An opportunity cost approach to sample size calculation in cost-effectiveness analysis.

PubMed

Gafni, A; Walter, S D; Birch, S; Sendi, P

2008-01-01

The inclusion of economic evaluations as part of clinical trials has led to concerns about the adequacy of trial sample size to support such analysis. The analytical tool of cost-effectiveness analysis is the incremental cost-effectiveness ratio (ICER), which is compared with a threshold value (lambda) as a method to determine the efficiency of a health-care intervention. Accordingly, many of the methods suggested to calculating the sample size requirements for the economic component of clinical trials are based on the properties of the ICER. However, use of the ICER and a threshold value as a basis for determining efficiency has been shown to be inconsistent with the economic concept of opportunity cost. As a result, the validity of the ICER-based approaches to sample size calculations can be challenged. Alternative methods for determining improvements in efficiency have been presented in the literature that does not depend upon ICER values. In this paper, we develop an opportunity cost approach to calculating sample size for economic evaluations alongside clinical trials, and illustrate the approach using a numerical example. We compare the sample size requirement of the opportunity cost method with the ICER threshold method. In general, either method may yield the larger required sample size. However, the opportunity cost approach, although simple to use, has additional data requirements. We believe that the additional data requirements represent a small price to pay for being able to perform an analysis consistent with both concept of opportunity cost and the problem faced by decision makers. Copyright (c) 2007 John Wiley & Sons, Ltd.

Unequal cluster sizes in stepped-wedge cluster randomised trials: a systematic review

PubMed Central

Morris, Tom; Gray, Laura

2017-01-01

Objectives To investigate the extent to which cluster sizes vary in stepped-wedge cluster randomised trials (SW-CRT) and whether any variability is accounted for during the sample size calculation and analysis of these trials. Setting Any, not limited to healthcare settings. Participants Any taking part in an SW-CRT published up to March 2016. Primary and secondary outcome measures The primary outcome is the variability in cluster sizes, measured by the coefficient of variation (CV) in cluster size. Secondary outcomes include the difference between the cluster sizes assumed during the sample size calculation and those observed during the trial, any reported variability in cluster sizes and whether the methods of sample size calculation and methods of analysis accounted for any variability in cluster sizes. Results Of the 101 included SW-CRTs, 48% mentioned that the included clusters were known to vary in size, yet only 13% of these accounted for this during the calculation of the sample size. However, 69% of the trials did use a method of analysis appropriate for when clusters vary in size. Full trial reports were available for 53 trials. The CV was calculated for 23 of these: the median CV was 0.41 (IQR: 0.22–0.52). Actual cluster sizes could be compared with those assumed during the sample size calculation for 14 (26%) of the trial reports; the cluster sizes were between 29% and 480% of that which had been assumed. Conclusions Cluster sizes often vary in SW-CRTs. Reporting of SW-CRTs also remains suboptimal. The effect of unequal cluster sizes on the statistical power of SW-CRTs needs further exploration and methods appropriate to studies with unequal cluster sizes need to be employed. PMID:29146637

Sampling strategies for estimating brook trout effective population size

Treesearch

Andrew R. Whiteley; Jason A. Coombs; Mark Hudy; Zachary Robinson; Keith H. Nislow; Benjamin H. Letcher

2012-01-01

The influence of sampling strategy on estimates of effective population size (Ne) from single-sample genetic methods has not been rigorously examined, though these methods are increasingly used. For headwater salmonids, spatially close kin association among age-0 individuals suggests that sampling strategy (number of individuals and location from...

Distribution of the two-sample t-test statistic following blinded sample size re-estimation.

PubMed

Lu, Kaifeng

2016-05-01

We consider the blinded sample size re-estimation based on the simple one-sample variance estimator at an interim analysis. We characterize the exact distribution of the standard two-sample t-test statistic at the final analysis. We describe a simulation algorithm for the evaluation of the probability of rejecting the null hypothesis at given treatment effect. We compare the blinded sample size re-estimation method with two unblinded methods with respect to the empirical type I error, the empirical power, and the empirical distribution of the standard deviation estimator and final sample size. We characterize the type I error inflation across the range of standardized non-inferiority margin for non-inferiority trials, and derive the adjusted significance level to ensure type I error control for given sample size of the internal pilot study. We show that the adjusted significance level increases as the sample size of the internal pilot study increases. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Sample size determination for equivalence assessment with multiple endpoints.

PubMed

Sun, Anna; Dong, Xiaoyu; Tsong, Yi

2014-01-01

Equivalence assessment between a reference and test treatment is often conducted by two one-sided tests (TOST). The corresponding power function and sample size determination can be derived from a joint distribution of the sample mean and sample variance. When an equivalence trial is designed with multiple endpoints, it often involves several sets of two one-sided tests. A naive approach for sample size determination in this case would select the largest sample size required for each endpoint. However, such a method ignores the correlation among endpoints. With the objective to reject all endpoints and when the endpoints are uncorrelated, the power function is the production of all power functions for individual endpoints. With correlated endpoints, the sample size and power should be adjusted for such a correlation. In this article, we propose the exact power function for the equivalence test with multiple endpoints adjusted for correlation under both crossover and parallel designs. We further discuss the differences in sample size for the naive method without and with correlation adjusted methods and illustrate with an in vivo bioequivalence crossover study with area under the curve (AUC) and maximum concentration (Cmax) as the two endpoints.

Confidence intervals for the population mean tailored to small sample sizes, with applications to survey sampling.

PubMed

Rosenblum, Michael A; Laan, Mark J van der

2009-01-07

The validity of standard confidence intervals constructed in survey sampling is based on the central limit theorem. For small sample sizes, the central limit theorem may give a poor approximation, resulting in confidence intervals that are misleading. We discuss this issue and propose methods for constructing confidence intervals for the population mean tailored to small sample sizes. We present a simple approach for constructing confidence intervals for the population mean based on tail bounds for the sample mean that are correct for all sample sizes. Bernstein's inequality provides one such tail bound. The resulting confidence intervals have guaranteed coverage probability under much weaker assumptions than are required for standard methods. A drawback of this approach, as we show, is that these confidence intervals are often quite wide. In response to this, we present a method for constructing much narrower confidence intervals, which are better suited for practical applications, and that are still more robust than confidence intervals based on standard methods, when dealing with small sample sizes. We show how to extend our approaches to much more general estimation problems than estimating the sample mean. We describe how these methods can be used to obtain more reliable confidence intervals in survey sampling. As a concrete example, we construct confidence intervals using our methods for the number of violent deaths between March 2003 and July 2006 in Iraq, based on data from the study "Mortality after the 2003 invasion of Iraq: A cross sectional cluster sample survey," by Burnham et al. (2006).

On sample size of the kruskal-wallis test with application to a mouse peritoneal cavity study.

PubMed

Fan, Chunpeng; Zhang, Donghui; Zhang, Cun-Hui

2011-03-01

As the nonparametric generalization of the one-way analysis of variance model, the Kruskal-Wallis test applies when the goal is to test the difference between multiple samples and the underlying population distributions are nonnormal or unknown. Although the Kruskal-Wallis test has been widely used for data analysis, power and sample size methods for this test have been investigated to a much lesser extent. This article proposes new power and sample size calculation methods for the Kruskal-Wallis test based on the pilot study in either a completely nonparametric model or a semiparametric location model. No assumption is made on the shape of the underlying population distributions. Simulation results show that, in terms of sample size calculation for the Kruskal-Wallis test, the proposed methods are more reliable and preferable to some more traditional methods. A mouse peritoneal cavity study is used to demonstrate the application of the methods. © 2010, The International Biometric Society.

Poly (lactic-co-glycolic acid) particles prepared by microfluidics and conventional methods. Modulated particle size and rheology.

PubMed

Perez, Aurora; Hernández, Rebeca; Velasco, Diego; Voicu, Dan; Mijangos, Carmen

2015-03-01

Microfluidic techniques are expected to provide narrower particle size distribution than conventional methods for the preparation of poly (lactic-co-glycolic acid) (PLGA) microparticles. Besides, it is hypothesized that the particle size distribution of poly (lactic-co-glycolic acid) microparticles influences the settling behavior and rheological properties of its aqueous dispersions. For the preparation of PLGA particles, two different methods, microfluidic and conventional oil-in-water emulsification methods were employed. The particle size and particle size distribution of PLGA particles prepared by microfluidics were studied as a function of the flow rate of the organic phase while particles prepared by conventional methods were studied as a function of stirring rate. In order to study the stability and structural organization of colloidal dispersions, settling experiments and oscillatory rheological measurements were carried out on aqueous dispersions of PLGA particles with different particle size distributions. Microfluidics technique allowed the control of size and size distribution of the droplets formed in the process of emulsification. This resulted in a narrower particle size distribution for samples prepared by MF with respect to samples prepared by conventional methods. Polydisperse samples showed a larger tendency to aggregate, thus confirming the advantages of microfluidics over conventional methods, especially if biomedical applications are envisaged. Copyright © 2014 Elsevier Inc. All rights reserved.

Generating Random Samples of a Given Size Using Social Security Numbers.

ERIC Educational Resources Information Center

Erickson, Richard C.; Brauchle, Paul E.

1984-01-01

The purposes of this article are (1) to present a method by which social security numbers may be used to draw cluster samples of a predetermined size and (2) to describe procedures used to validate this method of drawing random samples. (JOW)

Caution regarding the choice of standard deviations to guide sample size calculations in clinical trials.

PubMed

Chen, Henian; Zhang, Nanhua; Lu, Xiaosun; Chen, Sophie

2013-08-01

The method used to determine choice of standard deviation (SD) is inadequately reported in clinical trials. Underestimations of the population SD may result in underpowered clinical trials. This study demonstrates how using the wrong method to determine population SD can lead to inaccurate sample sizes and underpowered studies, and offers recommendations to maximize the likelihood of achieving adequate statistical power. We review the practice of reporting sample size and its effect on the power of trials published in major journals. Simulated clinical trials were used to compare the effects of different methods of determining SD on power and sample size calculations. Prior to 1996, sample size calculations were reported in just 1%-42% of clinical trials. This proportion increased from 38% to 54% after the initial Consolidated Standards of Reporting Trials (CONSORT) was published in 1996, and from 64% to 95% after the revised CONSORT was published in 2001. Nevertheless, underpowered clinical trials are still common. Our simulated data showed that all minimal and 25th-percentile SDs fell below 44 (the population SD), regardless of sample size (from 5 to 50). For sample sizes 5 and 50, the minimum sample SDs underestimated the population SD by 90.7% and 29.3%, respectively. If only one sample was available, there was less than 50% chance that the actual power equaled or exceeded the planned power of 80% for detecting a median effect size (Cohen's d = 0.5) when using the sample SD to calculate the sample size. The proportions of studies with actual power of at least 80% were about 95%, 90%, 85%, and 80% when we used the larger SD, 80% upper confidence limit (UCL) of SD, 70% UCL of SD, and 60% UCL of SD to calculate the sample size, respectively. When more than one sample was available, the weighted average SD resulted in about 50% of trials being underpowered; the proportion of trials with power of 80% increased from 90% to 100% when the 75th percentile and the maximum SD from 10 samples were used. Greater sample size is needed to achieve a higher proportion of studies having actual power of 80%. This study only addressed sample size calculation for continuous outcome variables. We recommend using the 60% UCL of SD, maximum SD, 80th-percentile SD, and 75th-percentile SD to calculate sample size when 1 or 2 samples, 3 samples, 4-5 samples, and more than 5 samples of data are available, respectively. Using the sample SD or average SD to calculate sample size should be avoided.

An imbalance in cluster sizes does not lead to notable loss of power in cross-sectional, stepped-wedge cluster randomised trials with a continuous outcome.

PubMed

Kristunas, Caroline A; Smith, Karen L; Gray, Laura J

2017-03-07

The current methodology for sample size calculations for stepped-wedge cluster randomised trials (SW-CRTs) is based on the assumption of equal cluster sizes. However, as is often the case in cluster randomised trials (CRTs), the clusters in SW-CRTs are likely to vary in size, which in other designs of CRT leads to a reduction in power. The effect of an imbalance in cluster size on the power of SW-CRTs has not previously been reported, nor what an appropriate adjustment to the sample size calculation should be to allow for any imbalance. We aimed to assess the impact of an imbalance in cluster size on the power of a cross-sectional SW-CRT and recommend a method for calculating the sample size of a SW-CRT when there is an imbalance in cluster size. The effect of varying degrees of imbalance in cluster size on the power of SW-CRTs was investigated using simulations. The sample size was calculated using both the standard method and two proposed adjusted design effects (DEs), based on those suggested for CRTs with unequal cluster sizes. The data were analysed using generalised estimating equations with an exchangeable correlation matrix and robust standard errors. An imbalance in cluster size was not found to have a notable effect on the power of SW-CRTs. The two proposed adjusted DEs resulted in trials that were generally considerably over-powered. We recommend that the standard method of sample size calculation for SW-CRTs be used, provided that the assumptions of the method hold. However, it would be beneficial to investigate, through simulation, what effect the maximum likely amount of inequality in cluster sizes would be on the power of the trial and whether any inflation of the sample size would be required.

Sampling the structure and chemical order in assemblies of ferromagnetic nanoparticles by nuclear magnetic resonance

PubMed Central

Liu, Yuefeng; Luo, Jingjie; Shin, Yooleemi; Moldovan, Simona; Ersen, Ovidiu; Hébraud, Anne; Schlatter, Guy; Pham-Huu, Cuong; Meny, Christian

2016-01-01

Assemblies of nanoparticles are studied in many research fields from physics to medicine. However, as it is often difficult to produce mono-dispersed particles, investigating the key parameters enhancing their efficiency is blurred by wide size distributions. Indeed, near-field methods analyse a part of the sample that might not be representative of the full size distribution and macroscopic methods give average information including all particle sizes. Here, we introduce temperature differential ferromagnetic nuclear resonance spectra that allow sampling the crystallographic structure, the chemical composition and the chemical order of non-interacting ferromagnetic nanoparticles for specific size ranges within their size distribution. The method is applied to cobalt nanoparticles for catalysis and allows extracting the size effect from the crystallographic structure effect on their catalytic activity. It also allows sampling of the chemical composition and chemical order within the size distribution of alloyed nanoparticles and can thus be useful in many research fields. PMID:27156575

Simple, Defensible Sample Sizes Based on Cost Efficiency

PubMed Central

Bacchetti, Peter; McCulloch, Charles E.; Segal, Mark R.

2009-01-01

Summary The conventional approach of choosing sample size to provide 80% or greater power ignores the cost implications of different sample size choices. Costs, however, are often impossible for investigators and funders to ignore in actual practice. Here, we propose and justify a new approach for choosing sample size based on cost efficiency, the ratio of a study’s projected scientific and/or practical value to its total cost. By showing that a study’s projected value exhibits diminishing marginal returns as a function of increasing sample size for a wide variety of definitions of study value, we are able to develop two simple choices that can be defended as more cost efficient than any larger sample size. The first is to choose the sample size that minimizes the average cost per subject. The second is to choose sample size to minimize total cost divided by the square root of sample size. This latter method is theoretically more justifiable for innovative studies, but also performs reasonably well and has some justification in other cases. For example, if projected study value is assumed to be proportional to power at a specific alternative and total cost is a linear function of sample size, then this approach is guaranteed either to produce more than 90% power or to be more cost efficient than any sample size that does. These methods are easy to implement, based on reliable inputs, and well justified, so they should be regarded as acceptable alternatives to current conventional approaches. PMID:18482055

RnaSeqSampleSize: real data based sample size estimation for RNA sequencing.

PubMed

Zhao, Shilin; Li, Chung-I; Guo, Yan; Sheng, Quanhu; Shyr, Yu

2018-05-30

One of the most important and often neglected components of a successful RNA sequencing (RNA-Seq) experiment is sample size estimation. A few negative binomial model-based methods have been developed to estimate sample size based on the parameters of a single gene. However, thousands of genes are quantified and tested for differential expression simultaneously in RNA-Seq experiments. Thus, additional issues should be carefully addressed, including the false discovery rate for multiple statistic tests, widely distributed read counts and dispersions for different genes. To solve these issues, we developed a sample size and power estimation method named RnaSeqSampleSize, based on the distributions of gene average read counts and dispersions estimated from real RNA-seq data. Datasets from previous, similar experiments such as the Cancer Genome Atlas (TCGA) can be used as a point of reference. Read counts and their dispersions were estimated from the reference's distribution; using that information, we estimated and summarized the power and sample size. RnaSeqSampleSize is implemented in R language and can be installed from Bioconductor website. A user friendly web graphic interface is provided at http://cqs.mc.vanderbilt.edu/shiny/RnaSeqSampleSize/ . RnaSeqSampleSize provides a convenient and powerful way for power and sample size estimation for an RNAseq experiment. It is also equipped with several unique features, including estimation for interested genes or pathway, power curve visualization, and parameter optimization.

High-resolution, submicron particle size distribution analysis using gravitational-sweep sedimentation.

PubMed Central

Mächtle, W

1999-01-01

Sedimentation velocity is a powerful tool for the analysis of complex solutions of macromolecules. However, sample turbidity imposes an upper limit to the size of molecular complexes currently amenable to such analysis. Furthermore, the breadth of the particle size distribution, combined with possible variations in the density of different particles, makes it difficult to analyze extremely complex mixtures. These same problems are faced in the polymer industry, where dispersions of latices, pigments, lacquers, and emulsions must be characterized. There is a rich history of methods developed for the polymer industry finding use in the biochemical sciences. Two such methods are presented. These use analytical ultracentrifugation to determine the density and size distributions for submicron-sized particles. Both methods rely on Stokes' equations to estimate particle size and density, whereas turbidity, corrected using Mie's theory, provides the concentration measurement. The first method uses the sedimentation time in dispersion media of different densities to evaluate the particle density and size distribution. This method works provided the sample is chemically homogeneous. The second method splices together data gathered at different sample concentrations, thus permitting the high-resolution determination of the size distribution of particle diameters ranging from 10 to 3000 nm. By increasing the rotor speed exponentially from 0 to 40,000 rpm over a 1-h period, size distributions may be measured for extremely broadly distributed dispersions. Presented here is a short history of particle size distribution analysis using the ultracentrifuge, along with a description of the newest experimental methods. Several applications of the methods are provided that demonstrate the breadth of its utility, including extensions to samples containing nonspherical and chromophoric particles. PMID:9916040

Sample Size Determination for Regression Models Using Monte Carlo Methods in R

ERIC Educational Resources Information Center

Beaujean, A. Alexander

2014-01-01

A common question asked by researchers using regression models is, What sample size is needed for my study? While there are formulae to estimate sample sizes, their assumptions are often not met in the collected data. A more realistic approach to sample size determination requires more information such as the model of interest, strength of the…

Sample size considerations for paired experimental design with incomplete observations of continuous outcomes.

PubMed

Zhu, Hong; Xu, Xiaohan; Ahn, Chul

2017-01-01

Paired experimental design is widely used in clinical and health behavioral studies, where each study unit contributes a pair of observations. Investigators often encounter incomplete observations of paired outcomes in the data collected. Some study units contribute complete pairs of observations, while the others contribute either pre- or post-intervention observations. Statistical inference for paired experimental design with incomplete observations of continuous outcomes has been extensively studied in literature. However, sample size method for such study design is sparsely available. We derive a closed-form sample size formula based on the generalized estimating equation approach by treating the incomplete observations as missing data in a linear model. The proposed method properly accounts for the impact of mixed structure of observed data: a combination of paired and unpaired outcomes. The sample size formula is flexible to accommodate different missing patterns, magnitude of missingness, and correlation parameter values. We demonstrate that under complete observations, the proposed generalized estimating equation sample size estimate is the same as that based on the paired t-test. In the presence of missing data, the proposed method would lead to a more accurate sample size estimate comparing with the crude adjustment. Simulation studies are conducted to evaluate the finite-sample performance of the generalized estimating equation sample size formula. A real application example is presented for illustration.

A Scanning Transmission Electron Microscopy Method for Determining Manganese Composition in Welding Fume as a Function of Primary Particle Size

PubMed Central

Richman, Julie D.; Livi, Kenneth J.T.; Geyh, Alison S.

2011-01-01

Increasing evidence suggests that the physicochemical properties of inhaled nanoparticles influence the resulting toxicokinetics and toxicodynamics. This report presents a method using scanning transmission electron microscopy (STEM) to measure the Mn content throughout the primary particle size distribution of welding fume particle samples collected on filters for application in exposure and health research. Dark field images were collected to assess the primary particle size distribution and energy-dispersive X-ray and electron energy loss spectroscopy were performed for measurement of Mn composition as a function of primary particle size. A manual method incorporating imaging software was used to measure the primary particle diameter and to select an integration region for compositional analysis within primary particles throughout the size range. To explore the variation in the developed metric, the method was applied to 10 gas metal arc welding (GMAW) fume particle samples of mild steel that were collected under a variety of conditions. The range of Mn composition by particle size was −0.10 to 0.19 %/nm, where a positive estimate indicates greater relative abundance of Mn increasing with primary particle size and a negative estimate conversely indicates decreasing Mn content with size. However, the estimate was only statistically significant (p<0.05) in half of the samples (n=5), which all had a positive estimate. In the remaining samples, no significant trend was measured. Our findings indicate that the method is reproducible and that differences in the abundance of Mn by primary particle size among welding fume samples can be detected. PMID:21625364

A Scanning Transmission Electron Microscopy Method for Determining Manganese Composition in Welding Fume as a Function of Primary Particle Size.

PubMed

Richman, Julie D; Livi, Kenneth J T; Geyh, Alison S

2011-06-01

Increasing evidence suggests that the physicochemical properties of inhaled nanoparticles influence the resulting toxicokinetics and toxicodynamics. This report presents a method using scanning transmission electron microscopy (STEM) to measure the Mn content throughout the primary particle size distribution of welding fume particle samples collected on filters for application in exposure and health research. Dark field images were collected to assess the primary particle size distribution and energy-dispersive X-ray and electron energy loss spectroscopy were performed for measurement of Mn composition as a function of primary particle size. A manual method incorporating imaging software was used to measure the primary particle diameter and to select an integration region for compositional analysis within primary particles throughout the size range. To explore the variation in the developed metric, the method was applied to 10 gas metal arc welding (GMAW) fume particle samples of mild steel that were collected under a variety of conditions. The range of Mn composition by particle size was -0.10 to 0.19 %/nm, where a positive estimate indicates greater relative abundance of Mn increasing with primary particle size and a negative estimate conversely indicates decreasing Mn content with size. However, the estimate was only statistically significant (p<0.05) in half of the samples (n=5), which all had a positive estimate. In the remaining samples, no significant trend was measured. Our findings indicate that the method is reproducible and that differences in the abundance of Mn by primary particle size among welding fume samples can be detected.

Estimating the probability that the sample mean is within a desired fraction of the standard deviation of the true mean.

PubMed

Schillaci, Michael A; Schillaci, Mario E

2009-02-01

The use of small sample sizes in human and primate evolutionary research is commonplace. Estimating how well small samples represent the underlying population, however, is not commonplace. Because the accuracy of determinations of taxonomy, phylogeny, and evolutionary process are dependant upon how well the study sample represents the population of interest, characterizing the uncertainty, or potential error, associated with analyses of small sample sizes is essential. We present a method for estimating the probability that the sample mean is within a desired fraction of the standard deviation of the true mean using small (n<10) or very small (n < or = 5) sample sizes. This method can be used by researchers to determine post hoc the probability that their sample is a meaningful approximation of the population parameter. We tested the method using a large craniometric data set commonly used by researchers in the field. Given our results, we suggest that sample estimates of the population mean can be reasonable and meaningful even when based on small, and perhaps even very small, sample sizes.

Unequal cluster sizes in stepped-wedge cluster randomised trials: a systematic review.

PubMed

Kristunas, Caroline; Morris, Tom; Gray, Laura

2017-11-15

To investigate the extent to which cluster sizes vary in stepped-wedge cluster randomised trials (SW-CRT) and whether any variability is accounted for during the sample size calculation and analysis of these trials. Any, not limited to healthcare settings. Any taking part in an SW-CRT published up to March 2016. The primary outcome is the variability in cluster sizes, measured by the coefficient of variation (CV) in cluster size. Secondary outcomes include the difference between the cluster sizes assumed during the sample size calculation and those observed during the trial, any reported variability in cluster sizes and whether the methods of sample size calculation and methods of analysis accounted for any variability in cluster sizes. Of the 101 included SW-CRTs, 48% mentioned that the included clusters were known to vary in size, yet only 13% of these accounted for this during the calculation of the sample size. However, 69% of the trials did use a method of analysis appropriate for when clusters vary in size. Full trial reports were available for 53 trials. The CV was calculated for 23 of these: the median CV was 0.41 (IQR: 0.22-0.52). Actual cluster sizes could be compared with those assumed during the sample size calculation for 14 (26%) of the trial reports; the cluster sizes were between 29% and 480% of that which had been assumed. Cluster sizes often vary in SW-CRTs. Reporting of SW-CRTs also remains suboptimal. The effect of unequal cluster sizes on the statistical power of SW-CRTs needs further exploration and methods appropriate to studies with unequal cluster sizes need to be employed. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Sampling methods, dispersion patterns, and fixed precision sequential sampling plans for western flower thrips (Thysanoptera: Thripidae) and cotton fleahoppers (Hemiptera: Miridae) in cotton.

PubMed

Parajulee, M N; Shrestha, R B; Leser, J F

2006-04-01

A 2-yr field study was conducted to examine the effectiveness of two sampling methods (visual and plant washing techniques) for western flower thrips, Frankliniella occidentalis (Pergande), and five sampling methods (visual, beat bucket, drop cloth, sweep net, and vacuum) for cotton fleahopper, Pseudatomoscelis seriatus (Reuter), in Texas cotton, Gossypium hirsutum (L.), and to develop sequential sampling plans for each pest. The plant washing technique gave similar results to the visual method in detecting adult thrips, but the washing technique detected significantly higher number of thrips larvae compared with the visual sampling. Visual sampling detected the highest number of fleahoppers followed by beat bucket, drop cloth, vacuum, and sweep net sampling, with no significant difference in catch efficiency between vacuum and sweep net methods. However, based on fixed precision cost reliability, the sweep net sampling was the most cost-effective method followed by vacuum, beat bucket, drop cloth, and visual sampling. Taylor's Power Law analysis revealed that the field dispersion patterns of both thrips and fleahoppers were aggregated throughout the crop growing season. For thrips management decision based on visual sampling (0.25 precision), 15 plants were estimated to be the minimum sample size when the estimated population density was one thrips per plant, whereas the minimum sample size was nine plants when thrips density approached 10 thrips per plant. The minimum visual sample size for cotton fleahoppers was 16 plants when the density was one fleahopper per plant, but the sample size decreased rapidly with an increase in fleahopper density, requiring only four plants to be sampled when the density was 10 fleahoppers per plant. Sequential sampling plans were developed and validated with independent data for both thrips and cotton fleahoppers.

Sample size for post-marketing safety studies based on historical controls.

PubMed

Wu, Yu-te; Makuch, Robert W

2010-08-01

As part of a drug's entire life cycle, post-marketing studies are an important part in the identification of rare, serious adverse events. Recently, the US Food and Drug Administration (FDA) has begun to implement new post-marketing safety mandates as a consequence of increased emphasis on safety. The purpose of this research is to provide exact sample size formula for the proposed hybrid design, based on a two-group cohort study with incorporation of historical external data. Exact sample size formula based on the Poisson distribution is developed, because the detection of rare events is our outcome of interest. Performance of exact method is compared to its approximate large-sample theory counterpart. The proposed hybrid design requires a smaller sample size compared to the standard, two-group prospective study design. In addition, the exact method reduces the number of subjects required in the treatment group by up to 30% compared to the approximate method for the study scenarios examined. The proposed hybrid design satisfies the advantages and rationale of the two-group design with smaller sample sizes generally required. 2010 John Wiley & Sons, Ltd.

Accounting for missing data in the estimation of contemporary genetic effective population size (N(e) ).

PubMed

Peel, D; Waples, R S; Macbeth, G M; Do, C; Ovenden, J R

2013-03-01

Theoretical models are often applied to population genetic data sets without fully considering the effect of missing data. Researchers can deal with missing data by removing individuals that have failed to yield genotypes and/or by removing loci that have failed to yield allelic determinations, but despite their best efforts, most data sets still contain some missing data. As a consequence, realized sample size differs among loci, and this poses a problem for unbiased methods that must explicitly account for random sampling error. One commonly used solution for the calculation of contemporary effective population size (N(e) ) is to calculate the effective sample size as an unweighted mean or harmonic mean across loci. This is not ideal because it fails to account for the fact that loci with different numbers of alleles have different information content. Here we consider this problem for genetic estimators of contemporary effective population size (N(e) ). To evaluate bias and precision of several statistical approaches for dealing with missing data, we simulated populations with known N(e) and various degrees of missing data. Across all scenarios, one method of correcting for missing data (fixed-inverse variance-weighted harmonic mean) consistently performed the best for both single-sample and two-sample (temporal) methods of estimating N(e) and outperformed some methods currently in widespread use. The approach adopted here may be a starting point to adjust other population genetics methods that include per-locus sample size components. © 2012 Blackwell Publishing Ltd.

A pretreatment method for grain size analysis of red mudstones

NASA Astrophysics Data System (ADS)

Jiang, Zaixing; Liu, Li'an

2011-11-01

Traditional sediment disaggregation methods work well for loose mud sediments, but not for tightly cemented mudstones by ferric oxide minerals. In this paper, a new pretreatment method for analyzing the grain size of red mudstones is presented. The experimental samples are Eocene red mudstones from the Dongying Depression, Bohai Bay Basin. The red mudstones are composed mainly of clay minerals, clastic sediments and ferric oxides that make the mudstones red and tightly compacted. The procedure of the method is as follows. Firstly, samples of the red mudstones were crushed into fragments with a diameter of 0.6-0.8 mm in size; secondly, the CBD (citrate-bicarbonate-dithionite) treatment was used to remove ferric oxides so that the cementation of intra-aggregates and inter-aggregates became weakened, and then 5% dilute hydrochloric acid was added to further remove the cements; thirdly, the fragments were further ground with a rubber pestle; lastly, an ultrasonicator was used to disaggregate the samples. After the treatment, the samples could then be used for grain size analysis or for other geological analyses of sedimentary grains. Compared with other pretreatment methods for size analysis of mudstones, this proposed method is more effective and has higher repeatability.

Detecting spatial structures in throughfall data: the effect of extent, sample size, sampling design, and variogram estimation method

NASA Astrophysics Data System (ADS)

Voss, Sebastian; Zimmermann, Beate; Zimmermann, Alexander

2016-04-01

In the last three decades, an increasing number of studies analyzed spatial patterns in throughfall to investigate the consequences of rainfall redistribution for biogeochemical and hydrological processes in forests. In the majority of cases, variograms were used to characterize the spatial properties of the throughfall data. The estimation of the variogram from sample data requires an appropriate sampling scheme: most importantly, a large sample and an appropriate layout of sampling locations that often has to serve both variogram estimation and geostatistical prediction. While some recommendations on these aspects exist, they focus on Gaussian data and high ratios of the variogram range to the extent of the study area. However, many hydrological data, and throughfall data in particular, do not follow a Gaussian distribution. In this study, we examined the effect of extent, sample size, sampling design, and calculation methods on variogram estimation of throughfall data. For our investigation, we first generated non-Gaussian random fields based on throughfall data with heavy outliers. Subsequently, we sampled the fields with three extents (plots with edge lengths of 25 m, 50 m, and 100 m), four common sampling designs (two grid-based layouts, transect and random sampling), and five sample sizes (50, 100, 150, 200, 400). We then estimated the variogram parameters by method-of-moments and residual maximum likelihood. Our key findings are threefold. First, the choice of the extent has a substantial influence on the estimation of the variogram. A comparatively small ratio of the extent to the correlation length is beneficial for variogram estimation. Second, a combination of a minimum sample size of 150, a design that ensures the sampling of small distances and variogram estimation by residual maximum likelihood offers a good compromise between accuracy and efficiency. Third, studies relying on method-of-moments based variogram estimation may have to employ at least 200 sampling points for reliable variogram estimates. These suggested sample sizes exceed the numbers recommended by studies dealing with Gaussian data by up to 100 %. Given that most previous throughfall studies relied on method-of-moments variogram estimation and sample sizes << 200, our current knowledge about throughfall spatial variability stands on shaky ground.

Detecting spatial structures in throughfall data: The effect of extent, sample size, sampling design, and variogram estimation method

NASA Astrophysics Data System (ADS)

Voss, Sebastian; Zimmermann, Beate; Zimmermann, Alexander

2016-09-01

In the last decades, an increasing number of studies analyzed spatial patterns in throughfall by means of variograms. The estimation of the variogram from sample data requires an appropriate sampling scheme: most importantly, a large sample and a layout of sampling locations that often has to serve both variogram estimation and geostatistical prediction. While some recommendations on these aspects exist, they focus on Gaussian data and high ratios of the variogram range to the extent of the study area. However, many hydrological data, and throughfall data in particular, do not follow a Gaussian distribution. In this study, we examined the effect of extent, sample size, sampling design, and calculation method on variogram estimation of throughfall data. For our investigation, we first generated non-Gaussian random fields based on throughfall data with large outliers. Subsequently, we sampled the fields with three extents (plots with edge lengths of 25 m, 50 m, and 100 m), four common sampling designs (two grid-based layouts, transect and random sampling) and five sample sizes (50, 100, 150, 200, 400). We then estimated the variogram parameters by method-of-moments (non-robust and robust estimators) and residual maximum likelihood. Our key findings are threefold. First, the choice of the extent has a substantial influence on the estimation of the variogram. A comparatively small ratio of the extent to the correlation length is beneficial for variogram estimation. Second, a combination of a minimum sample size of 150, a design that ensures the sampling of small distances and variogram estimation by residual maximum likelihood offers a good compromise between accuracy and efficiency. Third, studies relying on method-of-moments based variogram estimation may have to employ at least 200 sampling points for reliable variogram estimates. These suggested sample sizes exceed the number recommended by studies dealing with Gaussian data by up to 100 %. Given that most previous throughfall studies relied on method-of-moments variogram estimation and sample sizes ≪200, currently available data are prone to large uncertainties.

A comparison of confidence/credible interval methods for the area under the ROC curve for continuous diagnostic tests with small sample size.

PubMed

Feng, Dai; Cortese, Giuliana; Baumgartner, Richard

2017-12-01

The receiver operating characteristic (ROC) curve is frequently used as a measure of accuracy of continuous markers in diagnostic tests. The area under the ROC curve (AUC) is arguably the most widely used summary index for the ROC curve. Although the small sample size scenario is common in medical tests, a comprehensive study of small sample size properties of various methods for the construction of the confidence/credible interval (CI) for the AUC has been by and large missing in the literature. In this paper, we describe and compare 29 non-parametric and parametric methods for the construction of the CI for the AUC when the number of available observations is small. The methods considered include not only those that have been widely adopted, but also those that have been less frequently mentioned or, to our knowledge, never applied to the AUC context. To compare different methods, we carried out a simulation study with data generated from binormal models with equal and unequal variances and from exponential models with various parameters and with equal and unequal small sample sizes. We found that the larger the true AUC value and the smaller the sample size, the larger the discrepancy among the results of different approaches. When the model is correctly specified, the parametric approaches tend to outperform the non-parametric ones. Moreover, in the non-parametric domain, we found that a method based on the Mann-Whitney statistic is in general superior to the others. We further elucidate potential issues and provide possible solutions to along with general guidance on the CI construction for the AUC when the sample size is small. Finally, we illustrate the utility of different methods through real life examples.

[Effect sizes, statistical power and sample sizes in "the Japanese Journal of Psychology"].

PubMed

Suzukawa, Yumi; Toyoda, Hideki

2012-04-01

This study analyzed the statistical power of research studies published in the "Japanese Journal of Psychology" in 2008 and 2009. Sample effect sizes and sample statistical powers were calculated for each statistical test and analyzed with respect to the analytical methods and the fields of the studies. The results show that in the fields like perception, cognition or learning, the effect sizes were relatively large, although the sample sizes were small. At the same time, because of the small sample sizes, some meaningful effects could not be detected. In the other fields, because of the large sample sizes, meaningless effects could be detected. This implies that researchers who could not get large enough effect sizes would use larger samples to obtain significant results.

Efficient inference of population size histories and locus-specific mutation rates from large-sample genomic variation data.

PubMed

Bhaskar, Anand; Wang, Y X Rachel; Song, Yun S

2015-02-01

With the recent increase in study sample sizes in human genetics, there has been growing interest in inferring historical population demography from genomic variation data. Here, we present an efficient inference method that can scale up to very large samples, with tens or hundreds of thousands of individuals. Specifically, by utilizing analytic results on the expected frequency spectrum under the coalescent and by leveraging the technique of automatic differentiation, which allows us to compute gradients exactly, we develop a very efficient algorithm to infer piecewise-exponential models of the historical effective population size from the distribution of sample allele frequencies. Our method is orders of magnitude faster than previous demographic inference methods based on the frequency spectrum. In addition to inferring demography, our method can also accurately estimate locus-specific mutation rates. We perform extensive validation of our method on simulated data and show that it can accurately infer multiple recent epochs of rapid exponential growth, a signal that is difficult to pick up with small sample sizes. Lastly, we use our method to analyze data from recent sequencing studies, including a large-sample exome-sequencing data set of tens of thousands of individuals assayed at a few hundred genic regions. © 2015 Bhaskar et al.; Published by Cold Spring Harbor Laboratory Press.

A Bayesian sequential design with adaptive randomization for 2-sided hypothesis test.

PubMed

Yu, Qingzhao; Zhu, Lin; Zhu, Han

2017-11-01

Bayesian sequential and adaptive randomization designs are gaining popularity in clinical trials thanks to their potentials to reduce the number of required participants and save resources. We propose a Bayesian sequential design with adaptive randomization rates so as to more efficiently attribute newly recruited patients to different treatment arms. In this paper, we consider 2-arm clinical trials. Patients are allocated to the 2 arms with a randomization rate to achieve minimum variance for the test statistic. Algorithms are presented to calculate the optimal randomization rate, critical values, and power for the proposed design. Sensitivity analysis is implemented to check the influence on design by changing the prior distributions. Simulation studies are applied to compare the proposed method and traditional methods in terms of power and actual sample sizes. Simulations show that, when total sample size is fixed, the proposed design can obtain greater power and/or cost smaller actual sample size than the traditional Bayesian sequential design. Finally, we apply the proposed method to a real data set and compare the results with the Bayesian sequential design without adaptive randomization in terms of sample sizes. The proposed method can further reduce required sample size. Copyright © 2017 John Wiley & Sons, Ltd.

Influence of item distribution pattern and abundance on efficiency of benthic core sampling

USGS Publications Warehouse

Behney, Adam C.; O'Shaughnessy, Ryan; Eichholz, Michael W.; Stafford, Joshua D.

2014-01-01

ore sampling is a commonly used method to estimate benthic item density, but little information exists about factors influencing the accuracy and time-efficiency of this method. We simulated core sampling in a Geographic Information System framework by generating points (benthic items) and polygons (core samplers) to assess how sample size (number of core samples), core sampler size (cm2), distribution of benthic items, and item density affected the bias and precision of estimates of density, the detection probability of items, and the time-costs. When items were distributed randomly versus clumped, bias decreased and precision increased with increasing sample size and increased slightly with increasing core sampler size. Bias and precision were only affected by benthic item density at very low values (500–1,000 items/m2). Detection probability (the probability of capturing ≥ 1 item in a core sample if it is available for sampling) was substantially greater when items were distributed randomly as opposed to clumped. Taking more small diameter core samples was always more time-efficient than taking fewer large diameter samples. We are unable to present a single, optimal sample size, but provide information for researchers and managers to derive optimal sample sizes dependent on their research goals and environmental conditions.

Chi-Squared Test of Fit and Sample Size-A Comparison between a Random Sample Approach and a Chi-Square Value Adjustment Method.

PubMed

Bergh, Daniel

2015-01-01

Chi-square statistics are commonly used for tests of fit of measurement models. Chi-square is also sensitive to sample size, which is why several approaches to handle large samples in test of fit analysis have been developed. One strategy to handle the sample size problem may be to adjust the sample size in the analysis of fit. An alternative is to adopt a random sample approach. The purpose of this study was to analyze and to compare these two strategies using simulated data. Given an original sample size of 21,000, for reductions of sample sizes down to the order of 5,000 the adjusted sample size function works as good as the random sample approach. In contrast, when applying adjustments to sample sizes of lower order the adjustment function is less effective at approximating the chi-square value for an actual random sample of the relevant size. Hence, the fit is exaggerated and misfit under-estimated using the adjusted sample size function. Although there are big differences in chi-square values between the two approaches at lower sample sizes, the inferences based on the p-values may be the same.

Estimating numbers of females with cubs-of-the-year in the Yellowstone grizzly bear population

USGS Publications Warehouse

Keating, K.A.; Schwartz, C.C.; Haroldson, M.A.; Moody, D.

2001-01-01

For grizzly bears (Ursus arctos horribilis) in the Greater Yellowstone Ecosystem (GYE), minimum population size and allowable numbers of human-caused mortalities have been calculated as a function of the number of unique females with cubs-of-the-year (FCUB) seen during a 3- year period. This approach underestimates the total number of FCUB, thereby biasing estimates of population size and sustainable mortality. Also, it does not permit calculation of valid confidence bounds. Many statistical methods can resolve or mitigate these problems, but there is no universal best method. Instead, relative performances of different methods can vary with population size, sample size, and degree of heterogeneity among sighting probabilities for individual animals. We compared 7 nonparametric estimators, using Monte Carlo techniques to assess performances over the range of sampling conditions deemed plausible for the Yellowstone population. Our goal was to estimate the number of FCUB present in the population each year. Our evaluation differed from previous comparisons of such estimators by including sample coverage methods and by treating individual sightings, rather than sample periods, as the sample unit. Consequently, our conclusions also differ from earlier studies. Recommendations regarding estimators and necessary sample sizes are presented, together with estimates of annual numbers of FCUB in the Yellowstone population with bootstrap confidence bounds.

A note on power and sample size calculations for the Kruskal-Wallis test for ordered categorical data.

PubMed

Fan, Chunpeng; Zhang, Donghui

2012-01-01

Although the Kruskal-Wallis test has been widely used to analyze ordered categorical data, power and sample size methods for this test have been investigated to a much lesser extent when the underlying multinomial distributions are unknown. This article generalizes the power and sample size procedures proposed by Fan et al. ( 2011 ) for continuous data to ordered categorical data, when estimates from a pilot study are used in the place of knowledge of the true underlying distribution. Simulations show that the proposed power and sample size formulas perform well. A myelin oligodendrocyte glycoprotein (MOG) induced experimental autoimmunce encephalomyelitis (EAE) mouse study is used to demonstrate the application of the methods.

Monitoring Species of Concern Using Noninvasive Genetic Sampling and Capture-Recapture Methods

DTIC Science & Technology

2016-11-01

ABBREVIATIONS AICc Akaike’s Information Criterion with small sample size correction AZGFD Arizona Game and Fish Department BMGR Barry M. Goldwater...MNKA Minimum Number Known Alive N Abundance Ne Effective Population Size NGS Noninvasive Genetic Sampling NGS-CR Noninvasive Genetic...parameter estimates from capture-recapture models require sufficient sample sizes , capture probabilities and low capture biases. For NGS-CR, sample

At convenience and systematic random sampling: effects on the prognostic value of nuclear area assessments in breast cancer patients.

PubMed

Jannink, I; Bennen, J N; Blaauw, J; van Diest, P J; Baak, J P

1995-01-01

This study compares the influence of two different nuclear sampling methods on the prognostic value of assessments of mean and standard deviation of nuclear area (MNA, SDNA) in 191 consecutive invasive breast cancer patients with long term follow up. The first sampling method used was 'at convenience' sampling (ACS); the second, systematic random sampling (SRS). Both sampling methods were tested with a sample size of 50 nuclei (ACS-50 and SRS-50). To determine whether, besides the sampling methods, sample size had impact on prognostic value as well, the SRS method was also tested using a sample size of 100 nuclei (SRS-100). SDNA values were systematically lower for ACS, obviously due to (unconsciously) not including small and large nuclei. Testing prognostic value of a series of cut off points, MNA and SDNA values assessed by the SRS method were prognostically significantly stronger than the values obtained by the ACS method. This was confirmed in Cox regression analysis. For the MNA, the Mantel-Cox p-values from SRS-50 and SRS-100 measurements were not significantly different. However, for the SDNA, SRS-100 yielded significantly lower p-values than SRS-50. In conclusion, compared with the 'at convenience' nuclear sampling method, systematic random sampling of nuclei is not only superior with respect to reproducibility of results, but also provides a better prognostic value in patients with invasive breast cancer.

Exact tests using two correlated binomial variables in contemporary cancer clinical trials.

PubMed

Yu, Jihnhee; Kepner, James L; Iyer, Renuka

2009-12-01

New therapy strategies for the treatment of cancer are rapidly emerging because of recent technology advances in genetics and molecular biology. Although newer targeted therapies can improve survival without measurable changes in tumor size, clinical trial conduct has remained nearly unchanged. When potentially efficacious therapies are tested, current clinical trial design and analysis methods may not be suitable for detecting therapeutic effects. We propose an exact method with respect to testing cytostatic cancer treatment using correlated bivariate binomial random variables to simultaneously assess two primary outcomes. The method is easy to implement. It does not increase the sample size over that of the univariate exact test and in most cases reduces the sample size required. Sample size calculations are provided for selected designs.

Observational studies of patients in the emergency department: a comparison of 4 sampling methods.

PubMed

Valley, Morgan A; Heard, Kennon J; Ginde, Adit A; Lezotte, Dennis C; Lowenstein, Steven R

2012-08-01

We evaluate the ability of 4 sampling methods to generate representative samples of the emergency department (ED) population. We analyzed the electronic records of 21,662 consecutive patient visits at an urban, academic ED. From this population, we simulated different models of study recruitment in the ED by using 2 sample sizes (n=200 and n=400) and 4 sampling methods: true random, random 4-hour time blocks by exact sample size, random 4-hour time blocks by a predetermined number of blocks, and convenience or "business hours." For each method and sample size, we obtained 1,000 samples from the population. Using χ(2) tests, we measured the number of statistically significant differences between the sample and the population for 8 variables (age, sex, race/ethnicity, language, triage acuity, arrival mode, disposition, and payer source). Then, for each variable, method, and sample size, we compared the proportion of the 1,000 samples that differed from the overall ED population to the expected proportion (5%). Only the true random samples represented the population with respect to sex, race/ethnicity, triage acuity, mode of arrival, language, and payer source in at least 95% of the samples. Patient samples obtained using random 4-hour time blocks and business hours sampling systematically differed from the overall ED patient population for several important demographic and clinical variables. However, the magnitude of these differences was not large. Common sampling strategies selected for ED-based studies may affect parameter estimates for several representative population variables. However, the potential for bias for these variables appears small. Copyright © 2012. Published by Mosby, Inc.

Robust gene selection methods using weighting schemes for microarray data analysis.

PubMed

Kang, Suyeon; Song, Jongwoo

2017-09-02

A common task in microarray data analysis is to identify informative genes that are differentially expressed between two different states. Owing to the high-dimensional nature of microarray data, identification of significant genes has been essential in analyzing the data. However, the performances of many gene selection techniques are highly dependent on the experimental conditions, such as the presence of measurement error or a limited number of sample replicates. We have proposed new filter-based gene selection techniques, by applying a simple modification to significance analysis of microarrays (SAM). To prove the effectiveness of the proposed method, we considered a series of synthetic datasets with different noise levels and sample sizes along with two real datasets. The following findings were made. First, our proposed methods outperform conventional methods for all simulation set-ups. In particular, our methods are much better when the given data are noisy and sample size is small. They showed relatively robust performance regardless of noise level and sample size, whereas the performance of SAM became significantly worse as the noise level became high or sample size decreased. When sufficient sample replicates were available, SAM and our methods showed similar performance. Finally, our proposed methods are competitive with traditional methods in classification tasks for microarrays. The results of simulation study and real data analysis have demonstrated that our proposed methods are effective for detecting significant genes and classification tasks, especially when the given data are noisy or have few sample replicates. By employing weighting schemes, we can obtain robust and reliable results for microarray data analysis.

[Sample size calculation in clinical post-marketing evaluation of traditional Chinese medicine].

PubMed

Fu, Yingkun; Xie, Yanming

2011-10-01

In recent years, as the Chinese government and people pay more attention on the post-marketing research of Chinese Medicine, part of traditional Chinese medicine breed has or is about to begin after the listing of post-marketing evaluation study. In the post-marketing evaluation design, sample size calculation plays a decisive role. It not only ensures the accuracy and reliability of post-marketing evaluation. but also assures that the intended trials will have a desired power for correctly detecting a clinically meaningful difference of different medicine under study if such a difference truly exists. Up to now, there is no systemic method of sample size calculation in view of the traditional Chinese medicine. In this paper, according to the basic method of sample size calculation and the characteristic of the traditional Chinese medicine clinical evaluation, the sample size calculation methods of the Chinese medicine efficacy and safety are discussed respectively. We hope the paper would be beneficial to medical researchers, and pharmaceutical scientists who are engaged in the areas of Chinese medicine research.

Laboratory theory and methods for sediment analysis

USGS Publications Warehouse

Guy, Harold P.

1969-01-01

The diverse character of fluvial sediments makes the choice of laboratory analysis somewhat arbitrary and the pressing of sediment samples difficult. This report presents some theories and methods used by the Water Resources Division for analysis of fluvial sediments to determine the concentration of suspended-sediment samples and the particle-size distribution of both suspended-sediment and bed-material samples. Other analyses related to these determinations may include particle shape, mineral content, and specific gravity, the organic matter and dissolved solids of samples, and the specific weight of soils. The merits and techniques of both the evaporation and filtration methods for concentration analysis are discussed. Methods used for particle-size analysis of suspended-sediment samples may include the sieve pipet, the VA tube-pipet, or the BW tube-VA tube depending on the equipment available, the concentration and approximate size of sediment in the sample, and the settling medium used. The choice of method for most bed-material samples is usually limited to procedures suitable for sand or to some type of visual analysis for large sizes. Several tested forms are presented to help insure a well-ordered system in the laboratory to handle the samples, to help determine the kind of analysis required for each, to conduct the required processes, and to assist in the required computations. Use of the manual should further 'standardize' methods of fluvial sediment analysis among the many laboratories and thereby help to achieve uniformity and precision of the data.

Quantifying and Mitigating the Effect of Preferential Sampling on Phylodynamic Inference

PubMed Central

Karcher, Michael D.; Palacios, Julia A.; Bedford, Trevor; Suchard, Marc A.; Minin, Vladimir N.

2016-01-01

Phylodynamics seeks to estimate effective population size fluctuations from molecular sequences of individuals sampled from a population of interest. One way to accomplish this task formulates an observed sequence data likelihood exploiting a coalescent model for the sampled individuals’ genealogy and then integrating over all possible genealogies via Monte Carlo or, less efficiently, by conditioning on one genealogy estimated from the sequence data. However, when analyzing sequences sampled serially through time, current methods implicitly assume either that sampling times are fixed deterministically by the data collection protocol or that their distribution does not depend on the size of the population. Through simulation, we first show that, when sampling times do probabilistically depend on effective population size, estimation methods may be systematically biased. To correct for this deficiency, we propose a new model that explicitly accounts for preferential sampling by modeling the sampling times as an inhomogeneous Poisson process dependent on effective population size. We demonstrate that in the presence of preferential sampling our new model not only reduces bias, but also improves estimation precision. Finally, we compare the performance of the currently used phylodynamic methods with our proposed model through clinically-relevant, seasonal human influenza examples. PMID:26938243

Phase II Trials for Heterogeneous Patient Populations with a Time-to-Event Endpoint.

PubMed

Jung, Sin-Ho

2017-07-01

In this paper, we consider a single-arm phase II trial with a time-to-event end-point. We assume that the study population has multiple subpopulations with different prognosis, but the study treatment is expected to be similarly efficacious across the subpopulations. We review a stratified one-sample log-rank test and present its sample size calculation method under some practical design settings. Our sample size method requires specification of the prevalence of subpopulations. We observe that the power of the resulting sample size is not very sensitive to misspecification of the prevalence.

Sample size calculation in economic evaluations.

PubMed

Al, M J; van Hout, B A; Michel, B C; Rutten, F F

1998-06-01

A simulation method is presented for sample size calculation in economic evaluations. As input the method requires: the expected difference and variance of costs and effects, their correlation, the significance level (alpha) and the power of the testing method and the maximum acceptable ratio of incremental effectiveness to incremental costs. The method is illustrated with data from two trials. The first compares primary coronary angioplasty with streptokinase in the treatment of acute myocardial infarction, in the second trial, lansoprazole is compared with omeprazole in the treatment of reflux oesophagitis. These case studies show how the various parameters influence the sample size. Given the large number of parameters that have to be specified in advance, the lack of knowledge about costs and their standard deviation, and the difficulty of specifying the maximum acceptable ratio of incremental effectiveness to incremental costs, the conclusion of the study is that from a technical point of view it is possible to perform a sample size calculation for an economic evaluation, but one should wonder how useful it is.

A New Sample Size Formula for Regression.

ERIC Educational Resources Information Center

Brooks, Gordon P.; Barcikowski, Robert S.

The focus of this research was to determine the efficacy of a new method of selecting sample sizes for multiple linear regression. A Monte Carlo simulation was used to study both empirical predictive power rates and empirical statistical power rates of the new method and seven other methods: those of C. N. Park and A. L. Dudycha (1974); J. Cohen…

The feasibility of using explicit method for linear correction of the particle size variation using NIR Spectroscopy combined with PLS2regression method

NASA Astrophysics Data System (ADS)

Yulia, M.; Suhandy, D.

2018-03-01

NIR spectra obtained from spectral data acquisition system contains both chemical information of samples as well as physical information of the samples, such as particle size and bulk density. Several methods have been established for developing calibration models that can compensate for sample physical information variations. One common approach is to include physical information variation in the calibration model both explicitly and implicitly. The objective of this study was to evaluate the feasibility of using explicit method to compensate the influence of different particle size of coffee powder in NIR calibration model performance. A number of 220 coffee powder samples with two different types of coffee (civet and non-civet) and two different particle sizes (212 and 500 µm) were prepared. Spectral data was acquired using NIR spectrometer equipped with an integrating sphere for diffuse reflectance measurement. A discrimination method based on PLS-DA was conducted and the influence of different particle size on the performance of PLS-DA was investigated. In explicit method, we add directly the particle size as predicted variable results in an X block containing only the NIR spectra and a Y block containing the particle size and type of coffee. The explicit inclusion of the particle size into the calibration model is expected to improve the accuracy of type of coffee determination. The result shows that using explicit method the quality of the developed calibration model for type of coffee determination is a little bit superior with coefficient of determination (R2) = 0.99 and root mean square error of cross-validation (RMSECV) = 0.041. The performance of the PLS2 calibration model for type of coffee determination with particle size compensation was quite good and able to predict the type of coffee in two different particle sizes with relatively high R2 pred values. The prediction also resulted in low bias and RMSEP values.

Field test comparison of an autocorrelation technique for determining grain size using a digital 'beachball' camera versus traditional methods

USGS Publications Warehouse

Barnard, P.L.; Rubin, D.M.; Harney, J.; Mustain, N.

2007-01-01

This extensive field test of an autocorrelation technique for determining grain size from digital images was conducted using a digital bed-sediment camera, or 'beachball' camera. Using 205 sediment samples and >1200 images from a variety of beaches on the west coast of the US, grain size ranging from sand to granules was measured from field samples using both the autocorrelation technique developed by Rubin [Rubin, D.M., 2004. A simple autocorrelation algorithm for determining grain size from digital images of sediment. Journal of Sedimentary Research, 74(1): 160-165.] and traditional methods (i.e. settling tube analysis, sieving, and point counts). To test the accuracy of the digital-image grain size algorithm, we compared results with manual point counts of an extensive image data set in the Santa Barbara littoral cell. Grain sizes calculated using the autocorrelation algorithm were highly correlated with the point counts of the same images (r2 = 0.93; n = 79) and had an error of only 1%. Comparisons of calculated grain sizes and grain sizes measured from grab samples demonstrated that the autocorrelation technique works well on high-energy dissipative beaches with well-sorted sediment such as in the Pacific Northwest (r2 ??? 0.92; n = 115). On less dissipative, more poorly sorted beaches such as Ocean Beach in San Francisco, results were not as good (r2 ??? 0.70; n = 67; within 3% accuracy). Because the algorithm works well compared with point counts of the same image, the poorer correlation with grab samples must be a result of actual spatial and vertical variability of sediment in the field; closer agreement between grain size in the images and grain size of grab samples can be achieved by increasing the sampling volume of the images (taking more images, distributed over a volume comparable to that of a grab sample). In all field tests the autocorrelation method was able to predict the mean and median grain size with ???96% accuracy, which is more than adequate for the majority of sedimentological applications, especially considering that the autocorrelation technique is estimated to be at least 100 times faster than traditional methods.

Rock sampling. [method for controlling particle size distribution

NASA Technical Reports Server (NTRS)

Blum, P. (Inventor)

1971-01-01

A method for sampling rock and other brittle materials and for controlling resultant particle sizes is described. The method involves cutting grooves in the rock surface to provide a grouping of parallel ridges and subsequently machining the ridges to provide a powder specimen. The machining step may comprise milling, drilling, lathe cutting or the like; but a planing step is advantageous. Control of the particle size distribution is effected primarily by changing the height and width of these ridges. This control exceeds that obtainable by conventional grinding.

Affected States Soft Independent Modeling by Class Analogy from the Relation Between Independent Variables, Number of Independent Variables and Sample Size

PubMed Central

Kanık, Emine Arzu; Temel, Gülhan Orekici; Erdoğan, Semra; Kaya, İrem Ersöz

2013-01-01

Objective: The aim of study is to introduce method of Soft Independent Modeling of Class Analogy (SIMCA), and to express whether the method is affected from the number of independent variables, the relationship between variables and sample size. Study Design: Simulation study. Material and Methods: SIMCA model is performed in two stages. In order to determine whether the method is influenced by the number of independent variables, the relationship between variables and sample size, simulations were done. Conditions in which sample sizes in both groups are equal, and where there are 30, 100 and 1000 samples; where the number of variables is 2, 3, 5, 10, 50 and 100; moreover where the relationship between variables are quite high, in medium level and quite low were mentioned. Results: Average classification accuracy of simulation results which were carried out 1000 times for each possible condition of trial plan were given as tables. Conclusion: It is seen that diagnostic accuracy results increase as the number of independent variables increase. SIMCA method is a method in which the relationship between variables are quite high, the number of independent variables are many in number and where there are outlier values in the data that can be used in conditions having outlier values. PMID:25207065

Power calculation for overall hypothesis testing with high-dimensional commensurate outcomes.

PubMed

Chi, Yueh-Yun; Gribbin, Matthew J; Johnson, Jacqueline L; Muller, Keith E

2014-02-28

The complexity of system biology means that any metabolic, genetic, or proteomic pathway typically includes so many components (e.g., molecules) that statistical methods specialized for overall testing of high-dimensional and commensurate outcomes are required. While many overall tests have been proposed, very few have power and sample size methods. We develop accurate power and sample size methods and software to facilitate study planning for high-dimensional pathway analysis. With an account of any complex correlation structure between high-dimensional outcomes, the new methods allow power calculation even when the sample size is less than the number of variables. We derive the exact (finite-sample) and approximate non-null distributions of the 'univariate' approach to repeated measures test statistic, as well as power-equivalent scenarios useful to generalize our numerical evaluations. Extensive simulations of group comparisons support the accuracy of the approximations even when the ratio of number of variables to sample size is large. We derive a minimum set of constants and parameters sufficient and practical for power calculation. Using the new methods and specifying the minimum set to determine power for a study of metabolic consequences of vitamin B6 deficiency helps illustrate the practical value of the new results. Free software implementing the power and sample size methods applies to a wide range of designs, including one group pre-intervention and post-intervention comparisons, multiple parallel group comparisons with one-way or factorial designs, and the adjustment and evaluation of covariate effects. Copyright © 2013 John Wiley & Sons, Ltd.

Publication Bias in Psychology: A Diagnosis Based on the Correlation between Effect Size and Sample Size

PubMed Central

Kühberger, Anton; Fritz, Astrid; Scherndl, Thomas

2014-01-01

Background The p value obtained from a significance test provides no information about the magnitude or importance of the underlying phenomenon. Therefore, additional reporting of effect size is often recommended. Effect sizes are theoretically independent from sample size. Yet this may not hold true empirically: non-independence could indicate publication bias. Methods We investigate whether effect size is independent from sample size in psychological research. We randomly sampled 1,000 psychological articles from all areas of psychological research. We extracted p values, effect sizes, and sample sizes of all empirical papers, and calculated the correlation between effect size and sample size, and investigated the distribution of p values. Results We found a negative correlation of r = −.45 [95% CI: −.53; −.35] between effect size and sample size. In addition, we found an inordinately high number of p values just passing the boundary of significance. Additional data showed that neither implicit nor explicit power analysis could account for this pattern of findings. Conclusion The negative correlation between effect size and samples size, and the biased distribution of p values indicate pervasive publication bias in the entire field of psychology. PMID:25192357

Design of Phase II Non-inferiority Trials.

PubMed

Jung, Sin-Ho

2017-09-01

With the development of inexpensive treatment regimens and less invasive surgical procedures, we are confronted with non-inferiority study objectives. A non-inferiority phase III trial requires a roughly four times larger sample size than that of a similar standard superiority trial. Because of the large required sample size, we often face feasibility issues to open a non-inferiority trial. Furthermore, due to lack of phase II non-inferiority trial design methods, we do not have an opportunity to investigate the efficacy of the experimental therapy through a phase II trial. As a result, we often fail to open a non-inferiority phase III trial and a large number of non-inferiority clinical questions still remain unanswered. In this paper, we want to develop some designs for non-inferiority randomized phase II trials with feasible sample sizes. At first, we review a design method for non-inferiority phase III trials. Subsequently, we propose three different designs for non-inferiority phase II trials that can be used under different settings. Each method is demonstrated with examples. Each of the proposed design methods is shown to require a reasonable sample size for non-inferiority phase II trials. The three different non-inferiority phase II trial designs are used under different settings, but require similar sample sizes that are typical for phase II trials.

Determining the sample size for co-dominant molecular marker-assisted linkage detection for a monogenic qualitative trait by controlling the type-I and type-II errors in a segregating F2 population.

PubMed

Hühn, M; Piepho, H P

2003-03-01

Tests for linkage are usually performed using the lod score method. A critical question in linkage analyses is the choice of sample size. The appropriate sample size depends on the desired type-I error and power of the test. This paper investigates the exact type-I error and power of the lod score method in a segregating F(2) population with co-dominant markers and a qualitative monogenic dominant-recessive trait. For illustration, a disease-resistance trait is considered, where the susceptible allele is recessive. A procedure is suggested for finding the appropriate sample size. It is shown that recessive plants have about twice the information content of dominant plants, so the former should be preferred for linkage detection. In some cases the exact alpha-values for a given nominal alpha may be rather small due to the discrete nature of the sampling distribution in small samples. We show that a gain in power is possible by using exact methods.

Methods for flexible sample-size design in clinical trials: Likelihood, weighted, dual test, and promising zone approaches.

PubMed

Shih, Weichung Joe; Li, Gang; Wang, Yining

2016-03-01

Sample size plays a crucial role in clinical trials. Flexible sample-size designs, as part of the more general category of adaptive designs that utilize interim data, have been a popular topic in recent years. In this paper, we give a comparative review of four related methods for such a design. The likelihood method uses the likelihood ratio test with an adjusted critical value. The weighted method adjusts the test statistic with given weights rather than the critical value. The dual test method requires both the likelihood ratio statistic and the weighted statistic to be greater than the unadjusted critical value. The promising zone approach uses the likelihood ratio statistic with the unadjusted value and other constraints. All four methods preserve the type-I error rate. In this paper we explore their properties and compare their relationships and merits. We show that the sample size rules for the dual test are in conflict with the rules of the promising zone approach. We delineate what is necessary to specify in the study protocol to ensure the validity of the statistical procedure and what can be kept implicit in the protocol so that more flexibility can be attained for confirmatory phase III trials in meeting regulatory requirements. We also prove that under mild conditions, the likelihood ratio test still preserves the type-I error rate when the actual sample size is larger than the re-calculated one. Copyright © 2015 Elsevier Inc. All rights reserved.

Further improvement of hydrostatic pressure sample injection for microchip electrophoresis.

PubMed

Luo, Yong; Zhang, Qingquan; Qin, Jianhua; Lin, Bingcheng

2007-12-01

Hydrostatic pressure sample injection method is able to minimize the number of electrodes needed for a microchip electrophoresis process; however, it neither can be applied for electrophoretic DNA sizing, nor can be implemented on the widely used single-cross microchip. This paper presents an injector design that makes the hydrostatic pressure sample injection method suitable for DNA sizing. By introducing an assistant channel into the normal double-cross injector, a rugged DNA sample plug suitable for sizing can be successfully formed within the cross area during the sample loading. This paper also demonstrates that the hydrostatic pressure sample injection can be performed in the single-cross microchip by controlling the radial position of the detection point in the separation channel. Rhodamine 123 and its derivative as model sample were successfully separated.

A feasibility study in adapting Shamos Bickel and Hodges Lehman estimator into T-Method for normalization

NASA Astrophysics Data System (ADS)

Harudin, N.; Jamaludin, K. R.; Muhtazaruddin, M. Nabil; Ramlie, F.; Muhamad, Wan Zuki Azman Wan

2018-03-01

T-Method is one of the techniques governed under Mahalanobis Taguchi System that developed specifically for multivariate data predictions. Prediction using T-Method is always possible even with very limited sample size. The user of T-Method required to clearly understanding the population data trend since this method is not considering the effect of outliers within it. Outliers may cause apparent non-normality and the entire classical methods breakdown. There exist robust parameter estimate that provide satisfactory results when the data contain outliers, as well as when the data are free of them. The robust parameter estimates of location and scale measure called Shamos Bickel (SB) and Hodges Lehman (HL) which are used as a comparable method to calculate the mean and standard deviation of classical statistic is part of it. Embedding these into T-Method normalize stage feasibly help in enhancing the accuracy of the T-Method as well as analysing the robustness of T-method itself. However, the result of higher sample size case study shows that T-method is having lowest average error percentages (3.09%) on data with extreme outliers. HL and SB is having lowest error percentages (4.67%) for data without extreme outliers with minimum error differences compared to T-Method. The error percentages prediction trend is vice versa for lower sample size case study. The result shows that with minimum sample size, which outliers always be at low risk, T-Method is much better on that, while higher sample size with extreme outliers, T-Method as well show better prediction compared to others. For the case studies conducted in this research, it shows that normalization of T-Method is showing satisfactory results and it is not feasible to adapt HL and SB or normal mean and standard deviation into it since it’s only provide minimum effect of percentages errors. Normalization using T-method is still considered having lower risk towards outlier’s effect.

On Two-Stage Multiple Comparison Procedures When There Are Unequal Sample Sizes in the First Stage.

ERIC Educational Resources Information Center

Wilcox, Rand R.

1984-01-01

Two stage multiple-comparison procedures give an exact solution to problems of power and Type I errors, but require equal sample sizes in the first stage. This paper suggests a method of evaluating the experimentwise Type I error probability when the first stage has unequal sample sizes. (Author/BW)

Relative efficiency and sample size for cluster randomized trials with variable cluster sizes.

PubMed

You, Zhiying; Williams, O Dale; Aban, Inmaculada; Kabagambe, Edmond Kato; Tiwari, Hemant K; Cutter, Gary

2011-02-01

The statistical power of cluster randomized trials depends on two sample size components, the number of clusters per group and the numbers of individuals within clusters (cluster size). Variable cluster sizes are common and this variation alone may have significant impact on study power. Previous approaches have taken this into account by either adjusting total sample size using a designated design effect or adjusting the number of clusters according to an assessment of the relative efficiency of unequal versus equal cluster sizes. This article defines a relative efficiency of unequal versus equal cluster sizes using noncentrality parameters, investigates properties of this measure, and proposes an approach for adjusting the required sample size accordingly. We focus on comparing two groups with normally distributed outcomes using t-test, and use the noncentrality parameter to define the relative efficiency of unequal versus equal cluster sizes and show that statistical power depends only on this parameter for a given number of clusters. We calculate the sample size required for an unequal cluster sizes trial to have the same power as one with equal cluster sizes. Relative efficiency based on the noncentrality parameter is straightforward to calculate and easy to interpret. It connects the required mean cluster size directly to the required sample size with equal cluster sizes. Consequently, our approach first determines the sample size requirements with equal cluster sizes for a pre-specified study power and then calculates the required mean cluster size while keeping the number of clusters unchanged. Our approach allows adjustment in mean cluster size alone or simultaneous adjustment in mean cluster size and number of clusters, and is a flexible alternative to and a useful complement to existing methods. Comparison indicated that we have defined a relative efficiency that is greater than the relative efficiency in the literature under some conditions. Our measure of relative efficiency might be less than the measure in the literature under some conditions, underestimating the relative efficiency. The relative efficiency of unequal versus equal cluster sizes defined using the noncentrality parameter suggests a sample size approach that is a flexible alternative and a useful complement to existing methods.

Estimation of sample size and testing power (Part 4).

PubMed

Hu, Liang-ping; Bao, Xiao-lei; Guan, Xue; Zhou, Shi-guo

2012-01-01

Sample size estimation is necessary for any experimental or survey research. An appropriate estimation of sample size based on known information and statistical knowledge is of great significance. This article introduces methods of sample size estimation of difference test for data with the design of one factor with two levels, including sample size estimation formulas and realization based on the formulas and the POWER procedure of SAS software for quantitative data and qualitative data with the design of one factor with two levels. In addition, this article presents examples for analysis, which will play a leading role for researchers to implement the repetition principle during the research design phase.

Estimating population size with correlated sampling unit estimates

Treesearch

David C. Bowden; Gary C. White; Alan B. Franklin; Joseph L. Ganey

2003-01-01

Finite population sampling theory is useful in estimating total population size (abundance) from abundance estimates of each sampled unit (quadrat). We develop estimators that allow correlated quadrat abundance estimates, even for quadrats in different sampling strata. Correlated quadrat abundance estimates based on mark–recapture or distance sampling methods occur...

HYPERSAMP - HYPERGEOMETRIC ATTRIBUTE SAMPLING SYSTEM BASED ON RISK AND FRACTION DEFECTIVE

NASA Technical Reports Server (NTRS)

De, Salvo L. J.

1994-01-01

HYPERSAMP is a demonstration of an attribute sampling system developed to determine the minimum sample size required for any preselected value for consumer's risk and fraction of nonconforming. This statistical method can be used in place of MIL-STD-105E sampling plans when a minimum sample size is desirable, such as when tests are destructive or expensive. HYPERSAMP utilizes the Hypergeometric Distribution and can be used for any fraction nonconforming. The program employs an iterative technique that circumvents the obstacle presented by the factorial of a non-whole number. HYPERSAMP provides the required Hypergeometric sample size for any equivalent real number of nonconformances in the lot or batch under evaluation. Many currently used sampling systems, such as the MIL-STD-105E, utilize the Binomial or the Poisson equations as an estimate of the Hypergeometric when performing inspection by attributes. However, this is primarily because of the difficulty in calculation of the factorials required by the Hypergeometric. Sampling plans based on the Binomial or Poisson equations will result in the maximum sample size possible with the Hypergeometric. The difference in the sample sizes between the Poisson or Binomial and the Hypergeometric can be significant. For example, a lot size of 400 devices with an error rate of 1.0% and a confidence of 99% would require a sample size of 400 (all units would need to be inspected) for the Binomial sampling plan and only 273 for a Hypergeometric sampling plan. The Hypergeometric results in a savings of 127 units, a significant reduction in the required sample size. HYPERSAMP is a demonstration program and is limited to sampling plans with zero defectives in the sample (acceptance number of zero). Since it is only a demonstration program, the sample size determination is limited to sample sizes of 1500 or less. The Hypergeometric Attribute Sampling System demonstration code is a spreadsheet program written for IBM PC compatible computers running DOS and Lotus 1-2-3 or Quattro Pro. This program is distributed on a 5.25 inch 360K MS-DOS format diskette, and the program price includes documentation. This statistical method was developed in 1992.

Approximate sample size formulas for the two-sample trimmed mean test with unequal variances.

PubMed

Luh, Wei-Ming; Guo, Jiin-Huarng

2007-05-01

Yuen's two-sample trimmed mean test statistic is one of the most robust methods to apply when variances are heterogeneous. The present study develops formulas for the sample size required for the test. The formulas are applicable for the cases of unequal variances, non-normality and unequal sample sizes. Given the specified alpha and the power (1-beta), the minimum sample size needed by the proposed formulas under various conditions is less than is given by the conventional formulas. Moreover, given a specified size of sample calculated by the proposed formulas, simulation results show that Yuen's test can achieve statistical power which is generally superior to that of the approximate t test. A numerical example is provided.

Regression modeling of particle size distributions in urban storm water: advancements through improved sample collection methods

USGS Publications Warehouse

Fienen, Michael N.; Selbig, William R.

2012-01-01

A new sample collection system was developed to improve the representation of sediment entrained in urban storm water by integrating water quality samples from the entire water column. The depth-integrated sampler arm (DISA) was able to mitigate sediment stratification bias in storm water, thereby improving the characterization of suspended-sediment concentration and particle size distribution at three independent study locations. Use of the DISA decreased variability, which improved statistical regression to predict particle size distribution using surrogate environmental parameters, such as precipitation depth and intensity. The performance of this statistical modeling technique was compared to results using traditional fixed-point sampling methods and was found to perform better. When environmental parameters can be used to predict particle size distributions, environmental managers have more options when characterizing concentrations, loads, and particle size distributions in urban runoff.

Sample size in studies on diagnostic accuracy in ophthalmology: a literature survey.

PubMed

Bochmann, Frank; Johnson, Zoe; Azuara-Blanco, Augusto

2007-07-01

To assess the sample sizes used in studies on diagnostic accuracy in ophthalmology. Design and sources: A survey literature published in 2005. The frequency of reporting calculations of sample sizes and the samples' sizes were extracted from the published literature. A manual search of five leading clinical journals in ophthalmology with the highest impact (Investigative Ophthalmology and Visual Science, Ophthalmology, Archives of Ophthalmology, American Journal of Ophthalmology and British Journal of Ophthalmology) was conducted by two independent investigators. A total of 1698 articles were identified, of which 40 studies were on diagnostic accuracy. One study reported that sample size was calculated before initiating the study. Another study reported consideration of sample size without calculation. The mean (SD) sample size of all diagnostic studies was 172.6 (218.9). The median prevalence of the target condition was 50.5%. Only a few studies consider sample size in their methods. Inadequate sample sizes in diagnostic accuracy studies may result in misleading estimates of test accuracy. An improvement over the current standards on the design and reporting of diagnostic studies is warranted.

A general approach for sample size calculation for the three-arm 'gold standard' non-inferiority design.

PubMed

Stucke, Kathrin; Kieser, Meinhard

2012-12-10

In the three-arm 'gold standard' non-inferiority design, an experimental treatment, an active reference, and a placebo are compared. This design is becoming increasingly popular, and it is, whenever feasible, recommended for use by regulatory guidelines. We provide a general method to calculate the required sample size for clinical trials performed in this design. As special cases, the situations of continuous, binary, and Poisson distributed outcomes are explored. Taking into account the correlation structure of the involved test statistics, the proposed approach leads to considerable savings in sample size as compared with application of ad hoc methods for all three scale levels. Furthermore, optimal sample size allocation ratios are determined that result in markedly smaller total sample sizes as compared with equal assignment. As optimal allocation makes the active treatment groups larger than the placebo group, implementation of the proposed approach is also desirable from an ethical viewpoint. Copyright © 2012 John Wiley & Sons, Ltd.

Rectification of depth measurement using pulsed thermography with logarithmic peak second derivative method

NASA Astrophysics Data System (ADS)

Li, Xiaoli; Zeng, Zhi; Shen, Jingling; Zhang, Cunlin; Zhao, Yuejin

2018-03-01

Logarithmic peak second derivative (LPSD) method is the most popular method for depth prediction in pulsed thermography. It is widely accepted that this method is independent of defect size. The theoretical model for LPSD method is based on the one-dimensional solution of heat conduction without considering the effect of defect size. When a decay term considering defect aspect ratio is introduced into the solution to correct the three-dimensional thermal diffusion effect, we found that LPSD method is affected by defect size by analytical model. Furthermore, we constructed the relation between the characteristic time of LPSD method and defect aspect ratio, which was verified with the experimental results of stainless steel and glass fiber reinforced plate (GFRP) samples. We also proposed an improved LPSD method for depth prediction when the effect of defect size was considered, and the rectification results of stainless steel and GFRP samples were presented and discussed.

Affected States soft independent modeling by class analogy from the relation between independent variables, number of independent variables and sample size.

PubMed

Kanık, Emine Arzu; Temel, Gülhan Orekici; Erdoğan, Semra; Kaya, Irem Ersöz

2013-03-01

The aim of study is to introduce method of Soft Independent Modeling of Class Analogy (SIMCA), and to express whether the method is affected from the number of independent variables, the relationship between variables and sample size. Simulation study. SIMCA model is performed in two stages. In order to determine whether the method is influenced by the number of independent variables, the relationship between variables and sample size, simulations were done. Conditions in which sample sizes in both groups are equal, and where there are 30, 100 and 1000 samples; where the number of variables is 2, 3, 5, 10, 50 and 100; moreover where the relationship between variables are quite high, in medium level and quite low were mentioned. Average classification accuracy of simulation results which were carried out 1000 times for each possible condition of trial plan were given as tables. It is seen that diagnostic accuracy results increase as the number of independent variables increase. SIMCA method is a method in which the relationship between variables are quite high, the number of independent variables are many in number and where there are outlier values in the data that can be used in conditions having outlier values.

Sample size determination in group-sequential clinical trials with two co-primary endpoints

PubMed Central

Asakura, Koko; Hamasaki, Toshimitsu; Sugimoto, Tomoyuki; Hayashi, Kenichi; Evans, Scott R; Sozu, Takashi

2014-01-01

We discuss sample size determination in group-sequential designs with two endpoints as co-primary. We derive the power and sample size within two decision-making frameworks. One is to claim the test intervention’s benefit relative to control when superiority is achieved for the two endpoints at the same interim timepoint of the trial. The other is when the superiority is achieved for the two endpoints at any interim timepoint, not necessarily simultaneously. We evaluate the behaviors of sample size and power with varying design elements and provide a real example to illustrate the proposed sample size methods. In addition, we discuss sample size recalculation based on observed data and evaluate the impact on the power and Type I error rate. PMID:24676799

Measures of precision for dissimilarity-based multivariate analysis of ecological communities

PubMed Central

Anderson, Marti J; Santana-Garcon, Julia

2015-01-01

Ecological studies require key decisions regarding the appropriate size and number of sampling units. No methods currently exist to measure precision for multivariate assemblage data when dissimilarity-based analyses are intended to follow. Here, we propose a pseudo multivariate dissimilarity-based standard error (MultSE) as a useful quantity for assessing sample-size adequacy in studies of ecological communities. Based on sums of squared dissimilarities, MultSE measures variability in the position of the centroid in the space of a chosen dissimilarity measure under repeated sampling for a given sample size. We describe a novel double resampling method to quantify uncertainty in MultSE values with increasing sample size. For more complex designs, values of MultSE can be calculated from the pseudo residual mean square of a permanova model, with the double resampling done within appropriate cells in the design. R code functions for implementing these techniques, along with ecological examples, are provided. PMID:25438826

Study samples are too small to produce sufficiently precise reliability coefficients.

PubMed

Charter, Richard A

2003-04-01

In a survey of journal articles, test manuals, and test critique books, the author found that a mean sample size (N) of 260 participants had been used for reliability studies on 742 tests. The distribution was skewed because the median sample size for the total sample was only 90. The median sample sizes for the internal consistency, retest, and interjudge reliabilities were 182, 64, and 36, respectively. The author presented sample size statistics for the various internal consistency methods and types of tests. In general, the author found that the sample sizes that were used in the internal consistency studies were too small to produce sufficiently precise reliability coefficients, which in turn could cause imprecise estimates of examinee true-score confidence intervals. The results also suggest that larger sample sizes have been used in the last decade compared with those that were used in earlier decades.

Synthesis and characterization of nanocrystalline mesoporous zirconia using supercritical drying.

PubMed

Tyagi, Beena; Sidhpuria, Kalpesh; Shaik, Basha; Jasra, Raksh Vir

2006-06-01

Synthesis of nano-crystalline zirconia aerogel was done by sol-gel technique and supercritical drying using n-propanol solvent at and above supercritical temperature (235-280 degrees C) and pressure (48-52 bar) of n-propanol. Zirconia xerogel samples have also been prepared by conventional thermal drying method to compare with the super critically dried samples. Crystalline phase, crystallite size, surface area, pore volume, and pore size distribution were determined for all the samples in detail to understand the effect of gel drying methods on these properties. Supercritical drying of zirconia gel was observed to give thermally stable, nano-crystalline, tetragonal zirconia aerogels having high specific surface area and porosity with narrow and uniform pore size distribution as compared to thermally dried zirconia. With supercritical drying, zirconia samples show the formation of only mesopores whereas in thermally dried samples, substantial amount of micropores are observed along with mesopores. The samples prepared using supercritical drying yield nano-crystalline zirconia with smaller crystallite size (4-6 nm) as compared to higher crystallite size (13-20 nm) observed with thermally dried zirconia.

Determining the Population Size of Pond Phytoplankton.

ERIC Educational Resources Information Center

Hummer, Paul J.

1980-01-01

Discusses methods for determining the population size of pond phytoplankton, including water sampling techniques, laboratory analysis of samples, and additional studies worthy of investigation in class or as individual projects. (CS)

Sample Size Methods for Estimating HIV Incidence from Cross-Sectional Surveys

PubMed Central

Brookmeyer, Ron

2015-01-01

Summary Understanding HIV incidence, the rate at which new infections occur in populations, is critical for tracking and surveillance of the epidemic. In this paper we derive methods for determining sample sizes for cross-sectional surveys to estimate incidence with sufficient precision. We further show how to specify sample sizes for two successive cross-sectional surveys to detect changes in incidence with adequate power. In these surveys biomarkers such as CD4 cell count, viral load, and recently developed serological assays are used to determine which individuals are in an early disease stage of infection. The total number of individuals in this stage, divided by the number of people who are uninfected, is used to approximate the incidence rate. Our methods account for uncertainty in the durations of time spent in the biomarker defined early disease stage. We find that failure to account for this uncertainty when designing surveys can lead to imprecise estimates of incidence and underpowered studies. We evaluated our sample size methods in simulations and found that they performed well in a variety of underlying epidemics. Code for implementing our methods in R is available with this paper at the Biometrics website on Wiley Online Library. PMID:26302040

Sample size methods for estimating HIV incidence from cross-sectional surveys.

PubMed

Konikoff, Jacob; Brookmeyer, Ron

2015-12-01

Understanding HIV incidence, the rate at which new infections occur in populations, is critical for tracking and surveillance of the epidemic. In this article, we derive methods for determining sample sizes for cross-sectional surveys to estimate incidence with sufficient precision. We further show how to specify sample sizes for two successive cross-sectional surveys to detect changes in incidence with adequate power. In these surveys biomarkers such as CD4 cell count, viral load, and recently developed serological assays are used to determine which individuals are in an early disease stage of infection. The total number of individuals in this stage, divided by the number of people who are uninfected, is used to approximate the incidence rate. Our methods account for uncertainty in the durations of time spent in the biomarker defined early disease stage. We find that failure to account for this uncertainty when designing surveys can lead to imprecise estimates of incidence and underpowered studies. We evaluated our sample size methods in simulations and found that they performed well in a variety of underlying epidemics. Code for implementing our methods in R is available with this article at the Biometrics website on Wiley Online Library. © 2015, The International Biometric Society.

Sample size and power considerations in network meta-analysis

PubMed Central

2012-01-01

Background Network meta-analysis is becoming increasingly popular for establishing comparative effectiveness among multiple interventions for the same disease. Network meta-analysis inherits all methodological challenges of standard pairwise meta-analysis, but with increased complexity due to the multitude of intervention comparisons. One issue that is now widely recognized in pairwise meta-analysis is the issue of sample size and statistical power. This issue, however, has so far only received little attention in network meta-analysis. To date, no approaches have been proposed for evaluating the adequacy of the sample size, and thus power, in a treatment network. Findings In this article, we develop easy-to-use flexible methods for estimating the ‘effective sample size’ in indirect comparison meta-analysis and network meta-analysis. The effective sample size for a particular treatment comparison can be interpreted as the number of patients in a pairwise meta-analysis that would provide the same degree and strength of evidence as that which is provided in the indirect comparison or network meta-analysis. We further develop methods for retrospectively estimating the statistical power for each comparison in a network meta-analysis. We illustrate the performance of the proposed methods for estimating effective sample size and statistical power using data from a network meta-analysis on interventions for smoking cessation including over 100 trials. Conclusion The proposed methods are easy to use and will be of high value to regulatory agencies and decision makers who must assess the strength of the evidence supporting comparative effectiveness estimates. PMID:22992327

Measuring larval nematode contamination on cattle pastures: Comparing two herbage sampling methods.

PubMed

Verschave, S H; Levecke, B; Duchateau, L; Vercruysse, J; Charlier, J

2015-06-15

Assessing levels of pasture larval contamination is frequently used to study the population dynamics of the free-living stages of parasitic nematodes of livestock. Direct quantification of infective larvae (L3) on herbage is the most applied method to measure pasture larval contamination. However, herbage collection remains labour intensive and there is a lack of studies addressing the variation induced by the sampling method and the required sample size. The aim of this study was (1) to compare two different sampling methods in terms of pasture larval count results and time required to sample, (2) to assess the amount of variation in larval counts at the level of sample plot, pasture and season, respectively and (3) to calculate the required sample size to assess pasture larval contamination with a predefined precision using random plots across pasture. Eight young stock pastures of different commercial dairy herds were sampled in three consecutive seasons during the grazing season (spring, summer and autumn). On each pasture, herbage samples were collected through both a double-crossed W-transect with samples taken every 10 steps (method 1) and four random located plots of 0.16 m(2) with collection of all herbage within the plot (method 2). The average (± standard deviation (SD)) pasture larval contamination using sampling methods 1 and 2 was 325 (± 479) and 305 (± 444)L3/kg dry herbage (DH), respectively. Large discrepancies in pasture larval counts of the same pasture and season were often seen between methods, but no significant difference (P = 0.38) in larval counts between methods was found. Less time was required to collect samples with method 2. This difference in collection time between methods was most pronounced for pastures with a surface area larger than 1 ha. The variation in pasture larval counts from samples generated by random plot sampling was mainly due to the repeated measurements on the same pasture in the same season (residual variance component = 6.2), rather than due to pasture (variance component = 0.55) or season (variance component = 0.15). Using the observed distribution of L3, the required sample size (i.e. number of plots per pasture) for sampling a pasture through random plots with a particular precision was simulated. A higher relative precision was acquired when estimating PLC on pastures with a high larval contamination and a low level of aggregation compared to pastures with a low larval contamination when the same sample size was applied. In the future, herbage sampling through random plots across pasture (method 2) seems a promising method to develop further as no significant difference in counts between the methods was found and this method was less time consuming. Copyright © 2015 Elsevier B.V. All rights reserved.

A LDR-PCR approach for multiplex polymorphisms genotyping of severely degraded DNA with fragment sizes <100 bp.

PubMed

Zhang, Zhen; Wang, Bao-Jie; Guan, Hong-Yu; Pang, Hao; Xuan, Jin-Feng

2009-11-01

Reducing amplicon sizes has become a major strategy for analyzing degraded DNA typical of forensic samples. However, amplicon sizes in current mini-short tandem repeat-polymerase chain reaction (PCR) and mini-sequencing assays are still not suitable for analysis of severely degraded DNA. In this study, we present a multiplex typing method that couples ligase detection reaction with PCR that can be used to identify single nucleotide polymorphisms and small-scale insertion/deletions in a sample of severely fragmented DNA. This method adopts thermostable ligation for allele discrimination and subsequent PCR for signal enhancement. In this study, four polymorphic loci were used to assess the ability of this technique to discriminate alleles in an artificially degraded sample of DNA with fragment sizes <100 bp. Our results showed clear allelic discrimination of single or multiple loci, suggesting that this method might aid in the analysis of extremely degraded samples in which allelic drop out of larger fragments is observed.

Effects of Sample Preparation on the Infrared Reflectance Spectra of Powders

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

Brauer, Carolyn S.; Johnson, Timothy J.; Myers, Tanya L.

2015-05-22

While reflectance spectroscopy is a useful tool in identifying molecular compounds, laboratory measurement of solid (particularly powder) samples often is confounded by sample preparation methods. For example, both the packing density and surface roughness can have an effect on the quantitative reflectance spectra of powdered samples. Recent efforts in our group have focused on developing standard methods for measuring reflectance spectra that accounts for sample preparation, as well as other factors such as particle size and provenance. In this work, the effect of preparation method on sample reflectivity was investigated by measuring the directional-hemispherical spectra of samples that were hand-packedmore » as well as pressed into pellets using an integrating sphere attached to a Fourier transform infrared spectrometer. The results show that the methods used to prepare the sample have a substantial effect on the measured reflectance spectra, as do other factors such as particle size.« less

Effects of sample preparation on the infrared reflectance spectra of powders

NASA Astrophysics Data System (ADS)

Brauer, Carolyn S.; Johnson, Timothy J.; Myers, Tanya L.; Su, Yin-Fong; Blake, Thomas A.; Forland, Brenda M.

2015-05-01

While reflectance spectroscopy is a useful tool for identifying molecular compounds, laboratory measurement of solid (particularly powder) samples often is confounded by sample preparation methods. For example, both the packing density and surface roughness can have an effect on the quantitative reflectance spectra of powdered samples. Recent efforts in our group have focused on developing standard methods for measuring reflectance spectra that accounts for sample preparation, as well as other factors such as particle size and provenance. In this work, the effect of preparation method on sample reflectivity was investigated by measuring the directional-hemispherical spectra of samples that were hand-loaded as well as pressed into pellets using an integrating sphere attached to a Fourier transform infrared spectrometer. The results show that the methods used to prepare the sample can have a substantial effect on the measured reflectance spectra, as do other factors such as particle size.

After site selection and before data analysis: sampling, sorting, and laboratory procedures used in stream benthic macroinvertebrate monitoring programs by USA state agencies

USGS Publications Warehouse

Carter, James L.; Resh, Vincent H.

2001-01-01

A survey of methods used by US state agencies for collecting and processing benthic macroinvertebrate samples from streams was conducted by questionnaire; 90 responses were received and used to describe trends in methods. The responses represented an estimated 13,000-15,000 samples collected and processed per year. Kicknet devices were used in 64.5% of the methods; other sampling devices included fixed-area samplers (Surber and Hess), artificial substrates (Hester-Dendy and rock baskets), grabs, and dipnets. Regional differences existed, e.g., the 1-m kicknet was used more often in the eastern US than in the western US. Mesh sizes varied among programs but 80.2% of the methods used a mesh size between 500 and 600 (mu or u)m. Mesh size variations within US Environmental Protection Agency regions were large, with size differences ranging from 100 to 700 (mu or u)m. Most samples collected were composites; the mean area sampled was 1.7 m2. Samples rarely were collected using a random method (4.7%); most samples (70.6%) were collected using "expert opinion", which may make data obtained operator-specific. Only 26.3% of the methods sorted all the organisms from a sample; the remainder subsampled in the laboratory. The most common method of subsampling was to remove 100 organisms (range = 100-550). The magnification used for sorting ranged from 1 (sorting by eye) to 30x, which results in inconsistent separation of macroinvertebrates from detritus. In addition to subsampling, 53% of the methods sorted large/rare organisms from a sample. The taxonomic level used for identifying organisms varied among taxa; Ephemeroptera, Plecoptera, and Trichoptera were generally identified to a finer taxonomic resolution (genus and species) than other taxa. Because there currently exists a large range of field and laboratory methods used by state programs, calibration among all programs to increase data comparability would be exceptionally challenging. However, because many techniques are shared among methods, limited testing could be designed to evaluate whether procedural differences affect the ability to determine levels of environmental impairment using benthic macroinvertebrate communities.

Analysis of YBCO high temperature superconductor doped with silver nanoparticles and carbon nanotubes using Williamson-Hall and size-strain plot

NASA Astrophysics Data System (ADS)

Dadras, Sedigheh; Davoudiniya, Masoumeh

2018-05-01

This paper sets out to investigate and compare the effects of Ag nanoparticles and carbon nanotubes (CNTs) doping on the mechanical properties of Y1Ba2Cu3O7-δ (YBCO) high temperature superconductor. For this purpose, the pure and doped YBCO samples were synthesized by sol-gel method. The microstructural analysis of the samples is performed using X-ray diffraction (XRD). The crystalline size, lattice strain and stress of the pure and doped YBCO samples were estimated by modified forms of Williamson-Hall analysis (W-H), namely, uniform deformation model (UDM), uniform deformation stress model (UDSM) and the size-strain plot method (SSP). These results show that the crystalline size, lattice strain and stress of the YBCO samples declined by Ag nanoparticles and CNTs doping.

Unfolding sphere size distributions with a density estimator based on Tikhonov regularization

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

Weese, J.; Korat, E.; Maier, D.

1997-12-01

This report proposes a method for unfolding sphere size distributions given a sample of radii that combines the advantages of a density estimator with those of Tikhonov regularization methods. The following topics are discusses in this report to achieve this method: the relation between the profile and the sphere size distribution; the method for unfolding sphere size distributions; the results based on simulations; and the experimental data comparison.

Allocating Sample Sizes to Reduce Budget for Fixed-Effect 2×2 Heterogeneous Analysis of Variance

ERIC Educational Resources Information Center

Luh, Wei-Ming; Guo, Jiin-Huarng

2016-01-01

This article discusses the sample size requirements for the interaction, row, and column effects, respectively, by forming a linear contrast for a 2×2 factorial design for fixed-effects heterogeneous analysis of variance. The proposed method uses the Welch t test and its corresponding degrees of freedom to calculate the final sample size in a…

The effect of clustering on lot quality assurance sampling: a probabilistic model to calculate sample sizes for quality assessments

PubMed Central

2013-01-01

Background Traditional Lot Quality Assurance Sampling (LQAS) designs assume observations are collected using simple random sampling. Alternatively, randomly sampling clusters of observations and then individuals within clusters reduces costs but decreases the precision of the classifications. In this paper, we develop a general framework for designing the cluster(C)-LQAS system and illustrate the method with the design of data quality assessments for the community health worker program in Rwanda. Results To determine sample size and decision rules for C-LQAS, we use the beta-binomial distribution to account for inflated risk of errors introduced by sampling clusters at the first stage. We present general theory and code for sample size calculations. The C-LQAS sample sizes provided in this paper constrain misclassification risks below user-specified limits. Multiple C-LQAS systems meet the specified risk requirements, but numerous considerations, including per-cluster versus per-individual sampling costs, help identify optimal systems for distinct applications. Conclusions We show the utility of C-LQAS for data quality assessments, but the method generalizes to numerous applications. This paper provides the necessary technical detail and supplemental code to support the design of C-LQAS for specific programs. PMID:24160725

The effect of clustering on lot quality assurance sampling: a probabilistic model to calculate sample sizes for quality assessments.

PubMed

Hedt-Gauthier, Bethany L; Mitsunaga, Tisha; Hund, Lauren; Olives, Casey; Pagano, Marcello

2013-10-26

Traditional Lot Quality Assurance Sampling (LQAS) designs assume observations are collected using simple random sampling. Alternatively, randomly sampling clusters of observations and then individuals within clusters reduces costs but decreases the precision of the classifications. In this paper, we develop a general framework for designing the cluster(C)-LQAS system and illustrate the method with the design of data quality assessments for the community health worker program in Rwanda. To determine sample size and decision rules for C-LQAS, we use the beta-binomial distribution to account for inflated risk of errors introduced by sampling clusters at the first stage. We present general theory and code for sample size calculations.The C-LQAS sample sizes provided in this paper constrain misclassification risks below user-specified limits. Multiple C-LQAS systems meet the specified risk requirements, but numerous considerations, including per-cluster versus per-individual sampling costs, help identify optimal systems for distinct applications. We show the utility of C-LQAS for data quality assessments, but the method generalizes to numerous applications. This paper provides the necessary technical detail and supplemental code to support the design of C-LQAS for specific programs.

Cluster randomised crossover trials with binary data and unbalanced cluster sizes: application to studies of near-universal interventions in intensive care.

PubMed

Forbes, Andrew B; Akram, Muhammad; Pilcher, David; Cooper, Jamie; Bellomo, Rinaldo

2015-02-01

Cluster randomised crossover trials have been utilised in recent years in the health and social sciences. Methods for analysis have been proposed; however, for binary outcomes, these have received little assessment of their appropriateness. In addition, methods for determination of sample size are currently limited to balanced cluster sizes both between clusters and between periods within clusters. This article aims to extend this work to unbalanced situations and to evaluate the properties of a variety of methods for analysis of binary data, with a particular focus on the setting of potential trials of near-universal interventions in intensive care to reduce in-hospital mortality. We derive a formula for sample size estimation for unbalanced cluster sizes, and apply it to the intensive care setting to demonstrate the utility of the cluster crossover design. We conduct a numerical simulation of the design in the intensive care setting and for more general configurations, and we assess the performance of three cluster summary estimators and an individual-data estimator based on binomial-identity-link regression. For settings similar to the intensive care scenario involving large cluster sizes and small intra-cluster correlations, the sample size formulae developed and analysis methods investigated are found to be appropriate, with the unweighted cluster summary method performing well relative to the more optimal but more complex inverse-variance weighted method. More generally, we find that the unweighted and cluster-size-weighted summary methods perform well, with the relative efficiency of each largely determined systematically from the study design parameters. Performance of individual-data regression is adequate with small cluster sizes but becomes inefficient for large, unbalanced cluster sizes. When outcome prevalences are 6% or less and the within-cluster-within-period correlation is 0.05 or larger, all methods display sub-nominal confidence interval coverage, with the less prevalent the outcome the worse the coverage. As with all simulation studies, conclusions are limited to the configurations studied. We confined attention to detecting intervention effects on an absolute risk scale using marginal models and did not explore properties of binary random effects models. Cluster crossover designs with binary outcomes can be analysed using simple cluster summary methods, and sample size in unbalanced cluster size settings can be determined using relatively straightforward formulae. However, caution needs to be applied in situations with low prevalence outcomes and moderate to high intra-cluster correlations. © The Author(s) 2014.

Image analysis of representative food structures: application of the bootstrap method.

PubMed

Ramírez, Cristian; Germain, Juan C; Aguilera, José M

2009-08-01

Images (for example, photomicrographs) are routinely used as qualitative evidence of the microstructure of foods. In quantitative image analysis it is important to estimate the area (or volume) to be sampled, the field of view, and the resolution. The bootstrap method is proposed to estimate the size of the sampling area as a function of the coefficient of variation (CV(Bn)) and standard error (SE(Bn)) of the bootstrap taking sub-areas of different sizes. The bootstrap method was applied to simulated and real structures (apple tissue). For simulated structures, 10 computer-generated images were constructed containing 225 black circles (elements) and different coefficient of variation (CV(image)). For apple tissue, 8 images of apple tissue containing cellular cavities with different CV(image) were analyzed. Results confirmed that for simulated and real structures, increasing the size of the sampling area decreased the CV(Bn) and SE(Bn). Furthermore, there was a linear relationship between the CV(image) and CV(Bn) (.) For example, to obtain a CV(Bn) = 0.10 in an image with CV(image) = 0.60, a sampling area of 400 x 400 pixels (11% of whole image) was required, whereas if CV(image) = 1.46, a sampling area of 1000 x 100 pixels (69% of whole image) became necessary. This suggests that a large-size dispersion of element sizes in an image requires increasingly larger sampling areas or a larger number of images.

Conceptual data sampling for breast cancer histology image classification.

PubMed

Rezk, Eman; Awan, Zainab; Islam, Fahad; Jaoua, Ali; Al Maadeed, Somaya; Zhang, Nan; Das, Gautam; Rajpoot, Nasir

2017-10-01

Data analytics have become increasingly complicated as the amount of data has increased. One technique that is used to enable data analytics in large datasets is data sampling, in which a portion of the data is selected to preserve the data characteristics for use in data analytics. In this paper, we introduce a novel data sampling technique that is rooted in formal concept analysis theory. This technique is used to create samples reliant on the data distribution across a set of binary patterns. The proposed sampling technique is applied in classifying the regions of breast cancer histology images as malignant or benign. The performance of our method is compared to other classical sampling methods. The results indicate that our method is efficient and generates an illustrative sample of small size. It is also competing with other sampling methods in terms of sample size and sample quality represented in classification accuracy and F1 measure. Copyright © 2017 Elsevier Ltd. All rights reserved.

Sample size calculation for a proof of concept study.

PubMed

Yin, Yin

2002-05-01

Sample size calculation is vital for a confirmatory clinical trial since the regulatory agencies require the probability of making Type I error to be significantly small, usually less than 0.05 or 0.025. However, the importance of the sample size calculation for studies conducted by a pharmaceutical company for internal decision making, e.g., a proof of concept (PoC) study, has not received enough attention. This article introduces a Bayesian method that identifies the information required for planning a PoC and the process of sample size calculation. The results will be presented in terms of the relationships between the regulatory requirements, the probability of reaching the regulatory requirements, the goalpost for PoC, and the sample size used for PoC.

Synthesis, characterization, and hydrogen uptake studies of magnesium nanoparticles by solution reduction method

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

Rather, Sami ullah, E-mail: rathersami@gmail.com

2014-12-15

Graphical abstract: X-ray diffraction (XRD) pattern of magnesium nanoparticles synthesized by solution reduction method with and without TOPO. - Highlights: • Simple and convenient method of preparing Mg nanoparticles. • Characterized by XRD, SEM, FESEM and TEM. • Trioctylphosphine oxide offers a greater control over the size of the particles. • Hydrogen uptake of samples at different temperatures and pressure of 4.5 MPa. - Abstract: Facile and simple, surfactant-mediated solution reduction method was used to synthesize monodisperse magnesium nanoparticles. Little amount of magnesium oxide nanoparticles were also formed due to the presence of TOPO and easy oxidation of magnesium, eventhough,more » all precautions were taken to avoid oxidation of the sample. Precise size control of particles was achieved by carefully varying the concentration ratio of two different types of surfactants, – trioctylphosphine oxide and hexadecylamine. Recrystallized magnesium nanoparticle samples with and without TOPO were analyzed by X-ray diffraction, scanning electron microscope, field emission scanning electron microscope, and transmission electron microscope. The peak diameters of particles were estimated from size distribution analysis of the morphological data. The particles synthesized in the presence and absence of TOPO found to have diameters 46.5 and 34.8 nm, respectively. This observed dependence of particle size on the presence of TOPO offers a convenient method to control the particle size by simply using appropriate surfactant concentrations. Exceptional enhancement in hydrogen uptake and kinetics in synthesized magnesium nanoparticles as compared to commercial magnesium sample was due to the smaller particle size and improved morphology. Overall hydrogen uptake not affected by the little variation in particle size with and without TOPO.« less

Precision Efficacy Analysis for Regression.

ERIC Educational Resources Information Center

Brooks, Gordon P.

When multiple linear regression is used to develop a prediction model, sample size must be large enough to ensure stable coefficients. If the derivation sample size is inadequate, the model may not predict well for future subjects. The precision efficacy analysis for regression (PEAR) method uses a cross- validity approach to select sample sizes…

Estimation of sample size and testing power (part 5).

PubMed

Hu, Liang-ping; Bao, Xiao-lei; Guan, Xue; Zhou, Shi-guo

2012-02-01

Estimation of sample size and testing power is an important component of research design. This article introduced methods for sample size and testing power estimation of difference test for quantitative and qualitative data with the single-group design, the paired design or the crossover design. To be specific, this article introduced formulas for sample size and testing power estimation of difference test for quantitative and qualitative data with the above three designs, the realization based on the formulas and the POWER procedure of SAS software and elaborated it with examples, which will benefit researchers for implementing the repetition principle.

The Impact of Sample Size and Other Factors When Estimating Multilevel Logistic Models

ERIC Educational Resources Information Center

Schoeneberger, Jason A.

2016-01-01

The design of research studies utilizing binary multilevel models must necessarily incorporate knowledge of multiple factors, including estimation method, variance component size, or number of predictors, in addition to sample sizes. This Monte Carlo study examined the performance of random effect binary outcome multilevel models under varying…

Optimal sample sizes for the design of reliability studies: power consideration.

PubMed

Shieh, Gwowen

2014-09-01

Intraclass correlation coefficients are used extensively to measure the reliability or degree of resemblance among group members in multilevel research. This study concerns the problem of the necessary sample size to ensure adequate statistical power for hypothesis tests concerning the intraclass correlation coefficient in the one-way random-effects model. In view of the incomplete and problematic numerical results in the literature, the approximate sample size formula constructed from Fisher's transformation is reevaluated and compared with an exact approach across a wide range of model configurations. These comprehensive examinations showed that the Fisher transformation method is appropriate only under limited circumstances, and therefore it is not recommended as a general method in practice. For advance design planning of reliability studies, the exact sample size procedures are fully described and illustrated for various allocation and cost schemes. Corresponding computer programs are also developed to implement the suggested algorithms.

MUDMASTER: A Program for Calculating Crystalline Size Distributions and Strain from the Shapes of X-Ray Diffraction Peaks

USGS Publications Warehouse

Eberl, D.D.; Drits, V.A.; Środoń, Jan; Nüesch, R.

1996-01-01

Particle size may strongly influence the physical and chemical properties of a substance (e.g. its rheology, surface area, cation exchange capacity, solubility, etc.), and its measurement in rocks may yield geological information about ancient environments (sediment provenance, degree of metamorphism, degree of weathering, current directions, distance to shore, etc.). Therefore mineralogists, geologists, chemists, soil scientists, and others who deal with clay-size material would like to have a convenient method for measuring particle size distributions. Nano-size crystals generally are too fine to be measured by light microscopy. Laser scattering methods give only average particle sizes; therefore particle size can not be measured in a particular crystallographic direction. Also, the particles measured by laser techniques may be composed of several different minerals, and may be agglomerations of individual crystals. Measurement by electron and atomic force microscopy is tedious, expensive, and time consuming. It is difficult to measure more than a few hundred particles per sample by these methods. This many measurements, often taking several days of intensive effort, may yield an accurate mean size for a sample, but may be too few to determine an accurate distribution of sizes. Measurement of size distributions by X-ray diffraction (XRD) solves these shortcomings. An X-ray scan of a sample occurs automatically, taking a few minutes to a few hours. The resulting XRD peaks average diffraction effects from billions of individual nano-size crystals. The size that is measured by XRD may be related to the size of the individual crystals of the mineral in the sample, rather than to the size of particles formed from the agglomeration of these crystals. Therefore one can determine the size of a particular mineral in a mixture of minerals, and the sizes in a particular crystallographic direction of that mineral.

Effect of finite sample size on feature selection and classification: a simulation study.

PubMed

Way, Ted W; Sahiner, Berkman; Hadjiiski, Lubomir M; Chan, Heang-Ping

2010-02-01

The small number of samples available for training and testing is often the limiting factor in finding the most effective features and designing an optimal computer-aided diagnosis (CAD) system. Training on a limited set of samples introduces bias and variance in the performance of a CAD system relative to that trained with an infinite sample size. In this work, the authors conducted a simulation study to evaluate the performances of various combinations of classifiers and feature selection techniques and their dependence on the class distribution, dimensionality, and the training sample size. The understanding of these relationships will facilitate development of effective CAD systems under the constraint of limited available samples. Three feature selection techniques, the stepwise feature selection (SFS), sequential floating forward search (SFFS), and principal component analysis (PCA), and two commonly used classifiers, Fisher's linear discriminant analysis (LDA) and support vector machine (SVM), were investigated. Samples were drawn from multidimensional feature spaces of multivariate Gaussian distributions with equal or unequal covariance matrices and unequal means, and with equal covariance matrices and unequal means estimated from a clinical data set. Classifier performance was quantified by the area under the receiver operating characteristic curve Az. The mean Az values obtained by resubstitution and hold-out methods were evaluated for training sample sizes ranging from 15 to 100 per class. The number of simulated features available for selection was chosen to be 50, 100, and 200. It was found that the relative performance of the different combinations of classifier and feature selection method depends on the feature space distributions, the dimensionality, and the available training sample sizes. The LDA and SVM with radial kernel performed similarly for most of the conditions evaluated in this study, although the SVM classifier showed a slightly higher hold-out performance than LDA for some conditions and vice versa for other conditions. PCA was comparable to or better than SFS and SFFS for LDA at small samples sizes, but inferior for SVM with polynomial kernel. For the class distributions simulated from clinical data, PCA did not show advantages over the other two feature selection methods. Under this condition, the SVM with radial kernel performed better than the LDA when few training samples were available, while LDA performed better when a large number of training samples were available. None of the investigated feature selection-classifier combinations provided consistently superior performance under the studied conditions for different sample sizes and feature space distributions. In general, the SFFS method was comparable to the SFS method while PCA may have an advantage for Gaussian feature spaces with unequal covariance matrices. The performance of the SVM with radial kernel was better than, or comparable to, that of the SVM with polynomial kernel under most conditions studied.

Measures of precision for dissimilarity-based multivariate analysis of ecological communities.

PubMed

Anderson, Marti J; Santana-Garcon, Julia

2015-01-01

Ecological studies require key decisions regarding the appropriate size and number of sampling units. No methods currently exist to measure precision for multivariate assemblage data when dissimilarity-based analyses are intended to follow. Here, we propose a pseudo multivariate dissimilarity-based standard error (MultSE) as a useful quantity for assessing sample-size adequacy in studies of ecological communities. Based on sums of squared dissimilarities, MultSE measures variability in the position of the centroid in the space of a chosen dissimilarity measure under repeated sampling for a given sample size. We describe a novel double resampling method to quantify uncertainty in MultSE values with increasing sample size. For more complex designs, values of MultSE can be calculated from the pseudo residual mean square of a permanova model, with the double resampling done within appropriate cells in the design. R code functions for implementing these techniques, along with ecological examples, are provided. © 2014 The Authors. Ecology Letters published by John Wiley & Sons Ltd and CNRS.

Random vs. systematic sampling from administrative databases involving human subjects.

PubMed

Hagino, C; Lo, R J

1998-09-01

Two sampling techniques, simple random sampling (SRS) and systematic sampling (SS), were compared to determine whether they yield similar and accurate distributions for the following four factors: age, gender, geographic location and years in practice. Any point estimate within 7 yr or 7 percentage points of its reference standard (SRS or the entire data set, i.e., the target population) was considered "acceptably similar" to the reference standard. The sampling frame was from the entire membership database of the Canadian Chiropractic Association. The two sampling methods were tested using eight different sample sizes of n (50, 100, 150, 200, 250, 300, 500, 800). From the profile/characteristics, summaries of four known factors [gender, average age, number (%) of chiropractors in each province and years in practice], between- and within-methods chi 2 tests and unpaired t tests were performed to determine whether any of the differences [descriptively greater than 7% or 7 yr] were also statistically significant. The strengths of the agreements between the provincial distributions were quantified by calculating the percent agreements for each (provincial pairwise-comparison methods). Any percent agreement less than 70% was judged to be unacceptable. Our assessments of the two sampling methods (SRS and SS) for the different sample sizes tested suggest that SRS and SS yielded acceptably similar results. Both methods started to yield "correct" sample profiles at approximately the same sample size (n > 200). SS is not only convenient, it can be recommended for sampling from large databases in which the data are listed without any inherent order biases other than alphabetical listing by surname.

Internal pilots for a class of linear mixed models with Gaussian and compound symmetric data

PubMed Central

Gurka, Matthew J.; Coffey, Christopher S.; Muller, Keith E.

2015-01-01

SUMMARY An internal pilot design uses interim sample size analysis, without interim data analysis, to adjust the final number of observations. The approach helps to choose a sample size sufficiently large (to achieve the statistical power desired), but not too large (which would waste money and time). We report on recent research in cerebral vascular tortuosity (curvature in three dimensions) which would benefit greatly from internal pilots due to uncertainty in the parameters of the covariance matrix used for study planning. Unfortunately, observations correlated across the four regions of the brain and small sample sizes preclude using existing methods. However, as in a wide range of medical imaging studies, tortuosity data have no missing or mistimed data, a factorial within-subject design, the same between-subject design for all responses, and a Gaussian distribution with compound symmetry. For such restricted models, we extend exact, small sample univariate methods for internal pilots to linear mixed models with any between-subject design (not just two groups). Planning a new tortuosity study illustrates how the new methods help to avoid sample sizes that are too small or too large while still controlling the type I error rate. PMID:17318914

Comparison of Two Methods Used to Model Shape Parameters of Pareto Distributions

USGS Publications Warehouse

Liu, C.; Charpentier, R.R.; Su, J.

2011-01-01

Two methods are compared for estimating the shape parameters of Pareto field-size (or pool-size) distributions for petroleum resource assessment. Both methods assume mature exploration in which most of the larger fields have been discovered. Both methods use the sizes of larger discovered fields to estimate the numbers and sizes of smaller fields: (1) the tail-truncated method uses a plot of field size versus size rank, and (2) the log-geometric method uses data binned in field-size classes and the ratios of adjacent bin counts. Simulation experiments were conducted using discovered oil and gas pool-size distributions from four petroleum systems in Alberta, Canada and using Pareto distributions generated by Monte Carlo simulation. The estimates of the shape parameters of the Pareto distributions, calculated by both the tail-truncated and log-geometric methods, generally stabilize where discovered pool numbers are greater than 100. However, with fewer than 100 discoveries, these estimates can vary greatly with each new discovery. The estimated shape parameters of the tail-truncated method are more stable and larger than those of the log-geometric method where the number of discovered pools is more than 100. Both methods, however, tend to underestimate the shape parameter. Monte Carlo simulation was also used to create sequences of discovered pool sizes by sampling from a Pareto distribution with a discovery process model using a defined exploration efficiency (in order to show how biased the sampling was in favor of larger fields being discovered first). A higher (more biased) exploration efficiency gives better estimates of the Pareto shape parameters. ?? 2011 International Association for Mathematical Geosciences.

Automated sampling assessment for molecular simulations using the effective sample size

PubMed Central

Zhang, Xin; Bhatt, Divesh; Zuckerman, Daniel M.

2010-01-01

To quantify the progress in the development of algorithms and forcefields used in molecular simulations, a general method for the assessment of the sampling quality is needed. Statistical mechanics principles suggest the populations of physical states characterize equilibrium sampling in a fundamental way. We therefore develop an approach for analyzing the variances in state populations, which quantifies the degree of sampling in terms of the effective sample size (ESS). The ESS estimates the number of statistically independent configurations contained in a simulated ensemble. The method is applicable to both traditional dynamics simulations as well as more modern (e.g., multi–canonical) approaches. Our procedure is tested in a variety of systems from toy models to atomistic protein simulations. We also introduce a simple automated procedure to obtain approximate physical states from dynamic trajectories: this allows sample–size estimation in systems for which physical states are not known in advance. PMID:21221418

Power/Sample Size Calculations for Assessing Correlates of Risk in Clinical Efficacy Trials

PubMed Central

Gilbert, Peter B.; Janes, Holly E.; Huang, Yunda

2016-01-01

In a randomized controlled clinical trial that assesses treatment efficacy, a common objective is to assess the association of a measured biomarker response endpoint with the primary study endpoint in the active treatment group, using a case-cohort, case-control, or two-phase sampling design. Methods for power and sample size calculations for such biomarker association analyses typically do not account for the level of treatment efficacy, precluding interpretation of the biomarker association results in terms of biomarker effect modification of treatment efficacy, with detriment that the power calculations may tacitly and inadvertently assume that the treatment harms some study participants. We develop power and sample size methods accounting for this issue, and the methods also account for inter-individual variability of the biomarker that is not biologically relevant (e.g., due to technical measurement error). We focus on a binary study endpoint and on a biomarker subject to measurement error that is normally distributed or categorical with two or three levels. We illustrate the methods with preventive HIV vaccine efficacy trials, and include an R package implementing the methods. PMID:27037797

Sampling bee communities using pan traps: alternative methods increase sample size

USDA-ARS?s Scientific Manuscript database

Monitoring of the status of bee populations and inventories of bee faunas require systematic sampling. Efficiency and ease of implementation has encouraged the use of pan traps to sample bees. Efforts to find an optimal standardized sampling method for pan traps have focused on pan trap color. Th...

Maximum type I error rate inflation from sample size reassessment when investigators are blind to treatment labels.

PubMed

Żebrowska, Magdalena; Posch, Martin; Magirr, Dominic

2016-05-30

Consider a parallel group trial for the comparison of an experimental treatment to a control, where the second-stage sample size may depend on the blinded primary endpoint data as well as on additional blinded data from a secondary endpoint. For the setting of normally distributed endpoints, we demonstrate that this may lead to an inflation of the type I error rate if the null hypothesis holds for the primary but not the secondary endpoint. We derive upper bounds for the inflation of the type I error rate, both for trials that employ random allocation and for those that use block randomization. We illustrate the worst-case sample size reassessment rule in a case study. For both randomization strategies, the maximum type I error rate increases with the effect size in the secondary endpoint and the correlation between endpoints. The maximum inflation increases with smaller block sizes if information on the block size is used in the reassessment rule. Based on our findings, we do not question the well-established use of blinded sample size reassessment methods with nuisance parameter estimates computed from the blinded interim data of the primary endpoint. However, we demonstrate that the type I error rate control of these methods relies on the application of specific, binding, pre-planned and fully algorithmic sample size reassessment rules and does not extend to general or unplanned sample size adjustments based on blinded data. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Norm Block Sample Sizes: A Review of 17 Individually Administered Intelligence Tests

ERIC Educational Resources Information Center

Norfolk, Philip A.; Farmer, Ryan L.; Floyd, Randy G.; Woods, Isaac L.; Hawkins, Haley K.; Irby, Sarah M.

2015-01-01

The representativeness, recency, and size of norm samples strongly influence the accuracy of inferences drawn from their scores. Inadequate norm samples may lead to inflated or deflated scores for individuals and poorer prediction of developmental and academic outcomes. The purpose of this study was to apply Kranzler and Floyd's method for…

SnagPRO: snag and tree sampling and analysis methods for wildlife

Treesearch

Lisa J. Bate; Michael J. Wisdom; Edward O. Garton; Shawn C. Clabough

2008-01-01

We describe sampling methods and provide software to accurately and efficiently estimate snag and tree densities at desired scales to meet a variety of research and management objectives. The methods optimize sampling effort by choosing a plot size appropriate for the specified forest conditions and sampling goals. Plot selection and data analyses are supported by...

Estimation and applications of size-biased distributions in forestry

Treesearch

Jeffrey H. Gove

2003-01-01

Size-biased distributions arise naturally in several contexts in forestry and ecology. Simple power relationships (e.g. basal area and diameter at breast height) between variables are one such area of interest arising from a modelling perspective. Another, probability proportional to size PPS) sampling, is found in the most widely used methods for sampling standing or...

Variance Estimation, Design Effects, and Sample Size Calculations for Respondent-Driven Sampling

PubMed Central

2006-01-01

Hidden populations, such as injection drug users and sex workers, are central to a number of public health problems. However, because of the nature of these groups, it is difficult to collect accurate information about them, and this difficulty complicates disease prevention efforts. A recently developed statistical approach called respondent-driven sampling improves our ability to study hidden populations by allowing researchers to make unbiased estimates of the prevalence of certain traits in these populations. Yet, not enough is known about the sample-to-sample variability of these prevalence estimates. In this paper, we present a bootstrap method for constructing confidence intervals around respondent-driven sampling estimates and demonstrate in simulations that it outperforms the naive method currently in use. We also use simulations and real data to estimate the design effects for respondent-driven sampling in a number of situations. We conclude with practical advice about the power calculations that are needed to determine the appropriate sample size for a study using respondent-driven sampling. In general, we recommend a sample size twice as large as would be needed under simple random sampling. PMID:16937083

Selective counting and sizing of single virus particles using fluorescent aptamer-based nanoparticle tracking analysis.

PubMed

Szakács, Zoltán; Mészáros, Tamás; de Jonge, Marien I; Gyurcsányi, Róbert E

2018-05-30

Detection and counting of single virus particles in liquid samples are largely limited to narrow size distribution of viruses and purified formulations. To address these limitations, here we propose a calibration-free method that enables concurrently the selective recognition, counting and sizing of virus particles as demonstrated through the detection of human respiratory syncytial virus (RSV), an enveloped virus with a broad size distribution, in throat swab samples. RSV viruses were selectively labeled through their attachment glycoproteins (G) with fluorescent aptamers, which further enabled their identification, sizing and counting at the single particle level by fluorescent nanoparticle tracking analysis. The proposed approach seems to be generally applicable to virus detection and quantification. Moreover, it could be successfully applied to detect single RSV particles in swab samples of diagnostic relevance. Since the selective recognition is associated with the sizing of each detected particle, this method enables to discriminate viral elements linked to the virus as well as various virus forms and associations.

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

PubMed

Kunz, Cornelia U; Stallard, Nigel; Parsons, Nicholas; Todd, Susan; Friede, Tim

2017-03-01

Regulatory authorities require that the sample size of a confirmatory trial is calculated prior to the start of the trial. However, the sample size quite often depends on parameters that might not be known in advance of the study. Misspecification of these parameters can lead to under- or overestimation of the sample size. Both situations are unfavourable as the first one decreases the power and the latter one leads to a waste of resources. Hence, designs have been suggested that allow a re-assessment of the sample size in an ongoing trial. These methods usually focus on estimating the variance. However, for some methods the performance depends not only on the variance but also on the correlation between measurements. We develop and compare different methods for blinded estimation of the correlation coefficient that are less likely to introduce operational bias when the blinding is maintained. Their performance with respect to bias and standard error is compared to the unblinded estimator. We simulated two different settings: one assuming that all group means are the same and one assuming that different groups have different means. Simulation results show that the naïve (one-sample) estimator is only slightly biased and has a standard error comparable to that of the unblinded estimator. However, if the group means differ, other estimators have better performance depending on the sample size per group and the number of groups. © 2016 The Authors. Biometrical Journal Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed Central

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

2016-01-01

Regulatory authorities require that the sample size of a confirmatory trial is calculated prior to the start of the trial. However, the sample size quite often depends on parameters that might not be known in advance of the study. Misspecification of these parameters can lead to under‐ or overestimation of the sample size. Both situations are unfavourable as the first one decreases the power and the latter one leads to a waste of resources. Hence, designs have been suggested that allow a re‐assessment of the sample size in an ongoing trial. These methods usually focus on estimating the variance. However, for some methods the performance depends not only on the variance but also on the correlation between measurements. We develop and compare different methods for blinded estimation of the correlation coefficient that are less likely to introduce operational bias when the blinding is maintained. Their performance with respect to bias and standard error is compared to the unblinded estimator. We simulated two different settings: one assuming that all group means are the same and one assuming that different groups have different means. Simulation results show that the naïve (one‐sample) estimator is only slightly biased and has a standard error comparable to that of the unblinded estimator. However, if the group means differ, other estimators have better performance depending on the sample size per group and the number of groups. PMID:27886393

Minimum and Maximum Times Required to Obtain Representative Suspended Sediment Samples

NASA Astrophysics Data System (ADS)

Gitto, A.; Venditti, J. G.; Kostaschuk, R.; Church, M. A.

2014-12-01

Bottle sampling is a convenient method of obtaining suspended sediment measurements for the development of sediment budgets. While these methods are generally considered to be reliable, recent analysis of depth-integrated sampling has identified considerable uncertainty in measurements of grain-size concentration between grain-size classes of multiple samples. Point-integrated bottle sampling is assumed to represent the mean concentration of suspended sediment but the uncertainty surrounding this method is not well understood. Here we examine at-a-point variability in velocity, suspended sediment concentration, grain-size distribution, and grain-size moments to determine if traditional point-integrated methods provide a representative sample of suspended sediment. We present continuous hour-long observations of suspended sediment from the sand-bedded portion of the Fraser River at Mission, British Columbia, Canada, using a LISST laser-diffraction instrument. Spectral analysis suggests that there are no statistically significant peak in energy density, suggesting the absence of periodic fluctuations in flow and suspended sediment. However, a slope break in the spectra at 0.003 Hz corresponds to a period of 5.5 minutes. This coincides with the threshold between large-scale turbulent eddies that scale with channel width/mean velocity and hydraulic phenomena related to channel dynamics. This suggests that suspended sediment samples taken over a period longer than 5.5 minutes incorporate variability that is larger scale than turbulent phenomena in this channel. Examination of 5.5-minute periods of our time series indicate that ~20% of the time a stable mean value of volumetric concentration is reached within 30 seconds, a typical bottle sample duration. In ~12% of measurements a stable mean was not reached over the 5.5 minute sample duration. The remaining measurements achieve a stable mean in an even distribution over the intervening interval.

Methods for Determining Particle Size Distributions from Nuclear Detonations.

DTIC Science & Technology

1987-03-01

Debris . . . 30 IV. Summary of Sample Preparation Method . . . . 35 V. Set Parameters for PCS ... ........... 39 VI. Analysis by Vendors...54 XV. Results From Brookhaven Analysis Using The Method of Cumulants ... ........... . 54 XVI. Results From Brookhaven Analysis of Sample...R-3 Using Histogram Method ......... .55 XVII. Results From Brookhaven Analysis of Sample R-8 Using Histogram Method ........... 56 XVIII.TEM Particle

Improving the analysis of composite endpoints in rare disease trials.

PubMed

McMenamin, Martina; Berglind, Anna; Wason, James M S

2018-05-22

Composite endpoints are recommended in rare diseases to increase power and/or to sufficiently capture complexity. Often, they are in the form of responder indices which contain a mixture of continuous and binary components. Analyses of these outcomes typically treat them as binary, thus only using the dichotomisations of continuous components. The augmented binary method offers a more efficient alternative and is therefore especially useful for rare diseases. Previous work has indicated the method may have poorer statistical properties when the sample size is small. Here we investigate small sample properties and implement small sample corrections. We re-sample from a previous trial with sample sizes varying from 30 to 80. We apply the standard binary and augmented binary methods and determine the power, type I error rate, coverage and average confidence interval width for each of the estimators. We implement Firth's adjustment for the binary component models and a small sample variance correction for the generalized estimating equations, applying the small sample adjusted methods to each sub-sample as before for comparison. For the log-odds treatment effect the power of the augmented binary method is 20-55% compared to 12-20% for the standard binary method. Both methods have approximately nominal type I error rates. The difference in response probabilities exhibit similar power but both unadjusted methods demonstrate type I error rates of 6-8%. The small sample corrected methods have approximately nominal type I error rates. On both scales, the reduction in average confidence interval width when using the adjusted augmented binary method is 17-18%. This is equivalent to requiring a 32% smaller sample size to achieve the same statistical power. The augmented binary method with small sample corrections provides a substantial improvement for rare disease trials using composite endpoints. We recommend the use of the method for the primary analysis in relevant rare disease trials. We emphasise that the method should be used alongside other efforts in improving the quality of evidence generated from rare disease trials rather than replace them.

Comparing fixed sampling with minimizer sampling when using k-mer indexes to find maximal exact matches.

PubMed

Almutairy, Meznah; Torng, Eric

2018-01-01

Bioinformatics applications and pipelines increasingly use k-mer indexes to search for similar sequences. The major problem with k-mer indexes is that they require lots of memory. Sampling is often used to reduce index size and query time. Most applications use one of two major types of sampling: fixed sampling and minimizer sampling. It is well known that fixed sampling will produce a smaller index, typically by roughly a factor of two, whereas it is generally assumed that minimizer sampling will produce faster query times since query k-mers can also be sampled. However, no direct comparison of fixed and minimizer sampling has been performed to verify these assumptions. We systematically compare fixed and minimizer sampling using the human genome as our database. We use the resulting k-mer indexes for fixed sampling and minimizer sampling to find all maximal exact matches between our database, the human genome, and three separate query sets, the mouse genome, the chimp genome, and an NGS data set. We reach the following conclusions. First, using larger k-mers reduces query time for both fixed sampling and minimizer sampling at a cost of requiring more space. If we use the same k-mer size for both methods, fixed sampling requires typically half as much space whereas minimizer sampling processes queries only slightly faster. If we are allowed to use any k-mer size for each method, then we can choose a k-mer size such that fixed sampling both uses less space and processes queries faster than minimizer sampling. The reason is that although minimizer sampling is able to sample query k-mers, the number of shared k-mer occurrences that must be processed is much larger for minimizer sampling than fixed sampling. In conclusion, we argue that for any application where each shared k-mer occurrence must be processed, fixed sampling is the right sampling method.

Comparing fixed sampling with minimizer sampling when using k-mer indexes to find maximal exact matches

PubMed Central

Torng, Eric

2018-01-01

Bioinformatics applications and pipelines increasingly use k-mer indexes to search for similar sequences. The major problem with k-mer indexes is that they require lots of memory. Sampling is often used to reduce index size and query time. Most applications use one of two major types of sampling: fixed sampling and minimizer sampling. It is well known that fixed sampling will produce a smaller index, typically by roughly a factor of two, whereas it is generally assumed that minimizer sampling will produce faster query times since query k-mers can also be sampled. However, no direct comparison of fixed and minimizer sampling has been performed to verify these assumptions. We systematically compare fixed and minimizer sampling using the human genome as our database. We use the resulting k-mer indexes for fixed sampling and minimizer sampling to find all maximal exact matches between our database, the human genome, and three separate query sets, the mouse genome, the chimp genome, and an NGS data set. We reach the following conclusions. First, using larger k-mers reduces query time for both fixed sampling and minimizer sampling at a cost of requiring more space. If we use the same k-mer size for both methods, fixed sampling requires typically half as much space whereas minimizer sampling processes queries only slightly faster. If we are allowed to use any k-mer size for each method, then we can choose a k-mer size such that fixed sampling both uses less space and processes queries faster than minimizer sampling. The reason is that although minimizer sampling is able to sample query k-mers, the number of shared k-mer occurrences that must be processed is much larger for minimizer sampling than fixed sampling. In conclusion, we argue that for any application where each shared k-mer occurrence must be processed, fixed sampling is the right sampling method. PMID:29389989

Sample size determination for estimating antibody seroconversion rate under stable malaria transmission intensity.

PubMed

Sepúlveda, Nuno; Drakeley, Chris

2015-04-03

In the last decade, several epidemiological studies have demonstrated the potential of using seroprevalence (SP) and seroconversion rate (SCR) as informative indicators of malaria burden in low transmission settings or in populations on the cusp of elimination. However, most of studies are designed to control ensuing statistical inference over parasite rates and not on these alternative malaria burden measures. SP is in essence a proportion and, thus, many methods exist for the respective sample size determination. In contrast, designing a study where SCR is the primary endpoint, is not an easy task because precision and statistical power are affected by the age distribution of a given population. Two sample size calculators for SCR estimation are proposed. The first one consists of transforming the confidence interval for SP into the corresponding one for SCR given a known seroreversion rate (SRR). The second calculator extends the previous one to the most common situation where SRR is unknown. In this situation, data simulation was used together with linear regression in order to study the expected relationship between sample size and precision. The performance of the first sample size calculator was studied in terms of the coverage of the confidence intervals for SCR. The results pointed out to eventual problems of under or over coverage for sample sizes ≤250 in very low and high malaria transmission settings (SCR ≤ 0.0036 and SCR ≥ 0.29, respectively). The correct coverage was obtained for the remaining transmission intensities with sample sizes ≥ 50. Sample size determination was then carried out for cross-sectional surveys using realistic SCRs from past sero-epidemiological studies and typical age distributions from African and non-African populations. For SCR < 0.058, African studies require a larger sample size than their non-African counterparts in order to obtain the same precision. The opposite happens for the remaining transmission intensities. With respect to the second sample size calculator, simulation unravelled the likelihood of not having enough information to estimate SRR in low transmission settings (SCR ≤ 0.0108). In that case, the respective estimates tend to underestimate the true SCR. This problem is minimized by sample sizes of no less than 500 individuals. The sample sizes determined by this second method highlighted the prior expectation that, when SRR is not known, sample sizes are increased in relation to the situation of a known SRR. In contrast to the first sample size calculation, African studies would now require lesser individuals than their counterparts conducted elsewhere, irrespective of the transmission intensity. Although the proposed sample size calculators can be instrumental to design future cross-sectional surveys, the choice of a particular sample size must be seen as a much broader exercise that involves weighting statistical precision with ethical issues, available human and economic resources, and possible time constraints. Moreover, if the sample size determination is carried out on varying transmission intensities, as done here, the respective sample sizes can also be used in studies comparing sites with different malaria transmission intensities. In conclusion, the proposed sample size calculators are a step towards the design of better sero-epidemiological studies. Their basic ideas show promise to be applied to the planning of alternative sampling schemes that may target or oversample specific age groups.

A comparison of bootstrap methods and an adjusted bootstrap approach for estimating the prediction error in microarray classification.

PubMed

Jiang, Wenyu; Simon, Richard

2007-12-20

This paper first provides a critical review on some existing methods for estimating the prediction error in classifying microarray data where the number of genes greatly exceeds the number of specimens. Special attention is given to the bootstrap-related methods. When the sample size n is small, we find that all the reviewed methods suffer from either substantial bias or variability. We introduce a repeated leave-one-out bootstrap (RLOOB) method that predicts for each specimen in the sample using bootstrap learning sets of size ln. We then propose an adjusted bootstrap (ABS) method that fits a learning curve to the RLOOB estimates calculated with different bootstrap learning set sizes. The ABS method is robust across the situations we investigate and provides a slightly conservative estimate for the prediction error. Even with small samples, it does not suffer from large upward bias as the leave-one-out bootstrap and the 0.632+ bootstrap, and it does not suffer from large variability as the leave-one-out cross-validation in microarray applications. Copyright (c) 2007 John Wiley & Sons, Ltd.

How conservative is Fisher's exact test? A quantitative evaluation of the two-sample comparative binomial trial.

PubMed

Crans, Gerald G; Shuster, Jonathan J

2008-08-15

The debate as to which statistical methodology is most appropriate for the analysis of the two-sample comparative binomial trial has persisted for decades. Practitioners who favor the conditional methods of Fisher, Fisher's exact test (FET), claim that only experimental outcomes containing the same amount of information should be considered when performing analyses. Hence, the total number of successes should be fixed at its observed level in hypothetical repetitions of the experiment. Using conditional methods in clinical settings can pose interpretation difficulties, since results are derived using conditional sample spaces rather than the set of all possible outcomes. Perhaps more importantly from a clinical trial design perspective, this test can be too conservative, resulting in greater resource requirements and more subjects exposed to an experimental treatment. The actual significance level attained by FET (the size of the test) has not been reported in the statistical literature. Berger (J. R. Statist. Soc. D (The Statistician) 2001; 50:79-85) proposed assessing the conservativeness of conditional methods using p-value confidence intervals. In this paper we develop a numerical algorithm that calculates the size of FET for sample sizes, n, up to 125 per group at the two-sided significance level, alpha = 0.05. Additionally, this numerical method is used to define new significance levels alpha(*) = alpha+epsilon, where epsilon is a small positive number, for each n, such that the size of the test is as close as possible to the pre-specified alpha (0.05 for the current work) without exceeding it. Lastly, a sample size and power calculation example are presented, which demonstrates the statistical advantages of implementing the adjustment to FET (using alpha(*) instead of alpha) in the two-sample comparative binomial trial. 2008 John Wiley & Sons, Ltd

Comparison of particle sizes between 238PuO 2 before aqueous processing, after aqueous processing, and after ball milling

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

Mulford, Roberta Nancy

Particle sizes determined for a single lot of incoming Russian fuel and for a lot of fuel after aqueous processing are compared with particle sizes measured on fuel after ball-milling. The single samples of each type are believed to have particle size distributions typical of oxide from similar lots, as the processing of fuel lots is fairly uniform. Variation between lots is, as yet, uncharacterized. Sampling and particle size measurement methods are discussed elsewhere.

Analysis of $sup 239$Pu and $sup 241$Am in NAEG large-sized bovine samples

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

Major, W.J.; Lee, K.D.; Wessman, R.A.

Methods are described for the analysis of environmental levels of $sup 239$Pu and $sup 241$Am in large-sized bovine samples. Special procedure modifications to overcome the complexities of sample preparation and analyses and special techniques employed to prepare and analyze different types of bovine samples, such as muscle, blood, liver, and bone are discussed. (CH)

Field application of a multi-frequency acoustic instrument to monitor sediment for silt erosion study in Pelton turbine in Himalayan region, India

NASA Astrophysics Data System (ADS)

Rai, A. K.; Kumar, A.; Hies, T.; Nguyen, H. H.

2016-11-01

High sediment load passing through hydropower components erodes the hydraulic components resulting in loss of efficiency, interruptions in power production and downtime for repair/maintenance, especially in Himalayan regions. The size and concentration of sediment play a major role in silt erosion. The traditional process of collecting samples manually to analyse in laboratory cannot suffice the need of monitoring temporal variation in sediment properties. In this study, a multi-frequency acoustic instrument was applied at desilting chamber to monitor sediment size and concentration entering the turbine. The sediment size and concentration entering the turbine were also measured with manual samples collected twice daily. The samples collected manually were analysed in laboratory with a laser diffraction instrument for size and concentration apart from analysis by drying and filtering methods for concentration. A conductivity probe was used to calculate total dissolved solids, which was further used in results from drying method to calculate suspended solid content of the samples. The acoustic instrument was found to provide sediment concentration values similar to drying and filtering methods. However, no good match was found between mean grain size from the acoustic method with the current status of development and laser diffraction method in the first field application presented here. The future versions of the software and significant sensitivity improvements of the ultrasonic transducers are expected to increase the accuracy in the obtained results. As the instrument is able to capture the concentration and in the future most likely more accurate mean grain size of the suspended sediments, its application for monitoring silt erosion in hydropower plant shall be highly useful.

Sampling and data handling methods for inhalable particulate sampling. Final report nov 78-dec 80

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

Smith, W.B.; Cushing, K.M.; Johnson, J.W.

1982-05-01

The report reviews the objectives of a research program on sampling and measuring particles in the inhalable particulate (IP) size range in emissions from stationary sources, and describes methods and equipment required. A computer technique was developed to analyze data on particle-size distributions of samples taken with cascade impactors from industrial process streams. Research in sampling systems for IP matter included concepts for maintaining isokinetic sampling conditions, necessary for representative sampling of the larger particles, while flowrates in the particle-sizing device were constant. Laboratory studies were conducted to develop suitable IP sampling systems with overall cut diameters of 15 micrometersmore » and conforming to a specified collection efficiency curve. Collection efficiencies were similarly measured for a horizontal elutriator. Design parameters were calculated for horizontal elutriators to be used with impactors, the EPA SASS train, and the EPA FAS train. Two cyclone systems were designed and evaluated. Tests on an Andersen Size Selective Inlet, a 15-micrometer precollector for high-volume samplers, showed its performance to be with the proposed limits for IP samplers. A stack sampling system was designed in which the aerosol is diluted in flow patterns and with mixing times simulating those in stack plumes.« less

Support vector regression to predict porosity and permeability: Effect of sample size

NASA Astrophysics Data System (ADS)

Al-Anazi, A. F.; Gates, I. D.

2012-02-01

Porosity and permeability are key petrophysical parameters obtained from laboratory core analysis. Cores, obtained from drilled wells, are often few in number for most oil and gas fields. Porosity and permeability correlations based on conventional techniques such as linear regression or neural networks trained with core and geophysical logs suffer poor generalization to wells with only geophysical logs. The generalization problem of correlation models often becomes pronounced when the training sample size is small. This is attributed to the underlying assumption that conventional techniques employing the empirical risk minimization (ERM) inductive principle converge asymptotically to the true risk values as the number of samples increases. In small sample size estimation problems, the available training samples must span the complexity of the parameter space so that the model is able both to match the available training samples reasonably well and to generalize to new data. This is achieved using the structural risk minimization (SRM) inductive principle by matching the capability of the model to the available training data. One method that uses SRM is support vector regression (SVR) network. In this research, the capability of SVR to predict porosity and permeability in a heterogeneous sandstone reservoir under the effect of small sample size is evaluated. Particularly, the impact of Vapnik's ɛ-insensitivity loss function and least-modulus loss function on generalization performance was empirically investigated. The results are compared to the multilayer perception (MLP) neural network, a widely used regression method, which operates under the ERM principle. The mean square error and correlation coefficients were used to measure the quality of predictions. The results demonstrate that SVR yields consistently better predictions of the porosity and permeability with small sample size than the MLP method. Also, the performance of SVR depends on both kernel function type and loss functions used.

Consideration of Kaolinite Interference Correction for Quartz Measurements in Coal Mine Dust

PubMed Central

Lee, Taekhee; Chisholm, William P.; Kashon, Michael; Key-Schwartz, Rosa J.; Harper, Martin

2015-01-01

Kaolinite interferes with the infrared analysis of quartz. Improper correction can cause over- or underestimation of silica concentration. The standard sampling method for quartz in coal mine dust is size selective, and, since infrared spectrometry is sensitive to particle size, it is intuitively better to use the same size fractions for quantification of quartz and kaolinite. Standard infrared spectrometric methods for quartz measurement in coal mine dust correct interference from the kaolinite, but they do not specify a particle size for the material used for correction. This study compares calibration curves using as-received and respirable size fractions of nine different examples of kaolinite in the different correction methods from the National Institute for Occupational Safety and Health Manual of Analytical Methods (NMAM) 7603 and the Mine Safety and Health Administration (MSHA) P-7. Four kaolinites showed significant differences between calibration curves with as-received and respirable size fractions for NMAM 7603 and seven for MSHA P-7. The quartz mass measured in 48 samples spiked with respirable fraction silica and kaolinite ranged between 0.28 and 23% (NMAM 7603) and 0.18 and 26% (MSHA P-7) of the expected applied mass when the kaolinite interference was corrected with respirable size fraction kaolinite. This is termed “deviation,” not bias, because the applied mass is also subject to unknown variance. Generally, the deviations in the spiked samples are larger when corrected with the as-received size fraction of kaolinite than with the respirable size fraction. Results indicate that if a kaolinite correction with reference material of respirable size fraction is applied in current standard methods for quartz measurement in coal mine dust, the quartz result would be somewhat closer to the true exposure, although the actual mass difference would be small. Most kinds of kaolinite can be used for laboratory calibration, but preferably, the size fraction should be the same as the coal dust being collected. PMID:23767881

Consideration of kaolinite interference correction for quartz measurements in coal mine dust.

PubMed

Lee, Taekhee; Chisholm, William P; Kashon, Michael; Key-Schwartz, Rosa J; Harper, Martin

2013-01-01

Kaolinite interferes with the infrared analysis of quartz. Improper correction can cause over- or underestimation of silica concentration. The standard sampling method for quartz in coal mine dust is size selective, and, since infrared spectrometry is sensitive to particle size, it is intuitively better to use the same size fractions for quantification of quartz and kaolinite. Standard infrared spectrometric methods for quartz measurement in coal mine dust correct interference from the kaolinite, but they do not specify a particle size for the material used for correction. This study compares calibration curves using as-received and respirable size fractions of nine different examples of kaolinite in the different correction methods from the National Institute for Occupational Safety and Health Manual of Analytical Methods (NMAM) 7603 and the Mine Safety and Health Administration (MSHA) P-7. Four kaolinites showed significant differences between calibration curves with as-received and respirable size fractions for NMAM 7603 and seven for MSHA P-7. The quartz mass measured in 48 samples spiked with respirable fraction silica and kaolinite ranged between 0.28 and 23% (NMAM 7603) and 0.18 and 26% (MSHA P-7) of the expected applied mass when the kaolinite interference was corrected with respirable size fraction kaolinite. This is termed "deviation," not bias, because the applied mass is also subject to unknown variance. Generally, the deviations in the spiked samples are larger when corrected with the as-received size fraction of kaolinite than with the respirable size fraction. Results indicate that if a kaolinite correction with reference material of respirable size fraction is applied in current standard methods for quartz measurement in coal mine dust, the quartz result would be somewhat closer to the true exposure, although the actual mass difference would be small. Most kinds of kaolinite can be used for laboratory calibration, but preferably, the size fraction should be the same as the coal dust being collected.

Mass size distribution of particle-bound water

NASA Astrophysics Data System (ADS)

Canepari, S.; Simonetti, G.; Perrino, C.

2017-09-01

The thermal-ramp Karl-Fisher method (tr-KF) for the determination of PM-bound water has been applied to size-segregated PM samples collected in areas subjected to different environmental conditions (protracted atmospheric stability, desert dust intrusion, urban atmosphere). This method, based on the use of a thermal ramp for the desorption of water from PM samples and the subsequent analysis by the coulometric KF technique, had been previously shown to differentiate water contributes retained with different strength and associated to different chemical components in the atmospheric aerosol. The application of the method to size-segregated samples has revealed that water showed a typical mass size distribution in each one of the three environmental situations that were taken into consideration. A very similar size distribution was shown by the chemical PM components that prevailed during each event: ammonium nitrate in the case of atmospheric stability, crustal species in the case of desert dust, road-dust components in the case of urban sites. The shape of the tr-KF curve varied according to the size of the collected particles. Considering the size ranges that better characterize the event (fine fraction for atmospheric stability, coarse fraction for dust intrusion, bi-modal distribution for urban dust), this shape is coherent with the typical tr-KF shape shown by water bound to the chemical species that predominate in the same PM size range (ammonium nitrate, crustal species, secondary/combustion species - road dust components).

Sample Size and Power Estimates for a Confirmatory Factor Analytic Model in Exercise and Sport: A Monte Carlo Approach

ERIC Educational Resources Information Center

Myers, Nicholas D.; Ahn, Soyeon; Jin, Ying

2011-01-01

Monte Carlo methods can be used in data analytic situations (e.g., validity studies) to make decisions about sample size and to estimate power. The purpose of using Monte Carlo methods in a validity study is to improve the methodological approach within a study where the primary focus is on construct validity issues and not on advancing…

“Magnitude-based Inference”: A Statistical Review

PubMed Central

Welsh, Alan H.; Knight, Emma J.

2015-01-01

ABSTRACT Purpose We consider “magnitude-based inference” and its interpretation by examining in detail its use in the problem of comparing two means. Methods We extract from the spreadsheets, which are provided to users of the analysis (http://www.sportsci.org/), a precise description of how “magnitude-based inference” is implemented. We compare the implemented version of the method with general descriptions of it and interpret the method in familiar statistical terms. Results and Conclusions We show that “magnitude-based inference” is not a progressive improvement on modern statistics. The additional probabilities introduced are not directly related to the confidence interval but, rather, are interpretable either as P values for two different nonstandard tests (for different null hypotheses) or as approximate Bayesian calculations, which also lead to a type of test. We also discuss sample size calculations associated with “magnitude-based inference” and show that the substantial reduction in sample sizes claimed for the method (30% of the sample size obtained from standard frequentist calculations) is not justifiable so the sample size calculations should not be used. Rather than using “magnitude-based inference,” a better solution is to be realistic about the limitations of the data and use either confidence intervals or a fully Bayesian analysis. PMID:25051387

The endothelial sample size analysis in corneal specular microscopy clinical examinations.

PubMed

Abib, Fernando C; Holzchuh, Ricardo; Schaefer, Artur; Schaefer, Tania; Godois, Ronialci

2012-05-01

To evaluate endothelial cell sample size and statistical error in corneal specular microscopy (CSM) examinations. One hundred twenty examinations were conducted with 4 types of corneal specular microscopes: 30 with each BioOptics, CSO, Konan, and Topcon corneal specular microscopes. All endothelial image data were analyzed by respective instrument software and also by the Cells Analyzer software with a method developed in our lab. A reliability degree (RD) of 95% and a relative error (RE) of 0.05 were used as cut-off values to analyze images of the counted endothelial cells called samples. The sample size mean was the number of cells evaluated on the images obtained with each device. Only examinations with RE < 0.05 were considered statistically correct and suitable for comparisons with future examinations. The Cells Analyzer software was used to calculate the RE and customized sample size for all examinations. Bio-Optics: sample size, 97 ± 22 cells; RE, 6.52 ± 0.86; only 10% of the examinations had sufficient endothelial cell quantity (RE < 0.05); customized sample size, 162 ± 34 cells. CSO: sample size, 110 ± 20 cells; RE, 5.98 ± 0.98; only 16.6% of the examinations had sufficient endothelial cell quantity (RE < 0.05); customized sample size, 157 ± 45 cells. Konan: sample size, 80 ± 27 cells; RE, 10.6 ± 3.67; none of the examinations had sufficient endothelial cell quantity (RE > 0.05); customized sample size, 336 ± 131 cells. Topcon: sample size, 87 ± 17 cells; RE, 10.1 ± 2.52; none of the examinations had sufficient endothelial cell quantity (RE > 0.05); customized sample size, 382 ± 159 cells. A very high number of CSM examinations had sample errors based on Cells Analyzer software. The endothelial sample size (examinations) needs to include more cells to be reliable and reproducible. The Cells Analyzer tutorial routine will be useful for CSM examination reliability and reproducibility.

Investigating Test Equating Methods in Small Samples through Various Factors

ERIC Educational Resources Information Center

Asiret, Semih; Sünbül, Seçil Ömür

2016-01-01

In this study, equating methods for random group design using small samples through factors such as sample size, difference in difficulty between forms, and guessing parameter was aimed for comparison. Moreover, which method gives better results under which conditions was also investigated. In this study, 5,000 dichotomous simulated data…

Biomass Compositional Analysis Laboratory Procedures | Bioenergy | NREL

Science.gov Websites

Compositional Analysis This procedure describes methods for sample drying and size reduction, obtaining samples methods used to determine the amount of solids or moisture present in a solid or slurry biomass sample as values? We have found that neutral detergent fiber (NDF) and acid detergent fiber (ADF) methods report

Analysis of Duplicated Multiple-Samples Rank Data Using the Mack-Skillings Test.

PubMed

Carabante, Kennet Mariano; Alonso-Marenco, Jose Ramon; Chokumnoyporn, Napapan; Sriwattana, Sujinda; Prinyawiwatkul, Witoon

2016-07-01

Appropriate analysis for duplicated multiple-samples rank data is needed. This study compared analysis of duplicated rank preference data using the Friedman versus Mack-Skillings tests. Panelists (n = 125) ranked twice 2 orange juice sets: different-samples set (100%, 70%, vs. 40% juice) and similar-samples set (100%, 95%, vs. 90%). These 2 sample sets were designed to get contrasting differences in preference. For each sample set, rank sum data were obtained from (1) averaged rank data of each panelist from the 2 replications (n = 125), (2) rank data of all panelists from each of the 2 separate replications (n = 125 each), (3) jointed rank data of all panelists from the 2 replications (n = 125), and (4) rank data of all panelists pooled from the 2 replications (n = 250); rank data (1), (2), and (4) were separately analyzed by the Friedman test, although those from (3) by the Mack-Skillings test. The effect of sample sizes (n = 10 to 125) was evaluated. For the similar-samples set, higher variations in rank data from the 2 replications were observed; therefore, results of the main effects were more inconsistent among methods and sample sizes. Regardless of analysis methods, the larger the sample size, the higher the χ(2) value, the lower the P-value (testing H0 : all samples are not different). Analyzing rank data (2) separately by replication yielded inconsistent conclusions across sample sizes, hence this method is not recommended. The Mack-Skillings test was more sensitive than the Friedman test. Furthermore, it takes into account within-panelist variations and is more appropriate for analyzing duplicated rank data. © 2016 Institute of Food Technologists®

Sparse feature learning for instrument identification: Effects of sampling and pooling methods.

PubMed

Han, Yoonchang; Lee, Subin; Nam, Juhan; Lee, Kyogu

2016-05-01

Feature learning for music applications has recently received considerable attention from many researchers. This paper reports on the sparse feature learning algorithm for musical instrument identification, and in particular, focuses on the effects of the frame sampling techniques for dictionary learning and the pooling methods for feature aggregation. To this end, two frame sampling techniques are examined that are fixed and proportional random sampling. Furthermore, the effect of using onset frame was analyzed for both of proposed sampling methods. Regarding summarization of the feature activation, a standard deviation pooling method is used and compared with the commonly used max- and average-pooling techniques. Using more than 47 000 recordings of 24 instruments from various performers, playing styles, and dynamics, a number of tuning parameters are experimented including the analysis frame size, the dictionary size, and the type of frequency scaling as well as the different sampling and pooling methods. The results show that the combination of proportional sampling and standard deviation pooling achieve the best overall performance of 95.62% while the optimal parameter set varies among the instrument classes.

The choice of sample size: a mixed Bayesian / frequentist approach.

PubMed

Pezeshk, Hamid; Nematollahi, Nader; Maroufy, Vahed; Gittins, John

2009-04-01

Sample size computations are largely based on frequentist or classical methods. In the Bayesian approach the prior information on the unknown parameters is taken into account. In this work we consider a fully Bayesian approach to the sample size determination problem which was introduced by Grundy et al. and developed by Lindley. This approach treats the problem as a decision problem and employs a utility function to find the optimal sample size of a trial. Furthermore, we assume that a regulatory authority, which is deciding on whether or not to grant a licence to a new treatment, uses a frequentist approach. We then find the optimal sample size for the trial by maximising the expected net benefit, which is the expected benefit of subsequent use of the new treatment minus the cost of the trial.

Digital simulation of scalar optical diffraction: revisiting chirp function sampling criteria and consequences.

PubMed

Voelz, David G; Roggemann, Michael C

2009-11-10

Accurate simulation of scalar optical diffraction requires consideration of the sampling requirement for the phase chirp function that appears in the Fresnel diffraction expression. We describe three sampling regimes for FFT-based propagation approaches: ideally sampled, oversampled, and undersampled. Ideal sampling, where the chirp and its FFT both have values that match analytic chirp expressions, usually provides the most accurate results but can be difficult to realize in practical simulations. Under- or oversampling leads to a reduction in the available source plane support size, the available source bandwidth, or the available observation support size, depending on the approach and simulation scenario. We discuss three Fresnel propagation approaches: the impulse response/transfer function (angular spectrum) method, the single FFT (direct) method, and the two-step method. With illustrations and simulation examples we show the form of the sampled chirp functions and their discrete transforms, common relationships between the three methods under ideal sampling conditions, and define conditions and consequences to be considered when using nonideal sampling. The analysis is extended to describe the sampling limitations for the more exact Rayleigh-Sommerfeld diffraction solution.

Non-parametric methods for cost-effectiveness analysis: the central limit theorem and the bootstrap compared.

PubMed

Nixon, Richard M; Wonderling, David; Grieve, Richard D

2010-03-01

Cost-effectiveness analyses (CEA) alongside randomised controlled trials commonly estimate incremental net benefits (INB), with 95% confidence intervals, and compute cost-effectiveness acceptability curves and confidence ellipses. Two alternative non-parametric methods for estimating INB are to apply the central limit theorem (CLT) or to use the non-parametric bootstrap method, although it is unclear which method is preferable. This paper describes the statistical rationale underlying each of these methods and illustrates their application with a trial-based CEA. It compares the sampling uncertainty from using either technique in a Monte Carlo simulation. The experiments are repeated varying the sample size and the skewness of costs in the population. The results showed that, even when data were highly skewed, both methods accurately estimated the true standard errors (SEs) when sample sizes were moderate to large (n>50), and also gave good estimates for small data sets with low skewness. However, when sample sizes were relatively small and the data highly skewed, using the CLT rather than the bootstrap led to slightly more accurate SEs. We conclude that while in general using either method is appropriate, the CLT is easier to implement, and provides SEs that are at least as accurate as the bootstrap. (c) 2009 John Wiley & Sons, Ltd.

The albatross plot: A novel graphical tool for presenting results of diversely reported studies in a systematic review.

PubMed

Harrison, Sean; Jones, Hayley E; Martin, Richard M; Lewis, Sarah J; Higgins, Julian P T

2017-09-01

Meta-analyses combine the results of multiple studies of a common question. Approaches based on effect size estimates from each study are generally regarded as the most informative. However, these methods can only be used if comparable effect sizes can be computed from each study, and this may not be the case due to variation in how the studies were done or limitations in how their results were reported. Other methods, such as vote counting, are then used to summarize the results of these studies, but most of these methods are limited in that they do not provide any indication of the magnitude of effect. We propose a novel plot, the albatross plot, which requires only a 1-sided P value and a total sample size from each study (or equivalently a 2-sided P value, direction of effect and total sample size). The plot allows an approximate examination of underlying effect sizes and the potential to identify sources of heterogeneity across studies. This is achieved by drawing contours showing the range of effect sizes that might lead to each P value for given sample sizes, under simple study designs. We provide examples of albatross plots using data from previous meta-analyses, allowing for comparison of results, and an example from when a meta-analysis was not possible. Copyright © 2017 The Authors. Research Synthesis Methods Published by John Wiley & Sons Ltd.

Detection of linkage between a quantitative trait and a marker locus by the lod score method: sample size and sampling considerations.

PubMed

Demenais, F; Lathrop, G M; Lalouel, J M

1988-07-01

A simulation study is here conducted to measure the power of the lod score method to detect linkage between a quantitative trait and a marker locus in various situations. The number of families necessary to detect such linkage with 80% power is assessed for different sets of parameters at the trait locus and different values of the recombination fraction. The effects of varying the mode of sampling families and the sibship size are also evaluated.

Design and analysis of three-arm trials with negative binomially distributed endpoints.

PubMed

Mütze, Tobias; Munk, Axel; Friede, Tim

2016-02-20

A three-arm clinical trial design with an experimental treatment, an active control, and a placebo control, commonly referred to as the gold standard design, enables testing of non-inferiority or superiority of the experimental treatment compared with the active control. In this paper, we propose methods for designing and analyzing three-arm trials with negative binomially distributed endpoints. In particular, we develop a Wald-type test with a restricted maximum-likelihood variance estimator for testing non-inferiority or superiority. For this test, sample size and power formulas as well as optimal sample size allocations will be derived. The performance of the proposed test will be assessed in an extensive simulation study with regard to type I error rate, power, sample size, and sample size allocation. For the purpose of comparison, Wald-type statistics with a sample variance estimator and an unrestricted maximum-likelihood estimator are included in the simulation study. We found that the proposed Wald-type test with a restricted variance estimator performed well across the considered scenarios and is therefore recommended for application in clinical trials. The methods proposed are motivated and illustrated by a recent clinical trial in multiple sclerosis. The R package ThreeArmedTrials, which implements the methods discussed in this paper, is available on CRAN. Copyright © 2015 John Wiley & Sons, Ltd.

Visual accumulation tube for size analysis of sands

USGS Publications Warehouse

Colby, B.C.; Christensen, R.P.

1956-01-01

The visual-accumulation-tube method was developed primarily for making size analyses of the sand fractions of suspended-sediment and bed-material samples. Because the fundamental property governing the motion of a sediment particle in a fluid is believed to be its fall velocity. the analysis is designed to determine the fall-velocity-frequency distribution of the individual particles of the sample. The analysis is based on a stratified sedimentation system in which the sample is introduced at the top of a transparent settling tube containing distilled water. The procedure involves the direct visual tracing of the height of sediment accumulation in a contracted section at the bottom of the tube. A pen records the height on a moving chart. The method is simple and fast, provides a continuous and permanent record, gives highly reproducible results, and accurately determines the fall-velocity characteristics of the sample. The apparatus, procedure, results, and accuracy of the visual-accumulation-tube method for determining the sedimentation-size distribution of sands are presented in this paper.

Grays Harbor and Chehalis River Improvements to Navigation Environmental Studies. Grays Harbor Ocean Disposal Study. Literature Review and Preliminary Benthic Sampling,

DTIC Science & Technology

1980-05-01

transects extending approximately 16 kilometers from the mouth of Grays Harbor. Sub- samples were taken for grain size analysis and wood content. The...samples were thert was".d on a 1.0 mm screen to separate benthic organisms from non-living materials. Consideration of the grain size analysis ...Nutrients 17 B. Field Study 18 Methods 18 Grain Size Analysis 18 Wood Analysis 21 Wood Fragments 21 Sediment Types 21 Discussion 24 IV. BIOLOGICAL

Statistical Methods in Assembly Quality Management of Multi-Element Products on Automatic Rotor Lines

NASA Astrophysics Data System (ADS)

Pries, V. V.; Proskuriakov, N. E.

2018-04-01

To control the assembly quality of multi-element mass-produced products on automatic rotor lines, control methods with operational feedback are required. However, due to possible failures in the operation of the devices and systems of automatic rotor line, there is always a real probability of getting defective (incomplete) products into the output process stream. Therefore, a continuous sampling control of the products completeness, based on the use of statistical methods, remains an important element in managing the quality of assembly of multi-element mass products on automatic rotor lines. The feature of continuous sampling control of the multi-element products completeness in the assembly process is its breaking sort, which excludes the possibility of returning component parts after sampling control to the process stream and leads to a decrease in the actual productivity of the assembly equipment. Therefore, the use of statistical procedures for continuous sampling control of the multi-element products completeness when assembled on automatic rotor lines requires the use of such sampling plans that ensure a minimum size of control samples. Comparison of the values of the limit of the average output defect level for the continuous sampling plan (CSP) and for the automated continuous sampling plan (ACSP) shows the possibility of providing lower limit values for the average output defects level using the ACSP-1. Also, the average sample size when using the ACSP-1 plan is less than when using the CSP-1 plan. Thus, the application of statistical methods in the assembly quality management of multi-element products on automatic rotor lines, involving the use of proposed plans and methods for continuous selective control, will allow to automating sampling control procedures and the required level of quality of assembled products while minimizing sample size.

Probability of coincidental similarity among the orbits of small bodies - I. Pairing

NASA Astrophysics Data System (ADS)

Jopek, Tadeusz Jan; Bronikowska, Małgorzata

2017-09-01

Probability of coincidental clustering among orbits of comets, asteroids and meteoroids depends on many factors like: the size of the orbital sample searched for clusters or the size of the identified group, it is different for groups of 2,3,4,… members. Probability of coincidental clustering is assessed by the numerical simulation, therefore, it depends also on the method used for the synthetic orbits generation. We have tested the impact of some of these factors. For a given size of the orbital sample we have assessed probability of random pairing among several orbital populations of different sizes. We have found how these probabilities vary with the size of the orbital samples. Finally, keeping fixed size of the orbital sample we have shown that the probability of random pairing can be significantly different for the orbital samples obtained by different observation techniques. Also for the user convenience we have obtained several formulae which, for given size of the orbital sample can be used to calculate the similarity threshold corresponding to the small value of the probability of coincidental similarity among two orbits.

"Magnitude-based inference": a statistical review.

PubMed

Welsh, Alan H; Knight, Emma J

2015-04-01

We consider "magnitude-based inference" and its interpretation by examining in detail its use in the problem of comparing two means. We extract from the spreadsheets, which are provided to users of the analysis (http://www.sportsci.org/), a precise description of how "magnitude-based inference" is implemented. We compare the implemented version of the method with general descriptions of it and interpret the method in familiar statistical terms. We show that "magnitude-based inference" is not a progressive improvement on modern statistics. The additional probabilities introduced are not directly related to the confidence interval but, rather, are interpretable either as P values for two different nonstandard tests (for different null hypotheses) or as approximate Bayesian calculations, which also lead to a type of test. We also discuss sample size calculations associated with "magnitude-based inference" and show that the substantial reduction in sample sizes claimed for the method (30% of the sample size obtained from standard frequentist calculations) is not justifiable so the sample size calculations should not be used. Rather than using "magnitude-based inference," a better solution is to be realistic about the limitations of the data and use either confidence intervals or a fully Bayesian analysis.

A simple approach to power and sample size calculations in logistic regression and Cox regression models.

PubMed

Vaeth, Michael; Skovlund, Eva

2004-06-15

For a given regression problem it is possible to identify a suitably defined equivalent two-sample problem such that the power or sample size obtained for the two-sample problem also applies to the regression problem. For a standard linear regression model the equivalent two-sample problem is easily identified, but for generalized linear models and for Cox regression models the situation is more complicated. An approximately equivalent two-sample problem may, however, also be identified here. In particular, we show that for logistic regression and Cox regression models the equivalent two-sample problem is obtained by selecting two equally sized samples for which the parameters differ by a value equal to the slope times twice the standard deviation of the independent variable and further requiring that the overall expected number of events is unchanged. In a simulation study we examine the validity of this approach to power calculations in logistic regression and Cox regression models. Several different covariate distributions are considered for selected values of the overall response probability and a range of alternatives. For the Cox regression model we consider both constant and non-constant hazard rates. The results show that in general the approach is remarkably accurate even in relatively small samples. Some discrepancies are, however, found in small samples with few events and a highly skewed covariate distribution. Comparison with results based on alternative methods for logistic regression models with a single continuous covariate indicates that the proposed method is at least as good as its competitors. The method is easy to implement and therefore provides a simple way to extend the range of problems that can be covered by the usual formulas for power and sample size determination. Copyright 2004 John Wiley & Sons, Ltd.

Device for high spatial resolution chemical analysis of a sample and method of high spatial resolution chemical analysis

DOEpatents

Van Berkel, Gary J.

2015-10-06

A system and method for analyzing a chemical composition of a specimen are described. The system can include at least one pin; a sampling device configured to contact a liquid with a specimen on the at least one pin to form a testing solution; and a stepper mechanism configured to move the at least one pin and the sampling device relative to one another. The system can also include an analytical instrument for determining a chemical composition of the specimen from the testing solution. In particular, the systems and methods described herein enable chemical analysis of specimens, such as tissue, to be evaluated in a manner that the spatial-resolution is limited by the size of the pins used to obtain tissue samples, not the size of the sampling device used to solubilize the samples coupled to the pins.

A single test for rejecting the null hypothesis in subgroups and in the overall sample.

PubMed

Lin, Yunzhi; Zhou, Kefei; Ganju, Jitendra

2017-01-01

In clinical trials, some patient subgroups are likely to demonstrate larger effect sizes than other subgroups. For example, the effect size, or informally the benefit with treatment, is often greater in patients with a moderate condition of a disease than in those with a mild condition. A limitation of the usual method of analysis is that it does not incorporate this ordering of effect size by patient subgroup. We propose a test statistic which supplements the conventional test by including this information and simultaneously tests the null hypothesis in pre-specified subgroups and in the overall sample. It results in more power than the conventional test when the differences in effect sizes across subgroups are at least moderately large; otherwise it loses power. The method involves combining p-values from models fit to pre-specified subgroups and the overall sample in a manner that assigns greater weight to subgroups in which a larger effect size is expected. Results are presented for randomized trials with two and three subgroups.

Particle size analysis of amalgam powder and handpiece generated specimens.

PubMed

Drummond, J L; Hathorn, R M; Cailas, M D; Karuhn, R

2001-07-01

The increasing interest in the elimination of amalgam particles from the dental waste (DW) stream, requires efficient devices to remove these particles. The major objective of this project was to perform a comparative evaluation of five basic methods of particle size analysis in terms of the instrument's ability to quantify the size distribution of the various components within the DW stream. The analytical techniques chosen were image analysis via scanning electron microscopy, standard wire mesh sieves, X-ray sedigraphy, laser diffraction, and electrozone analysis. The DW particle stream components were represented by amalgam powders and handpiece/diamond bur generated specimens of enamel; dentin, whole tooth, and condensed amalgam. Each analytical method quantified the examined DW particle stream components. However, X-ray sedigraphy, electrozone, and laser diffraction particle analyses provided similar results for determining particle distributions of DW samples. These three methods were able to more clearly quantify the properties of the examined powder and condensed amalgam samples. Furthermore, these methods indicated that a significant fraction of the DW stream contains particles less than 20 microm. The findings of this study indicated that the electrozone method is likely to be the most effective technique for quantifying the particle size distribution in the DW particle stream. This method required a relative small volume of sample, was not affected by density, shape factors or optical properties, and measured a sufficient number of particles to provide a reliable representation of the particle size distribution curve.

Effect of synthesis methods with different annealing temperatures on micro structure, cations distribution and magnetic properties of nano-nickel ferrite

NASA Astrophysics Data System (ADS)

El-Sayed, Karimat; Mohamed, Mohamed Bakr; Hamdy, Sh.; Ata-Allah, S. S.

2017-02-01

Nano-crystalline NiFe2O4 was synthesized by citrate and sol-gel methods at different annealing temperatures and the results were compared with a bulk sample prepared by ceramic method. The effect of methods of preparation and different annealing temperatures on the crystallize size, strain, bond lengths, bond angles, cations distribution and degree of inversions were investigated by X-ray powder diffraction, high resolution transmission electron microscope, Mössbauer effect spectrometer and vibrating sample magnetometer. The cations distributions were determined at both octahedral and tetrahedral sites using both Mössbauer effect spectroscopy and a modified Bertaut method using Rietveld method. The Mössbauer effect spectra showed a regular decrease in the hyperfine field with decreasing particle size. Saturation magnetization and coercivity are found to be affected by the particle size and the cations distribution.

Automated grain mapping using wide angle convergent beam electron diffraction in transmission electron microscope for nanomaterials.

PubMed

Kumar, Vineet

2011-12-01

The grain size statistics, commonly derived from the grain map of a material sample, are important microstructure characteristics that greatly influence its properties. The grain map for nanomaterials is usually obtained manually by visual inspection of the transmission electron microscope (TEM) micrographs because automated methods do not perform satisfactorily. While the visual inspection method provides reliable results, it is a labor intensive process and is often prone to human errors. In this article, an automated grain mapping method is developed using TEM diffraction patterns. The presented method uses wide angle convergent beam diffraction in the TEM. The automated technique was applied on a platinum thin film sample to obtain the grain map and subsequently derive grain size statistics from it. The grain size statistics obtained with the automated method were found in good agreement with the visual inspection method.

The Grain-size Patchiness of Braided Gravel-Bed Streams: Example of the Urumqi River (northeast Tian Shan, China)

NASA Astrophysics Data System (ADS)

Guerit, L.; Barrier, L.; Narteau, C.; Métivier, F.; Liu, Y.; Lajeunesse, E.; Gayer, E.; Malverti, L.; Meunier, P.; Ye, B.

2012-04-01

In gravel-beds rivers, sediments are sorted into patches of different grain-sizes. For single-thread streams, it has long been shown that this local granulometric sorting is closely linked to the channel morpho-sedimentary elements. For braided streams, this relation is still unclear. In such rivers, many observations of vertical sediment sorting has led to the definition of a surface and a subsurface layers. Because of this common stratification, methods for sampling gravel-bed rivers have been divided in two families. The surface layer is generally sampled by surface methods and the subsurface layer by volumetric methods. Yet, the equivalency between the two kind of techniques is still a key question. In this study, we characterized the grain-size distribution of the surface layer of the Urumqi River, a shallow braided gravel-bed river in China, by surface-count (Wolman grid-by-number) and volumetric (sieve-by-weight) sampling methods. An analysis of two large samples (212 grains and 3226 kg) show that these two methods are equivalent to characterize the river-bed surface layer. Then, we looked at the grain-size distributions of the river-bed morpho-sedimentary elements: (1) chutes at flow constrictions, which pass downstream to (2) anabranches and (3) bars at flow expansions. Using both sampling methods, we measured the diameter of more than 2300 grains and weight more than 6000 kg of grains larger than 4 mm. Our results show that the three morpho-sedimentary elements correspond only to two kinds of grain-size patches: (1) chutes composed of one coarse-grained top layer lying on finer deposits, and (2) anabranches and bars made up of finer-grained deposits more homogeneous in depth. On the basis of these quantitative observations, together with the concave or convex morphology of the different elements, we propose that chute patches form by erosion and transit with size-selective entrainment, whereas anabranch and bar patches rather develop and migrate by transit and deposition. These patch features may be typical of shallow braided gravel-bed rivers and should be considered in future works about on bedload transport processes and their geomorphologic and stratigraphic results.

The albatross plot: A novel graphical tool for presenting results of diversely reported studies in a systematic review

PubMed Central

Jones, Hayley E.; Martin, Richard M.; Lewis, Sarah J.; Higgins, Julian P.T.

2017-01-01

Abstract Meta‐analyses combine the results of multiple studies of a common question. Approaches based on effect size estimates from each study are generally regarded as the most informative. However, these methods can only be used if comparable effect sizes can be computed from each study, and this may not be the case due to variation in how the studies were done or limitations in how their results were reported. Other methods, such as vote counting, are then used to summarize the results of these studies, but most of these methods are limited in that they do not provide any indication of the magnitude of effect. We propose a novel plot, the albatross plot, which requires only a 1‐sided P value and a total sample size from each study (or equivalently a 2‐sided P value, direction of effect and total sample size). The plot allows an approximate examination of underlying effect sizes and the potential to identify sources of heterogeneity across studies. This is achieved by drawing contours showing the range of effect sizes that might lead to each P value for given sample sizes, under simple study designs. We provide examples of albatross plots using data from previous meta‐analyses, allowing for comparison of results, and an example from when a meta‐analysis was not possible. PMID:28453179

Measurement of marine picoplankton cell size by using a cooled, charge-coupled device camera with image-analyzed fluorescence microscopy.

PubMed Central

Viles, C L; Sieracki, M E

1992-01-01

Accurate measurement of the biomass and size distribution of picoplankton cells (0.2 to 2.0 microns) is paramount in characterizing their contribution to the oceanic food web and global biogeochemical cycling. Image-analyzed fluorescence microscopy, usually based on video camera technology, allows detailed measurements of individual cells to be taken. The application of an imaging system employing a cooled, slow-scan charge-coupled device (CCD) camera to automated counting and sizing of individual picoplankton cells from natural marine samples is described. A slow-scan CCD-based camera was compared to a video camera and was superior for detecting and sizing very small, dim particles such as fluorochrome-stained bacteria. Several edge detection methods for accurately measuring picoplankton cells were evaluated. Standard fluorescent microspheres and a Sargasso Sea surface water picoplankton population were used in the evaluation. Global thresholding was inappropriate for these samples. Methods used previously in image analysis of nanoplankton cells (2 to 20 microns) also did not work well with the smaller picoplankton cells. A method combining an edge detector and an adaptive edge strength operator worked best for rapidly generating accurate cell sizes. A complete sample analysis of more than 1,000 cells averages about 50 min and yields size, shape, and fluorescence data for each cell. With this system, the entire size range of picoplankton can be counted and measured. Images PMID:1610183

Sample size requirements for estimating effective dose from computed tomography using solid-state metal-oxide-semiconductor field-effect transistor dosimetry

PubMed Central

Trattner, Sigal; Cheng, Bin; Pieniazek, Radoslaw L.; Hoffmann, Udo; Douglas, Pamela S.; Einstein, Andrew J.

2014-01-01

Purpose: Effective dose (ED) is a widely used metric for comparing ionizing radiation burden between different imaging modalities, scanners, and scan protocols. In computed tomography (CT), ED can be estimated by performing scans on an anthropomorphic phantom in which metal-oxide-semiconductor field-effect transistor (MOSFET) solid-state dosimeters have been placed to enable organ dose measurements. Here a statistical framework is established to determine the sample size (number of scans) needed for estimating ED to a desired precision and confidence, for a particular scanner and scan protocol, subject to practical limitations. Methods: The statistical scheme involves solving equations which minimize the sample size required for estimating ED to desired precision and confidence. It is subject to a constrained variation of the estimated ED and solved using the Lagrange multiplier method. The scheme incorporates measurement variation introduced both by MOSFET calibration, and by variation in MOSFET readings between repeated CT scans. Sample size requirements are illustrated on cardiac, chest, and abdomen–pelvis CT scans performed on a 320-row scanner and chest CT performed on a 16-row scanner. Results: Sample sizes for estimating ED vary considerably between scanners and protocols. Sample size increases as the required precision or confidence is higher and also as the anticipated ED is lower. For example, for a helical chest protocol, for 95% confidence and 5% precision for the ED, 30 measurements are required on the 320-row scanner and 11 on the 16-row scanner when the anticipated ED is 4 mSv; these sample sizes are 5 and 2, respectively, when the anticipated ED is 10 mSv. Conclusions: Applying the suggested scheme, it was found that even at modest sample sizes, it is feasible to estimate ED with high precision and a high degree of confidence. As CT technology develops enabling ED to be lowered, more MOSFET measurements are needed to estimate ED with the same precision and confidence. PMID:24694150

Self-navigation of a scanning tunneling microscope tip toward a micron-sized graphene sample.

PubMed

Li, Guohong; Luican, Adina; Andrei, Eva Y

2011-07-01

We demonstrate a simple capacitance-based method to quickly and efficiently locate micron-sized conductive samples, such as graphene flakes, on insulating substrates in a scanning tunneling microscope (STM). By using edge recognition, the method is designed to locate and to identify small features when the STM tip is far above the surface, allowing for crash-free search and navigation. The method can be implemented in any STM environment, even at low temperatures and in strong magnetic field, with minimal or no hardware modifications.

Confidence intervals for population allele frequencies: the general case of sampling from a finite diploid population of any size.

PubMed

Fung, Tak; Keenan, Kevin

2014-01-01

The estimation of population allele frequencies using sample data forms a central component of studies in population genetics. These estimates can be used to test hypotheses on the evolutionary processes governing changes in genetic variation among populations. However, existing studies frequently do not account for sampling uncertainty in these estimates, thus compromising their utility. Incorporation of this uncertainty has been hindered by the lack of a method for constructing confidence intervals containing the population allele frequencies, for the general case of sampling from a finite diploid population of any size. In this study, we address this important knowledge gap by presenting a rigorous mathematical method to construct such confidence intervals. For a range of scenarios, the method is used to demonstrate that for a particular allele, in order to obtain accurate estimates within 0.05 of the population allele frequency with high probability (> or = 95%), a sample size of > 30 is often required. This analysis is augmented by an application of the method to empirical sample allele frequency data for two populations of the checkerspot butterfly (Melitaea cinxia L.), occupying meadows in Finland. For each population, the method is used to derive > or = 98.3% confidence intervals for the population frequencies of three alleles. These intervals are then used to construct two joint > or = 95% confidence regions, one for the set of three frequencies for each population. These regions are then used to derive a > or = 95%% confidence interval for Jost's D, a measure of genetic differentiation between the two populations. Overall, the results demonstrate the practical utility of the method with respect to informing sampling design and accounting for sampling uncertainty in studies of population genetics, important for scientific hypothesis-testing and also for risk-based natural resource management.

Design and Weighting Methods for a Nationally Representative Sample of HIV-infected Adults Receiving Medical Care in the United States-Medical Monitoring Project

PubMed Central

Iachan, Ronaldo; H. Johnson, Christopher; L. Harding, Richard; Kyle, Tonja; Saavedra, Pedro; L. Frazier, Emma; Beer, Linda; L. Mattson, Christine; Skarbinski, Jacek

2016-01-01

Background: Health surveys of the general US population are inadequate for monitoring human immunodeficiency virus (HIV) infection because the relatively low prevalence of the disease (<0.5%) leads to small subpopulation sample sizes. Objective: To collect a nationally and locally representative probability sample of HIV-infected adults receiving medical care to monitor clinical and behavioral outcomes, supplementing the data in the National HIV Surveillance System. This paper describes the sample design and weighting methods for the Medical Monitoring Project (MMP) and provides estimates of the size and characteristics of this population. Methods: To develop a method for obtaining valid, representative estimates of the in-care population, we implemented a cross-sectional, three-stage design that sampled 23 jurisdictions, then 691 facilities, then 9,344 HIV patients receiving medical care, using probability-proportional-to-size methods. The data weighting process followed standard methods, accounting for the probabilities of selection at each stage and adjusting for nonresponse and multiplicity. Nonresponse adjustments accounted for differing response at both facility and patient levels. Multiplicity adjustments accounted for visits to more than one HIV care facility. Results: MMP used a multistage stratified probability sampling design that was approximately self-weighting in each of the 23 project areas and nationally. The probability sample represents the estimated 421,186 HIV-infected adults receiving medical care during January through April 2009. Methods were efficient (i.e., induced small, unequal weighting effects and small standard errors for a range of weighted estimates). Conclusion: The information collected through MMP allows monitoring trends in clinical and behavioral outcomes and informs resource allocation for treatment and prevention activities. PMID:27651851

Particle size analysis of sediments, soils and related particulate materials for forensic purposes using laser granulometry.

PubMed

Pye, Kenneth; Blott, Simon J

2004-08-11

Particle size is a fundamental property of any sediment, soil or dust deposit which can provide important clues to nature and provenance. For forensic work, the particle size distribution of sometimes very small samples requires precise determination using a rapid and reliable method with a high resolution. The Coulter trade mark LS230 laser granulometer offers rapid and accurate sizing of particles in the range 0.04-2000 microm for a variety of sample types, including soils, unconsolidated sediments, dusts, powders and other particulate materials. Reliable results are possible for sample weights of just 50 mg. Discrimination between samples is performed on the basis of the shape of the particle size curves and statistical measures of the size distributions. In routine forensic work laser granulometry data can rarely be used in isolation and should be considered in combination with results from other techniques to reach an overall conclusion.

76 FR 28786 - Proposed Data Collections Submitted for Public Comment and Recommendations

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-18

.... The sample size is based on recommendations related to qualitative interview methods and the research... than 10 employees (CPWR, 2007), and this establishment size experiences the highest fatality rate... out occupational safety and health training. This interview will be administered to a sample of...

Novel hybrid cryo-radial method: an emerging alternative to CT-guided biopsy in suspected lung cancer. A prospective case series and description of technique.

PubMed

Herath, Samantha; Yap, Elaine

2018-02-01

In diagnosing peripheral pulmonary lesions (PPL), radial endobronchial ultrasound (R-EBUS) is emerging as a safer method in comparison to CT-guided biopsy. Despite the better safety profile, the yield of R-EBUS remains lower (73%) than CT-guided biopsy (90%) due to the smaller size of samples. We adopted a hybrid method by adding cryobiopsy via the R-EBUS Guide Sheath (GS) to produce larger, non-crushed samples to improve diagnostic capability and enhance molecular testing. We report six prospective patients who underwent this procedure in our institution. R-EBUS samples were obtained via conventional sampling methods (needle aspiration, forceps biopsy, and cytology brush), followed by a cryobiopsy. An endobronchial blocker was placed near the planned area of biopsy in advance and inflated post-biopsy to minimize the risk of bleeding in all patients. A chest X-ray was performed 1 h post-procedure. All the PPLs were visualized with R-EBUS. The mean diameter of cryobiopsy samples was twice the size of forceps biopsy samples. In four patients, cryobiopsy samples were superior in size and the number of malignant cells per high power filed and was the preferred sample selected for mutation analysis and molecular testing. There was no pneumothorax or significant bleeding to report. Cryobiopsy samples were consistently larger and were the preferred samples for molecular testing, with an increase in the diagnostic yield and reduction in the need for repeat procedures, without hindering the marked safety profile of R-EBUS. Using an endobronchial blocker improves the safety of this procedure.

A Bayesian sequential design using alpha spending function to control type I error.

PubMed

Zhu, Han; Yu, Qingzhao

2017-10-01

We propose in this article a Bayesian sequential design using alpha spending functions to control the overall type I error in phase III clinical trials. We provide algorithms to calculate critical values, power, and sample sizes for the proposed design. Sensitivity analysis is implemented to check the effects from different prior distributions, and conservative priors are recommended. We compare the power and actual sample sizes of the proposed Bayesian sequential design with different alpha spending functions through simulations. We also compare the power of the proposed method with frequentist sequential design using the same alpha spending function. Simulations show that, at the same sample size, the proposed method provides larger power than the corresponding frequentist sequential design. It also has larger power than traditional Bayesian sequential design which sets equal critical values for all interim analyses. When compared with other alpha spending functions, O'Brien-Fleming alpha spending function has the largest power and is the most conservative in terms that at the same sample size, the null hypothesis is the least likely to be rejected at early stage of clinical trials. And finally, we show that adding a step of stop for futility in the Bayesian sequential design can reduce the overall type I error and reduce the actual sample sizes.

A novel measure of effect size for mediation analysis.

PubMed

Lachowicz, Mark J; Preacher, Kristopher J; Kelley, Ken

2018-06-01

Mediation analysis has become one of the most popular statistical methods in the social sciences. However, many currently available effect size measures for mediation have limitations that restrict their use to specific mediation models. In this article, we develop a measure of effect size that addresses these limitations. We show how modification of a currently existing effect size measure results in a novel effect size measure with many desirable properties. We also derive an expression for the bias of the sample estimator for the proposed effect size measure and propose an adjusted version of the estimator. We present a Monte Carlo simulation study conducted to examine the finite sampling properties of the adjusted and unadjusted estimators, which shows that the adjusted estimator is effective at recovering the true value it estimates. Finally, we demonstrate the use of the effect size measure with an empirical example. We provide freely available software so that researchers can immediately implement the methods we discuss. Our developments here extend the existing literature on effect sizes and mediation by developing a potentially useful method of communicating the magnitude of mediation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Extracting samples of high diversity from thematic collections of large gene banks using a genetic-distance based approach

PubMed Central

2010-01-01

Background Breeding programs are usually reluctant to evaluate and use germplasm accessions other than the elite materials belonging to their advanced populations. The concept of core collections has been proposed to facilitate the access of potential users to samples of small sizes, representative of the genetic variability contained within the gene pool of a specific crop. The eventual large size of a core collection perpetuates the problem it was originally proposed to solve. The present study suggests that, in addition to the classic core collection concept, thematic core collections should be also developed for a specific crop, composed of a limited number of accessions, with a manageable size. Results The thematic core collection obtained meets the minimum requirements for a core sample - maintenance of at least 80% of the allelic richness of the thematic collection, with, approximately, 15% of its size. The method was compared with other methodologies based on the M strategy, and also with a core collection generated by random sampling. Higher proportions of retained alleles (in a core collection of equal size) or similar proportions of retained alleles (in a core collection of smaller size) were detected in the two methods based on the M strategy compared to the proposed methodology. Core sub-collections constructed by different methods were compared regarding the increase or maintenance of phenotypic diversity. No change on phenotypic diversity was detected by measuring the trait "Weight of 100 Seeds", for the tested sampling methods. Effects on linkage disequilibrium between unlinked microsatellite loci, due to sampling, are discussed. Conclusions Building of a thematic core collection was here defined by prior selection of accessions which are diverse for the trait of interest, and then by pairwise genetic distances, estimated by DNA polymorphism analysis at molecular marker loci. The resulting thematic core collection potentially reflects the maximum allele richness with the smallest sample size from a larger thematic collection. As an example, we used the development of a thematic core collection for drought tolerance in rice. It is expected that such thematic collections increase the use of germplasm by breeding programs and facilitate the study of the traits under consideration. The definition of a core collection to study drought resistance is a valuable contribution towards the understanding of the genetic control and the physiological mechanisms involved in water use efficiency in plants. PMID:20576152

Elaboration of austenitic stainless steel samples with bimodal grain size distributions and investigation of their mechanical behavior

NASA Astrophysics Data System (ADS)

Flipon, B.; de la Cruz, L. Garcia; Hug, E.; Keller, C.; Barbe, F.

2017-10-01

Samples of 316L austenitic stainless steel with bimodal grain size distributions are elaborated using two distinct routes. The first one is based on powder metallurgy using spark plasma sintering of two powders with different particle sizes. The second route applies the reverse-annealing method: it consists in inducing martensitic phase transformation by plastic strain and further annealing in order to obtain two austenitic grain populations with different sizes. Microstructural analy ses reveal that both methods are suitable to generate significative grain size contrast and to control this contrast according to the elaboration conditions. Mechanical properties under tension are then characterized for different grain size distributions. Crystal plasticity finite element modelling is further applied in a configuration of bimodal distribution to analyse the role played by coarse grains within a matrix of fine grains, considering not only their volume fraction but also their spatial arrangement.

Measuring Compartment Size and Gas Solubility in Marine Mammals

DTIC Science & Technology

2014-09-30

analyzed by gas chromatography . Injection of the sample into the gas chromatograph is done using a sample loop to minimize volume injection error. We...1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Measuring Compartment Size and Gas Solubility in Marine...study is to develop methods to estimate marine mammal tissue compartment sizes, and tissue gas solubility. We aim to improve the data available for

Sampling methods for amphibians in streams in the Pacific Northwest.

Treesearch

R. Bruce Bury; Paul Stephen Corn

1991-01-01

Methods describing how to sample aquatic and semiaquatic amphibians in small streams and headwater habitats in the Pacific Northwest are presented. We developed a technique that samples 10-meter stretches of selected streams, which was adequate to detect presence or absence of amphibian species and provided sample sizes statistically sufficient to compare abundance of...

Sample size guidelines for fitting a lognormal probability distribution to censored most probable number data with a Markov chain Monte Carlo method.

PubMed

Williams, Michael S; Cao, Yong; Ebel, Eric D

2013-07-15

Levels of pathogenic organisms in food and water have steadily declined in many parts of the world. A consequence of this reduction is that the proportion of samples that test positive for the most contaminated product-pathogen pairings has fallen to less than 0.1. While this is unequivocally beneficial to public health, datasets with very few enumerated samples present an analytical challenge because a large proportion of the observations are censored values. One application of particular interest to risk assessors is the fitting of a statistical distribution function to datasets collected at some point in the farm-to-table continuum. The fitted distribution forms an important component of an exposure assessment. A number of studies have compared different fitting methods and proposed lower limits on the proportion of samples where the organisms of interest are identified and enumerated, with the recommended lower limit of enumerated samples being 0.2. This recommendation may not be applicable to food safety risk assessments for a number of reasons, which include the development of new Bayesian fitting methods, the use of highly sensitive screening tests, and the generally larger sample sizes found in surveys of food commodities. This study evaluates the performance of a Markov chain Monte Carlo fitting method when used in conjunction with a screening test and enumeration of positive samples by the Most Probable Number technique. The results suggest that levels of contamination for common product-pathogen pairs, such as Salmonella on poultry carcasses, can be reliably estimated with the proposed fitting method and samples sizes in excess of 500 observations. The results do, however, demonstrate that simple guidelines for this application, such as the proportion of positive samples, cannot be provided. Published by Elsevier B.V.

A Generalized Least Squares Regression Approach for Computing Effect Sizes in Single-Case Research: Application Examples

ERIC Educational Resources Information Center

Maggin, Daniel M.; Swaminathan, Hariharan; Rogers, Helen J.; O'Keeffe, Breda V.; Sugai, George; Horner, Robert H.

2011-01-01

A new method for deriving effect sizes from single-case designs is proposed. The strategy is applicable to small-sample time-series data with autoregressive errors. The method uses Generalized Least Squares (GLS) to model the autocorrelation of the data and estimate regression parameters to produce an effect size that represents the magnitude of…

Rock magnetic properties estimated from coercivity - blocking temperature diagram: application to recent volcanic rocks

NASA Astrophysics Data System (ADS)

Terada, T.; Sato, M.; Mochizuki, N.; Yamamoto, Y.; Tsunakawa, H.

2013-12-01

Magnetic properties of ferromagnetic minerals generally depend on their chemical composition, crystal structure, size, and shape. In the usual paleomagnetic study, we use a bulk sample which is the assemblage of magnetic minerals showing broad distributions of various magnetic properties. Microscopic and Curie-point observations of the bulk sample enable us to identify the constituent magnetic minerals, while other measurements, for example, stepwise thermal and/or alternating field demagnetizations (ThD, AFD) make it possible to estimate size, shape and domain state of the constituent magnetic grains. However, estimation based on stepwise demagnetizations has a limitation that magnetic grains with the same coercivity Hc (or blocking temperature Tb) can be identified as the single population even though they could have different size and shape. Dunlop and West (1969) carried out mapping of grain size and coercivity (Hc) using pTRM. However, it is considered that their mapping method is basically applicable to natural rocks containing only SD grains, since the grain sizes are estimated on the basis of the single domain theory (Neel, 1949). In addition, it is impossible to check thermal alteration due to laboratory heating in their experiment. In the present study we propose a new experimental method which makes it possible to estimate distribution of size and shape of magnetic minerals in a bulk sample. The present method is composed of simple procedures: (1) imparting ARM to a bulk sample, (2) ThD at a certain temperature, (3) stepwise AFD on the remaining ARM, (4) repeating the steps (1) ~ (3) with ThD at elevating temperatures up to the Curie temperature of the sample. After completion of the whole procedures, ARM spectra are calculated and mapped on the HC-Tb plane (hereafter called HC-Tb diagram). We analyze the Hc-Tb diagrams as follows: (1) For uniaxial SD populations, theoretical curve for a certain grain size (or shape anisotropy) is drawn on the Hc-Tb diagram. The curves are calculated using the single domain theory, since coercivity and blocking temperature of uniaxial SD grains can be expressed as a function of size and shape. (2) Boundary between SD and MD grains are calculated and drawn on the Hc-Tb diagram according to the theory by Butler and Banerjee (1975). (3) Theoretical predictions by (1) and (2) are compared with the obtained ARM spectra to estimate quantitive distribution of size, shape and domain state of magnetic grains in the sample. This mapping method has been applied to three samples: Hawaiian basaltic lava extruded in 1995, Ueno basaltic lava formed during Matsuyama chron, and Oshima basaltic lava extruded in 1986. We will discuss physical states of magnetic grains (size, shape, domain state, etc.) and their possible origins.

Fish assemblages

USGS Publications Warehouse

McGarvey, Daniel J.; Falke, Jeffrey A.; Li, Hiram W.; Li, Judith; Hauer, F. Richard; Lamberti, G.A.

2017-01-01

Methods to sample fishes in stream ecosystems and to analyze the raw data, focusing primarily on assemblage-level (all fish species combined) analyses, are presented in this chapter. We begin with guidance on sample site selection, permitting for fish collection, and information-gathering steps to be completed prior to conducting fieldwork. Basic sampling methods (visual surveying, electrofishing, and seining) are presented with specific instructions for estimating population sizes via visual, capture-recapture, and depletion surveys, in addition to new guidance on environmental DNA (eDNA) methods. Steps to process fish specimens in the field including the use of anesthesia and preservation of whole specimens or tissue samples (for genetic or stable isotope analysis) are also presented. Data analysis methods include characterization of size-structure within populations, estimation of species richness and diversity, and application of fish functional traits. We conclude with three advanced topics in assemblage-level analysis: multidimensional scaling (MDS), ecological networks, and loop analysis.

A comparative review of methods for comparing means using partially paired data.

PubMed

Guo, Beibei; Yuan, Ying

2017-06-01

In medical experiments with the objective of testing the equality of two means, data are often partially paired by design or because of missing data. The partially paired data represent a combination of paired and unpaired observations. In this article, we review and compare nine methods for analyzing partially paired data, including the two-sample t-test, paired t-test, corrected z-test, weighted t-test, pooled t-test, optimal pooled t-test, multiple imputation method, mixed model approach, and the test based on a modified maximum likelihood estimate. We compare the performance of these methods through extensive simulation studies that cover a wide range of scenarios with different effect sizes, sample sizes, and correlations between the paired variables, as well as true underlying distributions. The simulation results suggest that when the sample size is moderate, the test based on the modified maximum likelihood estimator is generally superior to the other approaches when the data is normally distributed and the optimal pooled t-test performs the best when the data is not normally distributed, with well-controlled type I error rates and high statistical power; when the sample size is small, the optimal pooled t-test is to be recommended when both variables have missing data and the paired t-test is to be recommended when only one variable has missing data.

Hindlimb muscle architecture in non-human great apes and a comparison of methods for analysing inter-species variation

PubMed Central

Myatt, Julia P; Crompton, Robin H; Thorpe, Susannah K S

2011-01-01

By relating an animal's morphology to its functional role and the behaviours performed, we can further develop our understanding of the selective factors and constraints acting on the adaptations of great apes. Comparison of muscle architecture between different ape species, however, is difficult because only small sample sizes are ever available. Further, such samples are often comprised of different age–sex classes, so studies have to rely on scaling techniques to remove body mass differences. However, the reliability of such scaling techniques has been questioned. As datasets increase in size, more reliable statistical analysis may eventually become possible. Here we employ geometric and allometric scaling techniques, and ancovas (a form of general linear model, GLM) to highlight and explore the different methods available for comparing functional morphology in the non-human great apes. Our results underline the importance of regressing data against a suitable body size variable to ascertain the relationship (geometric or allometric) and of choosing appropriate exponents by which to scale data. ancova models, while likely to be more robust than scaling for species comparisons when sample sizes are high, suffer from reduced power when sample sizes are low. Therefore, until sample sizes are radically increased it is preferable to include scaling analyses along with ancovas in data exploration. Overall, the results obtained from the different methods show little significant variation, whether in muscle belly mass, fascicle length or physiological cross-sectional area between the different species. This may reflect relatively close evolutionary relationships of the non-human great apes; a universal influence on morphology of generalised orthograde locomotor behaviours or, quite likely, both. PMID:21507000

Simulation analyses of space use: Home range estimates, variability, and sample size

USGS Publications Warehouse

Bekoff, Marc; Mech, L. David

1984-01-01

Simulations of space use by animals were run to determine the relationship among home range area estimates, variability, and sample size (number of locations). As sample size increased, home range size increased asymptotically, whereas variability decreased among mean home range area estimates generated by multiple simulations for the same sample size. Our results suggest that field workers should ascertain between 100 and 200 locations in order to estimate reliably home range area. In some cases, this suggested guideline is higher than values found in the few published studies in which the relationship between home range area and number of locations is addressed. Sampling differences for small species occupying relatively small home ranges indicate that fewer locations may be sufficient to allow for a reliable estimate of home range. Intraspecific variability in social status (group member, loner, resident, transient), age, sex, reproductive condition, and food resources also have to be considered, as do season, habitat, and differences in sampling and analytical methods. Comparative data still are needed.

Setting health research priorities using the CHNRI method: VI. Quantitative properties of human collective opinion

PubMed Central

Yoshida, Sachiyo; Rudan, Igor; Cousens, Simon

2016-01-01

Introduction Crowdsourcing has become an increasingly important tool to address many problems – from government elections in democracies, stock market prices, to modern online tools such as TripAdvisor or Internet Movie Database (IMDB). The CHNRI method (the acronym for the Child Health and Nutrition Research Initiative) for setting health research priorities has crowdsourcing as the major component, which it uses to generate, assess and prioritize between many competing health research ideas. Methods We conducted a series of analyses using data from a group of 91 scorers to explore the quantitative properties of their collective opinion. We were interested in the stability of their collective opinion as the sample size increases from 15 to 90. From a pool of 91 scorers who took part in a previous CHNRI exercise, we used sampling with replacement to generate multiple random samples of different size. First, for each sample generated, we identified the top 20 ranked research ideas, among 205 that were proposed and scored, and calculated the concordance with the ranking generated by the 91 original scorers. Second, we used rank correlation coefficients to compare the ranks assigned to all 205 proposed research ideas when samples of different size are used. We also analysed the original pool of 91 scorers to to look for evidence of scoring variations based on scorers' characteristics. Results The sample sizes investigated ranged from 15 to 90. The concordance for the top 20 scored research ideas increased with sample sizes up to about 55 experts. At this point, the median level of concordance stabilized at 15/20 top ranked questions (75%), with the interquartile range also generally stable (14–16). There was little further increase in overlap when the sample size increased from 55 to 90. When analysing the ranking of all 205 ideas, the rank correlation coefficient increased as the sample size increased, with a median correlation of 0.95 reached at the sample size of 45 experts (median of the rank correlation coefficient = 0.95; IQR 0.94–0.96). Conclusions Our analyses suggest that the collective opinion of an expert group on a large number of research ideas, expressed through categorical variables (Yes/No/Not Sure/Don't know), stabilises relatively quickly in terms of identifying the ideas that have most support. In the exercise we found a high degree of reproducibility of the identified research priorities was achieved with as few as 45–55 experts. PMID:27350874

Whole Brain Size and General Mental Ability: A Review

PubMed Central

Rushton, J. Philippe; Ankney, C. Davison

2009-01-01

We review the literature on the relation between whole brain size and general mental ability (GMA) both within and between species. Among humans, in 28 samples using brain imaging techniques, the mean brain size/GMA correlation is 0.40 (N = 1,389; p < 10−10); in 59 samples using external head size measures it is 0.20 (N = 63,405; p < 10−10). In 6 samples using the method of correlated vectors to distill g, the general factor of mental ability, the mean r is 0.63. We also describe the brain size/GMA correlations with age, socioeconomic position, sex, and ancestral population groups, which also provide information about brain–behavior relationships. Finally, we examine brain size and mental ability from an evolutionary and behavior genetic perspective. PMID:19283594

Improvements to sample processing and measurement to enable more widespread environmental application of tritium.

PubMed

Moran, James; Alexander, Thomas; Aalseth, Craig; Back, Henning; Mace, Emily; Overman, Cory; Seifert, Allen; Freeburg, Wilcox

2017-08-01

Previous measurements have demonstrated the wealth of information that tritium (T) can provide on environmentally relevant processes. We present modifications to sample preparation approaches that enable T measurement by proportional counting on small sample sizes equivalent to 120mg of water and demonstrate the accuracy of these methods on a suite of standardized water samples. We identify a current quantification limit of 92.2 TU which, combined with our small sample sizes, correlates to as little as 0.00133Bq of total T activity. This enhanced method should provide the analytical flexibility needed to address persistent knowledge gaps in our understanding of both natural and artificial T behavior in the environment. Copyright © 2017. Published by Elsevier Ltd.

Improvements to sample processing and measurement to enable more widespread environmental application of tritium

DOE PAGES

Moran, James; Alexander, Thomas; Aalseth, Craig; ...

2017-01-26

Previous measurements have demonstrated the wealth of information that tritium (T) can provide on environmentally relevant processes. Here, we present modifications to sample preparation approaches that enable T measurement by proportional counting on small sample sizes equivalent to 120 mg of water and demonstrate the accuracy of these methods on a suite of standardized water samples. We also identify a current quantification limit of 92.2 TU which, combined with our small sample sizes, correlates to as little as 0.00133 Bq of total T activity. Furthermore, this enhanced method should provide the analytical flexibility needed to address persistent knowledge gaps inmore » our understanding of both natural and artificial T behavior in the environment.« less

Caught Ya! A School-Based Practical Activity to Evaluate the Capture-Mark-Release-Recapture Method

ERIC Educational Resources Information Center

Kingsnorth, Crawford; Cruickshank, Chae; Paterson, David; Diston, Stephen

2017-01-01

The capture-mark-release-recapture method provides a simple way to estimate population size. However, when used as part of ecological sampling, this method does not easily allow an opportunity to evaluate the accuracy of the calculation because the actual population size is unknown. Here, we describe a method that can be used to measure the…

Measuring solids concentration in stormwater runoff: comparison of analytical methods.

PubMed

Clark, Shirley E; Siu, Christina Y S

2008-01-15

Stormwater suspended solids typically are quantified using one of two methods: aliquot/subsample analysis (total suspended solids [TSS]) or whole-sample analysis (suspended solids concentration [SSC]). Interproject comparisons are difficult because of inconsistencies in the methods and in their application. To address this concern, the suspended solids content has been measured using both methodologies in many current projects, but the question remains about how to compare these values with historical water-quality data where the analytical methodology is unknown. This research was undertaken to determine the effect of analytical methodology on the relationship between these two methods of determination of the suspended solids concentration, including the effect of aliquot selection/collection method and of particle size distribution (PSD). The results showed that SSC was best able to represent the known sample concentration and that the results were independent of the sample's PSD. Correlations between the results and the known sample concentration could be established for TSS samples, but they were highly dependent on the sample's PSD and on the aliquot collection technique. These results emphasize the need to report not only the analytical method but also the particle size information on the solids in stormwater runoff.

Repeated significance tests of linear combinations of sensitivity and specificity of a diagnostic biomarker

PubMed Central

Wu, Mixia; Shu, Yu; Li, Zhaohai; Liu, Aiyi

2016-01-01

A sequential design is proposed to test whether the accuracy of a binary diagnostic biomarker meets the minimal level of acceptance. The accuracy of a binary diagnostic biomarker is a linear combination of the marker’s sensitivity and specificity. The objective of the sequential method is to minimize the maximum expected sample size under the null hypothesis that the marker’s accuracy is below the minimal level of acceptance. The exact results of two-stage designs based on Youden’s index and efficiency indicate that the maximum expected sample sizes are smaller than the sample sizes of the fixed designs. Exact methods are also developed for estimation, confidence interval and p-value concerning the proposed accuracy index upon termination of the sequential testing. PMID:26947768

Sample size planning for composite reliability coefficients: accuracy in parameter estimation via narrow confidence intervals.

PubMed

Terry, Leann; Kelley, Ken

2012-11-01

Composite measures play an important role in psychology and related disciplines. Composite measures almost always have error. Correspondingly, it is important to understand the reliability of the scores from any particular composite measure. However, the point estimates of the reliability of composite measures are fallible and thus all such point estimates should be accompanied by a confidence interval. When confidence intervals are wide, there is much uncertainty in the population value of the reliability coefficient. Given the importance of reporting confidence intervals for estimates of reliability, coupled with the undesirability of wide confidence intervals, we develop methods that allow researchers to plan sample size in order to obtain narrow confidence intervals for population reliability coefficients. We first discuss composite reliability coefficients and then provide a discussion on confidence interval formation for the corresponding population value. Using the accuracy in parameter estimation approach, we develop two methods to obtain accurate estimates of reliability by planning sample size. The first method provides a way to plan sample size so that the expected confidence interval width for the population reliability coefficient is sufficiently narrow. The second method ensures that the confidence interval width will be sufficiently narrow with some desired degree of assurance (e.g., 99% assurance that the 95% confidence interval for the population reliability coefficient will be less than W units wide). The effectiveness of our methods was verified with Monte Carlo simulation studies. We demonstrate how to easily implement the methods with easy-to-use and freely available software. ©2011 The British Psychological Society.

Small sample sizes in the study of ontogenetic allometry; implications for palaeobiology

PubMed Central

Vavrek, Matthew J.

2015-01-01

Quantitative morphometric analyses, particularly ontogenetic allometry, are common methods used in quantifying shape, and changes therein, in both extinct and extant organisms. Due to incompleteness and the potential for restricted sample sizes in the fossil record, palaeobiological analyses of allometry may encounter higher rates of error. Differences in sample size between fossil and extant studies and any resulting effects on allometric analyses have not been thoroughly investigated, and a logical lower threshold to sample size is not clear. Here we show that studies based on fossil datasets have smaller sample sizes than those based on extant taxa. A similar pattern between vertebrates and invertebrates indicates this is not a problem unique to either group, but common to both. We investigate the relationship between sample size, ontogenetic allometric relationship and statistical power using an empirical dataset of skull measurements of modern Alligator mississippiensis. Across a variety of subsampling techniques, used to simulate different taphonomic and/or sampling effects, smaller sample sizes gave less reliable and more variable results, often with the result that allometric relationships will go undetected due to Type II error (failure to reject the null hypothesis). This may result in a false impression of fewer instances of positive/negative allometric growth in fossils compared to living organisms. These limitations are not restricted to fossil data and are equally applicable to allometric analyses of rare extant taxa. No mathematically derived minimum sample size for ontogenetic allometric studies is found; rather results of isometry (but not necessarily allometry) should not be viewed with confidence at small sample sizes. PMID:25780770

Particle Morphology Analysis of Biomass Material Based on Improved Image Processing Method

PubMed Central

Lu, Zhaolin

2017-01-01

Particle morphology, including size and shape, is an important factor that significantly influences the physical and chemical properties of biomass material. Based on image processing technology, a method was developed to process sample images, measure particle dimensions, and analyse the particle size and shape distributions of knife-milled wheat straw, which had been preclassified into five nominal size groups using mechanical sieving approach. Considering the great variation of particle size from micrometer to millimeter, the powders greater than 250 μm were photographed by a flatbed scanner without zoom function, and the others were photographed using a scanning electron microscopy (SEM) with high-image resolution. Actual imaging tests confirmed the excellent effect of backscattered electron (BSE) imaging mode of SEM. Particle aggregation is an important factor that affects the recognition accuracy of the image processing method. In sample preparation, the singulated arrangement and ultrasonic dispersion methods were used to separate powders into particles that were larger and smaller than the nominal size of 250 μm. In addition, an image segmentation algorithm based on particle geometrical information was proposed to recognise the finer clustered powders. Experimental results demonstrated that the improved image processing method was suitable to analyse the particle size and shape distributions of ground biomass materials and solve the size inconsistencies in sieving analysis. PMID:28298925

Point of data saturation was assessed using resampling methods in a survey with open-ended questions.

PubMed

Tran, Viet-Thi; Porcher, Raphael; Falissard, Bruno; Ravaud, Philippe

2016-12-01

To describe methods to determine sample sizes in surveys using open-ended questions and to assess how resampling methods can be used to determine data saturation in these surveys. We searched the literature for surveys with open-ended questions and assessed the methods used to determine sample size in 100 studies selected at random. Then, we used Monte Carlo simulations on data from a previous study on the burden of treatment to assess the probability of identifying new themes as a function of the number of patients recruited. In the literature, 85% of researchers used a convenience sample, with a median size of 167 participants (interquartile range [IQR] = 69-406). In our simulation study, the probability of identifying at least one new theme for the next included subject was 32%, 24%, and 12% after the inclusion of 30, 50, and 100 subjects, respectively. The inclusion of 150 participants at random resulted in the identification of 92% themes (IQR = 91-93%) identified in the original study. In our study, data saturation was most certainly reached for samples >150 participants. Our method may be used to determine when to continue the study to find new themes or stop because of futility. Copyright © 2016 Elsevier Inc. All rights reserved.

Sample size requirements for the design of reliability studies: precision consideration.

PubMed

Shieh, Gwowen

2014-09-01

In multilevel modeling, the intraclass correlation coefficient based on the one-way random-effects model is routinely employed to measure the reliability or degree of resemblance among group members. To facilitate the advocated practice of reporting confidence intervals in future reliability studies, this article presents exact sample size procedures for precise interval estimation of the intraclass correlation coefficient under various allocation and cost structures. Although the suggested approaches do not admit explicit sample size formulas and require special algorithms for carrying out iterative computations, they are more accurate than the closed-form formulas constructed from large-sample approximations with respect to the expected width and assurance probability criteria. This investigation notes the deficiency of existing methods and expands the sample size methodology for the design of reliability studies that have not previously been discussed in the literature.

Is it appropriate to composite fish samples for mercury trend monitoring and consumption advisories?

PubMed

Gandhi, Nilima; Bhavsar, Satyendra P; Gewurtz, Sarah B; Drouillard, Ken G; Arhonditsis, George B; Petro, Steve

2016-03-01

Monitoring mercury levels in fish can be costly because variation by space, time, and fish type/size needs to be captured. Here, we explored if compositing fish samples to decrease analytical costs would reduce the effectiveness of the monitoring objectives. Six compositing methods were evaluated by applying them to an existing extensive dataset, and examining their performance in reproducing the fish consumption advisories and temporal trends. The methods resulted in varying amount (average 34-72%) of reductions in samples, but all (except one) reproduced advisories very well (96-97% of the advisories did not change or were one category more restrictive compared to analysis of individual samples). Similarly, the methods performed reasonably well in recreating temporal trends, especially when longer-term and frequent measurements were considered. The results indicate that compositing samples within 5cm fish size bins or retaining the largest/smallest individuals and compositing in-between samples in batches of 5 with decreasing fish size would be the best approaches. Based on the literature, the findings from this study are applicable to fillet, muscle plug and whole fish mercury monitoring studies. The compositing methods may also be suitable for monitoring Persistent Organic Pollutants (POPs) in fish. Overall, compositing fish samples for mercury monitoring could result in a substantial savings (approximately 60% of the analytical cost) and should be considered in fish mercury monitoring, especially in long-term programs or when study cost is a concern. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Power and Sample Size Calculations for Logistic Regression Tests for Differential Item Functioning

ERIC Educational Resources Information Center

Li, Zhushan

2014-01-01

Logistic regression is a popular method for detecting uniform and nonuniform differential item functioning (DIF) effects. Theoretical formulas for the power and sample size calculations are derived for likelihood ratio tests and Wald tests based on the asymptotic distribution of the maximum likelihood estimators for the logistic regression model.…

An Investigation of Sample Size Splitting on ATFIND and DIMTEST

ERIC Educational Resources Information Center

Socha, Alan; DeMars, Christine E.

2013-01-01

Modeling multidimensional test data with a unidimensional model can result in serious statistical errors, such as bias in item parameter estimates. Many methods exist for assessing the dimensionality of a test. The current study focused on DIMTEST. Using simulated data, the effects of sample size splitting for use with the ATFIND procedure for…

State Estimates of Disability in America. Disability Statistics Report 3.

ERIC Educational Resources Information Center

LaPlante, Mitchell P.

This study presents and discusses existing data on disability by state, from the 1980 and 1990 censuses, the Current Population Survey (CPS), and the National Health Interview Survey (NHIS). The study used direct methods for states with large sample sizes and synthetic estimates for states with low sample sizes. The study's highlighted findings…

Grain size effect on the permittivity of La1.5Sr0.5NiO4 nanoparticles

NASA Astrophysics Data System (ADS)

Dang Thanh, Tran; Van Hong, Le

2009-09-01

Using the annealing at different temperatures the La1.5Sr0.5NiO4 ceramic samples with different mean grain size were manufactured. Mean grain size () of the samples was evaluated by Warren-Averbach method and their SEM images. The obtained results of both methods are almost the same, changing from 16.2 to 95 nm in dependence on the annealing temperature. The frequency dependence of dielectric constant in the frequency range of (1-13 MHz) was recorded for all samples. The real (ɛ') and the imaginary parts (ɛ") of the permittivity of La1.5Sr0.5NiO4 samples abnormally depend on the frequency, exhibiting a dielectric resonance around 500 kHz. R-L-C in series equivalent-circuit fitted well for the obtained result. It was supposed that there exists magnetic contribution in material that suggests the material is a multiferroic one. Dependence of the (ɛ') on the mean grain size supposed that the colossal dielectric property is an intrinsic behaviour of La1.5Sr0.5NiO4 material.

Analysis of small sample size studies using nonparametric bootstrap test with pooled resampling method.

PubMed

Dwivedi, Alok Kumar; Mallawaarachchi, Indika; Alvarado, Luis A

2017-06-30

Experimental studies in biomedical research frequently pose analytical problems related to small sample size. In such studies, there are conflicting findings regarding the choice of parametric and nonparametric analysis, especially with non-normal data. In such instances, some methodologists questioned the validity of parametric tests and suggested nonparametric tests. In contrast, other methodologists found nonparametric tests to be too conservative and less powerful and thus preferred using parametric tests. Some researchers have recommended using a bootstrap test; however, this method also has small sample size limitation. We used a pooled method in nonparametric bootstrap test that may overcome the problem related with small samples in hypothesis testing. The present study compared nonparametric bootstrap test with pooled resampling method corresponding to parametric, nonparametric, and permutation tests through extensive simulations under various conditions and using real data examples. The nonparametric pooled bootstrap t-test provided equal or greater power for comparing two means as compared with unpaired t-test, Welch t-test, Wilcoxon rank sum test, and permutation test while maintaining type I error probability for any conditions except for Cauchy and extreme variable lognormal distributions. In such cases, we suggest using an exact Wilcoxon rank sum test. Nonparametric bootstrap paired t-test also provided better performance than other alternatives. Nonparametric bootstrap test provided benefit over exact Kruskal-Wallis test. We suggest using nonparametric bootstrap test with pooled resampling method for comparing paired or unpaired means and for validating the one way analysis of variance test results for non-normal data in small sample size studies. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Sampling studies to estimate the HIV prevalence rate in female commercial sex workers.

PubMed

Pascom, Ana Roberta Pati; Szwarcwald, Célia Landmann; Barbosa Júnior, Aristides

2010-01-01

We investigated sampling methods being used to estimate the HIV prevalence rate among female commercial sex workers. The studies were classified according to the adequacy or not of the sample size to estimate HIV prevalence rate and according to the sampling method (probabilistic or convenience). We identified 75 studies that estimated the HIV prevalence rate among female sex workers. Most of the studies employed convenience samples. The sample size was not adequate to estimate HIV prevalence rate in 35 studies. The use of convenience sample limits statistical inference for the whole group. It was observed that there was an increase in the number of published studies since 2005, as well as in the number of studies that used probabilistic samples. This represents a large advance in the monitoring of risk behavior practices and HIV prevalence rate in this group.

Differentiating gold nanorod samples using particle size and shape distributions from transmission electron microscope images

NASA Astrophysics Data System (ADS)

Grulke, Eric A.; Wu, Xiaochun; Ji, Yinglu; Buhr, Egbert; Yamamoto, Kazuhiro; Song, Nam Woong; Stefaniak, Aleksandr B.; Schwegler-Berry, Diane; Burchett, Woodrow W.; Lambert, Joshua; Stromberg, Arnold J.

2018-04-01

Size and shape distributions of gold nanorod samples are critical to their physico-chemical properties, especially their longitudinal surface plasmon resonance. This interlaboratory comparison study developed methods for measuring and evaluating size and shape distributions for gold nanorod samples using transmission electron microscopy (TEM) images. The objective was to determine whether two different samples, which had different performance attributes in their application, were different with respect to their size and/or shape descriptor distributions. Touching particles in the captured images were identified using a ruggedness shape descriptor. Nanorods could be distinguished from nanocubes using an elongational shape descriptor. A non-parametric statistical test showed that cumulative distributions of an elongational shape descriptor, that is, the aspect ratio, were statistically different between the two samples for all laboratories. While the scale parameters of size and shape distributions were similar for both samples, the width parameters of size and shape distributions were statistically different. This protocol fulfills an important need for a standardized approach to measure gold nanorod size and shape distributions for applications in which quantitative measurements and comparisons are important. Furthermore, the validated protocol workflow can be automated, thus providing consistent and rapid measurements of nanorod size and shape distributions for researchers, regulatory agencies, and industry.

Confidence Interval Coverage for Cohen's Effect Size Statistic

ERIC Educational Resources Information Center

Algina, James; Keselman, H. J.; Penfield, Randall D.

2006-01-01

Kelley compared three methods for setting a confidence interval (CI) around Cohen's standardized mean difference statistic: the noncentral-"t"-based, percentile (PERC) bootstrap, and biased-corrected and accelerated (BCA) bootstrap methods under three conditions of nonnormality, eight cases of sample size, and six cases of population…

Sample size requirements for estimating effective dose from computed tomography using solid-state metal-oxide-semiconductor field-effect transistor dosimetry

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

Trattner, Sigal; Cheng, Bin; Pieniazek, Radoslaw L.

2014-04-15

Purpose: Effective dose (ED) is a widely used metric for comparing ionizing radiation burden between different imaging modalities, scanners, and scan protocols. In computed tomography (CT), ED can be estimated by performing scans on an anthropomorphic phantom in which metal-oxide-semiconductor field-effect transistor (MOSFET) solid-state dosimeters have been placed to enable organ dose measurements. Here a statistical framework is established to determine the sample size (number of scans) needed for estimating ED to a desired precision and confidence, for a particular scanner and scan protocol, subject to practical limitations. Methods: The statistical scheme involves solving equations which minimize the sample sizemore » required for estimating ED to desired precision and confidence. It is subject to a constrained variation of the estimated ED and solved using the Lagrange multiplier method. The scheme incorporates measurement variation introduced both by MOSFET calibration, and by variation in MOSFET readings between repeated CT scans. Sample size requirements are illustrated on cardiac, chest, and abdomen–pelvis CT scans performed on a 320-row scanner and chest CT performed on a 16-row scanner. Results: Sample sizes for estimating ED vary considerably between scanners and protocols. Sample size increases as the required precision or confidence is higher and also as the anticipated ED is lower. For example, for a helical chest protocol, for 95% confidence and 5% precision for the ED, 30 measurements are required on the 320-row scanner and 11 on the 16-row scanner when the anticipated ED is 4 mSv; these sample sizes are 5 and 2, respectively, when the anticipated ED is 10 mSv. Conclusions: Applying the suggested scheme, it was found that even at modest sample sizes, it is feasible to estimate ED with high precision and a high degree of confidence. As CT technology develops enabling ED to be lowered, more MOSFET measurements are needed to estimate ED with the same precision and confidence.« less

Non-invasive genetic censusing and monitoring of primate populations.

PubMed

Arandjelovic, Mimi; Vigilant, Linda

2018-03-01

Knowing the density or abundance of primate populations is essential for their conservation management and contextualizing socio-demographic and behavioral observations. When direct counts of animals are not possible, genetic analysis of non-invasive samples collected from wildlife populations allows estimates of population size with higher accuracy and precision than is possible using indirect signs. Furthermore, in contrast to traditional indirect survey methods, prolonged or periodic genetic sampling across months or years enables inference of group membership, movement, dynamics, and some kin relationships. Data may also be used to estimate sex ratios, sex differences in dispersal distances, and detect gene flow among locations. Recent advances in capture-recapture models have further improved the precision of population estimates derived from non-invasive samples. Simulations using these methods have shown that the confidence interval of point estimates includes the true population size when assumptions of the models are met, and therefore this range of population size minima and maxima should be emphasized in population monitoring studies. Innovations such as the use of sniffer dogs or anti-poaching patrols for sample collection are important to ensure adequate sampling, and the expected development of efficient and cost-effective genotyping by sequencing methods for DNAs derived from non-invasive samples will automate and speed analyses. © 2018 Wiley Periodicals, Inc.

Characterizing the size distribution of particles in urban stormwater by use of fixed-point sample-collection methods

USGS Publications Warehouse

Selbig, William R.; Bannerman, Roger T.

2011-01-01

The U.S Geological Survey, in cooperation with the Wisconsin Department of Natural Resources (WDNR) and in collaboration with the Root River Municipal Stormwater Permit Group monitored eight urban source areas representing six types of source areas in or near Madison, Wis. in an effort to improve characterization of particle-size distributions in urban stormwater by use of fixed-point sample collection methods. The types of source areas were parking lot, feeder street, collector street, arterial street, rooftop, and mixed use. This information can then be used by environmental managers and engineers when selecting the most appropriate control devices for the removal of solids from urban stormwater. Mixed-use and parking-lot study areas had the lowest median particle sizes (42 and 54 (u or mu)m, respectively), followed by the collector street study area (70 (u or mu)m). Both arterial street and institutional roof study areas had similar median particle sizes of approximately 95 (u or mu)m. Finally, the feeder street study area showed the largest median particle size of nearly 200 (u or mu)m. Median particle sizes measured as part of this study were somewhat comparable to those reported in previous studies from similar source areas. The majority of particle mass in four out of six source areas was silt and clay particles that are less than 32 (u or mu)m in size. Distributions of particles ranging from 500 (u or mu)m were highly variable both within and between source areas. Results of this study suggest substantial variability in data can inhibit the development of a single particle-size distribution that is representative of stormwater runoff generated from a single source area or land use. Continued development of improved sample collection methods, such as the depth-integrated sample arm, may reduce variability in particle-size distributions by mitigating the effect of sediment bias inherent with a fixed-point sampler.

A Bayesian nonparametric method for prediction in EST analysis

PubMed Central

Lijoi, Antonio; Mena, Ramsés H; Prünster, Igor

2007-01-01

Background Expressed sequence tags (ESTs) analyses are a fundamental tool for gene identification in organisms. Given a preliminary EST sample from a certain library, several statistical prediction problems arise. In particular, it is of interest to estimate how many new genes can be detected in a future EST sample of given size and also to determine the gene discovery rate: these estimates represent the basis for deciding whether to proceed sequencing the library and, in case of a positive decision, a guideline for selecting the size of the new sample. Such information is also useful for establishing sequencing efficiency in experimental design and for measuring the degree of redundancy of an EST library. Results In this work we propose a Bayesian nonparametric approach for tackling statistical problems related to EST surveys. In particular, we provide estimates for: a) the coverage, defined as the proportion of unique genes in the library represented in the given sample of reads; b) the number of new unique genes to be observed in a future sample; c) the discovery rate of new genes as a function of the future sample size. The Bayesian nonparametric model we adopt conveys, in a statistically rigorous way, the available information into prediction. Our proposal has appealing properties over frequentist nonparametric methods, which become unstable when prediction is required for large future samples. EST libraries, previously studied with frequentist methods, are analyzed in detail. Conclusion The Bayesian nonparametric approach we undertake yields valuable tools for gene capture and prediction in EST libraries. The estimators we obtain do not feature the kind of drawbacks associated with frequentist estimators and are reliable for any size of the additional sample. PMID:17868445

Non-destructive crystal size determination in geological samples of archaeological use by means of infrared spectroscopy.

PubMed

Olivares, M; Larrañaga, A; Irazola, M; Sarmiento, A; Murelaga, X; Etxebarria, N

2012-08-30

The determination of crystal size of chert samples can provide suitable information about the raw material used for the manufacture of archeological items. X-ray diffraction (XRD) has been widely used for this purpose in several scientific areas. However, the historical value of archeological pieces makes this procedure sometimes unfeasible and thus, non-invasive new analytical approaches are required. In this sense, a new method was developed relating the crystal size obtained by means of XRD and infrared spectroscopy (IR) using partial least squares regression. The IR spectra collected from a large amount of different geological chert samples of archeological use were pre-processed following different treatments (i.e., derivatization or sample-wise normalization) to obtain the best regression model. The full cross-validation was satisfactorily validated using real samples and the experimental root mean standard error of precision value was 165 Å whereas the average precision of the estimated size value was 3%. The features of infrared bands were also evaluated in order to know the background of the prediction ability. In the studied case, the variance in the model was associated to the differences in the characteristic stretching and bending infrared bands of SiO(2). Based on this fact, it would be feasible to estimate the crystal size if it is built beforehand a chemometric model relating the size measured by standard methods and the IR spectra. Copyright © 2012 Elsevier B.V. All rights reserved.

Novel hybrid cryo‐radial method: an emerging alternative to CT‐guided biopsy in suspected lung cancer. A prospective case series and description of technique

PubMed Central

Yap, Elaine

2017-01-01

In diagnosing peripheral pulmonary lesions (PPL), radial endobronchial ultrasound (R‐EBUS) is emerging as a safer method in comparison to CT‐guided biopsy. Despite the better safety profile, the yield of R‐EBUS remains lower (73%) than CT‐guided biopsy (90%) due to the smaller size of samples. We adopted a hybrid method by adding cryobiopsy via the R‐EBUS Guide Sheath (GS) to produce larger, non‐crushed samples to improve diagnostic capability and enhance molecular testing. We report six prospective patients who underwent this procedure in our institution. R‐EBUS samples were obtained via conventional sampling methods (needle aspiration, forceps biopsy, and cytology brush), followed by a cryobiopsy. An endobronchial blocker was placed near the planned area of biopsy in advance and inflated post‐biopsy to minimize the risk of bleeding in all patients. A chest X‐ray was performed 1 h post‐procedure. All the PPLs were visualized with R‐EBUS. The mean diameter of cryobiopsy samples was twice the size of forceps biopsy samples. In four patients, cryobiopsy samples were superior in size and the number of malignant cells per high power filed and was the preferred sample selected for mutation analysis and molecular testing. There was no pneumothorax or significant bleeding to report. Cryobiopsy samples were consistently larger and were the preferred samples for molecular testing, with an increase in the diagnostic yield and reduction in the need for repeat procedures, without hindering the marked safety profile of R‐EBUS. Using an endobronchial blocker improves the safety of this procedure. PMID:29321931

Measurement of particle size distribution of soil and selected aggregate sizes using the hydrometer method and laser diffractometry

NASA Astrophysics Data System (ADS)

Guzmán, G.; Gómez, J. A.; Giráldez, J. V.

2010-05-01

Soil particle size distribution has been traditionally determined by the hydrometer or the sieve-pipette methods, both of them time consuming and requiring a relatively large soil sample. This might be a limitation in situations, such as for instance analysis of suspended sediment, when the sample is small. A possible alternative to these methods are the optical techniques such as laser diffractometry. However the literature indicates that the use of this technique as an alternative to traditional methods is still limited, because the difficulty in replicating the results obtained with the standard methods. In this study we present the percentages of soil grain size determined using laser diffractometry within ranges set between 0.04 - 2000 μm. A Beckman-Coulter ® LS-230 with a 750 nm laser beam and software version 3.2 in five soils, representative of southern Spain: Alameda, Benacazón, Conchuela, Lanjarón and Pedrera. In three of the studied soils (Alameda, Benacazón and Conchuela) the particle size distribution of each aggregate size class was also determined. Aggregate size classes were obtained by dry sieve analysis using a Retsch AS 200 basic ®. Two hundred grams of air dried soil were sieved during 150 s, at amplitude 2 mm, getting nine different sizes between 2000 μm and 10 μm. Analyses were performed by triplicate. The soil sample preparation was also adapted to our conditions. A small amount each soil sample (less than 1 g) was transferred to the fluid module full of running water and disaggregated by ultrasonication at energy level 4 and 80 ml of sodium hexametaphosphate solution during 580 seconds. Two replicates of each sample were performed. Each measurement was made for a 90 second reading at a pump speed of 62. After the laser diffractometry analysis, each soil and its aggregate classes were processed calibrating its own optical model fitting the optical parameters that mainly depends on the color and the shape of the analyzed particle. As a second alternative a unique optical model valid for a broad range of soils developed by the Department of Soil, Water, and Environmental Science of the University of Arizona (personal communication, already submitted) was tested. The results were compared with the particle size distribution measured in the same soils and aggregate classes using the hydrometer method. Preliminary results indicate a better calibration of the technique using the optical model of the Department of Soil, Water, and Environmental Science of the University of Arizona, which obtained a good correlations (r2>0.85). This result suggests that with an appropriate calibration of the optical model laser diffractometry might provide a reliable soil particle characterization.

Addressing the "Replication Crisis": Using Original Studies to Design Replication Studies with Appropriate Statistical Power.

PubMed

Anderson, Samantha F; Maxwell, Scott E

2017-01-01

Psychology is undergoing a replication crisis. The discussion surrounding this crisis has centered on mistrust of previous findings. Researchers planning replication studies often use the original study sample effect size as the basis for sample size planning. However, this strategy ignores uncertainty and publication bias in estimated effect sizes, resulting in overly optimistic calculations. A psychologist who intends to obtain power of .80 in the replication study, and performs calculations accordingly, may have an actual power lower than .80. We performed simulations to reveal the magnitude of the difference between actual and intended power based on common sample size planning strategies and assessed the performance of methods that aim to correct for effect size uncertainty and/or bias. Our results imply that even if original studies reflect actual phenomena and were conducted in the absence of questionable research practices, popular approaches to designing replication studies may result in a low success rate, especially if the original study is underpowered. Methods correcting for bias and/or uncertainty generally had higher actual power, but were not a panacea for an underpowered original study. Thus, it becomes imperative that 1) original studies are adequately powered and 2) replication studies are designed with methods that are more likely to yield the intended level of power.

Field sampling of loose erodible material: A new method to consider the full particle-size range

NASA Astrophysics Data System (ADS)

Klose, Martina; Gill, Thomas E.

2017-04-01

The aerodynamic entrainment of sand and dust is determined by the atmospheric forces exerted onto the soil surface and by the soil-surface condition. If aerodynamic forces are strong enough to generate sand and dust lifting, the entrained sediment amount still critically depends on the supply of loose particles readily available for lifting. This loose erodible material (LEM) is sometimes defined as the thin layer of loose particles on top of a crusted surface. Here, we more generally define LEM as loose particles or particle aggregates available for entrainment, which may or may not overlay a soil crust. Field sampling of LEM is difficult and only few attempts have been made. Motivated by saltation as the most efficient process to generate dust emission, methods have focused on capturing LEM in the sand-size range or on determining the potential of a soil surface to be eroded by aerodynamic forces and particle impacts. Here, our focus is to capture the full particle-size distribution of LEM in situ, including the dust and sand-size range, to investigate the potential and likelihood of dust emission mechanisms (aerodynamic entrainment, saltation bombardment, aggregate disintegration) to occur. A new vacuum method is introduced and its capability to sample LEM without significant alteration of the LEM particle-size distribution is investigated.

An empirical analysis of the quantitative effect of data when fitting quadratic and cubic polynomials

NASA Technical Reports Server (NTRS)

Canavos, G. C.

1974-01-01

A study is made of the extent to which the size of the sample affects the accuracy of a quadratic or a cubic polynomial approximation of an experimentally observed quantity, and the trend with regard to improvement in the accuracy of the approximation as a function of sample size is established. The task is made possible through a simulated analysis carried out by the Monte Carlo method in which data are simulated by using several transcendental or algebraic functions as models. Contaminated data of varying amounts are fitted to either quadratic or cubic polynomials, and the behavior of the mean-squared error of the residual variance is determined as a function of sample size. Results indicate that the effect of the size of the sample is significant only for relatively small sizes and diminishes drastically for moderate and large amounts of experimental data.

Simulation of Particle Size Effect on Dynamic Properties and Fracture of PTFE-W-Al Composites

NASA Astrophysics Data System (ADS)

Herbold, Eric; Cai, Jing; Benson, David; Nesterenko, Vitali

2007-06-01

Recent investigations of the dynamic compressive strength of cold isostatically pressed (CIP) composites of polytetrafluoroethylene (PTFE), tungsten and aluminum powders show significant differences depending on the size of metallic particles. PTFE and aluminum mixtures are known to be energetic under dynamic and thermal loading. The addition of tungsten increases density and overall strength of the sample. Multi-material Eulerian and arbitrary Lagrangian-Eulerian methods were used for the investigation due to the complexity of the microstructure, relatively large deformations and the ability to handle the formation of free surfaces in a natural manner. The calculations indicate that the observed dependence of sample strength on particle size is due to the formation of force chains under dynamic loading in samples with small particle sizes even at larger porosity in comparison with samples with large grain size and larger density.

Size dependence of magnetorheological properties of cobalt ferrite ferrofluid

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

Radhika, B.; Sahoo, Rasmita; Srinath, S., E-mail: srinath@uohyd.ac.in

2015-06-24

Cobalt Ferrite nanoparticles were synthesized using co-precipitation method at reaction temperatures of 40°C and 80°C. X-Ray diffraction studies confirm cubic phase formation. The average crystallite sizes were found to be ∼30nm and ∼48nm for 40°C sample and 80°C sample respectively. Magnetic properties measured using vibrating sample magnetometer show higher coercivety and magnetization for sample prepared at 80°C. Magnetorheological properties of CoFe2O4 ferrofluids were measured and studied.

Evaluation of the method of collecting suspended sediment from large rivers by discharge-weighted pumping and separation by continuous- flow centrifugation

USGS Publications Warehouse

Moody, J.A.; Meade, R.H.

1994-01-01

The efficacy of the method is evaluated by comparing the particle size distributions of sediment collected by the discharge-weighted pumping method with the particle size distributions of sediment collected by depth integration and separated by gravitational settling. The pumping method was found to undersample the suspended sand sized particles (>63 ??m) but to collect a representative sample of the suspended silt and clay sized particles (<63??m). The success of the discharge-weighted pumping method depends on how homogeneously the silt and clay sized particles (<63 ??m) are distributed in the vertical direction in the river. The degree of homogeneity depends on the composition and degree of aggregation of the suspended sediment particles. -from Authors

Neuromuscular dose-response studies: determining sample size.

PubMed

Kopman, A F; Lien, C A; Naguib, M

2011-02-01

Investigators planning dose-response studies of neuromuscular blockers have rarely used a priori power analysis to determine the minimal sample size their protocols require. Institutional Review Boards and peer-reviewed journals now generally ask for this information. This study outlines a proposed method for meeting these requirements. The slopes of the dose-response relationships of eight neuromuscular blocking agents were determined using regression analysis. These values were substituted for γ in the Hill equation. When this is done, the coefficient of variation (COV) around the mean value of the ED₅₀ for each drug is easily calculated. Using these values, we performed an a priori one-sample two-tailed t-test of the means to determine the required sample size when the allowable error in the ED₅₀ was varied from ±10-20%. The COV averaged 22% (range 15-27%). We used a COV value of 25% in determining the sample size. If the allowable error in finding the mean ED₅₀ is ±15%, a sample size of 24 is needed to achieve a power of 80%. Increasing 'accuracy' beyond this point requires increasing greater sample sizes (e.g. an 'n' of 37 for a ±12% error). On the basis of the results of this retrospective analysis, a total sample size of not less than 24 subjects should be adequate for determining a neuromuscular blocking drug's clinical potency with a reasonable degree of assurance.

Sample Size for Tablet Compression and Capsule Filling Events During Process Validation.

PubMed

Charoo, Naseem Ahmad; Durivage, Mark; Rahman, Ziyaur; Ayad, Mohamad Haitham

2017-12-01

During solid dosage form manufacturing, the uniformity of dosage units (UDU) is ensured by testing samples at 2 stages, that is, blend stage and tablet compression or capsule/powder filling stage. The aim of this work is to propose a sample size selection approach based on quality risk management principles for process performance qualification (PPQ) and continued process verification (CPV) stages by linking UDU to potential formulation and process risk factors. Bayes success run theorem appeared to be the most appropriate approach among various methods considered in this work for computing sample size for PPQ. The sample sizes for high-risk (reliability level of 99%), medium-risk (reliability level of 95%), and low-risk factors (reliability level of 90%) were estimated to be 299, 59, and 29, respectively. Risk-based assignment of reliability levels was supported by the fact that at low defect rate, the confidence to detect out-of-specification units would decrease which must be supplemented with an increase in sample size to enhance the confidence in estimation. Based on level of knowledge acquired during PPQ and the level of knowledge further required to comprehend process, sample size for CPV was calculated using Bayesian statistics to accomplish reduced sampling design for CPV. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Rasch fit statistics and sample size considerations for polytomous data

PubMed Central

Smith, Adam B; Rush, Robert; Fallowfield, Lesley J; Velikova, Galina; Sharpe, Michael

2008-01-01

Background Previous research on educational data has demonstrated that Rasch fit statistics (mean squares and t-statistics) are highly susceptible to sample size variation for dichotomously scored rating data, although little is known about this relationship for polytomous data. These statistics help inform researchers about how well items fit to a unidimensional latent trait, and are an important adjunct to modern psychometrics. Given the increasing use of Rasch models in health research the purpose of this study was therefore to explore the relationship between fit statistics and sample size for polytomous data. Methods Data were collated from a heterogeneous sample of cancer patients (n = 4072) who had completed both the Patient Health Questionnaire – 9 and the Hospital Anxiety and Depression Scale. Ten samples were drawn with replacement for each of eight sample sizes (n = 25 to n = 3200). The Rating and Partial Credit Models were applied and the mean square and t-fit statistics (infit/outfit) derived for each model. Results The results demonstrated that t-statistics were highly sensitive to sample size, whereas mean square statistics remained relatively stable for polytomous data. Conclusion It was concluded that mean square statistics were relatively independent of sample size for polytomous data and that misfit to the model could be identified using published recommended ranges. PMID:18510722

Effects of sample size on KERNEL home range estimates

USGS Publications Warehouse

Seaman, D.E.; Millspaugh, J.J.; Kernohan, Brian J.; Brundige, Gary C.; Raedeke, Kenneth J.; Gitzen, Robert A.

1999-01-01

Kernel methods for estimating home range are being used increasingly in wildlife research, but the effect of sample size on their accuracy is not known. We used computer simulations of 10-200 points/home range and compared accuracy of home range estimates produced by fixed and adaptive kernels with the reference (REF) and least-squares cross-validation (LSCV) methods for determining the amount of smoothing. Simulated home ranges varied from simple to complex shapes created by mixing bivariate normal distributions. We used the size of the 95% home range area and the relative mean squared error of the surface fit to assess the accuracy of the kernel home range estimates. For both measures, the bias and variance approached an asymptote at about 50 observations/home range. The fixed kernel with smoothing selected by LSCV provided the least-biased estimates of the 95% home range area. All kernel methods produced similar surface fit for most simulations, but the fixed kernel with LSCV had the lowest frequency and magnitude of very poor estimates. We reviewed 101 papers published in The Journal of Wildlife Management (JWM) between 1980 and 1997 that estimated animal home ranges. A minority of these papers used nonparametric utilization distribution (UD) estimators, and most did not adequately report sample sizes. We recommend that home range studies using kernel estimates use LSCV to determine the amount of smoothing, obtain a minimum of 30 observations per animal (but preferably a?Y50), and report sample sizes in published results.

Bed-material characteristics of the Sacramento–San Joaquin Delta, California, 2010–13

USGS Publications Warehouse

Marineau, Mathieu D.; Wright, Scott A.

2017-02-10

The characteristics of bed material at selected sites within the Sacramento–San Joaquin Delta, California, during 2010–13 are described in a study conducted by the U.S. Geological Survey in cooperation with the Bureau of Reclamation. During 2010‒13, six complete sets of samples were collected. Samples were initially collected at 30 sites; however, starting in 2012, samples were collected at 7 additional sites. These sites are generally collocated with an active streamgage. At all but one site, a separate bed-material sample was collected at three locations within the channel (left, right, and center). Bed-material samples were collected using either a US BMH–60 or a US BM–54 (for sites with higher stream velocity) cable-suspended, scoop sampler. Samples from each location were oven-dried and sieved. Bed material finer than 2 millimeters was subsampled using a sieving riffler and processed using a Beckman Coulter LS 13–320 laser diffraction particle-size analyzer. To determine the organic content of the bed material, the loss on ignition method was used for one subsample from each location. Particle-size distributions are presented as cumulative percent finer than a given size. Median and 90th-percentile particle size, and the percentage of subsample mass lost using the loss on ignition method for each sample are also presented in this report.

Ranked set sampling: cost and optimal set size.

PubMed

Nahhas, Ramzi W; Wolfe, Douglas A; Chen, Haiying

2002-12-01

McIntyre (1952, Australian Journal of Agricultural Research 3, 385-390) introduced ranked set sampling (RSS) as a method for improving estimation of a population mean in settings where sampling and ranking of units from the population are inexpensive when compared with actual measurement of the units. Two of the major factors in the usefulness of RSS are the set size and the relative costs of the various operations of sampling, ranking, and measurement. In this article, we consider ranking error models and cost models that enable us to assess the effect of different cost structures on the optimal set size for RSS. For reasonable cost structures, we find that the optimal RSS set sizes are generally larger than had been anticipated previously. These results will provide a useful tool for determining whether RSS is likely to lead to an improvement over simple random sampling in a given setting and, if so, what RSS set size is best to use in this case.

Hierarchical modeling of cluster size in wildlife surveys

USGS Publications Warehouse

Royle, J. Andrew

2008-01-01

Clusters or groups of individuals are the fundamental unit of observation in many wildlife sampling problems, including aerial surveys of waterfowl, marine mammals, and ungulates. Explicit accounting of cluster size in models for estimating abundance is necessary because detection of individuals within clusters is not independent and detectability of clusters is likely to increase with cluster size. This induces a cluster size bias in which the average cluster size in the sample is larger than in the population at large. Thus, failure to account for the relationship between delectability and cluster size will tend to yield a positive bias in estimates of abundance or density. I describe a hierarchical modeling framework for accounting for cluster-size bias in animal sampling. The hierarchical model consists of models for the observation process conditional on the cluster size distribution and the cluster size distribution conditional on the total number of clusters. Optionally, a spatial model can be specified that describes variation in the total number of clusters per sample unit. Parameter estimation, model selection, and criticism may be carried out using conventional likelihood-based methods. An extension of the model is described for the situation where measurable covariates at the level of the sample unit are available. Several candidate models within the proposed class are evaluated for aerial survey data on mallard ducks (Anas platyrhynchos).

Estimating the Effective Sample Size of Tree Topologies from Bayesian Phylogenetic Analyses

PubMed Central

Lanfear, Robert; Hua, Xia; Warren, Dan L.

2016-01-01

Bayesian phylogenetic analyses estimate posterior distributions of phylogenetic tree topologies and other parameters using Markov chain Monte Carlo (MCMC) methods. Before making inferences from these distributions, it is important to assess their adequacy. To this end, the effective sample size (ESS) estimates how many truly independent samples of a given parameter the output of the MCMC represents. The ESS of a parameter is frequently much lower than the number of samples taken from the MCMC because sequential samples from the chain can be non-independent due to autocorrelation. Typically, phylogeneticists use a rule of thumb that the ESS of all parameters should be greater than 200. However, we have no method to calculate an ESS of tree topology samples, despite the fact that the tree topology is often the parameter of primary interest and is almost always central to the estimation of other parameters. That is, we lack a method to determine whether we have adequately sampled one of the most important parameters in our analyses. In this study, we address this problem by developing methods to estimate the ESS for tree topologies. We combine these methods with two new diagnostic plots for assessing posterior samples of tree topologies, and compare their performance on simulated and empirical data sets. Combined, the methods we present provide new ways to assess the mixing and convergence of phylogenetic tree topologies in Bayesian MCMC analyses. PMID:27435794

Estimating population sizes for elusive animals: the forest elephants of Kakum National Park, Ghana.

PubMed

Eggert, L S; Eggert, J A; Woodruff, D S

2003-06-01

African forest elephants are difficult to observe in the dense vegetation, and previous studies have relied upon indirect methods to estimate population sizes. Using multilocus genotyping of noninvasively collected samples, we performed a genetic survey of the forest elephant population at Kakum National Park, Ghana. We estimated population size, sex ratio and genetic variability from our data, then combined this information with field observations to divide the population into age groups. Our population size estimate was very close to that obtained using dung counts, the most commonly used indirect method of estimating the population sizes of forest elephant populations. As their habitat is fragmented by expanding human populations, management will be increasingly important to the persistence of forest elephant populations. The data that can be obtained from noninvasively collected samples will help managers plan for the conservation of this keystone species.

Probabilistic Design of a Mars Sample Return Earth Entry Vehicle Thermal Protection System

NASA Technical Reports Server (NTRS)

Dec, John A.; Mitcheltree, Robert A.

2002-01-01

The driving requirement for design of a Mars Sample Return mission is to assure containment of the returned samples. Designing to, and demonstrating compliance with, such a requirement requires physics based tools that establish the relationship between engineer's sizing margins and probabilities of failure. The traditional method of determining margins on ablative thermal protection systems, while conservative, provides little insight into the actual probability of an over-temperature during flight. The objective of this paper is to describe a new methodology for establishing margins on sizing the thermal protection system (TPS). Results of this Monte Carlo approach are compared with traditional methods.

Optimization of scat detection methods for a social ungulate, the wild pig, and experimental evaluation of factors affecting detection of scat

USGS Publications Warehouse

Keiter, David A.; Cunningham, Fred L.; Rhodes, Olin E.; Irwin, Brian J.; Beasley, James

2016-01-01

Collection of scat samples is common in wildlife research, particularly for genetic capture-mark-recapture applications. Due to high degradation rates of genetic material in scat, large numbers of samples must be collected to generate robust estimates. Optimization of sampling approaches to account for taxa-specific patterns of scat deposition is, therefore, necessary to ensure sufficient sample collection. While scat collection methods have been widely studied in carnivores, research to maximize scat collection and noninvasive sampling efficiency for social ungulates is lacking. Further, environmental factors or scat morphology may influence detection of scat by observers. We contrasted performance of novel radial search protocols with existing adaptive cluster sampling protocols to quantify differences in observed amounts of wild pig (Sus scrofa) scat. We also evaluated the effects of environmental (percentage of vegetative ground cover and occurrence of rain immediately prior to sampling) and scat characteristics (fecal pellet size and number) on the detectability of scat by observers. We found that 15- and 20-m radial search protocols resulted in greater numbers of scats encountered than the previously used adaptive cluster sampling approach across habitat types, and that fecal pellet size, number of fecal pellets, percent vegetative ground cover, and recent rain events were significant predictors of scat detection. Our results suggest that use of a fixed-width radial search protocol may increase the number of scats detected for wild pigs, or other social ungulates, allowing more robust estimation of population metrics using noninvasive genetic sampling methods. Further, as fecal pellet size affected scat detection, juvenile or smaller-sized animals may be less detectable than adult or large animals, which could introduce bias into abundance estimates. Knowledge of relationships between environmental variables and scat detection may allow researchers to optimize sampling protocols to maximize utility of noninvasive sampling for wild pigs and other social ungulates.

Optimization of scat detection methods for a social ungulate, the wild pig, and experimental evaluation of factors affecting detection of scat

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

Keiter, David A.; Cunningham, Fred L.; Rhodes, Jr., Olin E.

Collection of scat samples is common in wildlife research, particularly for genetic capture-mark-recapture applications. Due to high degradation rates of genetic material in scat, large numbers of samples must be collected to generate robust estimates. Optimization of sampling approaches to account for taxa-specific patterns of scat deposition is, therefore, necessary to ensure sufficient sample collection. While scat collection methods have been widely studied in carnivores, research to maximize scat collection and noninvasive sampling efficiency for social ungulates is lacking. Further, environmental factors or scat morphology may influence detection of scat by observers. We contrasted performance of novel radial search protocolsmore » with existing adaptive cluster sampling protocols to quantify differences in observed amounts of wild pig ( Sus scrofa) scat. We also evaluated the effects of environmental (percentage of vegetative ground cover and occurrence of rain immediately prior to sampling) and scat characteristics (fecal pellet size and number) on the detectability of scat by observers. We found that 15- and 20-m radial search protocols resulted in greater numbers of scats encountered than the previously used adaptive cluster sampling approach across habitat types, and that fecal pellet size, number of fecal pellets, percent vegetative ground cover, and recent rain events were significant predictors of scat detection. Our results suggest that use of a fixed-width radial search protocol may increase the number of scats detected for wild pigs, or other social ungulates, allowing more robust estimation of population metrics using noninvasive genetic sampling methods. Further, as fecal pellet size affected scat detection, juvenile or smaller-sized animals may be less detectable than adult or large animals, which could introduce bias into abundance estimates. In conclusion, knowledge of relationships between environmental variables and scat detection may allow researchers to optimize sampling protocols to maximize utility of noninvasive sampling for wild pigs and other social ungulates.« less

Optimization of Scat Detection Methods for a Social Ungulate, the Wild Pig, and Experimental Evaluation of Factors Affecting Detection of Scat.

PubMed

Keiter, David A; Cunningham, Fred L; Rhodes, Olin E; Irwin, Brian J; Beasley, James C

2016-01-01

Collection of scat samples is common in wildlife research, particularly for genetic capture-mark-recapture applications. Due to high degradation rates of genetic material in scat, large numbers of samples must be collected to generate robust estimates. Optimization of sampling approaches to account for taxa-specific patterns of scat deposition is, therefore, necessary to ensure sufficient sample collection. While scat collection methods have been widely studied in carnivores, research to maximize scat collection and noninvasive sampling efficiency for social ungulates is lacking. Further, environmental factors or scat morphology may influence detection of scat by observers. We contrasted performance of novel radial search protocols with existing adaptive cluster sampling protocols to quantify differences in observed amounts of wild pig (Sus scrofa) scat. We also evaluated the effects of environmental (percentage of vegetative ground cover and occurrence of rain immediately prior to sampling) and scat characteristics (fecal pellet size and number) on the detectability of scat by observers. We found that 15- and 20-m radial search protocols resulted in greater numbers of scats encountered than the previously used adaptive cluster sampling approach across habitat types, and that fecal pellet size, number of fecal pellets, percent vegetative ground cover, and recent rain events were significant predictors of scat detection. Our results suggest that use of a fixed-width radial search protocol may increase the number of scats detected for wild pigs, or other social ungulates, allowing more robust estimation of population metrics using noninvasive genetic sampling methods. Further, as fecal pellet size affected scat detection, juvenile or smaller-sized animals may be less detectable than adult or large animals, which could introduce bias into abundance estimates. Knowledge of relationships between environmental variables and scat detection may allow researchers to optimize sampling protocols to maximize utility of noninvasive sampling for wild pigs and other social ungulates.

Optimization of scat detection methods for a social ungulate, the wild pig, and experimental evaluation of factors affecting detection of scat

DOE PAGES

Keiter, David A.; Cunningham, Fred L.; Rhodes, Jr., Olin E.; ...

2016-05-25

Collection of scat samples is common in wildlife research, particularly for genetic capture-mark-recapture applications. Due to high degradation rates of genetic material in scat, large numbers of samples must be collected to generate robust estimates. Optimization of sampling approaches to account for taxa-specific patterns of scat deposition is, therefore, necessary to ensure sufficient sample collection. While scat collection methods have been widely studied in carnivores, research to maximize scat collection and noninvasive sampling efficiency for social ungulates is lacking. Further, environmental factors or scat morphology may influence detection of scat by observers. We contrasted performance of novel radial search protocolsmore » with existing adaptive cluster sampling protocols to quantify differences in observed amounts of wild pig ( Sus scrofa) scat. We also evaluated the effects of environmental (percentage of vegetative ground cover and occurrence of rain immediately prior to sampling) and scat characteristics (fecal pellet size and number) on the detectability of scat by observers. We found that 15- and 20-m radial search protocols resulted in greater numbers of scats encountered than the previously used adaptive cluster sampling approach across habitat types, and that fecal pellet size, number of fecal pellets, percent vegetative ground cover, and recent rain events were significant predictors of scat detection. Our results suggest that use of a fixed-width radial search protocol may increase the number of scats detected for wild pigs, or other social ungulates, allowing more robust estimation of population metrics using noninvasive genetic sampling methods. Further, as fecal pellet size affected scat detection, juvenile or smaller-sized animals may be less detectable than adult or large animals, which could introduce bias into abundance estimates. In conclusion, knowledge of relationships between environmental variables and scat detection may allow researchers to optimize sampling protocols to maximize utility of noninvasive sampling for wild pigs and other social ungulates.« less

Size Matters: Assessing Optimum Soil Sample Size for Fungal and Bacterial Community Structure Analyses Using High Throughput Sequencing of rRNA Gene Amplicons

PubMed Central

Penton, C. Ryan; Gupta, Vadakattu V. S. R.; Yu, Julian; Tiedje, James M.

2016-01-01

We examined the effect of different soil sample sizes obtained from an agricultural field, under a single cropping system uniform in soil properties and aboveground crop responses, on bacterial and fungal community structure and microbial diversity indices. DNA extracted from soil sample sizes of 0.25, 1, 5, and 10 g using MoBIO kits and from 10 and 100 g sizes using a bead-beating method (SARDI) were used as templates for high-throughput sequencing of 16S and 28S rRNA gene amplicons for bacteria and fungi, respectively, on the Illumina MiSeq and Roche 454 platforms. Sample size significantly affected overall bacterial and fungal community structure, replicate dispersion and the number of operational taxonomic units (OTUs) retrieved. Richness, evenness and diversity were also significantly affected. The largest diversity estimates were always associated with the 10 g MoBIO extractions with a corresponding reduction in replicate dispersion. For the fungal data, smaller MoBIO extractions identified more unclassified Eukaryota incertae sedis and unclassified glomeromycota while the SARDI method retrieved more abundant OTUs containing unclassified Pleosporales and the fungal genera Alternaria and Cercophora. Overall, these findings indicate that a 10 g soil DNA extraction is most suitable for both soil bacterial and fungal communities for retrieving optimal diversity while still capturing rarer taxa in concert with decreasing replicate variation. PMID:27313569

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

ERIC Educational Resources Information Center

Krishnamoorthy, K.; Xia, Yanping

2008-01-01

The problems of hypothesis testing and interval estimation of the squared multiple correlation coefficient of a multivariate normal distribution are considered. It is shown that available one-sided tests are uniformly most powerful, and the one-sided confidence intervals are uniformly most accurate. An exact method of calculating sample size to…

Determining sample size for tree utilization surveys

Treesearch

Stanley J. Zarnoch; James W. Bentley; Tony G. Johnson

2004-01-01

The U.S. Department of Agriculture Forest Service has conducted many studies to determine what proportion of the timber harvested in the South is actually utilized. This paper describes the statistical methods used to determine required sample sizes for estimating utilization ratios for a required level of precision. The data used are those for 515 hardwood and 1,557...

FIELD SAMPLING OF RESIDUAL AVIATION GASOLINE IN SANDY SOIL

EPA Science Inventory

Two complimentary field sampling methods for the determination of residual aviation gasoline content in the contaminated capillary fringe of a fine, uniform, sandy soil were investigated. The first method featured filed extrusion of core barrels into pint size Mason jars, while ...

Asymmetrical flow field flow fractionation methods to characterize submicron particles: application to carbon-based aggregates and nanoplastics.

PubMed

Gigault, Julien; El Hadri, Hind; Reynaud, Stéphanie; Deniau, Elise; Grassl, Bruno

2017-11-01

In the last 10 years, asymmetrical flow field flow fractionation (AF4) has been one of the most promising approaches to characterize colloidal particles. Nevertheless, despite its potentialities, it is still considered a complex technique to set up, and the theory is difficult to apply for the characterization of complex samples containing submicron particles and nanoparticles. In the present work, we developed and propose a simple analytical strategy to rapidly determine the presence of several submicron populations in an unknown sample with one programmed AF4 method. To illustrate this method, we analyzed polystyrene particles and fullerene aggregates of size covering the whole colloidal size distribution. A global and fast AF4 method (method O) allowed us to screen the presence of particles with size ranging from 1 to 800 nm. By examination of the fractionating power F d , as proposed in the literature, convenient fractionation resolution was obtained for size ranging from 10 to 400 nm. The global F d values, as well as the steric inversion diameter, for the whole colloidal size distribution correspond to the predicted values obtained by model studies. On the basis of this method and without the channel components or mobile phase composition being changed, four isocratic subfraction methods were performed to achieve further high-resolution separation as a function of different size classes: 10-100 nm, 100-200 nm, 200-450 nm, and 450-800 nm in diameter. Finally, all the methods developed were applied in characterization of nanoplastics, which has received great attention in recent years. Graphical Absract Characterization of the nanoplastics by asymmetrical flow field flow fractionation within the colloidal size range.

Preservation And Processing Methods For Molecular Genetic Detection And Quantification Of Nosema Ceranae

USDA-ARS?s Scientific Manuscript database

The prevalence of Nosema ceranae in managed honey bee colonies has increased dramatically in the past 10 – 20 years worldwide. A variety of genetic testing methods for species identification and prevalence are now available. However sample size and preservation method of samples prior to testing hav...

Improved ASTM G72 Test Method for Ensuring Adequate Fuel-to-Oxidizer Ratios

NASA Technical Reports Server (NTRS)

Juarez, Alfredo; Harper, Susana A.

2016-01-01

The ASTM G72/G72M-15 Standard Test Method for Autogenous Ignition Temperature of Liquids and Solids in a High-Pressure Oxygen-Enriched Environment is currently used to evaluate materials for the ignition susceptibility driven by exposure to external heat in an enriched oxygen environment. Testing performed on highly volatile liquids such as cleaning solvents has proven problematic due to inconsistent test results (non-ignitions). Non-ignition results can be misinterpreted as favorable oxygen compatibility, although they are more likely associated with inadequate fuel-to-oxidizer ratios. Forced evaporation during purging and inadequate sample size were identified as two potential causes for inadequate available sample material during testing. In an effort to maintain adequate fuel-to-oxidizer ratios within the reaction vessel during test, several parameters were considered, including sample size, pretest sample chilling, pretest purging, and test pressure. Tests on a variety of solvents exhibiting a range of volatilities are presented in this paper. A proposed improvement to the standard test protocol as a result of this evaluation is also presented. Execution of the final proposed improved test protocol outlines an incremental step method of determining optimal conditions using increased sample sizes while considering test system safety limits. The proposed improved test method increases confidence in results obtained by utilizing the ASTM G72 autogenous ignition temperature test method and can aid in the oxygen compatibility assessment of highly volatile liquids and other conditions that may lead to false non-ignition results.

A method for analysing small samples of floral pollen for free and protein-bound amino acids.

PubMed

Stabler, Daniel; Power, Eileen F; Borland, Anne M; Barnes, Jeremy D; Wright, Geraldine A

2018-02-01

Pollen provides floral visitors with essential nutrients including proteins, lipids, vitamins and minerals. As an important nutrient resource for pollinators, including honeybees and bumblebees, pollen quality is of growing interest in assessing available nutrition to foraging bees. To date, quantifying the protein-bound amino acids in pollen has been difficult and methods rely on large amounts of pollen, typically more than 1 g. More usual is to estimate a crude protein value based on the nitrogen content of pollen, however, such methods provide no information on the distribution of essential and non-essential amino acids constituting the proteins.Here, we describe a method of microwave-assisted acid hydrolysis using low amounts of pollen that allows exploration of amino acid composition, quantified using ultra high performance liquid chromatography (UHPLC), and a back calculation to estimate the crude protein content of pollen.Reliable analysis of protein-bound and free amino acids as well as an estimation of crude protein concentration was obtained from pollen samples as low as 1 mg. Greater variation in both protein-bound and free amino acids was found in pollen sample sizes <1 mg. Due to the variability in recovery of amino acids in smaller sample sizes, we suggest a correction factor to apply to specific sample sizes of pollen in order to estimate total crude protein content.The method described in this paper will allow researchers to explore the composition of amino acids in pollen and will aid research assessing the available nutrition to pollinating animals. This method will be particularly useful in assaying the pollen of wild plants, from which it is difficult to obtain large sample weights.

Sample manipulation and data assembly for robust microcrystal synchrotron crystallography

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

Guo, Gongrui; Fuchs, Martin R.; Shi, Wuxian

With the recent developments in microcrystal handling, synchrotron microdiffraction beamline instrumentation and data analysis, microcrystal crystallography with crystal sizes of less than 10 µm is appealing at synchrotrons. However, challenges remain in sample manipulation and data assembly for robust microcrystal synchrotron crystallography. Here, the development of micro-sized polyimide well-mounts for the manipulation of microcrystals of a few micrometres in size and the implementation of a robust data-analysis method for the assembly of rotational microdiffraction data sets from many microcrystals are described. Here, the method demonstrates that microcrystals may be routinely utilized for the acquisition and assembly of complete data setsmore » from synchrotron microdiffraction beamlines.« less

Sample manipulation and data assembly for robust microcrystal synchrotron crystallography

DOE PAGES

Guo, Gongrui; Fuchs, Martin R.; Shi, Wuxian; ...

2018-04-19

With the recent developments in microcrystal handling, synchrotron microdiffraction beamline instrumentation and data analysis, microcrystal crystallography with crystal sizes of less than 10 µm is appealing at synchrotrons. However, challenges remain in sample manipulation and data assembly for robust microcrystal synchrotron crystallography. Here, the development of micro-sized polyimide well-mounts for the manipulation of microcrystals of a few micrometres in size and the implementation of a robust data-analysis method for the assembly of rotational microdiffraction data sets from many microcrystals are described. Here, the method demonstrates that microcrystals may be routinely utilized for the acquisition and assembly of complete data setsmore » from synchrotron microdiffraction beamlines.« less

Sample size considerations for clinical research studies in nuclear cardiology.

PubMed

Chiuzan, Cody; West, Erin A; Duong, Jimmy; Cheung, Ken Y K; Einstein, Andrew J

2015-12-01

Sample size calculation is an important element of research design that investigators need to consider in the planning stage of the study. Funding agencies and research review panels request a power analysis, for example, to determine the minimum number of subjects needed for an experiment to be informative. Calculating the right sample size is crucial to gaining accurate information and ensures that research resources are used efficiently and ethically. The simple question "How many subjects do I need?" does not always have a simple answer. Before calculating the sample size requirements, a researcher must address several aspects, such as purpose of the research (descriptive or comparative), type of samples (one or more groups), and data being collected (continuous or categorical). In this article, we describe some of the most frequent methods for calculating the sample size with examples from nuclear cardiology research, including for t tests, analysis of variance (ANOVA), non-parametric tests, correlation, Chi-squared tests, and survival analysis. For the ease of implementation, several examples are also illustrated via user-friendly free statistical software.

Adaptive cluster sampling: An efficient method for assessing inconspicuous species

Treesearch

Andrea M. Silletti; Joan Walker

2003-01-01

Restorationistis typically evaluate the success of a project by estimating the population sizes of species that have been planted or seeded. Because total census is raely feasible, they must rely on sampling methods for population estimates. However, traditional random sampling designs may be inefficient for species that, for one reason or another, are challenging to...

Ultrafast image-based dynamic light scattering for nanoparticle sizing

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

Zhou, Wu; Zhang, Jie; Liu, Lili

An ultrafast sizing method for nanoparticles is proposed, called as UIDLS (Ultrafast Image-based Dynamic Light Scattering). This method makes use of the intensity fluctuation of scattered light from nanoparticles in Brownian motion, which is similar to the conventional DLS method. The difference in the experimental system is that the scattered light by nanoparticles is received by an image sensor instead of a photomultiplier tube. A novel data processing algorithm is proposed to directly get correlation coefficient between two images at a certain time interval (from microseconds to milliseconds) by employing a two-dimensional image correlation algorithm. This coefficient has been provedmore » to be a monotonic function of the particle diameter. Samples of standard latex particles (79/100/352/482/948 nm) were measured for validation of the proposed method. The measurement accuracy of higher than 90% was found with standard deviations less than 3%. A sample of nanosilver particle with nominal size of 20 ± 2 nm and a sample of polymethyl methacrylate emulsion with unknown size were also tested using UIDLS method. The measured results were 23.2 ± 3.0 nm and 246.1 ± 6.3 nm, respectively, which is substantially consistent with the transmission electron microscope results. Since the time for acquisition of two successive images has been reduced to less than 1 ms and the data processing time in about 10 ms, the total measuring time can be dramatically reduced from hundreds seconds to tens of milliseconds, which provides the potential for real-time and in situ nanoparticle sizing.« less

Diagnostic test accuracy and prevalence inferences based on joint and sequential testing with finite population sampling.

PubMed

Su, Chun-Lung; Gardner, Ian A; Johnson, Wesley O

2004-07-30

The two-test two-population model, originally formulated by Hui and Walter, for estimation of test accuracy and prevalence estimation assumes conditionally independent tests, constant accuracy across populations and binomial sampling. The binomial assumption is incorrect if all individuals in a population e.g. child-care centre, village in Africa, or a cattle herd are sampled or if the sample size is large relative to population size. In this paper, we develop statistical methods for evaluating diagnostic test accuracy and prevalence estimation based on finite sample data in the absence of a gold standard. Moreover, two tests are often applied simultaneously for the purpose of obtaining a 'joint' testing strategy that has either higher overall sensitivity or specificity than either of the two tests considered singly. Sequential versions of such strategies are often applied in order to reduce the cost of testing. We thus discuss joint (simultaneous and sequential) testing strategies and inference for them. Using the developed methods, we analyse two real and one simulated data sets, and we compare 'hypergeometric' and 'binomial-based' inferences. Our findings indicate that the posterior standard deviations for prevalence (but not sensitivity and specificity) based on finite population sampling tend to be smaller than their counterparts for infinite population sampling. Finally, we make recommendations about how small the sample size should be relative to the population size to warrant use of the binomial model for prevalence estimation. Copyright 2004 John Wiley & Sons, Ltd.

Effects of Al(OH)O nanoparticle agglomerate size in epoxy resin on tension, bending, and fracture properties

NASA Astrophysics Data System (ADS)

Jux, Maximilian; Finke, Benedikt; Mahrholz, Thorsten; Sinapius, Michael; Kwade, Arno; Schilde, Carsten

2017-04-01

Several epoxy Al(OH)O (boehmite) dispersions in an epoxy resin are produced in a kneader to study the mechanistic correlation between the nanoparticle size and mechanical properties of the prepared nanocomposites. The agglomerate size is set by a targeted variation in solid content and temperature during dispersion, resulting in a different level of stress intensity and thus a different final agglomerate size during the process. The suspension viscosity was used for the estimation of stress energy in laminar shear flow. Agglomerate size measurements are executed via dynamic light scattering to ensure the quality of the produced dispersions. Furthermore, various nanocomposite samples are prepared for three-point bending, tension, and fracture toughness tests. The screening of the size effect is executed with at least seven samples per agglomerate size and test method. The variation of solid content is found to be a reliable method to adjust the agglomerate size between 138-354 nm during dispersion. The size effect on the Young's modulus and the critical stress intensity is only marginal. Nevertheless, there is a statistically relevant trend showing a linear increase with a decrease in agglomerate size. In contrast, the size effect is more dominant to the sample's strain and stress at failure. Unlike microscaled agglomerates or particles, which lead to embrittlement of the composite material, nanoscaled agglomerates or particles cause the composite elongation to be nearly of the same level as the base material. The observed effect is valid for agglomerate sizes between 138-354 nm and a particle mass fraction of 10 wt%.

Human body mass estimation: a comparison of "morphometric" and "mechanical" methods.

PubMed

Auerbach, Benjamin M; Ruff, Christopher B

2004-12-01

In the past, body mass was reconstructed from hominin skeletal remains using both "mechanical" methods which rely on the support of body mass by weight-bearing skeletal elements, and "morphometric" methods which reconstruct body mass through direct assessment of body size and shape. A previous comparison of two such techniques, using femoral head breadth (mechanical) and stature and bi-iliac breadth (morphometric), indicated a good general correspondence between them (Ruff et al. [1997] Nature 387:173-176). However, the two techniques were never systematically compared across a large group of modern humans of diverse body form. This study incorporates skeletal measures taken from 1,173 Holocene adult individuals, representing diverse geographic origins, body sizes, and body shapes. Femoral head breadth, bi-iliac breadth (after pelvic rearticulation), and long bone lengths were measured on each individual. Statures were estimated from long bone lengths using appropriate reference samples. Body masses were calculated using three available femoral head breadth (FH) formulae and the stature/bi-iliac breadth (STBIB) formula, and compared. All methods yielded similar results. Correlations between FH estimates and STBIB estimates are 0.74-0.81. Slight differences in results between the three FH estimates can be attributed to sampling differences in the original reference samples, and in particular, the body-size ranges included in those samples. There is no evidence for systematic differences in results due to differences in body proportions. Since the STBIB method was validated on other samples, and the FH methods produced similar estimates, this argues that either may be applied to skeletal remains with some confidence. 2004 Wiley-Liss, Inc.

Evaluations of the Method to Measure Black Carbon Particles Suspended in Rainwater and Snow Samples

NASA Astrophysics Data System (ADS)

Ohata, S.; Moteki, N.; Schwarz, J. P.; Fahey, D. W.; Kondo, Y.

2012-12-01

The mass concentrations and size distributions of black carbon (BC) particles in rainwater and snow are important parameters for improved understanding of the wet deposition of BC, is a key process in quantifying the impacts of BC on climate. In this study, we have evaluated a new method to measure these parameters. The approach consists of an ultrasonic nebulizer (USN) used in conjunction with a Single Particle Soot Photometer (SP2). The USN converts sample water into micron-size droplets at a constant rate and then extracts airborne BC particles by dehydrating the water droplets. The mass of individual BC particles is measured by the SP2, based on the laser-induced incandescence technique. The combination of the USN and SP2 enabled the measurement of BC particles using only small amount of sample water, typically 10 ml (Ohata et al., 2011). However, the loss of BC during the extraction process depends on their size. We determined the size-dependent extraction efficiency using polystyrene latex spheres (PSLs) with twelve different diameters between 100-1050 nm. The PSL concentrations in water were determined by the light extinction of at 532nm. The extraction efficiency of the USN showed broad maximum in the diameter range of 200-500nm, and decreased substantially at larger sizes. The extraction efficiency determined using the PSL standards agreed to within ±40% with that determined using laboratory-generated BC concentration standards. We applied this method to the analysis of rainwater collected in Tokyo and Okinawa over the East China Sea. Measured BC size distributions in all rainwater samples showed negligible contribution of the BC particles larger than 600nm to the total BC amounts. However, for BC particles in surface snow collected in Greenland and Antarctica, size distributions were sometimes shifted to much larger size ranges.

Adequacy of laser diffraction for soil particle size analysis

PubMed Central

Fisher, Peter; Aumann, Colin; Chia, Kohleth; O'Halloran, Nick; Chandra, Subhash

2017-01-01

Sedimentation has been a standard methodology for particle size analysis since the early 1900s. In recent years laser diffraction is beginning to replace sedimentation as the prefered technique in some industries, such as marine sediment analysis. However, for the particle size analysis of soils, which have a diverse range of both particle size and shape, laser diffraction still requires evaluation of its reliability. In this study, the sedimentation based sieve plummet balance method and the laser diffraction method were used to measure the particle size distribution of 22 soil samples representing four contrasting Australian Soil Orders. Initially, a precise wet riffling methodology was developed capable of obtaining representative samples within the recommended obscuration range for laser diffraction. It was found that repeatable results were obtained even if measurements were made at the extreme ends of the manufacturer’s recommended obscuration range. Results from statistical analysis suggested that the use of sample pretreatment to remove soil organic carbon (and possible traces of calcium-carbonate content) made minor differences to the laser diffraction particle size distributions compared to no pretreatment. These differences were found to be marginally statistically significant in the Podosol topsoil and Vertosol subsoil. There are well known reasons why sedimentation methods may be considered to ‘overestimate’ plate-like clay particles, while laser diffraction will ‘underestimate’ the proportion of clay particles. In this study we used Lin’s concordance correlation coefficient to determine the equivalence of laser diffraction and sieve plummet balance results. The results suggested that the laser diffraction equivalent thresholds corresponding to the sieve plummet balance cumulative particle sizes of < 2 μm, < 20 μm, and < 200 μm, were < 9 μm, < 26 μm, < 275 μm respectively. The many advantages of laser diffraction for soil particle size analysis, and the empirical results of this study, suggest that deployment of laser diffraction as a standard test procedure can provide reliable results, provided consistent sample preparation is used. PMID:28472043

Reference interval computation: which method (not) to choose?

PubMed

Pavlov, Igor Y; Wilson, Andrew R; Delgado, Julio C

2012-07-11

When different methods are applied to reference interval (RI) calculation the results can sometimes be substantially different, especially for small reference groups. If there are no reliable RI data available, there is no way to confirm which method generates results closest to the true RI. We randomly drawn samples obtained from a public database for 33 markers. For each sample, RIs were calculated by bootstrapping, parametric, and Box-Cox transformed parametric methods. Results were compared to the values of the population RI. For approximately half of the 33 markers, results of all 3 methods were within 3% of the true reference value. For other markers, parametric results were either unavailable or deviated considerably from the true values. The transformed parametric method was more accurate than bootstrapping for sample size of 60, very close to bootstrapping for sample size 120, but in some cases unavailable. We recommend against using parametric calculations to determine RIs. The transformed parametric method utilizing Box-Cox transformation would be preferable way of RI calculation, if it satisfies normality test. If not, the bootstrapping is always available, and is almost as accurate and precise as the transformed parametric method. Copyright © 2012 Elsevier B.V. All rights reserved.

Joint inversion of NMR and SIP data to estimate pore size distribution of geomaterials

NASA Astrophysics Data System (ADS)

Niu, Qifei; Zhang, Chi

2018-03-01

There are growing interests in using geophysical tools to characterize the microstructure of geomaterials because of the non-invasive nature and the applicability in field. In these applications, multiple types of geophysical data sets are usually processed separately, which may be inadequate to constrain the key feature of target variables. Therefore, simultaneous processing of multiple data sets could potentially improve the resolution. In this study, we propose a method to estimate pore size distribution by joint inversion of nuclear magnetic resonance (NMR) T2 relaxation and spectral induced polarization (SIP) spectra. The petrophysical relation between NMR T2 relaxation time and SIP relaxation time is incorporated in a nonlinear least squares problem formulation, which is solved using Gauss-Newton method. The joint inversion scheme is applied to a synthetic sample and a Berea sandstone sample. The jointly estimated pore size distributions are very close to the true model and results from other experimental method. Even when the knowledge of the petrophysical models of the sample is incomplete, the joint inversion can still capture the main features of the pore size distribution of the samples, including the general shape and relative peak positions of the distribution curves. It is also found from the numerical example that the surface relaxivity of the sample could be extracted with the joint inversion of NMR and SIP data if the diffusion coefficient of the ions in the electrical double layer is known. Comparing to individual inversions, the joint inversion could improve the resolution of the estimated pore size distribution because of the addition of extra data sets. The proposed approach might constitute a first step towards a comprehensive joint inversion that can extract the full pore geometry information of a geomaterial from NMR and SIP data.

Densitometry By Acoustic Levitation

NASA Technical Reports Server (NTRS)

Trinh, Eugene H.

1989-01-01

"Static" and "dynamic" methods developed for measuring mass density of acoustically levitated solid particle or liquid drop. "Static" method, unknown density of sample found by comparison with another sample of known density. "Dynamic" method practiced with or without gravitational field. Advantages over conventional density-measuring techniques: sample does not have to make contact with container or other solid surface, size and shape of samples do not affect measurement significantly, sound field does not have to be know in detail, and sample can be smaller than microliter. Detailed knowledge of acoustic field not necessary.

A cautionary note on Bayesian estimation of population size by removal sampling with diffuse priors.

PubMed

Bord, Séverine; Bioche, Christèle; Druilhet, Pierre

2018-05-01

We consider the problem of estimating a population size by removal sampling when the sampling rate is unknown. Bayesian methods are now widespread and allow to include prior knowledge in the analysis. However, we show that Bayes estimates based on default improper priors lead to improper posteriors or infinite estimates. Similarly, weakly informative priors give unstable estimators that are sensitive to the choice of hyperparameters. By examining the likelihood, we show that population size estimates can be stabilized by penalizing small values of the sampling rate or large value of the population size. Based on theoretical results and simulation studies, we propose some recommendations on the choice of the prior. Then, we applied our results to real datasets. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Simulation of Particle Size Effect on Dynamic Properties and Fracture of PTFE-W-Al Composites

NASA Astrophysics Data System (ADS)

Herbold, E. B.; Cai, J.; Benson, D. J.; Nesterenko, V. F.

2007-12-01

Recent investigations of the dynamic compressive strength of cold isostatically pressed composites of polytetrafluoroethylene (PTFE), tungsten (W) and aluminum (Al) powders show significant differences depending on the size of metallic particles. The addition of W increases the density and changes the overall strength of the sample depending on the size of W particles. To investigate relatively large deformations, multi-material Eulerian and arbitrary Lagrangian-Eulerian methods, which have the ability to efficiently handle the formation of free surfaces, were used. The calculations indicate that the increased sample strength with fine metallic particles is due to the dynamic formation of force chains. This phenomenon occurs for samples with a higher porosity of the PTFE matrix compared to samples with larger particle size of W and a higher density PTFE matrix.

Performance of a Line Loss Correction Method for Gas Turbine Emission Measurements

NASA Astrophysics Data System (ADS)

Hagen, D. E.; Whitefield, P. D.; Lobo, P.

2015-12-01

International concern for the environmental impact of jet engine exhaust emissions in the atmosphere has led to increased attention on gas turbine engine emission testing. The Society of Automotive Engineers Aircraft Exhaust Emissions Measurement Committee (E-31) has published an Aerospace Information Report (AIR) 6241 detailing the sampling system for the measurement of non-volatile particulate matter from aircraft engines, and is developing an Aerospace Recommended Practice (ARP) for methodology and system specification. The Missouri University of Science and Technology (MST) Center for Excellence for Aerospace Particulate Emissions Reduction Research has led numerous jet engine exhaust sampling campaigns to characterize emissions at different locations in the expanding exhaust plume. Particle loss, due to various mechanisms, occurs in the sampling train that transports the exhaust sample from the engine exit plane to the measurement instruments. To account for the losses, both the size dependent penetration functions and the size distribution of the emitted particles need to be known. However in the proposed ARP, particle number and mass are measured, but size is not. Here we present a methodology to generate number and mass correction factors for line loss, without using direct size measurement. A lognormal size distribution is used to represent the exhaust aerosol at the engine exit plane and is defined by the measured number and mass at the downstream end of the sample train. The performance of this line loss correction is compared to corrections based on direct size measurements using data taken by MST during numerous engine test campaigns. The experimental uncertainty in these correction factors is estimated. Average differences between the line loss correction method and size based corrections are found to be on the order of 10% for number and 2.5% for mass.

Evaluation of alternative model selection criteria in the analysis of unimodal response curves using CART

USGS Publications Warehouse

Ribic, C.A.; Miller, T.W.

1998-01-01

We investigated CART performance with a unimodal response curve for one continuous response and four continuous explanatory variables, where two variables were important (ie directly related to the response) and the other two were not. We explored performance under three relationship strengths and two explanatory variable conditions: equal importance and one variable four times as important as the other. We compared CART variable selection performance using three tree-selection rules ('minimum risk', 'minimum risk complexity', 'one standard error') to stepwise polynomial ordinary least squares (OLS) under four sample size conditions. The one-standard-error and minimum-risk-complexity methods performed about as well as stepwise OLS with large sample sizes when the relationship was strong. With weaker relationships, equally important explanatory variables and larger sample sizes, the one-standard-error and minimum-risk-complexity rules performed better than stepwise OLS. With weaker relationships and explanatory variables of unequal importance, tree-structured methods did not perform as well as stepwise OLS. Comparing performance within tree-structured methods, with a strong relationship and equally important explanatory variables, the one-standard-error-rule was more likely to choose the correct model than were the other tree-selection rules 1) with weaker relationships and equally important explanatory variables; and 2) under all relationship strengths when explanatory variables were of unequal importance and sample sizes were lower.

Investigating effects of sample pretreatment on protein stability using size-exclusion chromatography and high-resolution continuum source atomic absorption spectrometry.

PubMed

Rakow, Tobias; El Deeb, Sami; Hahne, Thomas; El-Hady, Deia Abd; AlBishri, Hassan M; Wätzig, Hermann

2014-09-01

In this study, size-exclusion chromatography and high-resolution atomic absorption spectrometry methods have been developed and evaluated to test the stability of proteins during sample pretreatment. This especially includes different storage conditions but also adsorption before or even during the chromatographic process. For the development of the size exclusion method, a Biosep S3000 5 μm column was used for investigating a series of representative model proteins, namely bovine serum albumin, ovalbumin, monoclonal immunoglobulin G antibody, and myoglobin. Ambient temperature storage was found to be harmful to all model proteins, whereas short-term storage up to 14 days could be done in an ordinary refrigerator. Freezing the protein solutions was always complicated and had to be evaluated for each protein in the corresponding solvent. To keep the proteins in their native state a gentle freezing temperature should be chosen, hence liquid nitrogen should be avoided. Furthermore, a high-resolution continuum source atomic absorption spectrometry method was developed to observe the adsorption of proteins on container material and chromatographic columns. Adsorption to any container led to a sample loss and lowered the recovery rates. During the pretreatment and high-performance size-exclusion chromatography, adsorption caused sample losses of up to 33%. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Analysis of Crystallographic Structure of a Japanese Sword by the Pulsed Neutron Transmission Method

NASA Astrophysics Data System (ADS)

Kino, K.; Ayukawa, N.; Kiyanagi, Y.; Uchida, T.; Uno, S.; Grazzi, F.; Scherillo, A.

We measured two-dimensional transmission spectra of pulsed neutron beams for a Japanese sword sample. Atom density, crystalline size, and preferred orientation of crystals were obtained using the RITS code. The position dependence of the atomic density is consistent with the shape of the sample. The crystalline size is very small and shows position dependence, which is understood by the unique structure of Japanese swords. The preferred orientation has strong position dependence. Our study shows the usefulness of the pulsed neutron transmission method for cultural metal artifacts.

Quasi‐steady centrifuge method for unsaturated hydraulic properties

USGS Publications Warehouse

Caputo, Maria C.; Nimmo, John R.

2005-01-01

We have developed the quasi‐steady centrifuge (QSC) method as a variation of the steady state centrifuge method that can be implemented simply and inexpensively with greater versatility in terms of sample size and other features. It achieves these advantages by somewhat relaxing the criterion for steadiness of flow through the sample. This compromise entails an increase in measurement uncertainty but to a degree that is tolerable in most applications. We have tested this new approach with an easily constructed apparatus to establish a quasi‐steady flow of water in unsaturated porous rock samples spinning in a centrifuge, obtaining measurements of unsaturated hydraulic conductivity and water retention that agree with results of other methods. The QSC method is adaptable to essentially any centrifuge suitable for hydrogeologic applications, over a wide range of sizes and operating speeds. The simplified apparatus and greater adaptability of this method expands the potential for exploring situations that are common in nature but have been the subject of few laboratory investigations.

Interlinking backscatter, grain size and benthic community structure

NASA Astrophysics Data System (ADS)

McGonigle, Chris; Collier, Jenny S.

2014-06-01

The relationship between acoustic backscatter, sediment grain size and benthic community structure is examined using three different quantitative methods, covering image- and angular response-based approaches. Multibeam time-series backscatter (300 kHz) data acquired in 2008 off the coast of East Anglia (UK) are compared with grain size properties, macrofaunal abundance and biomass from 130 Hamon and 16 Clamshell grab samples. Three predictive methods are used: 1) image-based (mean backscatter intensity); 2) angular response-based (predicted mean grain size), and 3) image-based (1st principal component and classification) from Quester Tangent Corporation Multiview software. Relationships between grain size and backscatter are explored using linear regression. Differences in grain size and benthic community structure between acoustically defined groups are examined using ANOVA and PERMANOVA+. Results for the Hamon grab stations indicate significant correlations between measured mean grain size and mean backscatter intensity, angular response predicted mean grain size, and 1st principal component of QTC analysis (all p < 0.001). Results for the Clamshell grab for two of the methods have stronger positive correlations; mean backscatter intensity (r2 = 0.619; p < 0.001) and angular response predicted mean grain size (r2 = 0.692; p < 0.001). ANOVA reveals significant differences in mean grain size (Hamon) within acoustic groups for all methods: mean backscatter (p < 0.001), angular response predicted grain size (p < 0.001), and QTC class (p = 0.009). Mean grain size (Clamshell) shows a significant difference between groups for mean backscatter (p = 0.001); other methods were not significant. PERMANOVA for the Hamon abundance shows benthic community structure was significantly different between acoustic groups for all methods (p ≤ 0.001). Overall these results show considerable promise in that more than 60% of the variance in the mean grain size of the Clamshell grab samples can be explained by mean backscatter or acoustically-predicted grain size. These results show that there is significant predictive capacity for sediment characteristics from multibeam backscatter and that these acoustic classifications can have ecological validity.

Change-in-ratio methods for estimating population size

USGS Publications Warehouse

Udevitz, Mark S.; Pollock, Kenneth H.; McCullough, Dale R.; Barrett, Reginald H.

2002-01-01

Change-in-ratio (CIR) methods can provide an effective, low cost approach for estimating the size of wildlife populations. They rely on being able to observe changes in proportions of population subclasses that result from the removal of a known number of individuals from the population. These methods were first introduced in the 1940’s to estimate the size of populations with 2 subclasses under the assumption of equal subclass encounter probabilities. Over the next 40 years, closed population CIR models were developed to consider additional subclasses and use additional sampling periods. Models with assumptions about how encounter probabilities vary over time, rather than between subclasses, also received some attention. Recently, all of these CIR models have been shown to be special cases of a more general model. Under the general model, information from additional samples can be used to test assumptions about the encounter probabilities and to provide estimates of subclass sizes under relaxations of these assumptions. These developments have greatly extended the applicability of the methods. CIR methods are attractive because they do not require the marking of individuals, and subclass proportions often can be estimated with relatively simple sampling procedures. However, CIR methods require a carefully monitored removal of individuals from the population, and the estimates will be of poor quality unless the removals induce substantial changes in subclass proportions. In this paper, we review the state of the art for closed population estimation with CIR methods. Our emphasis is on the assumptions of CIR methods and on identifying situations where these methods are likely to be effective. We also identify some important areas for future CIR research.

Chance-corrected classification for use in discriminant analysis: Ecological applications

USGS Publications Warehouse

Titus, K.; Mosher, J.A.; Williams, B.K.

1984-01-01

A method for evaluating the classification table from a discriminant analysis is described. The statistic, kappa, is useful to ecologists in that it removes the effects of chance. It is useful even with equal group sample sizes although the need for a chance-corrected measure of prediction becomes greater with more dissimilar group sample sizes. Examples are presented.

Classifying plant series-level forest potential types: methods for subbasins sampled in the midscale assessment of the interior Columbia basin.

Treesearch

Paul F. Hessburg; Bradley G. Smith; Scott D. Kreiter; Craig A. Miller; Cecilia H. McNicoll; Michele. Wasienko-Holland

2000-01-01

In the interior Columbia River basin midscale ecological assessment, we mapped and characterized historical and current vegetation composition and structure of 337 randomly sampled subwatersheds (9500 ha average size) in 43 subbasins (404 000 ha average size). We compared landscape patterns, vegetation structure and composition, and landscape vulnerability to wildfires...

A new method for estimating the demographic history from DNA sequences: an importance sampling approach

PubMed Central

Ait Kaci Azzou, Sadoune; Larribe, Fabrice; Froda, Sorana

2015-01-01

The effective population size over time (demographic history) can be retraced from a sample of contemporary DNA sequences. In this paper, we propose a novel methodology based on importance sampling (IS) for exploring such demographic histories. Our starting point is the generalized skyline plot with the main difference being that our procedure, skywis plot, uses a large number of genealogies. The information provided by these genealogies is combined according to the IS weights. Thus, we compute a weighted average of the effective population sizes on specific time intervals (epochs), where the genealogies that agree more with the data are given more weight. We illustrate by a simulation study that the skywis plot correctly reconstructs the recent demographic history under the scenarios most commonly considered in the literature. In particular, our method can capture a change point in the effective population size, and its overall performance is comparable with the one of the bayesian skyline plot. We also introduce the case of serially sampled sequences and illustrate that it is possible to improve the performance of the skywis plot in the case of an exponential expansion of the effective population size. PMID:26300910

Sample size and power estimation for studies with health related quality of life outcomes: a comparison of four methods using the SF-36.

PubMed

Walters, Stephen J

2004-05-25

We describe and compare four different methods for estimating sample size and power, when the primary outcome of the study is a Health Related Quality of Life (HRQoL) measure. These methods are: 1. assuming a Normal distribution and comparing two means; 2. using a non-parametric method; 3. Whitehead's method based on the proportional odds model; 4. the bootstrap. We illustrate the various methods, using data from the SF-36. For simplicity this paper deals with studies designed to compare the effectiveness (or superiority) of a new treatment compared to a standard treatment at a single point in time. The results show that if the HRQoL outcome has a limited number of discrete values (< 7) and/or the expected proportion of cases at the boundaries is high (scoring 0 or 100), then we would recommend using Whitehead's method (Method 3). Alternatively, if the HRQoL outcome has a large number of distinct values and the proportion at the boundaries is low, then we would recommend using Method 1. If a pilot or historical dataset is readily available (to estimate the shape of the distribution) then bootstrap simulation (Method 4) based on this data will provide a more accurate and reliable sample size estimate than conventional methods (Methods 1, 2, or 3). In the absence of a reliable pilot set, bootstrapping is not appropriate and conventional methods of sample size estimation or simulation will need to be used. Fortunately, with the increasing use of HRQoL outcomes in research, historical datasets are becoming more readily available. Strictly speaking, our results and conclusions only apply to the SF-36 outcome measure. Further empirical work is required to see whether these results hold true for other HRQoL outcomes. However, the SF-36 has many features in common with other HRQoL outcomes: multi-dimensional, ordinal or discrete response categories with upper and lower bounds, and skewed distributions, so therefore, we believe these results and conclusions using the SF-36 will be appropriate for other HRQoL measures.

Laser Diffraction Techniques Replace Sieving for Lunar Soil Particle Size Distribution Data

NASA Technical Reports Server (NTRS)

Cooper, Bonnie L.; Gonzalez, C. P.; McKay, D. S.; Fruland, R. L.

2012-01-01

Sieving was used extensively until 1999 to determine the particle size distribution of lunar samples. This method is time-consuming, and requires more than a gram of material in order to obtain a result in which one may have confidence. This is demonstrated by the difference in geometric mean and median for samples measured by [1], in which a 14-gram sample produced a geometric mean of approx.52 micrometers, whereas two other samples of 1.5 grams resulted in gave means of approx.63 and approx.69 micrometers. Sample allocations for sieving are typically much smaller than a gram, and many of the sample allocations received by our lab are 0.5 to 0.25 grams in mass. Basu [2] has described how the finest fraction of the soil is easily lost in the sieving process, and this effect is compounded when sample sizes are small.

Sediment laboratory quality-assurance project: studies of methods and materials

USGS Publications Warehouse

Gordon, J.D.; Newland, C.A.; Gray, J.R.

2001-01-01

In August 1996 the U.S. Geological Survey initiated the Sediment Laboratory Quality-Assurance project. The Sediment Laboratory Quality Assurance project is part of the National Sediment Laboratory Quality-Assurance program. This paper addresses the fmdings of the sand/fme separation analysis completed for the single-blind reference sediment-sample project and differences in reported results between two different analytical procedures. From the results it is evident that an incomplete separation of fme- and sand-size material commonly occurs resulting in the classification of some of the fme-size material as sand-size material. Electron microscopy analysis supported the hypothesis that the negative bias for fme-size material and the positive bias for sand-size material is largely due to aggregation of some of the fine-size material into sand-size particles and adherence of fine-size material to the sand-size grains. Electron microscopy analysis showed that preserved river water, which was low in dissolved solids, specific conductance, and neutral pH, showed less aggregation and adhesion than preserved river water that was higher in dissolved solids and specific conductance with a basic pH. Bacteria were also found growing in the matrix, which may enhance fme-size material aggregation through their adhesive properties. Differences between sediment-analysis methods were also investigated as pan of this study. Suspended-sediment concentration results obtained from one participating laboratory that used a total-suspended solids (TSS) method had greater variability and larger negative biases than results obtained when this laboratory used a suspended-sediment concentration method. When TSS methods were used to analyze the reference samples, the median suspended sediment concentration percent difference was -18.04 percent. When the laboratory used a suspended-sediment concentration method, the median suspended-sediment concentration percent difference was -2.74 percent. The percent difference was calculated as follows: Percent difference = (( reported mass - known mass)/known mass ) X 100.

An internal pilot design for prospective cancer screening trials with unknown disease prevalence.

PubMed

Brinton, John T; Ringham, Brandy M; Glueck, Deborah H

2015-10-13

For studies that compare the diagnostic accuracy of two screening tests, the sample size depends on the prevalence of disease in the study population, and on the variance of the outcome. Both parameters may be unknown during the design stage, which makes finding an accurate sample size difficult. To solve this problem, we propose adapting an internal pilot design. In this adapted design, researchers will accrue some percentage of the planned sample size, then estimate both the disease prevalence and the variances of the screening tests. The updated estimates of the disease prevalence and variance are used to conduct a more accurate power and sample size calculation. We demonstrate that in large samples, the adapted internal pilot design produces no Type I inflation. For small samples (N less than 50), we introduce a novel adjustment of the critical value to control the Type I error rate. We apply the method to two proposed prospective cancer screening studies: 1) a small oral cancer screening study in individuals with Fanconi anemia and 2) a large oral cancer screening trial. Conducting an internal pilot study without adjusting the critical value can cause Type I error rate inflation in small samples, but not in large samples. An internal pilot approach usually achieves goal power and, for most studies with sample size greater than 50, requires no Type I error correction. Further, we have provided a flexible and accurate approach to bound Type I error below a goal level for studies with small sample size.

Sequential sampling: a novel method in farm animal welfare assessment.

PubMed

Heath, C A E; Main, D C J; Mullan, S; Haskell, M J; Browne, W J

2016-02-01

Lameness in dairy cows is an important welfare issue. As part of a welfare assessment, herd level lameness prevalence can be estimated from scoring a sample of animals, where higher levels of accuracy are associated with larger sample sizes. As the financial cost is related to the number of cows sampled, smaller samples are preferred. Sequential sampling schemes have been used for informing decision making in clinical trials. Sequential sampling involves taking samples in stages, where sampling can stop early depending on the estimated lameness prevalence. When welfare assessment is used for a pass/fail decision, a similar approach could be applied to reduce the overall sample size. The sampling schemes proposed here apply the principles of sequential sampling within a diagnostic testing framework. This study develops three sequential sampling schemes of increasing complexity to classify 80 fully assessed UK dairy farms, each with known lameness prevalence. Using the Welfare Quality herd-size-based sampling scheme, the first 'basic' scheme involves two sampling events. At the first sampling event half the Welfare Quality sample size is drawn, and then depending on the outcome, sampling either stops or is continued and the same number of animals is sampled again. In the second 'cautious' scheme, an adaptation is made to ensure that correctly classifying a farm as 'bad' is done with greater certainty. The third scheme is the only scheme to go beyond lameness as a binary measure and investigates the potential for increasing accuracy by incorporating the number of severely lame cows into the decision. The three schemes are evaluated with respect to accuracy and average sample size by running 100 000 simulations for each scheme, and a comparison is made with the fixed size Welfare Quality herd-size-based sampling scheme. All three schemes performed almost as well as the fixed size scheme but with much smaller average sample sizes. For the third scheme, an overall association between lameness prevalence and the proportion of lame cows that were severely lame on a farm was found. However, as this association was found to not be consistent across all farms, the sampling scheme did not prove to be as useful as expected. The preferred scheme was therefore the 'cautious' scheme for which a sampling protocol has also been developed.

Gear and seasonal bias associated with abundance and size structure estimates for lentic freshwater fishes

USGS Publications Warehouse

Fischer, Jesse R.; Quist, Michael C.

2014-01-01

All freshwater fish sampling methods are biased toward particular species, sizes, and sexes and are further influenced by season, habitat, and fish behavior changes over time. However, little is known about gear-specific biases for many common fish species because few multiple-gear comparison studies exist that have incorporated seasonal dynamics. We sampled six lakes and impoundments representing a diversity of trophic and physical conditions in Iowa, USA, using multiple gear types (i.e., standard modified fyke net, mini-modified fyke net, sinking experimental gill net, bag seine, benthic trawl, boat-mounted electrofisher used diurnally and nocturnally) to determine the influence of sampling methodology and season on fisheries assessments. Specifically, we describe the influence of season on catch per unit effort, proportional size distribution, and the number of samples required to obtain 125 stock-length individuals for 12 species of recreational and ecological importance. Mean catch per unit effort generally peaked in the spring and fall as a result of increased sampling effectiveness in shallow areas and seasonal changes in habitat use (e.g., movement offshore during summer). Mean proportional size distribution decreased from spring to fall for white bass Morone chrysops, largemouth bass Micropterus salmoides, bluegill Lepomis macrochirus, and black crappie Pomoxis nigromaculatus, suggesting selectivity for large and presumably sexually mature individuals in the spring and summer. Overall, the mean number of samples required to sample 125 stock-length individuals was minimized in the fall with sinking experimental gill nets, a boat-mounted electrofisher used at night, and standard modified nets for 11 of the 12 species evaluated. Our results provide fisheries scientists with relative comparisons between several recommended standard sampling methods and illustrate the effects of seasonal variation on estimates of population indices that will be critical to the future development of standardized sampling methods for freshwater fish in lentic ecosystems.

Analysis of spatial distribution of land cover maps accuracy

NASA Astrophysics Data System (ADS)

Khatami, R.; Mountrakis, G.; Stehman, S. V.

2017-12-01

Land cover maps have become one of the most important products of remote sensing science. However, classification errors will exist in any classified map and affect the reliability of subsequent map usage. Moreover, classification accuracy often varies over different regions of a classified map. These variations of accuracy will affect the reliability of subsequent analyses of different regions based on the classified maps. The traditional approach of map accuracy assessment based on an error matrix does not capture the spatial variation in classification accuracy. Here, per-pixel accuracy prediction methods are proposed based on interpolating accuracy values from a test sample to produce wall-to-wall accuracy maps. Different accuracy prediction methods were developed based on four factors: predictive domain (spatial versus spectral), interpolation function (constant, linear, Gaussian, and logistic), incorporation of class information (interpolating each class separately versus grouping them together), and sample size. Incorporation of spectral domain as explanatory feature spaces of classification accuracy interpolation was done for the first time in this research. Performance of the prediction methods was evaluated using 26 test blocks, with 10 km × 10 km dimensions, dispersed throughout the United States. The performance of the predictions was evaluated using the area under the curve (AUC) of the receiver operating characteristic. Relative to existing accuracy prediction methods, our proposed methods resulted in improvements of AUC of 0.15 or greater. Evaluation of the four factors comprising the accuracy prediction methods demonstrated that: i) interpolations should be done separately for each class instead of grouping all classes together; ii) if an all-classes approach is used, the spectral domain will result in substantially greater AUC than the spatial domain; iii) for the smaller sample size and per-class predictions, the spectral and spatial domain yielded similar AUC; iv) for the larger sample size (i.e., very dense spatial sample) and per-class predictions, the spatial domain yielded larger AUC; v) increasing the sample size improved accuracy predictions with a greater benefit accruing to the spatial domain; and vi) the function used for interpolation had the smallest effect on AUC.

Sample sizes needed for specified margins of relative error in the estimates of the repeatability and reproducibility standard deviations.

PubMed

McClure, Foster D; Lee, Jung K

2005-01-01

Sample size formulas are developed to estimate the repeatability and reproducibility standard deviations (Sr and S(R)) such that the actual error in (Sr and S(R)) relative to their respective true values, sigmar and sigmaR, are at predefined levels. The statistical consequences associated with AOAC INTERNATIONAL required sample size to validate an analytical method are discussed. In addition, formulas to estimate the uncertainties of (Sr and S(R)) were derived and are provided as supporting documentation. Formula for the Number of Replicates Required for a Specified Margin of Relative Error in the Estimate of the Repeatability Standard Deviation.

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

PubMed

Sim, Julius; Lewis, Martyn

2012-03-01

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

The efficacy of respondent-driven sampling for the health assessment of minority populations.

PubMed

Badowski, Grazyna; Somera, Lilnabeth P; Simsiman, Brayan; Lee, Hye-Ryeon; Cassel, Kevin; Yamanaka, Alisha; Ren, JunHao

2017-10-01

Respondent driven sampling (RDS) is a relatively new network sampling technique typically employed for hard-to-reach populations. Like snowball sampling, initial respondents or "seeds" recruit additional respondents from their network of friends. Under certain assumptions, the method promises to produce a sample independent from the biases that may have been introduced by the non-random choice of "seeds." We conducted a survey on health communication in Guam's general population using the RDS method, the first survey that has utilized this methodology in Guam. It was conducted in hopes of identifying a cost-efficient non-probability sampling strategy that could generate reasonable population estimates for both minority and general populations. RDS data was collected in Guam in 2013 (n=511) and population estimates were compared with 2012 BRFSS data (n=2031) and the 2010 census data. The estimates were calculated using the unweighted RDS sample and the weighted sample using RDS inference methods and compared with known population characteristics. The sample size was reached in 23days, providing evidence that the RDS method is a viable, cost-effective data collection method, which can provide reasonable population estimates. However, the results also suggest that the RDS inference methods used to reduce bias, based on self-reported estimates of network sizes, may not always work. Caution is needed when interpreting RDS study findings. For a more diverse sample, data collection should not be conducted in just one location. Fewer questions about network estimates should be asked, and more careful consideration should be given to the kind of incentives offered to participants. Copyright © 2017. Published by Elsevier Ltd.

Brief communication: the relation between standard error of the estimate and sample size of histomorphometric aging methods.

PubMed

Hennig, Cheryl; Cooper, David

2011-08-01

Histomorphometric aging methods report varying degrees of precision, measured through Standard Error of the Estimate (SEE). These techniques have been developed from variable samples sizes (n) and the impact of n on reported aging precision has not been rigorously examined in the anthropological literature. This brief communication explores the relation between n and SEE through a review of the literature (abstracts, articles, book chapters, theses, and dissertations), predictions based upon sampling theory and a simulation. Published SEE values for age prediction, derived from 40 studies, range from 1.51 to 16.48 years (mean 8.63; sd: 3.81 years). In general, these values are widely distributed for smaller samples and the distribution narrows as n increases--a pattern expected from sampling theory. For the two studies that have samples in excess of 200 individuals, the SEE values are very similar (10.08 and 11.10 years) with a mean of 10.59 years. Assuming this mean value is a 'true' characterization of the error at the population level, the 95% confidence intervals for SEE values from samples of 10, 50, and 150 individuals are on the order of ± 4.2, 1.7, and 1.0 years, respectively. While numerous sources of variation potentially affect the precision of different methods, the impact of sample size cannot be overlooked. The uncertainty associated with SEE values derived from smaller samples complicates the comparison of approaches based upon different methodology and/or skeletal elements. Meaningful comparisons require larger samples than have frequently been used and should ideally be based upon standardized samples. Copyright © 2011 Wiley-Liss, Inc.

Methods for specifying the target difference in a randomised controlled trial: the Difference ELicitation in TriAls (DELTA) systematic review.

PubMed

Hislop, Jenni; Adewuyi, Temitope E; Vale, Luke D; Harrild, Kirsten; Fraser, Cynthia; Gurung, Tara; Altman, Douglas G; Briggs, Andrew H; Fayers, Peter; Ramsay, Craig R; Norrie, John D; Harvey, Ian M; Buckley, Brian; Cook, Jonathan A

2014-05-01

Randomised controlled trials (RCTs) are widely accepted as the preferred study design for evaluating healthcare interventions. When the sample size is determined, a (target) difference is typically specified that the RCT is designed to detect. This provides reassurance that the study will be informative, i.e., should such a difference exist, it is likely to be detected with the required statistical precision. The aim of this review was to identify potential methods for specifying the target difference in an RCT sample size calculation. A comprehensive systematic review of medical and non-medical literature was carried out for methods that could be used to specify the target difference for an RCT sample size calculation. The databases searched were MEDLINE, MEDLINE In-Process, EMBASE, the Cochrane Central Register of Controlled Trials, the Cochrane Methodology Register, PsycINFO, Science Citation Index, EconLit, the Education Resources Information Center (ERIC), and Scopus (for in-press publications); the search period was from 1966 or the earliest date covered, to between November 2010 and January 2011. Additionally, textbooks addressing the methodology of clinical trials and International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) tripartite guidelines for clinical trials were also consulted. A narrative synthesis of methods was produced. Studies that described a method that could be used for specifying an important and/or realistic difference were included. The search identified 11,485 potentially relevant articles from the databases searched. Of these, 1,434 were selected for full-text assessment, and a further nine were identified from other sources. Fifteen clinical trial textbooks and the ICH tripartite guidelines were also reviewed. In total, 777 studies were included, and within them, seven methods were identified-anchor, distribution, health economic, opinion-seeking, pilot study, review of the evidence base, and standardised effect size. A variety of methods are available that researchers can use for specifying the target difference in an RCT sample size calculation. Appropriate methods may vary depending on the aim (e.g., specifying an important difference versus a realistic difference), context (e.g., research question and availability of data), and underlying framework adopted (e.g., Bayesian versus conventional statistical approach). Guidance on the use of each method is given. No single method provides a perfect solution for all contexts.

The ovenbird (Seiurus aurocapilla) as a model for testing food-value theory

USGS Publications Warehouse

Streby, Henry M.; Peterson, Sean M.; Scholtens, Brian; Monroe, Adrian; Andersen, David

2013-01-01

Food-value theory states that territorial animals space themselves such that each territory contains adequate food for rearing young. The ovenbird (Seiurus aurocapilla) is often cited as a species for which this hypothesis is supported because ovenbird territory size is inversely related to ground-invertebrate abundance within territories. However, little is known about juvenile ovenbird diet and whether food availability is accurately assessed using ground-sampling methods. We examined the relationship between ground-litter food availability and juvenile ovenbird diet in mixed northern hardwood-coniferous forests of north-central Minnesota. We sampled food availability with pitfall traps and litter samples, and concurrently sampled diet of juvenile ovenbirds from stomach samples. We found that juvenile ovenbirds were fed selectively from available food resources. In addition, we found that both ground-sampling methods greatly under-sampled forest caterpillars and snails, which together comprised 63% of juvenile ovenbird diet by mass. Combined with recent radio-telemetry findings that spot-mapping methods can poorly estimate territory size for forest songbirds, our results suggest that comparisons of spot-mapped ovenbird territories with ground-sampled invertebrate availability may not be reliable tests of food-value theory.

Size Matters: Assessing Optimum Soil Sample Size for Fungal and Bacterial Community Structure Analyses Using High Throughput Sequencing of rRNA Gene Amplicons

DOE PAGES

Penton, C. Ryan; Gupta, Vadakattu V. S. R.; Yu, Julian; ...

2016-06-02

We examined the effect of different soil sample sizes obtained from an agricultural field, under a single cropping system uniform in soil properties and aboveground crop responses, on bacterial and fungal community structure and microbial diversity indices. DNA extracted from soil sample sizes of 0.25, 1, 5, and 10 g using MoBIO kits and from 10 and 100 g sizes using a bead-beating method (SARDI) were used as templates for high-throughput sequencing of 16S and 28S rRNA gene amplicons for bacteria and fungi, respectively, on the Illumina MiSeq and Roche 454 platforms. Sample size significantly affected overall bacterial and fungalmore » community structure, replicate dispersion and the number of operational taxonomic units (OTUs) retrieved. Richness, evenness and diversity were also significantly affected. The largest diversity estimates were always associated with the 10 g MoBIO extractions with a corresponding reduction in replicate dispersion. For the fungal data, smaller MoBIO extractions identified more unclassified Eukaryota incertae sedis and unclassified glomeromycota while the SARDI method retrieved more abundant OTUs containing unclassified Pleosporales and the fungal genera Alternaria and Cercophora. Overall, these findings indicate that a 10 g soil DNA extraction is most suitable for both soil bacterial and fungal communities for retrieving optimal diversity while still capturing rarer taxa in concert with decreasing replicate variation.« less

Size Matters: Assessing Optimum Soil Sample Size for Fungal and Bacterial Community Structure Analyses Using High Throughput Sequencing of rRNA Gene Amplicons

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

Penton, C. Ryan; Gupta, Vadakattu V. S. R.; Yu, Julian

We examined the effect of different soil sample sizes obtained from an agricultural field, under a single cropping system uniform in soil properties and aboveground crop responses, on bacterial and fungal community structure and microbial diversity indices. DNA extracted from soil sample sizes of 0.25, 1, 5, and 10 g using MoBIO kits and from 10 and 100 g sizes using a bead-beating method (SARDI) were used as templates for high-throughput sequencing of 16S and 28S rRNA gene amplicons for bacteria and fungi, respectively, on the Illumina MiSeq and Roche 454 platforms. Sample size significantly affected overall bacterial and fungalmore » community structure, replicate dispersion and the number of operational taxonomic units (OTUs) retrieved. Richness, evenness and diversity were also significantly affected. The largest diversity estimates were always associated with the 10 g MoBIO extractions with a corresponding reduction in replicate dispersion. For the fungal data, smaller MoBIO extractions identified more unclassified Eukaryota incertae sedis and unclassified glomeromycota while the SARDI method retrieved more abundant OTUs containing unclassified Pleosporales and the fungal genera Alternaria and Cercophora. Overall, these findings indicate that a 10 g soil DNA extraction is most suitable for both soil bacterial and fungal communities for retrieving optimal diversity while still capturing rarer taxa in concert with decreasing replicate variation.« less

Studies on remote sensing method of particle size and water density distribution in mists and clouds using laser radar techniques

NASA Technical Reports Server (NTRS)

Shimizu, H.; Kobayasi, T.; Inaba, H.

1979-01-01

A method of remote measurement of the particle size and density distribution of water droplets was developed. In this method, the size of droplets is measured from the Mie scattering parameter which is defined as the total-to-backscattering ratio of the laser beam. The water density distribution is obtained by a combination of the Mie scattering parameter and the extinction coefficient of the laser beam. This method was examined experimentally for the mist generated by an ultrasonic mist generator and applied to clouds containing rain and snow. Compared with the conventional sampling method, the present method has advantages of remote measurement capability and improvement in accuracy.

Genetic Stock Identification Of Production Colonies Of Russian Honey Bees

USDA-ARS?s Scientific Manuscript database

The prevalence of Nosema ceranae in managed honey bee colonies has increased dramatically in the past 10 – 20 years worldwide. A variety of genetic testing methods for species identification and prevalence are now available. However sample size and preservation method of samples prior to testing hav...

Effects of growth rate, size, and light availability on tree survival across life stages: a demographic analysis accounting for missing values and small sample sizes.

PubMed

Moustakas, Aristides; Evans, Matthew R

2015-02-28

Plant survival is a key factor in forest dynamics and survival probabilities often vary across life stages. Studies specifically aimed at assessing tree survival are unusual and so data initially designed for other purposes often need to be used; such data are more likely to contain errors than data collected for this specific purpose. We investigate the survival rates of ten tree species in a dataset designed to monitor growth rates. As some individuals were not included in the census at some time points we use capture-mark-recapture methods both to allow us to account for missing individuals, and to estimate relocation probabilities. Growth rates, size, and light availability were included as covariates in the model predicting survival rates. The study demonstrates that tree mortality is best described as constant between years and size-dependent at early life stages and size independent at later life stages for most species of UK hardwood. We have demonstrated that even with a twenty-year dataset it is possible to discern variability both between individuals and between species. Our work illustrates the potential utility of the method applied here for calculating plant population dynamics parameters in time replicated datasets with small sample sizes and missing individuals without any loss of sample size, and including explanatory covariates.

Microstress, strain, band gap tuning and photocatalytic properties of thermally annealed and Cu-doped ZnO nanoparticles

NASA Astrophysics Data System (ADS)

Prasad, Neena; V. M. M, Saipavitra; Swaminathan, Hariharan; Thangaraj, Pandiyarajan; Ramalinga Viswanathan, Mangalaraja; Balasubramanian, Karthikeyan

2016-06-01

ZnO nanoparticles and Cu-doped ZnO nanoparticles were prepared by co-precipitation method. Also, a part of the pure ZnO nanoparticles were annealed at 750 °C for 3, 6, and 9 h. X-ray diffraction studies were carried out and the lattice parameters, unit cell volume, interplanar spacing, and Young's modulus were calculated for all the samples, and also the crystallite size was found using the Scherrer method. X-ray peak broadening analysis was used to estimate the crystallite sizes and the strain using the Williamson-Hall (W-H) method and the size-strain plot (SSP) method. Stress and the energy density were calculated using the W-H method assuming different models such as uniform deformation model, uniform strain deformation model, uniform deformation energy density model, and the SSP method. Optical absorption properties of the samples were understood from their UV-visible spectra. Photocatalytic activities of ZnO and 5 % Cu-doped ZnO were observed by the degradation of methylene blue dye in aqueous medium under the irradiation of 20-W compact fluorescent lamp for an hour.

Accounting for between-study variation in incremental net benefit in value of information methodology.

PubMed

Willan, Andrew R; Eckermann, Simon

2012-10-01

Previous applications of value of information methods for determining optimal sample size in randomized clinical trials have assumed no between-study variation in mean incremental net benefit. By adopting a hierarchical model, we provide a solution for determining optimal sample size with this assumption relaxed. The solution is illustrated with two examples from the literature. Expected net gain increases with increasing between-study variation, reflecting the increased uncertainty in incremental net benefit and reduced extent to which data are borrowed from previous evidence. Hence, a trial can become optimal where current evidence is sufficient assuming no between-study variation. However, despite the expected net gain increasing, the optimal sample size in the illustrated examples is relatively insensitive to the amount of between-study variation. Further percentage losses in expected net gain were small even when choosing sample sizes that reflected widely different between-study variation. Copyright © 2011 John Wiley & Sons, Ltd.

Method and apparatus for imaging a sample on a device

DOEpatents

Trulson, Mark; Stern, David; Fiekowsky, Peter; Rava, Richard; Walton, Ian; Fodor, Stephen P. A.

2001-01-01

A method and apparatus for imaging a sample are provided. An electromagnetic radiation source generates excitation radiation which is sized by excitation optics to a line. The line is directed at a sample resting on a support and excites a plurality of regions on the sample. Collection optics collect response radiation reflected from the sample I and image the reflected radiation. A detector senses the reflected radiation and is positioned to permit discrimination between radiation reflected from a certain focal plane in the sample and certain other planes within the sample.

Accuracy in parameter estimation for targeted effects in structural equation modeling: sample size planning for narrow confidence intervals.

PubMed

Lai, Keke; Kelley, Ken

2011-06-01

In addition to evaluating a structural equation model (SEM) as a whole, often the model parameters are of interest and confidence intervals for those parameters are formed. Given a model with a good overall fit, it is entirely possible for the targeted effects of interest to have very wide confidence intervals, thus giving little information about the magnitude of the population targeted effects. With the goal of obtaining sufficiently narrow confidence intervals for the model parameters of interest, sample size planning methods for SEM are developed from the accuracy in parameter estimation approach. One method plans for the sample size so that the expected confidence interval width is sufficiently narrow. An extended procedure ensures that the obtained confidence interval will be no wider than desired, with some specified degree of assurance. A Monte Carlo simulation study was conducted that verified the effectiveness of the procedures in realistic situations. The methods developed have been implemented in the MBESS package in R so that they can be easily applied by researchers. © 2011 American Psychological Association

Terahertz Spectroscopy for Proximal Soil Sensing: An Approach to Particle Size Analysis

PubMed Central

Dworak, Volker; Mahns, Benjamin; Selbeck, Jörn; Weltzien, Cornelia

2017-01-01

Spatially resolved soil parameters are some of the most important pieces of information for precision agriculture. These parameters, especially the particle size distribution (texture), are costly to measure by conventional laboratory methods, and thus, in situ assessment has become the focus of a new discipline called proximal soil sensing. Terahertz (THz) radiation is a promising method for nondestructive in situ measurements. The THz frequency range from 258 gigahertz (GHz) to 350 GHz provides a good compromise between soil penetration and the interaction of the electromagnetic waves with soil compounds. In particular, soil physical parameters influence THz measurements. This paper presents investigations of the spectral transmission signals from samples of different particle size fractions relevant for soil characterization. The sample thickness ranged from 5 to 17 mm. The transmission of THz waves was affected by the main mineral particle fractions, sand, silt and clay. The resulting signal changes systematically according to particle sizes larger than half the wavelength. It can be concluded that THz spectroscopic measurements provide information about soil texture and penetrate samples with thicknesses in the cm range. PMID:29048392

Performance of digital RGB reflectance color extraction for plaque lesion

NASA Astrophysics Data System (ADS)

Hashim, Hadzli; Taib, Mohd Nasir; Jailani, Rozita; Sulaiman, Saadiah; Baba, Roshidah

2005-01-01

Several clinical psoriasis lesion groups are been studied for digital RGB color features extraction. Previous works have used samples size that included all the outliers lying beyond the standard deviation factors from the peak histograms. This paper described the statistical performances of the RGB model with and without removing these outliers. Plaque lesion is experimented with other types of psoriasis. The statistical tests are compared with respect to three samples size; the original 90 samples, the first size reduction by removing outliers from 2 standard deviation distances (2SD) and the second size reduction by removing outliers from 1 standard deviation distance (1SD). Quantification of data images through the normal/direct and differential of the conventional reflectance method is considered. Results performances are concluded by observing the error plots with 95% confidence interval and findings of the inference T-tests applied. The statistical tests outcomes have shown that B component for conventional differential method can be used to distinctively classify plaque from the other psoriasis groups in consistent with the error plots finding with an improvement in p-value greater than 0.5.

The Petersen-Lincoln estimator and its extension to estimate the size of a shared population.

PubMed

Chao, Anne; Pan, H-Y; Chiang, Shu-Chuan

2008-12-01

The Petersen-Lincoln estimator has been used to estimate the size of a population in a single mark release experiment. However, the estimator is not valid when the capture sample and recapture sample are not independent. We provide an intuitive interpretation for "independence" between samples based on 2 x 2 categorical data formed by capture/non-capture in each of the two samples. From the interpretation, we review a general measure of "dependence" and quantify the correlation bias of the Petersen-Lincoln estimator when two types of dependences (local list dependence and heterogeneity of capture probability) exist. An important implication in the census undercount problem is that instead of using a post enumeration sample to assess the undercount of a census, one should conduct a prior enumeration sample to avoid correlation bias. We extend the Petersen-Lincoln method to the case of two populations. This new estimator of the size of the shared population is proposed and its variance is derived. We discuss a special case where the correlation bias of the proposed estimator due to dependence between samples vanishes. The proposed method is applied to a study of the relapse rate of illicit drug use in Taiwan. ((c) 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim).

Does increasing the size of bi-weekly samples of records influence results when using the Global Trigger Tool? An observational study of retrospective record reviews of two different sample sizes.

PubMed

Mevik, Kjersti; Griffin, Frances A; Hansen, Tonje E; Deilkås, Ellen T; Vonen, Barthold

2016-04-25

To investigate the impact of increasing sample of records reviewed bi-weekly with the Global Trigger Tool method to identify adverse events in hospitalised patients. Retrospective observational study. A Norwegian 524-bed general hospital trust. 1920 medical records selected from 1 January to 31 December 2010. Rate, type and severity of adverse events identified in two different samples sizes of records selected as 10 and 70 records, bi-weekly. In the large sample, 1.45 (95% CI 1.07 to 1.97) times more adverse events per 1000 patient days (39.3 adverse events/1000 patient days) were identified than in the small sample (27.2 adverse events/1000 patient days). Hospital-acquired infections were the most common category of adverse events in both the samples, and the distributions of the other categories of adverse events did not differ significantly between the samples. The distribution of severity level of adverse events did not differ between the samples. The findings suggest that while the distribution of categories and severity are not dependent on the sample size, the rate of adverse events is. Further studies are needed to conclude if the optimal sample size may need to be adjusted based on the hospital size in order to detect a more accurate rate of adverse events. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Field substitution of nonresponders can maintain sample size and structure without altering survey estimates-the experience of the Italian behavioral risk factors surveillance system (PASSI).

PubMed

Baldissera, Sandro; Ferrante, Gianluigi; Quarchioni, Elisa; Minardi, Valentina; Possenti, Valentina; Carrozzi, Giuliano; Masocco, Maria; Salmaso, Stefania

2014-04-01

Field substitution of nonrespondents can be used to maintain the planned sample size and structure in surveys but may introduce additional bias. Sample weighting is suggested as the preferable alternative; however, limited empirical evidence exists comparing the two methods. We wanted to assess the impact of substitution on surveillance results using data from Progressi delle Aziende Sanitarie per la Salute in Italia-Progress by Local Health Units towards a Healthier Italy (PASSI). PASSI is conducted by Local Health Units (LHUs) through telephone interviews of stratified random samples of residents. Nonrespondents are replaced with substitutes randomly preselected in the same LHU stratum. We compared the weighted estimates obtained in the original PASSI sample (used as a reference) and in the substitutes' sample. The differences were evaluated using a Wald test. In 2011, 50,697 units were selected: 37,252 were from the original sample and 13,445 were substitutes; 37,162 persons were interviewed. The initially planned size and demographic composition were restored. No significant differences in the estimates between the original and the substitutes' sample were found. In our experience, field substitution is an acceptable method for dealing with nonresponse, maintaining the characteristics of the original sample without affecting the results. This evidence can support appropriate decisions about planning and implementing a surveillance system. Copyright © 2014 Elsevier Inc. All rights reserved.

A Monte-Carlo method which is not based on Markov chain algorithm, used to study electrostatic screening of ion potential

NASA Astrophysics Data System (ADS)

Šantić, Branko; Gracin, Davor

2017-12-01

A new simple Monte Carlo method is introduced for the study of electrostatic screening by surrounding ions. The proposed method is not based on the generally used Markov chain method for sample generation. Each sample is pristine and there is no correlation with other samples. As the main novelty, the pairs of ions are gradually added to a sample provided that the energy of each ion is within the boundaries determined by the temperature and the size of ions. The proposed method provides reliable results, as demonstrated by the screening of ion in plasma and in water.

How large a training set is needed to develop a classifier for microarray data?

PubMed

Dobbin, Kevin K; Zhao, Yingdong; Simon, Richard M

2008-01-01

A common goal of gene expression microarray studies is the development of a classifier that can be used to divide patients into groups with different prognoses, or with different expected responses to a therapy. These types of classifiers are developed on a training set, which is the set of samples used to train a classifier. The question of how many samples are needed in the training set to produce a good classifier from high-dimensional microarray data is challenging. We present a model-based approach to determining the sample size required to adequately train a classifier. It is shown that sample size can be determined from three quantities: standardized fold change, class prevalence, and number of genes or features on the arrays. Numerous examples and important experimental design issues are discussed. The method is adapted to address ex post facto determination of whether the size of a training set used to develop a classifier was adequate. An interactive web site for performing the sample size calculations is provided. We showed that sample size calculations for classifier development from high-dimensional microarray data are feasible, discussed numerous important considerations, and presented examples.

Modeling and Simulation of A Microchannel Cooling System for Vitrification of Cells and Tissues.

PubMed

Wang, Y; Zhou, X M; Jiang, C J; Yu, Y T

The microchannel heat exchange system has several advantages and can be used to enhance heat transfer for vitrification. To evaluate the microchannel cooling method and to analyze the effects of key parameters such as channel structure, flow rate and sample size. A computational flow dynamics model is applied to study the two-phase flow in microchannels and its related heat transfer process. The fluid-solid coupling problem is solved with a whole field solution method (i.e., flow profile in channels and temperature distribution in the system being simulated simultaneously). Simulation indicates that a cooling rate >10 4 C/min is easily achievable using the microchannel method with the high flow rate for a board range of sample sizes. Channel size and material used have significant impact on cooling performance. Computational flow dynamics is useful for optimizing the design and operation of the microchannel system.

Particle size analysis of lamb meat: Effect of homogenization speed, comparison with myofibrillar fragmentation index and its relationship with shear force.

PubMed

Karumendu, L U; Ven, R van de; Kerr, M J; Lanza, M; Hopkins, D L

2009-08-01

The impact of homogenization speed on Particle Size (PS) results was examined using samples from the M.longissimus thoracis et lumborum (LL) of 40 lambs. One gram duplicate samples from meat aged for 1 and 5days were homogenized at five different speeds; 11,000, 13,000, 16,000, 19,000 and 22,000rpm. In addition to this LL samples from 30 different lamb carcases also aged for 1 and 5days were used to study the comparison between PS and myofibrillar fragmentation index (MFI) values. In this case, 1g duplicate samples (n=30) were homogenized at 16,000rpm and the other half (0.5g samples) at 11,000rpm (n=30). The homogenates were then subjected to respective combinations of treatments which included either PS analysis or the determination of MFI, both with or without three cycles of centrifugation. All 140 samples of LL included 65g blocks for subsequent shear force (SF) testing. Homogenization at 16,000rpm provided the greatest ability to detect ageing differences for particle size between samples aged for 1 and 5days. Particle size at the 25% quantile provided the best result for detecting differences due to ageing. It was observed that as ageing increased the mean PS decreased and was significantly (P<0.001) less for 5days aged samples compared to 1day aged samples, while MFI values significantly increased (P<0.001) as ageing period increased. When comparing the PS and MFI methods it became apparent that, as opposed to the MFI method, there was a greater coefficient of variation for the PS method which warranted a quality assurance system. Given this requirement and examination of the mean, standard deviation and the 25% quantile for PS data it was concluded that three cycles of centrifugation were not necessary and this also applied to the MFI method. There were significant correlations (P<0.001) within the same lamb loin sample aged for a given period between mean MFI and mean PS (-0.53), mean MFI and mean SF (-0.38) and mean PS and mean SF (0.23). It was concluded that PS analysis offers significant potential for streamlining determination of myofibrillar degradation when samples are measured after homogenization at 16,000rpm with no centrifugation.

Research on optimal DEM cell size for 3D visualization of loess terraces

NASA Astrophysics Data System (ADS)

Zhao, Weidong; Tang, Guo'an; Ji, Bin; Ma, Lei

2009-10-01

In order to represent the complex artificial terrains like loess terraces in Shanxi Province in northwest China, a new 3D visual method namely Terraces Elevation Incremental Visual Method (TEIVM) is put forth by the authors. 406 elevation points and 14 enclosed constrained lines are sampled according to the TIN-based Sampling Method (TSM) and DEM Elevation Points and Lines Classification (DEPLC). The elevation points and constrained lines are used to construct Constrained Delaunay Triangulated Irregular Networks (CD-TINs) of the loess terraces. In order to visualize the loess terraces well by use of optimal combination of cell size and Elevation Increment Value (EIV), the CD-TINs is converted to Grid-based DEM (G-DEM) by use of different combination of cell size and EIV with linear interpolating method called Bilinear Interpolation Method (BIM). Our case study shows that the new visual method can visualize the loess terraces steps very well when the combination of cell size and EIV is reasonable. The optimal combination is that the cell size is 1 m and the EIV is 6 m. Results of case study also show that the cell size should be at least smaller than half of both the terraces average width and the average vertical offset of terraces steps for representing the planar shapes of the terraces surfaces and steps well, while the EIV also should be larger than 4.6 times of the terraces average height. The TEIVM and results above is of great significance to the highly refined visualization of artificial terrains like loess terraces.

Glass frit nebulizer for atomic spectrometry

USGS Publications Warehouse

Layman, L.R.

1982-01-01

The nebuilizatlon of sample solutions Is a critical step In most flame or plasma atomic spectrometrlc methods. A novel nebulzatlon technique, based on a porous glass frit, has been Investigated. Basic operating parameters and characteristics have been studied to determine how thte new nebulizer may be applied to atomic spectrometrlc methods. The results of preliminary comparisons with pneumatic nebulizers Indicate several notable differences. The frit nebulizer produces a smaller droplet size distribution and has a higher sample transport efficiency. The mean droplet size te approximately 0.1 ??m, and up to 94% of the sample te converted to usable aerosol. The most significant limitations In the performance of the frit nebulizer are the stow sample equMbratton time and the requirement for wash cycles between samples. Loss of solute by surface adsorption and contamination of samples by leaching from the glass were both found to be limitations only In unusual cases. This nebulizer shows great promise where sample volume te limited or where measurements require long nebullzatlon times.

Fragment size distribution statistics in dynamic fragmentation of laser shock-loaded tin

NASA Astrophysics Data System (ADS)

He, Weihua; Xin, Jianting; Zhao, Yongqiang; Chu, Genbai; Xi, Tao; Shui, Min; Lu, Feng; Gu, Yuqiu

2017-06-01

This work investigates the geometric statistics method to characterize the size distribution of tin fragments produced in the laser shock-loaded dynamic fragmentation process. In the shock experiments, the ejection of the tin sample with etched V-shape groove in the free surface are collected by the soft recovery technique. Subsequently, the produced fragments are automatically detected with the fine post-shot analysis techniques including the X-ray micro-tomography and the improved watershed method. To characterize the size distributions of the fragments, a theoretical random geometric statistics model based on Poisson mixtures is derived for dynamic heterogeneous fragmentation problem, which reveals linear combinational exponential distribution. The experimental data related to fragment size distributions of the laser shock-loaded tin sample are examined with the proposed theoretical model, and its fitting performance is compared with that of other state-of-the-art fragment size distribution models. The comparison results prove that our proposed model can provide far more reasonable fitting result for the laser shock-loaded tin.

Characteristics of randomised trials on diseases in the digestive system registered in ClinicalTrials.gov: a retrospective analysis.

PubMed

Wildt, Signe; Krag, Aleksander; Gluud, Liselotte

2011-01-01

Objectives To evaluate the adequacy of reporting of protocols for randomised trials on diseases of the digestive system registered in http://ClinicalTrials.gov and the consistency between primary outcomes, secondary outcomes and sample size specified in http://ClinicalTrials.gov and published trials. Methods Randomised phase III trials on adult patients with gastrointestinal diseases registered before January 2009 in http://ClinicalTrials.gov were eligible for inclusion. From http://ClinicalTrials.gov all data elements in the database required by the International Committee of Medical Journal Editors (ICMJE) member journals were extracted. The subsequent publications for registered trials were identified. For published trials, data concerning publication date, primary and secondary endpoint, sample size, and whether the journal adhered to ICMJE principles were extracted. Differences between primary and secondary outcomes, sample size and sample size calculations data in http://ClinicalTrials.gov and in the published paper were registered. Results 105 trials were evaluated. 66 trials (63%) were published. 30% of trials were registered incorrectly after their completion date. Several data elements of the required ICMJE data list were not filled in, with missing data in 22% and 11%, respectively, of cases concerning the primary outcome measure and sample size. In 26% of the published papers, data on sample size calculations were missing and discrepancies between sample size reporting in http://ClinicalTrials.gov and published trials existed. Conclusion The quality of registration of randomised controlled trials still needs improvement.

Inferring the demographic history from DNA sequences: An importance sampling approach based on non-homogeneous processes.

PubMed

Ait Kaci Azzou, S; Larribe, F; Froda, S

2016-10-01

In Ait Kaci Azzou et al. (2015) we introduced an Importance Sampling (IS) approach for estimating the demographic history of a sample of DNA sequences, the skywis plot. More precisely, we proposed a new nonparametric estimate of a population size that changes over time. We showed on simulated data that the skywis plot can work well in typical situations where the effective population size does not undergo very steep changes. In this paper, we introduce an iterative procedure which extends the previous method and gives good estimates under such rapid variations. In the iterative calibrated skywis plot we approximate the effective population size by a piecewise constant function, whose values are re-estimated at each step. These piecewise constant functions are used to generate the waiting times of non homogeneous Poisson processes related to a coalescent process with mutation under a variable population size model. Moreover, the present IS procedure is based on a modified version of the Stephens and Donnelly (2000) proposal distribution. Finally, we apply the iterative calibrated skywis plot method to a simulated data set from a rapidly expanding exponential model, and we show that the method based on this new IS strategy correctly reconstructs the demographic history. Copyright © 2016. Published by Elsevier Inc.

Semi-automatic surface sediment sampling system - A prototype to be implemented in bivalve fishing surveys

NASA Astrophysics Data System (ADS)

Rufino, Marta M.; Baptista, Paulo; Pereira, Fábio; Gaspar, Miguel B.

2018-01-01

In the current work we propose a new method to sample surface sediment during bivalve fishing surveys. Fishing institutes all around the word carry out regular surveys with the aim of monitoring the stocks of commercial species. These surveys comprise often more than one hundred of sampling stations and cover large geographical areas. Although superficial sediment grain sizes are among the main drivers of benthic communities and provide crucial information for studies on coastal dynamics, overall there is a strong lack of this type of data, possibly, because traditional surface sediment sampling methods use grabs, that require considerable time and effort to be carried out on regular basis or on large areas. In face of these aspects, we developed an easy and un-expensive method to sample superficial sediments, during bivalve fisheries monitoring surveys, without increasing survey time or human resources. The method was successfully evaluated and validated during a typical bivalve survey carried out on the Northwest coast of Portugal, confirming that it had any interference with the survey objectives. Furthermore, the method was validated by collecting samples using a traditional Van Veen grabs (traditional method), which showed a similar grain size composition to the ones collected by the new method, on the same localities. We recommend that the procedure is implemented on regular bivalve fishing surveys, together with an image analysis system to analyse the collected samples. The new method will provide substantial quantity of data on surface sediment in coastal areas, using a non-expensive and efficient manner, with a high potential application in different fields of research.

The effect of sample size and disease prevalence on supervised machine learning of narrative data.

PubMed Central

McKnight, Lawrence K.; Wilcox, Adam; Hripcsak, George

2002-01-01

This paper examines the independent effects of outcome prevalence and training sample sizes on inductive learning performance. We trained 3 inductive learning algorithms (MC4, IB, and Naïve-Bayes) on 60 simulated datasets of parsed radiology text reports labeled with 6 disease states. Data sets were constructed to define positive outcome states at 4 prevalence rates (1, 5, 10, 25, and 50%) in training set sizes of 200 and 2,000 cases. We found that the effect of outcome prevalence is significant when outcome classes drop below 10% of cases. The effect appeared independent of sample size, induction algorithm used, or class label. Work is needed to identify methods of improving classifier performance when output classes are rare. PMID:12463878

Biostatistics Series Module 5: Determining Sample Size

PubMed Central

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Determining the appropriate sample size for a study, whatever be its type, is a fundamental aspect of biomedical research. An adequate sample ensures that the study will yield reliable information, regardless of whether the data ultimately suggests a clinically important difference between the interventions or elements being studied. The probability of Type 1 and Type 2 errors, the expected variance in the sample and the effect size are the essential determinants of sample size in interventional studies. Any method for deriving a conclusion from experimental data carries with it some risk of drawing a false conclusion. Two types of false conclusion may occur, called Type 1 and Type 2 errors, whose probabilities are denoted by the symbols σ and β. A Type 1 error occurs when one concludes that a difference exists between the groups being compared when, in reality, it does not. This is akin to a false positive result. A Type 2 error occurs when one concludes that difference does not exist when, in reality, a difference does exist, and it is equal to or larger than the effect size defined by the alternative to the null hypothesis. This may be viewed as a false negative result. When considering the risk of Type 2 error, it is more intuitive to think in terms of power of the study or (1 − β). Power denotes the probability of detecting a difference when a difference does exist between the groups being compared. Smaller α or larger power will increase sample size. Conventional acceptable values for power and α are 80% or above and 5% or below, respectively, when calculating sample size. Increasing variance in the sample tends to increase the sample size required to achieve a given power level. The effect size is the smallest clinically important difference that is sought to be detected and, rather than statistical convention, is a matter of past experience and clinical judgment. Larger samples are required if smaller differences are to be detected. Although the principles are long known, historically, sample size determination has been difficult, because of relatively complex mathematical considerations and numerous different formulas. However, of late, there has been remarkable improvement in the availability, capability, and user-friendliness of power and sample size determination software. Many can execute routines for determination of sample size and power for a wide variety of research designs and statistical tests. With the drudgery of mathematical calculation gone, researchers must now concentrate on determining appropriate sample size and achieving these targets, so that study conclusions can be accepted as meaningful. PMID:27688437

Controlled synthesis and luminescence properties of CaMoO4:Eu3+ microcrystals

NASA Astrophysics Data System (ADS)

Xie, Ying; Ma, Siming; Wang, Yu; Xu, Mai; Lu, Chengxi; Xiao, Linjiu; Deng, Shuguang

2018-03-01

Pure tetragonal-phased Ca0.9MoO4:0.1Eu3+ (CaMoO4:Eu3+) microcrystals with varying particle sizes were prepared via a co-deposition in water/oil (w/o) phase method. The particle sizes of as-prepared samples were controlled by calcination temperature and calcination time, and the crystallinity of the samples enhances with increasing particle size. The luminescence properties of CaMoO4:Eu3+ microcrystals were studied with varying particle size. The results reveal that the intensity of emission spectra of the CaMoO4:Eu3+ samples increases with increasing particle size, and they have closely correlation with each other. It is the same with the luminescence lifetime. The luminescence lifetime of the CaMoO4:Eu3+ samples decreases from 0.637 ms to 0.447 ms with increasing particle size from 0.12 μm to 1.79 μm, respectively. This study not only provides information for size-dependent luminescence properties of CaMoO4:Eu3+ but also gives a reference for potential applications in high voltage electric porcelain material.

Comparison of microstickies measurement methods. Part II, Results and discussion

Treesearch

Mahendra R. Doshi; Angeles Blanco; Carlos Negro; Concepcion Monte; Gilles M. Dorris; Carlos C. Castro; Axel Hamann; R. Daniel Haynes; Carl Houtman; Karen Scallon; Hans-Joachim Putz; Hans Johansson; R. A. Venditti; K. Copeland; H.-M. Chang

2003-01-01

In part I of the article we discussed sample preparation procedure and described various methods used for the measurement of microstickies. Some of the important features of different methods are highlighted in Table 1. Temperatures used in the measurement methods vary from room temperature in some cases, 45 °C to 65 °C in other cases. Sample size ranges from as low as...

Infrared reflectance spectra: Effects of particle size, provenance and preparation

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

Su, Yin-Fong; Myers, Tanya L.; Brauer, Carolyn S.

2014-09-22

We have recently developed methods for making more accurate infrared total and diffuse directional - hemispherical reflectance measurements using an integrating sphere. We have found that reflectance spectra of solids, especially powders, are influenced by a number of factors including the sample preparation method, the particle size and morphology, as well as the sample origin. On a quantitative basis we have investigated some of these parameters and the effects they have on reflectance spectra, particularly in the longwave infrared. In the IR the spectral features may be observed as either maxima or minima: In general, upward-going peaks in the reflectancemore » spectrum result from strong surface scattering, i.e. rays that are reflected from the surface without bulk penetration, whereas downward-going peaks are due to either absorption or volume scattering, i.e. rays that have penetrated or refracted into the sample interior and are not reflected. The light signals reflected from solids usually encompass all such effects, but with strong dependencies on particle size and preparation. This paper measures the reflectance spectra in the 1.3 – 16 micron range for various bulk materials that have a combination of strong and weak absorption bands in order to observe the effects on the spectral features: Bulk materials were ground with a mortar and pestle and sieved to separate the samples into various size fractions between 5 and 500 microns. The median particle size is demonstrated to have large effects on the reflectance spectra. For certain minerals we also observe significant spectral change depending on the geologic origin of the sample. All three such effects (particle size, preparation and provenance) result in substantial change in the reflectance spectra for solid materials; successful identification algorithms will require sufficient flexibility to account for these parameters.« less

Infrared reflectance spectra: effects of particle size, provenance and preparation

NASA Astrophysics Data System (ADS)

Su, Yin-Fong; Myers, Tanya L.; Brauer, Carolyn S.; Blake, Thomas A.; Forland, Brenda M.; Szecsody, J. E.; Johnson, Timothy J.

2014-10-01

We have recently developed methods for making more accurate infrared total and diffuse directional - hemispherical reflectance measurements using an integrating sphere. We have found that reflectance spectra of solids, especially powders, are influenced by a number of factors including the sample preparation method, the particle size and morphology, as well as the sample origin. On a quantitative basis we have investigated some of these parameters and the effects they have on reflectance spectra, particularly in the longwave infrared. In the IR the spectral features may be observed as either maxima or minima: In general, upward-going peaks in the reflectance spectrum result from strong surface scattering, i.e. rays that are reflected from the surface without bulk penetration, whereas downward-going peaks are due to either absorption or volume scattering, i.e. rays that have penetrated or refracted into the sample interior and are not reflected. The light signals reflected from solids usually encompass all such effects, but with strong dependencies on particle size and preparation. This paper measures the reflectance spectra in the 1.3 - 16 micron range for various bulk materials that have a combination of strong and weak absorption bands in order to observe the effects on the spectral features: Bulk materials were ground with a mortar and pestle and sieved to separate the samples into various size fractions between 5 and 500 microns. The median particle size is demonstrated to have large effects on the reflectance spectra. For certain minerals we also observe significant spectral change depending on the geologic origin of the sample. All three such effects (particle size, preparation and provenance) result in substantial change in the reflectance spectra for solid materials; successful identification algorithms will require sufficient flexibility to account for these parameters.

A log-linear model approach to estimation of population size using the line-transect sampling method

USGS Publications Warehouse

Anderson, D.R.; Burnham, K.P.; Crain, B.R.

1978-01-01

The technique of estimating wildlife population size and density using the belt or line-transect sampling method has been used in many past projects, such as the estimation of density of waterfowl nestling sites in marshes, and is being used currently in such areas as the assessment of Pacific porpoise stocks in regions of tuna fishing activity. A mathematical framework for line-transect methodology has only emerged in the last 5 yr. In the present article, we extend this mathematical framework to a line-transect estimator based upon a log-linear model approach.

Combining the boundary shift integral and tensor-based morphometry for brain atrophy estimation

NASA Astrophysics Data System (ADS)

Michalkiewicz, Mateusz; Pai, Akshay; Leung, Kelvin K.; Sommer, Stefan; Darkner, Sune; Sørensen, Lauge; Sporring, Jon; Nielsen, Mads

2016-03-01

Brain atrophy from structural magnetic resonance images (MRIs) is widely used as an imaging surrogate marker for Alzheimers disease. Their utility has been limited due to the large degree of variance and subsequently high sample size estimates. The only consistent and reasonably powerful atrophy estimation methods has been the boundary shift integral (BSI). In this paper, we first propose a tensor-based morphometry (TBM) method to measure voxel-wise atrophy that we combine with BSI. The combined model decreases the sample size estimates significantly when compared to BSI and TBM alone.

Sampling of illicit drugs for quantitative analysis--part II. Study of particle size and its influence on mass reduction.

PubMed

Bovens, M; Csesztregi, T; Franc, A; Nagy, J; Dujourdy, L

2014-01-01

The basic goal in sampling for the quantitative analysis of illicit drugs is to maintain the average concentration of the drug in the material from its original seized state (the primary sample) all the way through to the analytical sample, where the effect of particle size is most critical. The size of the largest particles of different authentic illicit drug materials, in their original state and after homogenisation, using manual or mechanical procedures, was measured using a microscope with a camera attachment. The comminution methods employed included pestle and mortar (manual) and various ball and knife mills (mechanical). The drugs investigated were amphetamine, heroin, cocaine and herbal cannabis. It was shown that comminution of illicit drug materials using these techniques reduces the nominal particle size from approximately 600 μm down to between 200 and 300 μm. It was demonstrated that the choice of 1 g increments for the primary samples of powdered drugs and cannabis resin, which were used in the heterogeneity part of our study (Part I) was correct for the routine quantitative analysis of illicit seized drugs. For herbal cannabis we found that the appropriate increment size was larger. Based on the results of this study we can generally state that: An analytical sample weight of between 20 and 35 mg of an illicit powdered drug, with an assumed purity of 5% or higher, would be considered appropriate and would generate an RSDsampling in the same region as the RSDanalysis for a typical quantitative method of analysis for the most common, powdered, illicit drugs. For herbal cannabis, with an assumed purity of 1% THC (tetrahydrocannabinol) or higher, an analytical sample weight of approximately 200 mg would be appropriate. In Part III we will pull together our homogeneity studies and particle size investigations and use them to devise sampling plans and sample preparations suitable for the quantitative instrumental analysis of the most common illicit drugs. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

A Simulation Approach to Assessing Sampling Strategies for Insect Pests: An Example with the Balsam Gall Midge

PubMed Central

Carleton, R. Drew; Heard, Stephen B.; Silk, Peter J.

2013-01-01

Estimation of pest density is a basic requirement for integrated pest management in agriculture and forestry, and efficiency in density estimation is a common goal. Sequential sampling techniques promise efficient sampling, but their application can involve cumbersome mathematics and/or intensive warm-up sampling when pests have complex within- or between-site distributions. We provide tools for assessing the efficiency of sequential sampling and of alternative, simpler sampling plans, using computer simulation with “pre-sampling” data. We illustrate our approach using data for balsam gall midge (Paradiplosis tumifex) attack in Christmas tree farms. Paradiplosis tumifex proved recalcitrant to sequential sampling techniques. Midge distributions could not be fit by a common negative binomial distribution across sites. Local parameterization, using warm-up samples to estimate the clumping parameter k for each site, performed poorly: k estimates were unreliable even for samples of n∼100 trees. These methods were further confounded by significant within-site spatial autocorrelation. Much simpler sampling schemes, involving random or belt-transect sampling to preset sample sizes, were effective and efficient for P. tumifex. Sampling via belt transects (through the longest dimension of a stand) was the most efficient, with sample means converging on true mean density for sample sizes of n∼25–40 trees. Pre-sampling and simulation techniques provide a simple method for assessing sampling strategies for estimating insect infestation. We suspect that many pests will resemble P. tumifex in challenging the assumptions of sequential sampling methods. Our software will allow practitioners to optimize sampling strategies before they are brought to real-world applications, while potentially avoiding the need for the cumbersome calculations required for sequential sampling methods. PMID:24376556

Power and sample-size estimation for microbiome studies using pairwise distances and PERMANOVA.

PubMed

Kelly, Brendan J; Gross, Robert; Bittinger, Kyle; Sherrill-Mix, Scott; Lewis, James D; Collman, Ronald G; Bushman, Frederic D; Li, Hongzhe

2015-08-01

The variation in community composition between microbiome samples, termed beta diversity, can be measured by pairwise distance based on either presence-absence or quantitative species abundance data. PERMANOVA, a permutation-based extension of multivariate analysis of variance to a matrix of pairwise distances, partitions within-group and between-group distances to permit assessment of the effect of an exposure or intervention (grouping factor) upon the sampled microbiome. Within-group distance and exposure/intervention effect size must be accurately modeled to estimate statistical power for a microbiome study that will be analyzed with pairwise distances and PERMANOVA. We present a framework for PERMANOVA power estimation tailored to marker-gene microbiome studies that will be analyzed by pairwise distances, which includes: (i) a novel method for distance matrix simulation that permits modeling of within-group pairwise distances according to pre-specified population parameters; (ii) a method to incorporate effects of different sizes within the simulated distance matrix; (iii) a simulation-based method for estimating PERMANOVA power from simulated distance matrices; and (iv) an R statistical software package that implements the above. Matrices of pairwise distances can be efficiently simulated to satisfy the triangle inequality and incorporate group-level effects, which are quantified by the adjusted coefficient of determination, omega-squared (ω2). From simulated distance matrices, available PERMANOVA power or necessary sample size can be estimated for a planned microbiome study. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

EXAFS analysis of cations distribution in structure of Co1-xNixFe2O4 nanoparticles obtained by hydrothermal method in aloe vera extract solution

NASA Astrophysics Data System (ADS)

Wongpratat, Unchista; Maensiri, Santi; Swatsitang, Ekaphan

2016-09-01

Effect of cations distribution upon EXAFS analysis on magnetic properties of Co1-xNixFe2O4 (x = 0, 0.25, 0.50, 0.75 and 1.0) nanoparticles prepared by the hydrothermal method in aloe vera extract solution were studied. XRD analysis confirmed a pure phase of cubic spinel ferrite of all samples. Changes in lattice parameter and particle size depended on the Ni content with partial substitution and site distributions of Co2+, Ni2+ ions of different ionic radii at both tetrahedral and octahedral sites in the crystal structure. Particle sizes of samples estimated by TEM images were found to be in the range of 10.87-62.50 nm. The VSM results at room temperature indicated the ferrimagnetic behavior of all samples. Superparamagnetic behavior was observed in NiFe2O4 sample. The coercivity (Hc) and remanance (Mr) values were related to the particle sizes of samples. The saturation magnetization (Ms) was increased by a factor of 1.4 to a value of 57.57 emu/g, whereas the coercivity (Hc) was decreased by a factor of 20 to a value of 63.15 Oe for a sample with x = 0.75. In addition to the cations distribution, the increase of aspect ratio (surface to volume ratio) due to the decrease of particle size could significantly affect the magnetic properties of the materials.

Setting health research priorities using the CHNRI method: VI. Quantitative properties of human collective opinion.

PubMed

Yoshida, Sachiyo; Rudan, Igor; Cousens, Simon

2016-06-01

Crowdsourcing has become an increasingly important tool to address many problems - from government elections in democracies, stock market prices, to modern online tools such as TripAdvisor or Internet Movie Database (IMDB). The CHNRI method (the acronym for the Child Health and Nutrition Research Initiative) for setting health research priorities has crowdsourcing as the major component, which it uses to generate, assess and prioritize between many competing health research ideas. We conducted a series of analyses using data from a group of 91 scorers to explore the quantitative properties of their collective opinion. We were interested in the stability of their collective opinion as the sample size increases from 15 to 90. From a pool of 91 scorers who took part in a previous CHNRI exercise, we used sampling with replacement to generate multiple random samples of different size. First, for each sample generated, we identified the top 20 ranked research ideas, among 205 that were proposed and scored, and calculated the concordance with the ranking generated by the 91 original scorers. Second, we used rank correlation coefficients to compare the ranks assigned to all 205 proposed research ideas when samples of different size are used. We also analysed the original pool of 91 scorers to to look for evidence of scoring variations based on scorers' characteristics. The sample sizes investigated ranged from 15 to 90. The concordance for the top 20 scored research ideas increased with sample sizes up to about 55 experts. At this point, the median level of concordance stabilized at 15/20 top ranked questions (75%), with the interquartile range also generally stable (14-16). There was little further increase in overlap when the sample size increased from 55 to 90. When analysing the ranking of all 205 ideas, the rank correlation coefficient increased as the sample size increased, with a median correlation of 0.95 reached at the sample size of 45 experts (median of the rank correlation coefficient = 0.95; IQR 0.94-0.96). Our analyses suggest that the collective opinion of an expert group on a large number of research ideas, expressed through categorical variables (Yes/No/Not Sure/Don't know), stabilises relatively quickly in terms of identifying the ideas that have most support. In the exercise we found a high degree of reproducibility of the identified research priorities was achieved with as few as 45-55 experts.

Apparatus and method for the determination of grain size in thin films

DOEpatents

Maris, Humphrey J

2000-01-01

A method for the determination of grain size in a thin film sample comprising the steps of measuring first and second changes in the optical response of the thin film, comparing the first and second changes to find the attenuation of a propagating disturbance in the film and associating the attenuation of the disturbance to the grain size of the film. The second change in optical response is time delayed from the first change in optical response.

Apparatus and method for the determination of grain size in thin films

DOEpatents

Maris, Humphrey J

2001-01-01

A method for the determination of grain size in a thin film sample comprising the steps of measuring first and second changes in the optical response of the thin film, comparing the first and second changes to find the attenuation of a propagating disturbance in the film and associating the attenuation of the disturbance to the grain size of the film. The second change in optical response is time delayed from the first change in optical response.

Generalizing the Network Scale-Up Method: A New Estimator for the Size of Hidden Populations*

PubMed Central

Feehan, Dennis M.; Salganik, Matthew J.

2018-01-01

The network scale-up method enables researchers to estimate the size of hidden populations, such as drug injectors and sex workers, using sampled social network data. The basic scale-up estimator offers advantages over other size estimation techniques, but it depends on problematic modeling assumptions. We propose a new generalized scale-up estimator that can be used in settings with non-random social mixing and imperfect awareness about membership in the hidden population. Further, the new estimator can be used when data are collected via complex sample designs and from incomplete sampling frames. However, the generalized scale-up estimator also requires data from two samples: one from the frame population and one from the hidden population. In some situations these data from the hidden population can be collected by adding a small number of questions to already planned studies. For other situations, we develop interpretable adjustment factors that can be applied to the basic scale-up estimator. We conclude with practical recommendations for the design and analysis of future studies. PMID:29375167

Comparison of sampling and test methods for determining asphalt content and moisture correction in asphalt concrete mixtures.

DOT National Transportation Integrated Search

1985-03-01

The purpose of this report is to identify the difference, if any, in AASHTO and OSHD test procedures and results. This report addresses the effect of the size of samples taken in the field and evaluates the methods of determining the moisture content...

Method for genetic identification of unknown organisms

DOEpatents

Colston, Jr., Billy W.; Fitch, Joseph P.; Hindson, Benjamin J.; Carter, Chance J.; Beer, Neil Reginald

2016-08-23

A method of rapid, genome and proteome based identification of unknown pathogenic or non-pathogenic organisms in a complex sample. The entire sample is analyzed by creating millions of emulsion encapsulated microdroplets, each containing a single pathogenic or non-pathogenic organism sized particle and appropriate reagents for amplification. Following amplification, the amplified product is analyzed.

Efficient computation of the joint sample frequency spectra for multiple populations.

PubMed

Kamm, John A; Terhorst, Jonathan; Song, Yun S

2017-01-01

A wide range of studies in population genetics have employed the sample frequency spectrum (SFS), a summary statistic which describes the distribution of mutant alleles at a polymorphic site in a sample of DNA sequences and provides a highly efficient dimensional reduction of large-scale population genomic variation data. Recently, there has been much interest in analyzing the joint SFS data from multiple populations to infer parameters of complex demographic histories, including variable population sizes, population split times, migration rates, admixture proportions, and so on. SFS-based inference methods require accurate computation of the expected SFS under a given demographic model. Although much methodological progress has been made, existing methods suffer from numerical instability and high computational complexity when multiple populations are involved and the sample size is large. In this paper, we present new analytic formulas and algorithms that enable accurate, efficient computation of the expected joint SFS for thousands of individuals sampled from hundreds of populations related by a complex demographic model with arbitrary population size histories (including piecewise-exponential growth). Our results are implemented in a new software package called momi (MOran Models for Inference). Through an empirical study we demonstrate our improvements to numerical stability and computational complexity.

Efficient computation of the joint sample frequency spectra for multiple populations

PubMed Central

Kamm, John A.; Terhorst, Jonathan; Song, Yun S.

2016-01-01

A wide range of studies in population genetics have employed the sample frequency spectrum (SFS), a summary statistic which describes the distribution of mutant alleles at a polymorphic site in a sample of DNA sequences and provides a highly efficient dimensional reduction of large-scale population genomic variation data. Recently, there has been much interest in analyzing the joint SFS data from multiple populations to infer parameters of complex demographic histories, including variable population sizes, population split times, migration rates, admixture proportions, and so on. SFS-based inference methods require accurate computation of the expected SFS under a given demographic model. Although much methodological progress has been made, existing methods suffer from numerical instability and high computational complexity when multiple populations are involved and the sample size is large. In this paper, we present new analytic formulas and algorithms that enable accurate, efficient computation of the expected joint SFS for thousands of individuals sampled from hundreds of populations related by a complex demographic model with arbitrary population size histories (including piecewise-exponential growth). Our results are implemented in a new software package called momi (MOran Models for Inference). Through an empirical study we demonstrate our improvements to numerical stability and computational complexity. PMID:28239248

Numerical sedimentation particle-size analysis using the Discrete Element Method

NASA Astrophysics Data System (ADS)

Bravo, R.; Pérez-Aparicio, J. L.; Gómez-Hernández, J. J.

2015-12-01

Sedimentation tests are widely used to determine the particle size distribution of a granular sample. In this work, the Discrete Element Method interacts with the simulation of flow using the well known one-way-coupling method, a computationally affordable approach for the time-consuming numerical simulation of the hydrometer, buoyancy and pipette sedimentation tests. These tests are used in the laboratory to determine the particle-size distribution of fine-grained aggregates. Five samples with different particle-size distributions are modeled by about six million rigid spheres projected on two-dimensions, with diameters ranging from 2.5 ×10-6 m to 70 ×10-6 m, forming a water suspension in a sedimentation cylinder. DEM simulates the particle's movement considering laminar flow interactions of buoyant, drag and lubrication forces. The simulation provides the temporal/spatial distributions of densities and concentrations of the suspension. The numerical simulations cannot replace the laboratory tests since they need the final granulometry as initial data, but, as the results show, these simulations can identify the strong and weak points of each method and eventually recommend useful variations and draw conclusions on their validity, aspects very difficult to achieve in the laboratory.

Improving the accuracy of sediment-associated constituent concentrations in whole storm water samples by wet-sieving

USGS Publications Warehouse

Selbig, W.R.; Bannerman, R.; Bowman, G.

2007-01-01

Sand-sized particles (>63 ??m) in whole storm water samples collected from urban runoff have the potential to produce data with substantial bias and/or poor precision both during sample splitting and laboratory analysis. New techniques were evaluated in an effort to overcome some of the limitations associated with sample splitting and analyzing whole storm water samples containing sand-sized particles. Wet-sieving separates sand-sized particles from a whole storm water sample. Once separated, both the sieved solids and the remaining aqueous (water suspension of particles less than 63 ??m) samples were analyzed for total recoverable metals using a modification of USEPA Method 200.7. The modified version digests the entire sample, rather than an aliquot, of the sample. Using a total recoverable acid digestion on the entire contents of the sieved solid and aqueous samples improved the accuracy of the derived sediment-associated constituent concentrations. Concentration values of sieved solid and aqueous samples can later be summed to determine an event mean concentration. ?? ASA, CSSA, SSSA.

Particles size distribution in diluted magnetic fluids

NASA Astrophysics Data System (ADS)

Yerin, Constantine V.

2017-06-01

Changes in particles and aggregates size distribution in diluted kerosene based magnetic fluids is studied by dynamic light scattering method. It has been found that immediately after dilution in magnetic fluids the system of aggregates with sizes ranging from 100 to 250-1000 nm is formed. In 50-100 h after dilution large aggregates are peptized and in the sample stationary particles and aggregates size distribution is fixed.

Modeling change in potential landscape vulnerability to forest insect and pathogen disturbances: methods for forested subwatersheds sampled in the midscale interior Columbia River basin assessment.

Treesearch

Paul F. Hessburg; Bradley G. Smith; Craig A. Miller; Scott D. Kreiter; R. Brion Salter

1999-01-01

In the interior Columbia River basin midscale ecological assessment, including portions of the Klamath and Great Basins, we mapped and characterized historical and current vegetation composition and structure of 337 randomly sampled subwatersheds (9500 ha average size) in 43 subbasins (404 000 ha average size). We compared landscape patterns, vegetation structure and...

Effect size measures in a two-independent-samples case with nonnormal and nonhomogeneous data.

PubMed

Li, Johnson Ching-Hong

2016-12-01

In psychological science, the "new statistics" refer to the new statistical practices that focus on effect size (ES) evaluation instead of conventional null-hypothesis significance testing (Cumming, Psychological Science, 25, 7-29, 2014). In a two-independent-samples scenario, Cohen's (1988) standardized mean difference (d) is the most popular ES, but its accuracy relies on two assumptions: normality and homogeneity of variances. Five other ESs-the unscaled robust d (d r * ; Hogarty & Kromrey, 2001), scaled robust d (d r ; Algina, Keselman, & Penfield, Psychological Methods, 10, 317-328, 2005), point-biserial correlation (r pb ; McGrath & Meyer, Psychological Methods, 11, 386-401, 2006), common-language ES (CL; Cliff, Psychological Bulletin, 114, 494-509, 1993), and nonparametric estimator for CL (A w ; Ruscio, Psychological Methods, 13, 19-30, 2008)-may be robust to violations of these assumptions, but no study has systematically evaluated their performance. Thus, in this simulation study the performance of these six ESs was examined across five factors: data distribution, sample, base rate, variance ratio, and sample size. The results showed that A w and d r were generally robust to these violations, and A w slightly outperformed d r . Implications for the use of A w and d r in real-world research are discussed.

mHealth Series: mHealth project in Zhao County, rural China – Description of objectives, field site and methods

PubMed Central

van Velthoven, Michelle Helena; Li, Ye; Wang, Wei; Du, Xiaozhen; Wu, Qiong; Chen, Li; Majeed, Azeem; Rudan, Igor; Zhang, Yanfeng; Car, Josip

2013-01-01

Background We set up a collaboration between researchers in China and the UK that aimed to explore the use of mHealth in China. This is the first paper in a series of papers on a large mHealth project part of this collaboration. This paper included the aims and objectives of the mHealth project, our field site, and the detailed methods of two studies. Field site The field site for this mHealth project was Zhao County, which lies 280 km south of Beijing in Hebei Province, China. Methods We described the methodology of two studies: (i) a mixed methods study exploring factors influencing sample size calculations for mHealth–based health surveys and (ii) a cross–over study determining validity of an mHealth text messaging data collection tool. The first study used mixed methods, both quantitative and qualitative, including: (i) two surveys with caregivers of young children, (ii) interviews with caregivers, village doctors and participants of the cross–over study, and (iii) researchers’ views. We combined data from caregivers, village doctors and researchers to provide an in–depth understanding of factors influencing sample size calculations for mHealth–based health surveys. The second study, a cross–over study, used a randomised cross–over study design to compare the traditional face–to–face survey method to the new text messaging survey method. We assessed data equivalence (intrarater agreement), the amount of information in responses, reasons for giving different responses, the response rate, characteristics of non–responders, and the error rate. Conclusions This paper described the objectives, field site and methods of a large mHealth project part of a collaboration between researchers in China and the UK. The mixed methods study evaluating factors that influence sample size calculations could help future studies with estimating reliable sample sizes. The cross–over study comparing face–to–face and text message survey data collection could help future studies with developing their mHealth tools. PMID:24363919

Variation of Strontium (Sr) in the Ferroelectric Material Barium Strontium Titanate (Ba1-xSrxTiO3) by Co precipitation Method

NASA Astrophysics Data System (ADS)

Subarwanti, Y.; Safitri, R. D.; Supriyanto, A.; Iriani, Y.; Jamaludin, A.

2017-02-01

Barium Strontium Titanate (BST) have been made with variation strontium (Sr) 10%, 30% and 50% by co-precipitation method. This study aims to determine influence addition Sr against the crystal structure, crystallite size, lattice parameter, grain size and dielectric constant. Samples have been made by co-precipitation method and then the samples were sintered by furnace at 1100°C with holding time 4 hours. Characterization of BST use X-Ray Diffraction instrument, Scanning Electron Microscopy and Resistance Capacitance Inductance (RCL meter). Based on result obtained, the larger Sr content cause the diffraction angle shift to the right (the greater) and crystallinity increasing. But, the value of dielectric constant, crystallite size and grain size decreasing with additional Sr content. Measurement of dielectric constant (K) performed in the frequency range 1 kHz to 100 kHz and the highest value at Sr content 0.1 i.e. 258.35. The addition of Sr content 30% and 50% change the crystal structure from tetragonal to cubic which has paraelectric phase.

Uniform deposition of size-selected clusters using Lissajous scanning

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

Beniya, Atsushi; Watanabe, Yoshihide, E-mail: e0827@mosk.tytlabs.co.jp; Hirata, Hirohito

2016-05-15

Size-selected clusters can be deposited on the surface using size-selected cluster ion beams. However, because of the cross-sectional intensity distribution of the ion beam, it is difficult to define the coverage of the deposited clusters. The aggregation probability of the cluster depends on coverage, whereas cluster size on the surface depends on the position, despite the size-selected clusters are deposited. It is crucial, therefore, to deposit clusters uniformly on the surface. In this study, size-selected clusters were deposited uniformly on surfaces by scanning the cluster ions in the form of Lissajous pattern. Two sets of deflector electrodes set in orthogonalmore » directions were placed in front of the sample surface. Triangular waves were applied to the electrodes with an irrational frequency ratio to ensure that the ion trajectory filled the sample surface. The advantages of this method are simplicity and low cost of setup compared with raster scanning method. The authors further investigated CO adsorption on size-selected Pt{sub n} (n = 7, 15, 20) clusters uniformly deposited on the Al{sub 2}O{sub 3}/NiAl(110) surface and demonstrated the importance of uniform deposition.« less

Optimized mtDNA Control Region Primer Extension Capture Analysis for Forensically Relevant Samples and Highly Compromised mtDNA of Different Age and Origin

PubMed Central

Eduardoff, Mayra; Xavier, Catarina; Strobl, Christina; Casas-Vargas, Andrea; Parson, Walther

2017-01-01

The analysis of mitochondrial DNA (mtDNA) has proven useful in forensic genetics and ancient DNA (aDNA) studies, where specimens are often highly compromised and DNA quality and quantity are low. In forensic genetics, the mtDNA control region (CR) is commonly sequenced using established Sanger-type Sequencing (STS) protocols involving fragment sizes down to approximately 150 base pairs (bp). Recent developments include Massively Parallel Sequencing (MPS) of (multiplex) PCR-generated libraries using the same amplicon sizes. Molecular genetic studies on archaeological remains that harbor more degraded aDNA have pioneered alternative approaches to target mtDNA, such as capture hybridization and primer extension capture (PEC) methods followed by MPS. These assays target smaller mtDNA fragment sizes (down to 50 bp or less), and have proven to be substantially more successful in obtaining useful mtDNA sequences from these samples compared to electrophoretic methods. Here, we present the modification and optimization of a PEC method, earlier developed for sequencing the Neanderthal mitochondrial genome, with forensic applications in mind. Our approach was designed for a more sensitive enrichment of the mtDNA CR in a single tube assay and short laboratory turnaround times, thus complying with forensic practices. We characterized the method using sheared, high quantity mtDNA (six samples), and tested challenging forensic samples (n = 2) as well as compromised solid tissue samples (n = 15) up to 8 kyrs of age. The PEC MPS method produced reliable and plausible mtDNA haplotypes that were useful in the forensic context. It yielded plausible data in samples that did not provide results with STS and other MPS techniques. We addressed the issue of contamination by including four generations of negative controls, and discuss the results in the forensic context. We finally offer perspectives for future research to enable the validation and accreditation of the PEC MPS method for final implementation in forensic genetic laboratories. PMID:28934125

ESTIMATING SAMPLE REQUIREMENTS FOR FIELD EVALUATIONS OF PESTICIDE LEACHING

EPA Science Inventory

A method is presented for estimating the number of samples needed to evaluate pesticide leaching threats to ground water at a desired level of precision. Sample size projections are based on desired precision (exhibited as relative tolerable error), level of confidence (90 or 95%...

40 CFR 761.243 - Standard wipe sample method and size.

Code of Federal Regulations, 2010 CFR

2010-07-01

..., AND USE PROHIBITIONS Determining a PCB Concentration for Purposes of Abandonment or Disposal of Natural Gas Pipeline: Selecting Sample Sites, Collecting Surface Samples, and Analyzing Standard PCB Wipe.../Rinse Cleanup as Recommended by the Environmental Protection Agency PCB Spill Cleanup Policy,” dated...

On the role of the grain size in the magnetic behavior of sintered permanent magnets

NASA Astrophysics Data System (ADS)

Efthimiadis, K. G.; Ntallis, N.

2018-02-01

In this work the finite elements method is used to simulate, by micromagnetic modeling, the magnetic behavior of sintered anisotropic magnets. Hysteresis loops were simulated for different grain sizes in an oriented multigrain sample. By keeping out other parameters that contribute to the magnetic microstructure, such as the sample size, the grain morphology and the grain boundaries mismatch, it has been found that the grain size affects the magnetic properties only if the grains are exchange-decoupled. In this case, as the grain size decreases, a decrease in the nucleation field of a reverse magnetic domain is observed and an increase in the coercive field due to the pinning of the magnetic domain walls at the grain boundaries.

Polymorphism in magic-sized Au144(SR)60 clusters

NASA Astrophysics Data System (ADS)

Jensen, Kirsten M. Ø.; Juhas, Pavol; Tofanelli, Marcus A.; Heinecke, Christine L.; Vaughan, Gavin; Ackerson, Christopher J.; Billinge, Simon J. L.

2016-06-01

Ultra-small, magic-sized metal nanoclusters represent an important new class of materials with properties between molecules and particles. However, their small size challenges the conventional methods for structure characterization. Here we present the structure of ultra-stable Au144(SR)60 magic-sized nanoclusters obtained from atomic pair distribution function analysis of X-ray powder diffraction data. The study reveals structural polymorphism in these archetypal nanoclusters. In addition to confirming the theoretically predicted icosahedral-cored cluster, we also find samples with a truncated decahedral core structure, with some samples exhibiting a coexistence of both cluster structures. Although the clusters are monodisperse in size, structural diversity is apparent. The discovery of polymorphism may open up a new dimension in nanoscale engineering.

Accuracy or precision: Implications of sample design and methodology on abundance estimation

USGS Publications Warehouse

Kowalewski, Lucas K.; Chizinski, Christopher J.; Powell, Larkin A.; Pope, Kevin L.; Pegg, Mark A.

2015-01-01

Sampling by spatially replicated counts (point-count) is an increasingly popular method of estimating population size of organisms. Challenges exist when sampling by point-count method, and it is often impractical to sample entire area of interest and impossible to detect every individual present. Ecologists encounter logistical limitations that force them to sample either few large-sample units or many small sample-units, introducing biases to sample counts. We generated a computer environment and simulated sampling scenarios to test the role of number of samples, sample unit area, number of organisms, and distribution of organisms in the estimation of population sizes using N-mixture models. Many sample units of small area provided estimates that were consistently closer to true abundance than sample scenarios with few sample units of large area. However, sample scenarios with few sample units of large area provided more precise abundance estimates than abundance estimates derived from sample scenarios with many sample units of small area. It is important to consider accuracy and precision of abundance estimates during the sample design process with study goals and objectives fully recognized, although and with consequence, consideration of accuracy and precision of abundance estimates is often an afterthought that occurs during the data analysis process.

Lipid Vesicle Shape Analysis from Populations Using Light Video Microscopy and Computer Vision

PubMed Central

Zupanc, Jernej; Drašler, Barbara; Boljte, Sabina; Kralj-Iglič, Veronika; Iglič, Aleš; Erdogmus, Deniz; Drobne, Damjana

2014-01-01

We present a method for giant lipid vesicle shape analysis that combines manually guided large-scale video microscopy and computer vision algorithms to enable analyzing vesicle populations. The method retains the benefits of light microscopy and enables non-destructive analysis of vesicles from suspensions containing up to several thousands of lipid vesicles (1–50 µm in diameter). For each sample, image analysis was employed to extract data on vesicle quantity and size distributions of their projected diameters and isoperimetric quotients (measure of contour roundness). This process enables a comparison of samples from the same population over time, or the comparison of a treated population to a control. Although vesicles in suspensions are heterogeneous in sizes and shapes and have distinctively non-homogeneous distribution throughout the suspension, this method allows for the capture and analysis of repeatable vesicle samples that are representative of the population inspected. PMID:25426933

Grain Size and Phase Purity Characterization of U 3Si 2 Pellet Fuel

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

Hoggan, Rita E.; Tolman, Kevin R.; Cappia, Fabiola

Characterization of U 3Si 2 fresh fuel pellets is important for quality assurance and validation of the finished product. Grain size measurement methods, phase identification methods using scanning electron microscopes equipped with energy dispersive spectroscopy and x-ray diffraction, and phase quantification methods via image analysis have been developed and implemented on U 3Si 2 pellet samples. A wide variety of samples have been characterized including representative pellets from an initial irradiation experiment, and samples produced using optimized methods to enhance phase purity from an extended fabrication effort. The average grain size for initial pellets was between 16 and 18 µm.more » The typical average grain size for pellets from the extended fabrication was between 20 and 30 µm with some samples exhibiting irregular grain growth. Pellets from the latter half of extended fabrication had a bimodal grain size distribution consisting of coarsened grains (>80 µm) surrounded by the typical (20-30 µm) grain structure around the surface. Phases identified in initial uranium silicide pellets included: U 3Si 2 as the main phase composing about 80 vol. %, Si rich phases (USi and U 5Si 4) composing about 13 vol. %, and UO 2 composing about 5 vol. %. Initial batches from the extended U 3Si 2 pellet fabrication had similar phases and phase quantities. The latter half of the extended fabrication pellet batches did not contain Si rich phases, and had between 1-5% UO 2: achieving U 3Si 2 phase purity between 95 vol. % and 98 vol. % U 3Si 2. The amount of UO 2 in sintered U 3Si 2 pellets is correlated to the length of time between U 3Si 2 powder fabrication and pellet formation. These measurements provide information necessary to optimize fabrication efforts and a baseline for future work on this fuel compound.« less

Synthesis, photoluminescence and Magnetic properties of iron oxide (α-Fe2O3) nanoparticles through precipitation or hydrothermal methods

NASA Astrophysics Data System (ADS)

Lassoued, Abdelmajid; Lassoued, Mohamed Saber; Dkhil, Brahim; Ammar, Salah; Gadri, Abdellatif

2018-07-01

In this work the iron oxide (α-Fe2O3) nanoparticles are synthesized using two different methods: precipitation and hydrothermal. Size, structural, optical and magnetic properties were determined and compared using X-ray diffraction (XRD), Transmission Electron Microscopy (TEM), Scanning Electron Microscopy (SEM), Fourier Transform Infra-Red (FT-IR), Raman spectroscopy, Differential Thermal Analysis (DTA), Thermogravimetric Analysis (TGA), Ultraviolet-Visible (UV-Vis) analysis, Superconducting QUantum Interference Device (SQUID) magnetometer and Photoluminescence (PL). XRD data further revealed a rhombohedral (hexagonal) structure with the space group (R-3c) and showed an average size of 21 nm for hydrothermal samples and 33 nm for precipitation samples which concorded with TEM and SEM images. FT-IR confirms the phase purity of the nanoparticles synthesized. The Raman spectroscopy was used not only to prove that we have synthesized pure α-Fe2O3 but also to identify their phonon modes. The TGA showed three mass losses, whereas DTA resulted in three endothermic peaks. The decrease in the particle size of hematite of 33 nm for precipitation samples to 21 nm for hydrothermal samples is responsible for increasing the optical band gap of 1.94-2.10 eV where, the relation between them is inverse relationship. The products exhibited the attractive magnetic properties with good saturation magnetization, which were examined by a SQUID magnetometer. Photoluminescence measurements showed a strong emission band at 450 nm. Pure hematite prepared by hydrothermal method has smallest size, best crystallinity, highest band gap and best value of saturation magnetization compared to the hematite elaborated by the precipitation method.

An In Situ Method for Sizing Insoluble Residues in Precipitation and Other Aqueous Samples

PubMed Central

Axson, Jessica L.; Creamean, Jessie M.; Bondy, Amy L.; Capracotta, Sonja S.; Warner, Katy Y.; Ault, Andrew P.

2015-01-01

Particles are frequently incorporated into clouds or precipitation, influencing climate by acting as cloud condensation or ice nuclei, taking up coatings during cloud processing, and removing species through wet deposition. Many of these particles, particularly ice nuclei, can remain suspended within cloud droplets/crystals as insoluble residues. While previous studies have measured the soluble or bulk mass of species within clouds and precipitation, no studies to date have determined the number concentration and size distribution of insoluble residues in precipitation or cloud water using in situ methods. Herein, for the first time we demonstrate that Nanoparticle Tracking Analysis (NTA) is a powerful in situ method for determining the total number concentration, number size distribution, and surface area distribution of insoluble residues in precipitation, both of rain and melted snow. The method uses 500 μL or less of liquid sample and does not require sample modification. Number concentrations for the insoluble residues in aqueous precipitation samples ranged from 2.0–3.0(±0.3)×108 particles cm−3, while surface area ranged from 1.8(±0.7)–3.2(±1.0)×107 μm2 cm−3. Number size distributions peaked between 133–150 nm, with both single and multi-modal character, while surface area distributions peaked between 173–270 nm. Comparison with electron microscopy of particles up to 10 μm show that, by number, > 97% residues are <1 μm in diameter, the upper limit of the NTA. The range of concentration and distribution properties indicates that insoluble residue properties vary with ambient aerosol concentrations, cloud microphysics, and meteorological dynamics. NTA has great potential for studying the role that insoluble residues play in critical atmospheric processes. PMID:25705069

Methods for Specifying the Target Difference in a Randomised Controlled Trial: The Difference ELicitation in TriAls (DELTA) Systematic Review

PubMed Central

Hislop, Jenni; Adewuyi, Temitope E.; Vale, Luke D.; Harrild, Kirsten; Fraser, Cynthia; Gurung, Tara; Altman, Douglas G.; Briggs, Andrew H.; Fayers, Peter; Ramsay, Craig R.; Norrie, John D.; Harvey, Ian M.; Buckley, Brian; Cook, Jonathan A.

2014-01-01

Background Randomised controlled trials (RCTs) are widely accepted as the preferred study design for evaluating healthcare interventions. When the sample size is determined, a (target) difference is typically specified that the RCT is designed to detect. This provides reassurance that the study will be informative, i.e., should such a difference exist, it is likely to be detected with the required statistical precision. The aim of this review was to identify potential methods for specifying the target difference in an RCT sample size calculation. Methods and Findings A comprehensive systematic review of medical and non-medical literature was carried out for methods that could be used to specify the target difference for an RCT sample size calculation. The databases searched were MEDLINE, MEDLINE In-Process, EMBASE, the Cochrane Central Register of Controlled Trials, the Cochrane Methodology Register, PsycINFO, Science Citation Index, EconLit, the Education Resources Information Center (ERIC), and Scopus (for in-press publications); the search period was from 1966 or the earliest date covered, to between November 2010 and January 2011. Additionally, textbooks addressing the methodology of clinical trials and International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) tripartite guidelines for clinical trials were also consulted. A narrative synthesis of methods was produced. Studies that described a method that could be used for specifying an important and/or realistic difference were included. The search identified 11,485 potentially relevant articles from the databases searched. Of these, 1,434 were selected for full-text assessment, and a further nine were identified from other sources. Fifteen clinical trial textbooks and the ICH tripartite guidelines were also reviewed. In total, 777 studies were included, and within them, seven methods were identified—anchor, distribution, health economic, opinion-seeking, pilot study, review of the evidence base, and standardised effect size. Conclusions A variety of methods are available that researchers can use for specifying the target difference in an RCT sample size calculation. Appropriate methods may vary depending on the aim (e.g., specifying an important difference versus a realistic difference), context (e.g., research question and availability of data), and underlying framework adopted (e.g., Bayesian versus conventional statistical approach). Guidance on the use of each method is given. No single method provides a perfect solution for all contexts. Please see later in the article for the Editors' Summary PMID:24824338

Pooling sheep faecal samples for the assessment of anthelmintic drug efficacy using McMaster and Mini-FLOTAC in gastrointestinal strongyle and Nematodirus infection.

PubMed

Kenyon, Fiona; Rinaldi, Laura; McBean, Dave; Pepe, Paola; Bosco, Antonio; Melville, Lynsey; Devin, Leigh; Mitchell, Gillian; Ianniello, Davide; Charlier, Johannes; Vercruysse, Jozef; Cringoli, Giuseppe; Levecke, Bruno

2016-07-30

In small ruminants, faecal egg counts (FECs) and reduction in FECs (FECR) are the most common methods for the assessment of intensity of gastrointestinal (GI) nematodes infections and anthelmintic drug efficacy, respectively. The main limitation of these methods is the time and cost to conduct FECs on a representative number of individual animals. A cost-saving alternative would be to examine pooled faecal samples, however little is known regarding whether pooling can give representative results. In the present study, we compared the FECR results obtained by both an individual and a pooled examination strategy across different pool sizes and analytical sensitivity of the FEC techniques. A survey was conducted on 5 sheep farms in Scotland, where anthelmintic resistance is known to be widespread. Lambs were treated with fenbendazole (4 groups), levamisole (3 groups), ivermectin (3 groups) or moxidectin (1 group). For each group, individual faecal samples were collected from 20 animals, at baseline (D0) and 14 days after (D14) anthelmintic administration. Faecal samples were analyzed as pools of 3-5, 6-10, and 14-20 individual samples. Both individual and pooled samples were screened for GI strongyle and Nematodirus eggs using two FEC techniques with three different levels of analytical sensitivity, including Mini-FLOTAC (analytical sensitivity of 10 eggs per gram of faeces (EPG)) and McMaster (analytical sensitivity of 15 or 50 EPG).For both Mini-FLOTAC and McMaster (analytical sensitivity of 15 EPG), there was a perfect agreement in classifying the efficacy of the anthelmintic as 'normal', 'doubtful' or 'reduced' regardless of pool size. When using the McMaster method (analytical sensitivity of 50 EPG) anthelmintic efficacy was often falsely classified as 'normal' or assessment was not possible due to zero FECs at D0, and this became more pronounced when the pool size increased. In conclusion, pooling ovine faecal samples holds promise as a cost-saving and efficient strategy for assessing GI nematode FECR. However, for the assessment FECR one will need to consider the baseline FEC, pool size and analytical sensitivity of the method. Copyright © 2016. Published by Elsevier B.V.

What is a species? A new universal method to measure differentiation and assess the taxonomic rank of allopatric populations, using continuous variables

PubMed Central

Donegan, Thomas M.

2018-01-01

Abstract Existing models for assigning species, subspecies, or no taxonomic rank to populations which are geographically separated from one another were analyzed. This was done by subjecting over 3,000 pairwise comparisons of vocal or biometric data based on birds to a variety of statistical tests that have been proposed as measures of differentiation. One current model which aims to test diagnosability (Isler et al. 1998) is highly conservative, applying a hard cut-off, which excludes from consideration differentiation below diagnosis. It also includes non-overlap as a requirement, a measure which penalizes increases to sample size. The “species scoring” model of Tobias et al. (2010) involves less drastic cut-offs, but unlike Isler et al. (1998), does not control adequately for sample size and attributes scores in many cases to differentiation which is not statistically significant. Four different models of assessing effect sizes were analyzed: using both pooled and unpooled standard deviations and controlling for sample size using t-distributions or omitting to do so. Pooled standard deviations produced more conservative effect sizes when uncontrolled for sample size but less conservative effect sizes when so controlled. Pooled models require assumptions to be made that are typically elusive or unsupported for taxonomic studies. Modifications to improving these frameworks are proposed, including: (i) introducing statistical significance as a gateway to attributing any weighting to findings of differentiation; (ii) abandoning non-overlap as a test; (iii) recalibrating Tobias et al. (2010) scores based on effect sizes controlled for sample size using t-distributions. A new universal method is proposed for measuring differentiation in taxonomy using continuous variables and a formula is proposed for ranking allopatric populations. This is based first on calculating effect sizes using unpooled standard deviations, controlled for sample size using t-distributions, for a series of different variables. All non-significant results are excluded by scoring them as zero. Distance between any two populations is calculated using Euclidian summation of non-zeroed effect size scores. If the score of an allopatric pair exceeds that of a related sympatric pair, then the allopatric population can be ranked as species and, if not, then at most subspecies rank should be assigned. A spreadsheet has been programmed and is being made available which allows this and other tests of differentiation and rank studied in this paper to be rapidly analyzed. PMID:29780266

Quantitative Reflectance Spectra of Solid Powders as a Function of Particle Size

DOE PAGES

Myers, Tanya L.; Brauer, Carolyn S.; Su, Yin-Fong; ...

2015-05-19

We have recently developed vetted methods for obtaining quantitative infrared directional-hemispherical reflectance spectra using a commercial integrating sphere. In this paper, the effects of particle size on the spectral properties are analyzed for several samples such as ammonium sulfate, calcium carbonate, and sodium sulfate as well as one organic compound, lactose. We prepared multiple size fractions for each sample and confirmed the mean sizes using optical microscopy. Most species displayed a wide range of spectral behavior depending on the mean particle size. General trends of reflectance vs. particle size are observed such as increased albedo for smaller particles: for mostmore » wavelengths, the reflectivity drops with increased size, sometimes displaying a factor of 4 or more drop in reflectivity along with a loss of spectral contrast. In the longwave infrared, several species with symmetric anions or cations exhibited reststrahlen features whose amplitude was nearly invariant with particle size, at least for intermediate- and large-sized sample fractions; that is, > ~150 microns. Trends of other types of bands (Christiansen minima, transparency features) are also investigated as well as quantitative analysis of the observed relationship between reflectance vs. particle diameter.« less

Quantitative Reflectance Spectra of Solid Powders as a Function of Particle Size

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

Myers, Tanya L.; Brauer, Carolyn S.; Su, Yin-Fong

We have recently developed vetted methods for obtaining quantitative infrared directional-hemispherical reflectance spectra using a commercial integrating sphere. In this paper, the effects of particle size on the spectral properties are analyzed for several samples such as ammonium sulfate, calcium carbonate, and sodium sulfate as well as one organic compound, lactose. We prepared multiple size fractions for each sample and confirmed the mean sizes using optical microscopy. Most species displayed a wide range of spectral behavior depending on the mean particle size. General trends of reflectance vs. particle size are observed such as increased albedo for smaller particles: for mostmore » wavelengths, the reflectivity drops with increased size, sometimes displaying a factor of 4 or more drop in reflectivity along with a loss of spectral contrast. In the longwave infrared, several species with symmetric anions or cations exhibited reststrahlen features whose amplitude was nearly invariant with particle size, at least for intermediate- and large-sized sample fractions; that is, > ~150 microns. Trends of other types of bands (Christiansen minima, transparency features) are also investigated as well as quantitative analysis of the observed relationship between reflectance vs. particle diameter.« less

Determining the linkage of disease-resistance genes to molecular markers: the LOD-SCORE method revisited with regard to necessary sample sizes.

PubMed

Hühn, M

1995-05-01

Some approaches to molecular marker-assisted linkage detection for a dominant disease-resistance trait based on a segregating F2 population are discussed. Analysis of two-point linkage is carried out by the traditional measure of maximum lod score. It depends on (1) the maximum-likelihood estimate of the recombination fraction between the marker and the disease-resistance gene locus, (2) the observed absolute frequencies, and (3) the unknown number of tested individuals. If one replaces the absolute frequencies by expressions depending on the unknown sample size and the maximum-likelihood estimate of recombination value, the conventional rule for significant linkage (maximum lod score exceeds a given linkage threshold) can be resolved for the sample size. For each sub-population used for linkage analysis [susceptible (= recessive) individuals, resistant (= dominant) individuals, complete F2] this approach gives a lower bound for the necessary number of individuals required for the detection of significant two-point linkage by the lod-score method.

Reference interval estimation: Methodological comparison using extensive simulations and empirical data.

PubMed

Daly, Caitlin H; Higgins, Victoria; Adeli, Khosrow; Grey, Vijay L; Hamid, Jemila S

2017-12-01

To statistically compare and evaluate commonly used methods of estimating reference intervals and to determine which method is best based on characteristics of the distribution of various data sets. Three approaches for estimating reference intervals, i.e. parametric, non-parametric, and robust, were compared with simulated Gaussian and non-Gaussian data. The hierarchy of the performances of each method was examined based on bias and measures of precision. The findings of the simulation study were illustrated through real data sets. In all Gaussian scenarios, the parametric approach provided the least biased and most precise estimates. In non-Gaussian scenarios, no single method provided the least biased and most precise estimates for both limits of a reference interval across all sample sizes, although the non-parametric approach performed the best for most scenarios. The hierarchy of the performances of the three methods was only impacted by sample size and skewness. Differences between reference interval estimates established by the three methods were inflated by variability. Whenever possible, laboratories should attempt to transform data to a Gaussian distribution and use the parametric approach to obtain the most optimal reference intervals. When this is not possible, laboratories should consider sample size and skewness as factors in their choice of reference interval estimation method. The consequences of false positives or false negatives may also serve as factors in this decision. Copyright © 2017 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Comparison of Methods for Analyzing Left-Censored Occupational Exposure Data

PubMed Central

Huynh, Tran; Ramachandran, Gurumurthy; Banerjee, Sudipto; Monteiro, Joao; Stenzel, Mark; Sandler, Dale P.; Engel, Lawrence S.; Kwok, Richard K.; Blair, Aaron; Stewart, Patricia A.

2014-01-01

The National Institute for Environmental Health Sciences (NIEHS) is conducting an epidemiologic study (GuLF STUDY) to investigate the health of the workers and volunteers who participated from April to December of 2010 in the response and cleanup of the oil release after the Deepwater Horizon explosion in the Gulf of Mexico. The exposure assessment component of the study involves analyzing thousands of personal monitoring measurements that were collected during this effort. A substantial portion of these data has values reported by the analytic laboratories to be below the limits of detection (LOD). A simulation study was conducted to evaluate three established methods for analyzing data with censored observations to estimate the arithmetic mean (AM), geometric mean (GM), geometric standard deviation (GSD), and the 95th percentile (X0.95) of the exposure distribution: the maximum likelihood (ML) estimation, the β-substitution, and the Kaplan–Meier (K-M) methods. Each method was challenged with computer-generated exposure datasets drawn from lognormal and mixed lognormal distributions with sample sizes (N) varying from 5 to 100, GSDs ranging from 2 to 5, and censoring levels ranging from 10 to 90%, with single and multiple LODs. Using relative bias and relative root mean squared error (rMSE) as the evaluation metrics, the β-substitution method generally performed as well or better than the ML and K-M methods in most simulated lognormal and mixed lognormal distribution conditions. The ML method was suitable for large sample sizes (N ≥ 30) up to 80% censoring for lognormal distributions with small variability (GSD = 2–3). The K-M method generally provided accurate estimates of the AM when the censoring was <50% for lognormal and mixed distributions. The accuracy and precision of all methods decreased under high variability (GSD = 4 and 5) and small to moderate sample sizes (N < 20) but the β-substitution was still the best of the three methods. When using the ML method, practitioners are cautioned to be aware of different ways of estimating the AM as they could lead to biased interpretation. A limitation of the β-substitution method is the absence of a confidence interval for the estimate. More research is needed to develop methods that could improve the estimation accuracy for small sample sizes and high percent censored data and also provide uncertainty intervals. PMID:25261453

Accounting for Incomplete Species Detection in Fish Community Monitoring

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

McManamay, Ryan A; Orth, Dr. Donald J; Jager, Yetta

2013-01-01

Riverine fish assemblages are heterogeneous and very difficult to characterize with a one-size-fits-all approach to sampling. Furthermore, detecting changes in fish assemblages over time requires accounting for variation in sampling designs. We present a modeling approach that permits heterogeneous sampling by accounting for site and sampling covariates (including method) in a model-based framework for estimation (versus a sampling-based framework). We snorkeled during three surveys and electrofished during a single survey in suite of delineated habitats stratified by reach types. We developed single-species occupancy models to determine covariates influencing patch occupancy and species detection probabilities whereas community occupancy models estimated speciesmore » richness in light of incomplete detections. For most species, information-theoretic criteria showed higher support for models that included patch size and reach as covariates of occupancy. In addition, models including patch size and sampling method as covariates of detection probabilities also had higher support. Detection probability estimates for snorkeling surveys were higher for larger non-benthic species whereas electrofishing was more effective at detecting smaller benthic species. The number of sites and sampling occasions required to accurately estimate occupancy varied among fish species. For rare benthic species, our results suggested that higher number of occasions, and especially the addition of electrofishing, may be required to improve detection probabilities and obtain accurate occupancy estimates. Community models suggested that richness was 41% higher than the number of species actually observed and the addition of an electrofishing survey increased estimated richness by 13%. These results can be useful to future fish assemblage monitoring efforts by informing sampling designs, such as site selection (e.g. stratifying based on patch size) and determining effort required (e.g. number of sites versus occasions).« less

Estimation and applications of size-based distributions in forestry

Treesearch

Jeffrey H. Gove

2003-01-01

Size-based distributions arise in several contexts in forestry and ecology. Simple power relationships (e.g., basal area and diameter at breast height) between variables are one such area of interest arising from a modeling perspective. Another, probability proportional to size sampline (PPS), is found in the most widely used methods for sampling standing or dead and...

Blinded and unblinded internal pilot study designs for clinical trials with count data.

PubMed

Schneider, Simon; Schmidli, Heinz; Friede, Tim

2013-07-01

Internal pilot studies are a popular design feature to address uncertainties in the sample size calculations caused by vague information on nuisance parameters. Despite their popularity, only very recently blinded sample size reestimation procedures for trials with count data were proposed and their properties systematically investigated. Although blinded procedures are favored by regulatory authorities, practical application is somewhat limited by fears that blinded procedures are prone to bias if the treatment effect was misspecified in the planning. Here, we compare unblinded and blinded procedures with respect to bias, error rates, and sample size distribution. We find that both procedures maintain the desired power and that the unblinded procedure is slightly liberal whereas the actual significance level of the blinded procedure is close to the nominal level. Furthermore, we show that in situations where uncertainty about the assumed treatment effect exists, the blinded estimator of the control event rate is biased in contrast to the unblinded estimator, which results in differences in mean sample sizes in favor of the unblinded procedure. However, these differences are rather small compared to the deviations of the mean sample sizes from the sample size required to detect the true, but unknown effect. We demonstrate that the variation of the sample size resulting from the blinded procedure is in many practically relevant situations considerably smaller than the one of the unblinded procedures. The methods are extended to overdispersed counts using a quasi-likelihood approach and are illustrated by trials in relapsing multiple sclerosis. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Robust Covariate-Adjusted Log-Rank Statistics and Corresponding Sample Size Formula for Recurrent Events Data

PubMed Central

Song, Rui; Kosorok, Michael R.; Cai, Jianwen

2009-01-01

Summary Recurrent events data are frequently encountered in clinical trials. This article develops robust covariate-adjusted log-rank statistics applied to recurrent events data with arbitrary numbers of events under independent censoring and the corresponding sample size formula. The proposed log-rank tests are robust with respect to different data-generating processes and are adjusted for predictive covariates. It reduces to the Kong and Slud (1997, Biometrika 84, 847–862) setting in the case of a single event. The sample size formula is derived based on the asymptotic normality of the covariate-adjusted log-rank statistics under certain local alternatives and a working model for baseline covariates in the recurrent event data context. When the effect size is small and the baseline covariates do not contain significant information about event times, it reduces to the same form as that of Schoenfeld (1983, Biometrics 39, 499–503) for cases of a single event or independent event times within a subject. We carry out simulations to study the control of type I error and the comparison of powers between several methods in finite samples. The proposed sample size formula is illustrated using data from an rhDNase study. PMID:18162107

Improvements to sample processing and measurement to enable more widespread environmental application of tritium

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

Moran, James; Alexander, Thomas; Aalseth, Craig

2017-08-01

Previous measurements have demonstrated the wealth of information that tritium (T) can provide on environmentally relevant processes. We present modifications to sample preparation approaches that enable T measurement by proportional counting on small sample sizes equivalent to 120 mg of water and demonstrate the accuracy of these methods on a suite of standardized water samples. This enhanced method should provide the analytical flexibility needed to address persistent knowledge gaps in our understanding of T behavior in the environment.

Signal Sampling for Efficient Sparse Representation of Resting State FMRI Data

PubMed Central

Ge, Bao; Makkie, Milad; Wang, Jin; Zhao, Shijie; Jiang, Xi; Li, Xiang; Lv, Jinglei; Zhang, Shu; Zhang, Wei; Han, Junwei; Guo, Lei; Liu, Tianming

2015-01-01

As the size of brain imaging data such as fMRI grows explosively, it provides us with unprecedented and abundant information about the brain. How to reduce the size of fMRI data but not lose much information becomes a more and more pressing issue. Recent literature studies tried to deal with it by dictionary learning and sparse representation methods, however, their computation complexities are still high, which hampers the wider application of sparse representation method to large scale fMRI datasets. To effectively address this problem, this work proposes to represent resting state fMRI (rs-fMRI) signals of a whole brain via a statistical sampling based sparse representation. First we sampled the whole brain’s signals via different sampling methods, then the sampled signals were aggregate into an input data matrix to learn a dictionary, finally this dictionary was used to sparsely represent the whole brain’s signals and identify the resting state networks. Comparative experiments demonstrate that the proposed signal sampling framework can speed-up by ten times in reconstructing concurrent brain networks without losing much information. The experiments on the 1000 Functional Connectomes Project further demonstrate its effectiveness and superiority. PMID:26646924

Direct Analysis of Low-Volatile Molecular Marker Extract from Airborne Particulate Matter Using Sensitivity Correction Method

PubMed Central

Irei, Satoshi

2016-01-01

Molecular marker analysis of environmental samples often requires time consuming preseparation steps. Here, analysis of low-volatile nonpolar molecular markers (5-6 ring polycyclic aromatic hydrocarbons or PAHs, hopanoids, and n-alkanes) without the preseparation procedure is presented. Analysis of artificial sample extracts was directly conducted by gas chromatography-mass spectrometry (GC-MS). After every sample injection, a standard mixture was also analyzed to make a correction on the variation of instrumental sensitivity caused by the unfavorable matrix contained in the extract. The method was further validated for the PAHs using the NIST standard reference materials (SRMs) and then applied to airborne particulate matter samples. Tests with the SRMs showed that overall our methodology was validated with the uncertainty of ~30%. The measurement results of airborne particulate matter (PM) filter samples showed a strong correlation between the PAHs, implying the contributions from the same emission source. Analysis of size-segregated PM filter samples showed that their size distributions were found to be in the PM smaller than 0.4 μm aerodynamic diameter. The observations were consistent with our expectation of their possible sources. Thus, the method was found to be useful for molecular marker studies. PMID:27127511

Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range.

PubMed

Wan, Xiang; Wang, Wenqian; Liu, Jiming; Tong, Tiejun

2014-12-19

In systematic reviews and meta-analysis, researchers often pool the results of the sample mean and standard deviation from a set of similar clinical trials. A number of the trials, however, reported the study using the median, the minimum and maximum values, and/or the first and third quartiles. Hence, in order to combine results, one may have to estimate the sample mean and standard deviation for such trials. In this paper, we propose to improve the existing literature in several directions. First, we show that the sample standard deviation estimation in Hozo et al.'s method (BMC Med Res Methodol 5:13, 2005) has some serious limitations and is always less satisfactory in practice. Inspired by this, we propose a new estimation method by incorporating the sample size. Second, we systematically study the sample mean and standard deviation estimation problem under several other interesting settings where the interquartile range is also available for the trials. We demonstrate the performance of the proposed methods through simulation studies for the three frequently encountered scenarios, respectively. For the first two scenarios, our method greatly improves existing methods and provides a nearly unbiased estimate of the true sample standard deviation for normal data and a slightly biased estimate for skewed data. For the third scenario, our method still performs very well for both normal data and skewed data. Furthermore, we compare the estimators of the sample mean and standard deviation under all three scenarios and present some suggestions on which scenario is preferred in real-world applications. In this paper, we discuss different approximation methods in the estimation of the sample mean and standard deviation and propose some new estimation methods to improve the existing literature. We conclude our work with a summary table (an Excel spread sheet including all formulas) that serves as a comprehensive guidance for performing meta-analysis in different situations.

Preconcentration and speciation of ultra-trace Se (IV) and Se (VI) in environmental water samples with nano-sized TiO2 colloid and determination by HG-AFS.

PubMed

Fu, Jiaqi; Zhang, Xu; Qian, Shahua; Zhang, Lin

2012-05-30

A united method for speciation analysis of Se (IV) and Se (VI) in environmental water samples was developed using nano-sized TiO(2) colloid as adsorbent and hydride generation atomic fluorescence spectrometry (HG-AFS) as determination means. When the pH values of bulk solution were between 6.0 and 7.0, successful adsorption onto 1 mL nano-sized TiO(2) colloid (0.2%) was achieved for more than 97.0% of Se (IV) while Se (VI) barely got adsorbed. Therefore, the method made it possible to preconcentrate and determine Se (IV) and Se (VI) separately. The precipitated TiO(2) with concentrated selenium was directly converted to colloid without desorption. Selenium in the resulting colloid was then determined by HG-AFS. The detection limits (3σ) and relative standard deviations (R.S.D) of this method were 24 ng/L and 42 ng/L, 7.8% (n=6) and 7.0% (n=6) for Se (IV) and Se (VI), respectively. This simple, sensitive, and united method was successfully applied to the separation and speciation of ultra-trace Se (IV) and Se (VI) in environmental water samples. Copyright © 2012 Elsevier B.V. All rights reserved.

Ferromagnetic linewidth measurements employing electrodynamic model of the magnetic plasmon resonance

NASA Astrophysics Data System (ADS)

Krupka, Jerzy; Aleshkevych, Pavlo; Salski, Bartlomiej; Kopyt, Pawel

2018-02-01

The mode of uniform precession, or Kittel mode, in a magnetized ferromagnetic sphere, has recently been proven to be the magnetic plasmon resonance. In this paper we show how to apply the electrodynamic model of the magnetic plasmon resonance for accurate measurements of the ferromagnetic resonance linewidth ΔH. Two measurement methods are presented. The first one employs Q-factor measurements of the magnetic plasmon resonance coupled to the resonance of an empty metallic cavity. Such coupled modes are known as magnon-polariton modes, i.e. hybridized modes between the collective spin excitation and the cavity excitation. The second one employs direct Q-factor measurements of the magnetic plasmon resonance in a filter setup with two orthogonal semi-loops used for coupling. Q-factor measurements are performed employing a vector network analyser. The methods presented in this paper allow one to extend the measurement range of the ferromagnetic resonance linewidth ΔH well beyond the limits of the commonly used measurement standards in terms of the size of the samples and the lowest measurable linewidths. Samples that can be measured with the newly proposed methods may have larger size as compared to the size of samples that were used in the standard methods restricted by the limits of perturbation theory.

Meta-analysis of multiple outcomes: a multilevel approach.

PubMed

Van den Noortgate, Wim; López-López, José Antonio; Marín-Martínez, Fulgencio; Sánchez-Meca, Julio

2015-12-01

In meta-analysis, dependent effect sizes are very common. An example is where in one or more studies the effect of an intervention is evaluated on multiple outcome variables for the same sample of participants. In this paper, we evaluate a three-level meta-analytic model to account for this kind of dependence, extending the simulation results of Van den Noortgate, López-López, Marín-Martínez, and Sánchez-Meca Behavior Research Methods, 45, 576-594 (2013) by allowing for a variation in the number of effect sizes per study, in the between-study variance, in the correlations between pairs of outcomes, and in the sample size of the studies. At the same time, we explore the performance of the approach if the outcomes used in a study can be regarded as a random sample from a population of outcomes. We conclude that although this approach is relatively simple and does not require prior estimates of the sampling covariances between effect sizes, it gives appropriate mean effect size estimates, standard error estimates, and confidence interval coverage proportions in a variety of realistic situations.

Improved radiation dose efficiency in solution SAXS using a sheath flow sample environment

PubMed Central

Kirby, Nigel; Cowieson, Nathan; Hawley, Adrian M.; Mudie, Stephen T.; McGillivray, Duncan J.; Kusel, Michael; Samardzic-Boban, Vesna; Ryan, Timothy M.

2016-01-01

Radiation damage is a major limitation to synchrotron small-angle X-ray scattering analysis of biomacromolecules. Flowing the sample during exposure helps to reduce the problem, but its effectiveness in the laminar-flow regime is limited by slow flow velocity at the walls of sample cells. To overcome this limitation, the coflow method was developed, where the sample flows through the centre of its cell surrounded by a flow of matched buffer. The method permits an order-of-magnitude increase of X-ray incident flux before sample damage, improves measurement statistics and maintains low sample concentration limits. The method also efficiently handles sample volumes of a few microlitres, can increase sample throughput, is intrinsically resistant to capillary fouling by sample and is suited to static samples and size-exclusion chromatography applications. The method unlocks further potential of third-generation synchrotron beamlines to facilitate new and challenging applications in solution scattering. PMID:27917826

Rapid detection of soils contaminated with heavy metals and oils by laser induced breakdown spectroscopy (LIBS).

PubMed

Kim, Gibaek; Kwak, Jihyun; Kim, Ki-Rak; Lee, Heesung; Kim, Kyoung-Woong; Yang, Hyeon; Park, Kihong

2013-12-15

A laser induced breakdown spectroscopy (LIBS) coupled with the chemometric method was applied to rapidly discriminate between soils contaminated with heavy metals or oils and clean soils. The effects of the water contents and grain sizes of soil samples on LIBS emissions were also investigated. The LIBS emission lines decreased by 59-75% when the water content increased from 1.2% to 7.8%, and soil samples with a grain size of 75 μm displayed higher LIBS emission lines with lower relative standard deviations than those with a 2mm grain size. The water content was found to have a more pronounced effect on the LIBS emission lines than the grain size. Pelletizing and sieving were conducted for all samples collected from abandoned mining areas and military camp to have similar water contents and grain sizes before being analyzed by the LIBS with the chemometric analysis. The data show that three types of soil samples were clearly discerned by using the first three principal components from the spectral data of soil samples. A blind test was conducted with a 100% correction rate for soil samples contaminated with heavy metals and oil residues. Copyright © 2013 Elsevier B.V. All rights reserved.

A new method for reporting and interpreting textural composition of spawning gravel.

Treesearch

Fredrick B. Lotspeich; Fred H. Everest

1981-01-01

A new method has been developed for collecting, sorting, and interpreting gravel quality. Samples are collected with a tri-tube freeze-core device and dry-sorted by using sieves based on the Wentworth scale. An index to the quality of gravel is obtained by dividing geometric mean particle size by the sorting coefficient (a measure of the distribution of grain sizes) of...

Performance of Bootstrapping Approaches To Model Test Statistics and Parameter Standard Error Estimation in Structural Equation Modeling.

ERIC Educational Resources Information Center

Nevitt, Jonathan; Hancock, Gregory R.

2001-01-01

Evaluated the bootstrap method under varying conditions of nonnormality, sample size, model specification, and number of bootstrap samples drawn from the resampling space. Results for the bootstrap suggest the resampling-based method may be conservative in its control over model rejections, thus having an impact on the statistical power associated…

Developing and refining NIR calibrations for total carbohydrate composition and isoflavones and saponins in ground whole soy meal

USDA-ARS?s Scientific Manuscript database

Although many near infrared (NIR) spectrometric calibrations exist for a variety of components in soy, current calibration methods are often limited by either a small sample size on which the calibrations are based or a wide variation in sample preparation and measurement methods, which yields unrel...

Flow field-flow fractionation for the analysis of nanoparticles used in drug delivery.

PubMed

Zattoni, Andrea; Roda, Barbara; Borghi, Francesco; Marassi, Valentina; Reschiglian, Pierluigi

2014-01-01

Structured nanoparticles (NPs) with controlled size distribution and novel physicochemical features present fundamental advantages as drug delivery systems with respect to bulk drugs. NPs can transport and release drugs to target sites with high efficiency and limited side effects. Regulatory institutions such as the US Food and Drug Administration (FDA) and the European Commission have pointed out that major limitations to the real application of current nanotechnology lie in the lack of homogeneous, pure and well-characterized NPs, also because of the lack of well-assessed, robust routine methods for their quality control and characterization. Many properties of NPs are size-dependent, thus the particle size distribution (PSD) plays a fundamental role in determining the NP properties. At present, scanning and transmission electron microscopy (SEM, TEM) are among the most used techniques to size characterize NPs. Size-exclusion chromatography (SEC) is also applied to the size separation of complex NP samples. SEC selectivity is, however, quite limited for very large molar mass analytes such as NPs, and interactions with the stationary phase can alter NP morphology. Flow field-flow fractionation (F4) is increasingly used as a mature separation method to size sort and characterize NPs in native conditions. Moreover, the hyphenation with light scattering (LS) methods can enhance the accuracy of size analysis of complex samples. In this paper, the applications of F4-LS to NP analysis used as drug delivery systems for their size analysis, and the study of stability and drug release effects are reviewed. Copyright © 2013 Elsevier B.V. All rights reserved.

Lunar soils grain size catalog

NASA Technical Reports Server (NTRS)

Graf, John C.

1993-01-01

This catalog compiles every available grain size distribution for Apollo surface soils, trench samples, cores, and Luna 24 soils. Original laboratory data are tabled, and cumulative weight distribution curves and histograms are plotted. Standard statistical parameters are calculated using the method of moments. Photos and location comments describe the sample environment and geological setting. This catalog can help researchers describe the geotechnical conditions and site variability of the lunar surface essential to the design of a lunar base.

How bandwidth selection algorithms impact exploratory data analysis using kernel density estimation.

PubMed

Harpole, Jared K; Woods, Carol M; Rodebaugh, Thomas L; Levinson, Cheri A; Lenze, Eric J

2014-09-01

Exploratory data analysis (EDA) can reveal important features of underlying distributions, and these features often have an impact on inferences and conclusions drawn from data. Graphical analysis is central to EDA, and graphical representations of distributions often benefit from smoothing. A viable method of estimating and graphing the underlying density in EDA is kernel density estimation (KDE). This article provides an introduction to KDE and examines alternative methods for specifying the smoothing bandwidth in terms of their ability to recover the true density. We also illustrate the comparison and use of KDE methods with 2 empirical examples. Simulations were carried out in which we compared 8 bandwidth selection methods (Sheather-Jones plug-in [SJDP], normal rule of thumb, Silverman's rule of thumb, least squares cross-validation, biased cross-validation, and 3 adaptive kernel estimators) using 5 true density shapes (standard normal, positively skewed, bimodal, skewed bimodal, and standard lognormal) and 9 sample sizes (15, 25, 50, 75, 100, 250, 500, 1,000, 2,000). Results indicate that, overall, SJDP outperformed all methods. However, for smaller sample sizes (25 to 100) either biased cross-validation or Silverman's rule of thumb was recommended, and for larger sample sizes the adaptive kernel estimator with SJDP was recommended. Information is provided about implementing the recommendations in the R computing language. PsycINFO Database Record (c) 2014 APA, all rights reserved.

A comparison of machine learning methods for classification using simulation with multiple real data examples from mental health studies.

PubMed

Khondoker, Mizanur; Dobson, Richard; Skirrow, Caroline; Simmons, Andrew; Stahl, Daniel

2016-10-01

Recent literature on the comparison of machine learning methods has raised questions about the neutrality, unbiasedness and utility of many comparative studies. Reporting of results on favourable datasets and sampling error in the estimated performance measures based on single samples are thought to be the major sources of bias in such comparisons. Better performance in one or a few instances does not necessarily imply so on an average or on a population level and simulation studies may be a better alternative for objectively comparing the performances of machine learning algorithms. We compare the classification performance of a number of important and widely used machine learning algorithms, namely the Random Forests (RF), Support Vector Machines (SVM), Linear Discriminant Analysis (LDA) and k-Nearest Neighbour (kNN). Using massively parallel processing on high-performance supercomputers, we compare the generalisation errors at various combinations of levels of several factors: number of features, training sample size, biological variation, experimental variation, effect size, replication and correlation between features. For smaller number of correlated features, number of features not exceeding approximately half the sample size, LDA was found to be the method of choice in terms of average generalisation errors as well as stability (precision) of error estimates. SVM (with RBF kernel) outperforms LDA as well as RF and kNN by a clear margin as the feature set gets larger provided the sample size is not too small (at least 20). The performance of kNN also improves as the number of features grows and outplays that of LDA and RF unless the data variability is too high and/or effect sizes are too small. RF was found to outperform only kNN in some instances where the data are more variable and have smaller effect sizes, in which cases it also provide more stable error estimates than kNN and LDA. Applications to a number of real datasets supported the findings from the simulation study. © The Author(s) 2013.

Problems with sampling desert tortoises: A simulation analysis based on field data

USGS Publications Warehouse

Freilich, J.E.; Camp, R.J.; Duda, J.J.; Karl, A.E.

2005-01-01

The desert tortoise (Gopherus agassizii) was listed as a U.S. threatened species in 1990 based largely on population declines inferred from mark-recapture surveys of 2.59-km2 (1-mi2) plots. Since then, several census methods have been proposed and tested, but all methods still pose logistical or statistical difficulties. We conducted computer simulations using actual tortoise location data from 2 1-mi2 plot surveys in southern California, USA, to identify strengths and weaknesses of current sampling strategies. We considered tortoise population estimates based on these plots as "truth" and then tested various sampling methods based on sampling smaller plots or transect lines passing through the mile squares. Data were analyzed using Schnabel's mark-recapture estimate and program CAPTURE. Experimental subsampling with replacement of the 1-mi2 data using 1-km2 and 0.25-km2 plot boundaries produced data sets of smaller plot sizes, which we compared to estimates from the 1-mi 2 plots. We also tested distance sampling by saturating a 1-mi 2 site with computer simulated transect lines, once again evaluating bias in density estimates. Subsampling estimates from 1-km2 plots did not differ significantly from the estimates derived at 1-mi2. The 0.25-km2 subsamples significantly overestimated population sizes, chiefly because too few recaptures were made. Distance sampling simulations were biased 80% of the time and had high coefficient of variation to density ratios. Furthermore, a prospective power analysis suggested limited ability to detect population declines as high as 50%. We concluded that poor performance and bias of both sampling procedures was driven by insufficient sample size, suggesting that all efforts must be directed to increasing numbers found in order to produce reliable results. Our results suggest that present methods may not be capable of accurately estimating desert tortoise populations.

Value of information methods to design a clinical trial in a small population to optimise a health economic utility function.

PubMed

Pearce, Michael; Hee, Siew Wan; Madan, Jason; Posch, Martin; Day, Simon; Miller, Frank; Zohar, Sarah; Stallard, Nigel

2018-02-08

Most confirmatory randomised controlled clinical trials (RCTs) are designed with specified power, usually 80% or 90%, for a hypothesis test conducted at a given significance level, usually 2.5% for a one-sided test. Approval of the experimental treatment by regulatory agencies is then based on the result of such a significance test with other information to balance the risk of adverse events against the benefit of the treatment to future patients. In the setting of a rare disease, recruiting sufficient patients to achieve conventional error rates for clinically reasonable effect sizes may be infeasible, suggesting that the decision-making process should reflect the size of the target population. We considered the use of a decision-theoretic value of information (VOI) method to obtain the optimal sample size and significance level for confirmatory RCTs in a range of settings. We assume the decision maker represents society. For simplicity we assume the primary endpoint to be normally distributed with unknown mean following some normal prior distribution representing information on the anticipated effectiveness of the therapy available before the trial. The method is illustrated by an application in an RCT in haemophilia A. We explicitly specify the utility in terms of improvement in primary outcome and compare this with the costs of treating patients, both financial and in terms of potential harm, during the trial and in the future. The optimal sample size for the clinical trial decreases as the size of the population decreases. For non-zero cost of treating future patients, either monetary or in terms of potential harmful effects, stronger evidence is required for approval as the population size increases, though this is not the case if the costs of treating future patients are ignored. Decision-theoretic VOI methods offer a flexible approach with both type I error rate and power (or equivalently trial sample size) depending on the size of the future population for whom the treatment under investigation is intended. This might be particularly suitable for small populations when there is considerable information about the patient population.

15N in tree rings as a bio-indicator of changing nitrogen cycling in tropical forests: an evaluation at three sites using two sampling methods

PubMed Central

van der Sleen, Peter; Vlam, Mart; Groenendijk, Peter; Anten, Niels P. R.; Bongers, Frans; Bunyavejchewin, Sarayudh; Hietz, Peter; Pons, Thijs L.; Zuidema, Pieter A.

2015-01-01

Anthropogenic nitrogen deposition is currently causing a more than twofold increase of reactive nitrogen input over large areas in the tropics. Elevated 15N abundance (δ15N) in the growth rings of some tropical trees has been hypothesized to reflect an increased leaching of 15N-depleted nitrate from the soil, following anthropogenic nitrogen deposition over the last decades. To find further evidence for altered nitrogen cycling in tropical forests, we measured long-term δ15N values in trees from Bolivia, Cameroon, and Thailand. We used two different sampling methods. In the first, wood samples were taken in a conventional way: from the pith to the bark across the stem of 28 large trees (the “radial” method). In the second, δ15N values were compared across a fixed diameter (the “fixed-diameter” method). We sampled 400 trees that differed widely in size, but measured δ15N in the stem around the same diameter (20 cm dbh) in all trees. As a result, the growth rings formed around this diameter differed in age and allowed a comparison of δ15N values over time with an explicit control for potential size-effects on δ15N values. We found a significant increase of tree-ring δ15N across the stem radius of large trees from Bolivia and Cameroon, but no change in tree-ring δ15N values over time was found in any of the study sites when controlling for tree size. This suggests that radial trends of δ15N values within trees reflect tree ontogeny (size development). However, for the trees from Cameroon and Thailand, a low statistical power in the fixed-diameter method prevents to conclude this with high certainty. For the trees from Bolivia, statistical power in the fixed-diameter method was high, showing that the temporal trend in tree-ring δ15N values in the radial method is primarily caused by tree ontogeny and unlikely by a change in nitrogen cycling. We therefore stress to account for tree size before tree-ring δ15N values can be properly interpreted. PMID:25914707

(15)N in tree rings as a bio-indicator of changing nitrogen cycling in tropical forests: an evaluation at three sites using two sampling methods.

PubMed

van der Sleen, Peter; Vlam, Mart; Groenendijk, Peter; Anten, Niels P R; Bongers, Frans; Bunyavejchewin, Sarayudh; Hietz, Peter; Pons, Thijs L; Zuidema, Pieter A

2015-01-01

Anthropogenic nitrogen deposition is currently causing a more than twofold increase of reactive nitrogen input over large areas in the tropics. Elevated (15)N abundance (δ(15)N) in the growth rings of some tropical trees has been hypothesized to reflect an increased leaching of (15)N-depleted nitrate from the soil, following anthropogenic nitrogen deposition over the last decades. To find further evidence for altered nitrogen cycling in tropical forests, we measured long-term δ(15)N values in trees from Bolivia, Cameroon, and Thailand. We used two different sampling methods. In the first, wood samples were taken in a conventional way: from the pith to the bark across the stem of 28 large trees (the "radial" method). In the second, δ(15)N values were compared across a fixed diameter (the "fixed-diameter" method). We sampled 400 trees that differed widely in size, but measured δ(15)N in the stem around the same diameter (20 cm dbh) in all trees. As a result, the growth rings formed around this diameter differed in age and allowed a comparison of δ(15)N values over time with an explicit control for potential size-effects on δ(15)N values. We found a significant increase of tree-ring δ(15)N across the stem radius of large trees from Bolivia and Cameroon, but no change in tree-ring δ(15)N values over time was found in any of the study sites when controlling for tree size. This suggests that radial trends of δ(15)N values within trees reflect tree ontogeny (size development). However, for the trees from Cameroon and Thailand, a low statistical power in the fixed-diameter method prevents to conclude this with high certainty. For the trees from Bolivia, statistical power in the fixed-diameter method was high, showing that the temporal trend in tree-ring δ(15)N values in the radial method is primarily caused by tree ontogeny and unlikely by a change in nitrogen cycling. We therefore stress to account for tree size before tree-ring δ(15)N values can be properly interpreted.

Mesoporous carbon synthesized from different pore sizes of SBA-15 for high density electrode supercapacitor application

NASA Astrophysics Data System (ADS)

Jamil, Farinaa Md; Sulaiman, Mohd Ali; Ibrahim, Suhaina Mohd; Masrom, Abdul Kadir; Yahya, Muhd Zu Azhan

2017-12-01

A series of mesoporous carbon sample was synthesized using silica template, SBA-15 with two different pore sizes. Impregnation method was applied using glucose as a precursor for converting it into carbon. An appropriate carbonization and silica removal process were carried out to produce a series of mesoporous carbon with different pore sizes and surface areas. Mesoporous carbon sample was then assembled as electrode and its performance was tested using cyclic voltammetry and impedance spectroscopy to study the effect of ion transportation into several pore sizes on electric double layer capacitor (EDLC) system. 6M KOH was used as electrolyte at various scan rates of 10, 20, 30 and 50 mVs-1. The results showed that the pore size of carbon increased as the pore size of template increased and the specific capacitance improved as the increasing of the pore size of carbon.

Development of a magnetic solid-phase extraction coupled with high-performance liquid chromatography method for the analysis of polyaromatic hydrocarbons.

PubMed

Ma, Yan; Xie, Jiawen; Jin, Jing; Wang, Wei; Yao, Zhijian; Zhou, Qing; Li, Aimin; Liang, Ying

2015-07-01

A novel magnetic solid phase extraction coupled with high-performance liquid chromatography method was established to analyze polyaromatic hydrocarbons in environmental water samples. The extraction conditions, including the amount of extraction agent, extraction time, pH and the surface structure of the magnetic extraction agent, were optimized. The results showed that the amount of extraction agent and extraction time significantly influenced the extraction performance. The increase in the specific surface area, the enlargement of pore size, and the reduction of particle size could enhance the extraction performance of the magnetic microsphere. The optimized magnetic extraction agent possessed a high surface area of 1311 m(2) /g, a large pore size of 6-9 nm, and a small particle size of 6-9 μm. The limit of detection for phenanthrene and benzo[g,h,i]perylene in the developed analysis method was 3.2 and 10.5 ng/L, respectively. When applied to river water samples, the spiked recovery of phenanthrene and benzo[g,h,i]perylene ranged from 89.5-98.6% and 82.9-89.1%, respectively. Phenanthrene was detected over a concentration range of 89-117 ng/L in three water samples withdrawn from the midstream of the Huai River, and benzo[g,h,i]perylene was below the detection limit. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Ratios of total suspended solids to suspended sediment concentrations by particle size

USGS Publications Warehouse

Selbig, W.R.; Bannerman, R.T.

2011-01-01

Wet-sieving sand-sized particles from a whole storm-water sample before splitting the sample into laboratory-prepared containers can reduce bias and improve the precision of suspended-sediment concentrations (SSC). Wet-sieving, however, may alter concentrations of total suspended solids (TSS) because the analytical method used to determine TSS may not have included the sediment retained on the sieves. Measuring TSS is still commonly used by environmental managers as a regulatory metric for solids in storm water. For this reason, a new method of correlating concentrations of TSS and SSC by particle size was used to develop a series of correction factors for SSC as a means to estimate TSS. In general, differences between TSS and SSC increased with greater particle size and higher sand content. Median correction factors to SSC ranged from 0.29 for particles larger than 500m to 0.85 for particles measuring from 32 to 63m. Great variability was observed in each fraction-a result of varying amounts of organic matter in the samples. Wide variability in organic content could reduce the transferability of the correction factors. ?? 2011 American Society of Civil Engineers.

Sample Size for Measuring Grammaticality in Preschool Children from Picture-Elicited Language Samples

ERIC Educational Resources Information Center

Eisenberg, Sarita L.; Guo, Ling-Yu

2015-01-01

Purpose: The purpose of this study was to investigate whether a shorter language sample elicited with fewer pictures (i.e., 7) would yield a percent grammatical utterances (PGU) score similar to that computed from a longer language sample elicited with 15 pictures for 3-year-old children. Method: Language samples were elicited by asking forty…

Noninvasive genetics provides insights into the population size and genetic diversity of an Amur tiger population in China.

PubMed

Wang, Dan; Hu, Yibo; Ma, Tianxiao; Nie, Yonggang; Xie, Yan; Wei, Fuwen

2016-01-01

Understanding population size and genetic diversity is critical for effective conservation of endangered species. The Amur tiger (Panthera tigris altaica) is the largest felid and a flagship species for wildlife conservation. Due to habitat loss and human activities, available habitat and population size are continuously shrinking. However, little is known about the true population size and genetic diversity of wild tiger populations in China. In this study, we collected 55 fecal samples and 1 hair sample to investigate the population size and genetic diversity of wild Amur tigers in Hunchun National Nature Reserve, Jilin Province, China. From the samples, we determined that 23 fecal samples and 1 hair sample were from 7 Amur tigers: 2 males, 4 females and 1 individual of unknown sex. Interestingly, 2 fecal samples that were presumed to be from tigers were from Amur leopards, highlighting the significant advantages of noninvasive genetics over traditional methods in studying rare and elusive animals. Analyses from this sample suggested that the genetic diversity of wild Amur tigers is much lower than that of Bengal tigers, consistent with previous findings. Furthermore, the genetic diversity of this Hunchun population in China was lower than that of the adjoining subpopulation in southwest Primorye Russia, likely due to sampling bias. Considering the small population size and relatively low genetic diversity, it is urgent to protect this endangered local subpopulation in China. © 2015 International Society of Zoological Sciences, Institute of Zoology/Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.

Integrating SANS and fluid-invasion methods to characterize pore structure of typical American shale oil reservoirs.

PubMed

Zhao, Jianhua; Jin, Zhijun; Hu, Qinhong; Jin, Zhenkui; Barber, Troy J; Zhang, Yuxiang; Bleuel, Markus

2017-11-13

An integration of small-angle neutron scattering (SANS), low-pressure N 2 physisorption (LPNP), and mercury injection capillary pressure (MICP) methods was employed to study the pore structure of four oil shale samples from leading Niobrara, Wolfcamp, Bakken, and Utica Formations in USA. Porosity values obtained from SANS are higher than those from two fluid-invasion methods, due to the ability of neutrons to probe pore spaces inaccessible to N 2 and mercury. However, SANS and LPNP methods exhibit a similar pore-size distribution, and both methods (in measuring total pore volume) show different results of porosity and pore-size distribution obtained from the MICP method (quantifying pore throats). Multi-scale (five pore-diameter intervals) inaccessible porosity to N 2 was determined using SANS and LPNP data. Overall, a large value of inaccessible porosity occurs at pore diameters <10 nm, which we attribute to low connectivity of organic matter-hosted and clay-associated pores in these shales. While each method probes a unique aspect of complex pore structure of shale, the discrepancy between pore structure results from different methods is explained with respect to their difference in measurable ranges of pore diameter, pore space, pore type, sample size and associated pore connectivity, as well as theoretical base and interpretation.

Study of vesicle size distribution dependence on pH value based on nanopore resistive pulse method

NASA Astrophysics Data System (ADS)

Lin, Yuqing; Rudzevich, Yauheni; Wearne, Adam; Lumpkin, Daniel; Morales, Joselyn; Nemec, Kathleen; Tatulian, Suren; Lupan, Oleg; Chow, Lee

2013-03-01

Vesicles are low-micron to sub-micron spheres formed by a lipid bilayer shell and serve as potential vehicles for drug delivery. The size of vesicle is proposed to be one of the instrumental variables affecting delivery efficiency since the size is correlated to factors like circulation and residence time in blood, the rate for cell endocytosis, and efficiency in cell targeting. In this work, we demonstrate accessible and reliable detection and size distribution measurement employing a glass nanopore device based on the resistive pulse method. This novel method enables us to investigate the size distribution dependence of pH difference across the membrane of vesicles with very small sample volume and rapid speed. This provides useful information for optimizing the efficiency of drug delivery in a pH sensitive environment.

Power and sample-size estimation for microbiome studies using pairwise distances and PERMANOVA

PubMed Central

Kelly, Brendan J.; Gross, Robert; Bittinger, Kyle; Sherrill-Mix, Scott; Lewis, James D.; Collman, Ronald G.; Bushman, Frederic D.; Li, Hongzhe

2015-01-01

Motivation: The variation in community composition between microbiome samples, termed beta diversity, can be measured by pairwise distance based on either presence–absence or quantitative species abundance data. PERMANOVA, a permutation-based extension of multivariate analysis of variance to a matrix of pairwise distances, partitions within-group and between-group distances to permit assessment of the effect of an exposure or intervention (grouping factor) upon the sampled microbiome. Within-group distance and exposure/intervention effect size must be accurately modeled to estimate statistical power for a microbiome study that will be analyzed with pairwise distances and PERMANOVA. Results: We present a framework for PERMANOVA power estimation tailored to marker-gene microbiome studies that will be analyzed by pairwise distances, which includes: (i) a novel method for distance matrix simulation that permits modeling of within-group pairwise distances according to pre-specified population parameters; (ii) a method to incorporate effects of different sizes within the simulated distance matrix; (iii) a simulation-based method for estimating PERMANOVA power from simulated distance matrices; and (iv) an R statistical software package that implements the above. Matrices of pairwise distances can be efficiently simulated to satisfy the triangle inequality and incorporate group-level effects, which are quantified by the adjusted coefficient of determination, omega-squared (ω2). From simulated distance matrices, available PERMANOVA power or necessary sample size can be estimated for a planned microbiome study. Availability and implementation: http://github.com/brendankelly/micropower. Contact: brendank@mail.med.upenn.edu or hongzhe@upenn.edu PMID:25819674

Concentration comparison of selected constituents between groundwater samples collected within the Missouri River alluvial aquifer using purge and pump and grab-sampling methods, near the city of Independence, Missouri, 2013

USGS Publications Warehouse

Krempa, Heather M.

2015-10-29

Relative percent differences between methods were greater than 10 percent for most analyzed trace elements. Barium, cobalt, manganese, and boron had concentrations that were significantly different between sampling methods. Barium, molybdenum, boron, and uranium method concentrations indicate a close association between pump and grab samples based on bivariate plots and simple linear regressions. Grab sample concentrations were generally larger than pump concentrations for these elements and may be because of using a larger pore sized filter for grab samples. Analysis of zinc blank samples suggests zinc contamination in filtered grab samples. Variations of analyzed trace elements between pump and grab samples could reduce the ability to monitor temporal changes and potential groundwater contamination threats. The degree of precision necessary for monitoring potential groundwater threats and application objectives need to be considered when determining acceptable variation amounts.

A predictive approach to selecting the size of a clinical trial, based on subjective clinical opinion.

PubMed

Spiegelhalter, D J; Freedman, L S

1986-01-01

The 'textbook' approach to determining sample size in a clinical trial has some fundamental weaknesses which we discuss. We describe a new predictive method which takes account of prior clinical opinion about the treatment difference. The method adopts the point of clinical equivalence (determined by interviewing the clinical participants) as the null hypothesis. Decision rules at the end of the study are based on whether the interval estimate of the treatment difference (classical or Bayesian) includes the null hypothesis. The prior distribution is used to predict the probabilities of making the decisions to use one or other treatment or to reserve final judgement. It is recommended that sample size be chosen to control the predicted probability of the last of these decisions. An example is given from a multi-centre trial of superficial bladder cancer.

Measurements of Regolith Simulant Thermal Conductivity Under Asteroid and Mars Surface Conditions

NASA Astrophysics Data System (ADS)

Ryan, A. J.; Christensen, P. R.

2017-12-01

Laboratory measurements have been necessary to interpret thermal data of planetary surfaces for decades. We present a novel radiometric laboratory method to determine temperature-dependent thermal conductivity of complex regolith simulants under rough to high vacuum and across a wide range of temperatures. This method relies on radiometric temperature measurements instead of contact measurements, eliminating the need to disturb the sample with thermal probes. We intend to determine the conductivity of grains that are up to 2 cm in diameter and to parameterize the effects of angularity, sorting, layering, composition, and eventually cementation. We present the experimental data and model results for a suite of samples that were selected to isolate and address regolith physical parameters that affect bulk conductivity. Spherical glass beads of various sizes were used to measure the effect of size frequency distribution. Spherical beads of polypropylene and well-rounded quartz sand have respectively lower and higher solid phase thermal conductivities than the glass beads and thus provide the opportunity to test the sensitivity of bulk conductivity to differences in solid phase conductivity. Gas pressure in our asteroid experimental chambers is held at 10^-6 torr, which is sufficient to negate gas thermal conduction in even our coarsest of samples. On Mars, the atmospheric pressure is such that the mean free path of the gas molecules is comparable to the pore size for many regolith particulates. Thus, subtle variations in pore size and/or atmospheric pressure can produce large changes in bulk regolith conductivity. For each sample measured in our martian environmental chamber, we repeat thermal measurement runs at multiple pressures to observe this behavior. Finally, we present conductivity measurements of angular basaltic simulant that is physically analogous to sand and gravel that may be present on Bennu. This simulant was used for OSIRIS-REx TAGSAM Sample Return Arm engineering tests. We measure the original size frequency distribution as well as several sorted size fractions. These results will support the efforts of the OSIRIS-REx team in selecting a site on asteroid Bennu that is safe for the spacecraft and meets grain size requirements for sampling.

Growth of group II-VI semiconductor quantum dots with strong quantum confinement and low size dispersion

NASA Astrophysics Data System (ADS)

Pandey, Praveen K.; Sharma, Kriti; Nagpal, Swati; Bhatnagar, P. K.; Mathur, P. C.

2003-11-01

CdTe quantum dots embedded in glass matrix are grown using two-step annealing method. The results for the optical transmission characterization are analysed and compared with the results obtained from CdTe quantum dots grown using conventional single-step annealing method. A theoretical model for the absorption spectra is used to quantitatively estimate the size dispersion in the two cases. In the present work, it is established that the quantum dots grown using two-step annealing method have stronger quantum confinement, reduced size dispersion and higher volume ratio as compared to the single-step annealed samples. (

Suitability of river delta sediment as proppant, Missouri and Niobrara Rivers, Nebraska and South Dakota, 2015

USGS Publications Warehouse

Zelt, Ronald B.; Hobza, Christopher M.; Burton, Bethany L.; Schaepe, Nathaniel J.; Piatak, Nadine

2017-11-16

Sediment management is a challenge faced by reservoir managers who have several potential options, including dredging, for mitigation of storage capacity lost to sedimentation. As sediment is removed from reservoir storage, potential use of the sediment for socioeconomic or ecological benefit could potentially defray some costs of its removal. Rivers that transport a sandy sediment load will deposit the sand load along a reservoir-headwaters reach where the current of the river slackens progressively as its bed approaches and then descends below the reservoir water level. Given a rare combination of factors, a reservoir deposit of alluvial sand has potential to be suitable for use as proppant for hydraulic fracturing in unconventional oil and gas development. In 2015, the U.S. Geological Survey began a program of researching potential sources of proppant sand from reservoirs, with an initial focus on the Missouri River subbasins that receive sand loads from the Nebraska Sand Hills. This report documents the methods and results of assessments of the suitability of river delta sediment as proppant for a pilot study area in the delta headwaters of Lewis and Clark Lake, Nebraska and South Dakota. Results from surface-geophysical surveys of electrical resistivity guided borings to collect 3.7-meter long cores at 25 sites on delta sandbars using the direct-push method to recover duplicate, 3.8-centimeter-diameter cores in April 2015. In addition, the U.S. Geological Survey collected samples of upstream sand sources in the lower Niobrara River valley.At the laboratory, samples were dried, weighed, washed, dried, and weighed again. Exploratory analysis of natural sand for determining its suitability as a proppant involved application of a modified subset of the standard protocols known as American Petroleum Institute (API) Recommended Practice (RP) 19C. The RP19C methods were not intended for exploration-stage evaluation of raw materials. Results for the washed samples are not directly applicable to evaluations of suitability for use as fracture sand because, except for particle-size distribution, the API-recommended practices for assessing proppant properties (sphericity, roundness, bulk density, and crush resistance) require testing of specific proppant size classes. An optical imaging particle-size analyzer was used to make measurements of particle-size distribution and particle shape. Measured samples were sieved to separate the dominant-size fraction, and the separated subsample was further tested for roundness, sphericity, bulk density, and crush resistance.For the bulk washed samples collected from the Missouri River delta, the geometric mean size averaged 0.27 millimeters (mm), 80 percent of the samples were predominantly sand in the API 40/70 size class, and 17 percent were predominantly sand in the API 70/140 size class. Distributions of geometric mean size among the four sandbar complexes were similar, but samples collected from sandbar complex B were slightly coarser sand than those from the other three complexes. The average geometric mean sizes among the four sandbar complexes ranged only from 0.26 to 0.30 mm. For 22 main-stem sampling locations along the lower Niobrara River, geometric mean size averaged 0.26 mm, an average of 61 percent was sand in the API 40/70 size class, and 28 percent was sand in the API 70/140 size class. Average composition for lower Niobrara River samples was 48 percent medium sand, 37 percent fine sand, and about 7 percent each very fine sand and coarse sand fractions. On average, samples were moderately well sorted.Particle shape and strength were assessed for the dominant-size class of each sample. For proppant strength, crush resistance was tested at a predetermined level of stress (34.5 megapascals [MPa], or 5,000 pounds-force per square inch). To meet the API minimum requirement for proppant, after the crush test not more than 10 percent of the tested sample should be finer than the precrush dominant-size class. For particle shape, all samples surpassed the recommended minimum criteria for sphericity and roundness, with most samples being well-rounded. For proppant strength, of 57 crush-resistance tested Missouri River delta samples of 40/70-sized sand, 23 (40 percent) were interpreted as meeting the minimum criterion at 34.5 MPa, or 5,000 pounds-force per square inch. Of 12 tested samples of 70/140-sized sand, 9 (75 percent) of the Missouri River delta samples had less than 10 percent fines by volume following crush testing, achieving the minimum criterion at 34.5 MPa. Crush resistance for delta samples was strongest at sandbar complex A, where 67 percent of tested samples met the 10-percent fines criterion at the 34.5-MPa threshold. This frequency was higher than was indicated by samples from sandbar complexes B, C, and D that had rates of 50, 46, and 42 percent, respectively. The group of sandbar complex A samples also contained the largest percentages of samples dominated by the API 70/140 size class, which overall had a higher percentage of samples meeting the minimum criterion compared to samples dominated by coarser size classes; however, samples from sandbar complex A that had the API 40/70 size class tested also had a higher rate for meeting the minimum criterion (57 percent) than did samples from sandbar complexes B, C, and D (50, 43, and 40 percent, respectively). For samples collected along the lower Niobrara River, of the 25 tested samples of 40/70-sized sand, 9 samples passed the API minimum criterion at 34.5 MPa, but only 3 samples passed the more-stringent criterion of 8 percent postcrush fines. All four tested samples of 70/140 sand passed the minimum criterion at 34.5 MPa, with postcrush fines percentage of at most 4.1 percent.For two reaches of the lower Niobrara River, where hydraulic sorting was energized artificially by the hydraulic head drop at and immediately downstream from Spencer Dam, suitability of channel deposits for potential use as fracture sand was confirmed by test results. All reach A washed samples were well-rounded and had sphericity scores above 0.65, and samples for 80 percent of sampled locations met the crush-resistance criterion at the 34.5-MPa stress level. A conservative lower-bound estimate of sand volume in the reach A deposits was about 86,000 cubic meters. All reach B samples were well-rounded but sphericity averaged 0.63, a little less than the average for upstream reaches A and SP. All four samples tested passed the crush-resistance test at 34.5 MPa. Of three reach B sandbars, two had no more than 3 percent fines after the crush test, surpassing more stringent criteria for crush resistance that accept a maximum of 6 percent fines following the crush test for the API 70/140 size class.Relative to the crush-resistance test results for the API 40/70 size fraction of two samples of mine output from Loup River settling-basin dredge spoils near Genoa, Nebr., four of five reach A sample locations compared favorably. The four samples had increases in fines composition of 1.6–5.9 percentage points, whereas fines in the two mine-output samples increased by an average 6.8 percentage points.

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

PubMed

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

2015-10-01

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

Standard-less analysis of Zircaloy clad samples by an instrumental neutron activation method

NASA Astrophysics Data System (ADS)

Acharya, R.; Nair, A. G. C.; Reddy, A. V. R.; Goswami, A.

2004-03-01

A non-destructive method for analysis of irregular shape and size samples of Zircaloy has been developed using the recently standardized k0-based internal mono standard instrumental neutron activation analysis (INAA). The samples of Zircaloy-2 and -4 tubes, used as fuel cladding in Indian boiling water reactors (BWR) and pressurized heavy water reactors (PHWR), respectively, have been analyzed. Samples weighing in the range of a few tens of grams were irradiated in the thermal column of Apsara reactor to minimize neutron flux perturbations and high radiation dose. The method utilizes in situ relative detection efficiency using the γ-rays of selected activation products in the sample for overcoming γ-ray self-attenuation. Since the major and minor constituents (Zr, Sn, Fe, Cr and/or Ni) in these samples were amenable to NAA, the absolute concentrations of all the elements were determined using mass balance instead of using the concentration of the internal mono standard. Concentrations were also determined in a smaller size Zircaloy-4 sample by irradiating in the core position of the reactor to validate the present methodology. The results were compared with literature specifications and were found to be satisfactory. Values of sensitivities and detection limits have been evaluated for the elements analyzed.

Pore-scale simulations of drainage in granular materials: Finite size effects and the representative elementary volume

NASA Astrophysics Data System (ADS)

Yuan, Chao; Chareyre, Bruno; Darve, Félix

2016-09-01

A pore-scale model is introduced for two-phase flow in dense packings of polydisperse spheres. The model is developed as a component of a more general hydromechanical coupling framework based on the discrete element method, which will be elaborated in future papers and will apply to various processes of interest in soil science, in geomechanics and in oil and gas production. Here the emphasis is on the generation of a network of pores mapping the void space between spherical grains, and the definition of local criteria governing the primary drainage process. The pore space is decomposed by Regular Triangulation, from which a set of pores connected by throats are identified. A local entry capillary pressure is evaluated for each throat, based on the balance of capillary pressure and surface tension at equilibrium. The model reflects the possible entrapment of disconnected patches of the receding wetting phase. It is validated by a comparison with drainage experiments. In the last part of the paper, a series of simulations are reported to illustrate size and boundary effects, key questions when studying small samples made of spherical particles be it in simulations or experiments. Repeated tests on samples of different sizes give evolution of water content which are not only scattered but also strongly biased for small sample sizes. More than 20,000 spheres are needed to reduce the bias on saturation below 0.02. Additional statistics are generated by subsampling a large sample of 64,000 spheres. They suggest that the minimal sampling volume for evaluating saturation is one hundred times greater that the sampling volume needed for measuring porosity with the same accuracy. This requirement in terms of sample size induces a need for efficient computer codes. The method described herein has a low algorithmic complexity in order to satisfy this requirement. It will be well suited to further developments toward coupled flow-deformation problems in which evolution of the microstructure require frequent updates of the pore network.

Polymorphism in magic-sized Au144(SR)60 clusters

DOE PAGES

Jensen, Kirsten M. O.; Juhas, Pavol; Tofanelli, Marcus A.; ...

2016-06-14

Ultra-small, magic-sized metal nanoclusters represent an important new class of materials with properties between molecules and particles. However, their small size challenges the conventional methods for structure characterization. We present the structure of ultra-stable Au144(SR)60 magic-sized nanoclusters obtained from atomic pair distribution function analysis of X-ray powder diffraction data. Our study reveals structural polymorphism in these archetypal nanoclusters. Additionally, in order to confirm the theoretically predicted icosahedral-cored cluster, we also find samples with a truncated decahedral core structure, with some samples exhibiting a coexistence of both cluster structures. Although the clusters are monodisperse in size, structural diversity is apparent. Finally,more » the discovery of polymorphism may open up a new dimension in nanoscale engineering.« less

XRD analysis of undoped and Fe doped TiO{sub 2} nanoparticles by Williamson Hall method

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

Bharti, Bandna; Barman, P. B.; Kumar, Rajesh, E-mail: rajesh.kumar@juit.ac.in

2015-08-28

Undoped and Fe doped titanium dioxide (TiO{sub 2}) nanoparticles were synthesized by sol-gel method at room temperature. The synthesized samples were annealed at 500°C. For structural analysis, the prepared samples were characterized by X-ray diffraction (XRD). The crystallite size of TiO{sub 2} and Fe doped TiO{sub 2} nanoparticles were calculated by Scherer’s formula, and was found to be 15 nm and 11 nm, respectively. Reduction in crystallite size of TiO{sub 2} with Fe doping was observed. The anatase phase of Fe-doped TiO{sub 2} nanoparticles was also confirmed by X-ray diffraction. By using Williamson-Hall method, lattice strain and crystallite size weremore » also calculated. Williamson–Hall plot indicates the presence of compressive strain for TiO{sub 2} and tensile strain for Fe-TiO{sub 2} nanoparticles annealed at 500°C.« less

Efficient Bayesian mixed model analysis increases association power in large cohorts

PubMed Central

Loh, Po-Ru; Tucker, George; Bulik-Sullivan, Brendan K; Vilhjálmsson, Bjarni J; Finucane, Hilary K; Salem, Rany M; Chasman, Daniel I; Ridker, Paul M; Neale, Benjamin M; Berger, Bonnie; Patterson, Nick; Price, Alkes L

2014-01-01

Linear mixed models are a powerful statistical tool for identifying genetic associations and avoiding confounding. However, existing methods are computationally intractable in large cohorts, and may not optimize power. All existing methods require time cost O(MN2) (where N = #samples and M = #SNPs) and implicitly assume an infinitesimal genetic architecture in which effect sizes are normally distributed, which can limit power. Here, we present a far more efficient mixed model association method, BOLT-LMM, which requires only a small number of O(MN)-time iterations and increases power by modeling more realistic, non-infinitesimal genetic architectures via a Bayesian mixture prior on marker effect sizes. We applied BOLT-LMM to nine quantitative traits in 23,294 samples from the Women’s Genome Health Study (WGHS) and observed significant increases in power, consistent with simulations. Theory and simulations show that the boost in power increases with cohort size, making BOLT-LMM appealing for GWAS in large cohorts. PMID:25642633

The Effect of Game-Assisted Mathematics Education on Academic Achievement in Turkey: A Meta-Analysis Study

ERIC Educational Resources Information Center

Turgut, Sedat; Temur, Özlem Dogan

2017-01-01

In this research, the effects of using game in mathematics teaching process on academic achievement in Turkey were examined by metaanalysis method. For this purpose, the average effect size value and the average effect size values of the moderator variables (education level, the field of education, game type, implementation period and sample size)…

Submicrometer Particle Sizing by Multiangle Light Scattering following Fractionation

PubMed

Wyatt

1998-01-01

The acid test for any particle sizing technique is its ability to determine the differential number fraction size distribution of a simple, well-defined sample. The very best characterized polystyrene latex sphere standards have been measured extensively using transmission electron microscope (TEM) images of a large subpopulation of such samples or by means of the electrostatic classification method as refined at the National Institute of Standards and Technology. The great success, in the past decade, of on-line multiangle light scattering (MALS) detection combined with size exclusion chromatography for the measurement of polymer mass and size distributions suggested, in the early 1990s, that a similar attack for particle characterization might prove useful as well. At that time, fractionation of particles was achievable by capillary hydrodynamic chromatography (CHDF) and field flow fractionation (FFF) methods. The latter has proven most useful when combined with MALS to provide accurate differential number fraction size distributions for a broad range of particle classes. The MALS/FFF combination provides unique advantages and precision relative to FFF, photon correlation spectroscopy, and CHDF techniques used alone. For many classes of particles, resolution of the MALS/FFF combination far exceeds that of TEM measurements. Copyright 1998 Academic Press. Copyright 1998Academic Press

The Statistical Power of Planned Comparisons.

ERIC Educational Resources Information Center

Benton, Roberta L.

Basic principles underlying statistical power are examined; and issues pertaining to effect size, sample size, error variance, and significance level are highlighted via the use of specific hypothetical examples. Analysis of variance (ANOVA) and related methods remain popular, although other procedures sometimes have more statistical power against…

Measuring the molecular dimensions of wine tannins: comparison of small-angle X-ray scattering, gel-permeation chromatography and mean degree of polymerization.

PubMed

McRae, Jacqui M; Kirby, Nigel; Mertens, Haydyn D T; Kassara, Stella; Smith, Paul A

2014-07-23

The molecular size of wine tannins can influence astringency, and yet it has been unclear as to whether the standard methods for determining average tannin molecular weight (MW), including gel-permeation chromatography (GPC) and depolymerization reactions, are actually related to the size of the tannin in wine-like conditions. Small-angle X-ray scattering (SAXS) was therefore used to determine the molecular sizes and corresponding MWs of wine tannin samples from 3 and 7 year old Cabernet Sauvignon wine in a variety of wine-like matrixes: 5-15% and 100% ethanol; 0-200 mM NaCl and pH 3.0-4.0, and compared to those measured using the standard methods. The SAXS results indicated that the tannin samples from the older wine were larger than those of the younger wine and that wine composition did not greatly impact on tannin molecular size. The average tannin MWs as determined by GPC correlated strongly with the SAXS results, suggesting that this method does give a good indication of tannin molecular size in wine-like conditions. The MW as determined from the depolymerization reactions did not correlate as strongly with the SAXS results. To our knowledge, SAXS measurements have not previously been attempted for wine tannins.

Novel Technology for Enrichment of Biomolecules from Cell-Free Body Fluids and Subsequent DNA Sizing.

PubMed

Patel, Vipulkumar; Celec, Peter; Grunt, Magdalena; Schwarzenbach, Heidi; Jenneckens, Ingo; Hillebrand, Timo

2016-01-01

Circulating cell-free DNA (ccfDNA) is a promising diagnostic tool and its size fractionation is of interest. However, kits for isolation of ccfDNA available on the market are designed for small volumes hence processing large sample volumes is laborious. We have tested a new method that enables enrichment of ccfDNA from large volumes of plasma and subsequently allows size-fractionation of isolated ccfDNA into two fractions with individually established cut-off levels of ccfDNA length. This method allows isolation of low-abundant DNA as well as separation of long and short DNA molecules. This procedure may be important e.g., in prenatal diagnostics and cancer research that have been already confirmed by our primary experiments. Here, we report the results of selective separation of 200- and 500-bp long synthetic DNA fragments spiked in plasma samples. Furthermore, we size-fractionated ccfDNA from the plasma of pregnant women and verified the prevalence of fetal ccfDNA in all fractions.

Six dimensional X-ray Tensor Tomography with a compact laboratory setup

NASA Astrophysics Data System (ADS)

Sharma, Y.; Wieczorek, M.; Schaff, F.; Seyyedi, S.; Prade, F.; Pfeiffer, F.; Lasser, T.

2016-09-01

Attenuation based X-ray micro computed tomography (XCT) provides three-dimensional images with micrometer resolution. However, there is a trade-off between the smallest size of the structures that can be resolved and the measurable sample size. In this letter, we present an imaging method using a compact laboratory setup that reveals information about micrometer-sized structures within samples that are several orders of magnitudes larger. We combine the anisotropic dark-field signal obtained in a grating interferometer and advanced tomographic reconstruction methods to reconstruct a six dimensional scattering tensor at every spatial location in three dimensions. The scattering tensor, thus obtained, encodes information about the orientation of micron-sized structures such as fibres in composite materials or dentinal tubules in human teeth. The sparse acquisition schemes presented in this letter enable the measurement of the full scattering tensor at every spatial location and can be easily incorporated in a practical, commercially feasible laboratory setup using conventional X-ray tubes, thus allowing for widespread industrial applications.

Minimal-assumption inference from population-genomic data

NASA Astrophysics Data System (ADS)

Weissman, Daniel; Hallatschek, Oskar

Samples of multiple complete genome sequences contain vast amounts of information about the evolutionary history of populations, much of it in the associations among polymorphisms at different loci. Current methods that take advantage of this linkage information rely on models of recombination and coalescence, limiting the sample sizes and populations that they can analyze. We introduce a method, Minimal-Assumption Genomic Inference of Coalescence (MAGIC), that reconstructs key features of the evolutionary history, including the distribution of coalescence times, by integrating information across genomic length scales without using an explicit model of recombination, demography or selection. Using simulated data, we show that MAGIC's performance is comparable to PSMC' on single diploid samples generated with standard coalescent and recombination models. More importantly, MAGIC can also analyze arbitrarily large samples and is robust to changes in the coalescent and recombination processes. Using MAGIC, we show that the inferred coalescence time histories of samples of multiple human genomes exhibit inconsistencies with a description in terms of an effective population size based on single-genome data.

Influences of Co doping on the structural and optical properties of ZnO nanostructured

NASA Astrophysics Data System (ADS)

Majeed Khan, M. A.; Wasi Khan, M.; Alhoshan, Mansour; Alsalhi, M. S.; Aldwayyan, A. S.

2010-07-01

Pure and Co-doped ZnO nanostructured samples have been synthesized by a chemical route. We have studied the structural and optical properties of the samples by using X-ray diffraction (XRD), field-emission scanning electron microscopy (FESEM), field-emission transmission electron microscope (FETEM), energy-dispersive X-ray (EDX) analysis and UV-VIS spectroscopy. The XRD patterns show that all the samples are hexagonal wurtzite structures. Changes in crystallite size due to mechanical activation were also determined from X-ray measurements. These results were correlated with changes in particle size followed by SEM and TEM. The average crystallite sizes obtained from XRD were between 20 to 25 nm. The TEM images showed the average particle size of undoped ZnO nanostructure was about 20 nm whereas the smallest average grain size at 3% Co was about 15 nm. Optical parameters such as absorption coefficient ( α), energy band gap ( E g ), the refractive index ( n), and dielectric constants ( σ) have been determined using different methods.

A Review and Comparison of Methods for Recreating Individual Patient Data from Published Kaplan-Meier Survival Curves for Economic Evaluations: A Simulation Study

PubMed Central

Wan, Xiaomin; Peng, Liubao; Li, Yuanjian

2015-01-01

Background In general, the individual patient-level data (IPD) collected in clinical trials are not available to independent researchers to conduct economic evaluations; researchers only have access to published survival curves and summary statistics. Thus, methods that use published survival curves and summary statistics to reproduce statistics for economic evaluations are essential. Four methods have been identified: two traditional methods 1) least squares method, 2) graphical method; and two recently proposed methods by 3) Hoyle and Henley, 4) Guyot et al. The four methods were first individually reviewed and subsequently assessed regarding their abilities to estimate mean survival through a simulation study. Methods A number of different scenarios were developed that comprised combinations of various sample sizes, censoring rates and parametric survival distributions. One thousand simulated survival datasets were generated for each scenario, and all methods were applied to actual IPD. The uncertainty in the estimate of mean survival time was also captured. Results All methods provided accurate estimates of the mean survival time when the sample size was 500 and a Weibull distribution was used. When the sample size was 100 and the Weibull distribution was used, the Guyot et al. method was almost as accurate as the Hoyle and Henley method; however, more biases were identified in the traditional methods. When a lognormal distribution was used, the Guyot et al. method generated noticeably less bias and a more accurate uncertainty compared with the Hoyle and Henley method. Conclusions The traditional methods should not be preferred because of their remarkable overestimation. When the Weibull distribution was used for a fitted model, the Guyot et al. method was almost as accurate as the Hoyle and Henley method. However, if the lognormal distribution was used, the Guyot et al. method was less biased compared with the Hoyle and Henley method. PMID:25803659

Analysis of hard coal quality for narrow size fraction under 20 mm

NASA Astrophysics Data System (ADS)

Niedoba, Tomasz; Pięta, Paulina

2018-01-01

The paper presents the results of an analysis of hard coal quality diversion in narrow size fraction by using taxonomic methods. Raw material samples were collected in selected mines of Upper Silesian Industrial Region and they were classified according to the Polish classification as types 31, 34.2 and 35. Then, each size fraction was characterized in terms of the following properties: density, ash content, calorific content, volatile content, total sulfur content and analytical moisture. As a result of the analysis it can be stated that the best quality in the entire range of the tested size fractions was the 34.2 coking coal type. At the same time, in terms of price parameters, high quality of raw material characterised the following size fractions: 0-6.3 mm of 31 energetic coal type and 0-3.15 mm of 35 coking coal type. The methods of grouping (Ward's method) and agglomeration (k-means method) have shown that the size fraction below 10 mm was characterized by higher quality in all the analyzed hard coal types. However, the selected taxonomic methods do not make it possible to identify individual size fraction or hard coal types based on chosen parameters.

Modified Toxicity Probability Interval Design: A Safer and More Reliable Method Than the 3 + 3 Design for Practical Phase I Trials

PubMed Central

Ji, Yuan; Wang, Sue-Jane

2013-01-01

The 3 + 3 design is the most common choice among clinicians for phase I dose-escalation oncology trials. In recent reviews, more than 95% of phase I trials have been based on the 3 + 3 design. Given that it is intuitive and its implementation does not require a computer program, clinicians can conduct 3 + 3 dose escalations in practice with virtually no logistic cost, and trial protocols based on the 3 + 3 design pass institutional review board and biostatistics reviews quickly. However, the performance of the 3 + 3 design has rarely been compared with model-based designs in simulation studies with matched sample sizes. In the vast majority of statistical literature, the 3 + 3 design has been shown to be inferior in identifying true maximum-tolerated doses (MTDs), although the sample size required by the 3 + 3 design is often orders-of-magnitude smaller than model-based designs. In this article, through comparative simulation studies with matched sample sizes, we demonstrate that the 3 + 3 design has higher risks of exposing patients to toxic doses above the MTD than the modified toxicity probability interval (mTPI) design, a newly developed adaptive method. In addition, compared with the mTPI design, the 3 + 3 design does not yield higher probabilities in identifying the correct MTD, even when the sample size is matched. Given that the mTPI design is equally transparent, costless to implement with free software, and more flexible in practical situations, we highly encourage its adoption in early dose-escalation studies whenever the 3 + 3 design is also considered. We provide free software to allow direct comparisons of the 3 + 3 design with other model-based designs in simulation studies with matched sample sizes. PMID:23569307

Classifier performance prediction for computer-aided diagnosis using a limited dataset.

PubMed

Sahiner, Berkman; Chan, Heang-Ping; Hadjiiski, Lubomir

2008-04-01

In a practical classifier design problem, the true population is generally unknown and the available sample is finite-sized. A common approach is to use a resampling technique to estimate the performance of the classifier that will be trained with the available sample. We conducted a Monte Carlo simulation study to compare the ability of the different resampling techniques in training the classifier and predicting its performance under the constraint of a finite-sized sample. The true population for the two classes was assumed to be multivariate normal distributions with known covariance matrices. Finite sets of sample vectors were drawn from the population. The true performance of the classifier is defined as the area under the receiver operating characteristic curve (AUC) when the classifier designed with the specific sample is applied to the true population. We investigated methods based on the Fukunaga-Hayes and the leave-one-out techniques, as well as three different types of bootstrap methods, namely, the ordinary, 0.632, and 0.632+ bootstrap. The Fisher's linear discriminant analysis was used as the classifier. The dimensionality of the feature space was varied from 3 to 15. The sample size n2 from the positive class was varied between 25 and 60, while the number of cases from the negative class was either equal to n2 or 3n2. Each experiment was performed with an independent dataset randomly drawn from the true population. Using a total of 1000 experiments for each simulation condition, we compared the bias, the variance, and the root-mean-squared error (RMSE) of the AUC estimated using the different resampling techniques relative to the true AUC (obtained from training on a finite dataset and testing on the population). Our results indicated that, under the study conditions, there can be a large difference in the RMSE obtained using different resampling methods, especially when the feature space dimensionality is relatively large and the sample size is small. Under this type of conditions, the 0.632 and 0.632+ bootstrap methods have the lowest RMSE, indicating that the difference between the estimated and the true performances obtained using the 0.632 and 0.632+ bootstrap will be statistically smaller than those obtained using the other three resampling methods. Of the three bootstrap methods, the 0.632+ bootstrap provides the lowest bias. Although this investigation is performed under some specific conditions, it reveals important trends for the problem of classifier performance prediction under the constraint of a limited dataset.

“Nanofiltration” Enabled by Super-Absorbent Polymer Beads for Concentrating Microorganisms in Water Samples

NASA Astrophysics Data System (ADS)

Xie, Xing; Bahnemann, Janina; Wang, Siwen; Yang, Yang; Hoffmann, Michael R.

2016-02-01

Detection and quantification of pathogens in water is critical for the protection of human health and for drinking water safety and security. When the pathogen concentrations are low, large sample volumes (several liters) are needed to achieve reliable quantitative results. However, most microbial identification methods utilize relatively small sample volumes. As a consequence, a concentration step is often required to detect pathogens in natural waters. Herein, we introduce a novel water sample concentration method based on superabsorbent polymer (SAP) beads. When SAP beads swell with water, small molecules can be sorbed within the beads, but larger particles are excluded and, thus, concentrated in the residual non-sorbed water. To illustrate this approach, millimeter-sized poly(acrylamide-co-itaconic acid) (P(AM-co-IA)) beads are synthesized and successfully applied to concentrate water samples containing two model microorganisms: Escherichia coli and bacteriophage MS2. Experimental results indicate that the size of the water channel within water swollen P(AM-co-IA) hydrogel beads is on the order of several nanometers. The millimeter size coupled with a negative surface charge of the beads are shown to be critical in order to achieve high levels of concentration. This new concentration procedure is very fast, effective, scalable, and low-cost with no need for complex instrumentation.

"Nanofiltration" Enabled by Super-Absorbent Polymer Beads for Concentrating Microorganisms in Water Samples.

PubMed

Xie, Xing; Bahnemann, Janina; Wang, Siwen; Yang, Yang; Hoffmann, Michael R

2016-02-15

Detection and quantification of pathogens in water is critical for the protection of human health and for drinking water safety and security. When the pathogen concentrations are low, large sample volumes (several liters) are needed to achieve reliable quantitative results. However, most microbial identification methods utilize relatively small sample volumes. As a consequence, a concentration step is often required to detect pathogens in natural waters. Herein, we introduce a novel water sample concentration method based on superabsorbent polymer (SAP) beads. When SAP beads swell with water, small molecules can be sorbed within the beads, but larger particles are excluded and, thus, concentrated in the residual non-sorbed water. To illustrate this approach, millimeter-sized poly(acrylamide-co-itaconic acid) (P(AM-co-IA)) beads are synthesized and successfully applied to concentrate water samples containing two model microorganisms: Escherichia coli and bacteriophage MS2. Experimental results indicate that the size of the water channel within water swollen P(AM-co-IA) hydrogel beads is on the order of several nanometers. The millimeter size coupled with a negative surface charge of the beads are shown to be critical in order to achieve high levels of concentration. This new concentration procedure is very fast, effective, scalable, and low-cost with no need for complex instrumentation.

“Nanofiltration” Enabled by Super-Absorbent Polymer Beads for Concentrating Microorganisms in Water Samples

PubMed Central

Xie, Xing; Bahnemann, Janina; Wang, Siwen; Yang, Yang; Hoffmann, Michael R.

2016-01-01

Detection and quantification of pathogens in water is critical for the protection of human health and for drinking water safety and security. When the pathogen concentrations are low, large sample volumes (several liters) are needed to achieve reliable quantitative results. However, most microbial identification methods utilize relatively small sample volumes. As a consequence, a concentration step is often required to detect pathogens in natural waters. Herein, we introduce a novel water sample concentration method based on superabsorbent polymer (SAP) beads. When SAP beads swell with water, small molecules can be sorbed within the beads, but larger particles are excluded and, thus, concentrated in the residual non-sorbed water. To illustrate this approach, millimeter-sized poly(acrylamide-co-itaconic acid) (P(AM-co-IA)) beads are synthesized and successfully applied to concentrate water samples containing two model microorganisms: Escherichia coli and bacteriophage MS2. Experimental results indicate that the size of the water channel within water swollen P(AM-co-IA) hydrogel beads is on the order of several nanometers. The millimeter size coupled with a negative surface charge of the beads are shown to be critical in order to achieve high levels of concentration. This new concentration procedure is very fast, effective, scalable, and low-cost with no need for complex instrumentation. PMID:26876979

Repopulation of calibrations with samples from the target site: effect of the size of the calibration.

NASA Astrophysics Data System (ADS)

Guerrero, C.; Zornoza, R.; Gómez, I.; Mataix-Solera, J.; Navarro-Pedreño, J.; Mataix-Beneyto, J.; García-Orenes, F.

2009-04-01

Near infrared (NIR) reflectance spectroscopy offers important advantages because is a non-destructive technique, the pre-treatments needed in samples are minimal, and the spectrum of the sample is obtained in less than 1 minute without the needs of chemical reagents. For these reasons, NIR is a fast and cost-effective method. Moreover, NIR allows the analysis of several constituents or parameters simultaneously from the same spectrum once it is obtained. For this, a needed steep is the development of soil spectral libraries (set of samples analysed and scanned) and calibrations (using multivariate techniques). The calibrations should contain the variability of the target site soils in which the calibration is to be used. Many times this premise is not easy to fulfil, especially in libraries recently developed. A classical way to solve this problem is through the repopulation of libraries and the subsequent recalibration of the models. In this work we studied the changes in the accuracy of the predictions as a consequence of the successive addition of samples to repopulation. In general, calibrations with high number of samples and high diversity are desired. But we hypothesized that calibrations with lower quantities of samples (lower size) will absorb more easily the spectral characteristics of the target site. Thus, we suspect that the size of the calibration (model) that will be repopulated could be important. For this reason we also studied this effect in the accuracy of predictions of the repopulated models. In this study we used those spectra of our library which contained data of soil Kjeldahl Nitrogen (NKj) content (near to 1500 samples). First, those spectra from the target site were removed from the spectral library. Then, different quantities of samples of the library were selected (representing the 5, 10, 25, 50, 75 and 100% of the total library). These samples were used to develop calibrations with different sizes (%) of samples. We used partial least squares regression, and leave-one-out cross validation as methods of calibration. Two methods were used to select the different quantities (size of models) of samples: (1) Based on Characteristics of Spectra (BCS), and (2) Based on NKj Values of Samples (BVS). Both methods tried to select representative samples. Each of the calibrations (containing the 5, 10, 25, 50, 75 or 100% of the total samples of the library) was repopulated with samples from the target site and then recalibrated (by leave-one-out cross validation). This procedure was sequential. In each step, 2 samples from the target site were added to the models, and then recalibrated. This process was repeated successively 10 times, being 20 the total number of samples added. A local model was also created with the 20 samples used for repopulation. The repopulated, non-repopulated and local calibrations were used to predict the NKj content in those samples from the target site not included in repopulations. For the measurement of the accuracy of the predictions, the r2, RMSEP and slopes were calculated comparing predicted with analysed NKj values. This scheme was repeated for each of the four target sites studied. In general, scarce differences can be found between results obtained with BCS and BVS models. We observed that the repopulation of models increased the r2 of the predictions in sites 1 and 3. The repopulation caused scarce changes of the r2 of the predictions in sites 2 and 4, maybe due to the high initial values (using non-repopulated models r2 >0.90). As consequence of repopulation, the RMSEP decreased in all the sites except in site 2, where a very low RMESP was obtained before the repopulation (0.4 g×kg-1). The slopes trended to approximate to 1, but this value was reached only in site 4 and after the repopulation with 20 samples. In sites 3 and 4, accurate predictions were obtained using the local models. Predictions obtained with models using similar size of samples (similar %) were averaged with the aim to describe the main patterns. The r2 of predictions obtained with models of higher size were not more accurate than those obtained with models of lower size. After repopulation, the RMSEP of predictions using models with lower sizes (5, 10 and 25% of samples of the library) were lower than RMSEP obtained with higher sizes (75 and 100%), indicating that small models can easily integrate the variability of the soils from the target site. The results suggest that calibrations of small size could be repopulated and "converted" in local calibrations. According to this, we can focus most of the efforts in the obtainment of highly accurate analytical values in a reduced set of samples (including some samples from the target sites). The patterns observed here are in opposition with the idea of global models. These results could encourage the expansion of this technique, because very large data based seems not to be needed. Future studies with very different samples will help to confirm the robustness of the patterns observed. Authors acknowledge to "Bancaja-UMH" for the financial support of the project "NIRPROS".

A review and comparison of methods for recreating individual patient data from published Kaplan-Meier survival curves for economic evaluations: a simulation study.

PubMed

Wan, Xiaomin; Peng, Liubao; Li, Yuanjian

2015-01-01

In general, the individual patient-level data (IPD) collected in clinical trials are not available to independent researchers to conduct economic evaluations; researchers only have access to published survival curves and summary statistics. Thus, methods that use published survival curves and summary statistics to reproduce statistics for economic evaluations are essential. Four methods have been identified: two traditional methods 1) least squares method, 2) graphical method; and two recently proposed methods by 3) Hoyle and Henley, 4) Guyot et al. The four methods were first individually reviewed and subsequently assessed regarding their abilities to estimate mean survival through a simulation study. A number of different scenarios were developed that comprised combinations of various sample sizes, censoring rates and parametric survival distributions. One thousand simulated survival datasets were generated for each scenario, and all methods were applied to actual IPD. The uncertainty in the estimate of mean survival time was also captured. All methods provided accurate estimates of the mean survival time when the sample size was 500 and a Weibull distribution was used. When the sample size was 100 and the Weibull distribution was used, the Guyot et al. method was almost as accurate as the Hoyle and Henley method; however, more biases were identified in the traditional methods. When a lognormal distribution was used, the Guyot et al. method generated noticeably less bias and a more accurate uncertainty compared with the Hoyle and Henley method. The traditional methods should not be preferred because of their remarkable overestimation. When the Weibull distribution was used for a fitted model, the Guyot et al. method was almost as accurate as the Hoyle and Henley method. However, if the lognormal distribution was used, the Guyot et al. method was less biased compared with the Hoyle and Henley method.

Fabrication of mesoporous silica nanoparticles by sol gel method followed various hydrothermal temperature

NASA Astrophysics Data System (ADS)

Purwaningsih, Hariyati; Pratiwi, Vania Mitha; Purwana, Siti Annisa Bani; Nurdiansyah, Haniffudin; Rahmawati, Yenny; Susanti, Diah

2018-04-01

Rice husk is an agricultural waste that is potentially used as natural silica resources. Natural silica claimed to be safe in handling, cheap and can be generate from cheap resource. In this study mesoporous silica was synthesized using sodium silicate extracted from rice husk ash. This research's aim are to study the optimization of silica extraction from rice husk, characterizing mesoporous silica from sol-gel method and surfactant templating from rice husk and the effect of hydrothermal temperature on mesoporous silica nanoparticle (MSNp) formation. In this research, rice husk was extracted with sol-gel method and was followed by hydrothermal treatment; several of hydrothermal temperatures were 85°C, 100°C, 115°C, 130°C and 145° for 24 hours. X-ray diffraction analysis was identified of α-SiO2 phase and NaCl compound impurities. Scherer's analysis method for crystallite size have resulted 6.27-40.3 nm. FTIR results of silica from extraction and MSNp indicated Si-O-Si bonds on the sample. SEM result showed the morphology of the sample that has spherical shape and smooth surface. TEM result showed particle size ranged between 69,69-84,42 nm. BET showed that the pore size classified as mesoporous with pore diameter size is 19,29 nm.

Tree Data (TD)

Treesearch

Robert E. Keane

2006-01-01

The Tree Data (TD) methods are used to sample individual live and dead trees on a fixed-area plot to estimate tree density, size, and age class distributions before and after fire in order to assess tree survival and mortality rates. This method can also be used to sample individual shrubs if they are over 4.5 ft tall. When trees are larger than the user-specified...

Simultaneous unbiased estimates of multiple downed wood attributes in perpendicular distance sampling

Treesearch

Mark J. Ducey; Jeffrey H. Gove; Harry T. Valentine

2008-01-01

Perpendicular distance sampling (PDS) is a fast probability-proportional-to-size method for inventory of downed wood. However, previous development of PDS had limited the method to estimating only one variable (such as volume per hectare, or surface area per hectare) at a time. Here, we develop a general design-unbiased estimator for PDS. We then show how that...

Uniform Sampling Table Method and its Applications II--Evaluating the Uniform Sampling by Experiment.

PubMed

Chen, Yibin; Chen, Jiaxi; Chen, Xuan; Wang, Min; Wang, Wei

2015-01-01

A new method of uniform sampling is evaluated in this paper. The items and indexes were adopted to evaluate the rationality of the uniform sampling. The evaluation items included convenience of operation, uniformity of sampling site distribution, and accuracy and precision of measured results. The evaluation indexes included operational complexity, occupation rate of sampling site in a row and column, relative accuracy of pill weight, and relative deviation of pill weight. They were obtained from three kinds of drugs with different shape and size by four kinds of sampling methods. Gray correlation analysis was adopted to make the comprehensive evaluation by comparing it with the standard method. The experimental results showed that the convenience of uniform sampling method was 1 (100%), odds ratio of occupation rate in a row and column was infinity, relative accuracy was 99.50-99.89%, reproducibility RSD was 0.45-0.89%, and weighted incidence degree exceeded the standard method. Hence, the uniform sampling method was easy to operate, and the selected samples were distributed uniformly. The experimental results demonstrated that the uniform sampling method has good accuracy and reproducibility, which can be put into use in drugs analysis.

Inferring Population Size History from Large Samples of Genome-Wide Molecular Data - An Approximate Bayesian Computation Approach

PubMed Central

Boitard, Simon; Rodríguez, Willy; Jay, Flora; Mona, Stefano; Austerlitz, Frédéric

2016-01-01

Inferring the ancestral dynamics of effective population size is a long-standing question in population genetics, which can now be tackled much more accurately thanks to the massive genomic data available in many species. Several promising methods that take advantage of whole-genome sequences have been recently developed in this context. However, they can only be applied to rather small samples, which limits their ability to estimate recent population size history. Besides, they can be very sensitive to sequencing or phasing errors. Here we introduce a new approximate Bayesian computation approach named PopSizeABC that allows estimating the evolution of the effective population size through time, using a large sample of complete genomes. This sample is summarized using the folded allele frequency spectrum and the average zygotic linkage disequilibrium at different bins of physical distance, two classes of statistics that are widely used in population genetics and can be easily computed from unphased and unpolarized SNP data. Our approach provides accurate estimations of past population sizes, from the very first generations before present back to the expected time to the most recent common ancestor of the sample, as shown by simulations under a wide range of demographic scenarios. When applied to samples of 15 or 25 complete genomes in four cattle breeds (Angus, Fleckvieh, Holstein and Jersey), PopSizeABC revealed a series of population declines, related to historical events such as domestication or modern breed creation. We further highlight that our approach is robust to sequencing errors, provided summary statistics are computed from SNPs with common alleles. PMID:26943927

Luminescence isochron dating: a new approach using different grain sizes.

PubMed

Zhao, H; Li, S H

2002-01-01

A new approach to isochron dating is described using different sizes of quartz and K-feldspar grains. The technique can be applied to sites with time-dependent external dose rates. It is assumed that any underestimation of the equivalent dose (De) using K-feldspar is by a factor F, which is independent of grain size (90-350 microm) for a given sample. Calibration of the beta source for different grain sizes is discussed, and then the sample ages are calculated using the differences between quartz and K-feldspar De from grains of similar size. Two aeolian sediment samples from north-eastern China are used to illustrate the application of the new method. It is confirmed that the observed values of De derived using K-feldspar underestimate the expected doses (based on the quartz De) but, nevertheless, these K-feldspar De values correlate linearly with the calculated internal dose rate contribution, supporting the assumption that the underestimation factor F is independent of grain size. The isochron ages are also compared with the results obtained using quartz De and the measured external dose rates.

Instrumentation for Measurement of Gas Permeability of Polymeric Membranes

NASA Technical Reports Server (NTRS)

Upchurch, Billy T.; Wood, George M.; Brown, Kenneth G.; Burns, Karen S.

1993-01-01

A mass spectrometric 'Dynamic Delta' method for the measurement of gas permeability of polymeric membranes has been developed. The method is universally applicable for measurement of the permeability of any gas through polymeric membrane materials. The usual large sample size of more than 100 square centimeters required for other methods is not necessary for this new method which requires a size less than one square centimeter. The new method should fulfill requirements and find applicability for industrial materials such as food packaging, contact lenses and other commercial materials where gas permeability or permselectivity properties are important.

Crystallite size strain analysis of nanocrystalline La0.7Sr0.3MnO3 perovskite by Williamson-Hall plot method

NASA Astrophysics Data System (ADS)

Kumar, Dinesh; Verma, Narendra Kumar; Singh, Chandra Bhal; Singh, Akhilesh Kumar

2018-04-01

The nanocrystalline Sr-doped LaMnO3 (La0.7Sr0.3MnO3 = LSMO) perovskite manganites having different crystallite size were synthesized using the nitrate-glycine auto-combustion method. The phase purity of the manganites was checked by X-ray diffraction (XRD) measurement. The XRD patterns of the sample reveal that La0.7S0.3MnO3 crystallizes into rhombohedral crystal structure with space group R-3c. The size-dependence of structural lattice parameters have been investigated with the help of Rietveld refinement. The structural parameters increase as a function of crystallite size. The crystallite-size and internal strain as a function of crystallite-size have been calculated using Williamson-Hall plot.

Systematic review finds major deficiencies in sample size methodology and reporting for stepped-wedge cluster randomised trials

PubMed Central

Martin, James; Taljaard, Monica; Girling, Alan; Hemming, Karla

2016-01-01

Background Stepped-wedge cluster randomised trials (SW-CRT) are increasingly being used in health policy and services research, but unless they are conducted and reported to the highest methodological standards, they are unlikely to be useful to decision-makers. Sample size calculations for these designs require allowance for clustering, time effects and repeated measures. Methods We carried out a methodological review of SW-CRTs up to October 2014. We assessed adherence to reporting each of the 9 sample size calculation items recommended in the 2012 extension of the CONSORT statement to cluster trials. Results We identified 32 completed trials and 28 independent protocols published between 1987 and 2014. Of these, 45 (75%) reported a sample size calculation, with a median of 5.0 (IQR 2.5–6.0) of the 9 CONSORT items reported. Of those that reported a sample size calculation, the majority, 33 (73%), allowed for clustering, but just 15 (33%) allowed for time effects. There was a small increase in the proportions reporting a sample size calculation (from 64% before to 84% after publication of the CONSORT extension, p=0.07). The type of design (cohort or cross-sectional) was not reported clearly in the majority of studies, but cohort designs seemed to be most prevalent. Sample size calculations in cohort designs were particularly poor with only 3 out of 24 (13%) of these studies allowing for repeated measures. Discussion The quality of reporting of sample size items in stepped-wedge trials is suboptimal. There is an urgent need for dissemination of the appropriate guidelines for reporting and methodological development to match the proliferation of the use of this design in practice. Time effects and repeated measures should be considered in all SW-CRT power calculations, and there should be clarity in reporting trials as cohort or cross-sectional designs. PMID:26846897

Analytical approaches for the characterization and quantification of nanoparticles in food and beverages.

PubMed

Mattarozzi, Monica; Suman, Michele; Cascio, Claudia; Calestani, Davide; Weigel, Stefan; Undas, Anna; Peters, Ruud

2017-01-01

Estimating consumer exposure to nanomaterials (NMs) in food products and predicting their toxicological properties are necessary steps in the assessment of the risks of this technology. To this end, analytical methods have to be available to detect, characterize and quantify NMs in food and materials related to food, e.g. food packaging and biological samples following metabolization of food. The challenge for the analytical sciences is that the characterization of NMs requires chemical as well as physical information. This article offers a comprehensive analysis of methods available for the detection and characterization of NMs in food and related products. Special attention was paid to the crucial role of sample preparation methods since these have been partially neglected in the scientific literature so far. The currently available instrumental methods are grouped as fractionation, counting and ensemble methods, and their advantages and limitations are discussed. We conclude that much progress has been made over the last 5 years but that many challenges still exist. Future perspectives and priority research needs are pointed out. Graphical Abstract Two possible analytical strategies for the sizing and quantification of Nanoparticles: Asymmetric Flow Field-Flow Fractionation with multiple detectors (allows the determination of true size and mass-based particle size distribution); Single Particle Inductively Coupled Plasma Mass Spectrometry (allows the determination of a spherical equivalent diameter of the particle and a number-based particle size distribution).

Demonstration of Multi- and Single-Reader Sample Size Program for Diagnostic Studies software.

PubMed

Hillis, Stephen L; Schartz, Kevin M

2015-02-01

The recently released software Multi- and Single-Reader Sample Size Sample Size Program for Diagnostic Studies , written by Kevin Schartz and Stephen Hillis, performs sample size computations for diagnostic reader-performance studies. The program computes the sample size needed to detect a specified difference in a reader performance measure between two modalities, when using the analysis methods initially proposed by Dorfman, Berbaum, and Metz (DBM) and Obuchowski and Rockette (OR), and later unified and improved by Hillis and colleagues. A commonly used reader performance measure is the area under the receiver-operating-characteristic curve. The program can be used with typical common reader-performance measures which can be estimated parametrically or nonparametrically. The program has an easy-to-use step-by-step intuitive interface that walks the user through the entry of the needed information. Features of the software include the following: (1) choice of several study designs; (2) choice of inputs obtained from either OR or DBM analyses; (3) choice of three different inference situations: both readers and cases random, readers fixed and cases random, and readers random and cases fixed; (4) choice of two types of hypotheses: equivalence or noninferiority; (6) choice of two output formats: power for specified case and reader sample sizes, or a listing of case-reader combinations that provide a specified power; (7) choice of single or multi-reader analyses; and (8) functionality in Windows, Mac OS, and Linux.

Application of SAXS and SANS in evaluation of porosity, pore size distribution and surface area of coal

USGS Publications Warehouse

Radlinski, A.P.; Mastalerz, Maria; Hinde, A.L.; Hainbuchner, M.; Rauch, H.; Baron, M.; Lin, J.S.; Fan, L.; Thiyagarajan, P.

2004-01-01

This paper discusses the applicability of small angle X-ray scattering (SAXS) and small angle neutron scattering (SANS) techniques for determining the porosity, pore size distribution and internal specific surface area in coals. The method is noninvasive, fast, inexpensive and does not require complex sample preparation. It uses coal grains of about 0.8 mm size mounted in standard pellets as used for petrographic studies. Assuming spherical pore geometry, the scattering data are converted into the pore size distribution in the size range 1 nm (10 A??) to 20 ??m (200,000 A??) in diameter, accounting for both open and closed pores. FTIR as well as SAXS and SANS data for seven samples of oriented whole coals and corresponding pellets with vitrinite reflectance (Ro) values in the range 0.55% to 5.15% are presented and analyzed. Our results demonstrate that pellets adequately represent the average microstructure of coal samples. The scattering data have been used to calculate the maximum surface area available for methane adsorption. Total porosity as percentage of sample volume is calculated and compared with worldwide trends. By demonstrating the applicability of SAXS and SANS techniques to determine the porosity, pore size distribution and surface area in coals, we provide a new and efficient tool, which can be used for any type of coal sample, from a thin slice to a representative sample of a thick seam. ?? 2004 Elsevier B.V. All rights reserved.

Recommendations for choosing an analysis method that controls Type I error for unbalanced cluster sample designs with Gaussian outcomes.

PubMed

Johnson, Jacqueline L; Kreidler, Sarah M; Catellier, Diane J; Murray, David M; Muller, Keith E; Glueck, Deborah H

2015-11-30

We used theoretical and simulation-based approaches to study Type I error rates for one-stage and two-stage analytic methods for cluster-randomized designs. The one-stage approach uses the observed data as outcomes and accounts for within-cluster correlation using a general linear mixed model. The two-stage model uses the cluster specific means as the outcomes in a general linear univariate model. We demonstrate analytically that both one-stage and two-stage models achieve exact Type I error rates when cluster sizes are equal. With unbalanced data, an exact size α test does not exist, and Type I error inflation may occur. Via simulation, we compare the Type I error rates for four one-stage and six two-stage hypothesis testing approaches for unbalanced data. With unbalanced data, the two-stage model, weighted by the inverse of the estimated theoretical variance of the cluster means, and with variance constrained to be positive, provided the best Type I error control for studies having at least six clusters per arm. The one-stage model with Kenward-Roger degrees of freedom and unconstrained variance performed well for studies having at least 14 clusters per arm. The popular analytic method of using a one-stage model with denominator degrees of freedom appropriate for balanced data performed poorly for small sample sizes and low intracluster correlation. Because small sample sizes and low intracluster correlation are common features of cluster-randomized trials, the Kenward-Roger method is the preferred one-stage approach. Copyright © 2015 John Wiley & Sons, Ltd.

Effect of sample inhomogeneity in KAr dating

USGS Publications Warehouse

Engels, J.C.; Ingamells, C.O.

1970-01-01

Error in K-Ar ages is often due more to deficiencies in the splitting process, whereby portions of the sample are taken for potassium and for argon determination, than to imprecision in the analytical methods. The effect of the grain size of a sample and of the composition of a contaminating mineral can be evaluated, and this provides a useful guide in attempts to minimize error. Rocks and minerals should be prepared for age determination with the effects of contaminants and grain size in mind. The magnitude of such effects can be much larger than intuitive estimates might indicate. ?? 1970.

The Role of Remote Sensing in Assessing Forest Biomass in Appalachian South Carolina

NASA Technical Reports Server (NTRS)

Shain, W.; Nix, L.

1982-01-01

Information is presented on the use of color infrared aerial photographs and ground sampling methods to quantify standing forest biomass in Appalachian South Carolina. Local tree biomass equations are given and subsequent evaluation of stand density and size classes using remote sensing methods is presented. Methods of terrain analysis, environmental hazard rating, and subsequent determination of accessibility of forest biomass are discussed. Computer-based statistical analyses are used to expand individual cover-type specific ground sample data to area-wide cover type inventory figures based on aerial photographic interpretation and area measurement. Forest biomass data are presented for the study area in terms of discriminant size classes, merchantability limits, accessibility (as related to terrain and yield/harvest constraints), and potential environmental impact of harvest.

Multiscale modeling of porous ceramics using movable cellular automaton method

NASA Astrophysics Data System (ADS)

Smolin, Alexey Yu.; Smolin, Igor Yu.; Smolina, Irina Yu.

2017-10-01

The paper presents a multiscale model for porous ceramics based on movable cellular automaton method, which is a particle method in novel computational mechanics of solid. The initial scale of the proposed approach corresponds to the characteristic size of the smallest pores in the ceramics. At this scale, we model uniaxial compression of several representative samples with an explicit account of pores of the same size but with the unique position in space. As a result, we get the average values of Young's modulus and strength, as well as the parameters of the Weibull distribution of these properties at the current scale level. These data allow us to describe the material behavior at the next scale level were only the larger pores are considered explicitly, while the influence of small pores is included via effective properties determined earliar. If the pore size distribution function of the material has N maxima we need to perform computations for N-1 levels in order to get the properties step by step from the lowest scale up to the macroscale. The proposed approach was applied to modeling zirconia ceramics with bimodal pore size distribution. The obtained results show correct behavior of the model sample at the macroscale.

Analysis of variability in additive manufactured open cell porous structures.

PubMed

Evans, Sam; Jones, Eric; Fox, Pete; Sutcliffe, Chris

2017-06-01

In this article, a novel method of analysing build consistency of additively manufactured open cell porous structures is presented. Conventionally, methods such as micro computed tomography or scanning electron microscopy imaging have been applied to the measurement of geometric properties of porous material; however, high costs and low speeds make them unsuitable for analysing high volumes of components. Recent advances in the image-based analysis of open cell structures have opened up the possibility of qualifying variation in manufacturing of porous material. Here, a photogrammetric method of measurement, employing image analysis to extract values for geometric properties, is used to investigate the variation between identically designed porous samples measuring changes in material thickness and pore size, both intra- and inter-build. Following the measurement of 125 samples, intra-build material thickness showed variation of ±12%, and pore size ±4% of the mean measured values across five builds. Inter-build material thickness and pore size showed mean ranges higher than those of intra-build, ±16% and ±6% of the mean material thickness and pore size, respectively. Acquired measurements created baseline variation values and demonstrated techniques suitable for tracking build deviation and inspecting additively manufactured porous structures to indicate unwanted process fluctuations.

Validation of PCR methods for quantitation of genetically modified plants in food.

PubMed

Hübner, P; Waiblinger, H U; Pietsch, K; Brodmann, P

2001-01-01

For enforcement of the recently introduced labeling threshold for genetically modified organisms (GMOs) in food ingredients, quantitative detection methods such as quantitative competitive (QC-PCR) and real-time PCR are applied by official food control laboratories. The experiences of 3 European food control laboratories in validating such methods were compared to describe realistic performance characteristics of quantitative PCR detection methods. The limit of quantitation (LOQ) of GMO-specific, real-time PCR was experimentally determined to reach 30-50 target molecules, which is close to theoretical prediction. Starting PCR with 200 ng genomic plant DNA, the LOQ depends primarily on the genome size of the target plant and ranges from 0.02% for rice to 0.7% for wheat. The precision of quantitative PCR detection methods, expressed as relative standard deviation (RSD), varied from 10 to 30%. Using Bt176 corn containing test samples and applying Bt176 specific QC-PCR, mean values deviated from true values by -7to 18%, with an average of 2+/-10%. Ruggedness of real-time PCR detection methods was assessed in an interlaboratory study analyzing commercial, homogeneous food samples. Roundup Ready soybean DNA contents were determined in the range of 0.3 to 36%, relative to soybean DNA, with RSDs of about 25%. Taking the precision of quantitative PCR detection methods into account, suitable sample plans and sample sizes for GMO analysis are suggested. Because quantitative GMO detection methods measure GMO contents of samples in relation to reference material (calibrants), high priority must be given to international agreements and standardization on certified reference materials.

Method and system for laser-based formation of micro-shapes in surfaces of optical elements

DOEpatents

Bass, Isaac Louis; Guss, Gabriel Mark

2013-03-05

A method of forming a surface feature extending into a sample includes providing a laser operable to emit an output beam and modulating the output beam to form a pulse train having a plurality of pulses. The method also includes a) directing the pulse train along an optical path intersecting an exposed portion of the sample at a position i and b) focusing a first portion of the plurality of pulses to impinge on the sample at the position i. Each of the plurality of pulses is characterized by a spot size at the sample. The method further includes c) ablating at least a portion of the sample at the position i to form a portion of the surface feature and d) incrementing counter i. The method includes e) repeating steps a) through d) to form the surface feature. The sample is free of a rim surrounding the surface feature.

Only pick the right grains: Modelling the bias due to subjective grain-size interval selection for chronometric and fingerprinting approaches.

NASA Astrophysics Data System (ADS)

Dietze, Michael; Fuchs, Margret; Kreutzer, Sebastian

2016-04-01

Many modern approaches of radiometric dating or geochemical fingerprinting rely on sampling sedimentary deposits. A key assumption of most concepts is that the extracted grain-size fraction of the sampled sediment adequately represents the actual process to be dated or the source area to be fingerprinted. However, these assumptions are not always well constrained. Rather, they have to align with arbitrary, method-determined size intervals, such as "coarse grain" or "fine grain" with partly even different definitions. Such arbitrary intervals violate principal process-based concepts of sediment transport and can thus introduce significant bias to the analysis outcome (i.e., a deviation of the measured from the true value). We present a flexible numerical framework (numOlum) for the statistical programming language R that allows quantifying the bias due to any given analysis size interval for different types of sediment deposits. This framework is applied to synthetic samples from the realms of luminescence dating and geochemical fingerprinting, i.e. a virtual reworked loess section. We show independent validation data from artificially dosed and subsequently mixed grain-size proportions and we present a statistical approach (end-member modelling analysis, EMMA) that allows accounting for the effect of measuring the compound dosimetric history or geochemical composition of a sample. EMMA separates polymodal grain-size distributions into the underlying transport process-related distributions and their contribution to each sample. These underlying distributions can then be used to adjust grain-size preparation intervals to minimise the incorporation of "undesired" grain-size fractions.

Optimizing Sampling Efficiency for Biomass Estimation Across NEON Domains

NASA Astrophysics Data System (ADS)

Abercrombie, H. H.; Meier, C. L.; Spencer, J. J.

2013-12-01

Over the course of 30 years, the National Ecological Observatory Network (NEON) will measure plant biomass and productivity across the U.S. to enable an understanding of terrestrial carbon cycle responses to ecosystem change drivers. Over the next several years, prior to operational sampling at a site, NEON will complete construction and characterization phases during which a limited amount of sampling will be done at each site to inform sampling designs, and guide standardization of data collection across all sites. Sampling biomass in 60+ sites distributed among 20 different eco-climatic domains poses major logistical and budgetary challenges. Traditional biomass sampling methods such as clip harvesting and direct measurements of Leaf Area Index (LAI) involve collecting and processing plant samples, and are time and labor intensive. Possible alternatives include using indirect sampling methods for estimating LAI such as digital hemispherical photography (DHP) or using a LI-COR 2200 Plant Canopy Analyzer. These LAI estimations can then be used as a proxy for biomass. The biomass estimates calculated can then inform the clip harvest sampling design during NEON operations, optimizing both sample size and number so that standardized uncertainty limits can be achieved with a minimum amount of sampling effort. In 2011, LAI and clip harvest data were collected from co-located sampling points at the Central Plains Experimental Range located in northern Colorado, a short grass steppe ecosystem that is the NEON Domain 10 core site. LAI was measured with a LI-COR 2200 Plant Canopy Analyzer. The layout of the sampling design included four, 300 meter transects, with clip harvests plots spaced every 50m, and LAI sub-transects spaced every 10m. LAI was measured at four points along 6m sub-transects running perpendicular to the 300m transect. Clip harvest plots were co-located 4m from corresponding LAI transects, and had dimensions of 0.1m by 2m. We conducted regression analyses with LAI and clip harvest data to determine whether LAI can be used as a suitable proxy for aboveground standing biomass. We also compared optimal sample sizes derived from LAI data, and clip-harvest data from two different size clip harvest areas (0.1m by 1m vs. 0.1m by 2m). Sample sizes were calculated in order to estimate the mean to within a standardized level of uncertainty that will be used to guide sampling effort across all vegetation types (i.e. estimated within × 10% with 95% confidence). Finally, we employed a Semivariogram approach to determine optimal sample size and spacing.

Size-selective separation of submicron particles in suspensions with ultrasonic atomization.

PubMed

Nii, Susumu; Oka, Naoyoshi

2014-11-01

Aqueous suspensions containing silica or polystyrene latex were ultrasonically atomized for separating particles of a specific size. With the help of a fog involving fine liquid droplets with a narrow size distribution, submicron particles in a limited size-range were successfully separated from suspensions. Performance of the separation was characterized by analyzing the size and the concentration of collected particles with a high resolution method. Irradiation of 2.4MHz ultrasound to sample suspensions allowed the separation of particles of specific size from 90 to 320nm without regarding the type of material. Addition of a small amount of nonionic surfactant, PONPE20 to SiO2 suspensions enhanced the collection of finer particles, and achieved a remarkable increase in the number of collected particles. Degassing of the sample suspension resulted in eliminating the separation performance. Dissolved air in suspensions plays an important role in this separation. Copyright © 2014 Elsevier B.V. All rights reserved.

Sample size determination for disease prevalence studies with partially validated data.

PubMed

Qiu, Shi-Fang; Poon, Wai-Yin; Tang, Man-Lai

2016-02-01

Disease prevalence is an important topic in medical research, and its study is based on data that are obtained by classifying subjects according to whether a disease has been contracted. Classification can be conducted with high-cost gold standard tests or low-cost screening tests, but the latter are subject to the misclassification of subjects. As a compromise between the two, many research studies use partially validated datasets in which all data points are classified by fallible tests, and some of the data points are validated in the sense that they are also classified by the completely accurate gold-standard test. In this article, we investigate the determination of sample sizes for disease prevalence studies with partially validated data. We use two approaches. The first is to find sample sizes that can achieve a pre-specified power of a statistical test at a chosen significance level, and the second is to find sample sizes that can control the width of a confidence interval with a pre-specified confidence level. Empirical studies have been conducted to demonstrate the performance of various testing procedures with the proposed sample sizes. The applicability of the proposed methods are illustrated by a real-data example. © The Author(s) 2012.

Manual of Scaling Methods

NASA Technical Reports Server (NTRS)

Bond, Thomas H. (Technical Monitor); Anderson, David N.

2004-01-01

This manual reviews the derivation of the similitude relationships believed to be important to ice accretion and examines ice-accretion data to evaluate their importance. Both size scaling and test-condition scaling methods employing the resulting similarity parameters are described, and experimental icing tests performed to evaluate scaling methods are reviewed with results. The material included applies primarily to unprotected, unswept geometries, but some discussion of how to approach other situations is included as well. The studies given here and scaling methods considered are applicable only to Appendix-C icing conditions. Nearly all of the experimental results presented have been obtained in sea-level tunnels. Recommendations are given regarding which scaling methods to use for both size scaling and test-condition scaling, and icing test results are described to support those recommendations. Facility limitations and size-scaling restrictions are discussed. Finally, appendices summarize the air, water and ice properties used in NASA scaling studies, give expressions for each of the similarity parameters used and provide sample calculations for the size-scaling and test-condition scaling methods advocated.

Concurrent measurements of size-segregated particulate sulfate, nitrate and ammonium using quartz fiber filters, glass fiber filters and cellulose membranes

NASA Astrophysics Data System (ADS)

Tian, Shili; Pan, Yuepeng; Wang, Jian; Wang, Yuesi

2016-11-01

Current science and policy requirements have focused attention on the need to expand and improve particulate matter (PM) sampling methods. To explore how sampling filter type affects artifacts in PM composition measurements, size-resolved particulate SO42-, NO3- and NH4+ (SNA) were measured on quartz fiber filters (QFF), glass fiber filters (GFF) and cellulose membranes (CM) concurrently in an urban area of Beijing on both clean and hazy days. The results showed that SNA concentrations in most of the size fractions exhibited the following patterns on different filters: CM > QFF > GFF for NH4+; GFF > QFF > CM for SO42-; and GFF > CM > QFF for NO3-. The different patterns in coarse particles were mainly affected by filter acidity, and that in fine particles were mainly affected by hygroscopicity of the filters (especially in size fraction of 0.65-2.1 μm). Filter acidity and hygroscopicity also shifted the peaks of the annual mean size distributions of SNA on QFF from 0.43-0.65 μm on clean days to 0.65-1.1 μm on hazy days. However, this size shift was not as distinct for samples measured with CM and GFF. In addition, relative humidity (RH) and pollution levels are important factors that can enhance particulate size mode shifts of SNA on clean and hazy days. Consequently, the annual mean size distributions of SNA had maxima at 0.65-1.1 μm for QFF samples and 0.43-0.65 μm for GFF and CM samples. Compared with NH4+ and SO42-, NO3- is more sensitive to RH and pollution levels, accordingly, the annual mean size distribution of NO3- exhibited peak at 0.65-1.1 μm for CM samples instead of 0.43-0.65 μm. These methodological uncertainties should be considered when quantifying the concentrations and size distributions of SNA under different RH and haze conditions.

Water quality monitoring: A comparative case study of municipal and Curtin Sarawak's lake samples

NASA Astrophysics Data System (ADS)

Anand Kumar, A.; Jaison, J.; Prabakaran, K.; Nagarajan, R.; Chan, Y. S.

2016-03-01

In this study, particle size distribution and zeta potential of the suspended particles in municipal water and lake surface water of Curtin Sarawak's lake were compared and the samples were analysed using dynamic light scattering method. High concentration of suspended particles affects the water quality as well as suppresses the aquatic photosynthetic systems. A new approach has been carried out in the current work to determine the particle size distribution and zeta potential of the suspended particles present in the water samples. The results for the lake samples showed that the particle size ranges from 180nm to 1345nm and the zeta potential values ranges from -8.58 mV to -26.1 mV. High zeta potential value was observed in the surface water samples of Curtin Sarawak's lake compared to the municipal water. The zeta potential values represent that the suspended particles are stable and chances of agglomeration is lower in lake water samples. Moreover, the effects of physico-chemical parameters on zeta potential of the water samples were also discussed.

Microfluidic sorting of protein nanocrystals by size for X-ray free-electron laser diffraction

PubMed Central

Abdallah, Bahige G.; Zatsepin, Nadia A.; Roy-Chowdhury, Shatabdi; Coe, Jesse; Conrad, Chelsie E.; Dörner, Katerina; Sierra, Raymond G.; Stevenson, Hilary P.; Camacho-Alanis, Fernanda; Grant, Thomas D.; Nelson, Garrett; James, Daniel; Calero, Guillermo; Wachter, Rebekka M.; Spence, John C. H.; Weierstall, Uwe; Fromme, Petra; Ros, Alexandra

2015-01-01

The advent and application of the X-ray free-electron laser (XFEL) has uncovered the structures of proteins that could not previously be solved using traditional crystallography. While this new technology is powerful, optimization of the process is still needed to improve data quality and analysis efficiency. One area is sample heterogeneity, where variations in crystal size (among other factors) lead to the requirement of large data sets (and thus 10–100 mg of protein) for determining accurate structure factors. To decrease sample dispersity, we developed a high-throughput microfluidic sorter operating on the principle of dielectrophoresis, whereby polydisperse particles can be transported into various fluid streams for size fractionation. Using this microsorter, we isolated several milliliters of photosystem I nanocrystal fractions ranging from 200 to 600 nm in size as characterized by dynamic light scattering, nanoparticle tracking, and electron microscopy. Sorted nanocrystals were delivered in a liquid jet via the gas dynamic virtual nozzle into the path of the XFEL at the Linac Coherent Light Source. We obtained diffraction to ∼4 Å resolution, indicating that the small crystals were not damaged by the sorting process. We also observed the shape transforms of photosystem I nanocrystals, demonstrating that our device can optimize data collection for the shape transform-based phasing method. Using simulations, we show that narrow crystal size distributions can significantly improve merged data quality in serial crystallography. From this proof-of-concept work, we expect that the automated size-sorting of protein crystals will become an important step for sample production by reducing the amount of protein needed for a high quality final structure and the development of novel phasing methods that exploit inter-Bragg reflection intensities or use variations in beam intensity for radiation damage-induced phasing. This method will also permit an analysis of the dependence of crystal quality on crystal size. PMID:26798818

Microfluidic sorting of protein nanocrystals by size for X-ray free-electron laser diffraction

DOE PAGES

Abdallah, Bahige G.; Zatsepin, Nadia A.; Roy-Chowdhury, Shatabdi; ...

2015-08-19

We report that the advent and application of the X-ray free-electron laser (XFEL) has uncovered the structures of proteins that could not previously be solved using traditional crystallography. While this new technology is powerful, optimization of the process is still needed to improve data quality and analysis efficiency. One area is sample heterogeneity, where variations in crystal size (among other factors) lead to the requirement of large data sets (and thus 10–100 mg of protein) for determining accurate structure factors. To decrease sample dispersity, we developed a high-throughput microfluidic sorter operating on the principle of dielectrophoresis, whereby polydisperse particles canmore » be transported into various fluid streams for size fractionation. Using this microsorter, we isolated several milliliters of photosystem I nanocrystal fractions ranging from 200 to 600 nm in size as characterized by dynamic light scattering, nanoparticle tracking, and electron microscopy. Sorted nanocrystals were delivered in a liquid jet via the gas dynamic virtual nozzle into the path of the XFEL at the Linac Coherent Light Source. We obtained diffraction to ~4 Å resolution, indicating that the small crystals were not damaged by the sorting process. We also observed the shape transforms of photosystem I nanocrystals, demonstrating that our device can optimize data collection for the shape transform-based phasing method. Using simulations, we show that narrow crystal size distributions can significantly improve merged data quality in serial crystallography. From this proof-of-concept work, we expect that the automated size-sorting of protein crystals will become an important step for sample production by reducing the amount of protein needed for a high quality final structure and the development of novel phasing methods that exploit inter-Bragg reflection intensities or use variations in beam intensity for radiation damage-induced phasing. Ultimately, this method will also permit an analysis of the dependence of crystal quality on crystal size.« less

Sample size calculation for studies with grouped survival data.

PubMed

Li, Zhiguo; Wang, Xiaofei; Wu, Yuan; Owzar, Kouros

2018-06-10

Grouped survival data arise often in studies where the disease status is assessed at regular visits to clinic. The time to the event of interest can only be determined to be between two adjacent visits or is right censored at one visit. In data analysis, replacing the survival time with the endpoint or midpoint of the grouping interval leads to biased estimators of the effect size in group comparisons. Prentice and Gloeckler developed a maximum likelihood estimator for the proportional hazards model with grouped survival data and the method has been widely applied. Previous work on sample size calculation for designing studies with grouped data is based on either the exponential distribution assumption or the approximation of variance under the alternative with variance under the null. Motivated by studies in HIV trials, cancer trials and in vitro experiments to study drug toxicity, we develop a sample size formula for studies with grouped survival endpoints that use the method of Prentice and Gloeckler for comparing two arms under the proportional hazards assumption. We do not impose any distributional assumptions, nor do we use any approximation of variance of the test statistic. The sample size formula only requires estimates of the hazard ratio and survival probabilities of the event time of interest and the censoring time at the endpoints of the grouping intervals for one of the two arms. The formula is shown to perform well in a simulation study and its application is illustrated in the three motivating examples. Copyright © 2018 John Wiley & Sons, Ltd.

Physically based method for measuring suspended-sediment concentration and grain size using multi-frequency arrays of acoustic-doppler profilers

USGS Publications Warehouse

Topping, David J.; Wright, Scott A.; Griffiths, Ronald; Dean, David

2014-01-01

As the result of a 12-year program of sediment-transport research and field testing on the Colorado River (6 stations in UT and AZ), Yampa River (2 stations in CO), Little Snake River (1 station in CO), Green River (1 station in CO and 2 stations in UT), and Rio Grande (2 stations in TX), we have developed a physically based method for measuring suspended-sediment concentration and grain size at 15-minute intervals using multifrequency arrays of acoustic-Doppler profilers. This multi-frequency method is able to achieve much higher accuracies than single-frequency acoustic methods because it allows removal of the influence of changes in grain size on acoustic backscatter. The method proceeds as follows. (1) Acoustic attenuation at each frequency is related to the concentration of silt and clay with a known grain-size distribution in a river cross section using physical samples and theory. (2) The combination of acoustic backscatter and attenuation at each frequency is uniquely related to the concentration of sand (with a known reference grain-size distribution) and the concentration of silt and clay (with a known reference grain-size distribution) in a river cross section using physical samples and theory. (3) Comparison of the suspended-sand concentrations measured at each frequency using this approach then allows theory-based calculation of the median grain size of the suspended sand and final correction of the suspended-sand concentration to compensate for the influence of changing grain size on backscatter. Although this method of measuring suspended-sediment concentration is somewhat less accurate than using conventional samplers in either the EDI or EWI methods, it is much more accurate than estimating suspended-sediment concentrations using calibrated pump measurements or single-frequency acoustics. Though the EDI and EWI methods provide the most accurate measurements of suspended-sediment concentration, these measurements are labor-intensive, expensive, and may be impossible to collect at time intervals less than discharge-independent changes in suspended-sediment concentration can occur (< hours). Therefore, our physically based multi-frequency acoustic method shows promise as a cost-effective, valid approach for calculating suspended-sediment loads in river at a level of accuracy sufficient for many scientific and management purposes.

Determination of the size, concentration, and refractive index of silica nanoparticles from turbidity spectra.

PubMed

Khlebtsov, Boris N; Khanadeev, Vitaly A; Khlebtsov, Nikolai G

2008-08-19

The size and concentration of silica cores determine the size and concentration of silica/gold nanoshells in final preparations. Until now, the concentration of silica/gold nanoshells with Stober's silica core has been evaluated through the material balance assumption. Here, we describe a method for simultaneous determination of the average size and concentration of silica nanospheres from turbidity spectra measured within the 400-600 nm spectral band. As the refractive index of silica nanoparticles is the key input parameter for optical determination of their concentration, we propose an optical method and provide experimental data on a direct determination of the refractive index of silica particles n = 1.475 +/- 0.005. Finally, we exemplify our method by determining the particle size and concentration for 10 samples and compare the results with transmission electron microscopy (TEM), atomic force microscopy (AFM), and dynamic light scattering data.

Microstructural and optical properties of Mn doped NiO nanostructures synthesized via sol-gel method

NASA Astrophysics Data System (ADS)

Shah, Shamim H.; Khan, Wasi; Naseem, Swaleha; Husain, Shahid; Nadeem, M.

2018-04-01

Undoped and Mn(0, 5%, 10% and 15%) doped NiO nanostructures were synthesized by sol-gel method. Structure, morphology and optical properties were investigated through XRD, FTIR, SEM/EDS and UV-visible absorption spectroscopy techniques. XRD data analysis reveals the single phase nature with cubic crystal symmetry of the samples and the average crystallite size decreases with the doping of Mn ions upto 10%. FTIR spectra further confirmed the purity and composition of the synthesized samples. The non-spherical shape of the nanostructures was observed from SEM micrographs and gain size of the nanostructures reduces with Mn doping in NiO, whereas agglomeration increases in doped sample. Optical band gap was estimated using Tauc'srelation and found to increase on incorporation of Mn upto 10% in host lattice and then decreases for further doping.

Variable aperture-based ptychographical iterative engine method

NASA Astrophysics Data System (ADS)

Sun, Aihui; Kong, Yan; Meng, Xin; He, Xiaoliang; Du, Ruijun; Jiang, Zhilong; Liu, Fei; Xue, Liang; Wang, Shouyu; Liu, Cheng

2018-02-01

A variable aperture-based ptychographical iterative engine (vaPIE) is demonstrated both numerically and experimentally to reconstruct the sample phase and amplitude rapidly. By adjusting the size of a tiny aperture under the illumination of a parallel light beam to change the illumination on the sample step by step and recording the corresponding diffraction patterns sequentially, both the sample phase and amplitude can be faithfully reconstructed with a modified ptychographical iterative engine (PIE) algorithm. Since many fewer diffraction patterns are required than in common PIE and the shape, the size, and the position of the aperture need not to be known exactly, this proposed vaPIE method remarkably reduces the data acquisition time and makes PIE less dependent on the mechanical accuracy of the translation stage; therefore, the proposed technique can be potentially applied for various scientific researches.

Urban Land Cover Mapping Accuracy Assessment - A Cost-benefit Analysis Approach

NASA Astrophysics Data System (ADS)

Xiao, T.

2012-12-01

One of the most important components in urban land cover mapping is mapping accuracy assessment. Many statistical models have been developed to help design simple schemes based on both accuracy and confidence levels. It is intuitive that an increased number of samples increases the accuracy as well as the cost of an assessment. Understanding cost and sampling size is crucial in implementing efficient and effective of field data collection. Few studies have included a cost calculation component as part of the assessment. In this study, a cost-benefit sampling analysis model was created by combining sample size design and sampling cost calculation. The sampling cost included transportation cost, field data collection cost, and laboratory data analysis cost. Simple Random Sampling (SRS) and Modified Systematic Sampling (MSS) methods were used to design sample locations and to extract land cover data in ArcGIS. High resolution land cover data layers of Denver, CO and Sacramento, CA, street networks, and parcel GIS data layers were used in this study to test and verify the model. The relationship between the cost and accuracy was used to determine the effectiveness of each sample method. The results of this study can be applied to other environmental studies that require spatial sampling.

Estimation of lattice strain in nanocrystalline RuO2 by Williamson-Hall and size-strain plot methods

NASA Astrophysics Data System (ADS)

Sivakami, R.; Dhanuskodi, S.; Karvembu, R.

2016-01-01

RuO2 nanoparticles (RuO2 NPs) have been successfully synthesized by the hydrothermal method. Structure and the particle size have been determined by X-ray diffraction (XRD), scanning electron microscopy (SEM), atomic force microscopy (AFM) and transmission electron microscopy (TEM). UV-Vis spectra reveal that the optical band gap of RuO2 nanoparticles is red shifted from 3.95 to 3.55 eV. BET measurements show a high specific surface area (SSA) of 118-133 m2/g and pore diameter (10-25 nm) has been estimated by Barret-Joyner-Halenda (BJH) method. The crystallite size and lattice strain in the samples have been investigated by Williamson-Hall (W-H) analysis assuming uniform deformation, deformation stress and deformation energy density, and the size-strain plot method. All other relevant physical parameters including stress, strain and energy density have been calculated. The average crystallite size and the lattice strain evaluated from XRD measurements are in good agreement with the results of TEM.

Effect on the grain size of single-mode microwave sintered NiCuZn ferrite and zinc titanate dielectric resonator ceramics.

PubMed

Sirugudu, Roopas Kiran; Vemuri, Rama Krishna Murthy; Venkatachalam, Subramanian; Gopalakrishnan, Anisha; Budaraju, Srinivasa Murty

2011-01-01

Microwave sintering of materials significantly depends on dielectric, magnetic and conductive Losses. Samples with high dielectric and magnetic loss such as ferrites could be sintered easily. But low dielectric loss material such as dielectric resonators (paraelectrics) finds difficulty in generation of heat during microwave interaction. Microwave sintering of materials of these two classes helps in understanding the variation in dielectric and magnetic characteristics with respect to the change in grain size. High-energy ball milled Ni0.6Cu0.2Zn0.2Fe1.98O4-delta and ZnTiO3 are sintered in conventional and microwave methods and characterized for respective dielectric and magnetic characteristics. The grain size variation with higher copper content is also observed with conventional and microwave sintering. The grain size in microwave sintered Ni0.6Cu0.2Zn0.2Fe1.98O4-delta is found to be much small and uniform in comparison with conventional sintered sample. However, the grain size of microwave sintered sample is almost equal to that of conventional sintered sample of Ni0.3Cu0.5Zn0.2Fe1.98O4-delta. In contrast to these high dielectric and magnetic loss ferrites, the paraelectric materials are observed to sinter in presence of microwaves. Although microwave sintered zinc titanate sample showed finer and uniform grains with respect to conventional samples, the dielectric characteristics of microwave sintered sample are found to be less than that of conventional sample. Low dielectric constant is attributed to the low density. Smaller grain size is found to be responsible for low quality factor and the presence of small percentage of TiO2 is observed to achieve the temperature stable resonant frequency.

Sources of variability in collection and preparation of paint and lead-coating samples.

PubMed

Harper, S L; Gutknecht, W F

2001-06-01

Chronic exposure of children to lead (Pb) can result in permanent physiological impairment. Since surfaces coated with lead-containing paints and varnishes are potential sources of exposure, it is extremely important that reliable methods for sampling and analysis be available. The sources of variability in the collection and preparation of samples were investigated to improve the performance and comparability of methods and to ensure that data generated will be adequate for its intended use. Paint samples of varying sizes (areas and masses) were collected at different locations across a variety of surfaces including metal, plaster, concrete, and wood. A variety of grinding techniques were compared. Manual mortar and pestle grinding for at least 1.5 min and mechanized grinding techniques were found to generate similar homogenous particle size distributions required for aliquots as small as 0.10 g. When 342 samples were evaluated for sample weight loss during mortar and pestle grinding, 4% had 20% or greater loss with a high of 41%. Homogenization and sub-sampling steps were found to be the principal sources of variability related to the size of the sample collected. Analysis of samples from different locations on apparently identical surfaces were found to vary by more than a factor of two both in Pb concentration (mg cm-2 or %) and areal coating density (g cm-2). Analyses of substrates were performed to determine the Pb remaining after coating removal. Levels as high as 1% Pb were found in some substrate samples, corresponding to more than 35 mg cm-2 Pb. In conclusion, these sources of variability must be considered in development and/or application of any sampling and analysis methodologies.

Internet Pornography Use and Sexual Body Image in a Dutch Sample

PubMed Central

Cranney, Stephen

2016-01-01

Objectives A commonly attributed cause of sexual body image dissatisfaction is pornography use. This relationship has received little verification. Methods The relationship between sexual body image dissatisfaction and Internet pornography use was tested using a large-N sample of Dutch respondents. Results/Conclusion Penis size dissatisfaction is associated with pornography use. The relationship between pornography use and breast size dissatisfaction is null. These results support prior speculation and self-reports about the relationship between pornography use and sexual body image among men. These results also support a prior null finding of the relationship between breast size satisfaction for women and pornography use. PMID:26918066

Stratospheric CCN sampling program

NASA Technical Reports Server (NTRS)

Rogers, C. F.

1981-01-01

When Mt. St. Helens produced several major eruptions in the late spring of 1980, there was a strong interest in the characterization of the cloud condensation nuclei (CCN) activity of the material that was injected into the troposphere and stratosphere. The scientific value of CCN measurements is two fold: CCN counts may be directly applied to calculations of the interaction of the aerosol (enlargement) at atmospherically-realistic relative humidities or supersaturations; and if the chemical constituency of the aerosol can be assumed, the number-versus-critical supersaturation spectrum may be converted into a dry aerosol size spectrum covering a size region not readily measured by other methods. The sampling method is described along with the instrumentation used in the experiments.

Cu-doped Cd1- x Zn x S alloy: synthesis and structural investigations

NASA Astrophysics Data System (ADS)

Yadav, Indu; Ahlawat, Dharamvir Singh; Ahlawat, Rachna

2016-03-01

Copper doped Cd1- x Zn x S ( x ≤ 1) quantum dots have been synthesized using chemical co-precipitation method. Structural investigation of the synthesized nanomaterials has been carried out by powder XRD method. The XRD results have confirmed that as-prepared Cu-doped Cd1- x Zn x S quantum dots have hexagonal structure. The average nanocrystallite size was estimated in the range 2-12 nm using Debye-Scherrer formula. The lattice constants, lattice plane, d-spacing, unit cell volume, Lorentz factor and dislocation density were also calculated from XRD data. The change in particle size was observed with the change in Zn concentration. Furthermore, FTIR spectra of the prepared samples were observed for identification of COO- and O-H functional groups. The TEM study has also reported the same size range of nanoparticles. The increase in agglomeration has been observed with the increase in Zn concentration in the prepared samples.

The size-reduced Eudragit® RS microparticles prepared by solvent evaporation method - monitoring the effect of selected variables on tested parameters.

PubMed

Vasileiou, Kalliopi; Vysloužil, Jakub; Pavelková, Miroslava; Vysloužil, Jan; Kubová, Kateřina

2018-01-01

Size-reduced microparticles were successfully obtained by solvent evaporation method. Different parameters were applied in each sample and their influence on microparticles was evaluated. As a model drug the insoluble ibuprofen was selected for the encapsulation process with Eudragit® RS. The obtained microparticles were inspected by optical microscopy and scanning electron microscopy. The effect of aqueous phase volume (600, 400, 200 ml) and the concentration of polyvinyl alcohol (PVA; 1.0% and 0.1%) were studied. It was evaluated how those variations and also size can affect microparticle characteristics such as encapsulation efficiency, drug loading, burst effect and microparticle morphology. It was observed that the sample prepared with 600 ml aqueous phase and 1% concentration of polyvinyl alcohol gave the most favorable results.Key words: microparticles solvent evaporation sustained drug release Eudragit RS®.

Single-image diffusion coefficient measurements of proteins in free solution.

PubMed

Zareh, Shannon Kian; DeSantis, Michael C; Kessler, Jonathan M; Li, Je-Luen; Wang, Y M

2012-04-04

Diffusion coefficient measurements are important for many biological and material investigations, such as studies of particle dynamics and kinetics, and size determinations. Among current measurement methods, single particle tracking (SPT) offers the unique ability to simultaneously obtain location and diffusion information about a molecule while using only femtomoles of sample. However, the temporal resolution of SPT is limited to seconds for single-color-labeled samples. By directly imaging three-dimensional diffusing fluorescent proteins and studying the widths of their intensity profiles, we were able to determine the proteins' diffusion coefficients using single protein images of submillisecond exposure times. This simple method improves the temporal resolution of diffusion coefficient measurements to submilliseconds, and can be readily applied to a range of particle sizes in SPT investigations and applications in which diffusion coefficient measurements are needed, such as reaction kinetics and particle size determinations. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Assessing the precision of a time-sampling-based study among GPs: balancing sample size and measurement frequency.

PubMed

van Hassel, Daniël; van der Velden, Lud; de Bakker, Dinny; van der Hoek, Lucas; Batenburg, Ronald

2017-12-04

Our research is based on a technique for time sampling, an innovative method for measuring the working hours of Dutch general practitioners (GPs), which was deployed in an earlier study. In this study, 1051 GPs were questioned about their activities in real time by sending them one SMS text message every 3 h during 1 week. The required sample size for this study is important for health workforce planners to know if they want to apply this method to target groups who are hard to reach or if fewer resources are available. In this time-sampling method, however, standard power analyses is not sufficient for calculating the required sample size as this accounts only for sample fluctuation and not for the fluctuation of measurements taken from every participant. We investigated the impact of the number of participants and frequency of measurements per participant upon the confidence intervals (CIs) for the hours worked per week. Statistical analyses of the time-use data we obtained from GPs were performed. Ninety-five percent CIs were calculated, using equations and simulation techniques, for various different numbers of GPs included in the dataset and for various frequencies of measurements per participant. Our results showed that the one-tailed CI, including sample and measurement fluctuation, decreased from 21 until 3 h between one and 50 GPs. As a result of the formulas to calculate CIs, the increase of the precision continued and was lower with the same additional number of GPs. Likewise, the analyses showed how the number of participants required decreased if more measurements per participant were taken. For example, one measurement per 3-h time slot during the week requires 300 GPs to achieve a CI of 1 h, while one measurement per hour requires 100 GPs to obtain the same result. The sample size needed for time-use research based on a time-sampling technique depends on the design and aim of the study. In this paper, we showed how the precision of the measurement of hours worked each week by GPs strongly varied according to the number of GPs included and the frequency of measurements per GP during the week measured. The best balance between both dimensions will depend upon different circumstances, such as the target group and the budget available.

Determination of phytate in high molecular weight, charged organic matrices by two-dimensional size exclusion-ion chromatography

USDA-ARS?s Scientific Manuscript database

A two-dimensional chromatography method for analyzing anionic targets (specifically phytate) in complex matrices is described. Prior to quantification by anion exchange chromatography, the sample matrix was prepared by size exclusion chromatography, which removed the majority of matrix complexities....

Quantitative x-ray phase-contrast imaging using a single grating of comparable pitch to sample feature size.

PubMed

Morgan, Kaye S; Paganin, David M; Siu, Karen K W

2011-01-01

The ability to quantitatively retrieve transverse phase maps during imaging by using coherent x rays often requires a precise grating or analyzer-crystal-based setup. Imaging of live animals presents further challenges when these methods require multiple exposures for image reconstruction. We present a simple method of single-exposure, single-grating quantitative phase contrast for a regime in which the grating period is much greater than the effective pixel size. A grating is used to create a high-visibility reference pattern incident on the sample, which is distorted according to the complex refractive index and thickness of the sample. The resolution, along a line parallel to the grating, is not restricted by the grating spacing, and the detector resolution becomes the primary determinant of the spatial resolution. We present a method of analysis that maps the displacement of interrogation windows in order to retrieve a quantitative phase map. Application of this analysis to the imaging of known phantoms shows excellent correspondence.

Power and sample size for multivariate logistic modeling of unmatched case-control studies.

PubMed

Gail, Mitchell H; Haneuse, Sebastien

2017-01-01

Sample size calculations are needed to design and assess the feasibility of case-control studies. Although such calculations are readily available for simple case-control designs and univariate analyses, there is limited theory and software for multivariate unconditional logistic analysis of case-control data. Here we outline the theory needed to detect scalar exposure effects or scalar interactions while controlling for other covariates in logistic regression. Both analytical and simulation methods are presented, together with links to the corresponding software.

Device and technique for in-process sampling and analysis of molten metals and other liquids presenting harsh sampling conditions

DOEpatents

Alvarez, J.L.; Watson, L.D.

1988-01-21

An apparatus and method for continuously analyzing liquids by creating a supersonic spray which is shaped and sized prior to delivery of the spray to a analysis apparatus. The gas and liquid is sheared into small particles which are of a size and uniformity to form a spray which can be controlled through adjustment of pressures and gas velocity. The spray is shaped by a concentric supplemental flow of gas. 5 figs.

Microwave Nondestructive Evaluation of Dielectric Materials with a Metamaterial Lens

NASA Technical Reports Server (NTRS)

Shreiber, Daniel; Gupta, Mool; Cravey, Robin L.

2008-01-01

A novel microwave Nondestructive Evaluation (NDE) sensor was developed in an attempt to increase the sensitivity of the microwave NDE method for detection of defects small relative to a wavelength. The sensor was designed on the basis of a negative index material (NIM) lens. Characterization of the lens was performed to determine its resonant frequency, index of refraction, focus spot size, and optimal focusing length (for proper sample location). A sub-wavelength spot size (3 dB) of 0.48 lambda was obtained. The proof of concept for the sensor was achieved when a fiberglass sample with a 3 mm diameter through hole (perpendicular to the propagation direction of the wave) was tested. The hole was successfully detected with an 8.2 cm wavelength electromagnetic wave. This method is able to detect a defect that is 0.037 lambda. This method has certain advantages over other far field and near field microwave NDE methods currently in use.

Multiple defocused coherent diffraction imaging: method for simultaneously reconstructing objects and probe using X-ray free-electron lasers.

PubMed

Hirose, Makoto; Shimomura, Kei; Suzuki, Akihiro; Burdet, Nicolas; Takahashi, Yukio

2016-05-30

The sample size must be less than the diffraction-limited focal spot size of the incident beam in single-shot coherent X-ray diffraction imaging (CXDI) based on a diffract-before-destruction scheme using X-ray free electron lasers (XFELs). This is currently a major limitation preventing its wider applications. We here propose multiple defocused CXDI, in which isolated objects are sequentially illuminated with a divergent beam larger than the objects and the coherent diffraction pattern of each object is recorded. This method can simultaneously reconstruct both objects and a probe from the coherent X-ray diffraction patterns without any a priori knowledge. We performed a computer simulation of the prposed method and then successfully demonstrated it in a proof-of-principle experiment at SPring-8. The prposed method allows us to not only observe broad samples but also characterize focused XFEL beams.

Design considerations for case series models with exposure onset measurement error.

PubMed

Mohammed, Sandra M; Dalrymple, Lorien S; Sentürk, Damla; Nguyen, Danh V

2013-02-28

The case series model allows for estimation of the relative incidence of events, such as cardiovascular events, within a pre-specified time window after an exposure, such as an infection. The method requires only cases (individuals with events) and controls for all fixed/time-invariant confounders. The measurement error case series model extends the original case series model to handle imperfect data, where the timing of an infection (exposure) is not known precisely. In this work, we propose a method for power/sample size determination for the measurement error case series model. Extensive simulation studies are used to assess the accuracy of the proposed sample size formulas. We also examine the magnitude of the relative loss of power due to exposure onset measurement error, compared with the ideal situation where the time of exposure is measured precisely. To facilitate the design of case series studies, we provide publicly available web-based tools for determining power/sample size for both the measurement error case series model as well as the standard case series model. Copyright © 2012 John Wiley & Sons, Ltd.

Microwave resonant and zero-field absorption study of doped magnetite prepared by a co-precipitation method.

PubMed

Aphesteguy, Juan Carlos; Jacobo, Silvia E; Lezama, Luis; Kurlyandskaya, Galina V; Schegoleva, Nina N

2014-06-19

Fe3O4 and ZnxFe3-xO4 pure and doped magnetite magnetic nanoparticles (NPs) were prepared in aqueous solution (Series A) or in a water-ethyl alcohol mixture (Series B) by the co-precipitation method. Only one ferromagnetic resonance line was observed in all cases under consideration indicating that the materials are magnetically uniform. The shortfall in the resonance fields from 3.27 kOe (for the frequency of 9.5 GHz) expected for spheres can be understood taking into account the dipolar forces, magnetoelasticity, or magnetocrystalline anisotropy. All samples show non-zero low field absorption. For Series A samples the grain size decreases with an increase of the Zn content. In this case zero field absorption does not correlate with the changes of the grain size. For Series B samples the grain size and zero field absorption behavior correlate with each other. The highest zero-field absorption corresponded to 0.2 zinc concentration in both A and B series. High zero-field absorption of Fe3O4 ferrite magnetic NPs can be interesting for biomedical applications.

Hard choices in assessing survival past dams — a comparison of single- and paired-release strategies

USGS Publications Warehouse

Zydlewski, Joseph D.; Stich, Daniel S.; Sigourney, Douglas B.

2017-01-01

Mark–recapture models are widely used to estimate survival of salmon smolts migrating past dams. Paired releases have been used to improve estimate accuracy by removing components of mortality not attributable to the dam. This method is accompanied by reduced precision because (i) sample size is reduced relative to a single, large release; and (ii) variance calculations inflate error. We modeled an idealized system with a single dam to assess trade-offs between accuracy and precision and compared methods using root mean squared error (RMSE). Simulations were run under predefined conditions (dam mortality, background mortality, detection probability, and sample size) to determine scenarios when the paired release was preferable to a single release. We demonstrate that a paired-release design provides a theoretical advantage over a single-release design only at large sample sizes and high probabilities of detection. At release numbers typical of many survival studies, paired release can result in overestimation of dam survival. Failures to meet model assumptions of a paired release may result in further overestimation of dam-related survival. Under most conditions, a single-release strategy was preferable.

Factors Associated with the Performance and Cost-Effectiveness of Using Lymphatic Filariasis Transmission Assessment Surveys for Monitoring Soil-Transmitted Helminths: A Case Study in Kenya

PubMed Central

Smith, Jennifer L.; Sturrock, Hugh J. W.; Assefa, Liya; Nikolay, Birgit; Njenga, Sammy M.; Kihara, Jimmy; Mwandawiro, Charles S.; Brooker, Simon J.

2015-01-01

Transmission assessment surveys (TAS) for lymphatic filariasis have been proposed as a platform to assess the impact of mass drug administration (MDA) on soil-transmitted helminths (STHs). This study used computer simulation and field data from pre- and post-MDA settings across Kenya to evaluate the performance and cost-effectiveness of the TAS design for STH assessment compared with alternative survey designs. Variations in the TAS design and different sample sizes and diagnostic methods were also evaluated. The district-level TAS design correctly classified more districts compared with standard STH designs in pre-MDA settings. Aggregating districts into larger evaluation units in a TAS design decreased performance, whereas age group sampled and sample size had minimal impact. The low diagnostic sensitivity of Kato-Katz and mini-FLOTAC methods was found to increase misclassification. We recommend using a district-level TAS among children 8–10 years of age to assess STH but suggest that key consideration is given to evaluation unit size. PMID:25487730

Lecturers and Postgraduates Perception of Libraries as Promoters of Teaching, Learning, and Research at the University of Ibadan, Nigeria

ERIC Educational Resources Information Center

Oyewole, Olawale; Adetimirin, Airen

2015-01-01

Lecturers and postgraduates are among the users of the university libraries and their perception of the libraries has influence on utilization of the information resources, hence the need for this study. Survey method was adopted for the study and simple random sampling method was used to select sample size of 38 lecturers and 233 postgraduates.…

Interpretation of correlations in clinical research.

PubMed

Hung, Man; Bounsanga, Jerry; Voss, Maren Wright

2017-11-01

Critically analyzing research is a key skill in evidence-based practice and requires knowledge of research methods, results interpretation, and applications, all of which rely on a foundation based in statistics. Evidence-based practice makes high demands on trained medical professionals to interpret an ever-expanding array of research evidence. As clinical training emphasizes medical care rather than statistics, it is useful to review the basics of statistical methods and what they mean for interpreting clinical studies. We reviewed the basic concepts of correlational associations, violations of normality, unobserved variable bias, sample size, and alpha inflation. The foundations of causal inference were discussed and sound statistical analyses were examined. We discuss four ways in which correlational analysis is misused, including causal inference overreach, over-reliance on significance, alpha inflation, and sample size bias. Recent published studies in the medical field provide evidence of causal assertion overreach drawn from correlational findings. The findings present a primer on the assumptions and nature of correlational methods of analysis and urge clinicians to exercise appropriate caution as they critically analyze the evidence before them and evaluate evidence that supports practice. Critically analyzing new evidence requires statistical knowledge in addition to clinical knowledge. Studies can overstate relationships, expressing causal assertions when only correlational evidence is available. Failure to account for the effect of sample size in the analyses tends to overstate the importance of predictive variables. It is important not to overemphasize the statistical significance without consideration of effect size and whether differences could be considered clinically meaningful.

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

Zhang, Fangyan; Zhang, Song; Chung Wong, Pak

Effectively visualizing large graphs and capturing the statistical properties are two challenging tasks. To aid in these two tasks, many sampling approaches for graph simplification have been proposed, falling into three categories: node sampling, edge sampling, and traversal-based sampling. It is still unknown which approach is the best. We evaluate commonly used graph sampling methods through a combined visual and statistical comparison of graphs sampled at various rates. We conduct our evaluation on three graph models: random graphs, small-world graphs, and scale-free graphs. Initial results indicate that the effectiveness of a sampling method is dependent on the graph model, themore » size of the graph, and the desired statistical property. This benchmark study can be used as a guideline in choosing the appropriate method for a particular graph sampling task, and the results presented can be incorporated into graph visualization and analysis tools.« less

Global Sensitivity Analysis of Environmental Models: Convergence, Robustness and Validation

NASA Astrophysics Data System (ADS)

Sarrazin, Fanny; Pianosi, Francesca; Khorashadi Zadeh, Farkhondeh; Van Griensven, Ann; Wagener, Thorsten

2015-04-01

Global Sensitivity Analysis aims to characterize the impact that variations in model input factors (e.g. the parameters) have on the model output (e.g. simulated streamflow). In sampling-based Global Sensitivity Analysis, the sample size has to be chosen carefully in order to obtain reliable sensitivity estimates while spending computational resources efficiently. Furthermore, insensitive parameters are typically identified through the definition of a screening threshold: the theoretical value of their sensitivity index is zero but in a sampling-base framework they regularly take non-zero values. There is little guidance available for these two steps in environmental modelling though. The objective of the present study is to support modellers in making appropriate choices, regarding both sample size and screening threshold, so that a robust sensitivity analysis can be implemented. We performed sensitivity analysis for the parameters of three hydrological models with increasing level of complexity (Hymod, HBV and SWAT), and tested three widely used sensitivity analysis methods (Elementary Effect Test or method of Morris, Regional Sensitivity Analysis, and Variance-Based Sensitivity Analysis). We defined criteria based on a bootstrap approach to assess three different types of convergence: the convergence of the value of the sensitivity indices, of the ranking (the ordering among the parameters) and of the screening (the identification of the insensitive parameters). We investigated the screening threshold through the definition of a validation procedure. The results showed that full convergence of the value of the sensitivity indices is not necessarily needed to rank or to screen the model input factors. Furthermore, typical values of the sample sizes that are reported in the literature can be well below the sample sizes that actually ensure convergence of ranking and screening.

Bias correction for selecting the minimal-error classifier from many machine learning models.

PubMed

Ding, Ying; Tang, Shaowu; Liao, Serena G; Jia, Jia; Oesterreich, Steffi; Lin, Yan; Tseng, George C

2014-11-15

Supervised machine learning is commonly applied in genomic research to construct a classifier from the training data that is generalizable to predict independent testing data. When test datasets are not available, cross-validation is commonly used to estimate the error rate. Many machine learning methods are available, and it is well known that no universally best method exists in general. It has been a common practice to apply many machine learning methods and report the method that produces the smallest cross-validation error rate. Theoretically, such a procedure produces a selection bias. Consequently, many clinical studies with moderate sample sizes (e.g. n = 30-60) risk reporting a falsely small cross-validation error rate that could not be validated later in independent cohorts. In this article, we illustrated the probabilistic framework of the problem and explored the statistical and asymptotic properties. We proposed a new bias correction method based on learning curve fitting by inverse power law (IPL) and compared it with three existing methods: nested cross-validation, weighted mean correction and Tibshirani-Tibshirani procedure. All methods were compared in simulation datasets, five moderate size real datasets and two large breast cancer datasets. The result showed that IPL outperforms the other methods in bias correction with smaller variance, and it has an additional advantage to extrapolate error estimates for larger sample sizes, a practical feature to recommend whether more samples should be recruited to improve the classifier and accuracy. An R package 'MLbias' and all source files are publicly available. tsenglab.biostat.pitt.edu/software.htm. ctseng@pitt.edu Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Gaps in Survey Data on Cancer in American Indian and Alaska Native Populations: Examination of US Population Surveys, 1960–2010

PubMed Central

Duran, Tinka; Stimpson, Jim P.; Smith, Corey

2013-01-01

Introduction Population-based data are essential for quantifying the problems and measuring the progress made by comprehensive cancer control programs. However, cancer information specific to the American Indian/Alaska Native (AI/AN) population is not readily available. We identified major population-based surveys conducted in the United States that contain questions related to cancer, documented the AI/AN sample size in these surveys, and identified gaps in the types of cancer-related information these surveys collect. Methods We conducted an Internet query of US Department of Health and Human Services agency websites and a Medline search to identify population-based surveys conducted in the United States from 1960 through 2010 that contained information about cancer. We used a data extraction form to collect information about the purpose, sample size, data collection methods, and type of information covered in the surveys. Results Seventeen survey sources met the inclusion criteria. Information on access to and use of cancer treatment, follow-up care, and barriers to receiving timely and quality care was not consistently collected. Estimates specific to the AI/AN population were often lacking because of inadequate AI/AN sample size. For example, 9 national surveys reviewed reported an AI/AN sample size smaller than 500, and 10 had an AI/AN sample percentage less than 1.5%. Conclusion Continued efforts are needed to increase the overall number of AI/AN participants in these surveys, improve the quality of information on racial/ethnic background, and collect more information on treatment and survivorship. PMID:23517582

Pharmaceutical production of tableting granules in an ultra-small-scale high-shear granulator as a pre-formulation study.

PubMed

Ogawa, Tatsuya; Uchino, Tomohiro; Takahashi, Daisuke; Izumi, Tsuyoshi; Otsuka, Makoto

2012-11-01

In some of drug developments, the amount of bulk drug powder to use in early stages is limited and it is not easy to supply a sufficient drug amount for conventional preparation methods. Therefore, an ultra-small-scale high-shear granulator (less than 5 g) (USG) was developed and applied to small-scale granulation as a pre-formulation. The sample powder consisted of 66.5% lactose, 28.5% microcrystalline cellulose and 5.0% hydroxypropylcellulose. The granules were obtained to agitate 5 g of the sample powder with 1.0 mL of water at 300 rpm for 5 min after pre-powder mixing for 3 min by the USG and the manual hand (HM) methods. The granules were evaluated by the 10% and 90% accumulated particle size and the recoveries of the granules and the powder solid. Median particle size for the USG and the HM methods was 159.2 ± 2.3 and 270.9 ± 14.9 µm, respectively. The USG method had a narrower particle size distribution than those by the HM method. The recovery of the granules by USG was significantly larger than that by the HM method. Characteristics of all of the granules indicated that the USG method could produce higher quality granules within a shorter time than the HM methods.

Heat and Bleach: A Cost-Efficient Method for Extracting Microplastics from Return Activated Sludge.

PubMed

Sujathan, Surya; Kniggendorf, Ann-Kathrin; Kumar, Arun; Roth, Bernhard; Rosenwinkel, Karl-Heinz; Nogueira, Regina

2017-11-01

The extraction of plastic microparticles, so-called microplastics, from sludge is a challenging task due to the complex, highly organic material often interspersed with other benign microparticles. The current procedures for microplastic extraction from sludge are time consuming and require expensive reagents for density separation as well as large volumes of oxidizing agents for organic removal, often resulting in tiny sample sizes and thus a disproportional risk of sample bias. In this work, we present an improved extraction method tested on return activated sludge (RAS). The treatment of 100 ml of RAS requires only 6% hydrogen peroxide (H 2 O 2 ) for bleaching at 70 °C, followed by density separation with sodium nitrate/sodium thiosulfate (SNT) solution, and is completed within 24 h. Extracted particles of all sizes were chemically analyzed with confocal Raman microscopy. An extraction efficiency of 78 ± 8% for plastic particle sizes 20 µm and up was confirmed in a recovery experiment. However, glass shards with a diameter of less than 20 µm remained in the sample despite the density of glass exceeding the density of the separating SNT solution by 1.1 g/cm 3 . This indicates that density separation may be unreliable for particle sizes in the lower micrometer range.

Particle-size dependence on metal(loid) distributions in mine wastes: Implications for water contamination and human exposure

USGS Publications Warehouse

Kim, C.S.; Wilson, K.M.; Rytuba, J.J.

2011-01-01

The mining and processing of metal-bearing ores has resulted in contamination issues where waste materials from abandoned mines remain in piles of untreated and unconsolidated material, posing the potential for waterborne and airborne transport of toxic elements. This study presents a systematic method of particle size separation, mass distribution, and bulk chemical analysis for mine tailings and adjacent background soil samples from the Rand historic mining district, California, in order to assess particle size distribution and related trends in metal(loid) concentration as a function of particle size. Mine tailings produced through stamp milling and leaching processes were found to have both a narrower and finer particle size distribution than background samples, with significant fractions of particles available in a size range (???250 ??m) that could be incidentally ingested. In both tailings and background samples, the majority of trace metal(loid)s display an inverse relationship between concentration and particle size, resulting in higher proportions of As, Cr, Cu, Pb and Zn in finer-sized fractions which are more susceptible to both water- and wind-borne transport as well as ingestion and/or inhalation. Established regulatory screening levels for such elements may, therefore, significantly underestimate potential exposure risk if relying solely on bulk sample concentrations to guide remediation decisions. Correlations in elemental concentration trends (such as between As and Fe) indicate relationships between elements that may be relevant to their chemical speciation. ?? 2011 Elsevier Ltd.

The program structure does not reliably recover the correct population structure when sampling is uneven: subsampling and new estimators alleviate the problem.

PubMed

Puechmaille, Sebastien J

2016-05-01

Inferences of population structure and more precisely the identification of genetically homogeneous groups of individuals are essential to the fields of ecology, evolutionary biology and conservation biology. Such population structure inferences are routinely investigated via the program structure implementing a Bayesian algorithm to identify groups of individuals at Hardy-Weinberg and linkage equilibrium. While the method is performing relatively well under various population models with even sampling between subpopulations, the robustness of the method to uneven sample size between subpopulations and/or hierarchical levels of population structure has not yet been tested despite being commonly encountered in empirical data sets. In this study, I used simulated and empirical microsatellite data sets to investigate the impact of uneven sample size between subpopulations and/or hierarchical levels of population structure on the detected population structure. The results demonstrated that uneven sampling often leads to wrong inferences on hierarchical structure and downward-biased estimates of the true number of subpopulations. Distinct subpopulations with reduced sampling tended to be merged together, while at the same time, individuals from extensively sampled subpopulations were generally split, despite belonging to the same panmictic population. Four new supervised methods to detect the number of clusters were developed and tested as part of this study and were found to outperform the existing methods using both evenly and unevenly sampled data sets. Additionally, a subsampling strategy aiming to reduce sampling unevenness between subpopulations is presented and tested. These results altogether demonstrate that when sampling evenness is accounted for, the detection of the correct population structure is greatly improved. © 2016 John Wiley & Sons Ltd.

Tangential Flow Ultrafiltration: A “Green” Method for the Size Selection and Concentration of Colloidal Silver Nanoparticles

PubMed Central

Anders, Catherine B.; Baker, Joshua D.; Stahler, Adam C.; Williams, Austin J.; Sisco, Jackie N.; Trefry, John C.; Wooley, Dawn P.; Pavel Sizemore, Ioana E.

2012-01-01

Nowadays, AgNPs are extensively used in the manufacture of consumer products,1 water disinfectants,2 therapeutics,1, 3 and biomedical devices4 due to their powerful antimicrobial properties.3-6 These nanoparticle applications are strongly influenced by the AgNP size and aggregation state. Many challenges exist in the controlled fabrication7 and size-based isolation4,8 of unfunctionalized, homogenous AgNPs that are free from chemically aggressive capping/stabilizing agents or organic solvents.7-13 Limitations emerge from the toxicity of reagents, high costs or reduced efficiency of the AgNP synthesis or isolation methods (e.g., centrifugation, size-dependent solubility, size-exclusion chromatography, etc.).10,14-18 To overcome this, we recently showed that TFU permits greater control over the size, concentration and aggregation state of Creighton AgNPs (300 ml of 15.3 μg ml-1 down to 10 ml of 198.7 μg ml-1) than conventional methods of isolation such as ultracentrifugation.19 TFU is a recirculation method commonly used for the weight-based isolation of proteins, viruses and cells.20,21 Briefly, the liquid sample is passed through a series of hollow fiber membranes with pore size ranging from 1,000 kD to 10 kD. Smaller suspended or dissolved constituents in the sample will pass through the porous barrier together with the solvent (filtrate), while the larger constituents are retained (retentate). TFU may be considered a "green" method as it neither damages the sample nor requires additional solvent to eliminate toxic excess reagents and byproducts. Furthermore, TFU may be applied to a large variety of nanoparticles as both hydrophobic and hydrophilic filters are available. The two main objectives of this study were: 1) to illustrate the experimental aspects of the TFU approach through an invited video experience and 2) to demonstrate the feasibility of the TFU method for larger volumes of colloidal nanoparticles and smaller volumes of retentate. First, unfuctionalized AgNPs (4 L, 15.2 μg ml-1) were synthesized using the well-established Creighton method22,23 by the reduction of AgNO3 with NaBH4. AgNP polydispersity was then minimized via a 3-step TFU using a 50-nm filter (460 cm2) to remove AgNPs and AgNP-aggregates larger than 50 nm, followed by two 100-kD (200 cm2 and 20 cm2) filters to concentrate the AgNPs. Representative samples were characterized using transmission electron microscopy, UV-Vis absorption spectrophotometry, Raman spectroscopy, and inductively coupled plasma optical emission spectroscopy. The final retentate consisted of highly concentrated (4 ml, 8,539.9 μg ml-1) yet lowly aggregated and homogeneous AgNPs of 1-20 nm in diameter. This corresponds to a silver concentration yield of about 62%. PMID:23070148

Tangential flow ultrafiltration: a "green" method for the size selection and concentration of colloidal silver nanoparticles.

PubMed

Anders, Catherine B; Baker, Joshua D; Stahler, Adam C; Williams, Austin J; Sisco, Jackie N; Trefry, John C; Wooley, Dawn P; Pavel Sizemore, Ioana E

2012-10-04

Nowadays, AgNPs are extensively used in the manufacture of consumer products,(1) water disinfectants,(2) therapeutics,(1, 3) and biomedical devices(4) due to their powerful antimicrobial properties.(3-6) These nanoparticle applications are strongly influenced by the AgNP size and aggregation state. Many challenges exist in the controlled fabrication(7) and size-based isolation(4,8) of unfunctionalized, homogenous AgNPs that are free from chemically aggressive capping/stabilizing agents or organic solvents.(7-13) Limitations emerge from the toxicity of reagents, high costs or reduced efficiency of the AgNP synthesis or isolation methods (e.g., centrifugation, size-dependent solubility, size-exclusion chromatography, etc.).(10,14-18) To overcome this, we recently showed that TFU permits greater control over the size, concentration and aggregation state of Creighton AgNPs (300 ml of 15.3 μg ml(-1) down to 10 ml of 198.7 μg ml(-1)) than conventional methods of isolation such as ultracentrifugation.(19) TFU is a recirculation method commonly used for the weight-based isolation of proteins, viruses and cells.(20,21) Briefly, the liquid sample is passed through a series of hollow fiber membranes with pore size ranging from 1,000 kD to 10 kD. Smaller suspended or dissolved constituents in the sample will pass through the porous barrier together with the solvent (filtrate), while the larger constituents are retained (retentate). TFU may be considered a "green" method as it neither damages the sample nor requires additional solvent to eliminate toxic excess reagents and byproducts. Furthermore, TFU may be applied to a large variety of nanoparticles as both hydrophobic and hydrophilic filters are available. The two main objectives of this study were: 1) to illustrate the experimental aspects of the TFU approach through an invited video experience and 2) to demonstrate the feasibility of the TFU method for larger volumes of colloidal nanoparticles and smaller volumes of retentate. First, unfuctionalized AgNPs (4 L, 15.2 μg ml(-1)) were synthesized using the well-established Creighton method(22,23) by the reduction of AgNO3 with NaBH4. AgNP polydispersity was then minimized via a 3-step TFU using a 50-nm filter (460 cm(2)) to remove AgNPs and AgNP-aggregates larger than 50 nm, followed by two 100-kD (200 cm(2) and 20 cm(2)) filters to concentrate the AgNPs. Representative samples were characterized using transmission electron microscopy, UV-Vis absorption spectrophotometry, Raman spectroscopy, and inductively coupled plasma optical emission spectroscopy. The final retentate consisted of highly concentrated (4 ml, 8,539.9 μg ml(-1)) yet lowly aggregated and homogeneous AgNPs of 1-20 nm in diameter. This corresponds to a silver concentration yield of about 62%.

Simulation of Powder Layer Deposition in Additive Manufacturing Processes Using the Discrete Element Method

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

Herbold, E. B.; Walton, O.; Homel, M. A.

2015-10-26

This document serves as a final report to a small effort where several improvements were added to a LLNL code GEODYN-­L to develop Discrete Element Method (DEM) algorithms coupled to Lagrangian Finite Element (FE) solvers to investigate powder-­bed formation problems for additive manufacturing. The results from these simulations will be assessed for inclusion as the initial conditions for Direct Metal Laser Sintering (DMLS) simulations performed with ALE3D. The algorithms were written and performed on parallel computing platforms at LLNL. The total funding level was 3-­4 weeks of an FTE split amongst two staff scientists and one post-­doc. The DEM simulationsmore » emulated, as much as was feasible, the physical process of depositing a new layer of powder over a bed of existing powder. The DEM simulations utilized truncated size distributions spanning realistic size ranges with a size distribution profile consistent with realistic sample set. A minimum simulation sample size on the order of 40-­particles square by 10-­particles deep was utilized in these scoping studies in order to evaluate the potential effects of size segregation variation with distance displaced in front of a screed blade. A reasonable method for evaluating the problem was developed and validated. Several simulations were performed to show the viability of the approach. Future investigations will focus on running various simulations investigating powder particle sizing and screen geometries.« less

An analysis of Apollo lunar soil samples 12070,889, 12030,187, and 12070,891: Basaltic diversity at the Apollo 12 landing site and implications for classification of small-sized lunar samples

NASA Astrophysics Data System (ADS)

Alexander, Louise; Snape, Joshua F.; Joy, Katherine H.; Downes, Hilary; Crawford, Ian A.

2016-09-01

Lunar mare basalts provide insights into the compositional diversity of the Moon's interior. Basalt fragments from the lunar regolith can potentially sample lava flows from regions of the Moon not previously visited, thus, increasing our understanding of lunar geological evolution. As part of a study of basaltic diversity at the Apollo 12 landing site, detailed petrological and geochemical data are provided here for 13 basaltic chips. In addition to bulk chemistry, we have analyzed the major, minor, and trace element chemistry of mineral phases which highlight differences between basalt groups. Where samples contain olivine, the equilibrium parent melt magnesium number (Mg#; atomic Mg/[Mg + Fe]) can be calculated to estimate parent melt composition. Ilmenite and plagioclase chemistry can also determine differences between basalt groups. We conclude that samples of approximately 1-2 mm in size can be categorized provided that appropriate mineral phases (olivine, plagioclase, and ilmenite) are present. Where samples are fine-grained (grain size <0.3 mm), a "paired samples t-test" can provide a statistical comparison between a particular sample and known lunar basalts. Of the fragments analyzed here, three are found to belong to each of the previously identified olivine and ilmenite basalt suites, four to the pigeonite basalt suite, one is an olivine cumulate, and two could not be categorized because of their coarse grain sizes and lack of appropriate mineral phases. Our approach introduces methods that can be used to investigate small sample sizes (i.e., fines) from future sample return missions to investigate lava flow diversity and petrological significance.

[Spectral studies on nano-sized titania photocatalysts prepared by different drying methods].

PubMed

Ye, Zhao; Zhang, Han-hui; Pan, Hai-bo; Pan, Hong-qing

2002-12-01

Nano-sized TiO2 photocatalysts were prepared by drying the ethanol gel of titanium tetrabutoxide through natural state, supercritical ethanol, supercritical carbon dioxide drying methods and characterized by XRD, FTIR spectroscopy, FT-Raman spectroscopy and fluorescent spectroscopy, respectively. We regard degradation of rhodamine B by photocatalyst as a model reaction, and compare photocatalytic activities of samples obtained. The experimental results show that different drying methods have strong effect on crystal structure, energy band structure, optical adsorption property, surface quality and photocatalytic activity, TiO2 photocatalyst prepared by supercritical carbon dioxide drying method has superior photocatalytic activity.

A Novel Multi-Approach Protocol for the Characterization of Occupational Exposure to Organic Dust-Swine Production Case Study.

PubMed

Viegas, Carla; Faria, Tiago; Monteiro, Ana; Caetano, Liliana Aranha; Carolino, Elisabete; Quintal Gomes, Anita; Viegas, Susana

2017-12-27

Swine production has been associated with health risks and workers' symptoms. In Portugal, as in other countries, large-scale swine production involves several activities in the swine environment that require direct intervention, increasing workers' exposure to organic dust. This study describes an updated protocol for the assessment of occupational exposure to organic dust, to unveil an accurate scenario regarding occupational and environmental risks for workers' health. The particle size distribution was characterized regarding mass concentration in five different size ranges (PM0.5, PM1, PM2.5, PM5, PM10). Bioburden was assessed, by both active and passive sampling methods, in air, on surfaces, floor covering and feed samples, and analyzed through culture based-methods and qPCR. Smaller size range particles exhibited the highest counts, with indoor particles showing higher particle counts and mass concentration than outdoor particles. The limit values suggested for total bacteria load were surpassed in 35.7% (10 out of 28) of samples and for fungi in 65.5% (19 out of 29) of samples. Among Aspergillus genera, section Circumdati was the most prevalent (55%) on malt extract agar (MEA) and Versicolores the most identified (50%) on dichloran glycerol (DG18). The results document a wide characterization of occupational exposure to organic dust on swine farms, being useful for policies and stakeholders to act to improve workers' safety. The methods of sampling and analysis employed were the most suitable considering the purpose of the study and should be adopted as a protocol to be followed in future exposure assessments in this occupational environment.

ELEMENTAL COMPOSITION OF FRESHLY NUCLEATED PARTICLES

EPA Science Inventory

The main objective of this work is to develop a method for real-time sampling and analysis of individual airborne nanoparticles in the 5 - 20 nm diameter range. The size range covered by this method is much smaller than existing single particle methods for chemical analysis. S...

TECHNICAL MANUAL: A SURVEY OF EQUIPMENT AND METHODS FOR PARTICULATE SAMPLING IN INDUSTRIAL PROCESS STREAMS

EPA Science Inventory

The manual lists and describes the instruments and techniques that are available for measuring the concentration or size distribution of particles suspended in process streams. The standard, official, well established methods are described as well as some experimental methods and...

Experimental and numerical modeling research of rubber material during microwave heating process

NASA Astrophysics Data System (ADS)

Chen, Hailong; Li, Tao; Li, Kunling; Li, Qingling

2018-05-01

This paper aims to investigate the heating behaviors of block rubber by experimental and simulated method. The COMSOL Multiphysics 5.0 software was utilized in numerical simulation work. The effects of microwave frequency, power and sample size on temperature distribution are examined. The effect of frequency on temperature distribution is obvious. The maximum and minimum temperatures of block rubber increase first and then decrease with frequency increasing. The microwave heating efficiency is maximum in the microwave frequency of 2450 MHz. However, more uniform temperature distribution is presented in other microwave frequencies. The influence of microwave power on temperature distribution is also remarkable. The smaller the power, the more uniform the temperature distribution on the block rubber. The effect of power on microwave heating efficiency is not obvious. The effect of sample size on temperature distribution is evidently found. The smaller the sample size, the more uniform the temperature distribution on the block rubber. However, the smaller the sample size, the lower the microwave heating efficiency. The results can serve as references for the research on heating rubber material by microwave technology.

VARIABLE SELECTION IN NONPARAMETRIC ADDITIVE MODELS

PubMed Central

Huang, Jian; Horowitz, Joel L.; Wei, Fengrong

2010-01-01

We consider a nonparametric additive model of a conditional mean function in which the number of variables and additive components may be larger than the sample size but the number of nonzero additive components is “small” relative to the sample size. The statistical problem is to determine which additive components are nonzero. The additive components are approximated by truncated series expansions with B-spline bases. With this approximation, the problem of component selection becomes that of selecting the groups of coefficients in the expansion. We apply the adaptive group Lasso to select nonzero components, using the group Lasso to obtain an initial estimator and reduce the dimension of the problem. We give conditions under which the group Lasso selects a model whose number of components is comparable with the underlying model, and the adaptive group Lasso selects the nonzero components correctly with probability approaching one as the sample size increases and achieves the optimal rate of convergence. The results of Monte Carlo experiments show that the adaptive group Lasso procedure works well with samples of moderate size. A data example is used to illustrate the application of the proposed method. PMID:21127739

Large exchange bias effect in NiFe2O4/CoO nanocomposites

NASA Astrophysics Data System (ADS)

Mohan, Rajendra; Prasad Ghosh, Mritunjoy; Mukherjee, Samrat

2018-03-01

In this work, we report the exchange bias effect of NiFe2O4/CoO nanocomposites, synthesized via chemical co-precipitation method. Four samples of different particle size ranging from 4 nm to 31 nm were prepared with the annealing temperature varying from 200 °C to 800 °C. X-ray diffraction analysis of all the samples confirmed the presence of cubic spinel phase of Nickel ferrite along with CoO phase without trace of any impurity. Sizes of the particles were studied from transmission electron micrographs and were found to be in agreement with those estimated from x-ray diffraction. Field cooled (FC) hysteresis loops at 5 K revealed an exchange bias (HE) of 2.2 kOe for the sample heated at 200 °C which decreased with the increase of particle size. Exchange bias expectedly vanished at 300 K due to high thermal energy (kBT) and low effective surface anisotropy. M-T curves revealed a blocking temperature of 135 K for the sample with smaller particle size.

A small-plane heat source method for measuring the thermal conductivities of anisotropic materials

NASA Astrophysics Data System (ADS)

Cheng, Liang; Yue, Kai; Wang, Jun; Zhang, Xinxin

2017-07-01

A new small-plane heat source method was proposed in this study to simultaneously measure the in-plane and cross-plane thermal conductivities of anisotropic insulating materials. In this method the size of the heat source element is smaller than the sample size and the boundary condition is thermal insulation due to no heat flux at the edge of the sample during the experiment. A three-dimensional model in a rectangular coordinate system was established to exactly describe the heat transfer process of the measurement system. Using the Laplace transform, variable separation, and Laplace inverse transform methods, the analytical solution of the temperature rise of the sample was derived. The temperature rises calculated by the analytical solution agree well with the results of numerical calculation. The result of the sensitivity analysis shows that the sensitivity coefficients of the estimated thermal conductivities are high and uncorrelated to each other. At room temperature and in a high-temperature environment, experimental measurements of anisotropic silica aerogel were carried out using the traditional one-dimensional plane heat source method and the proposed method, respectively. The results demonstrate that the measurement method developed in this study is effective and feasible for simultaneously obtaining the in-plane and cross-plane thermal conductivities of the anisotropic materials.

A novel method for correcting scanline-observational bias of discontinuity orientation

PubMed Central

Huang, Lei; Tang, Huiming; Tan, Qinwen; Wang, Dingjian; Wang, Liangqing; Ez Eldin, Mutasim A. M.; Li, Changdong; Wu, Qiong

2016-01-01

Scanline observation is known to introduce an angular bias into the probability distribution of orientation in three-dimensional space. In this paper, numerical solutions expressing the functional relationship between the scanline-observational distribution (in one-dimensional space) and the inherent distribution (in three-dimensional space) are derived using probability theory and calculus under the independence hypothesis of dip direction and dip angle. Based on these solutions, a novel method for obtaining the inherent distribution (also for correcting the bias) is proposed, an approach which includes two procedures: 1) Correcting the cumulative probabilities of orientation according to the solutions, and 2) Determining the distribution of the corrected orientations using approximation methods such as the one-sample Kolmogorov-Smirnov test. The inherent distribution corrected by the proposed method can be used for discrete fracture network (DFN) modelling, which is applied to such areas as rockmass stability evaluation, rockmass permeability analysis, rockmass quality calculation and other related fields. To maximize the correction capacity of the proposed method, the observed sample size is suggested through effectiveness tests for different distribution types, dispersions and sample sizes. The performance of the proposed method and the comparison of its correction capacity with existing methods are illustrated with two case studies. PMID:26961249

Pneumatic System for Concentration of Micrometer-Size Lunar Soil

NASA Technical Reports Server (NTRS)

McKay, David; Cooper, Bonnie

2012-01-01

A report describes a size-sorting method to separate and concentrate micrometer- size dust from a broad size range of particles without using sieves, fluids, or other processes that may modify the composition or the surface properties of the dust. The system consists of four processing units connected in series by tubing. Samples of dry particulates such as lunar soil are introduced into the first unit, a fluidized bed. The flow of introduced nitrogen fluidizes the particulates and preferentially moves the finer grain sizes on to the next unit, a flat plate impactor, followed by a cyclone separator, followed by a Nuclepore polycarbonate filter to collect the dust. By varying the gas flow rate and the sizes of various orifices in the system, the size of the final and intermediate particles can be varied to provide the desired products. The dust can be collected from the filter. In addition, electron microscope grids can be placed on the Nuclepore filter for direct sampling followed by electron microscope characterization of the dust without further handling.

Characterization of winemaking yeast by cell number-size distribution analysis through flow field-flow fractionation with multi-wavelength turbidimetric detection.

PubMed

Zattoni, Andrea; Melucci, Dora; Reschiglian, Pierluigi; Sanz, Ramsés; Puignou, Lluís; Galceran, Maria Teresa

2004-10-29

Yeasts are widely used in several areas of food industry, e.g. baking, beer brewing, and wine production. Interest in new analytical methods for quality control and characterization of yeast cells is thus increasing. The biophysical properties of yeast cells, among which cell size, are related to yeast cell capabilities to produce primary and secondary metabolites during the fermentation process. Biophysical properties of winemaking yeast strains can be screened by field-flow fractionation (FFF). In this work we present the use of flow FFF (FlFFF) with turbidimetric multi-wavelength detection for the number-size distribution analysis of different commercial winemaking yeast varieties. The use of a diode-array detector allows to apply to dispersed samples like yeast cells the recently developed method for number-size (or mass-size) analysis in flow-assisted separation techniques. Results for six commercial winemaking yeast strains are compared with data obtained by a standard method for cell sizing (Coulter counter). The method here proposed gives, at short analysis time, accurate information on the number of cells of a given size, and information on the total number of cells.

Automated system measuring triple oxygen and nitrogen isotope ratios in nitrate using the bacterial method and N2 O decomposition by microwave discharge.

PubMed

Hattori, Shohei; Savarino, Joel; Kamezaki, Kazuki; Ishino, Sakiko; Dyckmans, Jens; Fujinawa, Tamaki; Caillon, Nicolas; Barbero, Albane; Mukotaka, Arata; Toyoda, Sakae; Well, Reinhard; Yoshida, Naohiro

2016-12-30

Triple oxygen and nitrogen isotope ratios in nitrate are powerful tools for assessing atmospheric nitrate formation pathways and their contribution to ecosystems. N 2 O decomposition using microwave-induced plasma (MIP) has been used only for measurements of oxygen isotopes to date, but it is also possible to measure nitrogen isotopes during the same analytical run. The main improvements to a previous system are (i) an automated distribution system of nitrate to the bacterial medium, (ii) N 2 O separation by gas chromatography before N 2 O decomposition using the MIP, (iii) use of a corundum tube for microwave discharge, and (iv) development of an automated system for isotopic measurements. Three nitrate standards with sample sizes of 60, 80, 100, and 120 nmol were measured to investigate the sample size dependence of the isotope measurements. The δ 17 O, δ 18 O, and Δ 17 O values increased with increasing sample size, although the δ 15 N value showed no significant size dependency. Different calibration slopes and intercepts were obtained with different sample amounts. The slopes and intercepts for the regression lines in different sample amounts were dependent on sample size, indicating that the extent of oxygen exchange is also dependent on sample size. The sample-size-dependent slopes and intercepts were fitted using natural log (ln) regression curves, and the slopes and intercepts can be estimated to apply to any sample size corrections. When using 100 nmol samples, the standard deviations of residuals from the regression lines for this system were 0.5‰, 0.3‰, and 0.1‰, respectively, for the δ 18 O, Δ 17 O, and δ 15 N values, results that are not inferior to those from other systems using gold tube or gold wire. An automated system was developed to measure triple oxygen and nitrogen isotopes in nitrate using N 2 O decomposition by MIP. This system enables us to measure both triple oxygen and nitrogen isotopes in nitrate with comparable precision and sample throughput (23 min per sample on average), and minimal manual treatment. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Comparison of Bootstrapping and Markov Chain Monte Carlo for Copula Analysis of Hydrological Droughts

NASA Astrophysics Data System (ADS)

Yang, P.; Ng, T. L.; Yang, W.

2015-12-01

Effective water resources management depends on the reliable estimation of the uncertainty of drought events. Confidence intervals (CIs) are commonly applied to quantify this uncertainty. A CI seeks to be at the minimal length necessary to cover the true value of the estimated variable with the desired probability. In drought analysis where two or more variables (e.g., duration and severity) are often used to describe a drought, copulas have been found suitable for representing the joint probability behavior of these variables. However, the comprehensive assessment of the parameter uncertainties of copulas of droughts has been largely ignored, and the few studies that have recognized this issue have not explicitly compared the various methods to produce the best CIs. Thus, the objective of this study to compare the CIs generated using two widely applied uncertainty estimation methods, bootstrapping and Markov Chain Monte Carlo (MCMC). To achieve this objective, (1) the marginal distributions lognormal, Gamma, and Generalized Extreme Value, and the copula functions Clayton, Frank, and Plackett are selected to construct joint probability functions of two drought related variables. (2) The resulting joint functions are then fitted to 200 sets of simulated realizations of drought events with known distribution and extreme parameters and (3) from there, using bootstrapping and MCMC, CIs of the parameters are generated and compared. The effect of an informative prior on the CIs generated by MCMC is also evaluated. CIs are produced for different sample sizes (50, 100, and 200) of the simulated drought events for fitting the joint probability functions. Preliminary results assuming lognormal marginal distributions and the Clayton copula function suggest that for cases with small or medium sample sizes (~50-100), MCMC to be superior method if an informative prior exists. Where an informative prior is unavailable, for small sample sizes (~50), both bootstrapping and MCMC yield the same level of performance, and for medium sample sizes (~100), bootstrapping is better. For cases with a large sample size (~200), there is little difference between the CIs generated using bootstrapping and MCMC regardless of whether or not an informative prior exists.

Structural and magnetic characterization of La{sub 0.8}Sr{sub 0.2}MnO{sub 3} nanoparticles prepared via a facile microwave-assisted method

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

Moradi, J., E-mail: j_moradi@yahoo.com; Ghazi, M.E.; Ehsani, M.H., E-mail: mhe_ehsani@yahoo.com

2014-07-01

Nanoparticles of La{sub 0.8}Sr{sub 0.2}MnO{sub 3} (LSMO) with different particle sizes are synthesized by a very fast, inexpensive, reproducible, and environmentally friendly method: the microwave irradiation of the corresponding mixture of nitrates. The structural and magnetic properties of the samples are investigated by the X-Ray diffraction (XRD), Fourier transform infra-red (FT-IR) spectroscopy, field-emission scanning electron microscopy (FE-SEM), transmission electron microscopy (TEM), and magnetic (DC magnetization and AC susceptibility) measurements. The XRD study coupled with the Rietveld refinement show that all samples crystallize in a rhombohedral structure with the space group of R−3C. The FT-IR spectroscopy and FE-SEM images indicate formationmore » of the perovskite structure of LSMO. The DC magnetization measurements confirm the decrease in the particle size effects on the magnetic properties, e.g. reduction in the ferromagnetic (FM) moment and increase in the surface spin disorder. Magnetic dynamics of the samples studied by AC magnetic susceptibility shows that the magnetic behavior of the nanometer-sized samples is well-described by the Vogel-Fulcher and critical slowing down laws. Strong interaction between magnetic nanoparticles of LSMO was detected by fitting the experimental data with the mentioned models. - Graphical abstract: Temperature dependence of the magnetization M(T) was measured in the zero-field-cooling (ZFC) and field-cooling (FC) modes at the applied magnetic field of 100 Oe for the La{sub 0.8}Sr{sub 0.2}MnO{sub 3} with different size prepared via a facile microwave-assisted method. - Highlights: • Nanoparticles of La{sub 0.8}Sr{sub 0.2}MnO{sub 3} were synthesized by the microwave irradiation process. • The structural studies show that all samples crystallize in a rhombohedral structure with space group of R−3C. • The DC magnetic studies confirm tuning of the magnetic properties due to the particle size effects. • Magnetic dynamic studied by AC magnetic susceptibility indicate strong interaction between magnetic nanoparticles.« less