters for equal mass, zero spin, GW150914-like, and unequal mass, precessing spin sources. Our study of this new parameter estimation method demonstrates that we can quantify and understand the systematic and statistical error. This method allows us to use higher order modes from numerical relativity simulations to better constrain the black hole binary parameters.

The prognostic value of clinical characteristics and parameters of cerebrospinal fluid hydrodynamics in shunting for idiopathic normal pressure hydrocephalus.

PubMed

Delwel, E J; de Jong, D A; Avezaat, C J J

2005-10-01

It is difficult to predict which patients with symptoms and radiological signs of normal pressure hydrocephalus (NPH) will benefit from a shunting procedure and which patients will not. Risk of this procedure is also higher in patients with NPH than in the overall population of hydrocephalic patients. The aim of this study is to investigate which clinical characteristics, CT parameters and parameters of cerebrospinal fluid dynamics could predict improvement after shunting. Eighty-three consecutive patients with symptoms and radiological signs of NPH were included in a prospective study. Parameters of the cerebrospinal fluid dynamics were measured by calculation of computerised data obtained by a constant-flow lumbar infusion test. Sixty-six patients considered candidates for surgery were treated with a medium-pressure Spitz-Holter valve; in seventeen patients a shunting procedure was not considered indicated. Clinical and radiological follow-up was performed for at least one year postoperatively. The odds ratio, the sensitivity and specificity as well as the positive and negative predictive value of individual and combinations of measured parameters did not show a statistically significant relation to clinical improvement after shunting. We conclude that neither individual parameters nor combinations of measured parameters show any statistically significant relation to clinical improvement following shunting procedures in patients suspected of NPH. We suggest restricting the term normal pressure hydrocephalus to cases that improve after shunting and using the term normal pressure hydrocephalus syndrome for patients suspected of NPH and for patients not improving after implantation of a proven well-functioning shunt.

ModelTest Server: a web-based tool for the statistical selection of models of nucleotide substitution online

PubMed Central

Posada, David

2006-01-01

ModelTest server is a web-based application for the selection of models of nucleotide substitution using the program ModelTest. The server takes as input a text file with likelihood scores for the set of candidate models. Models can be selected with hierarchical likelihood ratio tests, or with the Akaike or Bayesian information criteria. The output includes several statistics for the assessment of model selection uncertainty, for model averaging or to estimate the relative importance of model parameters. The server can be accessed at . PMID:16845102

Model Parameter Variability for Enhanced Anaerobic Bioremediation of DNAPL Source Zones

NASA Astrophysics Data System (ADS)

Mao, X.; Gerhard, J. I.; Barry, D. A.

2005-12-01

The objective of the Source Area Bioremediation (SABRE) project, an international collaboration of twelve companies, two government agencies and three research institutions, is to evaluate the performance of enhanced anaerobic bioremediation for the treatment of chlorinated ethene source areas containing dense, non-aqueous phase liquids (DNAPL). This 4-year, 5.7 million dollars research effort focuses on a pilot-scale demonstration of enhanced bioremediation at a trichloroethene (TCE) DNAPL field site in the United Kingdom, and includes a significant program of laboratory and modelling studies. Prior to field implementation, a large-scale, multi-laboratory microcosm study was performed to determine the optimal system properties to support dehalogenation of TCE in site soil and groundwater. This statistically-based suite of experiments measured the influence of key variables (electron donor, nutrient addition, bioaugmentation, TCE concentration and sulphate concentration) in promoting the reductive dechlorination of TCE to ethene. As well, a comprehensive biogeochemical numerical model was developed for simulating the anaerobic dehalogenation of chlorinated ethenes. An appropriate (reduced) version of this model was combined with a parameter estimation method based on fitting of the experimental results. Each of over 150 individual microcosm calibrations involved matching predicted and observed time-varying concentrations of all chlorinated compounds. This study focuses on an analysis of this suite of fitted model parameter values. This includes determining the statistical correlation between parameters typically employed in standard Michaelis-Menten type rate descriptions (e.g., maximum dechlorination rates, half-saturation constants) and the key experimental variables. The analysis provides insight into the degree to which aqueous phase TCE and cis-DCE inhibit dechlorination of less-chlorinated compounds. Overall, this work provides a database of the numerical modelling parameters typically employed for simulating TCE dechlorination relevant for a range of system conditions (e.g, bioaugmented, high TCE concentrations, etc.). The significance of the obtained variability of parameters is illustrated with one-dimensional simulations of enhanced anaerobic bioremediation of residual TCE DNAPL.

Measurements of Time-Dependent CP-Asymmetry Parameters in B Meson Decays to η' K 0 and of Branching Fractions of SU(3) Related Modes with BaBar Experiment at SLAC

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

Biassoni, Pietro

2009-01-01

In this thesis work we have measured the following upper limits at 90% of confidence level, for B meson decays (in units of 10 -6), using a statistics of 465.0 x 10 6 Bmore » $$\\bar{B}$$ pairs: β(B 0 → ηK 0) < 1.6 β(B 0 → ηη) < 1.4 β(B 0 → η'η') < 2.1 β(B 0 → ηΦ) < 0.52 β(B 0 → ηω) < 1.6 β(B 0 → η'Φ) < 1.2 β(B 0 → η'ω) < 1.7 We have no observation of any decay mode, statistical significance for our measurements is in the range 1.3-3.5 standard deviation. We have a 3.5σ evidence for B → ηω and a 3.1 σ evidence for B → η'ω. The absence of observation of the B 0 → ηK 0 open an issue related to the large difference compared to the charged mode B + → ηK + branching fraction, which is measured to be 3.7 ± 0.4 ± 0.1 [118]. Our results represent substantial improvements of the previous ones [109, 110, 111] and are consistent with theoretical predictions. All these results were presented at Flavor Physics and CP Violation (FPCP) 2008 Conference, that took place in Taipei, Taiwan. They will be soon included into a paper to be submitted to Physical Review D. For time-dependent analysis, we have reconstructed 1820 ± 48 flavor-tagged B 0 → η'K 0 events, using the final BABAR statistic of 467.4 x 10 6 B$$\\bar{B}$$ pairs. We use these events to measure the time-dependent asymmetry parameters S and C. We find S = 0.59 ± 0.08 ± 0.02, and C = -0.06 ± 0.06 ± 0.02. A non-zero value of C would represent a directly CP non-conserving component in B 0 → η'K 0, while S would be equal to sin2β measured in B 0 → J/ΨK s 0 [108], a mixing-decay interference effect, provided the decay is dominated by amplitudes of a single weak phase. The new measured value of S can be considered in agreement with the expectations of the 'Standard Model', inside the experimental and theoretical uncertainties. Inconsistency of our result for S with CP conservation (S = 0) has a significance of 7.1 standard deviations (statistical and systematics included). Our result for the direct-CP violation parameter C is 0.9 standard deviations from zero (statistical and systematics included). Our results are in agreement with the previous ones [18]. Despite the statistics is only 20% larger than the one used in previous measurement, we improved of 20% the error on S and of 14% the error on C. This error is the smaller ever achieved, by both BABAR and Belle, in Time-Dependent CP Violation Parameters measurement is a b → s transition.« less

The impact of varicocelectomy on sperm parameters: a meta-analysis.

PubMed

Schauer, Ingrid; Madersbacher, Stephan; Jost, Romy; Hübner, Wilhelm Alexander; Imhof, Martin

2012-05-01

We determined the impact of 3 surgical techniques (high ligation, inguinal varicocelectomy and the subinguinal approach) for varicocelectomy on sperm parameters (count and motility) and pregnancy rates. By searching the literature using MEDLINE and the Cochrane Library with the last search performed in February 2011, focusing on the last 20 years, a total of 94 articles published between 1975 and 2011 reporting on sperm parameters before and after varicocelectomy were identified. Inclusion criteria for this meta-analysis were at least 2 semen analyses (before and 3 or more months after the procedure), patient age older than 19 years, clinical subfertility and/or abnormal semen parameters, and a clinically palpable varicocele. To rule out skewing factors a bias analysis was performed, and statistical analysis was done with RevMan5(®) and SPSS 15.0(®). A total of 14 articles were included in the statistical analysis. All 3 surgical approaches led to significant or highly significant postoperative improvement of both parameters with only slight numeric differences among the techniques. This difference did not reach statistical significance for sperm count (p = 0.973) or sperm motility (p = 0.372). After high ligation surgery sperm count increased by 10.85 million per ml (p = 0.006) and motility by 6.80% (p <0.00001) on the average. Inguinal varicocelectomy led to an improvement in sperm count of 7.17 million per ml (p <0.0001) while motility changed by 9.44% (p = 0.001). Subinguinal varicocelectomy provided an increase in sperm count of 9.75 million per ml (p = 0.002) and sperm motility by 12.25% (p = 0.001). Inguinal varicocelectomy showed the highest pregnancy rate of 41.48% compared to 26.90% and 26.56% after high ligation and subinguinal varicocelectomy, respectively, and the difference was statistically significant (p = 0.035). This meta-analysis suggests that varicocelectomy leads to significant improvements in sperm count and motility regardless of surgical technique, with the inguinal approach offering the highest pregnancy rate. Copyright © 2012 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

The platelet activating factor acetyl hydrolase, oxidized low-density lipoprotein, paraoxonase 1 and arylesterase levels in treated and untreated patients with polycystic ovary syndrome.

PubMed

Carlioglu, Ayse; Kaygusuz, Ikbal; Karakurt, Feridun; Gumus, Ilknur Inegol; Uysal, Aysel; Kasapoglu, Benan; Armutcu, Ferah; Uysal, Sema; Keskin, Esra Aktepe; Koca, Cemile

2014-11-01

To evaluate the platelet activating factor acetyl hydrolyze (PAF-AH), oxidized low-density lipoprotein (ox-LDL), paraoxonase 1 (PON1), arylesterase (ARE) levels and the effects of metformin and Diane-35 (ethinyl oestradiol + cyproterone acetate) therapies on these parameters and to determine the PON1 polymorphisms among PCOS patients. Ninety patients with PCOS, age 30, and body mass index-matched healthy controls were included in the study. Patients were divided into three groups: metformin treatment, Diane-35 treatment and no medication groups. The treatment with metformin or Diane-35 was continued for 6 months and all subjects were evaluated with clinical and biochemical parameters 6 months later. One-way Anova test, t test and non-parametric Mann-Whitney U tests were used for statistical analysis. PAF-AH and ox-LDL levels were statistically significantly higher in untreated PCOS patients than controls, and they were statistically significantly lower in patients treated with metformin or Diane-35 than untreated PCOS patients. In contrast, there were lower PON1 (not statistically significant) and ARE (statistically significant) levels in untreated PCOS patients than the control group and they significantly increased after metformin and Diane-35 treatments. In PCOS patients serum PON1 levels for QQ, QR and RR phenotypes were statistically significantly lower than the control group. In patients with PCOS, proatherogenic markers increase. The treatment of PCOS with metformin or Diane-35 had positive effects on lipid profile, increased PON1 level, which is a protector from atherosclerosis and decreased the proatherogenic PAF-AH and ox-LDL levels.

Measuring the statistical validity of summary meta‐analysis and meta‐regression results for use in clinical practice

PubMed Central

Riley, Richard D.

2017-01-01

An important question for clinicians appraising a meta‐analysis is: are the findings likely to be valid in their own practice—does the reported effect accurately represent the effect that would occur in their own clinical population? To this end we advance the concept of statistical validity—where the parameter being estimated equals the corresponding parameter for a new independent study. Using a simple (‘leave‐one‐out’) cross‐validation technique, we demonstrate how we may test meta‐analysis estimates for statistical validity using a new validation statistic, Vn, and derive its distribution. We compare this with the usual approach of investigating heterogeneity in meta‐analyses and demonstrate the link between statistical validity and homogeneity. Using a simulation study, the properties of Vn and the Q statistic are compared for univariate random effects meta‐analysis and a tailored meta‐regression model, where information from the setting (included as model covariates) is used to calibrate the summary estimate to the setting of application. Their properties are found to be similar when there are 50 studies or more, but for fewer studies Vn has greater power but a higher type 1 error rate than Q. The power and type 1 error rate of Vn are also shown to depend on the within‐study variance, between‐study variance, study sample size, and the number of studies in the meta‐analysis. Finally, we apply Vn to two published meta‐analyses and conclude that it usefully augments standard methods when deciding upon the likely validity of summary meta‐analysis estimates in clinical practice. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. PMID:28620945

Uncertainty quantification and risk analyses of CO2 leakage in heterogeneous geological formations

NASA Astrophysics Data System (ADS)

Hou, Z.; Murray, C. J.; Rockhold, M. L.

2012-12-01

A stochastic sensitivity analysis framework is adopted to evaluate the impact of spatial heterogeneity in permeability on CO2 leakage risk. The leakage is defined as the total mass of CO2 moving into the overburden through the caprock-overburden interface, in both gaseous and liquid (dissolved) phases. The entropy-based framework has the ability to quantify the uncertainty associated with the input parameters in the form of prior pdfs (probability density functions). Effective sampling of the prior pdfs enables us to fully explore the parameter space and systematically evaluate the individual and combined effects of the parameters of interest on CO2 leakage risk. The parameters that are considered in the study include: mean, variance, and horizontal to vertical spatial anisotropy ratio for caprock permeability, and those same parameters for reservoir permeability. Given the sampled spatial variogram parameters, multiple realizations of permeability fields were generated using GSLIB subroutines. For each permeability field, a numerical simulator, STOMP, (in the water-salt-CO2-energy operational mode) is used to simulate the CO2 migration within the reservoir and caprock up to 50 years after injection. Due to intensive computational demand, we run both a scalable version simulator eSTOMP and serial STOMP on various supercomputers. We then perform statistical analyses and summarize the relationships between the parameters of interest (mean/variance/anisotropy ratio of caprock and reservoir permeability) and CO2 leakage ratio. We also present the effects of those parameters on CO2 plume radius and reservoir injectivity. The statistical analysis provides a reduced order model that can be used to estimate the impact of heterogeneity on caprock leakage.

Ground-Based Telescope Parametric Cost Model

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Rowell, Ginger Holmes

2004-01-01

A parametric cost model for ground-based telescopes is developed using multi-variable statistical analysis, The model includes both engineering and performance parameters. While diameter continues to be the dominant cost driver, other significant factors include primary mirror radius of curvature and diffraction limited wavelength. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e.. multi-telescope phased-array systems). Additionally, single variable models based on aperture diameter are derived. This analysis indicates that recent mirror technology advances have indeed reduced the historical telescope cost curve.

Global tilt and lumbar lordosis index: two parameters correlating with health-related quality of life scores-but how do they truly impact disability?

PubMed

Boissière, Louis; Takemoto, Mitsuru; Bourghli, Anouar; Vital, Jean-Marc; Pellisé, Ferran; Alanay, Ahmet; Yilgor, Caglar; Acaroglu, Emre; Perez-Grueso, Francisco Javier; Kleinstück, Frank; Obeid, Ibrahim

2017-04-01

Many radiological parameters have been reported to correlate with patient's disability including sagittal vertical axis (SVA), pelvic tilt (PT), and pelvic incidence minus lumbar lordosis (PI-LL). European literature reports other parameters such as lumbar lordosis index (LLI) and the global tilt (GT). If most parameters correlate with health-related quality of life scores (HRQLs), their impact on disability remains unclear. This study aimed to validate these parameters by investigating their correlation with HRQLs. It also aimed to evaluate the relationship between each of these sagittal parameters and HRQLs to fully understand the impact in adult spinal deformity management. A retrospective review of a multicenter, prospective database was carried out. The database inclusion criteria were adults (>18 years old) presenting any of the following radiographic parameters: scoliosis (Cobb ≥20°), SVA ≥5 cm, thoracic kyphosis ≥60° or PT ≥25°. All patients with complete data at baseline were included. Health-related quality of life scores, demographic variables (DVs), and radiographic parameters were collected at baseline. Differences in HRQLs among groups of each DV were assessed with analyses of variance. Correlations between radiographic variables and HRQLs were assessed using the Spearman rank correlation. Multivariate linear regression models were fitted for each of the HRQLs (Oswestry Disability Index [ODI], Scoliosis Research Society-22 subtotal score, or physical component summaries) with sagittal parameters and covariants as independent variables. A p<.05 value was considered statistically significant. Among a total of 755 included patients (mean age, 52.1 years), 431 were non-surgical candidates and 324 were surgical candidates. Global tilt and LLI significantly correlated with HRQLs (r=0.4 and -0.3, respectively) for univariate analysis. Demographic variables such as age, gender, body mass index, past surgery, and surgical or non-surgical candidate were significant predictors of ODI score. The likelihood ratio tests for the addition of the sagittal parameters showed that SVA, GT, T1 sagittal tilt, PI-LL, and LLI were statistically significant predictors for ODI score even adjusted for covariates. The differences of R 2 values from Model 1 were 1.5% at maximum, indicating that the addition of sagittal parameters to the reference model increased only 1.5% of the variance of ODI explained by the models. GT and LLI appear to be independent radiographic parameters impacting ODI variance. If most of the parameters described in the literature are correlated with ODI, the impact of these radiographic parameters is less than 2% of ODI variance, whereas 40% are explained by DVs. The importance of radiographic parameters lies more on their purpose to describe and understand the malalignment mechanisms than their univariate correlation with HRQLs. Copyright © 2016 Elsevier Inc. All rights reserved.

THERMUS—A thermal model package for ROOT

NASA Astrophysics Data System (ADS)

Wheaton, S.; Cleymans, J.; Hauer, M.

2009-01-01

THERMUS is a package of C++ classes and functions allowing statistical-thermal model analyses of particle production in relativistic heavy-ion collisions to be performed within the ROOT framework of analysis. Calculations are possible within three statistical ensembles; a grand-canonical treatment of the conserved charges B, S and Q, a fully canonical treatment of the conserved charges, and a mixed-canonical ensemble combining a canonical treatment of strangeness with a grand-canonical treatment of baryon number and electric charge. THERMUS allows for the assignment of decay chains and detector efficiencies specific to each particle yield, which enables sensible fitting of model parameters to experimental data. Program summaryProgram title: THERMUS, version 2.1 Catalogue identifier: AEBW_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEBW_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 17 152 No. of bytes in distributed program, including test data, etc.: 93 581 Distribution format: tar.gz Programming language: C++ Computer: PC, Pentium 4, 1 GB RAM (not hardware dependent) Operating system: Linux: FEDORA, RedHat, etc. Classification: 17.7 External routines: Numerical Recipes in C [1], ROOT [2] Nature of problem: Statistical-thermal model analyses of heavy-ion collision data require the calculation of both primordial particle densities and contributions from resonance decay. A set of thermal parameters (the number depending on the particular model imposed) and a set of thermalized particles, with their decays specified, is required as input to these models. The output is then a complete set of primordial thermal quantities for each particle, together with the contributions to the final particle yields from resonance decay. In many applications of statistical-thermal models it is required to fit experimental particle multiplicities or particle ratios. In such analyses, the input is a set of experimental yields and ratios, a set of particles comprising the assumed hadron resonance gas formed in the collision and the constraints to be placed on the system. The thermal model parameters consistent with the specified constraints leading to the best-fit to the experimental data are then output. Solution method: THERMUS is a package designed for incorporation into the ROOT [2] framework, used extensively by the heavy-ion community. As such, it utilizes a great deal of ROOT's functionality in its operation. ROOT features used in THERMUS include its containers, the wrapper TMinuit implementing the MINUIT fitting package, and the TMath class of mathematical functions and routines. Arguably the most useful feature is the utilization of CINT as the control language, which allows interactive access to the THERMUS objects. Three distinct statistical ensembles are included in THERMUS, while additional options to include quantum statistics, resonance width and excluded volume corrections are also available. THERMUS provides a default particle list including all mesons (up to the K4∗ (2045)) and baryons (up to the Ω) listed in the July 2002 Particle Physics Booklet [3]. For each typically unstable particle in this list, THERMUS includes a text-file listing its decays. With thermal parameters specified, THERMUS calculates primordial thermal densities either by performing numerical integrations or else, in the case of the Boltzmann approximation without resonance width in the grand-canonical ensemble, by evaluating Bessel functions. Particle decay chains are then used to evaluate experimental observables (i.e. particle yields following resonance decay). Additional detector efficiency factors allow fine-tuning of the model predictions to a specific detector arrangement. When parameters are required to be constrained, use is made of the 'Numerical Recipes in C' [1] function which applies the Broyden globally convergent secant method of solving nonlinear systems of equations. Since the NRC software is not freely-available, it has to be purchased by the user. THERMUS provides the means of imposing a large number of constraints on the chosen model (amongst others, THERMUS can fix the baryon-to-charge ratio of the system, the strangeness density of the system and the primordial energy per hadron). Fits to experimental data are accomplished in THERMUS by using the ROOT TMinuit class. In its default operation, the standard χ function is minimized, yielding the set of best-fit thermal parameters. THERMUS allows the assignment of separate decay chains to each experimental input. In this way, the model is able to match the specific feed-down corrections of a particular data set. Running time: Depending on the analysis required, run-times vary from seconds (for the evaluation of particle multiplicities given a set of parameters) to several minutes (for fits to experimental data subject to constraints). References:W.H. Press, S.A. Teukolsky, W.T. Vetterling, B.P. Flannery, Numerical Recipes in C: The Art of Scientific Computing, Cambridge University Press, Cambridge, 2002. R. Brun, F. Rademakers, Nucl. Inst. Meth. Phys. Res. A 389 (1997) 81. See also http://root.cern.ch/. K. Hagiwara et al., Phys. Rev. D 66 (2002) 010001.

Sub-poissonian photon statistics in the coherent state Jaynes-Cummings model in non-resonance

NASA Astrophysics Data System (ADS)

Zhang, Jia-tai; Fan, An-fu

1992-03-01

We study a model with a two-level atom (TLA) non-resonance interacting with a single-mode quantized cavity field (QCF). The photon number probability function, the mean photon number and Mandel's fluctuation parameter are calculated. The sub-Poissonian distributions of the photon statistics are obtained in non-resonance interaction. This statistical properties are strongly dependent on the detuning parameters.

Distribution of water quality parameters in Dhemaji district, Assam (India).

PubMed

Buragohain, Mridul; Bhuyan, Bhabajit; Sarma, H P

2010-07-01

The primary objective of this study is to present a statistically significant water quality database of Dhemaji district, Assam (India) with special reference to pH, fluoride, nitrate, arsenic, iron, sodium and potassium. 25 water samples collected from different locations of five development blocks in Dhemaji district have been studied separately. The implications presented are based on statistical analyses of the raw data. Normal distribution statistics and reliability analysis (correlation and covariance matrix) have been employed to find out the distribution pattern, localisation of data, and other related information. Statistical observations show that all the parameters under investigation exhibit non uniform distribution with a long asymmetric tail either on the right or left side of the median. The width of the third quartile was consistently found to be more than the second quartile for each parameter. Differences among mean, mode and median, significant skewness and kurtosis value indicate that the distribution of various water quality parameters in the study area is widely off normal. Thus, the intrinsic water quality is not encouraging due to unsymmetrical distribution of various water quality parameters in the study area.

Relationship of body weight parameters with the incidence of common spontaneous tumors in Tg.rasH2 mice.

PubMed

Paranjpe, Madhav G; Denton, Melissa D; Vidmar, Tom J; Elbekai, Reem H

2014-10-01

The mechanistic relationship between increased food consumption, increased body weights, and increased incidence of tumors has been well established in 2-year rodent models. Body weight parameters such as initial body weights, terminal body weights, food consumption, and the body weight gains in grams and percentages were analyzed to determine whether such relationship exists between these parameters with the incidence of common spontaneous tumors in Tg.rasH2 mice. None of these body weight parameters had any statistically significant relationship with the incidence of common spontaneous tumors in Tg.rasH2 males, namely lung tumors, splenic hemangiosarcomas, nonsplenic hemangiosarcomas, combined incidence of all hemangiosarcomas, and Harderian gland tumors. These parameters also did not have any statistically significant relationship with the incidence of lung and Harderian gland tumors in females. However, in females, increased initial body weights did have a statistically significant relationship with the nonsplenic hemangiosarcomas, and increased terminal body weights did have a statistically significant relationship with the incidence of splenic hemangiosarcomas, nonsplenic hemangiosarcomas, and the combined incidence of all hemangiosarcomas. In addition, increased body weight gains in grams and percentages had a statistically significant relationship with the combined incidence of all hemangiosarcomas in females, but not separately with splenic and nonsplenic hemangiosarcomas. © 2013 by The Author(s).

Statistical Distributions of Optical Flares from Gamma-Ray Bursts

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

Yi, Shuang-Xi; Yu, Hai; Wang, F. Y.

2017-07-20

We statistically study gamma-ray burst (GRB) optical flares from the Swift /UVOT catalog. We compile 119 optical flares, including 77 flares with redshift measurements. Some tight correlations among the timescales of optical flares are found. For example, the rise time is correlated with the decay time, and the duration time is correlated with the peak time of optical flares. These two tight correlations indicate that longer rise times are associated with longer decay times of optical flares and also suggest that broader optical flares peak at later times, which are consistent with the corresponding correlations of X-ray flares. We alsomore » study the frequency distributions of optical flare parameters, including the duration time, rise time, decay time, peak time, and waiting time. Similar power-law distributions for optical and X-ray flares are found. Our statistic results imply that GRB optical flares and X-ray flares may share the similar physical origin, and both of them are possibly related to central engine activities.« less

VizieR Online Data Catalog: Fundamental parameters of Kepler stars (Silva Aguirre+, 2015)

NASA Astrophysics Data System (ADS)

Silva Aguirre, V.; Davies, G. R.; Basu, S.; Christensen-Dalsgaard, J.; Creevey, O.; Metcalfe, T. S.; Bedding, T. R.; Casagrande, L.; Handberg, R.; Lund, M. N.; Nissen, P. E.; Chaplin, W. J.; Huber, D.; Serenelli, A. M.; Stello, D.; van Eylen, V.; Campante, T. L.; Elsworth, Y.; Gilliland, R. L.; Hekker, S.; Karoff, C.; Kawaler, S. D.; Kjeldsen, H.; Lundkvist, M. S.

2016-02-01

Our sample has been extracted from the 77 exoplanet host stars presented in Huber et al. (2013, Cat. J/ApJ/767/127). We have made use of the full time-base of observations from the Kepler satellite to uniformly determine precise fundamental stellar parameters, including ages, for a sample of exoplanet host stars where high-quality asteroseismic data were available. We devised a Bayesian procedure flexible in its input and applied it to different grids of models to study systematics from input physics and extract statistically robust properties for all stars. (4 data files).

Wash-out in N{sub 2}-dominated leptogenesis

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

Hahn-Woernle, F., E-mail: fhahnwo@mppmu.mpg.de

2010-08-01

We study the wash-out of a cosmological baryon asymmetry produced via leptogenesis by subsequent interactions. Therefore we focus on a scenario in which a lepton asymmetry is established in the out-of-equilibrium decays of the next-to-lightest right-handed neutrino. We apply the full classical Boltzmann equations without the assumption of kinetic equilibrium and including all quantum statistical factors to calculate the wash-out of the lepton asymmetry by interactions of the lightest right-handed state. We include scattering processes with top quarks in our analysis. This is of particular interest since the wash-out is enhanced by scatterings and the use of mode equations withmore » quantum statistical distribution functions. In this way we provide a restriction on the parameter space for this scenario.« less

Peri-implant soft tissue colour around titanium and zirconia abutments: a prospective randomized controlled clinical study.

PubMed

Cosgarea, Raluca; Gasparik, Cristina; Dudea, Diana; Culic, Bogdan; Dannewitz, Bettina; Sculean, Anton

2015-05-01

To objectively determine the difference in colour between the peri-implant soft tissue at titanium and zirconia abutments. Eleven patients, each with two contralaterally inserted osteointegrated dental implants, were included in this study. The implants were restored either with titanium abutments and porcelain-fused-to-metal crowns, or with zirconia abutments and ceramic crowns. Prior and after crown cementation, multi-spectral images of the peri-implant soft tissues and the gingiva of the neighbouring teeth were taken with a colorimeter. The colour parameters L*, a*, b*, c* and the colour differences ΔE were calculated. Descriptive statistics, including non-parametric tests and correlation coefficients, were used for statistical analyses of the data. Compared to the gingiva of the neighbouring teeth, the peri-implant soft tissue around titanium and zirconia (test group), showed distinguishable ΔE both before and after crown cementation. Colour differences around titanium were statistically significant different (P = 0.01) only at 1 mm prior to crown cementation compared to zirconia. Compared to the gingiva of the neighbouring teeth, statistically significant (P < 0.01) differences were found for all colour parameter, either before or after crown cementation for both abutments; more significant differences were registered for titanium abutments. Tissue thickness correlated positively with c*-values for titanium at 1 mm and 2 mm from the gingival margin. Within their limits, the present data indicate that: (i) The peri-implant soft tissue around titanium and zirconia showed colour differences when compared to the soft tissue around natural teeth, and (ii) the peri-implant soft tissue around zirconia demonstrated a better colour match to the soft tissue at natural teeth than titanium. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The Tully-Fisher relation for flat galaxies

NASA Astrophysics Data System (ADS)

Makarov, D. I.; Zaitseva, N. A.; Bizyaev, D. V.

2018-06-01

We construct a multiparametric Tully-Fisher (TF) relation for a large sample of edge-on galaxies from the Revised Flat Galaxy Catalog using H I data from the EDD database and parameters from the EGIS catalog. We incorporate a variety of additional parameters including structural parameters of edge-on galaxies in different bandpasses. Besides the rotation curve maximum, only the H I-to-optical luminosity ratio and optical colours play a statistically significant role in the multiparametric TF relation. We are able to decrease the standard deviation of the multiparametric TF relation down to 0.32 mag, which is at the level of best modern samples of galaxies used for studies of the matter motion in the Universe via the TF-relation.

Identification of atypical flight patterns

NASA Technical Reports Server (NTRS)

Statler, Irving C. (Inventor); Ferryman, Thomas A. (Inventor); Amidan, Brett G. (Inventor); Whitney, Paul D. (Inventor); White, Amanda M. (Inventor); Willse, Alan R. (Inventor); Cooley, Scott K. (Inventor); Jay, Joseph Griffith (Inventor); Lawrence, Robert E. (Inventor); Mosbrucker, Chris (Inventor)

2005-01-01

Method and system for analyzing aircraft data, including multiple selected flight parameters for a selected phase of a selected flight, and for determining when the selected phase of the selected flight is atypical, when compared with corresponding data for the same phase for other similar flights. A flight signature is computed using continuous-valued and discrete-valued flight parameters for the selected flight parameters and is optionally compared with a statistical distribution of other observed flight signatures, yielding atypicality scores for the same phase for other similar flights. A cluster analysis is optionally applied to the flight signatures to define an optimal collection of clusters. A level of atypicality for a selected flight is estimated, based upon an index associated with the cluster analysis.

Information-Decay Pursuit of Dynamic Parameters in Student Models

DTIC Science & Technology

1994-04-01

simple worked-through example). Commercially available computer programs for structuring and using Bayesian inference include ERGO ( Noetic Systems...Tukey, J.W. (1977). Data analysis and Regression: A second course in statistics. Reading, MA: Addison-Wesley. Noetic Systems, Inc. (1991). ERGO...Naval Academy Division of Educational Studies Annapolis MD 21402-5002 Elmory Univerity Dr Janice Gifford 210 Fiabburne Bldg University of

Immunohistochemical expression of matrix metalloproteinase 13 in chronic periodontitis.

PubMed

Nagasupriya, Alapati; Rao, Donimukkala Bheemalingeswara; Ravikanth, Manyam; Kumar, Nalabolu Govind; Ramachandran, Cinnamanoor Rajmani; Saraswathi, Thillai Rajashekaran

2014-01-01

The extracellular matrix is a complex integrated system responsible for the physiologic properties of connective tissue. Collagen is the major extracellular component that is altered in pathologic conditions, mainly periodontitis. The destruction involves proteolytic enzymes, primarily matrix metalloproteinases (MMPs), which play a key role in mediating and regulating the connective tissue destruction in periodontitis. The study group included 40 patients with clinically diagnosed chronic periodontitis. The control group included 20 patients with clinically normal gingiva covering impacted third molars undergoing extraction or in areas where crown-lengthening procedures were performed. MMP-13 expression was demonstrated using immunohistochemistry in all the gingival biopsies, and the data were analyzed statistically. MMP-13 expression was observed more in chronic periodontitis when compared with normal gingiva. MMP-13 expression was expressed by fibroblasts, lymphocytes, macrophages, plasma cells, and basal cells of the sulcular epithelium. Comparative evaluation of all the clinical and histologic parameters with MMP-13 expression showed high statistical significance with Spearman correlation coefficient. Elevated levels of MMP-13 may play a role in the pathogenesis of chronic periodontitis. There is a direct correlation of increased expression of MMP-13 with various clinical and histologic parameters in disease severity.

A practical and systematic review of Weibull statistics for reporting strengths of dental materials

PubMed Central

Quinn, George D.; Quinn, Janet B.

2011-01-01

Objectives To review the history, theory and current applications of Weibull analyses sufficient to make informed decisions regarding practical use of the analysis in dental material strength testing. Data References are made to examples in the engineering and dental literature, but this paper also includes illustrative analyses of Weibull plots, fractographic interpretations, and Weibull distribution parameters obtained for a dense alumina, two feldspathic porcelains, and a zirconia. Sources Informational sources include Weibull's original articles, later articles specific to applications and theoretical foundations of Weibull analysis, texts on statistics and fracture mechanics and the international standards literature. Study Selection The chosen Weibull analyses are used to illustrate technique, the importance of flaw size distributions, physical meaning of Weibull parameters and concepts of “equivalent volumes” to compare measured strengths obtained from different test configurations. Conclusions Weibull analysis has a strong theoretical basis and can be of particular value in dental applications, primarily because of test specimen size limitations and the use of different test configurations. Also endemic to dental materials, however, is increased difficulty in satisfying application requirements, such as confirming fracture origin type and diligence in obtaining quality strength data. PMID:19945745

[Status and progress of stimulating parameters in acupuncture treatment of ischemic cerebrovascular disease].

PubMed

Wei, Yuan-yuan; Fan, Xiao-nong; Wang, Shu; Shi, Xue-min

2008-08-01

Acute ischemic cerebrovascular disease is one of the critical diseases seriously endangering human health. Acupuncture therapy, an effective treatment method for many types of disorders has been generally acknowledged. In recent years, many scientific researchers have studied the relationship between the effects of acupuncture in relieving cerebral ischemia-induced sequelae and the stimulating parameters. The acupuncture stimulating parameter includes the frequency of electroacupuncture (EA), the frequency of acupuncture treatment, and the acquired quantity of stimulation, etc for clinical patients and experimental animals. It was found that different stimulating parameters may have different efficacies. Current research results provide a good basis not only for analysis of the factors of acupuncture-produced effects, but also for determination of the optimal combination of stimulating parameters. However, acupuncture therapeutic effect involves multiple factors and multiple levels, and current quantitative acupuncture parameter researches have been mainly restricted to animal experiments. Hence, more researches in which statistics specialists take part are definitely needed.

Effects of suvorexant, an orexin receptor antagonist, on sleep parameters as measured by polysomnography in healthy men.

PubMed

Sun, Hong; Kennedy, William P; Wilbraham, Darren; Lewis, Nicole; Calder, Nicole; Li, Xiaodong; Ma, Junshui; Yee, Ka Lai; Ermlich, Susan; Mangin, Eric; Lines, Christopher; Rosen, Laura; Chodakewitz, Jeffrey; Murphy, Gail M

2013-02-01

Suvorexant (MK-4305) is an orexin receptor antagonist being developed for the treatment of insomnia. This report describes the effects of nighttime administration of suvorexant on polysomnography (PSG) sleep parameters in healthy young men. Randomized, double-blind, placebo-controlled, 4-period crossover PSG study, followed by an additional 5(th) period to assess pharmacokinetics. Sleep laboratory. Healthy young men between 18 and 45 years of age (22 enrolled, 19 completed). Periods 1-4: suvorexant (10 mg, 50 mg, or 100 mg) or placebo 1 h before nighttime PSG recording. Period 5: suvorexant 10 mg, 50 mg, or 100 mg. In Periods 1-4, overnight sleep parameters were recorded by PSG and next-morning residual effects were assessed by psychomotor performance tests and subjective assessments. Statistically significant sleep-promoting effects were observed with all doses of suvorexant compared to placebo. Suvorexant 50 mg and 100 mg significantly decreased latency to persistent sleep and wake after sleep onset time, and increased sleep efficiency. Suvorexant 10 mg significantly decreased wake after sleep onset time. There were no statistically significant effects of suvorexant on EEG frequency bands including delta (slow wave) activity based on power spectral analysis. Suvorexant was well tolerated. There was no evidence of next-day residual effects for suvorexant 10 mg. Suvorexant 50 mg statistically significantly reduced subjective alertness, and suvorexant 100 mg significantly increased reaction time and reduced subjective alertness. There were no statistically significant effects of any suvorexant dose on digit symbol substitution test performance. In Period 5, plasma samples of suvorexant were collected for pharmacokinetic evaluation. The median T(max) was 3 hours and apparent terminal t(½) was 9-13 hours. In healthy young men without sleep disorders, suvorexant promoted sleep with some evidence of residual effects at the highest doses.

Establishment of a center of excellence for applied mathematical and statistical research

NASA Technical Reports Server (NTRS)

Woodward, W. A.; Gray, H. L.

1983-01-01

The state of the art was assessed with regards to efforts in support of the crop production estimation problem and alternative generic proportion estimation techniques were investigated. Topics covered include modeling the greeness profile (Badhwarmos model), parameter estimation using mixture models such as CLASSY, and minimum distance estimation as an alternative to maximum likelihood estimation. Approaches to the problem of obtaining proportion estimates when the underlying distributions are asymmetric are examined including the properties of Weibull distribution.

Climate Considerations Of The Electricity Supply Systems In Industries

NASA Astrophysics Data System (ADS)

Asset, Khabdullin; Zauresh, Khabdullina

2014-12-01

The study is focused on analysis of climate considerations of electricity supply systems in a pellet industry. The developed analysis model consists of two modules: statistical data of active power losses evaluation module and climate aspects evaluation module. The statistical data module is presented as a universal mathematical model of electrical systems and components of industrial load. It forms a basis for detailed accounting of power loss from the voltage levels. On the basis of the universal model, a set of programs is designed to perform the calculation and experimental research. It helps to obtain the statistical characteristics of the power losses and loads of the electricity supply systems and to define the nature of changes in these characteristics. Within the module, several methods and algorithms for calculating parameters of equivalent circuits of low- and high-voltage ADC and SD with a massive smooth rotor with laminated poles are developed. The climate aspects module includes an analysis of the experimental data of power supply system in pellet production. It allows identification of GHG emission reduction parameters: operation hours, type of electrical motors, values of load factor and deviation of standard value of voltage.

The Global Signature of Ocean Wave Spectra

NASA Astrophysics Data System (ADS)

Portilla-Yandún, Jesús

2018-01-01

A global atlas of ocean wave spectra is developed and presented. The development is based on a new technique for deriving wave spectral statistics, which is applied to the extensive ERA-Interim database from European Centre of Medium-Range Weather Forecasts. Spectral statistics is based on the idea of long-term wave systems, which are unique and distinct at every geographical point. The identification of those wave systems allows their separation from the overall spectrum using the partition technique. Their further characterization is made using standard integrated parameters, which turn out much more meaningful when applied to the individual components than to the total spectrum. The parameters developed include the density distribution of spectral partitions, which is the main descriptor; the identified wave systems; the individual distribution of the characteristic frequencies, directions, wave height, wave age, seasonal variability of wind and waves; return periods derived from extreme value analysis; and crossing-sea probabilities. This information is made available in web format for public use at http://www.modemat.epn.edu.ec/#/nereo. It is found that wave spectral statistics offers the possibility to synthesize data while providing a direct and comprehensive view of the local and regional wave conditions.

Water Quality Sensing and Spatio-Temporal Monitoring Structure with Autocorrelation Kernel Methods.

PubMed

Vizcaíno, Iván P; Carrera, Enrique V; Muñoz-Romero, Sergio; Cumbal, Luis H; Rojo-Álvarez, José Luis

2017-10-16

Pollution on water resources is usually analyzed with monitoring campaigns, which consist of programmed sampling, measurement, and recording of the most representative water quality parameters. These campaign measurements yields a non-uniform spatio-temporal sampled data structure to characterize complex dynamics phenomena. In this work, we propose an enhanced statistical interpolation method to provide water quality managers with statistically interpolated representations of spatial-temporal dynamics. Specifically, our proposal makes efficient use of the a priori available information of the quality parameter measurements through Support Vector Regression (SVR) based on Mercer's kernels. The methods are benchmarked against previously proposed methods in three segments of the Machángara River and one segment of the San Pedro River in Ecuador, and their different dynamics are shown by statistically interpolated spatial-temporal maps. The best interpolation performance in terms of mean absolute error was the SVR with Mercer's kernel given by either the Mahalanobis spatial-temporal covariance matrix or by the bivariate estimated autocorrelation function. In particular, the autocorrelation kernel provides with significant improvement of the estimation quality, consistently for all the six water quality variables, which points out the relevance of including a priori knowledge of the problem.

Water Quality Sensing and Spatio-Temporal Monitoring Structure with Autocorrelation Kernel Methods

PubMed Central

Vizcaíno, Iván P.; Muñoz-Romero, Sergio; Cumbal, Luis H.

2017-01-01

Pollution on water resources is usually analyzed with monitoring campaigns, which consist of programmed sampling, measurement, and recording of the most representative water quality parameters. These campaign measurements yields a non-uniform spatio-temporal sampled data structure to characterize complex dynamics phenomena. In this work, we propose an enhanced statistical interpolation method to provide water quality managers with statistically interpolated representations of spatial-temporal dynamics. Specifically, our proposal makes efficient use of the a priori available information of the quality parameter measurements through Support Vector Regression (SVR) based on Mercer’s kernels. The methods are benchmarked against previously proposed methods in three segments of the Machángara River and one segment of the San Pedro River in Ecuador, and their different dynamics are shown by statistically interpolated spatial-temporal maps. The best interpolation performance in terms of mean absolute error was the SVR with Mercer’s kernel given by either the Mahalanobis spatial-temporal covariance matrix or by the bivariate estimated autocorrelation function. In particular, the autocorrelation kernel provides with significant improvement of the estimation quality, consistently for all the six water quality variables, which points out the relevance of including a priori knowledge of the problem. PMID:29035333

Statistical Properties of Echosignal Obtained from Human Dermis In Vivo

NASA Astrophysics Data System (ADS)

Piotrzkowska, Hanna; Litniewski, Jerzy; Nowicki, Andrzej; Szymańska, Elżbieta

The paper presents the classification of the healthy skin and the skin lesions (basal cell carcinoma and actinic keratosis), basing on the statistical parameters of the envelope of ultrasonic echoes. The envelope was modeled using Rayleigh and non-Rayleigh (K-distribution) statistics. Furthermore, the characteristic parameter of the K-distribution, the effective number of scatterers was investigated. Also the attenuation coefficient was used for the skin lesion assessment.

Optimal Regulation of Structural Systems with Uncertain Parameters.

DTIC Science & Technology

1981-02-02

been addressed, in part, by Statistical Energy Analysis . Moti- vated by a concern with high frequency vibration and acoustical- structural...Parameter Systems," AFOSR-TR-79-0753 (May, 1979). 25. R. H. Lyon, Statistical Energy Analysis of Dynamical Systems: Theory and Applications, (M.I.T...Press, Cambridge, Mass., 1975). 26. E. E. Ungar, " Statistical Energy Analysis of Vibrating Systems," Trans. ASME, J. Eng. Ind. 89, 626 (1967). 139 27

Robust functional statistics applied to Probability Density Function shape screening of sEMG data.

PubMed

Boudaoud, S; Rix, H; Al Harrach, M; Marin, F

2014-01-01

Recent studies pointed out possible shape modifications of the Probability Density Function (PDF) of surface electromyographical (sEMG) data according to several contexts like fatigue and muscle force increase. Following this idea, criteria have been proposed to monitor these shape modifications mainly using High Order Statistics (HOS) parameters like skewness and kurtosis. In experimental conditions, these parameters are confronted with small sample size in the estimation process. This small sample size induces errors in the estimated HOS parameters restraining real-time and precise sEMG PDF shape monitoring. Recently, a functional formalism, the Core Shape Model (CSM), has been used to analyse shape modifications of PDF curves. In this work, taking inspiration from CSM method, robust functional statistics are proposed to emulate both skewness and kurtosis behaviors. These functional statistics combine both kernel density estimation and PDF shape distances to evaluate shape modifications even in presence of small sample size. Then, the proposed statistics are tested, using Monte Carlo simulations, on both normal and Log-normal PDFs that mimic observed sEMG PDF shape behavior during muscle contraction. According to the obtained results, the functional statistics seem to be more robust than HOS parameters to small sample size effect and more accurate in sEMG PDF shape screening applications.

Compounding approach for univariate time series with nonstationary variances

NASA Astrophysics Data System (ADS)

Schäfer, Rudi; Barkhofen, Sonja; Guhr, Thomas; Stöckmann, Hans-Jürgen; Kuhl, Ulrich

2015-12-01

A defining feature of nonstationary systems is the time dependence of their statistical parameters. Measured time series may exhibit Gaussian statistics on short time horizons, due to the central limit theorem. The sample statistics for long time horizons, however, averages over the time-dependent variances. To model the long-term statistical behavior, we compound the local distribution with the distribution of its parameters. Here, we consider two concrete, but diverse, examples of such nonstationary systems: the turbulent air flow of a fan and a time series of foreign exchange rates. Our main focus is to empirically determine the appropriate parameter distribution for the compounding approach. To this end, we extract the relevant time scales by decomposing the time signals into windows and determine the distribution function of the thus obtained local variances.

Compounding approach for univariate time series with nonstationary variances.

PubMed

Schäfer, Rudi; Barkhofen, Sonja; Guhr, Thomas; Stöckmann, Hans-Jürgen; Kuhl, Ulrich

2015-12-01

A defining feature of nonstationary systems is the time dependence of their statistical parameters. Measured time series may exhibit Gaussian statistics on short time horizons, due to the central limit theorem. The sample statistics for long time horizons, however, averages over the time-dependent variances. To model the long-term statistical behavior, we compound the local distribution with the distribution of its parameters. Here, we consider two concrete, but diverse, examples of such nonstationary systems: the turbulent air flow of a fan and a time series of foreign exchange rates. Our main focus is to empirically determine the appropriate parameter distribution for the compounding approach. To this end, we extract the relevant time scales by decomposing the time signals into windows and determine the distribution function of the thus obtained local variances.

Noise level and MPEG-2 encoder statistics

NASA Astrophysics Data System (ADS)

Lee, Jungwoo

1997-01-01

Most software in the movie and broadcasting industries are still in analog film or tape format, which typically contains random noise that originated from film, CCD camera, and tape recording. The performance of the MPEG-2 encoder may be significantly degraded by the noise. It is also affected by the scene type that includes spatial and temporal activity. The statistical property of noise originating from camera and tape player is analyzed and the models for the two types of noise are developed. The relationship between the noise, the scene type, and encoder statistics of a number of MPEG-2 parameters such as motion vector magnitude, prediction error, and quant scale are discussed. This analysis is intended to be a tool for designing robust MPEG encoding algorithms such as preprocessing and rate control.

[How to start a neuroimaging study].

PubMed

Narumoto, Jin

2012-06-01

In order to help researchers understand how to start a neuroimaging study, several tips are described in this paper. These include 1) Choice of an imaging modality, 2) Statistical method, and 3) Interpretation of the results. 1) There are several imaging modalities available in clinical research. Advantages and disadvantages of each modality are described. 2) Statistical Parametric Mapping, which is the most common statistical software for neuroimaging analysis, is described in terms of parameter setting in normalization and level of significance. 3) In the discussion section, the region which shows a significant difference between patients and normal controls should be discussed in relation to the neurophysiology of the disease, making reference to previous reports from neuroimaging studies in normal controls, lesion studies and animal studies. A typical pattern of discussion is described.

A comparative study of hematological parameters of α and β thalassemias in a high prevalence zone: Saudi Arabia

PubMed Central

Mehdi, Syed Riaz; Al Dahmash, Badr Abdullah

2011-01-01

BACKGROUND AND AIMS: Saudi Arabia falls in the high prevalent zone of αα and β thalassemias. Early screening for the type of thalassemia is essential for further investigations and management. The study was carried out to differentiate the type of thalassemia based on red cell indices and other hematological parameters. MATERIALS AND METHODS: The study was carried out on 991 clinically suspected cases of thalassemias in Riyadh, Saudi Arabia. The hematological parameters were studied on Coulter STKS. Cellulose acetate hemoglobin electrophoresis and high-performance liquid chromatography (HPLC) were performed on all the blood samples. Gene deletion studies were carried out by restriction fragment length polymorphism (RFLP) technique using the restriction endonucleases Bam HI. STATISTICAL ANALYSIS: Statistical analysis was performed on SPSS 11.5 version. RESULTS: The hemoglobin electrophoresis and gene studies revealed that there were 406 (40.96%) and 59 (5.95 %) cases of β thalassemia trait and β thalassemia major respectively including adults and children. 426 cases of various deletion forms of α thalassemias were seen. Microcytosis was a common feature in β thalassemias trait and (-α/-α) and (--/αα) types of α thalassemias. MCH was a more significant distinguishing feature among thalassemias. β thalassemia major and α thalassemia (-α/αα) had almost normal hematological parameters. CONCLUSION: MCV and RBC counts are not statistically significant features for discriminating between α and β thalassemias. There is need for development of a discrimination index to differentiate between α and β thalassemias traits on the lines of discriminatory Indices available for distinguishing β thalassemias trait from iron deficiency anemia. PMID:22345994

Large-scale galaxy bias

NASA Astrophysics Data System (ADS)

Jeong, Donghui; Desjacques, Vincent; Schmidt, Fabian

2018-01-01

Here, we briefly introduce the key results of the recent review (arXiv:1611.09787), whose abstract is as following. This review presents a comprehensive overview of galaxy bias, that is, the statistical relation between the distribution of galaxies and matter. We focus on large scales where cosmic density fields are quasi-linear. On these scales, the clustering of galaxies can be described by a perturbative bias expansion, and the complicated physics of galaxy formation is absorbed by a finite set of coefficients of the expansion, called bias parameters. The review begins with a detailed derivation of this very important result, which forms the basis of the rigorous perturbative description of galaxy clustering, under the assumptions of General Relativity and Gaussian, adiabatic initial conditions. Key components of the bias expansion are all leading local gravitational observables, which include the matter density but also tidal fields and their time derivatives. We hence expand the definition of local bias to encompass all these contributions. This derivation is followed by a presentation of the peak-background split in its general form, which elucidates the physical meaning of the bias parameters, and a detailed description of the connection between bias parameters and galaxy (or halo) statistics. We then review the excursion set formalism and peak theory which provide predictions for the values of the bias parameters. In the remainder of the review, we consider the generalizations of galaxy bias required in the presence of various types of cosmological physics that go beyond pressureless matter with adiabatic, Gaussian initial conditions: primordial non-Gaussianity, massive neutrinos, baryon-CDM isocurvature perturbations, dark energy, and modified gravity. Finally, we discuss how the description of galaxy bias in the galaxies' rest frame is related to clustering statistics measured from the observed angular positions and redshifts in actual galaxy catalogs.

Large-scale galaxy bias

NASA Astrophysics Data System (ADS)

Desjacques, Vincent; Jeong, Donghui; Schmidt, Fabian

2018-02-01

This review presents a comprehensive overview of galaxy bias, that is, the statistical relation between the distribution of galaxies and matter. We focus on large scales where cosmic density fields are quasi-linear. On these scales, the clustering of galaxies can be described by a perturbative bias expansion, and the complicated physics of galaxy formation is absorbed by a finite set of coefficients of the expansion, called bias parameters. The review begins with a detailed derivation of this very important result, which forms the basis of the rigorous perturbative description of galaxy clustering, under the assumptions of General Relativity and Gaussian, adiabatic initial conditions. Key components of the bias expansion are all leading local gravitational observables, which include the matter density but also tidal fields and their time derivatives. We hence expand the definition of local bias to encompass all these contributions. This derivation is followed by a presentation of the peak-background split in its general form, which elucidates the physical meaning of the bias parameters, and a detailed description of the connection between bias parameters and galaxy statistics. We then review the excursion-set formalism and peak theory which provide predictions for the values of the bias parameters. In the remainder of the review, we consider the generalizations of galaxy bias required in the presence of various types of cosmological physics that go beyond pressureless matter with adiabatic, Gaussian initial conditions: primordial non-Gaussianity, massive neutrinos, baryon-CDM isocurvature perturbations, dark energy, and modified gravity. Finally, we discuss how the description of galaxy bias in the galaxies' rest frame is related to clustering statistics measured from the observed angular positions and redshifts in actual galaxy catalogs.

Peri-implant parameters, tumor necrosis factor-alpha, and interleukin-1 beta levels in vaping individuals.

PubMed

Al-Aali, Khulud A; Alrabiah, Mohammed; ArRejaie, Aws S; Abduljabbar, Tariq; Vohra, Fahim; Akram, Zohaib

2018-03-25

To the author's knowledge, there has been no study that has assessed clinical, radiographic, and immunological peri-implant parameters among individuals vaping e-cigarette (e-cig). This pilot study aimed to compare clinical and radiographic peri-implant parameters and levels of tumor necrosis factor alpha (TNF-α) and interleukin (IL)-1β levels among individuals vaping e-cigs and never smoker (NS). Forty-seven individuals vaping e-cigs (group-1) and 45 NS (group-2) were included. Demographic and implant-related data were collected using a structured baseline questionnaire. Peri-implant plaque index (PI), bleeding on probing (BOP), and probing depth (PD) were recorded and peri-implant bone loss (PIBL) were assessed using standardized digital radiographs. Enzyme-linked immunosorbent assay was used to assess the levels of TNF-α and IL-1β in peri-implant sulcular fluid. Bleeding on probing showed statistically significantly higher values in group-2 patients as compared to group-1 patients (P < .01). Probing depth ≥ 4 mm and PIBL was statistically significantly higher in group-1 patients as compared to group-2 patients (P < .05). Mean concentrations of TNF-α (P < .001) and IL-1β (P < .01) were statistically significantly increased in individuals in group 1 as compared with group 2. A significant positive correlations were found between TNF-α levels and BOP (P = .024) and PIBL (P = .016); and significant positive correlation was found between IL-1β and PIBL (P = .018) in group 1, respectively. Clinical and radiographic peri-implant parameters are compromised among vaping individuals. Increased levels of proinflammatory cytokines in peri-implant sulcular fluid may suggest greater local inflammatory response in vaping individuals for peri-implant inflammation. © 2018 Wiley Periodicals, Inc.

An Open Label Clinical Trial to Evaluate the Efficacy and Tolerance of a Retinol and Vitamin C Facial Regimen in Women With Mild-to-Moderate Hyperpigmentation and Photodamaged Facial Skin.

PubMed

Herndon, James H; Jiang, Lily I; Kononov, Tatiana; Fox, Theresa

2016-04-01

A 12-week open-label, single-center clinical usage trial was conducted to determine the effectiveness of a dual product regimen consisting of a 0.5% retinol treatment and an anti-aging moisturizer with 30% vitamin C in women with mild to moderate hyperpigmented and photodamaged facial skin. Clinical grading of several efficacy parameters, tolerability evaluations, subject self-assessment questionnaires, and digital photography were completed at baseline and at weeks 4, 8, and 12. A total of 44 women completed the study. Effective ingredients incorporated into the 0.5% retinol treatment included encapsulated retinol for a retinol concentration of 0.5%, bakuchiol, and Ophiopogon japonicus root extract. The anti-aging moisturizer with 30% vitamin C contained 30% vitamin C in the form of tetrahexyldecyl ascorbate (THD ascorbate), alpha-tocopheryl acetate (vitamin E) and ubiquinone (coenzyme Q10). The facial regimen produced a statistically significant decrease (improvement) in clinical grading scores for all parameters assessed at weeks 8 and 12 when compared with baseline scores. In addition, the majority of these parameters were improved at week 4. The test regimen was well-perceived by the subjects for various inquiries regarding facial skin condition, product efficacy, and product attributes. Several tolerability parameters were assessed with no statistically significant increase except for dryness. A statistically significant increase in clinical grading scores for dryness on the face occurred at weeks 4 and 8 when compared to baseline scores. The increase in dryness is expected when introducing a retinol product to a facial regimen and the dryness did not persist to the week 12 time point.

Evaluation of wind field statistics near and inside clouds using a coherent Doppler lidar

NASA Astrophysics Data System (ADS)

Lottman, Brian Todd

1998-09-01

This work proposes advanced techniques for measuring the spatial wind field statistics near and inside clouds using a vertically pointing solid state coherent Doppler lidar on a fixed ground based platform. The coherent Doppler lidar is an ideal instrument for high spatial and temporal resolution velocity estimates. The basic parameters of lidar are discussed, including a complete statistical description of the Doppler lidar signal. This description is extended to cases with simple functional forms for aerosol backscatter and velocity. An estimate for the mean velocity over a sensing volume is produced by estimating the mean spectra. There are many traditional spectral estimators, which are useful for conditions with slowly varying velocity and backscatter. A new class of estimators (novel) is introduced that produces reliable velocity estimates for conditions with large variations in aerosol backscatter and velocity with range, such as cloud conditions. Performance of traditional and novel estimators is computed for a variety of deterministic atmospheric conditions using computer simulated data. Wind field statistics are produced for actual data for a cloud deck, and for multi- layer clouds. Unique results include detection of possible spectral signatures for rain, estimates for the structure function inside a cloud deck, reliable velocity estimation techniques near and inside thin clouds, and estimates for simple wind field statistics between cloud layers.

Statistical models for the analysis and design of digital polymerase chain (dPCR) experiments

USGS Publications Warehouse

Dorazio, Robert; Hunter, Margaret

2015-01-01

Statistical methods for the analysis and design of experiments using digital PCR (dPCR) have received only limited attention and have been misused in many instances. To address this issue and to provide a more general approach to the analysis of dPCR data, we describe a class of statistical models for the analysis and design of experiments that require quantification of nucleic acids. These models are mathematically equivalent to generalized linear models of binomial responses that include a complementary, log–log link function and an offset that is dependent on the dPCR partition volume. These models are both versatile and easy to fit using conventional statistical software. Covariates can be used to specify different sources of variation in nucleic acid concentration, and a model’s parameters can be used to quantify the effects of these covariates. For purposes of illustration, we analyzed dPCR data from different types of experiments, including serial dilution, evaluation of copy number variation, and quantification of gene expression. We also showed how these models can be used to help design dPCR experiments, as in selection of sample sizes needed to achieve desired levels of precision in estimates of nucleic acid concentration or to detect differences in concentration among treatments with prescribed levels of statistical power.

Statistical Models for the Analysis and Design of Digital Polymerase Chain Reaction (dPCR) Experiments.

PubMed

Dorazio, Robert M; Hunter, Margaret E

2015-11-03

Statistical methods for the analysis and design of experiments using digital PCR (dPCR) have received only limited attention and have been misused in many instances. To address this issue and to provide a more general approach to the analysis of dPCR data, we describe a class of statistical models for the analysis and design of experiments that require quantification of nucleic acids. These models are mathematically equivalent to generalized linear models of binomial responses that include a complementary, log-log link function and an offset that is dependent on the dPCR partition volume. These models are both versatile and easy to fit using conventional statistical software. Covariates can be used to specify different sources of variation in nucleic acid concentration, and a model's parameters can be used to quantify the effects of these covariates. For purposes of illustration, we analyzed dPCR data from different types of experiments, including serial dilution, evaluation of copy number variation, and quantification of gene expression. We also showed how these models can be used to help design dPCR experiments, as in selection of sample sizes needed to achieve desired levels of precision in estimates of nucleic acid concentration or to detect differences in concentration among treatments with prescribed levels of statistical power.

Flood characteristics of urban watersheds in the United States

USGS Publications Warehouse

Sauer, Vernon B.; Thomas, W.O.; Stricker, V.A.; Wilson, K.V.

1983-01-01

A nationwide study of flood magnitude and frequency in urban areas was made for the purpose of reviewing available literature, compiling an urban flood data base, and developing methods of estimating urban floodflow characteristics in ungaged areas. The literature review contains synopses of 128 recent publications related to urban floodflow. A data base of 269 gaged basins in 56 cities and 31 States, including Hawaii, contains a wide variety of topographic and climatic characteristics, land-use variables, indices of urbanization, and flood-frequency estimates. Three sets of regression equations were developed to estimate flood discharges for ungaged sites for recurrence intervals of 2, 5, 10, 25, 50, 100, and 500 years. Two sets of regression equations are based on seven independent parameters and the third is based on three independent parameters. The only difference in the two sets of seven-parameter equations is the use of basin lag time in one and lake and reservoir storage in the other. Of primary importance in these equations is an independent estimate of the equivalent rural discharge for the ungaged basin. The equations adjust the equivalent rural discharge to an urban condition. The primary adjustment factor, or index of urbanization, is the basin development factor, a measure of the extent of development of the drainage system in the basin. This measure includes evaluations of storm drains (sewers), channel improvements, and curb-and-gutter streets. The basin development factor is statistically very significant and offers a simple and effective way of accounting for drainage development and runoff response in urban areas. Percentage of impervious area is also included in the seven-parameter equations as an additional measure of urbanization and apparently accounts for increased runoff volumes. This factor is not highly significant for large floods, which supports the generally held concept that imperviousness is not a dominant factor when soils become more saturated during large storms. Other parameters in the seven-parameter equations include drainage area size, channel slope, rainfall intensity, lake and reservoir storage, and basin lag time. These factors are all statistically significant and provide logical indices of basin conditions. The three-parameter equations include only the three most significant parameters: rural discharge, basin-development factor, and drainage area size. All three sets of regression equations provide unbiased estimates of urban flood frequency. The seven-parameter regression equations without basin lag time have average standard errors of regression varying from ? 37 percent for the 5-year flood to ? 44 percent for the 100-year flood and ? 49 percent for the 500-year flood. The other two sets of regression equations have similar accuracy. Several tests for bias, sensitivity, and hydrologic consistency are included which support the conclusion that the equations are useful throughout the United States. All estimating equations were developed from data collected on drainage basins where temporary in-channel storage, due to highway embankments, was not significant. Consequently, estimates made with these equations do not account for the reducing effect of this temporary detention storage.

Evaluation of bond strength of resin cements using different general-purpose statistical software packages for two-parameter Weibull statistics.

PubMed

Roos, Malgorzata; Stawarczyk, Bogna

2012-07-01

This study evaluated and compared Weibull parameters of resin bond strength values using six different general-purpose statistical software packages for two-parameter Weibull distribution. Two-hundred human teeth were randomly divided into 4 groups (n=50), prepared and bonded on dentin according to the manufacturers' instructions using the following resin cements: (i) Variolink (VAN, conventional resin cement), (ii) Panavia21 (PAN, conventional resin cement), (iii) RelyX Unicem (RXU, self-adhesive resin cement) and (iv) G-Cem (GCM, self-adhesive resin cement). Subsequently, all specimens were stored in water for 24h at 37°C. Shear bond strength was measured and the data were analyzed using Anderson-Darling goodness-of-fit (MINITAB 16) and two-parameter Weibull statistics with the following statistical software packages: Excel 2011, SPSS 19, MINITAB 16, R 2.12.1, SAS 9.1.3. and STATA 11.2 (p≤0.05). Additionally, the three-parameter Weibull was fitted using MNITAB 16. Two-parameter Weibull calculated with MINITAB and STATA can be compared using an omnibus test and using 95% CI. In SAS only 95% CI were directly obtained from the output. R provided no estimates of 95% CI. In both SAS and R the global comparison of the characteristic bond strength among groups is provided by means of the Weibull regression. EXCEL and SPSS provided no default information about 95% CI and no significance test for the comparison of Weibull parameters among the groups. In summary, conventional resin cement VAN showed the highest Weibull modulus and characteristic bond strength. There are discrepancies in the Weibull statistics depending on the software package and the estimation method. The information content in the default output provided by the software packages differs to very high extent. Copyright © 2012 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Income inequality, poverty, and population health: evidence from recent data for the United States.

PubMed

Ram, Rati

2005-12-01

In this study, state-level US data for the years 2000 and 1990 are used to provide additional evidence on the roles of income inequality and poverty in population health. Five main points are noted. First, contrary to the suggestion made in several recent studies, the income inequality parameter is observed to be quite robust and carries statistical significance in mortality equations estimated from several observation sets and a fairly wide variety of specificational choices. Second, the evidence does not indicate that significance of income inequality is lost when education variables are included. Third, similarly, the income inequality parameter shows significance when a race variable is added, and also when both race and urbanization terms are entered. Fourth, while poverty is seen to have some mortality-increasing consequence, the role of income inequality appears stronger. Fifth, income inequality retains statistical significance when a quadratic income term is added and also if the log-log version of a fairly inclusive model is estimated. I therefore suggest that the recent skepticism articulated by several scholars in regard to the robustness of the income inequality parameters in mortality equations estimated from the US data should be reconsidered.

Observability of ionospheric space-time structure with ISR: A simulation study

NASA Astrophysics Data System (ADS)

Swoboda, John; Semeter, Joshua; Zettergren, Matthew; Erickson, Philip J.

2017-02-01

The sources of error from electronically steerable array (ESA) incoherent scatter radar (ISR) systems are investigated both theoretically and with use of an open-source ISR simulator, developed by the authors, called Simulator for ISR (SimISR). The main sources of error incorporated in the simulator include statistical uncertainty, which arises due to nature of the measurement mechanism and the inherent space-time ambiguity from the sensor. SimISR can take a field of plasma parameters, parameterized by time and space, and create simulated ISR data at the scattered electric field (i.e., complex receiver voltage) level, subsequently processing these data to show possible reconstructions of the original parameter field. To demonstrate general utility, we show a number of simulation examples, with two cases using data from a self-consistent multifluid transport model. Results highlight the significant influence of the forward model of the ISR process and the resulting statistical uncertainty on plasma parameter measurements and the core experiment design trade-offs that must be made when planning observations. These conclusions further underscore the utility of this class of measurement simulator as a design tool for more optimal experiment design efforts using flexible ESA class ISR systems.

Quantitative analysis of spatial variability of geotechnical parameters

NASA Astrophysics Data System (ADS)

Fang, Xing

2018-04-01

Geotechnical parameters are the basic parameters of geotechnical engineering design, while the geotechnical parameters have strong regional characteristics. At the same time, the spatial variability of geotechnical parameters has been recognized. It is gradually introduced into the reliability analysis of geotechnical engineering. Based on the statistical theory of geostatistical spatial information, the spatial variability of geotechnical parameters is quantitatively analyzed. At the same time, the evaluation of geotechnical parameters and the correlation coefficient between geotechnical parameters are calculated. A residential district of Tianjin Survey Institute was selected as the research object. There are 68 boreholes in this area and 9 layers of mechanical stratification. The parameters are water content, natural gravity, void ratio, liquid limit, plasticity index, liquidity index, compressibility coefficient, compressive modulus, internal friction angle, cohesion and SP index. According to the principle of statistical correlation, the correlation coefficient of geotechnical parameters is calculated. According to the correlation coefficient, the law of geotechnical parameters is obtained.

[Dexpanthenol nasal spray as an effective therapeutic principle for treatment of rhinitis sicca anterior].

PubMed

Kehrl, W; Sonnemann, U

1998-09-01

Controlled clinical studies on medical treatment of rhinitis sicca anterior have not yet been published. Therapy recommendations are based on experiences but not on results of controlled clinical studies. The aim of this study was to examine the efficacy and tolerance of a new form of application of Dexpanthenol in physiologic saline solution (Nasicur). A randomized comparison of parallel groups was performed. One group was treated with the nasal spray while the control group received a placebo. The assessment of nasal breathing resistance and the extent of crust formation according to scores were defined as target parameters. Statistical analysis was carried out according to Wilcoxon at alpha < or = 0.05. Forty-eight outpatients diagnosed with rhinitis sicca anterior were included in this study. Twenty-four received the medication, and 29 were treated with a placebo. The superiority of the dexpanthenol nasal spray in comparison to the placebo medication was demonstrated for both target parameters as clinically relevant and statistically significant. The placebo spray showed clinical improvement of the other treatment outcome parameters. Dexpanthenol nasal spray showed no statistically significant difference in comparison to placebo. The clinically proven efficacy is emphasized by good tolerance of both treatments which was validated by the objective rhinoscopy findings. Good compliance was confirmed. The result of the controlled clinical study confirms that the dexpanthenol nasal spray is an effective medicinal treatment of rhinitis sicca anterior and is more effective than common medications.

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

Gilbert, Richard O.

The application of statistics to environmental pollution monitoring studies requires a knowledge of statistical analysis methods particularly well suited to pollution data. This book fills that need by providing sampling plans, statistical tests, parameter estimation procedure techniques, and references to pertinent publications. Most of the statistical techniques are relatively simple, and examples, exercises, and case studies are provided to illustrate procedures. The book is logically divided into three parts. Chapters 1, 2, and 3 are introductory chapters. Chapters 4 through 10 discuss field sampling designs and Chapters 11 through 18 deal with a broad range of statistical analysis procedures. Somemore » statistical techniques given here are not commonly seen in statistics book. For example, see methods for handling correlated data (Sections 4.5 and 11.12), for detecting hot spots (Chapter 10), and for estimating a confidence interval for the mean of a lognormal distribution (Section 13.2). Also, Appendix B lists a computer code that estimates and tests for trends over time at one or more monitoring stations using nonparametric methods (Chapters 16 and 17). Unfortunately, some important topics could not be included because of their complexity and the need to limit the length of the book. For example, only brief mention could be made of time series analysis using Box-Jenkins methods and of kriging techniques for estimating spatial and spatial-time patterns of pollution, although multiple references on these topics are provided. Also, no discussion of methods for assessing risks from environmental pollution could be included.« less

A statistical methodology for estimating transport parameters: Theory and applications to one-dimensional advectivec-dispersive systems

USGS Publications Warehouse

Wagner, Brian J.; Gorelick, Steven M.

1986-01-01

A simulation nonlinear multiple-regression methodology for estimating parameters that characterize the transport of contaminants is developed and demonstrated. Finite difference contaminant transport simulation is combined with a nonlinear weighted least squares multiple-regression procedure. The technique provides optimal parameter estimates and gives statistics for assessing the reliability of these estimates under certain general assumptions about the distributions of the random measurement errors. Monte Carlo analysis is used to estimate parameter reliability for a hypothetical homogeneous soil column for which concentration data contain large random measurement errors. The value of data collected spatially versus data collected temporally was investigated for estimation of velocity, dispersion coefficient, effective porosity, first-order decay rate, and zero-order production. The use of spatial data gave estimates that were 2–3 times more reliable than estimates based on temporal data for all parameters except velocity. Comparison of estimated linear and nonlinear confidence intervals based upon Monte Carlo analysis showed that the linear approximation is poor for dispersion coefficient and zero-order production coefficient when data are collected over time. In addition, examples demonstrate transport parameter estimation for two real one-dimensional systems. First, the longitudinal dispersivity and effective porosity of an unsaturated soil are estimated using laboratory column data. We compare the reliability of estimates based upon data from individual laboratory experiments versus estimates based upon pooled data from several experiments. Second, the simulation nonlinear regression procedure is extended to include an additional governing equation that describes delayed storage during contaminant transport. The model is applied to analyze the trends, variability, and interrelationship of parameters in a mourtain stream in northern California.

Variations in the Parameters of Background Seismic Noise during the Preparation Stages of Strong Earthquakes in the Kamchatka Region

NASA Astrophysics Data System (ADS)

Kasimova, V. A.; Kopylova, G. N.; Lyubushin, A. A.

2018-03-01

The results of the long (2011-2016) investigation of background seismic noise (BSN) in Kamchatka by the method suggested by Doct. Sci. (Phys.-Math.) A.A. Lyubushin with the use of the data from the network of broadband seismic stations of the Geophysical Survey of the Russian Academy of Sciences are presented. For characterizing the BSN field and its variability, continuous time series of the statistical parameters of the multifractal singularity spectra and wavelet expansion calculated from the records at each station are used. These parameters include the generalized Hurst exponent α*, singularity spectrum support width Δα, wavelet spectral exponent β, minimal normalized entropy of wavelet coefficients En, and spectral measure of their coherent behavior. The peculiarities in the spatiotemporal distribution of the BSN parameters as a probable response to the earthquakes with M w = 6.8-8.3 that occurred in Kamchatka in 2013 and 2016 are considered. It is established that these seismic events were preceded by regular variations in the BSN parameters, which lasted for a few months and consisted in the reduction of the median and mean α*, Δα, and β values estimated over all the stations and in the increase of the En values. Based on the increase in the spectral measure of the coherent behavior of the four-variate time series of the median and mean values of the considered statistics, the effect of the enhancement of the synchronism in the joint (collective) behavior of these parameters during a certain period prior to the mantle earthquake in the Sea of Okhotsk (May 24, 2013, M w = 8.3) is diagnosed. The procedures for revealing the precursory effects in the variations of the BSN parameters are described and the examples of these effects are presented.

Application of nonlinear least-squares regression to ground-water flow modeling, west-central Florida

USGS Publications Warehouse

Yobbi, D.K.

2000-01-01

A nonlinear least-squares regression technique for estimation of ground-water flow model parameters was applied to an existing model of the regional aquifer system underlying west-central Florida. The regression technique minimizes the differences between measured and simulated water levels. Regression statistics, including parameter sensitivities and correlations, were calculated for reported parameter values in the existing model. Optimal parameter values for selected hydrologic variables of interest are estimated by nonlinear regression. Optimal estimates of parameter values are about 140 times greater than and about 0.01 times less than reported values. Independently estimating all parameters by nonlinear regression was impossible, given the existing zonation structure and number of observations, because of parameter insensitivity and correlation. Although the model yields parameter values similar to those estimated by other methods and reproduces the measured water levels reasonably accurately, a simpler parameter structure should be considered. Some possible ways of improving model calibration are to: (1) modify the defined parameter-zonation structure by omitting and/or combining parameters to be estimated; (2) carefully eliminate observation data based on evidence that they are likely to be biased; (3) collect additional water-level data; (4) assign values to insensitive parameters, and (5) estimate the most sensitive parameters first, then, using the optimized values for these parameters, estimate the entire data set.

Modeling the Risk of Radiation-Induced Acute Esophagitis for Combined Washington University and RTOG Trial 93-11 Lung Cancer Patients

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

Huang, Ellen X.; Bradley, Jeffrey D.; El Naqa, Issam

2012-04-01

Purpose: To construct a maximally predictive model of the risk of severe acute esophagitis (AE) for patients who receive definitive radiation therapy (RT) for non-small-cell lung cancer. Methods and Materials: The dataset includes Washington University and RTOG 93-11 clinical trial data (events/patients: 120/374, WUSTL = 101/237, RTOG9311 = 19/137). Statistical model building was performed based on dosimetric and clinical parameters (patient age, sex, weight loss, pretreatment chemotherapy, concurrent chemotherapy, fraction size). A wide range of dose-volume parameters were extracted from dearchived treatment plans, including Dx, Vx, MOHx (mean of hottest x% volume), MOCx (mean of coldest x% volume), and gEUDmore » (generalized equivalent uniform dose) values. Results: The most significant single parameters for predicting acute esophagitis (RTOG Grade 2 or greater) were MOH85, mean esophagus dose (MED), and V30. A superior-inferior weighted dose-center position was derived but not found to be significant. Fraction size was found to be significant on univariate logistic analysis (Spearman R = 0.421, p < 0.00001) but not multivariate logistic modeling. Cross-validation model building was used to determine that an optimal model size needed only two parameters (MOH85 and concurrent chemotherapy, robustly selected on bootstrap model-rebuilding). Mean esophagus dose (MED) is preferred instead of MOH85, as it gives nearly the same statistical performance and is easier to compute. AE risk is given as a logistic function of (0.0688 Asterisk-Operator MED+1.50 Asterisk-Operator ConChemo-3.13), where MED is in Gy and ConChemo is either 1 (yes) if concurrent chemotherapy was given, or 0 (no). This model correlates to the observed risk of AE with a Spearman coefficient of 0.629 (p < 0.000001). Conclusions: Multivariate statistical model building with cross-validation suggests that a two-variable logistic model based on mean dose and the use of concurrent chemotherapy robustly predicts acute esophagitis risk in combined-data WUSTL and RTOG 93-11 trial datasets.« less

Definition of a simple statistical parameter for the quantification of orientation in two dimensions: application to cells on grooves of nanometric depths.

PubMed

Davidson, P; Bigerelle, M; Bounichane, B; Giazzon, M; Anselme, K

2010-07-01

Contact guidance is generally evaluated by measuring the orientation angle of cells. However, statistical analyses are rarely performed on these parameters. Here we propose a statistical analysis based on a new parameter sigma, the orientation parameter, defined as the dispersion of the distribution of orientation angles. This parameter can be used to obtain a truncated Gaussian distribution that models the distribution of the data between -90 degrees and +90 degrees. We established a threshold value of the orientation parameter below which the data can be considered to be aligned within a 95% confidence interval. Applying our orientation parameter to cells on grooves and using a modelling approach, we established the relationship sigma=alpha(meas)+(52 degrees -alpha(meas))/(1+C(GDE)R) where the parameter C(GDE) represents the sensitivity of cells to groove depth, and R the groove depth. The values of C(GDE) obtained allowed us to compare the contact guidance of human osteoprogenitor (HOP) cells across experiments involving different groove depths, times in culture and inoculation densities. We demonstrate that HOP cells are able to identify and respond to the presence of grooves 30, 100, 200 and 500 nm deep and that the deeper the grooves, the higher the cell orientation. The evolution of the sensitivity (C(GDE)) with culture time is roughly sigmoidal with an asymptote, which is a function of inoculation density. The sigma parameter defined here is a universal parameter that can be applied to all orientation measurements and does not require a mathematical background or knowledge of directional statistics. Copyright 2010 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Statistical mechanics in the context of special relativity.

PubMed

Kaniadakis, G

2002-11-01

In Ref. [Physica A 296, 405 (2001)], starting from the one parameter deformation of the exponential function exp(kappa)(x)=(sqrt[1+kappa(2)x(2)]+kappax)(1/kappa), a statistical mechanics has been constructed which reduces to the ordinary Boltzmann-Gibbs statistical mechanics as the deformation parameter kappa approaches to zero. The distribution f=exp(kappa)(-beta E+betamu) obtained within this statistical mechanics shows a power law tail and depends on the nonspecified parameter beta, containing all the information about the temperature of the system. On the other hand, the entropic form S(kappa)= integral d(3)p(c(kappa) f(1+kappa)+c(-kappa) f(1-kappa)), which after maximization produces the distribution f and reduces to the standard Boltzmann-Shannon entropy S0 as kappa-->0, contains the coefficient c(kappa) whose expression involves, beside the Boltzmann constant, another nonspecified parameter alpha. In the present effort we show that S(kappa) is the unique existing entropy obtained by a continuous deformation of S0 and preserving unaltered its fundamental properties of concavity, additivity, and extensivity. These properties of S(kappa) permit to determine unequivocally the values of the above mentioned parameters beta and alpha. Subsequently, we explain the origin of the deformation mechanism introduced by kappa and show that this deformation emerges naturally within the Einstein special relativity. Furthermore, we extend the theory in order to treat statistical systems in a time dependent and relativistic context. Then, we show that it is possible to determine in a self consistent scheme within the special relativity the values of the free parameter kappa which results to depend on the light speed c and reduces to zero as c--> infinity recovering in this way the ordinary statistical mechanics and thermodynamics. The statistical mechanics here presented, does not contain free parameters, preserves unaltered the mathematical and epistemological structure of the ordinary statistical mechanics and is suitable to describe a very large class of experimentally observed phenomena in low and high energy physics and in natural, economic, and social sciences. Finally, in order to test the correctness and predictability of the theory, as working example we consider the cosmic rays spectrum, which spans 13 decades in energy and 33 decades in flux, finding a high quality agreement between our predictions and observed data.

Statistical metrics for the characterization of karst network geometry and topology

NASA Astrophysics Data System (ADS)

Collon, Pauline; Bernasconi, David; Vuilleumier, Cécile; Renard, Philippe

2017-04-01

Statistical metrics can be used to analyse the morphology of natural or simulated karst systems; they allow describing, comparing, and quantifying their geometry and topology. In this paper, we present and discuss a set of such metrics. We study their properties and their usefulness based on a set of more than 30 karstic networks mapped by speleologists. The data set includes some of the largest explored cave systems in the world and represents a broad range of geological and speleogenetic conditions allowing us to test the proposed metrics, their variability, and their usefulness for the discrimination of different morphologies. All the proposed metrics require that the topographical survey of the caves are first converted to graphs consisting of vertices and edges. This data preprocessing includes several quality check operations and some corrections to ensure that the karst is represented as accurately as possible. The statistical parameters relating to the geometry of the system are then directly computed on the graphs, while the topological parameters are computed on a reduced version of the network focusing only on its structure. Among the tested metrics, we include some that were previously proposed such as tortuosity or the Howard's coefficients. We also investigate the possibility to use new metrics derived from graph theory. In total, 21 metrics are introduced, discussed in detail, and compared on the basis of our data set. This work shows that orientation analysis and, in particular, the entropy of the orientation data can help to detect the existence of inception features. The statistics on branch length are useful to describe the extension of the conduits within the network. Rather surprisingly, the tortuosity does not vary very significantly. It could be heavily influenced by the survey methodology. The degree of interconnectivity of the network, related to the presence of maze patterns, can be measured using different metrics such as the Howard's parameters, global cyclic coefficient, or the average vertex degree. The average vertex degree of the reduced graph proved to be the most useful as it is simple to compute, it discriminates properly the interconnected systems (mazes) from the acyclic ones (tree-like structures), and it permits us to classify the acyclic systems as a function of the total number of branches. This topological information is completed by three parameters, allowing us to refine the description. The correlation of vertex degree is rather simple to obtain. It is systematically positive on all studied data sets indicating a predominance of assortative networks among karst systems. The average shortest path length is related to the transport efficiency. It is shown to be mainly correlated to the size of the network. Finally, central point dominance allows us to identify the presence of a centralized organization.

Comparison of different parameters for recording sagittal maxillo mandibular relation using natural head posture: A cephalometric study

PubMed Central

Singh, Ashish Kumar; Ganeshkar, Sanjay V.; Mehrotra, Praveen; Bhagchandani, Jitendra

2013-01-01

Background: Commonly used parameters for anteroposterior assessment of the jaw relationship includes several analyses such as ANB, NA-Pog, AB-NPog, Wits appraisal, Harvold's unit length difference, Beta angle. Considering the fact that there are several parameters (with different range and values) which account for sagittal relation, and still the published literature for comparisons and correlation of these measurements is scarce. Therefore, the objective of this study was to correlate these values in subjects of Indian origin. Materials and Methods: The sample consisted of fifty adult individuals (age group 18-26 years) with equal number of males and females. The selection criteria included subjects with no previous history of orthodontic and/or orthognathic surgical treatment; orthognathic facial profile; Angle's Class I molar relation; clinical Frankfort Mandibular plane angle FMA of 30±5° and no gross facial asymmetry. The cephalograms were taken in natural head position (NHP). Seven sagittal skeletal parameters were measured in the cephalograms and subjected to statistical evaluation with Wits reading on the true horizontal as reference. A correlation coefficient analysis was done to assess the significance of association between these variables. Results: ANB angle showed statistically significant correlation for the total sample, though the values were insignificant for the individual groups and therefore may not be very accurate. Wits appraisal was seen to have a significant correlation only in the female sample group. Conclusions: If cephalograms cannot be recorded in a NHP, then the best indicator for recording A-P skeletal dimension would be angle AB-NPog, followed by Harvold's unit length difference. However, considering biologic variability, more than one reading should necessarily be used to verify the same. PMID:24987638

Development of a design space and predictive statistical model for capsule filling of low-fill-weight inhalation products.

PubMed

Faulhammer, E; Llusa, M; Wahl, P R; Paudel, A; Lawrence, S; Biserni, S; Calzolari, V; Khinast, J G

2016-01-01

The objectives of this study were to develop a predictive statistical model for low-fill-weight capsule filling of inhalation products with dosator nozzles via the quality by design (QbD) approach and based on that to create refined models that include quadratic terms for significant parameters. Various controllable process parameters and uncontrolled material attributes of 12 powders were initially screened using a linear model with partial least square (PLS) regression to determine their effect on the critical quality attributes (CQA; fill weight and weight variability). After identifying critical material attributes (CMAs) and critical process parameters (CPPs) that influenced the CQA, model refinement was performed to study if interactions or quadratic terms influence the model. Based on the assessment of the effects of the CPPs and CMAs on fill weight and weight variability for low-fill-weight inhalation products, we developed an excellent linear predictive model for fill weight (R(2 )= 0.96, Q(2 )= 0.96 for powders with good flow properties and R(2 )= 0.94, Q(2 )= 0.93 for cohesive powders) and a model that provides a good approximation of the fill weight variability for each powder group. We validated the model, established a design space for the performance of different types of inhalation grade lactose on low-fill weight capsule filling and successfully used the CMAs and CPPs to predict fill weight of powders that were not included in the development set.

Multiple Myeloma Index for Risk of Infection.

PubMed

T, Valkovic; V, Gacic; A, Nacinovic-Duletic

2018-01-01

Based on our earlier research into the main characteristics and risk factors for infections in hospitalized patients with multiple myeloma, we created the numerical Multiple Myeloma Index for Risk of Infection (MMIRI) to predict infection in myeloma patients. The included factors that could influence the pathogenesis and incidence of infections were sex, performance status, Durie Salmon stage of disease, International Staging System, serum creatinine level, immune paresis, neutropenia, serum ferritin level, the presence of any catheters, disease duration, stable/progressive disease, and type of therapy. For each of these parameters, the strength of association with infection was statistically estimated and specific number of points was assigned to each of these parameters, proportional to the strength of the association. When designing the MMIRI, we included only those parameters that we determined were pathophysiologically associated with the infection. After further statistical analysis, we identified an optimal cutoff score of 6 or above as indicating a significant risk for infection, with a sensitivity of 93.2% and specificity of 80.2%. The scoring system in the retrospective receiver operating characteristic analysis showed an area under the curve of 0.918. The potential value of the MMIRI is the possibility of identifying those patients who would benefit from the prophylactic administration of antibiotics and other anti-infective measures while minimizing the contribution to antibiotic resistance related to the overuse of these drugs. As far as we know, this index represents the first attempt to create such an instrument for predicting the occurrence of infections in myeloma patients.

Sleep respiratory parameters in children with idiopathic epilepsy: A cross-sectional study.

PubMed

Gogou, Maria; Haidopoulou, Katerina; Eboriadou, Maria; Pavlidou, Efterpi; Hatzistylianou, Maria; Pavlou, Evaggelos

2016-10-01

The aim of this study is to explore and compare through polysomnography respiratory sleep parameters between children with idiopathic epilepsy and healthy children. Our cross-sectional study included 40 children with idiopathic epilepsy and 27 healthy children, who underwent overnight polysomnography. Data about sleep respiratory parameters were obtained and statistically analyzed. The level of statistical significance was set at 0.05. The prevalence of Obstructive Sleep Apnea Syndrome was significantly higher in the epilepsy group (35% vs 7.4%, p<0.01). Moreover, the odds ratio of an obstructive apnea index ≥1 in the epilepsy group was 10.6 (95% Confidence Intervals: 3.08-37.08) in comparison to the control group. The mean value of the obstructive apnea-hypopnea index was significantly higher in children with epilepsy compared to healthy children (2.46±1.22 vs 1.21±0.83, p=0.027). The mean values of central apnea index and desaturation index were comparable between these two groups. Longest apnea duration was significantly higher in the group of poor seizure control. All other sleep respiratory variables did not differ significantly between children with poor and good seizure control and between children with generalized and focal epilepsy. Children with epilepsy seem to present more prominent sleep breathing instability in comparison to healthy children, which mainly includes a predisposition to obstructive respiratory events. More studies are needed to investigate the relationship between sleep apneas and seizure control. Copyright © 2016 Elsevier B.V. All rights reserved.

Nonlinear Curve-Fitting Program

NASA Technical Reports Server (NTRS)

Everhart, Joel L.; Badavi, Forooz F.

1989-01-01

Nonlinear optimization algorithm helps in finding best-fit curve. Nonlinear Curve Fitting Program, NLINEAR, interactive curve-fitting routine based on description of quadratic expansion of X(sup 2) statistic. Utilizes nonlinear optimization algorithm calculating best statistically weighted values of parameters of fitting function and X(sup 2) minimized. Provides user with such statistical information as goodness of fit and estimated values of parameters producing highest degree of correlation between experimental data and mathematical model. Written in FORTRAN 77.

Statistical hadronization with exclusive channels in e +e - annihilation

DOE PAGES

Ferroni, L.; Becattini, F.

2012-01-01

We present a systematic analysis of exclusive hadronic channels in e +e - collisions at centre-of-mass energies between 2.1 and 2.6 GeV within the statistical hadronization model. Because of the low multiplicities involved, calculations have been carried out in the full microcanonical ensemble, including conservation of energy-momentum, angular momentum, parity, isospin, and all relevant charges. We show that the data is in an overall good agreement with the model for an energy density of about 0.5 GeV/fm 3 and an extra strangeness suppression parameter γ S 0:7, essentially the same values found with fits to inclusive multiplicities at higher energy.

A new exact and more powerful unconditional test of no treatment effect from binary matched pairs.

PubMed

Lloyd, Chris J

2008-09-01

We consider the problem of testing for a difference in the probability of success from matched binary pairs. Starting with three standard inexact tests, the nuisance parameter is first estimated and then the residual dependence is eliminated by maximization, producing what I call an E+M P-value. The E+M P-value based on McNemar's statistic is shown numerically to dominate previous suggestions, including partially maximized P-values as described in Berger and Sidik (2003, Statistical Methods in Medical Research 12, 91-108). The latter method, however, may have computational advantages for large samples.

Statistical performance evaluation of ECG transmission using wireless networks.

PubMed

Shakhatreh, Walid; Gharaibeh, Khaled; Al-Zaben, Awad

2013-07-01

This paper presents simulation of the transmission of biomedical signals (using ECG signal as an example) over wireless networks. Investigation of the effect of channel impairments including SNR, pathloss exponent, path delay and network impairments such as packet loss probability; on the diagnosability of the received ECG signal are presented. The ECG signal is transmitted through a wireless network system composed of two communication protocols; an 802.15.4- ZigBee protocol and an 802.11b protocol. The performance of the transmission is evaluated using higher order statistics parameters such as kurtosis and Negative Entropy in addition to the common techniques such as the PRD, RMS and Cross Correlation.

A note on some statistical properties of rise time parameters used in muon arrival time measurements

NASA Technical Reports Server (NTRS)

Vanderwalt, D. J.; Devilliers, E. J.

1985-01-01

Most investigations of the muon arrival time distribution in EAS during the past decade made use of parameters which can collectively be called rise time parameters. The rise time parameter T sub A/B is defined as the time taken for the integrated pulse from a detector to rise from A% to B% of its full amplitude. The use of these parameters are usually restricted to the determination of the radial dependence thereof. This radial dependence of the rise time parameters are usually taken as a signature of the particle interaction characteristics in the shower. As these parameters have a stochastic nature, it seems reasonable that one should also take notice of this aspect of the rise time parameters. A statistical approach to rise time parameters is presented.

Performance evaluation of a hybrid-passive landfill leachate treatment system using multivariate statistical techniques

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

Wallace, Jack, E-mail: jack.wallace@ce.queensu.ca; Champagne, Pascale, E-mail: champagne@civil.queensu.ca; Monnier, Anne-Charlotte, E-mail: anne-charlotte.monnier@insa-lyon.fr

Highlights: • Performance of a hybrid passive landfill leachate treatment system was evaluated. • 33 Water chemistry parameters were sampled for 21 months and statistically analyzed. • Parameters were strongly linked and explained most (>40%) of the variation in data. • Alkalinity, ammonia, COD, heavy metals, and iron were criteria for performance. • Eight other parameters were key in modeling system dynamics and criteria. - Abstract: A pilot-scale hybrid-passive treatment system operated at the Merrick Landfill in North Bay, Ontario, Canada, treats municipal landfill leachate and provides for subsequent natural attenuation. Collected leachate is directed to a hybrid-passive treatment system,more » followed by controlled release to a natural attenuation zone before entering the nearby Little Sturgeon River. The study presents a comprehensive evaluation of the performance of the system using multivariate statistical techniques to determine the interactions between parameters, major pollutants in the leachate, and the biological and chemical processes occurring in the system. Five parameters (ammonia, alkalinity, chemical oxygen demand (COD), “heavy” metals of interest, with atomic weights above calcium, and iron) were set as criteria for the evaluation of system performance based on their toxicity to aquatic ecosystems and importance in treatment with respect to discharge regulations. System data for a full range of water quality parameters over a 21-month period were analyzed using principal components analysis (PCA), as well as principal components (PC) and partial least squares (PLS) regressions. PCA indicated a high degree of association for most parameters with the first PC, which explained a high percentage (>40%) of the variation in the data, suggesting strong statistical relationships among most of the parameters in the system. Regression analyses identified 8 parameters (set as independent variables) that were most frequently retained for modeling the five criteria parameters (set as dependent variables), on a statistically significant level: conductivity, dissolved oxygen (DO), nitrite (NO{sub 2}{sup −}), organic nitrogen (N), oxidation reduction potential (ORP), pH, sulfate and total volatile solids (TVS). The criteria parameters and the significant explanatory parameters were most important in modeling the dynamics of the passive treatment system during the study period. Such techniques and procedures were found to be highly valuable and could be applied to other sites to determine parameters of interest in similar naturalized engineered systems.« less

Estimation Model of Spacecraft Parameters and Cost Based on a Statistical Analysis of COMPASS Designs

NASA Technical Reports Server (NTRS)

Gerberich, Matthew W.; Oleson, Steven R.

2013-01-01

The Collaborative Modeling for Parametric Assessment of Space Systems (COMPASS) team at Glenn Research Center has performed integrated system analysis of conceptual spacecraft mission designs since 2006 using a multidisciplinary concurrent engineering process. The set of completed designs was archived in a database, to allow for the study of relationships between design parameters. Although COMPASS uses a parametric spacecraft costing model, this research investigated the possibility of using a top-down approach to rapidly estimate the overall vehicle costs. This paper presents the relationships between significant design variables, including breakdowns of dry mass, wet mass, and cost. It also develops a model for a broad estimate of these parameters through basic mission characteristics, including the target location distance, the payload mass, the duration, the delta-v requirement, and the type of mission, propulsion, and electrical power. Finally, this paper examines the accuracy of this model in regards to past COMPASS designs, with an assessment of outlying spacecraft, and compares the results to historical data of completed NASA missions.

Trajectory Dispersed Vehicle Process for Space Launch System

NASA Technical Reports Server (NTRS)

Statham, Tamara; Thompson, Seth

2017-01-01

The Space Launch System (SLS) vehicle is part of NASA's deep space exploration plans that includes manned missions to Mars. Manufacturing uncertainties in design parameters are key considerations throughout SLS development as they have significant effects on focus parameters such as lift-off-thrust-to-weight, vehicle payload, maximum dynamic pressure, and compression loads. This presentation discusses how the SLS program captures these uncertainties by utilizing a 3 degree of freedom (DOF) process called Trajectory Dispersed (TD) analysis. This analysis biases nominal trajectories to identify extremes in the design parameters for various potential SLS configurations and missions. This process utilizes a Design of Experiments (DOE) and response surface methodologies (RSM) to statistically sample uncertainties, and develop resulting vehicles using a Maximum Likelihood Estimate (MLE) process for targeting uncertainties bias. These vehicles represent various missions and configurations which are used as key inputs into a variety of analyses in the SLS design process, including 6 DOF dispersions, separation clearances, and engine out failure studies.

Ergodicity of Truncated Stochastic Navier Stokes with Deterministic Forcing and Dispersion

NASA Astrophysics Data System (ADS)

Majda, Andrew J.; Tong, Xin T.

2016-10-01

Turbulence in idealized geophysical flows is a very rich and important topic. The anisotropic effects of explicit deterministic forcing, dispersive effects from rotation due to the β -plane and F-plane, and topography together with random forcing all combine to produce a remarkable number of realistic phenomena. These effects have been studied through careful numerical experiments in the truncated geophysical models. These important results include transitions between coherent jets and vortices, and direct and inverse turbulence cascades as parameters are varied, and it is a contemporary challenge to explain these diverse statistical predictions. Here we contribute to these issues by proving with full mathematical rigor that for any values of the deterministic forcing, the β - and F-plane effects and topography, with minimal stochastic forcing, there is geometric ergodicity for any finite Galerkin truncation. This means that there is a unique smooth invariant measure which attracts all statistical initial data at an exponential rate. In particular, this rigorous statistical theory guarantees that there are no bifurcations to multiple stable and unstable statistical steady states as geophysical parameters are varied in contrast to claims in the applied literature. The proof utilizes a new statistical Lyapunov function to account for enstrophy exchanges between the statistical mean and the variance fluctuations due to the deterministic forcing. It also requires careful proofs of hypoellipticity with geophysical effects and uses geometric control theory to establish reachability. To illustrate the necessity of these conditions, a two-dimensional example is developed which has the square of the Euclidean norm as the Lyapunov function and is hypoelliptic with nonzero noise forcing, yet fails to be reachable or ergodic.

Implications of the methodological choices for hydrologic portrayals of climate change over the contiguous United States: Statistically downscaled forcing data and hydrologic models

USGS Publications Warehouse

Mizukami, Naoki; Clark, Martyn P.; Gutmann, Ethan D.; Mendoza, Pablo A.; Newman, Andrew J.; Nijssen, Bart; Livneh, Ben; Hay, Lauren E.; Arnold, Jeffrey R.; Brekke, Levi D.

2016-01-01

Continental-domain assessments of climate change impacts on water resources typically rely on statistically downscaled climate model outputs to force hydrologic models at a finer spatial resolution. This study examines the effects of four statistical downscaling methods [bias-corrected constructed analog (BCCA), bias-corrected spatial disaggregation applied at daily (BCSDd) and monthly scales (BCSDm), and asynchronous regression (AR)] on retrospective hydrologic simulations using three hydrologic models with their default parameters (the Community Land Model, version 4.0; the Variable Infiltration Capacity model, version 4.1.2; and the Precipitation–Runoff Modeling System, version 3.0.4) over the contiguous United States (CONUS). Biases of hydrologic simulations forced by statistically downscaled climate data relative to the simulation with observation-based gridded data are presented. Each statistical downscaling method produces different meteorological portrayals including precipitation amount, wet-day frequency, and the energy input (i.e., shortwave radiation), and their interplay affects estimations of precipitation partitioning between evapotranspiration and runoff, extreme runoff, and hydrologic states (i.e., snow and soil moisture). The analyses show that BCCA underestimates annual precipitation by as much as −250 mm, leading to unreasonable hydrologic portrayals over the CONUS for all models. Although the other three statistical downscaling methods produce a comparable precipitation bias ranging from −10 to 8 mm across the CONUS, BCSDd severely overestimates the wet-day fraction by up to 0.25, leading to different precipitation partitioning compared to the simulations with other downscaled data. Overall, the choice of downscaling method contributes to less spread in runoff estimates (by a factor of 1.5–3) than the choice of hydrologic model with use of the default parameters if BCCA is excluded.

CEval: All-in-one software for data processing and statistical evaluations in affinity capillary electrophoresis.

PubMed

Dubský, Pavel; Ördögová, Magda; Malý, Michal; Riesová, Martina

2016-05-06

We introduce CEval software (downloadable for free at echmet.natur.cuni.cz) that was developed for quicker and easier electrophoregram evaluation and further data processing in (affinity) capillary electrophoresis. This software allows for automatic peak detection and evaluation of common peak parameters, such as its migration time, area, width etc. Additionally, the software includes a nonlinear regression engine that performs peak fitting with the Haarhoff-van der Linde (HVL) function, including automated initial guess of the HVL function parameters. HVL is a fundamental peak-shape function in electrophoresis, based on which the correct effective mobility of the analyte represented by the peak is evaluated. Effective mobilities of an analyte at various concentrations of a selector can be further stored and plotted in an affinity CE mode. Consequently, the mobility of the free analyte, μA, mobility of the analyte-selector complex, μAS, and the apparent complexation constant, K('), are first guessed automatically from the linearized data plots and subsequently estimated by the means of nonlinear regression. An option that allows two complexation dependencies to be fitted at once is especially convenient for enantioseparations. Statistical processing of these data is also included, which allowed us to: i) express the 95% confidence intervals for the μA, μAS and K(') least-squares estimates, ii) do hypothesis testing on the estimated parameters for the first time. We demonstrate the benefits of the CEval software by inspecting complexation of tryptophan methyl ester with two cyclodextrins, neutral heptakis(2,6-di-O-methyl)-β-CD and charged heptakis(6-O-sulfo)-β-CD. Copyright © 2016 Elsevier B.V. All rights reserved.

Thyroid V50 Highly Predictive of Hypothyroidism in Head-and-Neck Cancer Patients Treated With Intensity-modulated Radiotherapy (IMRT).

PubMed

Sachdev, Sean; Refaat, Tamer; Bacchus, Ian D; Sathiaseelan, Vythialinga; Mittal, Bharat B

2017-08-01

Radiation-induced hypothyroidism affects a significant number of patients with head-and-neck squamous cell cancer (HNSCC). We examined detailed dosimetric and clinical parameters to better determine the risk of hypothyroidism in euthyroid HNSCC patients treated with intensity-modulated radiation therapy (IMRT). From 2006 to 2010, 75 clinically euthyroid patients with HNSCC were treated with sequential IMRT. The cohort included 59 men and 16 females with a median age of 55 years (range, 30 to 89 y) who were treated to a median dose of 70 Gy (range, 60 to 75 Gy) with concurrent chemotherapy in nearly all (95%) cases. Detailed thyroid dosimetric parameters including maximum dose, mean dose, and other parameters (eg, V50-percent volume receiving at least 50 Gy) were obtained. Freedom from hypothyroidism was evaluated using the Kaplan-Meier method. Univariate and multivariate analyses were conducted using Cox regression. After a median follow-up period of 50 months, 25 patients (33%) became hypothyroid. On univariate analysis, thyroid V50 was highly correlated with developing hypothyroidism (P=0.035). Other dosimetric paramaters including mean thyroid dose (P=0.11) and maximum thyroid dose (P=0.39) did not reach statistical significance. On multivariate analysis incorporating patient, tumor, and treatment variables, V50 remained highly statistically significant (P=0.037). Regardless of other factors, for V50>60%, the odds ratio of developing hypothyroidism was 6.76 (P=0.002). In HNSCC patients treated with IMRT, thyroid V50 highly predicts the risk of developing hypothyroidism. V50>60% puts patients at a significantly higher risk of becoming hypothyroid. This can be a useful dose constraint to consider during treatment planning.

Measurement of the hyperelastic properties of 44 pathological ex vivo breast tissue samples

NASA Astrophysics Data System (ADS)

O'Hagan, Joseph J.; Samani, Abbas

2009-04-01

The elastic and hyperelastic properties of biological soft tissues have been of interest to the medical community. There are several biomedical applications where parameters characterizing such properties are critical for a reliable clinical outcome. These applications include surgery planning, needle biopsy and brachtherapy where tissue biomechanical modeling is involved. Another important application is interpreting nonlinear elastography images. While there has been considerable research on the measurement of the linear elastic modulus of small tissue samples, little research has been conducted for measuring parameters that characterize the nonlinear elasticity of tissues included in tissue slice specimens. This work presents hyperelastic measurement results of 44 pathological ex vivo breast tissue samples. For each sample, five hyperelastic models have been used, including the Yeoh, N = 2 polynomial, N = 1 Ogden, Arruda-Boyce, and Veronda-Westmann models. Results show that the Yeoh, polynomial and Ogden models are the most accurate in terms of fitting experimental data. The results indicate that almost all of the parameters corresponding to the pathological tissues are between two times to over two orders of magnitude larger than those of normal tissues, with C11 showing the most significant difference. Furthermore, statistical analysis indicates that C02 of the Yeoh model, and C11 and C20 of the polynomial model have very good potential for cancer classification as they show statistically significant differences for various cancer types, especially for invasive lobular carcinoma. In addition to the potential for use in cancer classification, the presented data are very important for applications such as surgery planning and virtual reality based clinician training systems where accurate nonlinear tissue response modeling is required.

A Comparison of the Forecast Skills among Three Numerical Models

NASA Astrophysics Data System (ADS)

Lu, D.; Reddy, S. R.; White, L. J.

2003-12-01

Three numerical weather forecast models, MM5, COAMPS and WRF, operating with a joint effort of NOAA HU-NCAS and Jackson State University (JSU) during summer 2003 have been chosen to study their forecast skills against observations. The models forecast over the same region with the same initialization, boundary condition, forecast length and spatial resolution. AVN global dataset have been ingested as initial conditions. Grib resolution of 27 km is chosen to represent the current mesoscale model. The forecasts with the length of 36h are performed to output the result with 12h interval. The key parameters used to evaluate the forecast skill include 12h accumulated precipitation, sea level pressure, wind, surface temperature and dew point. Precipitation is evaluated statistically using conventional skill scores, Threat Score (TS) and Bias Score (BS), for different threshold values based on 12h rainfall observations whereas other statistical methods such as Mean Error (ME), Mean Absolute Error(MAE) and Root Mean Square Error (RMSE) are applied to other forecast parameters.

A self-consistency approach to improve microwave rainfall rate estimation from space

NASA Technical Reports Server (NTRS)

Kummerow, Christian; Mack, Robert A.; Hakkarinen, Ida M.

1989-01-01

A multichannel statistical approach is used to retrieve rainfall rates from the brightness temperature T(B) observed by passive microwave radiometers flown on a high-altitude NASA aircraft. T(B) statistics are based upon data generated by a cloud radiative model. This model simulates variabilities in the underlying geophysical parameters of interest, and computes their associated T(B) in each of the available channels. By further imposing the requirement that the observed T(B) agree with the T(B) values corresponding to the retrieved parameters through the cloud radiative transfer model, the results can be made to agree quite well with coincident radar-derived rainfall rates. Some information regarding the cloud vertical structure is also obtained by such an added requirement. The applicability of this technique to satellite retrievals is also investigated. Data which might be observed by satellite-borne radiometers, including the effects of nonuniformly filled footprints, are simulated by the cloud radiative model for this purpose.

Statistical classifiers on multifractal parameters for optical diagnosis of cervical cancer

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Sabyasachi; Pratiher, Sawon; Kumar, Rajeev; Krishnamoorthy, Vigneshram; Pradhan, Asima; Ghosh, Nirmalya; Panigrahi, Prasanta K.

2017-06-01

An augmented set of multifractal parameters with physical interpretations have been proposed to quantify the varying distribution and shape of the multifractal spectrum. The statistical classifier with accuracy of 84.17% validates the adequacy of multi-feature MFDFA characterization of elastic scattering spectroscopy for optical diagnosis of cancer.

Ensemble Solar Forecasting Statistical Quantification and Sensitivity Analysis: Preprint

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

Cheung, WanYin; Zhang, Jie; Florita, Anthony

2015-12-08

Uncertainties associated with solar forecasts present challenges to maintain grid reliability, especially at high solar penetrations. This study aims to quantify the errors associated with the day-ahead solar forecast parameters and the theoretical solar power output for a 51-kW solar power plant in a utility area in the state of Vermont, U.S. Forecasts were generated by three numerical weather prediction (NWP) models, including the Rapid Refresh, the High Resolution Rapid Refresh, and the North American Model, and a machine-learning ensemble model. A photovoltaic (PV) performance model was adopted to calculate theoretical solar power generation using the forecast parameters (e.g., irradiance,more » cell temperature, and wind speed). Errors of the power outputs were quantified using statistical moments and a suite of metrics, such as the normalized root mean squared error (NRMSE). In addition, the PV model's sensitivity to different forecast parameters was quantified and analyzed. Results showed that the ensemble model yielded forecasts in all parameters with the smallest NRMSE. The NRMSE of solar irradiance forecasts of the ensemble NWP model was reduced by 28.10% compared to the best of the three NWP models. Further, the sensitivity analysis indicated that the errors of the forecasted cell temperature attributed only approximately 0.12% to the NRMSE of the power output as opposed to 7.44% from the forecasted solar irradiance.« less

Paleomagnetism.org: An online multi-platform open source environment for paleomagnetic data analysis

NASA Astrophysics Data System (ADS)

Koymans, Mathijs R.; Langereis, Cor G.; Pastor-Galán, Daniel; van Hinsbergen, Douwe J. J.

2016-08-01

This contribution provides an overview of Paleomagnetism.org, an open-source, multi-platform online environment for paleomagnetic data analysis. Paleomagnetism.org provides an interactive environment where paleomagnetic data can be interpreted, evaluated, visualized, and exported. The Paleomagnetism.org application is split in to an interpretation portal, a statistics portal, and a portal for miscellaneous paleomagnetic tools. In the interpretation portal, principle component analysis can be performed on visualized demagnetization diagrams. Interpreted directions and great circles can be combined to find great circle solutions. These directions can be used in the statistics portal, or exported as data and figures. The tools in the statistics portal cover standard Fisher statistics for directions and VGPs, including other statistical parameters used as reliability criteria. Other available tools include an eigenvector approach foldtest, two reversal test including a Monte Carlo simulation on mean directions, and a coordinate bootstrap on the original data. An implementation is included for the detection and correction of inclination shallowing in sediments following TK03.GAD. Finally we provide a module to visualize VGPs and expected paleolatitudes, declinations, and inclinations relative to widely used global apparent polar wander path models in coordinates of major continent-bearing plates. The tools in the miscellaneous portal include a net tectonic rotation (NTR) analysis to restore a body to its paleo-vertical and a bootstrapped oroclinal test using linear regressive techniques, including a modified foldtest around a vertical axis. Paleomagnetism.org provides an integrated approach for researchers to work with visualized (e.g. hemisphere projections, Zijderveld diagrams) paleomagnetic data. The application constructs a custom exportable file that can be shared freely and included in public databases. This exported file contains all data and can later be imported to the application by other researchers. The accessibility and simplicity through which paleomagnetic data can be interpreted, analyzed, visualized, and shared makes Paleomagnetism.org of interest to the community.

Statistical Analysis of Large-Scale Structure of Universe

NASA Astrophysics Data System (ADS)

Tugay, A. V.

While galaxy cluster catalogs were compiled many decades ago, other structural elements of cosmic web are detected at definite level only in the newest works. For example, extragalactic filaments were described by velocity field and SDSS galaxy distribution during the last years. Large-scale structure of the Universe could be also mapped in the future using ATHENA observations in X-rays and SKA in radio band. Until detailed observations are not available for the most volume of Universe, some integral statistical parameters can be used for its description. Such methods as galaxy correlation function, power spectrum, statistical moments and peak statistics are commonly used with this aim. The parameters of power spectrum and other statistics are important for constraining the models of dark matter, dark energy, inflation and brane cosmology. In the present work we describe the growth of large-scale density fluctuations in one- and three-dimensional case with Fourier harmonics of hydrodynamical parameters. In result we get power-law relation for the matter power spectrum.

Histogram analysis of ADC in rectal cancer: associations with different histopathological findings including expression of EGFR, Hif1-alpha, VEGF, p53, PD1, and KI 67. A preliminary study.

PubMed

Meyer, Hans Jonas; Höhn, Annekathrin; Surov, Alexey

2018-04-06

Functional imaging modalities like Diffusion-weighted imaging are increasingly used to predict tumor behavior like cellularity and vascularity in different tumors. Histogram analysis is an emergent imaging analysis, in which every voxel is used to obtain a histogram and therefore statistically information about tumors can be provided. The purpose of this study was to elucidate possible associations between ADC histogram parameters and several immunhistochemical features in rectal cancer. Overall, 11 patients with histologically proven rectal cancer were included into the study. There were 2 (18.18%) females and 9 males with a mean age of 67.1 years. KI 67-index, expression of p53, EGFR, VEGF, and Hif1-alpha were semiautomatically estimated. The tumors were divided into PD1-positive and PD1-negative lesions. ADC histogram analysis was performed as a whole lesion measurement using an in-house matlab application. Spearman's correlation analysis revealed a strong correlation between EGFR expression and ADCmax (p=0.72, P=0.02). None of the vascular parameters (VEGF, Hif1-alpha) correlated with ADC parameters. Kurtosis and skewness correlated inversely with p53 expression (p=-0.64, P=0.03 and p=-0.81, P=0.002, respectively). ADCmedian and ADCmode correlated with Ki67 (p=-0.62, P=0.04 and p=-0.65, P=0.03, respectively). PD1-positive tumors showed statistically significant lower ADCmax values in comparison to PD1-negative tumors, 1.93 ± 0.36 vs 2.32 ± 0.47×10 -3 mm 2 /s, p=0.04. Several associations were identified between histogram parameter derived from ADC maps and EGFR, KI 67 and p53 expression in rectal cancer. Furthermore, ADCmax was different between PD1 positive and PD1 negative tumors indicating an important role of ADC parameters for possible future treatment prediction.

Histogram analysis of ADC in rectal cancer: associations with different histopathological findings including expression of EGFR, Hif1-alpha, VEGF, p53, PD1, and KI 67. A preliminary study

PubMed Central

Meyer, Hans Jonas; Höhn, Annekathrin; Surov, Alexey

2018-01-01

Functional imaging modalities like Diffusion-weighted imaging are increasingly used to predict tumor behavior like cellularity and vascularity in different tumors. Histogram analysis is an emergent imaging analysis, in which every voxel is used to obtain a histogram and therefore statistically information about tumors can be provided. The purpose of this study was to elucidate possible associations between ADC histogram parameters and several immunhistochemical features in rectal cancer. Overall, 11 patients with histologically proven rectal cancer were included into the study. There were 2 (18.18%) females and 9 males with a mean age of 67.1 years. KI 67-index, expression of p53, EGFR, VEGF, and Hif1-alpha were semiautomatically estimated. The tumors were divided into PD1-positive and PD1-negative lesions. ADC histogram analysis was performed as a whole lesion measurement using an in-house matlab application. Spearman's correlation analysis revealed a strong correlation between EGFR expression and ADCmax (p=0.72, P=0.02). None of the vascular parameters (VEGF, Hif1-alpha) correlated with ADC parameters. Kurtosis and skewness correlated inversely with p53 expression (p=-0.64, P=0.03 and p=-0.81, P=0.002, respectively). ADCmedian and ADCmode correlated with Ki67 (p=-0.62, P=0.04 and p=-0.65, P=0.03, respectively). PD1-positive tumors showed statistically significant lower ADCmax values in comparison to PD1-negative tumors, 1.93 ± 0.36 vs 2.32 ± 0.47×10−3mm2/s, p=0.04. Several associations were identified between histogram parameter derived from ADC maps and EGFR, KI 67 and p53 expression in rectal cancer. Furthermore, ADCmax was different between PD1 positive and PD1 negative tumors indicating an important role of ADC parameters for possible future treatment prediction. PMID:29719621

Evaluating performances of simplified physically based landslide susceptibility models.

NASA Astrophysics Data System (ADS)

Capparelli, Giovanna; Formetta, Giuseppe; Versace, Pasquale

2015-04-01

Rainfall induced shallow landslides cause significant damages involving loss of life and properties. Prediction of shallow landslides susceptible locations is a complex task that involves many disciplines: hydrology, geotechnical science, geomorphology, and statistics. Usually to accomplish this task two main approaches are used: statistical or physically based model. This paper presents a package of GIS based models for landslide susceptibility analysis. It was integrated in the NewAge-JGrass hydrological model using the Object Modeling System (OMS) modeling framework. The package includes three simplified physically based models for landslides susceptibility analysis (M1, M2, and M3) and a component for models verifications. It computes eight goodness of fit indices (GOF) by comparing pixel-by-pixel model results and measurements data. Moreover, the package integration in NewAge-JGrass allows the use of other components such as geographic information system tools to manage inputs-output processes, and automatic calibration algorithms to estimate model parameters. The system offers the possibility to investigate and fairly compare the quality and the robustness of models and models parameters, according a procedure that includes: i) model parameters estimation by optimizing each of the GOF index separately, ii) models evaluation in the ROC plane by using each of the optimal parameter set, and iii) GOF robustness evaluation by assessing their sensitivity to the input parameter variation. This procedure was repeated for all three models. The system was applied for a case study in Calabria (Italy) along the Salerno-Reggio Calabria highway, between Cosenza and Altilia municipality. The analysis provided that among all the optimized indices and all the three models, Average Index (AI) optimization coupled with model M3 is the best modeling solution for our test case. This research was funded by PON Project No. 01_01503 "Integrated Systems for Hydrogeological Risk Monitoring, Early Warning and Mitigation Along the Main Lifelines", CUP B31H11000370005, in the framework of the National Operational Program for "Research and Competitiveness" 2007-2013.

Fractional superstatistics from a kinetic approach

NASA Astrophysics Data System (ADS)

Ourabah, Kamel; Tribeche, Mouloud

2018-03-01

Through a kinetic approach, in which temperature fluctuations are taken into account, we obtain generalized fractional statistics interpolating between Fermi-Dirac and Bose-Einstein statistics. The latter correspond to the superstatistical analogues of the Polychronakos and Haldane-Wu statistics. The virial coefficients corresponding to these statistics are worked out and compared to those of an ideal two-dimensional anyon gas. It is shown that the obtained statistics reproduce correctly the second and third virial coefficients of an anyon gas. On this basis, a link is established between the statistical parameter and the strength of fluctuations. A further generalization is suggested by allowing the statistical parameter to fluctuate. As a by-product, superstatistics of ewkons, introduced recently to deal with dark energy [Phys. Rev. E 94, 062115 (2016), 10.1103/PhysRevE.94.062115], are also obtained within the same method.

Using Electronic Data Interchange to Report Product Quality

DTIC Science & Technology

1993-03-01

Numbers 0 31.1 S........................ . . . . ........... .... . .--- . ... N/U 140 SPS Sampling Parameters for Summary Statistics 0 1 N/U 150 REF...DTM Date/Time Reference 0 1 N/U 190 REF Reference Numbers 021 .................................. .......... .. ... NAU 200 STA Statistics 0 1 N/U 210...Measurements 0 1 N/U 120 DTM Date/Time Reference 0 >1 N/U 130 REF Reference Numbers 0 >1 :LOOIV f-SPS N/U 140 SPS Sampling Parameters for Summary Statistics 0 1

Crossover between the Gaussian orthogonal ensemble, the Gaussian unitary ensemble, and Poissonian statistics.

PubMed

Schweiner, Frank; Laturner, Jeanine; Main, Jörg; Wunner, Günter

2017-11-01

Until now only for specific crossovers between Poissonian statistics (P), the statistics of a Gaussian orthogonal ensemble (GOE), or the statistics of a Gaussian unitary ensemble (GUE) have analytical formulas for the level spacing distribution function been derived within random matrix theory. We investigate arbitrary crossovers in the triangle between all three statistics. To this aim we propose an according formula for the level spacing distribution function depending on two parameters. Comparing the behavior of our formula for the special cases of P→GUE, P→GOE, and GOE→GUE with the results from random matrix theory, we prove that these crossovers are described reasonably. Recent investigations by F. Schweiner et al. [Phys. Rev. E 95, 062205 (2017)2470-004510.1103/PhysRevE.95.062205] have shown that the Hamiltonian of magnetoexcitons in cubic semiconductors can exhibit all three statistics in dependence on the system parameters. Evaluating the numerical results for magnetoexcitons in dependence on the excitation energy and on a parameter connected with the cubic valence band structure and comparing the results with the formula proposed allows us to distinguish between regular and chaotic behavior as well as between existent or broken antiunitary symmetries. Increasing one of the two parameters, transitions between different crossovers, e.g., from the P→GOE to the P→GUE crossover, are observed and discussed.

Landslides triggered by the 12 January 2010 Port-au-Prince, Haiti, Mw = 7.0 earthquake: visual interpretation, inventory compiling, and spatial distribution statistical analysis

NASA Astrophysics Data System (ADS)

Xu, C.; Shyu, J. B. H.; Xu, X.

2014-07-01

The 12 January 2010 Port-au-Prince, Haiti, earthquake (Mw= 7.0) triggered tens of thousands of landslides. The purpose of this study is to investigate the correlations of the occurrence of landslides and the thicknesses of their erosion with topographic, geologic, and seismic parameters. A total of 30 828 landslides triggered by the earthquake covered a total area of 15.736 km2, distributed in an area more than 3000 km2, and the volume of landslide accumulation materials is estimated to be about 29 700 000 m3. These landslides are of various types, mostly belonging to shallow disrupted landslides and rock falls, but also include coherent deep-seated landslides and rock slides. These landslides were delineated using pre- and post-earthquake high-resolution satellite images. Spatial distribution maps and contour maps of landslide number density, landslide area percentage, and landslide erosion thickness were constructed in order to analyze the spatial distribution patterns of co-seismic landslides. Statistics of size distribution and morphometric parameters of co-seismic landslides were carried out and were compared with other earthquake events in the world. Four proxies of co-seismic landslide abundance, including landslides centroid number density (LCND), landslide top number density (LTND), landslide area percentage (LAP), and landslide erosion thickness (LET) were used to correlate co-seismic landslides with various environmental parameters. These parameters include elevation, slope angle, slope aspect, slope curvature, topographic position, distance from drainages, lithology, distance from the epicenter, distance from the Enriquillo-Plantain Garden fault, distance along the fault, and peak ground acceleration (PGA). A comparison of these impact parameters on co-seismic landslides shows that slope angle is the strongest impact parameter on co-seismic landslide occurrence. Our co-seismic landslide inventory is much more detailed than other inventories in several previous publications. Therefore, we carried out comparisons of inventories of landslides triggered by the Haiti earthquake with other published results and proposed possible reasons for any differences. We suggest that the empirical functions between earthquake magnitude and co-seismic landslides need to be updated on the basis of the abundant and more complete co-seismic landslide inventories recently available.

Landslides triggered by the 12 January 2010 Mw 7.0 Port-au-Prince, Haiti, earthquake: visual interpretation, inventory compiling and spatial distribution statistical analysis

NASA Astrophysics Data System (ADS)

Xu, C.; Shyu, J. B. H.; Xu, X.-W.

2014-02-01

The 12 January 2010 Port-au-Prince, Haiti, earthquake (Mw 7.0) triggered tens of thousands of landslides. The purpose of this study is to investigate the correlations of the occurrence of landslides and their erosion thicknesses with topographic factors, seismic parameters, and their distance from roads. A total of 30 828 landslides triggered by the earthquake covered a total area of 15.736 km2, distributed in an area more than 3000 km2, and the volume of landslide accumulation materials is estimated to be about 29 700 000 m3. These landslides are of various types, mostly belonging to shallow disrupted landslides and rock falls, but also include coherent deep-seated landslides and rock slides. These landslides were delineated using pre- and post-earthquake high-resolutions satellite images. Spatial distribution maps and contour maps of landslide number density, landslide area percentage, and landslide erosion thickness were constructed in order to analyze the spatial distribution patterns of co-seismic landslides. Statistics of size distribution and morphometric parameters of co-seismic landslides were carried out and were compared with other earthquake events in the world. Four proxies of co-seismic landslide abundance, including landslides centroid number density (LCND), landslide top number density (LTND), landslide area percentage (LAP), and landslide erosion thickness (LET) were used to correlate co-seismic landslides with various landslide controlling parameters. These controlling parameters include elevation, slope angle, slope aspect, slope curvature, topographic position, distance from drainages, lithology, distance from the epicenter, distance from the Enriquillo-Plantain Garden fault, distance along the fault, and peak ground acceleration (PGA). A comparison of these impact parameters on co-seismic landslides shows that slope angle is the strongest impact parameter on co-seismic landslide occurrence. Our co-seismic landslide inventory is much more detailed than other inventories in several previous publications. Therefore, we carried out comparisons of inventories of landslides triggered by the Haiti earthquake with other published results and proposed possible reasons of any differences. We suggest that the empirical functions between earthquake magnitude and co-seismic landslides need to update on the basis of the abundant and more complete co-seismic landslide inventories recently available.

Cosmology constraints from shear peak statistics in Dark Energy Survey Science Verification data

NASA Astrophysics Data System (ADS)

Kacprzak, T.; Kirk, D.; Friedrich, O.; Amara, A.; Refregier, A.; Marian, L.; Dietrich, J. P.; Suchyta, E.; Aleksić, J.; Bacon, D.; Becker, M. R.; Bonnett, C.; Bridle, S. L.; Chang, C.; Eifler, T. F.; Hartley, W. G.; Huff, E. M.; Krause, E.; MacCrann, N.; Melchior, P.; Nicola, A.; Samuroff, S.; Sheldon, E.; Troxel, M. A.; Weller, J.; Zuntz, J.; Abbott, T. M. C.; Abdalla, F. B.; Armstrong, R.; Benoit-Lévy, A.; Bernstein, G. M.; Bernstein, R. A.; Bertin, E.; Brooks, D.; Burke, D. L.; Carnero Rosell, A.; Carrasco Kind, M.; Carretero, J.; Castander, F. J.; Crocce, M.; D'Andrea, C. B.; da Costa, L. N.; Desai, S.; Diehl, H. T.; Evrard, A. E.; Neto, A. Fausti; Flaugher, B.; Fosalba, P.; Frieman, J.; Gerdes, D. W.; Goldstein, D. A.; Gruen, D.; Gruendl, R. A.; Gutierrez, G.; Honscheid, K.; Jain, B.; James, D. J.; Jarvis, M.; Kuehn, K.; Kuropatkin, N.; Lahav, O.; Lima, M.; March, M.; Marshall, J. L.; Martini, P.; Miller, C. J.; Miquel, R.; Mohr, J. J.; Nichol, R. C.; Nord, B.; Plazas, A. A.; Romer, A. K.; Roodman, A.; Rykoff, E. S.; Sanchez, E.; Scarpine, V.; Schubnell, M.; Sevilla-Noarbe, I.; Smith, R. C.; Soares-Santos, M.; Sobreira, F.; Swanson, M. E. C.; Tarle, G.; Thomas, D.; Vikram, V.; Walker, A. R.; Zhang, Y.; DES Collaboration

2016-12-01

Shear peak statistics has gained a lot of attention recently as a practical alternative to the two-point statistics for constraining cosmological parameters. We perform a shear peak statistics analysis of the Dark Energy Survey (DES) Science Verification (SV) data, using weak gravitational lensing measurements from a 139 deg2 field. We measure the abundance of peaks identified in aperture mass maps, as a function of their signal-to-noise ratio, in the signal-to-noise range 04 would require significant corrections, which is why we do not include them in our analysis. We compare our results to the cosmological constraints from the two-point analysis on the SV field and find them to be in good agreement in both the central value and its uncertainty. We discuss prospects for future peak statistics analysis with upcoming DES data.