Statistical methods for convergence detection of multi-objective evolutionary algorithms.

PubMed

Trautmann, H; Wagner, T; Naujoks, B; Preuss, M; Mehnen, J

2009-01-01

In this paper, two approaches for estimating the generation in which a multi-objective evolutionary algorithm (MOEA) shows statistically significant signs of convergence are introduced. A set-based perspective is taken where convergence is measured by performance indicators. The proposed techniques fulfill the requirements of proper statistical assessment on the one hand and efficient optimisation for real-world problems on the other hand. The first approach accounts for the stochastic nature of the MOEA by repeating the optimisation runs for increasing generation numbers and analysing the performance indicators using statistical tools. This technique results in a very robust offline procedure. Moreover, an online convergence detection method is introduced as well. This method automatically stops the MOEA when either the variance of the performance indicators falls below a specified threshold or a stagnation of their overall trend is detected. Both methods are analysed and compared for two MOEA and on different classes of benchmark functions. It is shown that the methods successfully operate on all stated problems needing less function evaluations while preserving good approximation quality at the same time.

[Adequate application of quantitative and qualitative statistic analytic methods in acupuncture clinical trials].

PubMed

Tan, Ming T; Liu, Jian-ping; Lao, Lixing

2012-08-01

Recently, proper use of the statistical methods in traditional Chinese medicine (TCM) randomized controlled trials (RCTs) has received increased attention. Statistical inference based on hypothesis testing is the foundation of clinical trials and evidence-based medicine. In this article, the authors described the methodological differences between literature published in Chinese and Western journals in the design and analysis of acupuncture RCTs and the application of basic statistical principles. In China, qualitative analysis method has been widely used in acupuncture and TCM clinical trials, while the between-group quantitative analysis methods on clinical symptom scores are commonly used in the West. The evidence for and against these analytical differences were discussed based on the data of RCTs assessing acupuncture for pain relief. The authors concluded that although both methods have their unique advantages, quantitative analysis should be used as the primary analysis while qualitative analysis can be a secondary criterion for analysis. The purpose of this paper is to inspire further discussion of such special issues in clinical research design and thus contribute to the increased scientific rigor of TCM research.

Quantifying Safety Margin Using the Risk-Informed Safety Margin Characterization (RISMC)

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

Grabaskas, David; Bucknor, Matthew; Brunett, Acacia

2015-04-26

The Risk-Informed Safety Margin Characterization (RISMC), developed by Idaho National Laboratory as part of the Light-Water Reactor Sustainability Project, utilizes a probabilistic safety margin comparison between a load and capacity distribution, rather than a deterministic comparison between two values, as is usually done in best-estimate plus uncertainty analyses. The goal is to determine the failure probability, or in other words, the probability of the system load equaling or exceeding the system capacity. While this method has been used in pilot studies, there has been little work conducted investigating the statistical significance of the resulting failure probability. In particular, it ismore » difficult to determine how many simulations are necessary to properly characterize the failure probability. This work uses classical (frequentist) statistics and confidence intervals to examine the impact in statistical accuracy when the number of simulations is varied. Two methods are proposed to establish confidence intervals related to the failure probability established using a RISMC analysis. The confidence interval provides information about the statistical accuracy of the method utilized to explore the uncertainty space, and offers a quantitative method to gauge the increase in statistical accuracy due to performing additional simulations.« less

A Third Moment Adjusted Test Statistic for Small Sample Factor Analysis.

PubMed

Lin, Johnny; Bentler, Peter M

2012-01-01

Goodness of fit testing in factor analysis is based on the assumption that the test statistic is asymptotically chi-square; but this property may not hold in small samples even when the factors and errors are normally distributed in the population. Robust methods such as Browne's asymptotically distribution-free method and Satorra Bentler's mean scaling statistic were developed under the presumption of non-normality in the factors and errors. This paper finds new application to the case where factors and errors are normally distributed in the population but the skewness of the obtained test statistic is still high due to sampling error in the observed indicators. An extension of Satorra Bentler's statistic is proposed that not only scales the mean but also adjusts the degrees of freedom based on the skewness of the obtained test statistic in order to improve its robustness under small samples. A simple simulation study shows that this third moment adjusted statistic asymptotically performs on par with previously proposed methods, and at a very small sample size offers superior Type I error rates under a properly specified model. Data from Mardia, Kent and Bibby's study of students tested for their ability in five content areas that were either open or closed book were used to illustrate the real-world performance of this statistic.

Multiple point statistical simulation using uncertain (soft) conditional data

NASA Astrophysics Data System (ADS)

Hansen, Thomas Mejer; Vu, Le Thanh; Mosegaard, Klaus; Cordua, Knud Skou

2018-05-01

Geostatistical simulation methods have been used to quantify spatial variability of reservoir models since the 80s. In the last two decades, state of the art simulation methods have changed from being based on covariance-based 2-point statistics to multiple-point statistics (MPS), that allow simulation of more realistic Earth-structures. In addition, increasing amounts of geo-information (geophysical, geological, etc.) from multiple sources are being collected. This pose the problem of integration of these different sources of information, such that decisions related to reservoir models can be taken on an as informed base as possible. In principle, though difficult in practice, this can be achieved using computationally expensive Monte Carlo methods. Here we investigate the use of sequential simulation based MPS simulation methods conditional to uncertain (soft) data, as a computational efficient alternative. First, it is demonstrated that current implementations of sequential simulation based on MPS (e.g. SNESIM, ENESIM and Direct Sampling) do not account properly for uncertain conditional information, due to a combination of using only co-located information, and a random simulation path. Then, we suggest two approaches that better account for the available uncertain information. The first make use of a preferential simulation path, where more informed model parameters are visited preferentially to less informed ones. The second approach involves using non co-located uncertain information. For different types of available data, these approaches are demonstrated to produce simulation results similar to those obtained by the general Monte Carlo based approach. These methods allow MPS simulation to condition properly to uncertain (soft) data, and hence provides a computationally attractive approach for integration of information about a reservoir model.

Secular Extragalactic Parallax and Geometric Distances with Gaia Proper Motions

NASA Astrophysics Data System (ADS)

Paine, Jennie; Darling, Jeremiah K.

2018-06-01

The motion of the Solar System with respect to the cosmic microwave background (CMB) rest frame creates a well measured dipole in the CMB, which corresponds to a linear solar velocity of about 78 AU/yr. This motion causes relatively nearby extragalactic objects to appear to move compared to more distant objects, an effect that can be measured in the proper motions of nearby galaxies. An object at 1 Mpc and perpendicular to the CMB apex will exhibit a secular parallax, observed as a proper motion, of 78 µas/yr. The relatively large peculiar motions of galaxies make the detection of secular parallax challenging for individual objects. Instead, a statistical parallax measurement can be made for a sample of objects with proper motions, where the global parallax signal is modeled as an E-mode dipole that diminishes linearly with distance. We present preliminary results of applying this model to a sample of nearby galaxies with Gaia proper motions to detect the statistical secular parallax signal. The statistical measurement can be used to calibrate the canonical cosmological “distance ladder.”

Statistical limitations in functional neuroimaging. I. Non-inferential methods and statistical models.

PubMed Central

Petersson, K M; Nichols, T E; Poline, J B; Holmes, A P

1999-01-01

Functional neuroimaging (FNI) provides experimental access to the intact living brain making it possible to study higher cognitive functions in humans. In this review and in a companion paper in this issue, we discuss some common methods used to analyse FNI data. The emphasis in both papers is on assumptions and limitations of the methods reviewed. There are several methods available to analyse FNI data indicating that none is optimal for all purposes. In order to make optimal use of the methods available it is important to know the limits of applicability. For the interpretation of FNI results it is also important to take into account the assumptions, approximations and inherent limitations of the methods used. This paper gives a brief overview over some non-inferential descriptive methods and common statistical models used in FNI. Issues relating to the complex problem of model selection are discussed. In general, proper model selection is a necessary prerequisite for the validity of the subsequent statistical inference. The non-inferential section describes methods that, combined with inspection of parameter estimates and other simple measures, can aid in the process of model selection and verification of assumptions. The section on statistical models covers approaches to global normalization and some aspects of univariate, multivariate, and Bayesian models. Finally, approaches to functional connectivity and effective connectivity are discussed. In the companion paper we review issues related to signal detection and statistical inference. PMID:10466149

An analytic technique for statistically modeling random atomic clock errors in estimation

NASA Technical Reports Server (NTRS)

Fell, P. J.

1981-01-01

Minimum variance estimation requires that the statistics of random observation errors be modeled properly. If measurements are derived through the use of atomic frequency standards, then one source of error affecting the observable is random fluctuation in frequency. This is the case, for example, with range and integrated Doppler measurements from satellites of the Global Positioning and baseline determination for geodynamic applications. An analytic method is presented which approximates the statistics of this random process. The procedure starts with a model of the Allan variance for a particular oscillator and develops the statistics of range and integrated Doppler measurements. A series of five first order Markov processes is used to approximate the power spectral density obtained from the Allan variance.

Development of Boundary Condition Independent Reduced Order Thermal Models using Proper Orthogonal Decomposition

NASA Astrophysics Data System (ADS)

Raghupathy, Arun; Ghia, Karman; Ghia, Urmila

2008-11-01

Compact Thermal Models (CTM) to represent IC packages has been traditionally developed using the DELPHI-based (DEvelopment of Libraries of PHysical models for an Integrated design) methodology. The drawbacks of this method are presented, and an alternative method is proposed. A reduced-order model that provides the complete thermal information accurately with less computational resources can be effectively used in system level simulations. Proper Orthogonal Decomposition (POD), a statistical method, can be used to reduce the order of the degree of freedom or variables of the computations for such a problem. POD along with the Galerkin projection allows us to create reduced-order models that reproduce the characteristics of the system with a considerable reduction in computational resources while maintaining a high level of accuracy. The goal of this work is to show that this method can be applied to obtain a boundary condition independent reduced-order thermal model for complex components. The methodology is applied to the 1D transient heat equation.

On state-of-charge determination for lithium-ion batteries

NASA Astrophysics Data System (ADS)

Li, Zhe; Huang, Jun; Liaw, Bor Yann; Zhang, Jianbo

2017-04-01

Accurate estimation of state-of-charge (SOC) of a battery through its life remains challenging in battery research. Although improved precisions continue to be reported at times, almost all are based on regression methods empirically, while the accuracy is often not properly addressed. Here, a comprehensive review is set to address such issues, from fundamental principles that are supposed to define SOC to methodologies to estimate SOC for practical use. It covers topics from calibration, regression (including modeling methods) to validation in terms of precision and accuracy. At the end, we intend to answer the following questions: 1) can SOC estimation be self-adaptive without bias? 2) Why Ah-counting is a necessity in almost all battery-model-assisted regression methods? 3) How to establish a consistent framework of coupling in multi-physics battery models? 4) To assess the accuracy in SOC estimation, statistical methods should be employed to analyze factors that contribute to the uncertainty. We hope, through this proper discussion of the principles, accurate SOC estimation can be widely achieved.

Generalized linear models and point count data: statistical considerations for the design and analysis of monitoring studies

Treesearch

Nathaniel E. Seavy; Suhel Quader; John D. Alexander; C. John Ralph

2005-01-01

The success of avian monitoring programs to effectively guide management decisions requires that studies be efficiently designed and data be properly analyzed. A complicating factor is that point count surveys often generate data with non-normal distributional properties. In this paper we review methods of dealing with deviations from normal assumptions, and we focus...

Statistical learning and selective inference.

PubMed

Taylor, Jonathan; Tibshirani, Robert J

2015-06-23

We describe the problem of "selective inference." This addresses the following challenge: Having mined a set of data to find potential associations, how do we properly assess the strength of these associations? The fact that we have "cherry-picked"--searched for the strongest associations--means that we must set a higher bar for declaring significant the associations that we see. This challenge becomes more important in the era of big data and complex statistical modeling. The cherry tree (dataset) can be very large and the tools for cherry picking (statistical learning methods) are now very sophisticated. We describe some recent new developments in selective inference and illustrate their use in forward stepwise regression, the lasso, and principal components analysis.

[Prevalence of thyroid function in pregnant and lactating women in areas with different iodine levels of Shanxi province].

PubMed

Ren, Y T; Jia, Q Z; Zhang, X D; Guo, B S; Zhang, F F; Cheng, X T; Wang, Y P

2018-05-10

Objective: To investigate the effects of high iodine intake on thyroid function in pregnant and lactating women. Methods: A cross sectional epidemiological study was conducted among 130 pregnant women and 220 lactating women aged 19-40 years in areas with high environment iodine level (>300 μg/L) or proper environment iodine level (50-100 μg/L) in Shanxi in 2014. The general information, urine samples and blood samples of the women surveyed and water samples were collected. The water and urine iodine levels were detected with arsenic and cerium catalysis spectrophotometric method, the blood TSH level was detected with electrochemiluminescence immunoassay, and thyroid stimulating hormone (FT(4)), antithyroid peroxidase autoantibody (TPOAb) and anti-thyroglobulin antibodies (TGAb) were detected with chemiluminescence immunoassay. Results: The median urine iodine levels of the four groups were 221.9, 282.5, 814.1 and 818.6 μg/L, respectively. The median serum FT(4) of lactating women in high iodine area and proper iodine area were 12.96 and 13.22 pmol/L, and the median serum TSH was 2.45 and 2.17 mIU/L, respectively. The median serum FT(4) of pregnant women in high iodine area and proper iodine area were 14.66 and 16.16 pmol/L, and the median serum TSH was 2.13 and 1.82 mIU/L, respectively. The serum FT(4) levels were lower and the abnormal rates of serum TSH were higher in lactating women than in pregnant women in both high iodine area and proper iodine area, the difference was statistically significant (FT(4): Z =-6.677, -4.041, P <0.01; TSH: Z =8.797, 8.910, P <0.01). In high iodine area, the abnormal rate of serum FT(4) in lactating women was higher than that in pregnant women, the difference was statistically significant ( Z =7.338, P =0.007). The serum FT(4) level of lactating women in high iodine area was lower than that in proper iodine area, the difference was statistically significant ( Z =-4.687, P =0.000). In high iodine area, the median serum FT(4) in early pregnancy, mid-pregnancy and late pregnancy was 16.26, 14.22 and 14.80 pmol/L, respectively, and the median serum TSH was 1.74, 1.91 and 2.38 mIU/L, respectively. In high iodine area, the serum FT(4) level in early pregnancy was higher than that in mid-pregnancy and late pregnancy, and the serum TSH level was lower than that in mid-pregnancy and late pregnancy, the difference was statistically significant (FT(4): Z =-2.174, -2.238, P <0.05; TSH: Z =-2.985, -1.978, P <0.05). There were no significant differences in the positive rates of serum thyroid autoantibodies among the four groups of women and women in different periods of pregnancy ( P >0.05). The morbidity rates of subclinical hyperthyroidism in pregnant women and lactating women in high iodine area were obviously higher than those in proper iodine areas, the difference was statistically significant ( χ (2)=5.363, 5.007, P <0.05). Conclusions: Excessive iodine intake might increase the risk of subclinical hypothyroidism in pregnant women and lactating women. It is suggested to strengthen the iodine nutrition and thyroid function monitoring in women, pregnant women and lactating women in areas with high environmental iodine.

A Third Moment Adjusted Test Statistic for Small Sample Factor Analysis

PubMed Central

Lin, Johnny; Bentler, Peter M.

2012-01-01

Goodness of fit testing in factor analysis is based on the assumption that the test statistic is asymptotically chi-square; but this property may not hold in small samples even when the factors and errors are normally distributed in the population. Robust methods such as Browne’s asymptotically distribution-free method and Satorra Bentler’s mean scaling statistic were developed under the presumption of non-normality in the factors and errors. This paper finds new application to the case where factors and errors are normally distributed in the population but the skewness of the obtained test statistic is still high due to sampling error in the observed indicators. An extension of Satorra Bentler’s statistic is proposed that not only scales the mean but also adjusts the degrees of freedom based on the skewness of the obtained test statistic in order to improve its robustness under small samples. A simple simulation study shows that this third moment adjusted statistic asymptotically performs on par with previously proposed methods, and at a very small sample size offers superior Type I error rates under a properly specified model. Data from Mardia, Kent and Bibby’s study of students tested for their ability in five content areas that were either open or closed book were used to illustrate the real-world performance of this statistic. PMID:23144511

A critical look at prospective surveillance using a scan statistic.

PubMed

Correa, Thais R; Assunção, Renato M; Costa, Marcelo A

2015-03-30

The scan statistic is a very popular surveillance technique for purely spatial, purely temporal, and spatial-temporal disease data. It was extended to the prospective surveillance case, and it has been applied quite extensively in this situation. When the usual signal rules, as those implemented in SaTScan(TM) (Boston, MA, USA) software, are used, we show that the scan statistic method is not appropriate for the prospective case. The reason is that it does not adjust properly for the sequential and repeated tests carried out during the surveillance. We demonstrate that the nominal significance level α is not meaningful and there is no relationship between α and the recurrence interval or the average run length (ARL). In some cases, the ARL may be equal to ∞, which makes the method ineffective. This lack of control of the type-I error probability and of the ARL leads us to strongly oppose the use of the scan statistic with the usual signal rules in the prospective context. Copyright © 2014 John Wiley & Sons, Ltd.

Menzerath-Altmann Law: Statistical Mechanical Interpretation as Applied to a Linguistic Organization

NASA Astrophysics Data System (ADS)

Eroglu, Sertac

2014-10-01

The distribution behavior described by the empirical Menzerath-Altmann law is frequently encountered during the self-organization of linguistic and non-linguistic natural organizations at various structural levels. This study presents a statistical mechanical derivation of the law based on the analogy between the classical particles of a statistical mechanical organization and the distinct words of a textual organization. The derived model, a transformed (generalized) form of the Menzerath-Altmann model, was termed as the statistical mechanical Menzerath-Altmann model. The derived model allows interpreting the model parameters in terms of physical concepts. We also propose that many organizations presenting the Menzerath-Altmann law behavior, whether linguistic or not, can be methodically examined by the transformed distribution model through the properly defined structure-dependent parameter and the energy associated states.

Redshift data and statistical inference

NASA Technical Reports Server (NTRS)

Newman, William I.; Haynes, Martha P.; Terzian, Yervant

1994-01-01

Frequency histograms and the 'power spectrum analysis' (PSA) method, the latter developed by Yu & Peebles (1969), have been widely employed as techniques for establishing the existence of periodicities. We provide a formal analysis of these two classes of methods, including controlled numerical experiments, to better understand their proper use and application. In particular, we note that typical published applications of frequency histograms commonly employ far greater numbers of class intervals or bins than is advisable by statistical theory sometimes giving rise to the appearance of spurious patterns. The PSA method generates a sequence of random numbers from observational data which, it is claimed, is exponentially distributed with unit mean and variance, essentially independent of the distribution of the original data. We show that the derived random processes is nonstationary and produces a small but systematic bias in the usual estimate of the mean and variance. Although the derived variable may be reasonably described by an exponential distribution, the tail of the distribution is far removed from that of an exponential, thereby rendering statistical inference and confidence testing based on the tail of the distribution completely unreliable. Finally, we examine a number of astronomical examples wherein these methods have been used giving rise to widespread acceptance of statistically unconfirmed conclusions.

Reservoir property grids improve with geostatistics

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

Vogt, J.

1993-09-01

Visualization software, reservoir simulators and many other E and P software applications need reservoir property grids as input. Using geostatistics, as compared to other gridding methods, to produce these grids leads to the best output from the software programs. For the purpose stated herein, geostatistics is simply two types of gridding methods. Mathematically, these methods are based on minimizing or duplicating certain statistical properties of the input data. One geostatical method, called kriging, is used when the highest possible point-by-point accuracy is desired. The other method, called conditional simulation, is used when one wants statistics and texture of the resultingmore » grid to be the same as for the input data. In the following discussion, each method is explained, compared to other gridding methods, and illustrated through example applications. Proper use of geostatistical data in flow simulations, use of geostatistical data for history matching, and situations where geostatistics has no significant advantage over other methods, also will be covered.« less

The application of the statistical classifying models for signal evaluation of the gas sensors analyzing mold contamination of the building materials

NASA Astrophysics Data System (ADS)

Majerek, Dariusz; Guz, Łukasz; Suchorab, Zbigniew; Łagód, Grzegorz; Sobczuk, Henryk

2017-07-01

Mold that develops on moistened building barriers is a major cause of the Sick Building Syndrome (SBS). Fungal contamination is normally evaluated using standard biological methods which are time-consuming and require a lot of manual labor. Fungi emit Volatile Organic Compounds (VOC) that can be detected in the indoor air using several techniques of detection e.g. chromatography. VOCs can be also detected using gas sensors arrays. All array sensors generate particular voltage signals that ought to be analyzed using properly selected statistical methods of interpretation. This work is focused on the attempt to apply statistical classifying models in evaluation of signals from gas sensors matrix to analyze the air sampled from the headspace of various types of the building materials at different level of contamination but also clean reference materials.

External model validation of binary clinical risk prediction models in cardiovascular and thoracic surgery.

PubMed

Hickey, Graeme L; Blackstone, Eugene H

2016-08-01

Clinical risk-prediction models serve an important role in healthcare. They are used for clinical decision-making and measuring the performance of healthcare providers. To establish confidence in a model, external model validation is imperative. When designing such an external model validation study, thought must be given to patient selection, risk factor and outcome definitions, missing data, and the transparent reporting of the analysis. In addition, there are a number of statistical methods available for external model validation. Execution of a rigorous external validation study rests in proper study design, application of suitable statistical methods, and transparent reporting. Copyright © 2016 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Orbital State Uncertainty Realism

NASA Astrophysics Data System (ADS)

Horwood, J.; Poore, A. B.

2012-09-01

Fundamental to the success of the space situational awareness (SSA) mission is the rigorous inclusion of uncertainty in the space surveillance network. The *proper characterization of uncertainty* in the orbital state of a space object is a common requirement to many SSA functions including tracking and data association, resolution of uncorrelated tracks (UCTs), conjunction analysis and probability of collision, sensor resource management, and anomaly detection. While tracking environments, such as air and missile defense, make extensive use of Gaussian and local linearity assumptions within algorithms for uncertainty management, space surveillance is inherently different due to long time gaps between updates, high misdetection rates, nonlinear and non-conservative dynamics, and non-Gaussian phenomena. The latter implies that "covariance realism" is not always sufficient. SSA also requires "uncertainty realism"; the proper characterization of both the state and covariance and all non-zero higher-order cumulants. In other words, a proper characterization of a space object's full state *probability density function (PDF)* is required. In order to provide a more statistically rigorous treatment of uncertainty in the space surveillance tracking environment and to better support the aforementioned SSA functions, a new class of multivariate PDFs are formulated which more accurately characterize the uncertainty of a space object's state or orbit. The new distribution contains a parameter set controlling the higher-order cumulants which gives the level sets a distinctive "banana" or "boomerang" shape and degenerates to a Gaussian in a suitable limit. Using the new class of PDFs within the general Bayesian nonlinear filter, the resulting filter prediction step (i.e., uncertainty propagation) is shown to have the *same computational cost as the traditional unscented Kalman filter* with the former able to maintain a proper characterization of the uncertainty for up to *ten times as long* as the latter. The filter correction step also furnishes a statistically rigorous *prediction error* which appears in the likelihood ratios for scoring the association of one report or observation to another. Thus, the new filter can be used to support multi-target tracking within a general multiple hypothesis tracking framework. Additionally, the new distribution admits a distance metric which extends the classical Mahalanobis distance (chi^2 statistic). This metric provides a test for statistical significance and facilitates single-frame data association methods with the potential to easily extend the covariance-based track association algorithm of Hill, Sabol, and Alfriend. The filtering, data fusion, and association methods using the new class of orbital state PDFs are shown to be mathematically tractable and operationally viable.

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)

Study on probability distributions for evolution in modified extremal optimization

NASA Astrophysics Data System (ADS)

Zeng, Guo-Qiang; Lu, Yong-Zai; Mao, Wei-Jie; Chu, Jian

2010-05-01

It is widely believed that the power-law is a proper probability distribution being effectively applied for evolution in τ-EO (extremal optimization), a general-purpose stochastic local-search approach inspired by self-organized criticality, and its applications in some NP-hard problems, e.g., graph partitioning, graph coloring, spin glass, etc. In this study, we discover that the exponential distributions or hybrid ones (e.g., power-laws with exponential cutoff) being popularly used in the research of network sciences may replace the original power-laws in a modified τ-EO method called self-organized algorithm (SOA), and provide better performances than other statistical physics oriented methods, such as simulated annealing, τ-EO and SOA etc., from the experimental results on random Euclidean traveling salesman problems (TSP) and non-uniform instances. From the perspective of optimization, our results appear to demonstrate that the power-law is not the only proper probability distribution for evolution in EO-similar methods at least for TSP, the exponential and hybrid distributions may be other choices.

Phase locking route behind complex periodic windows in a forced oscillator

NASA Astrophysics Data System (ADS)

Jan, Hengtai; Tsai, Kuo-Ting; Kuo, Li-wei

2013-09-01

Chaotic systems have complex reactions against an external driving force; even in cases with low-dimension oscillators, the routes to synchronization are diverse. We proposed a stroboscope-based method for analyzing driven chaotic systems in their phase space. According to two statistic quantities generated from time series, we could realize the system state and the driving behavior simultaneously. We demonstrated our method in a driven bi-stable system, which showed complex period windows under a proper driving force. With increasing periodic driving force, a route from interior periodic oscillation to phase synchronization through the chaos state could be found. Periodic windows could also be identified and the circumstances under which they occurred distinguished. Statistical results were supported by conditional Lyapunov exponent analysis to show the power in analyzing the unknown time series.

Truly random number generation: an example

NASA Astrophysics Data System (ADS)

Frauchiger, Daniela; Renner, Renato

2013-10-01

Randomness is crucial for a variety of applications, ranging from gambling to computer simulations, and from cryptography to statistics. However, many of the currently used methods for generating randomness do not meet the criteria that are necessary for these applications to work properly and safely. A common problem is that a sequence of numbers may look random but nevertheless not be truly random. In fact, the sequence may pass all standard statistical tests and yet be perfectly predictable. This renders it useless for many applications. For example, in cryptography, the predictability of a "andomly" chosen password is obviously undesirable. Here, we review a recently developed approach to generating true | and hence unpredictable | randomness.

Variability aware compact model characterization for statistical circuit design optimization

NASA Astrophysics Data System (ADS)

Qiao, Ying; Qian, Kun; Spanos, Costas J.

2012-03-01

Variability modeling at the compact transistor model level can enable statistically optimized designs in view of limitations imposed by the fabrication technology. In this work we propose an efficient variabilityaware compact model characterization methodology based on the linear propagation of variance. Hierarchical spatial variability patterns of selected compact model parameters are directly calculated from transistor array test structures. This methodology has been implemented and tested using transistor I-V measurements and the EKV-EPFL compact model. Calculation results compare well to full-wafer direct model parameter extractions. Further studies are done on the proper selection of both compact model parameters and electrical measurement metrics used in the method.

A method for determining the radius of an open cluster from stellar proper motions

NASA Astrophysics Data System (ADS)

Sánchez, Néstor; Alfaro, Emilio J.; López-Martínez, Fátima

2018-04-01

We propose a method for calculating the radius of an open cluster in an objective way from an astrometric catalogue containing, at least, positions and proper motions. It uses the minimum spanning tree in the proper motion space to discriminate cluster stars from field stars and it quantifies the strength of the cluster-field separation by means of a statistical parameter defined for the first time in this paper. This is done for a range of different sampling radii from where the cluster radius is obtained as the size at which the best cluster-field separation is achieved. The novelty of this strategy is that the cluster radius is obtained independently of how its stars are spatially distributed. We test the reliability and robustness of the method with both simulated and real data from a well-studied open cluster (NGC 188), and apply it to UCAC4 data for five other open clusters with different catalogued radius values. NGC 188, NGC 1647, NGC 6603, and Ruprecht 155 yielded unambiguous radius values of 15.2 ± 1.8, 29.4 ± 3.4, 4.2 ± 1.7, and 7.0 ± 0.3 arcmin, respectively. ASCC 19 and Collinder 471 showed more than one possible solution, but it is not possible to know whether this is due to the involved uncertainties or due to the presence of complex patterns in their proper motion distributions, something that could be inherent to the physical object or due to the way in which the catalogue was sampled.

Statistical Methods for Generalized Linear Models with Covariates Subject to Detection Limits.

PubMed

Bernhardt, Paul W; Wang, Huixia J; Zhang, Daowen

2015-05-01

Censored observations are a common occurrence in biomedical data sets. Although a large amount of research has been devoted to estimation and inference for data with censored responses, very little research has focused on proper statistical procedures when predictors are censored. In this paper, we consider statistical methods for dealing with multiple predictors subject to detection limits within the context of generalized linear models. We investigate and adapt several conventional methods and develop a new multiple imputation approach for analyzing data sets with predictors censored due to detection limits. We establish the consistency and asymptotic normality of the proposed multiple imputation estimator and suggest a computationally simple and consistent variance estimator. We also demonstrate that the conditional mean imputation method often leads to inconsistent estimates in generalized linear models, while several other methods are either computationally intensive or lead to parameter estimates that are biased or more variable compared to the proposed multiple imputation estimator. In an extensive simulation study, we assess the bias and variability of different approaches within the context of a logistic regression model and compare variance estimation methods for the proposed multiple imputation estimator. Lastly, we apply several methods to analyze the data set from a recently-conducted GenIMS study.

75 FR 37839 - Proposed Collection, Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-30

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Evaluating mediation and moderation effects in school psychology: A presentation of methods and review of current practice

PubMed Central

Fairchild, Amanda J.; McQuillin, Samuel D.

2017-01-01

Third variable effects elucidate the relation between two other variables, and can describe why they are related or under what conditions they are related. This article demonstrates methods to analyze two third-variable effects: moderation and mediation. The utility of examining moderation and mediation effects in school psychology is described and current use of the analyses in applied school psychology research is reviewed and evaluated. Proper statistical methods to test the effects are presented, and different effect size measures for the models are provided. Extensions of the basic moderator and mediator models are also described. PMID:20006988

Evaluating mediation and moderation effects in school psychology: a presentation of methods and review of current practice.

PubMed

Fairchild, Amanda J; McQuillin, Samuel D

2010-02-01

Third variable effects elucidate the relation between two other variables, and can describe why they are related or under what conditions they are related. This article demonstrates methods to analyze two third-variable effects: moderation and mediation. The utility of examining moderation and mediation effects in school psychology is described and current use of the analyses in applied school psychology research is reviewed and evaluated. Proper statistical methods to test the effects are presented, and different effect size measures for the models are provided. Extensions of the basic moderator and mediator models are also described.

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

Standard deviation and standard error of the mean.

PubMed

Lee, Dong Kyu; In, Junyong; Lee, Sangseok

2015-06-01

In most clinical and experimental studies, the standard deviation (SD) and the estimated standard error of the mean (SEM) are used to present the characteristics of sample data and to explain statistical analysis results. However, some authors occasionally muddle the distinctive usage between the SD and SEM in medical literature. Because the process of calculating the SD and SEM includes different statistical inferences, each of them has its own meaning. SD is the dispersion of data in a normal distribution. In other words, SD indicates how accurately the mean represents sample data. However the meaning of SEM includes statistical inference based on the sampling distribution. SEM is the SD of the theoretical distribution of the sample means (the sampling distribution). While either SD or SEM can be applied to describe data and statistical results, one should be aware of reasonable methods with which to use SD and SEM. We aim to elucidate the distinctions between SD and SEM and to provide proper usage guidelines for both, which summarize data and describe statistical results.

Standard deviation and standard error of the mean

PubMed Central

In, Junyong; Lee, Sangseok

2015-01-01

In most clinical and experimental studies, the standard deviation (SD) and the estimated standard error of the mean (SEM) are used to present the characteristics of sample data and to explain statistical analysis results. However, some authors occasionally muddle the distinctive usage between the SD and SEM in medical literature. Because the process of calculating the SD and SEM includes different statistical inferences, each of them has its own meaning. SD is the dispersion of data in a normal distribution. In other words, SD indicates how accurately the mean represents sample data. However the meaning of SEM includes statistical inference based on the sampling distribution. SEM is the SD of the theoretical distribution of the sample means (the sampling distribution). While either SD or SEM can be applied to describe data and statistical results, one should be aware of reasonable methods with which to use SD and SEM. We aim to elucidate the distinctions between SD and SEM and to provide proper usage guidelines for both, which summarize data and describe statistical results. PMID:26045923

Controlling bias and inflation in epigenome- and transcriptome-wide association studies using the empirical null distribution.

PubMed

van Iterson, Maarten; van Zwet, Erik W; Heijmans, Bastiaan T

2017-01-27

We show that epigenome- and transcriptome-wide association studies (EWAS and TWAS) are prone to significant inflation and bias of test statistics, an unrecognized phenomenon introducing spurious findings if left unaddressed. Neither GWAS-based methodology nor state-of-the-art confounder adjustment methods completely remove bias and inflation. We propose a Bayesian method to control bias and inflation in EWAS and TWAS based on estimation of the empirical null distribution. Using simulations and real data, we demonstrate that our method maximizes power while properly controlling the false positive rate. We illustrate the utility of our method in large-scale EWAS and TWAS meta-analyses of age and smoking.

ON THE FERMI -GBM EVENT 0.4 s AFTER GW150914

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

Greiner, J.; Yu, H.-F.; Burgess, J. M.

In view of the recent report by Connaughton et al., we analyze continuous time-tagged event (TTE) data of Fermi -gamma-ray burst monitor (GBM) around the time of the gravitational-wave event GW 150914. We find that after proper accounting for low-count statistics, the GBM transient event at 0.4 s after GW 150914 is likely not due to an astrophysical source, but consistent with a background fluctuation, removing the tension between the INTEGRAL /ACS non-detection and GBM. Additionally, reanalysis of other short GRBs shows that without proper statistical modeling the fluence of faint events is over-predicted, as verified for some joint GBM–ACSmore » detections of short GRBs. We detail the statistical procedure to correct these biases. As a result, faint short GRBs, verified by ACS detections, with significances in the broadband light curve even smaller than that of the GBM–GW150914 event are recovered as proper non-zero source, while the GBM–GW150914 event is consistent with zero fluence.« less

76 FR 6161 - Proposed Collection, Comment Request

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MyPMFs: a simple tool for creating statistical potentials to assess protein structural models.

PubMed

Postic, Guillaume; Hamelryck, Thomas; Chomilier, Jacques; Stratmann, Dirk

2018-05-29

Evaluating the model quality of protein structures that evolve in environments with particular physicochemical properties requires scoring functions that are adapted to their specific residue compositions and/or structural characteristics. Thus, computational methods developed for structures from the cytosol cannot work properly on membrane or secreted proteins. Here, we present MyPMFs, an easy-to-use tool that allows users to train statistical potentials of mean force (PMFs) on the protein structures of their choice, with all parameters being adjustable. We demonstrate its use by creating an accurate statistical potential for transmembrane protein domains. We also show its usefulness to study the influence of the physical environment on residue interactions within protein structures. Our open-source software is freely available for download at https://github.com/bibip-impmc/mypmfs. Copyright © 2018. Published by Elsevier B.V.

Methods for Determining Spontaneous Mutation Rates

PubMed Central

Foster, Patricia L.

2007-01-01

Spontaneous mutations arise as a result of cellular processes that act upon or damage DNA. Accurate determination of spontaneous mutation rates can contribute to our understanding of these processes and the enzymatic pathways that deal with them. The methods that are used to calculate mutation rates are based on the model for the expansion of mutant clones originally described by Luria and Delbrück and extended by Lea and Coulson. The accurate determination of mutation rates depends on understanding the strengths and limitations of these methods and how to optimize a fluctuation assay for a given method. This chapter describes the proper design of a fluctuation assay, several of the methods used to calculate mutation rates, and ways to evaluate the results statistically. PMID:16793403

A UNIFIED FRAMEWORK FOR VARIANCE COMPONENT ESTIMATION WITH SUMMARY STATISTICS IN GENOME-WIDE ASSOCIATION STUDIES.

PubMed

Zhou, Xiang

2017-12-01

Linear mixed models (LMMs) are among the most commonly used tools for genetic association studies. However, the standard method for estimating variance components in LMMs-the restricted maximum likelihood estimation method (REML)-suffers from several important drawbacks: REML requires individual-level genotypes and phenotypes from all samples in the study, is computationally slow, and produces downward-biased estimates in case control studies. To remedy these drawbacks, we present an alternative framework for variance component estimation, which we refer to as MQS. MQS is based on the method of moments (MoM) and the minimal norm quadratic unbiased estimation (MINQUE) criterion, and brings two seemingly unrelated methods-the renowned Haseman-Elston (HE) regression and the recent LD score regression (LDSC)-into the same unified statistical framework. With this new framework, we provide an alternative but mathematically equivalent form of HE that allows for the use of summary statistics. We provide an exact estimation form of LDSC to yield unbiased and statistically more efficient estimates. A key feature of our method is its ability to pair marginal z -scores computed using all samples with SNP correlation information computed using a small random subset of individuals (or individuals from a proper reference panel), while capable of producing estimates that can be almost as accurate as if both quantities are computed using the full data. As a result, our method produces unbiased and statistically efficient estimates, and makes use of summary statistics, while it is computationally efficient for large data sets. Using simulations and applications to 37 phenotypes from 8 real data sets, we illustrate the benefits of our method for estimating and partitioning SNP heritability in population studies as well as for heritability estimation in family studies. Our method is implemented in the GEMMA software package, freely available at www.xzlab.org/software.html.

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

PubMed Central

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

2017-01-01

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

Get Ready for Gaia: Cool White Dwarfs in Common Proper Motion with Tycho Stars

NASA Astrophysics Data System (ADS)

Hambly, N.; Rowell, N.; Lam, M.

2017-03-01

We discuss the Gaia Data Release 1 (September 2016) and preliminary work on maximising the benefit for cool white dwarf (WD) science in advance of the full parallax catalogue which will appear around one year later in DR2. The Tycho catalogue is used in conjunction with the all-sky ground based astrometric/ photometric SuperCOSMOS Sky Survey in order to identify candidate faint common proper motion objects to the Tycho stars. Gaia DR1 is supplemented by the Tycho-Gaia Astrometric Solution catalogue containing some 2 million parallaxes with Hipparcos-like precision for Tycho stars. While hotter, brighter WDs are present in Tycho, cooler examples are much rarer (if present at all) and CPM offers one method to infer precision distances for a statistically useful sample of these very faint WDs.

Understanding the Sampling Distribution and the Central Limit Theorem.

ERIC Educational Resources Information Center

Lewis, Charla P.

The sampling distribution is a common source of misuse and misunderstanding in the study of statistics. The sampling distribution, underlying distribution, and the Central Limit Theorem are all interconnected in defining and explaining the proper use of the sampling distribution of various statistics. The sampling distribution of a statistic is…

Identifying city PV roof resource based on Gabor filter

NASA Astrophysics Data System (ADS)

Ruhang, Xu; Zhilin, Liu; Yong, Huang; Xiaoyu, Zhang

2017-06-01

To identify a city’s PV roof resources, the area and ownership distribution of residential buildings in an urban district should be assessed. To achieve this assessment, remote sensing data analysing is a promising approach. Urban building roof area estimation is a major topic for remote sensing image information extraction. There are normally three ways to solve this problem. The first way is pixel-based analysis, which is based on mathematical morphology or statistical methods; the second way is object-based analysis, which is able to combine semantic information and expert knowledge; the third way is signal-processing view method. This paper presented a Gabor filter based method. This result shows that the method is fast and with proper accuracy.

Estimation of signal coherence threshold and concealed spectral lines applied to detection of turbofan engine combustion noise.

PubMed

Miles, Jeffrey Hilton

2011-05-01

Combustion noise from turbofan engines has become important, as the noise from sources like the fan and jet are reduced. An aligned and un-aligned coherence technique has been developed to determine a threshold level for the coherence and thereby help to separate the coherent combustion noise source from other noise sources measured with far-field microphones. This method is compared with a statistics based coherence threshold estimation method. In addition, the un-aligned coherence procedure at the same time also reveals periodicities, spectral lines, and undamped sinusoids hidden by broadband turbofan engine noise. In calculating the coherence threshold using a statistical method, one may use either the number of independent records or a larger number corresponding to the number of overlapped records used to create the average. Using data from a turbofan engine and a simulation this paper shows that applying the Fisher z-transform to the un-aligned coherence can aid in making the proper selection of samples and produce a reasonable statistics based coherence threshold. Examples are presented showing that the underlying tonal and coherent broad band structure which is buried under random broadband noise and jet noise can be determined. The method also shows the possible presence of indirect combustion noise.

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.

Statistical Tools And Artificial Intelligence Approaches To Predict Fracture In Bulk Forming Processes

NASA Astrophysics Data System (ADS)

Di Lorenzo, R.; Ingarao, G.; Fonti, V.

2007-05-01

The crucial task in the prevention of ductile fracture is the availability of a tool for the prediction of such defect occurrence. The technical literature presents a wide investigation on this topic and many contributions have been given by many authors following different approaches. The main class of approaches regards the development of fracture criteria: generally, such criteria are expressed by determining a critical value of a damage function which depends on stress and strain paths: ductile fracture is assumed to occur when such critical value is reached during the analysed process. There is a relevant drawback related to the utilization of ductile fracture criteria; in fact each criterion usually has good performances in the prediction of fracture for particular stress - strain paths, i.e. it works very well for certain processes but may provide no good results for other processes. On the other hand, the approaches based on damage mechanics formulation are very effective from a theoretical point of view but they are very complex and their proper calibration is quite difficult. In this paper, two different approaches are investigated to predict fracture occurrence in cold forming operations. The final aim of the proposed method is the achievement of a tool which has a general reliability i.e. it is able to predict fracture for different forming processes. The proposed approach represents a step forward within a research project focused on the utilization of innovative predictive tools for ductile fracture. The paper presents a comparison between an artificial neural network design procedure and an approach based on statistical tools; both the approaches were aimed to predict fracture occurrence/absence basing on a set of stress and strain paths data. The proposed approach is based on the utilization of experimental data available, for a given material, on fracture occurrence in different processes. More in detail, the approach consists in the analysis of experimental tests in which fracture occurs followed by the numerical simulations of such processes in order to track the stress-strain paths in the workpiece region where fracture is expected. Such data are utilized to build up a proper data set which was utilized both to train an artificial neural network and to perform a statistical analysis aimed to predict fracture occurrence. The developed statistical tool is properly designed and optimized and is able to recognize the fracture occurrence. The reliability and predictive capability of the statistical method were compared with the ones obtained from an artificial neural network developed to predict fracture occurrence. Moreover, the approach is validated also in forming processes characterized by a complex fracture mechanics.

[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.

A polynomial-chaos-expansion-based building block approach for stochastic analysis of photonic circuits

NASA Astrophysics Data System (ADS)

Waqas, Abi; Melati, Daniele; Manfredi, Paolo; Grassi, Flavia; Melloni, Andrea

2018-02-01

The Building Block (BB) approach has recently emerged in photonic as a suitable strategy for the analysis and design of complex circuits. Each BB can be foundry related and contains a mathematical macro-model of its functionality. As well known, statistical variations in fabrication processes can have a strong effect on their functionality and ultimately affect the yield. In order to predict the statistical behavior of the circuit, proper analysis of the uncertainties effects is crucial. This paper presents a method to build a novel class of Stochastic Process Design Kits for the analysis of photonic circuits. The proposed design kits directly store the information on the stochastic behavior of each building block in the form of a generalized-polynomial-chaos-based augmented macro-model obtained by properly exploiting stochastic collocation and Galerkin methods. Using this approach, we demonstrate that the augmented macro-models of the BBs can be calculated once and stored in a BB (foundry dependent) library and then used for the analysis of any desired circuit. The main advantage of this approach, shown here for the first time in photonics, is that the stochastic moments of an arbitrary photonic circuit can be evaluated by a single simulation only, without the need for repeated simulations. The accuracy and the significant speed-up with respect to the classical Monte Carlo analysis are verified by means of classical photonic circuit example with multiple uncertain variables.

45 CFR 153.350 - Risk adjustment data validation standards.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 45 Public Welfare 1 2013-10-01 2013-10-01 false Risk adjustment data validation standards. 153.350... validation standards. (a) General requirement. The State, or HHS on behalf of the State, must ensure proper implementation of any risk adjustment software and ensure proper validation of a statistically valid sample of...

45 CFR 153.350 - Risk adjustment data validation standards.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 45 Public Welfare 1 2014-10-01 2014-10-01 false Risk adjustment data validation standards. 153.350... validation standards. (a) General requirement. The State, or HHS on behalf of the State, must ensure proper implementation of any risk adjustment software and ensure proper validation of a statistically valid sample of...

40 CFR 91.512 - Request for public hearing.

Code of Federal Regulations, 2010 CFR

2010-07-01

... plans and statistical analyses have been properly applied (specifically, whether sampling procedures and statistical analyses specified in this subpart were followed and whether there exists a basis for... will be made available to the public during Agency business hours. ...

OH maser proper motions in Cepheus A

NASA Astrophysics Data System (ADS)

Migenes, V.; Cohen, R. J.; Brebner, G. C.

1992-02-01

MERLIN measurements made between 1982 and 1989 reveal proper motions of OH masers in the source Cepheus A. The proper motions are typically a few milliarcsec per year, and are mainly directed away from the central H II regions. Statistical analysis of the data suggests an expansion time-scale of some 300 yr. The distance of the source implied by the proper motions is 320+140/-80 pc, assuming that the expansion is isotropic. The proper motions can be reconciled with the larger distance of 730 pc which is generally accepted, provided that the masers are moving at large angles to the line of sight. The expansion time-scale agrees with that of the magnetic field decay recently reported by Cohen, et al. (1990).

A robust and efficient statistical method for genetic association studies using case and control samples from multiple cohorts

PubMed Central

2013-01-01

Background The theoretical basis of genome-wide association studies (GWAS) is statistical inference of linkage disequilibrium (LD) between any polymorphic marker and a putative disease locus. Most methods widely implemented for such analyses are vulnerable to several key demographic factors and deliver a poor statistical power for detecting genuine associations and also a high false positive rate. Here, we present a likelihood-based statistical approach that accounts properly for non-random nature of case–control samples in regard of genotypic distribution at the loci in populations under study and confers flexibility to test for genetic association in presence of different confounding factors such as population structure, non-randomness of samples etc. Results We implemented this novel method together with several popular methods in the literature of GWAS, to re-analyze recently published Parkinson’s disease (PD) case–control samples. The real data analysis and computer simulation show that the new method confers not only significantly improved statistical power for detecting the associations but also robustness to the difficulties stemmed from non-randomly sampling and genetic structures when compared to its rivals. In particular, the new method detected 44 significant SNPs within 25 chromosomal regions of size < 1 Mb but only 6 SNPs in two of these regions were previously detected by the trend test based methods. It discovered two SNPs located 1.18 Mb and 0.18 Mb from the PD candidates, FGF20 and PARK8, without invoking false positive risk. Conclusions We developed a novel likelihood-based method which provides adequate estimation of LD and other population model parameters by using case and control samples, the ease in integration of these samples from multiple genetically divergent populations and thus confers statistically robust and powerful analyses of GWAS. On basis of simulation studies and analysis of real datasets, we demonstrated significant improvement of the new method over the non-parametric trend test, which is the most popularly implemented in the literature of GWAS. PMID:23394771

40 CFR 90.712 - Request for public hearing.

Code of Federal Regulations, 2010 CFR

2010-07-01

... sampling plans and statistical analyses have been properly applied (specifically, whether sampling procedures and statistical analyses specified in this subpart were followed and whether there exists a basis... Clerk and will be made available to the public during Agency business hours. ...

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.

MSblender: A probabilistic approach for integrating peptide identifications from multiple database search engines.

PubMed

Kwon, Taejoon; Choi, Hyungwon; Vogel, Christine; Nesvizhskii, Alexey I; Marcotte, Edward M

2011-07-01

Shotgun proteomics using mass spectrometry is a powerful method for protein identification but suffers limited sensitivity in complex samples. Integrating peptide identifications from multiple database search engines is a promising strategy to increase the number of peptide identifications and reduce the volume of unassigned tandem mass spectra. Existing methods pool statistical significance scores such as p-values or posterior probabilities of peptide-spectrum matches (PSMs) from multiple search engines after high scoring peptides have been assigned to spectra, but these methods lack reliable control of identification error rates as data are integrated from different search engines. We developed a statistically coherent method for integrative analysis, termed MSblender. MSblender converts raw search scores from search engines into a probability score for every possible PSM and properly accounts for the correlation between search scores. The method reliably estimates false discovery rates and identifies more PSMs than any single search engine at the same false discovery rate. Increased identifications increment spectral counts for most proteins and allow quantification of proteins that would not have been quantified by individual search engines. We also demonstrate that enhanced quantification contributes to improve sensitivity in differential expression analyses.

MSblender: a probabilistic approach for integrating peptide identifications from multiple database search engines

PubMed Central

Kwon, Taejoon; Choi, Hyungwon; Vogel, Christine; Nesvizhskii, Alexey I.; Marcotte, Edward M.

2011-01-01

Shotgun proteomics using mass spectrometry is a powerful method for protein identification but suffers limited sensitivity in complex samples. Integrating peptide identifications from multiple database search engines is a promising strategy to increase the number of peptide identifications and reduce the volume of unassigned tandem mass spectra. Existing methods pool statistical significance scores such as p-values or posterior probabilities of peptide-spectrum matches (PSMs) from multiple search engines after high scoring peptides have been assigned to spectra, but these methods lack reliable control of identification error rates as data are integrated from different search engines. We developed a statistically coherent method for integrative analysis, termed MSblender. MSblender converts raw search scores from search engines into a probability score for all possible PSMs and properly accounts for the correlation between search scores. The method reliably estimates false discovery rates and identifies more PSMs than any single search engine at the same false discovery rate. Increased identifications increment spectral counts for all detected proteins and allow quantification of proteins that would not have been quantified by individual search engines. We also demonstrate that enhanced quantification contributes to improve sensitivity in differential expression analyses. PMID:21488652

On proper linearization, construction and analysis of the Boyle-van't Hoff plots and correct calculation of the osmotically inactive volume.

PubMed

Katkov, Igor I

2011-06-01

The Boyle-van't Hoff (BVH) law of physics has been widely used in cryobiology for calculation of the key osmotic parameters of cells and optimization of cryo-protocols. The proper use of linearization of the Boyle-vant'Hoff relationship for the osmotically inactive volume (v(b)) has been discussed in a rigorous way in (Katkov, Cryobiology, 2008, 57:142-149). Nevertheless, scientists in the field have been continuing to use inappropriate methods of linearization (and curve fitting) of the BVH data, plotting the BVH line and calculation of v(b). Here, we discuss the sources of incorrect linearization of the BVH relationship using concrete examples of recent publications, analyze the properties of the correct BVH line (which is unique for a given v(b)), provide appropriate statistical formulas for calculation of v(b) from the experimental data, and propose simplistic instructions (standard operation procedure, SOP) for proper normalization of the data, appropriate linearization and construction of the BVH plots, and correct calculation of v(b). The possible sources of non-linear behavior or poor fit of the data to the proper BVH line such as active water and/or solute transports, which can result in large discrepancy between the hyperosmotic and hypoosmotic parts of the BVH plot, are also discussed. Copyright © 2011 Elsevier Inc. All rights reserved.

ON THE CONNECTION OF THE APPARENT PROPER MOTION AND THE VLBI STRUCTURE OF COMPACT RADIO SOURCES

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

Moor, A.; Frey, S.; Lambert, S. B.

2011-06-15

Many of the compact extragalactic radio sources that are used as fiducial points to define the celestial reference frame are known to have proper motions detectable with long-term geodetic/astrometric very long baseline interferometry (VLBI) measurements. These changes can be as high as several hundred microarcseconds per year for certain objects. When imaged with VLBI at milliarcsecond (mas) angular resolution, these sources (radio-loud active galactic nuclei) typically show structures dominated by a compact, often unresolved 'core' and a one-sided 'jet'. The positional instability of compact radio sources is believed to be connected with changes in their brightness distribution structure. For themore » first time, we test this assumption in a statistical sense on a large sample rather than on only individual objects. We investigate a sample of 62 radio sources for which reliable long-term time series of astrometric positions as well as detailed 8 GHz VLBI brightness distribution models are available. We compare the characteristic direction of their extended jet structure and the direction of their apparent proper motion. We present our data and analysis method, and conclude that there is indeed a correlation between the two characteristic directions. However, there are cases where the {approx}1-10 mas scale VLBI jet directions are significantly misaligned with respect to the apparent proper motion direction.« less

The COSMIC-DANCE project: Unravelling the origin of the mass function

NASA Astrophysics Data System (ADS)

Bouy, H.; Bertin, E.; Sarro, L. M.; Barrado, D.; Berihuete, A.; Olivares, J.; Moraux, E.; Bouvier, J.; Tamura, M.; Cuillandre, J.-C.; Beletsky, Y.; Wright, N.; Huelamo, N.; Allen, L.; Solano, E.; Brandner, B.

2017-03-01

The COSMIC-DANCE project is an observational program aiming at understanding the origin and evolution of ultracool objects by measuring the mass function and internal dynamics of young nearby associations down to the fragmentation limit. The least massive members of young nearby associations are identified using modern statistical methods in a multi-dimensional space made of optical and infrared luminosities and colors and proper motions. The photometry and astrometry are obtained by combining ground and in some case space based archival observations with new observations, covering between one and two decades.

Aspergillosis

MedlinePlus

... Treatment Healthcare Professionals Statistics More Resources en español Definición Síntomas Riesgo y prevención Fuentes Diagnóstico y pruebas ... and Proper Management Statistics More Resources en español Definición Síntomas Las Personas en Riesgo y Prevención Fuentes ...

Candidiasis

MedlinePlus

... Treatment Healthcare Professionals Statistics More Resources en español Definición Síntomas Riesgo y prevención Fuentes Diagnóstico y pruebas ... and Proper Management Statistics More Resources en español Definición Síntomas Las Personas en Riesgo y Prevención Fuentes ...

Blastomycosis

MedlinePlus

... Treatment Healthcare Professionals Statistics More Resources en español Definición Síntomas Riesgo y prevención Fuentes Diagnóstico y pruebas ... and Proper Management Statistics More Resources en español Definición Síntomas Las Personas en Riesgo y Prevención Fuentes ...

Histoplasmosis

MedlinePlus

... Treatment Healthcare Professionals Statistics More Resources en español Definición Síntomas Riesgo y prevención Fuentes Diagnóstico y pruebas ... and Proper Management Statistics More Resources en español Definición Síntomas Las Personas en Riesgo y Prevención Fuentes ...

Infrared maritime target detection using the high order statistic filtering in fractional Fourier domain

NASA Astrophysics Data System (ADS)

Zhou, Anran; Xie, Weixin; Pei, Jihong

2018-06-01

Accurate detection of maritime targets in infrared imagery under various sea clutter conditions is always a challenging task. The fractional Fourier transform (FRFT) is the extension of the Fourier transform in the fractional order, and has richer spatial-frequency information. By combining it with the high order statistic filtering, a new ship detection method is proposed. First, the proper range of angle parameter is determined to make it easier for the ship components and background to be separated. Second, a new high order statistic curve (HOSC) at each fractional frequency point is designed. It is proved that maximal peak interval in HOSC reflects the target information, while the points outside the interval reflect the background. And the value of HOSC relative to the ship is much bigger than that to the sea clutter. Then, search the curve's maximal target peak interval and extract the interval by bandpass filtering in fractional Fourier domain. The value outside the peak interval of HOSC decreases rapidly to 0, so the background is effectively suppressed. Finally, the detection result is obtained by the double threshold segmenting and the target region selection method. The results show the proposed method is excellent for maritime targets detection with high clutters.

Hiding in plain sight

NASA Astrophysics Data System (ADS)

Riedel, Adric Richard

2012-05-01

Since the first successful measurements of stellar trigonometric parallax in the 1830s, the study of nearby stars has focused on the highest proper motion stars (micro > 0.18″ yr-1). Those high proper motion stars have formed the backbone of the last 150 years of study of the Solar Neighborhood and the composition of the Galaxy. Statistically speaking, though, there is a population of stars that will have low proper motions when their space motions have been projected onto the sky. At the same time, over the last twenty years, populations of relatively young stars (less than ˜ 100 Myr), most of them with low proper motions, have been revealed near (< 100 pc) the Sun. This dissertation is the result of two related projects: A photometric search for nearby (< 25pc) southern-hemisphere M dwarf stars with low proper motions (micro < 0.18″ yr-1), and a search for nearby (< 100 pc) pre-main-sequence (< 125 Myr old) M dwarf systems. The projects rely on a variety of photometric, spectroscopic, and astrometric analyses (including parallaxes from our program) using data from telescopes at CTIO via the SMARTS Consortium and at Lowell Observatory. Within this dissertation, I describe the identification and confirmation of 23 new nearby low proper motion M dwarf systems within 25 pc, 8 of which are within 15 pc (50% of the anticipated low-proper-motion 15 pc sample). I also report photometric, spectroscopic, and astrometric parameters and identifications for a selection of 25 known and new candidate nearby young M dwarfs, including new low-mass members of the TW Hydra, beta Pictoris, Tucana-Horologium, Argus, and AB Doradus associations, following the methods of my Riedel et al. (2011) paper and its discovery of AP Col, the closest pre-main-sequence star to the Solar System. These low proper motion and nearby star discoveries are put into the context of the Solar Neighborhood as a whole by means of the new RECONS 25 pc Database, to which I have now added (including my Riedel et al. (2010) paper) 81 star systems (4% of the total). INDEX WORDS: Astronomy, Astrometry, Photometry, Spectroscopy, Kinematics, Proper motion, Parallax, Nearby stars, Low-mass stars, Young stars, Pre-main-sequence stars.

Synthetic data sets for the identification of key ingredients for RNA-seq differential analysis.

PubMed

Rigaill, Guillem; Balzergue, Sandrine; Brunaud, Véronique; Blondet, Eddy; Rau, Andrea; Rogier, Odile; Caius, José; Maugis-Rabusseau, Cathy; Soubigou-Taconnat, Ludivine; Aubourg, Sébastien; Lurin, Claire; Martin-Magniette, Marie-Laure; Delannoy, Etienne

2018-01-01

Numerous statistical pipelines are now available for the differential analysis of gene expression measured with RNA-sequencing technology. Most of them are based on similar statistical frameworks after normalization, differing primarily in the choice of data distribution, mean and variance estimation strategy and data filtering. We propose an evaluation of the impact of these choices when few biological replicates are available through the use of synthetic data sets. This framework is based on real data sets and allows the exploration of various scenarios differing in the proportion of non-differentially expressed genes. Hence, it provides an evaluation of the key ingredients of the differential analysis, free of the biases associated with the simulation of data using parametric models. Our results show the relevance of a proper modeling of the mean by using linear or generalized linear modeling. Once the mean is properly modeled, the impact of the other parameters on the performance of the test is much less important. Finally, we propose to use the simple visualization of the raw P-value histogram as a practical evaluation criterion of the performance of differential analysis methods on real data sets. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Errors in reporting on dissolution research: methodological and statistical implications.

PubMed

Jasińska-Stroschein, Magdalena; Kurczewska, Urszula; Orszulak-Michalak, Daria

2017-02-01

In vitro dissolution testing provides useful information at clinical and preclinical stages of the drug development process. The study includes pharmaceutical papers on dissolution research published in Polish journals between 2010 and 2015. They were analyzed with regard to information provided by authors about chosen methods, performed validation, statistical reporting or assumptions used to properly compare release profiles considering the present guideline documents addressed to dissolution methodology and its validation. Of all the papers included in the study, 23.86% presented at least one set of validation parameters, 63.64% gave the results of the weight uniformity test, 55.68% content determination, 97.73% dissolution testing conditions, and 50% discussed a comparison of release profiles. The assumptions for methods used to compare dissolution profiles were discussed in 6.82% of papers. By means of example analyses, we demonstrate that the outcome can be influenced by the violation of several assumptions or selection of an improper method to compare dissolution profiles. A clearer description of the procedures would undoubtedly increase the quality of papers in this area.

The effects of training married men about premenstrual syndrome by pamphlets and short messages on marital satisfaction.

PubMed

Morowatisharifabad, Mohammad Ali; Karimiankakolaki, Zohreh; Bokaie, Mahshid; Fallahzadeh, Hossein; Gerayllo, Sakineh

2014-12-01

Premenstrual syndrome (PMS), which includes physical, psychological and emotional symptoms that occur during the luteal phase of the menstrual cycle, has a negative impact on the quality of the relationship among married couples. The purpose of the study was to examine the effects of educating married men by two methods, pamphlet and short messages (SMS), on marital satisfaction of the couples. The study was experimental in nature. The sample consisted of 80 couples who had visited health centers in Yazd, Iran. The subjects were randomly assigned to the two training methods and pretested and post-tested on the outcome measures. The before to after the training increase in knowledge and practice in men and marital satisfaction of couples were statistically significant. The differences between the two training methods were not statistically significant. Pamphlets and SMS, if designed properly and based on the principles of psychology, can act as influential and almost equally effective educational tools in the context of PMS. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Earth Observation System Flight Dynamics System Covariance Realism

NASA Technical Reports Server (NTRS)

Zaidi, Waqar H.; Tracewell, David

2016-01-01

This presentation applies a covariance realism technique to the National Aeronautics and Space Administration (NASA) Earth Observation System (EOS) Aqua and Aura spacecraft based on inferential statistics. The technique consists of three parts: collection calculation of definitive state estimates through orbit determination, calculation of covariance realism test statistics at each covariance propagation point, and proper assessment of those test statistics.

A New Method of Assessing Uncertainty of the Cross-Convolution Method of Shear Wave Splitting Measurement

NASA Astrophysics Data System (ADS)

Schutt, D.; Breidt, J.; Corbalan Castejon, A.; Witt, D. R.

2017-12-01

Shear wave splitting is a commonly used and powerful method for constraining such phenomena as lithospheric strain history or asthenospheric flow. However, a number of challenges with the statistics of shear wave splitting have been noted. This creates difficulties in assessing whether two separate measurements are statistically similar or are indicating real differences in anisotropic structure, as well as for created proper station averaged sets of parameters for more complex situations such as multiple or dipping layers of anisotropy. We present a new method for calculating the most likely splitting parameters using the Menke and Levin [2003] method of cross-convolution. The Menke and Levin method is used because it can more readily be applied to a wider range of anisotropic scenarios than the commonly used Silver and Chan [1991] technique. In our approach, we derive a formula for the spectral density of a function of the microseismic noise and the impulse response of the correct anisotropic model that holds for the true anisotropic model parameters. This is compared to the spectral density of the observed signal convolved with the impulse response for an estimated set of anisotropic parameters. The most likely parameters are found when the former and latter spectral densities are the same. By using the Whittle likelihood to compare the two spectral densities, a likelihood grid for all possible anisotropic parameter values is generated. Using bootstrapping, the uncertainty and covariance between the various anisotropic parameters can be evaluated. We will show this works with a single layer of anisotropy and a vertically incident ray, and discuss the usefulness for a more complex case. The method shows great promise for calculating multiple layer anisotropy parameters with proper assessment of uncertainty. References: Menke, W., and Levin, V. 2003. The cross-convolution method for interpreting SKS splitting observations, with application to one and two-layer anisotropic earth models. Geophysical Journal International, 154: 379-392. doi:10.1046/j.1365-246X.2003.01937.x. Silver, P.G., and Chan, W.W. 1991. Shear Wave Splitting and Sub continental Mantle Deformation. Journal of Geophysical Research, 96: 429-454. doi:10.1029/91JB00899.

Simple Statistics: - Summarized!

ERIC Educational Resources Information Center

Blai, Boris, Jr.

Statistics are an essential tool for making proper judgement decisions. It is concerned with probability distribution models, testing of hypotheses, significance tests and other means of determining the correctness of deductions and the most likely outcome of decisions. Measures of central tendency include the mean, median and mode. A second…

Fungal Diseases

MedlinePlus

... Treatment Healthcare Professionals Statistics More Resources en español Definición Síntomas Riesgo y prevención Fuentes Diagnóstico y pruebas ... and Proper Management Statistics More Resources en español Definición Síntomas Las Personas en Riesgo y Prevención Fuentes ...

Mucormycosis (Zygomycosis)

MedlinePlus

... Treatment Healthcare Professionals Statistics More Resources en español Definición Síntomas Riesgo y prevención Fuentes Diagnóstico y pruebas ... and Proper Management Statistics More Resources en español Definición Síntomas Las Personas en Riesgo y Prevención Fuentes ...

Valley Fever (Coccidioidomycosis)

MedlinePlus

... Treatment Healthcare Professionals Statistics More Resources en español Definición Síntomas Riesgo y prevención Fuentes Diagnóstico y pruebas ... and Proper Management Statistics More Resources en español Definición Síntomas Las Personas en Riesgo y Prevención Fuentes ...

Symptoms of Aspergillosis

MedlinePlus

... Treatment Healthcare Professionals Statistics More Resources en español Definición Síntomas Riesgo y prevención Fuentes Diagnóstico y pruebas ... and Proper Management Statistics More Resources en español Definición Síntomas Las Personas en Riesgo y Prevención Fuentes ...

Fungal Diseases: Ringworm

MedlinePlus

... Treatment Healthcare Professionals Statistics More Resources en español Definición Síntomas Riesgo y prevención Fuentes Diagnóstico y pruebas ... and Proper Management Statistics More Resources en español Definición Síntomas Las Personas en Riesgo y Prevención Fuentes ...

22 CFR 505.2 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-04-01

... record keeping functions; exercise of control over and hence responsibility and accountability for... proper and necessary uses even if any such uses occur infrequently. (h) Statistical record. A record in a system of records maintained for statistical research or reporting purposes only and not used in whole or...

CellTree: an R/bioconductor package to infer the hierarchical structure of cell populations from single-cell RNA-seq data.

PubMed

duVerle, David A; Yotsukura, Sohiya; Nomura, Seitaro; Aburatani, Hiroyuki; Tsuda, Koji

2016-09-13

Single-cell RNA sequencing is fast becoming one the standard method for gene expression measurement, providing unique insights into cellular processes. A number of methods, based on general dimensionality reduction techniques, have been suggested to help infer and visualise the underlying structure of cell populations from single-cell expression levels, yet their models generally lack proper biological grounding and struggle at identifying complex differentiation paths. Here we introduce cellTree: an R/Bioconductor package that uses a novel statistical approach, based on document analysis techniques, to produce tree structures outlining the hierarchical relationship between single-cell samples, while identifying latent groups of genes that can provide biological insights. With cellTree, we provide experimentalists with an easy-to-use tool, based on statistically and biologically-sound algorithms, to efficiently explore and visualise single-cell RNA data. The cellTree package is publicly available in the online Bionconductor repository at: http://bioconductor.org/packages/cellTree/ .

Accounting for response misclassification and covariate measurement error improves power and reduces bias in epidemiologic studies.

PubMed

Cheng, Dunlei; Branscum, Adam J; Stamey, James D

2010-07-01

To quantify the impact of ignoring misclassification of a response variable and measurement error in a covariate on statistical power, and to develop software for sample size and power analysis that accounts for these flaws in epidemiologic data. A Monte Carlo simulation-based procedure is developed to illustrate the differences in design requirements and inferences between analytic methods that properly account for misclassification and measurement error to those that do not in regression models for cross-sectional and cohort data. We found that failure to account for these flaws in epidemiologic data can lead to a substantial reduction in statistical power, over 25% in some cases. The proposed method substantially reduced bias by up to a ten-fold margin compared to naive estimates obtained by ignoring misclassification and mismeasurement. We recommend as routine practice that researchers account for errors in measurement of both response and covariate data when determining sample size, performing power calculations, or analyzing data from epidemiological studies. 2010 Elsevier Inc. All rights reserved.

Gaussian process regression for sensor networks under localization uncertainty

USGS Publications Warehouse

Jadaliha, M.; Xu, Yunfei; Choi, Jongeun; Johnson, N.S.; Li, Weiming

2013-01-01

In this paper, we formulate Gaussian process regression with observations under the localization uncertainty due to the resource-constrained sensor networks. In our formulation, effects of observations, measurement noise, localization uncertainty, and prior distributions are all correctly incorporated in the posterior predictive statistics. The analytically intractable posterior predictive statistics are proposed to be approximated by two techniques, viz., Monte Carlo sampling and Laplace's method. Such approximation techniques have been carefully tailored to our problems and their approximation error and complexity are analyzed. Simulation study demonstrates that the proposed approaches perform much better than approaches without considering the localization uncertainty properly. Finally, we have applied the proposed approaches on the experimentally collected real data from a dye concentration field over a section of a river and a temperature field of an outdoor swimming pool to provide proof of concept tests and evaluate the proposed schemes in real situations. In both simulation and experimental results, the proposed methods outperform the quick-and-dirty solutions often used in practice.

Reconstruction of a Real World Social Network using the Potts Model and Loopy Belief Propagation.

PubMed

Bisconti, Cristian; Corallo, Angelo; Fortunato, Laura; Gentile, Antonio A; Massafra, Andrea; Pellè, Piergiuseppe

2015-01-01

The scope of this paper is to test the adoption of a statistical model derived from Condensed Matter Physics, for the reconstruction of the structure of a social network. The inverse Potts model, traditionally applied to recursive observations of quantum states in an ensemble of particles, is here addressed to observations of the members' states in an organization and their (anti)correlations, thus inferring interactions as links among the members. Adopting proper (Bethe) approximations, such an inverse problem is showed to be tractable. Within an operational framework, this network-reconstruction method is tested for a small real-world social network, the Italian parliament. In this study case, it is easy to track statuses of the parliament members, using (co)sponsorships of law proposals as the initial dataset. In previous studies of similar activity-based networks, the graph structure was inferred directly from activity co-occurrences: here we compare our statistical reconstruction with such standard methods, outlining discrepancies and advantages.

Reconstruction of a Real World Social Network using the Potts Model and Loopy Belief Propagation

PubMed Central

Bisconti, Cristian; Corallo, Angelo; Fortunato, Laura; Gentile, Antonio A.; Massafra, Andrea; Pellè, Piergiuseppe

2015-01-01

The scope of this paper is to test the adoption of a statistical model derived from Condensed Matter Physics, for the reconstruction of the structure of a social network. The inverse Potts model, traditionally applied to recursive observations of quantum states in an ensemble of particles, is here addressed to observations of the members' states in an organization and their (anti)correlations, thus inferring interactions as links among the members. Adopting proper (Bethe) approximations, such an inverse problem is showed to be tractable. Within an operational framework, this network-reconstruction method is tested for a small real-world social network, the Italian parliament. In this study case, it is easy to track statuses of the parliament members, using (co)sponsorships of law proposals as the initial dataset. In previous studies of similar activity-based networks, the graph structure was inferred directly from activity co-occurrences: here we compare our statistical reconstruction with such standard methods, outlining discrepancies and advantages. PMID:26617539

[Triple-type theory of statistics and its application in the scientific research of biomedicine].

PubMed

Hu, Liang-ping; Liu, Hui-gang

2005-07-20

To point out the crux of why so many people failed to grasp statistics and to bring forth a "triple-type theory of statistics" to solve the problem in a creative way. Based on the experience in long-time teaching and research in statistics, the "three-type theory" was raised and clarified. Examples were provided to demonstrate that the 3 types, i.e., expressive type, prototype and the standardized type are the essentials for people to apply statistics rationally both in theory and practice, and moreover, it is demonstrated by some instances that the "three types" are correlated with each other. It can help people to see the essence by interpreting and analyzing the problems of experimental designs and statistical analyses in medical research work. Investigations reveal that for some questions, the three types are mutually identical; for some questions, the prototype is their standardized type; however, for some others, the three types are distinct from each other. It has been shown that in some multifactor experimental researches, it leads to the nonexistence of the standardized type corresponding to the prototype at all, because some researchers have committed the mistake of "incomplete control" in setting experimental groups. This is a problem which should be solved by the concept and method of "division". Once the "triple-type" for each question is clarified, a proper experimental design and statistical method can be carried out easily. "Triple-type theory of statistics" can help people to avoid committing statistical mistakes or at least to decrease the misuse rate dramatically and improve the quality, level and speed of biomedical research during the process of applying statistics. It can also help people to improve the quality of statistical textbooks and the teaching effect of statistics and it has demonstrated how to advance biomedical statistics.

Exploring the Connection Between Sampling Problems in Bayesian Inference and Statistical Mechanics

NASA Technical Reports Server (NTRS)

Pohorille, Andrew

2006-01-01

The Bayesian and statistical mechanical communities often share the same objective in their work - estimating and integrating probability distribution functions (pdfs) describing stochastic systems, models or processes. Frequently, these pdfs are complex functions of random variables exhibiting multiple, well separated local minima. Conventional strategies for sampling such pdfs are inefficient, sometimes leading to an apparent non-ergodic behavior. Several recently developed techniques for handling this problem have been successfully applied in statistical mechanics. In the multicanonical and Wang-Landau Monte Carlo (MC) methods, the correct pdfs are recovered from uniform sampling of the parameter space by iteratively establishing proper weighting factors connecting these distributions. Trivial generalizations allow for sampling from any chosen pdf. The closely related transition matrix method relies on estimating transition probabilities between different states. All these methods proved to generate estimates of pdfs with high statistical accuracy. In another MC technique, parallel tempering, several random walks, each corresponding to a different value of a parameter (e.g. "temperature"), are generated and occasionally exchanged using the Metropolis criterion. This method can be considered as a statistically correct version of simulated annealing. An alternative approach is to represent the set of independent variables as a Hamiltonian system. Considerab!e progress has been made in understanding how to ensure that the system obeys the equipartition theorem or, equivalently, that coupling between the variables is correctly described. Then a host of techniques developed for dynamical systems can be used. Among them, probably the most powerful is the Adaptive Biasing Force method, in which thermodynamic integration and biased sampling are combined to yield very efficient estimates of pdfs. The third class of methods deals with transitions between states described by rate constants. These problems are isomorphic with chemical kinetics problems. Recently, several efficient techniques for this purpose have been developed based on the approach originally proposed by Gillespie. Although the utility of the techniques mentioned above for Bayesian problems has not been determined, further research along these lines is warranted

Impact of Eliminating Anchor Items Flagged from Statistical Criteria on Test Score Classifications in Common Item Equating

ERIC Educational Resources Information Center

Karkee, Thakur; Choi, Seung

2005-01-01

Proper maintenance of a scale established in the baseline year would assure the accurate estimation of growth in subsequent years. Scale maintenance is especially important when the state performance standards must be preserved for future administrations. To ensure proper maintenance of a scale, the selection of anchor items and evaluation of…

Evaluation of forensic DNA mixture evidence: protocol for evaluation, interpretation, and statistical calculations using the combined probability of inclusion.

PubMed

Bieber, Frederick R; Buckleton, John S; Budowle, Bruce; Butler, John M; Coble, Michael D

2016-08-31

The evaluation and interpretation of forensic DNA mixture evidence faces greater interpretational challenges due to increasingly complex mixture evidence. Such challenges include: casework involving low quantity or degraded evidence leading to allele and locus dropout; allele sharing of contributors leading to allele stacking; and differentiation of PCR stutter artifacts from true alleles. There is variation in statistical approaches used to evaluate the strength of the evidence when inclusion of a specific known individual(s) is determined, and the approaches used must be supportable. There are concerns that methods utilized for interpretation of complex forensic DNA mixtures may not be implemented properly in some casework. Similar questions are being raised in a number of U.S. jurisdictions, leading to some confusion about mixture interpretation for current and previous casework. Key elements necessary for the interpretation and statistical evaluation of forensic DNA mixtures are described. Given the most common method for statistical evaluation of DNA mixtures in many parts of the world, including the USA, is the Combined Probability of Inclusion/Exclusion (CPI/CPE). Exposition and elucidation of this method and a protocol for use is the focus of this article. Formulae and other supporting materials are provided. Guidance and details of a DNA mixture interpretation protocol is provided for application of the CPI/CPE method in the analysis of more complex forensic DNA mixtures. This description, in turn, should help reduce the variability of interpretation with application of this methodology and thereby improve the quality of DNA mixture interpretation throughout the forensic community.

Point and interval estimation of pollinator importance: a study using pollination data of Silene caroliniana.

PubMed

Reynolds, Richard J; Fenster, Charles B

2008-05-01

Pollinator importance, the product of visitation rate and pollinator effectiveness, is a descriptive parameter of the ecology and evolution of plant-pollinator interactions. Naturally, sources of its variation should be investigated, but the SE of pollinator importance has never been properly reported. Here, a Monte Carlo simulation study and a result from mathematical statistics on the variance of the product of two random variables are used to estimate the mean and confidence limits of pollinator importance for three visitor species of the wildflower, Silene caroliniana. Both methods provided similar estimates of mean pollinator importance and its interval if the sample size of the visitation and effectiveness datasets were comparatively large. These approaches allowed us to determine that bumblebee importance was significantly greater than clearwing hawkmoth, which was significantly greater than beefly. The methods could be used to statistically quantify temporal and spatial variation in pollinator importance of particular visitor species. The approaches may be extended for estimating the variance of more than two random variables. However, unless the distribution function of the resulting statistic is known, the simulation approach is preferable for calculating the parameter's confidence limits.

Multivariate meta-analysis: potential and promise.

PubMed

Jackson, Dan; Riley, Richard; White, Ian R

2011-09-10

The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and disadvantages, we organized a one day 'Multivariate meta-analysis' event at the Royal Statistical Society. In addition to disseminating the most recent developments, we also received an abundance of comments, concerns, insights, critiques and encouragement. This article provides a balanced account of the day's discourse. By giving others the opportunity to respond to our assessment, we hope to ensure that the various view points and opinions are aired before multivariate meta-analysis simply becomes another widely used de facto method without any proper consideration of it by the medical statistics community. We describe the areas of application that multivariate meta-analysis has found, the methods available, the difficulties typically encountered and the arguments for and against the multivariate methods, using four representative but contrasting examples. We conclude that the multivariate methods can be useful, and in particular can provide estimates with better statistical properties, but also that these benefits come at the price of making more assumptions which do not result in better inference in every case. Although there is evidence that multivariate meta-analysis has considerable potential, it must be even more carefully applied than its univariate counterpart in practice. Copyright © 2011 John Wiley & Sons, Ltd.

Multivariate meta-analysis: Potential and promise

PubMed Central

Jackson, Dan; Riley, Richard; White, Ian R

2011-01-01

The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and disadvantages, we organized a one day ‘Multivariate meta-analysis’ event at the Royal Statistical Society. In addition to disseminating the most recent developments, we also received an abundance of comments, concerns, insights, critiques and encouragement. This article provides a balanced account of the day's discourse. By giving others the opportunity to respond to our assessment, we hope to ensure that the various view points and opinions are aired before multivariate meta-analysis simply becomes another widely used de facto method without any proper consideration of it by the medical statistics community. We describe the areas of application that multivariate meta-analysis has found, the methods available, the difficulties typically encountered and the arguments for and against the multivariate methods, using four representative but contrasting examples. We conclude that the multivariate methods can be useful, and in particular can provide estimates with better statistical properties, but also that these benefits come at the price of making more assumptions which do not result in better inference in every case. Although there is evidence that multivariate meta-analysis has considerable potential, it must be even more carefully applied than its univariate counterpart in practice. Copyright © 2011 John Wiley & Sons, Ltd. PMID:21268052

Treatment and Outcomes of Histoplasmosis

MedlinePlus

... Treatment Healthcare Professionals Statistics More Resources en español Definición Síntomas Riesgo y prevención Fuentes Diagnóstico y pruebas ... and Proper Management Statistics More Resources en español Definición Síntomas Las Personas en Riesgo y Prevención Fuentes ...

Symptoms of Valley Fever (Coccidioidomycosis)

MedlinePlus

... Treatment Healthcare Professionals Statistics More Resources en español Definición Síntomas Riesgo y prevención Fuentes Diagnóstico y pruebas ... and Proper Management Statistics More Resources en español Definición Síntomas Las Personas en Riesgo y Prevención Fuentes ...

Treatment for Valley Fever (Coccidioidomycosis)

MedlinePlus

... Treatment Healthcare Professionals Statistics More Resources en español Definición Síntomas Riesgo y prevención Fuentes Diagnóstico y pruebas ... and Proper Management Statistics More Resources en español Definición Síntomas Las Personas en Riesgo y Prevención Fuentes ...

Treatment and Outcomes of Aspergillosis

MedlinePlus

... Treatment Healthcare Professionals Statistics More Resources en español Definición Síntomas Riesgo y prevención Fuentes Diagnóstico y pruebas ... and Proper Management Statistics More Resources en español Definición Síntomas Las Personas en Riesgo y Prevención Fuentes ...

Statistical downscaling modeling with quantile regression using lasso to estimate extreme rainfall

NASA Astrophysics Data System (ADS)

Santri, Dewi; Wigena, Aji Hamim; Djuraidah, Anik

2016-02-01

Rainfall is one of the climatic elements with high diversity and has many negative impacts especially extreme rainfall. Therefore, there are several methods that required to minimize the damage that may occur. So far, Global circulation models (GCM) are the best method to forecast global climate changes include extreme rainfall. Statistical downscaling (SD) is a technique to develop the relationship between GCM output as a global-scale independent variables and rainfall as a local- scale response variable. Using GCM method will have many difficulties when assessed against observations because GCM has high dimension and multicollinearity between the variables. The common method that used to handle this problem is principal components analysis (PCA) and partial least squares regression. The new method that can be used is lasso. Lasso has advantages in simultaneuosly controlling the variance of the fitted coefficients and performing automatic variable selection. Quantile regression is a method that can be used to detect extreme rainfall in dry and wet extreme. Objective of this study is modeling SD using quantile regression with lasso to predict extreme rainfall in Indramayu. The results showed that the estimation of extreme rainfall (extreme wet in January, February and December) in Indramayu could be predicted properly by the model at quantile 90th.

ACCOUNTING FOR CALIBRATION UNCERTAINTIES IN X-RAY ANALYSIS: EFFECTIVE AREAS IN SPECTRAL FITTING

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

Lee, Hyunsook; Kashyap, Vinay L.; Drake, Jeremy J.

2011-04-20

While considerable advance has been made to account for statistical uncertainties in astronomical analyses, systematic instrumental uncertainties have been generally ignored. This can be crucial to a proper interpretation of analysis results because instrumental calibration uncertainty is a form of systematic uncertainty. Ignoring it can underestimate error bars and introduce bias into the fitted values of model parameters. Accounting for such uncertainties currently requires extensive case-specific simulations if using existing analysis packages. Here, we present general statistical methods that incorporate calibration uncertainties into spectral analysis of high-energy data. We first present a method based on multiple imputation that can bemore » applied with any fitting method, but is necessarily approximate. We then describe a more exact Bayesian approach that works in conjunction with a Markov chain Monte Carlo based fitting. We explore methods for improving computational efficiency, and in particular detail a method of summarizing calibration uncertainties with a principal component analysis of samples of plausible calibration files. This method is implemented using recently codified Chandra effective area uncertainties for low-resolution spectral analysis and is verified using both simulated and actual Chandra data. Our procedure for incorporating effective area uncertainty is easily generalized to other types of calibration uncertainties.« less

SAGITTARIUS STREAM THREE-DIMENSIONAL KINEMATICS FROM SLOAN DIGITAL SKY SURVEY STRIPE 82

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

Koposov, Sergey E.; Belokurov, Vasily; Evans, N. Wyn

2013-04-01

Using multi-epoch observations of the Stripe 82 region from the Sloan Digital Sky Survey (SDSS), we measure precise statistical proper motions of the stars in the Sagittarius (Sgr) stellar stream. The multi-band photometry and SDSS radial velocities allow us to efficiently select Sgr members and thus enhance the proper-motion precision to {approx}0.1 mas yr{sup -1}. We measure separately the proper motion of a photometrically selected sample of the main-sequence turn-off stars, as well as spectroscopically selected Sgr giants. The data allow us to determine the proper motion separately for the two Sgr streams in the south found in Koposov etmore » al. Together with the precise velocities from SDSS, our proper motions provide exquisite constraints of the three-dimensional motions of the stars in the Sgr streams.« less

A Maximum Entropy Method for Particle Filtering

NASA Astrophysics Data System (ADS)

Eyink, Gregory L.; Kim, Sangil

2006-06-01

Standard ensemble or particle filtering schemes do not properly represent states of low priori probability when the number of available samples is too small, as is often the case in practical applications. We introduce here a set of parametric resampling methods to solve this problem. Motivated by a general H-theorem for relative entropy, we construct parametric models for the filter distributions as maximum-entropy/minimum-information models consistent with moments of the particle ensemble. When the prior distributions are modeled as mixtures of Gaussians, our method naturally generalizes the ensemble Kalman filter to systems with highly non-Gaussian statistics. We apply the new particle filters presented here to two simple test cases: a one-dimensional diffusion process in a double-well potential and the three-dimensional chaotic dynamical system of Lorenz.

Detecting central fixation by means of artificial neural networks in a pediatric vision screener using retinal birefringence scanning.

PubMed

Gramatikov, Boris I

2017-04-27

Reliable detection of central fixation and eye alignment is essential in the diagnosis of amblyopia ("lazy eye"), which can lead to blindness. Our lab has developed and reported earlier a pediatric vision screener that performs scanning of the retina around the fovea and analyzes changes in the polarization state of light as the scan progresses. Depending on the direction of gaze and the instrument design, the screener produces several signal frequencies that can be utilized in the detection of central fixation. The objective of this study was to compare artificial neural networks with classical statistical methods, with respect to their ability to detect central fixation reliably. A classical feedforward, pattern recognition, two-layer neural network architecture was used, consisting of one hidden layer and one output layer. The network has four inputs, representing normalized spectral powers at four signal frequencies generated during retinal birefringence scanning. The hidden layer contains four neurons. The output suggests presence or absence of central fixation. Backpropagation was used to train the network, using the gradient descent algorithm and the cross-entropy error as the performance function. The network was trained, validated and tested on a set of controlled calibration data obtained from 600 measurements from ten eyes in a previous study, and was additionally tested on a clinical set of 78 eyes, independently diagnosed by an ophthalmologist. In the first part of this study, a neural network was designed around the calibration set. With a proper architecture and training, the network provided performance that was comparable to classical statistical methods, allowing perfect separation between the central and paracentral fixation data, with both the sensitivity and the specificity of the instrument being 100%. In the second part of the study, the neural network was applied to the clinical data. It allowed reliable separation between normal subjects and affected subjects, its accuracy again matching that of the statistical methods. With a proper choice of a neural network architecture and a good, uncontaminated training data set, the artificial neural network can be an efficient classification tool for detecting central fixation based on retinal birefringence scanning.

22 CFR 505.2 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-04-01

... individual's name or personal identifier, such as a social security number. (g) Routine use. With respect to... proper and necessary uses even if any such uses occur infrequently. (h) Statistical record. A record in a system of records maintained for statistical research or reporting purposes only and not used in whole or...

A multimembership catalogue for 1876 open clusters using UCAC4 data

NASA Astrophysics Data System (ADS)

Sampedro, L.; Dias, W. S.; Alfaro, E. J.; Monteiro, H.; Molino, A.

2017-10-01

The main objective of this work is to determine the cluster members of 1876 open clusters, using positions and proper motions of the astrometric fourth United States Naval Observatory (USNO) CCD Astrograph Catalog (UCAC4). For this purpose, we apply three different methods, all based on a Bayesian approach, but with different formulations: a purely parametric method, another completely non-parametric algorithm and a third, recently developed by Sampedro & Alfaro, using both formulations at different steps of the whole process. The first and second statistical moments of the members' phase-space subspace, obtained after applying the three methods, are compared for every cluster. Although, on average, the three methods yield similar results, there are also specific differences between them, as well as for some particular clusters. The comparison with other published catalogues shows good agreement. We have also estimated, for the first time, the mean proper motion for a sample of 18 clusters. The results are organized in a single catalogue formed by two main files, one with the most relevant information for each cluster, partially including that in UCAC4, and the other showing the individual membership probabilities for each star in the cluster area. The final catalogue, with an interface design that enables an easy interaction with the user, is available in electronic format at the Stellar Systems Group (SSG-IAA) web site (http://ssg.iaa.es/en/content/sampedro-cluster-catalog).

Meta-analysis of haplotype-association studies: comparison of methods and empirical evaluation of the literature

PubMed Central

2011-01-01

Background Meta-analysis is a popular methodology in several fields of medical research, including genetic association studies. However, the methods used for meta-analysis of association studies that report haplotypes have not been studied in detail. In this work, methods for performing meta-analysis of haplotype association studies are summarized, compared and presented in a unified framework along with an empirical evaluation of the literature. Results We present multivariate methods that use summary-based data as well as methods that use binary and count data in a generalized linear mixed model framework (logistic regression, multinomial regression and Poisson regression). The methods presented here avoid the inflation of the type I error rate that could be the result of the traditional approach of comparing a haplotype against the remaining ones, whereas, they can be fitted using standard software. Moreover, formal global tests are presented for assessing the statistical significance of the overall association. Although the methods presented here assume that the haplotypes are directly observed, they can be easily extended to allow for such an uncertainty by weighting the haplotypes by their probability. Conclusions An empirical evaluation of the published literature and a comparison against the meta-analyses that use single nucleotide polymorphisms, suggests that the studies reporting meta-analysis of haplotypes contain approximately half of the included studies and produce significant results twice more often. We show that this excess of statistically significant results, stems from the sub-optimal method of analysis used and, in approximately half of the cases, the statistical significance is refuted if the data are properly re-analyzed. Illustrative examples of code are given in Stata and it is anticipated that the methods developed in this work will be widely applied in the meta-analysis of haplotype association studies. PMID:21247440

A Methodology for Anatomic Ultrasound Image Diagnostic Quality Assessment.

PubMed

Hemmsen, Martin Christian; Lange, Theis; Brandt, Andreas Hjelm; Nielsen, Michael Bachmann; Jensen, Jorgen Arendt

2017-01-01

This paper discusses the methods for the assessment of ultrasound image quality based on our experiences with evaluating new methods for anatomic imaging. It presents a methodology to ensure a fair assessment between competing imaging methods using clinically relevant evaluations. The methodology is valuable in the continuing process of method optimization and guided development of new imaging methods. It includes a three phased study plan covering from initial prototype development to clinical assessment. Recommendations to the clinical assessment protocol, software, and statistical analysis are presented. Earlier uses of the methodology has shown that it ensures validity of the assessment, as it separates the influences between developer, investigator, and assessor once a research protocol has been established. This separation reduces confounding influences on the result from the developer to properly reveal the clinical value. This paper exemplifies the methodology using recent studies of synthetic aperture sequential beamforming tissue harmonic imaging.

A new method for skin color enhancement

NASA Astrophysics Data System (ADS)

Zeng, Huanzhao; Luo, Ronnier

2012-01-01

Skin tone is the most important color category in memory colors. Reproducing it pleasingly is an important factor in photographic color reproduction. Moving skin colors toward their preferred skin color center improves the skin color preference on photographic color reproduction. Two key factors to successfully enhance skin colors are: a method to detect original skin colors effectively even if they are shifted far away from the regular skin color region, and a method to morph skin colors toward a preferred skin color region properly without introducing artifacts. A method for skin color enhancement presented by the authors in the same conference last year applies a static skin color model for skin color detection, which may miss to detect skin colors that are far away from regular skin tones. In this paper, a new method using the combination of face detection and statistical skin color modeling is proposed to effectively detect skin pixels and to enhance skin colors more effectively.

Effects of special composite stretching on the swing of amateur golf players

PubMed Central

Lee, Joong-chul; Lee, Sung-wan; Yeo, Yun-ghi; Park, Gi Duck

2015-01-01

[Purpose] The study investigated stretching for safer a golf swing compared to present stretching methods for proper swings in order to examine the effects of stretching exercises on golf swings. [Subjects] The subjects were 20 amateur golf club members who were divided into two groups: an experimental group which performed stretching, and a control group which did not. The subjects had no bone deformity, muscle weakness, muscle soreness, or neurological problems. [Methods] A swing analyzer and a ROM measuring instrument were used as the measuring tools. The swing analyzer was a GS400-golf hit ball analyzer (Korea) and the ROM measuring instrument was a goniometer (Korea). [Results] The experimental group showed a statistically significant improvement in driving distance. After the special stretching training for golf, a statistically significant difference in hit-ball direction deviation after swings were found between the groups. The experimental group showed statistically significant decreases in hit ball direction deviation. After the special stretching training for golf, statistically significant differences in hit-ball speed were found between the groups. The experimental group showed significant increases in hit-ball speed. [Conclusion] To examine the effects of a special stretching program for golf on golf swing-related factors, 20 male amateur golf club members performed a 12-week stretching training program. After the golf stretching training, statistically significant differences were found between the groups in hit-ball driving distance, direction deviation, deflection distance, and speed. PMID:25995553

Effects of special composite stretching on the swing of amateur golf players.

PubMed

Lee, Joong-Chul; Lee, Sung-Wan; Yeo, Yun-Ghi; Park, Gi Duck

2015-04-01

[Purpose] The study investigated stretching for safer a golf swing compared to present stretching methods for proper swings in order to examine the effects of stretching exercises on golf swings. [Subjects] The subjects were 20 amateur golf club members who were divided into two groups: an experimental group which performed stretching, and a control group which did not. The subjects had no bone deformity, muscle weakness, muscle soreness, or neurological problems. [Methods] A swing analyzer and a ROM measuring instrument were used as the measuring tools. The swing analyzer was a GS400-golf hit ball analyzer (Korea) and the ROM measuring instrument was a goniometer (Korea). [Results] The experimental group showed a statistically significant improvement in driving distance. After the special stretching training for golf, a statistically significant difference in hit-ball direction deviation after swings were found between the groups. The experimental group showed statistically significant decreases in hit ball direction deviation. After the special stretching training for golf, statistically significant differences in hit-ball speed were found between the groups. The experimental group showed significant increases in hit-ball speed. [Conclusion] To examine the effects of a special stretching program for golf on golf swing-related factors, 20 male amateur golf club members performed a 12-week stretching training program. After the golf stretching training, statistically significant differences were found between the groups in hit-ball driving distance, direction deviation, deflection distance, and speed.

A data-driven approach to quality risk management

PubMed Central

Alemayehu, Demissie; Alvir, Jose; Levenstein, Marcia; Nickerson, David

2013-01-01

Aim: An effective clinical trial strategy to ensure patient safety as well as trial quality and efficiency involves an integrated approach, including prospective identification of risk factors, mitigation of the risks through proper study design and execution, and assessment of quality metrics in real-time. Such an integrated quality management plan may also be enhanced by using data-driven techniques to identify risk factors that are most relevant in predicting quality issues associated with a trial. In this paper, we illustrate such an approach using data collected from actual clinical trials. Materials and Methods: Several statistical methods were employed, including the Wilcoxon rank-sum test and logistic regression, to identify the presence of association between risk factors and the occurrence of quality issues, applied to data on quality of clinical trials sponsored by Pfizer. Results: Only a subset of the risk factors had a significant association with quality issues, and included: Whether study used Placebo, whether an agent was a biologic, unusual packaging label, complex dosing, and over 25 planned procedures. Conclusion: Proper implementation of the strategy can help to optimize resource utilization without compromising trial integrity and patient safety. PMID:24312890

A bivariate contaminated binormal model for robust fitting of proper ROC curves to a pair of correlated, possibly degenerate, ROC datasets.

PubMed

Zhai, Xuetong; Chakraborty, Dev P

2017-06-01

The objective was to design and implement a bivariate extension to the contaminated binormal model (CBM) to fit paired receiver operating characteristic (ROC) datasets-possibly degenerate-with proper ROC curves. Paired datasets yield two correlated ratings per case. Degenerate datasets have no interior operating points and proper ROC curves do not inappropriately cross the chance diagonal. The existing method, developed more than three decades ago utilizes a bivariate extension to the binormal model, implemented in CORROC2 software, which yields improper ROC curves and cannot fit degenerate datasets. CBM can fit proper ROC curves to unpaired (i.e., yielding one rating per case) and degenerate datasets, and there is a clear scientific need to extend it to handle paired datasets. In CBM, nondiseased cases are modeled by a probability density function (pdf) consisting of a unit variance peak centered at zero. Diseased cases are modeled with a mixture distribution whose pdf consists of two unit variance peaks, one centered at positive μ with integrated probability α, the mixing fraction parameter, corresponding to the fraction of diseased cases where the disease was visible to the radiologist, and one centered at zero, with integrated probability (1-α), corresponding to disease that was not visible. It is shown that: (a) for nondiseased cases the bivariate extension is a unit variances bivariate normal distribution centered at (0,0) with a specified correlation ρ 1 ; (b) for diseased cases the bivariate extension is a mixture distribution with four peaks, corresponding to disease not visible in either condition, disease visible in only one condition, contributing two peaks, and disease visible in both conditions. An expression for the likelihood function is derived. A maximum likelihood estimation (MLE) algorithm, CORCBM, was implemented in the R programming language that yields parameter estimates and the covariance matrix of the parameters, and other statistics. A limited simulation validation of the method was performed. CORCBM and CORROC2 were applied to two datasets containing nine readers each contributing paired interpretations. CORCBM successfully fitted the data for all readers, whereas CORROC2 failed to fit a degenerate dataset. All fits were visually reasonable. All CORCBM fits were proper, whereas all CORROC2 fits were improper. CORCBM and CORROC2 were in agreement (a) in declaring only one of the nine readers as having significantly different performances in the two modalities; (b) in estimating higher correlations for diseased cases than for nondiseased ones; and (c) in finding that the intermodality correlation estimates for nondiseased cases were consistent between the two methods. All CORCBM fits yielded higher area under curve (AUC) than the CORROC2 fits, consistent with the fact that a proper ROC model like CORCBM is based on a likelihood-ratio-equivalent decision variable, and consequently yields higher performance than the binormal model-based CORROC2. The method gave satisfactory fits to four simulated datasets. CORCBM is a robust method for fitting paired ROC datasets, always yielding proper ROC curves, and able to fit degenerate datasets. © 2017 American Association of Physicists in Medicine.

The Statistical Segment Length of DNA: Opportunities for Biomechanical Modeling in Polymer Physics and Next-Generation Genomics.

PubMed

Dorfman, Kevin D

2018-02-01

The development of bright bisintercalating dyes for deoxyribonucleic acid (DNA) in the 1990s, most notably YOYO-1, revolutionized the field of polymer physics in the ensuing years. These dyes, in conjunction with modern molecular biology techniques, permit the facile observation of polymer dynamics via fluorescence microscopy and thus direct tests of different theories of polymer dynamics. At the same time, they have played a key role in advancing an emerging next-generation method known as genome mapping in nanochannels. The effect of intercalation on the bending energy of DNA as embodied by a change in its statistical segment length (or, alternatively, its persistence length) has been the subject of significant controversy. The precise value of the statistical segment length is critical for the proper interpretation of polymer physics experiments and controls the phenomena underlying the aforementioned genomics technology. In this perspective, we briefly review the model of DNA as a wormlike chain and a trio of methods (light scattering, optical or magnetic tweezers, and atomic force microscopy (AFM)) that have been used to determine the statistical segment length of DNA. We then outline the disagreement in the literature over the role of bisintercalation on the bending energy of DNA, and how a multiscale biomechanical approach could provide an important model for this scientifically and technologically relevant problem.

Descriptive Statistics of the Genome: Phylogenetic Classification of Viruses.

PubMed

Hernandez, Troy; Yang, Jie

2016-10-01

The typical process for classifying and submitting a newly sequenced virus to the NCBI database involves two steps. First, a BLAST search is performed to determine likely family candidates. That is followed by checking the candidate families with the pairwise sequence alignment tool for similar species. The submitter's judgment is then used to determine the most likely species classification. The aim of this article is to show that this process can be automated into a fast, accurate, one-step process using the proposed alignment-free method and properly implemented machine learning techniques. We present a new family of alignment-free vectorizations of the genome, the generalized vector, that maintains the speed of existing alignment-free methods while outperforming all available methods. This new alignment-free vectorization uses the frequency of genomic words (k-mers), as is done in the composition vector, and incorporates descriptive statistics of those k-mers' positional information, as inspired by the natural vector. We analyze five different characterizations of genome similarity using k-nearest neighbor classification and evaluate these on two collections of viruses totaling over 10,000 viruses. We show that our proposed method performs better than, or as well as, other methods at every level of the phylogenetic hierarchy. The data and R code is available upon request.

Can bias correction and statistical downscaling methods improve the skill of seasonal precipitation forecasts?

NASA Astrophysics Data System (ADS)

Manzanas, R.; Lucero, A.; Weisheimer, A.; Gutiérrez, J. M.

2018-02-01

Statistical downscaling methods are popular post-processing tools which are widely used in many sectors to adapt the coarse-resolution biased outputs from global climate simulations to the regional-to-local scale typically required by users. They range from simple and pragmatic Bias Correction (BC) methods, which directly adjust the model outputs of interest (e.g. precipitation) according to the available local observations, to more complex Perfect Prognosis (PP) ones, which indirectly derive local predictions (e.g. precipitation) from appropriate upper-air large-scale model variables (predictors). Statistical downscaling methods have been extensively used and critically assessed in climate change applications; however, their advantages and limitations in seasonal forecasting are not well understood yet. In particular, a key problem in this context is whether they serve to improve the forecast quality/skill of raw model outputs beyond the adjustment of their systematic biases. In this paper we analyze this issue by applying two state-of-the-art BC and two PP methods to downscale precipitation from a multimodel seasonal hindcast in a challenging tropical region, the Philippines. To properly assess the potential added value beyond the reduction of model biases, we consider two validation scores which are not sensitive to changes in the mean (correlation and reliability categories). Our results show that, whereas BC methods maintain or worsen the skill of the raw model forecasts, PP methods can yield significant skill improvement (worsening) in cases for which the large-scale predictor variables considered are better (worse) predicted by the model than precipitation. For instance, PP methods are found to increase (decrease) model reliability in nearly 40% of the stations considered in boreal summer (autumn). Therefore, the choice of a convenient downscaling approach (either BC or PP) depends on the region and the season.

Data Analysis and Data Mining: Current Issues in Biomedical Informatics

PubMed Central

Bellazzi, Riccardo; Diomidous, Marianna; Sarkar, Indra Neil; Takabayashi, Katsuhiko; Ziegler, Andreas; McCray, Alexa T.

2011-01-01

Summary Background Medicine and biomedical sciences have become data-intensive fields, which, at the same time, enable the application of data-driven approaches and require sophisticated data analysis and data mining methods. Biomedical informatics provides a proper interdisciplinary context to integrate data and knowledge when processing available information, with the aim of giving effective decision-making support in clinics and translational research. Objectives To reflect on different perspectives related to the role of data analysis and data mining in biomedical informatics. Methods On the occasion of the 50th year of Methods of Information in Medicine a symposium was organized, that reflected on opportunities, challenges and priorities of organizing, representing and analysing data, information and knowledge in biomedicine and health care. The contributions of experts with a variety of backgrounds in the area of biomedical data analysis have been collected as one outcome of this symposium, in order to provide a broad, though coherent, overview of some of the most interesting aspects of the field. Results The paper presents sections on data accumulation and data-driven approaches in medical informatics, data and knowledge integration, statistical issues for the evaluation of data mining models, translational bioinformatics and bioinformatics aspects of genetic epidemiology. Conclusions Biomedical informatics represents a natural framework to properly and effectively apply data analysis and data mining methods in a decision-making context. In the future, it will be necessary to preserve the inclusive nature of the field and to foster an increasing sharing of data and methods between researchers. PMID:22146916

Estimation of Signal Coherence Threshold and Concealed Spectral Lines Applied to Detection of Turbofan Engine Combustion Noise

NASA Technical Reports Server (NTRS)

Miles, Jeffrey Hilton

2010-01-01

Combustion noise from turbofan engines has become important, as the noise from sources like the fan and jet are reduced. An aligned and un-aligned coherence technique has been developed to determine a threshold level for the coherence and thereby help to separate the coherent combustion noise source from other noise sources measured with far-field microphones. This method is compared with a statistics based coherence threshold estimation method. In addition, the un-aligned coherence procedure at the same time also reveals periodicities, spectral lines, and undamped sinusoids hidden by broadband turbofan engine noise. In calculating the coherence threshold using a statistical method, one may use either the number of independent records or a larger number corresponding to the number of overlapped records used to create the average. Using data from a turbofan engine and a simulation this paper shows that applying the Fisher z-transform to the un-aligned coherence can aid in making the proper selection of samples and produce a reasonable statistics based coherence threshold. Examples are presented showing that the underlying tonal and coherent broad band structure which is buried under random broadband noise and jet noise can be determined. The method also shows the possible presence of indirect combustion noise. Copyright 2011 Acoustical Society of America. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the Acoustical Society of America.

Bayesian models: A statistical primer for ecologists

USGS Publications Warehouse

Hobbs, N. Thompson; Hooten, Mevin B.

2015-01-01

Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods—in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach.Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probability and develops a step-by-step sequence of connected ideas, including basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and inference from single and multiple models. This unique book places less emphasis on computer coding, favoring instead a concise presentation of the mathematical statistics needed to understand how and why Bayesian analysis works. It also explains how to write out properly formulated hierarchical Bayesian models and use them in computing, research papers, and proposals.This primer enables ecologists to understand the statistical principles behind Bayesian modeling and apply them to research, teaching, policy, and management.Presents the mathematical and statistical foundations of Bayesian modeling in language accessible to non-statisticiansCovers basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and moreDeemphasizes computer coding in favor of basic principlesExplains how to write out properly factored statistical expressions representing Bayesian models

The prior statistics of object colors.

PubMed

Koenderink, Jan J

2010-02-01

The prior statistics of object colors is of much interest because extensive statistical investigations of reflectance spectra reveal highly non-uniform structure in color space common to several very different databases. This common structure is due to the visual system rather than to the statistics of environmental structure. Analysis involves an investigation of the proper sample space of spectral reflectance factors and of the statistical consequences of the projection of spectral reflectances on the color solid. Even in the case of reflectance statistics that are translationally invariant with respect to the wavelength dimension, the statistics of object colors is highly non-uniform. The qualitative nature of this non-uniformity is due to trichromacy.

An Attempt at Quantifying Factors that Affect Efficiency in the Management of Solid Waste Produced by Commercial Businesses in the City of Tshwane, South Africa

PubMed Central

Worku, Yohannes; Muchie, Mammo

2012-01-01

Objective. The objective was to investigate factors that affect the efficient management of solid waste produced by commercial businesses operating in the city of Pretoria, South Africa. Methods. Data was gathered from 1,034 businesses. Efficiency in solid waste management was assessed by using a structural time-based model designed for evaluating efficiency as a function of the length of time required to manage waste. Data analysis was performed using statistical procedures such as frequency tables, Pearson's chi-square tests of association, and binary logistic regression analysis. Odds ratios estimated from logistic regression analysis were used for identifying key factors that affect efficiency in the proper disposal of waste. Results. The study showed that 857 of the 1,034 businesses selected for the study (83%) were found to be efficient enough with regards to the proper collection and disposal of solid waste. Based on odds ratios estimated from binary logistic regression analysis, efficiency in the proper management of solid waste was significantly influenced by 4 predictor variables. These 4 influential predictor variables are lack of adherence to waste management regulations, wrong perception, failure to provide customers with enough trash cans, and operation of businesses by employed managers, in a decreasing order of importance. PMID:23209483

Modeling of carbon dioxide condensation in the high pressure flows using the statistical BGK approach

NASA Astrophysics Data System (ADS)

Kumar, Rakesh; Li, Zheng; Levin, Deborah A.

2011-05-01

In this work, we propose a new heat accommodation model to simulate freely expanding homogeneous condensation flows of gaseous carbon dioxide using a new approach, the statistical Bhatnagar-Gross-Krook method. The motivation for the present work comes from the earlier work of Li et al. [J. Phys. Chem. 114, 5276 (2010)] in which condensation models were proposed and used in the direct simulation Monte Carlo method to simulate the flow of carbon dioxide from supersonic expansions of small nozzles into near-vacuum conditions. Simulations conducted for stagnation pressures of one and three bar were compared with the measurements of gas and cluster number densities, cluster size, and carbon dioxide rotational temperature obtained by Ramos et al. [Phys. Rev. A 72, 3204 (2005)]. Due to the high computational cost of direct simulation Monte Carlo method, comparison between simulations and data could only be performed for these stagnation pressures, with good agreement obtained beyond the condensation onset point, in the farfield. As the stagnation pressure increases, the degree of condensation also increases; therefore, to improve the modeling of condensation onset, one must be able to simulate higher stagnation pressures. In simulations of an expanding flow of argon through a nozzle, Kumar et al. [AIAA J. 48, 1531 (2010)] found that the statistical Bhatnagar-Gross-Krook method provides the same accuracy as direct simulation Monte Carlo method, but, at one half of the computational cost. In this work, the statistical Bhatnagar-Gross-Krook method was modified to account for internal degrees of freedom for multi-species polyatomic gases. With the computational approach in hand, we developed and tested a new heat accommodation model for a polyatomic system to properly account for the heat release of condensation. We then developed condensation models in the framework of the statistical Bhatnagar-Gross-Krook method. Simulations were found to agree well with the experiment for all stagnation pressure cases (1-5 bar), validating the accuracy of the Bhatnagar-Gross-Krook based condensation model in capturing the physics of condensation.

Using the U.S. Geological Survey National Water Quality Laboratory LT-MDL to Evaluate and Analyze Data

USGS Publications Warehouse

Bonn, Bernadine A.

2008-01-01

A long-term method detection level (LT-MDL) and laboratory reporting level (LRL) are used by the U.S. Geological Survey?s National Water Quality Laboratory (NWQL) when reporting results from most chemical analyses of water samples. Changing to this method provided data users with additional information about their data and often resulted in more reported values in the low concentration range. Before this method was implemented, many of these values would have been censored. The use of the LT-MDL and LRL presents some challenges for the data user. Interpreting data in the low concentration range increases the need for adequate quality assurance because even small contamination or recovery problems can be relatively large compared to concentrations near the LT-MDL and LRL. In addition, the definition of the LT-MDL, as well as the inclusion of low values, can result in complex data sets with multiple censoring levels and reported values that are less than a censoring level. Improper interpretation or statistical manipulation of low-range results in these data sets can result in bias and incorrect conclusions. This document is designed to help data users use and interpret data reported with the LTMDL/ LRL method. The calculation and application of the LT-MDL and LRL are described. This document shows how to extract statistical information from the LT-MDL and LRL and how to use that information in USGS investigations, such as assessing the quality of field data, interpreting field data, and planning data collection for new projects. A set of 19 detailed examples are included in this document to help data users think about their data and properly interpret lowrange data without introducing bias. Although this document is not meant to be a comprehensive resource of statistical methods, several useful methods of analyzing censored data are demonstrated, including Regression on Order Statistics and Kaplan-Meier Estimation. These two statistical methods handle complex censored data sets without resorting to substitution, thereby avoiding a common source of bias and inaccuracy.

On the Occurrence of Wide Binaries in the Local Disk and Halo Populations

NASA Astrophysics Data System (ADS)

Hartman, Zachary; Lepine, Sebastien

2018-01-01

We present results from our search for wide binaries in the SUPERBLINK+GAIA all-sky catalog of 2.8 million high proper motion stars (μ>40 mas/yr). Through a Bayesian analysis of common proper motion pairs, we have identified highly probable wide binary/multiple systems based on statistics of their proper motion differences and angular separations. Using a reduced proper motion diagram, we determine whether these wide are part of the young disk, old disk, or Galactic halo population. We examine the relative occurrence rate for very wide companions in these respective populations. All groups are found to contain a significant number of wide binary systems, with about 1 percent of the stars in each group having pairs with separations >1,000 AU.

Multifractal analysis of mobile social networks

NASA Astrophysics Data System (ADS)

Zheng, Wei; Zhang, Zifeng; Deng, Yufan

2017-09-01

As Wireless Fidelity (Wi-Fi)-enabled handheld devices have been widely used, the mobile social networks (MSNs) has been attracting extensive attention. Fractal approaches have also been widely applied to characterierize natural networks as useful tools to depict their spatial distribution and scaling properties. Moreover, when the complexity of the spatial distribution of MSNs cannot be properly charaterized by single fractal dimension, multifractal analysis is required. For further research, we introduced a multifractal analysis method based on box-covering algorithm to describe the structure of MSNs. Using this method, we find that the networks are multifractal at different time interval. The simulation results demonstrate that the proposed method is efficient for analyzing the multifractal characteristic of MSNs, which provides a distribution of singularities adequately describing both the heterogeneity of fractal patterns and the statistics of measurements across spatial scales in MSNs.

Segment and fit thresholding: a new method for image analysis applied to microarray and immunofluorescence data.

PubMed

Ensink, Elliot; Sinha, Jessica; Sinha, Arkadeep; Tang, Huiyuan; Calderone, Heather M; Hostetter, Galen; Winter, Jordan; Cherba, David; Brand, Randall E; Allen, Peter J; Sempere, Lorenzo F; Haab, Brian B

2015-10-06

Experiments involving the high-throughput quantification of image data require algorithms for automation. A challenge in the development of such algorithms is to properly interpret signals over a broad range of image characteristics, without the need for manual adjustment of parameters. Here we present a new approach for locating signals in image data, called Segment and Fit Thresholding (SFT). The method assesses statistical characteristics of small segments of the image and determines the best-fit trends between the statistics. Based on the relationships, SFT identifies segments belonging to background regions; analyzes the background to determine optimal thresholds; and analyzes all segments to identify signal pixels. We optimized the initial settings for locating background and signal in antibody microarray and immunofluorescence data and found that SFT performed well over multiple, diverse image characteristics without readjustment of settings. When used for the automated analysis of multicolor, tissue-microarray images, SFT correctly found the overlap of markers with known subcellular localization, and it performed better than a fixed threshold and Otsu's method for selected images. SFT promises to advance the goal of full automation in image analysis.

Segment and Fit Thresholding: A New Method for Image Analysis Applied to Microarray and Immunofluorescence Data

PubMed Central

Ensink, Elliot; Sinha, Jessica; Sinha, Arkadeep; Tang, Huiyuan; Calderone, Heather M.; Hostetter, Galen; Winter, Jordan; Cherba, David; Brand, Randall E.; Allen, Peter J.; Sempere, Lorenzo F.; Haab, Brian B.

2016-01-01

Certain experiments involve the high-throughput quantification of image data, thus requiring algorithms for automation. A challenge in the development of such algorithms is to properly interpret signals over a broad range of image characteristics, without the need for manual adjustment of parameters. Here we present a new approach for locating signals in image data, called Segment and Fit Thresholding (SFT). The method assesses statistical characteristics of small segments of the image and determines the best-fit trends between the statistics. Based on the relationships, SFT identifies segments belonging to background regions; analyzes the background to determine optimal thresholds; and analyzes all segments to identify signal pixels. We optimized the initial settings for locating background and signal in antibody microarray and immunofluorescence data and found that SFT performed well over multiple, diverse image characteristics without readjustment of settings. When used for the automated analysis of multi-color, tissue-microarray images, SFT correctly found the overlap of markers with known subcellular localization, and it performed better than a fixed threshold and Otsu’s method for selected images. SFT promises to advance the goal of full automation in image analysis. PMID:26339978

Undergraduate medical students’ perceptions, attitudes, and competencies in evidence-based medicine (EBM), and their understanding of EBM reality in Syria

PubMed Central

2012-01-01

Background Teaching evidence-based medicine (EBM) should be evaluated and guided by evidence of its own effectiveness. However, no data are available on adoption of EBM by Syrian undergraduate, postgraduate, or practicing physicians. In fact, the teaching of EBM in Syria is not yet a part of undergraduate medical curricula. The authors evaluated education of evidence-based medicine through a two-day intensive training course. Methods The authors evaluated education of evidence-based medicine through a two-day intensive training course that took place in 2011. The course included didactic lectures as well as interactive hands-on workshops on all topics of EBM. A comprehensive questionnaire, that included the Berlin questionnaire, was used to inspect medical students’ awareness of, attitudes toward, and competencies’ in EBM. Results According to students, problems facing proper EBM practice in Syria were the absence of the following: an EBM teaching module in medical school curriculum (94%), role models among professors and instructors (92%), a librarian (70%), institutional subscription to medical journals (94%), and sufficient IT hardware (58%). After the course, there was a statistically significant increase in medical students' perceived ability to go through steps of EBM, namely: formulating PICO questions (56.9%), searching for evidence (39.8%), appraising the evidence (27.3%), understanding statistics (48%), and applying evidence at point of care (34.1%). However, mean increase in Berlin scores after the course was 2.68, a non-statistically significant increase of 17.86%. Conclusion The road to a better EBM reality in Syria starts with teaching EBM in medical school and developing the proper environment to facilitate transforming current medical education and practice to an evidence-based standard in Syria. PMID:22882872

Linear models: permutation methods

USGS Publications Warehouse

Cade, B.S.; Everitt, B.S.; Howell, D.C.

2005-01-01

Permutation tests (see Permutation Based Inference) for the linear model have applications in behavioral studies when traditional parametric assumptions about the error term in a linear model are not tenable. Improved validity of Type I error rates can be achieved with properly constructed permutation tests. Perhaps more importantly, increased statistical power, improved robustness to effects of outliers, and detection of alternative distributional differences can be achieved by coupling permutation inference with alternative linear model estimators. For example, it is well-known that estimates of the mean in linear model are extremely sensitive to even a single outlying value of the dependent variable compared to estimates of the median [7, 19]. Traditionally, linear modeling focused on estimating changes in the center of distributions (means or medians). However, quantile regression allows distributional changes to be estimated in all or any selected part of a distribution or responses, providing a more complete statistical picture that has relevance to many biological questions [6]...

The North American Forest Database: going beyond national-level forest resource assessment statistics.

PubMed

Smith, W Brad; Cuenca Lara, Rubí Angélica; Delgado Caballero, Carina Edith; Godínez Valdivia, Carlos Isaías; Kapron, Joseph S; Leyva Reyes, Juan Carlos; Meneses Tovar, Carmen Lourdes; Miles, Patrick D; Oswalt, Sonja N; Ramírez Salgado, Mayra; Song, Xilong Alex; Stinson, Graham; Villela Gaytán, Sergio Armando

2018-05-21

Forests cannot be managed sustainably without reliable data to inform decisions. National Forest Inventories (NFI) tend to report national statistics, with sub-national stratification based on domestic ecological classification systems. It is becoming increasingly important to be able to report statistics on ecosystems that span international borders, as global change and globalization expand stakeholders' spheres of concern. The state of a transnational ecosystem can only be properly assessed by examining the entire ecosystem. In global forest resource assessments, it may be useful to break national statistics down by ecosystem, especially for large countries. The Inventory and Monitoring Working Group (IMWG) of the North American Forest Commission (NAFC) has begun developing a harmonized North American Forest Database (NAFD) for managing forest inventory data, enabling consistent, continental-scale forest assessment supporting ecosystem-level reporting and relational queries. The first iteration of the database contains data describing 1.9 billion ha, including 677.5 million ha of forest. Data harmonization is made challenging by the existence of definitions and methodologies tailored to suit national circumstances, emerging from each country's professional forestry development. This paper reports the methods used to synchronize three national forest inventories, starting with a small suite of variables and attributes.

Statistical considerations on prognostic models for glioma

PubMed Central

Molinaro, Annette M.; Wrensch, Margaret R.; Jenkins, Robert B.; Eckel-Passow, Jeanette E.

2016-01-01

Given the lack of beneficial treatments in glioma, there is a need for prognostic models for therapeutic decision making and life planning. Recently several studies defining subtypes of glioma have been published. Here, we review the statistical considerations of how to build and validate prognostic models, explain the models presented in the current glioma literature, and discuss advantages and disadvantages of each model. The 3 statistical considerations to establishing clinically useful prognostic models are: study design, model building, and validation. Careful study design helps to ensure that the model is unbiased and generalizable to the population of interest. During model building, a discovery cohort of patients can be used to choose variables, construct models, and estimate prediction performance via internal validation. Via external validation, an independent dataset can assess how well the model performs. It is imperative that published models properly detail the study design and methods for both model building and validation. This provides readers the information necessary to assess the bias in a study, compare other published models, and determine the model's clinical usefulness. As editors, reviewers, and readers of the relevant literature, we should be cognizant of the needed statistical considerations and insist on their use. PMID:26657835

In pursuit of a science of agriculture: the role of statistics in field experiments.

PubMed

Parolini, Giuditta

2015-09-01

Since the beginning of the twentieth century statistics has reshaped the experimental cultures of agricultural research taking part in the subtle dialectic between the epistemic and the material that is proper to experimental systems. This transformation has become especially relevant in field trials and the paper will examine the British agricultural institution, Rothamsted Experimental Station, where statistical methods nowadays popular in the planning and analysis of field experiments were developed in the 1920s. At Rothamsted statistics promoted randomisation over systematic arrangements, factorisation over one-question trials, and emphasised the importance of the experimental error in assessing field trials. These changes in methodology transformed also the material culture of agricultural science, and a new body, the Field Plots Committee, was created to manage the field research of the agricultural institution. Although successful, the vision of field experimentation proposed by the Rothamsted statisticians was not unproblematic. Experimental scientists closely linked to the farming community questioned it in favour of a field research that could be more easily understood by farmers. The clash between the two agendas reveals how the role attributed to statistics in field experimentation defined different pursuits of agricultural research, alternately conceived of as a scientists' science or as a farmers' science.

Proper and Paradigmatic Metonymy as a Lens for Characterizing Student Conceptions of Distributions and Sampling

ERIC Educational Resources Information Center

Noll, Jennifer; Hancock, Stacey

2015-01-01

This research investigates what students' use of statistical language can tell us about their conceptions of distribution and sampling in relation to informal inference. Prior research documents students' challenges in understanding ideas of distribution and sampling as tools for making informal statistical inferences. We know that these…

Environmentally safe areas and routes in the Baltic proper using Eulerian tracers.

PubMed

Höglund, A; Meier, H E M

2012-07-01

In recent years, the shipping of environmentally hazardous cargo has increased considerably in the Baltic proper. In this study, a large number of hypothetical oil spills with an idealized, passive tracer are simulated. From the tracer distributions, statistical measures are calculated to optimize the quantity of tracer from a spill that would stay at sea as long as possible. Increased time may permit action to be taken against the spill before the oil reaches environmentally vulnerable coastal zones. The statistical measures are used to calculate maritime routes with maximum probability that an oil spill will stay at sea as long as possible. Under these assumptions, ships should follow routes that are located south of Bornholm instead of the northern routes in use currently. Our results suggest that the location of the optimal maritime routes depends on the season, although interannual variability is too large to identify statistically significant changes. Copyright © 2012. Published by Elsevier Ltd.

Improved Diagnostic Accuracy of SPECT Through Statistical Analysis and the Detection of Hot Spots at the Primary Sensorimotor Area for the Diagnosis of Alzheimer Disease in a Community-Based Study: "The Osaki-Tajiri Project".

PubMed

Kaneta, Tomohiro; Nakatsuka, Masahiro; Nakamura, Kei; Seki, Takashi; Yamaguchi, Satoshi; Tsuboi, Masahiro; Meguro, Kenichi

2016-01-01

SPECT is an important diagnostic tool for dementia. Recently, statistical analysis of SPECT has been commonly used for dementia research. In this study, we evaluated the accuracy of visual SPECT evaluation and/or statistical analysis for the diagnosis (Dx) of Alzheimer disease (AD) and other forms of dementia in our community-based study "The Osaki-Tajiri Project." Eighty-nine consecutive outpatients with dementia were enrolled and underwent brain perfusion SPECT with 99mTc-ECD. Diagnostic accuracy of SPECT was tested using 3 methods: visual inspection (SPECT Dx), automated diagnostic tool using statistical analysis with easy Z-score imaging system (eZIS Dx), and visual inspection plus eZIS (integrated Dx). Integrated Dx showed the highest sensitivity, specificity, and accuracy, whereas eZIS was the second most accurate method. We also observed that a higher than expected rate of SPECT images indicated false-negative cases of AD. Among these, 50% showed hypofrontality and were diagnosed as frontotemporal lobar degeneration. These cases typically showed regional "hot spots" in the primary sensorimotor cortex (ie, a sensorimotor hot spot sign), which we determined were associated with AD rather than frontotemporal lobar degeneration. We concluded that the diagnostic abilities were improved by the integrated use of visual assessment and statistical analysis. In addition, the detection of a sensorimotor hot spot sign was useful to detect AD when hypofrontality is present and improved the ability to properly diagnose AD.

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

The Optical Gravitational Lensing Experiment. The Catalog of Stellar Proper Motions toward the Magellanic Clouds

NASA Astrophysics Data System (ADS)

Poleski, R.; Soszyński, I.; Udalski, A.; Szymański, M. K.; Kubiak, M.; Pietrzyński, G.; Wyrzykowski, Ł.; Ulaczyk, K.

2012-03-01

We present a catalog of over 6.2 million stars with measured proper motions. All these stars are observed in the direction of the Magellanic Clouds within the brightness range 12

Conducting tests for statistically significant differences using forest inventory data

Treesearch

James A. Westfall; Scott A. Pugh; John W. Coulston

2013-01-01

Many forest inventory and monitoring programs are based on a sample of ground plots from which estimates of forest resources are derived. In addition to evaluating metrics such as number of trees or amount of cubic wood volume, it is often desirable to make comparisons between resource attributes. To properly conduct statistical tests for differences, it is imperative...

Overcoming urban GPS navigation challenges through the use of MEMS inertial sensors and proper verification of navigation system performance

NASA Astrophysics Data System (ADS)

Vinande, Eric T.

This research proposes several means to overcome challenges in the urban environment to ground vehicle global positioning system (GPS) receiver navigation performance through the integration of external sensor information. The effects of narrowband radio frequency interference and signal attenuation, both common in the urban environment, are examined with respect to receiver signal tracking processes. Low-cost microelectromechanical systems (MEMS) inertial sensors, suitable for the consumer market, are the focus of receiver augmentation as they provide an independent measure of motion and are independent of vehicle systems. A method for estimating the mounting angles of an inertial sensor cluster utilizing typical urban driving maneuvers is developed and is able to provide angular measurements within two degrees of truth. The integration of GPS and MEMS inertial sensors is developed utilizing a full state navigation filter. Appropriate statistical methods are developed to evaluate the urban environment navigation improvement due to the addition of MEMS inertial sensors. A receiver evaluation metric that combines accuracy, availability, and maximum error measurements is presented and evaluated over several drive tests. Following a description of proper drive test techniques, record and playback systems are evaluated as the optimal way of testing multiple receivers and/or integrated navigation systems in the urban environment as they simplify vehicle testing requirements.

Kinematics of our Galaxy from the PMA and TGAS catalogues

NASA Astrophysics Data System (ADS)

Velichko, Anna B.; Akhmetov, Volodymyr S.; Fedorov, Peter N.

2018-04-01

We derive and compare kinematic parameters of the Galaxy using the PMA and Gaia TGAS data. Two methods are used in calculations: evaluation of the Ogorodnikov-Milne model (OMM) parameters by the least square method (LSM) and a decomposition on a set of vector spherical harmonics (VSH). We trace dependencies on the distance of the derived parameters including the Oort constants A and B and the rotational velocity of the Galaxy V rot at the Solar distance for the common sample of stars of mixed spectral composition of the PMA and TGAS catalogues. The distances were obtained from the TGAS parallaxes or from reduced proper motions for fainter stars. The A, B and V rot parameters derived from proper motions of both catalogues used show identical behaviour but the values are systematically shifted by about 0.5 mas/yr. The Oort B parameter derived from the PMA sample of red giants shows gradual decrease with increasing the distance while the Oort A has a minimum at about 2 kpc and then gradually increases. As for models chosen for calculations, first, we confirm conclusions of other authors about the existence of extra-model harmonics in the stellar velocity field. Secondly, not all parameters of the OMM are statistically significant, and the set of parameters depends on the stellar sample used.

Better understanding of digital photography for skin color measurement: With a special emphasis on light characteristics.

PubMed

Seo, Soo Hong; Kim, Jae Hwan; Kim, Ji Woong; Kye, Young Chul; Ahn, Hyo Hyun

2011-02-01

Digital photography can be used to measure skin color colorimetrically when combined with proper techniques. To better understand the settings of digital photography for the evaluation and measurement of skin colors, we used a tungsten lamp with filters and the custom white balance (WB) function of a digital camera. All colored squares on a color chart were photographed with each original and filtered light, analyzed into CIELAB coordinates to produce the calibration method for each given light setting, and compared statistically with reference coordinates obtained using a reflectance spectrophotometer. They were summarized as to the typical color groups, such as skin colors. We compared these results according to the fixed vs. custom WB of a digital camera. The accuracy of color measurement was improved when using light with a proper color temperature conversion filter. The skin colors from color charts could be measured more accurately using a fixed WB. In vivo measurement of skin color was easy and possible with our method and settings. The color temperature conversion filter that produced daylight-like light from the tungsten lamp was the best choice when combined with fixed WB for the measurement of colors and acceptable photographs. © 2010 John Wiley & Sons A/S.

Impact of correction factors in human brain lesion-behavior inference.

PubMed

Sperber, Christoph; Karnath, Hans-Otto

2017-03-01

Statistical voxel-based lesion-behavior mapping (VLBM) in neurological patients with brain lesions is frequently used to examine the relationship between structure and function of the healthy human brain. Only recently, two simulation studies noted reduced anatomical validity of this method, observing the results of VLBM to be systematically misplaced by about 16 mm. However, both simulation studies differed from VLBM analyses of real data in that they lacked the proper use of two correction factors: lesion size and "sufficient lesion affection." In simulation experiments on a sample of 274 real stroke patients, we found that the use of these two correction factors reduced misplacement markedly compared to uncorrected VLBM. Apparently, the misplacement is due to physiological effects of brain lesion anatomy. Voxel-wise topographies of collateral damage in the real data were generated and used to compute a metric for the inter-voxel relation of brain damage. "Anatomical bias" vectors that were solely calculated from these inter-voxel relations in the patients' real anatomical data, successfully predicted the VLBM misplacement. The latter has the potential to help in the development of new VLBM methods that provide even higher anatomical validity than currently available by the proper use of correction factors. Hum Brain Mapp 38:1692-1701, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Interlaboratory study of free cyanide methods compared to total cyanide measurements and the effect of preservation with sodium hydroxide for secondary- and tertiary-treated waste water samples.

PubMed

Stanley, Brett J; Antonio, Karen

2012-11-01

Several methods exist for the measurement of cyanide levels in treated wastewater,typically requiring preservation of the sample with sodium hydroxide to minimize loss of hydrogen cyanide gas (HCN). Recent reports have shown that cyanide levels may increase with chlorination or preservation. In this study, three flow injection analysis methods involving colorimetric and amperometric detection were compared within one laboratory, as well as across separate laboratories and equipment. Split wastewater samples from eight facilities and three different sampling periods were tested. An interlaboratory confidence interval of 3.5 ppb was calculated compared with the intralaboratory reporting limit of 2 ppb. The results show that free cyanide measurements are not statistically different than total cyanide levels. An artificial increase in cyanide level is observed with all methods for preserved samples relative to nonpreserved samples, with an average increase of 2.3 ppb. The possible loss of cyanide without preservation is shown to be statistically insignificant if properly stored up to 48 hours. The cyanide increase with preservation is further substantiated with the method of standard additions and is not a matrix interference. The increase appears to be correlated with the amount of cyanide observed without preservation, which appears to be greater in those facilities that disinfect their wastewater with chlorine, followed by dechlorination with sodium bisulfite.

Nonparametric rank regression for analyzing water quality concentration data with multiple detection limits.

PubMed

Fu, Liya; Wang, You-Gan

2011-02-15

Environmental data usually include measurements, such as water quality data, which fall below detection limits, because of limitations of the instruments or of certain analytical methods used. The fact that some responses are not detected needs to be properly taken into account in statistical analysis of such data. However, it is well-known that it is challenging to analyze a data set with detection limits, and we often have to rely on the traditional parametric methods or simple imputation methods. Distributional assumptions can lead to biased inference and justification of distributions is often not possible when the data are correlated and there is a large proportion of data below detection limits. The extent of bias is usually unknown. To draw valid conclusions and hence provide useful advice for environmental management authorities, it is essential to develop and apply an appropriate statistical methodology. This paper proposes rank-based procedures for analyzing non-normally distributed data collected at different sites over a period of time in the presence of multiple detection limits. To take account of temporal correlations within each site, we propose an optimal linear combination of estimating functions and apply the induced smoothing method to reduce the computational burden. Finally, we apply the proposed method to the water quality data collected at Susquehanna River Basin in United States of America, which clearly demonstrates the advantages of the rank regression models.

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

Outlier identification in urban soils and its implications for identification of potential contaminated land

NASA Astrophysics Data System (ADS)

Zhang, Chaosheng

2010-05-01

Outliers in urban soil geochemical databases may imply potential contaminated land. Different methodologies which can be easily implemented for the identification of global and spatial outliers were applied for Pb concentrations in urban soils of Galway City in Ireland. Due to its strongly skewed probability feature, a Box-Cox transformation was performed prior to further analyses. The graphic methods of histogram and box-and-whisker plot were effective in identification of global outliers at the original scale of the dataset. Spatial outliers could be identified by a local indicator of spatial association of local Moran's I, cross-validation of kriging, and a geographically weighted regression. The spatial locations of outliers were visualised using a geographical information system. Different methods showed generally consistent results, but differences existed. It is suggested that outliers identified by statistical methods should be confirmed and justified using scientific knowledge before they are properly dealt with.

Semi-supervised vibration-based classification and condition monitoring of compressors

NASA Astrophysics Data System (ADS)

Potočnik, Primož; Govekar, Edvard

2017-09-01

Semi-supervised vibration-based classification and condition monitoring of the reciprocating compressors installed in refrigeration appliances is proposed in this paper. The method addresses the problem of industrial condition monitoring where prior class definitions are often not available or difficult to obtain from local experts. The proposed method combines feature extraction, principal component analysis, and statistical analysis for the extraction of initial class representatives, and compares the capability of various classification methods, including discriminant analysis (DA), neural networks (NN), support vector machines (SVM), and extreme learning machines (ELM). The use of the method is demonstrated on a case study which was based on industrially acquired vibration measurements of reciprocating compressors during the production of refrigeration appliances. The paper presents a comparative qualitative analysis of the applied classifiers, confirming the good performance of several nonlinear classifiers. If the model parameters are properly selected, then very good classification performance can be obtained from NN trained by Bayesian regularization, SVM and ELM classifiers. The method can be effectively applied for the industrial condition monitoring of compressors.

The average receiver operating characteristic curve in multireader multicase imaging studies

PubMed Central

Samuelson, F W

2014-01-01

Objective: In multireader, multicase (MRMC) receiver operating characteristic (ROC) studies for evaluating medical imaging systems, the area under the ROC curve (AUC) is often used as a summary metric. Owing to the limitations of AUC, plotting the average ROC curve to accompany the rigorous statistical inference on AUC is recommended. The objective of this article is to investigate methods for generating the average ROC curve from ROC curves of individual readers. Methods: We present both a non-parametric method and a parametric method for averaging ROC curves that produce a ROC curve, the area under which is equal to the average AUC of individual readers (a property we call area preserving). We use hypothetical examples, simulated data and a real-world imaging data set to illustrate these methods and their properties. Results: We show that our proposed methods are area preserving. We also show that the method of averaging the ROC parameters, either the conventional bi-normal parameters (a, b) or the proper bi-normal parameters (c, da), is generally not area preserving and may produce a ROC curve that is intuitively not an average of multiple curves. Conclusion: Our proposed methods are useful for making plots of average ROC curves in MRMC studies as a companion to the rigorous statistical inference on the AUC end point. The software implementing these methods is freely available from the authors. Advances in knowledge: Methods for generating the average ROC curve in MRMC ROC studies are formally investigated. The area-preserving criterion we defined is useful to evaluate such methods. PMID:24884728

Validation of surrogate endpoints in advanced solid tumors: systematic review of statistical methods, results, and implications for policy makers.

PubMed

Ciani, Oriana; Davis, Sarah; Tappenden, Paul; Garside, Ruth; Stein, Ken; Cantrell, Anna; Saad, Everardo D; Buyse, Marc; Taylor, Rod S

2014-07-01

Licensing of, and coverage decisions on, new therapies should rely on evidence from patient-relevant endpoints such as overall survival (OS). Nevertheless, evidence from surrogate endpoints may also be useful, as it may not only expedite the regulatory approval of new therapies but also inform coverage decisions. It is, therefore, essential that candidate surrogate endpoints be properly validated. However, there is no consensus on statistical methods for such validation and on how the evidence thus derived should be applied by policy makers. We review current statistical approaches to surrogate-endpoint validation based on meta-analysis in various advanced-tumor settings. We assessed the suitability of two surrogates (progression-free survival [PFS] and time-to-progression [TTP]) using three current validation frameworks: Elston and Taylor's framework, the German Institute of Quality and Efficiency in Health Care's (IQWiG) framework and the Biomarker-Surrogacy Evaluation Schema (BSES3). A wide variety of statistical methods have been used to assess surrogacy. The strength of the association between the two surrogates and OS was generally low. The level of evidence (observation-level versus treatment-level) available varied considerably by cancer type, by evaluation tools and was not always consistent even within one specific cancer type. Not in all solid tumors the treatment-level association between PFS or TTP and OS has been investigated. According to IQWiG's framework, only PFS achieved acceptable evidence of surrogacy in metastatic colorectal and ovarian cancer treated with cytotoxic agents. Our study emphasizes the challenges of surrogate-endpoint validation and the importance of building consensus on the development of evaluation frameworks.

Comparative evaluation of topographical data of dental implant surfaces applying optical interferometry and scanning electron microscopy.

PubMed

Kournetas, N; Spintzyk, S; Schweizer, E; Sawada, T; Said, F; Schmid, P; Geis-Gerstorfer, J; Eliades, G; Rupp, F

2017-08-01

Comparability of topographical data of implant surfaces in literature is low and their clinical relevance often equivocal. The aim of this study was to investigate the ability of scanning electron microscopy and optical interferometry to assess statistically similar 3-dimensional roughness parameter results and to evaluate these data based on predefined criteria regarded relevant for a favorable biological response. Four different commercial dental screw-type implants (NanoTite Certain Prevail, TiUnite Brånemark Mk III, XiVE S Plus and SLA Standard Plus) were analyzed by stereo scanning electron microscopy and white light interferometry. Surface height, spatial and hybrid roughness parameters (Sa, Sz, Ssk, Sku, Sal, Str, Sdr) were assessed from raw and filtered data (Gaussian 50μm and 5μm cut-off-filters), respectively. Data were statistically compared by one-way ANOVA and Tukey-Kramer post-hoc test. For a clinically relevant interpretation, a categorizing evaluation approach was used based on predefined threshold criteria for each roughness parameter. The two methods exhibited predominantly statistical differences. Dependent on roughness parameters and filter settings, both methods showed variations in rankings of the implant surfaces and differed in their ability to discriminate the different topographies. Overall, the analyses revealed scale-dependent roughness data. Compared to the pure statistical approach, the categorizing evaluation resulted in much more similarities between the two methods. This study suggests to reconsider current approaches for the topographical evaluation of implant surfaces and to further seek after proper experimental settings. Furthermore, the specific role of different roughness parameters for the bioresponse has to be studied in detail in order to better define clinically relevant, scale-dependent and parameter-specific thresholds and ranges. Copyright © 2017 The Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Meta-analysis methods for combining multiple expression profiles: comparisons, statistical characterization and an application guideline

PubMed Central

2013-01-01

Background As high-throughput genomic technologies become accurate and affordable, an increasing number of data sets have been accumulated in the public domain and genomic information integration and meta-analysis have become routine in biomedical research. In this paper, we focus on microarray meta-analysis, where multiple microarray studies with relevant biological hypotheses are combined in order to improve candidate marker detection. Many methods have been developed and applied in the literature, but their performance and properties have only been minimally investigated. There is currently no clear conclusion or guideline as to the proper choice of a meta-analysis method given an application; the decision essentially requires both statistical and biological considerations. Results We performed 12 microarray meta-analysis methods for combining multiple simulated expression profiles, and such methods can be categorized for different hypothesis setting purposes: (1) HS A : DE genes with non-zero effect sizes in all studies, (2) HS B : DE genes with non-zero effect sizes in one or more studies and (3) HS r : DE gene with non-zero effect in "majority" of studies. We then performed a comprehensive comparative analysis through six large-scale real applications using four quantitative statistical evaluation criteria: detection capability, biological association, stability and robustness. We elucidated hypothesis settings behind the methods and further apply multi-dimensional scaling (MDS) and an entropy measure to characterize the meta-analysis methods and data structure, respectively. Conclusions The aggregated results from the simulation study categorized the 12 methods into three hypothesis settings (HS A , HS B , and HS r ). Evaluation in real data and results from MDS and entropy analyses provided an insightful and practical guideline to the choice of the most suitable method in a given application. All source files for simulation and real data are available on the author’s publication website. PMID:24359104

Meta-analysis methods for combining multiple expression profiles: comparisons, statistical characterization and an application guideline.

PubMed

Chang, Lun-Ching; Lin, Hui-Min; Sibille, Etienne; Tseng, George C

2013-12-21

As high-throughput genomic technologies become accurate and affordable, an increasing number of data sets have been accumulated in the public domain and genomic information integration and meta-analysis have become routine in biomedical research. In this paper, we focus on microarray meta-analysis, where multiple microarray studies with relevant biological hypotheses are combined in order to improve candidate marker detection. Many methods have been developed and applied in the literature, but their performance and properties have only been minimally investigated. There is currently no clear conclusion or guideline as to the proper choice of a meta-analysis method given an application; the decision essentially requires both statistical and biological considerations. We performed 12 microarray meta-analysis methods for combining multiple simulated expression profiles, and such methods can be categorized for different hypothesis setting purposes: (1) HS(A): DE genes with non-zero effect sizes in all studies, (2) HS(B): DE genes with non-zero effect sizes in one or more studies and (3) HS(r): DE gene with non-zero effect in "majority" of studies. We then performed a comprehensive comparative analysis through six large-scale real applications using four quantitative statistical evaluation criteria: detection capability, biological association, stability and robustness. We elucidated hypothesis settings behind the methods and further apply multi-dimensional scaling (MDS) and an entropy measure to characterize the meta-analysis methods and data structure, respectively. The aggregated results from the simulation study categorized the 12 methods into three hypothesis settings (HS(A), HS(B), and HS(r)). Evaluation in real data and results from MDS and entropy analyses provided an insightful and practical guideline to the choice of the most suitable method in a given application. All source files for simulation and real data are available on the author's publication website.

Internal quality control: planning and implementation strategies.

PubMed

Westgard, James O

2003-11-01

The first essential in setting up internal quality control (IQC) of a test procedure in the clinical laboratory is to select the proper IQC procedure to implement, i.e. choosing the statistical criteria or control rules, and the number of control measurements, according to the quality required for the test and the observed performance of the method. Then the right IQC procedure must be properly implemented. This review focuses on strategies for planning and implementing IQC procedures in order to improve the quality of the IQC. A quantitative planning process is described that can be implemented with graphical tools such as power function or critical-error graphs and charts of operating specifications. Finally, a total QC strategy is formulated to minimize cost and maximize quality. A general strategy for IQC implementation is recommended that employs a three-stage design in which the first stage provides high error detection, the second stage low false rejection and the third stage prescribes the length of the analytical run, making use of an algorithm involving the average of normal patients' data.

A data-driven approach to quality risk management.

PubMed

Alemayehu, Demissie; Alvir, Jose; Levenstein, Marcia; Nickerson, David

2013-10-01

An effective clinical trial strategy to ensure patient safety as well as trial quality and efficiency involves an integrated approach, including prospective identification of risk factors, mitigation of the risks through proper study design and execution, and assessment of quality metrics in real-time. Such an integrated quality management plan may also be enhanced by using data-driven techniques to identify risk factors that are most relevant in predicting quality issues associated with a trial. In this paper, we illustrate such an approach using data collected from actual clinical trials. Several statistical methods were employed, including the Wilcoxon rank-sum test and logistic regression, to identify the presence of association between risk factors and the occurrence of quality issues, applied to data on quality of clinical trials sponsored by Pfizer. ONLY A SUBSET OF THE RISK FACTORS HAD A SIGNIFICANT ASSOCIATION WITH QUALITY ISSUES, AND INCLUDED: Whether study used Placebo, whether an agent was a biologic, unusual packaging label, complex dosing, and over 25 planned procedures. Proper implementation of the strategy can help to optimize resource utilization without compromising trial integrity and patient safety.

Uncertainty evaluation of nuclear reaction model parameters using integral and microscopic measurements. Covariances evaluation with CONRAD code

NASA Astrophysics Data System (ADS)

de Saint Jean, C.; Habert, B.; Archier, P.; Noguere, G.; Bernard, D.; Tommasi, J.; Blaise, P.

2010-10-01

In the [eV;MeV] energy range, modelling of the neutron induced reactions are based on nuclear reaction models having parameters. Estimation of co-variances on cross sections or on nuclear reaction model parameters is a recurrent puzzle in nuclear data evaluation. Major breakthroughs were asked by nuclear reactor physicists to assess proper uncertainties to be used in applications. In this paper, mathematical methods developped in the CONRAD code[2] will be presented to explain the treatment of all type of uncertainties, including experimental ones (statistical and systematic) and propagate them to nuclear reaction model parameters or cross sections. Marginalization procedure will thus be exposed using analytical or Monte-Carlo solutions. Furthermore, one major drawback found by reactor physicist is the fact that integral or analytical experiments (reactor mock-up or simple integral experiment, e.g. ICSBEP, …) were not taken into account sufficiently soon in the evaluation process to remove discrepancies. In this paper, we will describe a mathematical framework to take into account properly this kind of information.

Statistically optimal estimation of Greenland Ice Sheet mass variations from GRACE monthly solutions using an improved mascon approach

NASA Astrophysics Data System (ADS)

Ran, J.; Ditmar, P.; Klees, R.; Farahani, H. H.

2018-03-01

We present an improved mascon approach to transform monthly spherical harmonic solutions based on GRACE satellite data into mass anomaly estimates in Greenland. The GRACE-based spherical harmonic coefficients are used to synthesize gravity anomalies at satellite altitude, which are then inverted into mass anomalies per mascon. The limited spectral content of the gravity anomalies is properly accounted for by applying a low-pass filter as part of the inversion procedure to make the functional model spectrally consistent with the data. The full error covariance matrices of the monthly GRACE solutions are properly propagated using the law of covariance propagation. Using numerical experiments, we demonstrate the importance of a proper data weighting and of the spectral consistency between functional model and data. The developed methodology is applied to process real GRACE level-2 data (CSR RL05). The obtained mass anomaly estimates are integrated over five drainage systems, as well as over entire Greenland. We find that the statistically optimal data weighting reduces random noise by 35-69%, depending on the drainage system. The obtained mass anomaly time-series are de-trended to eliminate the contribution of ice discharge and are compared with de-trended surface mass balance (SMB) time-series computed with the Regional Atmospheric Climate Model (RACMO 2.3). We show that when using a statistically optimal data weighting in GRACE data processing, the discrepancies between GRACE-based estimates of SMB and modelled SMB are reduced by 24-47%.

Estimating statistical isotropy violation in CMB due to non-circular beam and complex scan in minutes

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

Pant, Nidhi; Das, Santanu; Mitra, Sanjit

Mild, unavoidable deviations from circular-symmetry of instrumental beams along with scan strategy can give rise to measurable Statistical Isotropy (SI) violation in Cosmic Microwave Background (CMB) experiments. If not accounted properly, this spurious signal can complicate the extraction of other SI violation signals (if any) in the data. However, estimation of this effect through exact numerical simulation is computationally intensive and time consuming. A generalized analytical formalism not only provides a quick way of estimating this signal, but also gives a detailed understanding connecting the leading beam anisotropy components to a measurable BipoSH characterisation of SI violation. In this paper,more » we provide an approximate generic analytical method for estimating the SI violation generated due to a non-circular (NC) beam and arbitrary scan strategy, in terms of the Bipolar Spherical Harmonic (BipoSH) spectra. Our analytical method can predict almost all the features introduced by a NC beam in a complex scan and thus reduces the need for extensive numerical simulation worth tens of thousands of CPU hours into minutes long calculations. As an illustrative example, we use WMAP beams and scanning strategy to demonstrate the easability, usability and efficiency of our method. We test all our analytical results against that from exact numerical simulations.« less

A new computerized diagnostic algorithm for quantitative evaluation of binocular misalignment in patients with strabismus

NASA Astrophysics Data System (ADS)

Nam, Kyoung Won; Kim, In Young; Kang, Ho Chul; Yang, Hee Kyung; Yoon, Chang Ki; Hwang, Jeong Min; Kim, Young Jae; Kim, Tae Yun; Kim, Kwang Gi

2012-10-01

Accurate measurement of binocular misalignment between both eyes is important for proper preoperative management, surgical planning, and postoperative evaluation of patients with strabismus. In this study, we proposed a new computerized diagnostic algorithm that can calculate the angle of binocular eye misalignment photographically by using a dedicated three-dimensional eye model mimicking the structure of the natural human eye. To evaluate the performance of the proposed algorithm, eight healthy volunteers and eight individuals with strabismus were recruited in this study, the horizontal deviation angle, vertical deviation angle, and angle of eye misalignment were calculated and the angular differences between the healthy and the strabismus groups were evaluated using the nonparametric Mann-Whitney test and the Pearson correlation test. The experimental results demonstrated a statistically significant difference between the healthy and strabismus groups (p = 0.015 < 0.05), but no statistically significant difference between the proposed method and the Krimsky test (p = 0.912 > 0.05). The measurements of the two methods were highly correlated (r = 0.969, p < 0.05). From the experimental results, we believe that the proposed diagnostic method has the potential to be a diagnostic tool that measures the physical disorder of the human eye to diagnose non-invasively the severity of strabismus.

On data processing required to derive mobility patterns from passively-generated mobile phone data

PubMed Central

Wang, Feilong; Chen, Cynthia

2018-01-01

Passively-generated mobile phone data is emerging as a potential data source for transportation research and applications. Despite the large amount of studies based on the mobile phone data, only a few have reported the properties of such data, and documented how they have processed the data. In this paper, we describe two types of common mobile phone data: Call Details Record (CDR) data and sightings data, and propose a data processing framework and the associated algorithms to address two key issues associated with the sightings data: locational uncertainty and oscillation. We show the effectiveness of our proposed methods in addressing these two issues compared to the state of art algorithms in the field. We also demonstrate that without proper processing applied to the data, the statistical regularity of human mobility patterns—a key, significant trait identified for human mobility—is over-estimated. We hope this study will stimulate more studies in examining the properties of such data and developing methods to address them. Though not as glamorous as those directly deriving insights on mobility patterns (such as statistical regularity), understanding properties of such data and developing methods to address them is a fundamental research topic on which important insights are derived on mobility patterns. PMID:29398790

Survey of Cancer Patient Safety Culture: A Comparison of Chemotherapy and Oncology Departments of Teaching Hospitals of Tehran

PubMed Central

Raeissi, Pouran; Sharifi, Marziye; Khosravizadeh, Omid; Heidari, Mohammad

2017-01-01

Background: Patient safety culture plays an important role in healthcare systems, especially in chemotherapy and oncology departments (CODs), and its assessment can help to improve quality of services and hospital care. Objective: This study aimed to evaluate and compare items and dimensions of patient safety culture in the CODs of selected teaching hospitals of Iran and Tehran University of Medical Sciences. Materials and Methods: This descriptive-analytical cross-sectional survey was conducted during a six-month period on 270 people from chemotherapy and oncology departments selected through a cluster sampling method. All participants answered the standard questionnaire for “Hospital Survey of Patient Safety Culture” (HSOPSC). Statistical analyses were performed using SPSS/18 software. Results: The average score for patient safety culture was three for the majority of the studied CODs. Statistically significant differences were observed for supervisor actions, teamwork within various units, feedback and communications about errors, and the level of hospital management support. (p<0.05). Relationships between studied hospitals and patient safety culture were not statistically significant (p>0.05). Conclusion: Our results showed that the overall status of patient safety culture is not good in the studied CODs. In particular, teamwork across different units and organizational learning with continuous improvement were the only two properly operating items among 12 dimensions of patient safety culture. Therefore, systematic interventions are strongly required to promote communication. PMID:29072411

Proper survey methods for research of aquatic plant ecology and management

USDA-ARS?s Scientific Manuscript database

Proper survey methods are essential for objective, quantitative assessment of the distribution and abundance of aquatic plants as part of research and demonstration efforts. For research, the use of the appropriate method is an essential part of the scientific method, to ensure that the experimenta...

PET image reconstruction: a robust state space approach.

PubMed

Liu, Huafeng; Tian, Yi; Shi, Pengcheng

2005-01-01

Statistical iterative reconstruction algorithms have shown improved image quality over conventional nonstatistical methods in PET by using accurate system response models and measurement noise models. Strictly speaking, however, PET measurements, pre-corrected for accidental coincidences, are neither Poisson nor Gaussian distributed and thus do not meet basic assumptions of these algorithms. In addition, the difficulty in determining the proper system response model also greatly affects the quality of the reconstructed images. In this paper, we explore the usage of state space principles for the estimation of activity map in tomographic PET imaging. The proposed strategy formulates the organ activity distribution through tracer kinetics models, and the photon-counting measurements through observation equations, thus makes it possible to unify the dynamic reconstruction problem and static reconstruction problem into a general framework. Further, it coherently treats the uncertainties of the statistical model of the imaging system and the noisy nature of measurement data. Since H(infinity) filter seeks minimummaximum-error estimates without any assumptions on the system and data noise statistics, it is particular suited for PET image reconstruction where the statistical properties of measurement data and the system model are very complicated. The performance of the proposed framework is evaluated using Shepp-Logan simulated phantom data and real phantom data with favorable results.

The Need for Speed in Rodent Locomotion Analyses

PubMed Central

Batka, Richard J.; Brown, Todd J.; Mcmillan, Kathryn P.; Meadows, Rena M.; Jones, Kathryn J.; Haulcomb, Melissa M.

2016-01-01

Locomotion analysis is now widely used across many animal species to understand the motor defects in disease, functional recovery following neural injury, and the effectiveness of various treatments. More recently, rodent locomotion analysis has become an increasingly popular method in a diverse range of research. Speed is an inseparable aspect of locomotion that is still not fully understood, and its effects are often not properly incorporated while analyzing data. In this hybrid manuscript, we accomplish three things: (1) review the interaction between speed and locomotion variables in rodent studies, (2) comprehensively analyze the relationship between speed and 162 locomotion variables in a group of 16 wild-type mice using the CatWalk gait analysis system, and (3) develop and test a statistical method in which locomotion variables are analyzed and reported in the context of speed. Notable results include the following: (1) over 90% of variables, reported by CatWalk, were dependent on speed with an average R2 value of 0.624, (2) most variables were related to speed in a nonlinear manner, (3) current methods of controlling for speed are insufficient, and (4) the linear mixed model is an appropriate and effective statistical method for locomotion analyses that is inclusive of speed-dependent relationships. Given the pervasive dependency of locomotion variables on speed, we maintain that valid conclusions from locomotion analyses cannot be made unless they are analyzed and reported within the context of speed. PMID:24890845

Autonomous celestial navigation based on Earth ultraviolet radiance and fast gradient statistic feature extraction

NASA Astrophysics Data System (ADS)

Lu, Shan; Zhang, Hanmo

2016-01-01

To meet the requirement of autonomous orbit determination, this paper proposes a fast curve fitting method based on earth ultraviolet features to obtain accurate earth vector direction, in order to achieve the high precision autonomous navigation. Firstly, combining the stable characters of earth ultraviolet radiance and the use of transmission model software of atmospheric radiation, the paper simulates earth ultraviolet radiation model on different time and chooses the proper observation band. Then the fast improved edge extracting method combined Sobel operator and local binary pattern (LBP) is utilized, which can both eliminate noises efficiently and extract earth ultraviolet limb features accurately. And earth's centroid locations on simulated images are estimated via the least square fitting method using part of the limb edges. Taken advantage of the estimated earth vector direction and earth distance, Extended Kalman Filter (EKF) is applied to realize the autonomous navigation finally. Experiment results indicate the proposed method can achieve a sub-pixel earth centroid location estimation and extremely enhance autonomous celestial navigation precision.

Children's weight and participation in organized sports.

PubMed

Quinto Romani, Annette

2011-11-01

Literature dealing with the impact of organized sports on children's weight has been marked by a lack of consensus. A major weakness characterizing most of this research is a lack of proper measurement methods. This paper seeks to fill an important knowledge gap through careful application of econometric methods. Estimations are carried out using data on 1,400 children attending 6th grade in 2008 in the municipality of Aalborg, Denmark. We use standard ordinary least squares (OLS) and class fixed effects to explore the effect of sports participation on body mass index (BMI) as well as underweight, overweight and obesity. Results indicate that participation in organized sports reduced BMI by 2.1%. Likewise it reduced the likelihood of being overweight by 8.2 percentage points and obese by 3.1 percentage points. It is the unique dataset combined with econometric methods that distinguishes our contribution from that of others in the field, thereby offering new insight. Results using statistically sound methods suggest that participation in organized sports has a beneficial effect on children's weight.

Technical Considerations on Scanning and Image Analysis for Amyloid PET in Dementia.

PubMed

Akamatsu, Go; Ohnishi, Akihito; Aita, Kazuki; Ikari, Yasuhiko; Yamamoto, Yasuji; Senda, Michio

2017-01-01

Brain imaging techniques, such as computed tomography (CT), magnetic resonance imaging (MRI), single photon emission computed tomography (SPECT), and positron emission tomography (PET), can provide essential and objective information for the early and differential diagnosis of dementia. Amyloid PET is especially useful to evaluate the amyloid-β pathological process as a biomarker of Alzheimer's disease. This article reviews critical points about technical considerations on the scanning and image analysis methods for amyloid PET. Each amyloid PET agent has its own proper administration instructions and recommended uptake time, scan duration, and the method of image display and interpretation. In addition, we have introduced general scanning information, including subject positioning, reconstruction parameters, and quantitative and statistical image analysis. We believe that this article could make amyloid PET a more reliable tool in clinical study and practice.

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.

Age of Local Galactic Disk from the Wdlf for Cpmbs

NASA Astrophysics Data System (ADS)

Smith, J. Allyn; Oswalt, Terry D.; Wood, Matt A.; Silvestri, Nicole M.

We present the white dwarf luminosity function (WDLF) for common proper motion systems. This WDLF was derived using the 1/Vmax method pioneered by Schmidt (1975) and detailed by Liebert Dahn and Monet (1988). New cooling models were used to determine the luminosities of the white dwarfs and the age of the local Galactic disk. Comparison to WDLFs developed using older colling models (Wood 1995) will be examined for changes in the derived disk age. Kinematic data is available for a subset of the WDs in the sample. Separate luminosity functions will be examined for each of the statistically significant subsets. JAS acknowledges support from NASA GSRP Fellowship NGT-51086.

Are your spectroscopic data being used?

NASA Astrophysics Data System (ADS)

Gordon, Iouli E.; Potterbusch, Megan R.; Bouquin, Daina; Erdmann, Christopher C.; Wilzewski, Jonas S.; Rothman, Laurence S.

2016-09-01

The issue of availability of data and their presentation in spectroscopic publications is discussed. Different current practices are critically reviewed from the point of view of potential users, government policies, and merit of success of the authors. Indeed, properly providing the data benefits not only users but also the authors of the spectroscopic research. We will show that this increases citations to the spectroscopy papers and visibility of the research groups. Examples based on the statistical analyses of the articles published in the Journal of Molecular Spectroscopy will be shown. We will discuss different methods including supplementary materials to the Journals, public-curated databases and also new tools that can be utilized by spectroscopists.

ASSESSMENT OF GOOD PRACTICES IN HOSPITAL FOOD SERVICE BY COMPARING EVALUATION TOOLS.

PubMed

Macedo Gonçalves, Juliana; Lameiro Rodrigues, Kelly; Santiago Almeida, Ângela Teresinha; Pereira, Giselda Maria; Duarte Buchweitz, Márcia Rúbia

2015-10-01

since food service in hospitals complements medical treatment, it should be produced in proper hygienic and sanitary conditions. It is a well-known fact that food-transmitted illnesses affect with greater severity hospitalized and immunosuppressed patients. good practices in hospital food service are evaluated by comparing assessment instruments. good practices were evaluated by a verification list following Resolution of Collegiate Directory n. 216 of the Brazilian Agency for Sanitary Vigilance. Interpretation of listed items followed parameters of RCD 216 and the Brazilian Association of Collective Meals Enterprises (BACME). Fisher's exact test was applied to detect whether there were statistically significant differences. Analysis of data grouping was undertaken with Unweighted Pair-group using Arithmetic Averages, coupled to a correlation study between dissimilarity matrixes to verify disagreement between the two methods. Good Practice was classified with mean total rates above 75% by the two methods. There were statistically significant differences between services and food evaluated by BACME instrument. Hospital Food Services have proved to show conditions of acceptable good practices. the comparison of interpretation tools based on RCD n. 216 and BACME provided similar results for the two classifications. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

Accounting for interim safety monitoring of an adverse event upon termination of a clinical trial.

PubMed

Dallas, Michael J

2008-01-01

Upon termination of a clinical trial that uses interim evaluations to determine whether the trial can be stopped, a proper statistical analysis must account for the interim evaluations. For example, in a group-sequential design where the efficacy of a treatment regimen is evaluated at interim stages, and the opportunity to stop the trial based on positive efficacy findings exists, the terminal p-value, point estimate, and confidence limits of the outcome of interest must be adjusted to eliminate bias. While it is standard practice to adjust terminal statistical analyses due to opportunities to stop for "positive" findings, adjusting due to opportunities to stop for "negative" findings is also important. Stopping rules for negative findings are particularly useful when monitoring a specific rare serious adverse event in trials designed to show safety with respect to the event. In these settings, establishing conservative stopping rules are appropriate, and therefore accounting for the interim monitoring can have a substantial effect on the final results. Here I present a method to account for interim safety monitoring and illustrate its usefulness. The method is demonstrated to have advantages over methodology that does not account for interim monitoring.

The Kinematics Parameters of the Galaxy Using Data of Modern Astrometric Catalogues

NASA Astrophysics Data System (ADS)

Akhmetov, V. S.; Fedorov, P. N.; Velichko, A. B.; Shulga, V. M.

Based on the Ogorodnikov-Milne model, we analyze the proper motions of XPM2, UCAC4 and PPMXL stars. To estimate distances to the stars we used the method of statistical parallaxes herewith the random errors of the distance estimations do not exceed 10%. The method of statistical parallaxes was used to estimate the distances to stars with random errors no larger than 14%. The linear solar velocity relative to the local standard of rest, which is well determined for the local entroid (d 150 p), was used as a reference. We have established that the model component that describes the rotation of all stars under consideration about the Galactic Y axis differs from zero. For the distant (d < 1000 pc) PPMXL and UCAC4 stars, the mean rotation about the Galactic Y axis has been found to be M-13 = -0.75± 0.04 mas yr-1. As for distances greater than 1 kpc M-13>derived from the data of only XPM2 catalogue becomes positive and exceeds 0.5 mas yr-1. We interpret this rotation found using the distant stars as a residual rotation of the ICRS/Tycho-2 system relative to the inertial reference frame.

Degrees of separation as a statistical tool for evaluating candidate genes.

PubMed

Nelson, Ronald M; Pettersson, Mats E

2014-12-01

Selection of candidate genes is an important step in the exploration of complex genetic architecture. The number of gene networks available is increasing and these can provide information to help with candidate gene selection. It is currently common to use the degree of connectedness in gene networks as validation in Genome Wide Association (GWA) and Quantitative Trait Locus (QTL) mapping studies. However, it can cause misleading results if not validated properly. Here we present a method and tool for validating the gene pairs from GWA studies given the context of the network they co-occur in. It ensures that proposed interactions and gene associations are not statistical artefacts inherent to the specific gene network architecture. The CandidateBacon package provides an easy and efficient method to calculate the average degree of separation (DoS) between pairs of genes to currently available gene networks. We show how these empirical estimates of average connectedness are used to validate candidate gene pairs. Validation of interacting genes by comparing their connectedness with the average connectedness in the gene network will provide support for said interactions by utilising the growing amount of gene network information available. Copyright © 2014 Elsevier Ltd. All rights reserved.

Confidence intervals for expected moments algorithm flood quantile estimates

USGS Publications Warehouse

Cohn, Timothy A.; Lane, William L.; Stedinger, Jery R.

2001-01-01

Historical and paleoflood information can substantially improve flood frequency estimates if appropriate statistical procedures are properly applied. However, the Federal guidelines for flood frequency analysis, set forth in Bulletin 17B, rely on an inefficient “weighting” procedure that fails to take advantage of historical and paleoflood information. This has led researchers to propose several more efficient alternatives including the Expected Moments Algorithm (EMA), which is attractive because it retains Bulletin 17B's statistical structure (method of moments with the Log Pearson Type 3 distribution) and thus can be easily integrated into flood analyses employing the rest of the Bulletin 17B approach. The practical utility of EMA, however, has been limited because no closed‐form method has been available for quantifying the uncertainty of EMA‐based flood quantile estimates. This paper addresses that concern by providing analytical expressions for the asymptotic variance of EMA flood‐quantile estimators and confidence intervals for flood quantile estimates. Monte Carlo simulations demonstrate the properties of such confidence intervals for sites where a 25‐ to 100‐year streamgage record is augmented by 50 to 150 years of historical information. The experiments show that the confidence intervals, though not exact, should be acceptable for most purposes.

Improving Accuracy and Temporal Resolution of Learning Curve Estimation for within- and across-Session Analysis

PubMed Central

Tabelow, Karsten; König, Reinhard; Polzehl, Jörg

2016-01-01

Estimation of learning curves is ubiquitously based on proportions of correct responses within moving trial windows. Thereby, it is tacitly assumed that learning performance is constant within the moving windows, which, however, is often not the case. In the present study we demonstrate that violations of this assumption lead to systematic errors in the analysis of learning curves, and we explored the dependency of these errors on window size, different statistical models, and learning phase. To reduce these errors in the analysis of single-subject data as well as on the population level, we propose adequate statistical methods for the estimation of learning curves and the construction of confidence intervals, trial by trial. Applied to data from an avoidance learning experiment with rodents, these methods revealed performance changes occurring at multiple time scales within and across training sessions which were otherwise obscured in the conventional analysis. Our work shows that the proper assessment of the behavioral dynamics of learning at high temporal resolution can shed new light on specific learning processes, and, thus, allows to refine existing learning concepts. It further disambiguates the interpretation of neurophysiological signal changes recorded during training in relation to learning. PMID:27303809

Historical Data Analysis of Hospital Discharges Related to the Amerithrax Attack in Florida

PubMed Central

Burke, Lauralyn K.; Brown, C. Perry; Johnson, Tammie M.

2016-01-01

Interrupted time-series analysis (ITSA) can be used to identify, quantify, and evaluate the magnitude and direction of an event on the basis of time-series data. This study evaluates the impact of the bioterrorist anthrax attacks (“Amerithrax”) on hospital inpatient discharges in the metropolitan statistical area of Palm Beach, Broward, and Miami-Dade counties in the fourth quarter of 2001. Three statistical methods—standardized incidence ratio (SIR), segmented regression, and an autoregressive integrated moving average (ARIMA)—were used to determine whether Amerithrax influenced inpatient utilization. The SIR found a non–statistically significant 2 percent decrease in hospital discharges. Although the segmented regression test found a slight increase in the discharge rate during the fourth quarter, it was also not statistically significant; therefore, it could not be attributed to Amerithrax. Segmented regression diagnostics preparing for ARIMA indicated that the quarterly data time frame was not serially correlated and violated one of the assumptions for the use of the ARIMA method and therefore could not properly evaluate the impact on the time-series data. Lack of data granularity of the time frames hindered the successful evaluation of the impact by the three analytic methods. This study demonstrates that the granularity of the data points is as important as the number of data points in a time series. ITSA is important for the ability to evaluate the impact that any hazard may have on inpatient utilization. Knowledge of hospital utilization patterns during disasters offer healthcare and civic professionals valuable information to plan, respond, mitigate, and evaluate any outcomes stemming from biothreats. PMID:27843420

Statistics of Land-Grant Colleges, Year Ended June 30, 1922. Bulletin, 1924, No. 6

ERIC Educational Resources Information Center

Blauch, L. E.

1924-01-01

This report is made in accordance with the provisions of the land-grant act of 1862 and the Morrill-Nelson Acts of 1890 and 1907. To assure the proper usage of these funds, the specialist in charge of land-grant college statistics makes, from reports submitted by the treasurers of the land-grant colleges, an audit of disbursements from the funds.…

Methods to control for unmeasured confounding in pharmacoepidemiology: an overview.

PubMed

Uddin, Md Jamal; Groenwold, Rolf H H; Ali, Mohammed Sanni; de Boer, Anthonius; Roes, Kit C B; Chowdhury, Muhammad A B; Klungel, Olaf H

2016-06-01

Background Unmeasured confounding is one of the principal problems in pharmacoepidemiologic studies. Several methods have been proposed to detect or control for unmeasured confounding either at the study design phase or the data analysis phase. Aim of the Review To provide an overview of commonly used methods to detect or control for unmeasured confounding and to provide recommendations for proper application in pharmacoepidemiology. Methods/Results Methods to control for unmeasured confounding in the design phase of a study are case only designs (e.g., case-crossover, case-time control, self-controlled case series) and the prior event rate ratio adjustment method. Methods that can be applied in the data analysis phase include, negative control method, perturbation variable method, instrumental variable methods, sensitivity analysis, and ecological analysis. A separate group of methods are those in which additional information on confounders is collected from a substudy. The latter group includes external adjustment, propensity score calibration, two-stage sampling, and multiple imputation. Conclusion As the performance and application of the methods to handle unmeasured confounding may differ across studies and across databases, we stress the importance of using both statistical evidence and substantial clinical knowledge for interpretation of the study results.

Vibration-based structural health monitoring using adaptive statistical method under varying environmental condition

NASA Astrophysics Data System (ADS)

Jin, Seung-Seop; Jung, Hyung-Jo

2014-03-01

It is well known that the dynamic properties of a structure such as natural frequencies depend not only on damage but also on environmental condition (e.g., temperature). The variation in dynamic characteristics of a structure due to environmental condition may mask damage of the structure. Without taking the change of environmental condition into account, false-positive or false-negative damage diagnosis may occur so that structural health monitoring becomes unreliable. In order to address this problem, an approach to construct a regression model based on structural responses considering environmental factors has been usually used by many researchers. The key to success of this approach is the formulation between the input and output variables of the regression model to take into account the environmental variations. However, it is quite challenging to determine proper environmental variables and measurement locations in advance for fully representing the relationship between the structural responses and the environmental variations. One alternative (i.e., novelty detection) is to remove the variations caused by environmental factors from the structural responses by using multivariate statistical analysis (e.g., principal component analysis (PCA), factor analysis, etc.). The success of this method is deeply depending on the accuracy of the description of normal condition. Generally, there is no prior information on normal condition during data acquisition, so that the normal condition is determined by subjective perspective with human-intervention. The proposed method is a novel adaptive multivariate statistical analysis for monitoring of structural damage detection under environmental change. One advantage of this method is the ability of a generative learning to capture the intrinsic characteristics of the normal condition. The proposed method is tested on numerically simulated data for a range of noise in measurement under environmental variation. A comparative study with conventional methods (i.e., fixed reference scheme) demonstrates the superior performance of the proposed method for structural damage detection.

A novel statistical approach for identification of the master regulator transcription factor.

PubMed

Sikdar, Sinjini; Datta, Susmita

2017-02-02

Transcription factors are known to play key roles in carcinogenesis and therefore, are gaining popularity as potential therapeutic targets in drug development. A 'master regulator' transcription factor often appears to control most of the regulatory activities of the other transcription factors and the associated genes. This 'master regulator' transcription factor is at the top of the hierarchy of the transcriptomic regulation. Therefore, it is important to identify and target the master regulator transcription factor for proper understanding of the associated disease process and identifying the best therapeutic option. We present a novel two-step computational approach for identification of master regulator transcription factor in a genome. At the first step of our method we test whether there exists any master regulator transcription factor in the system. We evaluate the concordance of two ranked lists of transcription factors using a statistical measure. In case the concordance measure is statistically significant, we conclude that there is a master regulator. At the second step, our method identifies the master regulator transcription factor, if there exists one. In the simulation scenario, our method performs reasonably well in validating the existence of a master regulator when the number of subjects in each treatment group is reasonably large. In application to two real datasets, our method ensures the existence of master regulators and identifies biologically meaningful master regulators. An R code for implementing our method in a sample test data can be found in http://www.somnathdatta.org/software . We have developed a screening method of identifying the 'master regulator' transcription factor just using only the gene expression data. Understanding the regulatory structure and finding the master regulator help narrowing the search space for identifying biomarkers for complex diseases such as cancer. In addition to identifying the master regulator our method provides an overview of the regulatory structure of the transcription factors which control the global gene expression profiles and consequently the cell functioning.

The evolution of autodigestion in the mushroom family Psathyrellaceae (Agaricales) inferred from Maximum Likelihood and Bayesian methods.

PubMed

Nagy, László G; Urban, Alexander; Orstadius, Leif; Papp, Tamás; Larsson, Ellen; Vágvölgyi, Csaba

2010-12-01

Recently developed comparative phylogenetic methods offer a wide spectrum of applications in evolutionary biology, although it is generally accepted that their statistical properties are incompletely known. Here, we examine and compare the statistical power of the ML and Bayesian methods with regard to selection of best-fit models of fruiting-body evolution and hypothesis testing of ancestral states on a real-life data set of a physiological trait (autodigestion) in the family Psathyrellaceae. Our phylogenies are based on the first multigene data set generated for the family. Two different coding regimes (binary and multistate) and two data sets differing in taxon sampling density are examined. The Bayesian method outperformed Maximum Likelihood with regard to statistical power in all analyses. This is particularly evident if the signal in the data is weak, i.e. in cases when the ML approach does not provide support to choose among competing hypotheses. Results based on binary and multistate coding differed only modestly, although it was evident that multistate analyses were less conclusive in all cases. It seems that increased taxon sampling density has favourable effects on inference of ancestral states, while model parameters are influenced to a smaller extent. The model best fitting our data implies that the rate of losses of deliquescence equals zero, although model selection in ML does not provide proper support to reject three of the four candidate models. The results also support the hypothesis that non-deliquescence (lack of autodigestion) has been ancestral in Psathyrellaceae, and that deliquescent fruiting bodies represent the preferred state, having evolved independently several times during evolution. Copyright © 2010 Elsevier Inc. All rights reserved.

Statistically Assessing Time-Averaged and Paleosecular Variation Field Models Against Paleomagnetic Directional Data Sets. Can Likely non-Zonal Features be Detected in a Robust way ?

NASA Astrophysics Data System (ADS)

Hulot, G.; Khokhlov, A.

2007-12-01

We recently introduced a method to rigorously test the statistical compatibility of combined time-averaged (TAF) and paleosecular variation (PSV) field models against any lava flow paleomagnetic database (Khokhlov et al., 2001, 2006). Applying this method to test (TAF+PSV) models against synthetic data produced from those shows that the method is very efficient at discriminating models, and very sensitive, provided those data errors are properly taken into account. This prompted us to test a variety of published combined (TAF+PSV) models against a test Bruhnes stable polarity data set extracted from the Quidelleur et al. (1994) data base. Not surprisingly, ignoring data errors leads all models to be rejected. But taking data errors into account leads to the stimulating conclusion that at least one (TAF+PSV) model appears to be compatible with the selected data set, this model being purely axisymmetric. This result shows that in practice also, and with the data bases currently available, the method can discriminate various candidate models and decide which actually best fits a given data set. But it also shows that likely non-zonal signatures of non-homogeneous boundary conditions imposed by the mantle are difficult to identify as statistically robust from paleomagnetic directional data sets. In the present paper, we will discuss the possibility that such signatures could eventually be identified as robust with the help of more recent data sets (such as the one put together under the collaborative "TAFI" effort, see e.g. Johnson et al. abstract #GP21A-0013, AGU Fall Meeting, 2005) or by taking additional information into account (such as the possible coincidence of non-zonal time-averaged field patterns with analogous patterns in the modern field).

Statistical auditing of toxicology reports.

PubMed

Deaton, R R; Obenchain, R L

1994-06-01

Statistical auditing is a new report review process used by the quality assurance unit at Eli Lilly and Co. Statistical auditing allows the auditor to review the process by which the report was generated, as opposed to the process by which the data was generated. We have the flexibility to use different sampling techniques and still obtain thorough coverage of the report data. By properly implementing our auditing process, we can work smarter rather than harder and continue to help our customers increase the quality of their products (reports). Statistical auditing is helping our quality assurance unit meet our customers' need, while maintaining or increasing the quality of our regulatory obligations.

ENVIRONMENTAL SAMPLING: A BRIEF REVIEW

EPA Science Inventory

Proper application of statistical principles at the outset of an environmental study can make the difference between an effective, efficient study and wasted resources. This review distills some of the thoughts current among environmental scientists from a variety of backgrounds ...

Imputation approaches for animal movement modeling

USGS Publications Warehouse

Scharf, Henry; Hooten, Mevin B.; Johnson, Devin S.

2017-01-01

The analysis of telemetry data is common in animal ecological studies. While the collection of telemetry data for individual animals has improved dramatically, the methods to properly account for inherent uncertainties (e.g., measurement error, dependence, barriers to movement) have lagged behind. Still, many new statistical approaches have been developed to infer unknown quantities affecting animal movement or predict movement based on telemetry data. Hierarchical statistical models are useful to account for some of the aforementioned uncertainties, as well as provide population-level inference, but they often come with an increased computational burden. For certain types of statistical models, it is straightforward to provide inference if the latent true animal trajectory is known, but challenging otherwise. In these cases, approaches related to multiple imputation have been employed to account for the uncertainty associated with our knowledge of the latent trajectory. Despite the increasing use of imputation approaches for modeling animal movement, the general sensitivity and accuracy of these methods have not been explored in detail. We provide an introduction to animal movement modeling and describe how imputation approaches may be helpful for certain types of models. We also assess the performance of imputation approaches in two simulation studies. Our simulation studies suggests that inference for model parameters directly related to the location of an individual may be more accurate than inference for parameters associated with higher-order processes such as velocity or acceleration. Finally, we apply these methods to analyze a telemetry data set involving northern fur seals (Callorhinus ursinus) in the Bering Sea. Supplementary materials accompanying this paper appear online.

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.

Soil erosion assessment and its correlation with landslide events using remote sensing data and GIS: a case study at Penang Island, Malaysia.

PubMed

Pradhan, Biswajeet; Chaudhari, Amruta; Adinarayana, J; Buchroithner, Manfred F

2012-01-01

In this paper, an attempt has been made to assess, prognosis and observe dynamism of soil erosion by universal soil loss equation (USLE) method at Penang Island, Malaysia. Multi-source (map-, space- and ground-based) datasets were used to obtain both static and dynamic factors of USLE, and an integrated analysis was carried out in raster format of GIS. A landslide location map was generated on the basis of image elements interpretation from aerial photos, satellite data and field observations and was used to validate soil erosion intensity in the study area. Further, a statistical-based frequency ratio analysis was carried out in the study area for correlation purposes. The results of the statistical correlation showed a satisfactory agreement between the prepared USLE-based soil erosion map and landslide events/locations, and are directly proportional to each other. Prognosis analysis on soil erosion helps the user agencies/decision makers to design proper conservation planning program to reduce soil erosion. Temporal statistics on soil erosion in these dynamic and rapid developments in Penang Island indicate the co-existence and balance of ecosystem.

Extending local canonical correlation analysis to handle general linear contrasts for FMRI data.

PubMed

Jin, Mingwu; Nandy, Rajesh; Curran, Tim; Cordes, Dietmar

2012-01-01

Local canonical correlation analysis (CCA) is a multivariate method that has been proposed to more accurately determine activation patterns in fMRI data. In its conventional formulation, CCA has several drawbacks that limit its usefulness in fMRI. A major drawback is that, unlike the general linear model (GLM), a test of general linear contrasts of the temporal regressors has not been incorporated into the CCA formalism. To overcome this drawback, a novel directional test statistic was derived using the equivalence of multivariate multiple regression (MVMR) and CCA. This extension will allow CCA to be used for inference of general linear contrasts in more complicated fMRI designs without reparameterization of the design matrix and without reestimating the CCA solutions for each particular contrast of interest. With the proper constraints on the spatial coefficients of CCA, this test statistic can yield a more powerful test on the inference of evoked brain regional activations from noisy fMRI data than the conventional t-test in the GLM. The quantitative results from simulated and pseudoreal data and activation maps from fMRI data were used to demonstrate the advantage of this novel test statistic.

Real-time in Situ Signal-to-noise Ratio Estimation for the Assessment of Operational Communications Links

NASA Technical Reports Server (NTRS)

Manning, Robert M.

2002-01-01

The work presented here formulates the rigorous statistical basis for the correct estimation of communication link SNR of a BPSK, QPSK, and for that matter, any M-ary phase-modulated digital signal from what is known about its statistical behavior at the output of the receiver demodulator. Many methods to accomplish this have been proposed and implemented in the past but all of them are based on tacit and unwarranted assumptions and are thus defective. However, the basic idea is well founded, i.e., the signal at the output of a communications demodulator has convolved within it the prevailing SNR characteristic of the link. The acquisition of the SNR characteristic is of the utmost importance to a communications system that must remain reliable in adverse propagation conditions. This work provides a correct and consistent mathematical basis for the proper statistical 'deconvolution' of the output of a demodulator to yield a measure of the SNR. The use of such techniques will alleviate the need and expense for a separate propagation link to assess the propagation conditions prevailing on the communications link. Furthermore, they are applicable for every situation involving the digital transmission of data over planetary and space communications links.

Extending Local Canonical Correlation Analysis to Handle General Linear Contrasts for fMRI Data

PubMed Central

Jin, Mingwu; Nandy, Rajesh; Curran, Tim; Cordes, Dietmar

2012-01-01

Local canonical correlation analysis (CCA) is a multivariate method that has been proposed to more accurately determine activation patterns in fMRI data. In its conventional formulation, CCA has several drawbacks that limit its usefulness in fMRI. A major drawback is that, unlike the general linear model (GLM), a test of general linear contrasts of the temporal regressors has not been incorporated into the CCA formalism. To overcome this drawback, a novel directional test statistic was derived using the equivalence of multivariate multiple regression (MVMR) and CCA. This extension will allow CCA to be used for inference of general linear contrasts in more complicated fMRI designs without reparameterization of the design matrix and without reestimating the CCA solutions for each particular contrast of interest. With the proper constraints on the spatial coefficients of CCA, this test statistic can yield a more powerful test on the inference of evoked brain regional activations from noisy fMRI data than the conventional t-test in the GLM. The quantitative results from simulated and pseudoreal data and activation maps from fMRI data were used to demonstrate the advantage of this novel test statistic. PMID:22461786

Gis-Based Spatial Statistical Analysis of College Graduates Employment

NASA Astrophysics Data System (ADS)

Tang, R.

2012-07-01

It is urgently necessary to be aware of the distribution and employment status of college graduates for proper allocation of human resources and overall arrangement of strategic industry. This study provides empirical evidence regarding the use of geocoding and spatial analysis in distribution and employment status of college graduates based on the data from 2004-2008 Wuhan Municipal Human Resources and Social Security Bureau, China. Spatio-temporal distribution of employment unit were analyzed with geocoding using ArcGIS software, and the stepwise multiple linear regression method via SPSS software was used to predict the employment and to identify spatially associated enterprise and professionals demand in the future. The results show that the enterprises in Wuhan east lake high and new technology development zone increased dramatically from 2004 to 2008, and tended to distributed southeastward. Furthermore, the models built by statistical analysis suggest that the specialty of graduates major in has an important impact on the number of the employment and the number of graduates engaging in pillar industries. In conclusion, the combination of GIS and statistical analysis which helps to simulate the spatial distribution of the employment status is a potential tool for human resource development research.

Considerations in the statistical analysis of clinical trials in periodontitis.

PubMed

Imrey, P B

1986-05-01

Adult periodontitis has been described as a chronic infectious process exhibiting sporadic, acute exacerbations which cause quantal, localized losses of dental attachment. Many analytic problems of periodontal trials are similar to those of other chronic diseases. However, the episodic, localized, infrequent, and relatively unpredictable behavior of exacerbations, coupled with measurement error difficulties, cause some specific problems. Considerable controversy exists as to the proper selection and treatment of multiple site data from the same patient for group comparisons for epidemiologic or therapeutic evaluative purposes. This paper comments, with varying degrees of emphasis, on several issues pertinent to the analysis of periodontal trials. Considerable attention is given to the ways in which measurement variability may distort analytic results. Statistical treatments of multiple site data for descriptive summaries are distinguished from treatments for formal statistical inference to validate therapeutic effects. Evidence suggesting that sites behave independently is contested. For inferential analyses directed at therapeutic or preventive effects, analytic models based on site independence are deemed unsatisfactory. Methods of summarization that may yield more powerful analyses than all-site mean scores, while retaining appropriate treatment of inter-site associations, are suggested. Brief comments and opinions on an assortment of other issues in clinical trial analysis are preferred.

GEE-based SNP set association test for continuous and discrete traits in family-based association studies.

PubMed

Wang, Xuefeng; Lee, Seunggeun; Zhu, Xiaofeng; Redline, Susan; Lin, Xihong

2013-12-01

Family-based genetic association studies of related individuals provide opportunities to detect genetic variants that complement studies of unrelated individuals. Most statistical methods for family association studies for common variants are single marker based, which test one SNP a time. In this paper, we consider testing the effect of an SNP set, e.g., SNPs in a gene, in family studies, for both continuous and discrete traits. Specifically, we propose a generalized estimating equations (GEEs) based kernel association test, a variance component based testing method, to test for the association between a phenotype and multiple variants in an SNP set jointly using family samples. The proposed approach allows for both continuous and discrete traits, where the correlation among family members is taken into account through the use of an empirical covariance estimator. We derive the theoretical distribution of the proposed statistic under the null and develop analytical methods to calculate the P-values. We also propose an efficient resampling method for correcting for small sample size bias in family studies. The proposed method allows for easily incorporating covariates and SNP-SNP interactions. Simulation studies show that the proposed method properly controls for type I error rates under both random and ascertained sampling schemes in family studies. We demonstrate through simulation studies that our approach has superior performance for association mapping compared to the single marker based minimum P-value GEE test for an SNP-set effect over a range of scenarios. We illustrate the application of the proposed method using data from the Cleveland Family GWAS Study. © 2013 WILEY PERIODICALS, INC.

Searching cause of death through different autopsy methods: A new initiative

PubMed Central

Das, Abhishek; Chowdhury, Ranadip

2017-01-01

A lawful disposal of human dead body is only possible after establishment of proper and valid cause of death. If the cause is obscure, autopsy is the only mean of search. Inadequacy and unavailability of health care facility often makes this situation more complicated in developing countries where many deaths remain unexplained and proper mortality statistics is missing, especially for infant and children. Tissue sampling by needle autopsy or use of various imaging technique in virtopsy have been tried globally to find out an easier alternative. An exclusive and unique initiative, by limited autopsy through tissue biopsy and body fluid analysis, has been taken to meet this dire need in African and some of Asian developing countries, as worldwide accepted institutional data are even missing or conflicting at times. Traditional autopsy has changed little in last century, consisting of external examination and evisceration, dissection of organs with identification of macroscopic pathologies and injuries, followed by histopathology. As some population groups have religious objections to autopsy, demand for minimally invasive alternative has increased of late. But assessment of cause of death is most important for medico-legal, epidemiological and research purposes. Thus minimally invasive technique is of high importance in primary care settings too. In this article, we have made a journey through different autopsy methods, their relevance and applicability in modern day perspective considering scientific research articles, textbooks and interviews. PMID:29302514

Testing stellar proper motions of TGAS stars using data from the HSOY, UCAC5 and PMA catalogues

NASA Astrophysics Data System (ADS)

Fedorov, P. N.; Akhmetov, V. S.; Velichko, A. B.

2018-05-01

We analyse the stellar proper motions from the Tycho-Gaia Astrometric Solution (TGAS) and those from the ground-based HSOY, UCAC5 and PMA catalogues derived by combining them with Gaia DR1 space data. Assuming that systematic differences in stellar proper motions of the two catalogues are caused by a mutual rigid-body rotation of the reference catalogue systems, we analyse components of the rotation vector between the systems. We found that the ωy component of the rotation vector is ˜1.5 mas yr-1 and it depends non-linearly on stellar magnitude for the objects of 9.5-11.5 mag used in all three comparisons of the catalogues HSOY, UCAC5 and PMA with respect to TGAS. We found that the Tycho-2 stars in TGAS appeared to have an inexplicable dependence of proper motion on stellar magnitude. We showed that the proper motions of the TGAS stars derived using AGIS differ from those obtained by the conventional (classical) method. Moreover, the application of both methods has not revealed such a difference between the proper motions of the Hipparcos and TGAS stars. An analysis of the systematic differences between the proper motions of the TGAS stars derived by the classical method and the proper motions of the HSOY, UCAC5 and PMA stars shows that the ωy component here does not depend on the magnitude. This indicates unambiguously that there is a magnitude error in the proper motions of the Tycho-2 stars derived with the AGIS.

The use and misuse of aircraft and missile RCS statistics

NASA Astrophysics Data System (ADS)

Bishop, Lee R.

1991-07-01

Both static and dynamic radar cross sections measurements are used for RCS predictions, but the static data are less complete than the dynamic. Integrated dynamics RCS data also have limitations for prediction radar detection performance. When raw static data are properly used, good first-order detection estimates are possible. The research to develop more-usable RCS statistics is reviewed, and windowing techniques for creating probability density functions from static RCS data are discussed.

Are infant mortality rate declines exponential? The general pattern of 20th century infant mortality rate decline

PubMed Central

Bishai, David; Opuni, Marjorie

2009-01-01

Background Time trends in infant mortality for the 20th century show a curvilinear pattern that most demographers have assumed to be approximately exponential. Virtually all cross-country comparisons and time series analyses of infant mortality have studied the logarithm of infant mortality to account for the curvilinear time trend. However, there is no evidence that the log transform is the best fit for infant mortality time trends. Methods We use maximum likelihood methods to determine the best transformation to fit time trends in infant mortality reduction in the 20th century and to assess the importance of the proper transformation in identifying the relationship between infant mortality and gross domestic product (GDP) per capita. We apply the Box Cox transform to infant mortality rate (IMR) time series from 18 countries to identify the best fitting value of lambda for each country and for the pooled sample. For each country, we test the value of λ against the null that λ = 0 (logarithmic model) and against the null that λ = 1 (linear model). We then demonstrate the importance of selecting the proper transformation by comparing regressions of ln(IMR) on same year GDP per capita against Box Cox transformed models. Results Based on chi-squared test statistics, infant mortality decline is best described as an exponential decline only for the United States. For the remaining 17 countries we study, IMR decline is neither best modelled as logarithmic nor as a linear process. Imposing a logarithmic transform on IMR can lead to bias in fitting the relationship between IMR and GDP per capita. Conclusion The assumption that IMR declines are exponential is enshrined in the Preston curve and in nearly all cross-country as well as time series analyses of IMR data since Preston's 1975 paper, but this assumption is seldom correct. Statistical analyses of IMR trends should assess the robustness of findings to transformations other than the log transform. PMID:19698144

Risk Factors of Congenital Heart Diseases: A Case-Control Study inNorthwest Iran.

PubMed

Naghavi-Behzad, Mohammad; Alizadeh, Mahasti; Azami, Saber; Foroughifar, Shirin; Ghasempour-Dabbaghi, Khazar; Karzad, Nazila; Ahadi, Hamid-Reza; Naghavi-Behzad, Ali

2013-01-01

Congenital heart diseases are of immense importance and also a high prevalence. Contributing factors to developing these defects have not been abundantly studied. Therefore, the current study was conducted aiming at determining the effective factors on Congenital Heart Disease (CHD) in newborn infants of Northwest Iran. A case-control study was carried out in North-West of Iran from 2002 to 2012 and a total of 473 infants entered the study. Required data were obtained through check lists completed by the information of hospital records and interview with mothers of 267 newborn infants with CHD together with medical records of mothers as the case group, and 206 medical records of healthy infants at the same period all together with those of their mothers as the control group. The obtained data were statistically analyzed using descriptive statistical methods, T-test, Spearman's correlation coefficient, and Multi-variable Logistic Regression Model (OR with 95% CI), using SPSS.19. In the present study, P value less than 0.05 was considered statistically significant. Based on the results of univariable analyses, the number of previous cesarean sections, past medical history of diseases, gestational age (GA), fetal weight at birth, diastolic blood pressure, fetal heart rate, pulse rate, fetal hemoglobin and hematocrit levels, and fetal head circumference at birth have significant relationship with incidence of congenital abnormalities (P<0.05). Family history, past cesarean sections history, past medical history and GA had significant relationship with CHD incidence. Based on the results of present study, in order to control and reduce the cases of CHD, it is crucial to make proper decisions and implement policies for reducing cesarean cases, lowering consanguineous marriages, providing proper pre-marriage counseling, prompt treatment of mothers' illnesses, improving pregnancy health care and mothers' health status for the purpose of better well-being of newborn infants.

Common Scientific and Statistical Errors in Obesity Research

PubMed Central

George, Brandon J.; Beasley, T. Mark; Brown, Andrew W.; Dawson, John; Dimova, Rositsa; Divers, Jasmin; Goldsby, TaShauna U.; Heo, Moonseong; Kaiser, Kathryn A.; Keith, Scott; Kim, Mimi Y.; Li, Peng; Mehta, Tapan; Oakes, J. Michael; Skinner, Asheley; Stuart, Elizabeth; Allison, David B.

2015-01-01

We identify 10 common errors and problems in the statistical analysis, design, interpretation, and reporting of obesity research and discuss how they can be avoided. The 10 topics are: 1) misinterpretation of statistical significance, 2) inappropriate testing against baseline values, 3) excessive and undisclosed multiple testing and “p-value hacking,” 4) mishandling of clustering in cluster randomized trials, 5) misconceptions about nonparametric tests, 6) mishandling of missing data, 7) miscalculation of effect sizes, 8) ignoring regression to the mean, 9) ignoring confirmation bias, and 10) insufficient statistical reporting. We hope that discussion of these errors can improve the quality of obesity research by helping researchers to implement proper statistical practice and to know when to seek the help of a statistician. PMID:27028280

Searching for High Proper Motion Sources Towards the Galactic Center using Convolution Neural Networks

NASA Astrophysics Data System (ADS)

Giongo Fernandes, Alexandre; Benjamin, Robert A.; Babler, Brian

2018-01-01

Two sets of infrared images of the Galactic Center region (|L|< 1 degree and |B| < 0.75 degrees) taken by the Spitzer Space Telescope in IRAC 3.6 micron and 4.5 micron bands are searched for high proper motion objects (> 100 mas/year). The two image sets come from GALCEN observations in 2005 and GLIMPSE proper observations in 2015 with matched observation modes. We use three different methods to search for these objects in extremely crowded fields: (1) comparing matched point source lists, (2) crowd sourcing by several college introductory astronomy classes in the state of Wisconsin (700 volunteers), and (3) convolutional neural networks trained using objects from the previous two methods. Before our search six high proper objects were known, four of which were found by the VVV near-infrared Galactic plane survey. We compare and describe our methods for this search, and present a preliminary catalog of high proper motions objects.

Statistical Methods for Proteomic Biomarker Discovery based on Feature Extraction or Functional Modeling Approaches.

PubMed

Morris, Jeffrey S

2012-01-01

In recent years, developments in molecular biotechnology have led to the increased promise of detecting and validating biomarkers, or molecular markers that relate to various biological or medical outcomes. Proteomics, the direct study of proteins in biological samples, plays an important role in the biomarker discovery process. These technologies produce complex, high dimensional functional and image data that present many analytical challenges that must be addressed properly for effective comparative proteomics studies that can yield potential biomarkers. Specific challenges include experimental design, preprocessing, feature extraction, and statistical analysis accounting for the inherent multiple testing issues. This paper reviews various computational aspects of comparative proteomic studies, and summarizes contributions I along with numerous collaborators have made. First, there is an overview of comparative proteomics technologies, followed by a discussion of important experimental design and preprocessing issues that must be considered before statistical analysis can be done. Next, the two key approaches to analyzing proteomics data, feature extraction and functional modeling, are described. Feature extraction involves detection and quantification of discrete features like peaks or spots that theoretically correspond to different proteins in the sample. After an overview of the feature extraction approach, specific methods for mass spectrometry ( Cromwell ) and 2D gel electrophoresis ( Pinnacle ) are described. The functional modeling approach involves modeling the proteomic data in their entirety as functions or images. A general discussion of the approach is followed by the presentation of a specific method that can be applied, wavelet-based functional mixed models, and its extensions. All methods are illustrated by application to two example proteomic data sets, one from mass spectrometry and one from 2D gel electrophoresis. While the specific methods presented are applied to two specific proteomic technologies, MALDI-TOF and 2D gel electrophoresis, these methods and the other principles discussed in the paper apply much more broadly to other expression proteomics technologies.

Primer of statistics in dental research: part I.

PubMed

Shintani, Ayumi

2014-01-01

Statistics play essential roles in evidence-based dentistry (EBD) practice and research. It ranges widely from formulating scientific questions, designing studies, collecting and analyzing data to interpreting, reporting, and presenting study findings. Mastering statistical concepts appears to be an unreachable goal among many dental researchers in part due to statistical authorities' limitations of explaining statistical principles to health researchers without elaborating complex mathematical concepts. This series of 2 articles aim to introduce dental researchers to 9 essential topics in statistics to conduct EBD with intuitive examples. The part I of the series includes the first 5 topics (1) statistical graph, (2) how to deal with outliers, (3) p-value and confidence interval, (4) testing equivalence, and (5) multiplicity adjustment. Part II will follow to cover the remaining topics including (6) selecting the proper statistical tests, (7) repeated measures analysis, (8) epidemiological consideration for causal association, and (9) analysis of agreement. Copyright © 2014. Published by Elsevier Ltd.

Testing the causal theory of reference.

PubMed

Domaneschi, Filippo; Vignolo, Massimiliano; Di Paola, Simona

2017-04-01

Theories of reference are a crucial research topic in analytic philosophy. Since the publication of Kripke's Naming and Necessity, most philosophers have endorsed the causal/historical theory of reference. The goal of this paper is twofold: (i) to discuss a method for testing experimentally the causal theory of reference for proper names by investigating linguistic usage and (ii) to present the results from two experiments conducted with that method. Data collected in our experiments confirm the causal theory of reference for people proper names and for geographical proper names. A secondary but interesting result is that the semantic domain affects reference assignment: while with people proper names speakers tend to assign the semantic reference, with geographical proper names they are prompted to assign the speaker's reference. Copyright © 2016 Elsevier B.V. All rights reserved.

An Assessment of Oral Hygiene in 7-14-Year-Old Children undergoing Orthodontic Treatment.

PubMed

Krupińska-Nanys, Magdalena; Zarzecka, Joanna

2015-01-01

The study is focused on increased risk of dental plaque accumulation among the children undergoing orthodontic treatment in consideration of individual hygiene and dietary habits. The study was conducted among 91 children aged 7-14 including 47 girls and 44 boys. The main objectives of the study were: API index, plaque pH, DMF index, proper hygiene and dietary habits. Statistical analysis was provided in Microsoft Office Exel spreadsheet and STATISTICA statistical software. The average API index among the children wearing removable appliance was 9 (SD = 13), and among children without appliances was 16 (SD = 21). DMF index for patients using appliances was 5 (SD = 3) and for those without appliances was 4 (SD = 2). The average plaque pH was 6 for children with appliances (SD = 0.9) and 6.2 without ones (SD = 0.3). In patients in whom there is a higher risk of dental plaque accumulating, correct oral hygiene supported with regular visits to the dentist is one of the best ways to control dental caries. In the fight against caries the most effective and only approach is to promote awareness of the problem, foster proper hygiene and nutritional habits, as well as educate children from a very young age in how to maintain proper oral hygiene.

Stochastic rainfall synthesis for urban applications using different regionalization methods

NASA Astrophysics Data System (ADS)

Callau Poduje, A. C.; Leimbach, S.; Haberlandt, U.

2017-12-01

The proper design and efficient operation of urban drainage systems require long and continuous rainfall series in a high temporal resolution. Unfortunately, these time series are usually available in a few locations and it is therefore suitable to develop a stochastic precipitation model to generate rainfall in locations without observations. The model presented is based on an alternating renewal process and involves an external and an internal structure. The members of these structures are described by probability distributions which are site specific. Different regionalization methods based on site descriptors are presented which are used for estimating the distributions for locations without observations. Regional frequency analysis, multiple linear regressions and a vine-copula method are applied for this purpose. An area located in the north-west of Germany is used to compare the different methods and involves a total of 81 stations with 5 min rainfall records. The site descriptors include information available for the whole region: position, topography and hydrometeorologic characteristics which are estimated from long term observations. The methods are compared directly by cross validation of different rainfall statistics. Given that the model is stochastic the evaluation is performed based on ensembles of many long synthetic time series which are compared with observed ones. The performance is as well indirectly evaluated by setting up a fictional urban hydrological system to test the capability of the different methods regarding flooding and overflow characteristics. The results show a good representation of the seasonal variability and good performance in reproducing the sample statistics of the rainfall characteristics. The copula based method shows to be the most robust of the three methods. Advantages and disadvantages of the different methods are presented and discussed.

Monitor-based evaluation of pollutant load from urban stormwater runoff in Beijing.

PubMed

Liu, Y; Che, W; Li, J

2005-01-01

As a major pollutant source to urban receiving waters, the non-point source pollution from urban runoff needs to be well studied and effectively controlled. Based on monitoring data from urban runoff pollutant sources, this article describes a systematic estimation of total pollutant loads from the urban areas of Beijing. A numerical model was developed to quantify main pollutant loads of urban runoff in Beijing. A sub-procedure is involved in this method, in which the flush process influences both the quantity and quality of stormwater runoff. A statistics-based method was applied in computing the annual pollutant load as an output of the runoff. The proportions of pollutant from point-source and non-point sources were compared. This provides a scientific basis for proper environmental input assessment of urban stormwater pollution to receiving waters, improvement of infrastructure performance, implementation of urban stormwater management, and utilization of stormwater.

Epidemiologic methods in clinical trials.

PubMed

Rothman, K J

1977-04-01

Epidemiologic methods developed to control confounding in non-experimental studies are equally applicable for experiments. In experiments, most confounding is usually controlled by random allocation of subjects to treatment groups, but randomization does not preclude confounding except for extremely large studies, the degree of confounding expected being inversely related to the size of the treatment groups. In experiments, as in non-experimental studies, the extent of confounding for each risk indicator should be assessed, and if sufficiently large, controlled. Confounding is properly assessed by comparing the unconfounded effect estimate to the crude effect estimate; a common error is to assess confounding by statistical tests of significance. Assessment of confounding involves its control as a prerequisite. Control is most readily and cogently achieved by stratification of the data, though with many factors to control simultaneously, multivariate analysis or a combination of multivariate analysis and stratification might be necessary.

Review of the results of the in vivo dosimetry during total skin electron beam therapy

PubMed Central

Guidi, Gabriele; Gottardi, Giovanni; Ceroni, Paola; Costi, Tiziana

2013-01-01

This work reviews results of in vivo dosimetry (IVD) for total skin electron beam (TSEB) therapy, focusing on new methods, data emerged within 2012. All quoted data are based on a careful review of the literature reporting IVD results for patients treated by means of TSEB therapy. Many of the reviewed papers refer mainly to now old studies and/or old guidelines and recommendations (by IAEA, AAPM and EORTC), because (due to intrinsic rareness of TSEB-treated pathologies) only a limited number of works and reports with a large set of numerical data and proper statistical analysis is up-to-day available in scientific literature. Nonetheless, a general summary of the results obtained by the now numerous IVD techniques available is reported; innovative devices and methods, together with areas of possible further and possibly multicenter investigations for TSEB therapies are highlighted. PMID:24936333

Iterative algorithms for a non-linear inverse problem in atmospheric lidar

NASA Astrophysics Data System (ADS)

Denevi, Giulia; Garbarino, Sara; Sorrentino, Alberto

2017-08-01

We consider the inverse problem of retrieving aerosol extinction coefficients from Raman lidar measurements. In this problem the unknown and the data are related through the exponential of a linear operator, the unknown is non-negative and the data follow the Poisson distribution. Standard methods work on the log-transformed data and solve the resulting linear inverse problem, but neglect to take into account the noise statistics. In this study we show that proper modelling of the noise distribution can improve substantially the quality of the reconstructed extinction profiles. To achieve this goal, we consider the non-linear inverse problem with non-negativity constraint, and propose two iterative algorithms derived using the Karush-Kuhn-Tucker conditions. We validate the algorithms with synthetic and experimental data. As expected, the proposed algorithms out-perform standard methods in terms of sensitivity to noise and reliability of the estimated profile.

Turbulent Flow Over Large Roughness Elements: Effect of Frontal and Plan Solidity on Turbulence Statistics and Structure

NASA Astrophysics Data System (ADS)

Placidi, M.; Ganapathisubramani, B.

2018-04-01

Wind-tunnel experiments were carried out on fully-rough boundary layers with large roughness (δ /h ≈ 10, where h is the height of the roughness elements and δ is the boundary-layer thickness). Twelve different surface conditions were created by using LEGO™ bricks of uniform height. Six cases are tested for a fixed plan solidity (λ _P) with variations in frontal density (λ _F), while the other six cases have varying λ _P for fixed λ _F. Particle image velocimetry and floating-element drag-balance measurements were performed. The current results complement those contained in Placidi and Ganapathisubramani (J Fluid Mech 782:541-566, 2015), extending the previous analysis to the turbulence statistics and spatial structure. Results indicate that mean velocity profiles in defect form agree with Townsend's similarity hypothesis with varying λ _F, however, the agreement is worse for cases with varying λ _P. The streamwise and wall-normal turbulent stresses, as well as the Reynolds shear stresses, show a lack of similarity across most examined cases. This suggests that the critical height of the roughness for which outer-layer similarity holds depends not only on the height of the roughness, but also on the local wall morphology. A new criterion based on shelter solidity, defined as the sheltered plan area per unit wall-parallel area, which is similar to the `effective shelter area' in Raupach and Shaw (Boundary-Layer Meteorol 22:79-90, 1982), is found to capture the departure of the turbulence statistics from outer-layer similarity. Despite this lack of similarity reported in the turbulence statistics, proper orthogonal decomposition analysis, as well as two-point spatial correlations, show that some form of universal flow structure is present, as all cases exhibit virtually identical proper orthogonal decomposition mode shapes and correlation fields. Finally, reduced models based on proper orthogonal decomposition reveal that the small scales of the turbulence play a significant role in assessing outer-layer similarity.

Civil Rightsspeak.

ERIC Educational Resources Information Center

Williams, Walter E.

1986-01-01

Today's civil rights debate is clouded by ambiguities of language. The following frequently misused words are clarified in the text so the issues can be properly addressed: 1) segregation; 2) desegregation; 3) minority group; 4) civil rights; 5) compensatory; 6) statistical disparities; and 7) racist. (PS)

45 CFR 153.350 - Risk adjustment data validation standards.

Code of Federal Regulations, 2012 CFR

2012-10-01

... implementation of any risk adjustment software and ensure proper validation of a statistically valid sample of... respect to implementation of risk adjustment software or as a result of data validation conducted pursuant... implementation of risk adjustment software or data validation. ...

[Epidemiological investigation on thyroid disease among fertile women in different iodine intake areas of Shanxi province].

PubMed

Ren, Yanting; Jia, Qingzhen; Zhang, Xiangdong; Guo, Baisuo; Wen, Xinping; Zhang, Fengfeng; Wang, Yongping; Wang, Juanjuan

2014-01-01

To understand the prevalence of thyroid diseases and its influencing factors of iodine on thyroid gland function and autoimmune among fertile women in different iodine intake areas. Cross-sectional method was used for descriptive epidemiology. 236 women aged 19 to 45 years were sampled in 2011, in Shanxi province. Questionnaire was used to include general data on place, name, age etc. Sample of water from home, one time random urine sample and venous blood were collected to test the iodine contents using arsenic and cerium catalysis spectrophotometric methods. Finally, in blood, free triiodothyronine (FT3), free thyroxine (FT4), thyrotrophin (TSH) in blood were tested under auto-CLIA and anti-thyroid peroxidase (anti-TPO), anti-thyroglobulin (anti-TG) through radio-immunological methods. 1)The urine iodine's medians were 486.9 µg/L for fertile women in high iodine areas, and 192.6 µg/L in low iodine areas, with difference on urine iodine level statistically significant (Z = -10.676, P = 0.000). 2) Levels of blood FT3 and FT4 in women from high iodine areas were obviously lower than those from proper iodine areas(t = -2.884, P = 0.004; t = -2.862, P = 0.005), but the level of TSH in high iodine areas was higher than that of proper iodine areas(t = 2.332, P = 0.021). 3) In both areas, the rate of the thyroid dysfunction with positive antibodies was obviously higher than those with negative antibodies (χ² = 20.941, P = 0.000;χ² = 5.596, P = 0.018), while the rate of the thyroid dysfunction with positive antibodies and the level of TSH in the blood for high iodine women higher than those in women with proper iodine level(χ² = 5.708, P = 0.37;t = -2.177, P = 0.031). 4)The morbidity rate of inferior clinical hyperthyroidism for women in high iodine areas was obviously higher than those in proper iodine areas(χ² = 9.542, P = 0.003), while the morbidity rate of inferior clinical hypothyroidism for women with positive antibodies in two areas obviously higher than those with negative antibodies (χ² = 17.264, P = 0.000; χ² = 6.002, P = 0.044). Morbidity rate of inferior clinical hypothyroidism for women in high iodine areas was obviously higher than those in proper iodine areas, suggesting that there were potential risks of hypothyroidism for overdose iodine intake which causing the existence of positive thyroid antibodies. Monitoring programs on iodine nutrition and thyroid function among women living in high iodine areas should be strengthened.

Statistical inference for the additive hazards model under outcome-dependent sampling.

PubMed

Yu, Jichang; Liu, Yanyan; Sandler, Dale P; Zhou, Haibo

2015-09-01

Cost-effective study design and proper inference procedures for data from such designs are always of particular interests to study investigators. In this article, we propose a biased sampling scheme, an outcome-dependent sampling (ODS) design for survival data with right censoring under the additive hazards model. We develop a weighted pseudo-score estimator for the regression parameters for the proposed design and derive the asymptotic properties of the proposed estimator. We also provide some suggestions for using the proposed method by evaluating the relative efficiency of the proposed method against simple random sampling design and derive the optimal allocation of the subsamples for the proposed design. Simulation studies show that the proposed ODS design is more powerful than other existing designs and the proposed estimator is more efficient than other estimators. We apply our method to analyze a cancer study conducted at NIEHS, the Cancer Incidence and Mortality of Uranium Miners Study, to study the risk of radon exposure to cancer.

Nonlinear model-order reduction for compressible flow solvers using the Discrete Empirical Interpolation Method

NASA Astrophysics Data System (ADS)

Fosas de Pando, Miguel; Schmid, Peter J.; Sipp, Denis

2016-11-01

Nonlinear model reduction for large-scale flows is an essential component in many fluid applications such as flow control, optimization, parameter space exploration and statistical analysis. In this article, we generalize the POD-DEIM method, introduced by Chaturantabut & Sorensen [1], to address nonlocal nonlinearities in the equations without loss of performance or efficiency. The nonlinear terms are represented by nested DEIM-approximations using multiple expansion bases based on the Proper Orthogonal Decomposition. These extensions are imperative, for example, for applications of the POD-DEIM method to large-scale compressible flows. The efficient implementation of the presented model-reduction technique follows our earlier work [2] on linearized and adjoint analyses and takes advantage of the modular structure of our compressible flow solver. The efficacy of the nonlinear model-reduction technique is demonstrated to the flow around an airfoil and its acoustic footprint. We could obtain an accurate and robust low-dimensional model that captures the main features of the full flow.

Outlier identification and visualization for Pb concentrations in urban soils and its implications for identification of potential contaminated land.

PubMed

Zhang, Chaosheng; Tang, Ya; Luo, Lin; Xu, Weilin

2009-11-01

Outliers in urban soil geochemical databases may imply potential contaminated land. Different methodologies which can be easily implemented for the identification of global and spatial outliers were applied for Pb concentrations in urban soils of Galway City in Ireland. Due to its strongly skewed probability feature, a Box-Cox transformation was performed prior to further analyses. The graphic methods of histogram and box-and-whisker plot were effective in identification of global outliers at the original scale of the dataset. Spatial outliers could be identified by a local indicator of spatial association of local Moran's I, cross-validation of kriging, and a geographically weighted regression. The spatial locations of outliers were visualised using a geographical information system. Different methods showed generally consistent results, but differences existed. It is suggested that outliers identified by statistical methods should be confirmed and justified using scientific knowledge before they are properly dealt with.

Statistical inference for the additive hazards model under outcome-dependent sampling

PubMed Central

Yu, Jichang; Liu, Yanyan; Sandler, Dale P.; Zhou, Haibo

2015-01-01

Cost-effective study design and proper inference procedures for data from such designs are always of particular interests to study investigators. In this article, we propose a biased sampling scheme, an outcome-dependent sampling (ODS) design for survival data with right censoring under the additive hazards model. We develop a weighted pseudo-score estimator for the regression parameters for the proposed design and derive the asymptotic properties of the proposed estimator. We also provide some suggestions for using the proposed method by evaluating the relative efficiency of the proposed method against simple random sampling design and derive the optimal allocation of the subsamples for the proposed design. Simulation studies show that the proposed ODS design is more powerful than other existing designs and the proposed estimator is more efficient than other estimators. We apply our method to analyze a cancer study conducted at NIEHS, the Cancer Incidence and Mortality of Uranium Miners Study, to study the risk of radon exposure to cancer. PMID:26379363

Synthesis of atmospheric turbulence point spread functions by sparse and redundant representations

NASA Astrophysics Data System (ADS)

Hunt, Bobby R.; Iler, Amber L.; Bailey, Christopher A.; Rucci, Michael A.

2018-02-01

Atmospheric turbulence is a fundamental problem in imaging through long slant ranges, horizontal-range paths, or uplooking astronomical cases through the atmosphere. An essential characterization of atmospheric turbulence is the point spread function (PSF). Turbulence images can be simulated to study basic questions, such as image quality and image restoration, by synthesizing PSFs of desired properties. In this paper, we report on a method to synthesize PSFs of atmospheric turbulence. The method uses recent developments in sparse and redundant representations. From a training set of measured atmospheric PSFs, we construct a dictionary of "basis functions" that characterize the atmospheric turbulence PSFs. A PSF can be synthesized from this dictionary by a properly weighted combination of dictionary elements. We disclose an algorithm to synthesize PSFs from the dictionary. The algorithm can synthesize PSFs in three orders of magnitude less computing time than conventional wave optics propagation methods. The resulting PSFs are also shown to be statistically representative of the turbulence conditions that were used to construct the dictionary.

Critical evaluation of methods to incorporate entropy loss upon binding in high-throughput docking.

PubMed

Salaniwal, Sumeet; Manas, Eric S; Alvarez, Juan C; Unwalla, Rayomand J

2007-02-01

Proper accounting of the positional/orientational/conformational entropy loss associated with protein-ligand binding is important to obtain reliable predictions of binding affinity. Herein, we critically examine two simplified statistical mechanics-based approaches, namely a constant penalty per rotor method, and a more rigorous method, referred to here as the partition function-based scoring (PFS) method, to account for such entropy losses in high-throughput docking calculations. Our results on the estrogen receptor beta and dihydrofolate reductase proteins demonstrate that, while the constant penalty method over-penalizes molecules for their conformational flexibility, the PFS method behaves in a more "DeltaG-like" manner by penalizing different rotors differently depending on their residual entropy in the bound state. Furthermore, in contrast to no entropic penalty or the constant penalty approximation, the PFS method does not exhibit any bias towards either rigid or flexible molecules in the hit list. Preliminary enrichment studies using a lead-like random molecular database suggest that an accurate representation of the "true" energy landscape of the protein-ligand complex is critical for reliable predictions of relative binding affinities by the PFS method. Copyright 2006 Wiley-Liss, Inc.

The Digital Shoreline Analysis System (DSAS) Version 4.0 - An ArcGIS extension for calculating shoreline change

USGS Publications Warehouse

Thieler, E. Robert; Himmelstoss, Emily A.; Zichichi, Jessica L.; Ergul, Ayhan

2009-01-01

The Digital Shoreline Analysis System (DSAS) version 4.0 is a software extension to ESRI ArcGIS v.9.2 and above that enables a user to calculate shoreline rate-of-change statistics from multiple historic shoreline positions. A user-friendly interface of simple buttons and menus guides the user through the major steps of shoreline change analysis. Components of the extension and user guide include (1) instruction on the proper way to define a reference baseline for measurements, (2) automated and manual generation of measurement transects and metadata based on user-specified parameters, and (3) output of calculated rates of shoreline change and other statistical information. DSAS computes shoreline rates of change using four different methods: (1) endpoint rate, (2) simple linear regression, (3) weighted linear regression, and (4) least median of squares. The standard error, correlation coefficient, and confidence interval are also computed for the simple and weighted linear-regression methods. The results of all rate calculations are output to a table that can be linked to the transect file by a common attribute field. DSAS is intended to facilitate the shoreline change-calculation process and to provide rate-of-change information and the statistical data necessary to establish the reliability of the calculated results. The software is also suitable for any generic application that calculates positional change over time, such as assessing rates of change of glacier limits in sequential aerial photos, river edge boundaries, land-cover changes, and so on.

Methods for processing microarray data.

PubMed

Ares, Manuel

2014-02-01

Quality control must be maintained at every step of a microarray experiment, from RNA isolation through statistical evaluation. Here we provide suggestions for analyzing microarray data. Because the utility of the results depends directly on the design of the experiment, the first critical step is to ensure that the experiment can be properly analyzed and interpreted. What is the biological question? What is the best way to perform the experiment? How many replicates will be required to obtain the desired statistical resolution? Next, the samples must be prepared, pass quality controls for integrity and representation, and be hybridized and scanned. Also, slides with defects, missing data, high background, or weak signal must be rejected. Data from individual slides must be normalized and combined so that the data are as free of systematic bias as possible. The third phase is to apply statistical filters and tests to the data to determine genes (1) expressed above background, (2) whose expression level changes in different samples, and (3) whose RNA-processing patterns or protein associations change. Next, a subset of the data should be validated by an alternative method, such as reverse transcription-polymerase chain reaction (RT-PCR). Provided that this endorses the general conclusions of the array analysis, gene sets whose expression, splicing, polyadenylation, protein binding, etc. change in different samples can be classified with respect to function, sequence motif properties, as well as other categories to extract hypotheses for their biological roles and regulatory logic.

Using expert knowledge to incorporate uncertainty in cause-of-death assignments for modeling of cause-specific mortality

USGS Publications Warehouse

Walsh, Daniel P.; Norton, Andrew S.; Storm, Daniel J.; Van Deelen, Timothy R.; Heisy, Dennis M.

2018-01-01

Implicit and explicit use of expert knowledge to inform ecological analyses is becoming increasingly common because it often represents the sole source of information in many circumstances. Thus, there is a need to develop statistical methods that explicitly incorporate expert knowledge, and can successfully leverage this information while properly accounting for associated uncertainty during analysis. Studies of cause-specific mortality provide an example of implicit use of expert knowledge when causes-of-death are uncertain and assigned based on the observer's knowledge of the most likely cause. To explicitly incorporate this use of expert knowledge and the associated uncertainty, we developed a statistical model for estimating cause-specific mortality using a data augmentation approach within a Bayesian hierarchical framework. Specifically, for each mortality event, we elicited the observer's belief of cause-of-death by having them specify the probability that the death was due to each potential cause. These probabilities were then used as prior predictive values within our framework. This hierarchical framework permitted a simple and rigorous estimation method that was easily modified to include covariate effects and regularizing terms. Although applied to survival analysis, this method can be extended to any event-time analysis with multiple event types, for which there is uncertainty regarding the true outcome. We conducted simulations to determine how our framework compared to traditional approaches that use expert knowledge implicitly and assume that cause-of-death is specified accurately. Simulation results supported the inclusion of observer uncertainty in cause-of-death assignment in modeling of cause-specific mortality to improve model performance and inference. Finally, we applied the statistical model we developed and a traditional method to cause-specific survival data for white-tailed deer, and compared results. We demonstrate that model selection results changed between the two approaches, and incorporating observer knowledge in cause-of-death increased the variability associated with parameter estimates when compared to the traditional approach. These differences between the two approaches can impact reported results, and therefore, it is critical to explicitly incorporate expert knowledge in statistical methods to ensure rigorous inference.

The status of botulism as a world health problem

PubMed Central

Meyer, K. F.

1956-01-01

The author reviews the international literature and brings up to date the published statistical data on botulism—a disease which, owing to its spectacular nature and high case-fatality rate, appears to occupy a place out of proportion to its frequency as a cause of death in some regions. Without exception, botulism is caused by carelessness in the preparation and preservation of vegetable and animal foods. Local customs of eating such food uncooked, in the form of salads, watery conserves, poorly cured or inadequately smoked pork and salted fish products create the botulism problem. The risk of botulism exists wherever the telluric incidence of Type A, B, and E spores is high. Surveys to appraise the extent of Clostridium botulinum in the soils of Asia and Africa are urgently needed so that the magnitude of the potential problem in these areas can be properly evaluated. Food processors must not relax in the use of properly calculated thermal processes now available for every food commodity. Agencies that promote or give instruction in preservation of food in the home should be thoroughly familiar with the most effective, practical, and inexpensive methods of preventing botulism. PMID:13383365

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.

The polar cusp from a particle point of view: A statistical study based on Viking data

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

Aparicio, B.; Thelin, B.; Lundin, R.

1991-08-01

The authors present results from the particle measurements made on board the Viking satellite. For the period of interest the Viking orbits covered at high latitudes the whole dayside sector. Data from the Viking V-3 particle experiment acquired during the Polar Region Outer Magnetospheric International Study period have been used to study the extension of the cusp and cleft in magnetic local time and invariant latitude, and furthermore, their dependence on solar wind and interplanetary magnetic field parameters. The study is limited to the MLT range from 0900 to 1500 and to invariant latitudes (ILAT) from 74{degree} to 82{degree}. Thismore » region is divided into bins of size. The authors concentrated on the region where magnetosheath solar wind plasma penetrates more directly into the magnetosphere and is measured at Viking altitudes. This region is called the cusp proper, to be distinguished from a broader region denoted the cleft, where more energetic particles are observed. Statistically, they find the cusp proper to extend from invariant latitudes of 75{degree} to 82{degree} and magnetic local times from 0930 to 1400 MLT. The width in ILAT is found to be on average {approx}2{degree} and in MLT {approx}2 hours. It is shown that a clear correlation exists between the densities in the cusp proper calculated from the Viking V-3 experiment in the cusp proper and those in the solar wind calculated from IMP 8 measurements. It is also shown that the position of the cusp proper in MLT depends on the sense of the By component of the interplanetary magnetic field (IMF By), giving a well-defined displacement of the region of maximum occurrence toward earlier MLTs for IMF By < 0 and a less defined displacement toward later MLTs for IMF By > 0.« less

A crash course on data analysis in asteroseismology

NASA Astrophysics Data System (ADS)

Appourchaux, Thierry

2014-02-01

In this course, I try to provide a few basics required for performing data analysis in asteroseismology. First, I address how one can properly treat times series: the sampling, the filtering effect, the use of Fourier transform, the associated statistics. Second, I address how one can apply statistics for decision making and for parameter estimation either in a frequentist of a Bayesian framework. Last, I review how these basic principle have been applied (or not) in asteroseismology.

Selecting statistical model and optimum maintenance policy: a case study of hydraulic pump.

PubMed

Ruhi, S; Karim, M R

2016-01-01

Proper maintenance policy can play a vital role for effective investigation of product reliability. Every engineered object such as product, plant or infrastructure needs preventive and corrective maintenance. In this paper we look at a real case study. It deals with the maintenance of hydraulic pumps used in excavators by a mining company. We obtain the data that the owner had collected and carry out an analysis and building models for pump failures. The data consist of both failure and censored lifetimes of the hydraulic pump. Different competitive mixture models are applied to analyze a set of maintenance data of a hydraulic pump. Various characteristics of the mixture models, such as the cumulative distribution function, reliability function, mean time to failure, etc. are estimated to assess the reliability of the pump. Akaike Information Criterion, adjusted Anderson-Darling test statistic, Kolmogrov-Smirnov test statistic and root mean square error are considered to select the suitable models among a set of competitive models. The maximum likelihood estimation method via the EM algorithm is applied mainly for estimating the parameters of the models and reliability related quantities. In this study, it is found that a threefold mixture model (Weibull-Normal-Exponential) fits well for the hydraulic pump failures data set. This paper also illustrates how a suitable statistical model can be applied to estimate the optimum maintenance period at a minimum cost of a hydraulic pump.

Cosmological Distance Scale to Gamma-Ray Bursts

NASA Astrophysics Data System (ADS)

Azzam, W. J.; Linder, E. V.; Petrosian, V.

1993-05-01

The source counts or the so-called log N -- log S relations are the primary data that constrain the spatial distribution of sources with unknown distances, such as gamma-ray bursts. In order to test galactic, halo, and cosmological models for gamma-ray bursts we compare theoretical characteristics of the log N -- log S relations to those obtained from data gathered by the BATSE instrument on board the Compton Observatory (GRO) and other instruments. We use a new and statistically correct method, that takes proper account of the variable nature of the triggering threshold, to analyze the data. Constraints on models obtained by this comparison will be presented. This work is supported by NASA grants NAGW 2290, NAG5 2036, and NAG5 1578.

Nyström type subsampling analyzed as a regularized projection

NASA Astrophysics Data System (ADS)

Kriukova, Galyna; Pereverzyev, Sergiy, Jr.; Tkachenko, Pavlo

2017-07-01

In the statistical learning theory the Nyström type subsampling methods are considered as tools for dealing with big data. In this paper we consider Nyström subsampling as a special form of the projected Lavrentiev regularization, and study it using the approaches developed in the regularization theory. As a result, we prove that the same capacity independent learning rates that are guaranteed for standard algorithms running with quadratic computational complexity can be obtained with subquadratic complexity by the Nyström subsampling approach, provided that the subsampling size is chosen properly. We propose a priori rule for choosing the subsampling size and a posteriori strategy for dealing with uncertainty in the choice of it. The theoretical results are illustrated by numerical experiments.

The Zombie Plot: A Simple Graphic Method for Visualizing the Efficacy of a Diagnostic Test.

PubMed

Richardson, Michael L

2016-08-09

One of the most important jobs of a radiologist is to pick the most appropriate imaging test for a particular clinical situation. Making a proper selection sometimes requires statistical analysis. The objective of this article is to introduce a simple graphic technique, an ROC plot that has been divided into zones of mostly bad imaging efficacy (ZOMBIE, hereafter referred to as the "zombie plot"), that transforms information about imaging efficacy from the numeric domain into the visual domain. The numeric rationale for the use of zombie plots is given, as are several examples of the clinical use of these plots. Two online calculators are described that simplify the process of producing a zombie plot.

Research on orbit prediction for solar-based calibration proper satellite

NASA Astrophysics Data System (ADS)

Chen, Xuan; Qi, Wenwen; Xu, Peng

2018-03-01

Utilizing the mathematical model of the orbit mechanics, the orbit prediction is to forecast the space target's orbit information of a certain time based on the orbit of the initial moment. The proper satellite radiometric calibration and calibration orbit prediction process are introduced briefly. On the basis of the research of the calibration space position design method and the radiative transfer model, an orbit prediction method for proper satellite radiometric calibration is proposed to select the appropriate calibration arc for the remote sensor and to predict the orbit information of the proper satellite and the remote sensor. By analyzing the orbit constraint of the proper satellite calibration, the GF-1solar synchronous orbit is chose as the proper satellite orbit in order to simulate the calibration visible durance for different satellites to be calibrated. The results of simulation and analysis provide the basis for the improvement of the radiometric calibration accuracy of the satellite remote sensor, which lays the foundation for the high precision and high frequency radiometric calibration.

A comparison between families obtained from different proper elements

NASA Technical Reports Server (NTRS)

Zappala, Vincenzo; Cellino, Alberto; Farinella, Paolo

1992-01-01

Using the hierarchical method of family identification developed by Zappala et al., the results coming from the data set of proper elements computed by Williams (about 2100 numbered + about 1200 PLS 2 asteroids) and by Milani and Knezevic (5.7 version, about 4200 asteroids) are compared. Apart from some expected discrepancies due to the different data sets and/or low accuracy of proper elements computed in peculiar dynamical zones, a good agreement was found in several cases. It follows that these high reliability families represent a sample which can be considered independent on the methods used for their proper elements computation. Therefore, they should be considered as the best candidates for detailed physical studies.

Reconstruction of spatio-temporal temperature from sparse historical records using robust probabilistic principal component regression

USGS Publications Warehouse

Tipton, John; Hooten, Mevin B.; Goring, Simon

2017-01-01

Scientific records of temperature and precipitation have been kept for several hundred years, but for many areas, only a shorter record exists. To understand climate change, there is a need for rigorous statistical reconstructions of the paleoclimate using proxy data. Paleoclimate proxy data are often sparse, noisy, indirect measurements of the climate process of interest, making each proxy uniquely challenging to model statistically. We reconstruct spatially explicit temperature surfaces from sparse and noisy measurements recorded at historical United States military forts and other observer stations from 1820 to 1894. One common method for reconstructing the paleoclimate from proxy data is principal component regression (PCR). With PCR, one learns a statistical relationship between the paleoclimate proxy data and a set of climate observations that are used as patterns for potential reconstruction scenarios. We explore PCR in a Bayesian hierarchical framework, extending classical PCR in a variety of ways. First, we model the latent principal components probabilistically, accounting for measurement error in the observational data. Next, we extend our method to better accommodate outliers that occur in the proxy data. Finally, we explore alternatives to the truncation of lower-order principal components using different regularization techniques. One fundamental challenge in paleoclimate reconstruction efforts is the lack of out-of-sample data for predictive validation. Cross-validation is of potential value, but is computationally expensive and potentially sensitive to outliers in sparse data scenarios. To overcome the limitations that a lack of out-of-sample records presents, we test our methods using a simulation study, applying proper scoring rules including a computationally efficient approximation to leave-one-out cross-validation using the log score to validate model performance. The result of our analysis is a spatially explicit reconstruction of spatio-temporal temperature from a very sparse historical record.

High-performance parallel computing in the classroom using the public goods game as an example

NASA Astrophysics Data System (ADS)

Perc, Matjaž

2017-07-01

The use of computers in statistical physics is common because the sheer number of equations that describe the behaviour of an entire system particle by particle often makes it impossible to solve them exactly. Monte Carlo methods form a particularly important class of numerical methods for solving problems in statistical physics. Although these methods are simple in principle, their proper use requires a good command of statistical mechanics, as well as considerable computational resources. The aim of this paper is to demonstrate how the usage of widely accessible graphics cards on personal computers can elevate the computing power in Monte Carlo simulations by orders of magnitude, thus allowing live classroom demonstration of phenomena that would otherwise be out of reach. As an example, we use the public goods game on a square lattice where two strategies compete for common resources in a social dilemma situation. We show that the second-order phase transition to an absorbing phase in the system belongs to the directed percolation universality class, and we compare the time needed to arrive at this result by means of the main processor and by means of a suitable graphics card. Parallel computing on graphics processing units has been developed actively during the last decade, to the point where today the learning curve for entry is anything but steep for those familiar with programming. The subject is thus ripe for inclusion in graduate and advanced undergraduate curricula, and we hope that this paper will facilitate this process in the realm of physics education. To that end, we provide a documented source code for an easy reproduction of presented results and for further development of Monte Carlo simulations of similar systems.

A survey for low-mass stellar and substellar members of the Hyades open cluster

NASA Astrophysics Data System (ADS)

Melnikov, Stanislav; Eislöffel, Jochen

2018-03-01

Context. Unlike young open clusters (with ages < 250 Myr), the Hyades cluster (age 600 Myr) has a clear deficit of very low-mass stars (VLM) and brown dwarfs (BD). Since this open cluster has a low stellar density and covers several tens of square degrees on the sky, extended surveys are required to improve the statistics of the VLM/BD objects in the cluster. Aim. We search for new VLM stars and BD candidates in the Hyades cluster to improve the present-day cluster mass function down to substellar masses. Methods: An imaging survey of the Hyades with a completeness limit of 21.m5 in the R band and 20.m5 in the I band was carried out with the 2k × 2k CCD Schmidt camera at the 2 m Alfred Jensch Telescope in Tautenburg. We performed a photometric selection of the cluster member candidates by combining results of our survey with 2MASS JHKs photometry Results: We present a photometric and proper motion survey covering 23.4 deg2 in the Hyades cluster core region. Using optical/IR colour-magnitude diagrams, we identify 66 photometric cluster member candidates in the magnitude range 14.m7 < I < 20.m5. The proper motion measurements are based on several all-sky surveys with an epoch difference of 60-70 yr for the bright objects. The proper motions allowed us to discriminate the cluster members from field objects and resulted in 14 proper motion members of the Hyades. We rediscover Hy 6 as a proper motion member and classify it as a substellar object candidate (BD) based on the comparison of the observed colour-magnitude diagram with theoretical model isochrones. Conclusions: With our results, the mass function of the Hyades continues to be shallow below 0.15 M⊙ indicating that the Hyades have probably lost their lowest mass members by means of dynamical evolution. We conclude that the Hyades core represents the "VLM/BD desert" and that most of the substeller objects may have already left the volume of the cluster.

The Use and Abuse of Limits of Detection in Environmental Analytical Chemistry

PubMed Central

Brown, Richard J. C.

2008-01-01

The limit of detection (LoD) serves as an important method performance measure that is useful for the comparison of measurement techniques and the assessment of likely signal to noise performance, especially in environmental analytical chemistry. However, the LoD is only truly related to the precision characteristics of the analytical instrument employed for the analysis and the content of analyte in the blank sample. This article discusses how other criteria, such as sampling volume, can serve to distort the quoted LoD artificially and make comparison between various analytical methods inequitable. In order to compare LoDs between methods properly, it is necessary to state clearly all of the input parameters relating to the measurements that have been used in the calculation of the LoD. Additionally, the article discusses that the use of LoDs in contexts other than the comparison of the attributes of analytical methods, in particular when reporting analytical results, may be confusing, less informative than quoting the actual result with an accompanying statement of uncertainty, and may act to bias descriptive statistics. PMID:18690384

True orbit simulation of piecewise linear and linear fractional maps of arbitrary dimension using algebraic numbers

NASA Astrophysics Data System (ADS)

Saito, Asaki; Yasutomi, Shin-ichi; Tamura, Jun-ichi; Ito, Shunji

2015-06-01

We introduce a true orbit generation method enabling exact simulations of dynamical systems defined by arbitrary-dimensional piecewise linear fractional maps, including piecewise linear maps, with rational coefficients. This method can generate sufficiently long true orbits which reproduce typical behaviors (inherent behaviors) of these systems, by properly selecting algebraic numbers in accordance with the dimension of the target system, and involving only integer arithmetic. By applying our method to three dynamical systems—that is, the baker's transformation, the map associated with a modified Jacobi-Perron algorithm, and an open flow system—we demonstrate that it can reproduce their typical behaviors that have been very difficult to reproduce with conventional simulation methods. In particular, for the first two maps, we show that we can generate true orbits displaying the same statistical properties as typical orbits, by estimating the marginal densities of their invariant measures. For the open flow system, we show that an obtained true orbit correctly converges to the stable period-1 orbit, which is inherently possessed by the system.

Multi-object segmentation using coupled nonparametric shape and relative pose priors

NASA Astrophysics Data System (ADS)

Uzunbas, Mustafa Gökhan; Soldea, Octavian; Çetin, Müjdat; Ünal, Gözde; Erçil, Aytül; Unay, Devrim; Ekin, Ahmet; Firat, Zeynep

2009-02-01

We present a new method for multi-object segmentation in a maximum a posteriori estimation framework. Our method is motivated by the observation that neighboring or coupling objects in images generate configurations and co-dependencies which could potentially aid in segmentation if properly exploited. Our approach employs coupled shape and inter-shape pose priors that are computed using training images in a nonparametric multi-variate kernel density estimation framework. The coupled shape prior is obtained by estimating the joint shape distribution of multiple objects and the inter-shape pose priors are modeled via standard moments. Based on such statistical models, we formulate an optimization problem for segmentation, which we solve by an algorithm based on active contours. Our technique provides significant improvements in the segmentation of weakly contrasted objects in a number of applications. In particular for medical image analysis, we use our method to extract brain Basal Ganglia structures, which are members of a complex multi-object system posing a challenging segmentation problem. We also apply our technique to the problem of handwritten character segmentation. Finally, we use our method to segment cars in urban scenes.

26 CFR 1.9002-3 - Election to have the provisions of section 481 of the Internal Revenue Code of 1954 not apply.

Code of Federal Regulations, 2010 CFR

2010-04-01

... the taxpayer is changed to a method proper under the accrual method of accounting, then the taxpayer may elect to have such change treated as not a change in method of accounting to which the provisions... recomputed under a proper method of accounting for dealer reserve income for each taxable year to which the...

Cluster membership probability: polarimetric approach

NASA Astrophysics Data System (ADS)

Medhi, Biman J.; Tamura, Motohide

2013-04-01

Interstellar polarimetric data of the six open clusters Hogg 15, NGC 6611, NGC 5606, NGC 6231, NGC 5749 and NGC 6250 have been used to estimate the membership probability for the stars within them. For proper-motion member stars, the membership probability estimated using the polarimetric data is in good agreement with the proper-motion cluster membership probability. However, for proper-motion non-member stars, the membership probability estimated by the polarimetric method is in total disagreement with the proper-motion cluster membership probability. The inconsistencies in the determined memberships may be because of the fundamental differences between the two methods of determination: one is based on stellar proper motion in space and the other is based on selective extinction of the stellar output by the asymmetric aligned dust grains present in the interstellar medium. The results and analysis suggest that the scatter of the Stokes vectors q (per cent) and u (per cent) for the proper-motion member stars depends on the interstellar and intracluster differential reddening in the open cluster. It is found that this method could be used to estimate the cluster membership probability if we have additional polarimetric and photometric information for a star to identify it as a probable member/non-member of a particular cluster, such as the maximum wavelength value (λmax), the unit weight error of the fit (σ1), the dispersion in the polarimetric position angles (overline{ɛ }), reddening (E(B - V)) or the differential intracluster reddening (ΔE(B - V)). This method could also be used to estimate the membership probability of known member stars having no membership probability as well as to resolve disagreements about membership among different proper-motion surveys.

Analysis of delay reducing and fuel saving sequencing and spacing algorithms for arrival traffic

NASA Technical Reports Server (NTRS)

Neuman, Frank; Erzberger, Heinz

1991-01-01

The air traffic control subsystem that performs sequencing and spacing is discussed. The function of the sequencing and spacing algorithms is to automatically plan the most efficient landing order and to assign optimally spaced landing times to all arrivals. Several algorithms are described and their statistical performance is examined. Sequencing brings order to an arrival sequence for aircraft. First-come-first-served sequencing (FCFS) establishes a fair order, based on estimated times of arrival, and determines proper separations. Because of the randomness of the arriving traffic, gaps will remain in the sequence of aircraft. Delays are reduced by time-advancing the leading aircraft of each group while still preserving the FCFS order. Tightly spaced groups of aircraft remain with a mix of heavy and large aircraft. Spacing requirements differ for different types of aircraft trailing each other. Traffic is reordered slightly to take advantage of this spacing criterion, thus shortening the groups and reducing average delays. For heavy traffic, delays for different traffic samples vary widely, even when the same set of statistical parameters is used to produce each sample. This report supersedes NASA TM-102795 on the same subject. It includes a new method of time-advance as well as an efficient method of sequencing and spacing for two dependent runways.

Dynamical Classifications of the Kuiper Belt

NASA Astrophysics Data System (ADS)

Maggard, Steven; Ragozzine, Darin

2018-04-01

The Minor Planet Center (MPC) contains a plethora of observational data on thousands of Kuiper Belt Objects (KBOs). Understanding their orbital properties refines our understanding of the formation of the solar system. My analysis pipeline, BUNSHIN, uses Bayesian methods to take the MPC observations and generate 30 statistically weighted orbital clones for each KBO that are propagated backwards along their orbits until the beginning of the solar system. These orbital integrations are saved as REBOUND SimulationArchive files (Rein & Tamayo 2017) which we will make publicly available, allowing many others to perform statistically-robust dynamical classification or complex dynamical investigations of outer solar system small bodies.This database has been used to expand the known collisional family members of the dwarf planet Haumea. Detailed orbital integrations are required to determine the dynamical distances between family members, in the form of "Delta v" as measured from conserved proper orbital elements (Ragozzine & Brown 2007). Our preliminary results have already ~tripled the number of known Haumea family members, allowing us to show that the Haumea family can be identified purely through dynamical clustering.We will discuss the methods associated with BUNSHIN and the database it generates, the refinement of the updated Haumea family, a brief search for other possible clusterings in the outer solar system, and the potential of our research to aid other dynamicists.

Taguchi Based Performance and Reliability Improvement of an Ion Chamber Amplifier for Enhanced Nuclear Reactor Safety

NASA Astrophysics Data System (ADS)

Kulkarni, R. D.; Agarwal, Vivek

2008-08-01

An ion chamber amplifier (ICA) is used as a safety device for neutronic power (flux) measurement in regulation and protection systems of nuclear reactors. Therefore, performance reliability of an ICA is an important issue. Appropriate quality engineering is essential to achieve a robust design and performance of the ICA circuit. It is observed that the low input bias current operational amplifiers used in the input stage of the ICA circuit are the most critical devices for proper functioning of the ICA. They are very sensitive to the gamma radiation present in their close vicinity. Therefore, the response of the ICA deteriorates with exposure to gamma radiation resulting in a decrease in the overall reliability, unless desired performance is ensured under all conditions. This paper presents a performance enhancement scheme for an ICA operated in the nuclear environment. The Taguchi method, which is a proven technique for reliability enhancement, has been used in this work. It is demonstrated that if a statistical, optimal design approach, like the Taguchi method is used, the cost of high quality and reliability may be brought down drastically. The complete methodology and statistical calculations involved are presented, as are the experimental and simulation results to arrive at a robust design of the ICA.

Va-Room: Motorcycle Safety.

ERIC Educational Resources Information Center

Keller, Rosanne

One of a series of instructional materials produced by the Literacy Council of Alaska, this booklet provides information about motorcycle safety. Using a simplified vocabulary and shorter sentences, it offers statistics concerning motorcycle accidents; information on how to choose the proper machine; basic information about the operation of the…

76 FR 52533 - Personnel Records

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-23

... financial impact on agencies. Another commenter stated that the OPM's Enterprise Human Resource Integration..., statistical analysis, and raw data used to justify the rule and the human capital cost increase to implement... activities that are properly considered functions of agency human resources offices and thus ensure that an...

A Proper Perspective on the Twin Deficits

DTIC Science & Technology

1989-05-01

deficit twins, the relation between them, and their consanguine parentage. The trade deficit or, to be more accurate, the current account deficit, is...In general, there is a small negative, but statistically significant, relationship between the size of the federal deficit in one year and the

77 FR 65358 - Submission for OMB Review; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-26

... National Agricultural Statistics Service (NASS) primary function of collecting, processing, and...) Whether the collection of information is necessary for the proper performance of the functions of the...'' program (non-immigrants who enter the United States for temporary or seasonal agricultural labor) and for...

INTEGRATION OF STATISTICS, REMOTE SENSING AND EXISTING DATA TO LOCATE CHANGES IN LAND RESOURCES

EPA Science Inventory

Stability of a nation is dependent on the availability of natural resources. When land is degraded and natural resources become limited, socioeconomic status declines and emigration increases in developing countries. Natural resource utilization without proper management may re...

A question of style: method, integrity and the meaning of proper science.

PubMed

Penders, Bart; Vos, Rein; Horstman, Klasien

2009-09-01

Controversies in science often centre on methodology and integrity; these are the gatekeepers of proper science. But what exactly defines proper science as proper is not universal, especially in collaborative fields of enquiry where different perspectives meet. These encounters often result in friction, yet may equally give rise to new perspectives on proper science. A tour of collaborative endeavours like structural biology and nutrigenomics highlights some of those frictions and the controversies that can result from the encounter of 'wet' and 'dry' science. Attuning scientists to the plurality of proper science may safeguard many a scientist's integrity from being questioned unjustly.

Analysis of defect structure in silicon. Characterization of samples from UCP ingot 5848-13C

NASA Technical Reports Server (NTRS)

Natesh, R.; Guyer, T.; Stringfellow, G. B.

1982-01-01

Statistically significant quantitative structural imperfection measurements were made on samples from ubiquitous crystalline process (UCP) Ingot 5848 - 13 C. Important trends were noticed between the measured data, cell efficiency, and diffusion length. Grain boundary substructure appears to have an important effect on the conversion efficiency of solar cells from Semix material. Quantitative microscopy measurements give statistically significant information compared to other microanalytical techniques. A surface preparation technique to obtain proper contrast of structural defects suitable for QTM analysis was perfected.

Practice, awareness and opinion of pharmacists toward disposal of unwanted medications in Kuwait

PubMed Central

Abahussain, Eman; Waheedi, Mohammad; Koshy, Samuel

2012-01-01

Background The disposal of unwanted medications has been a concern in many countries, as pharmaceutical waste enters the ecosystem, ultimately having an effect on human health and environment. Earlier studies in Kuwait found that the method of disposal by the public was by disposing in the garbage or by flushing down the drain. In accordance with patient preference and environment safety, it would be appropriate to use local government pharmacies as collection points for proper disposal. Objective To determine the practice of pharmacists, working in government healthcare sectors, with regard to disposal of returned unwanted medications by the public. This study also aims to assess pharmacists’ awareness toward the impact of improper disposal on the environment and to investigate whether pharmacists agree to have their pharmacies as collection points for future take-back programs. Method A random sample of 144 pharmacists from the six main governmental hospitals and 12 specialized polyclinics in Kuwait, completed a self-administered questionnaire about their practice of disposal, awareness and opinion on using pharmacies as collection points for proper disposal of UMs. Data were analyzed using descriptive statistics. Results A total of 144 pharmacists completed the survey. Throwing UMs in the trash was the main method of disposal by majority of the respondents (73%). Only 23 pharmacists disposed UMs according to the guidelines of Ministry of Health, Kuwait (MOH). However, about 82% are aware that improper disposal causes damage to the environment and 97% agree that it is their responsibility to protect the environment. About 86–88% of the pharmacists agree to have government hospital pharmacies and polyclinics as collection points for future take-back programs. Conclusion Even though the current practice of disposal by majority of pharmacists is inappropriate, they are aware of the damage and acknowledge their responsibilities toward environment protection. Concerned authorities should monitor and implement proper disposal guidelines in all pharmacies. Majority of pharmacists support the idea of having the government pharmacies as collection points for safe disposal of UMs in Kuwait. PMID:23960793

Yarkovsky footprints in the Eos family

NASA Astrophysics Data System (ADS)

Vokrouhlický, D.; Brož, M.; Morbidelli, A.; Bottke, W. F.; Nesvorný, D.; Lazzaro, D.; Rivkin, A. S.

2006-05-01

The Eos asteroid family is the third most populous, after Themis and Koronis, and one of the largest non-random groups of asteroids in the main belt. It has been known and studied for decades, but its structure and history still presented difficulties to understand. We first revise the Eos family identification as a statistical cluster in the space of proper elements. Using the most to-date catalogue of proper elements we determine a nominal Eos family, defined by us using the hierarchical-clustering method with the cut-off velocity of 55 m/s, contains some 4400 members. This unforeseen increase in known Eos asteroids allows us to perform a much more detailed study than was possible so far. We show, in particular, that most of the previously thought peculiar features are explained within the following model: (i) collisional disruption of the parent body leads to formation of a compact family in the proper element space (with characteristic escape velocities of the observed asteroids of tens of meters per second, compatible with hydrocode simulations), and (ii) as time goes, the family dynamically evolves due to a combination of the thermal effects and planetary perturbations. This model allows us to explain sharp termination of the family at the J7/3 mean motion resonance with Jupiter, uneven distribution of family members about the J9/4 mean motion resonance with Jupiter, semimajor axis distribution of large vs small members in the family and anomalous residence of Eos members inside the high-order secular resonance z. Our dynamical method also allows us to estimate Eos family age to 1.3-0.2+0.15 Gyr. Several formal members of the Eos family are in conflict with our model and these are suspected interlopers. We use spectroscopic observations, whose results are also reported here, and results of 5-color wide-band Sloan Digital Sky Survey photometry to prove some of them are indeed spectrally incompatible with the family.

Assessment of changing interdependencies between human electroencephalograms using nonlinear methods

NASA Astrophysics Data System (ADS)

Pereda, E.; Rial, R.; Gamundi, A.; González, J.

2001-01-01

We investigate the problems that might arise when two recently developed methods for detecting interdependencies between time series using state space embedding are applied to signals of different complexity. With this aim, these methods were used to assess the interdependencies between two electroencephalographic channels from 10 adult human subjects during different vigilance states. The significance and nature of the measured interdependencies were checked by comparing the results of the original data with those of different types of surrogates. We found that even with proper reconstructions of the dynamics of the time series, both methods may give wrong statistical evidence of decreasing interdependencies during deep sleep due to changes in the complexity of each individual channel. The main factor responsible for this result was the use of an insufficient number of neighbors in the calculations. Once this problem was surmounted, both methods showed the existence of a significant relationship between the channels which was mostly of linear type and increased from awake to slow wave sleep. We conclude that the significance of the qualitative results provided for both methods must be carefully tested before drawing any conclusion about the implications of such results.

Evaluation of Methods Used for Estimating Selected Streamflow Statistics, and Flood Frequency and Magnitude, for Small Basins in North Coastal California

USGS Publications Warehouse

Mann, Michael P.; Rizzardo, Jule; Satkowski, Richard

2004-01-01

Accurate streamflow statistics are essential to water resource agencies involved in both science and decision-making. When long-term streamflow data are lacking at a site, estimation techniques are often employed to generate streamflow statistics. However, procedures for accurately estimating streamflow statistics often are lacking. When estimation procedures are developed, they often are not evaluated properly before being applied. Use of unevaluated or underevaluated flow-statistic estimation techniques can result in improper water-resources decision-making. The California State Water Resources Control Board (SWRCB) uses two key techniques, a modified rational equation and drainage basin area-ratio transfer, to estimate streamflow statistics at ungaged locations. These techniques have been implemented to varying degrees, but have not been formally evaluated. For estimating peak flows at the 2-, 5-, 10-, 25-, 50-, and 100-year recurrence intervals, the SWRCB uses the U.S. Geological Surveys (USGS) regional peak-flow equations. In this study, done cooperatively by the USGS and SWRCB, the SWRCB estimated several flow statistics at 40 USGS streamflow gaging stations in the north coast region of California. The SWRCB estimates were made without reference to USGS flow data. The USGS used the streamflow data provided by the 40 stations to generate flow statistics that could be compared with SWRCB estimates for accuracy. While some SWRCB estimates compared favorably with USGS statistics, results were subject to varying degrees of error over the region. Flow-based estimation techniques generally performed better than rain-based methods, especially for estimation of December 15 to March 31 mean daily flows. The USGS peak-flow equations also performed well, but tended to underestimate peak flows. The USGS equations performed within reported error bounds, but will require updating in the future as peak-flow data sets grow larger. Little correlation was discovered between estimation errors and geographic locations or various basin characteristics. However, for 25-percentile year mean-daily-flow estimates for December 15 to March 31, the greatest estimation errors were at east San Francisco Bay area stations with mean annual precipitation less than or equal to 30 inches, and estimated 2-year/24-hour rainfall intensity less than 3 inches.

Parsec's astrometry direct approaches .

NASA Astrophysics Data System (ADS)

Andrei, A. H.

Parallaxes - and hence the fundamental establishment of stellar distances - rank among the oldest, keyest, and hardest of astronomical determinations. Arguably amongst the most essential too. The direct approach to obtain trigonometric parallaxes, using a constrained set of equations to derive positions, proper motions, and parallaxes, has been labeled as risky. Properly so, because the axis of the parallactic apparent ellipse is smaller than one arcsec even for the nearest stars, and just a fraction of its perimeter can be followed. Thus the classical approach is of linearizing the description by locking the solution to a set of precise positions of the Earth at the instants of observation, rather than to the dynamics of its orbit, and of adopting a close examination of the never many points available. In the PARSEC program the parallaxes of 143 brown dwarfs were aimed at. Five years of observation of the fields were taken with the WIFI camera at the ESO 2.2m telescope, in Chile. The goal is to provide a statistically significant number of trigonometric parallaxes to BD sub-classes from L0 to T7. Taking advantage of the large, regularly spaced, quantity of observations, here we take the risky approach to fit an ellipse in ecliptical observed coordinates and derive the parallaxes. We also combine the solutions from different centroiding methods, widely proven in prior astrometric investigations. As each of those methods assess diverse properties of the PSFs, they are taken as independent measurements, and combined into a weighted least-square general solution.

Brain Activity during Mental Imagery of Gait Versus Gait-Like Plantar Stimulation: A Novel Combined Functional MRI Paradigm to Better Understand Cerebral Gait Control.

PubMed

Labriffe, Matthieu; Annweiler, Cédric; Amirova, Liubov E; Gauquelin-Koch, Guillemette; Ter Minassian, Aram; Leiber, Louis-Marie; Beauchet, Olivier; Custaud, Marc-Antoine; Dinomais, Mickaël

2017-01-01

Human locomotion is a complex sensorimotor behavior whose central control remains difficult to explore using neuroimaging method due to technical constraints, notably the impossibility to walk with a scanner on the head and/or to walk for real inside current scanners. The aim of this functional Magnetic Resonance Imaging (fMRI) study was to analyze interactions between two paradigms to investigate the brain gait control network: (1) mental imagery of gait, and (2) passive mechanical stimulation of the plantar surface of the foot with the Korvit boots. The Korvit stimulator was used through two different modes, namely an organized ("gait like") sequence and a destructured (chaotic) pattern. Eighteen right-handed young healthy volunteers were recruited (mean age, 27 ± 4.7 years). Mental imagery activated a broad neuronal network including the supplementary motor area-proper (SMA-proper), pre-SMA, the dorsal premotor cortex, ventrolateral prefrontal cortex, anterior insula, and precuneus/superior parietal areas. The mechanical plantar stimulation activated the primary sensorimotor cortex and secondary somatosensory cortex bilaterally. The paradigms generated statistically common areas of activity, notably bilateral SMA-proper and right pre-SMA, highlighting the potential key role of SMA in gait control. There was no difference between the organized and chaotic Korvit sequences, highlighting the difficulty of developing a walking-specific plantar stimulation paradigm. In conclusion, this combined-fMRI paradigm combining mental imagery and gait-like plantar stimulation provides complementary information regarding gait-related brain activity and appears useful for the assessment of high-level gait control.

On the Least-Squares Fitting of Correlated Data: a Priorivs a PosterioriWeighting

NASA Astrophysics Data System (ADS)

Tellinghuisen, Joel

1996-10-01

One of the methods in common use for analyzing large data sets is a two-step procedure, in which subsets of the full data are first least-squares fitted to a preliminary set of parameters, and the latter are subsequently merged to yield the final parameters. The second step of this procedure is properly a correlated least-squares fit and requires the variance-covariance matrices from the first step to construct the weight matrix for the merge. There is, however, an ambiguity concerning the manner in which the first-step variance-covariance matrices are assessed, which leads to different statistical properties for the quantities determined in the merge. The issue is one ofa priorivsa posterioriassessment of weights, which is an application of what was originally calledinternalvsexternal consistencyby Birge [Phys. Rev.40,207-227 (1932)] and Deming ("Statistical Adjustment of Data." Dover, New York, 1964). In the present work the simplest case of a merge fit-that of an average as obtained from a global fit vs a two-step fit of partitioned data-is used to illustrate that only in the case of a priori weighting do the results have the usually expected and desired statistical properties: normal distributions for residuals,tdistributions for parameters assessed a posteriori, and χ2distributions for variances.

Optimizing the maximum reported cluster size in the spatial scan statistic for ordinal data.

PubMed

Kim, Sehwi; Jung, Inkyung

2017-01-01

The spatial scan statistic is an important tool for spatial cluster detection. There have been numerous studies on scanning window shapes. However, little research has been done on the maximum scanning window size or maximum reported cluster size. Recently, Han et al. proposed to use the Gini coefficient to optimize the maximum reported cluster size. However, the method has been developed and evaluated only for the Poisson model. We adopt the Gini coefficient to be applicable to the spatial scan statistic for ordinal data to determine the optimal maximum reported cluster size. Through a simulation study and application to a real data example, we evaluate the performance of the proposed approach. With some sophisticated modification, the Gini coefficient can be effectively employed for the ordinal model. The Gini coefficient most often picked the optimal maximum reported cluster sizes that were the same as or smaller than the true cluster sizes with very high accuracy. It seems that we can obtain a more refined collection of clusters by using the Gini coefficient. The Gini coefficient developed specifically for the ordinal model can be useful for optimizing the maximum reported cluster size for ordinal data and helpful for properly and informatively discovering cluster patterns.

Optimizing the maximum reported cluster size in the spatial scan statistic for ordinal data

PubMed Central

Kim, Sehwi

2017-01-01

The spatial scan statistic is an important tool for spatial cluster detection. There have been numerous studies on scanning window shapes. However, little research has been done on the maximum scanning window size or maximum reported cluster size. Recently, Han et al. proposed to use the Gini coefficient to optimize the maximum reported cluster size. However, the method has been developed and evaluated only for the Poisson model. We adopt the Gini coefficient to be applicable to the spatial scan statistic for ordinal data to determine the optimal maximum reported cluster size. Through a simulation study and application to a real data example, we evaluate the performance of the proposed approach. With some sophisticated modification, the Gini coefficient can be effectively employed for the ordinal model. The Gini coefficient most often picked the optimal maximum reported cluster sizes that were the same as or smaller than the true cluster sizes with very high accuracy. It seems that we can obtain a more refined collection of clusters by using the Gini coefficient. The Gini coefficient developed specifically for the ordinal model can be useful for optimizing the maximum reported cluster size for ordinal data and helpful for properly and informatively discovering cluster patterns. PMID:28753674

Antitumor Efficacy Testing in Rodents

PubMed Central

2008-01-01

The preclinical research and human clinical trials necessary for developing anticancer therapeutics are costly. One contributor to these costs is preclinical rodent efficacy studies, which, in addition to the costs associated with conducting them, often guide the selection of agents for clinical development. If inappropriate or inaccurate recommendations are made on the basis of these preclinical studies, then additional costs are incurred. In this commentary, I discuss the issues associated with preclinical rodent efficacy studies. These include the identification of proper preclinical efficacy models, the selection of appropriate experimental endpoints, and the correct statistical evaluation of the resulting data. I also describe important experimental design considerations, such as selecting the drug vehicle, optimizing the therapeutic treatment plan, properly powering the experiment by defining appropriate numbers of replicates in each treatment arm, and proper randomization. Improved preclinical selection criteria can aid in reducing unnecessary human studies, thus reducing the overall costs of anticancer drug development. PMID:18957675

Proper Motion of Components in 4C 39.25

NASA Technical Reports Server (NTRS)

Guirado, J. C.; Marcaide, J. M.; Alberdi, A.; Elosegui, P.; Ratner, M. I.; Shapiro, I. I.; Kilger, R.; Mantovani, F.; Venturi, T.; Rius, A.;

Radio Measurements of the Stellar Proper Motions in the Core of the Orion Nebula Cluster

NASA Astrophysics Data System (ADS)

Dzib, Sergio A.; Loinard, Laurent; Rodríguez, Luis F.; Gómez, Laura; Forbrich, Jan; Menten, Karl M.; Kounkel, Marina A.; Mioduszewski, Amy J.; Hartmann, Lee; Tobin, John J.; Rivera, Juana L.

2017-01-01

Using multi-epoch Very Large Array observations, covering a time baseline of 29.1 years, we have measured the proper motions of 88 young stars with compact radio emission in the core of the Orion Nebula Cluster (ONC) and the neighboring BN/KL region. Our work increases the number of young stars with measured proper motion at radio frequencies by a factor of 2.5 and enables us to perform a better statistical analysis of the kinematics of the region than was previously possible. Most stars (79 out of 88) have proper motions consistent with a Gaussian distribution centered on \\overline{{μ }α \\cos δ }=1.07+/- 0.09 mas yr-1, and \\overline{{μ }δ }=-0.84+/- 0.16 mas yr-1, with velocity dispersions of {σ }α =1.08+/- 0.07 mas yr-1, {σ }δ =1.27+/- 0.15 mas yr-1. We looked for organized movements of these stars but found no clear indication of radial expansion/contraction or rotation. The remaining nine stars in our sample show peculiar proper motions that differ from the mean proper motions of the ONC by more than 3σ. One of these stars, V 1326 Ori, could have been expelled from the Orion Trapezium 7000 years ago. Two could be related to the multi-stellar disintegration in the BN/KL region, in addition to the previously known sources BN, I and n. The others either have high uncertainties (so their anomalous proper motions are not firmly established) or could be foreground objects.

75 FR 69128 - Proposed Collection, Comment Request

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2010-11-10

... ensure that requested data can be provided in the desired format, reporting burden (time and financial... requirements on respondents can be properly assessed. The Bureau of Labor Statistics (BLS) is soliciting... Goods and Services Survey.'' A copy of the proposed information collection request (ICR) can be obtained...

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Analysis of sequencing and scheduling methods for arrival traffic

NASA Technical Reports Server (NTRS)

Neuman, Frank; Erzberger, Heinz

1990-01-01

The air traffic control subsystem that performs scheduling is discussed. The function of the scheduling algorithms is to plan automatically the most efficient landing order and to assign optimally spaced landing times to all arrivals. Several important scheduling algorithms are described and the statistical performance of the scheduling algorithms is examined. Scheduling brings order to an arrival sequence for aircraft. First-come-first-served scheduling (FCFS) establishes a fair order, based on estimated times of arrival, and determines proper separations. Because of the randomness of the traffic, gaps will remain in the scheduled sequence of aircraft. These gaps are filled, or partially filled, by time-advancing the leading aircraft after a gap while still preserving the FCFS order. Tightly scheduled groups of aircraft remain with a mix of heavy and large aircraft. Separation requirements differ for different types of aircraft trailing each other. Advantage is taken of this fact through mild reordering of the traffic, thus shortening the groups and reducing average delays. Actual delays for different samples with the same statistical parameters vary widely, especially for heavy traffic.

Alarms about structural alerts.

PubMed

Alves, Vinicius; Muratov, Eugene; Capuzzi, Stephen; Politi, Regina; Low, Yen; Braga, Rodolpho; Zakharov, Alexey V; Sedykh, Alexander; Mokshyna, Elena; Farag, Sherif; Andrade, Carolina; Kuz'min, Victor; Fourches, Denis; Tropsha, Alexander

2016-08-21

Structural alerts are widely accepted in chemical toxicology and regulatory decision support as a simple and transparent means to flag potential chemical hazards or group compounds into categories for read-across. However, there has been a growing concern that alerts disproportionally flag too many chemicals as toxic, which questions their reliability as toxicity markers. Conversely, the rigorously developed and properly validated statistical QSAR models can accurately and reliably predict the toxicity of a chemical; however, their use in regulatory toxicology has been hampered by the lack of transparency and interpretability. We demonstrate that contrary to the common perception of QSAR models as "black boxes" they can be used to identify statistically significant chemical substructures (QSAR-based alerts) that influence toxicity. We show through several case studies, however, that the mere presence of structural alerts in a chemical, irrespective of the derivation method (expert-based or QSAR-based), should be perceived only as hypotheses of possible toxicological effect. We propose a new approach that synergistically integrates structural alerts and rigorously validated QSAR models for a more transparent and accurate safety assessment of new chemicals.

``Physical Concepts in Cell Biology,'' an upper level interdisciplinary course in cell biophysics/mathematical biology

NASA Astrophysics Data System (ADS)

Vavylonis, Dimitrios

2009-03-01

I will describe my experience in developing an interdisciplinary biophysics course addressed to students at the upper undergraduate and graduate level, in collaboration with colleagues in physics and biology. The students had a background in physics, biology and engineering, and for many the course was their first exposure to interdisciplinary topics. The course did not depend on a formal knowledge of equilibrium statistical mechanics. Instead, the approach was based on dynamics. I used diffusion as a universal ``long time'' law to illustrate scaling concepts. The importance of statistics and proper counting of states/paths was introduced by calculating the maximum accuracy with which bacteria can measure the concentration of diffuse chemicals. The use of quantitative concepts and methods was introduced through specific biological examples, focusing on model organisms and extremes at the cell level. Examples included microtubule dynamic instability, the search and capture model, molecular motor cooperativity in muscle cells, mitotic spindle oscillations in C. elegans, polymerization forces and propulsion of pathogenic bacteria, Brownian ratchets, bacterial cell division and MinD oscillations.

Statistical Analyses of Femur Parameters for Designing Anatomical Plates.

PubMed

Wang, Lin; He, Kunjin; Chen, Zhengming

2016-01-01

Femur parameters are key prerequisites for scientifically designing anatomical plates. Meanwhile, individual differences in femurs present a challenge to design well-fitting anatomical plates. Therefore, to design anatomical plates more scientifically, analyses of femur parameters with statistical methods were performed in this study. The specific steps were as follows. First, taking eight anatomical femur parameters as variables, 100 femur samples were classified into three classes with factor analysis and Q-type cluster analysis. Second, based on the mean parameter values of the three classes of femurs, three sizes of average anatomical plates corresponding to the three classes of femurs were designed. Finally, based on Bayes discriminant analysis, a new femur could be assigned to the proper class. Thereafter, the average anatomical plate suitable for that new femur was selected from the three available sizes of plates. Experimental results showed that the classification of femurs was quite reasonable based on the anatomical aspects of the femurs. For instance, three sizes of condylar buttress plates were designed. Meanwhile, 20 new femurs are judged to which classes the femurs belong. Thereafter, suitable condylar buttress plates were determined and selected.

Development of statistical linear regression model for metals from transportation land uses.

PubMed

Maniquiz, Marla C; Lee, Soyoung; Lee, Eunju; Kim, Lee-Hyung

2009-01-01

The transportation landuses possessing impervious surfaces such as highways, parking lots, roads, and bridges were recognized as the highly polluted non-point sources (NPSs) in the urban areas. Lots of pollutants from urban transportation are accumulating on the paved surfaces during dry periods and are washed-off during a storm. In Korea, the identification and monitoring of NPSs still represent a great challenge. Since 2004, the Ministry of Environment (MOE) has been engaged in several researches and monitoring to develop stormwater management policies and treatment systems for future implementation. The data over 131 storm events during May 2004 to September 2008 at eleven sites were analyzed to identify correlation relationships between particulates and metals, and to develop simple linear regression (SLR) model to estimate event mean concentration (EMC). Results indicate that there was no significant relationship between metals and TSS EMC. However, the SLR estimation models although not providing useful results are valuable indicators of high uncertainties that NPS pollution possess. Therefore, long term monitoring employing proper methods and precise statistical analysis of the data should be undertaken to eliminate these uncertainties.

Statistical Approaches to Interpretation of Local, Regional, and National Highway-Runoff and Urban-Stormwater Data

USGS Publications Warehouse

Tasker, Gary D.; Granato, Gregory E.

2000-01-01

Decision makers need viable methods for the interpretation of local, regional, and national-highway runoff and urban-stormwater data including flows, concentrations and loads of chemical constituents and sediment, potential effects on receiving waters, and the potential effectiveness of various best management practices (BMPs). Valid (useful for intended purposes), current, and technically defensible stormwater-runoff models are needed to interpret data collected in field studies, to support existing highway and urban-runoffplanning processes, to meet National Pollutant Discharge Elimination System (NPDES) requirements, and to provide methods for computation of Total Maximum Daily Loads (TMDLs) systematically and economically. Historically, conceptual, simulation, empirical, and statistical models of varying levels of detail, complexity, and uncertainty have been used to meet various data-quality objectives in the decision-making processes necessary for the planning, design, construction, and maintenance of highways and for other land-use applications. Water-quality simulation models attempt a detailed representation of the physical processes and mechanisms at a given site. Empirical and statistical regional water-quality assessment models provide a more general picture of water quality or changes in water quality over a region. All these modeling techniques share one common aspect-their predictive ability is poor without suitable site-specific data for calibration. To properly apply the correct model, one must understand the classification of variables, the unique characteristics of water-resources data, and the concept of population structure and analysis. Classifying variables being used to analyze data may determine which statistical methods are appropriate for data analysis. An understanding of the characteristics of water-resources data is necessary to evaluate the applicability of different statistical methods, to interpret the results of these techniques, and to use tools and techniques that account for the unique nature of water-resources data sets. Populations of data on stormwater-runoff quantity and quality are often best modeled as logarithmic transformations. Therefore, these factors need to be considered to form valid, current, and technically defensible stormwater-runoff models. Regression analysis is an accepted method for interpretation of water-resources data and for prediction of current or future conditions at sites that fit the input data model. Regression analysis is designed to provide an estimate of the average response of a system as it relates to variation in one or more known variables. To produce valid models, however, regression analysis should include visual analysis of scatterplots, an examination of the regression equation, evaluation of the method design assumptions, and regression diagnostics. A number of statistical techniques are described in the text and in the appendixes to provide information necessary to interpret data by use of appropriate methods. Uncertainty is an important part of any decisionmaking process. In order to deal with uncertainty problems, the analyst needs to know the severity of the statistical uncertainty of the methods used to predict water quality. Statistical models need to be based on information that is meaningful, representative, complete, precise, accurate, and comparable to be deemed valid, up to date, and technically supportable. To assess uncertainty in the analytical tools, the modeling methods, and the underlying data set, all of these components need be documented and communicated in an accessible format within project publications.

SPSS and SAS programs for determining the number of components using parallel analysis and velicer's MAP test.

PubMed

O'Connor, B P

2000-08-01

Popular statistical software packages do not have the proper procedures for determining the number of components in factor and principal components analyses. Parallel analysis and Velicer's minimum average partial (MAP) test are validated procedures, recommended widely by statisticians. However, many researchers continue to use alternative, simpler, but flawed procedures, such as the eigenvalues-greater-than-one rule. Use of the proper procedures might be increased if these procedures could be conducted within familiar software environments. This paper describes brief and efficient programs for using SPSS and SAS to conduct parallel analyses and the MAP test.

Electricity Markets, Smart Grids and Smart Buildings

NASA Astrophysics Data System (ADS)

Falcey, Jonathan M.

A smart grid is an electricity network that accommodates two-way power flows, and utilizes two-way communications and increased measurement, in order to provide more information to customers and aid in the development of a more efficient electricity market. The current electrical network is outdated and has many shortcomings relating to power flows, inefficient electricity markets, generation/supply balance, a lack of information for the consumer and insufficient consumer interaction with electricity markets. Many of these challenges can be addressed with a smart grid, but there remain significant barriers to the implementation of a smart grid. This paper proposes a novel method for the development of a smart grid utilizing a bottom up approach (starting with smart buildings/campuses) with the goal of providing the framework and infrastructure necessary for a smart grid instead of the more traditional approach (installing many smart meters and hoping a smart grid emerges). This novel approach involves combining deterministic and statistical methods in order to accurately estimate building electricity use down to the device level. It provides model users with a cheaper alternative to energy audits and extensive sensor networks (the current methods of quantifying electrical use at this level) which increases their ability to modify energy consumption and respond to price signals The results of this method are promising, but they are still preliminary. As a result, there is still room for improvement. On days when there were no missing or inaccurate data, this approach has R2 of about 0.84, sometimes as high as 0.94 when compared to measured results. However, there were many days where missing data brought overall accuracy down significantly. In addition, the development and implementation of the calibration process is still underway and some functional additions must be made in order to maximize accuracy. The calibration process must be completed before a reliable accuracy can be determined. While this work shows that a combination of a deterministic and statistical methods can accurately forecast building energy usage, the ability to produce accurate results is heavily dependent upon software availability, accurate data and the proper calibration of the model. Creating the software required for a smart building model is time consuming and expensive. Bad or missing data have significant negative impacts on the accuracy of the results and can be caused by a hodgepodge of equipment and communication protocols. Proper calibration of the model is essential to ensure that the device level estimations are sufficiently accurate. Any building model which is to be successful at creating a smart building must be able to overcome these challenges.

76 FR 56136 - Lead-Based Paint Renovation, Repair and Painting, and Pre-Renovation Education Activities in...

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2011-09-12

... instructions for each method as provided in Section I of the SUPPLEMENTARY INFORMATION. To ensure proper..., by one of the following methods: 1. http://www.regulations.gov : Follow the on-line instructions for... teach renovation classes, that individuals performing renovation activities are properly trained and...

INTERNAL PROPER MOTIONS IN THE ESKIMO NEBULA

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

García-Díaz, Ma. T.; Gutiérrez, L.; Steffen, W.

We present measurements of internal proper motions at more than 500 positions of NGC 2392, the Eskimo Nebula, based on images acquired with WFPC2 on board the Hubble Space Telescope at two epochs separated by 7.695 yr. Comparisons of the two observations clearly show the expansion of the nebula. We measured the amplitude and direction of the motion of local structures in the nebula by determining their relative shift during that interval. In order to assess the potential uncertainties in the determination of proper motions in this object, in general, the measurements were performed using two different methods, used previously in themore » literature. We compare the results from the two methods, and to perform the scientific analysis of the results we choose one, the cross-correlation method, because it is more reliable. We go on to perform a ''criss-cross'' mapping analysis on the proper motion vectors, which helps in the interpretation of the velocity pattern. By combining our results of the proper motions with radial velocity measurements obtained from high resolution spectroscopic observations, and employing an existing 3D model, we estimate the distance to the nebula to be 1.3 kpc.« less

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.

DIGE Analysis of Human Tissues.

PubMed

Gelfi, Cecilia; Capitanio, Daniele

2018-01-01

Two-dimensional difference gel electrophoresis (2-D DIGE) is an advanced and elegant gel electrophoretic analytical tool for comparative protein assessment. It is based on two-dimensional gel electrophoresis (2-DE) separation of fluorescently labeled protein extracts. The tagging procedures are designed to not interfere with the chemical properties of proteins with respect to their pI and electrophoretic mobility, once a proper labeling protocol is followed. The two-dye or three-dye systems can be adopted and their choice depends on specific applications. Furthermore, the use of an internal pooled standard makes 2-D DIGE a highly accurate quantitative method enabling multiple protein samples to be separated on the same two-dimensional gel. The image matching and cross-gel statistical analysis generates robust quantitative results making data validation by independent technologies successful.

Computers and Cognitive Development at Work

ERIC Educational Resources Information Center

Roth, Wolff-Michael; Lee, Yew-Jin

2006-01-01

Data-logging exercises in science classrooms assume that with the proper scaffolding and provision of contexts by instructors, pupils are able to meaningfully comprehend the experimental variables under investigation. From a case study of knowing and learning in a fish hatchery using real-time computer statistical software, we show that…

Investigating the determining factors for transit travel demand by bus mode in US metropolitan statistical areas.

DOT National Transportation Integrated Search

2015-05-01

Proper understanding of the nature of the transit travel demand is at the heart of transportation policy making and the success of : transit systems. Unfortunately, most of the existing studies have focused on a single or few transit systems or metro...

Roots and Rogues in German Child Language

ERIC Educational Resources Information Center

Duffield, Nigel

2008-01-01

This article is concerned with the proper characterization of subject omission at a particular stage in German child language. It focuses on post-verbal null subjects in finite clauses, here termed Rogues. It is argued that the statistically significant presence of Rogues, in conjunction with their distinct developmental profile, speaks against a…

STATISTICAL EVALUATION OF CONFOCAL MICROSCOPY IMAGES

EPA Science Inventory

Abstract

In this study the CV is defined as the Mean/SD of the population of beads or pixels. Flow cytometry uses the CV of beads to determine if the machine is aligned correctly and performing properly. This CV concept to determine machine performance has been adapted to...

Protect Your Back: Guidelines for Safer Lifting.

ERIC Educational Resources Information Center

Cantu, Carolyn O.

2002-01-01

Examines back injury in teachers and child care providers; includes statistics, common causes of back pain (improper alignment, improper posture, improper lifting, and carrying), and types of back pain (acute and chronic). Focuses on preventing back injury, body mechanics for lifting and carrying, and proper lifting and carrying of children. (SD)

Predicting Contextual Informativeness for Vocabulary Learning

ERIC Educational Resources Information Center

Kapelner, Adam; Soterwood, Jeanine; Nessaiver, Shalev; Adlof, Suzanne

2018-01-01

Vocabulary knowledge is essential to educational progress. High quality vocabulary instruction requires supportive contextual examples to teach word meaning and proper usage. Identifying such contexts by hand for a large number of words can be difficult. In this work, we take a statistical learning approach to engineer a system that predicts…

Principles and Practice of Scaled Difference Chi-Square Testing

ERIC Educational Resources Information Center

Bryant, Fred B.; Satorra, Albert

2012-01-01

We highlight critical conceptual and statistical issues and how to resolve them in conducting Satorra-Bentler (SB) scaled difference chi-square tests. Concerning the original (Satorra & Bentler, 2001) and new (Satorra & Bentler, 2010) scaled difference tests, a fundamental difference exists in how to compute properly a model's scaling correction…

A Constrained Linear Estimator for Multiple Regression

ERIC Educational Resources Information Center

Davis-Stober, Clintin P.; Dana, Jason; Budescu, David V.

2010-01-01

"Improper linear models" (see Dawes, Am. Psychol. 34:571-582, "1979"), such as equal weighting, have garnered interest as alternatives to standard regression models. We analyze the general circumstances under which these models perform well by recasting a class of "improper" linear models as "proper" statistical models with a single predictor. We…

[Morphometry of pulmonary tissue: From manual to high throughput automation].

PubMed

Sallon, C; Soulet, D; Tremblay, Y

2017-12-01

Weibel's research has shown that any alteration of the pulmonary structure has effects on function. This demonstration required a quantitative analysis of lung structures called morphometry. This is possible thanks to stereology, a set of methods based on principles of geometry and statistics. His work has helped to better understand the morphological harmony of the lung, which is essential for its proper functioning. An imbalance leads to pathophysiology such as chronic obstructive pulmonary disease in adults and bronchopulmonary dysplasia in neonates. It is by studying this imbalance that new therapeutic approaches can be developed. These advances are achievable only through morphometric analytical methods, which are increasingly precise and focused, in particular thanks to the high-throughput automation of these methods. This review makes a comparison between an automated method that we developed in the laboratory and semi-manual methods of morphometric analyzes. The automation of morphometric measurements is a fundamental asset in the study of pulmonary pathophysiology because it is an assurance of robustness, reproducibility and speed. This tool will thus contribute significantly to the acceleration of the race for the development of new drugs. Copyright © 2017 SPLF. Published by Elsevier Masson SAS. All rights reserved.

Comparison of water-based foam and inert-gas mass emergency depopulation methods.

PubMed

Alphin, R L; Rankin, M K; Johnson, K J; Benson, E R

2010-03-01

Current control strategies for avian influenza (AI) and other highly contagious poultry diseases include surveillance, quarantine, depopulation, disposal, and decontamination. Selection of the best method of emergency mass depopulation involves maximizing human health and safety while minimizing disease spread and animal welfare concerns. Proper selection must ensure that the method is compatible with the species, age, housing type, and disposal options. No one single method is appropriate for all situations. Gassing is one of the accepted methods for euthanatizing poultry. Whole-house, partial-house, or containerized gassing procedures are currently used. The use of water-based foam was developed for emergency mass depopulation and was conditionally approved by the United States Department of Agriculture in 2006. Research has been done comparing these different methods; parameters such as time to brain death, consistency of time to brain death, and pretreatment and posttreatment corticosterone stress levels were considered. In Europe, the use of foam with carbon dioxide is preferred over conventional water-based foam. A recent experiment comparing CO2 gas, foam with CO2 gas, and foam without CO2 gas depopulation methods was conducted with the use of electroencephalometry results. Foam was as consistent as CO2 gassing and more consistent than argon-CO2 gassing. There were no statistically significant differences between foam methods.

Malaria among gold miners in southern Pará, Brazil: estimates of determinants and individual costs.

PubMed

Vosti, S A

1990-01-01

As malaria grows more prevalent in the Amazon frontier despite increased expenditures by disease control authorities, national and regional tropical disease control strategies are being called into question. The current crisis involving traditional control/eradication methods has broadened the search for feasible and effective malaria control strategies--a search that necessarily includes an investigation of the roles of a series of individual and community-level socioeconomic characteristics in determining malaria prevalence rates, and the proper methods of estimating these links. In addition, social scientists and policy makers alike know very little about the economic costs associated with malarial infections. In this paper, I use survey data from several Brazilian gold mining areas to (a) test the general reliability of malaria-related questionnaire response data, and suggest categorization methods to minimize the statistical influence of exaggerated responses, (b) estimate three statistical models aimed at detecting the socioeconomic determinants of individual malaria prevalence rates, and (c) calculate estimates of the average cost of a single bout of malaria. The results support the general reliability of survey response data gathered in conjunction with malaria research. Once the effects of vector exposure were controlled for, individual socioeconomic characteristics were only weakly linked to malaria prevalence rates in these very special miners' communities. Moreover, the socioeconomic and exposure links that were significant did not depend on the measure of malaria adopted. Finally, individual costs associated with malarial infections were found to be a significant portion of miners' incomes.

A bootstrap estimation scheme for chemical compositional data with nondetects

USGS Publications Warehouse

Palarea-Albaladejo, J; Martín-Fernández, J.A; Olea, Ricardo A.

2014-01-01

The bootstrap method is commonly used to estimate the distribution of estimators and their associated uncertainty when explicit analytic expressions are not available or are difficult to obtain. It has been widely applied in environmental and geochemical studies, where the data generated often represent parts of whole, typically chemical concentrations. This kind of constrained data is generically called compositional data, and they require specialised statistical methods to properly account for their particular covariance structure. On the other hand, it is not unusual in practice that those data contain labels denoting nondetects, that is, concentrations falling below detection limits. Nondetects impede the implementation of the bootstrap and represent an additional source of uncertainty that must be taken into account. In this work, a bootstrap scheme is devised that handles nondetects by adding an imputation step within the resampling process and conveniently propagates their associated uncertainly. In doing so, it considers the constrained relationships between chemical concentrations originated from their compositional nature. Bootstrap estimates using a range of imputation methods, including new stochastic proposals, are compared across scenarios of increasing difficulty. They are formulated to meet compositional principles following the log-ratio approach, and an adjustment is introduced in the multivariate case to deal with nonclosed samples. Results suggest that nondetect bootstrap based on model-based imputation is generally preferable. A robust approach based on isometric log-ratio transformations appears to be particularly suited in this context. Computer routines in the R statistical programming language are provided. 

Systematic survey of the design, statistical analysis, and reporting of studies published in the 2008 volume of the Journal of Cerebral Blood Flow and Metabolism.

PubMed

Vesterinen, Hanna M; Vesterinen, Hanna V; Egan, Kieren; Deister, Amelie; Schlattmann, Peter; Macleod, Malcolm R; Dirnagl, Ulrich

2011-04-01

Translating experimental findings into clinically effective therapies is one of the major bottlenecks of modern medicine. As this has been particularly true for cerebrovascular research, attention has turned to the quality and validity of experimental cerebrovascular studies. We set out to assess the study design, statistical analyses, and reporting of cerebrovascular research. We assessed all original articles published in the Journal of Cerebral Blood Flow and Metabolism during the year 2008 against a checklist designed to capture the key attributes relating to study design, statistical analyses, and reporting. A total of 156 original publications were included (animal, in vitro, human). Few studies reported a primary research hypothesis, statement of purpose, or measures to safeguard internal validity (such as randomization, blinding, exclusion or inclusion criteria). Many studies lacked sufficient information regarding methods and results to form a reasonable judgment about their validity. In nearly 20% of studies, statistical tests were either not appropriate or information to allow assessment of appropriateness was lacking. This study identifies a number of factors that should be addressed if the quality of research in basic and translational biomedicine is to be improved. We support the widespread implementation of the ARRIVE (Animal Research Reporting In Vivo Experiments) statement for the reporting of experimental studies in biomedicine, for improving training in proper study design and analysis, and that reviewers and editors adopt a more constructively critical approach in the assessment of manuscripts for publication.

Systematic survey of the design, statistical analysis, and reporting of studies published in the 2008 volume of the Journal of Cerebral Blood Flow and Metabolism

PubMed Central

Vesterinen, Hanna V; Egan, Kieren; Deister, Amelie; Schlattmann, Peter; Macleod, Malcolm R; Dirnagl, Ulrich

2011-01-01

Translating experimental findings into clinically effective therapies is one of the major bottlenecks of modern medicine. As this has been particularly true for cerebrovascular research, attention has turned to the quality and validity of experimental cerebrovascular studies. We set out to assess the study design, statistical analyses, and reporting of cerebrovascular research. We assessed all original articles published in the Journal of Cerebral Blood Flow and Metabolism during the year 2008 against a checklist designed to capture the key attributes relating to study design, statistical analyses, and reporting. A total of 156 original publications were included (animal, in vitro, human). Few studies reported a primary research hypothesis, statement of purpose, or measures to safeguard internal validity (such as randomization, blinding, exclusion or inclusion criteria). Many studies lacked sufficient information regarding methods and results to form a reasonable judgment about their validity. In nearly 20% of studies, statistical tests were either not appropriate or information to allow assessment of appropriateness was lacking. This study identifies a number of factors that should be addressed if the quality of research in basic and translational biomedicine is to be improved. We support the widespread implementation of the ARRIVE (Animal Research Reporting In Vivo Experiments) statement for the reporting of experimental studies in biomedicine, for improving training in proper study design and analysis, and that reviewers and editors adopt a more constructively critical approach in the assessment of manuscripts for publication. PMID:21157472

Temperature variation during apicectomy with Er:YAG laser.

PubMed

Bodrumlu, Emre; Keskiner, Ilker; Sumer, Mahmut; Sumer, A Pinar; Telcıoglu, N Tuba

2012-08-01

The purpose of this in vitro study was to evaluate the generated temperature of the Er:YAG laser, with three different pulse durations for apicectomy, compared with tungsten bur and surgical saw. Apicectomy is an endodontic surgery performed to remove the root apex and curette adjacent periapical tissue because of lesions of the apical area that are not healing properly. Sixty single-rooted extracted human teeth were resected by three cutting methods: tungsten bur, surgical saw, and Er:YAG laser irradiation with three different pulse durations; pulse duration 50 μs, pulse duration 100 μs, and pulse duration 300 μs. Teflon-insulated, type K thermocouples were used to measure temperature changes during the apicectomy process. Data were analyzed using the general linear models procedure of the SPSS statistical software program. Although there was no statistically significant difference for the mean values of temperature changes at 1 mm away to the cutting site of teeth, there was statistically significant difference among groups for the mean values of temperature changes at 3 mm away to the cutting site of teeth. Additionally, there was statistically significant difference among groups for the total time required for apicectomy. The laser irradiation with pulse duration 50 μs appears to have the lowest temperature rise and the shortest time required for apicectomy of the three pulse durations. However, Er:YAG laser for apicectomy in all pulse durations could be used safely for resection in endodontics in the presence of sufficient water.

ArraySolver: an algorithm for colour-coded graphical display and Wilcoxon signed-rank statistics for comparing microarray gene expression data.

PubMed

Khan, Haseeb Ahmad

2004-01-01

The massive surge in the production of microarray data poses a great challenge for proper analysis and interpretation. In recent years numerous computational tools have been developed to extract meaningful interpretation of microarray gene expression data. However, a convenient tool for two-groups comparison of microarray data is still lacking and users have to rely on commercial statistical packages that might be costly and require special skills, in addition to extra time and effort for transferring data from one platform to other. Various statistical methods, including the t-test, analysis of variance, Pearson test and Mann-Whitney U test, have been reported for comparing microarray data, whereas the utilization of the Wilcoxon signed-rank test, which is an appropriate test for two-groups comparison of gene expression data, has largely been neglected in microarray studies. The aim of this investigation was to build an integrated tool, ArraySolver, for colour-coded graphical display and comparison of gene expression data using the Wilcoxon signed-rank test. The results of software validation showed similar outputs with ArraySolver and SPSS for large datasets. Whereas the former program appeared to be more accurate for 25 or fewer pairs (n < or = 25), suggesting its potential application in analysing molecular signatures that usually contain small numbers of genes. The main advantages of ArraySolver are easy data selection, convenient report format, accurate statistics and the familiar Excel platform.

ArraySolver: An Algorithm for Colour-Coded Graphical Display and Wilcoxon Signed-Rank Statistics for Comparing Microarray Gene Expression Data

PubMed Central

2004-01-01

The massive surge in the production of microarray data poses a great challenge for proper analysis and interpretation. In recent years numerous computational tools have been developed to extract meaningful interpretation of microarray gene expression data. However, a convenient tool for two-groups comparison of microarray data is still lacking and users have to rely on commercial statistical packages that might be costly and require special skills, in addition to extra time and effort for transferring data from one platform to other. Various statistical methods, including the t-test, analysis of variance, Pearson test and Mann–Whitney U test, have been reported for comparing microarray data, whereas the utilization of the Wilcoxon signed-rank test, which is an appropriate test for two-groups comparison of gene expression data, has largely been neglected in microarray studies. The aim of this investigation was to build an integrated tool, ArraySolver, for colour-coded graphical display and comparison of gene expression data using the Wilcoxon signed-rank test. The results of software validation showed similar outputs with ArraySolver and SPSS for large datasets. Whereas the former program appeared to be more accurate for 25 or fewer pairs (n ≤ 25), suggesting its potential application in analysing molecular signatures that usually contain small numbers of genes. The main advantages of ArraySolver are easy data selection, convenient report format, accurate statistics and the familiar Excel platform. PMID:18629036

Identification of Microorganisms by High Resolution Tandem Mass Spectrometry with Accurate Statistical Significance

NASA Astrophysics Data System (ADS)

Alves, Gelio; Wang, Guanghui; Ogurtsov, Aleksey Y.; Drake, Steven K.; Gucek, Marjan; Suffredini, Anthony F.; Sacks, David B.; Yu, Yi-Kuo

2016-02-01

Correct and rapid identification of microorganisms is the key to the success of many important applications in health and safety, including, but not limited to, infection treatment, food safety, and biodefense. With the advance of mass spectrometry (MS) technology, the speed of identification can be greatly improved. However, the increasing number of microbes sequenced is challenging correct microbial identification because of the large number of choices present. To properly disentangle candidate microbes, one needs to go beyond apparent morphology or simple `fingerprinting'; to correctly prioritize the candidate microbes, one needs to have accurate statistical significance in microbial identification. We meet these challenges by using peptidome profiles of microbes to better separate them and by designing an analysis method that yields accurate statistical significance. Here, we present an analysis pipeline that uses tandem MS (MS/MS) spectra for microbial identification or classification. We have demonstrated, using MS/MS data of 81 samples, each composed of a single known microorganism, that the proposed pipeline can correctly identify microorganisms at least at the genus and species levels. We have also shown that the proposed pipeline computes accurate statistical significances, i.e., E-values for identified peptides and unified E-values for identified microorganisms. The proposed analysis pipeline has been implemented in MiCId, a freely available software for Microorganism Classification and Identification. MiCId is available for download at http://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html.

pROC: an open-source package for R and S+ to analyze and compare ROC curves.

PubMed

Robin, Xavier; Turck, Natacha; Hainard, Alexandre; Tiberti, Natalia; Lisacek, Frédérique; Sanchez, Jean-Charles; Müller, Markus

2011-03-17

Receiver operating characteristic (ROC) curves are useful tools to evaluate classifiers in biomedical and bioinformatics applications. However, conclusions are often reached through inconsistent use or insufficient statistical analysis. To support researchers in their ROC curves analysis we developed pROC, a package for R and S+ that contains a set of tools displaying, analyzing, smoothing and comparing ROC curves in a user-friendly, object-oriented and flexible interface. With data previously imported into the R or S+ environment, the pROC package builds ROC curves and includes functions for computing confidence intervals, statistical tests for comparing total or partial area under the curve or the operating points of different classifiers, and methods for smoothing ROC curves. Intermediary and final results are visualised in user-friendly interfaces. A case study based on published clinical and biomarker data shows how to perform a typical ROC analysis with pROC. pROC is a package for R and S+ specifically dedicated to ROC analysis. It proposes multiple statistical tests to compare ROC curves, and in particular partial areas under the curve, allowing proper ROC interpretation. pROC is available in two versions: in the R programming language or with a graphical user interface in the S+ statistical software. It is accessible at http://expasy.org/tools/pROC/ under the GNU General Public License. It is also distributed through the CRAN and CSAN public repositories, facilitating its installation.

Bond strength of repaired amalgam restorations.

PubMed

Rey, Rosalia; Mondragon, Eduardo; Shen, Chiayi

2015-01-01

This in vitro study investigated the interfacial flexural strength (FS) of amalgam repairs and the optimal combination of repair materials and mechanical retention required for a consistent and durable repair bond. Amalgam bricks were created, each with 1 end roughened to expose a fresh surface before repair. Four groups followed separate repair protocols: group 1, bonding agent with amalgam; group 2, bonding agent with composite resin; group 3, mechanical retention (slot) with amalgam; and group 4, slot with bonding agent and amalgam. Repaired specimens were stored in artificial saliva for 1, 10, 30, 120, or 360 days before being loaded to failure in a 3-point bending test. Statistical analysis showed significant changes in median FS over time in groups 2 and 4. The effect of the repair method on the FS values after each storage period was significant for most groups except the 30-day storage groups. Amalgam-amalgam repair with adequate condensation yielded the most consistent and durable bond. An amalgam bonding agent could be beneficial when firm condensation on the repair surface cannot be achieved or when tooth structure is involved. Composite resin can be a viable option for amalgam repair in an esthetically demanding region, but proper mechanical modification of the amalgam surface and selection of the proper bonding system are essential.

Statistical Analysis of speckle noise reduction techniques for echocardiographic Images

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Random dopant fluctuations and statistical variability in n-channel junctionless FETs

NASA Astrophysics Data System (ADS)

Akhavan, N. D.; Umana-Membreno, G. A.; Gu, R.; Antoszewski, J.; Faraone, L.

2018-01-01

The influence of random dopant fluctuations on the statistical variability of the electrical characteristics of n-channel silicon junctionless nanowire transistor (JNT) has been studied using three dimensional quantum simulations based on the non-equilibrium Green’s function (NEGF) formalism. Average randomly distributed body doping densities of 2 × 1019, 6 × 1019 and 1 × 1020 cm-3 have been considered employing an atomistic model for JNTs with gate lengths of 5, 10 and 15 nm. We demonstrate that by properly adjusting the doping density in the JNT, a near ideal statistical variability and electrical performance can be achieved, which can pave the way for the continuation of scaling in silicon CMOS technology.

Multi-scale statistical analysis of coronal solar activity

DOE PAGES

Gamborino, Diana; del-Castillo-Negrete, Diego; Martinell, Julio J.

2016-07-08

Multi-filter images from the solar corona are used to obtain temperature maps that are analyzed using techniques based on proper orthogonal decomposition (POD) in order to extract dynamical and structural information at various scales. Exploring active regions before and after a solar flare and comparing them with quiet regions, we show that the multi-scale behavior presents distinct statistical properties for each case that can be used to characterize the level of activity in a region. Information about the nature of heat transport is also to be extracted from the analysis.

Knowledge Discovery from Vibration Measurements

PubMed Central

Li, Jian; Wang, Daoyao

2014-01-01

The framework as well as the particular algorithms of pattern recognition process is widely adopted in structural health monitoring (SHM). However, as a part of the overall process of knowledge discovery from data bases (KDD), the results of pattern recognition are only changes and patterns of changes of data features. In this paper, based on the similarity between KDD and SHM and considering the particularity of SHM problems, a four-step framework of SHM is proposed which extends the final goal of SHM from detecting damages to extracting knowledge to facilitate decision making. The purposes and proper methods of each step of this framework are discussed. To demonstrate the proposed SHM framework, a specific SHM method which is composed by the second order structural parameter identification, statistical control chart analysis, and system reliability analysis is then presented. To examine the performance of this SHM method, real sensor data measured from a lab size steel bridge model structure are used. The developed four-step framework of SHM has the potential to clarify the process of SHM to facilitate the further development of SHM techniques. PMID:24574933

Evaluating the Generalization Value of Process-based Models in a Deep-in-time Machine Learning framework

NASA Astrophysics Data System (ADS)

Shen, C.; Fang, K.

2017-12-01

Deep Learning (DL) methods have made revolutionary strides in recent years. A core value proposition of DL is that abstract notions and patterns can be extracted purely from data, without the need for domain expertise. Process-based models (PBM), on the other hand, can be regarded as repositories of human knowledge or hypotheses about how systems function. Here, through computational examples, we argue that there is merit in integrating PBMs with DL due to the imbalance and lack of data in many situations, especially in hydrology. We trained a deep-in-time neural network, the Long Short-Term Memory (LSTM), to learn soil moisture dynamics from Soil Moisture Active Passive (SMAP) Level 3 product. We show that when PBM solutions are integrated into LSTM, the network is able to better generalize across regions. LSTM is able to better utilize PBM solutions than simpler statistical methods. Our results suggest PBMs have generalization value which should be carefully assessed and utilized. We also emphasize that when properly regularized, the deep network is robust and is of superior testing performance compared to simpler methods.

Improved sample preparation of glyphosate and methylphosphonic acid by EPA method 6800A and time-of-flight mass spectrometry using novel solid-phase extraction.

PubMed

Wagner, Rebecca; Wetzel, Stephanie J; Kern, John; Kingston, H M Skip

2012-02-01

The employment of chemical weapons by rogue states and/or terrorist organizations is an ongoing concern in the United States. The quantitative analysis of nerve agents must be rapid and reliable for use in the private and public sectors. Current methods describe a tedious and time-consuming derivatization for gas chromatography-mass spectrometry and liquid chromatography in tandem with mass spectrometry. Two solid-phase extraction (SPE) techniques for the analysis of glyphosate and methylphosphonic acid are described with the utilization of isotopically enriched analytes for quantitation via atmospheric pressure chemical ionization-quadrupole time-of-flight mass spectrometry (APCI-Q-TOF-MS) that does not require derivatization. Solid-phase extraction-isotope dilution mass spectrometry (SPE-IDMS) involves pre-equilibration of a naturally occurring sample with an isotopically enriched standard. The second extraction method, i-Spike, involves loading an isotopically enriched standard onto the SPE column before the naturally occurring sample. The sample and the spike are then co-eluted from the column enabling precise and accurate quantitation via IDMS. The SPE methods in conjunction with IDMS eliminate concerns of incomplete elution, matrix and sorbent effects, and MS drift. For accurate quantitation with IDMS, the isotopic contribution of all atoms in the target molecule must be statistically taken into account. This paper describes two newly developed sample preparation techniques for the analysis of nerve agent surrogates in drinking water as well as statistical probability analysis for proper molecular IDMS. The methods described in this paper demonstrate accurate molecular IDMS using APCI-Q-TOF-MS with limits of quantitation as low as 0.400 mg/kg for glyphosate and 0.031 mg/kg for methylphosphonic acid. Copyright © 2012 John Wiley & Sons, Ltd.

Determination of the Residual Anthracene Concentration in Cultures of Haloalkalitolerant Actinomycetes by Excitation Fluorescence, Emission Fluorescence, and Synchronous Fluorescence: Comparative Study

PubMed Central

Lara-Severino, Reyna del Carmen; Camacho-López, Miguel Ángel; García-Macedo, Jessica Marlene; Gómez-Oliván, Leobardo M.; Sandoval-Trujillo, Ángel H.; Isaac-Olive, Keila; Ramírez-Durán, Ninfa

2016-01-01

Polycyclic aromatic hydrocarbons (PAHs) are compounds that can be quantified by fluorescence due to their high quantum yield. Haloalkalitolerant bacteria tolerate wide concentration ranges of NaCl and pH. They are potentially useful in the PAHs bioremediation of saline environments. However, it is known that salinity of the sample affects fluorescence signal regardless of the method. The objective of this work was to carry out a comparative study based on the sensitivity, linearity, and detection limits of the excitation, emission, and synchronous fluorescence methods, during the quantification of the residual anthracene concentration from the following haloalkalitolerant actinomycetes cultures Kocuria rosea, Kocuria palustris, Microbacterium testaceum, and 4 strains of Nocardia farcinica, in order to establish the proper fluorescence method to study the PAHs biodegrading capacity of haloalkalitolerant actinobacteria. The study demonstrated statistical differences among the strains and among the fluorescence methods regarding the anthracene residual concentration. The results showed that excitation and emission fluorescence methods performed very similarly but sensitivity in excitation fluorescence is slightly higher. Synchronous fluorescence using Δλ = 150 nm is not the most convenient method. Therefore we propose the excitation fluorescence as the fluorescence method to be used in the study of the PAHs biodegrading capacity of haloalkalitolerant actinomycetes. PMID:26925294

Hybrid pairwise likelihood analysis of animal behavior experiments.

PubMed

Cattelan, Manuela; Varin, Cristiano

2013-12-01

The study of the determinants of fights between animals is an important issue in understanding animal behavior. For this purpose, tournament experiments among a set of animals are often used by zoologists. The results of these tournament experiments are naturally analyzed by paired comparison models. Proper statistical analysis of these models is complicated by the presence of dependence between the outcomes of fights because the same animal is involved in different contests. This paper discusses two different model specifications to account for between-fights dependence. Models are fitted through the hybrid pairwise likelihood method that iterates between optimal estimating equations for the regression parameters and pairwise likelihood inference for the association parameters. This approach requires the specification of means and covariances only. For this reason, the method can be applied also when the computation of the joint distribution is difficult or inconvenient. The proposed methodology is investigated by simulation studies and applied to real data about adult male Cape Dwarf Chameleons. © 2013, The International Biometric Society.

Signaling on the continuous spectrum of nonlinear optical fiber.

PubMed

Tavakkolnia, Iman; Safari, Majid

2017-08-07

This paper studies different signaling techniques on the continuous spectrum (CS) of nonlinear optical fiber defined by nonlinear Fourier transform. Three different signaling techniques are proposed and analyzed based on the statistics of the noise added to CS after propagation along the nonlinear optical fiber. The proposed methods are compared in terms of error performance, distance reach, and complexity. Furthermore, the effect of chromatic dispersion on the data rate and noise in nonlinear spectral domain is investigated. It is demonstrated that, for a given sequence of CS symbols, an optimal bandwidth (or symbol rate) can be determined so that the temporal duration of the propagated signal at the end of the fiber is minimized. In effect, the required guard interval between the subsequently transmitted data packets in time is minimized and the effective data rate is significantly enhanced. Moreover, by selecting the proper signaling method and design criteria a distance reach of 7100 km is reported by only singling on CS at a rate of 9.6 Gbps.

On the importance of avoiding shortcuts in applying cognitive models to hierarchical data.

PubMed

Boehm, Udo; Marsman, Maarten; Matzke, Dora; Wagenmakers, Eric-Jan

2018-06-12

Psychological experiments often yield data that are hierarchically structured. A number of popular shortcut strategies in cognitive modeling do not properly accommodate this structure and can result in biased conclusions. To gauge the severity of these biases, we conducted a simulation study for a two-group experiment. We first considered a modeling strategy that ignores the hierarchical data structure. In line with theoretical results, our simulations showed that Bayesian and frequentist methods that rely on this strategy are biased towards the null hypothesis. Secondly, we considered a modeling strategy that takes a two-step approach by first obtaining participant-level estimates from a hierarchical cognitive model and subsequently using these estimates in a follow-up statistical test. Methods that rely on this strategy are biased towards the alternative hypothesis. Only hierarchical models of the multilevel data lead to correct conclusions. Our results are particularly relevant for the use of hierarchical Bayesian parameter estimates in cognitive modeling.

AstroML: Python-powered Machine Learning for Astronomy

NASA Astrophysics Data System (ADS)

Vander Plas, Jake; Connolly, A. J.; Ivezic, Z.

2014-01-01

As astronomical data sets grow in size and complexity, automated machine learning and data mining methods are becoming an increasingly fundamental component of research in the field. The astroML project (http://astroML.org) provides a common repository for practical examples of the data mining and machine learning tools used and developed by astronomical researchers, written in Python. The astroML module contains a host of general-purpose data analysis and machine learning routines, loaders for openly-available astronomical datasets, and fast implementations of specific computational methods often used in astronomy and astrophysics. The associated website features hundreds of examples of these routines being used for analysis of real astronomical datasets, while the associated textbook provides a curriculum resource for graduate-level courses focusing on practical statistics, machine learning, and data mining approaches within Astronomical research. This poster will highlight several of the more powerful and unique examples of analysis performed with astroML, all of which can be reproduced in their entirety on any computer with the proper packages installed.

Simulations for designing and interpreting intervention trials in infectious diseases.

PubMed

Halloran, M Elizabeth; Auranen, Kari; Baird, Sarah; Basta, Nicole E; Bellan, Steven E; Brookmeyer, Ron; Cooper, Ben S; DeGruttola, Victor; Hughes, James P; Lessler, Justin; Lofgren, Eric T; Longini, Ira M; Onnela, Jukka-Pekka; Özler, Berk; Seage, George R; Smith, Thomas A; Vespignani, Alessandro; Vynnycky, Emilia; Lipsitch, Marc

2017-12-29

Interventions in infectious diseases can have both direct effects on individuals who receive the intervention as well as indirect effects in the population. In addition, intervention combinations can have complex interactions at the population level, which are often difficult to adequately assess with standard study designs and analytical methods. Herein, we urge the adoption of a new paradigm for the design and interpretation of intervention trials in infectious diseases, particularly with regard to emerging infectious diseases, one that more accurately reflects the dynamics of the transmission process. In an increasingly complex world, simulations can explicitly represent transmission dynamics, which are critical for proper trial design and interpretation. Certain ethical aspects of a trial can also be quantified using simulations. Further, after a trial has been conducted, simulations can be used to explore the possible explanations for the observed effects. Much is to be gained through a multidisciplinary approach that builds collaborations among experts in infectious disease dynamics, epidemiology, statistical science, economics, simulation methods, and the conduct of clinical trials.

A comparison of ensemble post-processing approaches that preserve correlation structures

NASA Astrophysics Data System (ADS)

Schefzik, Roman; Van Schaeybroeck, Bert; Vannitsem, Stéphane

2016-04-01

Despite the fact that ensemble forecasts address the major sources of uncertainty, they exhibit biases and dispersion errors and therefore are known to improve by calibration or statistical post-processing. For instance the ensemble model output statistics (EMOS) method, also known as non-homogeneous regression approach (Gneiting et al., 2005) is known to strongly improve forecast skill. EMOS is based on fitting and adjusting a parametric probability density function (PDF). However, EMOS and other common post-processing approaches apply to a single weather quantity at a single location for a single look-ahead time. They are therefore unable of taking into account spatial, inter-variable and temporal dependence structures. Recently many research efforts have been invested in designing post-processing methods that resolve this drawback but also in verification methods that enable the detection of dependence structures. New verification methods are applied on two classes of post-processing methods, both generating physically coherent ensembles. A first class uses the ensemble copula coupling (ECC) that starts from EMOS but adjusts the rank structure (Schefzik et al., 2013). The second class is a member-by-member post-processing (MBM) approach that maps each raw ensemble member to a corrected one (Van Schaeybroeck and Vannitsem, 2015). We compare variants of the EMOS-ECC and MBM classes and highlight a specific theoretical connection between them. All post-processing variants are applied in the context of the ensemble system of the European Centre of Weather Forecasts (ECMWF) and compared using multivariate verification tools including the energy score, the variogram score (Scheuerer and Hamill, 2015) and the band depth rank histogram (Thorarinsdottir et al., 2015). Gneiting, Raftery, Westveld, and Goldman, 2005: Calibrated probabilistic forecasting using ensemble model output statistics and minimum CRPS estimation. Mon. Wea. Rev., {133}, 1098-1118. Scheuerer and Hamill, 2015. Variogram-based proper scoring rules for probabilistic forecasts of multivariate quantities. Mon. Wea. Rev. {143},1321-1334. Schefzik, Thorarinsdottir, Gneiting. Uncertainty quantification in complex simulation models using ensemble copula coupling. Statistical Science {28},616-640, 2013. Thorarinsdottir, M. Scheuerer, and C. Heinz, 2015. Assessing the calibration of high-dimensional ensemble forecasts using rank histograms, arXiv:1310.0236. Van Schaeybroeck and Vannitsem, 2015: Ensemble post-processing using member-by-member approaches: theoretical aspects. Q.J.R. Meteorol. Soc., 141: 807-818.

Logistic Regression for Seismically Induced Landslide Predictions: Using Uniform Hazard and Geophysical Layers as Predictor Variables

NASA Astrophysics Data System (ADS)

Nowicki, M. A.; Hearne, M.; Thompson, E.; Wald, D. J.

2012-12-01

Seismically induced landslides present a costly and often fatal threats in many mountainous regions. Substantial effort has been invested to understand where seismically induced landslides may occur in the future. Both slope-stability methods and, more recently, statistical approaches to the problem are described throughout the literature. Though some regional efforts have succeeded, no uniformly agreed-upon method is available for predicting the likelihood and spatial extent of seismically induced landslides. For use in the U. S. Geological Survey (USGS) Prompt Assessment of Global Earthquakes for Response (PAGER) system, we would like to routinely make such estimates, in near-real time, around the globe. Here we use the recently produced USGS ShakeMap Atlas of historic earthquakes to develop an empirical landslide probability model. We focus on recent events, yet include any digitally-mapped landslide inventories for which well-constrained ShakeMaps are also available. We combine these uniform estimates of the input shaking (e.g., peak acceleration and velocity) with broadly available susceptibility proxies, such as topographic slope and surface geology. The resulting database is used to build a predictive model of the probability of landslide occurrence with logistic regression. The landslide database includes observations from the Northridge, California (1994); Wenchuan, China (2008); ChiChi, Taiwan (1999); and Chuetsu, Japan (2004) earthquakes; we also provide ShakeMaps for moderate-sized events without landslide for proper model testing and training. The performance of the regression model is assessed with both statistical goodness-of-fit metrics and a qualitative review of whether or not the model is able to capture the spatial extent of landslides for each event. Part of our goal is to determine which variables can be employed based on globally-available data or proxies, and whether or not modeling results from one region are transferrable to geomorphologically-similar regions that lack proper calibration events. Combined with near-real time ShakeMaps, we anticipate using our model to make generalized predictions of whether or not (and if so, where) landslides are likely to occur for earthquakes around the globe; we also intend to incorporate this functionality into the USGS PAGER system.

Multimedia Presentations in Educational Measurement and Statistics: Design Considerations and Instructional Approaches

ERIC Educational Resources Information Center

Sklar, Jeffrey C.; Zwick, Rebecca

2009-01-01

Proper interpretation of standardized test scores is a crucial skill for K-12 teachers and school personnel; however, many do not have sufficient knowledge of measurement concepts to appropriately interpret and communicate test results. In a recent four-year project funded by the National Science Foundation, three web-based instructional…

Estimation of the Prevalence of Autism Spectrum Disorder in South Korea, Revisited

ERIC Educational Resources Information Center

Pantelis, Peter C.; Kennedy, Daniel P.

2016-01-01

Two-phase designs in epidemiological studies of autism prevalence introduce methodological complications that can severely limit the precision of resulting estimates. If the assumptions used to derive the prevalence estimate are invalid or if the uncertainty surrounding these assumptions is not properly accounted for in the statistical inference…

The Consequences of Model Misidentification in the Interrupted Time-Series Experiment.

ERIC Educational Resources Information Center

Padia, William L.

Campbell (l969) argued for the interrupted time-series experiment as a useful methodology for testing intervention effects in the social sciences. The validity of the statistical hypothesis testing of time-series, is, however, dependent upon the proper identification of the underlying stochastic nature of the data. Several types of model…

NHEXAS PHASE I ARIZONA STUDY--STANDARD OPERATING PROCEDURE FOR SAMPLING WEIGHT CALCULATION (IIT-A-9.0)

EPA Science Inventory

The purpose of this SOP is to describe the procedures undertaken to calculate sampling weights. The sampling weights are needed to obtain weighted statistics of the NHEXAS data. This SOP uses data that have been properly coded and certified with appropriate QA/QC procedures by t...

Attention-Deficit/Hyperactivity Disorder Symptoms in Preschool Children: Examining Psychometric Properties Using Item Response Theory

ERIC Educational Resources Information Center

Purpura, David J.; Wilson, Shauna B.; Lonigan, Christopher J.

2010-01-01

Clear and empirically supported diagnostic symptoms are important for proper diagnosis and treatment of psychological disorders. Unfortunately, the symptoms of many disorders presented in the "Diagnostic and Statistical Manual of Mental Disorders" (4th ed., text rev.; DSM-IV-TR; American Psychiatric Association, 2000) lack sufficient psychometric…

Mechanical Characterization of Polysilicon MEMS: A Hybrid TMCMC/POD-Kriging Approach.

PubMed

Mirzazadeh, Ramin; Eftekhar Azam, Saeed; Mariani, Stefano

2018-04-17

Microscale uncertainties related to the geometry and morphology of polycrystalline silicon films, constituting the movable structures of micro electro-mechanical systems (MEMS), were investigated through a joint numerical/experimental approach. An on-chip testing device was designed and fabricated to deform a compliant polysilicon beam. In previous studies, we showed that the scattering in the input–output characteristics of the device can be properly described only if statistical features related to the morphology of the columnar polysilicon film and to the etching process adopted to release the movable structure are taken into account. In this work, a high fidelity finite element model of the device was used to feed a transitional Markov chain Monte Carlo (TMCMC) algorithm for the estimation of the unknown parameters governing the aforementioned statistical features. To reduce the computational cost of the stochastic analysis, a synergy of proper orthogonal decomposition (POD) and kriging interpolation was adopted. Results are reported for a batch of nominally identical tested devices, in terms of measurement error-affected probability distributions of the overall Young’s modulus of the polysilicon film and of the overetch depth.

Coherent vorticity extraction in resistive drift-wave turbulence: Comparison of orthogonal wavelets versus proper orthogonal decomposition

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

Futatani, S.; Bos, W.J.T.; Del-Castillo-Negrete, Diego B

2011-01-01

We assess two techniques for extracting coherent vortices out of turbulent flows: the wavelet based Coherent Vorticity Extraction (CVE) and the Proper Orthogonal Decomposition (POD). The former decomposes the flow field into an orthogonal wavelet representation and subsequent thresholding of the coefficients allows one to split the flow into organized coherent vortices with non-Gaussian statistics and an incoherent random part which is structureless. POD is based on the singular value decomposition and decomposes the flow into basis functions which are optimal with respect to the retained energy for the ensemble average. Both techniques are applied to direct numerical simulation datamore » of two-dimensional drift-wave turbulence governed by Hasegawa Wakatani equation, considering two limit cases: the quasi-hydrodynamic and the quasi-adiabatic regimes. The results are compared in terms of compression rate, retained energy, retained enstrophy and retained radial flux, together with the enstrophy spectrum and higher order statistics. (c) 2010 Published by Elsevier Masson SAS on behalf of Academie des sciences.« less

Earthquake prediction evaluation standards applied to the VAN Method

NASA Astrophysics Data System (ADS)

Jackson, David D.

Earthquake prediction research must meet certain standards before it can be suitably evaluated for potential application in decision making. For methods that result in a binary (on or off) alarm condition, requirements include (1) a quantitative description of observables that trigger an alarm, (2) a quantitative description, including ranges of time, location, and magnitude, of the predicted earthquakes, (3) documented evidence of all previous alarms, (4) a complete list of predicted earthquakes, (5) a complete list of unpredicted earthquakes. The VAN technique [Varotsos and Lazaridou, 1991; Varotsos et al., 1996] has not yet been stated as a testable hypothesis. It fails criteria (1) and (2) so it is not ready to be evaluated properly. Although telegrams were transmitted in advance of claimed successes, these telegrams did not fully specify the predicted events, and all of the published statistical evaluations involve many subjective ex post facto decisions. Lacking a statistically demonstrated relationship to earthquakes, a candidate prediction technique should satisfy several plausibility criteria, including: (1) a reasonable relationship between the location of the candidate precursor and that of the predicted earthquake, (2) some demonstration that the candidate precursory observations are related to stress, strain, or other quantities related to earthquakes, and (3) the existence of co-seismic as well as pre-seismic variations of the candidate precursor. The VAN technique meets none of these criteria.

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.

QSAR models for thiophene and imidazopyridine derivatives inhibitors of the Polo-Like Kinase 1.

PubMed

Comelli, Nieves C; Duchowicz, Pablo R; Castro, Eduardo A

2014-10-01

The inhibitory activity of 103 thiophene and 33 imidazopyridine derivatives against Polo-Like Kinase 1 (PLK1) expressed as pIC50 (-logIC50) was predicted by QSAR modeling. Multivariate linear regression (MLR) was employed to model the relationship between 0D and 3D molecular descriptors and biological activities of molecules using the replacement method (MR) as variable selection tool. The 136 compounds were separated into several training and test sets. Two splitting approaches, distribution of biological data and structural diversity, and the statistical experimental design procedure D-optimal distance were applied to the dataset. The significance of the training set models was confirmed by statistically higher values of the internal leave one out cross-validated coefficient of determination (Q2) and external predictive coefficient of determination for the test set (Rtest2). The model developed from a training set, obtained with the D-optimal distance protocol and using 3D descriptor space along with activity values, separated chemical features that allowed to distinguish high and low pIC50 values reasonably well. Then, we verified that such model was sufficient to reliably and accurately predict the activity of external diverse structures. The model robustness was properly characterized by means of standard procedures and their applicability domain (AD) was analyzed by leverage method. Copyright © 2014 Elsevier B.V. All rights reserved.

Automated diagnosis of congestive heart failure using dual tree complex wavelet transform and statistical features extracted from 2s of ECG signals.

PubMed

Sudarshan, Vidya K; Acharya, U Rajendra; Oh, Shu Lih; Adam, Muhammad; Tan, Jen Hong; Chua, Chua Kuang; Chua, Kok Poo; Tan, Ru San

2017-04-01

Identification of alarming features in the electrocardiogram (ECG) signal is extremely significant for the prediction of congestive heart failure (CHF). ECG signal analysis carried out using computer-aided techniques can speed up the diagnosis process and aid in the proper management of CHF patients. Therefore, in this work, dual tree complex wavelets transform (DTCWT)-based methodology is proposed for an automated identification of ECG signals exhibiting CHF from normal. In the experiment, we have performed a DTCWT on ECG segments of 2s duration up to six levels to obtain the coefficients. From these DTCWT coefficients, statistical features are extracted and ranked using Bhattacharyya, entropy, minimum redundancy maximum relevance (mRMR), receiver-operating characteristics (ROC), Wilcoxon, t-test and reliefF methods. Ranked features are subjected to k-nearest neighbor (KNN) and decision tree (DT) classifiers for automated differentiation of CHF and normal ECG signals. We have achieved 99.86% accuracy, 99.78% sensitivity and 99.94% specificity in the identification of CHF affected ECG signals using 45 features. The proposed method is able to detect CHF patients accurately using only 2s of ECG signal length and hence providing sufficient time for the clinicians to further investigate on the severity of CHF and treatments. Copyright © 2017 Elsevier Ltd. All rights reserved.

Chapter 9: Planting hardwood tree seedlings on reclaimed mine land in the Appalachian region

Treesearch

V. Davis; J. Franklin; C. Zipper; P. Angel

2017-01-01

The Forestry Reclamation Approach (FRA) is a method of reclaiming surface coal mines to forested postmining land use (Chapter 2, this volume). "Use proper tree planting techniques" is Step 5 of the FRA; when used with the other FRA steps, proper tree planting can help to ensure successful reforestation. Proper care and planting of tree seedlings is essential...

Spectral Properties and Dynamics of Gold Nanorods Revealed by EMCCD Based Spectral-Phasor Method

PubMed Central

Chen, Hongtao; Digman, Michelle A.

2015-01-01

Gold nanorods (NRs) with tunable plasmon-resonant absorption in the near-infrared region have considerable advantages over organic fluorophores as imaging agents. However, the luminescence spectral properties of NRs have not been fully explored at the single particle level in bulk due to lack of proper analytic tools. Here we present a global spectral phasor analysis method which allows investigations of NRs' spectra at single particle level with their statistic behavior and spatial information during imaging. The wide phasor distribution obtained by the spectral phasor analysis indicates spectra of NRs are different from particle to particle. NRs with different spectra can be identified graphically in corresponding spatial images with high spectral resolution. Furthermore, spectral behaviors of NRs under different imaging conditions, e.g. different excitation powers and wavelengths, were carefully examined by our laser-scanning multiphoton microscope with spectral imaging capability. Our results prove that the spectral phasor method is an easy and efficient tool in hyper-spectral imaging analysis to unravel subtle changes of the emission spectrum. Moreover, we applied this method to study the spectral dynamics of NRs during direct optical trapping and by optothermal trapping. Interestingly, spectral shifts were observed in both trapping phenomena. PMID:25684346

Quantitative image analysis for evaluating the coating thickness and pore distribution in coated small particles.

PubMed

Laksmana, F L; Van Vliet, L J; Hartman Kok, P J A; Vromans, H; Frijlink, H W; Van der Voort Maarschalk, K

2009-04-01

This study aims to develop a characterization method for coating structure based on image analysis, which is particularly promising for the rational design of coated particles in the pharmaceutical industry. The method applies the MATLAB image processing toolbox to images of coated particles taken with Confocal Laser Scanning Microscopy (CSLM). The coating thicknesses have been determined along the particle perimeter, from which a statistical analysis could be performed to obtain relevant thickness properties, e.g. the minimum coating thickness and the span of the thickness distribution. The characterization of the pore structure involved a proper segmentation of pores from the coating and a granulometry operation. The presented method facilitates the quantification of porosity, thickness and pore size distribution of a coating. These parameters are considered the important coating properties, which are critical to coating functionality. Additionally, the effect of the coating process variations on coating quality can straight-forwardly be assessed. Enabling a good characterization of the coating qualities, the presented method can be used as a fast and effective tool to predict coating functionality. This approach also enables the influence of different process conditions on coating properties to be effectively monitored, which latterly leads to process tailoring.

Walk-in Model for Ill Care in an Urban Academic Pediatric Clinic.

PubMed

Warrick, Stephen; Morehous, John; Samaan, Zeina M; Mansour, Mona; Huentelman, Tracy; Schoettker, Pamela J; Iyer, Srikant

2018-04-01

Since the Institute of Medicine's 2001 charge to reform health care, there has been a focus on the role of the medical home. Access to care in the proper setting and at the proper time is central to health care reform. We aimed to increase the volume of patients receiving care for acute illnesses within the medical home rather than the emergency department or urgent care center from 41% to 60%. We used quality improvement methods to create a separate nonemergency care stream in a large academic primary care clinic serving 19,000 patients (90% Medicaid). The pediatric primary care (PPC) walk-in clinic opened in July 2013 with service 4 hours per day and expanded to an all-day clinic in October 2013. Statistical process control methods were used to measure the change over time in the volume of ill patients and visits seen in the PPC walk-in clinic. Average weekly walk-in nonemergent ill-care visits increased from 61 to 158 after opening the PPC walk-in clinic. The percentage of nonemergent ill-care visits in the medical home increased from 41% to 45%. Visits during regular clinic hours increased from 55% to 60%. Clinic cycle time remained unchanged. Implementation of a walk-in care stream for acute illness within the medical home has allowed us to provide ill care to a higher proportion of patients, although we have not yet achieved our predicted volume. Matching access to demand is key to successfully meeting patient needs. Copyright © 2018 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.

PARSEC's Astrometry - The Risky Approach

NASA Astrophysics Data System (ADS)

Andrei, A. H.

2015-10-01

Parallaxes - and hence the fundamental establishment of stellar distances - rank among the oldest, most direct, and hardest of astronomical determinations. Arguably amongst the most essential too. The direct approach to obtain trigonometric parallaxes, using a constrained set of equations to derive positions, proper motions, and parallaxes, has been labelled as risky. Properly so, because the axis of the parallactic apparent ellipse is smaller than one arcsec even for the nearest stars, and just a fraction of its perimeter can be followed. Thus the classical approach is of linearizing the description by locking the solution to a set of precise positions of the Earth at the instants of observation, rather than to the dynamics of its orbit, and of adopting a close examination of the few observations available. In the PARSEC program the parallaxes of 143 brown dwarfs were planned. Five years of observation of the fields were taken with the WFI camera at the ESO 2.2m telescope in Chile. The goal is to provide a statistically significant number of trigonometric parallaxes for BD sub-classes from L0 to T7. Taking advantage of the large, regularly spaced, quantity of observations, here we take the risky approach to fit an ellipse to the observed ecliptic coordinates and derive the parallaxes. We also combine the solutions from different centroiding methods, widely proven in prior astrometric investigations. As each of those methods assess diverse properties of the PSFs, they are taken as independent measurements, and combined into a weighted least-squares general solution. The results obtained compare well with the literature and with the classical approach.

The absolute magnitudes of RR Lyraes from HIPPARCOS parallaxes and proper motions

NASA Astrophysics Data System (ADS)

Fernley, J.; Barnes, T. G.; Skillen, I.; Hawley, S. L.; Hanley, C. J.; Evans, D. W.; Solano, E.; Garrido, R.

1998-02-01

We have used HIPPARCOS proper motions and the method of Statistical Parallax to estimate the absolute magnitude of RR Lyrae stars. In addition we used the HIPPARCOS parallax of RR Lyrae itself to determine it's absolute magnitude. These two results are in excellent agreement with each other and give a zero-point for the RR Lyrae M_v,[Fe/H] relation of 0.77+/-0.15 at [Fe/H]=-1.53. This zero-point is in good agreement with that obtained recently by several groups using Baade-Wesselink methods which, averaged over the results from the different groups, gives M_v = 0.73+/-0.14 at [Fe/H]=-1.53. Taking the HIPPARCOS based zero-point and a value of 0.18+/-0.03 for the slope of the M_v,[Fe/H] relation from the literature we find firstly, the distance modulus of the LMC is 18.26+/-0.15 and secondly, the mean age of the Globular Clusters is 17.4+/-3.0 GYrs. These values are compared with recent estimates based on other "standard candles" that have also been calibrated with HIPPARCOS data. It is clear that, in addition to astrophysical problems, there are also problems in the application of HIPPARCOS data that are not yet fully understood. Table 1, which contains the basic data for the RR Lyraes, is available only at CDS. It may be retrieved via anonymous FTP at cdsarc.u-strasbg.fr (130.79.128.5) or via the Web at http://cdsweb.u-strasbg.fr/Abstract.html

Statistical Modelling of the Soil Dielectric Constant

NASA Astrophysics Data System (ADS)

Usowicz, Boguslaw; Marczewski, Wojciech; Bogdan Usowicz, Jerzy; Lipiec, Jerzy

2010-05-01

The dielectric constant of soil is the physical property being very sensitive on water content. It funds several electrical measurement techniques for determining the water content by means of direct (TDR, FDR, and others related to effects of electrical conductance and/or capacitance) and indirect RS (Remote Sensing) methods. The work is devoted to a particular statistical manner of modelling the dielectric constant as the property accounting a wide range of specific soil composition, porosity, and mass density, within the unsaturated water content. Usually, similar models are determined for few particular soil types, and changing the soil type one needs switching the model on another type or to adjust it by parametrization of soil compounds. Therefore, it is difficult comparing and referring results between models. The presented model was developed for a generic representation of soil being a hypothetical mixture of spheres, each representing a soil fraction, in its proper phase state. The model generates a serial-parallel mesh of conductive and capacitive paths, which is analysed for a total conductive or capacitive property. The model was firstly developed to determine the thermal conductivity property, and now it is extended on the dielectric constant by analysing the capacitive mesh. The analysis is provided by statistical means obeying physical laws related to the serial-parallel branching of the representative electrical mesh. Physical relevance of the analysis is established electrically, but the definition of the electrical mesh is controlled statistically by parametrization of compound fractions, by determining the number of representative spheres per unitary volume per fraction, and by determining the number of fractions. That way the model is capable covering properties of nearly all possible soil types, all phase states within recognition of the Lorenz and Knudsen conditions. In effect the model allows on generating a hypothetical representative of the soil type, and that way it enables clear comparing to results from other soil type dependent models. The paper is focused on proper representing possible range of porosity in commonly existing soils. This work is done with aim of implementing the statistical-physical model of the dielectric constant to a use in the model CMEM (Community Microwave Emission Model), applicable to SMOS (Soil Moisture and Ocean Salinity ESA Mission) data. The input data to the model clearly accepts definition of soil fractions in common physical measures, and in opposition to other empirical models, does not need calibrating. It is not dependent on recognition of the soil by type, but instead it offers the control of accuracy by proper determination of the soil compound fractions. SMOS employs CMEM being funded only by the sand-clay-silt composition. Common use of the soil data, is split on tens or even hundreds soil types depending on the region. We hope that only by determining three element compounds of sand-clay-silt, in few fractions may help resolving the question of relevance of soil data to the input of CMEM, for SMOS. Now, traditionally employed soil types are converted on sand-clay-silt compounds, but hardly cover effects of other specific properties like the porosity. It should bring advantageous effects in validating SMOS observation data, and is taken for the aim in the Cal/Val project 3275, in the campaigns for SVRT (SMOS Validation and Retrieval Team). Acknowledgements. This work was funded in part by the PECS - Programme for European Cooperating States, No. 98084 "SWEX/R - Soil Water and Energy Exchange/Research".

Cutting efficiency of Reciproc and waveOne reciprocating instruments.

PubMed

Plotino, Gianluca; Giansiracusa Rubini, Alessio; Grande, Nicola M; Testarelli, Luca; Gambarini, Gianluca

2014-08-01

The aim of the present study was to evaluate the cutting efficiency of 2 new reciprocating instruments, Reciproc and WaveOne. Twenty-four new Reciproc R25 and 24 new WaveOne Primary files were activated by using a torque-controlled motor (Silver Reciproc) and divided into 4 groups (n = 12): group 1, Reciproc activated by Reciproc ALL program; group 2, Reciproc activated by WaveOne ALL program; group 3, WaveOne activated by Reciproc ALL program; and group 4, WaveOne activated by WaveOne ALL program. The device used for the cutting test consisted of a main frame to which a mobile plastic support for the handpiece is connected and a stainless steel block containing a Plexiglas block (inPlexiglass, Rome, Italy) against which the cutting efficiency of the instruments was tested. The length of the block cut in 1 minute was measured in a computerized program with a precision of 0.1 mm. Means and standard deviations of each group were calculated, and data were statistically analyzed with 1-way analysis of variance and Bonferroni test (P < .05). Reciproc R25 displayed greater cutting efficiency than WaveOne Primary for both the movements used (P < .05); in particular, Reciproc instruments used with their proper reciprocating motion presented a statistically significant higher cutting efficiency than WaveOne instruments used with their proper reciprocating motion (P < .05). There was no statistically significant difference between the 2 movements for both instruments (P > .05). Reciproc instruments demonstrated statistically higher cutting efficiency than WaveOne instruments. Copyright © 2014 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Statistical Models for Averaging of the Pump–Probe Traces: Example of Denoising in Terahertz Time-Domain Spectroscopy

NASA Astrophysics Data System (ADS)

Skorobogatiy, Maksim; Sadasivan, Jayesh; Guerboukha, Hichem

2018-05-01

In this paper, we first discuss the main types of noise in a typical pump-probe system, and then focus specifically on terahertz time domain spectroscopy (THz-TDS) setups. We then introduce four statistical models for the noisy pulses obtained in such systems, and detail rigorous mathematical algorithms to de-noise such traces, find the proper averages and characterise various types of experimental noise. Finally, we perform a comparative analysis of the performance, advantages and limitations of the algorithms by testing them on the experimental data collected using a particular THz-TDS system available in our laboratories. We conclude that using advanced statistical models for trace averaging results in the fitting errors that are significantly smaller than those obtained when only a simple statistical average is used.

On the cause of the non-Gaussian distribution of residuals in geomagnetism

NASA Astrophysics Data System (ADS)

Hulot, G.; Khokhlov, A.

2017-12-01

To describe errors in the data, Gaussian distributions naturally come to mind. In many practical instances, indeed, Gaussian distributions are appropriate. In the broad field of geomagnetism, however, it has repeatedly been noted that residuals between data and models often display much sharper distributions, sometimes better described by a Laplace distribution. In the present study, we make the case that such non-Gaussian behaviors are very likely the result of what is known as mixture of distributions in the statistical literature. Mixtures arise as soon as the data do not follow a common distribution or are not properly normalized, the resulting global distribution being a mix of the various distributions followed by subsets of the data, or even individual datum. We provide examples of the way such mixtures can lead to distributions that are much sharper than Gaussian distributions and discuss the reasons why such mixtures are likely the cause of the non-Gaussian distributions observed in geomagnetism. We also show that when properly selecting sub-datasets based on geophysical criteria, statistical mixture can sometimes be avoided and much more Gaussian behaviors recovered. We conclude with some general recommendations and point out that although statistical mixture always tends to sharpen the resulting distribution, it does not necessarily lead to a Laplacian distribution. This needs to be taken into account when dealing with such non-Gaussian distributions.

An Alternative Approach to Analyze Ipsative Data. Revisiting Experiential Learning Theory.

PubMed

Batista-Foguet, Joan M; Ferrer-Rosell, Berta; Serlavós, Ricard; Coenders, Germà; Boyatzis, Richard E

2015-01-01

The ritualistic use of statistical models regardless of the type of data actually available is a common practice across disciplines which we dare to call type zero error. Statistical models involve a series of assumptions whose existence is often neglected altogether, this is specially the case with ipsative data. This paper illustrates the consequences of this ritualistic practice within Kolb's Experiential Learning Theory (ELT) operationalized through its Learning Style Inventory (KLSI). We show how using a well-known methodology in other disciplines-compositional data analysis (CODA) and log ratio transformations-KLSI data can be properly analyzed. In addition, the method has theoretical implications: a third dimension of the KLSI is unveiled providing room for future research. This third dimension describes an individual's relative preference for learning by prehension rather than by transformation. Using a sample of international MBA students, we relate this dimension with another self-assessment instrument, the Philosophical Orientation Questionnaire (POQ), and with an observer-assessed instrument, the Emotional and Social Competency Inventory (ESCI-U). Both show plausible statistical relationships. An intellectual operating philosophy (IOP) is linked to a preference for prehension, whereas a pragmatic operating philosophy (POP) is linked to transformation. Self-management and social awareness competencies are linked to a learning preference for transforming knowledge, whereas relationship management and cognitive competencies are more related to approaching learning by prehension.

An Alternative Approach to Analyze Ipsative Data. Revisiting Experiential Learning Theory

PubMed Central

Batista-Foguet, Joan M.; Ferrer-Rosell, Berta; Serlavós, Ricard; Coenders, Germà; Boyatzis, Richard E.

2015-01-01

The ritualistic use of statistical models regardless of the type of data actually available is a common practice across disciplines which we dare to call type zero error. Statistical models involve a series of assumptions whose existence is often neglected altogether, this is specially the case with ipsative data. This paper illustrates the consequences of this ritualistic practice within Kolb's Experiential Learning Theory (ELT) operationalized through its Learning Style Inventory (KLSI). We show how using a well-known methodology in other disciplines—compositional data analysis (CODA) and log ratio transformations—KLSI data can be properly analyzed. In addition, the method has theoretical implications: a third dimension of the KLSI is unveiled providing room for future research. This third dimension describes an individual's relative preference for learning by prehension rather than by transformation. Using a sample of international MBA students, we relate this dimension with another self-assessment instrument, the Philosophical Orientation Questionnaire (POQ), and with an observer-assessed instrument, the Emotional and Social Competency Inventory (ESCI-U). Both show plausible statistical relationships. An intellectual operating philosophy (IOP) is linked to a preference for prehension, whereas a pragmatic operating philosophy (POP) is linked to transformation. Self-management and social awareness competencies are linked to a learning preference for transforming knowledge, whereas relationship management and cognitive competencies are more related to approaching learning by prehension. PMID:26617561

On the systematics in apparent proper motions of radio sources observed by VLBI

NASA Astrophysics Data System (ADS)

Raposo-Pulido, V.; Lambert, S.; Capitaine, N.; Nilsson, T.; Heinkelmann, R.; Schuh, H.

2015-08-01

For about twenty years, several authors have been investigating the systematics in the apparent proper motions of radio source positions. In some cases, the theoretical work developed (Pyne et al., 1996) could not be assessed due to the few number of VLBI observations. In other cases, the effects attributed to apparent proper motion could not be related successfully because there were no significant evidences from a statistical point of view (MacMillan, 2005). In this work we provide considerations about the estimation of the coefficients of spherical harmonics, based on a three-step procedure used by Titov et al. (2011) and Titov and Lambert (2013). The early stage of this work has been to compare step by step the computations and estimation processes between the Calc/Solve (http://gemini.gsfc.nasa.gov/solve/) and VieVS software (Böhm et al., 2012). To achieve this, the results were analyzed and compared with the previous study done by Titov and Lambert (2013).

Green Chemistry Metrics with Special Reference to Green Analytical Chemistry.

PubMed

Tobiszewski, Marek; Marć, Mariusz; Gałuszka, Agnieszka; Namieśnik, Jacek

2015-06-12

The concept of green chemistry is widely recognized in chemical laboratories. To properly measure an environmental impact of chemical processes, dedicated assessment tools are required. This paper summarizes the current state of knowledge in the field of development of green chemistry and green analytical chemistry metrics. The diverse methods used for evaluation of the greenness of organic synthesis, such as eco-footprint, E-Factor, EATOS, and Eco-Scale are described. Both the well-established and recently developed green analytical chemistry metrics, including NEMI labeling and analytical Eco-scale, are presented. Additionally, this paper focuses on the possibility of the use of multivariate statistics in evaluation of environmental impact of analytical procedures. All the above metrics are compared and discussed in terms of their advantages and disadvantages. The current needs and future perspectives in green chemistry metrics are also discussed.

Cooperativity in plastic crystals

NASA Astrophysics Data System (ADS)

Pieruccini, Marco; Tombari, Elpidio

2018-03-01

A statistical mechanical model previously adopted for the analysis of the α -relaxation in structural glass formers is rederived within a general theoretical framework originally developed for systems approaching the ideal glassy state. The interplay between nonexponentiality and cooperativity is reconsidered in the light of energy landscape concepts. The method is used to estimate the cooperativity in orientationally disordered crystals, either from the analysis of literature data on linear dielectric response or from the enthalpy relaxation function obtained by temperature-modulated calorimetry. Knowledge of the specific heat step due to the freezing of the configurational or conformational modes at the glass transition is needed in order to properly account for the extent to which the relaxing system deviates from equilibrium during the rearrangement processes. A number of plastic crystals have been analyzed, and relatively higher cooperativities are found in the presence of hydrogen bonding interaction.

Fault Detection of Bearing Systems through EEMD and Optimization Algorithm

PubMed Central

Lee, Dong-Han; Ahn, Jong-Hyo; Koh, Bong-Hwan

2017-01-01

This study proposes a fault detection and diagnosis method for bearing systems using ensemble empirical mode decomposition (EEMD) based feature extraction, in conjunction with particle swarm optimization (PSO), principal component analysis (PCA), and Isomap. First, a mathematical model is assumed to generate vibration signals from damaged bearing components, such as the inner-race, outer-race, and rolling elements. The process of decomposing vibration signals into intrinsic mode functions (IMFs) and extracting statistical features is introduced to develop a damage-sensitive parameter vector. Finally, PCA and Isomap algorithm are used to classify and visualize this parameter vector, to separate damage characteristics from healthy bearing components. Moreover, the PSO-based optimization algorithm improves the classification performance by selecting proper weightings for the parameter vector, to maximize the visualization effect of separating and grouping of parameter vectors in three-dimensional space. PMID:29143772

Cohesive Modeling of Transverse Cracking in Laminates with a Single Layer of Elements per Ply

NASA Technical Reports Server (NTRS)

VanDerMeer, Frans P.; Davila, Carlos G.

2013-01-01

This study aims to bridge the gap between classical understanding of transverse cracking in cross-ply laminates and recent computational methods for the modeling of progressive laminate failure. Specifically, the study investigates under what conditions a finite element model with cohesive X-FEM cracks can reproduce the in situ effect for the ply strength. It is shown that it is possible to do so with a single element across the thickness of the ply, provided that the interface stiffness is properly selected. The optimal value for this interface stiffness is derived with an analytical shear lag model. It is also shown that, when the appropriate statistical variation of properties has been applied, models with a single element through the thickness of a ply can predict the density of transverse matrix cracks

Automated Statistical Forecast Method to 36-48H ahead of Storm Wind and Dangerous Precipitation at the Mediterranean Region

NASA Astrophysics Data System (ADS)

Perekhodtseva, E. V.

2009-09-01

Development of successful method of forecast of storm winds, including squalls and tornadoes and heavy rainfalls, that often result in human and material losses, could allow one to take proper measures against destruction of buildings and to protect people. Well-in-advance successful forecast (from 12 hours to 48 hour) makes possible to reduce the losses. Prediction of the phenomena involved is a very difficult problem for synoptic till recently. The existing graphic and calculation methods still depend on subjective decision of an operator. Nowadays in Russia there is no hydrodynamic model for forecast of the maximal precipitation and wind velocity V> 25m/c, hence the main tools of objective forecast are statistical methods using the dependence of the phenomena involved on a number of atmospheric parameters (predictors). Statistical decisive rule of the alternative and probability forecast of these events was obtained in accordance with the concept of "perfect prognosis" using the data of objective analysis. For this purpose the different teaching samples of present and absent of this storm wind and rainfalls were automatically arranged that include the values of forty physically substantiated potential predictors. Then the empirical statistical method was used that involved diagonalization of the mean correlation matrix R of the predictors and extraction of diagonal blocks of strongly correlated predictors. Thus for these phenomena the most informative predictors were selected without loosing information. The statistical decisive rules for diagnosis and prognosis of the phenomena involved U(X) were calculated for choosing informative vector-predictor. We used the criterion of distance of Mahalanobis and criterion of minimum of entropy by Vapnik-Chervonenkis for the selection predictors. Successful development of hydrodynamic models for short-term forecast and improvement of 36-48h forecasts of pressure, temperature and others parameters allowed us to use the prognostic fields of those models for calculations of the discriminant functions in the nodes of the grid 150x150km and the values of probabilities P of dangerous wind and thus to get fully automated forecasts. In order to change to the alternative forecast the author proposes the empirical threshold values specified for this phenomenon and advance period 36 hours. In the accordance to the Pirsey-Obukhov criterion (T), the success of these automated statistical methods of forecast of squalls and tornadoes to 36 -48 hours ahead and heavy rainfalls in the warm season for the territory of Italy, Spain and Balkan countries is T = 1-a-b=0,54: 0,78 after author experiments. A lot of examples of very successful forecasts of summer storm wind and heavy rainfalls over the Italy and Spain territory are submitted at this report. The same decisive rules were applied to the forecast of these phenomena during cold period in this year too. This winter heavy snowfalls in Spain and in Italy and storm wind at this territory were observed very often. And our forecasts are successful.

Dynamically biased statistical model for the ortho/para conversion in the H2 + H3+ → H3+ + H2 reaction.

PubMed

Gómez-Carrasco, Susana; González-Sánchez, Lola; Aguado, Alfredo; Sanz-Sanz, Cristina; Zanchet, Alexandre; Roncero, Octavio

2012-09-07

In this work we present a dynamically biased statistical model to describe the evolution of the title reaction from statistical to a more direct mechanism, using quasi-classical trajectories (QCT). The method is based on the one previously proposed by Park and Light [J. Chem. Phys. 126, 044305 (2007)]. A recent global potential energy surface is used here to calculate the capture probabilities, instead of the long-range ion-induced dipole interactions. The dynamical constraints are introduced by considering a scrambling matrix which depends on energy and determine the probability of the identity/hop/exchange mechanisms. These probabilities are calculated using QCT. It is found that the high zero-point energy of the fragments is transferred to the rest of the degrees of freedom, what shortens the lifetime of H(5)(+) complexes and, as a consequence, the exchange mechanism is produced with lower proportion. The zero-point energy (ZPE) is not properly described in quasi-classical trajectory calculations and an approximation is done in which the initial ZPE of the reactants is reduced in QCT calculations to obtain a new ZPE-biased scrambling matrix. This reduction of the ZPE is explained by the need of correcting the pure classical level number of the H(5)(+) complex, as done in classical simulations of unimolecular processes and to get equivalent quantum and classical rate constants using Rice-Ramsperger-Kassel-Marcus theory. This matrix allows to obtain a ratio of hop/exchange mechanisms, α(T), in rather good agreement with recent experimental results by Crabtree et al. [J. Chem. Phys. 134, 194311 (2011)] at room temperature. At lower temperatures, however, the present simulations predict too high ratios because the biased scrambling matrix is not statistical enough. This demonstrates the importance of applying quantum methods to simulate this reaction at the low temperatures of astrophysical interest.

Dynamically biased statistical model for the ortho/para conversion in the H2+H3+ --> H3++ H2 reaction

NASA Astrophysics Data System (ADS)

Gómez-Carrasco, Susana; González-Sánchez, Lola; Aguado, Alfredo; Sanz-Sanz, Cristina; Zanchet, Alexandre; Roncero, Octavio

2012-09-01

In this work we present a dynamically biased statistical model to describe the evolution of the title reaction from statistical to a more direct mechanism, using quasi-classical trajectories (QCT). The method is based on the one previously proposed by Park and Light [J. Chem. Phys. 126, 044305 (2007), 10.1063/1.2430711]. A recent global potential energy surface is used here to calculate the capture probabilities, instead of the long-range ion-induced dipole interactions. The dynamical constraints are introduced by considering a scrambling matrix which depends on energy and determine the probability of the identity/hop/exchange mechanisms. These probabilities are calculated using QCT. It is found that the high zero-point energy of the fragments is transferred to the rest of the degrees of freedom, what shortens the lifetime of H_5^+ complexes and, as a consequence, the exchange mechanism is produced with lower proportion. The zero-point energy (ZPE) is not properly described in quasi-classical trajectory calculations and an approximation is done in which the initial ZPE of the reactants is reduced in QCT calculations to obtain a new ZPE-biased scrambling matrix. This reduction of the ZPE is explained by the need of correcting the pure classical level number of the H_5^+ complex, as done in classical simulations of unimolecular processes and to get equivalent quantum and classical rate constants using Rice-Ramsperger-Kassel-Marcus theory. This matrix allows to obtain a ratio of hop/exchange mechanisms, α(T), in rather good agreement with recent experimental results by Crabtree et al. [J. Chem. Phys. 134, 194311 (2011), 10.1063/1.3587246] at room temperature. At lower temperatures, however, the present simulations predict too high ratios because the biased scrambling matrix is not statistical enough. This demonstrates the importance of applying quantum methods to simulate this reaction at the low temperatures of astrophysical interest.

Maximum-likelihood curve-fitting scheme for experiments with pulsed lasers subject to intensity fluctuations.

PubMed

Metz, Thomas; Walewski, Joachim; Kaminski, Clemens F

2003-03-20

Evaluation schemes, e.g., least-squares fitting, are not generally applicable to any types of experiments. If the evaluation schemes were not derived from a measurement model that properly described the experiment to be evaluated, poorer precision or accuracy than attainable from the measured data could result. We outline ways in which statistical data evaluation schemes should be derived for all types of experiment, and we demonstrate them for laser-spectroscopic experiments, in which pulse-to-pulse fluctuations of the laser power cause correlated variations of laser intensity and generated signal intensity. The method of maximum likelihood is demonstrated in the derivation of an appropriate fitting scheme for this type of experiment. Statistical data evaluation contains the following steps. First, one has to provide a measurement model that considers statistical variation of all enclosed variables. Second, an evaluation scheme applicable to this particular model has to be derived or provided. Third, the scheme has to be characterized in terms of accuracy and precision. A criterion for accepting an evaluation scheme is that it have accuracy and precision as close as possible to the theoretical limit. The fitting scheme derived for experiments with pulsed lasers is compared to well-established schemes in terms of fitting power and rational functions. The precision is found to be as much as three timesbetter than for simple least-squares fitting. Our scheme also suppresses the bias on the estimated model parameters that other methods may exhibit if they are applied in an uncritical fashion. We focus on experiments in nonlinear spectroscopy, but the fitting scheme derived is applicable in many scientific disciplines.

Using Bloom's Taxonomy to Evaluate the Cognitive Levels of Master Class Textbook's Questions

ERIC Educational Resources Information Center

Assaly, Ibtihal R.; Smadi, Oqlah M.

2015-01-01

This study aimed at evaluating the cognitive levels of the questions following the reading texts of Master Class textbook. A checklist based on Bloom's Taxonomy was the instrument used to categorize the cognitive levels of these questions. The researchers used proper statistics to rank the cognitive levels of the comprehension questions. The…

Predictor sort sampling and one-sided confidence bounds on quantiles

Treesearch

Steve Verrill; Victoria L. Herian; David W. Green

2002-01-01

Predictor sort experiments attempt to make use of the correlation between a predictor that can be measured prior to the start of an experiment and the response variable that we are investigating. Properly designed and analyzed, they can reduce necessary sample sizes, increase statistical power, and reduce the lengths of confidence intervals. However, if the non- random...

Brady, Our Firstborn Son, Has Autism

ERIC Educational Resources Information Center

Yeh-Kennedy, Mei

2008-01-01

Autism awareness is spreading like wildfire. Diagnoses have increased at an astounding rate. The statistic most often quoted is that 1 child in 150 has autism. As if the high rate of autism diagnoses were not worrisome enough, many doctors are not properly trained, or kept up to date, on how to detect autism at the earliest possible age. In many…

Computer Access and Computer Use for Science Performance of Racial and Linguistic Minority Students

ERIC Educational Resources Information Center

Chang, Mido; Kim, Sunha

2009-01-01

This study examined the effects of computer access and computer use on the science achievement of elementary school students, with focused attention on the effects for racial and linguistic minority students. The study used the Early Childhood Longitudinal Study (ECLS-K) database and conducted statistical analyses with proper weights and…

FORTRAN IV Program to Determine the Proper Sequence of Records in a Datafile

ERIC Educational Resources Information Center

Jones, Michael P.; Yoshida, Roland K.

1975-01-01

This FORTRAN IV program executes an essential editing procedure which determines whether a datafile contains an equal number of records (cards) per case which are also in the intended sequential order. The program which requires very little background in computer programming is designed primarily for the user of packaged statistical procedures.…

77 FR 3477 - Agency Information Collection Activities: Proposed Collection; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-24

... collection for the proper performance of the agency's functions; (2) the accuracy of the estimated burden; (3... submitted to CMS through the 372 web-based form. The report is used by CMS to compare actual data in the... provided is compared to that in the Medicaid Statistical Information System (CMS-R-284, OCN 0938-0345...

An Intuitive Graphical Approach to Understanding the Split-Plot Experiment

ERIC Educational Resources Information Center

Robinson, Timothy J.; Brenneman, William A.; Myers, William R.

2009-01-01

While split-plot designs have received considerable attention in the literature over the past decade, there seems to be a general lack of intuitive understanding of the error structure of these designs and the resulting statistical analysis. Typically, students learn the proper error terms for testing factors of a split-plot design via "expected…

U.S.-MEXICO BORDER PROGRAM ARIZONA BORDER STUDY--STANDARD OPERATING PROCEDURE FOR SAMPLING WEIGHT CALCULATION (IIT-A-9.0)

EPA Science Inventory

The purpose of this SOP is to describe the procedures undertaken to calculate sampling weights. The sampling weights are needed to obtain weighted statistics of the study data. This SOP uses data that have been properly coded and certified with appropriate QA/QC procedures by th...

76 FR 66875 - Informal Entry Limit and Removal of a Formal Entry Requirement

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-28

... to properly assess duties on the merchandise and collect accurate statistics with respect to the.... In Sec. 10.1: a. Introductory paragraph (a) is amended by removing the word ``shall'' and adding in... removing the word ``shall'' and adding in its place the word ``must''; m. Introductory paragraph (h)(4) is...

Knowledge of the pelvic floor in nulliparous women

PubMed Central

Neels, Hedwig; Wyndaele, Jean-Jacques; Tjalma, Wiebren A. A.; De Wachter, Stefan; Wyndaele, Michel; Vermandel, Alexandra

2016-01-01

[Purpose] Proper pelvic floor function is important to avoid serious dysfunctions including incontinence, prolapse, and sexual problems. The current study evaluated the knowledge of young nulliparous women about their pelvic floor and identified what additional information they wanted. [Subjects and Methods] In this cross-sectional survey, a validated, 36 item questionnaire was distributed to 212 nulliparous women. The questionnaire addressed demography, pelvic floor muscles, pelvic floor dysfunction, and possible information sources. Descriptive statistics were generated for all variables. Stability and validity testing were performed using Kappa statistics and intra class correlation coefficients to define agreement for each question. The study was approved by the ethics Committee (B300201318334). [Results] Using a VAS scale (0 to 10), the women rated their knowledge about the pelvic floor as a mean of 2.4 (SD 2.01). A total of 93% of the women were insufficiently informed and requested more information; 25% had concerns about developing urinary incontinence, and 14% about fecal incontinence. Many of the women were unaware what pelvic floor training meant. [Conclusion] There was a significant lack of knowledge about pelvic floor function among nulliparous women. The majority of nulliparous women expressed a need for education, which might offer a way to reduce dysfunction. PMID:27313364

Attracting Dynamics of Frontal Cortex Ensembles during Memory-Guided Decision-Making

PubMed Central

Seamans, Jeremy K.; Durstewitz, Daniel

2011-01-01

A common theoretical view is that attractor-like properties of neuronal dynamics underlie cognitive processing. However, although often proposed theoretically, direct experimental support for the convergence of neural activity to stable population patterns as a signature of attracting states has been sparse so far, especially in higher cortical areas. Combining state space reconstruction theorems and statistical learning techniques, we were able to resolve details of anterior cingulate cortex (ACC) multiple single-unit activity (MSUA) ensemble dynamics during a higher cognitive task which were not accessible previously. The approach worked by constructing high-dimensional state spaces from delays of the original single-unit firing rate variables and the interactions among them, which were then statistically analyzed using kernel methods. We observed cognitive-epoch-specific neural ensemble states in ACC which were stable across many trials (in the sense of being predictive) and depended on behavioral performance. More interestingly, attracting properties of these cognitively defined ensemble states became apparent in high-dimensional expansions of the MSUA spaces due to a proper unfolding of the neural activity flow, with properties common across different animals. These results therefore suggest that ACC networks may process different subcomponents of higher cognitive tasks by transiting among different attracting states. PMID:21625577

Impact of parametric uncertainty on estimation of the energy deposition into an irradiated brain tumor

NASA Astrophysics Data System (ADS)

Taverniers, Søren; Tartakovsky, Daniel M.

2017-11-01

Predictions of the total energy deposited into a brain tumor through X-ray irradiation are notoriously error-prone. We investigate how this predictive uncertainty is affected by uncertainty in both the location of the region occupied by a dose-enhancing iodinated contrast agent and the agent's concentration. This is done within the probabilistic framework in which these uncertain parameters are modeled as random variables. We employ the stochastic collocation (SC) method to estimate statistical moments of the deposited energy in terms of statistical moments of the random inputs, and the global sensitivity analysis (GSA) to quantify the relative importance of uncertainty in these parameters on the overall predictive uncertainty. A nonlinear radiation-diffusion equation dramatically magnifies the coefficient of variation of the uncertain parameters, yielding a large coefficient of variation for the predicted energy deposition. This demonstrates that accurate prediction of the energy deposition requires a proper treatment of even small parametric uncertainty. Our analysis also reveals that SC outperforms standard Monte Carlo, but its relative efficiency decreases as the number of uncertain parameters increases from one to three. A robust GSA ameliorates this problem by reducing this number.

Design of Neural Networks for Fast Convergence and Accuracy: Dynamics and Control

NASA Technical Reports Server (NTRS)

Maghami, Peiman G.; Sparks, Dean W., Jr.

1997-01-01

A procedure for the design and training of artificial neural networks, used for rapid and efficient controls and dynamics design and analysis for flexible space systems, has been developed. Artificial neural networks are employed, such that once properly trained, they provide a means of evaluating the impact of design changes rapidly. Specifically, two-layer feedforward neural networks are designed to approximate the functional relationship between the component/spacecraft design changes and measures of its performance or nonlinear dynamics of the system/components. A training algorithm, based on statistical sampling theory, is presented, which guarantees that the trained networks provide a designer-specified degree of accuracy in mapping the functional relationship. Within each iteration of this statistical-based algorithm, a sequential design algorithm is used for the design and training of the feedforward network to provide rapid convergence to the network goals. Here, at each sequence a new network is trained to minimize the error of previous network. The proposed method should work for applications wherein an arbitrary large source of training data can be generated. Two numerical examples are performed on a spacecraft application in order to demonstrate the feasibility of the proposed approach.

Multivariate approaches for stability control of the olive oil reference materials for sensory analysis - part I: framework and fundamentals.

PubMed

Valverde-Som, Lucia; Ruiz-Samblás, Cristina; Rodríguez-García, Francisco P; Cuadros-Rodríguez, Luis

2018-02-09

Virgin olive oil is the only food product for which sensory analysis is regulated to classify it in different quality categories. To harmonize the results of the sensorial method, the use of standards or reference materials is crucial. The stability of sensory reference materials is required to enable their suitable control, aiming to confirm that their specific target values are maintained on an ongoing basis. Currently, such stability is monitored by means of sensory analysis and the sensory panels are in the paradoxical situation of controlling the standards that are devoted to controlling the panels. In the present study, several approaches based on similarity analysis are exploited. For each approach, the specific methodology to build a proper multivariate control chart to monitor the stability of the sensory properties is explained and discussed. The normalized Euclidean and Mahalanobis distances, the so-called nearness and hardiness indices respectively, have been defined as new similarity indices to range the values from 0 to 1. Also, the squared mean from Hotelling's T 2 -statistic and Q 2 -statistic has been proposed as another similarity index. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

A subregion-based burden test for simultaneous identification of susceptibility loci and subregions within.

PubMed

Zhu, Bin; Mirabello, Lisa; Chatterjee, Nilanjan

2018-06-22

In rare variant association studies, aggregating rare and/or low frequency variants, may increase statistical power for detection of the underlying susceptibility gene or region. However, it is unclear which variants, or class of them, in a gene contribute most to the association. We proposed a subregion-based burden test (REBET) to simultaneously select susceptibility genes and identify important underlying subregions. The subregions are predefined by shared common biologic characteristics, such as the protein domain or functional impact. Based on a subset-based approach considering local correlations between combinations of test statistics of subregions, REBET is able to properly control the type I error rate while adjusting for multiple comparisons in a computationally efficient manner. Simulation studies show that REBET can achieve power competitive to alternative methods when rare variants cluster within subregions. In two case studies, REBET is able to identify known disease susceptibility genes, and more importantly pinpoint the unreported most susceptible subregions, which represent protein domains essential for gene function. R package REBET is available at https://dceg.cancer.gov/tools/analysis/rebet. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.

Design of neural networks for fast convergence and accuracy: dynamics and control.

PubMed

Maghami, P G; Sparks, D R

2000-01-01

A procedure for the design and training of artificial neural networks, used for rapid and efficient controls and dynamics design and analysis for flexible space systems, has been developed. Artificial neural networks are employed, such that once properly trained, they provide a means of evaluating the impact of design changes rapidly. Specifically, two-layer feedforward neural networks are designed to approximate the functional relationship between the component/spacecraft design changes and measures of its performance or nonlinear dynamics of the system/components. A training algorithm, based on statistical sampling theory, is presented, which guarantees that the trained networks provide a designer-specified degree of accuracy in mapping the functional relationship. Within each iteration of this statistical-based algorithm, a sequential design algorithm is used for the design and training of the feedforward network to provide rapid convergence to the network goals. Here, at each sequence a new network is trained to minimize the error of previous network. The proposed method should work for applications wherein an arbitrary large source of training data can be generated. Two numerical examples are performed on a spacecraft application in order to demonstrate the feasibility of the proposed approach.

The effect of center-of-mass motion on photon statistics

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

Zhang, Yang; Zhang, Jun; Wu, Shao-xiong

2015-10-15

We analyze the photon statistics of a weakly driven cavity quantum electrodynamics system and discuss the effects of photon blockade and photon-induced tunneling by effectively utilizing instead of avoiding the center-of-mass motion of a two-level atom trapped in the cavity. With the resonant interaction between atom, photon and phonon, it is shown that the bunching and anti-bunching of photons can occur with properly driving frequency. Our study shows the influence of the imperfect cooling of atom on the blockade and provides an attempt to take advantage of the center-of-mass motion.

Quantum statistical mechanics of dense partially ionized hydrogen

NASA Technical Reports Server (NTRS)

Dewitt, H. E.; Rogers, F. J.

1972-01-01

The theory of dense hydrogen plasmas beginning with the two component quantum grand partition function is reviewed. It is shown that ionization equilibrium and molecular dissociation equilibrium can be treated in the same manner with proper consideration of all two-body states. A quantum perturbation expansion is used to give an accurate calculation of the equation of state of the gas for any degree of dissociation and ionization. The statistical mechanical calculation of the plasma equation of state is intended for stellar interiors. The general approach is extended to the calculation of the equation of state of the outer layers of large planets.

Six Guidelines for Interesting Research.

PubMed

Gray, Kurt; Wegner, Daniel M

2013-09-01

There are many guides on proper psychology, but far fewer on interesting psychology. This article presents six guidelines for interesting research. The first three-Phenomena First, Be Surprising, and Grandmothers, Not Scientists-suggest how to choose your research question; the last three-Be The Participant, Simple Statistics, and Powerful Beginnings-suggest how to answer your research question and offer perspectives on experimental design, statistical analysis, and effective communication. These guidelines serve as reminders that replicability is necessary but not sufficient for compelling psychological science. Interesting research considers subjective experience; it listens to the music of the human condition. © The Author(s) 2013.

In vivo Comet assay--statistical analysis and power calculations of mice testicular cells.

PubMed

Hansen, Merete Kjær; Sharma, Anoop Kumar; Dybdahl, Marianne; Boberg, Julie; Kulahci, Murat

2014-11-01

The in vivo Comet assay is a sensitive method for evaluating DNA damage. A recurrent concern is how to analyze the data appropriately and efficiently. A popular approach is to summarize the raw data into a summary statistic prior to the statistical analysis. However, consensus on which summary statistic to use has yet to be reached. Another important consideration concerns the assessment of proper sample sizes in the design of Comet assay studies. This study aims to identify a statistic suitably summarizing the % tail DNA of mice testicular samples in Comet assay studies. A second aim is to provide curves for this statistic outlining the number of animals and gels to use. The current study was based on 11 compounds administered via oral gavage in three doses to male mice: CAS no. 110-26-9, CAS no. 512-56-1, CAS no. 111873-33-7, CAS no. 79-94-7, CAS no. 115-96-8, CAS no. 598-55-0, CAS no. 636-97-5, CAS no. 85-28-9, CAS no. 13674-87-8, CAS no. 43100-38-5 and CAS no. 60965-26-6. Testicular cells were examined using the alkaline version of the Comet assay and the DNA damage was quantified as % tail DNA using a fully automatic scoring system. From the raw data 23 summary statistics were examined. A linear mixed-effects model was fitted to the summarized data and the estimated variance components were used to generate power curves as a function of sample size. The statistic that most appropriately summarized the within-sample distributions was the median of the log-transformed data, as it most consistently conformed to the assumptions of the statistical model. Power curves for 1.5-, 2-, and 2.5-fold changes of the highest dose group compared to the control group when 50 and 100 cells were scored per gel are provided to aid in the design of future Comet assay studies on testicular cells. Copyright © 2014 Elsevier B.V. All rights reserved.

Beware of external validation! - A Comparative Study of Several Validation Techniques used in QSAR Modelling.

PubMed

Majumdar, Subhabrata; Basak, Subhash C

2018-04-26

Proper validation is an important aspect of QSAR modelling. External validation is one of the widely used validation methods in QSAR where the model is built on a subset of the data and validated on the rest of the samples. However, its effectiveness for datasets with a small number of samples but large number of predictors remains suspect. Calculating hundreds or thousands of molecular descriptors using currently available software has become the norm in QSAR research, owing to computational advances in the past few decades. Thus, for n chemical compounds and p descriptors calculated for each molecule, the typical chemometric dataset today has high value of p but small n (i.e. n < p). Motivated by the evidence of inadequacies of external validation in estimating the true predictive capability of a statistical model in recent literature, this paper performs an extensive and comparative study of this method with several other validation techniques. We compared four validation methods: leave-one-out, K-fold, external and multi-split validation, using statistical models built using the LASSO regression, which simultaneously performs variable selection and modelling. We used 300 simulated datasets and one real dataset of 95 congeneric amine mutagens for this evaluation. External validation metrics have high variation among different random splits of the data, hence are not recommended for predictive QSAR models. LOO has the overall best performance among all validation methods applied in our scenario. Results from external validation are too unstable for the datasets we analyzed. Based on our findings, we recommend using the LOO procedure for validating QSAR predictive models built on high-dimensional small-sample data. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Wide Binaries in TGAS: Search Method and First Results

NASA Astrophysics Data System (ADS)

Andrews, Jeff J.; Chanamé, Julio; Agüeros, Marcel A.

2018-04-01

Half of all stars reside in binary systems, many of which have orbital separations in excess of 1000 AU. Such binaries are typically identified in astrometric catalogs by matching the proper motions vectors of close stellar pairs. We present a fully Bayesian method that properly takes into account positions, proper motions, parallaxes, and their correlated uncertainties to identify widely separated stellar binaries. After applying our method to the >2 × 106 stars in the Tycho-Gaia astrometric solution from Gaia DR1, we identify over 6000 candidate wide binaries. For those pairs with separations less than 40,000 AU, we determine the contamination rate to be ~5%. This sample has an orbital separation (a) distribution that is roughly flat in log space for separations less than ~5000 AU and follows a power law of a -1.6 at larger separations.

Rapid Classification and Identification of Multiple Microorganisms with Accurate Statistical Significance via High-Resolution Tandem Mass Spectrometry

NASA Astrophysics Data System (ADS)

Alves, Gelio; Wang, Guanghui; Ogurtsov, Aleksey Y.; Drake, Steven K.; Gucek, Marjan; Sacks, David B.; Yu, Yi-Kuo

2018-06-01

Rapid and accurate identification and classification of microorganisms is of paramount importance to public health and safety. With the advance of mass spectrometry (MS) technology, the speed of identification can be greatly improved. However, the increasing number of microbes sequenced is complicating correct microbial identification even in a simple sample due to the large number of candidates present. To properly untwine candidate microbes in samples containing one or more microbes, one needs to go beyond apparent morphology or simple "fingerprinting"; to correctly prioritize the candidate microbes, one needs to have accurate statistical significance in microbial identification. We meet these challenges by using peptide-centric representations of microbes to better separate them and by augmenting our earlier analysis method that yields accurate statistical significance. Here, we present an updated analysis workflow that uses tandem MS (MS/MS) spectra for microbial identification or classification. We have demonstrated, using 226 MS/MS publicly available data files (each containing from 2500 to nearly 100,000 MS/MS spectra) and 4000 additional MS/MS data files, that the updated workflow can correctly identify multiple microbes at the genus and often the species level for samples containing more than one microbe. We have also shown that the proposed workflow computes accurate statistical significances, i.e., E values for identified peptides and unified E values for identified microbes. Our updated analysis workflow MiCId, a freely available software for Microorganism Classification and Identification, is available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html.

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

Lewis, John R.; Brooks, Dusty Marie

In pressurized water reactors, the prevention, detection, and repair of cracks within dissimilar metal welds is essential to ensure proper plant functionality and safety. Weld residual stresses, which are difficult to model and cannot be directly measured, contribute to the formation and growth of cracks due to primary water stress corrosion cracking. Additionally, the uncertainty in weld residual stress measurements and modeling predictions is not well understood, further complicating the prediction of crack evolution. The purpose of this document is to develop methodology to quantify the uncertainty associated with weld residual stress that can be applied to modeling predictions andmore » experimental measurements. Ultimately, the results can be used to assess the current state of uncertainty and to build confidence in both modeling and experimental procedures. The methodology consists of statistically modeling the variation in the weld residual stress profiles using functional data analysis techniques. Uncertainty is quantified using statistical bounds (e.g. confidence and tolerance bounds) constructed with a semi-parametric bootstrap procedure. Such bounds describe the range in which quantities of interest, such as means, are expected to lie as evidenced by the data. The methodology is extended to provide direct comparisons between experimental measurements and modeling predictions by constructing statistical confidence bounds for the average difference between the two quantities. The statistical bounds on the average difference can be used to assess the level of agreement between measurements and predictions. The methodology is applied to experimental measurements of residual stress obtained using two strain relief measurement methods and predictions from seven finite element models developed by different organizations during a round robin study.« less

Rapid Classification and Identification of Multiple Microorganisms with Accurate Statistical Significance via High-Resolution Tandem Mass Spectrometry.

PubMed

Alves, Gelio; Wang, Guanghui; Ogurtsov, Aleksey Y; Drake, Steven K; Gucek, Marjan; Sacks, David B; Yu, Yi-Kuo

2018-06-05

Rapid and accurate identification and classification of microorganisms is of paramount importance to public health and safety. With the advance of mass spectrometry (MS) technology, the speed of identification can be greatly improved. However, the increasing number of microbes sequenced is complicating correct microbial identification even in a simple sample due to the large number of candidates present. To properly untwine candidate microbes in samples containing one or more microbes, one needs to go beyond apparent morphology or simple "fingerprinting"; to correctly prioritize the candidate microbes, one needs to have accurate statistical significance in microbial identification. We meet these challenges by using peptide-centric representations of microbes to better separate them and by augmenting our earlier analysis method that yields accurate statistical significance. Here, we present an updated analysis workflow that uses tandem MS (MS/MS) spectra for microbial identification or classification. We have demonstrated, using 226 MS/MS publicly available data files (each containing from 2500 to nearly 100,000 MS/MS spectra) and 4000 additional MS/MS data files, that the updated workflow can correctly identify multiple microbes at the genus and often the species level for samples containing more than one microbe. We have also shown that the proposed workflow computes accurate statistical significances, i.e., E values for identified peptides and unified E values for identified microbes. Our updated analysis workflow MiCId, a freely available software for Microorganism Classification and Identification, is available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html . Graphical Abstract ᅟ.

Inferring monopartite projections of bipartite networks: an entropy-based approach

NASA Astrophysics Data System (ADS)

Saracco, Fabio; Straka, Mika J.; Di Clemente, Riccardo; Gabrielli, Andrea; Caldarelli, Guido; Squartini, Tiziano

2017-05-01

Bipartite networks are currently regarded as providing a major insight into the organization of many real-world systems, unveiling the mechanisms driving the interactions occurring between distinct groups of nodes. One of the most important issues encountered when modeling bipartite networks is devising a way to obtain a (monopartite) projection on the layer of interest, which preserves as much as possible the information encoded into the original bipartite structure. In the present paper we propose an algorithm to obtain statistically-validated projections of bipartite networks, according to which any two nodes sharing a statistically-significant number of neighbors are linked. Since assessing the statistical significance of nodes similarity requires a proper statistical benchmark, here we consider a set of four null models, defined within the exponential random graph framework. Our algorithm outputs a matrix of link-specific p-values, from which a validated projection is straightforwardly obtainable, upon running a multiple hypothesis testing procedure. Finally, we test our method on an economic network (i.e. the countries-products World Trade Web representation) and a social network (i.e. MovieLens, collecting the users’ ratings of a list of movies). In both cases non-trivial communities are detected: while projecting the World Trade Web on the countries layer reveals modules of similarly-industrialized nations, projecting it on the products layer allows communities characterized by an increasing level of complexity to be detected; in the second case, projecting MovieLens on the films layer allows clusters of movies whose affinity cannot be fully accounted for by genre similarity to be individuated.

Practice of Iranian Adolescents with Hemophilia in Prevention of Complications of Hemophilia

PubMed Central

Valizadeh, Leila; Hosseini, Fahimeh Alsadat; Zamanzadeh, Vahid; Heidarnezhad, Fatemeh; Jasemi, Madineh; Lankarani, Kamran Bagheri

2015-01-01

Background: Prerequisite for management of a chronic disease involves knowledge about its complications and their prevention. Hemophilia in adolescents influences all the aspects of their lives and thier performance. Objectives: The present study aimed to determine the performance of Iranian hemophilic adolescents in prevention of disease complications. Patients and Methods: In this descriptive-analytical study, 108 adolescents with hemophilia were selected through convenience sampling. Their performance in preventing the complications of hemophilia was evaluated by sending a semi-structured questionnaire to their addresses throughout Iran. Then, the data was analysed using the Statistical Package for Social Sciences (SPSS) software (v. 13) and descriptive and interferential statistics were used. Results: Overall, 32.1% of the participants controlled bleeding during the 1st hour. Inaccessibility of coagulation products was mainly responsible for inhibiting timely and proper bleeding control. In order to relieve bleeding associated pain, only 39.0% of the adolescents used analgesics. On the other hand, 19.8% of the subjects used nonpharmacological methods to relieve pain. The majority of the adolescents did not participate in sport activities (65.4%) others allocated less than 5 hours a week to physical activities (70.5%). In addition, the participants did not have favorable dietary patterns, exercise habits, and dental care. The results showed a significant relationship between the adolescents’ preventive practice with coagulation disorders and utilization of pharmacological pain relief methods. Also, significant relationships were found between severity of the disease; participating in physical activities, number of hours of physical activities; and disease complications. Conclusions: Iranian adolescents did not exhibit favorable practices towards complication prevention. PMID:26600702

PROPER: global protein interaction network alignment through percolation matching.

PubMed

Kazemi, Ehsan; Hassani, Hamed; Grossglauser, Matthias; Pezeshgi Modarres, Hassan

2016-12-12

The alignment of protein-protein interaction (PPI) networks enables us to uncover the relationships between different species, which leads to a deeper understanding of biological systems. Network alignment can be used to transfer biological knowledge between species. Although different PPI-network alignment algorithms were introduced during the last decade, developing an accurate and scalable algorithm that can find alignments with high biological and structural similarities among PPI networks is still challenging. In this paper, we introduce a new global network alignment algorithm for PPI networks called PROPER. Compared to other global network alignment methods, our algorithm shows higher accuracy and speed over real PPI datasets and synthetic networks. We show that the PROPER algorithm can detect large portions of conserved biological pathways between species. Also, using a simple parsimonious evolutionary model, we explain why PROPER performs well based on several different comparison criteria. We highlight that PROPER has high potential in further applications such as detecting biological pathways, finding protein complexes and PPI prediction. The PROPER algorithm is available at http://proper.epfl.ch .

To evaluate the influence of smear layer with different instruments and obturation methods on microleakage of root canal filled teeth: In vitro study.

PubMed

Likhitkar, Manoj S; Kulkarni, Shantaram V; Burande, Aravind; Solanke, Vishal; Kumar, C Sushil; Kamble, Babasaheb

2016-01-01

The success of root canal treatment depends on proper debridement, instrumentation, proper accessibility, and proper restoration. The presence of a smear layer is considered to be a significant factor. This in vitro study was conducted to assess the effect of the presence/absence of a smear layer on the microleakage of root canal filled teeth using different instruments and obturation methods. One hundred extracted mandibular premolars with closed apices and single roots were chosen and then divided into six groups, A to F, consisting of 15 teeth each. The control group included 10 teeth; 5 positive and 5 negative. The teeth were decoronated at the cementoenamel junction. Groups A, B, C, and D were instrumented with engine-driven rotary Protaper NiTi files. Groups E and F were instrumented with conventional stainless steel hand files. Groups A, C, and E were flushed with 3 ml of 17% EDTA to remove the smear layer prior to obturation. All teeth were flushed with 5.25% sodium hypochlorite solution and obturated with AH-Plus sealer with lateral condensation technique for Groups C, D, E, F and with thermoplasticized gutta-percha technique for Groups A and B. Using an electrochemical technique, leakages in the obturated canals were assessed for 45 days. The results were tabulated using Student's t-test (paired and unpaired t-test) with the Statistical Package for the Social Sciences Software Version 21 (IBM Company, New York, USA). Group A showed the lowest mean value at intervals of 10, 20, 30, and 45 days. There was no current flow in the negative controls during the test period. There was leakage in the positive controls within a few minutes of immersion. The results showed that rotary instrumentation contributed toward an exceptional preparation of root canals compared to hand instrumentation. Elimination of the smear layer enhanced the resistance to microleakage; thermoplasticized gutta-percha obturation technique produced a better seal compared to the lateral condensation technique.

Differential expression analysis for RNAseq using Poisson mixed models

PubMed Central

Sun, Shiquan; Hood, Michelle; Scott, Laura; Peng, Qinke; Mukherjee, Sayan; Tung, Jenny

2017-01-01

Abstract Identifying differentially expressed (DE) genes from RNA sequencing (RNAseq) studies is among the most common analyses in genomics. However, RNAseq DE analysis presents several statistical and computational challenges, including over-dispersed read counts and, in some settings, sample non-independence. Previous count-based methods rely on simple hierarchical Poisson models (e.g. negative binomial) to model independent over-dispersion, but do not account for sample non-independence due to relatedness, population structure and/or hidden confounders. Here, we present a Poisson mixed model with two random effects terms that account for both independent over-dispersion and sample non-independence. We also develop a scalable sampling-based inference algorithm using a latent variable representation of the Poisson distribution. With simulations, we show that our method properly controls for type I error and is generally more powerful than other widely used approaches, except in small samples (n <15) with other unfavorable properties (e.g. small effect sizes). We also apply our method to three real datasets that contain related individuals, population stratification or hidden confounders. Our results show that our method increases power in all three data compared to other approaches, though the power gain is smallest in the smallest sample (n = 6). Our method is implemented in MACAU, freely available at www.xzlab.org/software.html. PMID:28369632

Development of a real-time vibrator tracking system for intelligent concrete consolidation.

DOT National Transportation Integrated Search

2014-01-01

Proper consolidation of concrete is critical to the long-term strength of concrete bridge structures. Vibration : is a commonly used method to make concrete owable and to remove the excessive entrapped air, therefore : contributing to proper concr...

Economic efficiency of primary care for CVD prevention and treatment in Eastern European countries

PubMed Central

2013-01-01

Background Cardiovascular disease (CVD) is the main cause of morbidity and mortality worldwide, but it also is highly preventable. The prevention rate mainly depends on the patients’ readiness to follow recommendations and the state’s capacity to support patients. Our study aims to show that proper primary care can decrease the CVD-related morbidity rate and increase the economic efficiency of the healthcare system. Since their admission to the European Union (EU), the Eastern European countries have been in a quest to achieve the Western European standards of living. As a representative Eastern European country, Romania implemented the same strategies as the rest of Eastern Europe, reflected in the health status and lifestyle of its inhabitants. Thus, a valid health policy implemented in Romania should be valid for the rest of the Eastern European countries. Methods Based on the data collected during the EUROASPIRE III Romania Follow Up study, the potential costs of healthcare were estimated for various cases over a 10-year time period. The total costs were split into patient-supported costs and state-supported costs. The state-supported costs were used to deduce the rate of patients with severe CVD that can be treated yearly. A statistical model for the evolution of this rate was computed based on the readiness of the patients to comply with proper primary care treatment. Results We demonstrate that for patients ignoring the risks, a severe CVD has disadvantageous economic consequences, leading to increased healthcare expenses and even poverty. In contrast, performing appropriate prevention activities result in a decrease of the expenses allocated to a (eventual) CVD. In the long-term, the number of patients with severe CVD that can be treated increases as the number of patients receiving proper primary care increases. Conclusions Proper primary care can not only decrease the risk of major CVD but also decrease the healthcare costs and increase the number of patients that can be treated. Most importantly, the health standards of the EU can be achieved more rapidly when primary care is delivered appropriately. JEL I18, H51 PMID:23433501

[Analysis the epidemiological features of 3,258 patients with allergic rhinitis in Yichang City].

PubMed

Chen, Bo; Zhang, Zhimao; Pei, Zhi; Chen, Shihan; Du, Zhimei; Lan, Yan; Han, Bei; Qi, Qi

2015-02-01

To investigate the epidemiological features in patients with allergic rhinitis (AR) in Yichang city, and put forward effective prevention and control measures. Collecting the data of allergic rhinitis in city proper from 2010 to 2013, input the data into the database and used statistical analysis. In recent years, the AR patients in this area increased year by year. The spring and the winter were the peak season of onset. The patients was constituted by young men. There was statistically significant difference between the age, the area,and the gender (P < 0.01). The history of allergy and the diseases related to the gender composition had statistical significance difference (P < 0.05). The allergens and the positive degree in gender, age structure had statistically significant difference (P < 0.01). Need to conduct the healthy propaganda and education, optimizing the environment, change the bad habits, timely medical treatment, standard treatment.

Ages of the Bulge Globular Clusters NGC 6522 and NGC 6626 (M28) from HST Proper-motion-cleaned Color–Magnitude Diagrams

NASA Astrophysics Data System (ADS)

Kerber, L. O.; Nardiello, D.; Ortolani, S.; Barbuy, B.; Bica, E.; Cassisi, S.; Libralato, M.; Vieira, R. G.

2018-01-01

Bulge globular clusters (GCs) with metallicities [Fe/H] ≲ ‑1.0 and blue horizontal branches are candidates to harbor the oldest populations in the Galaxy. Based on the analysis of HST proper-motion-cleaned color–magnitude diagrams in filters F435W and F625W, we determine physical parameters for the old bulge GCs NGC 6522 and NGC 6626 (M28), both with well-defined blue horizontal branches. We compare these results with similar data for the inner halo cluster NGC 6362. These clusters have similar metallicities (‑1.3 ≤ [Fe/H] ≤ ‑1.0) obtained from high-resolution spectroscopy. We derive ages, distance moduli, and reddening values by means of statistical comparisons between observed and synthetic fiducial lines employing likelihood statistics and the Markov chain Monte Carlo method. The synthetic fiducial lines were generated using α-enhanced BaSTI and Dartmouth stellar evolutionary models, adopting both canonical (Y ∼ 0.25) and enhanced (Y ∼ 0.30–0.33) helium abundances. RR Lyrae stars were employed to determine the HB magnitude level, providing an independent indicator to constrain the apparent distance modulus and the helium enhancement. The shape of the observed fiducial line could be compatible with some helium enhancement for NGC 6522 and NGC 6626, but the average magnitudes of RR Lyrae stars tend to rule out this hypothesis. Assuming canonical helium abundances, BaSTI and Dartmouth models indicate that all three clusters are coeval, with ages between ∼12.5 and 13.0 Gyr. The present study also reveals that NGC 6522 has at least two stellar populations, since its CMD shows a significantly wide subgiant branch compatible with 14% ± 2% and 86% ± 5% for first and second generations, respectively. Based on observations with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute.

Strategies for Reduced-Order Models in Uncertainty Quantification of Complex Turbulent Dynamical Systems

NASA Astrophysics Data System (ADS)

Qi, Di

Turbulent dynamical systems are ubiquitous in science and engineering. Uncertainty quantification (UQ) in turbulent dynamical systems is a grand challenge where the goal is to obtain statistical estimates for key physical quantities. In the development of a proper UQ scheme for systems characterized by both a high-dimensional phase space and a large number of instabilities, significant model errors compared with the true natural signal are always unavoidable due to both the imperfect understanding of the underlying physical processes and the limited computational resources available. One central issue in contemporary research is the development of a systematic methodology for reduced order models that can recover the crucial features both with model fidelity in statistical equilibrium and with model sensitivity in response to perturbations. In the first part, we discuss a general mathematical framework to construct statistically accurate reduced-order models that have skill in capturing the statistical variability in the principal directions of a general class of complex systems with quadratic nonlinearity. A systematic hierarchy of simple statistical closure schemes, which are built through new global statistical energy conservation principles combined with statistical equilibrium fidelity, are designed and tested for UQ of these problems. Second, the capacity of imperfect low-order stochastic approximations to model extreme events in a passive scalar field advected by turbulent flows is investigated. The effects in complicated flow systems are considered including strong nonlinear and non-Gaussian interactions, and much simpler and cheaper imperfect models with model error are constructed to capture the crucial statistical features in the stationary tracer field. Several mathematical ideas are introduced to improve the prediction skill of the imperfect reduced-order models. Most importantly, empirical information theory and statistical linear response theory are applied in the training phase for calibrating model errors to achieve optimal imperfect model parameters; and total statistical energy dynamics are introduced to improve the model sensitivity in the prediction phase especially when strong external perturbations are exerted. The validity of reduced-order models for predicting statistical responses and intermittency is demonstrated on a series of instructive models with increasing complexity, including the stochastic triad model, the Lorenz '96 model, and models for barotropic and baroclinic turbulence. The skillful low-order modeling methods developed here should also be useful for other applications such as efficient algorithms for data assimilation.

Statistical Analysis for the Solomon Four-Group Design. Research Report 99-06.

ERIC Educational Resources Information Center

van Engelenburg, Gijsbert

The Solomon four-group design (R. Solomon, 1949) is a very useful experimental design to investigate the main effect of a pretest and the interaction of pretest and treatment. Although the design was proposed half a century ago, no proper data analysis techniques have been available. This paper describes how data from the Solomon four-group design…

Validity of the SAT® for Predicting First-Year Grades: 2011 SAT Validity Sample. Statistical Report 2013-3

ERIC Educational Resources Information Center

Patterson, Brian F.; Mattern, Krista D.

2013-01-01

The continued accumulation of validity evidence for the intended uses of educational assessments is critical to ensure that proper inferences will be made for those purposes. To that end, the College Board has continued to collect college outcome data to evaluate the relationship between SAT® scores and college success. This report provides…

Transitioning Florida NPs to opioid prescribing.

PubMed

Craig-Rodriguez, Alicia; Gordon, Glenna; Kaplan, Louise; Grubbs, Laurie

2017-09-21

Prior to statutory changes in prescriptive authority for controlled substances, this study examined the knowledge gaps and prescribing limitations of Florida advanced registered nurse practitioners regarding opioids. Study results revealed statistically significant knowledge gaps in the areas of federal and state guidelines; opioid classes and proper doses; risk assessment skills; monitoring of treatment; and confidence in dealing with challenges of opioid prescribing.

Contraceptive use and preferences of young married women in Kerala, India.

PubMed

Thulaseedharan, Jissa Vinoda

2018-01-01

As in other states of India, female sterilization is the most widely used contraceptive method in Kerala where women have higher levels of education compared to most other states in India. This paper describes the use and preferences of contraceptive methods among young married women in Trivandrum district, Kerala, India. A community-based cross-sectional survey was carried out among 203 young married women (18-28 years) during January-March 2015 using multistage cluster sampling method. Statistical analysis was mainly descriptive, and chi-squared test was used to test the statistical significance of the relationship between sociodemographic factors and contraceptive use. The average age at marriage for women was 21.3 years, and 23% of women had more than one child. Current use of any contraceptive methods was 58%. Female sterilization was preferred by 13% and it was significantly higher among women aged 25-28 years than in those aged 18-24 years (20% vs 2.6%, p <0.001). Female sterilization was significantly lower among women with higher levels of education than in women with an education level of plus two or below (5.8% vs 19%, p =0.006). Women were mostly in favor of female sterilization (91%), and a significantly lower proportion of highly educated women preferred female sterilization than women with an education of 12 years or below (85% vs 95.7%, p =0.008). A considerable number of females in the age group 25-28-years opting for sterilization and the unique preference for female sterilization when the family size is complete show the predominant reliance on female sterilization among young women. Higher education delays sterilization in young women due to delayed marriage and childbirth. Women empowerment, proper information and assuring availability and accessibility to different methods can gradually change the dominant preference for female-oriented permanent method of contraception.

Cross Contamination: Are Hospital Gloves Reservoirs for Nosocomial Infections?

PubMed

Moran, Vicki; Heuertz, Rita

2017-01-01

Use of disposable nonsterile gloves in the hospital setting is second only to proper hand washing in reducing contamination during patient contact. Because proper handwashing is not consistently practiced, added emphasis on glove use is warranted. There is a growing body of evidence that glove boxes and dispensers available to healthcare workers are contaminated by daily exposure to environmental organisms. This finding, in conjunction with new and emerging antibiotic-resistant bacteria, poses a threat to patients and healthcare workers alike. A newly designed glove dispenser may reduce contamination of disposable gloves. The authors investigated contamination of nonsterile examination gloves in an Emergency Department setting according to the type of dispenser used to access gloves. A statistically significant difference existed between the number of bacterial colonies and the type of dispenser: the downward-facing glove dispenser had a lower number of bacteria on the gloves. There was no statistically significant difference in the number of gloves contaminated between the two types of glove dispensers. The study demonstrated that contamination of disposable gloves existed. Additional research using a larger sample size would validate a difference in the contamination of disposable gloves using outward or downward glove dispensers.

Removing an intersubject variance component in a general linear model improves multiway factoring of event-related spectral perturbations in group EEG studies.

PubMed

Spence, Jeffrey S; Brier, Matthew R; Hart, John; Ferree, Thomas C

2013-03-01

Linear statistical models are used very effectively to assess task-related differences in EEG power spectral analyses. Mixed models, in particular, accommodate more than one variance component in a multisubject study, where many trials of each condition of interest are measured on each subject. Generally, intra- and intersubject variances are both important to determine correct standard errors for inference on functions of model parameters, but it is often assumed that intersubject variance is the most important consideration in a group study. In this article, we show that, under common assumptions, estimates of some functions of model parameters, including estimates of task-related differences, are properly tested relative to the intrasubject variance component only. A substantial gain in statistical power can arise from the proper separation of variance components when there is more than one source of variability. We first develop this result analytically, then show how it benefits a multiway factoring of spectral, spatial, and temporal components from EEG data acquired in a group of healthy subjects performing a well-studied response inhibition task. Copyright © 2011 Wiley Periodicals, Inc.

Does RAIM with Correct Exclusion Produce Unbiased Positions?

PubMed Central

Teunissen, Peter J. G.; Imparato, Davide; Tiberius, Christian C. J. M.

2017-01-01

As the navigation solution of exclusion-based RAIM follows from a combination of least-squares estimation and a statistically based exclusion-process, the computation of the integrity of the navigation solution has to take the propagated uncertainty of the combined estimation-testing procedure into account. In this contribution, we analyse, theoretically as well as empirically, the effect that this combination has on the first statistical moment, i.e., the mean, of the computed navigation solution. It will be shown, although statistical testing is intended to remove biases from the data, that biases will always remain under the alternative hypothesis, even when the correct alternative hypothesis is properly identified. The a posteriori exclusion of a biased satellite range from the position solution will therefore never remove the bias in the position solution completely. PMID:28672862

[Statistical validity of the Mexican Food Security Scale and the Latin American and Caribbean Food Security Scale].

PubMed

Villagómez-Ornelas, Paloma; Hernández-López, Pedro; Carrasco-Enríquez, Brenda; Barrios-Sánchez, Karina; Pérez-Escamilla, Rafael; Melgar-Quiñónez, Hugo

2014-01-01

This article validates the statistical consistency of two food security scales: the Mexican Food Security Scale (EMSA) and the Latin American and Caribbean Food Security Scale (ELCSA). Validity tests were conducted in order to verify that both scales were consistent instruments, conformed by independent, properly calibrated and adequately sorted items, arranged in a continuum of severity. The following tests were developed: sorting of items; Cronbach's alpha analysis; parallelism of prevalence curves; Rasch models; sensitivity analysis through mean differences' hypothesis test. The tests showed that both scales meet the required attributes and are robust statistical instruments for food security measurement. This is relevant given that the lack of access to food indicator, included in multidimensional poverty measurement in Mexico, is calculated with EMSA.

Truncated Linear Statistics Associated with the Eigenvalues of Random Matrices II. Partial Sums over Proper Time Delays for Chaotic Quantum Dots

NASA Astrophysics Data System (ADS)

Grabsch, Aurélien; Majumdar, Satya N.; Texier, Christophe

2017-06-01

Invariant ensembles of random matrices are characterized by the distribution of their eigenvalues \\{λ _1,\\ldots ,λ _N\\}. We study the distribution of truncated linear statistics of the form \\tilde{L}=\\sum _{i=1}^p f(λ _i) with p

Photoacoustic discrimination of vascular and pigmented lesions using classical and Bayesian methods

NASA Astrophysics Data System (ADS)

Swearingen, Jennifer A.; Holan, Scott H.; Feldman, Mary M.; Viator, John A.

2010-01-01

Discrimination of pigmented and vascular lesions in skin can be difficult due to factors such as size, subungual location, and the nature of lesions containing both melanin and vascularity. Misdiagnosis may lead to precancerous or cancerous lesions not receiving proper medical care. To aid in the rapid and accurate diagnosis of such pathologies, we develop a photoacoustic system to determine the nature of skin lesions in vivo. By irradiating skin with two laser wavelengths, 422 and 530 nm, we induce photoacoustic responses, and the relative response at these two wavelengths indicates whether the lesion is pigmented or vascular. This response is due to the distinct absorption spectrum of melanin and hemoglobin. In particular, pigmented lesions have ratios of photoacoustic amplitudes of approximately 1.4 to 1 at the two wavelengths, while vascular lesions have ratios of about 4.0 to 1. Furthermore, we consider two statistical methods for conducting classification of lesions: standard multivariate analysis classification techniques and a Bayesian-model-based approach. We study 15 human subjects with eight vascular and seven pigmented lesions. Using the classical method, we achieve a perfect classification rate, while the Bayesian approach has an error rate of 20%.

Can we improve C IV-based single epoch black hole mass estimations?

NASA Astrophysics Data System (ADS)

Mejía-Restrepo, J. E.; Trakhtenbrot, B.; Lira, P.; Netzer, H.

2018-05-01

In large optical surveys at high redshifts (z > 2), the C IV broad emission line is the most practical alternative to estimate the mass (MBH) of active super-massive black holes (SMBHs). However, mass determinations obtained with this line are known to be highly uncertain. In this work we use the Sloan Digital Sky Survey Data Release 7 and 12 quasar catalogues to statistically test three alternative methods put forward in the literature to improve C IV-based MBH estimations. These methods are constructed from correlations between the ratio of the C IV line-width to the low ionization line-widths (Hα, Hβ and Mg II) and several other properties of rest-frame UV emission lines. Our analysis suggests that these correction methods are of limited applicability, mostly because all of them depend on correlations that are driven by the linewidth of the C IV profile itself and not by an interconnection between the linewidth of the C IV line with the linewidth of the low ionization lines. Our results show that optical C IV-based mass estimates at high redshift cannot be a proper replacement for estimates based on IR spectroscopy of low ionization lines like Hα, Hβ and Mg II.

Efficient numerical methods for the random-field Ising model: Finite-size scaling, reweighting extrapolation, and computation of response functions.

PubMed

Fytas, Nikolaos G; Martín-Mayor, Víctor

2016-06-01

It was recently shown [Phys. Rev. Lett. 110, 227201 (2013)PRLTAO0031-900710.1103/PhysRevLett.110.227201] that the critical behavior of the random-field Ising model in three dimensions is ruled by a single universality class. This conclusion was reached only after a proper taming of the large scaling corrections of the model by applying a combined approach of various techniques, coming from the zero- and positive-temperature toolboxes of statistical physics. In the present contribution we provide a detailed description of this combined scheme, explaining in detail the zero-temperature numerical scheme and developing the generalized fluctuation-dissipation formula that allowed us to compute connected and disconnected correlation functions of the model. We discuss the error evolution of our method and we illustrate the infinite limit-size extrapolation of several observables within phenomenological renormalization. We present an extension of the quotients method that allows us to obtain estimates of the critical exponent α of the specific heat of the model via the scaling of the bond energy and we discuss the self-averaging properties of the system and the algorithmic aspects of the maximum-flow algorithm used.

Quantification of intensity variations in functional MR images using rotated principal components

NASA Astrophysics Data System (ADS)

Backfrieder, W.; Baumgartner, R.; Sámal, M.; Moser, E.; Bergmann, H.

1996-08-01

In functional MRI (fMRI), the changes in cerebral haemodynamics related to stimulated neural brain activity are measured using standard clinical MR equipment. Small intensity variations in fMRI data have to be detected and distinguished from non-neural effects by careful image analysis. Based on multivariate statistics we describe an algorithm involving oblique rotation of the most significant principal components for an estimation of the temporal and spatial distribution of the stimulated neural activity over the whole image matrix. This algorithm takes advantage of strong local signal variations. A mathematical phantom was designed to generate simulated data for the evaluation of the method. In simulation experiments, the potential of the method to quantify small intensity changes, especially when processing data sets containing multiple sources of signal variations, was demonstrated. In vivo fMRI data collected in both visual and motor stimulation experiments were analysed, showing a proper location of the activated cortical regions within well known neural centres and an accurate extraction of the activation time profile. The suggested method yields accurate absolute quantification of in vivo brain activity without the need of extensive prior knowledge and user interaction.

Development of a New Methodology for Computing Surface Sensible Heat Fluxes using Thermal Imagery

NASA Astrophysics Data System (ADS)

Morrison, T. J.; Calaf, M.; Fernando, H. J.; Price, T. A.; Pardyjak, E.

2017-12-01

Current numerical weather predication models utilize similarity to characterize momentum, moisture, and heat fluxes. Such formulations are only valid under the ideal assumptions of spatial homogeneity, statistical stationary, and zero subsidence. However, recent surface temperature measurements from the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) Program on the Salt Flats of Utah's West desert, show that even under the most a priori ideal conditions, heterogeneity of the aforementioned variables exists. We present a new method to extract spatially-distributed measurements of surface sensible heat flux from thermal imagery. The approach consists of using a surface energy budget, where the ground heat flux is easily computed from limited measurements using a force-restore-type methodology, the latent heat fluxes are neglected, and the energy storage is computed using a lumped capacitance model. Preliminary validation of the method is presented using experimental data acquired from a nearby sonic anemometer during the MATERHORN campaign. Additional evaluation is required to confirm the method's validity. Further decomposition analysis of on-site instrumentation (thermal camera, cold-hotwire probes, and sonic anemometers) using Proper Orthogonal Decomposition (POD), and wavelet analysis, reveals time scale similarity between the flow and surface fluctuations.

Methods for meta-analysis of multiple traits using GWAS summary statistics.

PubMed

Ray, Debashree; Boehnke, Michael

2018-03-01

Genome-wide association studies (GWAS) for complex diseases have focused primarily on single-trait analyses for disease status and disease-related quantitative traits. For example, GWAS on risk factors for coronary artery disease analyze genetic associations of plasma lipids such as total cholesterol, LDL-cholesterol, HDL-cholesterol, and triglycerides (TGs) separately. However, traits are often correlated and a joint analysis may yield increased statistical power for association over multiple univariate analyses. Recently several multivariate methods have been proposed that require individual-level data. Here, we develop metaUSAT (where USAT is unified score-based association test), a novel unified association test of a single genetic variant with multiple traits that uses only summary statistics from existing GWAS. Although the existing methods either perform well when most correlated traits are affected by the genetic variant in the same direction or are powerful when only a few of the correlated traits are associated, metaUSAT is designed to be robust to the association structure of correlated traits. metaUSAT does not require individual-level data and can test genetic associations of categorical and/or continuous traits. One can also use metaUSAT to analyze a single trait over multiple studies, appropriately accounting for overlapping samples, if any. metaUSAT provides an approximate asymptotic P-value for association and is computationally efficient for implementation at a genome-wide level. Simulation experiments show that metaUSAT maintains proper type-I error at low error levels. It has similar and sometimes greater power to detect association across a wide array of scenarios compared to existing methods, which are usually powerful for some specific association scenarios only. When applied to plasma lipids summary data from the METSIM and the T2D-GENES studies, metaUSAT detected genome-wide significant loci beyond the ones identified by univariate analyses. Evidence from larger studies suggest that the variants additionally detected by our test are, indeed, associated with lipid levels in humans. In summary, metaUSAT can provide novel insights into the genetic architecture of a common disease or traits. © 2017 WILEY PERIODICALS, INC.

Success Rate of Microimplants in a University Orthodontic Clinic

PubMed Central

Sharma, P.; Valiathan, A.; Sivakumar, A.

2011-01-01

Introduction. The purpose of this study was to examine the success rate and find factors affecting the clinical success of microimplants used as orthodontic anchorage. Methods. Seventy-three consecutive patients (25 male, 48 female; mean age, 22.45 years) with a total of 139 screw implants of 2 types were examined. Success rate was determined according to 18 clinical variables. Results. The overall success rate was 87.8%. The clinical variables of microimplant factors (type), patient factors (sex, skeletal and dental relationships, overbite, jaw involved, side involved and site involved), and treatment factors (type of insertion, time of loading, purpose of microimplant insertion, mode of loading, type of anchorage used, direction of forces applied) did not show any statistical difference in success rates. Mandibular angle, vertical position of implant placement, oral hygiene status, and inflammation showed significant difference in success rates. Conclusions. Proper case selection and following the recommended protocol are extremely essential to minimise failures. PMID:22084789

Study on the impulsive pressure of tank oscillating by force towards multiple degrees of freedom

NASA Astrophysics Data System (ADS)

Hibi, Shigeyuki

2018-06-01

Impulsive loads should be excited under nonlinear phenomena with free surface fluctuating severely such as sloshing and slamming. Estimating impulsive loads properly are important to recent numerical simulations. But it is still difficult to rely on the results of simulations perfectly because of the nonlinearity of the phenomena. In order to develop the algorithm of numerical simulations experimental results of nonlinear phenomena are needed. In this study an apparatus which can oscillate a tank by force was introduced in order to investigate impulsive pressure on the wall of the tank. This apparatus can oscillate it simultaneously towards 3 degrees of freedom with each phase differences. The impulsive pressure under the various combinations of oscillation direction was examined and the specific phase differences to appear the largest peak values of pressure were identified. Experimental results were verified through FFT analysis and statistical methods.

Determination of the Proper Rest Time for a Cyclic Mental Task Using ACT-R Architecture.

PubMed

Atashfeshan, Nooshin; Razavi, Hamideh

2017-03-01

Objective Analysis of the effect of mental fatigue on a cognitive task and determination of the right start time for rest breaks in work environments. Background Mental fatigue has been recognized as one of the most important factors influencing individual performance. Subjective and physiological measures are popular methods for analyzing fatigue, but they are restricted to physical experiments. Computational cognitive models are useful for predicting operator performance and can be used for analyzing fatigue in the design phase, particularly in industrial operations and inspections where cognitive tasks are frequent and the effects of mental fatigue are crucial. Method A cyclic mental task is modeled by the ACT-R architecture, and the effect of mental fatigue on response time and error rate is studied. The task includes visual inspections in a production line or control workstation where an operator has to check products' conformity to specifications. Initially, simulated and experimental results are compared using correlation coefficients and paired t test statistics. After validation of the model, the effects are studied by human and simulated results, which are obtained by running 50-minute tests. Results It is revealed that during the last 20 minutes of the tests, the response time increased by 20%, and during the last 12.5 minutes, the error rate increased by 7% on average. Conclusion The proper start time for the rest period can be identified by setting a limit on the error rate or response time. Application The proposed model can be applied early in production planning to decrease the negative effects of mental fatigue by predicting the operator performance. It can also be used for determining the rest breaks in the design phase without an operator in the loop.

Analysis of the seismicity preceding large earthquakes

NASA Astrophysics Data System (ADS)

Stallone, Angela; Marzocchi, Warner

2017-04-01

The most common earthquake forecasting models assume that the magnitude of the next earthquake is independent from the past. This feature is probably one of the most severe limitations of the capability to forecast large earthquakes. In this work, we investigate empirically on this specific aspect, exploring whether variations in seismicity in the space-time-magnitude domain encode some information on the size of the future earthquakes. For this purpose, and to verify the stability of the findings, we consider seismic catalogs covering quite different space-time-magnitude windows, such as the Alto Tiberina Near Fault Observatory (TABOO) catalogue, the California and Japanese seismic catalog. Our method is inspired by the statistical methodology proposed by Baiesi & Paczuski (2004) and elaborated by Zaliapin et al. (2008) to distinguish between triggered and background earthquakes, based on a pairwise nearest-neighbor metric defined by properly rescaled temporal and spatial distances. We generalize the method to a metric based on the k-nearest-neighbors that allows us to consider the overall space-time-magnitude distribution of k-earthquakes, which are the strongly correlated ancestors of a target event. Finally, we analyze the statistical properties of the clusters composed by the target event and its k-nearest-neighbors. In essence, the main goal of this study is to verify if different classes of target event magnitudes are characterized by distinctive "k-foreshocks" distributions. The final step is to show how the findings of this work may (or not) improve the skill of existing earthquake forecasting models.

Does quality of drinking water matter in kidney stone disease: A study in West Bengal, India

PubMed Central

Mitra, Pubali; Pal, Dilip Kumar

2018-01-01

Purpose The combined interaction of epidemiology, environmental exposure, dietary habits, and genetic factors causes kidney stone disease (KSD), a common public health problem worldwide. Because a high water intake (>3 L daily) is widely recommended by physicians to prevent KSD, the present study evaluated whether the quantity of water that people consume daily is associated with KSD and whether the quality of drinking water has any effect on disease prevalence. Materials and Methods Information regarding residential address, daily volume of water consumption, and source of drinking water was collected from 1,266 patients with kidney stones in West Bengal, India. Drinking water was collected by use of proper methods from case (high stone prevalence) and control (zero stone prevalence) areas thrice yearly. Water samples were analyzed for pH, alkalinity, hardness, total dissolved solutes, electrical conductivity, and salinity. Average values of the studied parameters were compared to determine if there were any statistically significant differences between the case and control areas. Results We observed that as many as 53.6% of the patients consumed <3 L of water daily. Analysis of drinking water samples from case and control areas, however, did not show any statistically significant alterations in the studied parameters. All water samples were found to be suitable for consumption. Conclusions It is not the quality of water, rather the quantity of water consumed that matters most in the occurrence of KSD. PMID:29744472

Application of Multi-Hypothesis Sequential Monte Carlo for Breakup Analysis

NASA Astrophysics Data System (ADS)

Faber, W. R.; Zaidi, W.; Hussein, I. I.; Roscoe, C. W. T.; Wilkins, M. P.; Schumacher, P. W., Jr.

As more objects are launched into space, the potential for breakup events and space object collisions is ever increasing. These events create large clouds of debris that are extremely hazardous to space operations. Providing timely, accurate, and statistically meaningful Space Situational Awareness (SSA) data is crucial in order to protect assets and operations in space. The space object tracking problem, in general, is nonlinear in both state dynamics and observations, making it ill-suited to linear filtering techniques such as the Kalman filter. Additionally, given the multi-object, multi-scenario nature of the problem, space situational awareness requires multi-hypothesis tracking and management that is combinatorially challenging in nature. In practice, it is often seen that assumptions of underlying linearity and/or Gaussianity are used to provide tractable solutions to the multiple space object tracking problem. However, these assumptions are, at times, detrimental to tracking data and provide statistically inconsistent solutions. This paper details a tractable solution to the multiple space object tracking problem applicable to space object breakup events. Within this solution, simplifying assumptions of the underlying probability density function are relaxed and heuristic methods for hypothesis management are avoided. This is done by implementing Sequential Monte Carlo (SMC) methods for both nonlinear filtering as well as hypothesis management. This goal of this paper is to detail the solution and use it as a platform to discuss computational limitations that hinder proper analysis of large breakup events.

Spatial variation of statistical properties of extreme water levels along the eastern Baltic Sea

NASA Astrophysics Data System (ADS)

Pindsoo, Katri; Soomere, Tarmo; Rocha, Eugénio

2016-04-01

Most of existing projections of future extreme water levels rely on the use of classic generalised extreme value distributions. The choice to use a particular distribution is often made based on the absolute value of the shape parameter of the Generalise Extreme Value distribution. If this parameter is small, the Gumbel distribution is most appropriate while in the opposite case the Weibull or Frechet distribution could be used. We demonstrate that the alongshore variation in the statistical properties of numerically simulated high water levels along the eastern coast of the Baltic Sea is so large that the use of a single distribution for projections of extreme water levels is highly questionable. The analysis is based on two simulated data sets produced in the Swedish Meteorological and Hydrological Institute. The output of the Rossby Centre Ocean model is sampled with a resolution of 6 h and the output of the circulation model NEMO with a resolution of 1 h. As the maxima of water levels of subsequent years may be correlated in the Baltic Sea, we also employ maxima for stormy seasons. We provide a detailed analysis of spatial variation of the parameters of the family of extreme value distributions along an approximately 600 km long coastal section from the north-western shore of Latvia in the Baltic Proper until the eastern Gulf of Finland. The parameters are evaluated using maximum likelihood method and method of moments. The analysis also covers the entire Gulf of Riga. The core parameter of this family of distributions, the shape parameter of the Generalised Extreme Value distribution, exhibits extensive variation in the study area. Its values evaluated using the Hydrognomon software and maximum likelihood method, vary from about -0.1 near the north-western coast of Latvia in the Baltic Proper up to about 0.05 in the eastern Gulf of Finland. This parameter is very close to zero near Tallinn in the western Gulf of Finland. Thus, it is natural that the Gumbel distribution gives adequate projections of extreme water levels for the vicinity of Tallinn. More importantly, this feature indicates that the use of a single distribution for the projections of extreme water levels and their return periods for the entire Baltic Sea coast is inappropriate. The physical reason is the interplay of the complex shape of large subbasins (such as the Gulf of Riga and Gulf of Finland) of the sea and highly anisotropic wind regime. The 'impact' of this anisotropy on the statistics of water level is amplified by the overall anisotropy of the distributions of the frequency of occurrence of high and low water levels. The most important conjecture is that long-term behaviour of water level extremes in different coastal sections of the Baltic Sea may be fundamentally different.

Strain gage installation and survivability on geosynthetics used in flexible pavements

NASA Astrophysics Data System (ADS)

Brooks, Jeremy A.

The use of foil type strain gages on geosynthetics is poorly documented. In addition, very few individuals are versed in proper installation techniques or calibration methods. Due to the limited number of knowledgeable technicians there is no information regarding the susceptibility of theses gages to errors in installation by inexperienced installers. Also lacking in the documentation related to the use of foil type strain gages on geosynthetics is the survivability of the gages in field conditions. This research documented procedures for installation, calibration, and survivability used by the project team to instruments a full scale field installation in Marked Tree, AR. This research also addressed sensitivity to installation errors on both geotextile and geogrid. To document the process of gage installation an experienced technician, Mr. Joe Ables, formerly of the UASCE Waterways Experiment Station, was consulted. His techniques were combined with those discovered in related literature and those developed by the research team to develop processes that were adaptable to multiple gage geometries and parent geosynthetics. These processes were described and documented in a step by step manner with accompanying photographs, which should allow virtually anyone with basic electronics knowledge to install these gages properly. Calibration of the various geosynthetic / strain gage combinations was completed using wide width tensile testing on multiple samples of each material. The tensile testing process was documented and analyzed using digital photography to analyze strain on the strain gage itself. Calibration factors for each geosynthtics used in the full scale field testing were developed. In addition, the process was thoroughly documented to allow future researchers to calibrate additional strain gage and geosynthetic combinations. The sensitivity of the strain gages to installation errors was analyzed using wide width tensile testing and digital photography to determine the variability of the data collected from gages with noticeable installation errors as compared to properly installed gages. Induced errors varied based on the parent geosynthetics material, but included excessive and minimal waterproofing, gage rotation, gage shift, excessive and minimal adhesive, and excessive and minimal adhesive impregnation loads. The results of this work indicated that minor errors in geotextile gage installation that are noticeable and preventable by the experienced installer have no statistical significance on the data recorded during the life span of geotextile gages; however the lifespan of the gage may be noticeably shortened by such errors. Geogrid gage installation errors were found to cause statistically significant changes in the data recorded from improper installations. The issue of gage survivability was analyzed using small scale test sections instrumented and loaded similarly to field conditions anticipated during traditional roadway construction. Five methods of protection were tested for both geotextile and geogrid including a sand blanket, inversion, semi-hemispherical PCV sections, neoprene mats, and geosynthetic wick drain. Based on this testing neoprene mats were selected to protect geotextile installed gages, and wick drains were selected to protect geogrid installed gages. These methods resulted in survivability rates of 73% and 100% in the full scale installation respectively. This research and documentation may be used to train technicians to install and calibrate geosynthetic mounted foil type strain gages. In addition, technicians should be able to install gages in the field with a high probability of gage survivability using the protection methods recommended.

The Baldwin-Lomax model for separated and wake flows using the entropy envelope concept

NASA Technical Reports Server (NTRS)

Brock, J. S.; Ng, W. F.

1992-01-01

Implementation of the Baldwin-Lomax algebraic turbulence model is difficult and ambiguous within flows characterized by strong viscous-inviscid interactions and flow separations. A new method of implementation is proposed which uses an entropy envelope concept and is demonstrated to ensure the proper evaluation of modeling parameters. The method is simple, computationally fast, and applicable to both wake and boundary layer flows. The method is general, making it applicable to any turbulence model which requires the automated determination of the proper maxima of a vorticity-based function. The new method is evalulated within two test cases involving strong viscous-inviscid interaction.

Profiling USGA putting greens using GPR - an as-built surveying method

USDA-ARS?s Scientific Manuscript database

Golf course greens that are constructed to U.S. Golf Association (USGA) standards must adhere to strict installation specifications in order to maintain proper subsurface drainage. Because the infrastructure is buried, it can be difficult to ascertain if these drainage pipes were properly installed...

Basics of Biosafety

NASA Technical Reports Server (NTRS)

Wong, Willy

2009-01-01

This slide presentation reviews the basics of biosafety and the importance of assuring proper biosafety practices. The objectives of the presentation are to review regulations about biosafety, and the different biosafety levels; the biosafety facilities at Johnson Space Center; the usage and maintenance of the biosafety cabinet, the proper methods to handle biologically hazardous materials upon exposure, and the methods of cleanup in the event of a spill, and the training requirements that are mandated for personnel handling biologically hazardous materials.

Methods for detection of haemophilia carriers: a Memorandum*

PubMed Central

1977-01-01

This Memorandum discusses the problems and techniques involved in the detection of carriers of haemophilia A (blood coagulation factor VIII deficiency) and haemophilia B (factor IX deficiency), particularly with a view to its application to genetic counselling. Apart from the personal suffering caused by haemophilia, the proper treatment of haemophiliacs places a great strain on the blood transfusion services, and it is therefore important that potential carriers should have precise information about the consequences of their having children. The Memorandum classifies the types of carrier and describes the laboratory methods used for the assessment of coagulant activity and antigen concentration in blood. Particular emphasis is laid on the establishment of international, national, and laboratory (working) standards for factors VIII and IX and their calibration in international units (IU). This is followed by a detailed account of the statistical analysis of pedigree and laboratory data, which leads to an assessment of the likelihood that a particular person will transmit the haemophilia gene to her children. Finally, the problems and responsibilities involved in genetic counselling are considered. PMID:304395

Removal of batch effects using distribution-matching residual networks.

PubMed

Shaham, Uri; Stanton, Kelly P; Zhao, Jun; Li, Huamin; Raddassi, Khadir; Montgomery, Ruth; Kluger, Yuval

2017-08-15

Sources of variability in experimentally derived data include measurement error in addition to the physical phenomena of interest. This measurement error is a combination of systematic components, originating from the measuring instrument and random measurement errors. Several novel biological technologies, such as mass cytometry and single-cell RNA-seq (scRNA-seq), are plagued with systematic errors that may severely affect statistical analysis if the data are not properly calibrated. We propose a novel deep learning approach for removing systematic batch effects. Our method is based on a residual neural network, trained to minimize the Maximum Mean Discrepancy between the multivariate distributions of two replicates, measured in different batches. We apply our method to mass cytometry and scRNA-seq datasets, and demonstrate that it effectively attenuates batch effects. our codes and data are publicly available at https://github.com/ushaham/BatchEffectRemoval.git. yuval.kluger@yale.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Quantifying the predictive accuracy of time-to-event models in the presence of competing risks.

PubMed

Schoop, Rotraut; Beyersmann, Jan; Schumacher, Martin; Binder, Harald

2011-02-01

Prognostic models for time-to-event data play a prominent role in therapy assignment, risk stratification and inter-hospital quality assurance. The assessment of their prognostic value is vital not only for responsible resource allocation, but also for their widespread acceptance. The additional presence of competing risks to the event of interest requires proper handling not only on the model building side, but also during assessment. Research into methods for the evaluation of the prognostic potential of models accounting for competing risks is still needed, as most proposed methods measure either their discrimination or calibration, but do not examine both simultaneously. We adapt the prediction error proposal of Graf et al. (Statistics in Medicine 1999, 18, 2529–2545) and Gerds and Schumacher (Biometrical Journal 2006, 48, 1029–1040) to handle models with competing risks, i.e. more than one possible event type, and introduce a consistent estimator. A simulation study investigating the behaviour of the estimator in small sample size situations and for different levels of censoring together with a real data application follows.

Technical note: Combining quantile forecasts and predictive distributions of streamflows

NASA Astrophysics Data System (ADS)

Bogner, Konrad; Liechti, Katharina; Zappa, Massimiliano

2017-11-01

The enhanced availability of many different hydro-meteorological modelling and forecasting systems raises the issue of how to optimally combine this great deal of information. Especially the usage of deterministic and probabilistic forecasts with sometimes widely divergent predicted future streamflow values makes it even more complicated for decision makers to sift out the relevant information. In this study multiple streamflow forecast information will be aggregated based on several different predictive distributions, and quantile forecasts. For this combination the Bayesian model averaging (BMA) approach, the non-homogeneous Gaussian regression (NGR), also known as the ensemble model output statistic (EMOS) techniques, and a novel method called Beta-transformed linear pooling (BLP) will be applied. By the help of the quantile score (QS) and the continuous ranked probability score (CRPS), the combination results for the Sihl River in Switzerland with about 5 years of forecast data will be compared and the differences between the raw and optimally combined forecasts will be highlighted. The results demonstrate the importance of applying proper forecast combination methods for decision makers in the field of flood and water resource management.

Outcome-based self-assessment on a team-teaching subject in the medical school

PubMed Central

Cho, Sa Sun

2014-01-01

We attempted to investigate the reason why the students got a worse grade in gross anatomy and the way how we can improve upon the teaching method since there were gaps between teaching and learning under recently changed integration curriculum. General characteristics of students and exploratory factors to testify the validity were compared between year 2011 and 2012. Students were asked to complete a short survey with a Likert scale. The results were as follows: although the percentage of acceptable items was similar between professors, professor C preferred questions with adequate item discrimination and inappropriate item difficulty whereas professor Y preferred adequate item discrimination and appropriate item difficulty with statistical significance (P<0.01). The survey revealed that 26.5% of total students gave up the exam on gross anatomy of professor Y irrespective of years. These results suggested that students were affected by the corrected item difficulty rather than item discrimination in order to obtain academic achievement. Therefore, professors in a team-teaching subject should reach a consensus on an item difficulty with proper teaching methods. PMID:25548724

The role of different sampling methods in improving biological activity prediction using deep belief network.

PubMed

Ghasemi, Fahimeh; Fassihi, Afshin; Pérez-Sánchez, Horacio; Mehri Dehnavi, Alireza

2017-02-05

Thousands of molecules and descriptors are available for a medicinal chemist thanks to the technological advancements in different branches of chemistry. This fact as well as the correlation between them has raised new problems in quantitative structure activity relationship studies. Proper parameter initialization in statistical modeling has merged as another challenge in recent years. Random selection of parameters leads to poor performance of deep neural network (DNN). In this research, deep belief network (DBN) was applied to initialize DNNs. DBN is composed of some stacks of restricted Boltzmann machine, an energy-based method that requires computing log likelihood gradient for all samples. Three different sampling approaches were suggested to solve this gradient. In this respect, the impact of DBN was applied based on the different sampling approaches mentioned above to initialize the DNN architecture in predicting biological activity of all fifteen Kaggle targets that contain more than 70k molecules. The same as other fields of processing research, the outputs of these models demonstrated significant superiority to that of DNN with random parameters. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Published GMO studies find no evidence of harm when corrected for multiple comparisons.

PubMed

Panchin, Alexander Y; Tuzhikov, Alexander I

2017-03-01

A number of widely debated research articles claiming possible technology-related health concerns have influenced the public opinion on genetically modified food safety. We performed a statistical reanalysis and review of experimental data presented in some of these studies and found that quite often in contradiction with the authors' conclusions the data actually provides weak evidence of harm that cannot be differentiated from chance. In our opinion the problem of statistically unaccounted multiple comparisons has led to some of the most cited anti-genetically modified organism health claims in history. We hope this analysis puts the original results of these studies into proper context.

Investigating the management performance of disinfection analysis of water distribution networks using data mining approaches.

PubMed

Zounemat-Kermani, Mohammad; Ramezani-Charmahineh, Abdollah; Adamowski, Jan; Kisi, Ozgur

2018-06-13

Chlorination, the basic treatment utilized for drinking water sources, is widely used for water disinfection and pathogen elimination in water distribution networks. Thereafter, the proper prediction of chlorine consumption is of great importance in water distribution network performance. In this respect, data mining techniques-which have the ability to discover the relationship between dependent variable(s) and independent variables-can be considered as alternative approaches in comparison to conventional methods (e.g., numerical methods). This study examines the applicability of three key methods, based on the data mining approach, for predicting chlorine levels in four water distribution networks. ANNs (artificial neural networks, including the multi-layer perceptron neural network, MLPNN, and radial basis function neural network, RBFNN), SVM (support vector machine), and CART (classification and regression tree) methods were used to estimate the concentration of residual chlorine in distribution networks for three villages in Kerman Province, Iran. Produced water (flow), chlorine consumption, and residual chlorine were collected daily for 3 years. An assessment of the studied models using several statistical criteria (NSC, RMSE, R 2 , and SEP) indicated that, in general, MLPNN has the greatest capability for predicting chlorine levels followed by CART, SVM, and RBF-ANN. Weaker performance of the data-driven methods in the water distribution networks, in some cases, could be attributed to improper chlorination management rather than the methods' capability.

A deep proper motion catalog within the Sloan digital sky survey footprint

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

Munn, Jeffrey A.; Harris, Hugh C.; Tilleman, Trudy M.

2014-12-01

A new proper motion catalog is presented, combining the Sloan Digital Sky Survey (SDSS) with second epoch observations in the r band within a portion of the SDSS imaging footprint. The new observations were obtained with the 90prime camera on the Steward Observatory Bok 90 inch telescope, and the Array Camera on the U.S. Naval Observatory, Flagstaff Station, 1.3 m telescope. The catalog covers 1098 square degrees to r = 22.0, an additional 1521 square degrees to r = 20.9, plus a further 488 square degrees of lesser quality data. Statistical errors in the proper motions range from 5 masmore » year{sup −1} at the bright end to 15 mas year{sup −1} at the faint end, for a typical epoch difference of six years. Systematic errors are estimated to be roughly 1 mas year{sup −1} for the Array Camera data, and as much as 2–4 mas year{sup −1} for the 90prime data (though typically less). The catalog also includes a second epoch of r band photometry.« less

Towards simulating and quantifying the light-cone EoR 21-cm signal

NASA Astrophysics Data System (ADS)

Mondal, Rajesh; Bharadwaj, Somnath; Datta, Kanan K.

2018-02-01

The light-cone (LC) effect causes the Epoch of Reionization (EoR) 21-cm signal T_b (\\hat{n}, ν ) to evolve significantly along the line-of-sight (LoS) direction ν. In the first part of this paper, we present a method to properly incorporate the LC effect in simulations of the EoR 21-cm signal that includes peculiar velocities. Subsequently, we discuss how to quantify the second-order statistics of the EoR 21-cm signal in the presence of the LC effect. We demonstrate that the 3D power spectrum P(k) fails to quantify the entire information because it assumes the signal to be ergodic and periodic, whereas the LC effect breaks these conditions along the LoS. Considering a LC simulation centred at redshift 8 where the mean neutral fraction drops from 0.65 to 0.35 across the box, we find that P(k) misses out ˜ 40 per cent of the information at the two ends of the 17.41 MHz simulation bandwidth. The multifrequency angular power spectrum (MAPS) C_{ℓ}(ν_1,ν_2) quantifies the statistical properties of T_b (\\hat{n}, ν ) without assuming the signal to be ergodic and periodic along the LoS. We expect this to quantify the entire statistical information of the EoR 21-cm signal. We apply MAPS to our LC simulation and present preliminary results for the EoR 21-cm signal.

Behavior of Filters and Smoothers for Strongly Nonlinear Dynamics

NASA Technical Reports Server (NTRS)

Zhu, Yanqui; Cohn, Stephen E.; Todling, Ricardo

1999-01-01

The Kalman filter is the optimal filter in the presence of known gaussian error statistics and linear dynamics. Filter extension to nonlinear dynamics is non trivial in the sense of appropriately representing high order moments of the statistics. Monte Carlo, ensemble-based, methods have been advocated as the methodology for representing high order moments without any questionable closure assumptions. Investigation along these lines has been conducted for highly idealized dynamics such as the strongly nonlinear Lorenz model as well as more realistic models of the means and atmosphere. A few relevant issues in this context are related to the necessary number of ensemble members to properly represent the error statistics and, the necessary modifications in the usual filter situations to allow for correct update of the ensemble members. The ensemble technique has also been applied to the problem of smoothing for which similar questions apply. Ensemble smoother examples, however, seem to be quite puzzling in that results state estimates are worse than for their filter analogue. In this study, we use concepts in probability theory to revisit the ensemble methodology for filtering and smoothing in data assimilation. We use the Lorenz model to test and compare the behavior of a variety of implementations of ensemble filters. We also implement ensemble smoothers that are able to perform better than their filter counterparts. A discussion of feasibility of these techniques to large data assimilation problems will be given at the time of the conference.

Prevalence and Associated Risk Factors of Bronchial Asthma in Children in Santo Domingo, Dominican Republic.

PubMed

Mejias, Stephanie G; Ramphul, Kamleshun

2018-02-20

Background Bronchial asthma is an important health problem worldwide. There is insufficient data on the prevalence of bronchial asthma among school children in Santo Domingo, Dominican Republic. Objective The objective of this study is to assess the prevalence of asthma and its related risk factors among school children in Santo Domingo, Dominican Republic. Materials and methods A cross-sectional study using a modified questionnaire was conducted in Santo Domingo among 600 children aged three to 11 eleven years. The prevalence of asthma and its associated risk factors such as birth order, family history of asthma, family history of allergy, exposure to pets at home, exposure to tobacco smoke, and source of fuel used at home were collected. The relevant data collected was analyzed using the Statistical Package for the Social Sciences (SPSS) 24.0. (IBM Corp., Armonk, NY) software. Results The prevalence of asthma was found to be 22.0%. Age, family history of asthma, family history of allergy, exposure to tobacco smoke, and birth order showed statistical significance. The source of fuel used at home, gender, and exposure to pets were not statistically significant to be considered as risk factors associated with asthma in the population studied. Conclusion With an asthma prevalence of 22.0% in the pediatric population, the Dominican Republic has one of the highest national rates of asthma in the pediatric population in Latin America. Proper education, screening, and prevention can help lower the burden of this disease economically and socially.

Analysing News for Stock Market Prediction

NASA Astrophysics Data System (ADS)

Ramalingam, V. V.; Pandian, A.; Dwivedi, shivam; Bhatt, Jigar P.

2018-04-01

Stock market means the aggregation of all sellers and buyers of stocks representing their ownership claims on the business. To be completely absolute about the investment on these stocks, proper knowledge about them as well as their pricing, for both present and future is very essential. Large amount of data is collected and parsed to obtain this essential information regarding the fluctuations in the stock market. This data can be any news or public opinions in general. Recently, many methods have been used, especially big unstructured data methods to predict the stock market values. We introduce another method of focusing on deriving the best statistical learning model for predicting the future values. The data set used is very large unstructured data collected from an online social platform, commonly known as Quindl. The data from this platform is then linked to a csv fie and cleaned to obtain the essential information for stock market prediction. The method consists of carrying out the NLP (Natural Language Processing) of the data and then making it easier for the system to understand, finds and identifies the correlation in between this data and the stock market fluctuations. The model is implemented using Python Programming Language throughout the entire project to obtain flexibility and convenience of the system.

Individual and population pharmacokinetic compartment analysis: a graphic procedure for quantification of predictive performance.

PubMed

Eksborg, Staffan

2013-01-01

Pharmacokinetic studies are important for optimizing of drug dosing, but requires proper validation of the used pharmacokinetic procedures. However, simple and reliable statistical methods suitable for evaluation of the predictive performance of pharmacokinetic analysis are essentially lacking. The aim of the present study was to construct and evaluate a graphic procedure for quantification of predictive performance of individual and population pharmacokinetic compartment analysis. Original data from previously published pharmacokinetic compartment analyses after intravenous, oral, and epidural administration, and digitized data, obtained from published scatter plots of observed vs predicted drug concentrations from population pharmacokinetic studies using the NPEM algorithm and NONMEM computer program and Bayesian forecasting procedures, were used for estimating the predictive performance according to the proposed graphical method and by the method of Sheiner and Beal. The graphical plot proposed in the present paper proved to be a useful tool for evaluation of predictive performance of both individual and population compartment pharmacokinetic analysis. The proposed method is simple to use and gives valuable information concerning time- and concentration-dependent inaccuracies that might occur in individual and population pharmacokinetic compartment analysis. Predictive performance can be quantified by the fraction of concentration ratios within arbitrarily specified ranges, e.g. within the range 0.8-1.2.

Measurement of the $B^-$ lifetime using a simulation free approach for trigger bias correction

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

Aaltonen, T.; /Helsinki Inst. of Phys.; Adelman, J.

2010-04-01

The collection of a large number of B hadron decays to hadronic final states at the CDF II detector is possible due to the presence of a trigger that selects events based on track impact parameters. However, the nature of the selection requirements of the trigger introduces a large bias in the observed proper decay time distribution. A lifetime measurement must correct for this bias and the conventional approach has been to use a Monte Carlo simulation. The leading sources of systematic uncertainty in the conventional approach are due to differences between the data and the Monte Carlo simulation. Inmore » this paper they present an analytic method for bias correction without using simulation, thereby removing any uncertainty between data and simulation. This method is presented in the form of a measurement of the lifetime of the B{sup -} using the mode B{sup -} {yields} D{sup 0}{pi}{sup -}. The B{sup -} lifetime is measured as {tau}{sub B{sup -}} = 1.663 {+-} 0.023 {+-} 0.015 ps, where the first uncertainty is statistical and the second systematic. This new method results in a smaller systematic uncertainty in comparison to methods that use simulation to correct for the trigger bias.« less

The questioned p value: clinical, practical and statistical significance.

PubMed

Jiménez-Paneque, Rosa

2016-09-09

The use of p-value and statistical significance have been questioned since the early 80s in the last century until today. Much has been discussed about it in the field of statistics and its applications, especially in Epidemiology and Public Health. As a matter of fact, the p-value and its equivalent, statistical significance, are difficult concepts to grasp for the many health professionals some way involved in research applied to their work areas. However, its meaning should be clear in intuitive terms although it is based on theoretical concepts of the field of Statistics. This paper attempts to present the p-value as a concept that applies to everyday life and therefore intuitively simple but whose proper use cannot be separated from theoretical and methodological elements of inherent complexity. The reasons behind the criticism received by the p-value and its isolated use are intuitively explained, mainly the need to demarcate statistical significance from clinical significance and some of the recommended remedies for these problems are approached as well. It finally refers to the current trend to vindicate the p-value appealing to the convenience of its use in certain situations and the recent statement of the American Statistical Association in this regard.

Hydrodaynamic - Statistical Forecast Method To 36-48h Ahead Of Storm Wind And Tornadoes Over The Territory Of Europe And Siberia

NASA Astrophysics Data System (ADS)

Perekhodtseva, Elvira V.

2010-05-01

Development of successful method of forecast of storm winds, including squalls and tornadoes, that often result in human and material losses, could allow one to take proper measures against destruction of buildings and to protect people. Well-in-advance successful forecast (from 12 hours to 48 hour) makes possible to reduce the losses. Prediction of the phenomena involved is a very difficult problem for synoptic till recently. The existing graphic and calculation methods still depend on subjective decision of an operator. Nowadays in Russia there is no hydrodynamic model for forecast of the maximal wind velocity V> 25m/c, hence the main tools of objective forecast are statistical methods using the dependence of the phenomena involved on a number of atmospheric parameters (predictors). . Statistical decisive rule of the alternative and probability forecast of these events was obtained in accordance with the concept of "perfect prognosis" using the data of objective analysis. For this purpose the different teaching samples of present and absent of this storm wind and rainfalls were automatically arranged that include the values of forty physically substantiated potential predictors. Then the empirical statistical method was used that involved diagonalization of the mean correlation matrix R of the predictors and extraction of diagonal blocks of strongly correlated predictors. Thus for these phenomena the most informative predictors were selected without loosing information. The statistical decisive rules for diagnosis and prognosis of the phenomena involved U(X) were calculated for choosing informative vector-predictor. We used the criterion of distance of Mahalanobis and criterion of minimum of entropy by Vapnik-Chervonenkis for the selection predictors. Successful development of hydrodynamic models for short-term forecast and improvement of 36-48h forecasts of pressure, temperature and others parameters allowed us to use the prognostic fields of those models for calculations of the discriminant functions in the nodes of the grid 75x75km and the values of probabilities P of dangerous wind and thus to get fully automated forecasts. . In order to apply the alternative forecast to European part of Russia and Europe the author proposes the empirical threshold values specified for this phenomenon and advance period 36 hours. According to the Pirsey-Obukhov criterion (T), the success of this hydrometeorological-statistical method of forecast of storm wind and tornadoes to 36 -48 hours ahead in the warm season for the territory of Europe part of Russia and Siberia is T = 1-a-b=0,54-0,78 after independent and author experiments during the period 2004-2009 years. A lot of examples of very successful forecasts are submitted at this report for the territory of Europe and Russia. The same decisive rules were applied to the forecast of these phenomena during cold period in 2009-2010 years too. On the first month of 2010 a lot of cases of storm wind with heavy snowfall were observed and were forecasting over the territory of France, Italy and Germany.

7 CFR 407.16 - Group risk plan for soybean.

Code of Federal Regulations, 2012 CFR

2012-01-01

... calculate indemnities. Planted acreage. Land in which the soybean seed has been placed by a machine... properly prepared for the planting method and production practice. Land on which seed is initially spread... accepted application; (b) Properly planted and reported by the acreage reporting date; (c) Planted with the...

7 CFR 407.17 - Group risk plan for wheat.

Code of Federal Regulations, 2011 CFR

2011-01-01

... calculate indemnities. Planted acreage. Land in which the wheat seed has been planted by a machine... properly prepared for the planting method and production practice. Land on which seed is initially spread... accepted application; (b) Properly planted and reported by the acreage reporting date; (c) Planted with the...

7 CFR 407.16 - Group risk plan for soybean.

Code of Federal Regulations, 2011 CFR

2011-01-01

... calculate indemnities. Planted acreage. Land in which the soybean seed has been placed by a machine... properly prepared for the planting method and production practice. Land on which seed is initially spread... accepted application; (b) Properly planted and reported by the acreage reporting date; (c) Planted with the...

7 CFR 407.17 - Group risk plan for wheat.

Code of Federal Regulations, 2012 CFR

2012-01-01

... calculate indemnities. Planted acreage. Land in which the wheat seed has been planted by a machine... properly prepared for the planting method and production practice. Land on which seed is initially spread... accepted application; (b) Properly planted and reported by the acreage reporting date; (c) Planted with the...

Toothbrushing: Do It Daily.

ERIC Educational Resources Information Center

Texas Child Care, 1993

1993-01-01

Offers a practical guide for promoting daily toothbrushing in young children. Discusses the importance of proper dental care, explains the causes of tooth decay, describes proper dental care for infants and young children, recommends materials and teaching methods, and discusses visits to the dentist and the benefits of fluoride for dental health.…

Probabilistic multi-catalogue positional cross-match

NASA Astrophysics Data System (ADS)

Pineau, F.-X.; Derriere, S.; Motch, C.; Carrera, F. J.; Genova, F.; Michel, L.; Mingo, B.; Mints, A.; Nebot Gómez-Morán, A.; Rosen, S. R.; Ruiz Camuñas, A.

2017-01-01

Context. Catalogue cross-correlation is essential to building large sets of multi-wavelength data, whether it be to study the properties of populations of astrophysical objects or to build reference catalogues (or timeseries) from survey observations. Nevertheless, resorting to automated processes with limited sets of information available on large numbers of sources detected at different epochs with various filters and instruments inevitably leads to spurious associations. We need both statistical criteria to select detections to be merged as unique sources, and statistical indicators helping in achieving compromises between completeness and reliability of selected associations. Aims: We lay the foundations of a statistical framework for multi-catalogue cross-correlation and cross-identification based on explicit simplified catalogue models. A proper identification process should rely on both astrometric and photometric data. Under some conditions, the astrometric part and the photometric part can be processed separately and merged a posteriori to provide a single global probability of identification. The present paper addresses almost exclusively the astrometrical part and specifies the proper probabilities to be merged with photometric likelihoods. Methods: To select matching candidates in n catalogues, we used the Chi (or, indifferently, the Chi-square) test with 2(n-1) degrees of freedom. We thus call this cross-match a χ-match. In order to use Bayes' formula, we considered exhaustive sets of hypotheses based on combinatorial analysis. The volume of the χ-test domain of acceptance - a 2(n-1)-dimensional acceptance ellipsoid - is used to estimate the expected numbers of spurious associations. We derived priors for those numbers using a frequentist approach relying on simple geometrical considerations. Likelihoods are based on standard Rayleigh, χ and Poisson distributions that we normalized over the χ-test acceptance domain. We validated our theoretical results by generating and cross-matching synthetic catalogues. Results: The results we obtain do not depend on the order used to cross-correlate the catalogues. We applied the formalism described in the present paper to build the multi-wavelength catalogues used for the science cases of the Astronomical Resource Cross-matching for High Energy Studies (ARCHES) project. Our cross-matching engine is publicly available through a multi-purpose web interface. In a longer term, we plan to integrate this tool into the CDS XMatch Service.

The Use of Public Enlightenment Campaign Strategy and School Disciplinary Measures in the Management of Cultism in Tertiary Institutions in Nigeria

ERIC Educational Resources Information Center

Omemu, Felix

2015-01-01

The study investigated the perceptions of staff and students on the use of school disciplinary measures and public awareness campaign strategy in the management of cultism in tertiary institutions in Nigeria. The study is guided by two hypotheses tested using the t-test statistics. An instrument containing 10 items properly validated was used in…

Validity of the SAT® for Predicting First-Year Grades: 2010 SAT Validity Sample. Statistical Report 2013-2

ERIC Educational Resources Information Center

Patterson, Brian F.; Mattern, Krista D.

2013-01-01

The continued accumulation of validity evidence for the core uses of educational assessments is critical to ensure that proper inferences will be made for those core purposes. To that end, the College Board has continued to follow previous cohorts of college students and this report provides updated validity evidence for using the SAT to predict…

NEUTRONIC REACTOR CHARGING AND DISCHARGING

DOEpatents

Zinn, W.H.

1959-07-14

A method and arrangement is presented for removing a fuel element from a neutronic reactor tube through which a liquid coolant is being circulaled. The fuel element is moved into a section of the tube beyond the reactor proper, and then the coolant in the tube between the fuel element and the reactor proper is frozen, so that the fuel element may be removed from the tube without loss of the coolant therein. The method is particularly useful in the case of a liquid metal- cooled reactor.

New Astrometric Limits on the Stochastic Gravitational Wave Background

NASA Astrophysics Data System (ADS)

Darling, Jeremiah K.; Truebenbach, Alexandra; Paine, Jennie

2018-06-01

We present new limits on the low frequency (f < 10-8 Hz) stochastic gravitational wave background using correlated extragalactic proper motions. The familiar methods for gravitational wave detection are ground- and space-based laser interferometry, pulsar timing, and polarization of the cosmic microwave background. Astrometry offers an additional path to gravitational wave detection because gravitational waves deflect the light rays of extragalactic objects, creating apparent proper motions in a quadrupolar (and higher order modes) pattern. Astrometry is sensitive to gravitational waves with frequencies between roughly 10-18 Hz and 10-8 Hz (between H0 and 1/3 yr-1), which overlaps and bridges the pulsar timing and CMB polarization regimes. We present the methods and results of two complementary approaches to astrometric gravitational wave detection: (1) a small ~500-object radio interferometric sample with low per-source proper motion uncertainty but large intrinsic proper motions caused by radio jets, and (2) a thousand-fold larger sample with large per-source uncertainties that has small intrinsic proper motions (Gaia active galactic nuclei). Both approaches produce limits on ΩGW, the energy density of gravitational waves as a fraction of the cosmological critical energy density.The authors acknowledge support from the NSF grant AST-1411605 and the NASA grant 14-ATP14-0086.

Quality Control of High-Dose-Rate Brachytherapy: Treatment Delivery Analysis Using Statistical Process Control

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

Able, Charles M., E-mail: cable@wfubmc.edu; Bright, Megan; Frizzell, Bart

Purpose: Statistical process control (SPC) is a quality control method used to ensure that a process is well controlled and operates with little variation. This study determined whether SPC was a viable technique for evaluating the proper operation of a high-dose-rate (HDR) brachytherapy treatment delivery system. Methods and Materials: A surrogate prostate patient was developed using Vyse ordnance gelatin. A total of 10 metal oxide semiconductor field-effect transistors (MOSFETs) were placed from prostate base to apex. Computed tomography guidance was used to accurately position the first detector in each train at the base. The plan consisted of 12 needles withmore » 129 dwell positions delivering a prescribed peripheral dose of 200 cGy. Sixteen accurate treatment trials were delivered as planned. Subsequently, a number of treatments were delivered with errors introduced, including wrong patient, wrong source calibration, wrong connection sequence, single needle displaced inferiorly 5 mm, and entire implant displaced 2 mm and 4 mm inferiorly. Two process behavior charts (PBC), an individual and a moving range chart, were developed for each dosimeter location. Results: There were 4 false positives resulting from 160 measurements from 16 accurately delivered treatments. For the inaccurately delivered treatments, the PBC indicated that measurements made at the periphery and apex (regions of high-dose gradient) were much more sensitive to treatment delivery errors. All errors introduced were correctly identified by either the individual or the moving range PBC in the apex region. Measurements at the urethra and base were less sensitive to errors. Conclusions: SPC is a viable method for assessing the quality of HDR treatment delivery. Further development is necessary to determine the most effective dose sampling, to ensure reproducible evaluation of treatment delivery accuracy.« less

Multi-objective calibration and uncertainty analysis of hydrologic models; A comparative study between formal and informal methods

NASA Astrophysics Data System (ADS)

Shafii, M.; Tolson, B.; Matott, L. S.

2012-04-01

Hydrologic modeling has benefited from significant developments over the past two decades. This has resulted in building of higher levels of complexity into hydrologic models, which eventually makes the model evaluation process (parameter estimation via calibration and uncertainty analysis) more challenging. In order to avoid unreasonable parameter estimates, many researchers have suggested implementation of multi-criteria calibration schemes. Furthermore, for predictive hydrologic models to be useful, proper consideration of uncertainty is essential. Consequently, recent research has emphasized comprehensive model assessment procedures in which multi-criteria parameter estimation is combined with statistically-based uncertainty analysis routines such as Bayesian inference using Markov Chain Monte Carlo (MCMC) sampling. Such a procedure relies on the use of formal likelihood functions based on statistical assumptions, and moreover, the Bayesian inference structured on MCMC samplers requires a considerably large number of simulations. Due to these issues, especially in complex non-linear hydrological models, a variety of alternative informal approaches have been proposed for uncertainty analysis in the multi-criteria context. This study aims at exploring a number of such informal uncertainty analysis techniques in multi-criteria calibration of hydrological models. The informal methods addressed in this study are (i) Pareto optimality which quantifies the parameter uncertainty using the Pareto solutions, (ii) DDS-AU which uses the weighted sum of objective functions to derive the prediction limits, and (iii) GLUE which describes the total uncertainty through identification of behavioral solutions. The main objective is to compare such methods with MCMC-based Bayesian inference with respect to factors such as computational burden, and predictive capacity, which are evaluated based on multiple comparative measures. The measures for comparison are calculated both for calibration and evaluation periods. The uncertainty analysis methodologies are applied to a simple 5-parameter rainfall-runoff model, called HYMOD.

Novel statistical tools for management of public databases facilitate community-wide replicability and control of false discovery.

PubMed

Rosset, Saharon; Aharoni, Ehud; Neuvirth, Hani

2014-07-01

Issues of publication bias, lack of replicability, and false discovery have long plagued the genetics community. Proper utilization of public and shared data resources presents an opportunity to ameliorate these problems. We present an approach to public database management that we term Quality Preserving Database (QPD). It enables perpetual use of the database for testing statistical hypotheses while controlling false discovery and avoiding publication bias on the one hand, and maintaining testing power on the other hand. We demonstrate it on a use case of a replication server for GWAS findings, underlining its practical utility. We argue that a shift to using QPD in managing current and future biological databases will significantly enhance the community's ability to make efficient and statistically sound use of the available data resources. © 2014 WILEY PERIODICALS, INC.

Descriptive statistics: the specification of statistical measures and their presentation in tables and graphs. Part 7 of a series on evaluation of scientific publications.

PubMed

Spriestersbach, Albert; Röhrig, Bernd; du Prel, Jean-Baptist; Gerhold-Ay, Aslihan; Blettner, Maria

2009-09-01

Descriptive statistics are an essential part of biometric analysis and a prerequisite for the understanding of further statistical evaluations, including the drawing of inferences. When data are well presented, it is usually obvious whether the author has collected and evaluated them correctly and in keeping with accepted practice in the field. Statistical variables in medicine may be of either the metric (continuous, quantitative) or categorical (nominal, ordinal) type. Easily understandable examples are given. Basic techniques for the statistical description of collected data are presented and illustrated with examples. The goal of a scientific study must always be clearly defined. The definition of the target value or clinical endpoint determines the level of measurement of the variables in question. Nearly all variables, whatever their level of measurement, can be usefully presented graphically and numerically. The level of measurement determines what types of diagrams and statistical values are appropriate. There are also different ways of presenting combinations of two independent variables graphically and numerically. The description of collected data is indispensable. If the data are of good quality, valid and important conclusions can already be drawn when they are properly described. Furthermore, data description provides a basis for inferential statistics.

An adaptive model order reduction by proper snapshot selection for nonlinear dynamical problems

NASA Astrophysics Data System (ADS)

Nigro, P. S. B.; Anndif, M.; Teixeira, Y.; Pimenta, P. M.; Wriggers, P.

2016-04-01

Model Order Reduction (MOR) methods are employed in many fields of Engineering in order to reduce the processing time of complex computational simulations. A usual approach to achieve this is the application of Galerkin projection to generate representative subspaces (reduced spaces). However, when strong nonlinearities in a dynamical system are present and this technique is employed several times along the simulation, it can be very inefficient. This work proposes a new adaptive strategy, which ensures low computational cost and small error to deal with this problem. This work also presents a new method to select snapshots named Proper Snapshot Selection (PSS). The objective of the PSS is to obtain a good balance between accuracy and computational cost by improving the adaptive strategy through a better snapshot selection in real time (online analysis). With this method, it is possible a substantial reduction of the subspace, keeping the quality of the model without the use of the Proper Orthogonal Decomposition (POD).

The Problems with the Kappa Statistic as a Metric of Interobserver Agreement on Lesion Detection Using a Third-reader Approach When Locations Are Not Prespecified.

PubMed

Shih, Joanna H; Greer, Matthew D; Turkbey, Baris

2018-03-16

To point out the problems with Cohen kappa statistic and to explore alternative metrics to determine interobserver agreement on lesion detection when locations are not prespecified. Use of kappa and two alternative methods, namely index of specific agreement (ISA) and modified kappa, for measuring interobserver agreement on the location of detected lesions are presented. These indices of agreement are illustrated by application to a retrospective multireader study in which nine readers detected and scored prostate cancer lesions in 163 consecutive patients (n = 110 cases, n = 53 controls) using the guideline of Prostate Imaging Reporting and Data System version 2 on multiparametric magnetic resonance imaging. The proposed modified kappa, which properly corrects for the amount of agreement by chance, is shown to be approximately equivalent to the ISA. In the prostate cancer data, average kappa, modified kappa, and ISA equaled 30%, 55%, and 57%, respectively, for all lesions and 20%, 87%, and 87%, respectively, for index lesions. The application of kappa could result in a substantial downward bias in reader agreement on lesion detection when locations are not prespecified. ISA is recommended for assessment of reader agreement on lesion detection. Published by Elsevier Inc.

Spatial and temporal variation of water quality of a segment of Marikina River using multivariate statistical methods.

PubMed

Chounlamany, Vanseng; Tanchuling, Maria Antonia; Inoue, Takanobu

2017-09-01

Payatas landfill in Quezon City, Philippines, releases leachate to the Marikina River through a creek. Multivariate statistical techniques were applied to study temporal and spatial variations in water quality of a segment of the Marikina River. The data set included 12 physico-chemical parameters for five monitoring stations over a year. Cluster analysis grouped the monitoring stations into four clusters and identified January-May as dry season and June-September as wet season. Principal components analysis showed that three latent factors are responsible for the data set explaining 83% of its total variance. The chemical oxygen demand, biochemical oxygen demand, total dissolved solids, Cl - and PO 4 3- are influenced by anthropogenic impact/eutrophication pollution from point sources. Total suspended solids, turbidity and SO 4 2- are influenced by rain and soil erosion. The highest state of pollution is at the Payatas creek outfall from March to May, whereas at downstream stations it is in May. The current study indicates that the river monitoring requires only four stations, nine water quality parameters and testing over three specific months of the year. The findings of this study imply that Payatas landfill requires a proper leachate collection and treatment system to reduce its impact on the Marikina River.

Perceptions of Nigerian Women about Human Papilloma Virus, Cervical Cancer, and HPV Vaccine

PubMed Central

Akanbi, Olusola Anuoluwapo; Iyanda, Abiodun; Osundare, Folakemi; Opaleye, Oluyinka Oladele

2015-01-01

Background. Cervical cancer caused by human papilloma virus (HPV) though preventable has claimed the lives of many women worldwide. This study was embarked upon to evaluate the general knowledge and perceptions of Nigerian women on HPV, cervical cancer, and HPV vaccine. Methods. Structured questionnaires were administered to a cross section of 737 women randomly selected from the general population in two southwestern States of Nigeria. Statistical analysis was done using SPSS computer software version 16. A P value >0.05 was considered statistically significant. Results. One hundred and seventy-six (23.9%) of the respondents had knowledge of HPV; 474 (64.3%) are aware of cervical cancer but only 136 (18.5%) know that HPV causes cervical cancer. 200 (27.1%) are aware that there is an HPV vaccine while 300 (40.7%) had knowledge of Pap smear test. Two hundred and sixty (35.3%) of the respondents know that early detection of HPV can prevent cervical cancer and in spite of this, only 110 (14.9%) have taken the Pap smear test before while 151 (20.5%) are not willing to go for the test at all. Conclusions. There is therefore the need to create proper awareness on the HPV and its possible consequence of cervical carcinoma. PMID:26550522

Using statistical model to simulate the impact of climate change on maize yield with climate and crop uncertainties

NASA Astrophysics Data System (ADS)

Zhang, Yi; Zhao, Yanxia; Wang, Chunyi; Chen, Sining

2017-11-01

Assessment of the impact of climate change on crop productions with considering uncertainties is essential for properly identifying and decision-making agricultural practices that are sustainable. In this study, we employed 24 climate projections consisting of the combinations of eight GCMs and three emission scenarios representing the climate projections uncertainty, and two crop statistical models with 100 sets of parameters in each model representing parameter uncertainty within the crop models. The goal of this study was to evaluate the impact of climate change on maize ( Zea mays L.) yield at three locations (Benxi, Changling, and Hailun) across Northeast China (NEC) in periods 2010-2039 and 2040-2069, taking 1976-2005 as the baseline period. The multi-models ensembles method is an effective way to deal with the uncertainties. The results of ensemble simulations showed that maize yield reductions were less than 5 % in both future periods relative to the baseline. To further understand the contributions of individual sources of uncertainty, such as climate projections and crop model parameters, in ensemble yield simulations, variance decomposition was performed. The results indicated that the uncertainty from climate projections was much larger than that contributed by crop model parameters. Increased ensemble yield variance revealed the increasing uncertainty in the yield simulation in the future periods.

VizieR Online Data Catalog: Proper motions of PM2000 open clusters (Krone-Martins+, 2010)

NASA Astrophysics Data System (ADS)

Krone-Martins, A.; Soubiran, C.; Ducourant, C.; Teixeira, R.; Le Campion, J. F.

2010-04-01

We present lists of proper-motions and kinematic membership probabilities in the region of 49 open clusters or possible open clusters. The stellar proper motions were taken from the Bordeaux PM2000 catalogue. The segregation between cluster and field stars and the assignment of membership probabilities was accomplished by applying a fully automated method based on parametrisations for the probability distribution functions and genetic algorithm optimisation heuristics associated with a derivative-based hill climbing algorithm for the likelihood optimization. (3 data files).

Iterative raw measurements restoration method with penalized weighted least squares approach for low-dose CT

NASA Astrophysics Data System (ADS)

Takahashi, Hisashi; Goto, Taiga; Hirokawa, Koichi; Miyazaki, Osamu

2014-03-01

Statistical iterative reconstruction and post-log data restoration algorithms for CT noise reduction have been widely studied and these techniques have enabled us to reduce irradiation doses while maintaining image qualities. In low dose scanning, electronic noise becomes obvious and it results in some non-positive signals in raw measurements. The nonpositive signal should be converted to positive signal so that it can be log-transformed. Since conventional conversion methods do not consider local variance on the sinogram, they have difficulty of controlling the strength of the filtering. Thus, in this work, we propose a method to convert the non-positive signal to the positive signal by mainly controlling the local variance. The method is implemented in two separate steps. First, an iterative restoration algorithm based on penalized weighted least squares is used to mitigate the effect of electronic noise. The algorithm preserves the local mean and reduces the local variance induced by the electronic noise. Second, smoothed raw measurements by the iterative algorithm are converted to the positive signal according to a function which replaces the non-positive signal with its local mean. In phantom studies, we confirm that the proposed method properly preserves the local mean and reduce the variance induced by the electronic noise. Our technique results in dramatically reduced shading artifacts and can also successfully cooperate with the post-log data filter to reduce streak artifacts.

Differential expression analysis for RNAseq using Poisson mixed models.

PubMed

Sun, Shiquan; Hood, Michelle; Scott, Laura; Peng, Qinke; Mukherjee, Sayan; Tung, Jenny; Zhou, Xiang

2017-06-20

Identifying differentially expressed (DE) genes from RNA sequencing (RNAseq) studies is among the most common analyses in genomics. However, RNAseq DE analysis presents several statistical and computational challenges, including over-dispersed read counts and, in some settings, sample non-independence. Previous count-based methods rely on simple hierarchical Poisson models (e.g. negative binomial) to model independent over-dispersion, but do not account for sample non-independence due to relatedness, population structure and/or hidden confounders. Here, we present a Poisson mixed model with two random effects terms that account for both independent over-dispersion and sample non-independence. We also develop a scalable sampling-based inference algorithm using a latent variable representation of the Poisson distribution. With simulations, we show that our method properly controls for type I error and is generally more powerful than other widely used approaches, except in small samples (n <15) with other unfavorable properties (e.g. small effect sizes). We also apply our method to three real datasets that contain related individuals, population stratification or hidden confounders. Our results show that our method increases power in all three data compared to other approaches, though the power gain is smallest in the smallest sample (n = 6). Our method is implemented in MACAU, freely available at www.xzlab.org/software.html. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Technologies and decision support systems to aid solid-waste management: a systematic review.

PubMed

Vitorino de Souza Melaré, Angelina; Montenegro González, Sahudy; Faceli, Katti; Casadei, Vitor

2017-01-01

Population growth associated with population migration to urban areas and industrial development have led to a consumption relation that results in environmental, social, and economic problems. With respect to the environment, a critical concern is the lack of control and the inadequate management of the solid waste generated in urban centers. Among the challenges are proper waste-collection management, treatment, and disposal, with an emphasis on sustainable management. This paper presents a systematic review on scientific publications concerning decision support systems applied to Solid Waste Management (SWM) using ICTs and OR in the period of 2010-2013. A statistical analysis of the eighty-seven most relevant publications is presented, encompassing the ICTs and OR methods adopted in SWM, the processes of solid-waste management where they were adopted, and which countries are investigating solutions for the management of solid waste. A detailed discussion on how the ICTs and OR methods have been combined in the solutions was also presented. The analysis and discussion provided aims to help researchers and managers to gather insights on technologies/methods suitable the SWM challenges they have at hand, and on gaps that can be explored regarding technologies/methods that could be useful as well as the processes in SWM that currently do not benefit from using ICTs and OR methods. Copyright © 2016 Elsevier Ltd. All rights reserved.

Sampling-based approaches to improve estimation of mortality among patient dropouts: experience from a large PEPFAR-funded program in Western Kenya.

PubMed

Yiannoutsos, Constantin T; An, Ming-Wen; Frangakis, Constantine E; Musick, Beverly S; Braitstein, Paula; Wools-Kaloustian, Kara; Ochieng, Daniel; Martin, Jeffrey N; Bacon, Melanie C; Ochieng, Vincent; Kimaiyo, Sylvester

2008-01-01

Monitoring and evaluation (M&E) of HIV care and treatment programs is impacted by losses to follow-up (LTFU) in the patient population. The severity of this effect is undeniable but its extent unknown. Tracing all lost patients addresses this but census methods are not feasible in programs involving rapid scale-up of HIV treatment in the developing world. Sampling-based approaches and statistical adjustment are the only scaleable methods permitting accurate estimation of M&E indices. In a large antiretroviral therapy (ART) program in western Kenya, we assessed the impact of LTFU on estimating patient mortality among 8,977 adult clients of whom, 3,624 were LTFU. Overall, dropouts were more likely male (36.8% versus 33.7%; p = 0.003), and younger than non-dropouts (35.3 versus 35.7 years old; p = 0.020), with lower median CD4 count at enrollment (160 versus 189 cells/ml; p<0.001) and WHO stage 3-4 disease (47.5% versus 41.1%; p<0.001). Urban clinic clients were 75.0% of non-dropouts but 70.3% of dropouts (p<0.001). Of the 3,624 dropouts, 1,143 were sought and 621 had their vital status ascertained. Statistical techniques were used to adjust mortality estimates based on information obtained from located LTFU patients. Observed mortality estimates one year after enrollment were 1.7% (95% CI 1.3%-2.0%), revised to 2.8% (2.3%-3.1%) when deaths discovered through outreach were added and adjusted to 9.2% (7.8%-10.6%) and 9.9% (8.4%-11.5%) through statistical modeling depending on the method used. The estimates 12 months after ART initiation were 1.7% (1.3%-2.2%), 3.4% (2.9%-4.0%), 10.5% (8.7%-12.3%) and 10.7% (8.9%-12.6%) respectively. CONCLUSIONS/SIGNIFICANCE ABSTRACT: Assessment of the impact of LTFU is critical in program M&E as estimated mortality based on passive monitoring may underestimate true mortality by up to 80%. This bias can be ameliorated by tracing a sample of dropouts and statistically adjust the mortality estimates to properly evaluate and guide large HIV care and treatment programs.

The Love of Large Numbers: A Popularity Bias in Consumer Choice.

PubMed

Powell, Derek; Yu, Jingqi; DeWolf, Melissa; Holyoak, Keith J

2017-10-01

Social learning-the ability to learn from observing the decisions of other people and the outcomes of those decisions-is fundamental to human evolutionary and cultural success. The Internet now provides social evidence on an unprecedented scale. However, properly utilizing this evidence requires a capacity for statistical inference. We examined how people's interpretation of online review scores is influenced by the numbers of reviews-a potential indicator both of an item's popularity and of the precision of the average review score. Our task was designed to pit statistical information against social information. We modeled the behavior of an "intuitive statistician" using empirical prior information from millions of reviews posted on Amazon.com and then compared the model's predictions with the behavior of experimental participants. Under certain conditions, people preferred a product with more reviews to one with fewer reviews even though the statistical model indicated that the latter was likely to be of higher quality than the former. Overall, participants' judgments suggested that they failed to make meaningful statistical inferences.

Blast Testing Issues and TBI: Experimental Models That Lead to Wrong Conclusions.

PubMed

Needham, Charles E; Ritzel, David; Rule, Gregory T; Wiri, Suthee; Young, Leanne

2015-01-01

Over the past several years, we have noticed an increase in the number of blast injury studies published in peer-reviewed biomedical journals that have utilized improperly conceived experiments. Data from these studies will lead to false conclusions and more confusion than advancement in the understanding of blast injury, particularly blast neurotrauma. Computational methods to properly characterize the blast environment have been available for decades. These methods, combined with a basic understanding of blast wave phenomena, enable researchers to extract useful information from well-documented experiments. This basic understanding must include the differences and interrelationships of static pressure, dynamic pressure, reflected pressure, and total or stagnation pressure in transient shockwave flows, how they relate to loading of objects, and how they are properly measured. However, it is critical that the research community effectively overcomes the confusion that has been compounded by a misunderstanding of the differences between the loading produced by a free field explosive blast and loading produced by a conventional shock tube. The principles of blast scaling have been well established for decades and when properly applied will do much to repair these problems. This paper provides guidance regarding proper experimental methods and offers insights into the implications of improperly designed and executed tests. Through application of computational methods, useful data can be extracted from well-documented historical tests, and future work can be conducted in a way to maximize the effectiveness and use of valuable biological test data.

Domain Adaption of Parsing for Operative Notes

PubMed Central

Wang, Yan; Pakhomov, Serguei; Ryan, James O.; Melton, Genevieve B.

2016-01-01

Background Full syntactic parsing of clinical text as a part of clinical natural language processing (NLP) is critical for a wide range of applications, such as identification of adverse drug reactions, patient cohort identification, and gene interaction extraction. Several robust syntactic parsers are publicly available to produce linguistic representations for sentences. However, these existing parsers are mostly trained on general English text and often require adaptation for optimal performance on clinical text. Our objective was to adapt an existing general English parser for the clinical text of operative reports via lexicon augmentation, statistics adjusting, and grammar rules modification based on a set of biomedical text. Method The Stanford unlexicalized probabilistic context-free grammar (PCFG) parser lexicon was expanded with SPECIALIST lexicon along with statistics collected from a limited set of operative notes tagged with a two of POS taggers (GENIA tagger and MedPost). The most frequently occurring verb entries of the SPECIALIST lexicon were adjusted based on manual review of verb usage in operative notes. Stanford parser grammar production rules were also modified based on linguistic features of operative reports. An analogous approach was then applied to the GENIA corpus to test the generalizability of this approach to biomedical text. Results The new unlexicalized PCFG parser extended with the extra lexicon from SPECIALIST along with accurate statistics collected from an operative note corpus tagged with GENIA POS tagger improved the parser performance by 2.26% from 87.64% to 89.90%. There was a progressive improvement with the addition of multiple approaches. Most of the improvement occurred with lexicon augmentation combined with statistics from the operative notes corpus. Application of this approach on the GENIA corpus showed that parsing performance was boosted by 3.81% with a simple new grammar and the addition of the GENIA corpus lexicon. Conclusion Using statistics collected from clinical text tagged with POS taggers along with proper modification of grammars and lexicons of an unlexicalized PCFG parser can improve parsing performance. PMID:25661593

Local systematic differences in 2MASS positions

NASA Astrophysics Data System (ADS)

Bustos Fierro, I. H.; Calderón, J. H.

2018-01-01

We have found that positions in the 2MASS All-sky Catalog of Point Sources show local systematic differences with characteristic length-scales of ˜ 5 to ˜ 8 arcminutes when compared with several catalogs. We have observed that when 2MASS positions are used in the computation of proper motions, the mentioned systematic differences cause systematic errors in the resulting proper motions. We have developed a method to locally rectify 2MASS with respect to UCAC4 in order to diminish the systematic differences between these catalogs. The rectified 2MASS catalog with the proposed method can be regarded as an extension of UCAC4 for astrometry with accuracy ˜ 90 mas in its positions, with negligible systematic errors. Also we show that the use of these rectified positions removes the observed systematic pattern in proper motions derived from original 2MASS positions.

Consideration of vertical uncertainty in elevation-based sea-level rise assessments: Mobile Bay, Alabama case study

USGS Publications Warehouse

Gesch, Dean B.

2013-01-01

The accuracy with which coastal topography has been mapped directly affects the reliability and usefulness of elevationbased sea-level rise vulnerability assessments. Recent research has shown that the qualities of the elevation data must be well understood to properly model potential impacts. The cumulative vertical uncertainty has contributions from elevation data error, water level data uncertainties, and vertical datum and transformation uncertainties. The concepts of minimum sealevel rise increment and minimum planning timeline, important parameters for an elevation-based sea-level rise assessment, are used in recognition of the inherent vertical uncertainty of the underlying data. These concepts were applied to conduct a sea-level rise vulnerability assessment of the Mobile Bay, Alabama, region based on high-quality lidar-derived elevation data. The results that detail the area and associated resources (land cover, population, and infrastructure) vulnerable to a 1.18-m sea-level rise by the year 2100 are reported as a range of values (at the 95% confidence level) to account for the vertical uncertainty in the base data. Examination of the tabulated statistics about land cover, population, and infrastructure in the minimum and maximum vulnerable areas shows that these resources are not uniformly distributed throughout the overall vulnerable zone. The methods demonstrated in the Mobile Bay analysis provide an example of how to consider and properly account for vertical uncertainty in elevation-based sea-level rise vulnerability assessments, and the advantages of doing so.

The pituitary gland under infrared light - in search of a representative spectrum for homogeneous regions.

PubMed

Banas, A; Banas, K; Furgal-Borzych, A; Kwiatek, W M; Pawlicki, B; Breese, M B H

2015-04-07

The pituitary gland is a small but vital organ in the human body. It is located at the base of the brain and is often described as the master gland due to its multiple functions. The pituitary gland secretes and stores hormones, such as the thyroid-stimulating hormone (TSH), adrenocorticotropic hormone (ACTH), growth hormone (hGH), prolactin, gonadotropins, and luteinizing hormones, as well as the antidiuretic hormone (ADH). A proper diagnosis of pituitary disorders is of utmost importance as this organ participates in regulating a variety of body functions. Typical histopathological analysis provides much valuable information, but it gives no insight into the biochemical background of the changes that occur within the gland. One approach that could be used to evaluate the biochemistry of tissue sections obtained from pituitary disorders is Fourier Transform Infra-Red (FTIR) spectromicroscopy. In order to collect diagnostically valuable information large areas of tissue must be investigated. This work focuses on obtaining a unique and representative FTIR spectrum characteristic of one type of cell architecture within a sample. The idea presented is based on using hierarchical cluster analysis (HCA) for data evaluation to search for uniform patterns within samples from the perspective of FTIR spectra. The results obtained demonstrate that FTIR spectromicroscopy, combined with proper statistical evaluation, can be treated as a complementary method for histopathological analysis and ipso facto can increase the sensitivity and specificity for detecting various disorders not only for the pituitary gland, but also for other human tissues.

Measures of Residential Energy Consumption and their Relationships to DOE Policy,

DTIC Science & Technology

1999-11-01

on consumer behavior is inconclusive. Du Pont and Lord report that "a large percentage of consumers either ignore or misinterpret the labels (du...residential per capita energy consumption. 2. Implications Consumer behavior with respect to energy efficiency remains poorly understood and the proper...question by studies of consumer behavior . The results are also subject to numerical instability. Descriptive statistics can be helpful in interpreting the

Prediction of the dollar to the ruble rate. A system-theoretic approach

NASA Astrophysics Data System (ADS)

Borodachev, Sergey M.

2017-07-01

Proposed a simple state-space model of dollar rate formation based on changes in oil prices and some mechanisms of money transfer between monetary and stock markets. Comparison of predictions by means of input-output model and state-space model is made. It concludes that with proper use of statistical data (Kalman filter) the second approach provides more adequate predictions of the dollar rate.

Comparison of V50 Shot Placement on Final Outcome

DTIC Science & Technology

2014-11-01

molecular- weight polyethylene (UHMWPE). In V50 testing of those types of materials, large delaminations may occur that influence the results. This...placement, a proper evaluation of materials may not be possible. 15. SUBJECT TERMS ballistics, V50 test, logistic regression , statistical inference...from an impact. While this may work with ceramics or metal armor, it is inappropriate for use on composite armors like ultra-high-molecular- weight

Development of Strategic Air Command, 1946 - 1976

DTIC Science & Technology

1976-03-01

flashes red. Azure , two clouds proper, one issuing from sinister chief and one issuing from dexter base, a cubit arm in armor in bend, issuing...security reasons, no statistics have been Included for those types of recon- naissance aircraft currently assigned. The text was prepared by Mr. J. C...Hopkins who was aided by Mr. Sheldon A. Goldberg, Command Archivist, who critically reviewed the text and selected the photographs. Special

Assessing statistical differences between parameters estimates in Partial Least Squares path modeling.

PubMed

Rodríguez-Entrena, Macario; Schuberth, Florian; Gelhard, Carsten

2018-01-01

Structural equation modeling using partial least squares (PLS-SEM) has become a main-stream modeling approach in various disciplines. Nevertheless, prior literature still lacks a practical guidance on how to properly test for differences between parameter estimates. Whereas existing techniques such as parametric and non-parametric approaches in PLS multi-group analysis solely allow to assess differences between parameters that are estimated for different subpopulations, the study at hand introduces a technique that allows to also assess whether two parameter estimates that are derived from the same sample are statistically different. To illustrate this advancement to PLS-SEM, we particularly refer to a reduced version of the well-established technology acceptance model.

[Practical aspects regarding sample size in clinical research].

PubMed

Vega Ramos, B; Peraza Yanes, O; Herrera Correa, G; Saldívar Toraya, S

1996-01-01

The knowledge of the right sample size let us to be sure if the published results in medical papers had a suitable design and a proper conclusion according to the statistics analysis. To estimate the sample size we must consider the type I error, type II error, variance, the size of the effect, significance and power of the test. To decide what kind of mathematics formula will be used, we must define what kind of study we have, it means if its a prevalence study, a means values one or a comparative one. In this paper we explain some basic topics of statistics and we describe four simple samples of estimation of sample size.

Analyzing self-controlled case series data when case confirmation rates are estimated from an internal validation sample.

PubMed

Xu, Stanley; Clarke, Christina L; Newcomer, Sophia R; Daley, Matthew F; Glanz, Jason M

2018-05-16

Vaccine safety studies are often electronic health record (EHR)-based observational studies. These studies often face significant methodological challenges, including confounding and misclassification of adverse event. Vaccine safety researchers use self-controlled case series (SCCS) study design to handle confounding effect and employ medical chart review to ascertain cases that are identified using EHR data. However, for common adverse events, limited resources often make it impossible to adjudicate all adverse events observed in electronic data. In this paper, we considered four approaches for analyzing SCCS data with confirmation rates estimated from an internal validation sample: (1) observed cases, (2) confirmed cases only, (3) known confirmation rate, and (4) multiple imputation (MI). We conducted a simulation study to evaluate these four approaches using type I error rates, percent bias, and empirical power. Our simulation results suggest that when misclassification of adverse events is present, approaches such as observed cases, confirmed case only, and known confirmation rate may inflate the type I error, yield biased point estimates, and affect statistical power. The multiple imputation approach considers the uncertainty of estimated confirmation rates from an internal validation sample, yields a proper type I error rate, largely unbiased point estimate, proper variance estimate, and statistical power. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Application of Linear Mixed-Effects Models in Human Neuroscience Research: A Comparison with Pearson Correlation in Two Auditory Electrophysiology Studies.

PubMed

Koerner, Tess K; Zhang, Yang

2017-02-27

Neurophysiological studies are often designed to examine relationships between measures from different testing conditions, time points, or analysis techniques within the same group of participants. Appropriate statistical techniques that can take into account repeated measures and multivariate predictor variables are integral and essential to successful data analysis and interpretation. This work implements and compares conventional Pearson correlations and linear mixed-effects (LME) regression models using data from two recently published auditory electrophysiology studies. For the specific research questions in both studies, the Pearson correlation test is inappropriate for determining strengths between the behavioral responses for speech-in-noise recognition and the multiple neurophysiological measures as the neural responses across listening conditions were simply treated as independent measures. In contrast, the LME models allow a systematic approach to incorporate both fixed-effect and random-effect terms to deal with the categorical grouping factor of listening conditions, between-subject baseline differences in the multiple measures, and the correlational structure among the predictor variables. Together, the comparative data demonstrate the advantages as well as the necessity to apply mixed-effects models to properly account for the built-in relationships among the multiple predictor variables, which has important implications for proper statistical modeling and interpretation of human behavior in terms of neural correlates and biomarkers.

Proper joint analysis of summary association statistics requires the adjustment of heterogeneity in SNP coverage pattern.

PubMed

Zhang, Han; Wheeler, William; Song, Lei; Yu, Kai

2017-07-07

As meta-analysis results published by consortia of genome-wide association studies (GWASs) become increasingly available, many association summary statistics-based multi-locus tests have been developed to jointly evaluate multiple single-nucleotide polymorphisms (SNPs) to reveal novel genetic architectures of various complex traits. The validity of these approaches relies on the accurate estimate of z-score correlations at considered SNPs, which in turn requires knowledge on the set of SNPs assessed by each study participating in the meta-analysis. However, this exact SNP coverage information is usually unavailable from the meta-analysis results published by GWAS consortia. In the absence of the coverage information, researchers typically estimate the z-score correlations by making oversimplified coverage assumptions. We show through real studies that such a practice can generate highly inflated type I errors, and we demonstrate the proper way to incorporate correct coverage information into multi-locus analyses. We advocate that consortia should make SNP coverage information available when posting their meta-analysis results, and that investigators who develop analytic tools for joint analyses based on summary data should pay attention to the variation in SNP coverage and adjust for it appropriately. Published by Oxford University Press 2017. This work is written by US Government employees and is in the public domain in the US.

Enhancing the detection of barcoded reads in high throughput DNA sequencing data by controlling the false discovery rate.

PubMed

Buschmann, Tilo; Zhang, Rong; Brash, Douglas E; Bystrykh, Leonid V

2014-08-07

DNA barcodes are short unique sequences used to label DNA or RNA-derived samples in multiplexed deep sequencing experiments. During the demultiplexing step, barcodes must be detected and their position identified. In some cases (e.g., with PacBio SMRT), the position of the barcode and DNA context is not well defined. Many reads start inside the genomic insert so that adjacent primers might be missed. The matter is further complicated by coincidental similarities between barcode sequences and reference DNA. Therefore, a robust strategy is required in order to detect barcoded reads and avoid a large number of false positives or negatives.For mass inference problems such as this one, false discovery rate (FDR) methods are powerful and balanced solutions. Since existing FDR methods cannot be applied to this particular problem, we present an adapted FDR method that is suitable for the detection of barcoded reads as well as suggest possible improvements. In our analysis, barcode sequences showed high rates of coincidental similarities with the Mus musculus reference DNA. This problem became more acute when the length of the barcode sequence decreased and the number of barcodes in the set increased. The method presented in this paper controls the tail area-based false discovery rate to distinguish between barcoded and unbarcoded reads. This method helps to establish the highest acceptable minimal distance between reads and barcode sequences. In a proof of concept experiment we correctly detected barcodes in 83% of the reads with a precision of 89%. Sensitivity improved to 99% at 99% precision when the adjacent primer sequence was incorporated in the analysis. The analysis was further improved using a paired end strategy. Following an analysis of the data for sequence variants induced in the Atp1a1 gene of C57BL/6 murine melanocytes by ultraviolet light and conferring resistance to ouabain, we found no evidence of cross-contamination of DNA material between samples. Our method offers a proper quantitative treatment of the problem of detecting barcoded reads in a noisy sequencing environment. It is based on the false discovery rate statistics that allows a proper trade-off between sensitivity and precision to be chosen.

Using Bona Adaptation to Improve Accent Defects as a Voice Training Method

ERIC Educational Resources Information Center

Aycan, Kivanc

2017-01-01

Purpose: In this research, it is observed that if solfeggio syllables, consonants, and vowels are spoken properly, voice intensity (accent), duration, pitch (high pitch-low pitch) and intonation (the ability to carry a musical voice) related to proper pitch level. In this study, it is observed that rhythmic structures do not form without…

The Evaluation of the Performed Activities According to ELVES Method

ERIC Educational Resources Information Center

Erdem, Aliye

2018-01-01

Listening habit has an important share in the individual perceiving his/her environment and the world properly and complying with the social environment he/she lives. Because listening is an important skill which enables the individual to use the communication skills he/she learned both at school and out of school properly and to understand…

Studies on the psychosomatic functioning of ill-health according to Eastern and Western medicine. 1. Visual observation of the sublingual vein for early detection of vital energy stagnation and blood stasis.

PubMed

Takeichi, M; Sato, T

1999-01-01

Computer-assisted image analyses were performed on the tongue color of 95 medical students without previous history of blood stasis-related condition to clarify the mutual relationship of the color of the tongue proper, the coating, and sublingual vein. The location of the measurement for the tongue proper was the underside of the tongue, and location of the measurement for the tongue coating was the upper surface of the tongue. A linear correlation analysis showed a correlation for each of the different positions for the non-normalized red value and normalized blue value. This analysis also demonstrated a statistically-significant relationship between the tongue proper and the sublingual vein using Red-Green-Blue components and normalized Red-Green-Blue components (r = +0.670 - 0.817, p < 0.0001). The most significant correlation between the tongue proper and the sublingual vein was the normalized red value and the normalized Red-Green-Blue values for minimizing the range of the standard error of the mean (r = +0.745, p < 0.0001), although non-normalized blue had the highest correlation coefficient. Therefore, it seems reasonable to select those normalized red values for the comparison in the tongue color analysis. Correlation of the color between the sublingual vein and the tongue proper strongly suggests that inspection with the naked eye of the sublingual vein is useful for the early detection of vital energy stagnation and blood stasis. Also, because of its close relation to sustained chronic stress, changes in the sublingual vein might be available as one physiological parameter of a stress reaction.

A Multi-Survey Approach to White Dwarf Discovery

DTIC Science & Technology

2012-04-01

LSPM-North), the Two Micron All Sky Survey ( 2MASS ), and the USNO-B1.0 catalog, we use a succession of methods to isolate white dwarf (WD) candidates...including SDSS, the Two Micron All Sky Survey ( 2MASS ; Skrutskie et al. 2006), USNO-B1.0 (Monet et al. 2003), and the proper motion survey of Lépine & Shara...Shara Proper Motion North Catalog (LSPM-North), the Two Micron All Sky Survey ( 2MASS ), and the USNO-B1.0 catalog, we use a succession of methods to

Asteroid families in the Cybele and Hungaria groups

NASA Astrophysics Data System (ADS)

Vinogradova, T.; Shor, V.

2014-07-01

Asteroid families are fragments of some disrupted parent bodies. Planetary perturbations force the primarily close orbits to evolve. One of the main features of the orbit evolution is the long-period variation of the osculating elements, such as the inclination and eccentricity. Proper elements are computed by elimination of short- and long-period perturbations, and, practically, they do not change with time. Therefore, proper elements are important for family-identification procedures. The techniques of proper-element computation have improved over time. More and more accurate dynamical theories are developed. Contrastingly, in this work, an empirical method is proposed for proper-element calculations. The long-term variations of osculating elements manifest themselves very clearly in the distributions of pairs: inclination and longitude of ascending node; eccentricity and longitude of perihelion in the corresponding planes. Both of these dependencies have a nearly sinusoidal form for most asteroid orbits with regular motion of node and perihelion. If these angular parameters librate, then the sinusoids transform to some closed curve. Hence, it is possible to obtain forced elements, as parameters of curves specified above. The proper elements can be calculated by an elimination of the forced ones. The method allows to obtain the proper elements in any region, if there is a sufficient number of asteroids. This fact and the simplicity of the calculations are advantages of the empirical method. The derived proper elements include the short-period perturbations, but their accuracy is sufficient to search for asteroid families. The special techniques have been developed for the identification of the families, but over a long time large discrepancies took place between the lists of families derived by different authors. As late as 1980, a list of 30 reliable families was formed. And now the list by D. Nesvorny includes about 80 robust families. To date, only two families have been found in the most outer part of the main asteroid belt or the Cybele group: Sylvia and Ulla. And the Hungaria group in the most inner part of the belt has always been considered as one family. In this work, the proper elements were calculated by the empirical method for all multi-opposition asteroids in these two zones. As the source of the initial osculating elements, the MPC catalogue (version Feb. 2014) was used. Due to the large set of proper elements used in our work, the families are apparent more clearly. An approach similar to the hierarchical clustering method (HCM) was used for the identification of the families. As a result, five additional families have been found in the Cybele region, associated with (121) Hermione, (643) Scheherezade, (1028) Lydina, (3141) Buchar, and (522) Helga. The small Helga family, including 15 members, is the family in the main belt (3.6--3.7 au) most distant from the Sun. Due to the isolation of this family, its identification is very reliable. As to the Hungaria region, two low-density families have been found additionally: (1453) Fennia and (3854) George. They have inclinations slightly greater than that of the Hungaria family (from 24 to 26 degrees). In contradiction to the predominant C-type of the Hungaria family asteroids, the taxonomy of these families is represented mainly by the S and L types. Most likely, these families are two parts of a single ancient family.

Efficacy testing of cosmetic products. A proposal to the European Community by the Danish Environmental Protection Agency, Ministry of Environment and Energy.

PubMed

Serup, J

2001-08-01

Regulations for cosmetic products primarily address safety of the products that may be used by large populations of healthy consumers. Requirements for documentation of efficacy claims are only fragmentary. This synopsis aims to review and conclude a set of standards that may be acceptable to the European Community, and the cosmetic industry, as a legal standard for efficacy documentation in Europe in the future. Ethical, formal, experimental, statistical and other aspects of efficacy testing are described, including validation, quality control and assurance. The importance of user relevant clinical end points, a controlled randomized trial design and evidence-based cosmetic product documentation, validation of methods, statistical power estimation and proper data handling, reporting and archiving is emphasized. The main principles of the International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) good clinical practice (GCP) should be followed by the cosmetics industry in a spirit of good documentation standard and scientific soundness, but full GCP is not considered mandatory in the field of cosmetics. Documentation by validated bio-instrumental methods may be acceptable, but efficacy documentation based on information about raw materials, reference to literature and laboratory experiments are only acceptable in exceptional cases. Principles for efficacy substantiation of cosmetic products in Europe, as described in this synopsis, are officially proposed by the Danish Ministry of Environment and Energy to the European Community as a basis for an amendment to the Cosmetics Directive or otherwise implemented as a European Community regulation.

Discrete wavelet-aided delineation of PCG signal events via analysis of an area curve length-based decision statistic.

PubMed

Homaeinezhad, M R; Atyabi, S A; Daneshvar, E; Ghaffari, A; Tahmasebi, M

2010-12-01

The aim of this study is to describe a robust unified framework for segmentation of the phonocardiogram (PCG) signal sounds based on the false-alarm probability (FAP) bounded segmentation of a properly calculated detection measure. To this end, first the original PCG signal is appropriately pre-processed and then, a fixed sample size sliding window is moved on the pre-processed signal. In each slid, the area under the excerpted segment is multiplied by its curve-length to generate the Area Curve Length (ACL) metric to be used as the segmentation decision statistic (DS). Afterwards, histogram parameters of the nonlinearly enhanced DS metric are used for regulation of the α-level Neyman-Pearson classifier for FAP-bounded delineation of the PCG events. The proposed method was applied to all 85 records of Nursing Student Heart Sounds database (NSHSDB) including stenosis, insufficiency, regurgitation, gallop, septal defect, split sound, rumble, murmur, clicks, friction rub and snap disorders with different sampling frequencies. Also, the method was applied to the records obtained from an electronic stethoscope board designed for fulfillment of this study in the presence of high-level power-line noise and external disturbing sounds and as the results, no false positive (FP) or false negative (FN) errors were detected. High noise robustness, acceptable detection-segmentation accuracy of PCG events in various cardiac system conditions, and having no parameters dependency to the acquisition sampling frequency can be mentioned as the principal virtues and abilities of the proposed ACL-based PCG events detection-segmentation algorithm.

Classification of HCV and HIV-1 Sequences with the Branching Index

PubMed Central

Hraber, Peter; Kuiken, Carla; Waugh, Mark; Geer, Shaun; Bruno, William J.; Leitner, Thomas

2009-01-01

SUMMARY Classification of viral sequences should be fast, objective, accurate, and reproducible. Most methods that classify sequences use either pairwise distances or phylogenetic relations, but cannot discern when a sequence is unclassifiable. The branching index (BI) combines distance and phylogeny methods to compute a ratio that quantifies how closely a query sequence clusters with a subtype clade. In the hypothesis-testing framework of statistical inference, the BI is compared with a threshold to test whether sufficient evidence exists for the query sequence to be classified among known sequences. If above the threshold, the null hypothesis of no support for the subtype relation is rejected and the sequence is taken as belonging to the subtype clade with which it clusters on the tree. This study evaluates statistical properties of the branching index for subtype classification in HCV and HIV-1. Pairs of BI values with known positive and negative test results were computed from 10,000 random fragments of reference alignments. Sampled fragments were of sufficient length to contain phylogenetic signal that groups reference sequences together properly into subtype clades. For HCV, a threshold BI of 0.71 yields 95.1% agreement with reference subtypes, with equal false positive and false negative rates. For HIV-1, a threshold of 0.66 yields 93.5% agreement. Higher thresholds can be used where lower false positive rates are required. In synthetic recombinants, regions without breakpoints are recognized accurately; regions with breakpoints do not uniquely represent any known subtype. Web-based services for viral subtype classification with the branching index are available online. PMID:18753218

On the correct implementation of Fermi-Dirac statistics and electron trapping in nonlinear electrostatic plane wave propagation in collisionless plasmas

NASA Astrophysics Data System (ADS)

Schamel, Hans; Eliasson, Bengt

2016-05-01

Quantum statistics and electron trapping have a decisive influence on the propagation characteristics of coherent stationary electrostatic waves. The description of these strictly nonlinear structures, which are of electron hole type and violate linear Vlasov theory due to the particle trapping at any excitation amplitude, is obtained by a correct reduction of the three-dimensional Fermi-Dirac distribution function to one dimension and by a proper incorporation of trapping. For small but finite amplitudes, the holes become of cnoidal wave type and the electron density is shown to be described by a ϕ ( x ) 1 / 2 rather than a ϕ ( x ) expansion, where ϕ ( x ) is the electrostatic potential. The general coefficients are presented for a degenerate plasma as well as the quantum statistical analogue to these steady state coherent structures, including the shape of ϕ ( x ) and the nonlinear dispersion relation, which describes their phase velocity.

Investigation on improved infrared image detail enhancement algorithm based on adaptive histogram statistical stretching and gradient filtering

NASA Astrophysics Data System (ADS)

Zeng, Bangze; Zhu, Youpan; Li, Zemin; Hu, Dechao; Luo, Lin; Zhao, Deli; Huang, Juan

2014-11-01

Duo to infrared image with low contrast, big noise and unclear visual effect, target is very difficult to observed and identified. This paper presents an improved infrared image detail enhancement algorithm based on adaptive histogram statistical stretching and gradient filtering (AHSS-GF). Based on the fact that the human eyes are very sensitive to the edges and lines, the author proposed to extract the details and textures by using the gradient filtering. New histogram could be acquired by calculating the sum of original histogram based on fixed window. With the minimum value for cut-off point, author carried on histogram statistical stretching. After the proper weights given to the details and background, the detail-enhanced results could be acquired finally. The results indicate image contrast could be improved and the details and textures could be enhanced effectively as well.

Electron Waiting Times in Mesoscopic Conductors

NASA Astrophysics Data System (ADS)

Albert, Mathias; Haack, Géraldine; Flindt, Christian; Büttiker, Markus

2012-05-01

Electron transport in mesoscopic conductors has traditionally involved investigations of the mean current and the fluctuations of the current. A complementary view on charge transport is provided by the distribution of waiting times between charge carriers, but a proper theoretical framework for coherent electronic systems has so far been lacking. Here we develop a quantum theory of electron waiting times in mesoscopic conductors expressed by a compact determinant formula. We illustrate our methodology by calculating the waiting time distribution for a quantum point contact and find a crossover from Wigner-Dyson statistics at full transmission to Poisson statistics close to pinch-off. Even when the low-frequency transport is noiseless, the electrons are not equally spaced in time due to their inherent wave nature. We discuss the implications for renewal theory in mesoscopic systems and point out several analogies with level spacing statistics and random matrix theory.

Impact of parental relationships in maximum lod score affected sib-pair method.

PubMed

Leutenegger, Anne-Louise; Génin, Emmanuelle; Thompson, Elizabeth A; Clerget-Darpoux, Françoise

2002-11-01

Many studies are done in small isolated populations and populations where marriages between relatives are encouraged. In this paper, we point out some problems with applying the maximum lod score (MLS) method (Risch, [1990] Am. J. Hum. Genet. 46:242-253) in these populations where relationships exist between the two parents of the affected sib-pairs. Characterizing the parental relationships by the kinship coefficient between the parents (f), the maternal inbreeding coefficient (alpha(m), and the paternal inbreeding coefficient (alpha(p)), we explored the relationship between the identity by descent (IBD) vector expected under the null hypothesis of no linkage and these quantities. We find that the expected IBD vector is no longer (0.25, 0.5, 0.25) when f, alpha(m), and alpha(p) differ from zero. In addition, the expected IBD vector does not always follow the triangle constraints recommended by Holmans ([1993] Am. J. Hum. Genet. 52:362-374). So the classically used MLS statistic needs to be adapted to the presence of parental relationships. We modified the software GENEHUNTER (Kruglyak et al. [1996] Am. J. Hum. Genet. 58: 1347-1363) to do so. Indeed, the current version of the software does not compute the likelihood properly under the null hypothesis. We studied the adapted statistic by simulating data on three different family structures: (1) parents are double first cousins (f=0.125, alpha(m)=alpha(p)=0), (2) each parent is the offspring of first cousins (f=0, alpha(m)=alpha(p)=0.0625), and (3) parents are related as in the pedigree from Goddard et al. ([1996] Am. J. Hum. Genet. 58:1286-1302) (f=0.109, alpha(m)=alpha(p)=0.0625). The appropriate threshold needs to be derived for each case in order to get the correct type I error. And using the classical statistic in the presence of both parental kinship and parental inbreeding almost always leads to false conclusions. Copyright 2002 Wiley-Liss, Inc.

Spinfoam cosmology with the proper vertex amplitude

NASA Astrophysics Data System (ADS)

Vilensky, Ilya

2017-11-01

The proper vertex amplitude is derived from the Engle-Pereira-Rovelli-Livine vertex by restricting to a single gravitational sector in order to achieve the correct semi-classical behaviour. We apply the proper vertex to calculate a cosmological transition amplitude that can be viewed as the Hartle-Hawking wavefunction. To perform this calculation we deduce the integral form of the proper vertex and use extended stationary phase methods to estimate the large-volume limit. We show that the resulting amplitude satisfies an operator constraint whose classical analogue is the Hamiltonian constraint of the Friedmann-Robertson-Walker cosmology. We find that the constraint dynamically selects the relevant family of coherent states and demonstrate a similar dynamic selection in standard quantum mechanics. We investigate the effects of dynamical selection on long-range correlations.

Contributions of adipose tissue architectural and tensile properties toward defining healthy and unhealthy obesity.

PubMed

Lackey, Denise E; Burk, David H; Ali, Mohamed R; Mostaedi, Rouzbeh; Smith, William H; Park, Jiyoung; Scherer, Philipp E; Seay, Shundra A; McCoin, Colin S; Bonaldo, Paolo; Adams, Sean H

2014-02-01

The extracellular matrix (ECM) plays an important role in the maintenance of white adipose tissue (WAT) architecture and function, and proper ECM remodeling is critical to support WAT malleability to accommodate changes in energy storage needs. Obesity and adipocyte hypertrophy place a strain on the ECM remodeling machinery, which may promote disordered ECM and altered tissue integrity and could promote proinflammatory and cell stress signals. To explore these questions, new methods were developed to quantify omental and subcutaneous WAT tensile strength and WAT collagen content by three-dimensional confocal imaging, using collagen VI knockout mice as a methods validation tool. These methods, combined with comprehensive measurement of WAT ECM proteolytic enzymes, transcript, and blood analyte analyses, were used to identify unique pathophenotypes of metabolic syndrome and type 2 diabetes mellitus in obese women, using multivariate statistical modeling and univariate comparisons with weight-matched healthy obese individuals. In addition to the expected differences in inflammation and glycemic control, approximately 20 ECM-related factors, including omental tensile strength, collagen, and enzyme transcripts, helped discriminate metabolically compromised obesity. This is consistent with the hypothesis that WAT ECM physiology is intimately linked to metabolic health in obese humans, and the studies provide new tools to explore this relationship.

Improved estimation of parametric images of cerebral glucose metabolic rate from dynamic FDG-PET using volume-wise principle component analysis

NASA Astrophysics Data System (ADS)

Dai, Xiaoqian; Tian, Jie; Chen, Zhe

2010-03-01

Parametric images can represent both spatial distribution and quantification of the biological and physiological parameters of tracer kinetics. The linear least square (LLS) method is a well-estimated linear regression method for generating parametric images by fitting compartment models with good computational efficiency. However, bias exists in LLS-based parameter estimates, owing to the noise present in tissue time activity curves (TTACs) that propagates as correlated error in the LLS linearized equations. To address this problem, a volume-wise principal component analysis (PCA) based method is proposed. In this method, firstly dynamic PET data are properly pre-transformed to standardize noise variance as PCA is a data driven technique and can not itself separate signals from noise. Secondly, the volume-wise PCA is applied on PET data. The signals can be mostly represented by the first few principle components (PC) and the noise is left in the subsequent PCs. Then the noise-reduced data are obtained using the first few PCs by applying 'inverse PCA'. It should also be transformed back according to the pre-transformation method used in the first step to maintain the scale of the original data set. Finally, the obtained new data set is used to generate parametric images using the linear least squares (LLS) estimation method. Compared with other noise-removal method, the proposed method can achieve high statistical reliability in the generated parametric images. The effectiveness of the method is demonstrated both with computer simulation and with clinical dynamic FDG PET study.