A criterion for establishing life limits. [for Space Shuttle Main Engine service

NASA Technical Reports Server (NTRS)

Skopp, G. H.; Porter, A. A.

1990-01-01

The development of a rigorous statistical method that would utilize hardware-demonstrated reliability to evaluate hardware capability and provide ground rules for safe flight margin is discussed. A statistical-based method using the Weibull/Weibayes cumulative distribution function is described. Its advantages and inadequacies are pointed out. Another, more advanced procedure, Single Flight Reliability (SFR), determines a life limit which ensures that the reliability of any single flight is never less than a stipulated value at a stipulated confidence level. Application of the SFR method is illustrated.

A Study on Predictive Analytics Application to Ship Machinery Maintenance

DTIC Science & Technology

2013-09-01

Looking at the nature of the time series forecasting method , it would be better applied to offline analysis . The application for real- time online...other system attributes in future. Two techniques of statistical analysis , mainly time series models and cumulative sum control charts, are discussed in...statistical tool employed for the two techniques of statistical analysis . Both time series forecasting as well as CUSUM control charts are shown to be

Real-time Mainshock Forecast by Statistical Discrimination of Foreshock Clusters

NASA Astrophysics Data System (ADS)

Nomura, S.; Ogata, Y.

2016-12-01

Foreshock discremination is one of the most effective ways for short-time forecast of large main shocks. Though many large earthquakes accompany their foreshocks, discreminating them from enormous small earthquakes is difficult and only probabilistic evaluation from their spatio-temporal features and magnitude evolution may be available. Logistic regression is the statistical learning method best suited to such binary pattern recognition problems where estimates of a-posteriori probability of class membership are required. Statistical learning methods can keep learning discreminating features from updating catalog and give probabilistic recognition of forecast in real time. We estimated a non-linear function of foreshock proportion by smooth spline bases and evaluate the possibility of foreshocks by the logit function. In this study, we classified foreshocks from earthquake catalog by the Japan Meteorological Agency by single-link clustering methods and learned spatial and temporal features of foreshocks by the probability density ratio estimation. We use the epicentral locations, time spans and difference in magnitudes for learning and forecasting. Magnitudes of main shocks are also predicted our method by incorporating b-values into our method. We discuss the spatial pattern of foreshocks from the classifier composed by our model. We also implement a back test to validate predictive performance of the model by this catalog.

Statistical methods and errors in family medicine articles between 2010 and 2014-Suez Canal University, Egypt: A cross-sectional study

PubMed Central

Nour-Eldein, Hebatallah

2016-01-01

Background: With limited statistical knowledge of most physicians it is not uncommon to find statistical errors in research articles. Objectives: To determine the statistical methods and to assess the statistical errors in family medicine (FM) research articles that were published between 2010 and 2014. Methods: This was a cross-sectional study. All 66 FM research articles that were published over 5 years by FM authors with affiliation to Suez Canal University were screened by the researcher between May and August 2015. Types and frequencies of statistical methods were reviewed in all 66 FM articles. All 60 articles with identified inferential statistics were examined for statistical errors and deficiencies. A comprehensive 58-item checklist based on statistical guidelines was used to evaluate the statistical quality of FM articles. Results: Inferential methods were recorded in 62/66 (93.9%) of FM articles. Advanced analyses were used in 29/66 (43.9%). Contingency tables 38/66 (57.6%), regression (logistic, linear) 26/66 (39.4%), and t-test 17/66 (25.8%) were the most commonly used inferential tests. Within 60 FM articles with identified inferential statistics, no prior sample size 19/60 (31.7%), application of wrong statistical tests 17/60 (28.3%), incomplete documentation of statistics 59/60 (98.3%), reporting P value without test statistics 32/60 (53.3%), no reporting confidence interval with effect size measures 12/60 (20.0%), use of mean (standard deviation) to describe ordinal/nonnormal data 8/60 (13.3%), and errors related to interpretation were mainly for conclusions without support by the study data 5/60 (8.3%). Conclusion: Inferential statistics were used in the majority of FM articles. Data analysis and reporting statistics are areas for improvement in FM research articles. PMID:27453839

IDENTIFICATION OF REGIME SHIFTS IN TIME SERIES USING NEIGHBORHOOD STATISTICS

EPA Science Inventory

The identification of alternative dynamic regimes in ecological systems requires several lines of evidence. Previous work on time series analysis of dynamic regimes includes mainly model-fitting methods. We introduce two methods that do not use models. These approaches use state-...

[The principal components analysis--method to classify the statistical variables with applications in medicine].

PubMed

Dascălu, Cristina Gena; Antohe, Magda Ecaterina

2009-01-01

Based on the eigenvalues and the eigenvectors analysis, the principal component analysis has the purpose to identify the subspace of the main components from a set of parameters, which are enough to characterize the whole set of parameters. Interpreting the data for analysis as a cloud of points, we find through geometrical transformations the directions where the cloud's dispersion is maximal--the lines that pass through the cloud's center of weight and have a maximal density of points around them (by defining an appropriate criteria function and its minimization. This method can be successfully used in order to simplify the statistical analysis on questionnaires--because it helps us to select from a set of items only the most relevant ones, which cover the variations of the whole set of data. For instance, in the presented sample we started from a questionnaire with 28 items and, applying the principal component analysis we identified 7 principal components--or main items--fact that simplifies significantly the further data statistical analysis.

Pitfalls of national routine death statistics for maternal mortality study.

PubMed

Saucedo, Monica; Bouvier-Colle, Marie-Hélène; Chantry, Anne A; Lamarche-Vadel, Agathe; Rey, Grégoire; Deneux-Tharaux, Catherine

2014-11-01

The lessons learned from the study of maternal deaths depend on the accuracy of data. Our objective was to assess time trends in the underestimation of maternal mortality (MM) in the national routine death statistics in France and to evaluate their current accuracy for the selection and causes of maternal deaths. National data obtained by enhanced methods in 1989, 1999, and 2007-09 were used as the gold standard to assess time trends in the underestimation of MM ratios (MMRs) in death statistics. Enhanced data and death statistics for 2007-09 were further compared by characterising false negatives (FNs) and false positives (FPs). The distribution of cause-specific MMRs, as assessed by each system, was described. Underestimation of MM in death statistics decreased from 55.6% in 1989 to 11.4% in 2007-09 (P < 0.001). In 2007-09, of 787 pregnancy-associated deaths, 254 were classified as maternal by the enhanced system and 211 by the death statistics; 34% of maternal deaths in the enhanced system were FNs in the death statistics, and 20% of maternal deaths in the death statistics were FPs. The hierarchy of causes of MM differed between the two systems. The discordances were mainly explained by the lack of precision in the drafting of death certificates by clinicians. Although the underestimation of MM in routine death statistics has decreased substantially over time, one third of maternal deaths remain unidentified, and the main causes of death are incorrectly identified in these data. Defining relevant priorities in maternal health requires the use of enhanced methods for MM study. © 2014 John Wiley & Sons Ltd.

Linear regression models and k-means clustering for statistical analysis of fNIRS data.

PubMed

Bonomini, Viola; Zucchelli, Lucia; Re, Rebecca; Ieva, Francesca; Spinelli, Lorenzo; Contini, Davide; Paganoni, Anna; Torricelli, Alessandro

2015-02-01

We propose a new algorithm, based on a linear regression model, to statistically estimate the hemodynamic activations in fNIRS data sets. The main concern guiding the algorithm development was the minimization of assumptions and approximations made on the data set for the application of statistical tests. Further, we propose a K-means method to cluster fNIRS data (i.e. channels) as activated or not activated. The methods were validated both on simulated and in vivo fNIRS data. A time domain (TD) fNIRS technique was preferred because of its high performances in discriminating cortical activation and superficial physiological changes. However, the proposed method is also applicable to continuous wave or frequency domain fNIRS data sets.

Linear regression models and k-means clustering for statistical analysis of fNIRS data

PubMed Central

Bonomini, Viola; Zucchelli, Lucia; Re, Rebecca; Ieva, Francesca; Spinelli, Lorenzo; Contini, Davide; Paganoni, Anna; Torricelli, Alessandro

2015-01-01

We propose a new algorithm, based on a linear regression model, to statistically estimate the hemodynamic activations in fNIRS data sets. The main concern guiding the algorithm development was the minimization of assumptions and approximations made on the data set for the application of statistical tests. Further, we propose a K-means method to cluster fNIRS data (i.e. channels) as activated or not activated. The methods were validated both on simulated and in vivo fNIRS data. A time domain (TD) fNIRS technique was preferred because of its high performances in discriminating cortical activation and superficial physiological changes. However, the proposed method is also applicable to continuous wave or frequency domain fNIRS data sets. PMID:25780751

The size of a pilot study for a clinical trial should be calculated in relation to considerations of precision and efficiency.

PubMed

Sim, Julius; Lewis, Martyn

2012-03-01

To investigate methods to determine the size of a pilot study to inform a power calculation for a randomized controlled trial (RCT) using an interval/ratio outcome measure. Calculations based on confidence intervals (CIs) for the sample standard deviation (SD). Based on CIs for the sample SD, methods are demonstrated whereby (1) the observed SD can be adjusted to secure the desired level of statistical power in the main study with a specified level of confidence; (2) the sample for the main study, if calculated using the observed SD, can be adjusted, again to obtain the desired level of statistical power in the main study; (3) the power of the main study can be calculated for the situation in which the SD in the pilot study proves to be an underestimate of the true SD; and (4) an "efficient" pilot size can be determined to minimize the combined size of the pilot and main RCT. Trialists should calculate the appropriate size of a pilot study, just as they should the size of the main RCT, taking into account the twin needs to demonstrate efficiency in terms of recruitment and to produce precise estimates of treatment effect. Copyright © 2012 Elsevier Inc. All rights reserved.

Application of statistical classification methods for predicting the acceptability of well-water quality

NASA Astrophysics Data System (ADS)

Cameron, Enrico; Pilla, Giorgio; Stella, Fabio A.

2018-06-01

The application of statistical classification methods is investigated—in comparison also to spatial interpolation methods—for predicting the acceptability of well-water quality in a situation where an effective quantitative model of the hydrogeological system under consideration cannot be developed. In the example area in northern Italy, in particular, the aquifer is locally affected by saline water and the concentration of chloride is the main indicator of both saltwater occurrence and groundwater quality. The goal is to predict if the chloride concentration in a water well will exceed the allowable concentration so that the water is unfit for the intended use. A statistical classification algorithm achieved the best predictive performances and the results of the study show that statistical classification methods provide further tools for dealing with groundwater quality problems concerning hydrogeological systems that are too difficult to describe analytically or to simulate effectively.

Detecting subtle hydrochemical anomalies with multivariate statistics: an example from homogeneous groundwaters in the Great Artesian Basin, Australia

NASA Astrophysics Data System (ADS)

O'Shea, Bethany; Jankowski, Jerzy

2006-12-01

The major ion composition of Great Artesian Basin groundwater in the lower Namoi River valley is relatively homogeneous in chemical composition. Traditional graphical techniques have been combined with multivariate statistical methods to determine whether subtle differences in the chemical composition of these waters can be delineated. Hierarchical cluster analysis and principal components analysis were successful in delineating minor variations within the groundwaters of the study area that were not visually identified in the graphical techniques applied. Hydrochemical interpretation allowed geochemical processes to be identified in each statistically defined water type and illustrated how these groundwaters differ from one another. Three main geochemical processes were identified in the groundwaters: ion exchange, precipitation, and mixing between waters from different sources. Both statistical methods delineated an anomalous sample suspected of being influenced by magmatic CO2 input. The use of statistical methods to complement traditional graphical techniques for waters appearing homogeneous is emphasized for all investigations of this type. Copyright

Comparison of Adaline and Multiple Linear Regression Methods for Rainfall Forecasting

NASA Astrophysics Data System (ADS)

Sutawinaya, IP; Astawa, INGA; Hariyanti, NKD

2018-01-01

Heavy rainfall can cause disaster, therefore need a forecast to predict rainfall intensity. Main factor that cause flooding is there is a high rainfall intensity and it makes the river become overcapacity. This will cause flooding around the area. Rainfall factor is a dynamic factor, so rainfall is very interesting to be studied. In order to support the rainfall forecasting, there are methods that can be used from Artificial Intelligence (AI) to statistic. In this research, we used Adaline for AI method and Regression for statistic method. The more accurate forecast result shows the method that used is good for forecasting the rainfall. Through those methods, we expected which is the best method for rainfall forecasting here.

A simple method to accurately position Port-A-Cath without the aid of intraoperative fluoroscopy or other localizing devices.

PubMed

Horng, Huann-Cheng; Yuan, Chiou-Chung; Chao, Kuan-Chong; Cheng, Ming-Huei; Wang, Peng-Hui

2007-06-01

To evaluate the efficacy and acceptability of the Port-A-Cath (PAC) insertion method with (conventional group as II) and without (modified group as I) the aid of intraoperative fluoroscopy or other localizing devices. A total of 158 women with various kinds of gynecological cancers warranting PAC insertion (n = 86 in group I and n = 72 in group II, respectively) were evaluated. Data for analyses included patient age, main disease, dislocation site, surgical time, complications, and catheter outcome. There was no statistical difference between the two groups in terms of age, main disease, complications, and the experiencing of patent catheters. However, appropriate positioning (100% in group I, and 82% in group II) in the superior vena cava (SVC) showed statistical differences between the two groups (P = 0.001). In addition, the surgical time in group I was statistically shorter than that in group II (P < 0.001). The modified method for inserting the PAC offered the following benefits: including avoiding X-ray exposure for both the operator and the patient, defining the appropriate position in the SVC, and less surgical time. (c) 2007 Wiley-Liss, Inc.

A model and variance reduction method for computing statistical outputs of stochastic elliptic partial differential equations

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

Vidal-Codina, F., E-mail: fvidal@mit.edu; Nguyen, N.C., E-mail: cuongng@mit.edu; Giles, M.B., E-mail: mike.giles@maths.ox.ac.uk

We present a model and variance reduction method for the fast and reliable computation of statistical outputs of stochastic elliptic partial differential equations. Our method consists of three main ingredients: (1) the hybridizable discontinuous Galerkin (HDG) discretization of elliptic partial differential equations (PDEs), which allows us to obtain high-order accurate solutions of the governing PDE; (2) the reduced basis method for a new HDG discretization of the underlying PDE to enable real-time solution of the parameterized PDE in the presence of stochastic parameters; and (3) a multilevel variance reduction method that exploits the statistical correlation among the different reduced basismore » approximations and the high-fidelity HDG discretization to accelerate the convergence of the Monte Carlo simulations. The multilevel variance reduction method provides efficient computation of the statistical outputs by shifting most of the computational burden from the high-fidelity HDG approximation to the reduced basis approximations. Furthermore, we develop a posteriori error estimates for our approximations of the statistical outputs. Based on these error estimates, we propose an algorithm for optimally choosing both the dimensions of the reduced basis approximations and the sizes of Monte Carlo samples to achieve a given error tolerance. We provide numerical examples to demonstrate the performance of the proposed method.« less

Statistical methods and errors in family medicine articles between 2010 and 2014-Suez Canal University, Egypt: A cross-sectional study.

PubMed

Nour-Eldein, Hebatallah

2016-01-01

With limited statistical knowledge of most physicians it is not uncommon to find statistical errors in research articles. To determine the statistical methods and to assess the statistical errors in family medicine (FM) research articles that were published between 2010 and 2014. This was a cross-sectional study. All 66 FM research articles that were published over 5 years by FM authors with affiliation to Suez Canal University were screened by the researcher between May and August 2015. Types and frequencies of statistical methods were reviewed in all 66 FM articles. All 60 articles with identified inferential statistics were examined for statistical errors and deficiencies. A comprehensive 58-item checklist based on statistical guidelines was used to evaluate the statistical quality of FM articles. Inferential methods were recorded in 62/66 (93.9%) of FM articles. Advanced analyses were used in 29/66 (43.9%). Contingency tables 38/66 (57.6%), regression (logistic, linear) 26/66 (39.4%), and t-test 17/66 (25.8%) were the most commonly used inferential tests. Within 60 FM articles with identified inferential statistics, no prior sample size 19/60 (31.7%), application of wrong statistical tests 17/60 (28.3%), incomplete documentation of statistics 59/60 (98.3%), reporting P value without test statistics 32/60 (53.3%), no reporting confidence interval with effect size measures 12/60 (20.0%), use of mean (standard deviation) to describe ordinal/nonnormal data 8/60 (13.3%), and errors related to interpretation were mainly for conclusions without support by the study data 5/60 (8.3%). Inferential statistics were used in the majority of FM articles. Data analysis and reporting statistics are areas for improvement in FM research articles.

Bayesian Tracking of Emerging Epidemics Using Ensemble Optimal Statistical Interpolation

PubMed Central

Cobb, Loren; Krishnamurthy, Ashok; Mandel, Jan; Beezley, Jonathan D.

2014-01-01

We present a preliminary test of the Ensemble Optimal Statistical Interpolation (EnOSI) method for the statistical tracking of an emerging epidemic, with a comparison to its popular relative for Bayesian data assimilation, the Ensemble Kalman Filter (EnKF). The spatial data for this test was generated by a spatial susceptible-infectious-removed (S-I-R) epidemic model of an airborne infectious disease. Both tracking methods in this test employed Poisson rather than Gaussian noise, so as to handle epidemic data more accurately. The EnOSI and EnKF tracking methods worked well on the main body of the simulated spatial epidemic, but the EnOSI was able to detect and track a distant secondary focus of infection that the EnKF missed entirely. PMID:25113590

Bayes and the Law

PubMed Central

Fenton, Norman; Neil, Martin; Berger, Daniel

2016-01-01

Although the last forty years has seen considerable growth in the use of statistics in legal proceedings, it is primarily classical statistical methods rather than Bayesian methods that have been used. Yet the Bayesian approach avoids many of the problems of classical statistics and is also well suited to a broader range of problems. This paper reviews the potential and actual use of Bayes in the law and explains the main reasons for its lack of impact on legal practice. These include misconceptions by the legal community about Bayes’ theorem, over-reliance on the use of the likelihood ratio and the lack of adoption of modern computational methods. We argue that Bayesian Networks (BNs), which automatically produce the necessary Bayesian calculations, provide an opportunity to address most concerns about using Bayes in the law. PMID:27398389

Bayes and the Law.

PubMed

Fenton, Norman; Neil, Martin; Berger, Daniel

2016-06-01

Although the last forty years has seen considerable growth in the use of statistics in legal proceedings, it is primarily classical statistical methods rather than Bayesian methods that have been used. Yet the Bayesian approach avoids many of the problems of classical statistics and is also well suited to a broader range of problems. This paper reviews the potential and actual use of Bayes in the law and explains the main reasons for its lack of impact on legal practice. These include misconceptions by the legal community about Bayes' theorem, over-reliance on the use of the likelihood ratio and the lack of adoption of modern computational methods. We argue that Bayesian Networks (BNs), which automatically produce the necessary Bayesian calculations, provide an opportunity to address most concerns about using Bayes in the law.

Potential errors and misuse of statistics in studies on leakage in endodontics.

PubMed

Lucena, C; Lopez, J M; Pulgar, R; Abalos, C; Valderrama, M J

2013-04-01

To assess the quality of the statistical methodology used in studies of leakage in Endodontics, and to compare the results found using appropriate versus inappropriate inferential statistical methods. The search strategy used the descriptors 'root filling' 'microleakage', 'dye penetration', 'dye leakage', 'polymicrobial leakage' and 'fluid filtration' for the time interval 2001-2010 in journals within the categories 'Dentistry, Oral Surgery and Medicine' and 'Materials Science, Biomaterials' of the Journal Citation Report. All retrieved articles were reviewed to find potential pitfalls in statistical methodology that may be encountered during study design, data management or data analysis. The database included 209 papers. In all the studies reviewed, the statistical methods used were appropriate for the category attributed to the outcome variable, but in 41% of the cases, the chi-square test or parametric methods were inappropriately selected subsequently. In 2% of the papers, no statistical test was used. In 99% of cases, a statistically 'significant' or 'not significant' effect was reported as a main finding, whilst only 1% also presented an estimation of the magnitude of the effect. When the appropriate statistical methods were applied in the studies with originally inappropriate data analysis, the conclusions changed in 19% of the cases. Statistical deficiencies in leakage studies may affect their results and interpretation and might be one of the reasons for the poor agreement amongst the reported findings. Therefore, more effort should be made to standardize statistical methodology. © 2012 International Endodontic Journal.

Effect Size as the Essential Statistic in Developing Methods for mTBI Diagnosis.

PubMed

Gibson, Douglas Brandt

2015-01-01

The descriptive statistic known as "effect size" measures the distinguishability of two sets of data. Distingishability is at the core of diagnosis. This article is intended to point out the importance of effect size in the development of effective diagnostics for mild traumatic brain injury and to point out the applicability of the effect size statistic in comparing diagnostic efficiency across the main proposed TBI diagnostic methods: psychological, physiological, biochemical, and radiologic. Comparing diagnostic approaches is difficult because different researcher in different fields have different approaches to measuring efficacy. Converting diverse measures to effect sizes, as is done in meta-analysis, is a relatively easy way to make studies comparable.

Relationships between airborne pollen grains, wind direction and land cover using GIS and circular statistics.

PubMed

Maya-Manzano, J M; Sadyś, M; Tormo-Molina, R; Fernández-Rodríguez, S; Oteros, J; Silva-Palacios, I; Gonzalo-Garijo, A

2017-04-15

Airborne bio-aerosol content (mainly pollen and spores) depends on the surrounding vegetation and weather conditions, particularly wind direction. In order to understand this issue, maps of the main land cover in influence areas of 10km in radius surrounding pollen traps were created. Atmospheric content of the most abundant 14 pollen types was analysed in relation to the predominant wind directions measured in three localities of SW of Iberian Peninsula, from March 2011 to March 2014. Three Hirst type traps were used for aerobiological monitoring. The surface area for each land cover category was calculated and wind direction analysis was approached by using circular statistics. This method could be helpful for estimating the potential risk of exposure to various pollen types. Thus, the main land cover was different for each monitoring location, being irrigated crops, pastures and hardwood forests the main categories among 11 types described. Comparison of the pollen content with the predominant winds and land cover shows that the atmospheric pollen concentration is related to some source areas identified in the inventory. The study found that some pollen types (e.g. Plantago, Fraxinus-Phillyrea, Alnus) come from local sources but other pollen types (e.g. Quercus) are mostly coming from longer distances. As main conclusions, airborne particle concentrations can be effectively split by addressing wind with circular statistics. By combining circular statistics and GIS method with aerobiological data, we have created a useful tool for understanding pollen origin. Some pollen loads can be explained by immediate surrounding landscape and observed wind patterns for most of the time. However, other factors like medium or long-distance transport or even pollen trap location within a city, may occasionally affect the pollen load recorded using an air sampler. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Woodroffe, J. R.; Brito, T. V.; Jordanova, V. K.

In the standard practice of neutron multiplicity counting , the first three sampled factorial moments of the event triggered neutron count distribution were used to quantify the three main neutron source terms: the spontaneous fissile material effective mass, the relative (α,n) production and the induced fission source responsible for multiplication. Our study compares three methods to quantify the statistical uncertainty of the estimated mass: the bootstrap method, propagation of variance through moments, and statistical analysis of cycle data method. Each of the three methods was implemented on a set of four different NMC measurements, held at the JRC-laboratory in Ispra,more » Italy, sampling four different Pu samples in a standard Plutonium Scrap Multiplicity Counter (PSMC) well counter.« less

Data-optimized source modeling with the Backwards Liouville Test–Kinetic method

DOE PAGES

Woodroffe, J. R.; Brito, T. V.; Jordanova, V. K.; ...

2017-09-14

In the standard practice of neutron multiplicity counting , the first three sampled factorial moments of the event triggered neutron count distribution were used to quantify the three main neutron source terms: the spontaneous fissile material effective mass, the relative (α,n) production and the induced fission source responsible for multiplication. Our study compares three methods to quantify the statistical uncertainty of the estimated mass: the bootstrap method, propagation of variance through moments, and statistical analysis of cycle data method. Each of the three methods was implemented on a set of four different NMC measurements, held at the JRC-laboratory in Ispra,more » Italy, sampling four different Pu samples in a standard Plutonium Scrap Multiplicity Counter (PSMC) well counter.« less

Statistical testing of association between menstruation and migraine.

PubMed

Barra, Mathias; Dahl, Fredrik A; Vetvik, Kjersti G

2015-02-01

To repair and refine a previously proposed method for statistical analysis of association between migraine and menstruation. Menstrually related migraine (MRM) affects about 20% of female migraineurs in the general population. The exact pathophysiological link from menstruation to migraine is hypothesized to be through fluctuations in female reproductive hormones, but the exact mechanisms remain unknown. Therefore, the main diagnostic criterion today is concurrency of migraine attacks with menstruation. Methods aiming to exclude spurious associations are wanted, so that further research into these mechanisms can be performed on a population with a true association. The statistical method is based on a simple two-parameter null model of MRM (which allows for simulation modeling), and Fisher's exact test (with mid-p correction) applied to standard 2 × 2 contingency tables derived from the patients' headache diaries. Our method is a corrected version of a previously published flawed framework. To our best knowledge, no other published methods for establishing a menstruation-migraine association by statistical means exist today. The probabilistic methodology shows good performance when subjected to receiver operator characteristic curve analysis. Quick reference cutoff values for the clinical setting were tabulated for assessing association given a patient's headache history. In this paper, we correct a proposed method for establishing association between menstruation and migraine by statistical methods. We conclude that the proposed standard of 3-cycle observations prior to setting an MRM diagnosis should be extended with at least one perimenstrual window to obtain sufficient information for statistical processing. © 2014 American Headache Society.

Advantages of Social Network Analysis in Educational Research

ERIC Educational Resources Information Center

Ushakov, K. M.; Kukso, K. N.

2015-01-01

Currently one of the main tools for the large scale studies of schools is statistical analysis. Although it is the most common method and it offers greatest opportunities for analysis, there are other quantitative methods for studying schools, such as network analysis. We discuss the potential advantages that network analysis has for educational…

Post-processing method for wind speed ensemble forecast using wind speed and direction

NASA Astrophysics Data System (ADS)

Sofie Eide, Siri; Bjørnar Bremnes, John; Steinsland, Ingelin

2017-04-01

Statistical methods are widely applied to enhance the quality of both deterministic and ensemble NWP forecasts. In many situations, like wind speed forecasting, most of the predictive information is contained in one variable in the NWP models. However, in statistical calibration of deterministic forecasts it is often seen that including more variables can further improve forecast skill. For ensembles this is rarely taken advantage of, mainly due to that it is generally not straightforward how to include multiple variables. In this study, it is demonstrated how multiple variables can be included in Bayesian model averaging (BMA) by using a flexible regression method for estimating the conditional means. The method is applied to wind speed forecasting at 204 Norwegian stations based on wind speed and direction forecasts from the ECMWF ensemble system. At about 85 % of the sites the ensemble forecasts were improved in terms of CRPS by adding wind direction as predictor compared to only using wind speed. On average the improvements were about 5 %, but mainly for moderate to strong wind situations. For weak wind speeds adding wind direction had more or less neutral impact.

[A Review on the Use of Effect Size in Nursing Research].

PubMed

Kang, Hyuncheol; Yeon, Kyupil; Han, Sang Tae

2015-10-01

The purpose of this study was to introduce the main concepts of statistical testing and effect size and to provide researchers in nursing science with guidance on how to calculate the effect size for the statistical analysis methods mainly used in nursing. For t-test, analysis of variance, correlation analysis, regression analysis which are used frequently in nursing research, the generally accepted definitions of the effect size were explained. Some formulae for calculating the effect size are described with several examples in nursing research. Furthermore, the authors present the required minimum sample size for each example utilizing G*Power 3 software that is the most widely used program for calculating sample size. It is noted that statistical significance testing and effect size measurement serve different purposes, and the reliance on only one side may be misleading. Some practical guidelines are recommended for combining statistical significance testing and effect size measure in order to make more balanced decisions in quantitative analyses.

Pathway analysis with next-generation sequencing data.

PubMed

Zhao, Jinying; Zhu, Yun; Boerwinkle, Eric; Xiong, Momiao

2015-04-01

Although pathway analysis methods have been developed and successfully applied to association studies of common variants, the statistical methods for pathway-based association analysis of rare variants have not been well developed. Many investigators observed highly inflated false-positive rates and low power in pathway-based tests of association of rare variants. The inflated false-positive rates and low true-positive rates of the current methods are mainly due to their lack of ability to account for gametic phase disequilibrium. To overcome these serious limitations, we develop a novel statistic that is based on the smoothed functional principal component analysis (SFPCA) for pathway association tests with next-generation sequencing data. The developed statistic has the ability to capture position-level variant information and account for gametic phase disequilibrium. By intensive simulations, we demonstrate that the SFPCA-based statistic for testing pathway association with either rare or common or both rare and common variants has the correct type 1 error rates. Also the power of the SFPCA-based statistic and 22 additional existing statistics are evaluated. We found that the SFPCA-based statistic has a much higher power than other existing statistics in all the scenarios considered. To further evaluate its performance, the SFPCA-based statistic is applied to pathway analysis of exome sequencing data in the early-onset myocardial infarction (EOMI) project. We identify three pathways significantly associated with EOMI after the Bonferroni correction. In addition, our preliminary results show that the SFPCA-based statistic has much smaller P-values to identify pathway association than other existing methods.

Practical statistics in pain research.

PubMed

Kim, Tae Kyun

2017-10-01

Pain is subjective, while statistics related to pain research are objective. This review was written to help researchers involved in pain research make statistical decisions. The main issues are related with the level of scales that are often used in pain research, the choice of statistical methods between parametric or nonparametric statistics, and problems which arise from repeated measurements. In the field of pain research, parametric statistics used to be applied in an erroneous way. This is closely related with the scales of data and repeated measurements. The level of scales includes nominal, ordinal, interval, and ratio scales. The level of scales affects the choice of statistics between parametric or non-parametric methods. In the field of pain research, the most frequently used pain assessment scale is the ordinal scale, which would include the visual analogue scale (VAS). There used to be another view, however, which considered the VAS to be an interval or ratio scale, so that the usage of parametric statistics would be accepted practically in some cases. Repeated measurements of the same subjects always complicates statistics. It means that measurements inevitably have correlations between each other, and would preclude the application of one-way ANOVA in which independence between the measurements is necessary. Repeated measures of ANOVA (RMANOVA), however, would permit the comparison between the correlated measurements as long as the condition of sphericity assumption is satisfied. Conclusively, parametric statistical methods should be used only when the assumptions of parametric statistics, such as normality and sphericity, are established.

A powerful score-based test statistic for detecting gene-gene co-association.

PubMed

Xu, Jing; Yuan, Zhongshang; Ji, Jiadong; Zhang, Xiaoshuai; Li, Hongkai; Wu, Xuesen; Xue, Fuzhong; Liu, Yanxun

2016-01-29

The genetic variants identified by Genome-wide association study (GWAS) can only account for a small proportion of the total heritability for complex disease. The existence of gene-gene joint effects which contains the main effects and their co-association is one of the possible explanations for the "missing heritability" problems. Gene-gene co-association refers to the extent to which the joint effects of two genes differ from the main effects, not only due to the traditional interaction under nearly independent condition but the correlation between genes. Generally, genes tend to work collaboratively within specific pathway or network contributing to the disease and the specific disease-associated locus will often be highly correlated (e.g. single nucleotide polymorphisms (SNPs) in linkage disequilibrium). Therefore, we proposed a novel score-based statistic (SBS) as a gene-based method for detecting gene-gene co-association. Various simulations illustrate that, under different sample sizes, marginal effects of causal SNPs and co-association levels, the proposed SBS has the better performance than other existed methods including single SNP-based and principle component analysis (PCA)-based logistic regression model, the statistics based on canonical correlations (CCU), kernel canonical correlation analysis (KCCU), partial least squares path modeling (PLSPM) and delta-square (δ (2)) statistic. The real data analysis of rheumatoid arthritis (RA) further confirmed its advantages in practice. SBS is a powerful and efficient gene-based method for detecting gene-gene co-association.

Statistical Design Model (SDM) of satellite thermal control subsystem

NASA Astrophysics Data System (ADS)

Mirshams, Mehran; Zabihian, Ehsan; Aarabi Chamalishahi, Mahdi

2016-07-01

Satellites thermal control, is a satellite subsystem that its main task is keeping the satellite components at its own survival and activity temperatures. Ability of satellite thermal control plays a key role in satisfying satellite's operational requirements and designing this subsystem is a part of satellite design. In the other hand due to the lack of information provided by companies and designers still doesn't have a specific design process while it is one of the fundamental subsystems. The aim of this paper, is to identify and extract statistical design models of spacecraft thermal control subsystem by using SDM design method. This method analyses statistical data with a particular procedure. To implement SDM method, a complete database is required. Therefore, we first collect spacecraft data and create a database, and then we extract statistical graphs using Microsoft Excel, from which we further extract mathematical models. Inputs parameters of the method are mass, mission, and life time of the satellite. For this purpose at first thermal control subsystem has been introduced and hardware using in the this subsystem and its variants has been investigated. In the next part different statistical models has been mentioned and a brief compare will be between them. Finally, this paper particular statistical model is extracted from collected statistical data. Process of testing the accuracy and verifying the method use a case study. Which by the comparisons between the specifications of thermal control subsystem of a fabricated satellite and the analyses results, the methodology in this paper was proved to be effective. Key Words: Thermal control subsystem design, Statistical design model (SDM), Satellite conceptual design, Thermal hardware

Estimating the mass variance in neutron multiplicity counting-A comparison of approaches

NASA Astrophysics Data System (ADS)

Dubi, C.; Croft, S.; Favalli, A.; Ocherashvili, A.; Pedersen, B.

2017-12-01

In the standard practice of neutron multiplicity counting , the first three sampled factorial moments of the event triggered neutron count distribution are used to quantify the three main neutron source terms: the spontaneous fissile material effective mass, the relative (α , n) production and the induced fission source responsible for multiplication. This study compares three methods to quantify the statistical uncertainty of the estimated mass: the bootstrap method, propagation of variance through moments, and statistical analysis of cycle data method. Each of the three methods was implemented on a set of four different NMC measurements, held at the JRC-laboratory in Ispra, Italy, sampling four different Pu samples in a standard Plutonium Scrap Multiplicity Counter (PSMC) well counter.

Estimating the mass variance in neutron multiplicity counting $-$ A comparison of approaches

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

Dubi, C.; Croft, S.; Favalli, A.

In the standard practice of neutron multiplicity counting, the first three sampled factorial moments of the event triggered neutron count distribution are used to quantify the three main neutron source terms: the spontaneous fissile material effective mass, the relative (α,n) production and the induced fission source responsible for multiplication. This study compares three methods to quantify the statistical uncertainty of the estimated mass: the bootstrap method, propagation of variance through moments, and statistical analysis of cycle data method. Each of the three methods was implemented on a set of four different NMC measurements, held at the JRC-laboratory in Ispra, Italy,more » sampling four different Pu samples in a standard Plutonium Scrap Multiplicity Counter (PSMC) well counter.« less

Estimating the mass variance in neutron multiplicity counting $-$ A comparison of approaches

DOE PAGES

Dubi, C.; Croft, S.; Favalli, A.; ...

2017-09-14

In the standard practice of neutron multiplicity counting, the first three sampled factorial moments of the event triggered neutron count distribution are used to quantify the three main neutron source terms: the spontaneous fissile material effective mass, the relative (α,n) production and the induced fission source responsible for multiplication. This study compares three methods to quantify the statistical uncertainty of the estimated mass: the bootstrap method, propagation of variance through moments, and statistical analysis of cycle data method. Each of the three methods was implemented on a set of four different NMC measurements, held at the JRC-laboratory in Ispra, Italy,more » sampling four different Pu samples in a standard Plutonium Scrap Multiplicity Counter (PSMC) well counter.« less

The assessment of lower face morphology changes in edentulous patients after prosthodontic rehabilitation, using two methods of measurement.

PubMed

Jivănescu, Anca; Bratu, Dana Cristina; Tomescu, Lucian; Măroiu, Alexandra Cristina; Popa, George; Bratu, Emanuel Adrian

2015-01-01

Using two measurement methods (a three-dimensional laser scanning system and a digital caliper), this study compares the lower face morphology of complete edentulous patients, before and after prosthodontic rehabilitation with bimaxillary complete dentures. Fourteen edentulous patients were randomly selected from the Department of Prosthodontics, at the Faculty of Dental Medicine, "Victor Babes" University of Medicine and Pharmacy, Timisoara, Romania. The changes that occurred in the lower third of the face after prosthodontic treatment were assessed quantitatively by measuring the vertical projection of the distances between two sets of anthropometric landmarks: Subnasale - cutaneous Pogonion (D1) and Labiale superius - Labiale inferius (D2). A two-way repeated measures ANOVA model design was carried out to test for significant interactions, main effects and differences between the two types of measuring devices and between the initial and final rehabilitation time points. The main effect of the type of measuring device showed no statistically significant differences in the measured distances (p=0.24 for D1 and p=0.39 for D2), between the initial and the final rehabilitation time points. Regarding the main effect of time, there were statistically significant differences in both the measured distances D1 and D2 (p=0.001), between the initial and the final rehabilitation time points. The two methods of measurement were equally reliable in the assessment of lower face morphology changes in edentulous patients after prosthodontic rehabilitation with bimaxillary complete dentures. The differences between the measurements taken before and after prosthodontic rehabilitation proved to be statistically significant.

[Analysis on influencing factor of the complications of percutaneous dilational tracheotomy].

PubMed

Zhai, Xiang; Zhang, Jinling; Hang, Wei; Wang, Ming; Shi, Zhan; Mi, Yue; Hu, Yunlei; Liu, Gang

2015-01-01

To Analyze the influence factors on the complications of percutaneous dilational tracheotomy. Between August 2008 and February 2014, there were 3 450 patients with the indications of tracheotomy accepted percutaneous dilational tracheostomy, mainly using percutaneous dilational and percutaneous guide wire forceps in these cases. Statistical analysis was performed by SPSS 19.0 software on postoperative complications, the possible influence factors including age, gender, etiology, preoperative hypoxia, obesity, preoperative pulmonary infection, state of consciousness, operation method, operation doctor and whether with tracheal intubation. Among 3 450 patients, there were 164 cases with intraoperative or postoperative complications, including postoperative bleeding in 74 cases (2.14%), subcutaneous emphysema in 54 cases (1.57%), wound infection in 16 cases (0.46%), pneumothorax in 6 cases (0.17%), mediastinal emphysema in 5 cases (0.14%), operation failed and change to conventional incision in 4 cases (0.12%), tracheoesophageal fistula in 2 cases (0.06%), death in 3 cases(0.09%).Obesity, etiology, preoperative hypoxia, preoperative pulmonary infection, state of consciousness and operation method were the main influence factors, with significant statistical difference (χ(2) value was 0.010, 0.000, 0.002, 0.000, 0.000, 0.000, all P < 0.05). Gender, age, operation doctor and whether there was the endotracheal intubation were not the main influence factors. There was no significant statistical difference (P > 0.05). Although percutaneous dilational tracheostomy is safe, but the complications can also happen. In order to reduce the complications, it is need to pay attention to the factors of obesity, etiology, preoperative hypoxia, preoperative pulmonary infection, state of consciousness and operation method.

A Statistical Method for Synthesizing Mediation Analyses Using the Product of Coefficient Approach Across Multiple Trials

PubMed Central

Huang, Shi; MacKinnon, David P.; Perrino, Tatiana; Gallo, Carlos; Cruden, Gracelyn; Brown, C Hendricks

2016-01-01

Mediation analysis often requires larger sample sizes than main effect analysis to achieve the same statistical power. Combining results across similar trials may be the only practical option for increasing statistical power for mediation analysis in some situations. In this paper, we propose a method to estimate: 1) marginal means for mediation path a, the relation of the independent variable to the mediator; 2) marginal means for path b, the relation of the mediator to the outcome, across multiple trials; and 3) the between-trial level variance-covariance matrix based on a bivariate normal distribution. We present the statistical theory and an R computer program to combine regression coefficients from multiple trials to estimate a combined mediated effect and confidence interval under a random effects model. Values of coefficients a and b, along with their standard errors from each trial are the input for the method. This marginal likelihood based approach with Monte Carlo confidence intervals provides more accurate inference than the standard meta-analytic approach. We discuss computational issues, apply the method to two real-data examples and make recommendations for the use of the method in different settings. PMID:28239330

Statistical results on restorative dentistry experiments: effect of the interaction between main variables

PubMed Central

CAVALCANTI, Andrea Nóbrega; MARCHI, Giselle Maria; AMBROSANO, Gláucia Maria Bovi

2010-01-01

Statistical analysis interpretation is a critical field in scientific research. When there is more than one main variable being studied in a research, the effect of the interaction between those variables is fundamental on experiments discussion. However, some doubts can occur when the p-value of the interaction is greater than the significance level. Objective To determine the most adequate interpretation for factorial experiments with p-values of the interaction nearly higher than the significance level. Materials and methods The p-values of the interactions found in two restorative dentistry experiments (0.053 and 0.068) were interpreted in two distinct ways: considering the interaction as not significant and as significant. Results Different findings were observed between the two analyses, and studies results became more coherent when the significant interaction was used. Conclusion The p-value of the interaction between main variables must be analyzed with caution because it can change the outcomes of research studies. Researchers are strongly advised to interpret carefully the results of their statistical analysis in order to discuss the findings of their experiments properly. PMID:20857003

Baseline estimation in flame's spectra by using neural networks and robust statistics

NASA Astrophysics Data System (ADS)

Garces, Hugo; Arias, Luis; Rojas, Alejandro

2014-09-01

This work presents a baseline estimation method in flame spectra based on artificial intelligence structure as a neural network, combining robust statistics with multivariate analysis to automatically discriminate measured wavelengths belonging to continuous feature for model adaptation, surpassing restriction of measuring target baseline for training. The main contributions of this paper are: to analyze a flame spectra database computing Jolliffe statistics from Principal Components Analysis detecting wavelengths not correlated with most of the measured data corresponding to baseline; to systematically determine the optimal number of neurons in hidden layers based on Akaike's Final Prediction Error; to estimate baseline in full wavelength range sampling measured spectra; and to train an artificial intelligence structure as a Neural Network which allows to generalize the relation between measured and baseline spectra. The main application of our research is to compute total radiation with baseline information, allowing to diagnose combustion process state for optimization in early stages.

Statistical prediction of dynamic distortion of inlet flow using minimum dynamic measurement. An application to the Melick statistical method and inlet flow dynamic distortion prediction without RMS measurements

NASA Technical Reports Server (NTRS)

Schweikhard, W. G.; Chen, Y. S.

1986-01-01

The Melick method of inlet flow dynamic distortion prediction by statistical means is outlined. A hypothetic vortex model is used as the basis for the mathematical formulations. The main variables are identified by matching the theoretical total pressure rms ratio with the measured total pressure rms ratio. Data comparisons, using the HiMAT inlet test data set, indicate satisfactory prediction of the dynamic peak distortion for cases with boundary layer control device vortex generators. A method for the dynamic probe selection was developed. Validity of the probe selection criteria is demonstrated by comparing the reduced-probe predictions with the 40-probe predictions. It is indicated that the the number of dynamic probes can be reduced to as few as two and still retain good accuracy.

A high-fidelity weather time series generator using the Markov Chain process on a piecewise level

NASA Astrophysics Data System (ADS)

Hersvik, K.; Endrerud, O.-E. V.

2017-12-01

A method is developed for generating a set of unique weather time-series based on an existing weather series. The method allows statistically valid weather variations to take place within repeated simulations of offshore operations. The numerous generated time series need to share the same statistical qualities as the original time series. Statistical qualities here refer mainly to the distribution of weather windows available for work, including durations and frequencies of such weather windows, and seasonal characteristics. The method is based on the Markov chain process. The core new development lies in how the Markov Process is used, specifically by joining small pieces of random length time series together rather than joining individual weather states, each from a single time step, which is a common solution found in the literature. This new Markov model shows favorable characteristics with respect to the requirements set forth and all aspects of the validation performed.

Statistical methods for thermonuclear reaction rates and nucleosynthesis simulations

NASA Astrophysics Data System (ADS)

Iliadis, Christian; Longland, Richard; Coc, Alain; Timmes, F. X.; Champagne, Art E.

2015-03-01

Rigorous statistical methods for estimating thermonuclear reaction rates and nucleosynthesis are becoming increasingly established in nuclear astrophysics. The main challenge being faced is that experimental reaction rates are highly complex quantities derived from a multitude of different measured nuclear parameters (e.g., astrophysical S-factors, resonance energies and strengths, particle and γ-ray partial widths). We discuss the application of the Monte Carlo method to two distinct, but related, questions. First, given a set of measured nuclear parameters, how can one best estimate the resulting thermonuclear reaction rates and associated uncertainties? Second, given a set of appropriate reaction rates, how can one best estimate the abundances from nucleosynthesis (i.e., reaction network) calculations? The techniques described here provide probability density functions that can be used to derive statistically meaningful reaction rates and final abundances for any desired coverage probability. Examples are given for applications to s-process neutron sources, core-collapse supernovae, classical novae, and Big Bang nucleosynthesis.

The Association of Chronic Hepatitis C with Respiratory Microbiota Disturbance on the Basis of Decreased Haemophilus Spp. Colonization

PubMed Central

Kosikowska, Urszula; Biernasiuk, Anna; Korona-Głowniak, Izabela; Kiciak, Sławomir; Tomasiewicz, Krzysztof; Malm, Anna

2016-01-01

Background Haemophilus species are the most common microbiota in humans. The aim of this paper was to investigate Haemophilus spp., mainly H. parainfluenzae prevalence, in the upper respiratory tract of chronic hepatitis C (CHC-positive) patients with or without therapy using pegylated interferon alfa and ribavirin. Material/Methods We collected 462 samples from 54 healthy people and 100 CHC-positive patients at various stages: before (group A), during (group B), and after (group C) antiviral therapy. Identification of bacterial isolates including biotypes and antimicrobials susceptibility was accomplished by means of standard microbiological methods. Results In 70.4% of healthy people (control group) and in 27.0% of CHC-positive patients, the presence of haemophili, mainly H. parainfluenzae was observed, and those differences were statistically significant (p<0.0001). Statistically significant differences in Haemophilus spp. colonization were also observed among healthy people and CHC-positive patients from group A (p=0.0012) and from B or C groups (p<0.0001). Resistance to ampicillin in beta-lactamase-positive isolates and multidrug resistance (MDR) of H. parainfluenzae was detected mainly in group A. Conclusions The obtained data suggest that chronic hepatitis C, together with antiviral therapy, may influence the respiratory tract microbiota composition as found using haemophili, mainly H. parainfluenzae. PMID:26912163

VALUE - Validating and Integrating Downscaling Methods for Climate Change Research

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Widmann, Martin; Benestad, Rasmus; Kotlarski, Sven; Huth, Radan; Hertig, Elke; Wibig, Joanna; Gutierrez, Jose

2013-04-01

Our understanding of global climate change is mainly based on General Circulation Models (GCMs) with a relatively coarse resolution. Since climate change impacts are mainly experienced on regional scales, high-resolution climate change scenarios need to be derived from GCM simulations by downscaling. Several projects have been carried out over the last years to validate the performance of statistical and dynamical downscaling, yet several aspects have not been systematically addressed: variability on sub-daily, decadal and longer time-scales, extreme events, spatial variability and inter-variable relationships. Different downscaling approaches such as dynamical downscaling, statistical downscaling and bias correction approaches have not been systematically compared. Furthermore, collaboration between different communities, in particular regional climate modellers, statistical downscalers and statisticians has been limited. To address these gaps, the EU Cooperation in Science and Technology (COST) action VALUE (www.value-cost.eu) has been brought into life. VALUE is a research network with participants from currently 23 European countries running from 2012 to 2015. Its main aim is to systematically validate and develop downscaling methods for climate change research in order to improve regional climate change scenarios for use in climate impact studies. Inspired by the co-design idea of the international research initiative "future earth", stakeholders of climate change information have been involved in the definition of research questions to be addressed and are actively participating in the network. The key idea of VALUE is to identify the relevant weather and climate characteristics required as input for a wide range of impact models and to define an open framework to systematically validate these characteristics. Based on a range of benchmark data sets, in principle every downscaling method can be validated and compared with competing methods. The results of this exercise will directly provide end users with important information about the uncertainty of regional climate scenarios, and will furthermore provide the basis for further developing downscaling methods. This presentation will provide background information on VALUE and discuss the identified characteristics and the validation framework.

Walking through the statistical black boxes of plant breeding.

PubMed

Xavier, Alencar; Muir, William M; Craig, Bruce; Rainey, Katy Martin

2016-10-01

The main statistical procedures in plant breeding are based on Gaussian process and can be computed through mixed linear models. Intelligent decision making relies on our ability to extract useful information from data to help us achieve our goals more efficiently. Many plant breeders and geneticists perform statistical analyses without understanding the underlying assumptions of the methods or their strengths and pitfalls. In other words, they treat these statistical methods (software and programs) like black boxes. Black boxes represent complex pieces of machinery with contents that are not fully understood by the user. The user sees the inputs and outputs without knowing how the outputs are generated. By providing a general background on statistical methodologies, this review aims (1) to introduce basic concepts of machine learning and its applications to plant breeding; (2) to link classical selection theory to current statistical approaches; (3) to show how to solve mixed models and extend their application to pedigree-based and genomic-based prediction; and (4) to clarify how the algorithms of genome-wide association studies work, including their assumptions and limitations.

A new method of power load prediction in electrification railway

NASA Astrophysics Data System (ADS)

Dun, Xiaohong

2018-04-01

Aiming at the character of electrification railway, the paper mainly studies the problem of load prediction in electrification railway. After the preprocessing of data, and the similar days are separated on the basis of its statistical characteristics. Meanwhile the accuracy of different methods is analyzed. The paper provides a new thought of prediction and a new method of accuracy of judgment for the load prediction of power system.

Statistical physics of hard combinatorial optimization: Vertex cover problem

NASA Astrophysics Data System (ADS)

Zhao, Jin-Hua; Zhou, Hai-Jun

2014-07-01

Typical-case computation complexity is a research topic at the boundary of computer science, applied mathematics, and statistical physics. In the last twenty years, the replica-symmetry-breaking mean field theory of spin glasses and the associated message-passing algorithms have greatly deepened our understanding of typical-case computation complexity. In this paper, we use the vertex cover problem, a basic nondeterministic-polynomial (NP)-complete combinatorial optimization problem of wide application, as an example to introduce the statistical physical methods and algorithms. We do not go into the technical details but emphasize mainly the intuitive physical meanings of the message-passing equations. A nonfamiliar reader shall be able to understand to a large extent the physics behind the mean field approaches and to adjust the mean field methods in solving other optimization problems.

Current approaches used in epidemiologic studies to examine short-term multipollutant air pollution exposures.

PubMed

Davalos, Angel D; Luben, Thomas J; Herring, Amy H; Sacks, Jason D

2017-02-01

Air pollution epidemiology traditionally focuses on the relationship between individual air pollutants and health outcomes (e.g., mortality). To account for potential copollutant confounding, individual pollutant associations are often estimated by adjusting or controlling for other pollutants in the mixture. Recently, the need to characterize the relationship between health outcomes and the larger multipollutant mixture has been emphasized in an attempt to better protect public health and inform more sustainable air quality management decisions. New and innovative statistical methods to examine multipollutant exposures were identified through a broad literature search, with a specific focus on those statistical approaches currently used in epidemiologic studies of short-term exposures to criteria air pollutants (i.e., particulate matter, carbon monoxide, sulfur dioxide, nitrogen dioxide, and ozone). Five broad classes of statistical approaches were identified for examining associations between short-term multipollutant exposures and health outcomes, specifically additive main effects, effect measure modification, unsupervised dimension reduction, supervised dimension reduction, and nonparametric methods. These approaches are characterized including advantages and limitations in different epidemiologic scenarios. By highlighting the characteristics of various studies in which multipollutant statistical methods have been used, this review provides epidemiologists and biostatisticians with a resource to aid in the selection of the most optimal statistical method to use when examining multipollutant exposures. Published by Elsevier Inc.

[Road Extraction in Remote Sensing Images Based on Spectral and Edge Analysis].

PubMed

Zhao, Wen-zhi; Luo, Li-qun; Guo, Zhou; Yue, Jun; Yu, Xue-ying; Liu, Hui; Wei, Jing

2015-10-01

Roads are typically man-made objects in urban areas. Road extraction from high-resolution images has important applications for urban planning and transportation development. However, due to the confusion of spectral characteristic, it is difficult to distinguish roads from other objects by merely using traditional classification methods that mainly depend on spectral information. Edge is an important feature for the identification of linear objects (e. g. , roads). The distribution patterns of edges vary greatly among different objects. It is crucial to merge edge statistical information into spectral ones. In this study, a new method that combines spectral information and edge statistical features has been proposed. First, edge detection is conducted by using self-adaptive mean-shift algorithm on the panchromatic band, which can greatly reduce pseudo-edges and noise effects. Then, edge statistical features are obtained from the edge statistical model, which measures the length and angle distribution of edges. Finally, by integrating the spectral and edge statistical features, SVM algorithm is used to classify the image and roads are ultimately extracted. A series of experiments are conducted and the results show that the overall accuracy of proposed method is 93% comparing with only 78% overall accuracy of the traditional. The results demonstrate that the proposed method is efficient and valuable for road extraction, especially on high-resolution images.

[The application of the multidimensional statistical methods in the evaluation of the influence of atmospheric pollution on the population's health].

PubMed

Surzhikov, V D; Surzhikov, D V

2014-01-01

The search and measurement of causal relationships between exposure to air pollution and health state of the population is based on the system analysis and risk assessment to improve the quality of research. With this purpose there is applied the modern statistical analysis with the use of criteria of independence, principal component analysis and discriminate function analysis. As a result of analysis out of all atmospheric pollutants there were separated four main components: for diseases of the circulatory system main principal component is implied with concentrations of suspended solids, nitrogen dioxide, carbon monoxide, hydrogen fluoride, for the respiratory diseases the main c principal component is closely associated with suspended solids, sulfur dioxide and nitrogen dioxide, charcoal black. The discriminant function was shown to be used as a measure of the level of air pollution.

[Bayesian statistics in medicine -- part II: main applications and inference].

PubMed

Montomoli, C; Nichelatti, M

2008-01-01

Bayesian statistics is not only used when one is dealing with 2-way tables, but it can be used for inferential purposes. Using the basic concepts presented in the first part, this paper aims to give a simple overview of Bayesian methods by introducing its foundation (Bayes' theorem) and then applying this rule to a very simple practical example; whenever possible, the elementary processes at the basis of analysis are compared to those of frequentist (classical) statistical analysis. The Bayesian reasoning is naturally connected to medical activity, since it appears to be quite similar to a diagnostic process.

Identification and characterization of earthquake clusters: a comparative analysis for selected sequences in Italy

NASA Astrophysics Data System (ADS)

Peresan, Antonella; Gentili, Stefania

2017-04-01

Identification and statistical characterization of seismic clusters may provide useful insights about the features of seismic energy release and their relation to physical properties of the crust within a given region. Moreover, a number of studies based on spatio-temporal analysis of main-shocks occurrence require preliminary declustering of the earthquake catalogs. Since various methods, relying on different physical/statistical assumptions, may lead to diverse classifications of earthquakes into main events and related events, we aim to investigate the classification differences among different declustering techniques. Accordingly, a formal selection and comparative analysis of earthquake clusters is carried out for the most relevant earthquakes in North-Eastern Italy, as reported in the local OGS-CRS bulletins, compiled at the National Institute of Oceanography and Experimental Geophysics since 1977. The comparison is then extended to selected earthquake sequences associated with a different seismotectonic setting, namely to events that occurred in the region struck by the recent Central Italy destructive earthquakes, making use of INGV data. Various techniques, ranging from classical space-time windows methods to ad hoc manual identification of aftershocks, are applied for detection of earthquake clusters. In particular, a statistical method based on nearest-neighbor distances of events in space-time-energy domain, is considered. Results from clusters identification by the nearest-neighbor method turn out quite robust with respect to the time span of the input catalogue, as well as to minimum magnitude cutoff. The identified clusters for the largest events reported in North-Eastern Italy since 1977 are well consistent with those reported in earlier studies, which were aimed at detailed manual aftershocks identification. The study shows that the data-driven approach, based on the nearest-neighbor distances, can be satisfactorily applied to decompose the seismic catalog into background seismicity and individual sequences of earthquake clusters, also in areas characterized by moderate seismic activity, where the standard declustering techniques may turn out rather gross approximations. With these results acquired, the main statistical features of seismic clusters are explored, including complex interdependence of related events, with the aim to characterize the space-time patterns of earthquakes occurrence in North-Eastern Italy and capture their basic differences with Central Italy sequences.

K-nearest neighbors based methods for identification of different gear crack levels under different motor speeds and loads: Revisited

NASA Astrophysics Data System (ADS)

Wang, Dong

2016-03-01

Gears are the most commonly used components in mechanical transmission systems. Their failures may cause transmission system breakdown and result in economic loss. Identification of different gear crack levels is important to prevent any unexpected gear failure because gear cracks lead to gear tooth breakage. Signal processing based methods mainly require expertize to explain gear fault signatures which is usually not easy to be achieved by ordinary users. In order to automatically identify different gear crack levels, intelligent gear crack identification methods should be developed. The previous case studies experimentally proved that K-nearest neighbors based methods exhibit high prediction accuracies for identification of 3 different gear crack levels under different motor speeds and loads. In this short communication, to further enhance prediction accuracies of existing K-nearest neighbors based methods and extend identification of 3 different gear crack levels to identification of 5 different gear crack levels, redundant statistical features are constructed by using Daubechies 44 (db44) binary wavelet packet transform at different wavelet decomposition levels, prior to the use of a K-nearest neighbors method. The dimensionality of redundant statistical features is 620, which provides richer gear fault signatures. Since many of these statistical features are redundant and highly correlated with each other, dimensionality reduction of redundant statistical features is conducted to obtain new significant statistical features. At last, the K-nearest neighbors method is used to identify 5 different gear crack levels under different motor speeds and loads. A case study including 3 experiments is investigated to demonstrate that the developed method provides higher prediction accuracies than the existing K-nearest neighbors based methods for recognizing different gear crack levels under different motor speeds and loads. Based on the new significant statistical features, some other popular statistical models including linear discriminant analysis, quadratic discriminant analysis, classification and regression tree and naive Bayes classifier, are compared with the developed method. The results show that the developed method has the highest prediction accuracies among these statistical models. Additionally, selection of the number of new significant features and parameter selection of K-nearest neighbors are thoroughly investigated.

Variance reduction for Fokker–Planck based particle Monte Carlo schemes

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

Gorji, M. Hossein, E-mail: gorjih@ifd.mavt.ethz.ch; Andric, Nemanja; Jenny, Patrick

Recently, Fokker–Planck based particle Monte Carlo schemes have been proposed and evaluated for simulations of rarefied gas flows [1–3]. In this paper, the variance reduction for particle Monte Carlo simulations based on the Fokker–Planck model is considered. First, deviational based schemes were derived and reviewed, and it is shown that these deviational methods are not appropriate for practical Fokker–Planck based rarefied gas flow simulations. This is due to the fact that the deviational schemes considered in this study lead either to instabilities in the case of two-weight methods or to large statistical errors if the direct sampling method is applied.more » Motivated by this conclusion, we developed a novel scheme based on correlated stochastic processes. The main idea here is to synthesize an additional stochastic process with a known solution, which is simultaneously solved together with the main one. By correlating the two processes, the statistical errors can dramatically be reduced; especially for low Mach numbers. To assess the methods, homogeneous relaxation, planar Couette and lid-driven cavity flows were considered. For these test cases, it could be demonstrated that variance reduction based on parallel processes is very robust and effective.« less

Interpreting “statistical hypothesis testing” results in clinical research

PubMed Central

Sarmukaddam, Sanjeev B.

2012-01-01

Difference between “Clinical Significance and Statistical Significance” should be kept in mind while interpreting “statistical hypothesis testing” results in clinical research. This fact is already known to many but again pointed out here as philosophy of “statistical hypothesis testing” is sometimes unnecessarily criticized mainly due to failure in considering such distinction. Randomized controlled trials are also wrongly criticized similarly. Some scientific method may not be applicable in some peculiar/particular situation does not mean that the method is useless. Also remember that “statistical hypothesis testing” is not for decision making and the field of “decision analysis” is very much an integral part of science of statistics. It is not correct to say that “confidence intervals have nothing to do with confidence” unless one understands meaning of the word “confidence” as used in context of confidence interval. Interpretation of the results of every study should always consider all possible alternative explanations like chance, bias, and confounding. Statistical tests in inferential statistics are, in general, designed to answer the question “How likely is the difference found in random sample(s) is due to chance” and therefore limitation of relying only on statistical significance in making clinical decisions should be avoided. PMID:22707861

Simulation Insights Using "R"

ERIC Educational Resources Information Center

Kostadinov, Boyan

2013-01-01

This article attempts to introduce the reader to computational thinking and solving problems involving randomness. The main technique being employed is the Monte Carlo method, using the freely available software "R for Statistical Computing." The author illustrates the computer simulation approach by focusing on several problems of…

Some statistical features of the seismic activity related to the recent M8.2 and M7.1 earthquakes in Mexico

NASA Astrophysics Data System (ADS)

Guzman, L.; Baeza-Blancas, E.; Reyes, I.; Angulo Brown, F.; Rudolf Navarro, A.

2017-12-01

By studying the magnitude earthquake catalogs, previous studies have reported evidence that some changes in the spatial and temporal organization of earthquake activity is observedbefore and after of a main-shock. These previous studies have used different approach methods for detecting clustering behavior and distance-events density in order topoint out the asymmetric behavior of before shocks and aftershocks. Here, we present a statistical analysis of the seismic activity related to the M8.2 and M7.1 earthquakes occurredon Sept. 7th and Sept. 19th, respectively. First, we calculated the interevent time and distance for the period Sept. 7th 2016 until Oct. 20th 2017 for each seismic region ( a radius of 150 km centeredat coordinates of the M8.1 and M7.1). Next, we calculated the "velocity" of the walker as the ratio between the interevent distance and interevent time, and similarly, we also constructed the"acceleration". A slider pointer is considered to estimate some statistical features within time windows of size τ for the velocity and acceleration sequences before and after the main shocks. Specifically, we applied the fractal dimension method to detect changes in the correlation (persistence) behavior of events in the period before the main events.Our preliminary results pointed out that the fractal dimension associated to the velocity and acceleration sequences exhibits changes in the persistence behavior before the mainshock, while thescaling dimension values after the main events resemble a more uncorrelated behavior. Moreover, the relationship between the standard deviation of the velocity and the local mean velocity valuefor a given time window-size τ is described by an exponent close to 1.5, and the cumulative distribution of velocity and acceleration are well described by power law functions after the crash and stretched-exponential-like distribution before the main shock. On the other hand, we present an analysis of patterns of seismicquiescence before the M8.2 earthquake based on the Schreider algorithmover a period of 27 years. This analysis also includes the modificationof the Schreider method proposed by Muñoz-Diosdado et al. (2015).

Evaluation of statistical treatments of left-censored environmental data using coincident uncensored data sets: I. Summary statistics

USGS Publications Warehouse

Antweiler, Ronald C.; Taylor, Howard E.

2008-01-01

The main classes of statistical treatment of below-detection limit (left-censored) environmental data for the determination of basic statistics that have been used in the literature are substitution methods, maximum likelihood, regression on order statistics (ROS), and nonparametric techniques. These treatments, along with using all instrument-generated data (even those below detection), were evaluated by examining data sets in which the true values of the censored data were known. It was found that for data sets with less than 70% censored data, the best technique overall for determination of summary statistics was the nonparametric Kaplan-Meier technique. ROS and the two substitution methods of assigning one-half the detection limit value to censored data or assigning a random number between zero and the detection limit to censored data were adequate alternatives. The use of these two substitution methods, however, requires a thorough understanding of how the laboratory censored the data. The technique of employing all instrument-generated data - including numbers below the detection limit - was found to be less adequate than the above techniques. At high degrees of censoring (greater than 70% censored data), no technique provided good estimates of summary statistics. Maximum likelihood techniques were found to be far inferior to all other treatments except substituting zero or the detection limit value to censored data.

Synthesis of instrumentally and historically recorded earthquakes and studying their spatial statistical relationship (A case study: Dasht-e-Biaz, Eastern Iran)

NASA Astrophysics Data System (ADS)

Jalali, Mohammad; Ramazi, Hamidreza

2018-06-01

Earthquake catalogues are the main source of statistical seismology for the long term studies of earthquake occurrence. Therefore, studying the spatiotemporal problems is important to reduce the related uncertainties in statistical seismology studies. A statistical tool, time normalization method, has been determined to revise time-frequency relationship in one of the most active regions of Asia, Eastern Iran and West of Afghanistan, (a and b were calculated around 8.84 and 1.99 in the exponential scale, not logarithmic scale). Geostatistical simulation method has been further utilized to reduce the uncertainties in the spatial domain. A geostatistical simulation produces a representative, synthetic catalogue with 5361 events to reduce spatial uncertainties. The synthetic database is classified using a Geographical Information System, GIS, based on simulated magnitudes to reveal the underlying seismicity patterns. Although some regions with highly seismicity correspond to known faults, significantly, as far as seismic patterns are concerned, the new method highlights possible locations of interest that have not been previously identified. It also reveals some previously unrecognized lineation and clusters in likely future strain release.

NUMERICAL ANALYSIS TECHNIQUE USING THE STATISTICAL ENERGY ANALYSIS METHOD CONCERNING THE BLASTING NOISE REDUCTION BY THE SOUND INSULATION DOOR USED IN TUNNEL CONSTRUCTIONS

NASA Astrophysics Data System (ADS)

Ishida, Shigeki; Mori, Atsuo; Shinji, Masato

The main method to reduce the blasting charge noise which occurs in a tunnel under construction is to install the sound insulation door in the tunnel. However, the numerical analysis technique to predict the accurate effect of the transmission loss in the sound insulation door is not established. In this study, we measured the blasting charge noise and the vibration of the sound insulation door in the tunnel with the blasting charge, and performed analysis and modified acoustic feature. In addition, we reproduced the noise reduction effect of the sound insulation door by statistical energy analysis method and confirmed that numerical simulation is possible by this procedure.

An Assessment of Phylogenetic Tools for Analyzing the Interplay Between Interspecific Interactions and Phenotypic Evolution.

PubMed

Drury, J P; Grether, G F; Garland, T; Morlon, H

2018-05-01

Much ecological and evolutionary theory predicts that interspecific interactions often drive phenotypic diversification and that species phenotypes in turn influence species interactions. Several phylogenetic comparative methods have been developed to assess the importance of such processes in nature; however, the statistical properties of these methods have gone largely untested. Focusing mainly on scenarios of competition between closely-related species, we assess the performance of available comparative approaches for analyzing the interplay between interspecific interactions and species phenotypes. We find that many currently used statistical methods often fail to detect the impact of interspecific interactions on trait evolution, that sister-taxa analyses are particularly unreliable in general, and that recently developed process-based models have more satisfactory statistical properties. Methods for detecting predictors of species interactions are generally more reliable than methods for detecting character displacement. In weighing the strengths and weaknesses of different approaches, we hope to provide a clear guide for empiricists testing hypotheses about the reciprocal effect of interspecific interactions and species phenotypes and to inspire further development of process-based models.

Comparison of Peak-Flow Estimation Methods for Small Drainage Basins in Maine

USGS Publications Warehouse

Hodgkins, Glenn A.; Hebson, Charles; Lombard, Pamela J.; Mann, Alexander

2007-01-01

Understanding the accuracy of commonly used methods for estimating peak streamflows is important because the designs of bridges, culverts, and other river structures are based on these flows. Different methods for estimating peak streamflows were analyzed for small drainage basins in Maine. For the smallest basins, with drainage areas of 0.2 to 1.0 square mile, nine peak streamflows from actual rainfall events at four crest-stage gaging stations were modeled by the Rational Method and the Natural Resource Conservation Service TR-20 method and compared to observed peak flows. The Rational Method had a root mean square error (RMSE) of -69.7 to 230 percent (which means that approximately two thirds of the modeled flows were within -69.7 to 230 percent of the observed flows). The TR-20 method had an RMSE of -98.0 to 5,010 percent. Both the Rational Method and TR-20 underestimated the observed flows in most cases. For small basins, with drainage areas of 1.0 to 10 square miles, modeled peak flows were compared to observed statistical peak flows with return periods of 2, 50, and 100 years for 17 streams in Maine and adjoining parts of New Hampshire. Peak flows were modeled by the Rational Method, the Natural Resources Conservation Service TR-20 method, U.S. Geological Survey regression equations, and the Probabilistic Rational Method. The regression equations were the most accurate method of computing peak flows in Maine for streams with drainage areas of 1.0 to 10 square miles with an RMSE of -34.3 to 52.2 percent for 50-year peak flows. The Probabilistic Rational Method was the next most accurate method (-38.5 to 62.6 percent). The Rational Method (-56.1 to 128 percent) and particularly the TR-20 method (-76.4 to 323 percent) had much larger errors. Both the TR-20 and regression methods had similar numbers of underpredictions and overpredictions. The Rational Method overpredicted most peak flows and the Probabilistic Rational Method tended to overpredict peak flows from the smaller (less than 5 square miles) drainage basins and underpredict peak flows from larger drainage basins. The results of this study are consistent with the most comprehensive analysis of observed and modeled peak streamflows in the United States, which analyzed statistical peak flows from 70 drainage basins in the Midwest and the Northwest.

Deciphering the complex: methodological overview of statistical models to derive OMICS-based biomarkers.

PubMed

Chadeau-Hyam, Marc; Campanella, Gianluca; Jombart, Thibaut; Bottolo, Leonardo; Portengen, Lutzen; Vineis, Paolo; Liquet, Benoit; Vermeulen, Roel C H

2013-08-01

Recent technological advances in molecular biology have given rise to numerous large-scale datasets whose analysis imposes serious methodological challenges mainly relating to the size and complex structure of the data. Considerable experience in analyzing such data has been gained over the past decade, mainly in genetics, from the Genome-Wide Association Study era, and more recently in transcriptomics and metabolomics. Building upon the corresponding literature, we provide here a nontechnical overview of well-established methods used to analyze OMICS data within three main types of regression-based approaches: univariate models including multiple testing correction strategies, dimension reduction techniques, and variable selection models. Our methodological description focuses on methods for which ready-to-use implementations are available. We describe the main underlying assumptions, the main features, and advantages and limitations of each of the models. This descriptive summary constitutes a useful tool for driving methodological choices while analyzing OMICS data, especially in environmental epidemiology, where the emergence of the exposome concept clearly calls for unified methods to analyze marginally and jointly complex exposure and OMICS datasets. Copyright © 2013 Wiley Periodicals, Inc.

A Review of Some Aspects of Robust Inference for Time Series.

DTIC Science & Technology

1984-09-01

REVIEW OF SOME ASPECTSOF ROBUST INFERNCE FOR TIME SERIES by Ad . Dougla Main TE "iAL REPOW No. 63 Septermber 1984 Department of Statistics University of ...clear. One cannot hope to have a good method for dealing with outliers in time series by using only an instantaneous nonlinear transformation of the data...AI.49 716 A REVIEWd OF SOME ASPECTS OF ROBUST INFERENCE FOR TIME 1/1 SERIES(U) WASHINGTON UNIV SEATTLE DEPT OF STATISTICS R D MARTIN SEP 84 TR-53

A method to evaluate process performance by integrating time and resources

NASA Astrophysics Data System (ADS)

Wang, Yu; Wei, Qingjie; Jin, Shuang

2017-06-01

The purpose of process mining is to improve the existing process of the enterprise, so how to measure the performance of the process is particularly important. However, the current research on the performance evaluation method is still insufficient. The main methods of evaluation are mainly using time or resource. These basic statistics cannot evaluate process performance very well. In this paper, a method of evaluating the performance of the process based on time dimension and resource dimension is proposed. This method can be used to measure the utilization and redundancy of resources in the process. This paper will introduce the design principle and formula of the evaluation algorithm. Then, the design and the implementation of the evaluation method will be introduced. Finally, we will use the evaluating method to analyse the event log from a telephone maintenance process and propose an optimization plan.

Statistical approaches used to assess and redesign surface water-quality-monitoring networks.

PubMed

Khalil, B; Ouarda, T B M J

2009-11-01

An up-to-date review of the statistical approaches utilized for the assessment and redesign of surface water quality monitoring (WQM) networks is presented. The main technical aspects of network design are covered in four sections, addressing monitoring objectives, water quality variables, sampling frequency and spatial distribution of sampling locations. This paper discusses various monitoring objectives and related procedures used for the assessment and redesign of long-term surface WQM networks. The appropriateness of each approach for the design, contraction or expansion of monitoring networks is also discussed. For each statistical approach, its advantages and disadvantages are examined from a network design perspective. Possible methods to overcome disadvantages and deficiencies in the statistical approaches that are currently in use are recommended.

SWToolbox: A surface-water tool-box for statistical analysis of streamflow time series

USGS Publications Warehouse

Kiang, Julie E.; Flynn, Kate; Zhai, Tong; Hummel, Paul; Granato, Gregory

2018-03-07

This report is a user guide for the low-flow analysis methods provided with version 1.0 of the Surface Water Toolbox (SWToolbox) computer program. The software combines functionality from two software programs—U.S. Geological Survey (USGS) SWSTAT and U.S. Environmental Protection Agency (EPA) DFLOW. Both of these programs have been used primarily for computation of critical low-flow statistics. The main analysis methods are the computation of hydrologic frequency statistics such as the 7-day minimum flow that occurs on average only once every 10 years (7Q10), computation of design flows including biologically based flows, and computation of flow-duration curves and duration hydrographs. Other annual, monthly, and seasonal statistics can also be computed. The interface facilitates retrieval of streamflow discharge data from the USGS National Water Information System and outputs text reports for a record of the analysis. Tools for graphing data and screening tests are available to assist the analyst in conducting the analysis.

Assessing the Links Between Anthropometrics Data and Akabane Test Results.

PubMed

Muzhikov, Valery; Vershinina, Elena; Belenky, Vadim; Muzhikov, Ruslan

2018-02-01

According to popular belief, metabolic disorders and imbalances are one of the main factors contributing to various human illnesses. Early diagnosis of these disorders is one of the main methods for preventing serious diseases. The goal of this study was to assess the correlations between main physical indicators and the activity of certain acupuncture channels using the thermal Akabane test based on ancient Chinese diagnostic methods. This test measures the pain thresholds' temperature sensitivity when a point source of heat is applied to the "entrance-exit" points of each channel. The skin temperature sensitivity in our bodies is a basic reactive system; it is as significant as such important indicators as body temperature and provides a very clear representation of functional and psychophysiological profiles. On the basis of our statistical study, we revealed reliable correspondence between the activity of certain acupuncture channels and main anthropometric and biometric data. Copyright © 2018. Published by Elsevier B.V.

Gene flow analysis method, the D-statistic, is robust in a wide parameter space.

PubMed

Zheng, Yichen; Janke, Axel

2018-01-08

We evaluated the sensitivity of the D-statistic, a parsimony-like method widely used to detect gene flow between closely related species. This method has been applied to a variety of taxa with a wide range of divergence times. However, its parameter space and thus its applicability to a wide taxonomic range has not been systematically studied. Divergence time, population size, time of gene flow, distance of outgroup and number of loci were examined in a sensitivity analysis. The sensitivity study shows that the primary determinant of the D-statistic is the relative population size, i.e. the population size scaled by the number of generations since divergence. This is consistent with the fact that the main confounding factor in gene flow detection is incomplete lineage sorting by diluting the signal. The sensitivity of the D-statistic is also affected by the direction of gene flow, size and number of loci. In addition, we examined the ability of the f-statistics, [Formula: see text] and [Formula: see text], to estimate the fraction of a genome affected by gene flow; while these statistics are difficult to implement to practical questions in biology due to lack of knowledge of when the gene flow happened, they can be used to compare datasets with identical or similar demographic background. The D-statistic, as a method to detect gene flow, is robust against a wide range of genetic distances (divergence times) but it is sensitive to population size. The D-statistic should only be applied with critical reservation to taxa where population sizes are large relative to branch lengths in generations.

Numerical solutions of ideal quantum gas dynamical flows governed by semiclassical ellipsoidal-statistical distribution.

PubMed

Yang, Jaw-Yen; Yan, Chih-Yuan; Diaz, Manuel; Huang, Juan-Chen; Li, Zhihui; Zhang, Hanxin

2014-01-08

The ideal quantum gas dynamics as manifested by the semiclassical ellipsoidal-statistical (ES) equilibrium distribution derived in Wu et al. (Wu et al . 2012 Proc. R. Soc. A 468 , 1799-1823 (doi:10.1098/rspa.2011.0673)) is numerically studied for particles of three statistics. This anisotropic ES equilibrium distribution was derived using the maximum entropy principle and conserves the mass, momentum and energy, but differs from the standard Fermi-Dirac or Bose-Einstein distribution. The present numerical method combines the discrete velocity (or momentum) ordinate method in momentum space and the high-resolution shock-capturing method in physical space. A decoding procedure to obtain the necessary parameters for determining the ES distribution is also devised. Computations of two-dimensional Riemann problems are presented, and various contours of the quantities unique to this ES model are illustrated. The main flow features, such as shock waves, expansion waves and slip lines and their complex nonlinear interactions, are depicted and found to be consistent with existing calculations for a classical gas.

Global vision of druggability issues: applications and perspectives.

PubMed

Abi Hussein, Hiba; Geneix, Colette; Petitjean, Michel; Borrel, Alexandre; Flatters, Delphine; Camproux, Anne-Claude

2017-02-01

During the preliminary stage of a drug discovery project, the lack of druggability information and poor target selection are the main causes of frequent failures. Elaborating on accurate computational druggability prediction methods is a requirement for prioritizing target selection, designing new drugs and avoiding side effects. In this review, we describe a survey of recently reported druggability prediction methods mainly based on networks, statistical pocket druggability predictions and virtual screening. An application for a frequent mutation of p53 tumor suppressor is presented, illustrating the complementarity of druggability prediction approaches, the remaining challenges and potential new drug development perspectives. Copyright © 2016 Elsevier Ltd. All rights reserved.

Regression modeling of ground-water flow

USGS Publications Warehouse

Cooley, R.L.; Naff, R.L.

1985-01-01

Nonlinear multiple regression methods are developed to model and analyze groundwater flow systems. Complete descriptions of regression methodology as applied to groundwater flow models allow scientists and engineers engaged in flow modeling to apply the methods to a wide range of problems. Organization of the text proceeds from an introduction that discusses the general topic of groundwater flow modeling, to a review of basic statistics necessary to properly apply regression techniques, and then to the main topic: exposition and use of linear and nonlinear regression to model groundwater flow. Statistical procedures are given to analyze and use the regression models. A number of exercises and answers are included to exercise the student on nearly all the methods that are presented for modeling and statistical analysis. Three computer programs implement the more complex methods. These three are a general two-dimensional, steady-state regression model for flow in an anisotropic, heterogeneous porous medium, a program to calculate a measure of model nonlinearity with respect to the regression parameters, and a program to analyze model errors in computed dependent variables such as hydraulic head. (USGS)

Valid statistical inference methods for a case-control study with missing data.

PubMed

Tian, Guo-Liang; Zhang, Chi; Jiang, Xuejun

2018-04-01

The main objective of this paper is to derive the valid sampling distribution of the observed counts in a case-control study with missing data under the assumption of missing at random by employing the conditional sampling method and the mechanism augmentation method. The proposed sampling distribution, called the case-control sampling distribution, can be used to calculate the standard errors of the maximum likelihood estimates of parameters via the Fisher information matrix and to generate independent samples for constructing small-sample bootstrap confidence intervals. Theoretical comparisons of the new case-control sampling distribution with two existing sampling distributions exhibit a large difference. Simulations are conducted to investigate the influence of the three different sampling distributions on statistical inferences. One finding is that the conclusion by the Wald test for testing independency under the two existing sampling distributions could be completely different (even contradictory) from the Wald test for testing the equality of the success probabilities in control/case groups under the proposed distribution. A real cervical cancer data set is used to illustrate the proposed statistical methods.

Comparison of classical statistical methods and artificial neural network in traffic noise prediction

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

Nedic, Vladimir, E-mail: vnedic@kg.ac.rs; Despotovic, Danijela, E-mail: ddespotovic@kg.ac.rs; Cvetanovic, Slobodan, E-mail: slobodan.cvetanovic@eknfak.ni.ac.rs

2014-11-15

Traffic is the main source of noise in urban environments and significantly affects human mental and physical health and labor productivity. Therefore it is very important to model the noise produced by various vehicles. Techniques for traffic noise prediction are mainly based on regression analysis, which generally is not good enough to describe the trends of noise. In this paper the application of artificial neural networks (ANNs) for the prediction of traffic noise is presented. As input variables of the neural network, the proposed structure of the traffic flow and the average speed of the traffic flow are chosen. Themore » output variable of the network is the equivalent noise level in the given time period L{sub eq}. Based on these parameters, the network is modeled, trained and tested through a comparative analysis of the calculated values and measured levels of traffic noise using the originally developed user friendly software package. It is shown that the artificial neural networks can be a useful tool for the prediction of noise with sufficient accuracy. In addition, the measured values were also used to calculate equivalent noise level by means of classical methods, and comparative analysis is given. The results clearly show that ANN approach is superior in traffic noise level prediction to any other statistical method. - Highlights: • We proposed an ANN model for prediction of traffic noise. • We developed originally designed user friendly software package. • The results are compared with classical statistical methods. • The results are much better predictive capabilities of ANN model.« less

Optical turbulence forecast: ready for an operational application

NASA Astrophysics Data System (ADS)

Masciadri, E.; Lascaux, F.; Turchi, A.; Fini, L.

2017-04-01

One of the main goals of the feasibility study MOSE (MOdelling ESO Sites) is to evaluate the performances of a method conceived to forecast the optical turbulence (OT) above the European Southern Observatory (ESO) sites of the Very Large Telescope (VLT) and the European Extremely Large Telescope (E-ELT) in Chile. The method implied the use of a dedicated code conceived for the OT called ASTRO-MESO-NH. In this paper, we present results we obtained at conclusion of this project concerning the performances of this method in forecasting the most relevant parameters related to the OT (CN^2, seeing ɛ, isoplanatic angle θ0 and wavefront coherence time τ0). Numerical predictions related to a very rich statistical sample of nights uniformly distributed along a solar year and belonging to different years have been compared to observations, and different statistical operators have been analysed such as the classical bias, root-mean-squared error, σ and more sophisticated statistical operators derived by the contingency tables that are able to quantify the score of success of a predictive method such as the percentage of correct detection (PC) and the probability to detect a parameter within a specific range of values (POD). The main conclusions of the study tell us that the ASTRO-MESO-NH model provides performances that are already very good to definitely guarantee a not negligible positive impact on the service mode of top-class telescopes and ELTs. A demonstrator for an automatic and operational version of the ASTRO-MESO-NH model will be soon implemented on the sites of VLT and E-ELT.

Spectrofluorimetric determination of 3-methylflavone-8-carboxylic acid, the main active metabolite of flavoxate hydrochloride in human urine.

PubMed

Zaazaa, Hala E; Mohamed, Afaf O; Hawwam, Maha A; Abdelkawy, Mohamed

2015-01-05

A simple, sensitive and selective spectrofluorimetric method has been developed for the determination of 3-methylflavone-8-carboxylic acid as the main active metabolite of flavoxate hydrochloride in human urine. The proposed method was based on the measurement of the native fluorescence of the metabolite in methanol at an emission wavelength 390 nm, upon excitation at 338 nm. Moreover, the urinary excretion pattern has been calculated using the proposed method. Taking the advantage that 3-methylflavone-8-carboxylic acid is also the alkaline degradate, the proposed method was applied to in vitro determination of flavoxate hydrochloride in tablets dosage form via the measurement of its corresponding degradate. The method was validated in accordance with the ICH requirements and statistically compared to the official method with no significant difference in performance. Copyright © 2014 Elsevier B.V. All rights reserved.

Multivariate statistical analysis of heavy metal concentration in soils of Yelagiri Hills, Tamilnadu, India--spectroscopical approach.

PubMed

Chandrasekaran, A; Ravisankar, R; Harikrishnan, N; Satapathy, K K; Prasad, M V R; Kanagasabapathy, K V

2015-02-25

Anthropogenic activities increase the accumulation of heavy metals in the soil environment. Soil pollution significantly reduces environmental quality and affects the human health. In the present study soil samples were collected at different locations of Yelagiri Hills, Tamilnadu, India for heavy metal analysis. The samples were analyzed for twelve selected heavy metals (Mg, Al, K, Ca, Ti, Fe, V, Cr, Mn, Co, Ni and Zn) using energy dispersive X-ray fluorescence (EDXRF) spectroscopy. Heavy metals concentration in soil were investigated using enrichment factor (EF), geo-accumulation index (Igeo), contamination factor (CF) and pollution load index (PLI) to determine metal accumulation, distribution and its pollution status. Heavy metal toxicity risk was assessed using soil quality guidelines (SQGs) given by target and intervention values of Dutch soil standards. The concentration of Ni, Co, Zn, Cr, Mn, Fe, Ti, K, Al, Mg were mainly controlled by natural sources. Multivariate statistical methods such as correlation matrix, principal component analysis and cluster analysis were applied for the identification of heavy metal sources (anthropogenic/natural origin). Geo-statistical methods such as kirging identified hot spots of metal contamination in road areas influenced mainly by presence of natural rocks. Copyright © 2014 Elsevier B.V. All rights reserved.

Use of Statistical Analyses in the Ophthalmic Literature

PubMed Central

Lisboa, Renato; Meira-Freitas, Daniel; Tatham, Andrew J.; Marvasti, Amir H.; Sharpsten, Lucie; Medeiros, Felipe A.

2014-01-01

Purpose To identify the most commonly used statistical analyses in the ophthalmic literature and to determine the likely gain in comprehension of the literature that readers could expect if they were to sequentially add knowledge of more advanced techniques to their statistical repertoire. Design Cross-sectional study Methods All articles published from January 2012 to December 2012 in Ophthalmology, American Journal of Ophthalmology and Archives of Ophthalmology were reviewed. A total of 780 peer-reviewed articles were included. Two reviewers examined each article and assigned categories to each one depending on the type of statistical analyses used. Discrepancies between reviewers were resolved by consensus. Main Outcome Measures Total number and percentage of articles containing each category of statistical analysis were obtained. Additionally we estimated the accumulated number and percentage of articles that a reader would be expected to be able to interpret depending on their statistical repertoire. Results Readers with little or no statistical knowledge would be expected to be able to interpret the statistical methods presented in only 20.8% of articles. In order to understand more than half (51.4%) of the articles published, readers were expected to be familiar with at least 15 different statistical methods. Knowledge of 21 categories of statistical methods was necessary to comprehend 70.9% of articles, while knowledge of more than 29 categories was necessary to comprehend more than 90% of articles. Articles in retina and glaucoma subspecialties showed a tendency for using more complex analysis when compared to cornea. Conclusions Readers of clinical journals in ophthalmology need to have substantial knowledge of statistical methodology to understand the results of published studies in the literature. The frequency of use of complex statistical analyses also indicates that those involved in the editorial peer-review process must have sound statistical knowledge in order to critically appraise articles submitted for publication. The results of this study could provide guidance to direct the statistical learning of clinical ophthalmologists, researchers and educators involved in the design of courses for residents and medical students. PMID:24612977

[The role of international comparison in surveying divorce trends].

PubMed

Cseh-szombathy, L

1982-04-01

In this study, the main survey methods and approaches to analyzing data on divorce in different countries are described. Some problems concerning the international comparability of divorce statistics are examined, and the value of international comparative studies for identifying common factors affecting divorce is stressed. (summary in ENG, RUS)

Modelling night-time ecosystem respiration by a constrained source optimization method

Treesearch

Chun-Tai Lai; Gabriel Katul; John Butnor; David Ellsworth; Ram Oren

2002-01-01

One of the main challenges to quantifying ecosystem carbon budgets is properly quantifying the magnitude of night-time ecosystem respiration. Inverse Lagrangian dispersion analysis provides a promising approach to addressing such a problem when measured mean CO2 concentration profiles and nocturnal velocity statistics are available. An inverse...

Identification of reliable gridded reference data for statistical downscaling methods in Alberta

NASA Astrophysics Data System (ADS)

Eum, H. I.; Gupta, A.

2017-12-01

Climate models provide essential information to assess impacts of climate change at regional and global scales. However, statistical downscaling methods have been applied to prepare climate model data for various applications such as hydrologic and ecologic modelling at a watershed scale. As the reliability and (spatial and temporal) resolution of statistically downscaled climate data mainly depend on a reference data, identifying the most reliable reference data is crucial for statistical downscaling. A growing number of gridded climate products are available for key climate variables which are main input data to regional modelling systems. However, inconsistencies in these climate products, for example, different combinations of climate variables, varying data domains and data lengths and data accuracy varying with physiographic characteristics of the landscape, have caused significant challenges in selecting the most suitable reference climate data for various environmental studies and modelling. Employing various observation-based daily gridded climate products available in public domain, i.e. thin plate spline regression products (ANUSPLIN and TPS), inverse distance method (Alberta Townships), and numerical climate model (North American Regional Reanalysis) and an optimum interpolation technique (Canadian Precipitation Analysis), this study evaluates the accuracy of the climate products at each grid point by comparing with the Adjusted and Homogenized Canadian Climate Data (AHCCD) observations for precipitation, minimum and maximum temperature over the province of Alberta. Based on the performance of climate products at AHCCD stations, we ranked the reliability of these publically available climate products corresponding to the elevations of stations discretized into several classes. According to the rank of climate products for each elevation class, we identified the most reliable climate products based on the elevation of target points. A web-based system was developed to allow users to easily select the most reliable reference climate data at each target point based on the elevation of grid cell. By constructing the best combination of reference data for the study domain, the accurate and reliable statistically downscaled climate projections could be significantly improved.

PCTO-SIM: Multiple-point geostatistical modeling using parallel conditional texture optimization

NASA Astrophysics Data System (ADS)

Pourfard, Mohammadreza; Abdollahifard, Mohammad J.; Faez, Karim; Motamedi, Sayed Ahmad; Hosseinian, Tahmineh

2017-05-01

Multiple-point Geostatistics is a well-known general statistical framework by which complex geological phenomena have been modeled efficiently. Pixel-based and patch-based are two major categories of these methods. In this paper, the optimization-based category is used which has a dual concept in texture synthesis as texture optimization. Our extended version of texture optimization uses the energy concept to model geological phenomena. While honoring the hard point, the minimization of our proposed cost function forces simulation grid pixels to be as similar as possible to training images. Our algorithm has a self-enrichment capability and creates a richer training database from a sparser one through mixing the information of all surrounding patches of the simulation nodes. Therefore, it preserves pattern continuity in both continuous and categorical variables very well. It also shows a fuzzy result in its every realization similar to the expected result of multi realizations of other statistical models. While the main core of most previous Multiple-point Geostatistics methods is sequential, the parallel main core of our algorithm enabled it to use GPU efficiently to reduce the CPU time. One new validation method for MPS has also been proposed in this paper.

Finding Statistically Significant Communities in Networks

PubMed Central

Lancichinetti, Andrea; Radicchi, Filippo; Ramasco, José J.; Fortunato, Santo

2011-01-01

Community structure is one of the main structural features of networks, revealing both their internal organization and the similarity of their elementary units. Despite the large variety of methods proposed to detect communities in graphs, there is a big need for multi-purpose techniques, able to handle different types of datasets and the subtleties of community structure. In this paper we present OSLOM (Order Statistics Local Optimization Method), the first method capable to detect clusters in networks accounting for edge directions, edge weights, overlapping communities, hierarchies and community dynamics. It is based on the local optimization of a fitness function expressing the statistical significance of clusters with respect to random fluctuations, which is estimated with tools of Extreme and Order Statistics. OSLOM can be used alone or as a refinement procedure of partitions/covers delivered by other techniques. We have also implemented sequential algorithms combining OSLOM with other fast techniques, so that the community structure of very large networks can be uncovered. Our method has a comparable performance as the best existing algorithms on artificial benchmark graphs. Several applications on real networks are shown as well. OSLOM is implemented in a freely available software (http://www.oslom.org), and we believe it will be a valuable tool in the analysis of networks. PMID:21559480

Permutation testing of orthogonal factorial effects in a language-processing experiment using fMRI.

PubMed

Suckling, John; Davis, Matthew H; Ooi, Cinly; Wink, Alle Meije; Fadili, Jalal; Salvador, Raymond; Welchew, David; Sendur, Levent; Maxim, Vochita; Bullmore, Edward T

2006-05-01

The block-paradigm of the Functional Image Analysis Contest (FIAC) dataset was analysed with the Brain Activation and Morphological Mapping software. Permutation methods in the wavelet domain were used for inference on cluster-based test statistics of orthogonal contrasts relevant to the factorial design of the study, namely: the average response across all active blocks, the main effect of speaker, the main effect of sentence, and the interaction between sentence and speaker. Extensive activation was seen with all these contrasts. In particular, different vs. same-speaker blocks produced elevated activation in bilateral regions of the superior temporal lobe and repetition suppression for linguistic materials (same vs. different-sentence blocks) in left inferior frontal regions. These are regions previously reported in the literature. Additional regions were detected in this study, perhaps due to the enhanced sensitivity of the methodology. Within-block sentence suppression was tested post-hoc by regression of an exponential decay model onto the extracted time series from the left inferior frontal gyrus, but no strong evidence of such an effect was found. The significance levels set for the activation maps are P-values at which we expect <1 false-positive cluster per image. Nominal type I error control was verified by empirical testing of a test statistic corresponding to a randomly ordered design matrix. The small size of the BOLD effect necessitates sensitive methods of detection of brain activation. Permutation methods permit the necessary flexibility to develop novel test statistics to meet this challenge.

Application of statistical experimental design to study the formulation variables influencing the coating process of lidocaine liposomes.

PubMed

González-Rodríguez, M L; Barros, L B; Palma, J; González-Rodríguez, P L; Rabasco, A M

2007-06-07

In this paper, we have used statistical experimental design to investigate the effect of several factors in coating process of lidocaine hydrochloride (LID) liposomes by a biodegradable polymer (chitosan, CH). These variables were the concentration of CH coating solution, the dripping rate of this solution on the liposome colloidal dispersion, the stirring rate, the time since the liposome production to the liposome coating and finally the amount of drug entrapped into liposomes. The selected response variables were drug encapsulation efficiency (EE, %), coating efficiency (CE, %) and zeta potential. Liposomes were obtained by thin-layer evaporation method. They were subsequently coated with CH according the experimental plan provided by a fractional factorial (2(5-1)) screening matrix. We have used spectroscopic methods to determine the zeta potential values. The EE (%) assay was carried out in dialysis bags and the brilliant red probe was used to determine CE (%) due to its property of forming molecular complexes with CH. The graphic analysis of the effects allowed the identification of the main formulation and technological factors by the analysis of the selected responses and permitted the determination of the proper level of these factors for the response improvement. Moreover, fractional design allowed quantifying the interactions between the factors, which will consider in next experiments. The results obtained pointed out that LID amount was the predominant factor that increased the drug entrapment capacity (EE). The CE (%) response was mainly affected by the concentration of the CH solution and the stirring rate, although all the interactions between the main factors have statistical significance.

Texture analysis with statistical methods for wheat ear extraction

NASA Astrophysics Data System (ADS)

Bakhouche, M.; Cointault, F.; Gouton, P.

2007-01-01

In agronomic domain, the simplification of crop counting, necessary for yield prediction and agronomic studies, is an important project for technical institutes such as Arvalis. Although the main objective of our global project is to conceive a mobile robot for natural image acquisition directly in a field, Arvalis has proposed us first to detect by image processing the number of wheat ears in images before to count them, which will allow to obtain the first component of the yield. In this paper we compare different texture image segmentation techniques based on feature extraction by first and higher order statistical methods which have been applied on our images. The extracted features are used for unsupervised pixel classification to obtain the different classes in the image. So, the K-means algorithm is implemented before the choice of a threshold to highlight the ears. Three methods have been tested in this feasibility study with very average error of 6%. Although the evaluation of the quality of the detection is visually done, automatic evaluation algorithms are currently implementing. Moreover, other statistical methods of higher order will be implemented in the future jointly with methods based on spatio-frequential transforms and specific filtering.

Sequential neural text compression.

PubMed

Schmidhuber, J; Heil, S

1996-01-01

The purpose of this paper is to show that neural networks may be promising tools for data compression without loss of information. We combine predictive neural nets and statistical coding techniques to compress text files. We apply our methods to certain short newspaper articles and obtain compression ratios exceeding those of the widely used Lempel-Ziv algorithms (which build the basis of the UNIX functions "compress" and "gzip"). The main disadvantage of our methods is that they are about three orders of magnitude slower than standard methods.

ReliefSeq: A Gene-Wise Adaptive-K Nearest-Neighbor Feature Selection Tool for Finding Gene-Gene Interactions and Main Effects in mRNA-Seq Gene Expression Data

PubMed Central

McKinney, Brett A.; White, Bill C.; Grill, Diane E.; Li, Peter W.; Kennedy, Richard B.; Poland, Gregory A.; Oberg, Ann L.

2013-01-01

Relief-F is a nonparametric, nearest-neighbor machine learning method that has been successfully used to identify relevant variables that may interact in complex multivariate models to explain phenotypic variation. While several tools have been developed for assessing differential expression in sequence-based transcriptomics, the detection of statistical interactions between transcripts has received less attention in the area of RNA-seq analysis. We describe a new extension and assessment of Relief-F for feature selection in RNA-seq data. The ReliefSeq implementation adapts the number of nearest neighbors (k) for each gene to optimize the Relief-F test statistics (importance scores) for finding both main effects and interactions. We compare this gene-wise adaptive-k (gwak) Relief-F method with standard RNA-seq feature selection tools, such as DESeq and edgeR, and with the popular machine learning method Random Forests. We demonstrate performance on a panel of simulated data that have a range of distributional properties reflected in real mRNA-seq data including multiple transcripts with varying sizes of main effects and interaction effects. For simulated main effects, gwak-Relief-F feature selection performs comparably to standard tools DESeq and edgeR for ranking relevant transcripts. For gene-gene interactions, gwak-Relief-F outperforms all comparison methods at ranking relevant genes in all but the highest fold change/highest signal situations where it performs similarly. The gwak-Relief-F algorithm outperforms Random Forests for detecting relevant genes in all simulation experiments. In addition, Relief-F is comparable to the other methods based on computational time. We also apply ReliefSeq to an RNA-Seq study of smallpox vaccine to identify gene expression changes between vaccinia virus-stimulated and unstimulated samples. ReliefSeq is an attractive tool for inclusion in the suite of tools used for analysis of mRNA-Seq data; it has power to detect both main effects and interaction effects. Software Availability: http://insilico.utulsa.edu/ReliefSeq.php. PMID:24339943

Heuristic Identification of Biological Architectures for Simulating Complex Hierarchical Genetic Interactions

PubMed Central

Moore, Jason H; Amos, Ryan; Kiralis, Jeff; Andrews, Peter C

2015-01-01

Simulation plays an essential role in the development of new computational and statistical methods for the genetic analysis of complex traits. Most simulations start with a statistical model using methods such as linear or logistic regression that specify the relationship between genotype and phenotype. This is appealing due to its simplicity and because these statistical methods are commonly used in genetic analysis. It is our working hypothesis that simulations need to move beyond simple statistical models to more realistically represent the biological complexity of genetic architecture. The goal of the present study was to develop a prototype genotype–phenotype simulation method and software that are capable of simulating complex genetic effects within the context of a hierarchical biology-based framework. Specifically, our goal is to simulate multilocus epistasis or gene–gene interaction where the genetic variants are organized within the framework of one or more genes, their regulatory regions and other regulatory loci. We introduce here the Heuristic Identification of Biological Architectures for simulating Complex Hierarchical Interactions (HIBACHI) method and prototype software for simulating data in this manner. This approach combines a biological hierarchy, a flexible mathematical framework, a liability threshold model for defining disease endpoints, and a heuristic search strategy for identifying high-order epistatic models of disease susceptibility. We provide several simulation examples using genetic models exhibiting independent main effects and three-way epistatic effects. PMID:25395175

Precipitation forecast using artificial neural networks. An application to the Guadalupe Valley, Baja California, Mexico

NASA Astrophysics Data System (ADS)

Herrera-Oliva, C. S.

2013-05-01

In this work we design and implement a method for the determination of precipitation forecast through the application of an elementary neuronal network (perceptron) to the statistical analysis of the precipitation reported in catalogues. The method is limited mainly by the catalogue length (and, in a smaller degree, by its accuracy). The method performance is measured using grading functions that evaluate a tradeoff between positive and negative aspects of performance. The method is applied to the Guadalupe Valley, Baja California, Mexico. Using consecutive intervals of dt=0.1 year, employing the data of several climatological stations situated in and surrounding this important wine industries zone. We evaluated the performance of different models of ANN, whose variables of entrance are the heights of precipitation. The results obtained were satisfactory, except for exceptional values of rain. Key words: precipitation forecast, artificial neural networks, statistical analysis

Clinical study of the Erlanger silver catheter--data management and biometry.

PubMed

Martus, P; Geis, C; Lugauer, S; Böswald, M; Guggenbichler, J P

1999-01-01

The clinical evaluation of venous catheters for catheter-induced infections must conform to a strict biometric methodology. The statistical planning of the study (target population, design, degree of blinding), data management (database design, definition of variables, coding), quality assurance (data inspection at several levels) and the biometric evaluation of the Erlanger silver catheter project are described. The three-step data flow included: 1) primary data from the hospital, 2) relational database, 3) files accessible for statistical evaluation. Two different statistical models were compared: analyzing the first catheter only of a patient in the analysis (independent data) and analyzing several catheters from the same patient (dependent data) by means of the generalized estimating equations (GEE) method. The main result of the study was based on the comparison of both statistical models.

Fine-Grained Indexing of the Biomedical Literature: MeSH Subheading Attachment for a MEDLINE Indexing Tool

PubMed Central

Névéol, Aurélie; Shooshan, Sonya E.; Mork, James G.; Aronson, Alan R.

2007-01-01

Objective This paper reports on the latest results of an Indexing Initiative effort addressing the automatic attachment of subheadings to MeSH main headings recommended by the NLM’s Medical Text Indexer. Material and Methods Several linguistic and statistical approaches are used to retrieve and attach the subheadings. Continuing collaboration with NLM indexers also provided insight on how automatic methods can better enhance indexing practice. Results The methods were evaluated on corpus of 50,000 MEDLINE citations. For main heading/subheading pair recommendations, the best precision is obtained with a post-processing rule method (58%) while the best recall is obtained by pooling all methods (64%). For stand-alone subheading recommendations, the best performance is obtained with the PubMed Related Citations algorithm. Conclusion Significant progress has been made in terms of subheading coverage. After further evaluation, some of this work may be integrated in the MEDLINE indexing workflow. PMID:18693897

[Application of statistics on chronic-diseases-relating observational research papers].

PubMed

Hong, Zhi-heng; Wang, Ping; Cao, Wei-hua

2012-09-01

To study the application of statistics on Chronic-diseases-relating observational research papers which were recently published in the Chinese Medical Association Magazines, with influential index above 0.5. Using a self-developed criterion, two investigators individually participated in assessing the application of statistics on Chinese Medical Association Magazines, with influential index above 0.5. Different opinions reached an agreement through discussion. A total number of 352 papers from 6 magazines, including the Chinese Journal of Epidemiology, Chinese Journal of Oncology, Chinese Journal of Preventive Medicine, Chinese Journal of Cardiology, Chinese Journal of Internal Medicine and Chinese Journal of Endocrinology and Metabolism, were reviewed. The rate of clear statement on the following contents as: research objectives, t target audience, sample issues, objective inclusion criteria and variable definitions were 99.43%, 98.57%, 95.43%, 92.86% and 96.87%. The correct rates of description on quantitative and qualitative data were 90.94% and 91.46%, respectively. The rates on correctly expressing the results, on statistical inference methods related to quantitative, qualitative data and modeling were 100%, 95.32% and 87.19%, respectively. 89.49% of the conclusions could directly response to the research objectives. However, 69.60% of the papers did not mention the exact names of the study design, statistically, that the papers were using. 11.14% of the papers were in lack of further statement on the exclusion criteria. Percentage of the papers that could clearly explain the sample size estimation only taking up as 5.16%. Only 24.21% of the papers clearly described the variable value assignment. Regarding the introduction on statistical conduction and on database methods, the rate was only 24.15%. 18.75% of the papers did not express the statistical inference methods sufficiently. A quarter of the papers did not use 'standardization' appropriately. As for the aspect of statistical inference, the rate of description on statistical testing prerequisite was only 24.12% while 9.94% papers did not even employ the statistical inferential method that should be used. The main deficiencies on the application of Statistics used in papers related to Chronic-diseases-related observational research were as follows: lack of sample-size determination, variable value assignment description not sufficient, methods on statistics were not introduced clearly or properly, lack of consideration for pre-requisition regarding the use of statistical inferences.

Uncertainty Quantification and Statistical Engineering for Hypersonic Entry Applications

NASA Technical Reports Server (NTRS)

Cozmuta, Ioana

2011-01-01

NASA has invested significant resources in developing and validating a mathematical construct for TPS margin management: a) Tailorable for low/high reliability missions; b) Tailorable for ablative/reusable TPS; c) Uncertainty Quantification and Statistical Engineering are valuable tools not exploited enough; and d) Need to define strategies combining both Theoretical Tools and Experimental Methods. The main reason for this lecture is to give a flavor of where UQ and SE could contribute and hope that the broader community will work with us to improve in these areas.

Comment on 'Imaging of prompt gamma rays emitted during delivery of clinical proton beams with a Compton camera: feasibility studies for range verification'.

PubMed

Sitek, Arkadiusz

2016-12-21

The origin ensemble (OE) algorithm is a new method used for image reconstruction from nuclear tomographic data. The main advantage of this algorithm is the ease of implementation for complex tomographic models and the sound statistical theory. In this comment, the author provides the basics of the statistical interpretation of OE and gives suggestions for the improvement of the algorithm in the application to prompt gamma imaging as described in Polf et al (2015 Phys. Med. Biol. 60 7085).

Comment on ‘Imaging of prompt gamma rays emitted during delivery of clinical proton beams with a Compton camera: feasibility studies for range verification’

NASA Astrophysics Data System (ADS)

Sitek, Arkadiusz

2016-12-01

The origin ensemble (OE) algorithm is a new method used for image reconstruction from nuclear tomographic data. The main advantage of this algorithm is the ease of implementation for complex tomographic models and the sound statistical theory. In this comment, the author provides the basics of the statistical interpretation of OE and gives suggestions for the improvement of the algorithm in the application to prompt gamma imaging as described in Polf et al (2015 Phys. Med. Biol. 60 7085).

Statistical analysis of the electrocatalytic activity of Pt nanoparticles supported on novel functionalized reduced graphene oxide-chitosan for methanol electrooxidation

NASA Astrophysics Data System (ADS)

Ekrami-Kakhki, Mehri-Saddat; Abbasi, Sedigheh; Farzaneh, Nahid

2018-01-01

The purpose of this study is to statistically analyze the anodic current density and peak potential of methanol oxidation at Pt nanoparticles supported on functionalized reduced graphene oxide (RGO), using design of experiments methodology. RGO is functionalized with methyl viologen (MV) and chitosan (CH). The novel Pt/MV-RGO-CH catalyst is successfully prepared and characterized with transmission electron microscopy (TEM) image. The electrocatalytic activity of Pt/MV-RGOCH catalyst is experimentally evaluated for methanol oxidation. The effects of methanol concentration and scan rate factors are also investigated experimentally and statistically. The effects of these two main factors and their interactions are investigated, using analysis of variance test, Duncan's multiple range test and response surface method. The results of the analysis of variance show that all the main factors and their interactions have a significant effect on anodic current density and peak potential of methanol oxidation at α = 0.05. The suggested models which encompass significant factors can predict the variation of the anodic current density and peak potential of methanol oxidation. The results of Duncan's multiple range test confirmed that there is a significant difference between the studied levels of the main factors. [Figure not available: see fulltext.

Quality evaluation of no-reference MR images using multidirectional filters and image statistics.

PubMed

Jang, Jinseong; Bang, Kihun; Jang, Hanbyol; Hwang, Dosik

2018-09-01

This study aimed to develop a fully automatic, no-reference image-quality assessment (IQA) method for MR images. New quality-aware features were obtained by applying multidirectional filters to MR images and examining the feature statistics. A histogram of these features was then fitted to a generalized Gaussian distribution function for which the shape parameters yielded different values depending on the type of distortion in the MR image. Standard feature statistics were established through a training process based on high-quality MR images without distortion. Subsequently, the feature statistics of a test MR image were calculated and compared with the standards. The quality score was calculated as the difference between the shape parameters of the test image and the undistorted standard images. The proposed IQA method showed a >0.99 correlation with the conventional full-reference assessment methods; accordingly, this proposed method yielded the best performance among no-reference IQA methods for images containing six types of synthetic, MR-specific distortions. In addition, for authentically distorted images, the proposed method yielded the highest correlation with subjective assessments by human observers, thus demonstrating its superior performance over other no-reference IQAs. Our proposed IQA was designed to consider MR-specific features and outperformed other no-reference IQAs designed mainly for photographic images. Magn Reson Med 80:914-924, 2018. © 2018 International Society for Magnetic Resonance in Medicine. © 2018 International Society for Magnetic Resonance in Medicine.

Damping Proceedings Held in Las Vegas, Nevada on 5-7 March 1986. Volume 2

DTIC Science & Technology

1986-05-01

than in metalZio materials. The main sources of internal damping in a composite material arise from microplastic or viscoelastic phenomena associated...introduction of damping treatment. The analysis of coupled structures have, to some extent, already been done using Statistical Energy Analysis ( SEA ) methods1...However SEA methods are only useful in those frequency regions with high modal density for all of the substructures. Thus for low to medium

Evaluating fMRI methods for assessing hemispheric language dominance in healthy subjects.

PubMed

Baciu, Monica; Juphard, Alexandra; Cousin, Emilie; Bas, Jean François Le

2005-08-01

We evaluated two methods for quantifying the hemispheric language dominance in healthy subjects, by using a rhyme detection (deciding whether couple of words rhyme) and a word fluency (generating words starting with a given letter) task. One of methods called "flip method" (FM) was based on the direct statistical comparison between hemispheres' activity. The second one, the classical lateralization indices method (LIM), was based on calculating lateralization indices by taking into account the number of activated pixels within hemispheres. The main difference between methods is the statistical assessment of the inter-hemispheric difference: while FM shows if the difference between hemispheres' activity is statistically significant, LIM shows only that if there is a difference between hemispheres. The robustness of LIM and FM was assessed by calculating correlation coefficients between LIs obtained with each of these methods and manual lateralization indices MLI obtained with Edinburgh inventory. Our results showed significant correlation between LIs provided by each method and the MIL, suggesting that both methods are robust for quantifying hemispheric dominance for language in healthy subjects. In the present study we also evaluated the effect of spatial normalization, smoothing and "clustering" (NSC) on the intra-hemispheric location of activated regions and inter-hemispheric asymmetry of the activation. Our results have shown that NSC did not affect the hemispheric specialization but increased the value of the inter-hemispheric difference.

Predictive Validity of DSM-IV and ICD-10 Criteria for ADHD and Hyperkinetic Disorder

ERIC Educational Resources Information Center

Lee, Soyoung I.; Schachar, Russell J.; Chen, Shirley X.; Ornstein, Tisha J.; Charach, Alice; Barr, Cathy; Ickowicz, Abel

2008-01-01

Background: The goal of this study was to compare the predictive validity of the two main diagnostic schemata for childhood hyperactivity--attention-deficit hyperactivity disorder (ADHD; "Diagnostic and Statistical Manual"-IV) and hyperkinetic disorder (HKD; "International Classification of Diseases"-10th Edition). Methods: Diagnostic criteria for…

A Data Analytical Framework for Improving Real-Time, Decision Support Systems in Healthcare

ERIC Educational Resources Information Center

Yahav, Inbal

2010-01-01

In this dissertation we develop a framework that combines data mining, statistics and operations research methods for improving real-time decision support systems in healthcare. Our approach consists of three main concepts: data gathering and preprocessing, modeling, and deployment. We introduce the notion of offline and semi-offline modeling to…

Implementing Peer-Assisted Writing Support in German Secondary Schools

ERIC Educational Resources Information Center

Rensing, Julia; Vierbuchen, Marie-Christine; Hillenbrand, Clemens; Grünke, Matthias

2016-01-01

The alarming results of large studies such as the National Assessment of Educational Progress (NAEP; National Center for Education Statistics, 2012) point to an urgent need for writing support and call for specific and effective methods to foster writing competencies. The main purpose of this paper is to describe an innovative peer-assisted…

Power Analysis in Two-Level Unbalanced Designs

ERIC Educational Resources Information Center

Konstantopoulos, Spyros

2010-01-01

Previous work on statistical power has discussed mainly single-level designs or 2-level balanced designs with random effects. Although balanced experiments are common, in practice balance cannot always be achieved. Work on class size is one example of unbalanced designs. This study provides methods for power analysis in 2-level unbalanced designs…

Introduction to Multilevel Item Response Theory Analysis: Descriptive and Explanatory Models

ERIC Educational Resources Information Center

Sulis, Isabella; Toland, Michael D.

2017-01-01

Item response theory (IRT) models are the main psychometric approach for the development, evaluation, and refinement of multi-item instruments and scaling of latent traits, whereas multilevel models are the primary statistical method when considering the dependence between person responses when primary units (e.g., students) are nested within…

The Seismic risk perception in Italy deduced by a statistical sample

NASA Astrophysics Data System (ADS)

Crescimbene, Massimo; La Longa, Federica; Camassi, Romano; Pino, Nicola Alessandro; Pessina, Vera; Peruzza, Laura; Cerbara, Loredana; Crescimbene, Cristiana

2015-04-01

In 2014 EGU Assembly we presented the results of a web a survey on the perception of seismic risk in Italy. The data were derived from over 8,500 questionnaires coming from all Italian regions. Our questionnaire was built by using the semantic differential method (Osgood et al. 1957) with a seven points Likert scale. The questionnaire is inspired the main theoretical approaches of risk perception (psychometric paradigm, cultural theory, etc.) .The results were promising and seem to clearly indicate an underestimation of seismic risk by the italian population. Based on these promising results, the DPC has funded our research for the second year. In 2015 EGU Assembly we present the results of a new survey deduced by an italian statistical sample. The importance of statistical significance at national scale was also suggested by ISTAT (Italian Statistic Institute), considering the study as of national interest, accepted the "project on the perception of seismic risk" as a pilot study inside the National Statistical System (SISTAN), encouraging our RU to proceed in this direction. The survey was conducted by a company specialised in population surveys using the CATI method (computer assisted telephone interview). Preliminary results will be discussed. The statistical support was provided by the research partner CNR-IRPPS. This research is funded by Italian Civil Protection Department (DPC).

[Prosthodontic research design from the standpoint of statistical analysis: learning and knowing the research design].

PubMed

Tanoue, Naomi

2007-10-01

For any kind of research, "Research Design" is the most important. The design is used to structure the research, to show how all of the major parts of the research project. It is necessary for all the researchers to begin the research after planning research design for what is the main theme, what is the background and reference, what kind of data is needed, and what kind of analysis is needed. It seems to be a roundabout route, but, in fact, it will be a shortcut. The research methods must be appropriate to the objectives of the study. Regarding the hypothesis-testing research that is the traditional style of the research, the research design based on statistics is undoubtedly necessary considering that the research basically proves "a hypothesis" with data and statistics theory. On the subject of the clinical trial, which is the clinical version of the hypothesis-testing research, the statistical method must be mentioned in a clinical trial planning. This report describes the basis of the research design for a prosthodontics study.

Identification of statistically independent climatic pattern in GRACE and hydrological model data over West-Africa

NASA Astrophysics Data System (ADS)

Kusche, J.; Forootan, E.; Eicker, A.; Hoffmann-Dobrev, H.

2012-04-01

West-African countries have been exposed to changes in rainfall patterns over the last decades, including a significant negative trend. This causes adverse effects on water resources, for instance reduced freshwater availability, and changes in the frequency, duration and magnitude of droughts and floods. Extracting the main patterns of water storage change in West Africa from remote sensing and linking them to climate variability, is therefore an essential step to understand the hydrological aspects of the region. In this study, the higher order statistical method of Independent Component Analysis (ICA) is employed to extract statistically independent water storage patterns from monthly Gravity Recovery And Climate Experiment (GRACE), from the WaterGAP Global Hydrology Model (WGHM) and from Tropical Rainfall Measuring Mission (TRMM) products over West Africa, for the period 2002-2012. Then, to reveal the influences of climatic teleconnections on the individual patterns, these results were correlated to the El Nino-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) indices. To study the predictability of water storage changes, advanced statistical methods were applied on the main independent Sea Surface Temperature (SST) patterns over the Atlantic and Indian Oceans for the period 2002-2012 and the ICA results. Our results show a water storage decrease over the coastal regions of West Africa (including Sierra Leone, Liberia, Togo and Nigeria), associated with rainfall decrease. The comparison between GRACE estimations and WGHM results indicates some inconsistencies that underline the importance of forcing data for hydrological modeling of West Africa. Keywords: West Africa; GRACE-derived water storage; ICA; ENSO; IOD

Numerical solutions of ideal quantum gas dynamical flows governed by semiclassical ellipsoidal-statistical distribution

PubMed Central

Yang, Jaw-Yen; Yan, Chih-Yuan; Diaz, Manuel; Huang, Juan-Chen; Li, Zhihui; Zhang, Hanxin

2014-01-01

The ideal quantum gas dynamics as manifested by the semiclassical ellipsoidal-statistical (ES) equilibrium distribution derived in Wu et al. (Wu et al. 2012 Proc. R. Soc. A 468, 1799–1823 (doi:10.1098/rspa.2011.0673)) is numerically studied for particles of three statistics. This anisotropic ES equilibrium distribution was derived using the maximum entropy principle and conserves the mass, momentum and energy, but differs from the standard Fermi–Dirac or Bose–Einstein distribution. The present numerical method combines the discrete velocity (or momentum) ordinate method in momentum space and the high-resolution shock-capturing method in physical space. A decoding procedure to obtain the necessary parameters for determining the ES distribution is also devised. Computations of two-dimensional Riemann problems are presented, and various contours of the quantities unique to this ES model are illustrated. The main flow features, such as shock waves, expansion waves and slip lines and their complex nonlinear interactions, are depicted and found to be consistent with existing calculations for a classical gas. PMID:24399919

Fine-grained indexing of the biomedical literature: MeSH subheading attachment for a MEDLINE indexing tool.

PubMed

Névéol, Aurélie; Shooshan, Sonya E; Mork, James G; Aronson, Alan R

2007-10-11

This paper reports on the latest results of an Indexing Initiative effort addressing the automatic attachment of subheadings to MeSH main headings recommended by the NLM's Medical Text Indexer. Several linguistic and statistical approaches are used to retrieve and attach the subheadings. Continuing collaboration with NLM indexers also provided insight on how automatic methods can better enhance indexing practice. The methods were evaluated on corpus of 50,000 MEDLINE citations. For main heading/subheading pair recommendations, the best precision is obtained with a post-processing rule method (58%) while the best recall is obtained by pooling all methods (64%). For stand-alone subheading recommendations, the best performance is obtained with the PubMed Related Citations algorithm. Significant progress has been made in terms of subheading coverage. After further evaluation, some of this work may be integrated in the MEDLINE indexing workflow.

[Study on commercial specification of atractylodes based on Delphi method].

PubMed

Wang, Hao; Chen, Li-Xiao; Huang, Lu-Qi; Zhang, Tian-Tian; Li, Ying; Zheng, Yu-Guang

2016-03-01

This research adopts "Delphi method" to evaluate atractylodes traditional traits and rank correlation. By using methods of mathematical statistics the relationship of the traditional identification indicators and atractylodes goods rank correlation was analyzed, It is found that the main characteristics affectingatractylodes commodity specifications and grades of main characters wereoil points of transaction,color of transaction,color of surface,grain of transaction,texture of transaction andspoilage. The study points out that the original "seventy-six kinds of medicinal materials commodity specification standards of atractylodes differentiate commodity specification" is not in conformity with the actual market situation, we need to formulate corresponding atractylodes medicinal products specifications and grades.This study combined with experimental results "Delphi method" and the market actual situation, proposed the new draft atractylodes commodity specifications and grades, as the new atractylodes commodity specifications and grades standards. It provides a reference and theoretical basis. Copyright© by the Chinese Pharmaceutical Association.

Precipitate statistics in an Al-Mg-Si-Cu alloy from scanning precession electron diffraction data

NASA Astrophysics Data System (ADS)

Sunde, J. K.; Paulsen, Ø.; Wenner, S.; Holmestad, R.

2017-09-01

The key microstructural feature providing strength to age-hardenable Al alloys is nanoscale precipitates. Alloy development requires a reliable statistical assessment of these precipitates, in order to link the microstructure with material properties. Here, it is demonstrated that scanning precession electron diffraction combined with computational analysis enable the semi-automated extraction of precipitate statistics in an Al-Mg-Si-Cu alloy. Among the main findings is the precipitate number density, which agrees well with a conventional method based on manual counting and measurements. By virtue of its data analysis objectivity, our methodology is therefore seen as an advantageous alternative to existing routines, offering reproducibility and efficiency in alloy statistics. Additional results include improved qualitative information on phase distributions. The developed procedure is generic and applicable to any material containing nanoscale precipitates.

Launch commit criteria performance trending analysis, phase 1, revision A. SRM and QA mission services

NASA Technical Reports Server (NTRS)

1989-01-01

An assessment of quantitative methods and measures for measuring launch commit criteria (LCC) performance measurement trends is made. A statistical performance trending analysis pilot study was processed and compared to STS-26 mission data. This study used four selected shuttle measurement types (solid rocket booster, external tank, space shuttle main engine, and range safety switch safe and arm device) from the five missions prior to mission 51-L. After obtaining raw data coordinates, each set of measurements was processed to obtain statistical confidence bounds and mean data profiles for each of the selected measurement types. STS-26 measurements were compared to the statistical data base profiles to verify the statistical capability of assessing occurrences of data trend anomalies and abnormal time-varying operational conditions associated with data amplitude and phase shifts.

Trends in Citations to Books on Epidemiological and Statistical Methods in the Biomedical Literature

PubMed Central

Porta, Miquel; Vandenbroucke, Jan P.; Ioannidis, John P. A.; Sanz, Sergio; Fernandez, Esteve; Bhopal, Raj; Morabia, Alfredo; Victora, Cesar; Lopez, Tomàs

2013-01-01

Background There are no analyses of citations to books on epidemiological and statistical methods in the biomedical literature. Such analyses may shed light on how concepts and methods changed while biomedical research evolved. Our aim was to analyze the number and time trends of citations received from biomedical articles by books on epidemiological and statistical methods, and related disciplines. Methods and Findings The data source was the Web of Science. The study books were published between 1957 and 2010. The first year of publication of the citing articles was 1945. We identified 125 books that received at least 25 citations. Books first published in 1980–1989 had the highest total and median number of citations per year. Nine of the 10 most cited texts focused on statistical methods. Hosmer & Lemeshow's Applied logistic regression received the highest number of citations and highest average annual rate. It was followed by books by Fleiss, Armitage, et al., Rothman, et al., and Kalbfleisch and Prentice. Fifth in citations per year was Sackett, et al., Evidence-based medicine. The rise of multivariate methods, clinical epidemiology, or nutritional epidemiology was reflected in the citation trends. Educational textbooks, practice-oriented books, books on epidemiological substantive knowledge, and on theory and health policies were much less cited. None of the 25 top-cited books had the theoretical or sociopolitical scope of works by Cochrane, McKeown, Rose, or Morris. Conclusions Books were mainly cited to reference methods. Books first published in the 1980s continue to be most influential. Older books on theory and policies were rooted in societal and general medical concerns, while the most modern books are almost purely on methods. PMID:23667447

EAS fluctuation approach to primary mass composition investigation

NASA Technical Reports Server (NTRS)

Stamenov, J. N.; Janminchev, V. D.

1985-01-01

The analysis of muon and electron fluctuation distribution shapes by statistical method of invers problem solution gives the possibility to obtain the relative contribution values of the five main primary nuclei groups. The method is model-independent for a big class of interaction models and can give good results for observation levels not too far from the development maximum and for the selection of showers with fixed sizes and zenith angles not bigger than 30 deg.

Outcomes Definitions and Statistical Tests in Oncology Studies: A Systematic Review of the Reporting Consistency

PubMed Central

Rivoirard, Romain; Duplay, Vianney; Oriol, Mathieu; Tinquaut, Fabien; Chauvin, Franck; Magne, Nicolas; Bourmaud, Aurelie

2016-01-01

Background Quality of reporting for Randomized Clinical Trials (RCTs) in oncology was analyzed in several systematic reviews, but, in this setting, there is paucity of data for the outcomes definitions and consistency of reporting for statistical tests in RCTs and Observational Studies (OBS). The objective of this review was to describe those two reporting aspects, for OBS and RCTs in oncology. Methods From a list of 19 medical journals, three were retained for analysis, after a random selection: British Medical Journal (BMJ), Annals of Oncology (AoO) and British Journal of Cancer (BJC). All original articles published between March 2009 and March 2014 were screened. Only studies whose main outcome was accompanied by a corresponding statistical test were included in the analysis. Studies based on censored data were excluded. Primary outcome was to assess quality of reporting for description of primary outcome measure in RCTs and of variables of interest in OBS. A logistic regression was performed to identify covariates of studies potentially associated with concordance of tests between Methods and Results parts. Results 826 studies were included in the review, and 698 were OBS. Variables were described in Methods section for all OBS studies and primary endpoint was clearly detailed in Methods section for 109 RCTs (85.2%). 295 OBS (42.2%) and 43 RCTs (33.6%) had perfect agreement for reported statistical test between Methods and Results parts. In multivariable analysis, variable "number of included patients in study" was associated with test consistency: aOR (adjusted Odds Ratio) for third group compared to first group was equal to: aOR Grp3 = 0.52 [0.31–0.89] (P value = 0.009). Conclusion Variables in OBS and primary endpoint in RCTs are reported and described with a high frequency. However, statistical tests consistency between methods and Results sections of OBS is not always noted. Therefore, we encourage authors and peer reviewers to verify consistency of statistical tests in oncology studies. PMID:27716793

Paleontology and Darwin's Theory of Evolution: The Subversive Role of Statistics at the End of the 19th Century.

PubMed

Tamborini, Marco

2015-11-01

This paper examines the subversive role of statistics paleontology at the end of the 19th and the beginning of the 20th centuries. In particular, I will focus on German paleontology and its relationship with statistics. I argue that in paleontology, the quantitative method was questioned and strongly limited by the first decade of the 20th century because, as its opponents noted, when the fossil record is treated statistically, it was found to generate results openly in conflict with the Darwinian theory of evolution. Essentially, statistics questions the gradual mode of evolution and the role of natural selection. The main objections to statistics were addressed during the meetings at the Kaiserlich-Königliche Geologische Reichsanstalt in Vienna in the 1880s. After having introduced the statistical treatment of the fossil record, I will use the works of Charles Léo Lesquereux (1806-1889), Joachim Barrande (1799-1833), and Henry Shaler Williams (1847-1918) to compare the objections raised in Vienna with how the statistical treatment of the data worked in practice. Furthermore, I will discuss the criticisms of Melchior Neumayr (1845-1890), one of the leading German opponents of statistical paleontology, to show why, and to what extent, statistics were questioned in Vienna. The final part of this paper considers what paleontologists can derive from a statistical notion of data: the necessity of opening a discussion about the completeness and nature of the paleontological data. The Vienna discussion about which method paleontologists should follow offers an interesting case study in order to understand the epistemic tensions within paleontology surrounding Darwin's theory as well as the variety of non-Darwinian alternatives that emerged from the statistical treatment of the fossil record at the end of the 19th century.

Utilizing the N beam position monitor method for turn-by-turn optics measurements

NASA Astrophysics Data System (ADS)

Langner, A.; Benedetti, G.; Carlà, M.; Iriso, U.; Martí, Z.; de Portugal, J. Coello; Tomás, R.

2016-09-01

The N beam position monitor method (N -BPM) which was recently developed for the LHC has significantly improved the precision of optics measurements that are based on BPM turn-by-turn data. The main improvement is due to the consideration of correlations for statistical and systematic error sources, as well as increasing the amount of BPM combinations which are used to derive the β -function at one location. We present how this technique can be applied at light sources like ALBA, and compare the results with other methods.

Accumuler le capital humain tout au long de la vie: Quels facteurs prédictifs de la participation à la formation permanente?

NASA Astrophysics Data System (ADS)

Boudard, Emmanuel; Morlaix, Sophie

2003-09-01

This article addresses the main predictors of adult education, using statistical methods different from those generally used by social science researchers. Its aim is twofold. First, it seeks to explain in a simple and comprehensible manner the methodological value of these methods (in relation to the use of structural models); secondly, it demonstrates the concrete usefulness of these methods on the basis of a recent piece of research on the data from the International Adult Literacy Survey (IALS).

Multifactor-Dimensionality Reduction Reveals High-Order Interactions among Estrogen-Metabolism Genes in Sporadic Breast Cancer

PubMed Central

Ritchie, Marylyn D.; Hahn, Lance W.; Roodi, Nady; Bailey, L. Renee; Dupont, William D.; Parl, Fritz F.; Moore, Jason H.

2001-01-01

One of the greatest challenges facing human geneticists is the identification and characterization of susceptibility genes for common complex multifactorial human diseases. This challenge is partly due to the limitations of parametric-statistical methods for detection of gene effects that are dependent solely or partially on interactions with other genes and with environmental exposures. We introduce multifactor-dimensionality reduction (MDR) as a method for reducing the dimensionality of multilocus information, to improve the identification of polymorphism combinations associated with disease risk. The MDR method is nonparametric (i.e., no hypothesis about the value of a statistical parameter is made), is model-free (i.e., it assumes no particular inheritance model), and is directly applicable to case-control and discordant-sib-pair studies. Using simulated case-control data, we demonstrate that MDR has reasonable power to identify interactions among two or more loci in relatively small samples. When it was applied to a sporadic breast cancer case-control data set, in the absence of any statistically significant independent main effects, MDR identified a statistically significant high-order interaction among four polymorphisms from three different estrogen-metabolism genes. To our knowledge, this is the first report of a four-locus interaction associated with a common complex multifactorial disease. PMID:11404819

Modeling Socially Desirable Responding and Its Effects

ERIC Educational Resources Information Center

Ziegler, Matthias; Buehner, Markus

2009-01-01

The impact of socially desirable responding or faking on noncognitive assessments remains an issue of strong debate. One of the main reasons for the controversy is the lack of a statistical method to model such response sets. This article introduces a new way to model faking based on the assumption that faking occurs due to an interaction between…

Automatic cloud coverage assessment of Formosat-2 image

NASA Astrophysics Data System (ADS)

Hsu, Kuo-Hsien

2011-11-01

Formosat-2 satellite equips with the high-spatial-resolution (2m ground sampling distance) remote sensing instrument. It has been being operated on the daily-revisiting mission orbit by National Space organization (NSPO) of Taiwan since May 21 2004. NSPO has also serving as one of the ground receiving stations for daily processing the received Formosat- 2 images. The current cloud coverage assessment of Formosat-2 image for NSPO Image Processing System generally consists of two major steps. Firstly, an un-supervised K-means method is used for automatically estimating the cloud statistic of Formosat-2 image. Secondly, manual estimation of cloud coverage from Formosat-2 image is processed by manual examination. Apparently, a more accurate Automatic Cloud Coverage Assessment (ACCA) method certainly increases the efficiency of processing step 2 with a good prediction of cloud statistic. In this paper, mainly based on the research results from Chang et al, Irish, and Gotoh, we propose a modified Formosat-2 ACCA method which considered pre-processing and post-processing analysis. For pre-processing analysis, cloud statistic is determined by using un-supervised K-means classification, Sobel's method, Otsu's method, non-cloudy pixels reexamination, and cross-band filter method. Box-Counting fractal method is considered as a post-processing tool to double check the results of pre-processing analysis for increasing the efficiency of manual examination.

Near-equilibrium dumb-bell-shaped figures for cohesionless small bodies

NASA Astrophysics Data System (ADS)

Descamps, Pascal

2016-02-01

In a previous paper (Descamps, P. [2015]. Icarus 245, 64-79), we developed a specific method aimed to retrieve the main physical characteristics (shape, density, surface scattering properties) of highly elongated bodies from their rotational lightcurves through the use of dumb-bell-shaped equilibrium figures. The present work is a test of this method. For that purpose we introduce near-equilibrium dumb-bell-shaped figures which are base dumb-bell equilibrium shapes modulated by lognormal statistics. Such synthetic irregular models are used to generate lightcurves from which our method is successfully applied. Shape statistical parameters of such near-equilibrium dumb-bell-shaped objects are in good agreement with those calculated for example for the Asteroid (216) Kleopatra from its dog-bone radar model. It may suggest that such bilobed and elongated asteroids can be approached by equilibrium figures perturbed be the interplay with a substantial internal friction modeled by a Gaussian random sphere.

Multi-classification of cell deformation based on object alignment and run length statistic.

PubMed

Li, Heng; Liu, Zhiwen; An, Xing; Shi, Yonggang

2014-01-01

Cellular morphology is widely applied in digital pathology and is essential for improving our understanding of the basic physiological processes of organisms. One of the main issues of application is to develop efficient methods for cell deformation measurement. We propose an innovative indirect approach to analyze dynamic cell morphology in image sequences. The proposed approach considers both the cellular shape change and cytoplasm variation, and takes each frame in the image sequence into account. The cell deformation is measured by the minimum energy function of object alignment, which is invariant to object pose. Then an indirect analysis strategy is employed to overcome the limitation of gradual deformation by run length statistic. We demonstrate the power of the proposed approach with one application: multi-classification of cell deformation. Experimental results show that the proposed method is sensitive to the morphology variation and performs better than standard shape representation methods.

From Tornadoes to Earthquakes: Forecast Verification for Binary Events Applied to the 1999 Chi-Chi, Taiwan, Earthquake

NASA Astrophysics Data System (ADS)

Chen, C.; Rundle, J. B.; Holliday, J. R.; Nanjo, K.; Turcotte, D. L.; Li, S.; Tiampo, K. F.

2005-12-01

Forecast verification procedures for statistical events with binary outcomes typically rely on the use of contingency tables and Relative Operating Characteristic (ROC) diagrams. Originally developed for the statistical evaluation of tornado forecasts on a county-by-county basis, these methods can be adapted to the evaluation of competing earthquake forecasts. Here we apply these methods retrospectively to two forecasts for the m = 7.3 1999 Chi-Chi, Taiwan, earthquake. These forecasts are based on a method, Pattern Informatics (PI), that locates likely sites for future large earthquakes based on large change in activity of the smallest earthquakes. A competing null hypothesis, Relative Intensity (RI), is based on the idea that future large earthquake locations are correlated with sites having the greatest frequency of small earthquakes. We show that for Taiwan, the PI forecast method is superior to the RI forecast null hypothesis. Inspection of the two maps indicates that their forecast locations are indeed quite different. Our results confirm an earlier result suggesting that the earthquake preparation process for events such as the Chi-Chi earthquake involves anomalous changes in activation or quiescence, and that signatures of these processes can be detected in precursory seismicity data. Furthermore, we find that our methods can accurately forecast the locations of aftershocks from precursory seismicity changes alone, implying that the main shock together with its aftershocks represent a single manifestation of the formation of a high-stress region nucleating prior to the main shock.

The Taguchi methodology as a statistical tool for biotechnological applications: a critical appraisal.

PubMed

Rao, Ravella Sreenivas; Kumar, C Ganesh; Prakasham, R Shetty; Hobbs, Phil J

2008-04-01

Success in experiments and/or technology mainly depends on a properly designed process or product. The traditional method of process optimization involves the study of one variable at a time, which requires a number of combinations of experiments that are time, cost and labor intensive. The Taguchi method of design of experiments is a simple statistical tool involving a system of tabulated designs (arrays) that allows a maximum number of main effects to be estimated in an unbiased (orthogonal) fashion with a minimum number of experimental runs. It has been applied to predict the significant contribution of the design variable(s) and the optimum combination of each variable by conducting experiments on a real-time basis. The modeling that is performed essentially relates signal-to-noise ratio to the control variables in a 'main effect only' approach. This approach enables both multiple response and dynamic problems to be studied by handling noise factors. Taguchi principles and concepts have made extensive contributions to industry by bringing focused awareness to robustness, noise and quality. This methodology has been widely applied in many industrial sectors; however, its application in biological sciences has been limited. In the present review, the application and comparison of the Taguchi methodology has been emphasized with specific case studies in the field of biotechnology, particularly in diverse areas like fermentation, food processing, molecular biology, wastewater treatment and bioremediation.

Statistical theory for protein combinatorial libraries. Packing interactions, backbone flexibility, and the sequence variability of a main-chain structure.

PubMed

Kono, H; Saven, J G

2001-02-23

Combinatorial experiments provide new ways to probe the determinants of protein folding and to identify novel folding amino acid sequences. These types of experiments, however, are complicated both by enormous conformational complexity and by large numbers of possible sequences. Therefore, a quantitative computational theory would be helpful in designing and interpreting these types of experiment. Here, we present and apply a statistically based, computational approach for identifying the properties of sequences compatible with a given main-chain structure. Protein side-chain conformations are included in an atom-based fashion. Calculations are performed for a variety of similar backbone structures to identify sequence properties that are robust with respect to minor changes in main-chain structure. Rather than specific sequences, the method yields the likelihood of each of the amino acids at preselected positions in a given protein structure. The theory may be used to quantify the characteristics of sequence space for a chosen structure without explicitly tabulating sequences. To account for hydrophobic effects, we introduce an environmental energy that it is consistent with other simple hydrophobicity scales and show that it is effective for side-chain modeling. We apply the method to calculate the identity probabilities of selected positions of the immunoglobulin light chain-binding domain of protein L, for which many variant folding sequences are available. The calculations compare favorably with the experimentally observed identity probabilities.

Trends in citations to books on epidemiological and statistical methods in the biomedical literature.

PubMed

Porta, Miquel; Vandenbroucke, Jan P; Ioannidis, John P A; Sanz, Sergio; Fernandez, Esteve; Bhopal, Raj; Morabia, Alfredo; Victora, Cesar; Lopez, Tomàs

2013-01-01

There are no analyses of citations to books on epidemiological and statistical methods in the biomedical literature. Such analyses may shed light on how concepts and methods changed while biomedical research evolved. Our aim was to analyze the number and time trends of citations received from biomedical articles by books on epidemiological and statistical methods, and related disciplines. The data source was the Web of Science. The study books were published between 1957 and 2010. The first year of publication of the citing articles was 1945. We identified 125 books that received at least 25 citations. Books first published in 1980-1989 had the highest total and median number of citations per year. Nine of the 10 most cited texts focused on statistical methods. Hosmer & Lemeshow's Applied logistic regression received the highest number of citations and highest average annual rate. It was followed by books by Fleiss, Armitage, et al., Rothman, et al., and Kalbfleisch and Prentice. Fifth in citations per year was Sackett, et al., Evidence-based medicine. The rise of multivariate methods, clinical epidemiology, or nutritional epidemiology was reflected in the citation trends. Educational textbooks, practice-oriented books, books on epidemiological substantive knowledge, and on theory and health policies were much less cited. None of the 25 top-cited books had the theoretical or sociopolitical scope of works by Cochrane, McKeown, Rose, or Morris. Books were mainly cited to reference methods. Books first published in the 1980s continue to be most influential. Older books on theory and policies were rooted in societal and general medical concerns, while the most modern books are almost purely on methods.

A rheumatoid arthritis study by Fourier transform infrared spectroscopy

NASA Astrophysics Data System (ADS)

Carvalho, Carolina S.; Silva, Ana Carla A.; Santos, Tatiano J. P. S.; Martin, Airton A.; dos Santos Fernandes, Ana Célia; Andrade, Luís E.; Raniero, Leandro

2012-01-01

Rheumatoid arthritis is a systemic inflammatory disease of unknown causes and a new methods to identify it in early stages are needed. The main purpose of this work is the biochemical differentiation of sera between normal and RA patients, through the establishment of a statistical method that can be appropriately used for serological analysis. The human sera from 39 healthy donors and 39 rheumatics donors were collected and analyzed by Fourier Transform Infrared Spectroscopy. The results show significant spectral variations with p<0.05 in regions corresponding to protein, lipids and immunoglobulins. The technique of latex particles, coated with human IgG and monoclonal anti-CRP by indirect agglutination known as FR and CRP, was performed to confirm possible false-negative results within the groups, facilitating the statistical interpretation and validation of the technique.

Wastewater-Based Epidemiology of Stimulant Drugs: Functional Data Analysis Compared to Traditional Statistical Methods.

PubMed

Salvatore, Stefania; Bramness, Jørgen Gustav; Reid, Malcolm J; Thomas, Kevin Victor; Harman, Christopher; Røislien, Jo

2015-01-01

Wastewater-based epidemiology (WBE) is a new methodology for estimating the drug load in a population. Simple summary statistics and specification tests have typically been used to analyze WBE data, comparing differences between weekday and weekend loads. Such standard statistical methods may, however, overlook important nuanced information in the data. In this study, we apply functional data analysis (FDA) to WBE data and compare the results to those obtained from more traditional summary measures. We analysed temporal WBE data from 42 European cities, using sewage samples collected daily for one week in March 2013. For each city, the main temporal features of two selected drugs were extracted using functional principal component (FPC) analysis, along with simpler measures such as the area under the curve (AUC). The individual cities' scores on each of the temporal FPCs were then used as outcome variables in multiple linear regression analysis with various city and country characteristics as predictors. The results were compared to those of functional analysis of variance (FANOVA). The three first FPCs explained more than 99% of the temporal variation. The first component (FPC1) represented the level of the drug load, while the second and third temporal components represented the level and the timing of a weekend peak. AUC was highly correlated with FPC1, but other temporal characteristic were not captured by the simple summary measures. FANOVA was less flexible than the FPCA-based regression, and even showed concordance results. Geographical location was the main predictor for the general level of the drug load. FDA of WBE data extracts more detailed information about drug load patterns during the week which are not identified by more traditional statistical methods. Results also suggest that regression based on FPC results is a valuable addition to FANOVA for estimating associations between temporal patterns and covariate information.

P values in display items are ubiquitous and almost invariably significant: A survey of top science journals

PubMed Central

Cristea, Ioana Alina

2018-01-01

P values represent a widely used, but pervasively misunderstood and fiercely contested method of scientific inference. Display items, such as figures and tables, often containing the main results, are an important source of P values. We conducted a survey comparing the overall use of P values and the occurrence of significant P values in display items of a sample of articles in the three top multidisciplinary journals (Nature, Science, PNAS) in 2017 and, respectively, in 1997. We also examined the reporting of multiplicity corrections and its potential influence on the proportion of statistically significant P values. Our findings demonstrated substantial and growing reliance on P values in display items, with increases of 2.5 to 14.5 times in 2017 compared to 1997. The overwhelming majority of P values (94%, 95% confidence interval [CI] 92% to 96%) were statistically significant. Methods to adjust for multiplicity were almost non-existent in 1997, but reported in many articles relying on P values in 2017 (Nature 68%, Science 48%, PNAS 38%). In their absence, almost all reported P values were statistically significant (98%, 95% CI 96% to 99%). Conversely, when any multiplicity corrections were described, 88% (95% CI 82% to 93%) of reported P values were statistically significant. Use of Bayesian methods was scant (2.5%) and rarely (0.7%) articles relied exclusively on Bayesian statistics. Overall, wider appreciation of the need for multiplicity corrections is a welcome evolution, but the rapid growth of reliance on P values and implausibly high rates of reported statistical significance are worrisome. PMID:29763472

P values in display items are ubiquitous and almost invariably significant: A survey of top science journals.

PubMed

Cristea, Ioana Alina; Ioannidis, John P A

2018-01-01

P values represent a widely used, but pervasively misunderstood and fiercely contested method of scientific inference. Display items, such as figures and tables, often containing the main results, are an important source of P values. We conducted a survey comparing the overall use of P values and the occurrence of significant P values in display items of a sample of articles in the three top multidisciplinary journals (Nature, Science, PNAS) in 2017 and, respectively, in 1997. We also examined the reporting of multiplicity corrections and its potential influence on the proportion of statistically significant P values. Our findings demonstrated substantial and growing reliance on P values in display items, with increases of 2.5 to 14.5 times in 2017 compared to 1997. The overwhelming majority of P values (94%, 95% confidence interval [CI] 92% to 96%) were statistically significant. Methods to adjust for multiplicity were almost non-existent in 1997, but reported in many articles relying on P values in 2017 (Nature 68%, Science 48%, PNAS 38%). In their absence, almost all reported P values were statistically significant (98%, 95% CI 96% to 99%). Conversely, when any multiplicity corrections were described, 88% (95% CI 82% to 93%) of reported P values were statistically significant. Use of Bayesian methods was scant (2.5%) and rarely (0.7%) articles relied exclusively on Bayesian statistics. Overall, wider appreciation of the need for multiplicity corrections is a welcome evolution, but the rapid growth of reliance on P values and implausibly high rates of reported statistical significance are worrisome.

EEG Sleep Stages Classification Based on Time Domain Features and Structural Graph Similarity.

PubMed

Diykh, Mohammed; Li, Yan; Wen, Peng

2016-11-01

The electroencephalogram (EEG) signals are commonly used in diagnosing and treating sleep disorders. Many existing methods for sleep stages classification mainly depend on the analysis of EEG signals in time or frequency domain to obtain a high classification accuracy. In this paper, the statistical features in time domain, the structural graph similarity and the K-means (SGSKM) are combined to identify six sleep stages using single channel EEG signals. Firstly, each EEG segment is partitioned into sub-segments. The size of a sub-segment is determined empirically. Secondly, statistical features are extracted, sorted into different sets of features and forwarded to the SGSKM to classify EEG sleep stages. We have also investigated the relationships between sleep stages and the time domain features of the EEG data used in this paper. The experimental results show that the proposed method yields better classification results than other four existing methods and the support vector machine (SVM) classifier. A 95.93% average classification accuracy is achieved by using the proposed method.

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

Kaurov, Alexander A., E-mail: kaurov@uchicago.edu

The methods for studying the epoch of cosmic reionization vary from full radiative transfer simulations to purely analytical models. While numerical approaches are computationally expensive and are not suitable for generating many mock catalogs, analytical methods are based on assumptions and approximations. We explore the interconnection between both methods. First, we ask how the analytical framework of excursion set formalism can be used for statistical analysis of numerical simulations and visual representation of the morphology of ionization fronts. Second, we explore the methods of training the analytical model on a given numerical simulation. We present a new code which emergedmore » from this study. Its main application is to match the analytical model with a numerical simulation. Then, it allows one to generate mock reionization catalogs with volumes exceeding the original simulation quickly and computationally inexpensively, meanwhile reproducing large-scale statistical properties. These mock catalogs are particularly useful for cosmic microwave background polarization and 21 cm experiments, where large volumes are required to simulate the observed signal.« less

Agreement between self-reported data on medicine use and prescription records vary according to method of analysis and therapeutic group.

PubMed

Nielsen, Merete Willemoes; Søndergaard, Birthe; Kjøller, Mette; Hansen, Ebba Holme

2008-09-01

This study compared national self-reported data on medicine use and national prescription records at the individual level. Data from the nationally representative Danish health survey conducted in 2000 (n=16,688) were linked at the individual level to national prescription records covering 1999-2000. Kappa statistics and 95% confidence intervals were calculated. Applying the legend time method to medicine groups used mainly on a chronic basis revealed good to very good agreement between the two data sources, whereas medicines used as needed showed fair to moderate agreement. When a fixed-time window was applied for analysis, agreement was unchanged for medicines used mainly on a chronic basis, whereas agreement increased somewhat compared to the legend time method when analyzing medicines used as needed. Agreement between national self-reported data and national prescription records differed according to method of analysis and therapeutic group. A fixed-time window is an appropriate method of analysis for most therapeutic groups.

Outcomes Definitions and Statistical Tests in Oncology Studies: A Systematic Review of the Reporting Consistency.

PubMed

Rivoirard, Romain; Duplay, Vianney; Oriol, Mathieu; Tinquaut, Fabien; Chauvin, Franck; Magne, Nicolas; Bourmaud, Aurelie

2016-01-01

Quality of reporting for Randomized Clinical Trials (RCTs) in oncology was analyzed in several systematic reviews, but, in this setting, there is paucity of data for the outcomes definitions and consistency of reporting for statistical tests in RCTs and Observational Studies (OBS). The objective of this review was to describe those two reporting aspects, for OBS and RCTs in oncology. From a list of 19 medical journals, three were retained for analysis, after a random selection: British Medical Journal (BMJ), Annals of Oncology (AoO) and British Journal of Cancer (BJC). All original articles published between March 2009 and March 2014 were screened. Only studies whose main outcome was accompanied by a corresponding statistical test were included in the analysis. Studies based on censored data were excluded. Primary outcome was to assess quality of reporting for description of primary outcome measure in RCTs and of variables of interest in OBS. A logistic regression was performed to identify covariates of studies potentially associated with concordance of tests between Methods and Results parts. 826 studies were included in the review, and 698 were OBS. Variables were described in Methods section for all OBS studies and primary endpoint was clearly detailed in Methods section for 109 RCTs (85.2%). 295 OBS (42.2%) and 43 RCTs (33.6%) had perfect agreement for reported statistical test between Methods and Results parts. In multivariable analysis, variable "number of included patients in study" was associated with test consistency: aOR (adjusted Odds Ratio) for third group compared to first group was equal to: aOR Grp3 = 0.52 [0.31-0.89] (P value = 0.009). Variables in OBS and primary endpoint in RCTs are reported and described with a high frequency. However, statistical tests consistency between methods and Results sections of OBS is not always noted. Therefore, we encourage authors and peer reviewers to verify consistency of statistical tests in oncology studies.

Attitude of teaching faculty towards statistics at a medical university in Karachi, Pakistan.

PubMed

Khan, Nazeer; Mumtaz, Yasmin

2009-01-01

Statistics is mainly used in biological research to verify the clinicians and researchers findings and feelings, and gives scientific validity for their inferences. In Pakistan, the educational curriculum is developed in such a way that the students who are interested in entering in the field of biological sciences do not study mathematics after grade 10. Therefore, due to their fragile background of mathematical skills, the Pakistani medical professionals feel that they do not have adequate base to understand the basic concepts of statistical techniques when they try to use it in their research or read a scientific article. The aim of the study was to assess the attitude of medical faculty towards statistics. A questionnaire containing 42 close-ended and 4 open-ended questions, related to the attitude and knowledge of statistics, was distributed among the teaching faculty of Dow University of Health Sciences (DUHS). One hundred and sixty-seven filled questionnaires were returned from 374 faculty members (response rate 44.7%). Forty-three percent of the respondents claimed that they had 'introductive' level of statistics courses, 63% of the respondents strongly agreed that a good researcher must have some training in statistics, 82% of the faculty was in favour (strongly agreed or agreed) that statistics was really useful for research. Only 17% correctly stated that statistics is the science of uncertainty. Half of the respondents accepted that they have problem of writing the statistical section of the article. 64% of the subjects indicated that statistical teaching methods were the main reasons for the impression of its difficulties. 53% of the faculty indicated that the co-authorship of the statistician should depend upon his/her contribution in the study. Gender did not show any significant difference among the responses. However, senior faculty showed higher level of the importance for the use of statistics and difficulties of writing result section of articles as compared to junior faculty. The study showed a low level of knowledge, but high level of the awareness for the use of statistical techniques in research and exhibited a good level of motivation for further training.

IMPLEMENTATION AND VALIDATION OF STATISTICAL TESTS IN RESEARCH'S SOFTWARE HELPING DATA COLLECTION AND PROTOCOLS ANALYSIS IN SURGERY.

PubMed

Kuretzki, Carlos Henrique; Campos, Antônio Carlos Ligocki; Malafaia, Osvaldo; Soares, Sandramara Scandelari Kusano de Paula; Tenório, Sérgio Bernardo; Timi, Jorge Rufino Ribas

2016-03-01

The use of information technology is often applied in healthcare. With regard to scientific research, the SINPE(c) - Integrated Electronic Protocols was created as a tool to support researchers, offering clinical data standardization. By the time, SINPE(c) lacked statistical tests obtained by automatic analysis. Add to SINPE(c) features for automatic realization of the main statistical methods used in medicine . The study was divided into four topics: check the interest of users towards the implementation of the tests; search the frequency of their use in health care; carry out the implementation; and validate the results with researchers and their protocols. It was applied in a group of users of this software in their thesis in the strict sensu master and doctorate degrees in one postgraduate program in surgery. To assess the reliability of the statistics was compared the data obtained both automatically by SINPE(c) as manually held by a professional in statistics with experience with this type of study. There was concern for the use of automatic statistical tests, with good acceptance. The chi-square, Mann-Whitney, Fisher and t-Student were considered as tests frequently used by participants in medical studies. These methods have been implemented and thereafter approved as expected. The incorporation of the automatic SINPE (c) Statistical Analysis was shown to be reliable and equal to the manually done, validating its use as a research tool for medical research.

swot: Super W Of Theta

NASA Astrophysics Data System (ADS)

Coupon, Jean; Leauthaud, Alexie; Kilbinger, Martin; Medezinski, Elinor

2017-07-01

SWOT (Super W Of Theta) computes two-point statistics for very large data sets, based on “divide and conquer” algorithms, mainly, but not limited to data storage in binary trees, approximation at large scale, parellelization (open MPI), and bootstrap and jackknife resampling methods “on the fly”. It currently supports projected and 3D galaxy auto and cross correlations, galaxy-galaxy lensing, and weighted histograms.

The Determinants of Academic Performance of under Graduate Students: In the Case of Arba Minch University Chamo Campus

ERIC Educational Resources Information Center

Yigermal, Moges Endalamaw

2017-01-01

The main objective of the paper is to investigate the determinant factors affecting the academic performance of regular undergraduate students of Arba Minch university (AMU) chamo campus students. To meet the objective, the Pearson product moment correlation statistical tool and econometrics data analysis (OLS regression) method were used with the…

Water quality and non-point sources of risk: the Jiulong River Watershed, P. R. of China.

PubMed

Zhang, Jingjing; Zhang, Luoping; Ricci, Paolo F

2012-01-01

Retrospective water quality assessment plays an essential role in identifying trends and causal associations between exposures and risks, thus it can be a guide for water resources management. We have developed empirical relationships between several time-varying social and economic factors of economic development, water quality variables such as nitrate-nitrogen, COD(Mn), BOD(5), and DO, in the Jiulong River Watershed and its main tributary, the West River. Our analyses used alternative statistical methods to reduce the dimensionality of the analysis first and then strengthen the study's causal associations. The statistical methods included: factor analysis (FA), trend analysis, Monte Carlo/bootstrap simulations, robust regressions and a coupled equations model, integrated into a framework that allows an investigation and resolution of the issues that may affect the estimated results. After resolving these, we found that the concentrations of nitrogen compounds increased over time in the West River region, and that fertilizer used in agricultural fruit crops was the main risk with regard to nitrogen pollution. The relationships we developed can identify hazards and explain the impact of sources of different types of pollution, such as urbanization, and agriculture.

A factor analysis of the SSQ (Speech, Spatial, and Qualities of Hearing Scale).

PubMed

Akeroyd, Michael A; Guy, Fiona H; Harrison, Dawn L; Suller, Sharon L

2014-02-01

The speech, spatial, and qualities of hearing questionnaire (SSQ) is a self-report test of auditory disability. The 49 items ask how well a listener would do in many complex listening situations illustrative of real life. The scores on the items are often combined into the three main sections or into 10 pragmatic subscales. We report here a factor analysis of the SSQ that we conducted to further investigate its statistical properties and to determine its structure. Statistical factor analysis of questionnaire data, using parallel analysis to determine the number of factors to retain, oblique rotation of factors, and a bootstrap method to estimate the confidence intervals. 1220 people who have attended MRC IHR over the last decade. We found three clear factors, essentially corresponding to the three main sections of the SSQ. They are termed "speech understanding", "spatial perception", and "clarity, separation, and identification". Thirty-five of the SSQ questions were included in the three factors. There was partial evidence for a fourth factor, "effort and concentration", representing two more questions. These results aid in the interpretation and application of the SSQ and indicate potential methods for generating average scores.

Utility of computed tomography in assessment of pulmonary hypertension secondary to biomass smoke exposure

PubMed Central

Sertogullarindan, Bunyamin; Bora, Aydin; Yavuz, Alpaslan; Ekin, Selami; Gunbatar, Hulya; Arisoy, Ahmet; Avcu, Serhat; Ozbay, Bulent

2014-01-01

Background The aim of this study was to investigate the feasibility of main pulmonary artery diameter quantification by thoracic computerized tomography (CT) in the diagnosis of pulmonary hypertension seconder to biomass smoke exposure. Material/Methods One hundred and four women subjects with biomass smoke exposure and 20 healthy women subjects were enrolled in the prospective study. The correlation between echocardiographic estimation of systolic pulmonary artery pressure and the main pulmonary artery diameter of the cases were studied. Results The main pulmonary artery diameter was 26.9±5.1 in the control subjects and 37.1±6.4 in subjects with biomass smoke exposure. This difference was statistically significant (p<0.001). The systolic pulmonary artery pressure was 22.7±12.4 in the control subjects and 57.3±22 in subjects with biomass smoke exposure. This difference was statistically significant (p<0.001). Systolic pulmonary artery pressure was significantly correlated with the main pulmonary artery diameter (r=0.614, p<0.01). A receiver operating characteristic (ROC) curve analysis showed that a value of 29 mm of the main pulmonary artery diameter differentiated between pulmonary hypertension and non-pulmonary hypertension patients. The sensitivity of the measurement to diagnose pulmonary hypertension was 91% and specificity was 80%. Conclusions Our results indicate that main pulmonary artery diameter measurements by SCT may suggest presence of pulmonary hypertension in biomass smoke exposed women. PMID:24618994

A novel approach to simulate gene-environment interactions in complex diseases.

PubMed

Amato, Roberto; Pinelli, Michele; D'Andrea, Daniel; Miele, Gennaro; Nicodemi, Mario; Raiconi, Giancarlo; Cocozza, Sergio

2010-01-05

Complex diseases are multifactorial traits caused by both genetic and environmental factors. They represent the major part of human diseases and include those with largest prevalence and mortality (cancer, heart disease, obesity, etc.). Despite a large amount of information that has been collected about both genetic and environmental risk factors, there are few examples of studies on their interactions in epidemiological literature. One reason can be the incomplete knowledge of the power of statistical methods designed to search for risk factors and their interactions in these data sets. An improvement in this direction would lead to a better understanding and description of gene-environment interactions. To this aim, a possible strategy is to challenge the different statistical methods against data sets where the underlying phenomenon is completely known and fully controllable, for example simulated ones. We present a mathematical approach that models gene-environment interactions. By this method it is possible to generate simulated populations having gene-environment interactions of any form, involving any number of genetic and environmental factors and also allowing non-linear interactions as epistasis. In particular, we implemented a simple version of this model in a Gene-Environment iNteraction Simulator (GENS), a tool designed to simulate case-control data sets where a one gene-one environment interaction influences the disease risk. The main aim has been to allow the input of population characteristics by using standard epidemiological measures and to implement constraints to make the simulator behaviour biologically meaningful. By the multi-logistic model implemented in GENS it is possible to simulate case-control samples of complex disease where gene-environment interactions influence the disease risk. The user has full control of the main characteristics of the simulated population and a Monte Carlo process allows random variability. A knowledge-based approach reduces the complexity of the mathematical model by using reasonable biological constraints and makes the simulation more understandable in biological terms. Simulated data sets can be used for the assessment of novel statistical methods or for the evaluation of the statistical power when designing a study.

Estimating the Proportion of True Null Hypotheses Using the Pattern of Observed p-values

PubMed Central

Tong, Tiejun; Feng, Zeny; Hilton, Julia S.; Zhao, Hongyu

2013-01-01

Estimating the proportion of true null hypotheses, π0, has attracted much attention in the recent statistical literature. Besides its apparent relevance for a set of specific scientific hypotheses, an accurate estimate of this parameter is key for many multiple testing procedures. Most existing methods for estimating π0 in the literature are motivated from the independence assumption of test statistics, which is often not true in reality. Simulations indicate that most existing estimators in the presence of the dependence among test statistics can be poor, mainly due to the increase of variation in these estimators. In this paper, we propose several data-driven methods for estimating π0 by incorporating the distribution pattern of the observed p-values as a practical approach to address potential dependence among test statistics. Specifically, we use a linear fit to give a data-driven estimate for the proportion of true-null p-values in (λ, 1] over the whole range [0, 1] instead of using the expected proportion at 1 − λ. We find that the proposed estimators may substantially decrease the variance of the estimated true null proportion and thus improve the overall performance. PMID:24078762

Estimating the Proportion of True Null Hypotheses Using the Pattern of Observed p-values.

PubMed

Tong, Tiejun; Feng, Zeny; Hilton, Julia S; Zhao, Hongyu

2013-01-01

Estimating the proportion of true null hypotheses, π 0 , has attracted much attention in the recent statistical literature. Besides its apparent relevance for a set of specific scientific hypotheses, an accurate estimate of this parameter is key for many multiple testing procedures. Most existing methods for estimating π 0 in the literature are motivated from the independence assumption of test statistics, which is often not true in reality. Simulations indicate that most existing estimators in the presence of the dependence among test statistics can be poor, mainly due to the increase of variation in these estimators. In this paper, we propose several data-driven methods for estimating π 0 by incorporating the distribution pattern of the observed p -values as a practical approach to address potential dependence among test statistics. Specifically, we use a linear fit to give a data-driven estimate for the proportion of true-null p -values in (λ, 1] over the whole range [0, 1] instead of using the expected proportion at 1 - λ. We find that the proposed estimators may substantially decrease the variance of the estimated true null proportion and thus improve the overall performance.

Valid Statistical Analysis for Logistic Regression with Multiple Sources

NASA Astrophysics Data System (ADS)

Fienberg, Stephen E.; Nardi, Yuval; Slavković, Aleksandra B.

Considerable effort has gone into understanding issues of privacy protection of individual information in single databases, and various solutions have been proposed depending on the nature of the data, the ways in which the database will be used and the precise nature of the privacy protection being offered. Once data are merged across sources, however, the nature of the problem becomes far more complex and a number of privacy issues arise for the linked individual files that go well beyond those that are considered with regard to the data within individual sources. In the paper, we propose an approach that gives full statistical analysis on the combined database without actually combining it. We focus mainly on logistic regression, but the method and tools described may be applied essentially to other statistical models as well.

Beyond the floor effect on the WISC-IV in individuals with Down syndrome: are there cognitive strengths and weaknesses?

PubMed

Pezzuti, L; Nacinovich, R; Oggiano, S; Bomba, M; Ferri, R; La Stella, A; Rossetti, S; Orsini, A

2018-07-01

Individuals with Down syndrome generally show a floor effect on Wechsler Scales that is manifested by flat profiles and with many or all of the weighted scores on the subtests equal to 1. The main aim of the present paper is to use the statistical Hessl method and the extended statistical method of Orsini, Pezzuti and Hulbert with a sample of individuals with Down syndrome (n = 128; 72 boys and 56 girls), to underline the variability of performance on Wechsler Intelligence Scale for Children-Fourth Edition subtests and indices, highlighting any strengths and weaknesses of this population that otherwise appear to be flattened. Based on results using traditional transformation of raw scores into weighted scores, a very high percentage of subtests with weighted score of 1 occurred in the Down syndrome sample, with a floor effect and without any statistically significant difference between four core Wechsler Intelligence Scale for Children-Fourth Edition indices. The results, using traditional transformation, confirm a deep cognitive impairment of those with Down syndrome. Conversely, using the new statistical method, it is immediately apparent that the variability of the scores, both on subtests and indices, is wider with respect to the traditional method. Children with Down syndrome show a greater ability in the Verbal Comprehension Index than in the Working Memory Index. © 2018 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

[Diversity and frequency of scientific research design and statistical methods in the "Arquivos Brasileiros de Oftalmologia": a systematic review of the "Arquivos Brasileiros de Oftalmologia"--1993-2002].

PubMed

Crosta, Fernando; Nishiwaki-Dantas, Maria Cristina; Silvino, Wilmar; Dantas, Paulo Elias Correa

2005-01-01

To verify the frequency of study design, applied statistical analysis and approval by institutional review offices (Ethics Committee) of articles published in the "Arquivos Brasileiros de Oftalmologia" during a 10-year interval, with later comparative and critical analysis by some of the main international journals in the field of Ophthalmology. Systematic review without metanalysis was performed. Scientific papers published in the "Arquivos Brasileiros de Oftalmologia" between January 1993 and December 2002 were reviewed by two independent reviewers and classified according to the applied study design, statistical analysis and approval by the institutional review offices. To categorize those variables, a descriptive statistical analysis was used. After applying inclusion and exclusion criteria, 584 articles for evaluation of statistical analysis and, 725 articles for evaluation of study design were reviewed. Contingency table (23.10%) was the most frequently applied statistical method, followed by non-parametric tests (18.19%), Student's t test (12.65%), central tendency measures (10.60%) and analysis of variance (9.81%). Of 584 reviewed articles, 291 (49.82%) presented no statistical analysis. Observational case series (26.48%) was the most frequently used type of study design, followed by interventional case series (18.48%), observational case description (13.37%), non-random clinical study (8.96%) and experimental study (8.55%). We found a higher frequency of observational clinical studies, lack of statistical analysis in almost half of the published papers. Increase in studies with approval by institutional review Ethics Committee was noted since it became mandatory in 1996.

A Matlab user interface for the statistically assisted fluid registration algorithm and tensor-based morphometry

NASA Astrophysics Data System (ADS)

Yepes-Calderon, Fernando; Brun, Caroline; Sant, Nishita; Thompson, Paul; Lepore, Natasha

2015-01-01

Tensor-Based Morphometry (TBM) is an increasingly popular method for group analysis of brain MRI data. The main steps in the analysis consist of a nonlinear registration to align each individual scan to a common space, and a subsequent statistical analysis to determine morphometric differences, or difference in fiber structure between groups. Recently, we implemented the Statistically-Assisted Fluid Registration Algorithm or SAFIRA,1 which is designed for tracking morphometric differences among populations. To this end, SAFIRA allows the inclusion of statistical priors extracted from the populations being studied as regularizers in the registration. This flexibility and degree of sophistication limit the tool to expert use, even more so considering that SAFIRA was initially implemented in command line mode. Here, we introduce a new, intuitive, easy to use, Matlab-based graphical user interface for SAFIRA's multivariate TBM. The interface also generates different choices for the TBM statistics, including both the traditional univariate statistics on the Jacobian matrix, and comparison of the full deformation tensors.2 This software will be freely disseminated to the neuroimaging research community.

Simultaneous assessment of phase chemistry, phase abundance and bulk chemistry with statistical electron probe micro-analyses: Application to cement clinkers

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

Wilson, William; Krakowiak, Konrad J.; Ulm, Franz-Josef, E-mail: ulm@mit.edu

2014-01-15

According to recent developments in cement clinker engineering, the optimization of chemical substitutions in the main clinker phases offers a promising approach to improve both reactivity and grindability of clinkers. Thus, monitoring the chemistry of the phases may become part of the quality control at the cement plants, along with the usual measurements of the abundance of the mineralogical phases (quantitative X-ray diffraction) and the bulk chemistry (X-ray fluorescence). This paper presents a new method to assess these three complementary quantities with a single experiment. The method is based on electron microprobe spot analyses, performed over a grid located onmore » a representative surface of the sample and interpreted with advanced statistical tools. This paper describes the method and the experimental program performed on industrial clinkers to establish the accuracy in comparison to conventional methods. -- Highlights: •A new method of clinker characterization •Combination of electron probe technique with cluster analysis •Simultaneous assessment of phase abundance, composition and bulk chemistry •Experimental validation performed on industrial clinkers.« less

VALUE - A Framework to Validate Downscaling Approaches for Climate Change Studies

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Widmann, Martin; Gutiérrez, José M.; Kotlarski, Sven; Chandler, Richard E.; Hertig, Elke; Wibig, Joanna; Huth, Radan; Wilke, Renate A. I.

2015-04-01

VALUE is an open European network to validate and compare downscaling methods for climate change research. VALUE aims to foster collaboration and knowledge exchange between climatologists, impact modellers, statisticians, and stakeholders to establish an interdisciplinary downscaling community. A key deliverable of VALUE is the development of a systematic validation framework to enable the assessment and comparison of both dynamical and statistical downscaling methods. Here, we present the key ingredients of this framework. VALUE's main approach to validation is user-focused: starting from a specific user problem, a validation tree guides the selection of relevant validation indices and performance measures. Several experiments have been designed to isolate specific points in the downscaling procedure where problems may occur: what is the isolated downscaling skill? How do statistical and dynamical methods compare? How do methods perform at different spatial scales? Do methods fail in representing regional climate change? How is the overall representation of regional climate, including errors inherited from global climate models? The framework will be the basis for a comprehensive community-open downscaling intercomparison study, but is intended also to provide general guidance for other validation studies.

VALUE: A framework to validate downscaling approaches for climate change studies

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Widmann, Martin; Gutiérrez, José M.; Kotlarski, Sven; Chandler, Richard E.; Hertig, Elke; Wibig, Joanna; Huth, Radan; Wilcke, Renate A. I.

2015-01-01

VALUE is an open European network to validate and compare downscaling methods for climate change research. VALUE aims to foster collaboration and knowledge exchange between climatologists, impact modellers, statisticians, and stakeholders to establish an interdisciplinary downscaling community. A key deliverable of VALUE is the development of a systematic validation framework to enable the assessment and comparison of both dynamical and statistical downscaling methods. In this paper, we present the key ingredients of this framework. VALUE's main approach to validation is user- focused: starting from a specific user problem, a validation tree guides the selection of relevant validation indices and performance measures. Several experiments have been designed to isolate specific points in the downscaling procedure where problems may occur: what is the isolated downscaling skill? How do statistical and dynamical methods compare? How do methods perform at different spatial scales? Do methods fail in representing regional climate change? How is the overall representation of regional climate, including errors inherited from global climate models? The framework will be the basis for a comprehensive community-open downscaling intercomparison study, but is intended also to provide general guidance for other validation studies.

System of Indicators in the Innovation Management: Business Intelligence Applied to Tourism

NASA Astrophysics Data System (ADS)

Lozada, Dayana; Araque, Francisco; Castillo, Jose Manuel; Salguero, Alberto; Delgado, Cecilia; Noda, Marcia; Hernández, Gilberto

The work presents an approach to study mechanisms that allows managers the Innovation Management (IM) measurements. It is assumed, as main motivation, the analysis of patterns for the design of an integral system of indicators. A methodology that integrates the thought process, focusing on the Business Intelligence and the Balance Scorecard will be presented. A group of indexes based on the multidimensionality of IM in organizations of the sector of tourism is proposed. To approach this quality it is necessary to contextualize, in the conditions of sectoral operation, the theories, models and systems used in our approach. It has been used intervention methods like experts' criteria, consensus search techniques by means of surveys, consultation of documents, and statistical methods such as analysis of the main components.

Data Model Performance in Data Warehousing

NASA Astrophysics Data System (ADS)

Rorimpandey, G. C.; Sangkop, F. I.; Rantung, V. P.; Zwart, J. P.; Liando, O. E. S.; Mewengkang, A.

2018-02-01

Data Warehouses have increasingly become important in organizations that have large amount of data. It is not a product but a part of a solution for the decision support system in those organizations. Data model is the starting point for designing and developing of data warehouses architectures. Thus, the data model needs stable interfaces and consistent for a longer period of time. The aim of this research is to know which data model in data warehousing has the best performance. The research method is descriptive analysis, which has 3 main tasks, such as data collection and organization, analysis of data and interpretation of data. The result of this research is discussed in a statistic analysis method, represents that there is no statistical difference among data models used in data warehousing. The organization can utilize four data model proposed when designing and developing data warehouse.

Basic biostatistics for post-graduate students

PubMed Central

Dakhale, Ganesh N.; Hiware, Sachin K.; Shinde, Abhijit T.; Mahatme, Mohini S.

2012-01-01

Statistical methods are important to draw valid conclusions from the obtained data. This article provides background information related to fundamental methods and techniques in biostatistics for the use of postgraduate students. Main focus is given to types of data, measurement of central variations and basic tests, which are useful for analysis of different types of observations. Few parameters like normal distribution, calculation of sample size, level of significance, null hypothesis, indices of variability, and different test are explained in detail by giving suitable examples. Using these guidelines, we are confident enough that postgraduate students will be able to classify distribution of data along with application of proper test. Information is also given regarding various free software programs and websites useful for calculations of statistics. Thus, postgraduate students will be benefitted in both ways whether they opt for academics or for industry. PMID:23087501

Computerized system for assessing heart rate variability.

PubMed

Frigy, A; Incze, A; Brânzaniuc, E; Cotoi, S

1996-01-01

The principal theoretical, methodological and clinical aspects of heart rate variability (HRV) analysis are reviewed. This method has been developed over the last 10 years as a useful noninvasive method of measuring the activity of the autonomic nervous system. The main components and the functioning of the computerized rhythm-analyzer system developed by our team are presented. The system is able to perform short-term (maximum 20 minutes) time domain HRV analysis and statistical analysis of the ventricular rate in any rhythm, particularly in atrial fibrillation. The performances of our system are demonstrated by using the graphics (RR histograms, delta RR histograms, RR scattergrams) and the statistical parameters resulted from the processing of three ECG recordings. These recordings are obtained from a normal subject, from a patient with advanced heart failure, and from a patient with atrial fibrillation.

Cycling transport safety quantification

NASA Astrophysics Data System (ADS)

Drbohlav, Jiri; Kocourek, Josef

2018-05-01

Dynamic interest in cycling transport brings the necessity to design safety cycling infrastructure. In las few years, couple of norms with safety elements have been designed and suggested for the cycling infrastructure. But these were not fully examined. The main parameter of suitable and fully functional transport infrastructure is the evaluation of its safety. Common evaluation of transport infrastructure safety is based on accident statistics. These statistics are suitable for motor vehicle transport but unsuitable for the cycling transport. Cycling infrastructure evaluation of safety is suitable for the traffic conflicts monitoring. The results of this method are fast, based on real traffic situations and can be applied on any traffic situations.

Effect of different mixing methods on the bacterial microleakage of calcium-enriched mixture cement.

PubMed

Shahi, Shahriar; Jeddi Khajeh, Soniya; Rahimi, Saeed; Yavari, Hamid R; Jafari, Farnaz; Samiei, Mohammad; Ghasemi, Negin; Milani, Amin S

2016-10-01

Calcium-enriched mixture (CEM) cement is used in the field of endodontics. It is similar to mineral trioxide aggregate in its main ingredients. The present study investigated the effect of different mixing methods on the bacterial microleakage of CEM cement. A total of 55 human single-rooted human permanent teeth were decoronated so that 14-mm-long samples were obtained and obturated with AH26 sealer and gutta-percha using lateral condensation technique. Three millimeters of the root end were cut off and randomly divided into 3 groups of 15 each (3 mixing methods of amalgamator, ultrasonic and conventional) and 2 negative and positive control groups (each containing 5 samples). BHI (brain-heart infusion agar) suspension containing Enterococcus faecalis was used for bacterial leakage assessment. Statistical analysis was carried out using descriptive statistics, Kaplan-Meier survival analysis with censored data and log rank test. Statistical significance was set at P<0.05. The survival means for conventional, amalgamator and ultrasonic methods were 62.13±12.44, 68.87±12.79 and 77.53±12.52 days, respectively. The log rank test showed no significant differences between the groups. Based on the results of the present study it can be concluded that different mixing methods had no significant effect on the bacterial microleakage of CEM cement.

The effect of repeated firings on the color change of dental ceramics using different glazing methods

PubMed Central

Yılmaz, Kerem; Ozturk, Caner

2014-01-01

PURPOSE Surface color is one of the main criteria to obtain an ideal esthetic. Many factors such as the type of the material, surface specifications, number of firings, firing temperature and thickness of the porcelain are all important to provide an unchanged surface color in dental ceramics. The aim of this study was to evaluate the color changes in dental ceramics according to the material type and glazing methods, during the multiple firings. MATERIALS AND METHODS Three different types of dental ceramics (IPS Classical metal ceramic, Empress Esthetic and Empress 2 ceramics) were used in the study. Porcelains were evaluated under five main groups according to glaze and natural glaze methods. Color changes (ΔE) and changes in color parameters (ΔL, Δa, Δb) were determined using colorimeter during the control, the first, third, fifth, and seventh firings. The statistical analysis of the results was performed using ANOVA and Tukey test. RESULTS The color changes which occurred upon material-method-firing interaction were statistically significant (P<.05). ΔE, ΔL, Δa and Δb values also demonstrated a negative trend. The MC-G group was less affected in terms of color changes compared to other groups. In all-ceramic specimens, the surface color was significantly affected by multiple firings. CONCLUSION Firing detrimentally affected the structure of the porcelain surface and hence caused fading of the color and prominence of yellow and red characters. Compressible all-ceramics were remarkably affected by repeated firings due to their crystalline structure. PMID:25551001

Individual Fit Testing of Hearing Protection Devices Based on Microphone in Real Ear.

PubMed

Biabani, Azam; Aliabadi, Mohsen; Golmohammadi, Rostam; Farhadian, Maryam

2017-12-01

Labeled noise reduction (NR) data presented by manufacturers are considered one of the main challenging issues for occupational experts in employing hearing protection devices (HPDs). This study aimed to determine the actual NR data of typical HPDs using the objective fit testing method with a microphone in real ear (MIRE) method. Five available commercially earmuff protectors were investigated in 30 workers exposed to reference noise source according to the standard method, ISO 11904-1. Personal attenuation rating (PAR) of the earmuffs was measured based on the MIRE method using a noise dosimeter (SVANTEK, model SV 102). The results showed that means of PAR of the earmuffs are from 49% to 86% of the nominal NR rating. The PAR values of earmuffs when a typical eyewear was worn differed statistically ( p < 0.05). It is revealed that a typical safety eyewear can reduce the mean of the PAR value by approximately 2.5 dB. The results also showed that measurements based on the MIRE method resulted in low variability. The variability in NR values between individuals, within individuals, and within earmuffs was not the statistically significant ( p > 0.05). This study could provide local individual fit data. Ergonomic aspects of the earmuffs and different levels of users experience and awareness can be considered the main factors affecting individual fitting compared with the laboratory condition for acquiring the labeled NR data. Based on the obtained fit testing results, the field application of MIRE can be employed for complementary studies in real workstations while workers perform their regular work duties.

Large-scale online semantic indexing of biomedical articles via an ensemble of multi-label classification models.

PubMed

Papanikolaou, Yannis; Tsoumakas, Grigorios; Laliotis, Manos; Markantonatos, Nikos; Vlahavas, Ioannis

2017-09-22

In this paper we present the approach that we employed to deal with large scale multi-label semantic indexing of biomedical papers. This work was mainly implemented within the context of the BioASQ challenge (2013-2017), a challenge concerned with biomedical semantic indexing and question answering. Our main contribution is a MUlti-Label Ensemble method (MULE) that incorporates a McNemar statistical significance test in order to validate the combination of the constituent machine learning algorithms. Some secondary contributions include a study on the temporal aspects of the BioASQ corpus (observations apply also to the BioASQ's super-set, the PubMed articles collection) and the proper parametrization of the algorithms used to deal with this challenging classification task. The ensemble method that we developed is compared to other approaches in experimental scenarios with subsets of the BioASQ corpus giving positive results. In our participation in the BioASQ challenge we obtained the first place in 2013 and the second place in the four following years, steadily outperforming MTI, the indexing system of the National Library of Medicine (NLM). The results of our experimental comparisons, suggest that employing a statistical significance test to validate the ensemble method's choices, is the optimal approach for ensembling multi-label classifiers, especially in contexts with many rare labels.

Field-effect transistors (2nd revised and enlarged edition)

NASA Astrophysics Data System (ADS)

Bocharov, L. N.

The design, principle of operation, and principal technical characteristics of field-effect transistors produced in the USSR are described. Problems related to the use of field-effect transistors in various radioelectronic devices are examined, and tables of parameters and mean statistical characteristics are presented for the main types of field-effect transistors. Methods for calculating various circuit components are discussed and illustrated by numerical examples.

Partial discharge detection and analysis in low pressure environments

NASA Astrophysics Data System (ADS)

Liu, Xin

Typical aerospace vehicles (aircraft and spacecraft) experience a wide range of operating pressures during ascending and returning to earth. Compared to the sea-level atmospheric pressure (760 Torr), the pressure at about 60 km altitude is 2 Torr. The performance of the electric power system components of the aerospace vehicles must remain reliable even under such sub-atmospheric operating conditions. It is well known that the dielectric strength of gaseous insulators, while the electrode arrangement remains unchanged, is pressure dependent. Therefore, characterization of the performance and behavior of the electrical insulation in flight vehicles in low-pressure environments is extremely important. Partial discharge testing is one of the practical methods for evaluating the integrity of electrical insulation in aerospace vehicles. This dissertation describes partial discharge (PD) measurements performed mainly with 60 Hz ac energization in air, argon and helium, for pressures between 2 and 760 Torr. Two main electrode arrangements were used. One was a needle-plane electrode arrangement with a Teflon insulating barrier. The other one was a twisted pair of insulated conductors taken from a standard aircraft wiring harness. The measurement results are presented in terms of typical PD current pulse waveforms and waveform analysis for both main electrode arrangements. The evaluation criteria are the waveform polarity, magnitude, shape, rise time, and phase angle (temporal location) relative to the source voltage. Two-variable histograms and statistical averages of the PD parameters are presented. The PD physical mechanisms are analyzed. For PD pattern recognition, both statistical methods (such as discharge parameter dot pattern representation, discharge parameter phase distribution, statistical operator calculations, and PD fingerprint development) and wavelet transform applications are investigated. The main conclusions of the dissertation include: (1) The PD current pulse waveforms are dependent on the pressure. (2) The rise time of the waveform is another effective PD current pulse characteristic indicator. (3) PD fingerprint patterns that are already available for atmospheric pressure (760 Torr) conditions are inadequate for the evaluation of PD pulses at low pressures. (4) Various wavelet transform techniques can be used effectively for PD pulse signal denoising purposes, and for PD pulse waveform transient feature recognition.

Application of the experimental design of experiments (DoE) for the determination of organotin compounds in water samples using HS-SPME and GC-MS/MS.

PubMed

Coscollà, Clara; Navarro-Olivares, Santiago; Martí, Pedro; Yusà, Vicent

2014-02-01

When attempting to discover the important factors and then optimise a response by tuning these factors, experimental design (design of experiments, DoE) gives a powerful suite of statistical methodology. DoE identify significant factors and then optimise a response with respect to them in method development. In this work, a headspace-solid-phase micro-extraction (HS-SPME) combined with gas chromatography tandem mass spectrometry (GC-MS/MS) methodology for the simultaneous determination of six important organotin compounds namely monobutyltin (MBT), dibutyltin (DBT), tributyltin (TBT), monophenyltin (MPhT), diphenyltin (DPhT), triphenyltin (TPhT) has been optimized using a statistical design of experiments (DOE). The analytical method is based on the ethylation with NaBEt4 and simultaneous headspace-solid-phase micro-extraction of the derivative compounds followed by GC-MS/MS analysis. The main experimental parameters influencing the extraction efficiency selected for optimization were pre-incubation time, incubation temperature, agitator speed, extraction time, desorption temperature, buffer (pH, concentration and volume), headspace volume, sample salinity, preparation of standards, ultrasonic time and desorption time in the injector. The main factors (excitation voltage, excitation time, ion source temperature, isolation time and electron energy) affecting the GC-IT-MS/MS response were also optimized using the same statistical design of experiments. The proposed method presented good linearity (coefficient of determination R(2)>0.99) and repeatibilty (1-25%) for all the compounds under study. The accuracy of the method measured as the average percentage recovery of the compounds in spiked surface and marine waters was higher than 70% for all compounds studied. Finally, the optimized methodology was applied to real aqueous samples enabled the simultaneous determination of all compounds under study in surface and marine water samples obtained from Valencia region (Spain). © 2013 Elsevier B.V. All rights reserved.

Statistical complexity measure of pseudorandom bit generators

NASA Astrophysics Data System (ADS)

González, C. M.; Larrondo, H. A.; Rosso, O. A.

2005-08-01

Pseudorandom number generators (PRNG) are extensively used in Monte Carlo simulations, gambling machines and cryptography as substitutes of ideal random number generators (RNG). Each application imposes different statistical requirements to PRNGs. As L’Ecuyer clearly states “the main goal for Monte Carlo methods is to reproduce the statistical properties on which these methods are based whereas for gambling machines and cryptology, observing the sequence of output values for some time should provide no practical advantage for predicting the forthcoming numbers better than by just guessing at random”. In accordance with different applications several statistical test suites have been developed to analyze the sequences generated by PRNGs. In a recent paper a new statistical complexity measure [Phys. Lett. A 311 (2003) 126] has been defined. Here we propose this measure, as a randomness quantifier of a PRNGs. The test is applied to three very well known and widely tested PRNGs available in the literature. All of them are based on mathematical algorithms. Another PRNGs based on Lorenz 3D chaotic dynamical system is also analyzed. PRNGs based on chaos may be considered as a model for physical noise sources and important new results are recently reported. All the design steps of this PRNG are described, and each stage increase the PRNG randomness using different strategies. It is shown that the MPR statistical complexity measure is capable to quantify this randomness improvement. The PRNG based on the chaotic 3D Lorenz dynamical system is also evaluated using traditional digital signal processing tools for comparison.

Adaptive multiple super fast simulated annealing for stochastic microstructure reconstruction

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

Ryu, Seun; Lin, Guang; Sun, Xin

2013-01-01

Fast image reconstruction from statistical information is critical in image fusion from multimodality chemical imaging instrumentation to create high resolution image with large domain. Stochastic methods have been used widely in image reconstruction from two point correlation function. The main challenge is to increase the efficiency of reconstruction. A novel simulated annealing method is proposed for fast solution of image reconstruction. Combining the advantage of very fast cooling schedules, dynamic adaption and parallelization, the new simulation annealing algorithm increases the efficiencies by several orders of magnitude, making the large domain image fusion feasible.

Metrically adjusted questionnaires can provide more information for scientists- an example from the tourism.

PubMed

Sindik, Joško; Miljanović, Maja

2017-03-01

The article deals with the issue of research methodology, illustrating the use of known research methods for new purposes. Questionnaires that originally do not have metric characteristics can be called »handy questionnaires«. In this article, the author is trying to consider the possibilities of their improved scientific usability, which can be primarily ensured by improving their metric characteristics, consequently using multivariate instead of univariate statistical methods. In order to establish the base for the application of multivariate statistical procedures, the main idea is to develop strategies to design measurement instruments from parts of the handy questionnaires. This can be accomplished in two ways: before deciding upon the methods for data collection (redesigning the handy questionnaires) and before the collection of the data (a priori) or after the data has been collected, without modifying the questionnaire (a posteriori). The basic principles of applying these two strategies of the metrical adaptation of handy questionnaires are described.

Testing Nelder-Mead based repulsion algorithms for multiple roots of nonlinear systems via a two-level factorial design of experiments.

PubMed

Ramadas, Gisela C V; Rocha, Ana Maria A C; Fernandes, Edite M G P

2015-01-01

This paper addresses the challenging task of computing multiple roots of a system of nonlinear equations. A repulsion algorithm that invokes the Nelder-Mead (N-M) local search method and uses a penalty-type merit function based on the error function, known as 'erf', is presented. In the N-M algorithm context, different strategies are proposed to enhance the quality of the solutions and improve the overall efficiency. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm.

A Low-Cost Method for Multiple Disease Prediction.

PubMed

Bayati, Mohsen; Bhaskar, Sonia; Montanari, Andrea

Recently, in response to the rising costs of healthcare services, employers that are financially responsible for the healthcare costs of their workforce have been investing in health improvement programs for their employees. A main objective of these so called "wellness programs" is to reduce the incidence of chronic illnesses such as cardiovascular disease, cancer, diabetes, and obesity, with the goal of reducing future medical costs. The majority of these wellness programs include an annual screening to detect individuals with the highest risk of developing chronic disease. Once these individuals are identified, the company can invest in interventions to reduce the risk of those individuals. However, capturing many biomarkers per employee creates a costly screening procedure. We propose a statistical data-driven method to address this challenge by minimizing the number of biomarkers in the screening procedure while maximizing the predictive power over a broad spectrum of diseases. Our solution uses multi-task learning and group dimensionality reduction from machine learning and statistics. We provide empirical validation of the proposed solution using data from two different electronic medical records systems, with comparisons to a statistical benchmark.

A Current Application of the Methods of Secular and Statistical Parallax

NASA Astrophysics Data System (ADS)

Turner, D. G.

The methods of secular and statistical parallax for homogeneous groups of Galactic stars are applied in a practical (classroom) exercise to establish the luminosity of bright B3 V stars. The solar motion of 20 km s-1 relative to group stars exceeds their random velocities of ±10 km s-1, a condition adopted for preference of secular parallax to statistical parallax. The group parallax of πups = 5.81 ± 0.83 mas and derived luminosity MV = -0.98 ± 0.33 for B3 V stars from upsilon components of proper motion should be close to the true value. The weighted mean Hipparcos parallax of ±Hip = 5.75±0.27 mas for the same sample, and implied luminosity of MV = -1.00 ± 0.15, confirm the secular parallax solution. Both solutions are close to MV = -0.83 for ZAMS stars of the same type, implying that Malmquist bias in the selection of stars mainly accounts for the presence of unresolved binaries, slightly evolved objects, and rapidly rotating stars in the sample.

Probabilistic-driven oriented Speckle reducing anisotropic diffusion with application to cardiac ultrasonic images.

PubMed

Vegas-Sanchez-Ferrero, G; Aja-Fernandez, S; Martin-Fernandez, M; Frangi, A F; Palencia, C

2010-01-01

A novel anisotropic diffusion filter is proposed in this work with application to cardiac ultrasonic images. It includes probabilistic models which describe the probability density function (PDF) of tissues and adapts the diffusion tensor to the image iteratively. For this purpose, a preliminary study is performed in order to select the probability models that best fit the stastitical behavior of each tissue class in cardiac ultrasonic images. Then, the parameters of the diffusion tensor are defined taking into account the statistical properties of the image at each voxel. When the structure tensor of the probability of belonging to each tissue is included in the diffusion tensor definition, a better boundaries estimates can be obtained instead of calculating directly the boundaries from the image. This is the main contribution of this work. Additionally, the proposed method follows the statistical properties of the image in each iteration. This is considered as a second contribution since state-of-the-art methods suppose that noise or statistical properties of the image do not change during the filter process.

Continuum radiation from active galactic nuclei: A statistical study

NASA Technical Reports Server (NTRS)

Isobe, T.; Feigelson, E. D.; Singh, K. P.; Kembhavi, A.

1986-01-01

The physics of the continuum spectrum of active galactic nuclei (AGNs) was examined using a large data set and rigorous statistical methods. A data base was constructed for 469 objects which include radio selected quasars, optically selected quasars, X-ray selected AGNs, BL Lac objects, and optically unidentified compact radio sources. Each object has measurements of its radio, optical, X-ray core continuum luminosity, though many of them are upper limits. Since many radio sources have extended components, the core component were carefully selected out from the total radio luminosity. With survival analysis statistical methods, which can treat upper limits correctly, these data can yield better statistical results than those previously obtained. A variety of statistical tests are performed, such as the comparison of the luminosity functions in different subsamples, and linear regressions of luminosities in different bands. Interpretation of the results leads to the following tentative conclusions: the main emission mechanism of optically selected quasars and X-ray selected AGNs is thermal, while that of BL Lac objects is synchrotron; radio selected quasars may have two different emission mechanisms in the X-ray band; BL Lac objects appear to be special cases of the radio selected quasars; some compact radio sources show the possibility of synchrotron self-Compton (SSC) in the optical band; and the spectral index between the optical and the X-ray bands depends on the optical luminosity.

Forest wildlife habitat statistics for Maine - 1982

Treesearch

Robert T. Brooks; Thomas S. Frieswyk; Arthur Ritter

1986-01-01

A statistical report on the first forest wildlife habitat survey of Maine (1982). Eighty-five tables show estimates of forest area and several attributes of forest land wildlife habitat. Data are presented at two levels: state and geographic sampling unit.

Mapping of epistatic quantitative trait loci in four-way crosses.

PubMed

He, Xiao-Hong; Qin, Hongde; Hu, Zhongli; Zhang, Tianzhen; Zhang, Yuan-Ming

2011-01-01

Four-way crosses (4WC) involving four different inbred lines often appear in plant and animal commercial breeding programs. Direct mapping of quantitative trait loci (QTL) in these commercial populations is both economical and practical. However, the existing statistical methods for mapping QTL in a 4WC population are built on the single-QTL genetic model. This simple genetic model fails to take into account QTL interactions, which play an important role in the genetic architecture of complex traits. In this paper, therefore, we attempted to develop a statistical method to detect epistatic QTL in 4WC population. Conditional probabilities of QTL genotypes, computed by the multi-point single locus method, were used to sample the genotypes of all putative QTL in the entire genome. The sampled genotypes were used to construct the design matrix for QTL effects. All QTL effects, including main and epistatic effects, were simultaneously estimated by the penalized maximum likelihood method. The proposed method was confirmed by a series of Monte Carlo simulation studies and real data analysis of cotton. The new method will provide novel tools for the genetic dissection of complex traits, construction of QTL networks, and analysis of heterosis.

Combining statistical inference and decisions in ecology

USGS Publications Warehouse

Williams, Perry J.; Hooten, Mevin B.

2016-01-01

Statistical decision theory (SDT) is a sub-field of decision theory that formally incorporates statistical investigation into a decision-theoretic framework to account for uncertainties in a decision problem. SDT provides a unifying analysis of three types of information: statistical results from a data set, knowledge of the consequences of potential choices (i.e., loss), and prior beliefs about a system. SDT links the theoretical development of a large body of statistical methods including point estimation, hypothesis testing, and confidence interval estimation. The theory and application of SDT have mainly been developed and published in the fields of mathematics, statistics, operations research, and other decision sciences, but have had limited exposure in ecology. Thus, we provide an introduction to SDT for ecologists and describe its utility for linking the conventionally separate tasks of statistical investigation and decision making in a single framework. We describe the basic framework of both Bayesian and frequentist SDT, its traditional use in statistics, and discuss its application to decision problems that occur in ecology. We demonstrate SDT with two types of decisions: Bayesian point estimation, and an applied management problem of selecting a prescribed fire rotation for managing a grassland bird species. Central to SDT, and decision theory in general, are loss functions. Thus, we also provide basic guidance and references for constructing loss functions for an SDT problem.

Coloc-stats: a unified web interface to perform colocalization analysis of genomic features.

PubMed

Simovski, Boris; Kanduri, Chakravarthi; Gundersen, Sveinung; Titov, Dmytro; Domanska, Diana; Bock, Christoph; Bossini-Castillo, Lara; Chikina, Maria; Favorov, Alexander; Layer, Ryan M; Mironov, Andrey A; Quinlan, Aaron R; Sheffield, Nathan C; Trynka, Gosia; Sandve, Geir K

2018-06-05

Functional genomics assays produce sets of genomic regions as one of their main outputs. To biologically interpret such region-sets, researchers often use colocalization analysis, where the statistical significance of colocalization (overlap, spatial proximity) between two or more region-sets is tested. Existing colocalization analysis tools vary in the statistical methodology and analysis approaches, thus potentially providing different conclusions for the same research question. As the findings of colocalization analysis are often the basis for follow-up experiments, it is helpful to use several tools in parallel and to compare the results. We developed the Coloc-stats web service to facilitate such analyses. Coloc-stats provides a unified interface to perform colocalization analysis across various analytical methods and method-specific options (e.g. colocalization measures, resolution, null models). Coloc-stats helps the user to find a method that supports their experimental requirements and allows for a straightforward comparison across methods. Coloc-stats is implemented as a web server with a graphical user interface that assists users with configuring their colocalization analyses. Coloc-stats is freely available at https://hyperbrowser.uio.no/coloc-stats/.

Numerical solutions of the semiclassical Boltzmann ellipsoidal-statistical kinetic model equation

PubMed Central

Yang, Jaw-Yen; Yan, Chin-Yuan; Huang, Juan-Chen; Li, Zhihui

2014-01-01

Computations of rarefied gas dynamical flows governed by the semiclassical Boltzmann ellipsoidal-statistical (ES) kinetic model equation using an accurate numerical method are presented. The semiclassical ES model was derived through the maximum entropy principle and conserves not only the mass, momentum and energy, but also contains additional higher order moments that differ from the standard quantum distributions. A different decoding procedure to obtain the necessary parameters for determining the ES distribution is also devised. The numerical method in phase space combines the discrete-ordinate method in momentum space and the high-resolution shock capturing method in physical space. Numerical solutions of two-dimensional Riemann problems for two configurations covering various degrees of rarefaction are presented and various contours of the quantities unique to this new model are illustrated. When the relaxation time becomes very small, the main flow features a display similar to that of ideal quantum gas dynamics, and the present solutions are found to be consistent with existing calculations for classical gas. The effect of a parameter that permits an adjustable Prandtl number in the flow is also studied. PMID:25104904

Lung adenocarcinoma with intraoperatively diagnosed pleural seeding: Is main tumor resection beneficial for prognosis?

PubMed

Li, Chi; Kuo, Shuenn-Wen; Hsu, Hsao-Hsun; Lin, Mong-Wei; Chen, Jin-Shing

2018-03-01

To evaluate whether main tumor resection improves survival compared with pleural biopsy alone in patients with lung adenocarcinoma with intraoperatively diagnosed pleural seeding. Forty-three patients with lung adenocarcinoma with pleural seeding diagnosed unexpectedly during surgery performed between January 2006 and December 2014 were included in this retrospective study using a prospectively collected lung cancer database. Each surgeon decided whether to perform main tumor resection or pleural biopsy alone. Main tumor and visible pleural nodule resection was performed in 30 patients (tumor resection group). The remaining 13 patients underwent pleural nodule biopsy alone (open-close group). The clinical T stage was higher in the open-close group than in the tumor resection group (P = .02). The tumor resection group had longer operative times compared with the open-close group (mean, 141.8 vs 80.3 minutes). There were no other statistically significant differences in perioperative parameters. The surgical method was the sole statistically significant prognostic factor. Patients in the tumor resection group had better progression-free survival (3-year survival: 44.5% vs 0%; P = .009) and overall survival (3-year survival: 82.9% vs 38.5%; P = .013) than did the open-close group. There was no significant survival difference between sublobar resection and lobectomy for the main tumor resection. Our study demonstrated improved progression-free and overall survival after main tumor and visible pleural nodule resection in patients with lung adenocarcinoma with intraoperatively diagnosed pleural seeding. Further randomized trials are needed to define the role of main tumor resection in these patients. Copyright © 2017 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Asymptotic modal analysis and statistical energy analysis

NASA Technical Reports Server (NTRS)

Dowell, Earl H.

1992-01-01

Asymptotic Modal Analysis (AMA) is a method which is used to model linear dynamical systems with many participating modes. The AMA method was originally developed to show the relationship between statistical energy analysis (SEA) and classical modal analysis (CMA). In the limit of a large number of modes of a vibrating system, the classical modal analysis result can be shown to be equivalent to the statistical energy analysis result. As the CMA result evolves into the SEA result, a number of systematic assumptions are made. Most of these assumptions are based upon the supposition that the number of modes approaches infinity. It is for this reason that the term 'asymptotic' is used. AMA is the asymptotic result of taking the limit of CMA as the number of modes approaches infinity. AMA refers to any of the intermediate results between CMA and SEA, as well as the SEA result which is derived from CMA. The main advantage of the AMA method is that individual modal characteristics are not required in the model or computations. By contrast, CMA requires that each modal parameter be evaluated at each frequency. In the latter, contributions from each mode are computed and the final answer is obtained by summing over all the modes in the particular band of interest. AMA evaluates modal parameters only at their center frequency and does not sum the individual contributions from each mode in order to obtain a final result. The method is similar to SEA in this respect. However, SEA is only capable of obtaining spatial averages or means, as it is a statistical method. Since AMA is systematically derived from CMA, it can obtain local spatial information as well.

Control chart pattern recognition using RBF neural network with new training algorithm and practical features.

PubMed

Addeh, Abdoljalil; Khormali, Aminollah; Golilarz, Noorbakhsh Amiri

2018-05-04

The control chart patterns are the most commonly used statistical process control (SPC) tools to monitor process changes. When a control chart produces an out-of-control signal, this means that the process has been changed. In this study, a new method based on optimized radial basis function neural network (RBFNN) is proposed for control chart patterns (CCPs) recognition. The proposed method consists of four main modules: feature extraction, feature selection, classification and learning algorithm. In the feature extraction module, shape and statistical features are used. Recently, various shape and statistical features have been presented for the CCPs recognition. In the feature selection module, the association rules (AR) method has been employed to select the best set of the shape and statistical features. In the classifier section, RBFNN is used and finally, in RBFNN, learning algorithm has a high impact on the network performance. Therefore, a new learning algorithm based on the bees algorithm has been used in the learning module. Most studies have considered only six patterns: Normal, Cyclic, Increasing Trend, Decreasing Trend, Upward Shift and Downward Shift. Since three patterns namely Normal, Stratification, and Systematic are very similar to each other and distinguishing them is very difficult, in most studies Stratification and Systematic have not been considered. Regarding to the continuous monitoring and control over the production process and the exact type detection of the problem encountered during the production process, eight patterns have been investigated in this study. The proposed method is tested on a dataset containing 1600 samples (200 samples from each pattern) and the results showed that the proposed method has a very good performance. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Estimating statistical uncertainty of Monte Carlo efficiency-gain in the context of a correlated sampling Monte Carlo code for brachytherapy treatment planning with non-normal dose distribution.

PubMed

Mukhopadhyay, Nitai D; Sampson, Andrew J; Deniz, Daniel; Alm Carlsson, Gudrun; Williamson, Jeffrey; Malusek, Alexandr

2012-01-01

Correlated sampling Monte Carlo methods can shorten computing times in brachytherapy treatment planning. Monte Carlo efficiency is typically estimated via efficiency gain, defined as the reduction in computing time by correlated sampling relative to conventional Monte Carlo methods when equal statistical uncertainties have been achieved. The determination of the efficiency gain uncertainty arising from random effects, however, is not a straightforward task specially when the error distribution is non-normal. The purpose of this study is to evaluate the applicability of the F distribution and standardized uncertainty propagation methods (widely used in metrology to estimate uncertainty of physical measurements) for predicting confidence intervals about efficiency gain estimates derived from single Monte Carlo runs using fixed-collision correlated sampling in a simplified brachytherapy geometry. A bootstrap based algorithm was used to simulate the probability distribution of the efficiency gain estimates and the shortest 95% confidence interval was estimated from this distribution. It was found that the corresponding relative uncertainty was as large as 37% for this particular problem. The uncertainty propagation framework predicted confidence intervals reasonably well; however its main disadvantage was that uncertainties of input quantities had to be calculated in a separate run via a Monte Carlo method. The F distribution noticeably underestimated the confidence interval. These discrepancies were influenced by several photons with large statistical weights which made extremely large contributions to the scored absorbed dose difference. The mechanism of acquiring high statistical weights in the fixed-collision correlated sampling method was explained and a mitigation strategy was proposed. Copyright © 2011 Elsevier Ltd. All rights reserved.

Recent Development on O(+) - O Collision Frequency and Ionosphere-Thermosphere Coupling

NASA Technical Reports Server (NTRS)

Omidvar, K.; Menard, R.

1999-01-01

The collision frequency between an oxygen atom and its singly charged ion controls the momentum transfer between the ionosphere and the thermosphere. There has been a long standing discrepancy, extending over a decade, between the theoretical and empirical determination of this frequency: the empirical value of this frequency exceeded the theoretical value by a factor of 1.7. Recent improvements in theory were obtained by using accurate oxygen ion-oxygen atom potential energy curves, and partial wave quantum mechanical calculations. We now have applied three independent statistical methods to the observational data, obtained at the MIT/Millstone Hill Observatory, consisting of two sets A and B. These methods give results consistent with each other, and together with the recent theoretical improvements, bring the ratio close to unity, as it should be. The three statistical methods lead to an average for the ratio of the empirical to the theoretical values equal to 0.98, with an uncertainty of +/-8%, resolving the old discrepancy between theory and observation. The Hines statistics, and the lognormal distribution statistics, both give lower and upper bounds for the Set A equal to 0.89 and 1.02, respectively. The related bounds for the Set B are 1.06 and 1.17. The average values of these bounds thus bracket the ideal value of the ratio which should be equal to unity. The main source of uncertainties are errors in the profile of the oxygen atom density, which is of the order of 11%. An alternative method to find the oxygen atom density is being suggested.

[The clinical predictors of heteroaggressive behaviour of the women serving sentence in penitentiary].

PubMed

Shaklein, K N; Bardenshtein, L M; Demcheva, N K

To identify clinical predictors of heteroaggressive behavior. Three hundreds and three women serving sentence in a penal colony were examined using clinical, neurologic and statistical methods. The main group consisted of 225 women with heteroaggressive behavior, the control group included 78 women without aggressive behavior. Differences between the main and control groups in the structure of mental disorders and key syndromes were revealed. The authors conclude that the states with elements of dysphoria, dysthymia, decompensation of personality disorders, which are defined in the various forms of mental pathology, are the most significant predictors of heteroaggressive behavior in women in the penal colony.

Waste management barriers in developing country hospitals: Case study and AHP analysis.

PubMed

Delmonico, Diego V de Godoy; Santos, Hugo H Dos; Pinheiro, Marco Ap; de Castro, Rosani; de Souza, Regiane M

2018-01-01

Healthcare waste management is an essential field for both researchers and practitioners. Although there have been few studies using statistical methods for its evaluation, it has been the subject of several studies in different contexts. Furthermore, the known precarious practices for waste management in developing countries raise questions about its potential barriers. This study aims to investigate the barriers in healthcare waste management and their relevance. For this purpose, this paper analyses waste management practices in two Brazilian hospitals by using case study and the Analytic Hierarchy Process method. The barriers were organized into three categories - human factors, management, and infrastructure, and the main findings suggest that cost and employee awareness were the most significant barriers. These results highlight the main barriers to more sustainable waste management, and provide an empirical basis for multi-criteria evaluation of the literature.

Forest Statistics for Maine, 1995

Treesearch

Douglas M. Griffith; Carol L. Alerich; Carol L. Alerich

1996-01-01

A statistical report on the fourth forest inventory of Maine conducted in 1994-96. Findings are displayed in 117 tables containing estimates of forest area numbers of trees, timber volume, and growth. Data are presented at three levels: state, geographic unit, and county.

[Clinical outcomes research of use of Shenfu injection based on hospital information system].

PubMed

Yang, Jing; Zhao, Ruo-Qi; Xie, Yan-Ming; Yang, Hu; Li, Lin; Zhuang, Yan

2012-09-01

To know how Shenfu injection is used in clinical practice and to provide a reference for guiding clinical use of Shenfu injection. Extract Shenfu injection's post-marketing re-evaluation data from the hospital information system (HIS) of 20 national grade III-A General Hospitals, use basic statistical analysis methods to analyze Shenfu injection's indications, usage and dosage, treatment course etc. in clinical practice. In patients using Shenfu injection, the average age was 62. 15, and patients mainly concentrated in cardiovascular medicine. In clinical practice, Shenfu injection was used mainly for treatment of coronary heart disease (diagnosed as chest obstruction in traditional Chinese medicine). The treatment course mainly ranged from 3 to 7 days, and the dosage was within the limits prescribed by the instruction. Shenfu injection was mainly used for elderly patients, and has been used according to instruction in practice almostly.

Seasonality of climate change and oscillations in the Northeast Asia and Northwest Pacific

NASA Astrophysics Data System (ADS)

Ponomarev, V.; Salomatin, A.; Kaplunenko, D.; Krokhin, V.

2003-04-01

The main goals of this study are to estimate and compare the seasonality of centennial/semi-centennial climatic tendencies and dominated oscillations in surface air temperature and precipitation over continental and marginal areas of the Northeast Asia, as well as in the Northwest Pacific SST. We use monthly mean data for the 20th century from the NOAA Global History Climatic Network, JMA data base and WMU/COADS World Atlas of Surface Marine Data. Details of climate change/oscillations associated with cooling or warming in different areas and periods of a year are revealed. Wavelet analyses and two methods of the linear trend estimation are applied. First one is least-squares (LS) method with Fisher’s test for statistical significance level. Second one is nonparametric robust (NR) method, based on Theil's rank regression and Kendall's test for statistical significance level. The NR method should be applied to time series with abnormal distribution function typical for precipitation time series. Application of the NR method result in increase the statistical significance of both positive and negative linear trends in all cases of abnormal distribution with negative/positive skewness and low/high kurtosis. Using this method, we have determined spatial patterns of statistically significant climatic trends in surface air temperature, precipitation in the Northeast Asia, and in the Northwest Pacific SST. The most substantial centennial warming in the vast continental area of the mid-latitude band is found mainly for December March. The semi-centennial/ centennial cooling occurs in South Siberia and the subarctic mid-continental area in June September. Opposite tendencies were also revealed in precipitation and SST. Positive semi-centennial tendency in the SST in the second half of the 20th century predominates in the Kuroshio region and in the northwestern area of the subarctic gyre in winter. Negative tendency in the SST dominates in the southwestern subarctic gyre and the offshore area of the subtropic gyre in summer. Comparison of air temperature, precipitation, SST trends and oscillations in different seasons over land marginal and continental areas, as well as in the subarctic and subtropic zones indicates general features of the Northeast Asian Monsoon change/oscillation in 20th century and its second half. Similar features of seasonality in centennial, semi-centennial trends and dominated oscillations are manifested. Climate change and oscillation in the Northwest Pacific marginal seas revealed for the 20th century are explained.

Seasonality of climate change and oscillations in the Northeast Asia and Northwest Pacific

NASA Astrophysics Data System (ADS)

Ponomarev, V.; Salomatin, A.; Kaplunenko, D.; Krokhin, V.

2003-04-01

The main goals of this study are to estimate and compare the centennial/semi-centennial climatic tendencies and oscillations in surface air temperature and precipitation over continental and marginal areas of the Northeast Asian, as well as in the Northwest Pacific SST for all months of a year. We use monthly mean data for the 20th century from the NOAA Global History Climatic Network, JMA data base and WMU/COADS World Atlas of Surface Marine Data. Details of climate change/oscillations associated with cooling or warming in different areas and periods of a year are revealed. Wavelet analyses and two methods of the linear trend estimation are applied. First one is least-squares (LS) method with Fisher’s test for statistical significance level. Second one is nonparametric robust (NR) method, based on Theil's rank regression and Kendall's test for statistical significance level. The NR method should be applied to time series with abnormal distribution function typical for precipitation time series. Application of the NR method result in increase the statistical significance of both positive and negative linear trends in all cases of abnormal distribution with negative/positive skewness and low/high kurtosis. Using this method, we have determined spatial patterns of statistically significant climatic trends in surface air temperature, precipitation in the Northeast Asia, and in the Northwest Pacific SST. The most substantial centennial warming in the vast continental area of the mid-latitude band is found mainly for December March. The semi-centennial/ centennial cooling occurs in South Siberia and the subarctic mid-continental area in June September. Opposite tendencies were also revealed in precipitation and SST. Positive semi-centennial tendency in the SST in the second half of the 20th century predominates in the Kuroshio region and in the northwestern area of the subarctic gyre in winter. Negative tendency in the SST dominates in the southwestern subarctic gyre and the offshore area of the subtropic gyre in summer. Comparison of air temperature, precipitation, SST trends and oscillations in different seasons over land marginal and continental areas, as well as in the subarctic and subtropic zones indicates general features of the Northeast Asian Monsoon change/oscillation in 20th century and its second half. Similar features of seasonality in centennial, semi-centennial trends and dominated oscillations are manifested. Climate change and oscillation in the Northwest Pacific marginal seas revealed for the 20th century are explained.

Statistical Study on Variations of the Ionospheric Ion Density Observed by DEMETER and Related to Seismic Activities

NASA Astrophysics Data System (ADS)

Yan, Rui; Parrot, Michel; Pinçon, Jean-Louis

2017-12-01

In this paper, we present the result of a statistical study performed on the ionospheric ion density variations above areas of seismic activity. The ion density was observed by the low altitude satellite DEMETER between 2004 and 2010. In the statistical analysis a superposed epoch method is used where the observed ionospheric ion density close to the epicenters both in space and in time is compared to background values recorded at the same location and in the same conditions. Data associated with aftershocks have been carefully removed from the database to prevent spurious effects on the statistics. It is shown that, during nighttime, anomalous ionospheric perturbations related to earthquakes with magnitudes larger than 5 are evidenced. At the time of these perturbations the background ion fluctuation departs from a normal distribution. They occur up to 200 km from the epicenters and mainly 5 days before the earthquakes. As expected, an ion density perturbation occurring just after the earthquakes and close to the epicenters is also evidenced.

The V-band Empirical Mass-luminosity Relation for Main Sequence Stars

NASA Astrophysics Data System (ADS)

Xia, Fang; Fu, Yan-Ning

2010-07-01

Stellar mass is an indispensable parameter in the studies of stellar physics and stellar dynamics. On the one hand, the most reliable way to determine the stellar dynamical mass is via orbital determinations of binaries. On the other hand, however, most stellar masses have to be estimated by using the mass luminosity relation (MLR). Therefore, it is important to obtain the empirical MLR through fitting the data of stellar dynamical mass and luminosity. The effect of metallicity can make this relation disperse in the V-band, but studies show that this is mainly limited to the case when the stellar mass is less than 0.6M⊙ Recently, many relevant data have been accumulated for main sequence stars with larger masses, which make it possible to significantly improve the corresponding MLR. Using a fitting method which can reasonably assign weights to the observational data including two quantities with different dimensions, we obtain a V-band MLR based on the dynamical masses and luminosities of 203 main sequence stars. In comparison with the previous work, the improved MLR is statistically significant, and the relative error of mass estimation reaches about 5%. Therefore, our MLR is useful not only in the studies of statistical nature, but also in the studies of concrete stellar systems, such as the long-term dynamical study and the short-term positioning study of a specific multiple star system.

The V Band Empirical Mass-Luminosity Relation for Main Sequence Stars

NASA Astrophysics Data System (ADS)

Xia, F.; Fu, Y. N.

2010-01-01

Stellar mass is an indispensable parameter in the studies of stellar physics and stellar dynamics. On the one hand, the most reliable way to determine the stellar dynamical mass is via orbital determination of binaries. On the other hand, however, most stellar masses have to be estimated by using the mass-luminosity relation (MLR). Therefore, it is important to obtain the empirical MLR through fitting the data of stellar dynamical mass and luminosity. The effect of metallicity can make this relation disperse in the V-band, but studies show that this is mainly limited to the case when the stellar mass is less than 0.6M⊙. Recently, many relevant data have been accumulated for main sequence stars with larger mass, which make it possible to significantly improve the corresponding MLR. Using a fitting method which can reasonably assign weight to the observational data including two quantities with different dimensions, we obtain a V-band MLR based on the dynamical masses and luminosities of 203 main sequence stars. Compared with the previous work, the improved MLR is statistically significant, and the relative error of mass estimation reaches about 5%. Therefore, our MLR is useful not only in studies of statistical nature, but also in studies of concrete stellar systems, such as the long-term dynamical study and the short-term positioning study of a specific multiple star system.

Integrated Application of Multivariate Statistical Methods to Source Apportionment of Watercourses in the Liao River Basin, Northeast China

PubMed Central

Chen, Jiabo; Li, Fayun; Fan, Zhiping; Wang, Yanjie

2016-01-01

Source apportionment of river water pollution is critical in water resource management and aquatic conservation. Comprehensive application of various GIS-based multivariate statistical methods was performed to analyze datasets (2009–2011) on water quality in the Liao River system (China). Cluster analysis (CA) classified the 12 months of the year into three groups (May–October, February–April and November–January) and the 66 sampling sites into three groups (groups A, B and C) based on similarities in water quality characteristics. Discriminant analysis (DA) determined that temperature, dissolved oxygen (DO), pH, chemical oxygen demand (CODMn), 5-day biochemical oxygen demand (BOD5), NH4+–N, total phosphorus (TP) and volatile phenols were significant variables affecting temporal variations, with 81.2% correct assignments. Principal component analysis (PCA) and positive matrix factorization (PMF) identified eight potential pollution factors for each part of the data structure, explaining more than 61% of the total variance. Oxygen-consuming organics from cropland and woodland runoff were the main latent pollution factor for group A. For group B, the main pollutants were oxygen-consuming organics, oil, nutrients and fecal matter. For group C, the evaluated pollutants primarily included oxygen-consuming organics, oil and toxic organics. PMID:27775679

Spatial uncertainty of a geoid undulation model in Guayaquil, Ecuador

NASA Astrophysics Data System (ADS)

Chicaiza, E. G.; Leiva, C. A.; Arranz, J. J.; Buenańo, X. E.

2017-06-01

Geostatistics is a discipline that deals with the statistical analysis of regionalized variables. In this case study, geostatistics is used to estimate geoid undulation in the rural area of Guayaquil town in Ecuador. The geostatistical approach was chosen because the estimation error of prediction map is getting. Open source statistical software R and mainly geoR, gstat and RGeostats libraries were used. Exploratory data analysis (EDA), trend and structural analysis were carried out. An automatic model fitting by Iterative Least Squares and other fitting procedures were employed to fit the variogram. Finally, Kriging using gravity anomaly of Bouguer as external drift and Universal Kriging were used to get a detailed map of geoid undulation. The estimation uncertainty was reached in the interval [-0.5; +0.5] m for errors and a maximum estimation standard deviation of 2 mm in relation with the method of interpolation applied. The error distribution of the geoid undulation map obtained in this study provides a better result than Earth gravitational models publicly available for the study area according the comparison with independent validation points. The main goal of this paper is to confirm the feasibility to use geoid undulations from Global Navigation Satellite Systems and leveling field measurements and geostatistical techniques methods in order to use them in high-accuracy engineering projects.

Using NOAA/AVHRR based remote sensing data and PCR method for estimation of Aus rice yield in Bangladesh

NASA Astrophysics Data System (ADS)

Nizamuddin, Mohammad; Akhand, Kawsar; Roytman, Leonid; Kogan, Felix; Goldberg, Mitch

2015-06-01

Rice is a dominant food crop of Bangladesh accounting about 75 percent of agricultural land use for rice cultivation and currently Bangladesh is the world's fourth largest rice producing country. Rice provides about two-third of total calorie supply and about one-half of the agricultural GDP and one-sixth of the national income in Bangladesh. Aus is one of the main rice varieties in Bangladesh. Crop production, especially rice, the main food staple, is the most susceptible to climate change and variability. Any change in climate will, thus, increase uncertainty regarding rice production as climate is major cause year-to-year variability in rice productivity. This paper shows the application of remote sensing data for estimating Aus rice yield in Bangladesh using official statistics of rice yield with real time acquired satellite data from Advanced Very High Resolution Radiometer (AVHRR) sensor and Principal Component Regression (PCR) method was used to construct a model. The simulated result was compared with official agricultural statistics showing that the error of estimation of Aus rice yield was less than 10%. Remote sensing, therefore, is a valuable tool for estimating crop yields well in advance of harvest, and at a low cost.

A factor analysis of the SSQ (Speech, Spatial, and Qualities of Hearing Scale)

PubMed Central

2014-01-01

Objective The speech, spatial, and qualities of hearing questionnaire (SSQ) is a self-report test of auditory disability. The 49 items ask how well a listener would do in many complex listening situations illustrative of real life. The scores on the items are often combined into the three main sections or into 10 pragmatic subscales. We report here a factor analysis of the SSQ that we conducted to further investigate its statistical properties and to determine its structure. Design Statistical factor analysis of questionnaire data, using parallel analysis to determine the number of factors to retain, oblique rotation of factors, and a bootstrap method to estimate the confidence intervals. Study sample 1220 people who have attended MRC IHR over the last decade. Results We found three clear factors, essentially corresponding to the three main sections of the SSQ. They are termed “speech understanding”, “spatial perception”, and “clarity, separation, and identification”. Thirty-five of the SSQ questions were included in the three factors. There was partial evidence for a fourth factor, “effort and concentration”, representing two more questions. Conclusions These results aid in the interpretation and application of the SSQ and indicate potential methods for generating average scores. PMID:24417459

Maine School Library Survey. Statistics of Public School Libraries in Maine Serving Grades K-12, from Data Gathered February 1990.

ERIC Educational Resources Information Center

Soule, Margaret

This survey of the current status of public school libraries in Maine was intended to provide statistical data as a basis for improving the school library media center program in these schools. Information was gathered that detailed how resources and delivery of services differed across grade level; across variation in size of school; between…

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.

Assessing Fire Weather Index using statistical downscaling and spatial interpolation techniques in Greece

NASA Astrophysics Data System (ADS)

Karali, Anna; Giannakopoulos, Christos; Frias, Maria Dolores; Hatzaki, Maria; Roussos, Anargyros; Casanueva, Ana

2013-04-01

Forest fires have always been present in the Mediterranean ecosystems, thus they constitute a major ecological and socio-economic issue. The last few decades though, the number of forest fires has significantly increased, as well as their severity and impact on the environment. Local fire danger projections are often required when dealing with wild fire research. In the present study the application of statistical downscaling and spatial interpolation methods was performed to the Canadian Fire Weather Index (FWI), in order to assess forest fire risk in Greece. The FWI is used worldwide (including the Mediterranean basin) to estimate the fire danger in a generalized fuel type, based solely on weather observations. The meteorological inputs to the FWI System are noon values of dry-bulb temperature, air relative humidity, 10m wind speed and precipitation during the previous 24 hours. The statistical downscaling methods are based on a statistical model that takes into account empirical relationships between large scale variables (used as predictors) and local scale variables. In the framework of the current study the statistical downscaling portal developed by the Santander Meteorology Group (https://www.meteo.unican.es/downscaling) in the framework of the EU project CLIMRUN (www.climrun.eu) was used to downscale non standard parameters related to forest fire risk. In this study, two different approaches were adopted. Firstly, the analogue downscaling technique was directly performed to the FWI index values and secondly the same downscaling technique was performed indirectly through the meteorological inputs of the index. In both cases, the statistical downscaling portal was used considering the ERA-Interim reanalysis as predictands due to the lack of observations at noon. Additionally, a three-dimensional (3D) interpolation method of position and elevation, based on Thin Plate Splines (TPS) was used, to interpolate the ERA-Interim data used to calculate the index. Results from this method were compared with the statistical downscaling results obtained from the portal. Finally, FWI was computed using weather observations obtained from the Hellenic National Meteorological Service, mainly in the south continental part of Greece and a comparison with the previous results was performed.

In silico environmental chemical science: properties and processes from statistical and computational modelling

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

Tratnyek, Paul G.; Bylaska, Eric J.; Weber, Eric J.

2017-01-01

Quantitative structure–activity relationships (QSARs) have long been used in the environmental sciences. More recently, molecular modeling and chemoinformatic methods have become widespread. These methods have the potential to expand and accelerate advances in environmental chemistry because they complement observational and experimental data with “in silico” results and analysis. The opportunities and challenges that arise at the intersection between statistical and theoretical in silico methods are most apparent in the context of properties that determine the environmental fate and effects of chemical contaminants (degradation rate constants, partition coefficients, toxicities, etc.). The main example of this is the calibration of QSARs usingmore » descriptor variable data calculated from molecular modeling, which can make QSARs more useful for predicting property data that are unavailable, but also can make them more powerful tools for diagnosis of fate determining pathways and mechanisms. Emerging opportunities for “in silico environmental chemical science” are to move beyond the calculation of specific chemical properties using statistical models and toward more fully in silico models, prediction of transformation pathways and products, incorporation of environmental factors into model predictions, integration of databases and predictive models into more comprehensive and efficient tools for exposure assessment, and extending the applicability of all the above from chemicals to biologicals and materials.« less

Identifying trends in climate: an application to the cenozoic

NASA Astrophysics Data System (ADS)

Richards, Gordon R.

1998-05-01

The recent literature on trending in climate has raised several issues, whether trends should be modeled as deterministic or stochastic, whether trends are nonlinear, and the relative merits of statistical models versus models based on physics. This article models trending since the late Cretaceous. This 68 million-year interval is selected because the reliability of tests for trending is critically dependent on the length of time spanned by the data. Two main hypotheses are tested, that the trend has been caused primarily by CO2 forcing, and that it reflects a variety of forcing factors which can be approximated by statistical methods. The CO2 data is obtained from model simulations. Several widely-used statistical models are found to be inadequate. ARIMA methods parameterize too much of the short-term variation, and do not identify low frequency movements. Further, the unit root in the ARIMA process does not predict the long-term path of temperature. Spectral methods also have little ability to predict temperature at long horizons. Instead, the statistical trend is estimated using a nonlinear smoothing filter. Both of these paradigms make it possible to model climate as a cointegrated process, in which temperature can wander quite far from the trend path in the intermediate term, but converges back over longer horizons. Comparing the forecasting properties of the two trend models demonstrates that the optimal forecasting model includes CO2 forcing and a parametric representation of the nonlinear variability in climate.

[Landscape pattern change of Dongzhai Harbour mangrove, South China analyzed with a patch-based method and its driving forces].

PubMed

Huang, Xing; Xin, Kun; Li, Xiu-zhen; Wang, Xue-ping; Ren, Lin-jing; Li, Xi-zhi; Yan, Zhong-zheng

2015-05-01

According to the interpreted results of three satellite images of Dongzhai Harbour obtained in 1988, 1998 and 2009, the changes of landscape pattern and the differences of its driving forces of mangrove forest in Dongzhai Harbour were analyzed with a patch-based method on spatial distribution dynamics. The results showed that the areas of mangrove forest in 1988, 1998 and 2009 were 1809.4, 1738.7 and 1608.2 hm2 respectively, which presented a trend of decrease with enhanced degree of landscape fragmentation. The transformations among different landscape types indicated that the mangrove, agricultural land and forest land were mainly changed into built-up land and aquaculture pond. The statistical results obtained from three different methods, i.e., accumulative counting, percentage counting and main transformation route counting, showed that natural factors were the main reason for the changes of patch number, responsible for 58.6%, 72.2% and 72.1% of patch number change, respectively, while the percentages of patch area change induced by human activities were 70.4%, 70.3% and 76.4%, respectively, indicating that human activities were the primary factors of the change of patch areas.

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.

Using A New Model for Main Sequence Turnoff Absolute Magnitudes to Measure Stellar Streams in the Milky Way Halo

NASA Astrophysics Data System (ADS)

Weiss, Jake; Newberg, Heidi Jo; Arsenault, Matthew; Bechtel, Torrin; Desell, Travis; Newby, Matthew; Thompson, Jeffery M.

2016-01-01

Statistical photometric parallax is a method for using the distribution of absolute magnitudes of stellar tracers to statistically recover the underlying density distribution of these tracers. In previous work, statistical photometric parallax was used to trace the Sagittarius Dwarf tidal stream, the so-called bifurcated piece of the Sagittaritus stream, and the Virgo Overdensity through the Milky Way. We use an improved knowledge of this distribution in a new algorithm that accounts for the changes in the stellar population of color-selected stars near the photometric limit of the Sloan Digital Sky Survey (SDSS). Although we select bluer main sequence turnoff stars (MSTO) as tracers, large color errors near the survey limit cause many stars to be scattered out of our selection box and many fainter, redder stars to be scattered into our selection box. We show that we are able to recover parameters for analogues of these streams in simulated data using a maximum likelihood optimization on MilkyWay@home. We also present the preliminary results of fitting the density distribution of major Milky Way tidal streams in SDSS data. This research is supported by generous gifts from the Marvin Clan, Babette Josephs, Manit Limlamai, and the MilkyWay@home volunteers.

An Efficient Statistical Method to Compute Molecular Collisional Rate Coefficients

NASA Astrophysics Data System (ADS)

Loreau, Jérôme; Lique, François; Faure, Alexandre

2018-01-01

Our knowledge about the “cold” universe often relies on molecular spectra. A general property of such spectra is that the energy level populations are rarely at local thermodynamic equilibrium. Solving the radiative transfer thus requires the availability of collisional rate coefficients with the main colliding partners over the temperature range ∼10–1000 K. These rate coefficients are notoriously difficult to measure and expensive to compute. In particular, very few reliable collisional data exist for inelastic collisions involving reactive radicals or ions. In this Letter, we explore the use of a fast quantum statistical method to determine molecular collisional excitation rate coefficients. The method is benchmarked against accurate (but costly) rigid-rotor close-coupling calculations. For collisions proceeding through the formation of a strongly bound complex, the method is found to be highly satisfactory up to room temperature. Its accuracy decreases with decreasing potential well depth and with increasing temperature, as expected. This new method opens the way to the determination of accurate inelastic collisional data involving key reactive species such as {{{H}}}3+, H2O+, and H3O+ for which exact quantum calculations are currently not feasible.

The same analysis approach: Practical protection against the pitfalls of novel neuroimaging analysis methods.

PubMed

Görgen, Kai; Hebart, Martin N; Allefeld, Carsten; Haynes, John-Dylan

2017-12-27

Standard neuroimaging data analysis based on traditional principles of experimental design, modelling, and statistical inference is increasingly complemented by novel analysis methods, driven e.g. by machine learning methods. While these novel approaches provide new insights into neuroimaging data, they often have unexpected properties, generating a growing literature on possible pitfalls. We propose to meet this challenge by adopting a habit of systematic testing of experimental design, analysis procedures, and statistical inference. Specifically, we suggest to apply the analysis method used for experimental data also to aspects of the experimental design, simulated confounds, simulated null data, and control data. We stress the importance of keeping the analysis method the same in main and test analyses, because only this way possible confounds and unexpected properties can be reliably detected and avoided. We describe and discuss this Same Analysis Approach in detail, and demonstrate it in two worked examples using multivariate decoding. With these examples, we reveal two sources of error: A mismatch between counterbalancing (crossover designs) and cross-validation which leads to systematic below-chance accuracies, and linear decoding of a nonlinear effect, a difference in variance. Copyright © 2017 Elsevier Inc. All rights reserved.

Grouping of Bulgarian wines according to grape variety by using statistical methods

NASA Astrophysics Data System (ADS)

Milev, M.; Nikolova, Kr.; Ivanova, Ir.; Minkova, St.; Evtimov, T.; Krustev, St.

2017-12-01

68 different types of Bulgarian wines were studied in accordance with 9 optical parameters as follows: color parameters in XYZ and SIE Lab color systems, lightness, Hue angle, chroma, fluorescence intensity and emission wavelength. The main objective of this research is using hierarchical cluster analysis to evaluate the similarity and the distance between examined different types of Bulgarian wines and their grouping based on physical parameters. We have found that wines are grouped in clusters on the base of the degree of identity between them. There are two main clusters each one with two subclusters. The first one contains white wines and Sira, the second contains red wines and rose. The results from cluster analysis are presented graphically by a dendrogram. The other statistical technique used is factor analysis performed by the Method of Principal Components (PCA). The aim is to reduce the large number of variables to a few factors by grouping the correlated variables into one factor and subdividing the noncorrelated variables into different factors. Moreover the factor analysis provided the possibility to determine the parameters with the greatest influence over the distribution of samples in different clusters. In our study after the rotation of the factors with Varimax method the parameters were combined into two factors, which explain about 80 % of the total variation. The first one explains the 61.49% and correlates with color characteristics, the second one explains 18.34% from the variation and correlates with the parameters connected with fluorescence spectroscopy.

Signal Detection Techniques for Diagnostic Monitoring of Space Shuttle Main Engine Turbomachinery

NASA Technical Reports Server (NTRS)

Coffin, Thomas; Jong, Jen-Yi

1986-01-01

An investigation to develop, implement, and evaluate signal analysis techniques for the detection and classification of incipient mechanical failures in turbomachinery is reviewed. A brief description of the Space Shuttle Main Engine (SSME) test/measurement program is presented. Signal analysis techniques available to describe dynamic measurement characteristics are reviewed. Time domain and spectral methods are described, and statistical classification in terms of moments is discussed. Several of these waveform analysis techniques have been implemented on a computer and applied to dynamc signals. A laboratory evaluation of the methods with respect to signal detection capability is described. A unique coherence function (the hyper-coherence) was developed through the course of this investigation, which appears promising as a diagnostic tool. This technique and several other non-linear methods of signal analysis are presented and illustrated by application. Software for application of these techniques has been installed on the signal processing system at the NASA/MSFC Systems Dynamics Laboratory.

Finnish upper secondary students' collaborative processes in learning statistics in a CSCL environment

NASA Astrophysics Data System (ADS)

Kaleva Oikarinen, Juho; Järvelä, Sanna; Kaasila, Raimo

2014-04-01

This design-based research project focuses on documenting statistical learning among 16-17-year-old Finnish upper secondary school students (N = 78) in a computer-supported collaborative learning (CSCL) environment. One novel value of this study is in reporting the shift from teacher-led mathematical teaching to autonomous small-group learning in statistics. The main aim of this study is to examine how student collaboration occurs in learning statistics in a CSCL environment. The data include material from videotaped classroom observations and the researcher's notes. In this paper, the inter-subjective phenomena of students' interactions in a CSCL environment are analysed by using a contact summary sheet (CSS). The development of the multi-dimensional coding procedure of the CSS instrument is presented. Aptly selected video episodes were transcribed and coded in terms of conversational acts, which were divided into non-task-related and task-related categories to depict students' levels of collaboration. The results show that collaborative learning (CL) can facilitate cohesion and responsibility and reduce students' feelings of detachment in our classless, periodic school system. The interactive .pdf material and collaboration in small groups enable statistical learning. It is concluded that CSCL is one possible method of promoting statistical teaching. CL using interactive materials seems to foster and facilitate statistical learning processes.

Accounting for Population Structure in Gene-by-Environment Interactions in Genome-Wide Association Studies Using Mixed Models.

PubMed

Sul, Jae Hoon; Bilow, Michael; Yang, Wen-Yun; Kostem, Emrah; Furlotte, Nick; He, Dan; Eskin, Eleazar

2016-03-01

Although genome-wide association studies (GWASs) have discovered numerous novel genetic variants associated with many complex traits and diseases, those genetic variants typically explain only a small fraction of phenotypic variance. Factors that account for phenotypic variance include environmental factors and gene-by-environment interactions (GEIs). Recently, several studies have conducted genome-wide gene-by-environment association analyses and demonstrated important roles of GEIs in complex traits. One of the main challenges in these association studies is to control effects of population structure that may cause spurious associations. Many studies have analyzed how population structure influences statistics of genetic variants and developed several statistical approaches to correct for population structure. However, the impact of population structure on GEI statistics in GWASs has not been extensively studied and nor have there been methods designed to correct for population structure on GEI statistics. In this paper, we show both analytically and empirically that population structure may cause spurious GEIs and use both simulation and two GWAS datasets to support our finding. We propose a statistical approach based on mixed models to account for population structure on GEI statistics. We find that our approach effectively controls population structure on statistics for GEIs as well as for genetic variants.

Attitudes toward statistics in medical postgraduates: measuring, evaluating and monitoring

PubMed Central

2012-01-01

Background In medical training, statistics is considered a very difficult course to learn and teach. Current studies have found that students’ attitudes toward statistics can influence their learning process. Measuring, evaluating and monitoring the changes of students’ attitudes toward statistics are important. Few studies have focused on the attitudes of postgraduates, especially medical postgraduates. Our purpose was to understand current attitudes regarding statistics held by medical postgraduates and explore their effects on students’ achievement. We also wanted to explore the influencing factors and the sources of these attitudes and monitor their changes after a systematic statistics course. Methods A total of 539 medical postgraduates enrolled in a systematic statistics course completed the pre-form of the Survey of Attitudes Toward Statistics −28 scale, and 83 postgraduates were selected randomly from among them to complete the post-form scale after the course. Results Most medical postgraduates held positive attitudes toward statistics, but they thought statistics was a very difficult subject. The attitudes mainly came from experiences in a former statistical or mathematical class. Age, level of statistical education, research experience, specialty and mathematics basis may influence postgraduate attitudes toward statistics. There were significant positive correlations between course achievement and attitudes toward statistics. In general, student attitudes showed negative changes after completing a statistics course. Conclusions The importance of student attitudes toward statistics must be recognized in medical postgraduate training. To make sure all students have a positive learning environment, statistics teachers should measure their students’ attitudes and monitor their change of status during a course. Some necessary assistance should be offered for those students who develop negative attitudes. PMID:23173770

Successive ratio subtraction as a novel manipulation of ratio spectra for quantitative determination of a mixture of furosemide, spironolactone and canrenone

NASA Astrophysics Data System (ADS)

Emam, Aml A.; Abdelaleem, Eglal A.; Naguib, Ibrahim A.; Abdallah, Fatma F.; Ali, Nouruddin W.

2018-03-01

Furosemide and spironolactone are commonly prescribed antihypertensive drugs. Canrenone is the main degradation product and main metabolite of spironolactone. Ratio subtraction and extended ratio subtraction spectrophotometric methods were previously applied for quantitation of only binary mixtures. An extension of the above mentioned methods; successive ratio subtraction, is introduced in the presented work for quantitative determination of ternary mixtures exemplified by furosemide, spironolactone and canrenone. Manipulating the ratio spectra of the ternary mixture allowed their determination at 273.6 nm, 285 nm and 240 nm and in the concentration ranges of (2-16 μg mL- 1), (4-32 μg mL- 1) and (1-18 μg mL- 1) for furosemide, spironolactone and canrenone, respectively. Method specificity was ensured by the application to laboratory prepared mixtures. The introduced method was ensured to be accurate and precise. Validation of the developed method was done with respect to ICH guidelines and its validity was further ensured by the application to the pharmaceutical formulation. Statistical comparison between the obtained results and those obtained from the reported HPLC method was achieved concerning student's t-test and F ratio test where no significant difference was observed.

Sources of international migration statistics in Africa.

PubMed

1984-01-01

The sources of international migration data for Africa may be classified into 2 main categories: administrative records and 2) censuses and survey data. Both categories are sources for the direct measurement of migration, but the 2nd category can be used for the indirect estimation of net international migration. The administrative records from which data on international migration may be derived include 1) entry/departure cards or forms completed at international borders, 2) residence/work permits issued to aliens, and 3) general population registers and registers of aliens. The statistics derived from the entry/departure cards may be described as 1) land frontier control statistics and 2) port control statistics. The former refer to data derived from movements across land borders and the latter refer to information collected at international airports and seaports. Other administrative records which are potential sources of statistics on international migration in some African countries include some limited population registers, records of the registration of aliens, and particulars of residence/work permits issued to aliens. Although frontier control data are considered the most important source of international migration statistics, in many African countries these data are too deficient to provide a satisfactory indication of the level of international migration. Thus decennial population censuses and/or sample surveys are the major sources of the available statistics on the stock and characteristics of international migration. Indirect methods can be used to supplement census data with intercensal estimates of net migration using census data on the total population. This indirect method of obtaining information on migration can be used to evaluate estimates derived from frontier control records, and it also offers the means of obtaining alternative information on international migration in African countries which have not directly investigated migration topics in their censuses or surveys.

STRengthening analytical thinking for observational studies: the STRATOS initiative.

PubMed

Sauerbrei, Willi; Abrahamowicz, Michal; Altman, Douglas G; le Cessie, Saskia; Carpenter, James

2014-12-30

The validity and practical utility of observational medical research depends critically on good study design, excellent data quality, appropriate statistical methods and accurate interpretation of results. Statistical methodology has seen substantial development in recent times. Unfortunately, many of these methodological developments are ignored in practice. Consequently, design and analysis of observational studies often exhibit serious weaknesses. The lack of guidance on vital practical issues discourages many applied researchers from using more sophisticated and possibly more appropriate methods when analyzing observational studies. Furthermore, many analyses are conducted by researchers with a relatively weak statistical background and limited experience in using statistical methodology and software. Consequently, even 'standard' analyses reported in the medical literature are often flawed, casting doubt on their results and conclusions. An efficient way to help researchers to keep up with recent methodological developments is to develop guidance documents that are spread to the research community at large. These observations led to the initiation of the strengthening analytical thinking for observational studies (STRATOS) initiative, a large collaboration of experts in many different areas of biostatistical research. The objective of STRATOS is to provide accessible and accurate guidance in the design and analysis of observational studies. The guidance is intended for applied statisticians and other data analysts with varying levels of statistical education, experience and interests. In this article, we introduce the STRATOS initiative and its main aims, present the need for guidance documents and outline the planned approach and progress so far. We encourage other biostatisticians to become involved. © 2014 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd.

Investigation of methods for hydroclimatic data homogenization

NASA Astrophysics Data System (ADS)

Steirou, E.; Koutsoyiannis, D.

2012-04-01

We investigate the methods used for the adjustment of inhomogeneities of temperature time series covering the last 100 years. Based on a systematic study of scientific literature, we classify and evaluate the observed inhomogeneities in historical and modern time series, as well as their adjustment methods. It turns out that these methods are mainly statistical, not well justified by experiments and are rarely supported by metadata. In many of the cases studied the proposed corrections are not even statistically significant. From the global database GHCN-Monthly Version 2, we examine all stations containing both raw and adjusted data that satisfy certain criteria of continuity and distribution over the globe. In the United States of America, because of the large number of available stations, stations were chosen after a suitable sampling. In total we analyzed 181 stations globally. For these stations we calculated the differences between the adjusted and non-adjusted linear 100-year trends. It was found that in the two thirds of the cases, the homogenization procedure increased the positive or decreased the negative temperature trends. One of the most common homogenization methods, 'SNHT for single shifts', was applied to synthetic time series with selected statistical characteristics, occasionally with offsets. The method was satisfactory when applied to independent data normally distributed, but not in data with long-term persistence. The above results cast some doubts in the use of homogenization procedures and tend to indicate that the global temperature increase during the last century is between 0.4°C and 0.7°C, where these two values are the estimates derived from raw and adjusted data, respectively.

A reliability study on brain activation during active and passive arm movements supported by an MRI-compatible robot.

PubMed

Estévez, Natalia; Yu, Ningbo; Brügger, Mike; Villiger, Michael; Hepp-Reymond, Marie-Claude; Riener, Robert; Kollias, Spyros

2014-11-01

In neurorehabilitation, longitudinal assessment of arm movement related brain function in patients with motor disability is challenging due to variability in task performance. MRI-compatible robots monitor and control task performance, yielding more reliable evaluation of brain function over time. The main goals of the present study were first to define the brain network activated while performing active and passive elbow movements with an MRI-compatible arm robot (MaRIA) in healthy subjects, and second to test the reproducibility of this activation over time. For the fMRI analysis two models were compared. In model 1 movement onset and duration were included, whereas in model 2 force and range of motion were added to the analysis. Reliability of brain activation was tested with several statistical approaches applied on individual and group activation maps and on summary statistics. The activated network included mainly the primary motor cortex, primary and secondary somatosensory cortex, superior and inferior parietal cortex, medial and lateral premotor regions, and subcortical structures. Reliability analyses revealed robust activation for active movements with both fMRI models and all the statistical methods used. Imposed passive movements also elicited mainly robust brain activation for individual and group activation maps, and reliability was improved by including additional force and range of motion using model 2. These findings demonstrate that the use of robotic devices, such as MaRIA, can be useful to reliably assess arm movement related brain activation in longitudinal studies and may contribute in studies evaluating therapies and brain plasticity following injury in the nervous system.

Classification of boreal forest by satellite and inventory data using neural network approach

NASA Astrophysics Data System (ADS)

Romanov, A. A.

2012-12-01

The main objective of this research was to develop methodology for boreal (Siberian Taiga) land cover classification in a high accuracy level. The study area covers the territories of Central Siberian several parts along the Yenisei River (60-62 degrees North Latitude): the right bank includes mixed forest and dark taiga, the left - pine forests; so were taken as a high heterogeneity and statistically equal surfaces concerning spectral characteristics. Two main types of data were used: time series of middle spatial resolution satellite images (Landsat 5, 7 and SPOT4) and inventory datasets from the nature fieldworks (used for training samples sets preparation). Method of collecting field datasets included a short botany description (type/species of vegetation, density, compactness of the crowns, individual height and max/min diameters representative of each type, surface altitude of the plot), at the same time the geometric characteristic of each training sample unit corresponded to the spatial resolution of satellite images and geo-referenced (prepared datasets both of the preliminary processing and verification). The network of test plots was planned as irregular and determined by the landscape oriented approach. The main focus of the thematic data processing has been allocated for the use of neural networks (fuzzy logic inc.); therefore, the results of field studies have been converting input parameter of type / species of vegetation cover of each unit and the degree of variability. Proposed approach involves the processing of time series separately for each image mainly for the verification: shooting parameters taken into consideration (time, albedo) and thus expected to assess the quality of mapping. So the input variables for the networks were sensor bands, surface altitude, solar angels and land surface temperature (for a few experiments); also given attention to the formation of the formula class on the basis of statistical pre-processing of results of field research (prevalence type). Besides some statistical methods of supervised classification has been used (minimal distance, maximum likelihood, Mahalanobis). During the study received various types of neural classifiers suitable for the mapping, and even for the high heterogenic areas neural network approach has shown better results in precision despite the validity of the assumption of Gaussian distribution (Table). Experimentally chosen optimum network structure consisting of three layers of ten neuron in each, but it should be clarified that such configuration requires larges computational resources in comparison the statistical methods presented above; necessary to increase the number of iteration in network learning process for RMS errors minimization. It should also be emphasized that the key issues of accuracy estimation of the classification results is lack of completeness of the training sets, this is especially true with summer image processing of mixed forest. However seems that proposed methodology can be used also for measure local dynamic of boreal land surface by the type of vegetation.Comparison of classification accuracyt;

The Quantitative Analysis on the Individual Characteristics of Urban Residents and Their Sport Consumption Motivation

NASA Astrophysics Data System (ADS)

Xianliang, Lei; Hongying, Yu

Using the questionnaire, mathematical statistics and entropy measurement methods, the quantitative relationship between the individual characteristics urban residents and their sports consumption motivation are studied. The results show that the most main sports consumption motivation of urban residents is fitness motivation and social motivation. Urban residents of different gender, age, education and income levels are different in regulating psychological motivation, rational consumption motivation and seeking common motivation.

Overlay improvement methods with diffraction based overlay and integrated metrology

NASA Astrophysics Data System (ADS)

Nam, Young-Sun; Kim, Sunny; Shin, Ju Hee; Choi, Young Sin; Yun, Sang Ho; Kim, Young Hoon; Shin, Si Woo; Kong, Jeong Heung; Kang, Young Seog; Ha, Hun Hwan

2015-03-01

To accord with new requirement of securing more overlay margin, not only the optical overlay measurement is faced with the technical limitations to represent cell pattern's behavior, but also the larger measurement samples are inevitable for minimizing statistical errors and better estimation of circumstance in a lot. From these reasons, diffraction based overlay (DBO) and integrated metrology (IM) were mainly proposed as new approaches for overlay enhancement in this paper.

Galton's legacy to research on intelligence.

PubMed

Jensen, Arthur R

2002-04-01

In the 1999 Galton Lecture for the annual conference of The Galton Institute, the author summarizes the main elements of Galton's ideas about human mental ability and the research paradigm they generated, including the concept of 'general' mental ability, its hereditary component, its physical basis, racial differences, and methods for measuring individual differences in general ability. Although the conclusions Galton drew from his empirical studies were seldom compelling for lack of the needed technology and methods of statistical inference in his day, contemporary research has generally borne out most of Galton's original and largely intuitive ideas, which still inspire mainstream scientific research on intelligence.

Signal analysis techniques for incipient failure detection in turbomachinery

NASA Technical Reports Server (NTRS)

Coffin, T.

1985-01-01

Signal analysis techniques for the detection and classification of incipient mechanical failures in turbomachinery were developed, implemented and evaluated. Signal analysis techniques available to describe dynamic measurement characteristics are reviewed. Time domain and spectral methods are described, and statistical classification in terms of moments is discussed. Several of these waveform analysis techniques were implemented on a computer and applied to dynamic signals. A laboratory evaluation of the methods with respect to signal detection capability is described. Plans for further technique evaluation and data base development to characterize turbopump incipient failure modes from Space Shuttle main engine (SSME) hot firing measurements are outlined.

STRengthening Analytical Thinking for Observational Studies: the STRATOS initiative

PubMed Central

Sauerbrei, Willi; Abrahamowicz, Michal; Altman, Douglas G; le Cessie, Saskia; Carpenter, James

2014-01-01

The validity and practical utility of observational medical research depends critically on good study design, excellent data quality, appropriate statistical methods and accurate interpretation of results. Statistical methodology has seen substantial development in recent times. Unfortunately, many of these methodological developments are ignored in practice. Consequently, design and analysis of observational studies often exhibit serious weaknesses. The lack of guidance on vital practical issues discourages many applied researchers from using more sophisticated and possibly more appropriate methods when analyzing observational studies. Furthermore, many analyses are conducted by researchers with a relatively weak statistical background and limited experience in using statistical methodology and software. Consequently, even ‘standard’ analyses reported in the medical literature are often flawed, casting doubt on their results and conclusions. An efficient way to help researchers to keep up with recent methodological developments is to develop guidance documents that are spread to the research community at large. These observations led to the initiation of the strengthening analytical thinking for observational studies (STRATOS) initiative, a large collaboration of experts in many different areas of biostatistical research. The objective of STRATOS is to provide accessible and accurate guidance in the design and analysis of observational studies. The guidance is intended for applied statisticians and other data analysts with varying levels of statistical education, experience and interests. In this article, we introduce the STRATOS initiative and its main aims, present the need for guidance documents and outline the planned approach and progress so far. We encourage other biostatisticians to become involved. PMID:25074480

In vivo evaluation of the effect of stimulus distribution on FIR statistical efficiency in event-related fMRI

PubMed Central

Jansma, J Martijn; de Zwart, Jacco A; van Gelderen, Peter; Duyn, Jeff H; Drevets, Wayne C; Furey, Maura L

2013-01-01

Technical developments in MRI have improved signal to noise, allowing use of analysis methods such as Finite impulse response (FIR) of rapid event related functional MRI (er-fMRI). FIR is one of the most informative analysis methods as it determines onset and full shape of the hemodynamic response function (HRF) without any a-priori assumptions. FIR is however vulnerable to multicollinearity, which is directly related to the distribution of stimuli over time. Efficiency can be optimized by simplifying a design, and restricting stimuli distribution to specific sequences, while more design flexibility necessarily reduces efficiency. However, the actual effect of efficiency on fMRI results has never been tested in vivo. Thus, it is currently difficult to make an informed choice between protocol flexibility and statistical efficiency. The main goal of this study was to assign concrete fMRI signal to noise values to the abstract scale of FIR statistical efficiency. Ten subjects repeated a perception task with five random and m-sequence based protocol, with varying but, according to literature, acceptable levels of multicollinearity. Results indicated substantial differences in signal standard deviation, while the level was a function of multicollinearity. Experiment protocols varied up to 55.4% in standard deviation. Results confirm that quality of fMRI in an FIR analysis can significantly and substantially vary with statistical efficiency. Our in vivo measurements can be used to aid in making an informed decision between freedom in protocol design and statistical efficiency. PMID:23473798

An intercomparison of a large ensemble of statistical downscaling methods for Europe: Overall results from the VALUE perfect predictor cross-validation experiment

NASA Astrophysics Data System (ADS)

Gutiérrez, Jose Manuel; Maraun, Douglas; Widmann, Martin; Huth, Radan; Hertig, Elke; Benestad, Rasmus; Roessler, Ole; Wibig, Joanna; Wilcke, Renate; Kotlarski, Sven

2016-04-01

VALUE is an open European network to validate and compare downscaling methods for climate change research (http://www.value-cost.eu). A key deliverable of VALUE is the development of a systematic validation framework to enable the assessment and comparison of both dynamical and statistical downscaling methods. This framework is based on a user-focused validation tree, guiding the selection of relevant validation indices and performance measures for different aspects of the validation (marginal, temporal, spatial, multi-variable). Moreover, several experiments have been designed to isolate specific points in the downscaling procedure where problems may occur (assessment of intrinsic performance, effect of errors inherited from the global models, effect of non-stationarity, etc.). The list of downscaling experiments includes 1) cross-validation with perfect predictors, 2) GCM predictors -aligned with EURO-CORDEX experiment- and 3) pseudo reality predictors (see Maraun et al. 2015, Earth's Future, 3, doi:10.1002/2014EF000259, for more details). The results of these experiments are gathered, validated and publicly distributed through the VALUE validation portal, allowing for a comprehensive community-open downscaling intercomparison study. In this contribution we describe the overall results from Experiment 1), consisting of a European wide 5-fold cross-validation (with consecutive 6-year periods from 1979 to 2008) using predictors from ERA-Interim to downscale precipitation and temperatures (minimum and maximum) over a set of 86 ECA&D stations representative of the main geographical and climatic regions in Europe. As a result of the open call for contribution to this experiment (closed in Dec. 2015), over 40 methods representative of the main approaches (MOS and Perfect Prognosis, PP) and techniques (linear scaling, quantile mapping, analogs, weather typing, linear and generalized regression, weather generators, etc.) were submitted, including information both data (downscaled values) and metadata (characterizing different aspects of the downscaling methods). This constitutes the largest and most comprehensive to date intercomparison of statistical downscaling methods. Here, we present an overall validation, analyzing marginal and temporal aspects to assess the intrinsic performance and added value of statistical downscaling methods at both annual and seasonal levels. This validation takes into account the different properties/limitations of different approaches and techniques (as reported in the provided metadata) in order to perform a fair comparison. It is pointed out that this experiment alone is not sufficient to evaluate the limitations of (MOS) bias correction techniques. Moreover, it also does not fully validate PP since we don't learn whether we have the right predictors and whether the PP assumption is valid. These problems will be analyzed in the subsequent community-open VALUE experiments 2) and 3), which will be open for participation along the present year.

A vessel segmentation method for multi-modality angiographic images based on multi-scale filtering and statistical models.

PubMed

Lu, Pei; Xia, Jun; Li, Zhicheng; Xiong, Jing; Yang, Jian; Zhou, Shoujun; Wang, Lei; Chen, Mingyang; Wang, Cheng

2016-11-08

Accurate segmentation of blood vessels plays an important role in the computer-aided diagnosis and interventional treatment of vascular diseases. The statistical method is an important component of effective vessel segmentation; however, several limitations discourage the segmentation effect, i.e., dependence of the image modality, uneven contrast media, bias field, and overlapping intensity distribution of the object and background. In addition, the mixture models of the statistical methods are constructed relaying on the characteristics of the image histograms. Thus, it is a challenging issue for the traditional methods to be available in vessel segmentation from multi-modality angiographic images. To overcome these limitations, a flexible segmentation method with a fixed mixture model has been proposed for various angiography modalities. Our method mainly consists of three parts. Firstly, multi-scale filtering algorithm was used on the original images to enhance vessels and suppress noises. As a result, the filtered data achieved a new statistical characteristic. Secondly, a mixture model formed by three probabilistic distributions (two Exponential distributions and one Gaussian distribution) was built to fit the histogram curve of the filtered data, where the expectation maximization (EM) algorithm was used for parameters estimation. Finally, three-dimensional (3D) Markov random field (MRF) were employed to improve the accuracy of pixel-wise classification and posterior probability estimation. To quantitatively evaluate the performance of the proposed method, two phantoms simulating blood vessels with different tubular structures and noises have been devised. Meanwhile, four clinical angiographic data sets from different human organs have been used to qualitatively validate the method. To further test the performance, comparison tests between the proposed method and the traditional ones have been conducted on two different brain magnetic resonance angiography (MRA) data sets. The results of the phantoms were satisfying, e.g., the noise was greatly suppressed, the percentages of the misclassified voxels, i.e., the segmentation error ratios, were no more than 0.3%, and the Dice similarity coefficients (DSCs) were above 94%. According to the opinions of clinical vascular specialists, the vessels in various data sets were extracted with high accuracy since complete vessel trees were extracted while lesser non-vessels and background were falsely classified as vessel. In the comparison experiments, the proposed method showed its superiority in accuracy and robustness for extracting vascular structures from multi-modality angiographic images with complicated background noises. The experimental results demonstrated that our proposed method was available for various angiographic data. The main reason was that the constructed mixture probability model could unitarily classify vessel object from the multi-scale filtered data of various angiography images. The advantages of the proposed method lie in the following aspects: firstly, it can extract the vessels with poor angiography quality, since the multi-scale filtering algorithm can improve the vessel intensity in the circumstance such as uneven contrast media and bias field; secondly, it performed well for extracting the vessels in multi-modality angiographic images despite various signal-noises; and thirdly, it was implemented with better accuracy, and robustness than the traditional methods. Generally, these traits declare that the proposed method would have significant clinical application.

On the design of henon and logistic map-based random number generator

NASA Astrophysics Data System (ADS)

Magfirawaty; Suryadi, M. T.; Ramli, Kalamullah

2017-10-01

The key sequence is one of the main elements in the cryptosystem. True Random Number Generators (TRNG) method is one of the approaches to generating the key sequence. The randomness source of the TRNG divided into three main groups, i.e. electrical noise based, jitter based and chaos based. The chaos based utilizes a non-linear dynamic system (continuous time or discrete time) as an entropy source. In this study, a new design of TRNG based on discrete time chaotic system is proposed, which is then simulated in LabVIEW. The principle of the design consists of combining 2D and 1D chaotic systems. A mathematical model is implemented for numerical simulations. We used comparator process as a harvester method to obtain the series of random bits. Without any post processing, the proposed design generated random bit sequence with high entropy value and passed all NIST 800.22 statistical tests.

Fractal and topological sustainable methods of overcoming expected uncertainty in the radiolocation of low-contrast targets and in the processing of weak multi-dimensional signals on the background of high-intensity noise: A new direction in the statistical decision theory

NASA Astrophysics Data System (ADS)

Potapov, A. A.

2017-11-01

The main purpose of this work is to interpret the main directions of radio physics, radio engineering and radio location in “fractal” language that makes new ways and generalizations on future promising radio systems. We introduce a new kind and approach of up-to-date radiolocation: fractal-scaling or scale-invariant radiolocation. The new topologic signs and methods of detecting the low-contrast objects against the high-intensity noise background are presented. It leads to basic changes in the theoretical radiolocation structure itself and also in its mathematical apparatus. The fractal radio systems conception, sampling topology, global fractal-scaling approach and the fractal paradigm underlie the scientific direction established by the author in Russia and all over the world for the first time ever.

Immunohistochemical assessment of Fhit protein expression in advanced gastric carcinomas in correlation with Helicobacter pylori infection and survival time.

PubMed

Czyzewska, Jolanta; Guzińska-Ustymowicz, Katarzyna; Pryczynicz, Anna; Kemona, Andrzej; Bandurski, Roman

2009-01-01

Fhit protein is known to play a role in the process of neoplastic transformation. It has been demonstrated that FHIT gene inactivation is manifested by a lack or very low concentration of Fhit protein in tissues collected from tumours in many organs, including head, neck, breast, lungs, stomach or large intestine. The study included a group of 80 patients with advanced gastric carcinomas. The expression of Fhit protein was assessed by means of the immunohistochemical method (avidin-biotin-streptavidin) in the sections fixed in formalin and embedded in paraffin, using rabbit polyclonal antiFhit antibody (Abcam, UK) at 1: 200. Statistical analysis did not show any correlation of the expression of Fhit protein in the main mass of tumour and in the metastasis to lymph node with gender, depth of wall invasion, histological differentiation, Lauren's classification, Bormann's classification, metastases to local lymph nodes or Helicobacter pylori infection. However, a strong statistical correlation was revealed of Fhit protein expression in the main mass of tumour with patients' age (p=0.04) and tumour location in the stomach (p=0.02). No relationship was found between Fhit expression in the main mass of tumour and survival time (p=0.26).

Sedimentological analysis and bed thickness statistics from a Carboniferous deep-water channel-levee complex: Myall Trough, SE Australia

NASA Astrophysics Data System (ADS)

Palozzi, Jason; Pantopoulos, George; Maravelis, Angelos G.; Nordsvan, Adam; Zelilidis, Avraam

2018-02-01

This investigation presents an outcrop-based integrated study of internal division analysis and statistical treatment of turbidite bed thickness applied to a Carboniferous deep-water channel-levee complex in the Myall Trough, southeast Australia. Turbidite beds of the studied succession are characterized by a range of sedimentary structures grouped into two main associations, a thick-bedded and a thin-bedded one, that reflect channel-fill and overbank/levee deposits, respectively. Three vertically stacked channel-levee cycles have been identified. Results of statistical analysis of bed thickness, grain-size and internal division patterns applied on the studied channel-levee succession, indicate that turbidite bed thickness data seem to be well characterized by a bimodal lognormal distribution, which is possibly reflecting the difference between deposition from lower-density flows (in a levee/overbank setting) and very high-density flows (in a channel fill setting). Power law and exponential distributions were observed to hold only for the thick-bedded parts of the succession and cannot characterize the whole bed thickness range of the studied sediments. The succession also exhibits non-random clustering of bed thickness and grain-size measurements. The studied sediments are also characterized by the presence of statistically detected fining-upward sandstone packets. A novel quantitative approach (change-point analysis) is proposed for the detection of those packets. Markov permutation statistics also revealed the existence of order in the alternation of internal divisions in the succession expressed by an optimal internal division cycle reflecting two main types of gravity flow events deposited within both thick-bedded conglomeratic and thin-bedded sandstone associations. The analytical methods presented in this study can be used as additional tools for quantitative analysis and recognition of depositional environments in hydrocarbon-bearing research of ancient deep-water channel-levee settings.

Bayesian statistics in radionuclide metrology: measurement of a decaying source

NASA Astrophysics Data System (ADS)

Bochud, François O.; Bailat, Claude J.; Laedermann, Jean-Pascal

2007-08-01

The most intuitive way of defining a probability is perhaps through the frequency at which it appears when a large number of trials are realized in identical conditions. The probability derived from the obtained histogram characterizes the so-called frequentist or conventional statistical approach. In this sense, probability is defined as a physical property of the observed system. By contrast, in Bayesian statistics, a probability is not a physical property or a directly observable quantity, but a degree of belief or an element of inference. The goal of this paper is to show how Bayesian statistics can be used in radionuclide metrology and what its advantages and disadvantages are compared with conventional statistics. This is performed through the example of an yttrium-90 source typically encountered in environmental surveillance measurement. Because of the very low activity of this kind of source and the small half-life of the radionuclide, this measurement takes several days, during which the source decays significantly. Several methods are proposed to compute simultaneously the number of unstable nuclei at a given reference time, the decay constant and the background. Asymptotically, all approaches give the same result. However, Bayesian statistics produces coherent estimates and confidence intervals in a much smaller number of measurements. Apart from the conceptual understanding of statistics, the main difficulty that could deter radionuclide metrologists from using Bayesian statistics is the complexity of the computation.

Combining statistical inference and decisions in ecology.

PubMed

Williams, Perry J; Hooten, Mevin B

2016-09-01

Statistical decision theory (SDT) is a sub-field of decision theory that formally incorporates statistical investigation into a decision-theoretic framework to account for uncertainties in a decision problem. SDT provides a unifying analysis of three types of information: statistical results from a data set, knowledge of the consequences of potential choices (i.e., loss), and prior beliefs about a system. SDT links the theoretical development of a large body of statistical methods, including point estimation, hypothesis testing, and confidence interval estimation. The theory and application of SDT have mainly been developed and published in the fields of mathematics, statistics, operations research, and other decision sciences, but have had limited exposure in ecology. Thus, we provide an introduction to SDT for ecologists and describe its utility for linking the conventionally separate tasks of statistical investigation and decision making in a single framework. We describe the basic framework of both Bayesian and frequentist SDT, its traditional use in statistics, and discuss its application to decision problems that occur in ecology. We demonstrate SDT with two types of decisions: Bayesian point estimation and an applied management problem of selecting a prescribed fire rotation for managing a grassland bird species. Central to SDT, and decision theory in general, are loss functions. Thus, we also provide basic guidance and references for constructing loss functions for an SDT problem. © 2016 by the Ecological Society of America.

Hydrometeor classification through statistical clustering of polarimetric radar measurements: a semi-supervised approach

NASA Astrophysics Data System (ADS)

Besic, Nikola; Ventura, Jordi Figueras i.; Grazioli, Jacopo; Gabella, Marco; Germann, Urs; Berne, Alexis

2016-09-01

Polarimetric radar-based hydrometeor classification is the procedure of identifying different types of hydrometeors by exploiting polarimetric radar observations. The main drawback of the existing supervised classification methods, mostly based on fuzzy logic, is a significant dependency on a presumed electromagnetic behaviour of different hydrometeor types. Namely, the results of the classification largely rely upon the quality of scattering simulations. When it comes to the unsupervised approach, it lacks the constraints related to the hydrometeor microphysics. The idea of the proposed method is to compensate for these drawbacks by combining the two approaches in a way that microphysical hypotheses can, to a degree, adjust the content of the classes obtained statistically from the observations. This is done by means of an iterative approach, performed offline, which, in a statistical framework, examines clustered representative polarimetric observations by comparing them to the presumed polarimetric properties of each hydrometeor class. Aside from comparing, a routine alters the content of clusters by encouraging further statistical clustering in case of non-identification. By merging all identified clusters, the multi-dimensional polarimetric signatures of various hydrometeor types are obtained for each of the studied representative datasets, i.e. for each radar system of interest. These are depicted by sets of centroids which are then employed in operational labelling of different hydrometeors. The method has been applied on three C-band datasets, each acquired by different operational radar from the MeteoSwiss Rad4Alp network, as well as on two X-band datasets acquired by two research mobile radars. The results are discussed through a comparative analysis which includes a corresponding supervised and unsupervised approach, emphasising the operational potential of the proposed method.

[Psychopathology of anxiety-phobic disorders that led to hospitalization in a psychiatric hospital].

PubMed

Chugunov, D A; Schmilovitch, A A

To study the psychopathology of anxiety-phobic disorders and motives of hospitalization of patients in a psychiatric hospital. One hundred and thirty-two patients were examined, 72 patients of the main group were admitted to general psychiatric departments, 60 patients of the control group in the sanatorium psychiatric departments. Clinical-psychopathological, follow-up, psychometric and statistical methods were used. Patients with hospital anxiety-phobic disorders had agoraphobia with panic disorder, social phobias, hypochondriacal phobias, specific phobias and multiple phobias. The main reasons for hospitalization were: the intensity of anxiety-phobic disorders, contrast content of phobias, multiplicity of anxiety-phobic disorders, ambulance calls, personality accentuations and rental aims.

Protein mass spectra data analysis for clinical biomarker discovery: a global review.

PubMed

Roy, Pascal; Truntzer, Caroline; Maucort-Boulch, Delphine; Jouve, Thomas; Molinari, Nicolas

2011-03-01

The identification of new diagnostic or prognostic biomarkers is one of the main aims of clinical cancer research. In recent years there has been a growing interest in using high throughput technologies for the detection of such biomarkers. In particular, mass spectrometry appears as an exciting tool with great potential. However, to extract any benefit from the massive potential of clinical proteomic studies, appropriate methods, improvement and validation are required. To better understand the key statistical points involved with such studies, this review presents the main data analysis steps of protein mass spectra data analysis, from the pre-processing of the data to the identification and validation of biomarkers.

Brain vascular image enhancement based on gradient adjust with split Bregman

NASA Astrophysics Data System (ADS)

Liang, Xiao; Dong, Di; Hui, Hui; Zhang, Liwen; Fang, Mengjie; Tian, Jie

2016-04-01

Light Sheet Microscopy is a high-resolution fluorescence microscopic technique which enables to observe the mouse brain vascular network clearly with immunostaining. However, micro-vessels are stained with few fluorescence antibodies and their signals are much weaker than large vessels, which make micro-vessels unclear in LSM images. In this work, we developed a vascular image enhancement method to enhance micro-vessel details which should be useful for vessel statistics analysis. Since gradient describes the edge information of the vessel, the main idea of our method is to increase the gradient values of the enhanced image to improve the micro-vessels contrast. Our method contained two steps: 1) calculate the gradient image of LSM image, and then amplify high gradient values of the original image to enhance the vessel edge and suppress low gradient values to remove noises. Then we formulated a new L1-norm regularization optimization problem to find an image with the expected gradient while keeping the main structure information of the original image. 2) The split Bregman iteration method was used to deal with the L1-norm regularization problem and generate the final enhanced image. The main advantage of the split Bregman method is that it has both fast convergence and low memory cost. In order to verify the effectiveness of our method, we applied our method to a series of mouse brain vascular images acquired from a commercial LSM system in our lab. The experimental results showed that our method could greatly enhance micro-vessel edges which were unclear in the original images.

Measurement of turbulent spatial structure and kinetic energy spectrum by exact temporal-to-spatial mapping

NASA Astrophysics Data System (ADS)

Buchhave, Preben; Velte, Clara M.

2017-08-01

We present a method for converting a time record of turbulent velocity measured at a point in a flow to a spatial velocity record consisting of consecutive convection elements. The spatial record allows computation of dynamic statistical moments such as turbulent kinetic wavenumber spectra and spatial structure functions in a way that completely bypasses the need for Taylor's hypothesis. The spatial statistics agree with the classical counterparts, such as the total kinetic energy spectrum, at least for spatial extents up to the Taylor microscale. The requirements for applying the method are access to the instantaneous velocity magnitude, in addition to the desired flow quantity, and a high temporal resolution in comparison to the relevant time scales of the flow. We map, without distortion and bias, notoriously difficult developing turbulent high intensity flows using three main aspects that distinguish these measurements from previous work in the field: (1) The measurements are conducted using laser Doppler anemometry and are therefore not contaminated by directional ambiguity (in contrast to, e.g., frequently employed hot-wire anemometers); (2) the measurement data are extracted using a correctly and transparently functioning processor and are analysed using methods derived from first principles to provide unbiased estimates of the velocity statistics; (3) the exact mapping proposed herein has been applied to the high turbulence intensity flows investigated to avoid the significant distortions caused by Taylor's hypothesis. The method is first confirmed to produce the correct statistics using computer simulations and later applied to measurements in some of the most difficult regions of a round turbulent jet—the non-equilibrium developing region and the outermost parts of the developed jet. The proposed mapping is successfully validated using corresponding directly measured spatial statistics in the fully developed jet, even in the difficult outer regions of the jet where the average convection velocity is negligible and turbulence intensities increase dramatically. The measurements in the developing region reveal interesting features of an incomplete Richardson-Kolmogorov cascade under development.

The Kepler Mission: Search for Habitable Planets

NASA Technical Reports Server (NTRS)

Borucki, William; Likins, B.; DeVincenzi, Donald L. (Technical Monitor)

1998-01-01

Detecting extrasolar terrestrial planets orbiting main-sequence stars is of great interest and importance. Current ground-based methods are only capable of detecting objects about the size or mass of Jupiter or larger. The difficulties encountered with direct imaging of Earth-size planets from space are expected to be resolved in the next twenty years. Spacebased photometry of planetary transits is currently the only viable method for detection of terrestrial planets (30-600 times less massive than Jupiter). This method searches the extended solar neighborhood, providing a statistically large sample and the detailed characteristics of each individual case. A robust concept has been developed and proposed as a Discovery-class mission. Its capabilities and strengths are presented.

Accurate mass measurement: terminology and treatment of data.

PubMed

Brenton, A Gareth; Godfrey, A Ruth

2010-11-01

High-resolution mass spectrometry has become ever more accessible with improvements in instrumentation, such as modern FT-ICR and Orbitrap mass spectrometers. This has resulted in an increase in the number of articles submitted for publication quoting accurate mass data. There is a plethora of terms related to accurate mass analysis that are in current usage, many employed incorrectly or inconsistently. This article is based on a set of notes prepared by the authors for research students and staff in our laboratories as a guide to the correct terminology and basic statistical procedures to apply in relation to mass measurement, particularly for accurate mass measurement. It elaborates on the editorial by Gross in 1994 regarding the use of accurate masses for structure confirmation. We have presented and defined the main terms in use with reference to the International Union of Pure and Applied Chemistry (IUPAC) recommendations for nomenclature and symbolism for mass spectrometry. The correct use of statistics and treatment of data is illustrated as a guide to new and existing mass spectrometry users with a series of examples as well as statistical methods to compare different experimental methods and datasets. Copyright © 2010. Published by Elsevier Inc.

Plackett-Burman experimental design to facilitate syntactic foam development

DOE PAGES

Smith, Zachary D.; Keller, Jennie R.; Bello, Mollie; ...

2015-09-14

The use of an eight-experiment Plackett–Burman method can assess six experimental variables and eight responses in a polysiloxane-glass microsphere syntactic foam. The approach aims to decrease the time required to develop a tunable polymer composite by identifying a reduced set of variables and responses suitable for future predictive modeling. The statistical design assesses the main effects of mixing process parameters, polymer matrix composition, microsphere density and volume loading, and the blending of two grades of microspheres, using a dummy factor in statistical calculations. Responses cover rheological, physical, thermal, and mechanical properties. The cure accelerator content of the polymer matrix andmore » the volume loading of the microspheres have the largest effects on foam properties. These factors are the most suitable for controlling the gel point of the curing foam, and the density of the cured foam. The mixing parameters introduce widespread variability and therefore should be fixed at effective levels during follow-up testing. Some responses may require greater contrast in microsphere-related factors. As a result, compared to other possible statistical approaches, the run economy of the Plackett–Burman method makes it a valuable tool for rapidly characterizing new foams.« less

Identification of robust statistical downscaling methods based on a comprehensive suite of performance metrics for South Korea

NASA Astrophysics Data System (ADS)

Eum, H. I.; Cannon, A. J.

2015-12-01

Climate models are a key provider to investigate impacts of projected future climate conditions on regional hydrologic systems. However, there is a considerable mismatch of spatial resolution between GCMs and regional applications, in particular a region characterized by complex terrain such as Korean peninsula. Therefore, a downscaling procedure is an essential to assess regional impacts of climate change. Numerous statistical downscaling methods have been used mainly due to the computational efficiency and simplicity. In this study, four statistical downscaling methods [Bias-Correction/Spatial Disaggregation (BCSD), Bias-Correction/Constructed Analogue (BCCA), Multivariate Adaptive Constructed Analogs (MACA), and Bias-Correction/Climate Imprint (BCCI)] are applied to downscale the latest Climate Forecast System Reanalysis data to stations for precipitation, maximum temperature, and minimum temperature over South Korea. By split sampling scheme, all methods are calibrated with observational station data for 19 years from 1973 to 1991 are and tested for the recent 19 years from 1992 to 2010. To assess skill of the downscaling methods, we construct a comprehensive suite of performance metrics that measure an ability of reproducing temporal correlation, distribution, spatial correlation, and extreme events. In addition, we employ Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to identify robust statistical downscaling methods based on the performance metrics for each season. The results show that downscaling skill is considerably affected by the skill of CFSR and all methods lead to large improvements in representing all performance metrics. According to seasonal performance metrics evaluated, when TOPSIS is applied, MACA is identified as the most reliable and robust method for all variables and seasons. Note that such result is derived from CFSR output which is recognized as near perfect climate data in climate studies. Therefore, the ranking of this study may be changed when various GCMs are downscaled and evaluated. Nevertheless, it may be informative for end-users (i.e. modelers or water resources managers) to understand and select more suitable downscaling methods corresponding to priorities on regional applications.

Size Matters: What Are the Characteristic Source Areas for Urban Planning Strategies?

PubMed Central

Fan, Chao; Myint, Soe W.; Wang, Chenghao

2016-01-01

Urban environmental measurements and observational statistics should reflect the properties generated over an adjacent area of adequate length where homogeneity is usually assumed. The determination of this characteristic source area that gives sufficient representation of the horizontal coverage of a sensing instrument or the fetch of transported quantities is of critical importance to guide the design and implementation of urban landscape planning strategies. In this study, we aim to unify two different methods for estimating source areas, viz. the statistical correlation method commonly used by geographers for landscape fragmentation and the mechanistic footprint model by meteorologists for atmospheric measurements. Good agreement was found in the intercomparison of the estimate of source areas by the two methods, based on 2-m air temperature measurement collected using a network of weather stations. The results can be extended to shed new lights on urban planning strategies, such as the use of urban vegetation for heat mitigation. In general, a sizable patch of landscape is required in order to play an effective role in regulating the local environment, proportional to the height at which stakeholders’ interest is mainly concerned. PMID:27832111

Transport of nitrogen oxides, carbon monoxide and ozone to the Alpine Global Atmosphere Watch stations Jungfraujoch (Switzerland), Zugspitze and Hohenpeissenberg (Germany), Sonnblick (Austria) and Mt. Krvavec (Slovenia)

NASA Astrophysics Data System (ADS)

Kaiser, August; Scheifinger, Helfried; Spangl, Wolfgang; Weiss, Andrea; Gilge, Stefan; Fricke, Wolfgang; Ries, Ludwig; Cemas, Danijel; Jesenovec, Brigita

The Alpine stations Zugspitze, Hohenpeissenberg, Sonnblick, Jungfraujoch and Mt. Krvavec contribute to the Global Atmosphere Watch Programme (GAW) of the World Meteorological Organization (WMO). The aim of GAW is the surveillance of the large-scale chemical composition of the atmosphere. Thus, the detection of air pollutant transport from regional sources is of particular interest. In this paper, the origin of NO x (measured with a photo-converter), CO and O 3 at the four Alpine GAW stations is studied by trajectory residence time statistics. Although these methods originated during the early 1980s, no comprehensive study of different atmospheric trace gases measured simultaneously at several background observatories in the Alps was conducted up to present. The main NO x source regions detected by the trajectory statistics are the northwest of Europe and the region covering East Germany, Czech Republic and southeast Poland, whereas the main CO source areas are the central, north eastern and eastern parts of Europe with some gradient from low to high latitudes. Subsiding air masses from west and southwest are relatively poor in NO x and CO. The statistics for ozone show strong seasonal effects. Near ground air masses are poor in ozone in winter but rich in ozone in summer. The main source for high ozone concentration in winter is air masses that subside from higher elevations, often enhanced by foehn effects at Hohenpeissenberg. During summer, the Mediterranean constitutes an important additional source for high ozone concentrations. Especially during winter, large differences between Hohenpeissenberg and the higher elevated stations are found. Hohenpeissenberg is frequently within the inversion, whereas the higher elevated stations are above the inversion. Jungfraujoch is the only station where the statistics detect an influence of air rich in CO and NO x from the Po Basin.

Interactive educational technologies as a method of communicative competency development of optical and fiber optic communication systems specialists

NASA Astrophysics Data System (ADS)

Matveeva, Tatiana U.; Osadchiy, Igor S.; Husnutdinova, Marina N.

2017-04-01

The article examines the process of formation of communicative competencies of optic and fiber optic communication systems specialists; the role of communicative competencies is examined in the structure of professionally important skills, together with the contents of professional activity. The stages of empirical research into formation of communicative competencies have been presented, and the values of statistical reliability of data have been provided. The model of formation of communicative competency using interactive technology has been developed based on the research done, and main stages of model implementation and motives of formation of communicative competency have been highlighted. A scheme of "Communicative competence as a base of future success" training session has been suggested as one of the basic interactive technologies. Main components of education that are used during the stages of the training cycle have been examined. The statistical data on the effectiveness of use of interactive educational technologies has been presented; it allowed development of communicative competency of specialists in the field of optical and fiber optic communication system.

Evaluation of Anomaly Detection Method Based on Pattern Recognition

NASA Astrophysics Data System (ADS)

Fontugne, Romain; Himura, Yosuke; Fukuda, Kensuke

The number of threats on the Internet is rapidly increasing, and anomaly detection has become of increasing importance. High-speed backbone traffic is particularly degraded, but their analysis is a complicated task due to the amount of data, the lack of payload data, the asymmetric routing and the use of sampling techniques. Most anomaly detection schemes focus on the statistical properties of network traffic and highlight anomalous traffic through their singularities. In this paper, we concentrate on unusual traffic distributions, which are easily identifiable in temporal-spatial space (e.g., time/address or port). We present an anomaly detection method that uses a pattern recognition technique to identify anomalies in pictures representing traffic. The main advantage of this method is its ability to detect attacks involving mice flows. We evaluate the parameter set and the effectiveness of this approach by analyzing six years of Internet traffic collected from a trans-Pacific link. We show several examples of detected anomalies and compare our results with those of two other methods. The comparison indicates that the only anomalies detected by the pattern-recognition-based method are mainly malicious traffic with a few packets.

A risk assessment methodology using intuitionistic fuzzy set in FMEA

NASA Astrophysics Data System (ADS)

Chang, Kuei-Hu; Cheng, Ching-Hsue

2010-12-01

Most current risk assessment methods use the risk priority number (RPN) value to evaluate the risk of failure. However, conventional RPN methodology has been criticised as having five main shortcomings as follows: (1) the assumption that the RPN elements are equally weighted leads to over simplification; (2) the RPN scale itself has some non-intuitive statistical properties; (3) the RPN elements have many duplicate numbers; (4) the RPN is derived from only three factors mainly in terms of safety; and (5) the conventional RPN method has not considered indirect relations between components. To address the above issues, an efficient and comprehensive algorithm to evaluate the risk of failure is needed. This article proposes an innovative approach, which integrates the intuitionistic fuzzy set (IFS) and the decision-making trial and evaluation laboratory (DEMATEL) approach on risk assessment. The proposed approach resolves some of the shortcomings of the conventional RPN method. A case study, which assesses the risk of 0.15 µm DRAM etching process, is used to demonstrate the effectiveness of the proposed approach. Finally, the result of the proposed method is compared with the listing approaches of risk assessment methods.

Effect of numbers vs pictures on perceived effectiveness of a public safety awareness advertisement.

PubMed

Bochniak, S; Lammers, H B

1991-08-01

In a 2 x 2 completely randomized factorial experiment, 24 women and 16 men rated the perceived effectiveness of an earthquake preparedness advertisement which contained either a picture or no picture of prior earthquake damage and contained either statistics or no statistics on likelihood of an earthquake. A main effect for superiority of the picture was found. The presence of statistics had no main or interactive effects on the perceived effectiveness of the advertisement.

Evaluation of dissolution profile similarity - Comparison between the f2, the multivariate statistical distance and the f2 bootstrapping methods.

PubMed

Paixão, Paulo; Gouveia, Luís F; Silva, Nuno; Morais, José A G

2017-03-01

A simulation study is presented, evaluating the performance of the f 2 , the model-independent multivariate statistical distance and the f 2 bootstrap methods in the ability to conclude similarity between two dissolution profiles. Different dissolution profiles, based on the Noyes-Whitney equation and ranging from theoretical f 2 values between 100 and 40, were simulated. Variability was introduced in the dissolution model parameters in an increasing order, ranging from a situation complying with the European guidelines requirements for the use of the f 2 metric to several situations where the f 2 metric could not be used anymore. Results have shown that the f 2 is an acceptable metric when used according to the regulatory requirements, but loses its applicability when variability increases. The multivariate statistical distance presented contradictory results in several of the simulation scenarios, which makes it an unreliable metric for dissolution profile comparisons. The bootstrap f 2 , although conservative in its conclusions is an alternative suitable method. Overall, as variability increases, all of the discussed methods reveal problems that can only be solved by increasing the number of dosage form units used in the comparison, which is usually not practical or feasible. Additionally, experimental corrective measures may be undertaken in order to reduce the overall variability, particularly when it is shown that it is mainly due to the dissolution assessment instead of being intrinsic to the dosage form. Copyright © 2016. Published by Elsevier B.V.

Student's Conceptions in Statistical Graph's Interpretation

ERIC Educational Resources Information Center

Kukliansky, Ida

2016-01-01

Histograms, box plots and cumulative distribution graphs are popular graphic representations for statistical distributions. The main research question that this study focuses on is how college students deal with interpretation of these statistical graphs when translating graphical representations into analytical concepts in descriptive statistics.…

Evaluation of redundancy analysis to identify signatures of local adaptation.

PubMed

Capblancq, Thibaut; Luu, Keurcien; Blum, Michael G B; Bazin, Eric

2018-05-26

Ordination is a common tool in ecology that aims at representing complex biological information in a reduced space. In landscape genetics, ordination methods such as principal component analysis (PCA) have been used to detect adaptive variation based on genomic data. Taking advantage of environmental data in addition to genotype data, redundancy analysis (RDA) is another ordination approach that is useful to detect adaptive variation. This paper aims at proposing a test statistic based on RDA to search for loci under selection. We compare redundancy analysis to pcadapt, which is a nonconstrained ordination method, and to a latent factor mixed model (LFMM), which is a univariate genotype-environment association method. Individual-based simulations identify evolutionary scenarios where RDA genome scans have a greater statistical power than genome scans based on PCA. By constraining the analysis with environmental variables, RDA performs better than PCA in identifying adaptive variation when selection gradients are weakly correlated with population structure. Additionally, we show that if RDA and LFMM have a similar power to identify genetic markers associated with environmental variables, the RDA-based procedure has the advantage to identify the main selective gradients as a combination of environmental variables. To give a concrete illustration of RDA in population genomics, we apply this method to the detection of outliers and selective gradients on an SNP data set of Populus trichocarpa (Geraldes et al., 2013). The RDA-based approach identifies the main selective gradient contrasting southern and coastal populations to northern and continental populations in the northwestern American coast. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Exploring and accounting for publication bias in mental health: a brief overview of methods.

PubMed

Mavridis, Dimitris; Salanti, Georgia

2014-02-01

OBJECTIVE Publication bias undermines the integrity of published research. The aim of this paper is to present a synopsis of methods for exploring and accounting for publication bias. METHODS We discussed the main features of the following methods to assess publication bias: funnel plot analysis; trim-and-fill methods; regression techniques and selection models. We applied these methods to a well-known example of antidepressants trials that compared trials submitted to the Food and Drug Administration (FDA) for regulatory approval. RESULTS The funnel plot-related methods (visual inspection, trim-and-fill, regression models) revealed an association between effect size and SE. Contours of statistical significance showed that asymmetry in the funnel plot is probably due to publication bias. Selection model found a significant correlation between effect size and propensity for publication. CONCLUSIONS Researchers should always consider the possible impact of publication bias. Funnel plot-related methods should be seen as a means of examining for small-study effects and not be directly equated with publication bias. Possible causes for funnel plot asymmetry should be explored. Contours of statistical significance may help disentangle whether asymmetry in a funnel plot is caused by publication bias or not. Selection models, although underused, could be useful resource when publication bias and heterogeneity are suspected because they address directly the problem of publication bias and not that of small-study effects.

Evaluating the statistical methodology of randomized trials on dentin hypersensitivity management.

PubMed

Matranga, Domenica; Matera, Federico; Pizzo, Giuseppe

2017-12-27

The present study aimed to evaluate the characteristics and quality of statistical methodology used in clinical studies on dentin hypersensitivity management. An electronic search was performed for data published from 2009 to 2014 by using PubMed, Ovid/MEDLINE, and Cochrane Library databases. The primary search terms were used in combination. Eligibility criteria included randomized clinical trials that evaluated the efficacy of desensitizing agents in terms of reducing dentin hypersensitivity. A total of 40 studies were considered eligible for assessment of quality statistical methodology. The four main concerns identified were i) use of nonparametric tests in the presence of large samples, coupled with lack of information about normality and equality of variances of the response; ii) lack of P-value adjustment for multiple comparisons; iii) failure to account for interactions between treatment and follow-up time; and iv) no information about the number of teeth examined per patient and the consequent lack of cluster-specific approach in data analysis. Owing to these concerns, statistical methodology was judged as inappropriate in 77.1% of the 35 studies that used parametric methods. Additional studies with appropriate statistical analysis are required to obtain appropriate assessment of the efficacy of desensitizing agents.

Statistical alignment: computational properties, homology testing and goodness-of-fit.

PubMed

Hein, J; Wiuf, C; Knudsen, B; Møller, M B; Wibling, G

2000-09-08

The model of insertions and deletions in biological sequences, first formulated by Thorne, Kishino, and Felsenstein in 1991 (the TKF91 model), provides a basis for performing alignment within a statistical framework. Here we investigate this model.Firstly, we show how to accelerate the statistical alignment algorithms several orders of magnitude. The main innovations are to confine likelihood calculations to a band close to the similarity based alignment, to get good initial guesses of the evolutionary parameters and to apply an efficient numerical optimisation algorithm for finding the maximum likelihood estimate. In addition, the recursions originally presented by Thorne, Kishino and Felsenstein can be simplified. Two proteins, about 1500 amino acids long, can be analysed with this method in less than five seconds on a fast desktop computer, which makes this method practical for actual data analysis.Secondly, we propose a new homology test based on this model, where homology means that an ancestor to a sequence pair can be found finitely far back in time. This test has statistical advantages relative to the traditional shuffle test for proteins.Finally, we describe a goodness-of-fit test, that allows testing the proposed insertion-deletion (indel) process inherent to this model and find that real sequences (here globins) probably experience indels longer than one, contrary to what is assumed by the model. Copyright 2000 Academic Press.

Directions for new developments on statistical design and analysis of small population group trials.

PubMed

Hilgers, Ralf-Dieter; Roes, Kit; Stallard, Nigel

2016-06-14

Most statistical design and analysis methods for clinical trials have been developed and evaluated where at least several hundreds of patients could be recruited. These methods may not be suitable to evaluate therapies if the sample size is unavoidably small, which is usually termed by small populations. The specific sample size cut off, where the standard methods fail, needs to be investigated. In this paper, the authors present their view on new developments for design and analysis of clinical trials in small population groups, where conventional statistical methods may be inappropriate, e.g., because of lack of power or poor adherence to asymptotic approximations due to sample size restrictions. Following the EMA/CHMP guideline on clinical trials in small populations, we consider directions for new developments in the area of statistical methodology for design and analysis of small population clinical trials. We relate the findings to the research activities of three projects, Asterix, IDeAl, and InSPiRe, which have received funding since 2013 within the FP7-HEALTH-2013-INNOVATION-1 framework of the EU. As not all aspects of the wide research area of small population clinical trials can be addressed, we focus on areas where we feel advances are needed and feasible. The general framework of the EMA/CHMP guideline on small population clinical trials stimulates a number of research areas. These serve as the basis for the three projects, Asterix, IDeAl, and InSPiRe, which use various approaches to develop new statistical methodology for design and analysis of small population clinical trials. Small population clinical trials refer to trials with a limited number of patients. Small populations may result form rare diseases or specific subtypes of more common diseases. New statistical methodology needs to be tailored to these specific situations. The main results from the three projects will constitute a useful toolbox for improved design and analysis of small population clinical trials. They address various challenges presented by the EMA/CHMP guideline as well as recent discussions about extrapolation. There is a need for involvement of the patients' perspective in the planning and conduct of small population clinical trials for a successful therapy evaluation.

Using spatial analysis to demonstrate the heterogeneity of the cardiovascular drug-prescribing pattern in Taiwan

PubMed Central

2011-01-01

Background Geographic Information Systems (GIS) combined with spatial analytical methods could be helpful in examining patterns of drug use. Little attention has been paid to geographic variation of cardiovascular prescription use in Taiwan. The main objective was to use local spatial association statistics to test whether or not the cardiovascular medication-prescribing pattern is homogenous across 352 townships in Taiwan. Methods The statistical methods used were the global measures of Moran's I and Local Indicators of Spatial Association (LISA). While Moran's I provides information on the overall spatial distribution of the data, LISA provides information on types of spatial association at the local level. LISA statistics can also be used to identify influential locations in spatial association analysis. The major classes of prescription cardiovascular drugs were taken from Taiwan's National Health Insurance Research Database (NHIRD), which has a coverage rate of over 97%. The dosage of each prescription was converted into defined daily doses to measure the consumption of each class of drugs. Data were analyzed with ArcGIS and GeoDa at the township level. Results The LISA statistics showed an unusual use of cardiovascular medications in the southern townships with high local variation. Patterns of drug use also showed more low-low spatial clusters (cold spots) than high-high spatial clusters (hot spots), and those low-low associations were clustered in the rural areas. Conclusions The cardiovascular drug prescribing patterns were heterogeneous across Taiwan. In particular, a clear pattern of north-south disparity exists. Such spatial clustering helps prioritize the target areas that require better education concerning drug use. PMID:21609462

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.

A fast exact simulation method for a class of Markov jump processes.

PubMed

Li, Yao; Hu, Lili

2015-11-14

A new method of the stochastic simulation algorithm (SSA), named the Hashing-Leaping method (HLM), for exact simulations of a class of Markov jump processes, is presented in this paper. The HLM has a conditional constant computational cost per event, which is independent of the number of exponential clocks in the Markov process. The main idea of the HLM is to repeatedly implement a hash-table-like bucket sort algorithm for all times of occurrence covered by a time step with length τ. This paper serves as an introduction to this new SSA method. We introduce the method, demonstrate its implementation, analyze its properties, and compare its performance with three other commonly used SSA methods in four examples. Our performance tests and CPU operation statistics show certain advantages of the HLM for large scale problems.

A Discriminative Sentence Compression Method as Combinatorial Optimization Problem

NASA Astrophysics Data System (ADS)

Hirao, Tsutomu; Suzuki, Jun; Isozaki, Hideki

In the study of automatic summarization, the main research topic was `important sentence extraction' but nowadays `sentence compression' is a hot research topic. Conventional sentence compression methods usually transform a given sentence into a parse tree or a dependency tree, and modify them to get a shorter sentence. However, this method is sometimes too rigid. In this paper, we regard sentence compression as an combinatorial optimization problem that extracts an optimal subsequence of words. Hori et al. also proposed a similar method, but they used only a small number of features and their weights were tuned by hand. We introduce a large number of features such as part-of-speech bigrams and word position in the sentence. Furthermore, we train the system by discriminative learning. According to our experiments, our method obtained better score than other methods with statistical significance.

Yarkovsky effect and V-shapes: New method to compute family ages

NASA Astrophysics Data System (ADS)

Spoto, F.; Milani, A.; Cellino, A.; Knezevic, Z.; Novakovic, B.; Paolicchi, P.

2014-07-01

The computation of family ages is a high-priority goal. As a matter of principle, it can be achieved by using V-shape plots for the families old enough to have the Yarkovsky effect dominating the spread of the proper a and large enough for a statistically significant analysis of the shape. By performing an asteroid family classification with a very enlarged dataset, the results are not just ''more families'', but there are interesting qualitative changes. These are due to the large-number statistics, but also to the larger fraction of smaller objects contained in recently numbered asteroids. We are convinced that our method is effective in adding many smaller asteroids to the core families. As a result, we have a large number of families with very well defined V-shapes, thus with a good possibility of age estimation. We have developed our method to compute ages, which we believe is better than those used previously because it is more objective. Since there are no models for error in absolute magnitude H and for albedo, we have also developed a model of the error in the inverse of the diameter and then we have performed a weighted least-squares fit. We report at least 5/6 examples of dynamical families for which the computation of the V-shape is possible. These examples show the presence of different internal structure of the families, e.g., in the dynamical family of (4) Vesta, we have found two collisional families. The main problem in estimating the ages is the calibration. The difficulty in the Yarkovsky calibration, due to the need to extrapolate from near-Earth asteroids (NEAs) with measured da/dt to main-belt asteroids, is in most cases the main limitation to the accuracy of the age estimation. We obtain an age estimation by scaling the results for the NEA for which there is the best Yarkovsky effect determination, namely (101955) Bennu.

Citizen surveillance for environmental monitoring: combining the efforts of citizen science and crowdsourcing in a quantitative data framework.

PubMed

Welvaert, Marijke; Caley, Peter

2016-01-01

Citizen science and crowdsourcing have been emerging as methods to collect data for surveillance and/or monitoring activities. They could be gathered under the overarching term citizen surveillance . The discipline, however, still struggles to be widely accepted in the scientific community, mainly because these activities are not embedded in a quantitative framework. This results in an ongoing discussion on how to analyze and make useful inference from these data. When considering the data collection process, we illustrate how citizen surveillance can be classified according to the nature of the underlying observation process measured in two dimensions-the degree of observer reporting intention and the control in observer detection effort. By classifying the observation process in these dimensions we distinguish between crowdsourcing, unstructured citizen science and structured citizen science. This classification helps the determine data processing and statistical treatment of these data for making inference. Using our framework, it is apparent that published studies are overwhelmingly associated with structured citizen science, and there are well developed statistical methods for the resulting data. In contrast, methods for making useful inference from purely crowd-sourced data remain under development, with the challenges of accounting for the unknown observation process considerable. Our quantitative framework for citizen surveillance calls for an integration of citizen science and crowdsourcing and provides a way forward to solve the statistical challenges inherent to citizen-sourced data.

Statistical multi-path exposure method for assessing the whole-body SAR in a heterogeneous human body model in a realistic environment.

PubMed

Vermeeren, Günter; Joseph, Wout; Martens, Luc

2013-04-01

Assessing the whole-body absorption in a human in a realistic environment requires a statistical approach covering all possible exposure situations. This article describes the development of a statistical multi-path exposure method for heterogeneous realistic human body models. The method is applied for the 6-year-old Virtual Family boy (VFB) exposed to the GSM downlink at 950 MHz. It is shown that the whole-body SAR does not differ significantly over the different environments at an operating frequency of 950 MHz. Furthermore, the whole-body SAR in the VFB for multi-path exposure exceeds the whole-body SAR for worst-case single-incident plane wave exposure by 3.6%. Moreover, the ICNIRP reference levels are not conservative with the basic restrictions in 0.3% of the exposure samples for the VFB at the GSM downlink of 950 MHz. The homogeneous spheroid with the dielectric properties of the head suggested by the IEC underestimates the absorption compared to realistic human body models. Moreover, the variation in the whole-body SAR for realistic human body models is larger than for homogeneous spheroid models. This is mainly due to the heterogeneity of the tissues and the irregular shape of the realistic human body model compared to homogeneous spheroid human body models. Copyright © 2012 Wiley Periodicals, Inc.

A survey and evaluations of histogram-based statistics in alignment-free sequence comparison.

PubMed

Luczak, Brian B; James, Benjamin T; Girgis, Hani Z

2017-12-06

Since the dawn of the bioinformatics field, sequence alignment scores have been the main method for comparing sequences. However, alignment algorithms are quadratic, requiring long execution time. As alternatives, scientists have developed tens of alignment-free statistics for measuring the similarity between two sequences. We surveyed tens of alignment-free k-mer statistics. Additionally, we evaluated 33 statistics and multiplicative combinations between the statistics and/or their squares. These statistics are calculated on two k-mer histograms representing two sequences. Our evaluations using global alignment scores revealed that the majority of the statistics are sensitive and capable of finding similar sequences to a query sequence. Therefore, any of these statistics can filter out dissimilar sequences quickly. Further, we observed that multiplicative combinations of the statistics are highly correlated with the identity score. Furthermore, combinations involving sequence length difference or Earth Mover's distance, which takes the length difference into account, are always among the highest correlated paired statistics with identity scores. Similarly, paired statistics including length difference or Earth Mover's distance are among the best performers in finding the K-closest sequences. Interestingly, similar performance can be obtained using histograms of shorter words, resulting in reducing the memory requirement and increasing the speed remarkably. Moreover, we found that simple single statistics are sufficient for processing next-generation sequencing reads and for applications relying on local alignment. Finally, we measured the time requirement of each statistic. The survey and the evaluations will help scientists with identifying efficient alternatives to the costly alignment algorithm, saving thousands of computational hours. The source code of the benchmarking tool is available as Supplementary Materials. © The Author 2017. Published by Oxford University Press.

Methods for detecting, quantifying, and adjusting for dissemination bias in meta-analysis are described.

PubMed

Mueller, Katharina Felicitas; Meerpohl, Joerg J; Briel, Matthias; Antes, Gerd; von Elm, Erik; Lang, Britta; Motschall, Edith; Schwarzer, Guido; Bassler, Dirk

2016-12-01

To systematically review methodological articles which focus on nonpublication of studies and to describe methods of detecting and/or quantifying and/or adjusting for dissemination in meta-analyses. To evaluate whether the methods have been applied to an empirical data set for which one can be reasonably confident that all studies conducted have been included. We systematically searched Medline, the Cochrane Library, and Web of Science, for methodological articles that describe at least one method of detecting and/or quantifying and/or adjusting for dissemination bias in meta-analyses. The literature search retrieved 2,224 records, of which we finally included 150 full-text articles. A great variety of methods to detect, quantify, or adjust for dissemination bias were described. Methods included graphical methods mainly based on funnel plot approaches, statistical methods, such as regression tests, selection models, sensitivity analyses, and a great number of more recent statistical approaches. Only few methods have been validated in empirical evaluations using unpublished studies obtained from regulators (Food and Drug Administration, European Medicines Agency). We present an overview of existing methods to detect, quantify, or adjust for dissemination bias. It remains difficult to advise which method should be used as they are all limited and their validity has rarely been assessed. Therefore, a thorough literature search remains crucial in systematic reviews, and further steps to increase the availability of all research results need to be taken. Copyright © 2016 Elsevier Inc. All rights reserved.

Classification and statistical analysis of mine spoils chemical composition from Oliete basin (Teruel, NE Spain)

NASA Astrophysics Data System (ADS)

Meseguer, S.; Sanfeliu, T.; Jordán, M. M.

2009-02-01

The Oliete basin (Early Cretaceous, NE Teruel, Spain) is one of the most important areas for the supply of mine spoils used as ball clays for the production of white and red stoneware in the Spanish ceramic industry of wall and floor tiles. This study corresponds to the second part of the paper published recently by Meseguer et al. (Environ Geol 2008) about the use of mine spoils from Teruel coal mining district. The present study shows a statistical data analysis from chemical data (major, minor and trace elements). The performed statistical analysis of chemical data included descriptive statistics and cluster analysis (with ANOVA and Scheffé methods). The cluster analysis of chemical data provided three main groups: C3 with the highest mean SiO2 content (66%) and lowest mean Al2O3 content (20%); C2 with lower SiO2 content (48%) and higher mean Al2O3 content (28%); and C1 with medium values for the SiO2 and Al2O3 mean content. The main applications of these materials are refractory, white and red ceramics, stoneware, heavy ceramics (including red earthenware, bricks and roof tiles), and components of white Portland cement and aluminous cement. Clays from group 2 are used in refractories (with higher kaolinite content, and constrictions to CaO + MgO and K2O + Na2O contents). All materials can be used in fine ceramics (white or red, according to the Fe2O3 + TiO2 content).

The statistical evaluation and comparison of ADMS-Urban model for the prediction of nitrogen dioxide with air quality monitoring network.

PubMed

Dėdelė, Audrius; Miškinytė, Auksė

2015-09-01

In many countries, road traffic is one of the main sources of air pollution associated with adverse effects on human health and environment. Nitrogen dioxide (NO2) is considered to be a measure of traffic-related air pollution, with concentrations tending to be higher near highways, along busy roads, and in the city centers, and the exceedances are mainly observed at measurement stations located close to traffic. In order to assess the air quality in the city and the air pollution impact on public health, air quality models are used. However, firstly, before the model can be used for these purposes, it is important to evaluate the accuracy of the dispersion modelling as one of the most widely used method. The monitoring and dispersion modelling are two components of air quality monitoring system (AQMS), in which statistical comparison was made in this research. The evaluation of the Atmospheric Dispersion Modelling System (ADMS-Urban) was made by comparing monthly modelled NO2 concentrations with the data of continuous air quality monitoring stations in Kaunas city. The statistical measures of model performance were calculated for annual and monthly concentrations of NO2 for each monitoring station site. The spatial analysis was made using geographic information systems (GIS). The calculation of statistical parameters indicated a good ADMS-Urban model performance for the prediction of NO2. The results of this study showed that the agreement of modelled values and observations was better for traffic monitoring stations compared to the background and residential stations.

Reliable clarity automatic-evaluation method for optical remote sensing images

NASA Astrophysics Data System (ADS)

Qin, Bangyong; Shang, Ren; Li, Shengyang; Hei, Baoqin; Liu, Zhiwen

2015-10-01

Image clarity, which reflects the sharpness degree at the edge of objects in images, is an important quality evaluate index for optical remote sensing images. Scholars at home and abroad have done a lot of work on estimation of image clarity. At present, common clarity-estimation methods for digital images mainly include frequency-domain function methods, statistical parametric methods, gradient function methods and edge acutance methods. Frequency-domain function method is an accurate clarity-measure approach. However, its calculation process is complicate and cannot be carried out automatically. Statistical parametric methods and gradient function methods are both sensitive to clarity of images, while their results are easy to be affected by the complex degree of images. Edge acutance method is an effective approach for clarity estimate, while it needs picking out the edges manually. Due to the limits in accuracy, consistent or automation, these existing methods are not applicable to quality evaluation of optical remote sensing images. In this article, a new clarity-evaluation method, which is based on the principle of edge acutance algorithm, is proposed. In the new method, edge detection algorithm and gradient search algorithm are adopted to automatically search the object edges in images. Moreover, The calculation algorithm for edge sharpness has been improved. The new method has been tested with several groups of optical remote sensing images. Compared with the existing automatic evaluation methods, the new method perform better both in accuracy and consistency. Thus, the new method is an effective clarity evaluation method for optical remote sensing images.

Planck 2015 results. XVI. Isotropy and statistics of the CMB

NASA Astrophysics Data System (ADS)

Planck Collaboration; Ade, P. A. R.; Aghanim, N.; Akrami, Y.; Aluri, P. K.; Arnaud, M.; Ashdown, M.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Bartolo, N.; Basak, S.; Battaner, E.; Benabed, K.; Benoît, A.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bock, J. J.; Bonaldi, A.; Bonavera, L.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Boulanger, F.; Bucher, M.; Burigana, C.; Butler, R. C.; Calabrese, E.; Cardoso, J.-F.; Casaponsa, B.; Catalano, A.; Challinor, A.; Chamballu, A.; Chiang, H. C.; Christensen, P. R.; Church, S.; Clements, D. L.; Colombi, S.; Colombo, L. P. L.; Combet, C.; Contreras, D.; Couchot, F.; Coulais, A.; Crill, B. P.; Cruz, M.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R. D.; Davis, R. J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Désert, F.-X.; Diego, J. M.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Ducout, A.; Dupac, X.; Efstathiou, G.; Elsner, F.; Enßlin, T. A.; Eriksen, H. K.; Fantaye, Y.; Fergusson, J.; Fernandez-Cobos, R.; Finelli, F.; Forni, O.; Frailis, M.; Fraisse, A. A.; Franceschi, E.; Frejsel, A.; Frolov, A.; Galeotta, S.; Galli, S.; Ganga, K.; Gauthier, C.; Ghosh, T.; Giard, M.; Giraud-Héraud, Y.; Gjerløw, E.; González-Nuevo, J.; Górski, K. M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Gudmundsson, J. E.; Hansen, F. K.; Hanson, D.; Harrison, D. L.; Henrot-Versillé, S.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huang, Z.; Huffenberger, K. M.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Jones, W. C.; Juvela, M.; Keihänen, E.; Keskitalo, R.; Kim, J.; Kisner, T. S.; Knoche, J.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lähteenmäki, A.; Lamarre, J.-M.; Lasenby, A.; Lattanzi, M.; Lawrence, C. R.; Leonardi, R.; Lesgourgues, J.; Levrier, F.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; Liu, H.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maggio, G.; Maino, D.; Mandolesi, N.; Mangilli, A.; Marinucci, D.; Maris, M.; Martin, P. G.; Martínez-González, E.; Masi, S.; Matarrese, S.; McGehee, P.; Meinhold, P. R.; Melchiorri, A.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mikkelsen, K.; Mitra, S.; Miville-Deschênes, M.-A.; Molinari, D.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Moss, A.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Netterfield, C. B.; Nørgaard-Nielsen, H. U.; Noviello, F.; Novikov, D.; Novikov, I.; Oxborrow, C. A.; Paci, F.; Pagano, L.; Pajot, F.; Pant, N.; Paoletti, D.; Pasian, F.; Patanchon, G.; Pearson, T. J.; Perdereau, O.; Perotto, L.; Perrotta, F.; Pettorino, V.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Popa, L.; Pratt, G. W.; Prézeau, G.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renault, C.; Renzi, A.; Ristorcelli, I.; Rocha, G.; Rosset, C.; Rossetti, M.; Rotti, A.; Roudier, G.; Rubiño-Martín, J. A.; Rusholme, B.; Sandri, M.; Santos, D.; Savelainen, M.; Savini, G.; Scott, D.; Seiffert, M. D.; Shellard, E. P. S.; Souradeep, T.; Spencer, L. D.; Stolyarov, V.; Stompor, R.; Sudiwala, R.; Sunyaev, R.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Trombetti, T.; Tucci, M.; Tuovinen, J.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vielva, P.; Villa, F.; Wade, L. A.; Wandelt, B. D.; Wehus, I. K.; Yvon, D.; Zacchei, A.; Zibin, J. P.; Zonca, A.

2016-09-01

We test the statistical isotropy and Gaussianity of the cosmic microwave background (CMB) anisotropies using observations made by the Planck satellite. Our results are based mainly on the full Planck mission for temperature, but also include some polarization measurements. In particular, we consider the CMB anisotropy maps derived from the multi-frequency Planck data by several component-separation methods. For the temperature anisotropies, we find excellent agreement between results based on these sky maps over both a very large fraction of the sky and a broad range of angular scales, establishing that potential foreground residuals do not affect our studies. Tests of skewness, kurtosis, multi-normality, N-point functions, and Minkowski functionals indicate consistency with Gaussianity, while a power deficit at large angular scales is manifested in several ways, for example low map variance. The results of a peak statistics analysis are consistent with the expectations of a Gaussian random field. The "Cold Spot" is detected with several methods, including map kurtosis, peak statistics, and mean temperature profile. We thoroughly probe the large-scale dipolar power asymmetry, detecting it with several independent tests, and address the subject of a posteriori correction. Tests of directionality suggest the presence of angular clustering from large to small scales, but at a significance that is dependent on the details of the approach. We perform the first examination of polarization data, finding the morphology of stacked peaks to be consistent with the expectations of statistically isotropic simulations. Where they overlap, these results are consistent with the Planck 2013 analysis based on the nominal mission data and provide our most thorough view of the statistics of the CMB fluctuations to date.

Planck 2015 results: XVI. Isotropy and statistics of the CMB

DOE PAGES

Ade, P. A. R.; Aghanim, N.; Akrami, Y.; ...

2016-09-20

In this paper, we test the statistical isotropy and Gaussianity of the cosmic microwave background (CMB) anisotropies using observations made by the Planck satellite. Our results are based mainly on the full Planck mission for temperature, but also include some polarization measurements. In particular, we consider the CMB anisotropy maps derived from the multi-frequency Planck data by several component-separation methods. For the temperature anisotropies, we find excellent agreement between results based on these sky maps over both a very large fraction of the sky and a broad range of angular scales, establishing that potential foreground residuals do not affect ourmore » studies. Tests of skewness, kurtosis, multi-normality, N-point functions, and Minkowski functionals indicate consistency with Gaussianity, while a power deficit at large angular scales is manifested in several ways, for example low map variance. The results of a peak statistics analysis are consistent with the expectations of a Gaussian random field. The “Cold Spot” is detected with several methods, including map kurtosis, peak statistics, and mean temperature profile. We thoroughly probe the large-scale dipolar power asymmetry, detecting it with several independent tests, and address the subject of a posteriori correction. Tests of directionality suggest the presence of angular clustering from large to small scales, but at a significance that is dependent on the details of the approach. We perform the first examination of polarization data, finding the morphology of stacked peaks to be consistent with the expectations of statistically isotropic simulations. Finally, where they overlap, these results are consistent with the Planck 2013 analysis based on the nominal mission data and provide our most thorough view of the statistics of the CMB fluctuations to date.« less

[Factors conditioning primary care services utilization. Empirical evidence and methodological inconsistencies].

PubMed

Sáez, M

2003-01-01

In Spain, the degree and characteristics of primary care services utilization have been the subject of analysis since at least the 1980s. One of the main reasons for this interest is to assess the extent to which utilization matches primary care needs. In fact, the provision of an adequate health service for those who most need it is a generally accepted priority. The evidence shows that individual characteristics, mainly health status, are the factors most closely related to primary care utilization. Other personal characteristics, such as gender and age, could act as modulators of health care need. Some family and/or cultural variables, as well as factors related to the health care professional and institutions, could explain some of the observed variability in primary care services utilization. Socioeconomic variables, such as income, reveal a paradox. From an aggregate perspective, income is the main determinant of utilization as well as of health care expenditure. When data are analyzed for individuals, however, income is not related to primary health utilization. The situation is controversial, with methodological implications and, above all, consequences for the assessment of the efficiency in primary care utilization. Review of the literature reveals certain methodological inconsistencies that could at least partly explain the disparity of the empirical results. Among others, the following flaws can be highlighted: design problems, measurement errors, misspecification, and misleading statistical methods.Some solutions, among others, are quasi-experiments, the use of large administrative databases and of primary data sources (design problems); differentiation between types of utilization and between units of analysis other than consultations, and correction of measurement errors in the explanatory variables (measurement errors); consideration of relevant explanatory variables (misspecification); and the use of multilevel models (statistical methods).

Color edges extraction using statistical features and automatic threshold technique: application to the breast cancer cells.

PubMed

Ben Chaabane, Salim; Fnaiech, Farhat

2014-01-23

Color image segmentation has been so far applied in many areas; hence, recently many different techniques have been developed and proposed. In the medical imaging area, the image segmentation may be helpful to provide assistance to doctor in order to follow-up the disease of a certain patient from the breast cancer processed images. The main objective of this work is to rebuild and also to enhance each cell from the three component images provided by an input image. Indeed, from an initial segmentation obtained using the statistical features and histogram threshold techniques, the resulting segmentation may represent accurately the non complete and pasted cells and enhance them. This allows real help to doctors, and consequently, these cells become clear and easy to be counted. A novel method for color edges extraction based on statistical features and automatic threshold is presented. The traditional edge detector, based on the first and the second order neighborhood, describing the relationship between the current pixel and its neighbors, is extended to the statistical domain. Hence, color edges in an image are obtained by combining the statistical features and the automatic threshold techniques. Finally, on the obtained color edges with specific primitive color, a combination rule is used to integrate the edge results over the three color components. Breast cancer cell images were used to evaluate the performance of the proposed method both quantitatively and qualitatively. Hence, a visual and a numerical assessment based on the probability of correct classification (PC), the false classification (Pf), and the classification accuracy (Sens(%)) are presented and compared with existing techniques. The proposed method shows its superiority in the detection of points which really belong to the cells, and also the facility of counting the number of the processed cells. Computer simulations highlight that the proposed method substantially enhances the segmented image with smaller error rates better than other existing algorithms under the same settings (patterns and parameters). Moreover, it provides high classification accuracy, reaching the rate of 97.94%. Additionally, the segmentation method may be extended to other medical imaging types having similar properties.

Price corrected domestic technology assumption--a method to assess pollution embodied in trade using primary official statistics only. With a case on CO2 emissions embodied in imports to Europe.

PubMed

Tukker, Arnold; de Koning, Arjan; Wood, Richard; Moll, Stephan; Bouwmeester, Maaike C

2013-02-19

Environmentally extended input output (EE IO) analysis is increasingly used to assess the carbon footprint of final consumption. Official EE IO data are, however, at best available for single countries or regions such as the EU27. This causes problems in assessing pollution embodied in imported products. The popular "domestic technology assumption (DTA)" leads to errors. Improved approaches based on Life Cycle Inventory data, Multiregional EE IO tables, etc. rely on unofficial research data and modeling, making them difficult to implement by statistical offices. The DTA can lead to errors for three main reasons: exporting countries can have higher impact intensities; may use more intermediate inputs for the same output; or may sell the imported products for lower/other prices than those produced domestically. The last factor is relevant for sustainable consumption policies of importing countries, whereas the first factors are mainly a matter of making production in exporting countries more eco-efficient. We elaborated a simple correction for price differences in imports and domestic production using monetary and physical data from official import and export statistics. A case study for the EU27 shows that this "price-adjusted DTA" gives a partial but meaningful adjustment of pollution embodied in trade compared to multiregional EE IO studies.

Analyzing the effect of selected control policy measures and sociodemographic factors on alcoholic beverage consumption in Europe within the AMPHORA project: statistical methods.

PubMed

Baccini, Michela; Carreras, Giulia

2014-10-01

This paper describes the methods used to investigate variations in total alcoholic beverage consumption as related to selected control intervention policies and other socioeconomic factors (unplanned factors) within 12 European countries involved in the AMPHORA project. The analysis presented several critical points: presence of missing values, strong correlation among the unplanned factors, long-term waves or trends in both the time series of alcohol consumption and the time series of the main explanatory variables. These difficulties were addressed by implementing a multiple imputation procedure for filling in missing values, then specifying for each country a multiple regression model which accounted for time trend, policy measures and a limited set of unplanned factors, selected in advance on the basis of sociological and statistical considerations are addressed. This approach allowed estimating the "net" effect of the selected control policies on alcohol consumption, but not the association between each unplanned factor and the outcome.

Wavelet Statistical Analysis of Low-Latitude Geomagnetic Measurements

NASA Astrophysics Data System (ADS)

Papa, A. R.; Akel, A. F.

2009-05-01

Following previous works by our group (Papa et al., JASTP, 2006), where we analyzed a series of records acquired at the Vassouras National Geomagnetic Observatory in Brazil for the month of October 2000, we introduced a wavelet analysis for the same type of data and for other periods. It is well known that wavelets allow a more detailed study in several senses: the time window for analysis can be drastically reduced if compared to other traditional methods (Fourier, for example) and at the same time allow an almost continuous accompaniment of both amplitude and frequency of signals as time goes by. This advantage brings some possibilities for potentially useful forecasting methods of the type also advanced by our group in previous works (see for example, Papa and Sosman, JASTP, 2008). However, the simultaneous statistical analysis of both time series (in our case amplitude and frequency) is a challenging matter and is in this sense that we have found what we consider our main goal. Some possible trends for future works are advanced.

An Overview of data science uses in bioimage informatics.

PubMed

Chessel, Anatole

2017-02-15

This review aims at providing a practical overview of the use of statistical features and associated data science methods in bioimage informatics. To achieve a quantitative link between images and biological concepts, one typically replaces an object coming from an image (a segmented cell or intracellular object, a pattern of expression or localisation, even a whole image) by a vector of numbers. They range from carefully crafted biologically relevant measurements to features learnt through deep neural networks. This replacement allows for the use of practical algorithms for visualisation, comparison and inference, such as the ones from machine learning or multivariate statistics. While originating mainly, for biology, in high content screening, those methods are integral to the use of data science for the quantitative analysis of microscopy images to gain biological insight, and they are sure to gather more interest as the need to make sense of the increasing amount of acquired imaging data grows more pressing. Copyright © 2017 Elsevier Inc. All rights reserved.

Multiple Kernel Learning with Random Effects for Predicting Longitudinal Outcomes and Data Integration

PubMed Central

Chen, Tianle; Zeng, Donglin

2015-01-01

Summary Predicting disease risk and progression is one of the main goals in many clinical research studies. Cohort studies on the natural history and etiology of chronic diseases span years and data are collected at multiple visits. Although kernel-based statistical learning methods are proven to be powerful for a wide range of disease prediction problems, these methods are only well studied for independent data but not for longitudinal data. It is thus important to develop time-sensitive prediction rules that make use of the longitudinal nature of the data. In this paper, we develop a novel statistical learning method for longitudinal data by introducing subject-specific short-term and long-term latent effects through a designed kernel to account for within-subject correlation of longitudinal measurements. Since the presence of multiple sources of data is increasingly common, we embed our method in a multiple kernel learning framework and propose a regularized multiple kernel statistical learning with random effects to construct effective nonparametric prediction rules. Our method allows easy integration of various heterogeneous data sources and takes advantage of correlation among longitudinal measures to increase prediction power. We use different kernels for each data source taking advantage of the distinctive feature of each data modality, and then optimally combine data across modalities. We apply the developed methods to two large epidemiological studies, one on Huntington's disease and the other on Alzheimer's Disease (Alzheimer's Disease Neuroimaging Initiative, ADNI) where we explore a unique opportunity to combine imaging and genetic data to study prediction of mild cognitive impairment, and show a substantial gain in performance while accounting for the longitudinal aspect of the data. PMID:26177419

Ensemble Methods

NASA Astrophysics Data System (ADS)

Re, Matteo; Valentini, Giorgio

2012-03-01

Ensemble methods are statistical and computational learning procedures reminiscent of the human social learning behavior of seeking several opinions before making any crucial decision. The idea of combining the opinions of different "experts" to obtain an overall “ensemble” decision is rooted in our culture at least from the classical age of ancient Greece, and it has been formalized during the Enlightenment with the Condorcet Jury Theorem[45]), which proved that the judgment of a committee is superior to those of individuals, provided the individuals have reasonable competence. Ensembles are sets of learning machines that combine in some way their decisions, or their learning algorithms, or different views of data, or other specific characteristics to obtain more reliable and more accurate predictions in supervised and unsupervised learning problems [48,116]. A simple example is represented by the majority vote ensemble, by which the decisions of different learning machines are combined, and the class that receives the majority of “votes” (i.e., the class predicted by the majority of the learning machines) is the class predicted by the overall ensemble [158]. In the literature, a plethora of terms other than ensembles has been used, such as fusion, combination, aggregation, and committee, to indicate sets of learning machines that work together to solve a machine learning problem [19,40,56,66,99,108,123], but in this chapter we maintain the term ensemble in its widest meaning, in order to include the whole range of combination methods. Nowadays, ensemble methods represent one of the main current research lines in machine learning [48,116], and the interest of the research community on ensemble methods is witnessed by conferences and workshops specifically devoted to ensembles, first of all the multiple classifier systems (MCS) conference organized by Roli, Kittler, Windeatt, and other researchers of this area [14,62,85,149,173]. Several theories have been proposed to explain the characteristics and the successful application of ensembles to different application domains. For instance, Allwein, Schapire, and Singer interpreted the improved generalization capabilities of ensembles of learning machines in the framework of large margin classifiers [4,177], Kleinberg in the context of stochastic discrimination theory [112], and Breiman and Friedman in the light of the bias-variance analysis borrowed from classical statistics [21,70]. Empirical studies showed that both in classification and regression problems, ensembles improve on single learning machines, and moreover large experimental studies compared the effectiveness of different ensemble methods on benchmark data sets [10,11,49,188]. The interest in this research area is motivated also by the availability of very fast computers and networks of workstations at a relatively low cost that allow the implementation and the experimentation of complex ensemble methods using off-the-shelf computer platforms. However, as explained in Section 26.2 there are deeper reasons to use ensembles of learning machines, motivated by the intrinsic characteristics of the ensemble methods. The main aim of this chapter is to introduce ensemble methods and to provide an overview and a bibliography of the main areas of research, without pretending to be exhaustive or to explain the detailed characteristics of each ensemble method. The paper is organized as follows. In the next section, the main theoretical and practical reasons for combining multiple learners are introduced. Section 26.3 depicts the main taxonomies on ensemble methods proposed in the literature. In Section 26.4 and 26.5, we present an overview of the main supervised ensemble methods reported in the literature, adopting a simple taxonomy, originally proposed in Ref. [201]. Applications of ensemble methods are only marginally considered, but a specific section on some relevant applications of ensemble methods in astronomy and astrophysics has been added (Section 26.6). The conclusion (Section 26.7) ends this paper and lists some issues not covered in this work.

Protein Structure Classification and Loop Modeling Using Multiple Ramachandran Distributions.

PubMed

Najibi, Seyed Morteza; Maadooliat, Mehdi; Zhou, Lan; Huang, Jianhua Z; Gao, Xin

2017-01-01

Recently, the study of protein structures using angular representations has attracted much attention among structural biologists. The main challenge is how to efficiently model the continuous conformational space of the protein structures based on the differences and similarities between different Ramachandran plots. Despite the presence of statistical methods for modeling angular data of proteins, there is still a substantial need for more sophisticated and faster statistical tools to model the large-scale circular datasets. To address this need, we have developed a nonparametric method for collective estimation of multiple bivariate density functions for a collection of populations of protein backbone angles. The proposed method takes into account the circular nature of the angular data using trigonometric spline which is more efficient compared to existing methods. This collective density estimation approach is widely applicable when there is a need to estimate multiple density functions from different populations with common features. Moreover, the coefficients of adaptive basis expansion for the fitted densities provide a low-dimensional representation that is useful for visualization, clustering, and classification of the densities. The proposed method provides a novel and unique perspective to two important and challenging problems in protein structure research: structure-based protein classification and angular-sampling-based protein loop structure prediction.

Forest statistics for Maine: 1971 and 1982

Treesearch

Douglas S. Powell; David R. Dickson

1984-01-01

A statistical report on the third forest survey of Maine (1982) and reprocessed data from the second survey (1971). Results of the surveys are displayed in a 169 tables containing estimates of forest and timberland area, numbers of trees, timber volume, tree biomass, timber products output, and components of average annual net change in growing-stock volume for the...

New methods of testing nonlinear hypothesis using iterative NLLS estimator

NASA Astrophysics Data System (ADS)

Mahaboob, B.; Venkateswarlu, B.; Mokeshrayalu, G.; Balasiddamuni, P.

2017-11-01

This research paper discusses the method of testing nonlinear hypothesis using iterative Nonlinear Least Squares (NLLS) estimator. Takeshi Amemiya [1] explained this method. However in the present research paper, a modified Wald test statistic due to Engle, Robert [6] is proposed to test the nonlinear hypothesis using iterative NLLS estimator. An alternative method for testing nonlinear hypothesis using iterative NLLS estimator based on nonlinear hypothesis using iterative NLLS estimator based on nonlinear studentized residuals has been proposed. In this research article an innovative method of testing nonlinear hypothesis using iterative restricted NLLS estimator is derived. Pesaran and Deaton [10] explained the methods of testing nonlinear hypothesis. This paper uses asymptotic properties of nonlinear least squares estimator proposed by Jenrich [8]. The main purpose of this paper is to provide very innovative methods of testing nonlinear hypothesis using iterative NLLS estimator, iterative NLLS estimator based on nonlinear studentized residuals and iterative restricted NLLS estimator. Eakambaram et al. [12] discussed least absolute deviation estimations versus nonlinear regression model with heteroscedastic errors and also they studied the problem of heteroscedasticity with reference to nonlinear regression models with suitable illustration. William Grene [13] examined the interaction effect in nonlinear models disused by Ai and Norton [14] and suggested ways to examine the effects that do not involve statistical testing. Peter [15] provided guidelines for identifying composite hypothesis and addressing the probability of false rejection for multiple hypotheses.

The Role of Statistics in Kosovo Enterprises

ERIC Educational Resources Information Center

Gjonbalaj, Muje; Dema, Marjan; Miftari, Iliriana

2009-01-01

Considering science as the main contributor to contemporary developments has encouraged us to raise a scientific discussion regarding the role of statistics in business decision-making and economic development. Statistics, as an applicative science, is growing and being widely applied in different fields and professions. Statistical thinking is…

Challenges in Species Tree Estimation Under the Multispecies Coalescent Model

PubMed Central

Xu, Bo; Yang, Ziheng

2016-01-01

The multispecies coalescent (MSC) model has emerged as a powerful framework for inferring species phylogenies while accounting for ancestral polymorphism and gene tree-species tree conflict. A number of methods have been developed in the past few years to estimate the species tree under the MSC. The full likelihood methods (including maximum likelihood and Bayesian inference) average over the unknown gene trees and accommodate their uncertainties properly but involve intensive computation. The approximate or summary coalescent methods are computationally fast and are applicable to genomic datasets with thousands of loci, but do not make an efficient use of information in the multilocus data. Most of them take the two-step approach of reconstructing the gene trees for multiple loci by phylogenetic methods and then treating the estimated gene trees as observed data, without accounting for their uncertainties appropriately. In this article we review the statistical nature of the species tree estimation problem under the MSC, and explore the conceptual issues and challenges of species tree estimation by focusing mainly on simple cases of three or four closely related species. We use mathematical analysis and computer simulation to demonstrate that large differences in statistical performance may exist between the two classes of methods. We illustrate that several counterintuitive behaviors may occur with the summary methods but they are due to inefficient use of information in the data by summary methods and vanish when the data are analyzed using full-likelihood methods. These include (i) unidentifiability of parameters in the model, (ii) inconsistency in the so-called anomaly zone, (iii) singularity on the likelihood surface, and (iv) deterioration of performance upon addition of more data. We discuss the challenges and strategies of species tree inference for distantly related species when the molecular clock is violated, and highlight the need for improving the computational efficiency and model realism of the likelihood methods as well as the statistical efficiency of the summary methods. PMID:27927902

Evaluation of adding item-response theory analysis for evaluation of the European Board of Ophthalmology Diploma examination.

PubMed

Mathysen, Danny G P; Aclimandos, Wagih; Roelant, Ella; Wouters, Kristien; Creuzot-Garcher, Catherine; Ringens, Peter J; Hawlina, Marko; Tassignon, Marie-José

2013-11-01

To investigate whether introduction of item-response theory (IRT) analysis, in parallel to the 'traditional' statistical analysis methods available for performance evaluation of multiple T/F items as used in the European Board of Ophthalmology Diploma (EBOD) examination, has proved beneficial, and secondly, to study whether the overall assessment performance of the current written part of EBOD is sufficiently high (KR-20≥ 0.90) to be kept as examination format in future EBOD editions. 'Traditional' analysis methods for individual MCQ item performance comprise P-statistics, Rit-statistics and item discrimination, while overall reliability is evaluated through KR-20 for multiple T/F items. The additional set of statistical analysis methods for the evaluation of EBOD comprises mainly IRT analysis. These analysis techniques are used to monitor whether the introduction of negative marking for incorrect answers (since EBOD 2010) has a positive influence on the statistical performance of EBOD as a whole and its individual test items in particular. Item-response theory analysis demonstrated that item performance parameters should not be evaluated individually, but should be related to one another. Before the introduction of negative marking, the overall EBOD reliability (KR-20) was good though with room for improvement (EBOD 2008: 0.81; EBOD 2009: 0.78). After the introduction of negative marking, the overall reliability of EBOD improved significantly (EBOD 2010: 0.92; EBOD 2011:0.91; EBOD 2012: 0.91). Although many statistical performance parameters are available to evaluate individual items, our study demonstrates that the overall reliability assessment remains the only crucial parameter to be evaluated allowing comparison. While individual item performance analysis is worthwhile to undertake as secondary analysis, drawing final conclusions seems to be more difficult. Performance parameters need to be related, as shown by IRT analysis. Therefore, IRT analysis has proved beneficial for the statistical analysis of EBOD. Introduction of negative marking has led to a significant increase in the reliability (KR-20 > 0.90), indicating that the current examination format can be kept for future EBOD examinations. © 2013 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

Trends and sources for heavy metals in urban atmosphere

NASA Astrophysics Data System (ADS)

Kemp, Kåre

2002-04-01

The concentrations of a number of heavy metals in the air in three Danish cities have been measured by means of PIXE for more than two decades. The well-known capability of PIXE for fast and efficient analysis of aerosol samples has been employed for analysis of daily samples from several sites during the whole period. The main sources are traffic, domestic heating and long-range transport. Source apportionment and trends for single metals are assessed by means of simple statistical methods. The most striking change has occurred for the Pb concentration, which is reduced by almost a factor of 100 following the reduction of the Pb content in petrol. The main source of Cu, Cr and Zn is the traffic. The concentrations of these elements have been slightly increasing. The concentrations for most of the other heavy metals, which originate mainly from sources outside the cities, have been decreasing.

Discrepancy between results and abstract conclusions in industry- vs nonindustry-funded studies comparing topical prostaglandins.

PubMed

Alasbali, Tariq; Smith, Michael; Geffen, Noa; Trope, Graham E; Flanagan, John G; Jin, Yaping; Buys, Yvonne M

2009-01-01

To investigate the relationship between industry- vs nonindustry-funded publications comparing the efficacy of topical prostaglandin analogs by evaluating the correspondence between the statistical significance of the publication's main outcome measure and its abstract conclusions. Retrospective, observational cohort study. English publications comparing the ocular hypotensive efficacy between any or all of latanoprost, travoprost, and bimatoprost were searched from the MEDLINE database. Each article was reviewed by three independent observers and was evaluated for source of funding, study quality, statistically significant main outcome measure, correspondence between results of main outcome measure and abstract conclusion, number of intraocular pressure outcomes compared, and journal impact factor. Funding was determined by published disclosure or, in cases of no documented disclosure, the corresponding author was contacted directly to confirm industry funding. Discrepancies were resolved by consensus. The main outcome measure was correspondence between abstract conclusion and reported statistical significance of the publications' main outcome measure. Thirty-nine publications were included, of which 29 were industry funded and 10 were nonindustry funded. The published abstract conclusion was not consistent with the results of the main outcome measure in 18 (62%) of 29 of the industry-funded studies compared with zero (0%) of 10 of the nonindustry-funded studies (P = .0006). Twenty-six (90%) of the industry-funded studies had proindustry abstract conclusions. Twenty-four percent of the industry-funded publications had a statistically significant main outcome measure; however, 90% of the industry-funded studies had proindustry abstract conclusions. Both readers and reviewers should scrutinize publications carefully to ensure that data support the authors' conclusions.

Factor Structure and Psychometric Properties of the Brief Illness Perception Questionnaire in Turkish Cancer Patients

PubMed Central

Karataş, Tuğba; Özen, Şükrü; Kutlutürkan, Sevinç

2017-01-01

Objective: The main aim of this study was to investigate the factor structure and psychometric properties of the Brief Illness Perception Questionnaire (BIPQ) in Turkish cancer patients. Methods: This methodological study involved 135 cancer patients. Statistical methods included confirmatory or exploratory factor analysis and Cronbach alpha coefficients for internal consistency. Results: The values of fit indices are within the acceptable range. The alpha coefficients for emotional illness representations, cognitive illness representations, and total scale are 0.83, 0.80, and 0.85, respectively. Conclusions: The results confirm the two-factor structure of the Turkish BIPQ and demonstrate its reliability and validity. PMID:28217734

Best Merge Region Growing with Integrated Probabilistic Classification for Hyperspectral Imagery

NASA Technical Reports Server (NTRS)

Tarabalka, Yuliya; Tilton, James C.

2011-01-01

A new method for spectral-spatial classification of hyperspectral images is proposed. The method is based on the integration of probabilistic classification within the hierarchical best merge region growing algorithm. For this purpose, preliminary probabilistic support vector machines classification is performed. Then, hierarchical step-wise optimization algorithm is applied, by iteratively merging regions with the smallest Dissimilarity Criterion (DC). The main novelty of this method consists in defining a DC between regions as a function of region statistical and geometrical features along with classification probabilities. Experimental results are presented on a 200-band AVIRIS image of the Northwestern Indiana s vegetation area and compared with those obtained by recently proposed spectral-spatial classification techniques. The proposed method improves classification accuracies when compared to other classification approaches.

Application of Scan Statistics to Detect Suicide Clusters in Australia

PubMed Central

Cheung, Yee Tak Derek; Spittal, Matthew J.; Williamson, Michelle Kate; Tung, Sui Jay; Pirkis, Jane

2013-01-01

Background Suicide clustering occurs when multiple suicide incidents take place in a small area or/and within a short period of time. In spite of the multi-national research attention and particular efforts in preparing guidelines for tackling suicide clusters, the broader picture of epidemiology of suicide clustering remains unclear. This study aimed to develop techniques in using scan statistics to detect clusters, with the detection of suicide clusters in Australia as example. Methods and Findings Scan statistics was applied to detect clusters among suicides occurring between 2004 and 2008. Manipulation of parameter settings and change of area for scan statistics were performed to remedy shortcomings in existing methods. In total, 243 suicides out of 10,176 (2.4%) were identified as belonging to 15 suicide clusters. These clusters were mainly located in the Northern Territory, the northern part of Western Australia, and the northern part of Queensland. Among the 15 clusters, 4 (26.7%) were detected by both national and state cluster detections, 8 (53.3%) were only detected by the state cluster detection, and 3 (20%) were only detected by the national cluster detection. Conclusions These findings illustrate that the majority of spatial-temporal clusters of suicide were located in the inland northern areas, with socio-economic deprivation and higher proportions of indigenous people. Discrepancies between national and state/territory cluster detection by scan statistics were due to the contrast of the underlying suicide rates across states/territories. Performing both small-area and large-area analyses, and applying multiple parameter settings may yield the maximum benefits for exploring clusters. PMID:23342098

In vivo evaluation of the effect of stimulus distribution on FIR statistical efficiency in event-related fMRI.

PubMed

Jansma, J Martijn; de Zwart, Jacco A; van Gelderen, Peter; Duyn, Jeff H; Drevets, Wayne C; Furey, Maura L

2013-05-15

Technical developments in MRI have improved signal to noise, allowing use of analysis methods such as Finite impulse response (FIR) of rapid event related functional MRI (er-fMRI). FIR is one of the most informative analysis methods as it determines onset and full shape of the hemodynamic response function (HRF) without any a priori assumptions. FIR is however vulnerable to multicollinearity, which is directly related to the distribution of stimuli over time. Efficiency can be optimized by simplifying a design, and restricting stimuli distribution to specific sequences, while more design flexibility necessarily reduces efficiency. However, the actual effect of efficiency on fMRI results has never been tested in vivo. Thus, it is currently difficult to make an informed choice between protocol flexibility and statistical efficiency. The main goal of this study was to assign concrete fMRI signal to noise values to the abstract scale of FIR statistical efficiency. Ten subjects repeated a perception task with five random and m-sequence based protocol, with varying but, according to literature, acceptable levels of multicollinearity. Results indicated substantial differences in signal standard deviation, while the level was a function of multicollinearity. Experiment protocols varied up to 55.4% in standard deviation. Results confirm that quality of fMRI in an FIR analysis can significantly and substantially vary with statistical efficiency. Our in vivo measurements can be used to aid in making an informed decision between freedom in protocol design and statistical efficiency. Published by Elsevier B.V.

Radar error statistics for the space shuttle

NASA Technical Reports Server (NTRS)

Lear, W. M.

1979-01-01

Radar error statistics of C-band and S-band that are recommended for use with the groundtracking programs to process space shuttle tracking data are presented. The statistics are divided into two parts: bias error statistics, using the subscript B, and high frequency error statistics, using the subscript q. Bias errors may be slowly varying to constant. High frequency random errors (noise) are rapidly varying and may or may not be correlated from sample to sample. Bias errors were mainly due to hardware defects and to errors in correction for atmospheric refraction effects. High frequency noise was mainly due to hardware and due to atmospheric scintillation. Three types of atmospheric scintillation were identified: horizontal, vertical, and line of sight. This was the first time that horizontal and line of sight scintillations were identified.

Statistics Report on TEQSA Registered Higher Education Providers

ERIC Educational Resources Information Center

Australian Government Tertiary Education Quality and Standards Agency, 2015

2015-01-01

This statistics report provides a comprehensive snapshot of national statistics on all parts of the sector for the year 2013, by bringing together data collected directly by TEQSA with data sourced from the main higher education statistics collections managed by the Australian Government Department of Education and Training. The report provides…

A Localized Ensemble Kalman Smoother

NASA Technical Reports Server (NTRS)

Butala, Mark D.

2012-01-01

Numerous geophysical inverse problems prove difficult because the available measurements are indirectly related to the underlying unknown dynamic state and the physics governing the system may involve imperfect models or unobserved parameters. Data assimilation addresses these difficulties by combining the measurements and physical knowledge. The main challenge in such problems usually involves their high dimensionality and the standard statistical methods prove computationally intractable. This paper develops and addresses the theoretical convergence of a new high-dimensional Monte-Carlo approach called the localized ensemble Kalman smoother.

Landslide Hazard Assessment and Mapping in the Guil Catchment (Queyras, Southern French Alps): From Landslide Inventory to Susceptibility Modelling

NASA Astrophysics Data System (ADS)

Roulleau, Louise; Bétard, François; Carlier, Benoît; Lissak, Candide; Fort, Monique

2016-04-01

Landslides are common natural hazards in the Southern French Alps, where they may affect human lives and cause severe damages to infrastructures. As a part of the SAMCO research project dedicated to risk evaluation in mountain areas, this study focuses on the Guil river catchment (317 km2), Queyras, to assess landslide hazard poorly studied until now. In that area, landslides are mainly occasional, low amplitude phenomena, with limited direct impacts when compared to other hazards such as floods or snow avalanches. However, when interacting with floods during extreme rainfall events, landslides may have indirect consequences of greater importance because of strong hillslope-channel connectivity along the Guil River and its tributaries (i.e. positive feedbacks). This specific morphodynamic functioning reinforces the need to have a better understanding of landslide hazards and their spatial distribution at the catchment scale to prevent local population from disasters with multi-hazard origin. The aim of this study is to produce a landslide susceptibility mapping at 1:50 000 scale as a first step towards global estimation of landslide hazard and risk. The three main methodologies used for assessing landslide susceptibility are qualitative (i.e. expert opinion), deterministic (i.e. physics-based models) and statistical methods (i.e. probabilistic models). Due to the rapid development of geographical information systems (GIS) during the last two decades, statistical methods are today widely used because they offer a greater objectivity and reproducibility at large scales. Among them, multivariate analyses are considered as the most robust techniques, especially the logistic regression method commonly used in landslide susceptibility mapping. However, this method like others is strongly dependent on the accuracy of the input data to avoid significant errors in the final results. In particular, a complete and accurate landslide inventory is required before the modelling. The methodology used in our study includes five main steps: (i) a landslide inventory was compiled through extraction of landslide occurrences in existing national databases (BDMvt, RTM), photointerpretation of aerial photographs and extensive field surveys; (ii) the main predisposing factors were identified and implemented as digital layers into a GIS together with the landslide inventory map, thus constituting the predictive variables to introduce into the model; (iii) a logistic regression model was applied to analyze the spatial and mathematical relationships between the response variable (i.e. absence/presence of landslides) and the set of predictive variables (i.e. predisposing factors), after a selection procedure based on statistical tests (χ2-test and Cramer's V coefficient); (iv) an evaluation of the model performance and quality results was conducted using a validation strategy based on ROC curve and AUC analyses; (v) a final susceptibility map in four classes was proposed using a discretization method based on success/prediction rate curves. The results of the susceptibility modelling were finally interpreted and discussed in the light of what was previously known about landslide occurrence and triggering in the study area. The major influence of the distance-to-streams variable on the model confirms the strong hillslope-channel coupling observed empirically during rainfall-induced landslide events.

A Kepler Mission, A Search for Habitable Planets: Concept, Capabilities and Strengths

NASA Technical Reports Server (NTRS)

Koch, David; Borucki, William; Lissauer, Jack; Dunham, Edward; Jenkins, Jon; DeVincenzi, D. (Technical Monitor)

1998-01-01

The detection of extrasolar terrestrial planets orbiting main-sequence stars is of great interest and importance. Current ground-based methods are only capable of detecting objects about the size or mass of Jupiter or larger. The technological challenges of direct imaging of Earth-size planets from space are expected to be resolved over the next twenty years. Spacebased photometry of planetary transits is currently the only viable method for detection of terrestrial planets (30-600 times less massive than Jupiter). The method searches the extended solar neighborhood, providing a statistically large sample and the detailed characteristics of each individual case. A robust concept has been developed and proposed as a Discovery-class mission. The concept, its capabilities and strengths are presented.

Medical image security using modified chaos-based cryptography approach

NASA Astrophysics Data System (ADS)

Talib Gatta, Methaq; Al-latief, Shahad Thamear Abd

2018-05-01

The progressive development in telecommunication and networking technologies have led to the increased popularity of telemedicine usage which involve storage and transfer of medical images and related information so security concern is emerged. This paper presents a method to provide the security to the medical images since its play a major role in people healthcare organizations. The main idea in this work based on the chaotic sequence in order to provide efficient encryption method that allows reconstructing the original image from the encrypted image with high quality and minimum distortion in its content and doesn’t effect in human treatment and diagnosing. Experimental results prove the efficiency of the proposed method using some of statistical measures and robust correlation between original image and decrypted image.

Recurrence Density Enhanced Complex Networks for Nonlinear Time Series Analysis

NASA Astrophysics Data System (ADS)

Costa, Diego G. De B.; Reis, Barbara M. Da F.; Zou, Yong; Quiles, Marcos G.; Macau, Elbert E. N.

We introduce a new method, which is entitled Recurrence Density Enhanced Complex Network (RDE-CN), to properly analyze nonlinear time series. Our method first transforms a recurrence plot into a figure of a reduced number of points yet preserving the main and fundamental recurrence properties of the original plot. This resulting figure is then reinterpreted as a complex network, which is further characterized by network statistical measures. We illustrate the computational power of RDE-CN approach by time series by both the logistic map and experimental fluid flows, which show that our method distinguishes different dynamics sufficiently well as the traditional recurrence analysis. Therefore, the proposed methodology characterizes the recurrence matrix adequately, while using a reduced set of points from the original recurrence plots.

Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows.

PubMed

Excoffier, Laurent; Lischer, Heidi E L

2010-05-01

We present here a new version of the Arlequin program available under three different forms: a Windows graphical version (Winarl35), a console version of Arlequin (arlecore), and a specific console version to compute summary statistics (arlsumstat). The command-line versions run under both Linux and Windows. The main innovations of the new version include enhanced outputs in XML format, the possibility to embed graphics displaying computation results directly into output files, and the implementation of a new method to detect loci under selection from genome scans. Command-line versions are designed to handle large series of files, and arlsumstat can be used to generate summary statistics from simulated data sets within an Approximate Bayesian Computation framework. © 2010 Blackwell Publishing Ltd.

Machine learning for neuroimaging with scikit-learn.

PubMed

Abraham, Alexandre; Pedregosa, Fabian; Eickenberg, Michael; Gervais, Philippe; Mueller, Andreas; Kossaifi, Jean; Gramfort, Alexandre; Thirion, Bertrand; Varoquaux, Gaël

2014-01-01

Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of activation images or resting-state time series. Supervised learning is typically used in decoding or encoding settings to relate brain images to behavioral or clinical observations, while unsupervised learning can uncover hidden structures in sets of images (e.g., resting state functional MRI) or find sub-populations in large cohorts. By considering different functional neuroimaging applications, we illustrate how scikit-learn, a Python machine learning library, can be used to perform some key analysis steps. Scikit-learn contains a very large set of statistical learning algorithms, both supervised and unsupervised, and its application to neuroimaging data provides a versatile tool to study the brain.

Machine learning for neuroimaging with scikit-learn

PubMed Central

Abraham, Alexandre; Pedregosa, Fabian; Eickenberg, Michael; Gervais, Philippe; Mueller, Andreas; Kossaifi, Jean; Gramfort, Alexandre; Thirion, Bertrand; Varoquaux, Gaël

2014-01-01

Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of activation images or resting-state time series. Supervised learning is typically used in decoding or encoding settings to relate brain images to behavioral or clinical observations, while unsupervised learning can uncover hidden structures in sets of images (e.g., resting state functional MRI) or find sub-populations in large cohorts. By considering different functional neuroimaging applications, we illustrate how scikit-learn, a Python machine learning library, can be used to perform some key analysis steps. Scikit-learn contains a very large set of statistical learning algorithms, both supervised and unsupervised, and its application to neuroimaging data provides a versatile tool to study the brain. PMID:24600388

The Statistical point of view of Quality: the Lean Six Sigma methodology

PubMed Central

Viti, Andrea; Terzi, Alberto

2015-01-01

Six Sigma and Lean are two quality improvement methodologies. The Lean Six Sigma methodology is applicable to repetitive procedures. Therefore, the use of this methodology in the health-care arena has focused mainly on areas of business operations, throughput, and case management and has focused on efficiency outcomes. After the revision of methodology, the paper presents a brief clinical example of the use of Lean Six Sigma as a quality improvement method in the reduction of the complications during and after lobectomies. Using Lean Six Sigma methodology, the multidisciplinary teams could identify multiple modifiable points across the surgical process. These process improvements could be applied to different surgical specialties and could result in a measurement, from statistical point of view, of the surgical quality. PMID:25973253

The Statistical point of view of Quality: the Lean Six Sigma methodology.

PubMed

Bertolaccini, Luca; Viti, Andrea; Terzi, Alberto

2015-04-01

Six Sigma and Lean are two quality improvement methodologies. The Lean Six Sigma methodology is applicable to repetitive procedures. Therefore, the use of this methodology in the health-care arena has focused mainly on areas of business operations, throughput, and case management and has focused on efficiency outcomes. After the revision of methodology, the paper presents a brief clinical example of the use of Lean Six Sigma as a quality improvement method in the reduction of the complications during and after lobectomies. Using Lean Six Sigma methodology, the multidisciplinary teams could identify multiple modifiable points across the surgical process. These process improvements could be applied to different surgical specialties and could result in a measurement, from statistical point of view, of the surgical quality.

Statistics is not enough: revisiting Ronald A. Fisher's critique (1936) of Mendel's experimental results (1866).

PubMed

Pilpel, Avital

2007-09-01

This paper is concerned with the role of rational belief change theory in the philosophical understanding of experimental error. Today, philosophers seek insight about error in the investigation of specific experiments, rather than in general theories. Nevertheless, rational belief change theory adds to our understanding of just such cases: R. A. Fisher's criticism of Mendel's experiments being a case in point. After an historical introduction, the main part of this paper investigates Fisher's paper from the point of view of rational belief change theory: what changes of belief about Mendel's experiment does Fisher go through and with what justification. It leads to surprising insights about what Fisher had done right and wrong, and, more generally, about the limits of statistical methods in detecting error.

Trends in statistical methods in articles published in Archives of Plastic Surgery between 2012 and 2017.

PubMed

Han, Kyunghwa; Jung, Inkyung

2018-05-01

This review article presents an assessment of trends in statistical methods and an evaluation of their appropriateness in articles published in the Archives of Plastic Surgery (APS) from 2012 to 2017. We reviewed 388 original articles published in APS between 2012 and 2017. We categorized the articles that used statistical methods according to the type of statistical method, the number of statistical methods, and the type of statistical software used. We checked whether there were errors in the description of statistical methods and results. A total of 230 articles (59.3%) published in APS between 2012 and 2017 used one or more statistical method. Within these articles, there were 261 applications of statistical methods with continuous or ordinal outcomes, and 139 applications of statistical methods with categorical outcome. The Pearson chi-square test (17.4%) and the Mann-Whitney U test (14.4%) were the most frequently used methods. Errors in describing statistical methods and results were found in 133 of the 230 articles (57.8%). Inadequate description of P-values was the most common error (39.1%). Among the 230 articles that used statistical methods, 71.7% provided details about the statistical software programs used for the analyses. SPSS was predominantly used in the articles that presented statistical analyses. We found that the use of statistical methods in APS has increased over the last 6 years. It seems that researchers have been paying more attention to the proper use of statistics in recent years. It is expected that these positive trends will continue in APS.

Climatic water balance and agricultural productivity dynamics in Dobrogea, southeastern Romania, against the background of climate change over the past decades

NASA Astrophysics Data System (ADS)

Bandoc, Georgeta; Pravalie, Remus

2015-04-01

Interdisciplinary analyses of the relationship between climate system dynamics and agricultural system variation are an essential component for increasing the efficiency of water resource management, and for adapting crops at local level. This paper analyzes the dynamics of the climate water balance (CWB) in the past five decades in Romania's most arid region, Dobrogea, against the background of climate change, as well as the statistical relationship between the variation of CWB values and that of regional agricultural systems. Thus, a first stage consisted in detailed climatic analyses of CWB value variation between 1961 and 2009, based on climatic data provided by 9 regional weather stations. The study mainly focused on CWB trends (mm) recorded annually and seasonally (winter, spring, summer and autumn), using statistical methods such as the Mann-Kendall test and the Sen's slope method, as well as GIS methods in order to visualize the results. The second main stage was directed towards the analysis of the statistical relationship between the aforementioned climate indicator's dynamics and agricultural yields (t / ha / year) in the administrative-territorial units overlapping Dobrogea (generally the plateau region), while corn was considered for the case study as it is one of the region's main crops. In this instance, the agro-climatic data were analyzed / statistically correlated in the 1990-2003 period (depending on data availability for corn production output at administrative unit level), based on Thiessen-Voronoi polygons which were considered to be compact spatial units in which both data categories can be grouped in order to establish interannual relationships. In terms of climate, the results indicated an annual increase of the climatic water deficit at the stations located in the northern region of the study area, with maximum rates of -3.2 mm / year. In contrast, CWB values decreased seasonally (the climatic water deficit increased) roughly throughout Dobrogea (winter, spring and summer, with maximum negative rates of -1.4 mm / year in the warmest season), except for autumn, characterized by general increasing rates, with maximum values in the southwest (2.3 mm / year). However, a general trend overview indicated an overall lack of statistical significance. Considering the 1990-2003 time interval, the data analysis in the Thiessen polygons showed an overall similarity of agro-climatic oscillations, a first assessment of which indicated a general correlation between climate and agricultural data. However, upon analysis of the data series normality criterion, it was found that, during the 14 years, the CWB index variation influenced the dynamics of corn yields especially in the south-central region, in certain cases by up to 50%, causing losses of up to 11 kg / ha / year when the deficit increased by 1 mm. Therefore, while climatic results indicated CWB summer decreases (the most important season in corn productivity dynamics) in the northern region as well, the asymmetries found in agro-climatic data distributions in the northern region did not allow a statistical assessment of the dependence of agriculture on climatic conditions. Hence, for the northern region of the study area, the results indicate the role of additional factors in the dynamics of agricultural systems, which can be both natural (soil and groundwater characteristics) and anthropogenic (management conditions).

Parametric Analysis to Study the Influence of Aerogel-Based Renders' Components on Thermal and Mechanical Performance.

PubMed

Ximenes, Sofia; Silva, Ana; Soares, António; Flores-Colen, Inês; de Brito, Jorge

2016-05-04

Statistical models using multiple linear regression are some of the most widely used methods to study the influence of independent variables in a given phenomenon. This study's objective is to understand the influence of the various components of aerogel-based renders on their thermal and mechanical performance, namely cement (three types), fly ash, aerial lime, silica sand, expanded clay, type of aerogel, expanded cork granules, expanded perlite, air entrainers, resins (two types), and rheological agent. The statistical analysis was performed using SPSS (Statistical Package for Social Sciences), based on 85 mortar mixes produced in the laboratory and on their values of thermal conductivity and compressive strength obtained using tests in small-scale samples. The results showed that aerial lime assumes the main role in improving the thermal conductivity of the mortars. Aerogel type, fly ash, expanded perlite and air entrainers are also relevant components for a good thermal conductivity. Expanded clay can improve the mechanical behavior and aerogel has the opposite effect.

On the radiated EMI current extraction of dc transmission line based on corona current statistical measurements

NASA Astrophysics Data System (ADS)

Yi, Yong; Chen, Zhengying; Wang, Liming

2018-05-01

Corona-originated discharge of DC transmission lines is the main reason for the radiated electromagnetic interference (EMI) field in the vicinity of transmission lines. A joint time-frequency analysis technique was proposed to extract the radiated EMI current (excitation current) of DC corona based on corona current statistical measurements. A reduced-scale experimental platform was setup to measure the statistical distributions of current waveform parameters of aluminum conductor steel reinforced. Based on the measured results, the peak value, root-mean-square value and average value with 9 kHz and 200 Hz band-with of 0.5 MHz radiated EMI current were calculated by the technique proposed and validated with conventional excitation function method. Radio interference (RI) was calculated based on the radiated EMI current and a wire-to-plate platform was built for the validity of the RI computation results. The reason for the certain deviation between the computations and measurements was detailed analyzed.

Fundamentals of poly(lactic acid) microstructure, crystallization behavior, and properties

NASA Astrophysics Data System (ADS)

Kang, Shuhui

Poly(lactic acid) is an environmentally-benign biodegradable and sustainable thermoplastic material, which has found broad applications as food packaging films and as non-woven fibers. The crystallization and deformation mechanisms of the polymer are largely determined by the distribution of conformation and configuration. Knowledge of these mechanisms is needed to understand the mechanical and thermal properties on which processing conditions mainly depend. In conjunction with laser light scattering, Raman spectroscopy and normal coordinate analysis are used in this thesis to elucidate these properties. Vibrational spectroscopic theory, Flory's rotational isomeric state (RIS) theory, Gaussian chain statistics and statistical mechanics are used to relate experimental data to molecular chain structure. A refined RIS model is proposed, chain rigidity recalculated and chain statistics discussed. A Raman spectroscopic characterization method for crystalline and amorphous phase orientation has been developed. A shrinkage model is also proposed to interpret the dimensional stability for fibers and uni- or biaxially stretched films. A study of stereocomplexation formed by poly(l-lactic acid) and poly(d-lactic acid) is also presented.

Analysis of the procedures used to evaluate suicide crime scenes in Brazil: a statistical approach to interpret reports.

PubMed

Bruni, Aline Thaís; Velho, Jesus Antonio; Ferreira, Arthur Serra Lopes; Tasso, Maria Júlia; Ferrari, Raíssa Santos; Yoshida, Ricardo Luís; Dias, Marcos Salvador; Leite, Vitor Barbanti Pereira

2014-08-01

This study uses statistical techniques to evaluate reports on suicide scenes; it utilizes 80 reports from different locations in Brazil, randomly collected from both federal and state jurisdictions. We aimed to assess a heterogeneous group of cases in order to obtain an overall perspective of the problem. We evaluated variables regarding the characteristics of the crime scene, such as the detected traces (blood, instruments and clothes) that were found and we addressed the methodology employed by the experts. A qualitative approach using basic statistics revealed a wide distribution as to how the issue was addressed in the documents. We examined a quantitative approach involving an empirical equation and we used multivariate procedures to validate the quantitative methodology proposed for this empirical equation. The methodology successfully identified the main differences in the information presented in the reports, showing that there is no standardized method of analyzing evidences. Copyright © 2014 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Lagrangian statistics in compressible isotropic homogeneous turbulence

NASA Astrophysics Data System (ADS)

Yang, Yantao; Wang, Jianchun; Shi, Yipeng; Chen, Shiyi

2011-11-01

In this work we conducted the Direct Numerical Simulation (DNS) of a forced compressible isotropic homogeneous turbulence and investigated the flow statistics from the Lagrangian point of view, namely the statistics is computed following the passive tracers trajectories. The numerical method combined the Eulerian field solver which was developed by Wang et al. (2010, J. Comp. Phys., 229, 5257-5279), and a Lagrangian module for tracking the tracers and recording the data. The Lagrangian probability density functions (p.d.f.'s) have then been calculated for both kinetic and thermodynamic quantities. In order to isolate the shearing part from the compressing part of the flow, we employed the Helmholtz decomposition to decompose the flow field (mainly the velocity field) into the solenoidal and compressive parts. The solenoidal part was compared with the incompressible case, while the compressibility effect showed up in the compressive part. The Lagrangian structure functions and cross-correlation between various quantities will also be discussed. This work was supported in part by the China's Turbulence Program under Grant No.2009CB724101.

Parametric Analysis to Study the Influence of Aerogel-Based Renders’ Components on Thermal and Mechanical Performance

PubMed Central

Ximenes, Sofia; Silva, Ana; Soares, António; Flores-Colen, Inês; de Brito, Jorge

2016-01-01

Statistical models using multiple linear regression are some of the most widely used methods to study the influence of independent variables in a given phenomenon. This study’s objective is to understand the influence of the various components of aerogel-based renders on their thermal and mechanical performance, namely cement (three types), fly ash, aerial lime, silica sand, expanded clay, type of aerogel, expanded cork granules, expanded perlite, air entrainers, resins (two types), and rheological agent. The statistical analysis was performed using SPSS (Statistical Package for Social Sciences), based on 85 mortar mixes produced in the laboratory and on their values of thermal conductivity and compressive strength obtained using tests in small-scale samples. The results showed that aerial lime assumes the main role in improving the thermal conductivity of the mortars. Aerogel type, fly ash, expanded perlite and air entrainers are also relevant components for a good thermal conductivity. Expanded clay can improve the mechanical behavior and aerogel has the opposite effect. PMID:28773460

A statistical approach to the brittle fracture of a multi-phase solid

NASA Technical Reports Server (NTRS)

Liu, W. K.; Lua, Y. I.; Belytschko, T.

1991-01-01

A stochastic damage model is proposed to quantify the inherent statistical distribution of the fracture toughness of a brittle, multi-phase solid. The model, based on the macrocrack-microcrack interaction, incorporates uncertainties in locations and orientations of microcracks. Due to the high concentration of microcracks near the macro-tip, a higher order analysis based on traction boundary integral equations is formulated first for an arbitrary array of cracks. The effects of uncertainties in locations and orientations of microcracks at a macro-tip are analyzed quantitatively by using the boundary integral equations method in conjunction with the computer simulation of the random microcrack array. The short range interactions resulting from surrounding microcracks closet to the main crack tip are investigated. The effects of microcrack density parameter are also explored in the present study. The validity of the present model is demonstrated by comparing its statistical output with the Neville distribution function, which gives correct fits to sets of experimental data from multi-phase solids.

A fast exact simulation method for a class of Markov jump processes

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

Li, Yao, E-mail: yaoli@math.umass.edu; Hu, Lili, E-mail: lilyhu86@gmail.com

2015-11-14

A new method of the stochastic simulation algorithm (SSA), named the Hashing-Leaping method (HLM), for exact simulations of a class of Markov jump processes, is presented in this paper. The HLM has a conditional constant computational cost per event, which is independent of the number of exponential clocks in the Markov process. The main idea of the HLM is to repeatedly implement a hash-table-like bucket sort algorithm for all times of occurrence covered by a time step with length τ. This paper serves as an introduction to this new SSA method. We introduce the method, demonstrate its implementation, analyze itsmore » properties, and compare its performance with three other commonly used SSA methods in four examples. Our performance tests and CPU operation statistics show certain advantages of the HLM for large scale problems.« less

A novel energy conversion based method for velocity correction in molecular dynamics simulations

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

Jin, Hanhui; Collaborative Innovation Center of Advanced Aero-Engine, Hangzhou 310027; Liu, Ningning

2017-05-01

Molecular dynamics (MD) simulation has become an important tool for studying micro- or nano-scale dynamics and the statistical properties of fluids and solids. In MD simulations, there are mainly two approaches: equilibrium and non-equilibrium molecular dynamics (EMD and NEMD). In this paper, a new energy conversion based correction (ECBC) method for MD is developed. Unlike the traditional systematic correction based on macroscopic parameters, the ECBC method is developed strictly based on the physical interaction processes between the pair of molecules or atoms. The developed ECBC method can apply to EMD and NEMD directly. While using MD with this method, themore » difference between the EMD and NEMD is eliminated, and no macroscopic parameters such as external imposed potentials or coefficients are needed. With this method, many limits of using MD are lifted. The application scope of MD is greatly extended.« less

A study of best practices in promoting sustainable urbanization in China.

PubMed

Tan, Yongtao; Xu, Hui; Jiao, Liudan; Ochoa, J Jorge; Shen, Liyin

2017-05-15

In the past twenty years, various sustainable urban development policies and methods had been implemented within China, such that sustainable urbanization is now more widely accepted. Some of these policies and methods have been found to be successful in improving the sustainability of cities in China. Those practices can be defined as the best practices of sustainable urbanization, which can provide useful references for future urban developments. However, few existing studies examine how to learn from these best practices. Combining the methods of content analysis and social network analysis, this paper conducts a comprehensive study on 150 best practices of sustainable urbanization in China. The methods and outcomes of the 150 best practices are identified. The research findings demonstrate the statistics of categories, methods and outcomes of the 150 best practices and the main adopted methods. The achieved outcomes in different regions of China are also presented. Copyright © 2017 Elsevier Ltd. All rights reserved.

Statistical methods used in articles published by the Journal of Periodontal and Implant Science.

PubMed

Choi, Eunsil; Lyu, Jiyoung; Park, Jinyoung; Kim, Hae-Young

2014-12-01

The purposes of this study were to assess the trend of use of statistical methods including parametric and nonparametric methods and to evaluate the use of complex statistical methodology in recent periodontal studies. This study analyzed 123 articles published in the Journal of Periodontal & Implant Science (JPIS) between 2010 and 2014. Frequencies and percentages were calculated according to the number of statistical methods used, the type of statistical method applied, and the type of statistical software used. Most of the published articles considered (64.4%) used statistical methods. Since 2011, the percentage of JPIS articles using statistics has increased. On the basis of multiple counting, we found that the percentage of studies in JPIS using parametric methods was 61.1%. Further, complex statistical methods were applied in only 6 of the published studies (5.0%), and nonparametric statistical methods were applied in 77 of the published studies (38.9% of a total of 198 studies considered). We found an increasing trend towards the application of statistical methods and nonparametric methods in recent periodontal studies and thus, concluded that increased use of complex statistical methodology might be preferred by the researchers in the fields of study covered by JPIS.

[Correlation coefficient-based principle and method for the classification of jump degree in hydrological time series].

PubMed

Wu, Zi Yi; Xie, Ping; Sang, Yan Fang; Gu, Hai Ting

2018-04-01

The phenomenon of jump is one of the importantly external forms of hydrological variabi-lity under environmental changes, representing the adaption of hydrological nonlinear systems to the influence of external disturbances. Presently, the related studies mainly focus on the methods for identifying the jump positions and jump times in hydrological time series. In contrast, few studies have focused on the quantitative description and classification of jump degree in hydrological time series, which make it difficult to understand the environmental changes and evaluate its potential impacts. Here, we proposed a theatrically reliable and easy-to-apply method for the classification of jump degree in hydrological time series, using the correlation coefficient as a basic index. The statistical tests verified the accuracy, reasonability, and applicability of this method. The relationship between the correlation coefficient and the jump degree of series were described using mathematical equation by derivation. After that, several thresholds of correlation coefficients under different statistical significance levels were chosen, based on which the jump degree could be classified into five levels: no, weak, moderate, strong and very strong. Finally, our method was applied to five diffe-rent observed hydrological time series, with diverse geographic and hydrological conditions in China. The results of the classification of jump degrees in those series were closely accorded with their physically hydrological mechanisms, indicating the practicability of our method.

Determination of rate of customer focus in educational programs at Isfahan University of Medical Sciences1 based on students’ viewpoints

PubMed Central

Shams, Assadollah; Yarmohammadian, Mohammad Hosein; Abbarik, Hadi Hayati

2012-01-01

Background: Today, the challenges of quality improvement and customer focus as well as systems development are important and inevitable matters in higher education institutes. There are some highly competitive challenges among educational institutes, including accountability to social needs, increasing costs of education, diversity in educational methods and centers and their consequent increasing competition, and the need for adaptation of new information and knowledge to focus on students as the main customers. Hence, the purpose of this study was to determine the rate of costumer focus based on Isfahan University of Medical Sciences students’ viewpoints and to suggest solutions to improve this rate. Materials and Methods: This was a cross-sectional study carried out in 2011. The statistical population included all the students of seven faculties of Isfahan University of Medical Sciences. According to statistical formulae, the sample size consisted of 384 subjects. Data collection tools included researcher-made questionnaire whose reliability was found to be 87% by Cronbach's alpha coefficient. Finally, using the SPSS statistical software and statistical methods of independent t-test and one-way analysis of variance (ANOVA), Likert scale based data were analyzed. Results: The mean of overall score for customer focus (student-centered) of Isfahan University of Medical Sciences was 46.54. Finally, there was a relation between the mean of overall score for customer focus and gender, educational levels, and students’ faculties. Researcher suggest more investigation between Medical University and others. Conclusion: It is a difference between medical sciences universities and others regarding the customer focus area, since students’ gender must be considered as an effective factor in giving healthcare services quality. In order to improve the customer focus, it is essential to take facilities, field of study, faculties, and syllabus into consideration. PMID:23555127

A primer on the study of transitory dynamics in ecological series using the scale-dependent correlation analysis.

PubMed

Rodríguez-Arias, Miquel Angel; Rodó, Xavier

2004-03-01

Here we describe a practical, step-by-step primer to scale-dependent correlation (SDC) analysis. The analysis of transitory processes is an important but often neglected topic in ecological studies because only a few statistical techniques appear to detect temporary features accurately enough. We introduce here the SDC analysis, a statistical and graphical method to study transitory processes at any temporal or spatial scale. SDC analysis, thanks to the combination of conventional procedures and simple well-known statistical techniques, becomes an improved time-domain analogue of wavelet analysis. We use several simple synthetic series to describe the method, a more complex example, full of transitory features, to compare SDC and wavelet analysis, and finally we analyze some selected ecological series to illustrate the methodology. The SDC analysis of time series of copepod abundances in the North Sea indicates that ENSO primarily is the main climatic driver of short-term changes in population dynamics. SDC also uncovers some long-term, unexpected features in the population. Similarly, the SDC analysis of Nicholson's blowflies data locates where the proposed models fail and provides new insights about the mechanism that drives the apparent vanishing of the population cycle during the second half of the series.

Relation between diagnosis of atheromatous plaque from orthopantomographs and cardiovascular risk factors. A study of cases and control subjects

PubMed Central

Gutierrez-Bonet, Carmen; Leco-Berrocal, Isabel; Fernández-Cáliz, Fernando; Martínez-González, José-María

2016-01-01

Background In recent years the use of orthopantomography has been proposed as a low-cost, reliable and non-invasive diagnostic medium for detecting atheromatous plaque. The purpose of this study was to correlate the presence of carotid calcifications (atheroma) in orthopantomographs with specific risk factors for cerebrovascular accidents (previous cerebrovascular accidents, arterial hypertension, and diabetes). Material and Methods The methods used in this observational study of cases and control subjects followed STROBE (Strengthening the Reporting of Observational studies in Epidemiology) recommendations. The study analyzed a total of 1,602 panoramic radiographs taken for dental diagnostic purposes between January 2010 and February 2014. The main variables analyzed were the incidence of atheromatous plaque and other cardiovascular risk factors. Epidat 3.1 statistical software was used to determine minimum sample sizes and the results were analyzed using PASW (Predictive Analytics Software) Statistics 10.0.0. Results For all the variables analyzed, the correlation between radiographic detection of atheromatous plaque and the presence of cardiovascular disease risk factors was found to be statistically significant (RR>1.5). Conclusions The presence of cardiovascular risk factors is related to the incidence of radiopaque lesions at the carotid artery bifurcation, indicating the presence of atheromatous plaque. Key words:Orthopantomography, atheromatous plaque, cerebrovascular accident, diabetes, arterial hypertension. PMID:26595828

Analysis of variance to assess statistical significance of Laplacian estimation accuracy improvement due to novel variable inter-ring distances concentric ring electrodes.

PubMed

Makeyev, Oleksandr; Joe, Cody; Lee, Colin; Besio, Walter G

2017-07-01

Concentric ring electrodes have shown promise in non-invasive electrophysiological measurement demonstrating their superiority to conventional disc electrodes, in particular, in accuracy of Laplacian estimation. Recently, we have proposed novel variable inter-ring distances concentric ring electrodes. Analytic and finite element method modeling results for linearly increasing distances electrode configurations suggested they may decrease the truncation error resulting in more accurate Laplacian estimates compared to currently used constant inter-ring distances configurations. This study assesses statistical significance of Laplacian estimation accuracy improvement due to novel variable inter-ring distances concentric ring electrodes. Full factorial design of analysis of variance was used with one categorical and two numerical factors: the inter-ring distances, the electrode diameter, and the number of concentric rings in the electrode. The response variables were the Relative Error and the Maximum Error of Laplacian estimation computed using a finite element method model for each of the combinations of levels of three factors. Effects of the main factors and their interactions on Relative Error and Maximum Error were assessed and the obtained results suggest that all three factors have statistically significant effects in the model confirming the potential of using inter-ring distances as a means of improving accuracy of Laplacian estimation.

Detecting associated single-nucleotide polymorphisms on the X chromosome in case control genome-wide association studies.

PubMed

Chen, Zhongxue; Ng, Hon Keung Tony; Li, Jing; Liu, Qingzhong; Huang, Hanwen

2017-04-01

In the past decade, hundreds of genome-wide association studies have been conducted to detect the significant single-nucleotide polymorphisms that are associated with certain diseases. However, most of the data from the X chromosome were not analyzed and only a few significant associated single-nucleotide polymorphisms from the X chromosome have been identified from genome-wide association studies. This is mainly due to the lack of powerful statistical tests. In this paper, we propose a novel statistical approach that combines the information of single-nucleotide polymorphisms on the X chromosome from both males and females in an efficient way. The proposed approach avoids the need of making strong assumptions about the underlying genetic models. Our proposed statistical test is a robust method that only makes the assumption that the risk allele is the same for both females and males if the single-nucleotide polymorphism is associated with the disease for both genders. Through simulation study and a real data application, we show that the proposed procedure is robust and have excellent performance compared to existing methods. We expect that many more associated single-nucleotide polymorphisms on the X chromosome will be identified if the proposed approach is applied to current available genome-wide association studies data.

Improve ay101 teaching by single modifications versus unchanged controls: statistically-supported examples

NASA Astrophysics Data System (ADS)

Byrd, Gene G.; Byrd, Dana

2017-06-01

The two main purposes of this paper on improving Ay101 courses are presentations of (1) some very effective single changes and (2) a method to improve teaching by making just single changes which are evaluated statistically versus a control group class. We show how simple statistical comparison can be done even with Excel in Windows. Of course, other more sophisticated and powerful methods could be used if available. One of several examples to be discussed on our poster is our modification of an online introductory astronomy lab course evaluated by the multiple choice final exam. We composed questions related to the learning objectives of the course modules (LOQs). Students could “talk to themselves” by discursively answering these for extra credit prior to the final. Results were compared to an otherwise identical previous unmodified class. Modified classes showed statistically much better final exam average scores (78% vs. 66%). This modification helped those students who most need help. Students in the lower third of the class preferentially answered the LOQs to improve their scores and the class average on the exam. These results also show the effectiveness of relevant extra credit work. Other examples will be discussed as specific examples of evaluating improvement by making one change and then testing it versus a control. Essentially, this is an evolutionary approach in which single favorable “mutations” are retained and the unfavorable removed. The temptation to make more than one change each time must be resisted!

Sampling based State of Health estimation methodology for Li-ion batteries

NASA Astrophysics Data System (ADS)

Camci, Fatih; Ozkurt, Celil; Toker, Onur; Atamuradov, Vepa

2015-03-01

Storage and management of energy is becoming a more and more important problem every day, especially for electric and hybrid vehicle applications. Li-ion battery is one of the most important technological alternatives for high capacity energy storage and related industrial applications. State of Health (SoH) of Li-ion batteries plays a critical role in their deployment from economic, safety, and availability aspects. Most, if not all, of the studies related to SoH estimation focus on the measurement of a new parameter/physical phenomena related to SoH, or development of new statistical/computational methods using several parameters. This paper presents a new approach for SoH estimation for Li-ion battery systems with multiple battery cells: The main idea is a new circuit topology which enables separation of battery cells into two groups, main and test batteries, whenever a SoH related measurement is to be conducted. All battery cells will be connected to the main battery during the normal mode of operation. When a measurement is needed for SoH estimation, some of the cells will be separated from the main battery, and SoH estimation related measurements will be performed on these units. Compared to classical SoH measurement methods which deal with whole battery system, the proposed method estimates the SoH of the system by separating a small but representative set of cells. While SoH measurements are conducted on these isolated cells, remaining cells in the main battery continue to function in normal mode, albeit in slightly reduced performance levels. Preliminary experimental results are quite promising, and validate the feasibility of the proposed approach. Technical details of the proposed circuit architecture are also summarized in the paper.

Joint Inversion of Geochemical Data and Geophysical Logs for Lithology Identification in CCSD Main Hole

NASA Astrophysics Data System (ADS)

Deng, Chengxiang; Pan, Heping; Luo, Miao

2017-12-01

The Chinese Continental Scientific Drilling (CCSD) main hole is located in the Sulu ultrahigh-pressure metamorphic (UHPM) belt, providing significant opportunities for studying the metamorphic strata structure, kinetics process and tectonic evolution. Lithology identification is the primary and crucial stage for above geoscientific researches. To release the burden of log analyst and improve the efficiency of lithology interpretation, many algorithms have been developed to automate the process of lithology prediction. While traditional statistical techniques, such as discriminant analysis and K-nearest neighbors classifier, are incompetent in extracting nonlinear features of metamorphic rocks from complex geophysical log data; artificial intelligence algorithms are capable of solving nonlinear problems, but most of the algorithms suffer from tuning parameters to be global optimum to establish model rather than local optimum, and also encounter challenges in making the balance between training accuracy and generalization ability. Optimization methods have been applied extensively in the inversion of reservoir parameters of sedimentary formations using well logs. However, it is difficult to obtain accurate solution from the logging response equations of optimization method because of the strong overlapping of nonstationary log signals when applied in metamorphic formations. As oxide contents of each kinds of metamorphic rocks are relatively less overlapping, this study explores an approach, set in a metamorphic formation model and using the Broyden Fletcher Goldfarb Shanno (BFGS) optimization algorithm to identify lithology from oxide data. We first incorporate 11 geophysical logs and lab-collected geochemical data of 47 core samples to construct oxide profile of CCSD main hole by using backwards stepwise multiple regression method, which eliminates irrelevant input logs step by step for higher statistical significance and accuracy. Then we establish oxide response equations in accordance with the metamorphic formation model and employ BFGS algorithm to minimize the objective function. Finally, we identify lithology according to the composition content which accounts for the largest proportion. The results show that lithology identified by the method of this paper is consistent with core description. Moreover, this method demonstrates the benefits of using oxide content as an adhesive to connect logging data with lithology, can make the metamorphic formation model more understandable and accurate, and avoid selecting complex formation model and building nonlinear logging response equations.

[Flavouring estimation of quality of grape wines with use of methods of mathematical statistics].

PubMed

Yakuba, Yu F; Khalaphyan, A A; Temerdashev, Z A; Bessonov, V V; Malinkin, A D

2016-01-01

The questions of forming of wine's flavour integral estimation during the tasting are discussed, the advantages and disadvantages of the procedures are declared. As investigating materials we used the natural white and red wines of Russian manufactures, which were made with the traditional technologies from Vitis Vinifera, straight hybrids, blending and experimental wines (more than 300 different samples). The aim of the research was to set the correlation between the content of wine's nonvolatile matter and wine's tasting quality rating by mathematical statistics methods. The content of organic acids, amino acids and cations in wines were considered as the main factors influencing on the flavor. Basically, they define the beverage's quality. The determination of those components in wine's samples was done by the electrophoretic method «CAPEL». Together with the analytical checking of wine's samples quality the representative group of specialists simultaneously carried out wine's tasting estimation using 100 scores system. The possibility of statistical modelling of correlation of wine's tasting estimation based on analytical data of amino acids and cations determination reasonably describing the wine's flavour was examined. The statistical modelling of correlation between the wine's tasting estimation and the content of major cations (ammonium, potassium, sodium, magnesium, calcium), free amino acids (proline, threonine, arginine) and the taking into account the level of influence on flavour and analytical valuation within fixed limits of quality accordance were done with Statistica. Adequate statistical models which are able to predict tasting estimation that is to determine the wine's quality using the content of components forming the flavour properties have been constructed. It is emphasized that along with aromatic (volatile) substances the nonvolatile matter - mineral substances and organic substances - amino acids such as proline, threonine, arginine influence on wine's flavour properties. It has been shown the nonvolatile components contribute in organoleptic and flavour quality estimation of wines as aromatic volatile substances but they take part in forming the expert's evaluation.

An approach for the assessment of the statistical aspects of the SEA coupling loss factors and the vibrational energy transmission in complex aircraft structures: Experimental investigation and methods benchmark

NASA Astrophysics Data System (ADS)

Bouhaj, M.; von Estorff, O.; Peiffer, A.

2017-09-01

In the application of Statistical Energy Analysis "SEA" to complex assembled structures, a purely predictive model often exhibits errors. These errors are mainly due to a lack of accurate modelling of the power transmission mechanism described through the Coupling Loss Factors (CLF). Experimental SEA (ESEA) is practically used by the automotive and aerospace industry to verify and update the model or to derive the CLFs for use in an SEA predictive model when analytical estimates cannot be made. This work is particularly motivated by the lack of procedures that allow an estimate to be made of the variance and confidence intervals of the statistical quantities when using the ESEA technique. The aim of this paper is to introduce procedures enabling a statistical description of measured power input, vibration energies and the derived SEA parameters. Particular emphasis is placed on the identification of structural CLFs of complex built-up structures comparing different methods. By adopting a Stochastic Energy Model (SEM), the ensemble average in ESEA is also addressed. For this purpose, expressions are obtained to randomly perturb the energy matrix elements and generate individual samples for the Monte Carlo (MC) technique applied to derive the ensemble averaged CLF. From results of ESEA tests conducted on an aircraft fuselage section, the SEM approach provides a better performance of estimated CLFs compared to classical matrix inversion methods. The expected range of CLF values and the synthesized energy are used as quality criteria of the matrix inversion, allowing to assess critical SEA subsystems, which might require a more refined statistical description of the excitation and the response fields. Moreover, the impact of the variance of the normalized vibration energy on uncertainty of the derived CLFs is outlined.

Comparison of Artificial Neural Networks and ARIMA statistical models in simulations of target wind time series

NASA Astrophysics Data System (ADS)

Kolokythas, Kostantinos; Vasileios, Salamalikis; Athanassios, Argiriou; Kazantzidis, Andreas

2015-04-01

The wind is a result of complex interactions of numerous mechanisms taking place in small or large scales, so, the better knowledge of its behavior is essential in a variety of applications, especially in the field of power production coming from wind turbines. In the literature there is a considerable number of models, either physical or statistical ones, dealing with the problem of simulation and prediction of wind speed. Among others, Artificial Neural Networks (ANNs) are widely used for the purpose of wind forecasting and, in the great majority of cases, outperform other conventional statistical models. In this study, a number of ANNs with different architectures, which have been created and applied in a dataset of wind time series, are compared to Auto Regressive Integrated Moving Average (ARIMA) statistical models. The data consist of mean hourly wind speeds coming from a wind farm on a hilly Greek region and cover a period of one year (2013). The main goal is to evaluate the models ability to simulate successfully the wind speed at a significant point (target). Goodness-of-fit statistics are performed for the comparison of the different methods. In general, the ANN showed the best performance in the estimation of wind speed prevailing over the ARIMA models.

Probabilistic assessment method of the non-monotonic dose-responses-Part I: Methodological approach.

PubMed

Chevillotte, Grégoire; Bernard, Audrey; Varret, Clémence; Ballet, Pascal; Bodin, Laurent; Roudot, Alain-Claude

2017-08-01

More and more studies aim to characterize non-monotonic dose response curves (NMDRCs). The greatest difficulty is to assess the statistical plausibility of NMDRCs from previously conducted dose response studies. This difficulty is linked to the fact that these studies present (i) few doses tested, (ii) a low sample size per dose, and (iii) the absence of any raw data. In this study, we propose a new methodological approach to probabilistically characterize NMDRCs. The methodology is composed of three main steps: (i) sampling from summary data to cover all the possibilities that may be presented by the responses measured by dose and to obtain a new raw database, (ii) statistical analysis of each sampled dose-response curve to characterize the slopes and their signs, and (iii) characterization of these dose-response curves according to the variation of the sign in the slope. This method allows characterizing all types of dose-response curves and can be applied both to continuous data and to discrete data. The aim of this study is to present the general principle of this probabilistic method which allows to assess the non-monotonic dose responses curves, and to present some results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Housing decision making methods for initiation development phase process

NASA Astrophysics Data System (ADS)

Zainal, Rozlin; Kasim, Narimah; Sarpin, Norliana; Wee, Seow Ta; Shamsudin, Zarina

2017-10-01

Late delivery and sick housing project problems were attributed to poor decision making. These problems are the string of housing developer that prefers to create their own approach based on their experiences and expertise with the simplest approach by just applying the obtainable standards and rules in decision making. This paper seeks to identify the decision making methods for housing development at the initiation phase in Malaysia. The research involved Delphi method by using questionnaire survey which involved 50 numbers of developers as samples for the primary stage of collect data. However, only 34 developers contributed to the second stage of the information gathering process. At the last stage, only 12 developers were left for the final data collection process. Finding affirms that Malaysian developers prefer to make their investment decisions based on simple interpolation of historical data and using simple statistical or mathematical techniques in producing the required reports. It was suggested that they seemed to skip several important decision-making functions at the primary development stage. These shortcomings were mainly due to time and financial constraints and the lack of statistical or mathematical expertise among the professional and management groups in the developer organisations.

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.

Networks and the Epidemiology of Infectious Disease

PubMed Central

Danon, Leon; Ford, Ashley P.; House, Thomas; Jewell, Chris P.; Keeling, Matt J.; Roberts, Gareth O.; Ross, Joshua V.; Vernon, Matthew C.

2011-01-01

The science of networks has revolutionised research into the dynamics of interacting elements. It could be argued that epidemiology in particular has embraced the potential of network theory more than any other discipline. Here we review the growing body of research concerning the spread of infectious diseases on networks, focusing on the interplay between network theory and epidemiology. The review is split into four main sections, which examine: the types of network relevant to epidemiology; the multitude of ways these networks can be characterised; the statistical methods that can be applied to infer the epidemiological parameters on a realised network; and finally simulation and analytical methods to determine epidemic dynamics on a given network. Given the breadth of areas covered and the ever-expanding number of publications, a comprehensive review of all work is impossible. Instead, we provide a personalised overview into the areas of network epidemiology that have seen the greatest progress in recent years or have the greatest potential to provide novel insights. As such, considerable importance is placed on analytical approaches and statistical methods which are both rapidly expanding fields. Throughout this review we restrict our attention to epidemiological issues. PMID:21437001

[Study on ecological suitability regionalization of Eucommia ulmoides in Guizhou].

PubMed

Kang, Chuan-Zhi; Wang, Qing-Qing; Zhou, Tao; Jiang, Wei-Ke; Xiao, Cheng-Hong; Xie, Yu

2014-05-01

To study the ecological suitability regionalization of Eucommia ulmoides, for selecting artificial planting base and high-quality industrial raw material purchase area of the herb in Guizhou. Based on the investigation of 14 Eucommia ulmoides producing areas, pinoresinol diglucoside content and ecological factors were obtained. Using spatial analysis method to carry on ecological suitability regionalization. Meanwhile, combining pinoresinol diglucoside content, the correlation of major active components and environmental factors were analyzed by statistical analysis. The most suitability planting area of Eucommia ulmoides was the northwest of Guizhou. The distribution of Eucommia ulmoides was mainly affected by the type and pH value of soil, and monthly precipitation. The spatial structure of major active components in Eucommia ulmoides were randomly distributed in global space, but had only one aggregation point which had a high positive correlation in local space. The major active components of Eucommia ulmoides had no correlation with altitude, longitude or latitude. Using the spatial analysis method and statistical analysis method, based on environmental factor and pinoresinol diglucoside content, the ecological suitability regionalization of Eucommia ulmoides can provide reference for the selection of suitable planting area, artificial planting base and directing production layout.

Students perception on the usage of PowerPoint in learning calculus

NASA Astrophysics Data System (ADS)

Othman, Zarith Sofiah; Tarmuji, Nor Habibah; Hilmi, Zulkifli Ab Ghani

2017-04-01

Mathematics is a core subject in most of the science and technology courses and in some social sciences programs. However, the low achievement of students in the subject especially in topics such as Differentiation and Integration is always an issue. Many factors contribute to the low performance such as motivation, environment, method of learning, academic background and others. The purpose of this paper is to determine the perception of learning mathematics using PowerPoint on Integration concepts at the undergraduate level with respect to mathematics anxiety, learning enjoyment, mobility and learning satisfaction. The main content of the PowerPoint presentation focused on the integration method with historical elements as an added value. The study was conducted on 48 students randomly selected from students in computer and applied sciences program as experimental group. Questionnaires were distributed to students to explore their learning experiences. Another 51 students who were taught using the traditional chalkboard method were used as the control group. Both groups were given a test on Integration. The statistical methods used were descriptive statistics and independent sample t-test between the experimental and the control group. The finding showed that most students perceived positively to the PowerPoint presentations with respect to mobility and learning satisfaction. The experimental group performed better than the control group.

Adaptively Tuned Iterative Low Dose CT Image Denoising

PubMed Central

Hashemi, SayedMasoud; Paul, Narinder S.; Beheshti, Soosan; Cobbold, Richard S. C.

2015-01-01

Improving image quality is a critical objective in low dose computed tomography (CT) imaging and is the primary focus of CT image denoising. State-of-the-art CT denoising algorithms are mainly based on iterative minimization of an objective function, in which the performance is controlled by regularization parameters. To achieve the best results, these should be chosen carefully. However, the parameter selection is typically performed in an ad hoc manner, which can cause the algorithms to converge slowly or become trapped in a local minimum. To overcome these issues a noise confidence region evaluation (NCRE) method is used, which evaluates the denoising residuals iteratively and compares their statistics with those produced by additive noise. It then updates the parameters at the end of each iteration to achieve a better match to the noise statistics. By combining NCRE with the fundamentals of block matching and 3D filtering (BM3D) approach, a new iterative CT image denoising method is proposed. It is shown that this new denoising method improves the BM3D performance in terms of both the mean square error and a structural similarity index. Moreover, simulations and patient results show that this method preserves the clinically important details of low dose CT images together with a substantial noise reduction. PMID:26089972

Modeling and optimization of dough recipe for breadsticks

NASA Astrophysics Data System (ADS)

Krivosheev, A. Yu; Ponomareva, E. I.; Zhuravlev, A. A.; Lukina, S. I.; Alekhina, N. N.

2018-05-01

During the work, the authors studied the combined effect of non-traditional raw materials on indicators of quality breadsticks, mathematical methods of experiment planning were applied. The main factors chosen were the dosages of flaxseed flour and grape seed oil. The output parameters were the swelling factor of the products and their strength. Optimization of the formulation composition of the dough for bread sticks was carried out by experimental- statistical methods. As a result of the experiment, mathematical models were constructed in the form of regression equations, adequately describing the process of studies. The statistical processing of the experimental data was carried out by the criteria of Student, Cochran and Fisher (with a confidence probability of 0.95). A mathematical interpretation of the regression equations was given. Optimization of the formulation of the dough for bread sticks was carried out by the method of uncertain Lagrange multipliers. The rational values of the factors were determined: the dosage of flaxseed flour - 14.22% and grape seed oil - 7.8%, ensuring the production of products with the best combination of swelling ratio and strength. On the basis of the data obtained, a recipe and a method for the production of breadsticks "Idea" were proposed (TU (Russian Technical Specifications) 9117-443-02068106-2017).

[Application of chemometrics in composition-activity relationship research of traditional Chinese medicine].

PubMed

Han, Sheng-Nan

2014-07-01

Chemometrics is a new branch of chemistry which is widely applied to various fields of analytical chemistry. Chemometrics can use theories and methods of mathematics, statistics, computer science and other related disciplines to optimize the chemical measurement process and maximize access to acquire chemical information and other information on material systems by analyzing chemical measurement data. In recent years, traditional Chinese medicine has attracted widespread attention. In the research of traditional Chinese medicine, it has been a key problem that how to interpret the relationship between various chemical components and its efficacy, which seriously restricts the modernization of Chinese medicine. As chemometrics brings the multivariate analysis methods into the chemical research, it has been applied as an effective research tool in the composition-activity relationship research of Chinese medicine. This article reviews the applications of chemometrics methods in the composition-activity relationship research in recent years. The applications of multivariate statistical analysis methods (such as regression analysis, correlation analysis, principal component analysis, etc. ) and artificial neural network (such as back propagation artificial neural network, radical basis function neural network, support vector machine, etc. ) are summarized, including the brief fundamental principles, the research contents and the advantages and disadvantages. Finally, the existing main problems and prospects of its future researches are proposed.

Baseline Estimation and Outlier Identification for Halocarbons

NASA Astrophysics Data System (ADS)

Wang, D.; Schuck, T.; Engel, A.; Gallman, F.

2017-12-01

The aim of this paper is to build a baseline model for halocarbons and to statistically identify the outliers under specific conditions. In this paper, time series of regional CFC-11 and Chloromethane measurements was discussed, which taken over the last 4 years at two locations, including a monitoring station at northwest of Frankfurt am Main (Germany) and Mace Head station (Ireland). In addition to analyzing time series of CFC-11 and Chloromethane, more importantly, a statistical approach of outlier identification is also introduced in this paper in order to make a better estimation of baseline. A second-order polynomial plus harmonics are fitted to CFC-11 and chloromethane mixing ratios data. Measurements with large distance to the fitting curve are regard as outliers and flagged. Under specific requirement, the routine is iteratively adopted without the flagged measurements until no additional outliers are found. Both model fitting and the proposed outlier identification method are realized with the help of a programming language, Python. During the period, CFC-11 shows a gradual downward trend. And there is a slightly upward trend in the mixing ratios of Chloromethane. The concentration of chloromethane also has a strong seasonal variation, mostly due to the seasonal cycle of OH. The usage of this statistical method has a considerable effect on the results. This method efficiently identifies a series of outliers according to the standard deviation requirements. After removing the outliers, the fitting curves and trend estimates are more reliable.

The Acute Effects of Upper Extremity Stretching on Throwing Velocity in Baseball Throwers

PubMed Central

Melton, Jason; Delobel, Ashley; Puentedura, Emilio J.

2013-01-01

Purpose. To examine the effects of static and proprioceptive neuromuscular facilitation (PNF) stretching of the shoulder internal rotators on throwing velocity. Subjects. 27 male throwers (mean age = 25.1 years old, SD = 2.4) with adequate knowledge of demonstrable throwing mechanics. Study Design. Randomized crossover trial with repeated measures. Methods. Subjects warmed up, threw 10 pitches at their maximum velocity, were randomly assigned to 1 of 3 stretching protocols (static, PNF, or no stretch), and then repeated their 10 pitches. Velocities were recorded after each pitch and average and peak velocities were recorded after each session. Results. Data were analyzed using a 3 × 2 repeated measures ANOVA. No significant interaction between stretching and throwing velocity was observed. Main effects for time were not statistically significant. Main effects for the stretching groups were statistically significant. Discussion. Results suggest that stretching of the shoulder internal rotators did not significantly affect throwing velocity immediately after stretching. This may be due to the complexity of the throwing task. Conclusions. Stretching may be included in a thrower's warm-up without any effects on throwing velocity. Further research should be performed using a population with more throwing experience and skill. PMID:26464880

DASS: efficient discovery and p-value calculation of substructures in unordered data.

PubMed

Hollunder, Jens; Friedel, Maik; Beyer, Andreas; Workman, Christopher T; Wilhelm, Thomas

2007-01-01

Pattern identification in biological sequence data is one of the main objectives of bioinformatics research. However, few methods are available for detecting patterns (substructures) in unordered datasets. Data mining algorithms mainly developed outside the realm of bioinformatics have been adapted for that purpose, but typically do not determine the statistical significance of the identified patterns. Moreover, these algorithms do not exploit the often modular structure of biological data. We present the algorithm DASS (Discovery of All Significant Substructures) that first identifies all substructures in unordered data (DASS(Sub)) in a manner that is especially efficient for modular data. In addition, DASS calculates the statistical significance of the identified substructures, for sets with at most one element of each type (DASS(P(set))), or for sets with multiple occurrence of elements (DASS(P(mset))). The power and versatility of DASS is demonstrated by four examples: combinations of protein domains in multi-domain proteins, combinations of proteins in protein complexes (protein subcomplexes), combinations of transcription factor target sites in promoter regions and evolutionarily conserved protein interaction subnetworks. The program code and additional data are available at http://www.fli-leibniz.de/tsb/DASS

Measurement and calibration of differential Mueller matrix of distributed targets

NASA Technical Reports Server (NTRS)

Sarabandi, Kamal; Oh, Yisok; Ulaby, Fawwaz T.

1992-01-01

A rigorous method for calibrating polarimetric backscatter measurements of distributed targets is presented. By characterizing the radar distortions over the entire mainlobe of the antenna, the differential Mueller matrix is derived from the measured scattering matrices with a high degree of accuracy. It is shown that the radar distortions can be determined by measuring the polarimetric response of a metallic sphere over the main lobe of the antenna. Comparison of results obtained with the new algorithm with the results derived from the old calibration method show that the discrepancy between the two methods is less than 1 dB for the backscattering coefficients. The discrepancy is more drastic for the phase-difference statistics, indicating that removal of the radar distortions from the cross products of the scattering matrix elements cannot be accomplished with the traditional calibration methods.

Ground target recognition using rectangle estimation.

PubMed

Grönwall, Christina; Gustafsson, Fredrik; Millnert, Mille

2006-11-01

We propose a ground target recognition method based on 3-D laser radar data. The method handles general 3-D scattered data. It is based on the fact that man-made objects of complex shape can be decomposed to a set of rectangles. The ground target recognition method consists of four steps; 3-D size and orientation estimation, target segmentation into parts of approximately rectangular shape, identification of segments that represent the target's functional/main parts, and target matching with CAD models. The core in this approach is rectangle estimation. The performance of the rectangle estimation method is evaluated statistically using Monte Carlo simulations. A case study on tank recognition is shown, where 3-D data from four fundamentally different types of laser radar systems are used. Although the approach is tested on rather few examples, we believe that the approach is promising.

Meta-analysis and The Cochrane Collaboration: 20 years of the Cochrane Statistical Methods Group

PubMed Central

2013-01-01

The Statistical Methods Group has played a pivotal role in The Cochrane Collaboration over the past 20 years. The Statistical Methods Group has determined the direction of statistical methods used within Cochrane reviews, developed guidance for these methods, provided training, and continued to discuss and consider new and controversial issues in meta-analysis. The contribution of Statistical Methods Group members to the meta-analysis literature has been extensive and has helped to shape the wider meta-analysis landscape. In this paper, marking the 20th anniversary of The Cochrane Collaboration, we reflect on the history of the Statistical Methods Group, beginning in 1993 with the identification of aspects of statistical synthesis for which consensus was lacking about the best approach. We highlight some landmark methodological developments that Statistical Methods Group members have contributed to in the field of meta-analysis. We discuss how the Group implements and disseminates statistical methods within The Cochrane Collaboration. Finally, we consider the importance of robust statistical methodology for Cochrane systematic reviews, note research gaps, and reflect on the challenges that the Statistical Methods Group faces in its future direction. PMID:24280020

Prediction of CpG-island function: CpG clustering vs. sliding-window methods

PubMed Central

2010-01-01

Background Unmethylated stretches of CpG dinucleotides (CpG islands) are an outstanding property of mammal genomes. Conventionally, these regions are detected by sliding window approaches using %G + C, CpG observed/expected ratio and length thresholds as main parameters. Recently, clustering methods directly detect clusters of CpG dinucleotides as a statistical property of the genome sequence. Results We compare sliding-window to clustering (i.e. CpGcluster) predictions by applying new ways to detect putative functionality of CpG islands. Analyzing the co-localization with several genomic regions as a function of window size vs. statistical significance (p-value), CpGcluster shows a higher overlap with promoter regions and highly conserved elements, at the same time showing less overlap with Alu retrotransposons. The major difference in the prediction was found for short islands (CpG islets), often exclusively predicted by CpGcluster. Many of these islets seem to be functional, as they are unmethylated, highly conserved and/or located within the promoter region. Finally, we show that window-based islands can spuriously overlap several, differentially regulated promoters as well as different methylation domains, which might indicate a wrong merge of several CpG islands into a single, very long island. The shorter CpGcluster islands seem to be much more specific when concerning the overlap with alternative transcription start sites or the detection of homogenous methylation domains. Conclusions The main difference between sliding-window approaches and clustering methods is the length of the predicted islands. Short islands, often differentially methylated, are almost exclusively predicted by CpGcluster. This suggests that CpGcluster may be the algorithm of choice to explore the function of these short, but putatively functional CpG islands. PMID:20500903

Exploring the relationship between the engineering and physical sciences and the health and life sciences by advanced bibliometric methods.

PubMed

Waltman, Ludo; van Raan, Anthony F J; Smart, Sue

2014-01-01

We investigate the extent to which advances in the health and life sciences (HLS) are dependent on research in the engineering and physical sciences (EPS), particularly physics, chemistry, mathematics, and engineering. The analysis combines two different bibliometric approaches. The first approach to analyze the 'EPS-HLS interface' is based on term map visualizations of HLS research fields. We consider 16 clinical fields and five life science fields. On the basis of expert judgment, EPS research in these fields is studied by identifying EPS-related terms in the term maps. In the second approach, a large-scale citation-based network analysis is applied to publications from all fields of science. We work with about 22,000 clusters of publications, each representing a topic in the scientific literature. Citation relations are used to identify topics at the EPS-HLS interface. The two approaches complement each other. The advantages of working with textual data compensate for the limitations of working with citation relations and the other way around. An important advantage of working with textual data is in the in-depth qualitative insights it provides. Working with citation relations, on the other hand, yields many relevant quantitative statistics. We find that EPS research contributes to HLS developments mainly in the following five ways: new materials and their properties; chemical methods for analysis and molecular synthesis; imaging of parts of the body as well as of biomaterial surfaces; medical engineering mainly related to imaging, radiation therapy, signal processing technology, and other medical instrumentation; mathematical and statistical methods for data analysis. In our analysis, about 10% of all EPS and HLS publications are classified as being at the EPS-HLS interface. This percentage has remained more or less constant during the past decade.

Theory and computation of non-RRKM lifetime distributions and rates in chemical systems with three or more degrees of freedom

NASA Astrophysics Data System (ADS)

Gabern, Frederic; Koon, Wang S.; Marsden, Jerrold E.; Ross, Shane D.

2005-11-01

The computation, starting from basic principles, of chemical reaction rates in realistic systems (with three or more degrees of freedom) has been a longstanding goal of the chemistry community. Our current work, which merges tube dynamics with Monte Carlo methods provides some key theoretical and computational tools for achieving this goal. We use basic tools of dynamical systems theory, merging the ideas of Koon et al. [W.S. Koon, M.W. Lo, J.E. Marsden, S.D. Ross, Heteroclinic connections between periodic orbits and resonance transitions in celestial mechanics, Chaos 10 (2000) 427-469.] and De Leon et al. [N. De Leon, M.A. Mehta, R.Q. Topper, Cylindrical manifolds in phase space as mediators of chemical reaction dynamics and kinetics. I. Theory, J. Chem. Phys. 94 (1991) 8310-8328.], particularly the use of invariant manifold tubes that mediate the reaction, into a tool for the computation of lifetime distributions and rates of chemical reactions and scattering phenomena, even in systems that exhibit non-statistical behavior. Previously, the main problem with the application of tube dynamics has been with the computation of volumes in phase spaces of high dimension. The present work provides a starting point for overcoming this hurdle with some new ideas and implements them numerically. Specifically, an algorithm that uses tube dynamics to provide the initial bounding box for a Monte Carlo volume determination is used. The combination of a fine scale method for determining the phase space structure (invariant manifold theory) with statistical methods for volume computations (Monte Carlo) is the main contribution of this paper. The methodology is applied here to a three degree of freedom model problem and may be useful for higher degree of freedom systems as well.

Exploring the Relationship between the Engineering and Physical Sciences and the Health and Life Sciences by Advanced Bibliometric Methods

PubMed Central

Waltman, Ludo; van Raan, Anthony F. J.; Smart, Sue

2014-01-01

We investigate the extent to which advances in the health and life sciences (HLS) are dependent on research in the engineering and physical sciences (EPS), particularly physics, chemistry, mathematics, and engineering. The analysis combines two different bibliometric approaches. The first approach to analyze the ‘EPS-HLS interface’ is based on term map visualizations of HLS research fields. We consider 16 clinical fields and five life science fields. On the basis of expert judgment, EPS research in these fields is studied by identifying EPS-related terms in the term maps. In the second approach, a large-scale citation-based network analysis is applied to publications from all fields of science. We work with about 22,000 clusters of publications, each representing a topic in the scientific literature. Citation relations are used to identify topics at the EPS-HLS interface. The two approaches complement each other. The advantages of working with textual data compensate for the limitations of working with citation relations and the other way around. An important advantage of working with textual data is in the in-depth qualitative insights it provides. Working with citation relations, on the other hand, yields many relevant quantitative statistics. We find that EPS research contributes to HLS developments mainly in the following five ways: new materials and their properties; chemical methods for analysis and molecular synthesis; imaging of parts of the body as well as of biomaterial surfaces; medical engineering mainly related to imaging, radiation therapy, signal processing technology, and other medical instrumentation; mathematical and statistical methods for data analysis. In our analysis, about 10% of all EPS and HLS publications are classified as being at the EPS-HLS interface. This percentage has remained more or less constant during the past decade. PMID:25360616

An Improved Image Ringing Evaluation Method with Weighted Sum of Gray Extreme Value

NASA Astrophysics Data System (ADS)

Yang, Ling; Meng, Yanhua; Wang, Bo; Bai, Xu

2018-03-01

Blind image restoration algorithm usually produces ringing more obvious at the edges. Ringing phenomenon is mainly affected by noise, species of restoration algorithm, and the impact of the blur kernel estimation during restoration. Based on the physical mechanism of ringing, a method of evaluating the ringing on blind restoration images is proposed. The method extracts the ringing image overshooting and ripple region to make the weighted statistics for the regional gradient value. According to the weights set by multiple experiments, the edge information is used to characterize the details of the edge to determine the weight, quantify the seriousness of the ring effect, and propose the evaluation method of the ringing caused by blind restoration. The experimental results show that the method can effectively evaluate the ring effect in the restoration images under different restoration algorithms and different restoration parameters. The evaluation results are consistent with the visual evaluation results.

A comparison between IMSC, PI and MIMSC methods in controlling the vibration of flexible systems

NASA Technical Reports Server (NTRS)

Baz, A.; Poh, S.

1987-01-01

A comparative study is presented between three active control algorithms which have proven to be successful in controlling the vibrations of large flexible systems. These algorithms are: the Independent Modal Space Control (IMSC), the Pseudo-inverse (PI), and the Modified Independent Modal Space Control (MIMSC). Emphasis is placed on demonstrating the effectiveness of the MIMSC method in controlling the vibration of large systems with small number of actuators by using an efficient time sharing strategy. Such a strategy favors the MIMSC over the IMSC method, which requires a large number of actuators to control equal number of modes, and also over the PI method which attempts to control large number of modes with smaller number of actuators through the use of an in-exact statistical realization of a modal controller. Numerical examples are presented to illustrate the main features of the three algorithms and the merits of the MIMSC method.

Comparing the index-flood and multiple-regression methods using L-moments

NASA Astrophysics Data System (ADS)

Malekinezhad, H.; Nachtnebel, H. P.; Klik, A.

In arid and semi-arid regions, the length of records is usually too short to ensure reliable quantile estimates. Comparing index-flood and multiple-regression analyses based on L-moments was the main objective of this study. Factor analysis was applied to determine main influencing variables on flood magnitude. Ward’s cluster and L-moments approaches were applied to several sites in the Namak-Lake basin in central Iran to delineate homogeneous regions based on site characteristics. Homogeneity test was done using L-moments-based measures. Several distributions were fitted to the regional flood data and index-flood and multiple-regression methods as two regional flood frequency methods were compared. The results of factor analysis showed that length of main waterway, compactness coefficient, mean annual precipitation, and mean annual temperature were the main variables affecting flood magnitude. The study area was divided into three regions based on the Ward’s method of clustering approach. The homogeneity test based on L-moments showed that all three regions were acceptably homogeneous. Five distributions were fitted to the annual peak flood data of three homogeneous regions. Using the L-moment ratios and the Z-statistic criteria, GEV distribution was identified as the most robust distribution among five candidate distributions for all the proposed sub-regions of the study area, and in general, it was concluded that the generalised extreme value distribution was the best-fit distribution for every three regions. The relative root mean square error (RRMSE) measure was applied for evaluating the performance of the index-flood and multiple-regression methods in comparison with the curve fitting (plotting position) method. In general, index-flood method gives more reliable estimations for various flood magnitudes of different recurrence intervals. Therefore, this method should be adopted as regional flood frequency method for the study area and the Namak-Lake basin in central Iran. To estimate floods of various return periods for gauged catchments in the study area, the mean annual peak flood of the catchments may be multiplied by corresponding values of the growth factors, and computed using the GEV distribution.

Reconstructing the size distribution of the primordial Main Belt

NASA Astrophysics Data System (ADS)

Tsirvoulis, G.; Morbidelli, A.; Delbo, M.; Tsiganis, K.

2018-04-01

In this work we aim to constrain the slope of the size distribution of main-belt asteroids, at their primordial state. To do so we turn out attention to the part of the main asteroid belt between 2.82 and 2.96 AU, the so-called "pristine zone", which has a low number density of asteroids and few, well separated asteroid families. Exploiting these unique characteristics, and using a modified version of the hierarchical clustering method we are able to remove the majority of asteroid family members from the region. The remaining, background asteroids should be of primordial origin, as the strong 5/2 and 7/3 mean-motion resonances with Jupiter inhibit transfer of asteroids to and from the neighboring regions. The size-frequency distribution of asteroids in the size range 17 < D(km) < 70 has a slope q ≃ - 1 . Using Monte-Carlo methods, we are able to simulate, and compensate for the collisional and dynamical evolution of the asteroid population, and get an upper bound for its size distribution slope q = - 1.43 . In addition, applying the same 'family extraction' method to the neighboring regions, i.e. the middle and outer belts, and comparing the size distributions of the respective background populations, we find statistical evidence that no large asteroid families of primordial origin had formed in the middle or pristine zones.

One-dimensional anyons under three-body interactions.

NASA Astrophysics Data System (ADS)

Silva-Valencia, Jereson; Arcila-Forero, Julian; Franco, Roberto

Anyons are a third class of particles with nontrivial exchange statistics, particles carrying fractional statistics that interpolate between bosons and fermions. In the last years, it has been made some proposals to emulate an anyon gas by confining bosonic atoms in optical lattices [ Nat. Commun. 2, 361 (2011)]. In this work, we studied the ground state of anyons interacting through local three-body terms in one-dimension, motivated by recent experimental and theoretical studies about multi-body interactions in cold atoms setups. We used the density-matrix renormalization group method to find the phase diagram and the von Neumann block entropy to determinate the critical point position. The main quantum phases found are the superfluid and the Mott insulator ones. For the statistical angle θ = π /4, the phase diagram shows that the Mott lobes are surrounded by superfluid regions, the Mott lobes increase with the density and the first Mott lobe has two anyons per site. We found that a Mott lobe with one anyon per site, it is possible for larger statistical angles, a fact that it is impossible with bosons. DIBE- Universidad Nacional de Colombia and Departamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCAS) (Grant No. FP44842-057-2015).

Assessment and statistics of surgically induced astigmatism.

PubMed

Naeser, Kristian

2008-05-01

The aim of the thesis was to develop methods for assessment of surgically induced astigmatism (SIA) in individual eyes, and in groups of eyes. The thesis is based on 12 peer-reviewed publications, published over a period of 16 years. In these publications older and contemporary literature was reviewed(1). A new method (the polar system) for analysis of SIA was developed. Multivariate statistical analysis of refractive data was described(2-4). Clinical validation studies were performed. The description of a cylinder surface with polar values and differential geometry was compared. The main results were: refractive data in the form of sphere, cylinder and axis may define an individual patient or data set, but are unsuited for mathematical and statistical analyses(1). The polar value system converts net astigmatisms to orthonormal components in dioptric space. A polar value is the difference in meridional power between two orthogonal meridians(5,6). Any pair of polar values, separated by an arch of 45 degrees, characterizes a net astigmatism completely(7). The two polar values represent the net curvital and net torsional power over the chosen meridian(8). The spherical component is described by the spherical equivalent power. Several clinical studies demonstrated the efficiency of multivariate statistical analysis of refractive data(4,9-11). Polar values and formal differential geometry describe astigmatic surfaces with similar concepts and mathematical functions(8). Other contemporary methods, such as Long's power matrix, Holladay's and Alpins' methods, Zernike(12) and Fourier analyses(8), are correlated to the polar value system. In conclusion, analysis of SIA should be performed with polar values or other contemporary component systems. The study was supported by Statens Sundhedsvidenskabeligt Forskningsråd, Cykelhandler P. Th. Rasmussen og Hustrus Mindelegat, Hotelejer Carl Larsen og Hustru Nicoline Larsens Mindelegat, Landsforeningen til Vaern om Synet, Forskningsinitiativet for Arhus Amt, Alcon Denmark, and Desirée and Niels Ydes Fond.

Comparative analysis of a nontraditional general chemistry textbook and selected traditional textbooks used in Texas community colleges

NASA Astrophysics Data System (ADS)

Salvato, Steven Walter

The purpose of this study was to analyze questions within the chapters of a nontraditional general chemistry textbook and the four general chemistry textbooks most widely used by Texas community colleges in order to determine if the questions require higher- or lower-order thinking according to Bloom's taxonomy. The study employed quantitative methods. Bloom's taxonomy (Bloom, Engelhart, Furst, Hill, & Krathwohl, 1956) was utilized as the main instrument in the study. Additional tools were used to help classify the questions into the proper category of the taxonomy (McBeath, 1992; Metfessel, Michael, & Kirsner, 1969). The top four general chemistry textbooks used in Texas community colleges and Chemistry: A Project of the American Chemical Society (Bell et al., 2005) were analyzed during the fall semester of 2010 in order to categorize the questions within the chapters into one of the six levels of Bloom's taxonomy. Two coders were used to assess reliability. The data were analyzed using descriptive and inferential methods. The descriptive method involved calculation of the frequencies and percentages of coded questions from the books as belonging to the six categories of the taxonomy. Questions were dichotomized into higher- and lower-order thinking questions. The inferential methods involved chi-square tests of association to determine if there were statistically significant differences among the four traditional college general chemistry textbooks in the proportions of higher- and lower-order questions and if there were statistically significant differences between the nontraditional chemistry textbook and the four traditional general chemistry textbooks. Findings indicated statistically significant differences among the four textbooks frequently used in Texas community colleges in the number of higher- and lower-level questions. Statistically significant differences were also found among the four textbooks and the nontraditional textbook. After the analysis of the data, conclusions were drawn, implications for practice were delineated, and recommendations for future research were given.

Summary of water body extraction methods based on ZY-3 satellite

NASA Astrophysics Data System (ADS)

Zhu, Yu; Sun, Li Jian; Zhang, Chuan Yin

2017-12-01

Extracting from remote sensing images is one of the main means of water information extraction. Affected by spectral characteristics, many methods can be not applied to the satellite image of ZY-3. To solve this problem, we summarize the extraction methods for ZY-3 and analyze the extraction results of existing methods. According to the characteristics of extraction results, the method of WI& single band threshold and the method of texture filtering based on probability statistics are explored. In addition, the advantages and disadvantages of all methods are compared, which provides some reference for the research of water extraction from images. The obtained conclusions are as follows. 1) NIR has higher water sensitivity, consequently when the surface reflectance in the study area is less similar to water, using single band threshold method or multi band operation can obtain the ideal effect. 2) Compared with the water index and HIS optimal index method, object extraction method based on rules, which takes into account not only the spectral information of the water, but also space and texture feature constraints, can obtain better extraction effect, yet the image segmentation process is time consuming and the definition of the rules requires a certain knowledge. 3) The combination of the spectral relationship and water index can eliminate the interference of the shadow to a certain extent. When there is less small water or small water is not considered in further study, texture filtering based on probability statistics can effectively reduce the noises in result and avoid mixing shadows or paddy field with water in a certain extent.

3D automatic anatomy recognition based on iterative graph-cut-ASM

NASA Astrophysics Data System (ADS)

Chen, Xinjian; Udupa, Jayaram K.; Bagci, Ulas; Alavi, Abass; Torigian, Drew A.

2010-02-01

We call the computerized assistive process of recognizing, delineating, and quantifying organs and tissue regions in medical imaging, occurring automatically during clinical image interpretation, automatic anatomy recognition (AAR). The AAR system we are developing includes five main parts: model building, object recognition, object delineation, pathology detection, and organ system quantification. In this paper, we focus on the delineation part. For the modeling part, we employ the active shape model (ASM) strategy. For recognition and delineation, we integrate several hybrid strategies of combining purely image based methods with ASM. In this paper, an iterative Graph-Cut ASM (IGCASM) method is proposed for object delineation. An algorithm called GC-ASM was presented at this symposium last year for object delineation in 2D images which attempted to combine synergistically ASM and GC. Here, we extend this method to 3D medical image delineation. The IGCASM method effectively combines the rich statistical shape information embodied in ASM with the globally optimal delineation capability of the GC method. We propose a new GC cost function, which effectively integrates the specific image information with the ASM shape model information. The proposed methods are tested on a clinical abdominal CT data set. The preliminary results show that: (a) it is feasible to explicitly bring prior 3D statistical shape information into the GC framework; (b) the 3D IGCASM delineation method improves on ASM and GC and can provide practical operational time on clinical images.

Interference in the classical probabilistic model and its representation in complex Hilbert space

NASA Astrophysics Data System (ADS)

Khrennikov, Andrei Yu.

2005-10-01

The notion of a context (complex of physical conditions, that is to say: specification of the measurement setup) is basic in this paper.We show that the main structures of quantum theory (interference of probabilities, Born's rule, complex probabilistic amplitudes, Hilbert state space, representation of observables by operators) are present already in a latent form in the classical Kolmogorov probability model. However, this model should be considered as a calculus of contextual probabilities. In our approach it is forbidden to consider abstract context independent probabilities: “first context and only then probability”. We construct the representation of the general contextual probabilistic dynamics in the complex Hilbert space. Thus dynamics of the wave function (in particular, Schrödinger's dynamics) can be considered as Hilbert space projections of a realistic dynamics in a “prespace”. The basic condition for representing of the prespace-dynamics is the law of statistical conservation of energy-conservation of probabilities. In general the Hilbert space projection of the “prespace” dynamics can be nonlinear and even irreversible (but it is always unitary). Methods developed in this paper can be applied not only to quantum mechanics, but also to classical statistical mechanics. The main quantum-like structures (e.g., interference of probabilities) might be found in some models of classical statistical mechanics. Quantum-like probabilistic behavior can be demonstrated by biological systems. In particular, it was recently found in some psychological experiments.

Statistical estimation via convex optimization for trending and performance monitoring

NASA Astrophysics Data System (ADS)

Samar, Sikandar

This thesis presents an optimization-based statistical estimation approach to find unknown trends in noisy data. A Bayesian framework is used to explicitly take into account prior information about the trends via trend models and constraints. The main focus is on convex formulation of the Bayesian estimation problem, which allows efficient computation of (globally) optimal estimates. There are two main parts of this thesis. The first part formulates trend estimation in systems described by known detailed models as a convex optimization problem. Statistically optimal estimates are then obtained by maximizing a concave log-likelihood function subject to convex constraints. We consider the problem of increasing problem dimension as more measurements become available, and introduce a moving horizon framework to enable recursive estimation of the unknown trend by solving a fixed size convex optimization problem at each horizon. We also present a distributed estimation framework, based on the dual decomposition method, for a system formed by a network of complex sensors with local (convex) estimation. Two specific applications of the convex optimization-based Bayesian estimation approach are described in the second part of the thesis. Batch estimation for parametric diagnostics in a flight control simulation of a space launch vehicle is shown to detect incipient fault trends despite the natural masking properties of feedback in the guidance and control loops. Moving horizon approach is used to estimate time varying fault parameters in a detailed nonlinear simulation model of an unmanned aerial vehicle. An excellent performance is demonstrated in the presence of winds and turbulence.

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.

The application of remote sensing image sea ice monitoring method in Bohai Bay based on C4.5 decision tree algorithm

NASA Astrophysics Data System (ADS)

Ye, Wei; Song, Wei

2018-02-01

In The Paper, the remote sensing monitoring of sea ice problem was turned into a classification problem in data mining. Based on the statistic of the related band data of HJ1B remote sensing images, the main bands of HJ1B images related with the reflectance of seawater and sea ice were found. On the basis, the decision tree rules for sea ice monitoring were constructed by the related bands found above, and then the rules were applied to Liaodong Bay area seriously covered by sea ice for sea ice monitoring. The result proved that the method is effective.

Statistical research into low-power solar flares. Main phase duration

NASA Astrophysics Data System (ADS)

Borovik, Aleksandr; Zhdanov, Anton

2017-12-01

This paper is a sequel to earlier papers on time parameters of solar flares in the Hα line. Using data from the International Flare Patrol, an electronic database of solar flares for the period 1972-2010 has been created. The statistical analysis of the duration of the main phase has shown that it increases with increasing flare class and brightness. It has been found that the duration of the main phase depends on the type and features of development of solar flares. Flares with one brilliant point have the shortest main phase; flares with several intensity maxima and two-ribbon flares, the longest one. We have identified more than 3000 cases with an ultra-long duration of the main phase (more than 60 minutes). For 90% of such flares the duration of the main phase is 2-3 hrs, but sometimes it reaches 12 hrs.

Numerical and Statistical Analysis of Fractures in Mechanically Dissimilar Rocks of Limestone Interbedded with Shale from Nash Point in Bristol Channel, South Wales, UK.

NASA Astrophysics Data System (ADS)

Adeoye-Akinde, K.; Gudmundsson, A.

2017-12-01

Heterogeneity and anisotropy, especially with layered strata within the same reservoir, makes the geometry and permeability of an in-situ fracture network challenging to forecast. This study looks at outcrops analogous to reservoir rocks for a better understanding of in-situ fracture networks and permeability, especially fracture formation, propagation, and arrest/deflection. Here, fracture geometry (e.g. length and aperture) from interbedded limestone and shale is combined with statistical and numerical modelling (using the Finite Element Method) to better forecast fracture network properties and permeability. The main aim is to bridge the gap between fracture data obtained at the core level (cm-scale) and at the seismic level (km-scale). Analysis has been made of geometric properties of over 250 fractures from the blue Lias in Nash Point, UK. As fractures propagate, energy is required to keep them going, and according to the laws of thermodynamics, this energy can be linked to entropy. As fractures grow, entropy increases, therefore, the result shows a strong linear correlation between entropy and the scaling exponent of fracture length and aperture-size distributions. Modelling is used to numerically simulate the stress/fracture behaviour in mechanically dissimilar rocks. Results show that the maximum principal compressive stress orientation changes in the host rock as the fracture-induced stress tip moves towards a more compliant (shale) layer. This behaviour can be related to the three mechanisms of fracture arrest/deflection at an interface, namely: elastic mismatch, stress barrier and Cook-Gordon debonding. Tensile stress concentrates at the contact between the stratigraphic layers, ahead of and around the propagating fracture. However, as shale stiffens with time, the stresses concentrated at the contact start to dissipate into it. This can happen in nature through diagenesis, and with greater depth of burial. This study also investigates how induced fractures propagate and interact with existing discontinuities in layered rocks using analogue modelling. Further work will introduce the Maximum Entropy Method for more accurate statistical modelling. This method is mainly useful to forecast likely fracture-size probability distributions from incomplete subsurface information.

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

Ade, P. A. R.; Aghanim, N.; Akrami, Y.

In this paper, we test the statistical isotropy and Gaussianity of the cosmic microwave background (CMB) anisotropies using observations made by the Planck satellite. Our results are based mainly on the full Planck mission for temperature, but also include some polarization measurements. In particular, we consider the CMB anisotropy maps derived from the multi-frequency Planck data by several component-separation methods. For the temperature anisotropies, we find excellent agreement between results based on these sky maps over both a very large fraction of the sky and a broad range of angular scales, establishing that potential foreground residuals do not affect ourmore » studies. Tests of skewness, kurtosis, multi-normality, N-point functions, and Minkowski functionals indicate consistency with Gaussianity, while a power deficit at large angular scales is manifested in several ways, for example low map variance. The results of a peak statistics analysis are consistent with the expectations of a Gaussian random field. The “Cold Spot” is detected with several methods, including map kurtosis, peak statistics, and mean temperature profile. We thoroughly probe the large-scale dipolar power asymmetry, detecting it with several independent tests, and address the subject of a posteriori correction. Tests of directionality suggest the presence of angular clustering from large to small scales, but at a significance that is dependent on the details of the approach. We perform the first examination of polarization data, finding the morphology of stacked peaks to be consistent with the expectations of statistically isotropic simulations. Finally, where they overlap, these results are consistent with the Planck 2013 analysis based on the nominal mission data and provide our most thorough view of the statistics of the CMB fluctuations to date.« less

Hydraulic and separation characteristics of an industrial gas centrifuge calculated with neural networks

NASA Astrophysics Data System (ADS)

Butov, Vladimir; Timchenko, Sergey; Ushakov, Ivan; Golovkov, Nikita; Poberezhnikov, Andrey

2018-03-01

Single gas centrifuge (GC) is generally used for the separation of binary mixtures of isotopes. Processes taking place within the centrifuge are complex and non-linear. Their characteristics can change over time with long-term operation due to wear of the main structural elements of the GC construction. The paper is devoted to the determination of basic operation parameters of the centrifuge with the help of neural networks. We have developed a method for determining the parameters of the industrial GC operation by processing statistical data. In this work, we have constructed a neural network that is capable of determining the main hydraulic and separation characteristics of the gas centrifuge, depending on the geometric dimensions of the gas centrifuge, load value, and rotor speed.

Cluster analysis as a prediction tool for pregnancy outcomes.

PubMed

Banjari, Ines; Kenjerić, Daniela; Šolić, Krešimir; Mandić, Milena L

2015-03-01

Considering specific physiology changes during gestation and thinking of pregnancy as a "critical window", classification of pregnant women at early pregnancy can be considered as crucial. The paper demonstrates the use of a method based on an approach from intelligent data mining, cluster analysis. Cluster analysis method is a statistical method which makes possible to group individuals based on sets of identifying variables. The method was chosen in order to determine possibility for classification of pregnant women at early pregnancy to analyze unknown correlations between different variables so that the certain outcomes could be predicted. 222 pregnant women from two general obstetric offices' were recruited. The main orient was set on characteristics of these pregnant women: their age, pre-pregnancy body mass index (BMI) and haemoglobin value. Cluster analysis gained a 94.1% classification accuracy rate with three branch- es or groups of pregnant women showing statistically significant correlations with pregnancy outcomes. The results are showing that pregnant women both of older age and higher pre-pregnancy BMI have a significantly higher incidence of delivering baby of higher birth weight but they gain significantly less weight during pregnancy. Their babies are also longer, and these women have significantly higher probability for complications during pregnancy (gestosis) and higher probability of induced or caesarean delivery. We can conclude that the cluster analysis method can appropriately classify pregnant women at early pregnancy to predict certain outcomes.

Inverse probability weighting and doubly robust methods in correcting the effects of non-response in the reimbursed medication and self-reported turnout estimates in the ATH survey.

PubMed

Härkänen, Tommi; Kaikkonen, Risto; Virtala, Esa; Koskinen, Seppo

2014-11-06

To assess the nonresponse rates in a questionnaire survey with respect to administrative register data, and to correct the bias statistically. The Finnish Regional Health and Well-being Study (ATH) in 2010 was based on a national sample and several regional samples. Missing data analysis was based on socio-demographic register data covering the whole sample. Inverse probability weighting (IPW) and doubly robust (DR) methods were estimated using the logistic regression model, which was selected using the Bayesian information criteria. The crude, weighted and true self-reported turnout in the 2008 municipal election and prevalences of entitlements to specially reimbursed medication, and the crude and weighted body mass index (BMI) means were compared. The IPW method appeared to remove a relatively large proportion of the bias compared to the crude prevalence estimates of the turnout and the entitlements to specially reimbursed medication. Several demographic factors were shown to be associated with missing data, but few interactions were found. Our results suggest that the IPW method can improve the accuracy of results of a population survey, and the model selection provides insight into the structure of missing data. However, health-related missing data mechanisms are beyond the scope of statistical methods, which mainly rely on socio-demographic information to correct the results.

Study on 1H-NMR fingerprinting of Rhodiolae Crenulatae Radix et Rhizoma.

PubMed

Wen, Shi-yuan; Zhou, Jiang-tao; Chen, Yan-yan; Ding, Li-qin; Jiang, Miao-miao

2015-07-01

Nuclear magnetic resonance (1H-NMR) fingerprint of Rhodiola rosea medicinal materials was established, and used to distinguish the quality of raw materials from different sources. Pulse sequence for water peak inhibition was employed to acquire 1H-NMR spectra with the temperature at 298 K and spectrometer frequency of 400.13 MHz. Through subsection integral method, the obtained NMR data was subjected to similarity analysis and principal component analysis (PCA). 10 batches raw materials of Rhodiola rosea from different origins were successfully distinguished by PCA. The statistical results indicated that rhodiola glucoside, butyl alcohol, maleic acid and alanine were the main differential ingredients. This method provides an auxiliary method of Chinese quality approach to evaluate the quality of Rhodiola crenulata without using natural reference substances.

Losing Count: The Federal Statistical System. Population Trends and Public Policy Occasional Paper Number 16.

ERIC Educational Resources Information Center

Wallman, Katherine K.

The main responsibility of the U.S. Bureau of the Census, Bureau of Labor Statistics, and the National Centers for Health and Education Statistics is to collect, process, analyze, and disseminate statistical data on the economic, physical, and social characteristics of the United States. Under the Paperwork Reduction Act of 1980, the federal…

Potentiation Following Ballistic and Nonballistic Complexes: The Effect of Strength Level.

PubMed

Suchomel, Timothy J; Sato, Kimitake; DeWeese, Brad H; Ebben, William P; Stone, Michael H

2016-07-01

Suchomel, TJ, Sato, K, DeWeese, BH, Ebben, WP, and Stone, MH. Potentiation following ballistic and nonballistic complexes: the effect of strength level. J Strength Cond Res 30(7): 1825-1833, 2016-The purpose of this study was to compare the temporal profile of strong and weak subjects during ballistic and nonballistic potentiation complexes. Eight strong (relative back squat = 2.1 ± 0.1 times body mass) and 8 weak (relative back squat = 1.6 ± 0.2 times body mass) males performed squat jumps immediately and every minute up to 10 minutes following potentiation complexes that included ballistic or nonballistic concentric-only half-squat (COHS) performed at 90% of their 1 repetition maximum COHS. Jump height (JH) and allometrically scaled peak power (PPa) were compared using a series of 2 × 12 repeated measures analyses of variance. No statistically significant strength level main effects for JH (p = 0.442) or PPa (p = 0.078) existed during the ballistic condition. In contrast, statistically significant main effects for time existed for both JH (p = 0.014) and PPa (p < 0.001); however, no statistically significant pairwise comparisons were present (p > 0.05). Statistically significant strength level main effects existed for PPa (p = 0.039) but not for JH (p = 0.137) during the nonballistic condition. Post hoc analysis revealed that the strong subjects produced statistically greater PPa than the weaker subjects (p = 0.039). Statistically significant time main effects existed for time existed for PPa (p = 0.015), but not for JH (p = 0.178). No statistically significant strength level × time interaction effects for JH (p = 0.319) or PPa (p = 0.203) were present for the ballistic or nonballistic conditions. Practical significance indicated by effect sizes and the relationships between maximum potentiation and relative strength suggest that stronger subjects potentiate earlier and to a greater extent than weaker subjects during ballistic and nonballistic potentiation complexes.

Immigration Statistics for the 21st Century

PubMed Central

Massey, Douglas S.

2013-01-01

Of the three main contributors to population growth—fertility, mortality, and net migration—the latter is by far the most difficult to capture statistically. This article discusses the main sources of federal statistical data on immigration, each with its own characteristic set of strengths, weaknesses, possibilities, and limitations in the context of the interested social scientist. Among the key limitations, the article argues, are the elimination of parental birthplace from the Census and the lack of complete data concerning the legal statuses of the U.S. population. This article will conclude with suggestions on remedying such deficiencies, at relatively low marginal cost, such as the inclusion of questions on parental birthplace, instituting a regular survey of randomly selected legal immigrants, and the use of the “two-card method” in statistical data. PMID:23990685

Power analysis to detect treatment effect in longitudinal studies with heterogeneous errors and incomplete data.

PubMed

Vallejo, Guillermo; Ato, Manuel; Fernández García, Paula; Livacic Rojas, Pablo E; Tuero Herrero, Ellián

2016-08-01

 S. Usami (2014) describes a method to realistically determine sample size in longitudinal research using a multilevel model. The present research extends the aforementioned work to situations where it is likely that the assumption of homogeneity of the errors across groups is not met and the error term does not follow a scaled identity covariance structure.   For this purpose, we followed a procedure based on transforming the variance components of the linear growth model and the parameter related to the treatment effect into specific and easily understandable indices. At the same time, we provide the appropriate statistical machinery for researchers to use when data loss is unavoidable, and changes in the expected value of the observed responses are not linear.   The empirical powers based on unknown variance components were virtually the same as the theoretical powers derived from the use of statistically processed indexes.   The main conclusion of the study is the accuracy of the proposed method to calculate sample size in the described situations with the stipulated power criteria.

Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package

NASA Astrophysics Data System (ADS)

Donges, Jonathan F.; Heitzig, Jobst; Beronov, Boyan; Wiedermann, Marc; Runge, Jakob; Feng, Qing Yi; Tupikina, Liubov; Stolbova, Veronika; Donner, Reik V.; Marwan, Norbert; Dijkstra, Henk A.; Kurths, Jürgen

2015-11-01

We introduce the pyunicorn (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. pyunicorn is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics, or network surrogates. Additionally, pyunicorn provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence quantification analysis, recurrence networks, visibility graphs, and construction of surrogate time series. The range of possible applications of the library is outlined, drawing on several examples mainly from the field of climatology.

Applying compressive sensing to TEM video: A substantial frame rate increase on any camera

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

Stevens, Andrew; Kovarik, Libor; Abellan, Patricia

One of the main limitations of imaging at high spatial and temporal resolution during in-situ transmission electron microscopy (TEM) experiments is the frame rate of the camera being used to image the dynamic process. While the recent development of direct detectors has provided the hardware to achieve frame rates approaching 0.1 ms, the cameras are expensive and must replace existing detectors. In this paper, we examine the use of coded aperture compressive sensing (CS) methods to increase the frame rate of any camera with simple, low-cost hardware modifications. The coded aperture approach allows multiple sub-frames to be coded and integratedmore » into a single camera frame during the acquisition process, and then extracted upon readout using statistical CS inversion. Here we describe the background of CS and statistical methods in depth and simulate the frame rates and efficiencies for in-situ TEM experiments. Depending on the resolution and signal/noise of the image, it should be possible to increase the speed of any camera by more than an order of magnitude using this approach.« less

Applying compressive sensing to TEM video: A substantial frame rate increase on any camera

DOE PAGES

Stevens, Andrew; Kovarik, Libor; Abellan, Patricia; ...

2015-08-13

One of the main limitations of imaging at high spatial and temporal resolution during in-situ transmission electron microscopy (TEM) experiments is the frame rate of the camera being used to image the dynamic process. While the recent development of direct detectors has provided the hardware to achieve frame rates approaching 0.1 ms, the cameras are expensive and must replace existing detectors. In this paper, we examine the use of coded aperture compressive sensing (CS) methods to increase the frame rate of any camera with simple, low-cost hardware modifications. The coded aperture approach allows multiple sub-frames to be coded and integratedmore » into a single camera frame during the acquisition process, and then extracted upon readout using statistical CS inversion. Here we describe the background of CS and statistical methods in depth and simulate the frame rates and efficiencies for in-situ TEM experiments. Depending on the resolution and signal/noise of the image, it should be possible to increase the speed of any camera by more than an order of magnitude using this approach.« less

Introduction to multivariate discrimination

NASA Astrophysics Data System (ADS)

Kégl, Balázs

2013-07-01

Multivariate discrimination or classification is one of the best-studied problem in machine learning, with a plethora of well-tested and well-performing algorithms. There are also several good general textbooks [1-9] on the subject written to an average engineering, computer science, or statistics graduate student; most of them are also accessible for an average physics student with some background on computer science and statistics. Hence, instead of writing a generic introduction, we concentrate here on relating the subject to a practitioner experimental physicist. After a short introduction on the basic setup (Section 1) we delve into the practical issues of complexity regularization, model selection, and hyperparameter optimization (Section 2), since it is this step that makes high-complexity non-parametric fitting so different from low-dimensional parametric fitting. To emphasize that this issue is not restricted to classification, we illustrate the concept on a low-dimensional but non-parametric regression example (Section 2.1). Section 3 describes the common algorithmic-statistical formal framework that unifies the main families of multivariate classification algorithms. We explain here the large-margin principle that partly explains why these algorithms work. Section 4 is devoted to the description of the three main (families of) classification algorithms, neural networks, the support vector machine, and AdaBoost. We do not go into the algorithmic details; the goal is to give an overview on the form of the functions these methods learn and on the objective functions they optimize. Besides their technical description, we also make an attempt to put these algorithm into a socio-historical context. We then briefly describe some rather heterogeneous applications to illustrate the pattern recognition pipeline and to show how widespread the use of these methods is (Section 5). We conclude the chapter with three essentially open research problems that are either relevant to or even motivated by certain unorthodox applications of multivariate discrimination in experimental physics.

Statistical Validation for Clinical Measures: Repeatability and Agreement of Kinect™-Based Software

PubMed Central

Tello, Emanuel; Rodrigo, Alejandro; Valentinuzzi, Max E.

2018-01-01

Background The rehabilitation process is a fundamental stage for recovery of people's capabilities. However, the evaluation of the process is performed by physiatrists and medical doctors, mostly based on their observations, that is, a subjective appreciation of the patient's evolution. This paper proposes a tracking platform of the movement made by an individual's upper limb using Kinect sensor(s) to be applied for the patient during the rehabilitation process. The main contribution is the development of quantifying software and the statistical validation of its performance, repeatability, and clinical use in the rehabilitation process. Methods The software determines joint angles and upper limb trajectories for the construction of a specific rehabilitation protocol and quantifies the treatment evolution. In turn, the information is presented via a graphical interface that allows the recording, storage, and report of the patient's data. For clinical purposes, the software information is statistically validated with three different methodologies, comparing the measures with a goniometer in terms of agreement and repeatability. Results The agreement of joint angles measured with the proposed software and goniometer is evaluated with Bland-Altman plots; all measurements fell well within the limits of agreement, meaning interchangeability of both techniques. Additionally, the results of Bland-Altman analysis of repeatability show 95% confidence. Finally, the physiotherapists' qualitative assessment shows encouraging results for the clinical use. Conclusion The main conclusion is that the software is capable of offering a clinical history of the patient and is useful for quantification of the rehabilitation success. The simplicity, low cost, and visualization possibilities enhance the use of the software Kinect for rehabilitation and other applications, and the expert's opinion endorses the choice of our approach for clinical practice. Comparison of the new measurement technique with established goniometric methods determines that the proposed software agrees sufficiently to be used interchangeably. PMID:29750166

Gesellschaft fuer angewandte Mathematik und Mechanik, Annual Scientific Meeting, Technische Universitaet Berlin, Berlin, West Germany, April 8-11, 1980, Reports. Parts 1 & 2

NASA Astrophysics Data System (ADS)

1981-04-01

The main topics discussed were related to nonparametric statistics, plane and antiplane states in finite elasticity, free-boundary-variational inequalities, the numerical solution of free boundary-value problems, discrete and combinatorial optimization, mathematical modelling in fluid mechanics, a survey and comparison regarding thermodynamic theories, invariant and almost invariant subspaces in linear systems with applications to disturbance isolation, nonlinear acoustics, and methods of function theory in the case of partial differential equations, giving particular attention to elliptic problems in the plane.

Land mobile satellite propagation measurements in Japan using ETS-V satellite

NASA Technical Reports Server (NTRS)

Obara, Noriaki; Tanaka, Kenji; Yamamoto, Shin-Ichi; Wakana, Hiromitsu

1993-01-01

Propagation characteristics of land mobile satellite communications channels have been investigated actively in recent years. Information of propagation characteristics associated with multipath fading and shadowing is required to design commercial land mobile satellite communications systems, including protocol and error correction method. CRL (Communications Research Laboratory) has carried out propagation measurements using the Engineering Test Satellite-V (ETS-V) at L band (1.5 GHz) through main roads in Japan by a medium gain antenna with an autotracking capability. This paper presents the propagation statistics obtained in this campaign.

Long-range correlation in cosmic microwave background radiation.

PubMed

Movahed, M Sadegh; Ghasemi, F; Rahvar, Sohrab; Tabar, M Reza Rahimi

2011-08-01

We investigate the statistical anisotropy and gaussianity of temperature fluctuations of Cosmic Microwave Background (CMB) radiation data from the Wilkinson Microwave Anisotropy Probe survey, using the Multifractal Detrended Fluctuation Analysis, Rescaled Range, and Scaled Windowed Variance methods. Multifractal Detrended Fluctuation Analysis shows that CMB fluctuations has a long-range correlation function with a multifractal behavior. By comparing the shuffled and surrogate series of CMB data, we conclude that the multifractality nature of the temperature fluctuation of CMB radiation is mainly due to the long-range correlations, and the map is consistent with a gaussian distribution.

Applications of statistical physics to the social and economic sciences

NASA Astrophysics Data System (ADS)

Petersen, Alexander M.

2011-12-01

This thesis applies statistical physics concepts and methods to quantitatively analyze socioeconomic systems. For each system we combine theoretical models and empirical data analysis in order to better understand the real-world system in relation to the complex interactions between the underlying human agents. This thesis is separated into three parts: (i) response dynamics in financial markets, (ii) dynamics of career trajectories, and (iii) a stochastic opinion model with quenched disorder. In Part I we quantify the response of U.S. markets to financial shocks, which perturb markets and trigger "herding behavior" among traders. We use concepts from earthquake physics to quantify the decay of volatility shocks after the "main shock." We also find, surprisingly, that we can make quantitative statements even before the main shock. In order to analyze market behavior before as well as after "anticipated news" we use Federal Reserve interest-rate announcements, which are regular events that are also scheduled in advance. In Part II we analyze the statistical physics of career longevity. We construct a stochastic model for career progress which has two main ingredients: (a) random forward progress in the career and (b) random termination of the career. We incorporate the rich-get-richer (Matthew) effect into ingredient (a), meaning that it is easier to move forward in the career the farther along one is in the career. We verify the model predictions analyzing data on 400,000 scientific careers and 20,000 professional sports careers. Our model highlights the importance of early career development, showing that many careers are stunted by the relative disadvantage associated with inexperience. In Part III we analyze a stochastic two-state spin model which represents a system of voters embedded on a network. We investigate the role in consensus formation of "zealots", which are agents with time-independent opinion. Our main result is the unexpected finding that it is the number and not the density of zealots which deter- mines the steady-state opinion polarization. We compare our findings with results for United States Presidential elections.

Research design and statistical methods in Pakistan Journal of Medical Sciences (PJMS).

PubMed

Akhtar, Sohail; Shah, Syed Wadood Ali; Rafiq, M; Khan, Ajmal

2016-01-01

This article compares the study design and statistical methods used in 2005, 2010 and 2015 of Pakistan Journal of Medical Sciences (PJMS). Only original articles of PJMS were considered for the analysis. The articles were carefully reviewed for statistical methods and designs, and then recorded accordingly. The frequency of each statistical method and research design was estimated and compared with previous years. A total of 429 articles were evaluated (n=74 in 2005, n=179 in 2010, n=176 in 2015) in which 171 (40%) were cross-sectional and 116 (27%) were prospective study designs. A verity of statistical methods were found in the analysis. The most frequent methods include: descriptive statistics (n=315, 73.4%), chi-square/Fisher's exact tests (n=205, 47.8%) and student t-test (n=186, 43.4%). There was a significant increase in the use of statistical methods over time period: t-test, chi-square/Fisher's exact test, logistic regression, epidemiological statistics, and non-parametric tests. This study shows that a diverse variety of statistical methods have been used in the research articles of PJMS and frequency improved from 2005 to 2015. However, descriptive statistics was the most frequent method of statistical analysis in the published articles while cross-sectional study design was common study design.

Spike Pattern Structure Influences Synaptic Efficacy Variability under STDP and Synaptic Homeostasis. II: Spike Shuffling Methods on LIF Networks

PubMed Central

Bi, Zedong; Zhou, Changsong

2016-01-01

Synapses may undergo variable changes during plasticity because of the variability of spike patterns such as temporal stochasticity and spatial randomness. Here, we call the variability of synaptic weight changes during plasticity to be efficacy variability. In this paper, we investigate how four aspects of spike pattern statistics (i.e., synchronous firing, burstiness/regularity, heterogeneity of rates and heterogeneity of cross-correlations) influence the efficacy variability under pair-wise additive spike-timing dependent plasticity (STDP) and synaptic homeostasis (the mean strength of plastic synapses into a neuron is bounded), by implementing spike shuffling methods onto spike patterns self-organized by a network of excitatory and inhibitory leaky integrate-and-fire (LIF) neurons. With the increase of the decay time scale of the inhibitory synaptic currents, the LIF network undergoes a transition from asynchronous state to weak synchronous state and then to synchronous bursting state. We first shuffle these spike patterns using a variety of methods, each designed to evidently change a specific pattern statistics; and then investigate the change of efficacy variability of the synapses under STDP and synaptic homeostasis, when the neurons in the network fire according to the spike patterns before and after being treated by a shuffling method. In this way, we can understand how the change of pattern statistics may cause the change of efficacy variability. Our results are consistent with those of our previous study which implements spike-generating models on converging motifs. We also find that burstiness/regularity is important to determine the efficacy variability under asynchronous states, while heterogeneity of cross-correlations is the main factor to cause efficacy variability when the network moves into synchronous bursting states (the states observed in epilepsy). PMID:27555816

Research design and statistical methods in Pakistan Journal of Medical Sciences (PJMS)

PubMed Central

Akhtar, Sohail; Shah, Syed Wadood Ali; Rafiq, M.; Khan, Ajmal

2016-01-01

Objective: This article compares the study design and statistical methods used in 2005, 2010 and 2015 of Pakistan Journal of Medical Sciences (PJMS). Methods: Only original articles of PJMS were considered for the analysis. The articles were carefully reviewed for statistical methods and designs, and then recorded accordingly. The frequency of each statistical method and research design was estimated and compared with previous years. Results: A total of 429 articles were evaluated (n=74 in 2005, n=179 in 2010, n=176 in 2015) in which 171 (40%) were cross-sectional and 116 (27%) were prospective study designs. A verity of statistical methods were found in the analysis. The most frequent methods include: descriptive statistics (n=315, 73.4%), chi-square/Fisher’s exact tests (n=205, 47.8%) and student t-test (n=186, 43.4%). There was a significant increase in the use of statistical methods over time period: t-test, chi-square/Fisher’s exact test, logistic regression, epidemiological statistics, and non-parametric tests. Conclusion: This study shows that a diverse variety of statistical methods have been used in the research articles of PJMS and frequency improved from 2005 to 2015. However, descriptive statistics was the most frequent method of statistical analysis in the published articles while cross-sectional study design was common study design. PMID:27022365

Approaching Career Criminals With An Intelligence Cycle

DTIC Science & Technology

2015-12-01

including arrest statistics and “arrest statistics have been used as the main barometer of juvenile delinquent activity, (but) many juvenile... Statistical Briefing Book,” 187. 26 guided by theories about the causes of delinquent behavior, but there was no determination if those efforts achieved the...children.”110 However, the most evidence-based comparison of juvenile delinquency reduction programs is the statistical meta-analysis (a systematic

Statistical downscaling of daily precipitation over Llobregat river basin in Catalonia (Spain) using three downscaling methods.

NASA Astrophysics Data System (ADS)

Ballinas, R.; Versini, P.-A.; Sempere, D.; Escaler, I.

2009-09-01

Any long-term change in the patterns of average weather in a global or regional scale is called climate change. It may cause a progressive increase of atmospheric temperature and consequently may change the amount, frequency and intensity of precipitation. All these changes of meteorological parameters may modify the water cycle: run-off, infiltration, aquifer recharge, etc. Recent studies in Catalonia foresee changes in hydrological systems caused by climate change. This will lead to alterations in the hydrological cycle that could impact in land use, in the regimen of water extractions, in the hydrological characteristics of the territory and reduced groundwater recharge. Besides, can expect a loss of flow in rivers. In addition to possible increases in the frequency of extreme rainfall, being necessary to modify the design of infrastructure. Because this, it work focuses on studying the impacts of climate change in one of the most important basins in Catalonia, the Llobregat River Basin. The basin is the hub of the province of Barcelona. It is a highly populated and urbanized catchment, where water resources are used for different purposes, as drinking water production, agricultural irrigation, industry and hydro-electrical energy production. In consequence, many companies and communities depend on these resources. To study the impact of climate change in the Llobregat basin, storms (frequency, intensity) mainly, we will need regional climate change information. A regional climate is determined by interactions at large, regional and local scales. The general circulation models (GCMs) are run at too coarse resolution to permit accurate description of these regional and local interactions. So far, they have been unable to provide consistent estimates of climate change on a local scale. Several regionalization techniques have been developed to bridge the gap between the large-scale information provided by GCMs and fine spatial scales required for regional and environmental impact studies. Downscaling methods to assess the effect of large-scale circulations on local parameters have. Statistical downscaling methods are based on the view that regional climate can be conditioned by two factors: large-scale climatic state and regional/local features. Local climate information is derived by first developing a statistical model which relates large-scale variables or "predictors" for which GCMs are trustable to regional or local surface "predictands" for which models are less skilful. The main advantage of these methods is that they are computationally inexpensive, and can be applied to outputs from different GCM experiments. Three statistical downscaling methods are applied: Analogue method, Delta Change and Direct Forcing. These methods have been used to determine daily precipitation projections at rain gauge location to study the intensity, frequency and variability of storms in a context of climate change in the Llobregat River Basin in Catalonia, Spain. This work is part of the European project "Water Change" (included in the LIFE + Environment Policy and Governance program). It deals with Medium and long term water resources modelling as a tool for planning and global change adaptation. Two stakeholders involved in the project provided the historical time series: Catalan Water Agency (ACA) and the State Meteorological Agency (AEMET).

A review of downscaling procedures - a contribution to the research on climate change impacts at city scale

NASA Astrophysics Data System (ADS)

Smid, Marek; Costa, Ana; Pebesma, Edzer; Granell, Carlos; Bhattacharya, Devanjan

2016-04-01

Human kind is currently predominantly urban based, and the majority of ever continuing population growth will take place in urban agglomerations. Urban systems are not only major drivers of climate change, but also the impact hot spots. Furthermore, climate change impacts are commonly managed at city scale. Therefore, assessing climate change impacts on urban systems is a very relevant subject of research. Climate and its impacts on all levels (local, meso and global scale) and also the inter-scale dependencies of those processes should be a subject to detail analysis. While global and regional projections of future climate are currently available, local-scale information is lacking. Hence, statistical downscaling methodologies represent a potentially efficient way to help to close this gap. In general, the methodological reviews of downscaling procedures cover the various methods according to their application (e.g. downscaling for the hydrological modelling). Some of the most recent and comprehensive studies, such as the ESSEM COST Action ES1102 (VALUE), use the concept of Perfect Prog and MOS. Other examples of classification schemes of downscaling techniques consider three main categories: linear methods, weather classifications and weather generators. Downscaling and climate modelling represent a multidisciplinary field, where researchers from various backgrounds intersect their efforts, resulting in specific terminology, which may be somewhat confusing. For instance, the Polynomial Regression (also called the Surface Trend Analysis) is a statistical technique. In the context of the spatial interpolation procedures, it is commonly classified as a deterministic technique, and kriging approaches are classified as stochastic. Furthermore, the terms "statistical" and "stochastic" (frequently used as names of sub-classes in downscaling methodological reviews) are not always considered as synonymous, even though both terms could be seen as identical since they are referring to methods handling input modelling factors as variables with certain probability distributions. In addition, the recent development is going towards multi-step methodologies containing deterministic and stochastic components. This evolution leads to the introduction of new terms like hybrid or semi-stochastic approaches, which makes the efforts to systematically classifying downscaling methods to the previously defined categories even more challenging. This work presents a review of statistical downscaling procedures, which classifies the methods in two steps. In the first step, we describe several techniques that produce a single climatic surface based on observations. The methods are classified into two categories using an approximation to the broadest consensual statistical terms: linear and non-linear methods. The second step covers techniques that use simulations to generate alternative surfaces, which correspond to different realizations of the same processes. Those simulations are essential because there is a limited number of real observational data, and such procedures are crucial for modelling extremes. This work emphasises the link between statistical downscaling methods and the research of climate change impacts at city scale.

Bias correction of nutritional status estimates when reported age is used for calculating WHO indicators in children under five years of age.

PubMed

Quezada, Amado D; García-Guerra, Armando; Escobar, Leticia

2016-06-01

To assess the performance of a simple correction method for nutritional status estimates in children under five years of age when exact age is not available from the data. The proposed method was based on the assumption of symmetry of age distributions within a given month of age and validated in a large population-based survey sample of Mexican preschool children. The main distributional assumption was consistent with the data. All prevalence estimates derived from the correction method showed no statistically significant bias. In contrast, failing to correct attained age resulted in an underestimation of stunting in general and an overestimation of overweight or obesity among the youngest. The proposed method performed remarkably well in terms of bias correction of estimates and could be easily applied in situations in which either birth or interview dates are not available from the data.

Comparative effectiveness research and its utility in In-clinic practice

PubMed Central

Dang, Amit; Kaur, Kirandeep

2016-01-01

One of the important components of patient-centered healthcare is comparative effectiveness research (CER), which aims at generating evidence from the real-life setting. The primary purpose of CER is to provide comparative information to the healthcare providers, patients, and policy makers about the standard of care available. This involves research on clinical questions unanswered by the explanatory trials during the regulatory approval process. Main methods of CER involve randomized controlled trials and observational methods. The limitations of these two methods have been overcome with the help of new statistical methods. After the evidence generation, it is equally important to communicate the results to all the interested organizations. CER is beginning to have its impact in the clinical practice as its results become part of the clinical practice guidelines. CER will have far-reaching scientific and financial impact. CER will make both the treating physician and the patient equally responsible for the treatment offered. PMID:26955571

Deep learning for low-dose CT

NASA Astrophysics Data System (ADS)

Chen, Hu; Zhang, Yi; Zhou, Jiliu; Wang, Ge

2017-09-01

Given the potential risk of X-ray radiation to the patient, low-dose CT has attracted a considerable interest in the medical imaging field. Currently, the main stream low-dose CT methods include vendor-specific sinogram domain filtration and iterative reconstruction algorithms, but they need to access raw data whose formats are not transparent to most users. Due to the difficulty of modeling the statistical characteristics in the image domain, the existing methods for directly processing reconstructed images cannot eliminate image noise very well while keeping structural details. Inspired by the idea of deep learning, here we combine the autoencoder, deconvolution network, and shortcut connections into the residual encoder-decoder convolutional neural network (RED-CNN) for low-dose CT imaging. After patch-based training, the proposed RED-CNN achieves a competitive performance relative to the-state-of-art methods. Especially, our method has been favorably evaluated in terms of noise suppression and structural preservation.

Statistics of software vulnerability detection in certification testing

NASA Astrophysics Data System (ADS)

Barabanov, A. V.; Markov, A. S.; Tsirlov, V. L.

2018-05-01

The paper discusses practical aspects of introduction of the methods to detect software vulnerability in the day-to-day activities of the accredited testing laboratory. It presents the approval results of the vulnerability detection methods as part of the study of the open source software and the software that is a test object of the certification tests under information security requirements, including software for communication networks. Results of the study showing the allocation of identified vulnerabilities by types of attacks, country of origin, programming languages used in the development, methods for detecting vulnerability, etc. are given. The experience of foreign information security certification systems related to the detection of certified software vulnerabilities is analyzed. The main conclusion based on the study is the need to implement practices for developing secure software in the development life cycle processes. The conclusions and recommendations for the testing laboratories on the implementation of the vulnerability analysis methods are laid down.

Characterisation of seasonal flood types according to timescales in mixed probability distributions

NASA Astrophysics Data System (ADS)

Fischer, Svenja; Schumann, Andreas; Schulte, Markus

2016-08-01

When flood statistics are based on annual maximum series (AMS), the sample often contains flood peaks, which differ in their genesis. If the ratios among event types change over the range of observations, the extrapolation of a probability distribution function (pdf) can be dominated by a majority of events that belong to a certain flood type. If this type is not typical for extraordinarily large extremes, such an extrapolation of the pdf is misleading. To avoid this breach of the assumption of homogeneity, seasonal models were developed that differ between winter and summer floods. We show that a distinction between summer and winter floods is not always sufficient if seasonal series include events with different geneses. Here, we differentiate floods by their timescales into groups of long and short events. A statistical method for such a distinction of events is presented. To demonstrate their applicability, timescales for winter and summer floods in a German river basin were estimated. It is shown that summer floods can be separated into two main groups, but in our study region, the sample of winter floods consists of at least three different flood types. The pdfs of the two groups of summer floods are combined via a new mixing model. This model considers that information about parallel events that uses their maximum values only is incomplete because some of the realisations are overlaid. A statistical method resulting in an amendment of statistical parameters is proposed. The application in a German case study demonstrates the advantages of the new model, with specific emphasis on flood types.

Investigating spousal concordance of diabetes through statistical analysis and data mining

PubMed Central

Liu, Chiu-Shong; Lung, Chi-Hsuan; Yang, Ya-Tun; Lin, Ming-Hung

2017-01-01

Objective Spousal clustering of diabetes merits attention. Whether old-age vulnerability or a shared family environment determines the concordance of diabetes is also uncertain. This study investigated the spousal concordance of diabetes and compared the risk of diabetes concordance between couples and noncouples by using nationally representative data. Methods A total of 22,572 individuals identified from the 2002–2013 National Health Insurance Research Database of Taiwan constituted 5,643 couples and 5,643 noncouples through 1:1 dual propensity score matching (PSM). Factors associated with concordance in both spouses with diabetes were analyzed at the individual level. The risk of diabetes concordance between couples and noncouples was compared at the couple level. Logistic regression was the main statistical method. Statistical data were analyzed using SAS 9.4. C&RT and Apriori of data mining conducted in IBM SPSS Modeler 13 served as a supplement to statistics. Results High odds of the spousal concordance of diabetes were associated with old age, middle levels of urbanization, and high comorbidities (all P < 0.05). The dual PSM analysis revealed that the risk of diabetes concordance was significantly higher in couples (5.19%) than in noncouples (0.09%; OR = 61.743, P < 0.0001). Conclusions A high concordance rate of diabetes in couples may indicate the influences of assortative mating and shared environment. Diabetes in a spouse implicates its risk in the partner. Family-based diabetes care that emphasizes the screening of couples at risk of diabetes by using the identified risk factors is suggested in prospective clinical practice interventions. PMID:28817654

Poisson Regression Analysis of Illness and Injury Surveillance Data

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

Frome E.L., Watkins J.P., Ellis E.D.

2012-12-12

The Department of Energy (DOE) uses illness and injury surveillance to monitor morbidity and assess the overall health of the work force. Data collected from each participating site include health events and a roster file with demographic information. The source data files are maintained in a relational data base, and are used to obtain stratified tables of health event counts and person time at risk that serve as the starting point for Poisson regression analysis. The explanatory variables that define these tables are age, gender, occupational group, and time. Typical response variables of interest are the number of absences duemore » to illness or injury, i.e., the response variable is a count. Poisson regression methods are used to describe the effect of the explanatory variables on the health event rates using a log-linear main effects model. Results of fitting the main effects model are summarized in a tabular and graphical form and interpretation of model parameters is provided. An analysis of deviance table is used to evaluate the importance of each of the explanatory variables on the event rate of interest and to determine if interaction terms should be considered in the analysis. Although Poisson regression methods are widely used in the analysis of count data, there are situations in which over-dispersion occurs. This could be due to lack-of-fit of the regression model, extra-Poisson variation, or both. A score test statistic and regression diagnostics are used to identify over-dispersion. A quasi-likelihood method of moments procedure is used to evaluate and adjust for extra-Poisson variation when necessary. Two examples are presented using respiratory disease absence rates at two DOE sites to illustrate the methods and interpretation of the results. In the first example the Poisson main effects model is adequate. In the second example the score test indicates considerable over-dispersion and a more detailed analysis attributes the over-dispersion to extra-Poisson variation. The R open source software environment for statistical computing and graphics is used for analysis. Additional details about R and the data that were used in this report are provided in an Appendix. Information on how to obtain R and utility functions that can be used to duplicate results in this report are provided.« less

Risk prediction model: Statistical and artificial neural network approach

NASA Astrophysics Data System (ADS)

Paiman, Nuur Azreen; Hariri, Azian; Masood, Ibrahim

2017-04-01

Prediction models are increasingly gaining popularity and had been used in numerous areas of studies to complement and fulfilled clinical reasoning and decision making nowadays. The adoption of such models assist physician's decision making, individual's behavior, and consequently improve individual outcomes and the cost-effectiveness of care. The objective of this paper is to reviewed articles related to risk prediction model in order to understand the suitable approach, development and the validation process of risk prediction model. A qualitative review of the aims, methods and significant main outcomes of the nineteen published articles that developed risk prediction models from numerous fields were done. This paper also reviewed on how researchers develop and validate the risk prediction models based on statistical and artificial neural network approach. From the review done, some methodological recommendation in developing and validating the prediction model were highlighted. According to studies that had been done, artificial neural network approached in developing the prediction model were more accurate compared to statistical approach. However currently, only limited published literature discussed on which approach is more accurate for risk prediction model development.

Brownian motion or Lévy walk? Stepping towards an extended statistical mechanics for animal locomotion.

PubMed

Gautestad, Arild O

2012-09-07

Animals moving under the influence of spatio-temporal scaling and long-term memory generate a kind of space-use pattern that has proved difficult to model within a coherent theoretical framework. An extended kind of statistical mechanics is needed, accounting for both the effects of spatial memory and scale-free space use, and put into a context of ecological conditions. Simulations illustrating the distinction between scale-specific and scale-free locomotion are presented. The results show how observational scale (time lag between relocations of an individual) may critically influence the interpretation of the underlying process. In this respect, a novel protocol is proposed as a method to distinguish between some main movement classes. For example, the 'power law in disguise' paradox-from a composite Brownian motion consisting of a superposition of independent movement processes at different scales-may be resolved by shifting the focus from pattern analysis at one particular temporal resolution towards a more process-oriented approach involving several scales of observation. A more explicit consideration of system complexity within a statistical mechanical framework, supplementing the more traditional mechanistic modelling approach, is advocated.

iTTVis: Interactive Visualization of Table Tennis Data.

PubMed

Wu, Yingcai; Lan, Ji; Shu, Xinhuan; Ji, Chenyang; Zhao, Kejian; Wang, Jiachen; Zhang, Hui

2018-01-01

The rapid development of information technology paved the way for the recording of fine-grained data, such as stroke techniques and stroke placements, during a table tennis match. This data recording creates opportunities to analyze and evaluate matches from new perspectives. Nevertheless, the increasingly complex data poses a significant challenge to make sense of and gain insights into. Analysts usually employ tedious and cumbersome methods which are limited to watching videos and reading statistical tables. However, existing sports visualization methods cannot be applied to visualizing table tennis competitions due to different competition rules and particular data attributes. In this work, we collaborate with data analysts to understand and characterize the sophisticated domain problem of analysis of table tennis data. We propose iTTVis, a novel interactive table tennis visualization system, which to our knowledge, is the first visual analysis system for analyzing and exploring table tennis data. iTTVis provides a holistic visualization of an entire match from three main perspectives, namely, time-oriented, statistical, and tactical analyses. The proposed system with several well-coordinated views not only supports correlation identification through statistics and pattern detection of tactics with a score timeline but also allows cross analysis to gain insights. Data analysts have obtained several new insights by using iTTVis. The effectiveness and usability of the proposed system are demonstrated with four case studies.

Characteristics of zircons from volcanic ash-derived tonsteins in Late Permian coal fields of eastern Yunnan, China

USGS Publications Warehouse

Zhou, Y.; Ren, Y.; Tang, D.; Bohor, B.

1994-01-01

Kaolinitic tonsteins of altered synsedimentary volcanic ash-fall origin are well developed in the Late Permian coal-bearing formations of eastern Yunnan Province. Because of their unique origin, wide lateral extent, relatively constant thickness and sharp contacts with enclosing strata, great importance has been attached to these isochronous petrographic markers. In order to compare tonsteins with co-existing, non-cineritic claystones and characterize the individuality of tonsteins from different horizons for coal bed correlation, a semi-quantitative method was developed that is based on statistical analyses of the concentration and morphology of zircons and their spatial distribution patterns. This zircon-based analytical method also serves as a means for reconstructing volcanic ash-fall dispersal patterns. The results demonstrate that zircons from claystones of two different origins (i.e., tonstein and non-cineritic claystone) differ greatly in their relative abundances, crystal morphologies and spatial distribution patterns. Tonsteins from the same area but from different horizons are characterized by their own unique statistical patterns in terms of zircon concentration values and morphologic parameters (crystal length, width and the ratio of these values), thus facilitating stratigraphic correlation. Zircons from the same tonstein horizon also show continuous variation in these statistical patterns as a function of areal distribution, making it possible to identify the main path and direction in which the volcanic source materials were transported by prevailing winds. ?? 1994.

High resolution probabilistic precipitation forecast over Spain combining the statistical downscaling tool PROMETEO and the AEMET short range EPS system (AEMET/SREPS)

NASA Astrophysics Data System (ADS)

Cofino, A. S.; Santos, C.; Garcia-Moya, J. A.; Gutierrez, J. M.; Orfila, B.

2009-04-01

The Short-Range Ensemble Prediction System (SREPS) is a multi-LAM (UM, HIRLAM, MM5, LM and HRM) multi analysis/boundary conditions (ECMWF, UKMetOffice, DWD and GFS) run twice a day by AEMET (72 hours lead time) over a European domain, with a total of 5 (LAMs) x 4 (GCMs) = 20 members. One of the main goals of this project is analyzing the impact of models and boundary conditions in the short-range high-resolution forecasted precipitation. A previous validation of this method has been done considering a set of climate networks in Spain, France and Germany, by interpolating the prediction to the gauge locations (SREPS, 2008). In this work we compare these results with those obtained by using a statistical downscaling method to post-process the global predictions, obtaining an "advanced interpolation" for the local precipitation using climate network precipitation observations. In particular, we apply the PROMETEO downscaling system based on analogs and compare the SREPS ensemble of 20 members with the PROMETEO statistical ensemble of 5 (analog ensemble) x 4 (GCMs) = 20 members. Moreover, we will also compare the performance of a combined approach post-processing the SREPS outputs using the PROMETEO system. References: SREPS 2008. 2008 EWGLAM-SRNWP Meeting (http://www.aemet.es/documentos/va/divulgacion/conferencias/prediccion/Ewglam/PRED_CSantos.pdf)

Algal bioassessment metrics for wadeable streams and rivers of Maine, USA

USGS Publications Warehouse

Danielson, Thomas J.; Loftin, Cynthia S.; Tsomides, Leonidas; DiFranco, Jeanne L.; Connors, Beth

2011-01-01

Many state water-quality agencies use biological assessment methods based on lotic fish and macroinvertebrate communities, but relatively few states have incorporated algal multimetric indices into monitoring programs. Algae are good indicators for monitoring water quality because they are sensitive to many environmental stressors. We evaluated benthic algal community attributes along a landuse gradient affecting wadeable streams and rivers in Maine, USA, to identify potential bioassessment metrics. We collected epilithic algal samples from 193 locations across the state. We computed weighted-average optima for common taxa for total P, total N, specific conductance, % impervious cover, and % developed watershed, which included all land use that is no longer forest or wetland. We assigned Maine stream tolerance values and categories (sensitive, intermediate, tolerant) to taxa based on their optima and responses to watershed disturbance. We evaluated performance of algal community metrics used in multimetric indices from other regions and novel metrics based on Maine data. Metrics specific to Maine data, such as the relative richness of species characterized as being sensitive in Maine, were more correlated with % developed watershed than most metrics used in other regions. Few community-structure attributes (e.g., species richness) were useful metrics in Maine. Performance of algal bioassessment models would be improved if metrics were evaluated with attributes of local data before inclusion in multimetric indices or statistical models. ?? 2011 by The North American Benthological Society.

Simulation of Earth textures by conditional image quilting

NASA Astrophysics Data System (ADS)

Mahmud, K.; Mariethoz, G.; Caers, J.; Tahmasebi, P.; Baker, A.

2014-04-01

Training image-based approaches for stochastic simulations have recently gained attention in surface and subsurface hydrology. This family of methods allows the creation of multiple realizations of a study domain, with a spatial continuity based on a training image (TI) that contains the variability, connectivity, and structural properties deemed realistic. A major drawback of these methods is their computational and/or memory cost, making certain applications challenging. It was found that similar methods, also based on training images or exemplars, have been proposed in computer graphics. One such method, image quilting (IQ), is introduced in this paper and adapted for hydrogeological applications. The main difficulty is that Image Quilting was originally not designed to produce conditional simulations and was restricted to 2-D images. In this paper, the original method developed in computer graphics has been modified to accommodate conditioning data and 3-D problems. This new conditional image quilting method (CIQ) is patch based, does not require constructing a pattern databases, and can be used with both categorical and continuous training images. The main concept is to optimally cut the patches such that they overlap with minimum discontinuity. The optimal cut is determined using a dynamic programming algorithm. Conditioning is accomplished by prior selection of patches that are compatible with the conditioning data. The performance of CIQ is tested for a variety of hydrogeological test cases. The results, when compared with previous multiple-point statistics (MPS) methods, indicate an improvement in CPU time by a factor of at least 50.

Statistical Approaches to Adjusting Weights for Dependent Arms in Network Meta-analysis.

PubMed

Su, Yu-Xuan; Tu, Yu-Kang

2018-05-22

Network meta-analysis compares multiple treatments in terms of their efficacy and harm by including evidence from randomized controlled trials. Most clinical trials use parallel design, where patients are randomly allocated to different treatments and receive only one treatment. However, some trials use within person designs such as split-body, split-mouth and cross-over designs, where each patient may receive more than one treatment. Data from treatment arms within these trials are no longer independent, so the correlations between dependent arms need to be accounted for within the statistical analyses. Ignoring these correlations may result in incorrect conclusions. The main objective of this study is to develop statistical approaches to adjusting weights for dependent arms within special design trials. In this study, we demonstrate the following three approaches: the data augmentation approach, the adjusting variance approach, and the reducing weight approach. These three methods could be perfectly applied in current statistic tools such as R and STATA. An example of periodontal regeneration was used to demonstrate how these approaches could be undertaken and implemented within statistical software packages, and to compare results from different approaches. The adjusting variance approach can be implemented within the network package in STATA, while reducing weight approach requires computer software programming to set up the within-study variance-covariance matrix. This article is protected by copyright. All rights reserved.

Method for appraising model validity of randomised controlled trials of homeopathic treatment: multi-rater concordance study

PubMed Central

2012-01-01

Background A method for assessing the model validity of randomised controlled trials of homeopathy is needed. To date, only conventional standards for assessing intrinsic bias (internal validity) of trials have been invoked, with little recognition of the special characteristics of homeopathy. We aimed to identify relevant judgmental domains to use in assessing the model validity of homeopathic treatment (MVHT). We define MVHT as the extent to which a homeopathic intervention and the main measure of its outcome, as implemented in a randomised controlled trial (RCT), reflect 'state-of-the-art' homeopathic practice. Methods Using an iterative process, an international group of experts developed a set of six judgmental domains, with associated descriptive criteria. The domains address: (I) the rationale for the choice of the particular homeopathic intervention; (II) the homeopathic principles reflected in the intervention; (III) the extent of homeopathic practitioner input; (IV) the nature of the main outcome measure; (V) the capability of the main outcome measure to detect change; (VI) the length of follow-up to the endpoint of the study. Six papers reporting RCTs of homeopathy of varying design were randomly selected from the literature. A standard form was used to record each assessor's independent response per domain, using the optional verdicts 'Yes', 'Unclear', 'No'. Concordance among the eight verdicts per domain, across all six papers, was evaluated using the kappa (κ) statistic. Results The six judgmental domains enabled MVHT to be assessed with 'fair' to 'almost perfect' concordance in each case. For the six RCTs examined, the method allowed MVHT to be classified overall as 'acceptable' in three, 'unclear' in two, and 'inadequate' in one. Conclusion Future systematic reviews of RCTs in homeopathy should adopt the MVHT method as part of a complete appraisal of trial validity. PMID:22510227

Ocean Drilling Program: Web Site Access Statistics

Science.gov Websites

and products Drilling services and tools Online Janus database Search the ODP/TAMU web site ODP's main See statistics for JOIDES members. See statistics for Janus database. 1997 October November December accessible only on www-odp.tamu.edu. ** End of ODP, start of IODP. Privacy Policy ODP | Search | Database

A Method to Predict the Structure and Stability of RNA/RNA Complexes.

PubMed

Xu, Xiaojun; Chen, Shi-Jie

2016-01-01

RNA/RNA interactions are essential for genomic RNA dimerization and regulation of gene expression. Intermolecular loop-loop base pairing is a widespread and functionally important tertiary structure motif in RNA machinery. However, computational prediction of intermolecular loop-loop base pairing is challenged by the entropy and free energy calculation due to the conformational constraint and the intermolecular interactions. In this chapter, we describe a recently developed statistical mechanics-based method for the prediction of RNA/RNA complex structures and stabilities. The method is based on the virtual bond RNA folding model (Vfold). The main emphasis in the method is placed on the evaluation of the entropy and free energy for the loops, especially tertiary kissing loops. The method also uses recursive partition function calculations and two-step screening algorithm for large, complicated structures of RNA/RNA complexes. As case studies, we use the HIV-1 Mal dimer and the siRNA/HIV-1 mutant (T4) to illustrate the method.

Therapeutic play: preparing the child for the vaccine

PubMed Central

Pontes, Jéssica Etienne Dourado; Tabet, Elaine; Folkmann, Maria Áurea dos Santos; Cunha, Mariana Lucas da Rocha; Almeida, Fabiane de Amorim

2015-01-01

ABSTRACT Objective: To identify and compare behaviors of children during vaccination, who were prepared or not for the procedure using an instructional therapeutic play. Methods: A quasi experimental study, with quantitative approach of 60 children aged 3 to 6 years. The child's reactions were recorded in a checklist. Data were analyzed using descriptive and inferential statistics and Fisher's test. Results: The main reactions in the experimental group were stay still (25;83%) and spontaneously collaborate (24;80%). In the control group, the main reactions were cries and cling to parents (15; 50%), flushing (11;36.67%) and moving the body/agitated (10;33.3%). Conclusion: The reactions of cooperation were more frequent in the experimental group, while low acceptance was observed only in the control group. Therapeutic play has proved an important tool in preparing for the vaccine. PMID:26154545

Collision lifetimes and impact statistics of near-Earth asteroids

NASA Technical Reports Server (NTRS)

Bottke, W. F., Jr.; Nolan, M. C.; Greenberg, R.

1993-01-01

We have examined the lifetimes of Near-Earth asteroids (NEA's) by directly computing the collision probabilities with other asteroids and with the terrestrial planets. We compare these to the dynamical lifetimes, and to collisional lifetimes assumed by other workers. We discuss the implications of the differences. The lifetimes of NEA's are important because, along with the statistics of craters on the Earth and Moon, they help us to compute the number of NEA's and the rate at which new NEA's are brought to the vicinity of the Earth. Assuming that the NEA population is in steady-state, the lifetimes determine the flux of new bodies needed to replenish the population. Earlier estimates of the lifetimes ignored (or incompletely accounted for) the differences in the velocities of asteroids as they move in their orbits, so our results differ from (for example) Greenberg and Chapman (1983, Icarus 55, 455) and Wetherill (1988, Icarus 76, 1) by factors of 2 to 10. We have computed the collision rates and relative velocities of NEA's with each other, the main-belt asteroids, and the terrestrial planets, using the corrected method described by Bottke et. al. (1992, GRL, in press). We find that NEA's typically have shorter collisional lifetimes than do main-belt asteroids of the same size, due to their high eccentricities, which typically give them aphelia in the main belt. Consequently, they spend a great deal of time in the main belt, and are moving much slower than the bodies around them, making them 'sitting ducks' for impacts with other asteroids. They cross the paths of many objects, and their typical collision velocities are much higher (10-15 km/s) than the collision velocities (5 km/s) among objects within the main belt. These factors combine to give them substantially shorter lifetimes than had been previously estimated.

Statistical methods and neural network approaches for classification of data from multiple sources

NASA Technical Reports Server (NTRS)

Benediktsson, Jon Atli; Swain, Philip H.

1990-01-01

Statistical methods for classification of data from multiple data sources are investigated and compared to neural network models. A problem with using conventional multivariate statistical approaches for classification of data of multiple types is in general that a multivariate distribution cannot be assumed for the classes in the data sources. Another common problem with statistical classification methods is that the data sources are not equally reliable. This means that the data sources need to be weighted according to their reliability but most statistical classification methods do not have a mechanism for this. This research focuses on statistical methods which can overcome these problems: a method of statistical multisource analysis and consensus theory. Reliability measures for weighting the data sources in these methods are suggested and investigated. Secondly, this research focuses on neural network models. The neural networks are distribution free since no prior knowledge of the statistical distribution of the data is needed. This is an obvious advantage over most statistical classification methods. The neural networks also automatically take care of the problem involving how much weight each data source should have. On the other hand, their training process is iterative and can take a very long time. Methods to speed up the training procedure are introduced and investigated. Experimental results of classification using both neural network models and statistical methods are given, and the approaches are compared based on these results.

A study on the sources of sexual knowledge acquisition among high school students in northwest Iran.

PubMed

Malek, Ayyoub; Abbasi Shokoohi, Hamid; Faghihi, Ali Naghi; Bina, Mahdi; Shafiee-Kandjani, Ali Reza

2010-11-01

Considering the importance of sexual drive among teenagers, parental and societal concerns about teenagers' sexual drives, particularly in religious communities such as Iran is of practical importance; therefore, this present research was designed to study students' sources of sexual knowledge acquisition. This research was carried out among 2600 high school students in the cities of Tabriz, Urmia, and Ardabil in Northwest Iran. Students were selected through a multi-staged randomized sampling method in Tabriz and by the convenience method in Ardabil and Urmia. The instrument was a self-administered questionnaire, which included 19 different resources. The resources were categorized into seven main groups and the results were statistically analyzed with SPSS version 11.5 software. Based on the mean score of each of the seven main groups of resources, the ranking order of the resources was as follows: 1) immediate friends and peers 2) pictures, magazines, and books 3) audiovisual (CDs, foreign movies, satellite programs, and the Internet) 4) school trainings 5) physicians, clergy, and counseling centers 6) family (parents and siblings) and 7) close family members. The differences between the resources were statistically significant (P value= 0.0001). Results of the present study emphasize that teenagers should be educated in different areas of sexual problems with the help of parents, schools, and official sources and centers in the society as confident sources of obtaining sexual knowledge. There is a need to prepare a codified educational curriculum in different levels in order to offer teenagers' sexual education in the form of books or specific school credits.

Appraisal of levels and patterns of occupational exposure to 1,3-butadiene.

PubMed

Scarselli, Alberto; Corfiati, Marisa; Di Marzi, Davide; Iavicoli, Sergio

2017-09-01

Objectives 1,3-butadiene is classified as carcinogenic to human by inhalation and the association with leukemia has been observed in several epidemiological studies. The aim of this study was to evaluate data about occupational exposure levels to 1,3-butadiene in the Italian working force. Methods Airborne concentrations of 1,3-butadiene were extracted from the Italian database on occupational exposure to carcinogens in the period 1996-2015. Descriptive statistics were calculated for exposure-related variables. An analysis through linear mixed model was performed to determine factors influencing the exposure level. The probability of exceeding the exposure limit was predicted using a mixed-effects logistic model. Concurrent exposures with other occupational carcinogens were investigated using the two-step cluster analysis. Results The total number of exposure measurements selected was 23 885, with an overall arithmetic mean of 0.12 mg/m3. The economic sector with the highest number of measurements was manufacturing of chemicals (18 744). The most predictive variables of the exposure level resulted to be the occupational group and its interaction with the measurement year. The highest likelihood of exceeding the exposure limit was found in the manufacture of coke and refined petroleum products. Concurrent exposures were frequently detected, mainly with benzene, acrylonitrile and ethylene dichloride, and three main clusters were identified. Conclusions Exposure to 1,3-butadiene occurs in a wide variety of activity sectors and occupational groups. The use of several statistical analysis methods applied to occupational exposure databases can help to identify exposure situations at high risk for workers' health and better target preventive interventions and research projects.

Issues Surrounding HIV Status Disclosure: Experiences of Seropositive Women in Lagos, Nigeria

PubMed Central

Oseni, Oluwaseun E.; Okafor, Ifeoma P.; Sekoni, Adekemi O.

2017-01-01

Background: Disclosure of human immunodeficiency virus (HIV) seropositivity by infected women is crucial in HIV control. To determine the rates, patterns, effects, and determinants of disclosure of status among HIV-positive women in Lagos, Nigeria. Methods: This was a descriptive cross-sectional study. Simple random sampling method was used to select 364 HIV-positive women accessing care in HIV treatment centers in Lagos Island. Data were collected using interviewer-administered questionnaires and analyzed with Epi Info (version 3.5.3). Inferential statistics done was Chi-square test and level of statistical significance was set at <5%. Results: Mean age of respondents was 37.3 ± 3 years, and most were married or cohabiting in monogamous families. The disclosure rates were 81.9% to anyone (excluding a health care professional); 60.4% to spouse/sexual partners; and 67.7% disclosed on the same day of diagnosis. Main reasons for disclosure were failing health (49.3%) and a sense of responsibility to the spouse/sexual partner (33.6%). Major reasons for nondisclosure were negative public opinion (84.8%) and fear of losing relationships (40.3%). Positive reactions following disclosure were mostly acceptance: 75.2% (family member) and 72.3% (spouse/sexual partner) while blame was the main negative outcome. Longer duration of diagnosis significantly improved disclosure to anyone (P < 0.001). Older age (P < 0.001) and awareness of spouse/sexual partner's HIV status (P < 0.001) significantly improved disclosure to spouse/sexual partner. Conclusions: Many respondents had not disclosed their status and require support and counseling to do so. Community education regarding stigmatization should be intensified. PMID:28966749

Transcranial Magnetic Stimulation as an Additional Diagnostic Tool in Children with Acute Inflammatory Demyelinating Polyneuropathy

PubMed Central

Voitenkov, Voitenkov Vladislav; Andrey, Klimkin; Natalia, Skripchenko; Anastasia, Aksenova

2017-01-01

Context: The diagnosis of polyneuropathy may be challenging at the early stages of the disease. Despite electromyography (EMG) efficacy in the establishment of polyneuropathy diagnosis, in some cases, results are dubious and neurophysiologists may implement additional techniques to ensure that conduction is affected. Aims: The aim of the study was to evaluate motor-evoked potential (MEP) characteristics in children with acute inflammatory demyelinating polyneuropathy (AIDP). Settings and Design: The study was conducted at a pediatric research and clinical center for infectious diseases. Subjects and Methods: Twenty healthy children (7–14 years old) without signs of neurological disorders were enrolled as controls. Thirty-seven patients (8–13 years old) with AIDP were enrolled as the main group. EMG and transcranial magnetic stimulation (TMS) were performed on the 3rd–7th days from the onset of the first symptoms. Statistical Analysis Used: Descriptive statistics and Student's t-test were used. Bonferroni method was applied to implement appropriate corrections for multiple comparisons. Results: Significant differences between children with AIDP and controls on latencies of both cortical and lumbar MEPs were registered. Cortical MEP shapes were disperse in 100% of the cases and lumbar MEPs were disperse in 57% of the cases. Conclusions: Diagnostic TMS on the early stage of the AIDP in children may be implemented as the additional tool. The main finding in this population is lengthening of the latency of cortical and lumbar MEPs. Disperse shape of the lumbar MEPs may be used as the early sign of the acute demyelization. PMID:28904571

Allelic-based gene-gene interaction associated with quantitative traits.

PubMed

Jung, Jeesun; Sun, Bin; Kwon, Deukwoo; Koller, Daniel L; Foroud, Tatiana M

2009-05-01

Recent studies have shown that quantitative phenotypes may be influenced not only by multiple single nucleotide polymorphisms (SNPs) within a gene but also by the interaction between SNPs at unlinked genes. We propose a new statistical approach that can detect gene-gene interactions at the allelic level which contribute to the phenotypic variation in a quantitative trait. By testing for the association of allelic combinations at multiple unlinked loci with a quantitative trait, we can detect the SNP allelic interaction whether or not it can be detected as a main effect. Our proposed method assigns a score to unrelated subjects according to their allelic combination inferred from observed genotypes at two or more unlinked SNPs, and then tests for the association of the allelic score with a quantitative trait. To investigate the statistical properties of the proposed method, we performed a simulation study to estimate type I error rates and power and demonstrated that this allelic approach achieves greater power than the more commonly used genotypic approach to test for gene-gene interaction. As an example, the proposed method was applied to data obtained as part of a candidate gene study of sodium retention by the kidney. We found that this method detects an interaction between the calcium-sensing receptor gene (CaSR), the chloride channel gene (CLCNKB) and the Na, K, 2Cl cotransporter gene (CLC12A1) that contributes to variation in diastolic blood pressure.

A Novel Approach for Adaptive Signal Processing

NASA Technical Reports Server (NTRS)

Chen, Ya-Chin; Juang, Jer-Nan

1998-01-01

Adaptive linear predictors have been used extensively in practice in a wide variety of forms. In the main, their theoretical development is based upon the assumption of stationarity of the signals involved, particularly with respect to the second order statistics. On this basis, the well-known normal equations can be formulated. If high- order statistical stationarity is assumed, then the equivalent normal equations involve high-order signal moments. In either case, the cross moments (second or higher) are needed. This renders the adaptive prediction procedure non-blind. A novel procedure for blind adaptive prediction has been proposed and considerable implementation has been made in our contributions in the past year. The approach is based upon a suitable interpretation of blind equalization methods that satisfy the constant modulus property and offers significant deviations from the standard prediction methods. These blind adaptive algorithms are derived by formulating Lagrange equivalents from mechanisms of constrained optimization. In this report, other new update algorithms are derived from the fundamental concepts of advanced system identification to carry out the proposed blind adaptive prediction. The results of the work can be extended to a number of control-related problems, such as disturbance identification. The basic principles are outlined in this report and differences from other existing methods are discussed. The applications implemented are speech processing, such as coding and synthesis. Simulations are included to verify the novel modelling method.

A Method to Search for Correlations of Ultra-high Energy Cosmic-Ray Masses with the Large-scale Structures in the Local Galaxy Density Field

NASA Astrophysics Data System (ADS)

Ivanov, A. A.

2013-02-01

One of the main goals of investigations using present and future giant extensive air shower (EAS) arrays is the mass composition of ultra-high energy cosmic rays (UHECRs). A new approach to the problem is presented, combining the analysis of arrival directions with the statistical test of the paired EAS samples. One of the ideas of the method is to search for possible correlations between UHECR masses and their separate sources; for instance, if there are two sources in different areas of the celestial sphere injecting different nuclei, but the fluxes are comparable so that arrival directions are isotropic, then the aim is to reveal a difference in the mass composition of cosmic-ray fluxes. The method is based on a non-parametric statistical test—the Wilcoxon signed-rank routine—which does not depend on the populations fitting any parameterized distributions. Two particular algorithms are proposed: first, using measurements of the depth of the EAS maximum position in the atmosphere; and second, relying on the age variance of air showers initiated by different primary particles. The formulated method is applied to the Yakutsk array data, in order to demonstrate the possibility of searching for a difference in average mass composition between the two UHECR sets, arriving particularly from the supergalactic plane and a complementary region.

Landslide early warning based on failure forecast models: the example of Mt. de La Saxe rockslide, northern Italy

NASA Astrophysics Data System (ADS)

Manconi, A.; Giordan, D.

2015-02-01

We investigate the use of landslide failure forecast models by exploiting near-real-time monitoring data. Starting from the inverse velocity theory, we analyze landslide surface displacements on different temporal windows, and apply straightforward statistical methods to obtain confidence intervals on the estimated time of failure. Here we describe the main concepts of our method, and show an example of application to a real emergency scenario, the La Saxe rockslide, Aosta Valley region, northern Italy. Based on the herein presented case study, we identify operational thresholds based on the reliability of the forecast models, in order to support the management of early warning systems in the most critical phases of the landslide emergency.

Deployment of paired pushnets from jet-propelled kayaks to sample ichthyoplankton

USGS Publications Warehouse

Acre, Matthew R.; Grabowski, Timothy B.

2015-01-01

Accessing and effectively sampling the off-channel habitats that are considered crucial for early life stages of freshwater fishes constitute a difficult challenge when common ichthyoplankton survey methods, such as push nets, are used. We describe a new method of deploying push nets from jet-propelled kayaks to enable the sampling of previously inaccessible off-channel habitats. The described rig is also functional in more open and accessible habitats, such as the main channel of rivers or reservoirs. Although further evaluation is necessary to ensure that results are comparable across studies, the described push-net system offers a statistically rigorous methodology that generates replicate samples from a wide range of freshwater habitats that were previously inaccessible to this gear type.

Applying temporal abstraction and case-based reasoning to predict approaching influenza waves.

PubMed

Schmidt, Rainer; Gierl, Lothar

2002-01-01

The goal of the TeCoMed project is to send early warnings against forthcoming waves or even epidemics of infectious diseases, especially of influenza, to interested practitioners, pharmacists etc. in the German federal state Mecklenburg-Western Pomerania. The forecast of these waves is based on written confirmations of unfitness for work of the main German health insurance company. Since influenza waves are difficult to predict because of their cyclic but not regular behaviour, statistical methods based on the computation of mean values are not helpful. Instead, we have developed a prognostic model that makes use of similar former courses. Our method combines Case-based Reasoning with Temporal Abstraction to decide whether early warning is appropriate.

Statistical approach to tunneling time in attosecond experiments

NASA Astrophysics Data System (ADS)

Demir, Durmuş; Güner, Tuğrul

2017-11-01

Tunneling, transport of particles through classically forbidden regions, is a pure quantum phenomenon. It governs numerous phenomena ranging from single-molecule electronics to donor-acceptor transition reactions. The main problem is the absence of a universal method to compute tunneling time. This problem has been attacked in various ways in the literature. Here, in the present work, we show that a statistical approach to the problem, motivated by the imaginary nature of time in the forbidden regions, lead to a novel tunneling time formula which is real and subluminal (in contrast to various known time definitions implying superluminal tunneling). In addition to this, we show explicitly that the entropic time formula is in good agreement with the tunneling time measurements in laser-driven He ionization. Moreover, it sets an accurate range for long-range electron transfer reactions. The entropic time formula is general enough to extend to the photon and phonon tunneling phenomena.

[Therapy of organic brain syndrome with nicergoline given once a day].

PubMed

Ladurner, G; Erhart, P; Erhart, C; Scheiber, V

1991-01-01

In a double-blind, active-controlled study 30 patients with mild to moderate multiinfarct dementia diagnosed according to DSM III definition were treated by either 20 mg nicergoline or 4.5 mg co-dergocrine mesilate once daily during eight weeks. Therapeutic effects on symptoms of the organic brain syndrome were quantitatively measured by standardized psychological and psychometric methods evaluating cognitive and thymopsychic functions. Main criteria, which were tested by inferential analysis, were SCAG total score (Sandoz Clinical Assessment Geriatric Scale), SCAG overall impression and the AD Test (alphabetischer Durchstreichtest). Other results were assessed by descriptive statistics. Both treatments resulted in a statistically significant improvement in most of the tested functions. The effects of 4.5 mg co-dergocrine mesilate s.i.d. were in accordance with published results. Although differing slightly with respect to individual results 20 mg of nicergoline once daily showed the same efficacy on the whole.

Difference between healthy children and ADHD based on wavelet spectral analysis of nuclear magnetic resonance images

NASA Astrophysics Data System (ADS)

González Gómez, Dulce I.; Moreno Barbosa, E.; Martínez Hernández, Mario Iván; Ramos Méndez, José; Hidalgo Tobón, Silvia; Dies Suarez, Pilar; Barragán Pérez, Eduardo; De Celis Alonso, Benito

2014-11-01

The main goal of this project was to create a computer algorithm based on wavelet analysis of region of homogeneity images obtained during resting state studies. Ideally it would automatically diagnose ADHD. Because the cerebellum is an area known to be affected by ADHD, this study specifically analysed this region. Male right handed volunteers (infants with ages between 7 and 11 years old) were studied and compared with age matched controls. Statistical differences between the values of the absolute integrated wavelet spectrum were found and showed significant differences (p<0.0015) between groups. This difference might help in the future to distinguish healthy from ADHD patients and therefore diagnose ADHD. Even if results were statistically significant, the small size of the sample limits the applicability of this methods as it is presented here, and further work with larger samples and using freely available datasets must be done.

Optimal experimental designs for fMRI when the model matrix is uncertain.

PubMed

Kao, Ming-Hung; Zhou, Lin

2017-07-15

This study concerns optimal designs for functional magnetic resonance imaging (fMRI) experiments when the model matrix of the statistical model depends on both the selected stimulus sequence (fMRI design), and the subject's uncertain feedback (e.g. answer) to each mental stimulus (e.g. question) presented to her/him. While practically important, this design issue is challenging. This mainly is because that the information matrix cannot be fully determined at the design stage, making it difficult to evaluate the quality of the selected designs. To tackle this challenging issue, we propose an easy-to-use optimality criterion for evaluating the quality of designs, and an efficient approach for obtaining designs optimizing this criterion. Compared with a previously proposed method, our approach requires a much less computing time to achieve designs with high statistical efficiencies. Copyright © 2017 Elsevier Inc. All rights reserved.

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

González Gómez Dulce, I., E-mail: isabeldgg@hotmail.com, E-mail: emoreno@fcfm.buap.mx, E-mail: mim@fcfm.buap.mx, E-mail: joserm84@gmail.com; Moreno Barbosa, E., E-mail: isabeldgg@hotmail.com, E-mail: emoreno@fcfm.buap.mx, E-mail: mim@fcfm.buap.mx, E-mail: joserm84@gmail.com; Hernández, Mario Iván Martínez, E-mail: isabeldgg@hotmail.com, E-mail: emoreno@fcfm.buap.mx, E-mail: mim@fcfm.buap.mx, E-mail: joserm84@gmail.com

The main goal of this project was to create a computer algorithm based on wavelet analysis of region of homogeneity images obtained during resting state studies. Ideally it would automatically diagnose ADHD. Because the cerebellum is an area known to be affected by ADHD, this study specifically analysed this region. Male right handed volunteers (infants with ages between 7 and 11 years old) were studied and compared with age matched controls. Statistical differences between the values of the absolute integrated wavelet spectrum were found and showed significant differences (p<0.0015) between groups. This difference might help in the future to distinguishmore » healthy from ADHD patients and therefore diagnose ADHD. Even if results were statistically significant, the small size of the sample limits the applicability of this methods as it is presented here, and further work with larger samples and using freely available datasets must be done.« less

Colloquium: Hierarchy of scales in language dynamics

NASA Astrophysics Data System (ADS)

Blythe, Richard A.

2015-11-01

Methods and insights from statistical physics are finding an increasing variety of applications where one seeks to understand the emergent properties of a complex interacting system. One such area concerns the dynamics of language at a variety of levels of description, from the behaviour of individual agents learning simple artificial languages from each other, up to changes in the structure of languages shared by large groups of speakers over historical timescales. In this Colloquium, we survey a hierarchy of scales at which language and linguistic behaviour can be described, along with the main progress in understanding that has been made at each of them - much of which has come from the statistical physics community. We argue that future developments may arise by linking the different levels of the hierarchy together in a more coherent fashion, in particular where this allows more effective use of rich empirical data sets.

STATCONT: A statistical continuum level determination method for line-rich sources

NASA Astrophysics Data System (ADS)

Sánchez-Monge, Á.; Schilke, P.; Ginsburg, A.; Cesaroni, R.; Schmiedeke, A.

2018-01-01

STATCONT is a python-based tool designed to determine the continuum emission level in spectral data, in particular for sources with a line-rich spectrum. The tool inspects the intensity distribution of a given spectrum and automatically determines the continuum level by using different statistical approaches. The different methods included in STATCONT are tested against synthetic data. We conclude that the sigma-clipping algorithm provides the most accurate continuum level determination, together with information on the uncertainty in its determination. This uncertainty can be used to correct the final continuum emission level, resulting in the here called `corrected sigma-clipping method' or c-SCM. The c-SCM has been tested against more than 750 different synthetic spectra reproducing typical conditions found towards astronomical sources. The continuum level is determined with a discrepancy of less than 1% in 50% of the cases, and less than 5% in 90% of the cases, provided at least 10% of the channels are line free. The main products of STATCONT are the continuum emission level, together with a conservative value of its uncertainty, and datacubes containing only spectral line emission, i.e., continuum-subtracted datacubes. STATCONT also includes the option to estimate the spectral index, when different files covering different frequency ranges are provided.

Experimental and statistical post-validation of positive example EST sequences carrying peroxisome targeting signals type 1 (PTS1)

PubMed Central

Lingner, Thomas; Kataya, Amr R. A.; Reumann, Sigrun

2012-01-01

We recently developed the first algorithms specifically for plants to predict proteins carrying peroxisome targeting signals type 1 (PTS1) from genome sequences.1 As validated experimentally, the prediction methods are able to correctly predict unknown peroxisomal Arabidopsis proteins and to infer novel PTS1 tripeptides. The high prediction performance is primarily determined by the large number and sequence diversity of the underlying positive example sequences, which mainly derived from EST databases. However, a few constructs remained cytosolic in experimental validation studies, indicating sequencing errors in some ESTs. To identify erroneous sequences, we validated subcellular targeting of additional positive example sequences in the present study. Moreover, we analyzed the distribution of prediction scores separately for each orthologous group of PTS1 proteins, which generally resembled normal distributions with group-specific mean values. The cytosolic sequences commonly represented outliers of low prediction scores and were located at the very tail of a fitted normal distribution. Three statistical methods for identifying outliers were compared in terms of sensitivity and specificity.” Their combined application allows elimination of erroneous ESTs from positive example data sets. This new post-validation method will further improve the prediction accuracy of both PTS1 and PTS2 protein prediction models for plants, fungi, and mammals. PMID:22415050

Sulcal depth-based cortical shape analysis in normal healthy control and schizophrenia groups

NASA Astrophysics Data System (ADS)

Lyu, Ilwoo; Kang, Hakmook; Woodward, Neil D.; Landman, Bennett A.

2018-03-01

Sulcal depth is an important marker of brain anatomy in neuroscience/neurological function. Previously, sulcal depth has been explored at the region-of-interest (ROI) level to increase statistical sensitivity to group differences. In this paper, we present a fully automated method that enables inferences of ROI properties from a sulcal region- focused perspective consisting of two main components: 1) sulcal depth computation and 2) sulcal curve-based refined ROIs. In conventional statistical analysis, the average sulcal depth measurements are employed in several ROIs of the cortical surface. However, taking the average sulcal depth over the full ROI blurs overall sulcal depth measurements which may result in reduced sensitivity to detect sulcal depth changes in neurological and psychiatric disorders. To overcome such a blurring effect, we focus on sulcal fundic regions in each ROI by filtering out other gyral regions. Consequently, the proposed method results in more sensitive to group differences than a traditional ROI approach. In the experiment, we focused on a cortical morphological analysis to sulcal depth reduction in schizophrenia with a comparison to the normal healthy control group. We show that the proposed method is more sensitivity to abnormalities of sulcal depth in schizophrenia; sulcal depth is significantly smaller in most cortical lobes in schizophrenia compared to healthy controls (p < 0.05).

Experimental and statistical post-validation of positive example EST sequences carrying peroxisome targeting signals type 1 (PTS1).

PubMed

Lingner, Thomas; Kataya, Amr R A; Reumann, Sigrun

2012-02-01

We recently developed the first algorithms specifically for plants to predict proteins carrying peroxisome targeting signals type 1 (PTS1) from genome sequences. As validated experimentally, the prediction methods are able to correctly predict unknown peroxisomal Arabidopsis proteins and to infer novel PTS1 tripeptides. The high prediction performance is primarily determined by the large number and sequence diversity of the underlying positive example sequences, which mainly derived from EST databases. However, a few constructs remained cytosolic in experimental validation studies, indicating sequencing errors in some ESTs. To identify erroneous sequences, we validated subcellular targeting of additional positive example sequences in the present study. Moreover, we analyzed the distribution of prediction scores separately for each orthologous group of PTS1 proteins, which generally resembled normal distributions with group-specific mean values. The cytosolic sequences commonly represented outliers of low prediction scores and were located at the very tail of a fitted normal distribution. Three statistical methods for identifying outliers were compared in terms of sensitivity and specificity." Their combined application allows elimination of erroneous ESTs from positive example data sets. This new post-validation method will further improve the prediction accuracy of both PTS1 and PTS2 protein prediction models for plants, fungi, and mammals.

Estimation of usual occasion-based individual drinking patterns using diary survey data.

PubMed

Hill-McManus, Daniel; Angus, Colin; Meng, Yang; Holmes, John; Brennan, Alan; Sylvia Meier, Petra

2014-01-01

In order to successfully address excessive alcohol consumption it is essential to have a means of measuring the drinking patterns of a nation. Owing to the multi-dimensional nature of drinking patterns, usual survey methods have their limitations. The aim of this study was to make use of extremely detailed diary survey data to demonstrate a method of combining different survey measures of drinking in order to reduce these limitations. Data for 1724 respondents of the 2000/01 National Diet and Nutrition Survey was used to obtain a drinking occasion dataset, by plotting the respondent's blood alcohol content over time. Drinking frequency, level and variation measures were chosen to characterise drinking behaviour and usual behaviour was estimated via statistical methods. Complex patterns in drinking behaviour were observed amongst population subgroups using the chosen consumption measures. The predicted drinking distribution combines diary data equivalent coverage with a more accurate proportion of non-drinkers. This statistical analysis provides a means of obtaining average consumption measures from diary data and thus reducing the main limitation of this type of data for many applications. We hope that this will facilitate the use of such data in a wide range of applications such as risk modelling, especially for acute harms, and burden of disease studies. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Methodes entropiques appliquees au probleme inverse en magnetoencephalographie

NASA Astrophysics Data System (ADS)

Lapalme, Ervig

2005-07-01

This thesis is devoted to biomagnetic source localization using magnetoencephalography. This problem is known to have an infinite number of solutions. So methods are required to take into account anatomical and functional information on the solution. The work presented in this thesis uses the maximum entropy on the mean method to constrain the solution. This method originates from statistical mechanics and information theory. This thesis is divided into two main parts containing three chapters each. The first part reviews the magnetoencephalographic inverse problem: the theory needed to understand its context and the hypotheses for simplifying the problem. In the last chapter of this first part, the maximum entropy on the mean method is presented: its origins are explained and also how it is applied to our problem. The second part is the original work of this thesis presenting three articles; one of them already published and two others submitted for publication. In the first article, a biomagnetic source model is developed and applied in a theoretical con text but still demonstrating the efficiency of the method. In the second article, we go one step further towards a realistic modelization of the cerebral activation. The main priors are estimated using the magnetoencephalographic data. This method proved to be very efficient in realistic simulations. In the third article, the previous method is extended to deal with time signals thus exploiting the excellent time resolution offered by magnetoencephalography. Compared with our previous work, the temporal method is applied to real magnetoencephalographic data coming from a somatotopy experience and results agree with previous physiological knowledge about this kind of cognitive process.

Occupational Dermatoses by Type of Work in Greece

PubMed Central

Zorba, Eleni; Karpouzis, Antony; Zorbas, Alexandros; Bazas, Theodore; Zorbas, Sam; Alexopoulos, Elias; Zorbas, Ilias; Kouskoukis, Konstantinos; Konstandinidis, Theodoros

2013-01-01

Background To elucidate the relationship between seven occupational dermatoses (ODs) and 20 types of work in Greece. Methods This was a prevalence epidemiologic study of certain ODs among 4,000 workers employed in 20 types of enterprise, in 104 companies, in 2006–2012, using data from company medical records, questionnaires, occupational medical, and special examinations. The χ2 test was applied to reveal statistically significant relationships between types of enterprises and occurrence of ODs. Results A high percentage (39.9%) of employees included in the study population suffered from ODs. The highest prevalence rates were noted among hairdressers (of contact dermatitis: 30%), cooks (of contact dermatitis: 29.5%), bitumen workers (of acne: 23.5%), car industry workers (of mechanical injury: 15%), construction workers (of contact urticaria: 29.5%), industrial cleaning workers (of chemical burns: 13%), and farmers (of malignant tumors: 5.5%). We observed several statistical significant correlations between ODs (acute and chronic contact dermatitis, urticaria, mechanical injury, acne, burns, skin cancer) and certain types of enterprises. There was no statistically significant correlation between gender and prevalence of ODs, except for dermatoses caused by mechanical injuries afflicting mainly men [χ2 (1) = 13.40, p < 0.001] and for chronic contact dermatitis [χ2 (1) = 5.53, p = 0.019] afflicting mainly women. Conclusion Prevalence of ODs is high in Greece, contrary to all official reports by the Greek National Institute of Health. There is a need to introduce a nationwide voluntary surveillance system for reporting ODs and to enhance skin protection measures at work. PMID:24106644

Assessment of water quality parameters using multivariate analysis for Klang River basin, Malaysia.

PubMed

Mohamed, Ibrahim; Othman, Faridah; Ibrahim, Adriana I N; Alaa-Eldin, M E; Yunus, Rossita M

2015-01-01

This case study uses several univariate and multivariate statistical techniques to evaluate and interpret a water quality data set obtained from the Klang River basin located within the state of Selangor and the Federal Territory of Kuala Lumpur, Malaysia. The river drains an area of 1,288 km(2), from the steep mountain rainforests of the main Central Range along Peninsular Malaysia to the river mouth in Port Klang, into the Straits of Malacca. Water quality was monitored at 20 stations, nine of which are situated along the main river and 11 along six tributaries. Data was collected from 1997 to 2007 for seven parameters used to evaluate the status of the water quality, namely dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, suspended solids, ammoniacal nitrogen, pH, and temperature. The data were first investigated using descriptive statistical tools, followed by two practical multivariate analyses that reduced the data dimensions for better interpretation. The analyses employed were factor analysis and principal component analysis, which explain 60 and 81.6% of the total variation in the data, respectively. We found that the resulting latent variables from the factor analysis are interpretable and beneficial for describing the water quality in the Klang River. This study presents the usefulness of several statistical methods in evaluating and interpreting water quality data for the purpose of monitoring the effectiveness of water resource management. The results should provide more straightforward data interpretation as well as valuable insight for managers to conceive optimum action plans for controlling pollution in river water.

Application of statistical downscaling technique for the production of wine grapes (Vitis vinifera L.) in Spain

NASA Astrophysics Data System (ADS)

Gaitán Fernández, E.; García Moreno, R.; Pino Otín, M. R.; Ribalaygua Batalla, J.

2012-04-01

Climate and soil are two of the most important limiting factors for agricultural production. Nowadays climate change has been documented in many geographical locations affecting different cropping systems. The General Circulation Models (GCM) has become important tools to simulate the more relevant aspects of the climate expected for the XXI century in the frame of climatic change. These models are able to reproduce the general features of the atmospheric dynamic but their low resolution (about 200 Km) avoids a proper simulation of lower scale meteorological effects. Downscaling techniques allow overcoming this problem by adapting the model outcomes to local scale. In this context, FIC (Fundación para la Investigación del Clima) has developed a statistical downscaling technique based on a two step analogue methods. This methodology has been broadly tested on national and international environments leading to excellent results on future climate models. In a collaboration project, this statistical downscaling technique was applied to predict future scenarios for the grape growing systems in Spain. The application of such model is very important to predict expected climate for the different growing crops, mainly for grape, where the success of different varieties are highly related to climate and soil. The model allowed the implementation of agricultural conservation practices in the crop production, detecting highly sensible areas to negative impacts produced by any modification of climate in the different regions, mainly those protected with protected designation of origin, and the definition of new production areas with optimal edaphoclimatic conditions for the different varieties.

Statistical analysis plan for the Laser-1st versus Drops-1st for Glaucoma and Ocular Hypertension Trial (LiGHT): a multi-centre randomised controlled trial.

PubMed

Vickerstaff, Victoria; Ambler, Gareth; Bunce, Catey; Xing, Wen; Gazzard, Gus

2015-11-11

The LiGHT trial (Laser-1st versus Drops-1st for Glaucoma and Ocular Hypertension Trial) is a multicentre randomised controlled trial of two treatment pathways for patients who are newly diagnosed with open-angle glaucoma (OAG) and ocular hypertension (OHT). The main hypothesis for the trial is that lowering intraocular pressure (IOP) with selective laser trabeculoplasty (SLT) as the primary treatment ('Laser-1st') leads to a better health-related quality of life than for those started on IOP-lowering drops as their primary treatment ('Medicine-1st') and that this is associated with reduced costs and improved tolerability of treatment. This paper describes the statistical analysis plan for the study. The LiGHT trial is an unmasked, multi-centre randomised controlled trial. A total of 718 patients (359 per arm) are being randomised to two groups: medicine-first or laser-first treatment. Outcomes are recorded at baseline and at 6-month intervals up to 36 months. The primary outcome measure is health-related quality of life (HRQL) at 36 months measured using the EQ-5D-5L. The main secondary outcome is the Glaucoma Utility Index. We plan to analyse the patient outcome data according to the group to which the patient was originally assigned. Methods of statistical analysis are described, including the handling of missing data, the covariates used in the adjusted analyses and the planned sensitivity analyses. The trial was registered with the ISRCTN register on 23/07/2012, number ISRCTN32038223 .

Bias-correction and Spatial Disaggregation for Climate Change Impact Assessments at a basin scale

NASA Astrophysics Data System (ADS)

Nyunt, Cho; Koike, Toshio; Yamamoto, Akio; Nemoto, Toshihoro; Kitsuregawa, Masaru

2013-04-01

Basin-scale climate change impact studies mainly rely on general circulation models (GCMs) comprising the related emission scenarios. Realistic and reliable data from GCM is crucial for national scale or basin scale impact and vulnerability assessments to build safety society under climate change. However, GCM fail to simulate regional climate features due to the imprecise parameterization schemes in atmospheric physics and coarse resolution scale. This study describes how to exclude some unsatisfactory GCMs with respect to focused basin, how to minimize the biases of GCM precipitation through statistical bias correction and how to cover spatial disaggregation scheme, a kind of downscaling, within in a basin. GCMs rejection is based on the regional climate features of seasonal evolution as a bench mark and mainly depends on spatial correlation and root mean square error of precipitation and atmospheric variables over the target region. Global Precipitation Climatology Project (GPCP) and Japanese 25-uear Reanalysis Project (JRA-25) are specified as references in figuring spatial pattern and error of GCM. Statistical bias-correction scheme comprises improvements of three main flaws of GCM precipitation such as low intensity drizzled rain days with no dry day, underestimation of heavy rainfall and inter-annual variability of local climate. Biases of heavy rainfall are conducted by generalized Pareto distribution (GPD) fitting over a peak over threshold series. Frequency of rain day error is fixed by rank order statistics and seasonal variation problem is solved by using a gamma distribution fitting in each month against insi-tu stations vs. corresponding GCM grids. By implementing the proposed bias-correction technique to all insi-tu stations and their respective GCM grid, an easy and effective downscaling process for impact studies at the basin scale is accomplished. The proposed method have been examined its applicability to some of the basins in various climate regions all over the world. The biases are controlled very well by using this scheme in all applied basins. After that, bias-corrected and downscaled GCM precipitation are ready to use for simulating the Water and Energy Budget based Distributed Hydrological Model (WEB-DHM) to analyse the stream flow change or water availability of a target basin under the climate change in near future. Furthermore, it can be investigated any inter-disciplinary studies such as drought, flood, food, health and so on.In summary, an effective and comprehensive statistical bias-correction method was established to fulfil the generative applicability of GCM scale to basin scale without difficulty. This gap filling also promotes the sound decision of river management in the basin with more reliable information to build the resilience society.

The change and development of statistical methods used in research articles in child development 1930-2010.

PubMed

Køppe, Simo; Dammeyer, Jesper

2014-09-01

The evolution of developmental psychology has been characterized by the use of different quantitative and qualitative methods and procedures. But how does the use of methods and procedures change over time? This study explores the change and development of statistical methods used in articles published in Child Development from 1930 to 2010. The methods used in every article in the first issue of every volume were categorized into four categories. Until 1980 relatively simple statistical methods were used. During the last 30 years there has been an explosive use of more advanced statistical methods employed. The absence of statistical methods or use of simple methods had been eliminated.

Cluster categorization of urban roads to optimize their noise monitoring.

PubMed

Zambon, G; Benocci, R; Brambilla, G

2016-01-01

Road traffic in urban areas is recognized to be associated with urban mobility and public health, and it is often the main source of noise pollution. Lately, noise maps have been considered a powerful tool to estimate the population exposure to environmental noise, but they need to be validated by measured noise data. The project Dynamic Acoustic Mapping (DYNAMAP), co-funded in the framework of the LIFE 2013 program, is aimed to develop a statistically based method to optimize the choice and the number of monitoring sites and to automate the noise mapping update using the data retrieved from a low-cost monitoring network. Indeed, the first objective should improve the spatial sampling based on the legislative road classification, as this classification is mainly based on the geometrical characteristics of the road, rather than its noise emission. The present paper describes the statistical approach of the methodology under development and the results of its preliminary application to a limited sample of roads in the city of Milan. The resulting categorization of roads, based on clustering the 24-h hourly L Aeqh, looks promising to optimize the spatial sampling of noise monitoring toward a description of the noise pollution due to complex urban road networks more efficient than that based on the legislative road classification.

Non-Asbestos Insulation Testing Using a Plasma Torch

NASA Technical Reports Server (NTRS)

Morgan, R. E.; Prince, A. S.; Selvidge, S. A.; Phelps, J.; Martin, C. L.; Lawrence, T. W.

2000-01-01

Insulation obsolescence issues are a major concern for the Reusable Solid Rocket Motor (RSRM). As old sources of raw materials disappear, new sources must be found and qualified. No simple, inexpensive test presently exists for predicting the erosion performance of a candidate insulation in the full-scale motor, Large motor tests cost million of dollars and therefore can only be used on a few very select candidates. There is a need for a simple, low cost method of screening insulation performance that can simulate some of the different erosion environments found in the RSRM. This paper describes a series of erosion tests on two different non-asbestos insulation formulations, a KEVLAR(registered) fiber-filled and a carbon fiber-filled insulation containing Ethylene-Propylene-Diene Monomer (EPDM) rubber as the binder. The test instrument was a plasma torch device. The two main variables investigated were heat flux and alumina particle impingement concentration. Statistical analysis revealed that the two different formulations had very different responses to the main variable. The results of this work indicate that there may be fundamental differences in how these insulation formulations perform in the motor operating environment. The plasma torch appears to offer a low-cost means of obtaining a fundamental understanding of insulation response to critical factors in a series of statistically designed experiments.

Additive interaction between heterogeneous environmental ...

EPA Pesticide Factsheets

BACKGROUND Environmental exposures often occur in tandem; however, epidemiological research often focuses on singular exposures. Statistical interactions among broad, well-characterized environmental domains have not yet been evaluated in association with health. We address this gap by conducting a county-level cross-sectional analysis of interactions between Environmental Quality Index (EQI) domain indices on preterm birth in the Unites States from 2000-2005.METHODS: The EQI, a county-level index constructed for the 2000-2005 time period, was constructed from five domain-specific indices (air, water, land, built and sociodemographic) using principal component analyses. County-level preterm birth rates (n=3141) were estimated using live births from the National Center for Health Statistics. Linear regression was used to estimate prevalence differences (PD) and 95% confidence intervals (CI) comparing worse environmental quality to the better quality for each model for a) each individual domain main effect b) the interaction contrast and c) the two main effects plus interaction effect (i.e. the “net effect”) to show departure from additive interaction for the all U.S counties. Analyses were also performed for subgroupings by four urban/rural strata. RESULTS: We found the suggestion of antagonistic interactions but no synergism, along with several purely additive (i.e., no interaction) associations. In the non-stratified model, we observed antagonistic interac

Potential use of telephone-based survey for non-communicable disease surveillance in Sri Lanka.

PubMed

Herath, H M M; Weerasinghe, N P; Weerarathna, T P; Hemantha, A; Amarathunga, A

2017-12-29

Telephone survey (TS) has been a popular tool for conducting health surveys, particularly in developed countries. However, the feasibility, and reliability of TS are not adequately explored in Sri Lanka. The main aim of this study is to assess the effectiveness of telephone-based survey in estimating the prevalence of common non-communicable diseases (NCDs) in Sri Lanka. We carried out an observational cross-sectional study using telephone interview method in Galle district, Sri Lanka. The study participants were selected randomly from the residents living in the households with fixed land telephone lines. The prevalence of the main NCDs was estimated using descriptive statistics. Overall, 975 telephone numbers belonging to six main areas of Galle district were called, and 48% agreed to participate in the study. Of the non-respondents, 22% actively declined to participate. Data on NCDs were gathered from 1470 individuals. The most common self-reported NCD was hypertension (17.%), followed by diabetes (16.3%) and dyslipidaemia (15.6%). Smoking was exclusively seen in males (7.4%), and regular alcohol use was significantly more common in males (19.2%) than females (0.4%, P < .001). Our study revealed average response rate for telephone based interview in Sri Lankan setting. Overall prevalence of main NCDs in this study showed a comparable prevalence to studies used face to face interview method. This study supports the potential use of telephone-based survey to assess heath related information in Sri Lanka.

Guidelines for Design and Analysis of Large, Brittle Spacecraft Components

NASA Technical Reports Server (NTRS)

Robinson, E. Y.

1993-01-01

There were two related parts to this work. The first, conducted at The Aerospace Corporation was to develop and define methods for integrating the statistical theory of brittle strength with conventional finite element stress analysis, and to carry out a limited laboratory test program to illustrate the methods. The second part, separately funded at Aerojet Electronic Systems Division, was to create the finite element postprocessing program for integrating the statistical strength analysis with the structural analysis. The second part was monitored by Capt. Jeff McCann of USAF/SMC, as Special Study No.11, which authorized Aerojet to support Aerospace on this work requested by NASA. This second part is documented in Appendix A. The activity at Aerojet was guided by the Aerospace methods developed in the first part of this work. This joint work of Aerospace and Aerojet stemmed from prior related work for the Defense Support Program (DSP) Program Office, to qualify the DSP sensor main mirror and corrector lens for flight as part of a shuttle payload. These large brittle components of the DSP sensor are provided by Aerojet. This document defines rational methods for addressing the structural integrity and safety of large, brittle, payload components, which have low and variable tensile strength and can suddenly break or shatter. The methods are applicable to the evaluation and validation of such components, which, because of size and configuration restrictions, cannot be validated by direct proof test.

Evaluating the effectiveness of Behavior-Based Safety education methods for commercial vehicle drivers.

PubMed

Wang, Xuesong; Xing, Yilun; Luo, Lian; Yu, Rongjie

2018-08-01

Risky driving behavior is one of the main causes of commercial vehicle related crashes. In order to achieve safer vehicle operation, safety education for drivers is often provided. However, the education programs vary in quality and may not always be successful in reducing crash rates. Behavior-Based Safety (BBS) education is a popular approach found effective by numerous studies, but even this approach varies as to the combination of frequency, mode and content used by different education providers. This study therefore evaluates and compares the effectiveness of BBS education methods. Thirty-five drivers in Shanghai, China, were coached with one of three different BBS education methods for 13 weeks following a 13-week baseline phase with no education. A random-effects negative binomial (NB) model was built and calibrated to investigate the relationship between BBS education and the driver at-fault safety-related event rate. Based on the results of the random-effects NB model, event modification factors (EMF) were calculated to evaluate and compare the effectiveness of the methods. Results show that (1) BBS education was confirmed to be effective in safety-related event reduction; (2) the most effective method among the three applied monthly face-to-face coaching, including feedback with video and statistical data, and training on strategies to avoid driver-specific unsafe behaviors; (3) weekly telephone coaching using statistics and strategies was rated by drivers as the most convenient delivery mode, and was also significantly effective. Copyright © 2018 Elsevier Ltd. All rights reserved.

Perceptron ensemble of graph-based positive-unlabeled learning for disease gene identification.

PubMed

Jowkar, Gholam-Hossein; Mansoori, Eghbal G

2016-10-01

Identification of disease genes, using computational methods, is an important issue in biomedical and bioinformatics research. According to observations that diseases with the same or similar phenotype have the same biological characteristics, researchers have tried to identify genes by using machine learning tools. In recent attempts, some semi-supervised learning methods, called positive-unlabeled learning, is used for disease gene identification. In this paper, we present a Perceptron ensemble of graph-based positive-unlabeled learning (PEGPUL) on three types of biological attributes: gene ontologies, protein domains and protein-protein interaction networks. In our method, a reliable set of positive and negative genes are extracted using co-training schema. Then, the similarity graph of genes is built using metric learning by concentrating on multi-rank-walk method to perform inference from labeled genes. At last, a Perceptron ensemble is learned from three weighted classifiers: multilevel support vector machine, k-nearest neighbor and decision tree. The main contributions of this paper are: (i) incorporating the statistical properties of gene data through choosing proper metrics, (ii) statistical evaluation of biological features, and (iii) noise robustness characteristic of PEGPUL via using multilevel schema. In order to assess PEGPUL, we have applied it on 12950 disease genes with 949 positive genes from six class of diseases and 12001 unlabeled genes. Compared with some popular disease gene identification methods, the experimental results show that PEGPUL has reasonable performance. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

Statistical Analysis of Crystallization Database Links Protein Physico-Chemical Features with Crystallization Mechanisms

PubMed Central

Fusco, Diana; Barnum, Timothy J.; Bruno, Andrew E.; Luft, Joseph R.; Snell, Edward H.; Mukherjee, Sayan; Charbonneau, Patrick

2014-01-01

X-ray crystallography is the predominant method for obtaining atomic-scale information about biological macromolecules. Despite the success of the technique, obtaining well diffracting crystals still critically limits going from protein to structure. In practice, the crystallization process proceeds through knowledge-informed empiricism. Better physico-chemical understanding remains elusive because of the large number of variables involved, hence little guidance is available to systematically identify solution conditions that promote crystallization. To help determine relationships between macromolecular properties and their crystallization propensity, we have trained statistical models on samples for 182 proteins supplied by the Northeast Structural Genomics consortium. Gaussian processes, which capture trends beyond the reach of linear statistical models, distinguish between two main physico-chemical mechanisms driving crystallization. One is characterized by low levels of side chain entropy and has been extensively reported in the literature. The other identifies specific electrostatic interactions not previously described in the crystallization context. Because evidence for two distinct mechanisms can be gleaned both from crystal contacts and from solution conditions leading to successful crystallization, the model offers future avenues for optimizing crystallization screens based on partial structural information. The availability of crystallization data coupled with structural outcomes analyzed through state-of-the-art statistical models may thus guide macromolecular crystallization toward a more rational basis. PMID:24988076

Statistical analysis of crystallization database links protein physico-chemical features with crystallization mechanisms.

PubMed

Fusco, Diana; Barnum, Timothy J; Bruno, Andrew E; Luft, Joseph R; Snell, Edward H; Mukherjee, Sayan; Charbonneau, Patrick

2014-01-01

X-ray crystallography is the predominant method for obtaining atomic-scale information about biological macromolecules. Despite the success of the technique, obtaining well diffracting crystals still critically limits going from protein to structure. In practice, the crystallization process proceeds through knowledge-informed empiricism. Better physico-chemical understanding remains elusive because of the large number of variables involved, hence little guidance is available to systematically identify solution conditions that promote crystallization. To help determine relationships between macromolecular properties and their crystallization propensity, we have trained statistical models on samples for 182 proteins supplied by the Northeast Structural Genomics consortium. Gaussian processes, which capture trends beyond the reach of linear statistical models, distinguish between two main physico-chemical mechanisms driving crystallization. One is characterized by low levels of side chain entropy and has been extensively reported in the literature. The other identifies specific electrostatic interactions not previously described in the crystallization context. Because evidence for two distinct mechanisms can be gleaned both from crystal contacts and from solution conditions leading to successful crystallization, the model offers future avenues for optimizing crystallization screens based on partial structural information. The availability of crystallization data coupled with structural outcomes analyzed through state-of-the-art statistical models may thus guide macromolecular crystallization toward a more rational basis.

[Review of research design and statistical methods in Chinese Journal of Cardiology].

PubMed

Zhang, Li-jun; Yu, Jin-ming

2009-07-01

To evaluate the research design and the use of statistical methods in Chinese Journal of Cardiology. Peer through the research design and statistical methods in all of the original papers in Chinese Journal of Cardiology from December 2007 to November 2008. The most frequently used research designs are cross-sectional design (34%), prospective design (21%) and experimental design (25%). In all of the articles, 49 (25%) use wrong statistical methods, 29 (15%) lack some sort of statistic analysis, 23 (12%) have inconsistencies in description of methods. There are significant differences between different statistical methods (P < 0.001). The correction rates of multifactor analysis were low and repeated measurement datas were not used repeated measurement analysis. Many problems exist in Chinese Journal of Cardiology. Better research design and correct use of statistical methods are still needed. More strict review by statistician and epidemiologist is also required to improve the literature qualities.

Model-based economic evaluation in Alzheimer's disease: a review of the methods available to model Alzheimer's disease progression.

PubMed

Green, Colin; Shearer, James; Ritchie, Craig W; Zajicek, John P

2011-01-01

To consider the methods available to model Alzheimer's disease (AD) progression over time to inform on the structure and development of model-based evaluations, and the future direction of modelling methods in AD. A systematic search of the health care literature was undertaken to identify methods to model disease progression in AD. Modelling methods are presented in a descriptive review. The literature search identified 42 studies presenting methods or applications of methods to model AD progression over time. The review identified 10 general modelling frameworks available to empirically model the progression of AD as part of a model-based evaluation. Seven of these general models are statistical models predicting progression of AD using a measure of cognitive function. The main concerns with models are on model structure, around the limited characterization of disease progression, and on the use of a limited number of health states to capture events related to disease progression over time. None of the available models have been able to present a comprehensive model of the natural history of AD. Although helpful, there are serious limitations in the methods available to model progression of AD over time. Advances are needed to better model the progression of AD and the effects of the disease on peoples' lives. Recent evidence supports the need for a multivariable approach to the modelling of AD progression, and indicates that a latent variable analytic approach to characterising AD progression is a promising avenue for advances in the statistical development of modelling methods. Copyright © 2011 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

ConvAn: a convergence analyzing tool for optimization of biochemical networks.

PubMed

Kostromins, Andrejs; Mozga, Ivars; Stalidzans, Egils

2012-01-01

Dynamic models of biochemical networks usually are described as a system of nonlinear differential equations. In case of optimization of models for purpose of parameter estimation or design of new properties mainly numerical methods are used. That causes problems of optimization predictability as most of numerical optimization methods have stochastic properties and the convergence of the objective function to the global optimum is hardly predictable. Determination of suitable optimization method and necessary duration of optimization becomes critical in case of evaluation of high number of combinations of adjustable parameters or in case of large dynamic models. This task is complex due to variety of optimization methods, software tools and nonlinearity features of models in different parameter spaces. A software tool ConvAn is developed to analyze statistical properties of convergence dynamics for optimization runs with particular optimization method, model, software tool, set of optimization method parameters and number of adjustable parameters of the model. The convergence curves can be normalized automatically to enable comparison of different methods and models in the same scale. By the help of the biochemistry adapted graphical user interface of ConvAn it is possible to compare different optimization methods in terms of ability to find the global optima or values close to that as well as the necessary computational time to reach them. It is possible to estimate the optimization performance for different number of adjustable parameters. The functionality of ConvAn enables statistical assessment of necessary optimization time depending on the necessary optimization accuracy. Optimization methods, which are not suitable for a particular optimization task, can be rejected if they have poor repeatability or convergence properties. The software ConvAn is freely available on www.biosystems.lv/convan. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Debating Curricular Strategies for Teaching Statistics and Research Methods: What Does the Current Evidence Suggest?

ERIC Educational Resources Information Center

Barron, Kenneth E.; Apple, Kevin J.

2014-01-01

Coursework in statistics and research methods is a core requirement in most undergraduate psychology programs. However, is there an optimal way to structure and sequence methodology courses to facilitate student learning? For example, should statistics be required before research methods, should research methods be required before statistics, or…

Development of a Research Methods and Statistics Concept Inventory

ERIC Educational Resources Information Center

Veilleux, Jennifer C.; Chapman, Kate M.

2017-01-01

Research methods and statistics are core courses in the undergraduate psychology major. To assess learning outcomes, it would be useful to have a measure that assesses research methods and statistical literacy beyond course grades. In two studies, we developed and provided initial validation results for a research methods and statistical knowledge…

Understanding common statistical methods, Part I: descriptive methods, probability, and continuous data.

PubMed

Skinner, Carl G; Patel, Manish M; Thomas, Jerry D; Miller, Michael A

2011-01-01

Statistical methods are pervasive in medical research and general medical literature. Understanding general statistical concepts will enhance our ability to critically appraise the current literature and ultimately improve the delivery of patient care. This article intends to provide an overview of the common statistical methods relevant to medicine.

Factors Influencing the Behavioural Intention to Use Statistical Software: The Perspective of the Slovenian Students of Social Sciences

ERIC Educational Resources Information Center

Brezavšcek, Alenka; Šparl, Petra; Žnidaršic, Anja

2017-01-01

The aim of the paper is to investigate the main factors influencing the adoption and continuous utilization of statistical software among university social sciences students in Slovenia. Based on the Technology Acceptance Model (TAM), a conceptual model was derived where five external variables were taken into account: statistical software…

Comparison of the Various Methodologies Used in Studying Runoff and Sediment Load in the Yellow River Basin

NASA Astrophysics Data System (ADS)

Xu, M., III; Liu, X.

2017-12-01

In the past 60 years, both the runoff and sediment load in the Yellow River Basin showed significant decreasing trends owing to the influences of human activities and climate change. Quantifying the impact of each factor (e.g. precipitation, sediment trapping dams, pasture, terrace, etc.) on the runoff and sediment load is among the key issues to guide the implement of water and soil conservation measures, and to predict the variation trends in the future. Hundreds of methods have been developed for studying the runoff and sediment load in the Yellow River Basin. Generally, these methods can be classified into empirical methods and physical-based models. The empirical methods, including hydrological method, soil and water conservation method, etc., are widely used in the Yellow River management engineering. These methods generally apply the statistical analyses like the regression analysis to build the empirical relationships between the main characteristic variables in a river basin. The elasticity method extensively used in the hydrological research can be classified into empirical method as it is mathematically deduced to be equivalent with the hydrological method. Physical-based models mainly include conceptual models and distributed models. The conceptual models are usually lumped models (e.g. SYMHD model, etc.) and can be regarded as transition of empirical models and distributed models. Seen from the publications that less studies have been conducted applying distributed models than empirical models as the simulation results of runoff and sediment load based on distributed models (e.g. the Digital Yellow Integrated Model, the Geomorphology-Based Hydrological Model, etc.) were usually not so satisfied owing to the intensive human activities in the Yellow River Basin. Therefore, this study primarily summarizes the empirical models applied in the Yellow River Basin and theoretically analyzes the main causes for the significantly different results using different empirical researching methods. Besides, we put forward an assessment frame for the researching methods of the runoff and sediment load variations in the Yellow River Basin from the point of view of inputting data, model structure and result output. And the assessment frame was then applied in the Huangfuchuan River.

Compendium of abstracts on statistical applications in geotechnical engineering

NASA Astrophysics Data System (ADS)

Hynes-Griffin, M. E.; Deer, G. W.

1983-09-01

The results of a literature search of geotechnical and statistical abstracts are presented in tables listing specific topics, title of the abstract, main author and the file number under which the abstract can be found.

A Primer on Bayesian Analysis for Experimental Psychopathologists

PubMed Central

Krypotos, Angelos-Miltiadis; Blanken, Tessa F.; Arnaudova, Inna; Matzke, Dora; Beckers, Tom

2016-01-01

The principal goals of experimental psychopathology (EPP) research are to offer insights into the pathogenic mechanisms of mental disorders and to provide a stable ground for the development of clinical interventions. The main message of the present article is that those goals are better served by the adoption of Bayesian statistics than by the continued use of null-hypothesis significance testing (NHST). In the first part of the article we list the main disadvantages of NHST and explain why those disadvantages limit the conclusions that can be drawn from EPP research. Next, we highlight the advantages of Bayesian statistics. To illustrate, we then pit NHST and Bayesian analysis against each other using an experimental data set from our lab. Finally, we discuss some challenges when adopting Bayesian statistics. We hope that the present article will encourage experimental psychopathologists to embrace Bayesian statistics, which could strengthen the conclusions drawn from EPP research. PMID:28748068

[Establishment of the mathematic model of total quantum statistical moment standard similarity for application to medical theoretical research].

PubMed

He, Fu-yuan; Deng, Kai-wen; Huang, Sheng; Liu, Wen-long; Shi, Ji-lian

2013-09-01

The paper aims to elucidate and establish a new mathematic model: the total quantum statistical moment standard similarity (TQSMSS) on the base of the original total quantum statistical moment model and to illustrate the application of the model to medical theoretical research. The model was established combined with the statistical moment principle and the normal distribution probability density function properties, then validated and illustrated by the pharmacokinetics of three ingredients in Buyanghuanwu decoction and of three data analytical method for them, and by analysis of chromatographic fingerprint for various extracts with different solubility parameter solvents dissolving the Buyanghanwu-decoction extract. The established model consists of four mainly parameters: (1) total quantum statistical moment similarity as ST, an overlapped area by two normal distribution probability density curves in conversion of the two TQSM parameters; (2) total variability as DT, a confidence limit of standard normal accumulation probability which is equal to the absolute difference value between the two normal accumulation probabilities within integration of their curve nodical; (3) total variable probability as 1-Ss, standard normal distribution probability within interval of D(T); (4) total variable probability (1-beta)alpha and (5) stable confident probability beta(1-alpha): the correct probability to make positive and negative conclusions under confident coefficient alpha. With the model, we had analyzed the TQSMS similarities of pharmacokinetics of three ingredients in Buyanghuanwu decoction and of three data analytical methods for them were at range of 0.3852-0.9875 that illuminated different pharmacokinetic behaviors of each other; and the TQSMS similarities (ST) of chromatographic fingerprint for various extracts with different solubility parameter solvents dissolving Buyanghuanwu-decoction-extract were at range of 0.6842-0.999 2 that showed different constituents with various solvent extracts. The TQSMSS can characterize the sample similarity, by which we can quantitate the correct probability with the test of power under to make positive and negative conclusions no matter the samples come from same population under confident coefficient a or not, by which we can realize an analysis at both macroscopic and microcosmic levels, as an important similar analytical method for medical theoretical research.

Mapping rice areas of South Asia using MODIS multitemporal data

NASA Astrophysics Data System (ADS)

Gumma, Murali Krishna; Nelson, Andrew; Thenkabail, Prasad S.; Singh, Amrendra N.

2011-01-01

Our goal is to map the rice areas of six South Asian countries using moderate-resolution imaging spectroradiometer (MODIS) time-series data for the time period 2000 to 2001. South Asia accounts for almost 40% of the world's harvested rice area and is also home to 74% of the population that lives on less than $2.00 a day. The population of the region is growing faster than its ability to produce rice. Thus, accurate and timely assessment of where and how rice is cultivated is important to craft food security and poverty alleviation strategies. We used a time series of eight-day, 500-m spatial resolution composite images from the MODIS sensor to produce rice maps and rice characteristics (e.g., intensity of cropping, cropping calendar) taking data for the years 2000 to 2001 and by adopting a suite of methods that include spectral matching techniques, decision trees, and ideal temporal profile data banks to rapidly identify and classify rice areas over large spatial extents. These methods are used in conjunction with ancillary spatial data sets (e.g., elevation, precipitation), national statistics, and maps, and a large volume of field-plot data. The resulting rice maps and statistics are compared against a subset of independent field-plot points and the best available subnational statistics on rice areas for the main crop growing season (kharif season). A fuzzy classification accuracy assessment for the 2000 to 2001 rice-map product, based on field-plot data, demonstrated accuracies from 67% to 100% for individual rice classes, with an overall accuracy of 80% for all classes. Most of the mixing was within rice classes. The derived physical rice area was highly correlated with the subnational statistics with R2 values of 97% at the district level and 99% at the state level for 2000 to 2001. These results suggest that the methods, approaches, algorithms, and data sets we used are ideal for rapid, accurate, and large-scale mapping of paddy rice as well as for generating their statistics over large areas.

Mapping rice areas of South Asia using MODIS multitemporal data

USGS Publications Warehouse

Gumma, M.K.; Nelson, A.; Thenkabail, P.S.; Singh, A.N.

2011-01-01

Our goal is to map the rice areas of six South Asian countries using moderate-resolution imaging spectroradiometer (MODIS) time-series data for the time period 2000 to 2001. South Asia accounts for almost 40% of the world's harvested rice area and is also home to 74% of the population that lives on less than $2.00 a day. The population of the region is growing faster than its ability to produce rice. Thus, accurate and timely assessment of where and how rice is cultivated is important to craft food security and poverty alleviation strategies. We used a time series of eight-day, 500-m spatial resolution composite images from the MODIS sensor to produce rice maps and rice characteristics (e.g., intensity of cropping, cropping calendar) taking data for the years 2000 to 2001 and by adopting a suite of methods that include spectral matching techniques, decision trees, and ideal temporal profile data banks to rapidly identify and classify rice areas over large spatial extents. These methods are used in conjunction with ancillary spatial data sets (e.g., elevation, precipitation), national statistics, and maps, and a large volume of field-plot data. The resulting rice maps and statistics are compared against a subset of independent field-plot points and the best available subnational statistics on rice areas for the main crop growing season (kharif season). A fuzzy classification accuracy assessment for the 2000 to 2001 rice-map product, based on field-plot data, demonstrated accuracies from 67% to 100% for individual rice classes, with an overall accuracy of 80% for all classes. Most of the mixing was within rice classes. The derived physical rice area was highly correlated with the subnational statistics with R2 values of 97% at the district level and 99% at the state level for 2000 to 2001. These results suggest that the methods, approaches, algorithms, and data sets we used are ideal for rapid, accurate, and large-scale mapping of paddy rice as well as for generating their statistics over large areas. ?? 2011 Society of Photo-Optical Instrumentation Engineers (SPIE).

Introducing 3D U-statistic method for separating anomaly from background in exploration geochemical data with associated software development

NASA Astrophysics Data System (ADS)

Ghannadpour, Seyyed Saeed; Hezarkhani, Ardeshir

2016-03-01

The U-statistic method is one of the most important structural methods to separate the anomaly from the background. It considers the location of samples and carries out the statistical analysis of the data without judging from a geochemical point of view and tries to separate subpopulations and determine anomalous areas. In the present study, to use U-statistic method in three-dimensional (3D) condition, U-statistic is applied on the grade of two ideal test examples, by considering sample Z values (elevation). So far, this is the first time that this method has been applied on a 3D condition. To evaluate the performance of 3D U-statistic method and in order to compare U-statistic with one non-structural method, the method of threshold assessment based on median and standard deviation (MSD method) is applied on the two example tests. Results show that the samples indicated by U-statistic method as anomalous are more regular and involve less dispersion than those indicated by the MSD method. So that, according to the location of anomalous samples, denser areas of them can be determined as promising zones. Moreover, results show that at a threshold of U = 0, the total error of misclassification for U-statistic method is much smaller than the total error of criteria of bar {x}+n× s. Finally, 3D model of two test examples for separating anomaly from background using 3D U-statistic method is provided. The source code for a software program, which was developed in the MATLAB programming language in order to perform the calculations of the 3D U-spatial statistic method, is additionally provided. This software is compatible with all the geochemical varieties and can be used in similar exploration projects.

Evolution of massive stars in very young clusters and associations

NASA Technical Reports Server (NTRS)

Stothers, R. B.

1985-01-01

Statistics concerning the stellar content of young galactic clusters and associations which show well defined main sequence turnups have been analyzed in order to derive information about stellar evolution in high-mass galaxies. The analytical approach is semiempirical and uses natural spectroscopic groups of stars on the H-R diagram together with the stars' apparent magnitudes. The new approach does not depend on absolute luminosities and requires only the most basic elements of stellar evolution theory. The following conclusions are offered on the basis of the statistical analysis: (1) O-tupe main-sequence stars evolve to a spectral type of B1 during core hydrogen burning; (2) most O-type blue stragglers are newly formed massive stars burning core hydrogen; (3) supergiants lying redward of the main-sequence turnup are burning core helium; and most Wolf-Rayet stars are burning core helium and originally had masses greater than 30-40 solar mass. The statistics of the natural spectroscopic stars in young galactic clusters and associations are given in a table.

Cognition of and Demand for Education and Teaching in Medical Statistics in China: A Systematic Review and Meta-Analysis

PubMed Central

Li, Gaoming; Yi, Dali; Wu, Xiaojiao; Liu, Xiaoyu; Zhang, Yanqi; Liu, Ling; Yi, Dong

2015-01-01

Background Although a substantial number of studies focus on the teaching and application of medical statistics in China, few studies comprehensively evaluate the recognition of and demand for medical statistics. In addition, the results of these various studies differ and are insufficiently comprehensive and systematic. Objectives This investigation aimed to evaluate the general cognition of and demand for medical statistics by undergraduates, graduates, and medical staff in China. Methods We performed a comprehensive database search related to the cognition of and demand for medical statistics from January 2007 to July 2014 and conducted a meta-analysis of non-controlled studies with sub-group analysis for undergraduates, graduates, and medical staff. Results There are substantial differences with respect to the cognition of theory in medical statistics among undergraduates (73.5%), graduates (60.7%), and medical staff (39.6%). The demand for theory in medical statistics is high among graduates (94.6%), undergraduates (86.1%), and medical staff (88.3%). Regarding specific statistical methods, the cognition of basic statistical methods is higher than of advanced statistical methods. The demand for certain advanced statistical methods, including (but not limited to) multiple analysis of variance (ANOVA), multiple linear regression, and logistic regression, is higher than that for basic statistical methods. The use rates of the Statistical Package for the Social Sciences (SPSS) software and statistical analysis software (SAS) are only 55% and 15%, respectively. Conclusion The overall statistical competence of undergraduates, graduates, and medical staff is insufficient, and their ability to practically apply their statistical knowledge is limited, which constitutes an unsatisfactory state of affairs for medical statistics education. Because the demand for skills in this area is increasing, the need to reform medical statistics education in China has become urgent. PMID:26053876

Probabilistic structural analysis methods for improving Space Shuttle engine reliability

NASA Technical Reports Server (NTRS)

Boyce, L.

1989-01-01

Probabilistic structural analysis methods are particularly useful in the design and analysis of critical structural components and systems that operate in very severe and uncertain environments. These methods have recently found application in space propulsion systems to improve the structural reliability of Space Shuttle Main Engine (SSME) components. A computer program, NESSUS, based on a deterministic finite-element program and a method of probabilistic analysis (fast probability integration) provides probabilistic structural analysis for selected SSME components. While computationally efficient, it considers both correlated and nonnormal random variables as well as an implicit functional relationship between independent and dependent variables. The program is used to determine the response of a nickel-based superalloy SSME turbopump blade. Results include blade tip displacement statistics due to the variability in blade thickness, modulus of elasticity, Poisson's ratio or density. Modulus of elasticity significantly contributed to blade tip variability while Poisson's ratio did not. Thus, a rational method for choosing parameters to be modeled as random is provided.

GOTHiC, a probabilistic model to resolve complex biases and to identify real interactions in Hi-C data.

PubMed

Mifsud, Borbala; Martincorena, Inigo; Darbo, Elodie; Sugar, Robert; Schoenfelder, Stefan; Fraser, Peter; Luscombe, Nicholas M

2017-01-01

Hi-C is one of the main methods for investigating spatial co-localisation of DNA in the nucleus. However, the raw sequencing data obtained from Hi-C experiments suffer from large biases and spurious contacts, making it difficult to identify true interactions. Existing methods use complex models to account for biases and do not provide a significance threshold for detecting interactions. Here we introduce a simple binomial probabilistic model that resolves complex biases and distinguishes between true and false interactions. The model corrects biases of known and unknown origin and yields a p-value for each interaction, providing a reliable threshold based on significance. We demonstrate this experimentally by testing the method against a random ligation dataset. Our method outperforms previous methods and provides a statistical framework for further data analysis, such as comparisons of Hi-C interactions between different conditions. GOTHiC is available as a BioConductor package (http://www.bioconductor.org/packages/release/bioc/html/GOTHiC.html).

Surveying immigrants without sampling frames - evaluating the success of alternative field methods.

PubMed

Reichel, David; Morales, Laura

2017-01-01

This paper evaluates the sampling methods of an international survey, the Immigrant Citizens Survey, which aimed at surveying immigrants from outside the European Union (EU) in 15 cities in seven EU countries. In five countries, no sample frame was available for the target population. Consequently, alternative ways to obtain a representative sample had to be found. In three countries 'location sampling' was employed, while in two countries traditional methods were used with adaptations to reach the target population. The paper assesses the main methodological challenges of carrying out a survey among a group of immigrants for whom no sampling frame exists. The samples of the survey in these five countries are compared to results of official statistics in order to assess the accuracy of the samples obtained through the different sampling methods. It can be shown that alternative sampling methods can provide meaningful results in terms of core demographic characteristics although some estimates differ to some extent from the census results.

Manchester Triage System: main flowcharts, discriminators and outcomes of a pediatric emergency care 1

PubMed Central

Amthauer, Camila; da Cunha, Maria Luzia Chollopetz

2016-01-01

ABSTRACT Objetive: to characterize the care services performed through risk rating by the Manchester Triage System, identifying demographics (age, gender), main flowcharts, discriminators and outcomes in pediatric emergency Method: cross-sectional quantitative study. Data on risk classification were obtained through a search of computerized registration data from medical records of patients treated in the pediatric emergency within one year. Descriptive statistics with absolute and relative frequencies was used for the analysis. Results: 10,921 visits were conducted in the pediatric emergency, mostly male (54.4%), aged between 29 days and two years (44.5%). There was a prevalence of the urgent risk category (43.6%). The main flowchart used in the care was worried parents (22.4%) and the most prevalent discriminator was recent event (15.3%). The hospitalization outcome occurred in 10.4% of care performed in the pediatric emergency, however 61.8% of care needed to stay under observation and / or being under the health team care in the pediatric emergency. Conclusion: worried parents was the main flowchart used and recent events the most prevalent discriminator, comprising the hospitalization outcomes and permanency in observation in the pediatric emergency before discharge from the hospital. PMID:27579934

The characteristics of hydrogeochemical zonation of groundwater in inland plain

NASA Astrophysics Data System (ADS)

Xin-yu, HOU; Li-ting, XING; Yi, YANG; Wen-jing, ZHANG; Guang-yao, CHI

2018-05-01

To find out the hydrochemical zoning of groundwaterin the inland plain, taking Jiyang plain as an example, based on mathematical statistics, ion ratio coefficient and isotopic analysis method, the characteristics of water chemical composition and its zoning at different depths of 500m were studied. The result shows: ①The groundwater flow system in the study area can be divided into local flow system, intermediate flow system and regional flow system. ②The hydrochemical type of shallow groundwater is complex. The hydrochemical types of middle confined water are mainly ClṡSO4—MgṡNa and SO4ṡCl—NaṡMg. The deep confined water is mainly HCO3. ③The TDS of shallow groundwater increases gradually along the direction of groundwater flow. ④The shallow saltwater and freshwater are alternately distributed in horizontal direction, and saltwater is distributed sporadically in the interfluve area with sporadic punctate or banded, and hydrochemical types are mainly ClṡSO4—NaṡMgṡCa. Conclusion: Groundwater in the study area is affected by complicated hydrogeochemical action, mainly in the form of filtration, cation exchange and evaporation. The inland plain area is characterized by hydrogeochemical zonation in horizontal and vertical.

Models of Pilot Behavior and Their Use to Evaluate the State of Pilot Training

NASA Astrophysics Data System (ADS)

Jirgl, Miroslav; Jalovecky, Rudolf; Bradac, Zdenek

2016-07-01

This article discusses the possibilities of obtaining new information related to human behavior, namely the changes or progressive development of pilots' abilities during training. The main assumption is that a pilot's ability can be evaluated based on a corresponding behavioral model whose parameters are estimated using mathematical identification procedures. The mean values of the identified parameters are obtained via statistical methods. These parameters are then monitored and their changes evaluated. In this context, the paper introduces and examines relevant mathematical models of human (pilot) behavior, the pilot-aircraft interaction, and an example of the mathematical analysis.

Development and Validation of Methods for Applying Pharmacokinetic Data in Risk Assessment. Volume 7. PBPK SIM

DTIC Science & Technology

1990-12-01

keys 7 Executing PBPKSIM 10 Main Menu 12 File Selection 13 Data 13 simulation 13 All 14 sTatistics 14 Change directory 14 dos Shell 15 eXit 15 Data...the PBPKSIM program are based upon the window design seen here: TITLE I MENU BAR I INFORMATION LINE I I I IMIN DISPLAY AREAI1 1 I I I I I I I STATUS...AREAI Title shows the location of the program by supplying the name of the window being exeLuted. Menu Bar displays the other windows or other

Evaluating statistical approaches to leverage large clinical datasets for uncovering therapeutic and adverse medication effects.

PubMed

Choi, Leena; Carroll, Robert J; Beck, Cole; Mosley, Jonathan D; Roden, Dan M; Denny, Joshua C; Van Driest, Sara L

2018-04-18

Phenome-wide association studies (PheWAS) have been used to discover many genotype-phenotype relationships and have the potential to identify therapeutic and adverse drug outcomes using longitudinal data within electronic health records (EHRs). However, the statistical methods for PheWAS applied to longitudinal EHR medication data have not been established. In this study, we developed methods to address two challenges faced with reuse of EHR for this purpose: confounding by indication, and low exposure and event rates. We used Monte Carlo simulation to assess propensity score (PS) methods, focusing on two of the most commonly used methods, PS matching and PS adjustment, to address confounding by indication. We also compared two logistic regression approaches (the default of Wald vs. Firth's penalized maximum likelihood, PML) to address complete separation due to sparse data with low exposure and event rates. PS adjustment resulted in greater power than propensity score matching, while controlling Type I error at 0.05. The PML method provided reasonable p-values, even in cases with complete separation, with well controlled Type I error rates. Using PS adjustment and the PML method, we identify novel latent drug effects in pediatric patients exposed to two common antibiotic drugs, ampicillin and gentamicin. R packages PheWAS and EHR are available at https://github.com/PheWAS/PheWAS and at CRAN (https://www.r-project.org/), respectively. The R script for data processing and the main analysis is available at https://github.com/choileena/EHR. leena.choi@vanderbilt.edu. Supplementary data are available at Bioinformatics online.

Spectral region optimization for Raman-based optical biopsy of inflammatory lesions.

PubMed

de Carvalho, Luis Felipe das Chagas E Silva; Bitar, Renata Andrade; Arisawa, Emília Angela Loschiavo; Brandão, Adriana Aigotti Haberbeck; Honório, Kathia Maria; Cabral, Luiz Antônio Guimarães; Martin, Airton Abrahão; Martinho, Herculano da Silva; Almeida, Janete Dias

2010-08-01

The biochemical alterations between inflammatory fibrous hyperplasia (IFH) and normal tissues of buccal mucosa were probed by using the FT-Raman spectroscopy technique. The aim was to find the minimal set of Raman bands that would furnish the best discrimination. Raman-based optical biopsy is a widely recognized potential technique for noninvasive real-time diagnosis. However, few studies had been devoted to the discrimination of very common subtle or early pathologic states as inflammatory processes that are always present on, for example, cancer lesion borders. Seventy spectra of IFH from 14 patients were compared with 30 spectra of normal tissues from six patients. The statistical analysis was performed with principal components analysis and soft independent modeling class analogy cross-validated, leave-one-out methods. Bands close to 574, 1,100, 1,250 to 1,350, and 1,500 cm(-1) (mainly amino acids and collagen bands) showed the main intragroup variations that are due to the acanthosis process in the IFH epithelium. The 1,200 (C-C aromatic/DNA), 1,350 (CH(2) bending/collagen 1), and 1,730 cm(-1) (collagen III) regions presented the main intergroup variations. This finding was interpreted as originating in an extracellular matrix-degeneration process occurring in the inflammatory tissues. The statistical analysis results indicated that the best discrimination capability (sensitivity of 95% and specificity of 100%) was found by using the 530-580 cm(-1) spectral region. The existence of this narrow spectral window enabling normal and inflammatory diagnosis also had useful implications for an in vivo dispersive Raman setup for clinical applications.

Statistical methods used in the public health literature and implications for training of public health professionals

PubMed Central

Hayat, Matthew J.; Powell, Amanda; Johnson, Tessa; Cadwell, Betsy L.

2017-01-01

Statistical literacy and knowledge is needed to read and understand the public health literature. The purpose of this study was to quantify basic and advanced statistical methods used in public health research. We randomly sampled 216 published articles from seven top tier general public health journals. Studies were reviewed by two readers and a standardized data collection form completed for each article. Data were analyzed with descriptive statistics and frequency distributions. Results were summarized for statistical methods used in the literature, including descriptive and inferential statistics, modeling, advanced statistical techniques, and statistical software used. Approximately 81.9% of articles reported an observational study design and 93.1% of articles were substantively focused. Descriptive statistics in table or graphical form were reported in more than 95% of the articles, and statistical inference reported in more than 76% of the studies reviewed. These results reveal the types of statistical methods currently used in the public health literature. Although this study did not obtain information on what should be taught, information on statistical methods being used is useful for curriculum development in graduate health sciences education, as well as making informed decisions about continuing education for public health professionals. PMID:28591190

Statistical methods used in the public health literature and implications for training of public health professionals.

PubMed

Hayat, Matthew J; Powell, Amanda; Johnson, Tessa; Cadwell, Betsy L

2017-01-01

Statistical literacy and knowledge is needed to read and understand the public health literature. The purpose of this study was to quantify basic and advanced statistical methods used in public health research. We randomly sampled 216 published articles from seven top tier general public health journals. Studies were reviewed by two readers and a standardized data collection form completed for each article. Data were analyzed with descriptive statistics and frequency distributions. Results were summarized for statistical methods used in the literature, including descriptive and inferential statistics, modeling, advanced statistical techniques, and statistical software used. Approximately 81.9% of articles reported an observational study design and 93.1% of articles were substantively focused. Descriptive statistics in table or graphical form were reported in more than 95% of the articles, and statistical inference reported in more than 76% of the studies reviewed. These results reveal the types of statistical methods currently used in the public health literature. Although this study did not obtain information on what should be taught, information on statistical methods being used is useful for curriculum development in graduate health sciences education, as well as making informed decisions about continuing education for public health professionals.

Energy Statistics : A Supplement to the Summary of National Transportation Statistics

DOT National Transportation Integrated Search

1973-09-01

This annual report is a compendium of selected time-series data describing the transportation, production, processing, and consumption of energy. The report is divided into three main sections. The first, entitled Energy Transport, contains such item...

Energy Statistics : A Supplement to the Summary of Transportation Statistics

DOT National Transportation Integrated Search

1974-08-01

This annual report is a compendium of selected time-series data describing the transportation, production, processing, and consumption of energy. The report is divided into three main sections. The first, entitled Energy Transport, contains such item...

Quality of reporting statistics in two Indian pharmacology journals

PubMed Central

Jaykaran; Yadav, Preeti

2011-01-01

Objective: To evaluate the reporting of the statistical methods in articles published in two Indian pharmacology journals. Materials and Methods: All original articles published since 2002 were downloaded from the journals’ (Indian Journal of Pharmacology (IJP) and Indian Journal of Physiology and Pharmacology (IJPP)) website. These articles were evaluated on the basis of appropriateness of descriptive statistics and inferential statistics. Descriptive statistics was evaluated on the basis of reporting of method of description and central tendencies. Inferential statistics was evaluated on the basis of fulfilling of assumption of statistical methods and appropriateness of statistical tests. Values are described as frequencies, percentage, and 95% confidence interval (CI) around the percentages. Results: Inappropriate descriptive statistics was observed in 150 (78.1%, 95% CI 71.7–83.3%) articles. Most common reason for this inappropriate descriptive statistics was use of mean ± SEM at the place of “mean (SD)” or “mean ± SD.” Most common statistical method used was one-way ANOVA (58.4%). Information regarding checking of assumption of statistical test was mentioned in only two articles. Inappropriate statistical test was observed in 61 (31.7%, 95% CI 25.6–38.6%) articles. Most common reason for inappropriate statistical test was the use of two group test for three or more groups. Conclusion: Articles published in two Indian pharmacology journals are not devoid of statistical errors. PMID:21772766

HYPE: a WFD tool for the identification of significant and sustained upward trends in groundwater time series

NASA Astrophysics Data System (ADS)

Lopez, Benjamin; Croiset, Nolwenn; Laurence, Gourcy

2014-05-01

The Water Framework Directive 2006/11/CE (WFD) on the protection of groundwater against pollution and deterioration asks Member States to identify significant and sustained upward trends in all bodies or groups of bodies of groundwater that are characterised as being at risk in accordance with Annex II to Directive 2000/60/EC. The Directive indicates that the procedure for the identification of significant and sustained upward trends must be based on a statistical method. Moreover, for significant increases of concentrations of pollutants, trend reversals are identified as being necessary. This means to be able to identify significant trend reversals. A specific tool, named HYPE, has been developed in order to help stakeholders working on groundwater trend assessment. The R encoded tool HYPE provides statistical analysis of groundwater time series. It follows several studies on the relevancy of the use of statistical tests on groundwater data series (Lopez et al., 2011) and other case studies on the thematic (Bourgine et al., 2012). It integrates the most powerful and robust statistical tests for hydrogeological applications. HYPE is linked to the French national database on groundwater data (ADES). So monitoring data gathered by the Water Agencies can be directly processed. HYPE has two main modules: - a characterisation module, which allows to visualize time series. HYPE calculates the main statistical characteristics and provides graphical representations; - a trend module, which identifies significant breaks, trends and trend reversals in time series, providing result table and graphical representation (cf figure). Additional modules are also implemented to identify regional and seasonal trends and to sample time series in a relevant way. HYPE has been used successfully in 2012 by the French Water Agencies to satisfy requirements of the WFD, concerning characterization of groundwater bodies' qualitative status and evaluation of the risk of non-achievement of good status. Bourgine B. et al. 2012, Ninth International Geostatistics Congress, Oslo, Norway June 11 - 15. Lopez B. et al. 2011, Final Report BRGM/RP-59515-FR. 166p.

The Development of Official Social Statistics in Italy with a Life Quality Approach

ERIC Educational Resources Information Center

Sabbadini, Linda Laura

2011-01-01

The article covers the main steps of official statistics in the second half of the Nineties through the illustration of the transition from economic oriented official statistics to the quality of life approach. The system of the Multipurpose Surveys introduced in 1993 to give an answer to questions at social level and to provide indicators for…

Response statistics of rotating shaft with non-linear elastic restoring forces by path integration

NASA Astrophysics Data System (ADS)

Gaidai, Oleg; Naess, Arvid; Dimentberg, Michael

2017-07-01

Extreme statistics of random vibrations is studied for a Jeffcott rotor under uniaxial white noise excitation. Restoring force is modelled as elastic non-linear; comparison is done with linearized restoring force to see the force non-linearity effect on the response statistics. While for the linear model analytical solutions and stability conditions are available, it is not generally the case for non-linear system except for some special cases. The statistics of non-linear case is studied by applying path integration (PI) method, which is based on the Markov property of the coupled dynamic system. The Jeffcott rotor response statistics can be obtained by solving the Fokker-Planck (FP) equation of the 4D dynamic system. An efficient implementation of PI algorithm is applied, namely fast Fourier transform (FFT) is used to simulate dynamic system additive noise. The latter allows significantly reduce computational time, compared to the classical PI. Excitation is modelled as Gaussian white noise, however any kind distributed white noise can be implemented with the same PI technique. Also multidirectional Markov noise can be modelled with PI in the same way as unidirectional. PI is accelerated by using Monte Carlo (MC) estimated joint probability density function (PDF) as initial input. Symmetry of dynamic system was utilized to afford higher mesh resolution. Both internal (rotating) and external damping are included in mechanical model of the rotor. The main advantage of using PI rather than MC is that PI offers high accuracy in the probability distribution tail. The latter is of critical importance for e.g. extreme value statistics, system reliability, and first passage probability.

Development of new on-line statistical program for the Korean Society for Radiation Oncology

PubMed Central

Song, Si Yeol; Ahn, Seung Do; Chung, Weon Kuu; Choi, Eun Kyung; Cho, Kwan Ho

2015-01-01

Purpose To develop new on-line statistical program for the Korean Society for Radiation Oncology (KOSRO) to collect and extract medical data in radiation oncology more efficiently. Materials and Methods The statistical program is a web-based program. The directory was placed in a sub-folder of the homepage of KOSRO and its web address is http://www.kosro.or.kr/asda. The operating systems server is Linux and the webserver is the Apache HTTP server. For database (DB) server, MySQL is adopted and dedicated scripting language is the PHP. Each ID and password are controlled independently and all screen pages for data input or analysis are made to be friendly to users. Scroll-down menu is actively used for the convenience of user and the consistence of data analysis. Results Year of data is one of top categories and main topics include human resource, equipment, clinical statistics, specialized treatment and research achievement. Each topic or category has several subcategorized topics. Real-time on-line report of analysis is produced immediately after entering each data and the administrator is able to monitor status of data input of each hospital. Backup of data as spread sheets can be accessed by the administrator and be used for academic works by any members of the KOSRO. Conclusion The new on-line statistical program was developed to collect data from nationwide departments of radiation oncology. Intuitive screen and consistent input structure are expected to promote entering data of member hospitals and annual statistics should be a cornerstone of advance in radiation oncology. PMID:26157684

Determination of rate of customer focus in educational programs at Isfahan University of Medical Sciences(1) based on students' viewpoints.

PubMed

Shams, Assadollah; Yarmohammadian, Mohammad Hosein; Abbarik, Hadi Hayati

2012-01-01

Today, the challenges of quality improvement and customer focus as well as systems development are important and inevitable matters in higher education institutes. There are some highly competitive challenges among educational institutes, including accountability to social needs, increasing costs of education, diversity in educational methods and centers and their consequent increasing competition, and the need for adaptation of new information and knowledge to focus on students as the main customers. Hence, the purpose of this study was to determine the rate of costumer focus based on Isfahan University of Medical Sciences students' viewpoints and to suggest solutions to improve this rate. This was a cross-sectional study carried out in 2011. The statistical population included all the students of seven faculties of Isfahan University of Medical Sciences. According to statistical formulae, the sample size consisted of 384 subjects. Data collection tools included researcher-made questionnaire whose reliability was found to be 87% by Cronbach's alpha coefficient. Finally, using the SPSS statistical software and statistical methods of independent t-test and one-way analysis of variance (ANOVA), Likert scale based data were analyzed. The mean of overall score for customer focus (student-centered) of Isfahan University of Medical Sciences was 46.54. Finally, there was a relation between the mean of overall score for customer focus and gender, educational levels, and students' faculties. Researcher suggest more investigation between Medical University and others. It is a difference between medical sciences universities and others regarding the customer focus area, since students' gender must be considered as an effective factor in giving healthcare services quality. In order to improve the customer focus, it is essential to take facilities, field of study, faculties, and syllabus into consideration.

Rydberg Atoms in Strong Fields: a Testing Ground for Quantum Chaos.

NASA Astrophysics Data System (ADS)

Courtney, Michael

1995-01-01

Rydberg atoms in strong static electric and magnetic fields provide experimentally accessible systems for studying the connections between classical chaos and quantum mechanics in the semiclassical limit. This experimental accessibility has motivated the development of reliable quantum mechanical solutions. This thesis uses both experimental and computed quantum spectra to test the central approaches to quantum chaos. These central approaches consist mainly of developing methods to compute the spectra of quantum systems in non -perturbative regimes, correlating statistical descriptions of eigenvalues with the classical behavior of the same Hamiltonian, and the development of semiclassical methods such as periodic-orbit theory. Particular emphasis is given to identifying the spectral signature of recurrences --quantum wave packets which follow classical orbits. The new findings include: the breakdown of the connection between energy-level statistics and classical chaos in odd-parity diamagnetic lithium, the discovery of the signature of very long period orbits in atomic spectra, quantitative evidence for the scattering of recurrences by the alkali -metal core, quantitative description of the behavior of recurrences near bifurcations, and a semiclassical interpretation of the evolution of continuum Stark spectra. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.).