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

Publication bias in psychology: a diagnosis based on the correlation between effect size and sample size.

PubMed

Kühberger, Anton; Fritz, Astrid; Scherndl, Thomas

2014-01-01

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. 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. 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. 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.

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).

The effect of machine learning regression algorithms and sample size on individualized behavioral prediction with functional connectivity features.

PubMed

Cui, Zaixu; Gong, Gaolang

2018-06-02

Individualized behavioral/cognitive prediction using machine learning (ML) regression approaches is becoming increasingly applied. The specific ML regression algorithm and sample size are two key factors that non-trivially influence prediction accuracies. However, the effects of the ML regression algorithm and sample size on individualized behavioral/cognitive prediction performance have not been comprehensively assessed. To address this issue, the present study included six commonly used ML regression algorithms: ordinary least squares (OLS) regression, least absolute shrinkage and selection operator (LASSO) regression, ridge regression, elastic-net regression, linear support vector regression (LSVR), and relevance vector regression (RVR), to perform specific behavioral/cognitive predictions based on different sample sizes. Specifically, the publicly available resting-state functional MRI (rs-fMRI) dataset from the Human Connectome Project (HCP) was used, and whole-brain resting-state functional connectivity (rsFC) or rsFC strength (rsFCS) were extracted as prediction features. Twenty-five sample sizes (ranged from 20 to 700) were studied by sub-sampling from the entire HCP cohort. The analyses showed that rsFC-based LASSO regression performed remarkably worse than the other algorithms, and rsFCS-based OLS regression performed markedly worse than the other algorithms. Regardless of the algorithm and feature type, both the prediction accuracy and its stability exponentially increased with increasing sample size. The specific patterns of the observed algorithm and sample size effects were well replicated in the prediction using re-testing fMRI data, data processed by different imaging preprocessing schemes, and different behavioral/cognitive scores, thus indicating excellent robustness/generalization of the effects. The current findings provide critical insight into how the selected ML regression algorithm and sample size influence individualized predictions of behavior/cognition and offer important guidance for choosing the ML regression algorithm or sample size in relevant investigations. Copyright © 2018 Elsevier Inc. All rights reserved.

Sample size and power calculations for detecting changes in malaria transmission using antibody seroconversion rate.

PubMed

Sepúlveda, Nuno; Paulino, Carlos Daniel; Drakeley, Chris

2015-12-30

Several studies have highlighted the use of serological data in detecting a reduction in malaria transmission intensity. These studies have typically used serology as an adjunct measure and no formal examination of sample size calculations for this approach has been conducted. A sample size calculator is proposed for cross-sectional surveys using data simulation from a reverse catalytic model assuming a reduction in seroconversion rate (SCR) at a given change point before sampling. This calculator is based on logistic approximations for the underlying power curves to detect a reduction in SCR in relation to the hypothesis of a stable SCR for the same data. Sample sizes are illustrated for a hypothetical cross-sectional survey from an African population assuming a known or unknown change point. Overall, data simulation demonstrates that power is strongly affected by assuming a known or unknown change point. Small sample sizes are sufficient to detect strong reductions in SCR, but invariantly lead to poor precision of estimates for current SCR. In this situation, sample size is better determined by controlling the precision of SCR estimates. Conversely larger sample sizes are required for detecting more subtle reductions in malaria transmission but those invariantly increase precision whilst reducing putative estimation bias. The proposed sample size calculator, although based on data simulation, shows promise of being easily applicable to a range of populations and survey types. Since the change point is a major source of uncertainty, obtaining or assuming prior information about this parameter might reduce both the sample size and the chance of generating biased SCR estimates.

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

Designing a two-rank acceptance sampling plan for quality inspection of geospatial data products

NASA Astrophysics Data System (ADS)

Tong, Xiaohua; Wang, Zhenhua; Xie, Huan; Liang, Dan; Jiang, Zuoqin; Li, Jinchao; Li, Jun

2011-10-01

To address the disadvantages of classical sampling plans designed for traditional industrial products, we originally propose a two-rank acceptance sampling plan (TRASP) for the inspection of geospatial data outputs based on the acceptance quality level (AQL). The first rank sampling plan is to inspect the lot consisting of map sheets, and the second is to inspect the lot consisting of features in an individual map sheet. The TRASP design is formulated as an optimization problem with respect to sample size and acceptance number, which covers two lot size cases. The first case is for a small lot size with nonconformities being modeled by a hypergeometric distribution function, and the second is for a larger lot size with nonconformities being modeled by a Poisson distribution function. The proposed TRASP is illustrated through two empirical case studies. Our analysis demonstrates that: (1) the proposed TRASP provides a general approach for quality inspection of geospatial data outputs consisting of non-uniform items and (2) the proposed acceptance sampling plan based on TRASP performs better than other classical sampling plans. It overcomes the drawbacks of percent sampling, i.e., "strictness for large lot size, toleration for small lot size," and those of a national standard used specifically for industrial outputs, i.e., "lots with different sizes corresponding to the same sampling plan."

A computer program for sample size computations for banding studies

USGS Publications Warehouse

Wilson, K.R.; Nichols, J.D.; Hines, J.E.

1989-01-01

Sample sizes necessary for estimating survival rates of banded birds, adults and young, are derived based on specified levels of precision. The banding study can be new or ongoing. The desired coefficient of variation (CV) for annual survival estimates, the CV for mean annual survival estimates, and the length of the study must be specified to compute sample sizes. A computer program is available for computation of the sample sizes, and a description of the input and output is provided.

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.

Capturing heterogeneity: The role of a study area's extent for estimating mean throughfall

NASA Astrophysics Data System (ADS)

Zimmermann, Alexander; Voss, Sebastian; Metzger, Johanna Clara; Hildebrandt, Anke; Zimmermann, Beate

2016-11-01

The selection of an appropriate spatial extent of a sampling plot is one among several important decisions involved in planning a throughfall sampling scheme. In fact, the choice of the extent may determine whether or not a study can adequately characterize the hydrological fluxes of the studied ecosystem. Previous attempts to optimize throughfall sampling schemes focused on the selection of an appropriate sample size, support, and sampling design, while comparatively little attention has been given to the role of the extent. In this contribution, we investigated the influence of the extent on the representativeness of mean throughfall estimates for three forest ecosystems of varying stand structure. Our study is based on virtual sampling of simulated throughfall fields. We derived these fields from throughfall data sampled in a simply structured forest (young tropical forest) and two heterogeneous forests (old tropical forest, unmanaged mixed European beech forest). We then sampled the simulated throughfall fields with three common extents and various sample sizes for a range of events and for accumulated data. Our findings suggest that the size of the study area should be carefully adapted to the complexity of the system under study and to the required temporal resolution of the throughfall data (i.e. event-based versus accumulated). Generally, event-based sampling in complex structured forests (conditions that favor comparatively long autocorrelations in throughfall) requires the largest extents. For event-based sampling, the choice of an appropriate extent can be as important as using an adequate sample size.

Sample allocation balancing overall representativeness and stratum precision.

PubMed

Diaz-Quijano, Fredi Alexander

2018-05-07

In large-scale surveys, it is often necessary to distribute a preset sample size among a number of strata. Researchers must make a decision between prioritizing overall representativeness or precision of stratum estimates. Hence, I evaluated different sample allocation strategies based on stratum size. The strategies evaluated herein included allocation proportional to stratum population; equal sample for all strata; and proportional to the natural logarithm, cubic root, and square root of the stratum population. This study considered the fact that, from a preset sample size, the dispersion index of stratum sampling fractions is correlated with the population estimator error and the dispersion index of stratum-specific sampling errors would measure the inequality in precision distribution. Identification of a balanced and efficient strategy was based on comparing those both dispersion indices. Balance and efficiency of the strategies changed depending on overall sample size. As the sample to be distributed increased, the most efficient allocation strategies were equal sample for each stratum; proportional to the logarithm, to the cubic root, to square root; and that proportional to the stratum population, respectively. Depending on sample size, each of the strategies evaluated could be considered in optimizing the sample to keep both overall representativeness and stratum-specific precision. Copyright © 2018 Elsevier Inc. All rights reserved.

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

Planning Community-Based Assessments of HIV Educational Intervention Programs in Sub-Saharan Africa

ERIC Educational Resources Information Center

Kelcey, Ben; Shen, Zuchao

2017-01-01

A key consideration in planning studies of community-based HIV education programs is identifying a sample size large enough to ensure a reasonable probability of detecting program effects if they exist. Sufficient sample sizes for community- or group-based designs are proportional to the correlation or similarity of individuals within communities.…

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.

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...

Determination of Minimum Training Sample Size for Microarray-Based Cancer Outcome Prediction–An Empirical Assessment

PubMed Central

Cheng, Ningtao; Wu, Leihong; Cheng, Yiyu

2013-01-01

The promise of microarray technology in providing prediction classifiers for cancer outcome estimation has been confirmed by a number of demonstrable successes. However, the reliability of prediction results relies heavily on the accuracy of statistical parameters involved in classifiers. It cannot be reliably estimated with only a small number of training samples. Therefore, it is of vital importance to determine the minimum number of training samples and to ensure the clinical value of microarrays in cancer outcome prediction. We evaluated the impact of training sample size on model performance extensively based on 3 large-scale cancer microarray datasets provided by the second phase of MicroArray Quality Control project (MAQC-II). An SSNR-based (scale of signal-to-noise ratio) protocol was proposed in this study for minimum training sample size determination. External validation results based on another 3 cancer datasets confirmed that the SSNR-based approach could not only determine the minimum number of training samples efficiently, but also provide a valuable strategy for estimating the underlying performance of classifiers in advance. Once translated into clinical routine applications, the SSNR-based protocol would provide great convenience in microarray-based cancer outcome prediction in improving classifier reliability. PMID:23861920

Tungsten Carbide Grain Size Computation for WC-Co Dissimilar Welds

NASA Astrophysics Data System (ADS)

Zhou, Dongran; Cui, Haichao; Xu, Peiquan; Lu, Fenggui

2016-06-01

A "two-step" image processing method based on electron backscatter diffraction in scanning electron microscopy was used to compute the tungsten carbide (WC) grain size distribution for tungsten inert gas (TIG) welds and laser welds. Twenty-four images were collected on randomly set fields per sample located at the top, middle, and bottom of a cross-sectional micrograph. Each field contained 500 to 1500 WC grains. The images were recognized through clustering-based image segmentation and WC grain growth recognition. According to the WC grain size computation and experiments, a simple WC-WC interaction model was developed to explain the WC dissolution, grain growth, and aggregation in welded joints. The WC-WC interaction and blunt corners were characterized using scanning and transmission electron microscopy. The WC grain size distribution and the effects of heat input E on grain size distribution for the laser samples were discussed. The results indicate that (1) the grain size distribution follows a Gaussian distribution. Grain sizes at the top of the weld were larger than those near the middle and weld root because of power attenuation. (2) Significant WC grain growth occurred during welding as observed in the as-welded micrographs. The average grain size was 11.47 μm in the TIG samples, which was much larger than that in base metal 1 (BM1 2.13 μm). The grain size distribution curves for the TIG samples revealed a broad particle size distribution without fine grains. The average grain size (1.59 μm) in laser samples was larger than that in base metal 2 (BM2 1.01 μm). (3) WC-WC interaction exhibited complex plane, edge, and blunt corner characteristics during grain growth. A WC ( { 1 {bar{{1}}}00} ) to WC ( {0 1 1 {bar{{0}}}} ) edge disappeared and became a blunt plane WC ( { 10 1 {bar{{0}}}} ) , several grains with two- or three-sided planes and edges disappeared into a multi-edge, and a WC-WC merged.

"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.

Improving the accuracy of livestock distribution estimates through spatial interpolation.

PubMed

Bryssinckx, Ward; Ducheyne, Els; Muhwezi, Bernard; Godfrey, Sunday; Mintiens, Koen; Leirs, Herwig; Hendrickx, Guy

2012-11-01

Animal distribution maps serve many purposes such as estimating transmission risk of zoonotic pathogens to both animals and humans. The reliability and usability of such maps is highly dependent on the quality of the input data. However, decisions on how to perform livestock surveys are often based on previous work without considering possible consequences. A better understanding of the impact of using different sample designs and processing steps on the accuracy of livestock distribution estimates was acquired through iterative experiments using detailed survey. The importance of sample size, sample design and aggregation is demonstrated and spatial interpolation is presented as a potential way to improve cattle number estimates. As expected, results show that an increasing sample size increased the precision of cattle number estimates but these improvements were mainly seen when the initial sample size was relatively low (e.g. a median relative error decrease of 0.04% per sampled parish for sample sizes below 500 parishes). For higher sample sizes, the added value of further increasing the number of samples declined rapidly (e.g. a median relative error decrease of 0.01% per sampled parish for sample sizes above 500 parishes. When a two-stage stratified sample design was applied to yield more evenly distributed samples, accuracy levels were higher for low sample densities and stabilised at lower sample sizes compared to one-stage stratified sampling. Aggregating the resulting cattle number estimates yielded significantly more accurate results because of averaging under- and over-estimates (e.g. when aggregating cattle number estimates from subcounty to district level, P <0.009 based on a sample of 2,077 parishes using one-stage stratified samples). During aggregation, area-weighted mean values were assigned to higher administrative unit levels. However, when this step is preceded by a spatial interpolation to fill in missing values in non-sampled areas, accuracy is improved remarkably. This counts especially for low sample sizes and spatially even distributed samples (e.g. P <0.001 for a sample of 170 parishes using one-stage stratified sampling and aggregation on district level). Whether the same observations apply on a lower spatial scale should be further investigated.

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.

Sampling guidelines for oral fluid-based surveys of group-housed animals.

PubMed

Rotolo, Marisa L; Sun, Yaxuan; Wang, Chong; Giménez-Lirola, Luis; Baum, David H; Gauger, Phillip C; Harmon, Karen M; Hoogland, Marlin; Main, Rodger; Zimmerman, Jeffrey J

2017-09-01

Formulas and software for calculating sample size for surveys based on individual animal samples are readily available. However, sample size formulas are not available for oral fluids and other aggregate samples that are increasingly used in production settings. Therefore, the objective of this study was to develop sampling guidelines for oral fluid-based porcine reproductive and respiratory syndrome virus (PRRSV) surveys in commercial swine farms. Oral fluid samples were collected in 9 weekly samplings from all pens in 3 barns on one production site beginning shortly after placement of weaned pigs. Samples (n=972) were tested by real-time reverse-transcription PCR (RT-rtPCR) and the binary results analyzed using a piecewise exponential survival model for interval-censored, time-to-event data with misclassification. Thereafter, simulation studies were used to study the barn-level probability of PRRSV detection as a function of sample size, sample allocation (simple random sampling vs fixed spatial sampling), assay diagnostic sensitivity and specificity, and pen-level prevalence. These studies provided estimates of the probability of detection by sample size and within-barn prevalence. Detection using fixed spatial sampling was as good as, or better than, simple random sampling. Sampling multiple barns on a site increased the probability of detection with the number of barns sampled. These results are relevant to PRRSV control or elimination projects at the herd, regional, or national levels, but the results are also broadly applicable to contagious pathogens of swine for which oral fluid tests of equivalent performance are available. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

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.

Forestry inventory based on multistage sampling with probability proportional to size

NASA Technical Reports Server (NTRS)

Lee, D. C. L.; Hernandez, P., Jr.; Shimabukuro, Y. E.

1983-01-01

A multistage sampling technique, with probability proportional to size, is developed for a forest volume inventory using remote sensing data. The LANDSAT data, Panchromatic aerial photographs, and field data are collected. Based on age and homogeneity, pine and eucalyptus classes are identified. Selection of tertiary sampling units is made through aerial photographs to minimize field work. The sampling errors for eucalyptus and pine ranged from 8.34 to 21.89 percent and from 7.18 to 8.60 percent, respectively.

"PowerUp"!: A Tool for Calculating Minimum Detectable Effect Sizes and Minimum Required Sample Sizes for Experimental and Quasi-Experimental Design Studies

ERIC Educational Resources Information Center

Dong, Nianbo; Maynard, Rebecca

2013-01-01

This paper and the accompanying tool are intended to complement existing supports for conducting power analysis tools by offering a tool based on the framework of Minimum Detectable Effect Sizes (MDES) formulae that can be used in determining sample size requirements and in estimating minimum detectable effect sizes for a range of individual- and…

Field size, length, and width distributions based on LACIE ground truth data. [large area crop inventory experiment

NASA Technical Reports Server (NTRS)

Pitts, D. E.; Badhwar, G.

1980-01-01

The development of agricultural remote sensing systems requires knowledge of agricultural field size distributions so that the sensors, sampling frames, image interpretation schemes, registration systems, and classification systems can be properly designed. Malila et al. (1976) studied the field size distribution for wheat and all other crops in two Kansas LACIE (Large Area Crop Inventory Experiment) intensive test sites using ground observations of the crops and measurements of their field areas based on current year rectified aerial photomaps. The field area and size distributions reported in the present investigation are derived from a representative subset of a stratified random sample of LACIE sample segments. In contrast to previous work, the obtained results indicate that most field-size distributions are not log-normally distributed. The most common field size observed in this study was 10 acres for most crops studied.

Sample size, confidence, and contingency judgement.

PubMed

Clément, Mélanie; Mercier, Pierre; Pastò, Luigi

2002-06-01

According to statistical models, the acquisition function of contingency judgement is due to confidence increasing with sample size. According to associative models, the function reflects the accumulation of associative strength on which the judgement is based. Which view is right? Thirty university students assessed the relation between a fictitious medication and a symptom of skin discoloration in conditions that varied sample size (4, 6, 8 or 40 trials) and contingency (delta P = .20, .40, .60 or .80). Confidence was also collected. Contingency judgement was lower for smaller samples, while confidence level correlated inversely with sample size. This dissociation between contingency judgement and confidence contradicts the statistical perspective.

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.

Dispersion and sampling of adult Dermacentor andersoni in rangeland in Western North America.

PubMed

Rochon, K; Scoles, G A; Lysyk, T J

2012-03-01

A fixed precision sampling plan was developed for off-host populations of adult Rocky Mountain wood tick, Dermacentor andersoni (Stiles) based on data collected by dragging at 13 locations in Alberta, Canada; Washington; and Oregon. In total, 222 site-date combinations were sampled. Each site-date combination was considered a sample, and each sample ranged in size from 86 to 250 10 m2 quadrats. Analysis of simulated quadrats ranging in size from 10 to 50 m2 indicated that the most precise sample unit was the 10 m2 quadrat. Samples taken when abundance < 0.04 ticks per 10 m2 were more likely to not depart significantly from statistical randomness than samples taken when abundance was greater. Data were grouped into ten abundance classes and assessed for fit to the Poisson and negative binomial distributions. The Poisson distribution fit only data in abundance classes < 0.02 ticks per 10 m2, while the negative binomial distribution fit data from all abundance classes. A negative binomial distribution with common k = 0.3742 fit data in eight of the 10 abundance classes. Both the Taylor and Iwao mean-variance relationships were fit and used to predict sample sizes for a fixed level of precision. Sample sizes predicted using the Taylor model tended to underestimate actual sample sizes, while sample sizes estimated using the Iwao model tended to overestimate actual sample sizes. Using a negative binomial with common k provided estimates of required sample sizes closest to empirically calculated sample sizes.

Accounting for twin births in sample size calculations for randomised trials.

PubMed

Yelland, Lisa N; Sullivan, Thomas R; Collins, Carmel T; Price, David J; McPhee, Andrew J; Lee, Katherine J

2018-05-04

Including twins in randomised trials leads to non-independence or clustering in the data. Clustering has important implications for sample size calculations, yet few trials take this into account. Estimates of the intracluster correlation coefficient (ICC), or the correlation between outcomes of twins, are needed to assist with sample size planning. Our aims were to provide ICC estimates for infant outcomes, describe the information that must be specified in order to account for clustering due to twins in sample size calculations, and develop a simple tool for performing sample size calculations for trials including twins. ICCs were estimated for infant outcomes collected in four randomised trials that included twins. The information required to account for clustering due to twins in sample size calculations is described. A tool that calculates the sample size based on this information was developed in Microsoft Excel and in R as a Shiny web app. ICC estimates ranged between -0.12, indicating a weak negative relationship, and 0.98, indicating a strong positive relationship between outcomes of twins. Example calculations illustrate how the ICC estimates and sample size calculator can be used to determine the target sample size for trials including twins. Clustering among outcomes measured on twins should be taken into account in sample size calculations to obtain the desired power. Our ICC estimates and sample size calculator will be useful for designing future trials that include twins. Publication of additional ICCs is needed to further assist with sample size planning for future trials. © 2018 John Wiley & Sons Ltd.

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.

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.

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.

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.

Sample Size and Statistical Conclusions from Tests of Fit to the Rasch Model According to the Rasch Unidimensional Measurement Model (Rumm) Program in Health Outcome Measurement.

PubMed

Hagell, Peter; Westergren, Albert

Sample size is a major factor in statistical null hypothesis testing, which is the basis for many approaches to testing Rasch model fit. Few sample size recommendations for testing fit to the Rasch model concern the Rasch Unidimensional Measurement Models (RUMM) software, which features chi-square and ANOVA/F-ratio based fit statistics, including Bonferroni and algebraic sample size adjustments. This paper explores the occurrence of Type I errors with RUMM fit statistics, and the effects of algebraic sample size adjustments. Data with simulated Rasch model fitting 25-item dichotomous scales and sample sizes ranging from N = 50 to N = 2500 were analysed with and without algebraically adjusted sample sizes. Results suggest the occurrence of Type I errors with N less then or equal to 500, and that Bonferroni correction as well as downward algebraic sample size adjustment are useful to avoid such errors, whereas upward adjustment of smaller samples falsely signal misfit. Our observations suggest that sample sizes around N = 250 to N = 500 may provide a good balance for the statistical interpretation of the RUMM fit statistics studied here with respect to Type I errors and under the assumption of Rasch model fit within the examined frame of reference (i.e., about 25 item parameters well targeted to the sample).

Sample sizes and model comparison metrics for species distribution models

Treesearch

B.B. Hanberry; H.S. He; D.C. Dey

2012-01-01

Species distribution models use small samples to produce continuous distribution maps. The question of how small a sample can be to produce an accurate model generally has been answered based on comparisons to maximum sample sizes of 200 observations or fewer. In addition, model comparisons often are made with the kappa statistic, which has become controversial....

Sample size determination for mediation analysis of longitudinal data.

PubMed

Pan, Haitao; Liu, Suyu; Miao, Danmin; Yuan, Ying

2018-03-27

Sample size planning for longitudinal data is crucial when designing mediation studies because sufficient statistical power is not only required in grant applications and peer-reviewed publications, but is essential to reliable research results. However, sample size determination is not straightforward for mediation analysis of longitudinal design. To facilitate planning the sample size for longitudinal mediation studies with a multilevel mediation model, this article provides the sample size required to achieve 80% power by simulations under various sizes of the mediation effect, within-subject correlations and numbers of repeated measures. The sample size calculation is based on three commonly used mediation tests: Sobel's method, distribution of product method and the bootstrap method. Among the three methods of testing the mediation effects, Sobel's method required the largest sample size to achieve 80% power. Bootstrapping and the distribution of the product method performed similarly and were more powerful than Sobel's method, as reflected by the relatively smaller sample sizes. For all three methods, the sample size required to achieve 80% power depended on the value of the ICC (i.e., within-subject correlation). A larger value of ICC typically required a larger sample size to achieve 80% power. Simulation results also illustrated the advantage of the longitudinal study design. The sample size tables for most encountered scenarios in practice have also been published for convenient use. Extensive simulations study showed that the distribution of the product method and bootstrapping method have superior performance to the Sobel's method, but the product method was recommended to use in practice in terms of less computation time load compared to the bootstrapping method. A R package has been developed for the product method of sample size determination in mediation longitudinal study design.

The Precision Efficacy Analysis for Regression Sample Size Method.

ERIC Educational Resources Information Center

Brooks, Gordon P.; Barcikowski, Robert S.

The general purpose of this study was to examine the efficiency of the Precision Efficacy Analysis for Regression (PEAR) method for choosing appropriate sample sizes in regression studies used for precision. The PEAR method, which is based on the algebraic manipulation of an accepted cross-validity formula, essentially uses an effect size to…

Weighting by Inverse Variance or by Sample Size in Random-Effects Meta-Analysis

ERIC Educational Resources Information Center

Marin-Martinez, Fulgencio; Sanchez-Meca, Julio

2010-01-01

Most of the statistical procedures in meta-analysis are based on the estimation of average effect sizes from a set of primary studies. The optimal weight for averaging a set of independent effect sizes is the inverse variance of each effect size, but in practice these weights have to be estimated, being affected by sampling error. When assuming a…

“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

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.

Assessment of sampling stability in ecological applications of discriminant analysis

USGS Publications Warehouse

Williams, B.K.; Titus, K.

1988-01-01

A simulation study was undertaken to assess the sampling stability of the variable loadings in linear discriminant function analysis. A factorial design was used for the factors of multivariate dimensionality, dispersion structure, configuration of group means, and sample size. A total of 32,400 discriminant analyses were conducted, based on data from simulated populations with appropriate underlying statistical distributions. A review of 60 published studies and 142 individual analyses indicated that sample sizes in ecological studies often have met that requirement. However, individual group sample sizes frequently were very unequal, and checks of assumptions usually were not reported. The authors recommend that ecologists obtain group sample sizes that are at least three times as large as the number of variables measured.

Speeding Up Non-Parametric Bootstrap Computations for Statistics Based on Sample Moments in Small/Moderate Sample Size Applications

PubMed Central

Chaibub Neto, Elias

2015-01-01

In this paper we propose a vectorized implementation of the non-parametric bootstrap for statistics based on sample moments. Basically, we adopt the multinomial sampling formulation of the non-parametric bootstrap, and compute bootstrap replications of sample moment statistics by simply weighting the observed data according to multinomial counts instead of evaluating the statistic on a resampled version of the observed data. Using this formulation we can generate a matrix of bootstrap weights and compute the entire vector of bootstrap replications with a few matrix multiplications. Vectorization is particularly important for matrix-oriented programming languages such as R, where matrix/vector calculations tend to be faster than scalar operations implemented in a loop. We illustrate the application of the vectorized implementation in real and simulated data sets, when bootstrapping Pearson’s sample correlation coefficient, and compared its performance against two state-of-the-art R implementations of the non-parametric bootstrap, as well as a straightforward one based on a for loop. Our investigations spanned varying sample sizes and number of bootstrap replications. The vectorized bootstrap compared favorably against the state-of-the-art implementations in all cases tested, and was remarkably/considerably faster for small/moderate sample sizes. The same results were observed in the comparison with the straightforward implementation, except for large sample sizes, where the vectorized bootstrap was slightly slower than the straightforward implementation due to increased time expenditures in the generation of weight matrices via multinomial sampling. PMID:26125965

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.

Discriminant Analysis of Defective and Non-Defective Field Pea (Pisum sativum L.) into Broad Market Grades Based on Digital Image Features.

PubMed

McDonald, Linda S; Panozzo, Joseph F; Salisbury, Phillip A; Ford, Rebecca

2016-01-01

Field peas (Pisum sativum L.) are generally traded based on seed appearance, which subjectively defines broad market-grades. In this study, we developed an objective Linear Discriminant Analysis (LDA) model to classify market grades of field peas based on seed colour, shape and size traits extracted from digital images. Seeds were imaged in a high-throughput system consisting of a camera and laser positioned over a conveyor belt. Six colour intensity digital images were captured (under 405, 470, 530, 590, 660 and 850nm light) for each seed, and surface height was measured at each pixel by laser. Colour, shape and size traits were compiled across all seed in each sample to determine the median trait values. Defective and non-defective seed samples were used to calibrate and validate the model. Colour components were sufficient to correctly classify all non-defective seed samples into correct market grades. Defective samples required a combination of colour, shape and size traits to achieve 87% and 77% accuracy in market grade classification of calibration and validation sample-sets respectively. Following these results, we used the same colour, shape and size traits to develop an LDA model which correctly classified over 97% of all validation samples as defective or non-defective.

Discriminant Analysis of Defective and Non-Defective Field Pea (Pisum sativum L.) into Broad Market Grades Based on Digital Image Features

PubMed Central

McDonald, Linda S.; Panozzo, Joseph F.; Salisbury, Phillip A.; Ford, Rebecca

2016-01-01

Field peas (Pisum sativum L.) are generally traded based on seed appearance, which subjectively defines broad market-grades. In this study, we developed an objective Linear Discriminant Analysis (LDA) model to classify market grades of field peas based on seed colour, shape and size traits extracted from digital images. Seeds were imaged in a high-throughput system consisting of a camera and laser positioned over a conveyor belt. Six colour intensity digital images were captured (under 405, 470, 530, 590, 660 and 850nm light) for each seed, and surface height was measured at each pixel by laser. Colour, shape and size traits were compiled across all seed in each sample to determine the median trait values. Defective and non-defective seed samples were used to calibrate and validate the model. Colour components were sufficient to correctly classify all non-defective seed samples into correct market grades. Defective samples required a combination of colour, shape and size traits to achieve 87% and 77% accuracy in market grade classification of calibration and validation sample-sets respectively. Following these results, we used the same colour, shape and size traits to develop an LDA model which correctly classified over 97% of all validation samples as defective or non-defective. PMID:27176469

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.

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

Jomekian, A.; Faculty of Chemical Engineering, Iran University of Science and Technology; Behbahani, R.M., E-mail: behbahani@put.ac.ir

Ultra porous ZIF-8 particles synthesized using PEO/PA6 based poly(ether-block-amide) (Pebax 1657) as structure directing agent. Structural properties of ZIF-8 samples prepared under different synthesis parameters were investigated by laser particle size analysis, XRD, N{sub 2} adsorption analysis, BJH and BET tests. The overall results showed that: (1) The mean pore size of all ZIF-8 samples increased remarkably (from 0.34 nm to 1.1–2.5 nm) compared to conventionally synthesized ZIF-8 samples. (2) Exceptional BET surface area of 1869 m{sup 2}/g was obtained for a ZIF-8 sample with mean pore size of 2.5 nm. (3) Applying high concentrations of Pebax 1657 to themore » synthesis solution lead to higher surface area, larger pore size and smaller particle size for ZIF-8 samples. (4) Both, Increase in temperature and decrease in molar ratio of MeIM/Zn{sup 2+} had increasing effect on ZIF-8 particle size, pore size, pore volume, crystallinity and BET surface area of all investigated samples. - Highlights: • The pore size of ZIF-8 samples synthesized with Pebax 1657 increased remarkably. • The BET surface area of 1869 m{sup 2}/gr obtained for a ZIF-8 synthesized sample with Pebax. • Increase in temperature had increasing effect on textural properties of ZIF-8 samples. • Decrease in MeIM/Zn{sup 2+} had increasing effect on textural properties of ZIF-8 samples.« less

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.

ENHANCEMENT OF LEARNING ON SAMPLE SIZE CALCULATION WITH A SMARTPHONE APPLICATION: A CLUSTER-RANDOMIZED CONTROLLED TRIAL.

PubMed

Ngamjarus, Chetta; Chongsuvivatwong, Virasakdi; McNeil, Edward; Holling, Heinz

2017-01-01

Sample size determination usually is taught based on theory and is difficult to understand. Using a smartphone application to teach sample size calculation ought to be more attractive to students than using lectures only. This study compared levels of understanding of sample size calculations for research studies between participants attending a lecture only versus lecture combined with using a smartphone application to calculate sample sizes, to explore factors affecting level of post-test score after training sample size calculation, and to investigate participants’ attitude toward a sample size application. A cluster-randomized controlled trial involving a number of health institutes in Thailand was carried out from October 2014 to March 2015. A total of 673 professional participants were enrolled and randomly allocated to one of two groups, namely, 341 participants in 10 workshops to control group and 332 participants in 9 workshops to intervention group. Lectures on sample size calculation were given in the control group, while lectures using a smartphone application were supplied to the test group. Participants in the intervention group had better learning of sample size calculation (2.7 points out of maximnum 10 points, 95% CI: 24 - 2.9) than the participants in the control group (1.6 points, 95% CI: 1.4 - 1.8). Participants doing research projects had a higher post-test score than those who did not have a plan to conduct research projects (0.9 point, 95% CI: 0.5 - 1.4). The majority of the participants had a positive attitude towards the use of smartphone application for learning sample size calculation.

Study design requirements for RNA sequencing-based breast cancer diagnostics.

PubMed

Mer, Arvind Singh; Klevebring, Daniel; Grönberg, Henrik; Rantalainen, Mattias

2016-02-01

Sequencing-based molecular characterization of tumors provides information required for individualized cancer treatment. There are well-defined molecular subtypes of breast cancer that provide improved prognostication compared to routine biomarkers. However, molecular subtyping is not yet implemented in routine breast cancer care. Clinical translation is dependent on subtype prediction models providing high sensitivity and specificity. In this study we evaluate sample size and RNA-sequencing read requirements for breast cancer subtyping to facilitate rational design of translational studies. We applied subsampling to ascertain the effect of training sample size and the number of RNA sequencing reads on classification accuracy of molecular subtype and routine biomarker prediction models (unsupervised and supervised). Subtype classification accuracy improved with increasing sample size up to N = 750 (accuracy = 0.93), although with a modest improvement beyond N = 350 (accuracy = 0.92). Prediction of routine biomarkers achieved accuracy of 0.94 (ER) and 0.92 (Her2) at N = 200. Subtype classification improved with RNA-sequencing library size up to 5 million reads. Development of molecular subtyping models for cancer diagnostics requires well-designed studies. Sample size and the number of RNA sequencing reads directly influence accuracy of molecular subtyping. Results in this study provide key information for rational design of translational studies aiming to bring sequencing-based diagnostics to the clinic.

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

What is the optimum sample size for the study of peatland testate amoeba assemblages?

PubMed

Mazei, Yuri A; Tsyganov, Andrey N; Esaulov, Anton S; Tychkov, Alexander Yu; Payne, Richard J

2017-10-01

Testate amoebae are widely used in ecological and palaeoecological studies of peatlands, particularly as indicators of surface wetness. To ensure data are robust and comparable it is important to consider methodological factors which may affect results. One significant question which has not been directly addressed in previous studies is how sample size (expressed here as number of Sphagnum stems) affects data quality. In three contrasting locations in a Russian peatland we extracted samples of differing size, analysed testate amoebae and calculated a number of widely-used indices: species richness, Simpson diversity, compositional dissimilarity from the largest sample and transfer function predictions of water table depth. We found that there was a trend for larger samples to contain more species across the range of commonly-used sample sizes in ecological studies. Smaller samples sometimes failed to produce counts of testate amoebae often considered minimally adequate. It seems likely that analyses based on samples of different sizes may not produce consistent data. Decisions about sample size need to reflect trade-offs between logistics, data quality, spatial resolution and the disturbance involved in sample extraction. For most common ecological applications we suggest that samples of more than eight Sphagnum stems are likely to be desirable. Copyright © 2017 Elsevier GmbH. All rights reserved.

Size and modal analyses of fines and ultrafines from some Apollo 17 samples

NASA Technical Reports Server (NTRS)

Greene, G. M.; King, D. T., Jr.; Banholzer, G. S., Jr.; King, E. A.

1975-01-01

Scanning electron and optical microscopy techniques have been used to determine the grain-size frequency distributions and morphology-based modal analyses of fine and ultrafine fractions of some Apollo 17 regolith samples. There are significant and large differences between the grain-size frequency distributions of the less than 10-micron size fraction of Apollo 17 samples, but there are no clear relations to the local geologic setting from which individual samples have been collected. This may be due to effective lateral mixing of regolith particles in this size range by micrometeoroid impacts. None of the properties of the frequency distributions support the idea of selective transport of any fine grain-size fraction, as has been proposed by other workers. All of the particle types found in the coarser size fractions also occur in the less than 10-micron particles. In the size range from 105 to 10 microns there is a strong tendency for the percentage of regularly shaped glass to increase as the graphic mean grain size of the less than 1-mm size fraction decreases, both probably being controlled by exposure age.

Effects of tree-to-tree variations on sap flux-based transpiration estimates in a forested watershed

NASA Astrophysics Data System (ADS)

Kume, Tomonori; Tsuruta, Kenji; Komatsu, Hikaru; Kumagai, Tomo'omi; Higashi, Naoko; Shinohara, Yoshinori; Otsuki, Kyoichi

2010-05-01

To estimate forest stand-scale water use, we assessed how sample sizes affect confidence of stand-scale transpiration (E) estimates calculated from sap flux (Fd) and sapwood area (AS_tree) measurements of individual trees. In a Japanese cypress plantation, we measured Fd and AS_tree in all trees (n = 58) within a 20 × 20 m study plot, which was divided into four 10 × 10 subplots. We calculated E from stand AS_tree (AS_stand) and mean stand Fd (JS) values. Using Monte Carlo analyses, we examined potential errors associated with sample sizes in E, AS_stand, and JS by using the original AS_tree and Fd data sets. Consequently, we defined optimal sample sizes of 10 and 15 for AS_stand and JS estimates, respectively, in the 20 × 20 m plot. Sample sizes greater than the optimal sample sizes did not decrease potential errors. The optimal sample sizes for JS changed according to plot size (e.g., 10 × 10 m and 10 × 20 m), while the optimal sample sizes for AS_stand did not. As well, the optimal sample sizes for JS did not change in different vapor pressure deficit conditions. In terms of E estimates, these results suggest that the tree-to-tree variations in Fd vary among different plots, and that plot size to capture tree-to-tree variations in Fd is an important factor. This study also discusses planning balanced sampling designs to extrapolate stand-scale estimates to catchment-scale estimates.

The local environment of ice particles in arctic mixed-phase clouds

NASA Astrophysics Data System (ADS)

Schlenczek, Oliver; Fugal, Jacob P.; Schledewitz, Waldemar; Borrmann, Stephan

2015-04-01

During the RACEPAC field campaign in April and May 2014, research flights were made with the Polar 5 and Polar 6 aircraft from the Alfred Wegener Institute in Arctic clouds near Inuvik, Northwest Territories, Canada. One flight with the Polar 6 aircraft, done on May 16, 2014, flew under precipitating, stratiform, mid-level clouds with several penetrations through cloud base. Measurements with HALOHolo, an airborne digital in-line holographic instrument for cloud particles, show ice particles in a field of other cloud particles in a local three-dimensional sample volume (~14x19x130 mm3 or ~35 cm^3). Each holographic sample volume is a snapshot of a 3-dimensional piece of cloud at the cm-scale with typically thousands of cloud droplets per sample volume, so each sample volume yields a statistically significant droplet size distribution. Holograms are recorded at a rate of six times per second, which provides one volume sample approx. every 12 meters along the flight path. The size resolution limit for cloud droplets is better than 1 µm due to advanced sizing algorithms. Shown are preliminary results of, (1) the ice/liquid water partitioning at the cloud base and the distribution of water droplets around each ice particle, and (2) spatial and temporal variability of the cloud droplet size distributions at cloud base.

Sample size adjustments for varying cluster sizes in cluster randomized trials with binary outcomes analyzed with second-order PQL mixed logistic regression.

PubMed

Candel, Math J J M; Van Breukelen, Gerard J P

2010-06-30

Adjustments of sample size formulas are given for varying cluster sizes in cluster randomized trials with a binary outcome when testing the treatment effect with mixed effects logistic regression using second-order penalized quasi-likelihood estimation (PQL). Starting from first-order marginal quasi-likelihood (MQL) estimation of the treatment effect, the asymptotic relative efficiency of unequal versus equal cluster sizes is derived. A Monte Carlo simulation study shows this asymptotic relative efficiency to be rather accurate for realistic sample sizes, when employing second-order PQL. An approximate, simpler formula is presented to estimate the efficiency loss due to varying cluster sizes when planning a trial. In many cases sampling 14 per cent more clusters is sufficient to repair the efficiency loss due to varying cluster sizes. Since current closed-form formulas for sample size calculation are based on first-order MQL, planning a trial also requires a conversion factor to obtain the variance of the second-order PQL estimator. In a second Monte Carlo study, this conversion factor turned out to be 1.25 at most. (c) 2010 John Wiley & Sons, Ltd.

Effect of resin infiltration on the thermal and mechanical properties of nano-sized silica-based thermal insulation.

PubMed

Lee, Jae Chun; Kim, Yun-Il; Lee, Dong-Hun; Kim, Won-Jun; Park, Sung; Lee, Dong Bok

2011-08-01

Several kinds of nano-sized silica-based thermal insulation were prepared by dry processing of mixtures consisting of fumed silica, ceramic fiber, and a SiC opacifier. Infiltration of phenolic resin solution into the insulation, followed by hot-pressing, was attempted to improve the mechanical strength of the insulation. More than 22% resin content was necessary to increase the strength of the insulation by a factor of two or more. The structural integrity of the resin-infiltrated samples could be maintained, even after resin burn-out, presumably due to reinforcement from ceramic fibers. For all temperature ranges and similar sample bulk density values, the thermal conductivities of the samples after resin burn-out were consistently higher than those of the samples obtained from the dry process. Mercury intrusion curves indicated that the median size of the nanopores formed by primary silica aggregates in the samples after resin burn-out is consistently larger than that of the sample without resin infiltration.

Inventory implications of using sampling variances in estimation of growth model coefficients

Treesearch

Albert R. Stage; William R. Wykoff

2000-01-01

Variables based on stand densities or stocking have sampling errors that depend on the relation of tree size to plot size and on the spatial structure of the population, ignoring the sampling errors of such variables, which include most measures of competition used in both distance-dependent and distance-independent growth models, can bias the predictions obtained from...

Novel joint selection methods can reduce sample size for rheumatoid arthritis clinical trials with ultrasound endpoints.

PubMed

Allen, John C; Thumboo, Julian; Lye, Weng Kit; Conaghan, Philip G; Chew, Li-Ching; Tan, York Kiat

2018-03-01

To determine whether novel methods of selecting joints through (i) ultrasonography (individualized-ultrasound [IUS] method), or (ii) ultrasonography and clinical examination (individualized-composite-ultrasound [ICUS] method) translate into smaller rheumatoid arthritis (RA) clinical trial sample sizes when compared to existing methods utilizing predetermined joint sites for ultrasonography. Cohen's effect size (ES) was estimated (ES^) and a 95% CI (ES^L, ES^U) calculated on a mean change in 3-month total inflammatory score for each method. Corresponding 95% CIs [nL(ES^U), nU(ES^L)] were obtained on a post hoc sample size reflecting the uncertainty in ES^. Sample size calculations were based on a one-sample t-test as the patient numbers needed to provide 80% power at α = 0.05 to reject a null hypothesis H 0 : ES = 0 versus alternative hypotheses H 1 : ES = ES^, ES = ES^L and ES = ES^U. We aimed to provide point and interval estimates on projected sample sizes for future studies reflecting the uncertainty in our study ES^S. Twenty-four treated RA patients were followed up for 3 months. Utilizing the 12-joint approach and existing methods, the post hoc sample size (95% CI) was 22 (10-245). Corresponding sample sizes using ICUS and IUS were 11 (7-40) and 11 (6-38), respectively. Utilizing a seven-joint approach, the corresponding sample sizes using ICUS and IUS methods were nine (6-24) and 11 (6-35), respectively. Our pilot study suggests that sample size for RA clinical trials with ultrasound endpoints may be reduced using the novel methods, providing justification for larger studies to confirm these observations. © 2017 Asia Pacific League of Associations for Rheumatology and John Wiley & Sons Australia, Ltd.

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.

Revisiting sample size: are big trials the answer?

PubMed

Lurati Buse, Giovanna A L; Botto, Fernando; Devereaux, P J

2012-07-18

The superiority of the evidence generated in randomized controlled trials over observational data is not only conditional to randomization. Randomized controlled trials require proper design and implementation to provide a reliable effect estimate. Adequate random sequence generation, allocation implementation, analyses based on the intention-to-treat principle, and sufficient power are crucial to the quality of a randomized controlled trial. Power, or the probability of the trial to detect a difference when a real difference between treatments exists, strongly depends on sample size. The quality of orthopaedic randomized controlled trials is frequently threatened by a limited sample size. This paper reviews basic concepts and pitfalls in sample-size estimation and focuses on the importance of large trials in the generation of valid evidence.

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...

76 FR 44590 - Agency Forms Undergoing Paperwork Reduction Act Review

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-26

... health training. This interview will be administered to a sample of approximately 30 owners of construction businesses with 10 or fewer employees from the Greater Cincinnati area. The sample size is based... size experiences the highest fatality rate within construction (U.S. Dept. of Labor, 2008). The need...

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...

Diet- and Body Size-Related Attitudes and Behaviors Associated with Vitamin Supplement Use in a Representative Sample of Fourth-Grade Students in Texas

ERIC Educational Resources Information Center

George, Goldy C.; Hoelscher, Deanna M.; Nicklas, Theresa A.; Kelder, Steven H.

2009-01-01

Objective: To examine diet- and body size-related attitudes and behaviors associated with supplement use in a representative sample of fourth-grade students in Texas. Design: Cross-sectional data from the School Physical Activity and Nutrition study, a probability-based sample of schoolchildren. Children completed a questionnaire that assessed…

Effect of sample area and sieve size on benthic macrofaunal community condition assessments in California enclosed bays and estuaries.

PubMed

Hammerstrom, Kamille K; Ranasinghe, J Ananda; Weisberg, Stephen B; Oliver, John S; Fairey, W Russell; Slattery, Peter N; Oakden, James M

2012-10-01

Benthic macrofauna are used extensively for environmental assessment, but the area sampled and sieve sizes used to capture animals often differ among studies. Here, we sampled 80 sites using 3 different sized sampling areas (0.1, 0.05, 0.0071 m(2)) and sieved those sediments through each of 2 screen sizes (0.5, 1 mm) to evaluate their effect on number of individuals, number of species, dominance, nonmetric multidimensional scaling (MDS) ordination, and benthic community condition indices that are used to assess sediment quality in California. Sample area had little effect on abundance but substantially affected numbers of species, which are not easily scaled to a standard area. Sieve size had a substantial effect on both measures, with the 1-mm screen capturing only 74% of the species and 68% of the individuals collected in the 0.5-mm screen. These differences, though, had little effect on the ability to differentiate samples along gradients in ordination space. Benthic indices generally ranked sample condition in the same order regardless of gear, although the absolute scoring of condition was affected by gear type. The largest differences in condition assessment were observed for the 0.0071-m(2) gear. Benthic indices based on numbers of species were more affected than those based on relative abundance, primarily because we were unable to scale species number to a common area as we did for abundance. Copyright © 2010 SETAC.

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.

Effects of sample size on estimates of population growth rates calculated with matrix models.

PubMed

Fiske, Ian J; Bruna, Emilio M; Bolker, Benjamin M

2008-08-28

Matrix models are widely used to study the dynamics and demography of populations. An important but overlooked issue is how the number of individuals sampled influences estimates of the population growth rate (lambda) calculated with matrix models. Even unbiased estimates of vital rates do not ensure unbiased estimates of lambda-Jensen's Inequality implies that even when the estimates of the vital rates are accurate, small sample sizes lead to biased estimates of lambda due to increased sampling variance. We investigated if sampling variability and the distribution of sampling effort among size classes lead to biases in estimates of lambda. Using data from a long-term field study of plant demography, we simulated the effects of sampling variance by drawing vital rates and calculating lambda for increasingly larger populations drawn from a total population of 3842 plants. We then compared these estimates of lambda with those based on the entire population and calculated the resulting bias. Finally, we conducted a review of the literature to determine the sample sizes typically used when parameterizing matrix models used to study plant demography. We found significant bias at small sample sizes when survival was low (survival = 0.5), and that sampling with a more-realistic inverse J-shaped population structure exacerbated this bias. However our simulations also demonstrate that these biases rapidly become negligible with increasing sample sizes or as survival increases. For many of the sample sizes used in demographic studies, matrix models are probably robust to the biases resulting from sampling variance of vital rates. However, this conclusion may depend on the structure of populations or the distribution of sampling effort in ways that are unexplored. We suggest more intensive sampling of populations when individual survival is low and greater sampling of stages with high elasticities.

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.

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.

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).

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

Reproducibility of preclinical animal research improves with heterogeneity of study samples

PubMed Central

Vogt, Lucile; Sena, Emily S.; Würbel, Hanno

2018-01-01

Single-laboratory studies conducted under highly standardized conditions are the gold standard in preclinical animal research. Using simulations based on 440 preclinical studies across 13 different interventions in animal models of stroke, myocardial infarction, and breast cancer, we compared the accuracy of effect size estimates between single-laboratory and multi-laboratory study designs. Single-laboratory studies generally failed to predict effect size accurately, and larger sample sizes rendered effect size estimates even less accurate. By contrast, multi-laboratory designs including as few as 2 to 4 laboratories increased coverage probability by up to 42 percentage points without a need for larger sample sizes. These findings demonstrate that within-study standardization is a major cause of poor reproducibility. More representative study samples are required to improve the external validity and reproducibility of preclinical animal research and to prevent wasting animals and resources for inconclusive research. PMID:29470495

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.

Addressing small sample size bias in multiple-biomarker trials: Inclusion of biomarker-negative patients and Firth correction.

PubMed

Habermehl, Christina; Benner, Axel; Kopp-Schneider, Annette

2018-03-01

In recent years, numerous approaches for biomarker-based clinical trials have been developed. One of these developments are multiple-biomarker trials, which aim to investigate multiple biomarkers simultaneously in independent subtrials. For low-prevalence biomarkers, small sample sizes within the subtrials have to be expected, as well as many biomarker-negative patients at the screening stage. The small sample sizes may make it unfeasible to analyze the subtrials individually. This imposes the need to develop new approaches for the analysis of such trials. With an expected large group of biomarker-negative patients, it seems reasonable to explore options to benefit from including them in such trials. We consider advantages and disadvantages of the inclusion of biomarker-negative patients in a multiple-biomarker trial with a survival endpoint. We discuss design options that include biomarker-negative patients in the study and address the issue of small sample size bias in such trials. We carry out a simulation study for a design where biomarker-negative patients are kept in the study and are treated with standard of care. We compare three different analysis approaches based on the Cox model to examine if the inclusion of biomarker-negative patients can provide a benefit with respect to bias and variance of the treatment effect estimates. We apply the Firth correction to reduce the small sample size bias. The results of the simulation study suggest that for small sample situations, the Firth correction should be applied to adjust for the small sample size bias. Additional to the Firth penalty, the inclusion of biomarker-negative patients in the analysis can lead to further but small improvements in bias and standard deviation of the estimates. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.…

What is an adequate sample size? Operationalising data saturation for theory-based interview studies.

PubMed

Francis, Jill J; Johnston, Marie; Robertson, Clare; Glidewell, Liz; Entwistle, Vikki; Eccles, Martin P; Grimshaw, Jeremy M

2010-12-01

In interview studies, sample size is often justified by interviewing participants until reaching 'data saturation'. However, there is no agreed method of establishing this. We propose principles for deciding saturation in theory-based interview studies (where conceptual categories are pre-established by existing theory). First, specify a minimum sample size for initial analysis (initial analysis sample). Second, specify how many more interviews will be conducted without new ideas emerging (stopping criterion). We demonstrate these principles in two studies, based on the theory of planned behaviour, designed to identify three belief categories (Behavioural, Normative and Control), using an initial analysis sample of 10 and stopping criterion of 3. Study 1 (retrospective analysis of existing data) identified 84 shared beliefs of 14 general medical practitioners about managing patients with sore throat without prescribing antibiotics. The criterion for saturation was achieved for Normative beliefs but not for other beliefs or studywise saturation. In Study 2 (prospective analysis), 17 relatives of people with Paget's disease of the bone reported 44 shared beliefs about taking genetic testing. Studywise data saturation was achieved at interview 17. We propose specification of these principles for reporting data saturation in theory-based interview studies. The principles may be adaptable for other types of studies.

Interpreting and Reporting Effect Sizes in Research Investigations.

ERIC Educational Resources Information Center

Tapia, Martha; Marsh, George E., II

Since 1994, the American Psychological Association (APA) has advocated the inclusion of effect size indices in reporting research to elucidate the statistical significance of studies based on sample size. In 2001, the fifth edition of the APA "Publication Manual" stressed the importance of including an index of effect size to clarify…

Conservative Sample Size Determination for Repeated Measures Analysis of Covariance.

PubMed

Morgan, Timothy M; Case, L Douglas

2013-07-05

In the design of a randomized clinical trial with one pre and multiple post randomized assessments of the outcome variable, one needs to account for the repeated measures in determining the appropriate sample size. Unfortunately, one seldom has a good estimate of the variance of the outcome measure, let alone the correlations among the measurements over time. We show how sample sizes can be calculated by making conservative assumptions regarding the correlations for a variety of covariance structures. The most conservative choice for the correlation depends on the covariance structure and the number of repeated measures. In the absence of good estimates of the correlations, the sample size is often based on a two-sample t-test, making the 'ultra' conservative and unrealistic assumption that there are zero correlations between the baseline and follow-up measures while at the same time assuming there are perfect correlations between the follow-up measures. Compared to the case of taking a single measurement, substantial savings in sample size can be realized by accounting for the repeated measures, even with very conservative assumptions regarding the parameters of the assumed correlation matrix. Assuming compound symmetry, the sample size from the two-sample t-test calculation can be reduced at least 44%, 56%, and 61% for repeated measures analysis of covariance by taking 2, 3, and 4 follow-up measures, respectively. The results offer a rational basis for determining a fairly conservative, yet efficient, sample size for clinical trials with repeated measures and a baseline value.

A U-statistics based approach to sample size planning of two-arm trials with discrete outcome criterion aiming to establish either superiority or noninferiority.

PubMed

Wellek, Stefan

2017-02-28

In current practice, the most frequently applied approach to the handling of ties in the Mann-Whitney-Wilcoxon (MWW) test is based on the conditional distribution of the sum of mid-ranks, given the observed pattern of ties. Starting from this conditional version of the testing procedure, a sample size formula was derived and investigated by Zhao et al. (Stat Med 2008). In contrast, the approach we pursue here is a nonconditional one exploiting explicit representations for the variances of and the covariance between the two U-statistics estimators involved in the Mann-Whitney form of the test statistic. The accuracy of both ways of approximating the sample sizes required for attaining a prespecified level of power in the MWW test for superiority with arbitrarily tied data is comparatively evaluated by means of simulation. The key qualitative conclusions to be drawn from these numerical comparisons are as follows: With the sample sizes calculated by means of the respective formula, both versions of the test maintain the level and the prespecified power with about the same degree of accuracy. Despite the equivalence in terms of accuracy, the sample size estimates obtained by means of the new formula are in many cases markedly lower than that calculated for the conditional test. Perhaps, a still more important advantage of the nonconditional approach based on U-statistics is that it can be also adopted for noninferiority trials. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Robustness of methods for blinded sample size re-estimation with overdispersed count data.

PubMed

Schneider, Simon; Schmidli, Heinz; Friede, Tim

2013-09-20

Counts of events are increasingly common as primary endpoints in randomized clinical trials. With between-patient heterogeneity leading to variances in excess of the mean (referred to as overdispersion), statistical models reflecting this heterogeneity by mixtures of Poisson distributions are frequently employed. Sample size calculation in the planning of such trials requires knowledge on the nuisance parameters, that is, the control (or overall) event rate and the overdispersion parameter. Usually, there is only little prior knowledge regarding these parameters in the design phase resulting in considerable uncertainty regarding the sample size. In this situation internal pilot studies have been found very useful and very recently several blinded procedures for sample size re-estimation have been proposed for overdispersed count data, one of which is based on an EM-algorithm. In this paper we investigate the EM-algorithm based procedure with respect to aspects of their implementation by studying the algorithm's dependence on the choice of convergence criterion and find that the procedure is sensitive to the choice of the stopping criterion in scenarios relevant to clinical practice. We also compare the EM-based procedure to other competing procedures regarding their operating characteristics such as sample size distribution and power. Furthermore, the robustness of these procedures to deviations from the model assumptions is explored. We find that some of the procedures are robust to at least moderate deviations. The results are illustrated using data from the US National Heart, Lung and Blood Institute sponsored Asymptomatic Cardiac Ischemia Pilot study. Copyright © 2013 John Wiley & Sons, Ltd.

Spatial variations in annual cycles of body-size spectra of planktonic ciliates and their environmental drivers in marine ecosystems.

PubMed

Xu, Henglong; Jiang, Yong; Xu, Guangjian

2016-11-15

Body-size spectra has proved to be a useful taxon-free resolution to summarize a community structure for bioassessment. The spatial variations in annual cycles of body-size spectra of planktonic ciliates and their environmental drivers were studied based on an annual dataset. Samples were biweekly collected at five stations in a bay of the Yellow Sea, northern China during a 1-year cycle. Based on a multivariate approach, the second-stage analysis, it was shown that the annual cycles of the body-size spectra were significantly different among five sampling stations. Correlation analysis demonstrated that the spatial variations in the body-size spectra were significantly related to changes of environmental conditions, especially dissolved nitrogen, alone or in combination with salinity and dissolve oxygen. Based on results, it is suggested that the nutrients may be the environmental drivers to shape the spatial variations in annual cycles of planktonic ciliates in terms of body-size spectra in marine ecosystems. Copyright © 2016 Elsevier Ltd. All rights reserved.

The effective elastic properties of human trabecular bone may be approximated using micro-finite element analyses of embedded volume elements.

PubMed

Daszkiewicz, Karol; Maquer, Ghislain; Zysset, Philippe K

2017-06-01

Boundary conditions (BCs) and sample size affect the measured elastic properties of cancellous bone. Samples too small to be representative appear stiffer under kinematic uniform BCs (KUBCs) than under periodicity-compatible mixed uniform BCs (PMUBCs). To avoid those effects, we propose to determine the effective properties of trabecular bone using an embedded configuration. Cubic samples of various sizes (2.63, 5.29, 7.96, 10.58 and 15.87 mm) were cropped from [Formula: see text] scans of femoral heads and vertebral bodies. They were converted into [Formula: see text] models and their stiffness tensor was established via six uniaxial and shear load cases. PMUBCs- and KUBCs-based tensors were determined for each sample. "In situ" stiffness tensors were also evaluated for the embedded configuration, i.e. when the loads were transmitted to the samples via a layer of trabecular bone. The Zysset-Curnier model accounting for bone volume fraction and fabric anisotropy was fitted to those stiffness tensors, and model parameters [Formula: see text] (Poisson's ratio) [Formula: see text] and [Formula: see text] (elastic and shear moduli) were compared between sizes. BCs and sample size had little impact on [Formula: see text]. However, KUBCs- and PMUBCs-based [Formula: see text] and [Formula: see text], respectively, decreased and increased with growing size, though convergence was not reached even for our largest samples. Both BCs produced upper and lower bounds for the in situ values that were almost constant across samples dimensions, thus appearing as an approximation of the effective properties. PMUBCs seem also appropriate for mimicking the trabecular core, but they still underestimate its elastic properties (especially in shear) even for nearly orthotropic samples.

The effects of sample size on population genomic analyses--implications for the tests of neutrality.

PubMed

Subramanian, Sankar

2016-02-20

One of the fundamental measures of molecular genetic variation is the Watterson's estimator (θ), which is based on the number of segregating sites. The estimation of θ is unbiased only under neutrality and constant population growth. It is well known that the estimation of θ is biased when these assumptions are violated. However, the effects of sample size in modulating the bias was not well appreciated. We examined this issue in detail based on large-scale exome data and robust simulations. Our investigation revealed that sample size appreciably influences θ estimation and this effect was much higher for constrained genomic regions than that of neutral regions. For instance, θ estimated for synonymous sites using 512 human exomes was 1.9 times higher than that obtained using 16 exomes. However, this difference was 2.5 times for the nonsynonymous sites of the same data. We observed a positive correlation between the rate of increase in θ estimates (with respect to the sample size) and the magnitude of selection pressure. For example, θ estimated for the nonsynonymous sites of highly constrained genes (dN/dS < 0.1) using 512 exomes was 3.6 times higher than that estimated using 16 exomes. In contrast this difference was only 2 times for the less constrained genes (dN/dS > 0.9). The results of this study reveal the extent of underestimation owing to small sample sizes and thus emphasize the importance of sample size in estimating a number of population genomic parameters. Our results have serious implications for neutrality tests such as Tajima D, Fu-Li D and those based on the McDonald and Kreitman test: Neutrality Index and the fraction of adaptive substitutions. For instance, use of 16 exomes produced 2.4 times higher proportion of adaptive substitutions compared to that obtained using 512 exomes (24% vs 10 %).

Sample size and number of outcome measures of veterinary randomised controlled trials of pharmaceutical interventions funded by different sources, a cross-sectional study.

PubMed

Wareham, K J; Hyde, R M; Grindlay, D; Brennan, M L; Dean, R S

2017-10-04

Randomised controlled trials (RCTs) are a key component of the veterinary evidence base. Sample sizes and defined outcome measures are crucial components of RCTs. To describe the sample size and number of outcome measures of veterinary RCTs either funded by the pharmaceutical industry or not, published in 2011. A structured search of PubMed identified RCTs examining the efficacy of pharmaceutical interventions. Number of outcome measures, number of animals enrolled per trial, whether a primary outcome was identified, and the presence of a sample size calculation were extracted from the RCTs. The source of funding was identified for each trial and groups compared on the above parameters. Literature searches returned 972 papers; 86 papers comprising 126 individual trials were analysed. The median number of outcomes per trial was 5.0; there were no significant differences across funding groups (p = 0.133). The median number of animals enrolled per trial was 30.0; this was similar across funding groups (p = 0.302). A primary outcome was identified in 40.5% of trials and was significantly more likely to be stated in trials funded by a pharmaceutical company. A very low percentage of trials reported a sample size calculation (14.3%). Failure to report primary outcomes, justify sample sizes and the reporting of multiple outcome measures was a common feature in all of the clinical trials examined in this study. It is possible some of these factors may be affected by the source of funding of the studies, but the influence of funding needs to be explored with a larger number of trials. Some veterinary RCTs provide a weak evidence base and targeted strategies are required to improve the quality of veterinary RCTs to ensure there is reliable evidence on which to base clinical decisions.

The large sample size fallacy.

PubMed

Lantz, Björn

2013-06-01

Significance in the statistical sense has little to do with significance in the common practical sense. Statistical significance is a necessary but not a sufficient condition for practical significance. Hence, results that are extremely statistically significant may be highly nonsignificant in practice. The degree of practical significance is generally determined by the size of the observed effect, not the p-value. The results of studies based on large samples are often characterized by extreme statistical significance despite small or even trivial effect sizes. Interpreting such results as significant in practice without further analysis is referred to as the large sample size fallacy in this article. The aim of this article is to explore the relevance of the large sample size fallacy in contemporary nursing research. Relatively few nursing articles display explicit measures of observed effect sizes or include a qualitative discussion of observed effect sizes. Statistical significance is often treated as an end in itself. Effect sizes should generally be calculated and presented along with p-values for statistically significant results, and observed effect sizes should be discussed qualitatively through direct and explicit comparisons with the effects in related literature. © 2012 Nordic College of Caring Science.

Model selection with multiple regression on distance matrices leads to incorrect inferences.

PubMed

Franckowiak, Ryan P; Panasci, Michael; Jarvis, Karl J; Acuña-Rodriguez, Ian S; Landguth, Erin L; Fortin, Marie-Josée; Wagner, Helene H

2017-01-01

In landscape genetics, model selection procedures based on Information Theoretic and Bayesian principles have been used with multiple regression on distance matrices (MRM) to test the relationship between multiple vectors of pairwise genetic, geographic, and environmental distance. Using Monte Carlo simulations, we examined the ability of model selection criteria based on Akaike's information criterion (AIC), its small-sample correction (AICc), and the Bayesian information criterion (BIC) to reliably rank candidate models when applied with MRM while varying the sample size. The results showed a serious problem: all three criteria exhibit a systematic bias toward selecting unnecessarily complex models containing spurious random variables and erroneously suggest a high level of support for the incorrectly ranked best model. These problems effectively increased with increasing sample size. The failure of AIC, AICc, and BIC was likely driven by the inflated sample size and different sum-of-squares partitioned by MRM, and the resulting effect on delta values. Based on these findings, we strongly discourage the continued application of AIC, AICc, and BIC for model selection with MRM.

Freeze-cast alumina pore networks: Effects of freezing conditions and dispersion medium

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

Miller, S. M.; Xiao, X.; Faber, K. T.

Alumina ceramics were freeze-cast from water- and camphene-based slurries under varying freezing conditions and examined using X-ray computed tomography (XCT). Pore network characteristics, i.e., porosity, pore size, geometric surface area, and tortuosity, were measured from XCT reconstructions and the data were used to develop a model to predict feature size from processing conditions. Classical solidification theory was used to examine relationships between pore size, temperature gradients, and freezing front velocity. Freezing front velocity was subsequently predicted from casting conditions via the two-phase Stefan problem. Resulting models for water-based samples agreed with solidification-based theories predicting lamellar spacing of binary eutectic alloys,more » and models for camphene-based samples concurred with those for dendritic growth. Relationships between freezing conditions and geometric surface area were also modeled by considering the inverse relationship between pore size and surface area. Tortuosity was determined to be dependent primarily on the type of dispersion medium. (C) 2015 Elsevier Ltd. All rights reserved.« less

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

Development of a copula-based particle filter (CopPF) approach for hydrologic data assimilation under consideration of parameter interdependence

NASA Astrophysics Data System (ADS)

Fan, Y. R.; Huang, G. H.; Baetz, B. W.; Li, Y. P.; Huang, K.

2017-06-01

In this study, a copula-based particle filter (CopPF) approach was developed for sequential hydrological data assimilation by considering parameter correlation structures. In CopPF, multivariate copulas are proposed to reflect parameter interdependence before the resampling procedure with new particles then being sampled from the obtained copulas. Such a process can overcome both particle degeneration and sample impoverishment. The applicability of CopPF is illustrated with three case studies using a two-parameter simplified model and two conceptual hydrologic models. The results for the simplified model indicate that model parameters are highly correlated in the data assimilation process, suggesting a demand for full description of their dependence structure. Synthetic experiments on hydrologic data assimilation indicate that CopPF can rejuvenate particle evolution in large spaces and thus achieve good performances with low sample size scenarios. The applicability of CopPF is further illustrated through two real-case studies. It is shown that, compared with traditional particle filter (PF) and particle Markov chain Monte Carlo (PMCMC) approaches, the proposed method can provide more accurate results for both deterministic and probabilistic prediction with a sample size of 100. Furthermore, the sample size would not significantly influence the performance of CopPF. Also, the copula resampling approach dominates parameter evolution in CopPF, with more than 50% of particles sampled by copulas in most sample size scenarios.

Optimal number of features as a function of sample size for various classification rules.

PubMed

Hua, Jianping; Xiong, Zixiang; Lowey, James; Suh, Edward; Dougherty, Edward R

2005-04-15

Given the joint feature-label distribution, increasing the number of features always results in decreased classification error; however, this is not the case when a classifier is designed via a classification rule from sample data. Typically (but not always), for fixed sample size, the error of a designed classifier decreases and then increases as the number of features grows. The potential downside of using too many features is most critical for small samples, which are commonplace for gene-expression-based classifiers for phenotype discrimination. For fixed sample size and feature-label distribution, the issue is to find an optimal number of features. Since only in rare cases is there a known distribution of the error as a function of the number of features and sample size, this study employs simulation for various feature-label distributions and classification rules, and across a wide range of sample and feature-set sizes. To achieve the desired end, finding the optimal number of features as a function of sample size, it employs massively parallel computation. Seven classifiers are treated: 3-nearest-neighbor, Gaussian kernel, linear support vector machine, polynomial support vector machine, perceptron, regular histogram and linear discriminant analysis. Three Gaussian-based models are considered: linear, nonlinear and bimodal. In addition, real patient data from a large breast-cancer study is considered. To mitigate the combinatorial search for finding optimal feature sets, and to model the situation in which subsets of genes are co-regulated and correlation is internal to these subsets, we assume that the covariance matrix of the features is blocked, with each block corresponding to a group of correlated features. Altogether there are a large number of error surfaces for the many cases. These are provided in full on a companion website, which is meant to serve as resource for those working with small-sample classification. For the companion website, please visit http://public.tgen.org/tamu/ofs/ e-dougherty@ee.tamu.edu.

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.

A Fracture Mechanics Approach to Thermal Shock Investigation in Alumina-Based Refractory

NASA Astrophysics Data System (ADS)

Volkov-Husović, T.; Heinemann, R. Jančić; Mitraković, D.

2008-02-01

The thermal shock behavior of large grain size, alumina-based refractories was investigated experimentally using a standard water quench test. A mathematical model was employed to simulate the thermal stability behavior. Behavior of the samples under repeated thermal shock was monitored using ultrasonic measurements of dynamic Young's modulus. Image analysis was used to observe the extent of surface degradation. Analysis of the obtained results for the behavior of large grain size samples under conditions of rapid temperature changes is given.

Size selective isocyanate aerosols personal air sampling using porous plastic foams

NASA Astrophysics Data System (ADS)

Khanh Huynh, Cong; Duc, Trinh Vu

2009-02-01

As part of a European project (SMT4-CT96-2137), various European institutions specialized in occupational hygiene (BGIA, HSL, IOM, INRS, IST, Ambiente e Lavoro) have established a program of scientific collaboration to develop one or more prototypes of European personal samplers for the collection of simultaneous three dust fractions: inhalable, thoracic and respirable. These samplers based on existing sampling heads (IOM, GSP and cassettes) use Polyurethane Plastic Foam (PUF) according to their porosity to support sampling and separator size of the particles. In this study, the authors present an original application of size selective personal air sampling using chemical impregnated PUF to perform isocyanate aerosols capturing and derivatizing in industrial spray-painting shops.

Standardized mean differences cause funnel plot distortion in publication bias assessments.

PubMed

Zwetsloot, Peter-Paul; Van Der Naald, Mira; Sena, Emily S; Howells, David W; IntHout, Joanna; De Groot, Joris Ah; Chamuleau, Steven Aj; MacLeod, Malcolm R; Wever, Kimberley E

2017-09-08

Meta-analyses are increasingly used for synthesis of evidence from biomedical research, and often include an assessment of publication bias based on visual or analytical detection of asymmetry in funnel plots. We studied the influence of different normalisation approaches, sample size and intervention effects on funnel plot asymmetry, using empirical datasets and illustrative simulations. We found that funnel plots of the Standardized Mean Difference (SMD) plotted against the standard error (SE) are susceptible to distortion, leading to overestimation of the existence and extent of publication bias. Distortion was more severe when the primary studies had a small sample size and when an intervention effect was present. We show that using the Normalised Mean Difference measure as effect size (when possible), or plotting the SMD against a sample size-based precision estimate, are more reliable alternatives. We conclude that funnel plots using the SMD in combination with the SE are unsuitable for publication bias assessments and can lead to false-positive results.

Standardized mean differences cause funnel plot distortion in publication bias assessments

PubMed Central

Van Der Naald, Mira; Sena, Emily S; Howells, David W; IntHout, Joanna; De Groot, Joris AH; Chamuleau, Steven AJ; MacLeod, Malcolm R

2017-01-01

Meta-analyses are increasingly used for synthesis of evidence from biomedical research, and often include an assessment of publication bias based on visual or analytical detection of asymmetry in funnel plots. We studied the influence of different normalisation approaches, sample size and intervention effects on funnel plot asymmetry, using empirical datasets and illustrative simulations. We found that funnel plots of the Standardized Mean Difference (SMD) plotted against the standard error (SE) are susceptible to distortion, leading to overestimation of the existence and extent of publication bias. Distortion was more severe when the primary studies had a small sample size and when an intervention effect was present. We show that using the Normalised Mean Difference measure as effect size (when possible), or plotting the SMD against a sample size-based precision estimate, are more reliable alternatives. We conclude that funnel plots using the SMD in combination with the SE are unsuitable for publication bias assessments and can lead to false-positive results. PMID:28884685

Four hundred or more participants needed for stable contingency table estimates of clinical prediction rule performance.

PubMed

Kent, Peter; Boyle, Eleanor; Keating, Jennifer L; Albert, Hanne B; Hartvigsen, Jan

2017-02-01

To quantify variability in the results of statistical analyses based on contingency tables and discuss the implications for the choice of sample size for studies that derive clinical prediction rules. An analysis of three pre-existing sets of large cohort data (n = 4,062-8,674) was performed. In each data set, repeated random sampling of various sample sizes, from n = 100 up to n = 2,000, was performed 100 times at each sample size and the variability in estimates of sensitivity, specificity, positive and negative likelihood ratios, posttest probabilities, odds ratios, and risk/prevalence ratios for each sample size was calculated. There were very wide, and statistically significant, differences in estimates derived from contingency tables from the same data set when calculated in sample sizes below 400 people, and typically, this variability stabilized in samples of 400-600 people. Although estimates of prevalence also varied significantly in samples below 600 people, that relationship only explains a small component of the variability in these statistical parameters. To reduce sample-specific variability, contingency tables should consist of 400 participants or more when used to derive clinical prediction rules or test their performance. Copyright © 2016 Elsevier Inc. All rights reserved.

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

ERIC Educational Resources Information Center

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

2014-01-01

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

An improved methodology of asymmetric flow field flow fractionation hyphenated with inductively coupled mass spectrometry for the determination of size distribution of gold nanoparticles in dietary supplements.

PubMed

Mudalige, Thilak K; Qu, Haiou; Linder, Sean W

2015-11-13

Engineered nanoparticles are available in large numbers of commercial products claiming various health benefits. Nanoparticle absorption, distribution, metabolism, excretion, and toxicity in a biological system are dependent on particle size, thus the determination of size and size distribution is essential for full characterization. Number based average size and size distribution is a major parameter for full characterization of the nanoparticle. In the case of polydispersed samples, large numbers of particles are needed to obtain accurate size distribution data. Herein, we report a rapid methodology, demonstrating improved nanoparticle recovery and excellent size resolution, for the characterization of gold nanoparticles in dietary supplements using asymmetric flow field flow fractionation coupled with visible absorption spectrometry and inductively coupled plasma mass spectrometry. A linear relationship between gold nanoparticle size and retention times was observed, and used for characterization of unknown samples. The particle size results from unknown samples were compared to results from traditional size analysis by transmission electron microscopy, and found to have less than a 5% deviation in size for unknown product over the size range from 7 to 30 nm. Published by Elsevier B.V.

Go big or … don't? A field-based diet evaluation of freshwater piscivore and prey fish size relationships

PubMed Central

Ahrenstorff, Tyler D.; Diana, James S.; Fetzer, William W.; Jones, Thomas S.; Lawson, Zach J.; McInerny, Michael C.; Santucci, Victor J.; Vander Zanden, M. Jake

2018-01-01

Body size governs predator-prey interactions, which in turn structure populations, communities, and food webs. Understanding predator-prey size relationships is valuable from a theoretical perspective, in basic research, and for management applications. However, predator-prey size data are limited and costly to acquire. We quantified predator-prey total length and mass relationships for several freshwater piscivorous taxa: crappie (Pomoxis spp.), largemouth bass (Micropterus salmoides), muskellunge (Esox masquinongy), northern pike (Esox lucius), rock bass (Ambloplites rupestris), smallmouth bass (Micropterus dolomieu), and walleye (Sander vitreus). The range of prey total lengths increased with predator total length. The median and maximum ingested prey total length varied with predator taxon and length, but generally ranged from 10–20% and 32–46% of predator total length, respectively. Predators tended to consume larger fusiform prey than laterally compressed prey. With the exception of large muskellunge, predators most commonly consumed prey between 16 and 73 mm. A sensitivity analysis indicated estimates can be very accurate at sample sizes greater than 1,000 diet items and fairly accurate at sample sizes greater than 100. However, sample sizes less than 50 should be evaluated with caution. Furthermore, median log10 predator-prey body mass ratios ranged from 1.9–2.5, nearly 50% lower than values previously reported for freshwater fishes. Managers, researchers, and modelers could use our findings as a tool for numerous predator-prey evaluations from stocking size optimization to individual-based bioenergetics analyses identifying prey size structure. To this end, we have developed a web-based user interface to maximize the utility of our models that can be found at www.LakeEcologyLab.org/pred_prey. PMID:29543856

Go big or … don't? A field-based diet evaluation of freshwater piscivore and prey fish size relationships.

PubMed

Gaeta, Jereme W; Ahrenstorff, Tyler D; Diana, James S; Fetzer, William W; Jones, Thomas S; Lawson, Zach J; McInerny, Michael C; Santucci, Victor J; Vander Zanden, M Jake

2018-01-01

Body size governs predator-prey interactions, which in turn structure populations, communities, and food webs. Understanding predator-prey size relationships is valuable from a theoretical perspective, in basic research, and for management applications. However, predator-prey size data are limited and costly to acquire. We quantified predator-prey total length and mass relationships for several freshwater piscivorous taxa: crappie (Pomoxis spp.), largemouth bass (Micropterus salmoides), muskellunge (Esox masquinongy), northern pike (Esox lucius), rock bass (Ambloplites rupestris), smallmouth bass (Micropterus dolomieu), and walleye (Sander vitreus). The range of prey total lengths increased with predator total length. The median and maximum ingested prey total length varied with predator taxon and length, but generally ranged from 10-20% and 32-46% of predator total length, respectively. Predators tended to consume larger fusiform prey than laterally compressed prey. With the exception of large muskellunge, predators most commonly consumed prey between 16 and 73 mm. A sensitivity analysis indicated estimates can be very accurate at sample sizes greater than 1,000 diet items and fairly accurate at sample sizes greater than 100. However, sample sizes less than 50 should be evaluated with caution. Furthermore, median log10 predator-prey body mass ratios ranged from 1.9-2.5, nearly 50% lower than values previously reported for freshwater fishes. Managers, researchers, and modelers could use our findings as a tool for numerous predator-prey evaluations from stocking size optimization to individual-based bioenergetics analyses identifying prey size structure. To this end, we have developed a web-based user interface to maximize the utility of our models that can be found at www.LakeEcologyLab.org/pred_prey.

Magnetic hyperthermia in water based ferrofluids: Effects of initial susceptibility and size polydispersity on heating efficiency

NASA Astrophysics Data System (ADS)

Lahiri, B. B.; Ranoo, Surojit; Muthukumaran, T.; Philip, John

2018-04-01

The effects of initial susceptibility and size polydispersity on magnetic hyperthermia efficiency in two water based ferrofluids containing phosphate and TMAOH coated superparamagnetic Fe3O4 nanoparticles were studied. Experiments were performed at a fixed frequency of 126 kHz on four different concentrations of both samples and under different external field amplitudes. It was observed that for field amplitudes beyond 45.0 kAm-1, the maximum temperature rise was in the vicinity of 42°C (hyperthermia limit) which indicated the suitability of the water based ferrofluids for hyperthermia applications. The maximum temperature rise and specific absorption rate were found to vary linearly with square of the applied field amplitudes, in accordance with theoretical predictions. It was further observed that for a fixed sample concentration, specific absorption rate was higher for the phosphate coated samples which was attributed to the higher initial static susceptibility and lower size polydispersity of phosphate coated Fe3O4.

Spatial interpolation techniques using R

EPA Science Inventory

Interpolation techniques are used to predict the cell values of a raster based on sample data points. For example, interpolation can be used to predict the distribution of sediment particle size throughout an estuary based on discrete sediment samples. We demonstrate some inter...

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.

Synthesis of Copper Birnessite, Cu xMnO y·nH 2O with Crystallite Size Control: Impact of Crystallite Size on Electrochemistry

DOE PAGES

Li, Yue Ru; Marschilok, Amy C.; Takeuchi, Esther S.; ...

2015-11-24

This report describes the first detailed electrochemical examination of a series of copper birnessite samples under lithium-based battery conditions, allowing a structure/function analysis of the electrochemistry and related material properties. To obtain the series of copper birnessite samples, a novel synthetic approach for the preparation of copper birnessite, Cu xMnO y·nH 2O is reported. The copper content (x) in Cu xMnO y·nH 2O, 0.28 >= x >= 0.20, was inversely proportional to crystallite size, which ranged from 12 to 19 nm. The electrochemistry under lithium-based battery conditions showed that the higher copper content (x = 0.28) and small crystallite sizemore » (similar to 12 nm) sample delivered similar to 194 mAh/g, about 20% higher capacity than the low copper content (x = 0.22) and larger crystallite size (similar to 19 nm) material. In addition, Cu xMnO y·nH 2O displays quasi-reversible electrochemistry in magnesium based electrolytes, indicating that copper birnessite could be a candidate for future application in magnesium-ion batteries.« less

[An investigation of the statistical power of the effect size in randomized controlled trials for the treatment of patients with type 2 diabetes mellitus using Chinese medicine].

PubMed

Ma, Li-Xin; Liu, Jian-Ping

2012-01-01

To investigate whether the power of the effect size was based on adequate sample size in randomized controlled trials (RCTs) for the treatment of patients with type 2 diabetes mellitus (T2DM) using Chinese medicine. China Knowledge Resource Integrated Database (CNKI), VIP Database for Chinese Technical Periodicals (VIP), Chinese Biomedical Database (CBM), and Wangfang Data were systematically recruited using terms like "Xiaoke" or diabetes, Chinese herbal medicine, patent medicine, traditional Chinese medicine, randomized, controlled, blinded, and placebo-controlled. Limitation was set on the intervention course > or = 3 months in order to identify the information of outcome assessement and the sample size. Data collection forms were made according to the checking lists found in the CONSORT statement. Independent double data extractions were performed on all included trials. The statistical power of the effects size for each RCT study was assessed using sample size calculation equations. (1) A total of 207 RCTs were included, including 111 superiority trials and 96 non-inferiority trials. (2) Among the 111 superiority trials, fasting plasma glucose (FPG) and glycosylated hemoglobin HbA1c (HbA1c) outcome measure were reported in 9% and 12% of the RCTs respectively with the sample size > 150 in each trial. For the outcome of HbA1c, only 10% of the RCTs had more than 80% power. For FPG, 23% of the RCTs had more than 80% power. (3) In the 96 non-inferiority trials, the outcomes FPG and HbA1c were reported as 31% and 36% respectively. These RCTs had a samples size > 150. For HbA1c only 36% of the RCTs had more than 80% power. For FPG, only 27% of the studies had more than 80% power. The sample size for statistical analysis was distressingly low and most RCTs did not achieve 80% power. In order to obtain a sufficient statistic power, it is recommended that clinical trials should establish clear research objective and hypothesis first, and choose scientific and evidence-based study design and outcome measurements. At the same time, calculate required sample size to ensure a precise research conclusion.

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

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/

Got Power? A Systematic Review of Sample Size Adequacy in Health Professions Education Research

ERIC Educational Resources Information Center

Cook, David A.; Hatala, Rose

2015-01-01

Many education research studies employ small samples, which in turn lowers statistical power. We re-analyzed the results of a meta-analysis of simulation-based education to determine study power across a range of effect sizes, and the smallest effect that could be plausibly excluded. We systematically searched multiple databases through May 2011,…

Thermal conductivity of graphene mediated by strain and size

DOE PAGES

Kuang, Youdi; Shi, Sanqiang; Wang, Xinjiang; ...

2016-06-09

Based on first-principles calculations and full iterative solution of the linearized Boltzmann–Peierls transport equation for phonons, we systematically investigate effects of strain, size and temperature on the thermal conductivity k of suspended graphene. The calculated size-dependent and temperature-dependent k for finite samples agree well with experimental data. The results show that, contrast to the convergent room-temperature k = 5450 W/m-K of unstrained graphene at a sample size ~8 cm, k of strained graphene diverges with increasing the sample size even at high temperature. Out-of-plane acoustic phonons are responsible for the significant size effect in unstrained and strained graphene due tomore » their ultralong mean free path and acoustic phonons with wavelength smaller than 10 nm contribute 80% to the intrinsic room temperature k of unstrained graphene. Tensile strain hardens the flexural modes and increases their lifetimes, causing interesting dependence of k on sample size and strain due to the competition between boundary scattering and intrinsic phonon–phonon scattering. k of graphene can be tuned within a large range by strain for the size larger than 500 μm. These findings shed light on the nature of thermal transport in two-dimensional materials and may guide predicting and engineering k of graphene by varying strain and size.« less

Online submicron particle sizing by dynamic light scattering using autodilution

NASA Technical Reports Server (NTRS)

Nicoli, David F.; Elings, V. B.

1989-01-01

Efficient production of a wide range of commercial products based on submicron colloidal dispersions would benefit from instrumentation for online particle sizing, permitting real time monitoring and control of the particle size distribution. Recent advances in the technology of dynamic light scattering (DLS), especially improvements in algorithms for inversion of the intensity autocorrelation function, have made it ideally suited to the measurement of simple particle size distributions in the difficult submicron region. Crucial to the success of an online DSL based instrument is a simple mechanism for automatically sampling and diluting the starting concentrated sample suspension, yielding a final concentration which is optimal for the light scattering measurement. A proprietary method and apparatus was developed for performing this function, designed to be used with a DLS based particle sizing instrument. A PC/AT computer is used as a smart controller for the valves in the sampler diluter, as well as an input-output communicator, video display and data storage device. Quantitative results are presented for a latex suspension and an oil-in-water emulsion.

A normative inference approach for optimal sample sizes in decisions from experience

PubMed Central

Ostwald, Dirk; Starke, Ludger; Hertwig, Ralph

2015-01-01

“Decisions from experience” (DFE) refers to a body of work that emerged in research on behavioral decision making over the last decade. One of the major experimental paradigms employed to study experience-based choice is the “sampling paradigm,” which serves as a model of decision making under limited knowledge about the statistical structure of the world. In this paradigm respondents are presented with two payoff distributions, which, in contrast to standard approaches in behavioral economics, are specified not in terms of explicit outcome-probability information, but by the opportunity to sample outcomes from each distribution without economic consequences. Participants are encouraged to explore the distributions until they feel confident enough to decide from which they would prefer to draw from in a final trial involving real monetary payoffs. One commonly employed measure to characterize the behavior of participants in the sampling paradigm is the sample size, that is, the number of outcome draws which participants choose to obtain from each distribution prior to terminating sampling. A natural question that arises in this context concerns the “optimal” sample size, which could be used as a normative benchmark to evaluate human sampling behavior in DFE. In this theoretical study, we relate the DFE sampling paradigm to the classical statistical decision theoretic literature and, under a probabilistic inference assumption, evaluate optimal sample sizes for DFE. In our treatment we go beyond analytically established results by showing how the classical statistical decision theoretic framework can be used to derive optimal sample sizes under arbitrary, but numerically evaluable, constraints. Finally, we critically evaluate the value of deriving optimal sample sizes under this framework as testable predictions for the experimental study of sampling behavior in DFE. PMID:26441720

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.

Generalized SAMPLE SIZE Determination Formulas for Investigating Contextual Effects by a Three-Level Random Intercept Model.

PubMed

Usami, Satoshi

2017-03-01

Behavioral and psychological researchers have shown strong interests in investigating contextual effects (i.e., the influences of combinations of individual- and group-level predictors on individual-level outcomes). The present research provides generalized formulas for determining the sample size needed in investigating contextual effects according to the desired level of statistical power as well as width of confidence interval. These formulas are derived within a three-level random intercept model that includes one predictor/contextual variable at each level to simultaneously cover various kinds of contextual effects that researchers can show interest. The relative influences of indices included in the formulas on the standard errors of contextual effects estimates are investigated with the aim of further simplifying sample size determination procedures. In addition, simulation studies are performed to investigate finite sample behavior of calculated statistical power, showing that estimated sample sizes based on derived formulas can be both positively and negatively biased due to complex effects of unreliability of contextual variables, multicollinearity, and violation of assumption regarding the known variances. Thus, it is advisable to compare estimated sample sizes under various specifications of indices and to evaluate its potential bias, as illustrated in the example.

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.

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.

Visual search for tropical web spiders: the influence of plot length, sampling effort, and phase of the day on species richness.

PubMed

Pinto-Leite, C M; Rocha, P L B

2012-12-01

Empirical studies using visual search methods to investigate spider communities were conducted with different sampling protocols, including a variety of plot sizes, sampling efforts, and diurnal periods for sampling. We sampled 11 plots ranging in size from 5 by 10 m to 5 by 60 m. In each plot, we computed the total number of species detected every 10 min during 1 hr during the daytime and during the nighttime (0630 hours to 1100 hours, both a.m. and p.m.). We measured the influence of time effort on the measurement of species richness by comparing the curves produced by sample-based rarefaction and species richness estimation (first-order jackknife). We used a general linear model with repeated measures to assess whether the phase of the day during which sampling occurred and the differences in the plot lengths influenced the number of species observed and the number of species estimated. To measure the differences in species composition between the phases of the day, we used a multiresponse permutation procedure and a graphical representation based on nonmetric multidimensional scaling. After 50 min of sampling, we noted a decreased rate of species accumulation and a tendency of the estimated richness curves to reach an asymptote. We did not detect an effect of plot size on the number of species sampled. However, differences in observed species richness and species composition were found between phases of the day. Based on these results, we propose guidelines for visual search for tropical web spiders.

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

How Methodological Features Affect Effect Sizes in Education

ERIC Educational Resources Information Center

Cheung, Alan; Slavin, Robert

2016-01-01

As evidence-based reform becomes increasingly important in educational policy, it is becoming essential to understand how research design might contribute to reported effect sizes in experiments evaluating educational programs. The purpose of this study was to examine how methodological features such as types of publication, sample sizes, and…

The generalization ability of online SVM classification based on Markov sampling.

PubMed

Xu, Jie; Yan Tang, Yuan; Zou, Bin; Xu, Zongben; Li, Luoqing; Lu, Yang

2015-03-01

In this paper, we consider online support vector machine (SVM) classification learning algorithms with uniformly ergodic Markov chain (u.e.M.c.) samples. We establish the bound on the misclassification error of an online SVM classification algorithm with u.e.M.c. samples based on reproducing kernel Hilbert spaces and obtain a satisfactory convergence rate. We also introduce a novel online SVM classification algorithm based on Markov sampling, and present the numerical studies on the learning ability of online SVM classification based on Markov sampling for benchmark repository. The numerical studies show that the learning performance of the online SVM classification algorithm based on Markov sampling is better than that of classical online SVM classification based on random sampling as the size of training samples is larger.

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.

A critical review on characterization strategies of organic matter for wastewater and water treatment processes.

PubMed

Tran, Ngoc Han; Ngo, Huu Hao; Urase, Taro; Gin, Karina Yew-Hoong

2015-10-01

The presence of organic matter (OM) in raw wastewater, treated wastewater effluents, and natural water samples has been known to cause many problems in wastewater treatment and water reclamation processes, such as treatability, membrane fouling, and the formation of potentially toxic by-products during wastewater treatment. This paper summarizes the current knowledge on the methods for characterization and quantification of OM in water samples in relation to wastewater and water treatment processes including: (i) characterization based on the biodegradability; (ii) characterization based on particle size distribution; (iii) fractionation based on the hydrophilic/hydrophobic properties; (iv) characterization based on the molecular weight (MW) size distribution; and (v) characterization based on fluorescence excitation emission matrix. In addition, the advantages, disadvantages and applications of these methods are discussed in detail. The establishment of correlations among biodegradability, hydrophobic/hydrophilic fractions, MW size distribution of OM, membrane fouling and formation of toxic by-products potential is highly recommended for further studies. Copyright © 2015 Elsevier Ltd. All rights reserved.

Effect of Microstructural Interfaces on the Mechanical Response of Crystalline Metallic Materials

NASA Astrophysics Data System (ADS)

Aitken, Zachary H.

Advances in nano-scale mechanical testing have brought about progress in the understanding of physical phenomena in materials and a measure of control in the fabrication of novel materials. In contrast to bulk materials that display size-invariant mechanical properties, sub-micron metallic samples show a critical dependence on sample size. The strength of nano-scale single crystalline metals is well-described by a power-law function, sigma ∝ D-n, where D is a critical sample size and n is a experimentally-fit positive exponent. This relationship is attributed to source-driven plasticity and demonstrates a strengthening as the decreasing sample size begins to limit the size and number of dislocation sources. A full understanding of this size-dependence is complicated by the presence of microstructural features such as interfaces that can compete with the dominant dislocation-based deformation mechanisms. In this thesis, the effects of microstructural features such as grain boundaries and anisotropic crystallinity on nano-scale metals are investigated through uniaxial compression testing. We find that nano-sized Cu covered by a hard coating displays a Bauschinger effect and the emergence of this behavior can be explained through a simple dislocation-based analytic model. Al nano-pillars containing a single vertically-oriented coincident site lattice grain boundary are found to show similar deformation to single-crystalline nano-pillars with slip traces passing through the grain boundary. With increasing tilt angle of the grain boundary from the pillar axis, we observe a transition from dislocation-dominated deformation to grain boundary sliding. Crystallites are observed to shear along the grain boundary and molecular dynamics simulations reveal a mechanism of atomic migration that accommodates boundary sliding. We conclude with an analysis of the effects of inherent crystal anisotropy and alloying on the mechanical behavior of the Mg alloy, AZ31. Through comparison to pure Mg, we show that the size effect dominates the strength of samples below 10 microm, that differences in the size effect between hexagonal slip systems is due to the inherent crystal anisotropy, suggesting that the fundamental mechanism of the size effect in these slip systems is the same.

Passive vs. Parachute System Architecture for Robotic Sample Return Vehicles

NASA Technical Reports Server (NTRS)

Maddock, Robert W.; Henning, Allen B.; Samareh, Jamshid A.

2016-01-01

The Multi-Mission Earth Entry Vehicle (MMEEV) is a flexible vehicle concept based on the Mars Sample Return (MSR) EEV design which can be used in the preliminary sample return mission study phase to parametrically investigate any trade space of interest to determine the best entry vehicle design approach for that particular mission concept. In addition to the trade space dimensions often considered (e.g. entry conditions, payload size and mass, vehicle size, etc.), the MMEEV trade space considers whether it might be more beneficial for the vehicle to utilize a parachute system during descent/landing or to be fully passive (i.e. not use a parachute). In order to evaluate this trade space dimension, a simplified parachute system model has been developed based on inputs such as vehicle size/mass, payload size/mass and landing requirements. This model works in conjunction with analytical approximations of a mission trade space dataset provided by the MMEEV System Analysis for Planetary EDL (M-SAPE) tool to help quantify the differences between an active (with parachute) and a passive (no parachute) vehicle concept.

Sampling system for wheat (Triticum aestivum L) area estimation using digital LANDSAT MSS data and aerial photographs. [Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Moreira, M. A.; Chen, S. C.; Batista, G. T.

1984-01-01

A procedure to estimate wheat (Triticum aestivum L) area using sampling technique based on aerial photographs and digital LANDSAT MSS data is developed. Aerial photographs covering 720 square km are visually analyzed. To estimate wheat area, a regression approach is applied using different sample sizes and various sampling units. As the size of sampling unit decreased, the percentage of sampled area required to obtain similar estimation performance also decreased. The lowest percentage of the area sampled for wheat estimation with relatively high precision and accuracy through regression estimation is 13.90% using 10 square km as the sampling unit. Wheat area estimation using only aerial photographs is less precise and accurate than those obtained by regression estimation.

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.

Size measuring techniques as tool to monitor pea proteins intramolecular crosslinking by transglutaminase treatment.

PubMed

Djoullah, Attaf; Krechiche, Ghali; Husson, Florence; Saurel, Rémi

2016-01-01

In this work, techniques for monitoring the intramolecular transglutaminase cross-links of pea proteins, based on protein size determination, were developed. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis profiles of transglutaminase-treated low concentration (0.01% w/w) pea albumin samples, compared to the untreated one (control), showed a higher electrophoretic migration of the major albumin fraction band (26 kDa), reflecting a decrease in protein size. This protein size decrease was confirmed, after DEAE column purification, by dynamic light scattering (DLS) where the hydrodynamic radius of treated samples appears to be reduced compared to the control one. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

Thermal Stability of Zone Melting p-Type (Bi, Sb)2Te3 Ingots and Comparison with the Corresponding Powder Metallurgy Samples

NASA Astrophysics Data System (ADS)

Jiang, Chengpeng; Fan, Xi'an; Hu, Jie; Feng, Bo; Xiang, Qiusheng; Li, Guangqiang; Li, Yawei; He, Zhu

2018-04-01

During the past few decades, Bi2Te3-based alloys have been investigated extensively because of their promising application in the area of low temperature waste heat thermoelectric power generation. However, their thermal stability must be evaluated to explore the appropriate service temperature. In this work, the thermal stability of zone melting p-type (Bi, Sb)2Te3-based ingots was investigated under different annealing treatment conditions. The effect of service temperature on the thermoelectric properties and hardness of the samples was also discussed in detail. The results showed that the grain size, density, dimension size and mass remained nearly unchanged when the service temperature was below 523 K, which suggested that the geometry size of zone melting p-type (Bi, Sb)2Te3-based materials was stable below 523 K. The power factor and Vickers hardness of the ingots also changed little and maintained good thermal stability. Unfortunately, the thermal conductivity increased with increasing annealing temperature, which resulted in an obvious decrease of the zT value. In addition, the thermal stabilities of the zone melting p-type (Bi, Sb)2Te3-based materials and the corresponding powder metallurgy samples were also compared. All evidence implied that the thermal stabilities of the zone-melted (ZMed) p-type (Bi, Sb)2Te3 ingots in terms of crystal structure, geometry size, power factor (PF) and hardness were better than those of the corresponding powder metallurgy samples. However, their thermal stabilities in terms of zT values were similar under different annealing temperatures.

Validation of abundance estimates from mark–recapture and removal techniques for rainbow trout captured by electrofishing in small streams

USGS Publications Warehouse

Rosenberger, Amanda E.; Dunham, Jason B.

2005-01-01

Estimation of fish abundance in streams using the removal model or the Lincoln - Peterson mark - recapture model is a common practice in fisheries. These models produce misleading results if their assumptions are violated. We evaluated the assumptions of these two models via electrofishing of rainbow trout Oncorhynchus mykiss in central Idaho streams. For one-, two-, three-, and four-pass sampling effort in closed sites, we evaluated the influences of fish size and habitat characteristics on sampling efficiency and the accuracy of removal abundance estimates. We also examined the use of models to generate unbiased estimates of fish abundance through adjustment of total catch or biased removal estimates. Our results suggested that the assumptions of the mark - recapture model were satisfied and that abundance estimates based on this approach were unbiased. In contrast, the removal model assumptions were not met. Decreasing sampling efficiencies over removal passes resulted in underestimated population sizes and overestimates of sampling efficiency. This bias decreased, but was not eliminated, with increased sampling effort. Biased removal estimates based on different levels of effort were highly correlated with each other but were less correlated with unbiased mark - recapture estimates. Stream size decreased sampling efficiency, and stream size and instream wood increased the negative bias of removal estimates. We found that reliable estimates of population abundance could be obtained from models of sampling efficiency for different levels of effort. Validation of abundance estimates requires extra attention to routine sampling considerations but can help fisheries biologists avoid pitfalls associated with biased data and facilitate standardized comparisons among studies that employ different sampling methods.

THE CHALLENGE OF DETECTING CLASSICAL SWINE FEVER VIRUS CIRCULATION IN WILD BOAR (SUS SCROFA): SIMULATION OF SAMPLING OPTIONS.

PubMed

Sonnenburg, Jana; Schulz, Katja; Blome, Sandra; Staubach, Christoph

2016-10-01

Classical swine fever (CSF) is one of the most important viral diseases of domestic pigs ( Sus scrofa domesticus) and wild boar ( Sus scrofa ). For at least 4 decades, several European Union member states were confronted with outbreaks among wild boar and, as it had been shown that infected wild boar populations can be a major cause of primary outbreaks in domestic pigs, strict control measures for both species were implemented. To guarantee early detection and to demonstrate freedom from disease, intensive surveillance is carried out based on a hunting bag sample. In this context, virologic investigations play a major role in the early detection of new introductions and in regions immunized with a conventional vaccine. The required financial resources and personnel for reliable testing are often large, and sufficient sample sizes to detect low virus prevalences are difficult to obtain. We conducted a simulation to model the possible impact of changes in sample size and sampling intervals on the probability of CSF virus detection based on a study area of 65 German hunting grounds. A 5-yr period with 4,652 virologic investigations was considered. Results suggest that low prevalences could not be detected with a justifiable effort. The simulation of increased sample sizes per sampling interval showed only a slightly better performance but would be unrealistic in practice, especially outside the main hunting season. Further studies on other approaches such as targeted or risk-based sampling for virus detection in connection with (marker) antibody surveillance are needed.

Large sample area and size are needed for forest soil seed bank studies to ensure low discrepancy with standing vegetation.

PubMed

Shen, You-xin; Liu, Wei-li; Li, Yu-hui; Guan, Hui-lin

2014-01-01

A large number of small-sized samples invariably shows that woody species are absent from forest soil seed banks, leading to a large discrepancy with the seedling bank on the forest floor. We ask: 1) Does this conventional sampling strategy limit the detection of seeds of woody species? 2) Are large sample areas and sample sizes needed for higher recovery of seeds of woody species? We collected 100 samples that were 10 cm (length) × 10 cm (width) × 10 cm (depth), referred to as larger number of small-sized samples (LNSS) in a 1 ha forest plot, and placed them to germinate in a greenhouse, and collected 30 samples that were 1 m × 1 m × 10 cm, referred to as small number of large-sized samples (SNLS) and placed them (10 each) in a nearby secondary forest, shrub land and grass land. Only 15.7% of woody plant species of the forest stand were detected by the 100 LNSS, contrasting with 22.9%, 37.3% and 20.5% woody plant species being detected by SNLS in the secondary forest, shrub land and grassland, respectively. The increased number of species vs. sampled areas confirmed power-law relationships for forest stand, the LNSS and SNLS at all three recipient sites. Our results, although based on one forest, indicate that conventional LNSS did not yield a high percentage of detection for woody species, but SNLS strategy yielded a higher percentage of detection for woody species in the seed bank if samples were exposed to a better field germination environment. A 4 m2 minimum sample area derived from power equations is larger than the sampled area in most studies in the literature. Increased sample size also is needed to obtain an increased sample area if the number of samples is to remain relatively low.

Rule-of-thumb adjustment of sample sizes to accommodate dropouts in a two-stage analysis of repeated measurements.

PubMed

Overall, John E; Tonidandel, Scott; Starbuck, Robert R

2006-01-01

Recent contributions to the statistical literature have provided elegant model-based solutions to the problem of estimating sample sizes for testing the significance of differences in mean rates of change across repeated measures in controlled longitudinal studies with differentially correlated error and missing data due to dropouts. However, the mathematical complexity and model specificity of these solutions make them generally inaccessible to most applied researchers who actually design and undertake treatment evaluation research in psychiatry. In contrast, this article relies on a simple two-stage analysis in which dropout-weighted slope coefficients fitted to the available repeated measurements for each subject separately serve as the dependent variable for a familiar ANCOVA test of significance for differences in mean rates of change. This article is about how a sample of size that is estimated or calculated to provide desired power for testing that hypothesis without considering dropouts can be adjusted appropriately to take dropouts into account. Empirical results support the conclusion that, whatever reasonable level of power would be provided by a given sample size in the absence of dropouts, essentially the same power can be realized in the presence of dropouts simply by adding to the original dropout-free sample size the number of subjects who would be expected to drop from a sample of that original size under conditions of the proposed study.

Is the permeability of naturally fractured rocks scale dependent?

NASA Astrophysics Data System (ADS)

Azizmohammadi, Siroos; Matthäi, Stephan K.

2017-09-01

The equivalent permeability, keq of stratified fractured porous rocks and its anisotropy is important for hydrocarbon reservoir engineering, groundwater hydrology, and subsurface contaminant transport. However, it is difficult to constrain this tensor property as it is strongly influenced by infrequent large fractures. Boreholes miss them and their directional sampling bias affects the collected geostatistical data. Samples taken at any scale smaller than that of interest truncate distributions and this bias leads to an incorrect characterization and property upscaling. To better understand this sampling problem, we have investigated a collection of outcrop-data-based Discrete Fracture and Matrix (DFM) models with mechanically constrained fracture aperture distributions, trying to establish a useful Representative Elementary Volume (REV). Finite-element analysis and flow-based upscaling have been used to determine keq eigenvalues and anisotropy. While our results indicate a convergence toward a scale-invariant keq REV with increasing sample size, keq magnitude can have multi-modal distributions. REV size relates to the length of dilated fracture segments as opposed to overall fracture length. Tensor orientation and degree of anisotropy also converge with sample size. However, the REV for keq anisotropy is larger than that for keq magnitude. Across scales, tensor orientation varies spatially, reflecting inhomogeneity of the fracture patterns. Inhomogeneity is particularly pronounced where the ambient stress selectively activates late- as opposed to early (through-going) fractures. While we cannot detect any increase of keq with sample size as postulated in some earlier studies, our results highlight a strong keq anisotropy that influences scale dependence.

Dynamic relationships between body size, species richness, abundance, and energy use in a shallow marine epibenthic faunal community

PubMed Central

Labra, Fabio A; Hernández-Miranda, Eduardo; Quiñones, Renato A

2015-01-01

We study the temporal variation in the empirical relationships among body size (S), species richness (R), and abundance (A) in a shallow marine epibenthic faunal community in Coliumo Bay, Chile. We also extend previous analyses by calculating individual energy use (E) and test whether its bivariate and trivariate relationships with S and R are in agreement with expectations derived from the energetic equivalence rule. Carnivorous and scavenger species representing over 95% of sample abundance and biomass were studied. For each individual, body size (g) was measured and E was estimated following published allometric relationships. Data for each sample were tabulated into exponential body size bins, comparing species-averaged values with individual-based estimates which allow species to potentially occupy multiple size classes. For individual-based data, both the number of individuals and species across body size classes are fit by a Weibull function rather than by a power law scaling. Species richness is also a power law of the number of individuals. Energy use shows a piecewise scaling relationship with body size, with energetic equivalence holding true only for size classes above the modal abundance class. Species-based data showed either weak linear or no significant patterns, likely due to the decrease in the number of data points across body size classes. Hence, for individual-based size spectra, the SRA relationship seems to be general despite seasonal forcing and strong disturbances in Coliumo Bay. The unimodal abundance distribution results in a piecewise energy scaling relationship, with small individuals showing a positive scaling and large individuals showing energetic equivalence. Hence, strict energetic equivalence should not be expected for unimodal abundance distributions. On the other hand, while species-based data do not show unimodal SRA relationships, energy use across body size classes did not show significant trends, supporting energetic equivalence. PMID:25691966

Variable criteria sequential stopping rule: Validity and power with repeated measures ANOVA, multiple correlation, MANOVA and relation to Chi-square distribution.

PubMed

Fitts, Douglas A

2017-09-21

The variable criteria sequential stopping rule (vcSSR) is an efficient way to add sample size to planned ANOVA tests while holding the observed rate of Type I errors, α o , constant. The only difference from regular null hypothesis testing is that criteria for stopping the experiment are obtained from a table based on the desired power, rate of Type I errors, and beginning sample size. The vcSSR was developed using between-subjects ANOVAs, but it should work with p values from any type of F test. In the present study, the α o remained constant at the nominal level when using the previously published table of criteria with repeated measures designs with various numbers of treatments per subject, Type I error rates, values of ρ, and four different sample size models. New power curves allow researchers to select the optimal sample size model for a repeated measures experiment. The criteria held α o constant either when used with a multiple correlation that varied the sample size model and the number of predictor variables, or when used with MANOVA with multiple groups and two levels of a within-subject variable at various levels of ρ. Although not recommended for use with χ 2 tests such as the Friedman rank ANOVA test, the vcSSR produces predictable results based on the relation between F and χ 2 . Together, the data confirm the view that the vcSSR can be used to control Type I errors during sequential sampling with any t- or F-statistic rather than being restricted to certain ANOVA designs.

VARS-TOOL: A Comprehensive, Efficient, and Robust Sensitivity Analysis Toolbox

NASA Astrophysics Data System (ADS)

Razavi, S.; Sheikholeslami, R.; Haghnegahdar, A.; Esfahbod, B.

2016-12-01

VARS-TOOL is an advanced sensitivity and uncertainty analysis toolbox, applicable to the full range of computer simulation models, including Earth and Environmental Systems Models (EESMs). The toolbox was developed originally around VARS (Variogram Analysis of Response Surfaces), which is a general framework for Global Sensitivity Analysis (GSA) that utilizes the variogram/covariogram concept to characterize the full spectrum of sensitivity-related information, thereby providing a comprehensive set of "global" sensitivity metrics with minimal computational cost. VARS-TOOL is unique in that, with a single sample set (set of simulation model runs), it generates simultaneously three philosophically different families of global sensitivity metrics, including (1) variogram-based metrics called IVARS (Integrated Variogram Across a Range of Scales - VARS approach), (2) variance-based total-order effects (Sobol approach), and (3) derivative-based elementary effects (Morris approach). VARS-TOOL is also enabled with two novel features; the first one being a sequential sampling algorithm, called Progressive Latin Hypercube Sampling (PLHS), which allows progressively increasing the sample size for GSA while maintaining the required sample distributional properties. The second feature is a "grouping strategy" that adaptively groups the model parameters based on their sensitivity or functioning to maximize the reliability of GSA results. These features in conjunction with bootstrapping enable the user to monitor the stability, robustness, and convergence of GSA with the increase in sample size for any given case study. VARS-TOOL has been shown to achieve robust and stable results within 1-2 orders of magnitude smaller sample sizes (fewer model runs) than alternative tools. VARS-TOOL, available in MATLAB and Python, is under continuous development and new capabilities and features are forthcoming.

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.

Evaluation of species richness estimators based on quantitative performance measures and sensitivity to patchiness and sample grain size

NASA Astrophysics Data System (ADS)

Willie, Jacob; Petre, Charles-Albert; Tagg, Nikki; Lens, Luc

2012-11-01

Data from forest herbaceous plants in a site of known species richness in Cameroon were used to test the performance of rarefaction and eight species richness estimators (ACE, ICE, Chao1, Chao2, Jack1, Jack2, Bootstrap and MM). Bias, accuracy, precision and sensitivity to patchiness and sample grain size were the evaluation criteria. An evaluation of the effects of sampling effort and patchiness on diversity estimation is also provided. Stems were identified and counted in linear series of 1-m2 contiguous square plots distributed in six habitat types. Initially, 500 plots were sampled in each habitat type. The sampling process was monitored using rarefaction and a set of richness estimator curves. Curves from the first dataset suggested adequate sampling in riparian forest only. Additional plots ranging from 523 to 2143 were subsequently added in the undersampled habitats until most of the curves stabilized. Jack1 and ICE, the non-parametric richness estimators, performed better, being more accurate and less sensitive to patchiness and sample grain size, and significantly reducing biases that could not be detected by rarefaction and other estimators. This study confirms the usefulness of non-parametric incidence-based estimators, and recommends Jack1 or ICE alongside rarefaction while describing taxon richness and comparing results across areas sampled using similar or different grain sizes. As patchiness varied across habitat types, accurate estimations of diversity did not require the same number of plots. The number of samples needed to fully capture diversity is not necessarily the same across habitats, and can only be known when taxon sampling curves have indicated adequate sampling. Differences in observed species richness between habitats were generally due to differences in patchiness, except between two habitats where they resulted from differences in abundance. We suggest that communities should first be sampled thoroughly using appropriate taxon sampling curves before explaining differences in diversity.

Longitudinal white matter change in frontotemporal dementia subtypes and sporadic late onset Alzheimer's disease.

PubMed

Elahi, Fanny M; Marx, Gabe; Cobigo, Yann; Staffaroni, Adam M; Kornak, John; Tosun, Duygu; Boxer, Adam L; Kramer, Joel H; Miller, Bruce L; Rosen, Howard J

2017-01-01

Degradation of white matter microstructure has been demonstrated in frontotemporal lobar degeneration (FTLD) and Alzheimer's disease (AD). In preparation for clinical trials, ongoing studies are investigating the utility of longitudinal brain imaging for quantification of disease progression. To date only one study has examined sample size calculations based on longitudinal changes in white matter integrity in FTLD. To quantify longitudinal changes in white matter microstructural integrity in the three canonical subtypes of frontotemporal dementia (FTD) and AD using diffusion tensor imaging (DTI). 60 patients with clinical diagnoses of FTD, including 27 with behavioral variant frontotemporal dementia (bvFTD), 14 with non-fluent variant primary progressive aphasia (nfvPPA), and 19 with semantic variant PPA (svPPA), as well as 19 patients with AD and 69 healthy controls were studied. We used a voxel-wise approach to calculate annual rate of change in fractional anisotropy (FA) and mean diffusivity (MD) in each group using two time points approximately one year apart. Mean rates of change in FA and MD in 48 atlas-based regions-of-interest, as well as global measures of cognitive function were used to calculate sample sizes for clinical trials (80% power, alpha of 5%). All FTD groups showed statistically significant baseline and longitudinal white matter degeneration, with predominant involvement of frontal tracts in the bvFTD group, frontal and temporal tracts in the PPA groups and posterior tracts in the AD group. Longitudinal change in MD yielded a larger number of regions with sample sizes below 100 participants per therapeutic arm in comparison with FA. SvPPA had the smallest sample size based on change in MD in the fornix (n = 41 participants per study arm to detect a 40% effect of drug), and nfvPPA and AD had their smallest sample sizes based on rate of change in MD within the left superior longitudinal fasciculus (n = 49 for nfvPPA, and n = 23 for AD). BvFTD generally showed the largest sample size estimates (minimum n = 140 based on MD in the corpus callosum). The corpus callosum appeared to be the best region for a potential study that would include all FTD subtypes. Change in global measure of functional status (CDR box score) yielded the smallest sample size for bvFTD (n = 71), but clinical measures were inferior to white matter change for the other groups. All three of the canonical subtypes of FTD are associated with significant change in white matter integrity over one year. These changes are consistent enough that drug effects in future clinical trials could be detected with relatively small numbers of participants. While there are some differences in regions of change across groups, the genu of the corpus callosum is a region that could be used to track progression in studies that include all subtypes.

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

Beyond Gorilla and Pongo: alternative models for evaluating variation and sexual dimorphism in fossil hominoid samples.

PubMed

Scott, Jeremiah E; Schrein, Caitlin M; Kelley, Jay

2009-10-01

Sexual size dimorphism in the postcanine dentition of the late Miocene hominoid Lufengpithecus lufengensis exceeds that in Pongo pygmaeus, demonstrating that the maximum degree of molar size dimorphism in apes is not represented among the extant Hominoidea. It has not been established, however, that the molars of Pongo are more dimorphic than those of any other living primate. In this study, we used resampling-based methods to compare molar dimorphism in Gorilla, Pongo, and Lufengpithecus to that in the papionin Mandrillus leucophaeus to test two hypotheses: (1) Pongo possesses the most size-dimorphic molars among living primates and (2) molar size dimorphism in Lufengpithecus is greater than that in the most dimorphic living primates. Our results show that M. leucophaeus exceeds great apes in its overall level of dimorphism and that L. lufengensis is more dimorphic than the extant species. Using these samples, we also evaluated molar dimorphism and taxonomic composition in two other Miocene ape samples--Ouranopithecus macedoniensis from Greece, specimens of which can be sexed based on associated canines and P(3)s, and the Sivapithecus sample from Haritalyangar, India. Ouranopithecus is more dimorphic than the extant taxa but is similar to Lufengpithecus, demonstrating that the level of molar dimorphism required for the Greek fossil sample under the single-species taxonomy is not unprecedented when the comparative framework is expanded to include extinct primates. In contrast, the Haritalyangar Sivapithecus sample, if itrepresents a single species, exhibits substantially greater molar dimorphism than does Lufengpithecus. Given these results, the taxonomic status of this sample remains equivocal.

Solution and Aging of MAR-M246 Nickel-Based Superalloy

NASA Astrophysics Data System (ADS)

Baldan, Renato; da Silva, Antonio Augusto Araújo Pinto; Nunes, Carlos Angelo; Couto, Antonio Augusto; Gabriel, Sinara Borborema; Alkmin, Luciano Braga

2017-02-01

Solution and aging heat-treatments play a key role for the application of the superalloys. The aim of this work is to evaluate the microstructure of the MAR-M246 nickel-based superalloy solutioned at 1200 and 1250 °C for 330 min and aged at 780, 880 and 980 °C for 5, 20 and 80 h. The γ' solvus, solidus and liquidus temperatures were calculated with the aid of the JMatPro software (Ni database). The as-cast and heat-treated samples were characterized by SEM/EDS and SEM-FEG. The γ' size precipitated in the aged samples was measured and compared with JMatPro simulations. The results have shown that the sample solutioned at 1250 °C for 330 min showed a very homogeneous γ matrix with carbides and cubic γ' precipitates uniformly distributed. The mean γ' size of aged samples at 780 and 880 °C for 5, 20 and 80 h did not present significant differences when compared to the solutioned sample. However, a significant increasing in the γ' particles was observed at 980 °C, evidenced by the large mean size of these particles after 80 h of aging heat-treatment.

Statistical aspects of genetic association testing in small samples, based on selective DNA pooling data in the arctic fox.

PubMed

Szyda, Joanna; Liu, Zengting; Zatoń-Dobrowolska, Magdalena; Wierzbicki, Heliodor; Rzasa, Anna

2008-01-01

We analysed data from a selective DNA pooling experiment with 130 individuals of the arctic fox (Alopex lagopus), which originated from 2 different types regarding body size. The association between alleles of 6 selected unlinked molecular markers and body size was tested by using univariate and multinomial logistic regression models, applying odds ratio and test statistics from the power divergence family. Due to the small sample size and the resulting sparseness of the data table, in hypothesis testing we could not rely on the asymptotic distributions of the tests. Instead, we tried to account for data sparseness by (i) modifying confidence intervals of odds ratio; (ii) using a normal approximation of the asymptotic distribution of the power divergence tests with different approaches for calculating moments of the statistics; and (iii) assessing P values empirically, based on bootstrap samples. As a result, a significant association was observed for 3 markers. Furthermore, we used simulations to assess the validity of the normal approximation of the asymptotic distribution of the test statistics under the conditions of small and sparse samples.

One-step estimation of networked population size: Respondent-driven capture-recapture with anonymity.

PubMed

Khan, Bilal; Lee, Hsuan-Wei; Fellows, Ian; Dombrowski, Kirk

2018-01-01

Size estimation is particularly important for populations whose members experience disproportionate health issues or pose elevated health risks to the ambient social structures in which they are embedded. Efforts to derive size estimates are often frustrated when the population is hidden or hard-to-reach in ways that preclude conventional survey strategies, as is the case when social stigma is associated with group membership or when group members are involved in illegal activities. This paper extends prior research on the problem of network population size estimation, building on established survey/sampling methodologies commonly used with hard-to-reach groups. Three novel one-step, network-based population size estimators are presented, for use in the context of uniform random sampling, respondent-driven sampling, and when networks exhibit significant clustering effects. We give provably sufficient conditions for the consistency of these estimators in large configuration networks. Simulation experiments across a wide range of synthetic network topologies validate the performance of the estimators, which also perform well on a real-world location-based social networking data set with significant clustering. Finally, the proposed schemes are extended to allow them to be used in settings where participant anonymity is required. Systematic experiments show favorable tradeoffs between anonymity guarantees and estimator performance. Taken together, we demonstrate that reasonable population size estimates are derived from anonymous respondent driven samples of 250-750 individuals, within ambient populations of 5,000-40,000. The method thus represents a novel and cost-effective means for health planners and those agencies concerned with health and disease surveillance to estimate the size of hidden populations. We discuss limitations and future work in the concluding section.

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.

Salmonella enteritidis surveillance by egg immunology: impact of the sampling scheme on the release of contaminated table eggs.

PubMed

Klinkenberg, Don; Thomas, Ekelijn; Artavia, Francisco F Calvo; Bouma, Annemarie

2011-08-01

Design of surveillance programs to detect infections could benefit from more insight into sampling schemes. We address the effect of sampling schemes for Salmonella Enteritidis surveillance in laying hens. Based on experimental estimates for the transmission rate in flocks, and the characteristics of an egg immunological test, we have simulated outbreaks with various sampling schemes, and with the current boot swab program with a 15-week sampling interval. Declaring a flock infected based on a single positive egg was not possible because test specificity was too low. Thus, a threshold number of positive eggs was defined to declare a flock infected, and, for small sample sizes, eggs from previous samplings had to be included in a cumulative sample to guarantee a minimum flock level specificity. Effectiveness of surveillance was measured by the proportion of outbreaks detected, and by the number of contaminated table eggs brought on the market. The boot swab program detected 90% of the outbreaks, with 75% fewer contaminated eggs compared to no surveillance, whereas the baseline egg program (30 eggs each 15 weeks) detected 86%, with 73% fewer contaminated eggs. We conclude that a larger sample size results in more detected outbreaks, whereas a smaller sampling interval decreases the number of contaminated eggs. Decreasing sample size and interval simultaneously reduces the number of contaminated eggs, but not indefinitely: the advantage of more frequent sampling is counterbalanced by the cumulative sample including less recently laid eggs. Apparently, optimizing surveillance has its limits when test specificity is taken into account. © 2011 Society for Risk Analysis.

Sample size determinations for group-based randomized clinical trials with different levels of data hierarchy between experimental and control arms.

PubMed

Heo, Moonseong; Litwin, Alain H; Blackstock, Oni; Kim, Namhee; Arnsten, Julia H

2017-02-01

We derived sample size formulae for detecting main effects in group-based randomized clinical trials with different levels of data hierarchy between experimental and control arms. Such designs are necessary when experimental interventions need to be administered to groups of subjects whereas control conditions need to be administered to individual subjects. This type of trial, often referred to as a partially nested or partially clustered design, has been implemented for management of chronic diseases such as diabetes and is beginning to emerge more commonly in wider clinical settings. Depending on the research setting, the level of hierarchy of data structure for the experimental arm can be three or two, whereas that for the control arm is two or one. Such different levels of data hierarchy assume correlation structures of outcomes that are different between arms, regardless of whether research settings require two or three level data structure for the experimental arm. Therefore, the different correlations should be taken into account for statistical modeling and for sample size determinations. To this end, we considered mixed-effects linear models with different correlation structures between experimental and control arms to theoretically derive and empirically validate the sample size formulae with simulation studies.

Upward counterfactual thinking and depression: A meta-analysis.

PubMed

Broomhall, Anne Gene; Phillips, Wendy J; Hine, Donald W; Loi, Natasha M

2017-07-01

This meta-analysis examined the strength of association between upward counterfactual thinking and depressive symptoms. Forty-two effect sizes from a pooled sample of 13,168 respondents produced a weighted average effect size of r=.26, p<.001. Moderator analyses using an expanded set of 96 effect sizes indicated that upward counterfactuals and regret produced significant positive effects that were similar in strength. Effects also did not vary as a function of the theme of the counterfactual-inducing situation or study design (cross-sectional versus longitudinal). Significant effect size heterogeneity was observed across sample types, methods of assessing upward counterfactual thinking, and types of depression scale. Significant positive effects were found in studies that employed samples of bereaved individuals, older adults, terminally ill patients, or university students, but not adolescent mothers or mixed samples. Both number-based and Likert-based upward counterfactual thinking assessments produced significant positive effects, with the latter generating a larger effect. All depression scales produced significant positive effects, except for the Psychiatric Epidemiology Research Interview. Research and theoretical implications are discussed in relation to cognitive theories of depression and the functional theory of upward counterfactual thinking, and important gaps in the extant research literature are identified. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

Long-term effective population size dynamics of an intensively monitored vertebrate population

PubMed Central

Mueller, A-K; Chakarov, N; Krüger, O; Hoffman, J I

2016-01-01

Long-term genetic data from intensively monitored natural populations are important for understanding how effective population sizes (Ne) can vary over time. We therefore genotyped 1622 common buzzard (Buteo buteo) chicks sampled over 12 consecutive years (2002–2013 inclusive) at 15 microsatellite loci. This data set allowed us to both compare single-sample with temporal approaches and explore temporal patterns in the effective number of parents that produced each cohort in relation to the observed population dynamics. We found reasonable consistency between linkage disequilibrium-based single-sample and temporal estimators, particularly during the latter half of the study, but no clear relationship between annual Ne estimates () and census sizes. We also documented a 14-fold increase in between 2008 and 2011, a period during which the census size doubled, probably reflecting a combination of higher adult survival and immigration from further afield. Our study thus reveals appreciable temporal heterogeneity in the effective population size of a natural vertebrate population, confirms the need for long-term studies and cautions against drawing conclusions from a single sample. PMID:27553455

Robust Face Recognition via Multi-Scale Patch-Based Matrix Regression.

PubMed

Gao, Guangwei; Yang, Jian; Jing, Xiaoyuan; Huang, Pu; Hua, Juliang; Yue, Dong

2016-01-01

In many real-world applications such as smart card solutions, law enforcement, surveillance and access control, the limited training sample size is the most fundamental problem. By making use of the low-rank structural information of the reconstructed error image, the so-called nuclear norm-based matrix regression has been demonstrated to be effective for robust face recognition with continuous occlusions. However, the recognition performance of nuclear norm-based matrix regression degrades greatly in the face of the small sample size problem. An alternative solution to tackle this problem is performing matrix regression on each patch and then integrating the outputs from all patches. However, it is difficult to set an optimal patch size across different databases. To fully utilize the complementary information from different patch scales for the final decision, we propose a multi-scale patch-based matrix regression scheme based on which the ensemble of multi-scale outputs can be achieved optimally. Extensive experiments on benchmark face databases validate the effectiveness and robustness of our method, which outperforms several state-of-the-art patch-based face recognition algorithms.

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.

(I Can't Get No) Saturation: A simulation and guidelines for sample sizes in qualitative research.

PubMed

van Rijnsoever, Frank J

2017-01-01

I explore the sample size in qualitative research that is required to reach theoretical saturation. I conceptualize a population as consisting of sub-populations that contain different types of information sources that hold a number of codes. Theoretical saturation is reached after all the codes in the population have been observed once in the sample. I delineate three different scenarios to sample information sources: "random chance," which is based on probability sampling, "minimal information," which yields at least one new code per sampling step, and "maximum information," which yields the largest number of new codes per sampling step. Next, I use simulations to assess the minimum sample size for each scenario for systematically varying hypothetical populations. I show that theoretical saturation is more dependent on the mean probability of observing codes than on the number of codes in a population. Moreover, the minimal and maximal information scenarios are significantly more efficient than random chance, but yield fewer repetitions per code to validate the findings. I formulate guidelines for purposive sampling and recommend that researchers follow a minimum information scenario.

Are power calculations useful? A multicentre neuroimaging study

PubMed Central

Suckling, John; Henty, Julian; Ecker, Christine; Deoni, Sean C; Lombardo, Michael V; Baron-Cohen, Simon; Jezzard, Peter; Barnes, Anna; Chakrabarti, Bhismadev; Ooi, Cinly; Lai, Meng-Chuan; Williams, Steven C; Murphy, Declan GM; Bullmore, Edward

2014-01-01

There are now many reports of imaging experiments with small cohorts of typical participants that precede large-scale, often multicentre studies of psychiatric and neurological disorders. Data from these calibration experiments are sufficient to make estimates of statistical power and predictions of sample size and minimum observable effect sizes. In this technical note, we suggest how previously reported voxel-based power calculations can support decision making in the design, execution and analysis of cross-sectional multicentre imaging studies. The choice of MRI acquisition sequence, distribution of recruitment across acquisition centres, and changes to the registration method applied during data analysis are considered as examples. The consequences of modification are explored in quantitative terms by assessing the impact on sample size for a fixed effect size and detectable effect size for a fixed sample size. The calibration experiment dataset used for illustration was a precursor to the now complete Medical Research Council Autism Imaging Multicentre Study (MRC-AIMS). Validation of the voxel-based power calculations is made by comparing the predicted values from the calibration experiment with those observed in MRC-AIMS. The effect of non-linear mappings during image registration to a standard stereotactic space on the prediction is explored with reference to the amount of local deformation. In summary, power calculations offer a validated, quantitative means of making informed choices on important factors that influence the outcome of studies that consume significant resources. PMID:24644267

MSeq-CNV: accurate detection of Copy Number Variation from Sequencing of Multiple samples.

PubMed

Malekpour, Seyed Amir; Pezeshk, Hamid; Sadeghi, Mehdi

2018-03-05

Currently a few tools are capable of detecting genome-wide Copy Number Variations (CNVs) based on sequencing of multiple samples. Although aberrations in mate pair insertion sizes provide additional hints for the CNV detection based on multiple samples, the majority of the current tools rely only on the depth of coverage. Here, we propose a new algorithm (MSeq-CNV) which allows detecting common CNVs across multiple samples. MSeq-CNV applies a mixture density for modeling aberrations in depth of coverage and abnormalities in the mate pair insertion sizes. Each component in this mixture density applies a Binomial distribution for modeling the number of mate pairs with aberration in the insertion size and also a Poisson distribution for emitting the read counts, in each genomic position. MSeq-CNV is applied on simulated data and also on real data of six HapMap individuals with high-coverage sequencing, in 1000 Genomes Project. These individuals include a CEU trio of European ancestry and a YRI trio of Nigerian ethnicity. Ancestry of these individuals is studied by clustering the identified CNVs. MSeq-CNV is also applied for detecting CNVs in two samples with low-coverage sequencing in 1000 Genomes Project and six samples form the Simons Genome Diversity Project.

Reliability of confidence intervals calculated by bootstrap and classical methods using the FIA 1-ha plot design

Treesearch

H. T. Schreuder; M. S. Williams

2000-01-01

In simulation sampling from forest populations using sample sizes of 20, 40, and 60 plots respectively, confidence intervals based on the bootstrap (accelerated, percentile, and t-distribution based) were calculated and compared with those based on the classical t confidence intervals for mapped populations and subdomains within those populations. A 68.1 ha mapped...

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

A comparison of two sampling approaches for assessing the urban forest canopy cover from aerial photography.

Treesearch

Ucar Zennure; Pete Bettinger; Krista Merry; Jacek Siry; J.M. Bowker

2016-01-01

Two different sampling approaches for estimating urban tree canopy cover were applied to two medium-sized cities in the United States, in conjunction with two freely available remotely sensed imagery products. A random point-based sampling approach, which involved 1000 sample points, was compared against a plot/grid sampling (cluster sampling) approach that involved a...

Sediment Grain-Size and Loss-on-Ignition Analyses from 2002 Englebright Lake Coring and Sampling Campaigns

USGS Publications Warehouse

Snyder, Noah P.; Allen, James R.; Dare, Carlin; Hampton, Margaret A.; Schneider, Gary; Wooley, Ryan J.; Alpers, Charles N.; Marvin-DiPasquale, Mark C.

2004-01-01

This report presents sedimentologic data from three 2002 sampling campaigns conducted in Englebright Lake on the Yuba River in northern California. This work was done to assess the properties of the material deposited in the reservoir between completion of Englebright Dam in 1940 and 2002, as part of the Upper Yuba River Studies Program. Included are the results of grain-size-distribution and loss-on-ignition analyses for 561 samples, as well as an error analysis based on replicate pairs of subsamples.

Insights into bioassessment of marine pollution using body-size distinctness of planktonic ciliates based on a modified trait hierarchy.

PubMed

Xu, Henglong; Jiang, Yong; Xu, Guangjian

2016-06-15

Based on a modified trait hierarchy of body-size units, the feasibility for bioassessment of water pollution using body-size distinctness of planktonic ciliates was studied in a semi-enclosed bay, northern China. An annual dataset was collected at five sampling stations within a gradient of heavy metal contaminants. Results showed that: (1) in terms of probability density, the body-size spectra of the ciliates represented significant differences among the five stations; (2) bootstrap average analysis demonstrated a spatial variation in body-size rank patterns in response to pollution stress due to heavy metals; and (3) the average body-size distinctness (Δz(+)) and variation in body-size distinctness (Λz(+)), based on the modified trait hierarchy, revealed a clear departure pattern from the expected body-size spectra in areas with pollutants. These results suggest that the body-size diversity measures based on the modified trait hierarchy of the ciliates may be used as a potential indicator of marine pollution. Copyright © 2016 Elsevier Ltd. All rights reserved.

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%...

Optimally estimating the sample mean from the sample size, median, mid-range, and/or mid-quartile range.

PubMed

Luo, Dehui; Wan, Xiang; Liu, Jiming; Tong, Tiejun

2018-06-01

The era of big data is coming, and evidence-based medicine is attracting increasing attention to improve decision making in medical practice via integrating evidence from well designed and conducted clinical research. Meta-analysis is a statistical technique widely used in evidence-based medicine for analytically combining the findings from independent clinical trials to provide an overall estimation of a treatment effectiveness. The sample mean and standard deviation are two commonly used statistics in meta-analysis but some trials use the median, the minimum and maximum values, or sometimes the first and third quartiles to report the results. Thus, to pool results in a consistent format, researchers need to transform those information back to the sample mean and standard deviation. In this article, we investigate the optimal estimation of the sample mean for meta-analysis from both theoretical and empirical perspectives. A major drawback in the literature is that the sample size, needless to say its importance, is either ignored or used in a stepwise but somewhat arbitrary manner, e.g. the famous method proposed by Hozo et al. We solve this issue by incorporating the sample size in a smoothly changing weight in the estimators to reach the optimal estimation. Our proposed estimators not only improve the existing ones significantly but also share the same virtue of the simplicity. The real data application indicates that our proposed estimators are capable to serve as "rules of thumb" and will be widely applied in evidence-based medicine.

Purification of complex samples: Implementation of a modular and reconfigurable droplet-based microfluidic platform with cascaded deterministic lateral displacement separation modules

PubMed Central

Pudda, Catherine; Boizot, François; Verplanck, Nicolas; Revol-Cavalier, Frédéric; Berthier, Jean; Thuaire, Aurélie

2018-01-01

Particle separation in microfluidic devices is a common problematic for sample preparation in biology. Deterministic lateral displacement (DLD) is efficiently implemented as a size-based fractionation technique to separate two populations of particles around a specific size. However, real biological samples contain components of many different sizes and a single DLD separation step is not sufficient to purify these complex samples. When connecting several DLD modules in series, pressure balancing at the DLD outlets of each step becomes critical to ensure an optimal separation efficiency. A generic microfluidic platform is presented in this paper to optimize pressure balancing, when DLD separation is connected either to another DLD module or to a different microfluidic function. This is made possible by generating droplets at T-junctions connected to the DLD outlets. Droplets act as pressure controllers, which perform at the same time the encapsulation of DLD sorted particles and the balance of output pressures. The optimized pressures to apply on DLD modules and on T-junctions are determined by a general model that ensures the equilibrium of the entire platform. The proposed separation platform is completely modular and reconfigurable since the same predictive model applies to any cascaded DLD modules of the droplet-based cartridge. PMID:29768490

Sample size allocation for food item radiation monitoring and safety inspection.

PubMed

Seto, Mayumi; Uriu, Koichiro

2015-03-01

The objective of this study is to identify a procedure for determining sample size allocation for food radiation inspections of more than one food item to minimize the potential risk to consumers of internal radiation exposure. We consider a simplified case of food radiation monitoring and safety inspection in which a risk manager is required to monitor two food items, milk and spinach, in a contaminated area. Three protocols for food radiation monitoring with different sample size allocations were assessed by simulating random sampling and inspections of milk and spinach in a conceptual monitoring site. Distributions of (131)I and radiocesium concentrations were determined in reference to (131)I and radiocesium concentrations detected in Fukushima prefecture, Japan, for March and April 2011. The results of the simulations suggested that a protocol that allocates sample size to milk and spinach based on the estimation of (131)I and radiocesium concentrations using the apparent decay rate constants sequentially calculated from past monitoring data can most effectively minimize the potential risks of internal radiation exposure. © 2014 Society for Risk Analysis.

Estimation of the diagnostic threshold accounting for decision costs and sampling uncertainty.

PubMed

Skaltsa, Konstantina; Jover, Lluís; Carrasco, Josep Lluís

2010-10-01

Medical diagnostic tests are used to classify subjects as non-diseased or diseased. The classification rule usually consists of classifying subjects using the values of a continuous marker that is dichotomised by means of a threshold. Here, the optimum threshold estimate is found by minimising a cost function that accounts for both decision costs and sampling uncertainty. The cost function is optimised either analytically in a normal distribution setting or empirically in a free-distribution setting when the underlying probability distributions of diseased and non-diseased subjects are unknown. Inference of the threshold estimates is based on approximate analytically standard errors and bootstrap-based approaches. The performance of the proposed methodology is assessed by means of a simulation study, and the sample size required for a given confidence interval precision and sample size ratio is also calculated. Finally, a case example based on previously published data concerning the diagnosis of Alzheimer's patients is provided in order to illustrate the procedure.

The Effect of Brain Based Learning on Academic Achievement: A Meta-Analytical Study

ERIC Educational Resources Information Center

Gozuyesil, Eda; Dikici, Ayhan

2014-01-01

This study's aim is to measure the effect sizes of the quantitative studies that examined the effectiveness of brain-based learning on students' academic achievement and to examine with the meta-analytical method if there is a significant difference in effect in terms of the factors of education level, subject matter, sampling size, and the…

Effects of normalization on quantitative traits in association test

PubMed Central

2009-01-01

Background Quantitative trait loci analysis assumes that the trait is normally distributed. In reality, this is often not observed and one strategy is to transform the trait. However, it is not clear how much normality is required and which transformation works best in association studies. Results We performed simulations on four types of common quantitative traits to evaluate the effects of normalization using the logarithm, Box-Cox, and rank-based transformations. The impact of sample size and genetic effects on normalization is also investigated. Our results show that rank-based transformation gives generally the best and consistent performance in identifying the causal polymorphism and ranking it highly in association tests, with a slight increase in false positive rate. Conclusion For small sample size or genetic effects, the improvement in sensitivity for rank transformation outweighs the slight increase in false positive rate. However, for large sample size and genetic effects, normalization may not be necessary since the increase in sensitivity is relatively modest. PMID:20003414

Data splitting for artificial neural networks using SOM-based stratified sampling.

PubMed

May, R J; Maier, H R; Dandy, G C

2010-03-01

Data splitting is an important consideration during artificial neural network (ANN) development where hold-out cross-validation is commonly employed to ensure generalization. Even for a moderate sample size, the sampling methodology used for data splitting can have a significant effect on the quality of the subsets used for training, testing and validating an ANN. Poor data splitting can result in inaccurate and highly variable model performance; however, the choice of sampling methodology is rarely given due consideration by ANN modellers. Increased confidence in the sampling is of paramount importance, since the hold-out sampling is generally performed only once during ANN development. This paper considers the variability in the quality of subsets that are obtained using different data splitting approaches. A novel approach to stratified sampling, based on Neyman sampling of the self-organizing map (SOM), is developed, with several guidelines identified for setting the SOM size and sample allocation in order to minimize the bias and variance in the datasets. Using an example ANN function approximation task, the SOM-based approach is evaluated in comparison to random sampling, DUPLEX, systematic stratified sampling, and trial-and-error sampling to minimize the statistical differences between data sets. Of these approaches, DUPLEX is found to provide benchmark performance with good model performance, with no variability. The results show that the SOM-based approach also reliably generates high-quality samples and can therefore be used with greater confidence than other approaches, especially in the case of non-uniform datasets, with the benefit of scalability to perform data splitting on large datasets. Copyright 2009 Elsevier Ltd. All rights reserved.

Estimating accuracy of land-cover composition from two-stage cluster sampling

USGS Publications Warehouse

Stehman, S.V.; Wickham, J.D.; Fattorini, L.; Wade, T.D.; Baffetta, F.; Smith, J.H.

2009-01-01

Land-cover maps are often used to compute land-cover composition (i.e., the proportion or percent of area covered by each class), for each unit in a spatial partition of the region mapped. We derive design-based estimators of mean deviation (MD), mean absolute deviation (MAD), root mean square error (RMSE), and correlation (CORR) to quantify accuracy of land-cover composition for a general two-stage cluster sampling design, and for the special case of simple random sampling without replacement (SRSWOR) at each stage. The bias of the estimators for the two-stage SRSWOR design is evaluated via a simulation study. The estimators of RMSE and CORR have small bias except when sample size is small and the land-cover class is rare. The estimator of MAD is biased for both rare and common land-cover classes except when sample size is large. A general recommendation is that rare land-cover classes require large sample sizes to ensure that the accuracy estimators have small bias. ?? 2009 Elsevier Inc.

Experiments with central-limit properties of spatial samples from locally covariant random fields

USGS Publications Warehouse

Barringer, T.H.; Smith, T.E.

1992-01-01

When spatial samples are statistically dependent, the classical estimator of sample-mean standard deviation is well known to be inconsistent. For locally dependent samples, however, consistent estimators of sample-mean standard deviation can be constructed. The present paper investigates the sampling properties of one such estimator, designated as the tau estimator of sample-mean standard deviation. In particular, the asymptotic normality properties of standardized sample means based on tau estimators are studied in terms of computer experiments with simulated sample-mean distributions. The effects of both sample size and dependency levels among samples are examined for various value of tau (denoting the size of the spatial kernel for the estimator). The results suggest that even for small degrees of spatial dependency, the tau estimator exhibits significantly stronger normality properties than does the classical estimator of standardized sample means. ?? 1992.

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.

Annual design-based estimation for the annualized inventories of forest inventory and analysis: sample size determination

Treesearch

Hans T. Schreuder; Jin-Mann S. Lin; John Teply

2000-01-01

The Forest Inventory and Analysis units in the USDA Forest Service have been mandated by Congress to go to an annualized inventory where a certain percentage of plots, say 20 percent, will be measured in each State each year. Although this will result in an annual sample size that will be too small for reliable inference for many areas, it is a sufficiently large...

The generalization ability of SVM classification based on Markov sampling.

PubMed

Xu, Jie; Tang, Yuan Yan; Zou, Bin; Xu, Zongben; Li, Luoqing; Lu, Yang; Zhang, Baochang

2015-06-01

The previously known works studying the generalization ability of support vector machine classification (SVMC) algorithm are usually based on the assumption of independent and identically distributed samples. In this paper, we go far beyond this classical framework by studying the generalization ability of SVMC based on uniformly ergodic Markov chain (u.e.M.c.) samples. We analyze the excess misclassification error of SVMC based on u.e.M.c. samples, and obtain the optimal learning rate of SVMC for u.e.M.c. We also introduce a new Markov sampling algorithm for SVMC to generate u.e.M.c. samples from given dataset, and present the numerical studies on the learning performance of SVMC based on Markov sampling for benchmark datasets. The numerical studies show that the SVMC based on Markov sampling not only has better generalization ability as the number of training samples are bigger, but also the classifiers based on Markov sampling are sparsity when the size of dataset is bigger with regard to the input dimension.

Massively parallel sequencing of 17 commonly used forensic autosomal STRs and amelogenin with small amplicons.

PubMed

Kim, Eun Hye; Lee, Hwan Young; Yang, In Seok; Jung, Sang-Eun; Yang, Woo Ick; Shin, Kyoung-Jin

2016-05-01

The next-generation sequencing (NGS) method has been utilized to analyze short tandem repeat (STR) markers, which are routinely used for human identification purposes in the forensic field. Some researchers have demonstrated the successful application of the NGS system to STR typing, suggesting that NGS technology may be an alternative or additional method to overcome limitations of capillary electrophoresis (CE)-based STR profiling. However, there has been no available multiplex PCR system that is optimized for NGS analysis of forensic STR markers. Thus, we constructed a multiplex PCR system for the NGS analysis of 18 markers (13CODIS STRs, D2S1338, D19S433, Penta D, Penta E and amelogenin) by designing amplicons in the size range of 77-210 base pairs. Then, PCR products were generated from two single-sources, mixed samples and artificially degraded DNA samples using a multiplex PCR system, and were prepared for sequencing on the MiSeq system through construction of a subsequent barcoded library. By performing NGS and analyzing the data, we confirmed that the resultant STR genotypes were consistent with those of CE-based typing. Moreover, sequence variations were detected in targeted STR regions. Through the use of small-sized amplicons, the developed multiplex PCR system enables researchers to obtain successful STR profiles even from artificially degraded DNA as well as STR loci which are analyzed with large-sized amplicons in the CE-based commercial kits. In addition, successful profiles can be obtained from mixtures up to a 1:19 ratio. Consequently, the developed multiplex PCR system, which produces small size amplicons, can be successfully applied to STR NGS analysis of forensic casework samples such as mixtures and degraded DNA samples. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Testing homogeneity of proportion ratios for stratified correlated bilateral data in two-arm randomized clinical trials.

PubMed

Pei, Yanbo; Tian, Guo-Liang; Tang, Man-Lai

2014-11-10

Stratified data analysis is an important research topic in many biomedical studies and clinical trials. In this article, we develop five test statistics for testing the homogeneity of proportion ratios for stratified correlated bilateral binary data based on an equal correlation model assumption. Bootstrap procedures based on these test statistics are also considered. To evaluate the performance of these statistics and procedures, we conduct Monte Carlo simulations to study their empirical sizes and powers under various scenarios. Our results suggest that the procedure based on score statistic performs well generally and is highly recommended. When the sample size is large, procedures based on the commonly used weighted least square estimate and logarithmic transformation with Mantel-Haenszel estimate are recommended as they do not involve any computation of maximum likelihood estimates requiring iterative algorithms. We also derive approximate sample size formulas based on the recommended test procedures. Finally, we apply the proposed methods to analyze a multi-center randomized clinical trial for scleroderma patients. Copyright © 2014 John Wiley & Sons, Ltd.

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.

[Effect of gap size between tooth and restorative materials on microbiolism based caries in vitro].

PubMed

Lu, Wen-bin; Li, Yun

2012-05-01

To evaluate the effect of gap size between tooth and restorative materials on microbiolism based caries in vitro. Tooth blocks made of human molars without caries and the same size composite resin blocks were selected and prepared. Tooth-resin matrix was mounted on resin base with a gap size of 0, 25, 50, 100, 190, 250 µm and a control group was dealed with adhesive system. Six experimental groups and one control group were included, with 8 samples in one group and a total of 56 samples. The samples were cultured by a 14-day sequential batch culture technique. The development of outer surface lesion and wall lesion was assessed with confocal laser scanning microscope (CLSM) by measuring the maximum lesion depth, fluorescence areas and average fluorescence value. The data were collected and statistically analyzed. The deposits of the tooth-restoration interface and the development of the carious lesion were observed by scanning electron microscope (SEM). Most groups showed outer surface lesion and wall surface lesions observed by CLSM and SEM except 2 samples in control group. There was no significant difference on the outer surface lesion (P > 0.05). The maximum lesion depth [(1145.37 ± 198.98), (1190.12 ± 290.80) µm respectively], the maximum lesion length, fluorescence areas and average fluorescence value of 190 and 250 µm groups' wall lesions were significantly higher than the 0, 25, 50 and 100 µm groups [the maximum lesion depth was (205.25 ± 122.61), (303.87 ± 118.80), (437.75 ± 154.88), (602.87 ± 269.13) µm respectively], P < 0.01. With the increase of the gap size, the demineralization developed more seriously. While the maximum lesion depth, the maximum lesion length and fluorescence areas of 0, 25, 50 µm groups' wall lesions were of no significant difference. There was close relationship between gap size and wall lesion when the gap was above 100 µm at tooth-composite resin interface. The existence of gap was the main influencing factor on the development of microbiolism based caries lesion.

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.

EPR investigation of UV light effect on calcium carbonate powders with different grain sizes.

PubMed

Kabacińska, Zuzanna; Krzyminiewski, Ryszard; Dobosz, Bernadeta

2014-06-01

This study is based on investigation of calcium carbonate powders with different grain sizes exposed to UV light. Calcium carbonate is widely used in many branches of industry, e.g. as a filler for polymer materials; therefore, knowing its properties, among them also its reaction to UV light, is essential. Samples of powdered calcium carbonate with average grain sizes of 69 and 300 nm and 2.1, 6, 16, 25 µm were used in this investigation. Measurements were performed at room temperature using EPR X-band spectrometer, and they have shown the additional signals induced by the light from Hg lamp. The effect of annealing of the micro-grain samples was also studied. The spectra of four micro-grain samples after irradiation are similar, but there are differences between them and the other two powders, which could be related to the different sizes of their grains. Further studies based on these preliminary results may prove useful in research of photodegradation of CaCO3-filled materials, as well as helpful in increasing the accuracy of dating of archaeological and geological objects. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Characterization of the Particle Size and Polydispersity of Dicumarol Using Solid-State NMR Spectroscopy.

PubMed

Dempah, Kassibla Elodie; Lubach, Joseph W; Munson, Eric J

2017-03-06

A variety of particle sizes of a model compound, dicumarol, were prepared and characterized in order to investigate the correlation between particle size and solid-state NMR (SSNMR) proton spin-lattice relaxation ( 1 H T 1 ) times. Conventional laser diffraction and scanning electron microscopy were used as particle size measurement techniques and showed crystalline dicumarol samples with sizes ranging from tens of micrometers to a few micrometers. Dicumarol samples were prepared using both bottom-up and top-down particle size control approaches, via antisolvent microprecipitation and cryogrinding. It was observed that smaller particles of dicumarol generally had shorter 1 H T 1 times than larger ones. Additionally, cryomilled particles had the shortest 1 H T 1 times encountered (8 s). SSNMR 1 H T 1 times of all the samples were measured and showed as-received dicumarol to have a T 1 of 1500 s, whereas the 1 H T 1 times of the precipitated samples ranged from 20 to 80 s, with no apparent change in the physical form of dicumarol. Physical mixtures of different sized particles were also analyzed to determine the effect of sample inhomogeneity on 1 H T 1 values. Mixtures of cryoground and as-received dicumarol were clearly inhomogeneous as they did not fit well to a one-component relaxation model, but could be fit much better to a two-component model with both fast-and slow-relaxing regimes. Results indicate that samples of crystalline dicumarol containing two significantly different particle size populations could be deconvoluted solely based on their differences in 1 H T 1 times. Relative populations of each particle size regime could also be approximated using two-component fitting models. Using NMR theory on spin diffusion as a reference, and taking into account the presence of crystal defects, a model for the correlation between the particle size of dicumarol and its 1 H T 1 time was proposed.

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.

Sequential ensemble-based optimal design for parameter estimation: SEQUENTIAL ENSEMBLE-BASED OPTIMAL DESIGN

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

Man, Jun; Zhang, Jiangjiang; Li, Weixuan

2016-10-01

The ensemble Kalman filter (EnKF) has been widely used in parameter estimation for hydrological models. The focus of most previous studies was to develop more efficient analysis (estimation) algorithms. On the other hand, it is intuitively understandable that a well-designed sampling (data-collection) strategy should provide more informative measurements and subsequently improve the parameter estimation. In this work, a Sequential Ensemble-based Optimal Design (SEOD) method, coupled with EnKF, information theory and sequential optimal design, is proposed to improve the performance of parameter estimation. Based on the first-order and second-order statistics, different information metrics including the Shannon entropy difference (SD), degrees ofmore » freedom for signal (DFS) and relative entropy (RE) are used to design the optimal sampling strategy, respectively. The effectiveness of the proposed method is illustrated by synthetic one-dimensional and two-dimensional unsaturated flow case studies. It is shown that the designed sampling strategies can provide more accurate parameter estimation and state prediction compared with conventional sampling strategies. Optimal sampling designs based on various information metrics perform similarly in our cases. The effect of ensemble size on the optimal design is also investigated. Overall, larger ensemble size improves the parameter estimation and convergence of optimal sampling strategy. Although the proposed method is applied to unsaturated flow problems in this study, it can be equally applied in any other hydrological problems.« less

Transport Loss Estimation of Fine Particulate Matter in Sampling Tube Based on Numerical Computation

NASA Astrophysics Data System (ADS)

Luo, L.; Cheng, Z.

2016-12-01

In-situ measurement of PM2.5 physical and chemical properties is one substantial approach for the mechanism investigation of PM2.5 pollution. Minimizing PM2.5 transport loss in sampling tube is essential for ensuring the accuracy of the measurement result. In order to estimate the integrated PM2.5 transport efficiency in sampling tube and optimize tube designs, the effects of different tube factors (length, bore size and bend number) on the PM2.5 transport were analyzed based on the numerical computation. The results shows that PM2.5 mass concentration transport efficiency of vertical tube with flowrate at 20.0 L·min-1, bore size at 4 mm, length at 1.0 m was 89.6%. However, the transport efficiency will increase to 98.3% when the bore size is increased to 14 mm. PM2.5 mass concentration transport efficiency of horizontal tube with flowrate at 1.0 L·min-1, bore size at 4mm, length at 10.0 m is 86.7%, increased to 99.2% with length at 0.5 m. Low transport efficiency of 85.2% for PM2.5 mass concentration is estimated in bend with flowrate at 20.0 L·min-1, bore size at 4mm, curvature angle at 90o. Laminar flow of air in tube through keeping the ratio of flowrate (L·min-1) and bore size (mm) less than 1.4 is beneficial to decrease the PM2.5 transport loss. For the target of PM2.5 transport efficiency higher than 97%, it is advised to use vertical sampling tubes with length less than 6.0 m for the flowrates of 2.5, 5.0, 10.0 L·min-1 and bore size larger than 12 mm for the flowrates of 16.7 or 20.0 L·min-1. For horizontal sampling tubes, tube length is decided by the ratio of flowrate and bore size. Meanwhile, it is suggested to decrease the amount of the bends in tube of turbulent flow.

Estimation After a Group Sequential Trial.

PubMed

Milanzi, Elasma; Molenberghs, Geert; Alonso, Ariel; Kenward, Michael G; Tsiatis, Anastasios A; Davidian, Marie; Verbeke, Geert

2015-10-01

Group sequential trials are one important instance of studies for which the sample size is not fixed a priori but rather takes one of a finite set of pre-specified values, dependent on the observed data. Much work has been devoted to the inferential consequences of this design feature. Molenberghs et al (2012) and Milanzi et al (2012) reviewed and extended the existing literature, focusing on a collection of seemingly disparate, but related, settings, namely completely random sample sizes, group sequential studies with deterministic and random stopping rules, incomplete data, and random cluster sizes. They showed that the ordinary sample average is a viable option for estimation following a group sequential trial, for a wide class of stopping rules and for random outcomes with a distribution in the exponential family. Their results are somewhat surprising in the sense that the sample average is not optimal, and further, there does not exist an optimal, or even, unbiased linear estimator. However, the sample average is asymptotically unbiased, both conditionally upon the observed sample size as well as marginalized over it. By exploiting ignorability they showed that the sample average is the conventional maximum likelihood estimator. They also showed that a conditional maximum likelihood estimator is finite sample unbiased, but is less efficient than the sample average and has the larger mean squared error. Asymptotically, the sample average and the conditional maximum likelihood estimator are equivalent. This previous work is restricted, however, to the situation in which the the random sample size can take only two values, N = n or N = 2 n . In this paper, we consider the more practically useful setting of sample sizes in a the finite set { n 1 , n 2 , …, n L }. It is shown that the sample average is then a justifiable estimator , in the sense that it follows from joint likelihood estimation, and it is consistent and asymptotically unbiased. We also show why simulations can give the false impression of bias in the sample average when considered conditional upon the sample size. The consequence is that no corrections need to be made to estimators following sequential trials. When small-sample bias is of concern, the conditional likelihood estimator provides a relatively straightforward modification to the sample average. Finally, it is shown that classical likelihood-based standard errors and confidence intervals can be applied, obviating the need for technical corrections.

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.

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.

Size-based cell sorting with a resistive pulse sensor and an electromagnetic pump in a microfluidic chip.

PubMed

Song, Yongxin; Li, Mengqi; Pan, Xinxiang; Wang, Qi; Li, Dongqing

2015-02-01

An electrokinetic microfluidic chip is developed to detect and sort target cells by size from human blood samples. Target-cell detection is achieved by a differential resistive pulse sensor (RPS) based on the size difference between the target cell and other cells. Once a target cell is detected, the detected RPS signal will automatically actuate an electromagnetic pump built in a microchannel to push the target cell into a collecting channel. This method was applied to automatically detect and sort A549 cells and T-lymphocytes from a peripheral fingertip blood sample. The viability of A549 cells sorted in the collecting well was verified by Hoechst33342 and propidium iodide staining. The results show that as many as 100 target cells per minute can be sorted out from the sample solution and thus is particularly suitable for sorting very rare target cells, such as circulating tumor cells. The actuation of the electromagnetic valve has no influence on RPS cell detection and the consequent cell-sorting process. The viability of the collected A549 cell is not impacted by the applied electric field when the cell passes the RPS detection area. The device described in this article is simple, automatic, and label-free and has wide applications in size-based rare target cell sorting for medical diagnostics. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Crystal Face Distributions and Surface Site Densities of Two Synthetic Goethites: Implications for Adsorption Capacities as a Function of Particle Size.

PubMed

Livi, Kenneth J T; Villalobos, Mario; Leary, Rowan; Varela, Maria; Barnard, Jon; Villacís-García, Milton; Zanella, Rodolfo; Goodridge, Anna; Midgley, Paul

2017-09-12

Two synthetic goethites of varying crystal size distributions were analyzed by BET, conventional TEM, cryo-TEM, atomic resolution STEM and HRTEM, and electron tomography in order to determine the effects of crystal size, shape, and atomic scale surface roughness on their adsorption capacities. The two samples were determined by BET to have very different site densities based on Cr VI adsorption experiments. Model specific surface areas generated from TEM observations showed that, based on size and shape, there should be little difference in their adsorption capacities. Electron tomography revealed that both samples crystallized with an asymmetric {101} tablet habit. STEM and HRTEM images showed a significant increase in atomic-scale surface roughness of the larger goethite. This difference in roughness was quantified based on measurements of relative abundances of crystal faces {101} and {201} for the two goethites, and a reactive surface site density was calculated for each goethite. Singly coordinated sites on face {210} are 2.5 more dense than on face {101}, and the larger goethite showed an average total of 36% {210} as compared to 14% for the smaller goethite. This difference explains the considerably larger adsorption capacitiy of the larger goethite vs the smaller sample and points toward the necessity of knowing the atomic scale surface structure in predicting mineral adsorption processes.

Estimation of within-stratum variance for sample allocation: Foreign commodity production forecasting

NASA Technical Reports Server (NTRS)

Chhikara, R. S.; Perry, C. R., Jr. (Principal Investigator)

1980-01-01

The problem of determining the stratum variances required for an optimum sample allocation for remotely sensed crop surveys is investigated with emphasis on an approach based on the concept of stratum variance as a function of the sampling unit size. A methodology using the existing and easily available information of historical statistics is developed for obtaining initial estimates of stratum variances. The procedure is applied to variance for wheat in the U.S. Great Plains and is evaluated based on the numerical results obtained. It is shown that the proposed technique is viable and performs satisfactorily with the use of a conservative value (smaller than the expected value) for the field size and with the use of crop statistics from the small political division level.

Implications of sampling design and sample size for national carbon accounting systems

Treesearch

Michael Köhl; Andrew Lister; Charles T. Scott; Thomas Baldauf; Daniel Plugge

2011-01-01

Countries willing to adopt a REDD regime need to establish a national Measurement, Reporting and Verification (MRV) system that provides information on forest carbon stocks and carbon stock changes. Due to the extensive areas covered by forests the information is generally obtained by sample based surveys. Most operational sampling approaches utilize a combination of...

Properties of hypothesis testing techniques and (Bayesian) model selection for exploration-based and theory-based (order-restricted) hypotheses.

PubMed

Kuiper, Rebecca M; Nederhoff, Tim; Klugkist, Irene

2015-05-01

In this paper, the performance of six types of techniques for comparisons of means is examined. These six emerge from the distinction between the method employed (hypothesis testing, model selection using information criteria, or Bayesian model selection) and the set of hypotheses that is investigated (a classical, exploration-based set of hypotheses containing equality constraints on the means, or a theory-based limited set of hypotheses with equality and/or order restrictions). A simulation study is conducted to examine the performance of these techniques. We demonstrate that, if one has specific, a priori specified hypotheses, confirmation (i.e., investigating theory-based hypotheses) has advantages over exploration (i.e., examining all possible equality-constrained hypotheses). Furthermore, examining reasonable order-restricted hypotheses has more power to detect the true effect/non-null hypothesis than evaluating only equality restrictions. Additionally, when investigating more than one theory-based hypothesis, model selection is preferred over hypothesis testing. Because of the first two results, we further examine the techniques that are able to evaluate order restrictions in a confirmatory fashion by examining their performance when the homogeneity of variance assumption is violated. Results show that the techniques are robust to heterogeneity when the sample sizes are equal. When the sample sizes are unequal, the performance is affected by heterogeneity. The size and direction of the deviations from the baseline, where there is no heterogeneity, depend on the effect size (of the means) and on the trend in the group variances with respect to the ordering of the group sizes. Importantly, the deviations are less pronounced when the group variances and sizes exhibit the same trend (e.g., are both increasing with group number). © 2014 The British Psychological Society.

Effect of kernel size and mill type on protein, milling yield, and baking quality of hard red spring wheat

USDA-ARS?s Scientific Manuscript database

Optimization of flour yield and quality is important in the milling industry. The objective of this study was to determine the effect of kernel size and mill type on flour yield and end-use quality. A hard red spring wheat composite sample was segregated, based on kernel size, into large, medium, ...

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

The use of group sequential, information-based sample size re-estimation in the design of the PRIMO study of chronic kidney disease.

PubMed

Pritchett, Yili; Jemiai, Yannis; Chang, Yuchiao; Bhan, Ishir; Agarwal, Rajiv; Zoccali, Carmine; Wanner, Christoph; Lloyd-Jones, Donald; Cannata-Andía, Jorge B; Thompson, Taylor; Appelbaum, Evan; Audhya, Paul; Andress, Dennis; Zhang, Wuyan; Solomon, Scott; Manning, Warren J; Thadhani, Ravi

2011-04-01

Chronic kidney disease is associated with a marked increase in risk for left ventricular hypertrophy and cardiovascular mortality compared with the general population. Therapy with vitamin D receptor activators has been linked with reduced mortality in chronic kidney disease and an improvement in left ventricular hypertrophy in animal studies. PRIMO (Paricalcitol capsules benefits in Renal failure Induced cardia MOrbidity) is a multinational, multicenter randomized controlled trial to assess the effects of paricalcitol (a selective vitamin D receptor activator) on mild to moderate left ventricular hypertrophy in patients with chronic kidney disease. Subjects with mild-moderate chronic kidney disease are randomized to paricalcitol or placebo after confirming left ventricular hypertrophy using a cardiac echocardiogram. Cardiac magnetic resonance imaging is then used to assess left ventricular mass index at baseline, 24 and 48 weeks, which is the primary efficacy endpoint of the study. Because of limited prior data to estimate sample size, a maximum information group sequential design with sample size re-estimation is implemented to allow sample size adjustment based on the nuisance parameter estimated using the interim data. An interim efficacy analysis is planned at a pre-specified time point conditioned on the status of enrollment. The decision to increase sample size depends on the observed treatment effect. A repeated measures analysis model, using available data at Week 24 and 48 with a backup model of an ANCOVA analyzing change from baseline to the final nonmissing observation, are pre-specified to evaluate the treatment effect. Gamma-family of spending function is employed to control family-wise Type I error rate as stopping for success is planned in the interim efficacy analysis. If enrollment is slower than anticipated, the smaller sample size used in the interim efficacy analysis and the greater percent of missing week 48 data might decrease the parameter estimation accuracy, either for the nuisance parameter or for the treatment effect, which might in turn affect the interim decision-making. The application of combining a group sequential design with a sample-size re-estimation in clinical trial design has the potential to improve efficiency and to increase the probability of trial success while ensuring integrity of the study.

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.

Body mass estimates of hominin fossils and the evolution of human body size.

PubMed

Grabowski, Mark; Hatala, Kevin G; Jungers, William L; Richmond, Brian G

2015-08-01

Body size directly influences an animal's place in the natural world, including its energy requirements, home range size, relative brain size, locomotion, diet, life history, and behavior. Thus, an understanding of the biology of extinct organisms, including species in our own lineage, requires accurate estimates of body size. Since the last major review of hominin body size based on postcranial morphology over 20 years ago, new fossils have been discovered, species attributions have been clarified, and methods improved. Here, we present the most comprehensive and thoroughly vetted set of individual fossil hominin body mass predictions to date, and estimation equations based on a large (n = 220) sample of modern humans of known body masses. We also present species averages based exclusively on fossils with reliable taxonomic attributions, estimates of species averages by sex, and a metric for levels of sexual dimorphism. Finally, we identify individual traits that appear to be the most reliable for mass estimation for each fossil species, for use when only one measurement is available for a fossil. Our results show that many early hominins were generally smaller-bodied than previously thought, an outcome likely due to larger estimates in previous studies resulting from the use of large-bodied modern human reference samples. Current evidence indicates that modern human-like large size first appeared by at least 3-3.5 Ma in some Australopithecus afarensis individuals. Our results challenge an evolutionary model arguing that body size increased from Australopithecus to early Homo. Instead, we show that there is no reliable evidence that the body size of non-erectus early Homo differed from that of australopiths, and confirm that Homo erectus evolved larger average body size than earlier hominins. Copyright © 2015 Elsevier Ltd. All rights reserved.

Generic Learning-Based Ensemble Framework for Small Sample Size Face Recognition in Multi-Camera Networks.

PubMed

Zhang, Cuicui; Liang, Xuefeng; Matsuyama, Takashi

2014-12-08

Multi-camera networks have gained great interest in video-based surveillance systems for security monitoring, access control, etc. Person re-identification is an essential and challenging task in multi-camera networks, which aims to determine if a given individual has already appeared over the camera network. Individual recognition often uses faces as a trial and requires a large number of samples during the training phrase. This is difficult to fulfill due to the limitation of the camera hardware system and the unconstrained image capturing conditions. Conventional face recognition algorithms often encounter the "small sample size" (SSS) problem arising from the small number of training samples compared to the high dimensionality of the sample space. To overcome this problem, interest in the combination of multiple base classifiers has sparked research efforts in ensemble methods. However, existing ensemble methods still open two questions: (1) how to define diverse base classifiers from the small data; (2) how to avoid the diversity/accuracy dilemma occurring during ensemble. To address these problems, this paper proposes a novel generic learning-based ensemble framework, which augments the small data by generating new samples based on a generic distribution and introduces a tailored 0-1 knapsack algorithm to alleviate the diversity/accuracy dilemma. More diverse base classifiers can be generated from the expanded face space, and more appropriate base classifiers are selected for ensemble. Extensive experimental results on four benchmarks demonstrate the higher ability of our system to cope with the SSS problem compared to the state-of-the-art system.

Sources of variability and comparability between salmonid stomach contents and isotopic analyses: study design lessons and recommendations

USGS Publications Warehouse

Vinson, M.R.; Budy, P.

2011-01-01

We compared sources of variability and cost in paired stomach content and stable isotope samples from three salmonid species collected in September 2001–2005 and describe the relative information provided by each method in terms of measuring diet overlap and food web study design. Based on diet analyses, diet overlap among brown trout, rainbow trout, and mountain whitefish was high, and we observed little variation in diets among years. In contrast, for sample sizes n ≥ 25, 95% confidence interval (CI) around mean δ15Ν and δ13C for the three target species did not overlap, and species, year, and fish size effects were significantly different, implying that these species likely consumed similar prey but in different proportions. Stable isotope processing costs were US$12 per sample, while stomach content analysis costs averaged US$25.49 ± $2.91 (95% CI) and ranged from US$1.50 for an empty stomach to US$291.50 for a sample with 2330 items. Precision in both δ15Ν and δ13C and mean diet overlap values based on stomach contents increased considerably up to a sample size of n = 10 and plateaued around n = 25, with little further increase in precision.

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.

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.

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.

Quality control considerations for size exclusion chromatography with online ICP-MS: a powerful tool for evaluating the size dependence of metal-organic matter complexation.

PubMed

McKenzie, Erica R; Young, Thomas M

2013-01-01

Size exclusion chromatography (SEC), which separates molecules based on molecular volume, can be coupled with online inductively coupled plasma mass spectrometry (ICP-MS) to explore size-dependent metal-natural organic matter (NOM) complexation. To make effective use of this analytical dual detector system, the operator should be mindful of quality control measures. Al, Cr, Fe, Se, and Sn all exhibited columnless attenuation, which indicated unintended interactions with system components. Based on signal-to-noise ratio and peak reproducibility between duplicate analyses of environmental samples, consistent peak time and height were observed for Mg, Cl, Mn, Cu, Br, and Pb. Al, V, Fe, Co, Ni, Zn, Se, Cd, Sn, and Sb were less consistent overall, but produced consistent measurements in select samples. Ultrafiltering and centrifuging produced similar peak distributions, but glass fiber filtration produced more high molecular weight (MW) peaks. Storage in glass also produced more high MW peaks than did plastic bottles.

Overlap between treatment and control distributions as an effect size measure in experiments.

PubMed

Hedges, Larry V; Olkin, Ingram

2016-03-01

The proportion π of treatment group observations that exceed the control group mean has been proposed as an effect size measure for experiments that randomly assign independent units into 2 groups. We give the exact distribution of a simple estimator of π based on the standardized mean difference and use it to study the small sample bias of this estimator. We also give the minimum variance unbiased estimator of π under 2 models, one in which the variance of the mean difference is known and one in which the variance is unknown. We show how to use the relation between the standardized mean difference and the overlap measure to compute confidence intervals for π and show that these results can be used to obtain unbiased estimators, large sample variances, and confidence intervals for 3 related effect size measures based on the overlap. Finally, we show how the effect size π can be used in a meta-analysis. (c) 2016 APA, all rights reserved).

Statistical power analysis in wildlife research

USGS Publications Warehouse

Steidl, R.J.; Hayes, J.P.

1997-01-01

Statistical power analysis can be used to increase the efficiency of research efforts and to clarify research results. Power analysis is most valuable in the design or planning phases of research efforts. Such prospective (a priori) power analyses can be used to guide research design and to estimate the number of samples necessary to achieve a high probability of detecting biologically significant effects. Retrospective (a posteriori) power analysis has been advocated as a method to increase information about hypothesis tests that were not rejected. However, estimating power for tests of null hypotheses that were not rejected with the effect size observed in the study is incorrect; these power estimates will always be a??0.50 when bias adjusted and have no relation to true power. Therefore, retrospective power estimates based on the observed effect size for hypothesis tests that were not rejected are misleading; retrospective power estimates are only meaningful when based on effect sizes other than the observed effect size, such as those effect sizes hypothesized to be biologically significant. Retrospective power analysis can be used effectively to estimate the number of samples or effect size that would have been necessary for a completed study to have rejected a specific null hypothesis. Simply presenting confidence intervals can provide additional information about null hypotheses that were not rejected, including information about the size of the true effect and whether or not there is adequate evidence to 'accept' a null hypothesis as true. We suggest that (1) statistical power analyses be routinely incorporated into research planning efforts to increase their efficiency, (2) confidence intervals be used in lieu of retrospective power analyses for null hypotheses that were not rejected to assess the likely size of the true effect, (3) minimum biologically significant effect sizes be used for all power analyses, and (4) if retrospective power estimates are to be reported, then the I?-level, effect sizes, and sample sizes used in calculations must also be reported.

The effects of sample scheduling and sample numbers on estimates of the annual fluxes of suspended sediment in fluvial systems

USGS Publications Warehouse

Horowitz, Arthur J.; Clarke, Robin T.; Merten, Gustavo Henrique

2015-01-01

Since the 1970s, there has been both continuing and growing interest in developing accurate estimates of the annual fluvial transport (fluxes and loads) of suspended sediment and sediment-associated chemical constituents. This study provides an evaluation of the effects of manual sample numbers (from 4 to 12 year−1) and sample scheduling (random-based, calendar-based and hydrology-based) on the precision, bias and accuracy of annual suspended sediment flux estimates. The evaluation is based on data from selected US Geological Survey daily suspended sediment stations in the USA and covers basins ranging in area from just over 900 km2 to nearly 2 million km2 and annual suspended sediment fluxes ranging from about 4 Kt year−1 to about 200 Mt year−1. The results appear to indicate that there is a scale effect for random-based and calendar-based sampling schemes, with larger sample numbers required as basin size decreases. All the sampling schemes evaluated display some level of positive (overestimates) or negative (underestimates) bias. The study further indicates that hydrology-based sampling schemes are likely to generate the most accurate annual suspended sediment flux estimates with the fewest number of samples, regardless of basin size. This type of scheme seems most appropriate when the determination of suspended sediment concentrations, sediment-associated chemical concentrations, annual suspended sediment and annual suspended sediment-associated chemical fluxes only represent a few of the parameters of interest in multidisciplinary, multiparameter monitoring programmes. The results are just as applicable to the calibration of autosamplers/suspended sediment surrogates currently used to measure/estimate suspended sediment concentrations and ultimately, annual suspended sediment fluxes, because manual samples are required to adjust the sample data/measurements generated by these techniques so that they provide depth-integrated and cross-sectionally representative data. 

(I Can’t Get No) Saturation: A simulation and guidelines for sample sizes in qualitative research

PubMed Central

2017-01-01

I explore the sample size in qualitative research that is required to reach theoretical saturation. I conceptualize a population as consisting of sub-populations that contain different types of information sources that hold a number of codes. Theoretical saturation is reached after all the codes in the population have been observed once in the sample. I delineate three different scenarios to sample information sources: “random chance,” which is based on probability sampling, “minimal information,” which yields at least one new code per sampling step, and “maximum information,” which yields the largest number of new codes per sampling step. Next, I use simulations to assess the minimum sample size for each scenario for systematically varying hypothetical populations. I show that theoretical saturation is more dependent on the mean probability of observing codes than on the number of codes in a population. Moreover, the minimal and maximal information scenarios are significantly more efficient than random chance, but yield fewer repetitions per code to validate the findings. I formulate guidelines for purposive sampling and recommend that researchers follow a minimum information scenario. PMID:28746358

Sampling errors in the estimation of empirical orthogonal functions. [for climatology studies

NASA Technical Reports Server (NTRS)

North, G. R.; Bell, T. L.; Cahalan, R. F.; Moeng, F. J.

1982-01-01

Empirical Orthogonal Functions (EOF's), eigenvectors of the spatial cross-covariance matrix of a meteorological field, are reviewed with special attention given to the necessary weighting factors for gridded data and the sampling errors incurred when too small a sample is available. The geographical shape of an EOF shows large intersample variability when its associated eigenvalue is 'close' to a neighboring one. A rule of thumb indicating when an EOF is likely to be subject to large sampling fluctuations is presented. An explicit example, based on the statistics of the 500 mb geopotential height field, displays large intersample variability in the EOF's for sample sizes of a few hundred independent realizations, a size seldom exceeded by meteorological data sets.

Nanoparticle Analysis by Online Comprehensive Two-Dimensional Liquid Chromatography combining Hydrodynamic Chromatography and Size-Exclusion Chromatography with Intermediate Sample Transformation

PubMed Central

2017-01-01

Polymeric nanoparticles have become indispensable in modern society with a wide array of applications ranging from waterborne coatings to drug-carrier-delivery systems. While a large range of techniques exist to determine a multitude of properties of these particles, relating physicochemical properties of the particle to the chemical structure of the intrinsic polymers is still challenging. A novel, highly orthogonal separation system based on comprehensive two-dimensional liquid chromatography (LC × LC) has been developed. The system combines hydrodynamic chromatography (HDC) in the first-dimension to separate the particles based on their size, with ultrahigh-performance size-exclusion chromatography (SEC) in the second dimension to separate the constituting polymer molecules according to their hydrodynamic radius for each of 80 to 100 separated fractions. A chip-based mixer is incorporated to transform the sample by dissolving the separated nanoparticles from the first-dimension online in tetrahydrofuran. The polymer bands are then focused using stationary-phase-assisted modulation to enhance sensitivity, and the water from the first-dimension eluent is largely eliminated to allow interaction-free SEC. Using the developed system, the combined two-dimensional distribution of the particle-size and the molecular-size of a mixture of various polystyrene (PS) and polyacrylate (PACR) nanoparticles has been obtained within 60 min. PMID:28745485

A combined Settling Tube-Photometer for rapid measurement of effective sediment particle size

NASA Astrophysics Data System (ADS)

Kuhn, Nikolaus J.; Kuhn, Brigitte; Rüegg, Hans-Rudolf; Zimmermann, Lukas

2017-04-01

Sediment and its movement in water is commonly described based on the size distribution of the mineral particles forming the sediment. While this approach works for coarse sand, pebbles and gravel, smaller particles often form aggregates, creating material of larger diameters than the mineral grain size distribution indicates, but lower densities than often assumed 2.65 g cm-3 of quartz. The measurement of the actual size and density of such aggregated sediment is difficult. For the assessment of sediment movement an effective particle size for the use in mathematical can be derived based on the settling velocity of sediment. Settling velocity of commonly measured in settling tubes which fractionate the sample in settling velocity classes by sampling material at the base in selected time intervals. This process takes up to several hours, requires a laboratory setting and carries the risk of either destruction of aggregates during transport or coagulation while sitting in rather still water. Measuring the velocity of settling particles in situ, or at least a rapidly after collection, could avoids these problems. In this study, a settling tube equipped with four photometers used to measure the darkening of a settling particle cloud is presented and the potential to improve the measurement of settling velocities are discussed.

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

Analyses of sweep-up, ejecta, and fallback material from the 4250 metric ton high explosive test ''MISTY PICTURE'

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

Wohletz, K.H.; Raymond, R. Jr.; Rawson, G.

1988-01-01

The MISTY PICTURE surface burst was detonated at the White Sands Missle range in May of 1987. The Los Alamos National Laboratory dust characterization program was expanded to help correlate and interrelate aspects of the overall MISTY PICTURE dust and ejecta characterization program. Pre-shot sampling of the test bed included composite samples from 15 to 75 m distance from Surface Ground Zero (SGZ) representing depths down to 2.5 m, interval samples from 15 to 25 m from SGZ representing depths down to 3m, and samples of surface material (top 0.5 cm) out to distances of 190 m from SGZ. Sweep-upmore » samples were collected in GREG/SNOB gages located within the DPR. All samples were dry-sieved between 8.0 mm and 0.045 mm (16 size fractures); selected samples were analyzed for fines by a contrifugal settling technique. The size distributions were analyzed using spectral decomposition based upon a sequential fragmentation model. Results suggest that the same particle size subpopulations are present in the ejecta, fallout, and sweep-up samples as are present in the pre-shot test bed. The particle size distribution in post-shot environments apparently can be modelled taking into account heterogeneities in the pre-shot test bed and dominant wind direction during and following the shot. 13 refs., 12 figs., 2 tabs.« less

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.

A novel, efficient method for estimating the prevalence of acute malnutrition in resource-constrained and crisis-affected settings: A simulation study.

PubMed

Frison, Severine; Kerac, Marko; Checchi, Francesco; Nicholas, Jennifer

2017-01-01

The assessment of the prevalence of acute malnutrition in children under five is widely used for the detection of emergencies, planning interventions, advocacy, and monitoring and evaluation. This study examined PROBIT Methods which convert parameters (mean and standard deviation (SD)) of a normally distributed variable to a cumulative probability below any cut-off to estimate acute malnutrition in children under five using Middle-Upper Arm Circumference (MUAC). We assessed the performance of: PROBIT Method I, with mean MUAC from the survey sample and MUAC SD from a database of previous surveys; and PROBIT Method II, with mean and SD of MUAC observed in the survey sample. Specifically, we generated sub-samples from 852 survey datasets, simulating 100 surveys for eight sample sizes. Overall the methods were tested on 681 600 simulated surveys. PROBIT methods relying on sample sizes as small as 50 had better performance than the classic method for estimating and classifying the prevalence of acute malnutrition. They had better precision in the estimation of acute malnutrition for all sample sizes and better coverage for smaller sample sizes, while having relatively little bias. They classified situations accurately for a threshold of 5% acute malnutrition. Both PROBIT methods had similar outcomes. PROBIT Methods have a clear advantage in the assessment of acute malnutrition prevalence based on MUAC, compared to the classic method. Their use would require much lower sample sizes, thus enable great time and resource savings and permit timely and/or locally relevant prevalence estimates of acute malnutrition for a swift and well-targeted response.

Lab-on-a-disc agglutination assay for protein detection by optomagnetic readout and optical imaging using nano- and micro-sized magnetic beads.

PubMed

Uddin, Rokon; Burger, Robert; Donolato, Marco; Fock, Jeppe; Creagh, Michael; Hansen, Mikkel Fougt; Boisen, Anja

2016-11-15

We present a biosensing platform for the detection of proteins based on agglutination of aptamer coated magnetic nano- or microbeads. The assay, from sample to answer, is integrated on an automated, low-cost microfluidic disc platform. This ensures fast and reliable results due to a minimum of manual steps involved. The detection of the target protein was achieved in two ways: (1) optomagnetic readout using magnetic nanobeads (MNBs); (2) optical imaging using magnetic microbeads (MMBs). The optomagnetic readout of agglutination is based on optical measurement of the dynamics of MNB aggregates whereas the imaging method is based on direct visualization and quantification of the average size of MMB aggregates. By enhancing magnetic particle agglutination via application of strong magnetic field pulses, we obtained identical limits of detection of 25pM with the same sample-to-answer time (15min 30s) using the two differently sized beads for the two detection methods. In both cases a sample volume of only 10µl is required. The demonstrated automation, low sample-to-answer time and portability of both detection instruments as well as integration of the assay on a low-cost disc are important steps for the implementation of these as portable tools in an out-of-lab setting. Copyright © 2016 Elsevier B.V. All rights reserved.

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…

Sampling effort and estimates of species richness based on prepositioned area electrofisher samples

USGS Publications Warehouse

Bowen, Z.H.; Freeman, Mary C.

1998-01-01

Estimates of species richness based on electrofishing data are commonly used to describe the structure of fish communities. One electrofishing method for sampling riverine fishes that has become popular in the last decade is the prepositioned area electrofisher (PAE). We investigated the relationship between sampling effort and fish species richness at seven sites in the Tallapoosa River system, USA based on 1,400 PAE samples collected during 1994 and 1995. First, we estimated species richness at each site using the first-order jackknife and compared observed values for species richness and jackknife estimates of species richness to estimates based on historical collection data. Second, we used a permutation procedure and nonlinear regression to examine rates of species accumulation. Third, we used regression to predict the number of PAE samples required to collect the jackknife estimate of species richness at each site during 1994 and 1995. We found that jackknife estimates of species richness generally were less than or equal to estimates based on historical collection data. The relationship between PAE electrofishing effort and species richness in the Tallapoosa River was described by a positive asymptotic curve as found in other studies using different electrofishing gears in wadable streams. Results from nonlinear regression analyses indicted that rates of species accumulation were variable among sites and between years. Across sites and years, predictions of sampling effort required to collect jackknife estimates of species richness suggested that doubling sampling effort (to 200 PAEs) would typically increase observed species richness by not more than six species. However, sampling effort beyond about 60 PAE samples typically increased observed species richness by < 10%. We recommend using historical collection data in conjunction with a preliminary sample size of at least 70 PAE samples to evaluate estimates of species richness in medium-sized rivers. Seventy PAE samples should provide enough information to describe the relationship between sampling effort and species richness and thus facilitate evaluation of a sampling effort.

Personal Exposure to Particulate Matter and Endotoxin in California Dairy Workers

NASA Astrophysics Data System (ADS)

Garcia, Johnny

The average number of cows per dairy has increased over the last thirty years, with little known about how this increase may impact occupational exposure. Thirteen California dairies and 226 workers participated in this study throughout the 2008 summer months. Particulate Matter (PM) and endotoxin concentrations were quantified using ambient area based and personal air samplers. Two size fractions were collected, Total Suspended Particulate matter (TSP) and PM 2.5. Differences across dairies were evaluated by placing area based integrated air samplers in established locations on the dairies, e.g. milking parlor, drylot corral, and freestall barns. The workers occupational exposure was quantified using personal air samplers. We analyzed concentrations along with the time workers spent conducting specific job tasks during their shift to identify high exposure job tasks. Biological and chemical analytical methods were employed to ascertain endotoxin concentrations in personal and area based air samples. Recombinant factor C assays (rFC) were used to analyze biologically active endotoxin and gas chromatography coupled with mass spectrometry in tandem (GC-MS/MS) was used to quantify total endotoxin. The PM2.5 concentrations ranged from 2-116 mug/m3 for ambient area concentration and 7-495 mug/m3 for personal concentrations while TSP concentrations ranged from 74-1690 mug/m3 for area ambient concentrations and 191-4950 mug/m3 for personal concentrations. Biologically active endotoxin concentrations in the TSP size fraction from ambient area based samples ranged from 11-2095 EU/m3 and 45-2061 EU/m3 for personal samples. Total endotoxin in the TSP size fraction ranged from 75-10,166 pmol/m3 for area based samples and 34-11,689 pmol/m3 for personal samples. Drylot corrals were found to have higher sample mean concentrations when compared to other locations on the dairies for PM and endotoxin. Re-bedding, of the freestalls, was found to consistently lead to higher personal sample mean concentrations when compared to other tasks performed on dairies for both endotoxin and PM. In mixed effect regression models, regional ambient concentrations of PM 2.5 helped account for variation in PM2.5 concentration outcomes. We found that while upwind and downwind mean concentrations were not significantly different, central mean concentrations were higher than upwind concentration. Variation in TSP levels was largely explained by dairy-level characteristics such as the age of the dairy and number of animals in the drylot corrals and freestall barns. The different locations within the dairy were found to differ in mean concentrations for TSP. Biologically active and total endotoxin concentration variation was explained by meteorological data, wind speed, relative humidity, and dairy waste management practices. Personal exposure levels where found to be higher than area based concentrations for PM and endotoxin. Endotoxin characteristics differed by particle size and location within the dairy. The chain length proportion for endotoxin in the PM 2.5 size fraction was dominated by C12 and C16 in the TSP size fraction.

An integrated approach to piezoactuator positioning in high-speed atomic force microscope imaging

NASA Astrophysics Data System (ADS)

Yan, Yan; Wu, Ying; Zou, Qingze; Su, Chanmin

2008-07-01

In this paper, an integrated approach to achieve high-speed atomic force microscope (AFM) imaging of large-size samples is proposed, which combines the enhanced inversion-based iterative control technique to drive the piezotube actuator control for lateral x-y axis positioning with the use of a dual-stage piezoactuator for vertical z-axis positioning. High-speed, large-size AFM imaging is challenging because in high-speed lateral scanning of the AFM imaging at large size, large positioning error of the AFM probe relative to the sample can be generated due to the adverse effects—the nonlinear hysteresis and the vibrational dynamics of the piezotube actuator. In addition, vertical precision positioning of the AFM probe is even more challenging (than the lateral scanning) because the desired trajectory (i.e., the sample topography profile) is unknown in general, and the probe positioning is also effected by and sensitive to the probe-sample interaction. The main contribution of this article is the development of an integrated approach that combines advanced control algorithm with an advanced hardware platform. The proposed approach is demonstrated in experiments by imaging a large-size (50μm ) calibration sample at high-speed (50Hz scan rate).

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.

Angiographic core laboratory reproducibility analyses: implications for planning clinical trials using coronary angiography and left ventriculography end-points.

PubMed

Steigen, Terje K; Claudio, Cheryl; Abbott, David; Schulzer, Michael; Burton, Jeff; Tymchak, Wayne; Buller, Christopher E; John Mancini, G B

2008-06-01

To assess reproducibility of core laboratory performance and impact on sample size calculations. Little information exists about overall reproducibility of core laboratories in contradistinction to performance of individual technicians. Also, qualitative parameters are being adjudicated increasingly as either primary or secondary end-points. The comparative impact of using diverse indexes on sample sizes has not been previously reported. We compared initial and repeat assessments of five quantitative parameters [e.g., minimum lumen diameter (MLD), ejection fraction (EF), etc.] and six qualitative parameters [e.g., TIMI myocardial perfusion grade (TMPG) or thrombus grade (TTG), etc.], as performed by differing technicians and separated by a year or more. Sample sizes were calculated from these results. TMPG and TTG were also adjudicated by a second core laboratory. MLD and EF were the most reproducible, yielding the smallest sample size calculations, whereas percent diameter stenosis and centerline wall motion require substantially larger trials. Of the qualitative parameters, all except TIMI flow grade gave reproducibility characteristics yielding sample sizes of many 100's of patients. Reproducibility of TMPG and TTG was only moderately good both within and between core laboratories, underscoring an intrinsic difficulty in assessing these. Core laboratories can be shown to provide reproducibility performance that is comparable to performance commonly ascribed to individual technicians. The differences in reproducibility yield huge differences in sample size when comparing quantitative and qualitative parameters. TMPG and TTG are intrinsically difficult to assess and conclusions based on these parameters should arise only from very large trials.

Heavy metals relationship with water and size-fractionated sediments in rivers using canonical correlation analysis (CCA) case study, rivers of south western Caspian Sea.

PubMed

Vosoogh, Ali; Saeedi, Mohsen; Lak, Raziyeh

2016-11-01

Some pollutants can qualitatively affect aquatic freshwater such as rivers, and heavy metals are one of the most important pollutants in aquatic fresh waters. Heavy metals can be found in the form of components dissolved in these waters or in compounds with suspended particles and surface sediments. It can be said that heavy metals are in equilibrium between water and sediment. In this study, the amount of heavy metals is determined in water and different sizes of sediment. To obtain the relationship between heavy metals in water and size-fractionated sediments, a canonical correlation analysis (CCA) was utilized in rivers of the southwestern Caspian Sea. In this research, a case study was carried out on 18 sampling stations in nine rivers. In the first step, the concentrations of heavy metals (Cu, Zn, Cr, Fe, Mn, Pb, Ni, and Cd) were determined in water and size-fractionated sediment samples. Water sampling sites were classified by hierarchical cluster analysis (HCA) utilizing squared Euclidean distance with Ward's method. In addition, for interpreting the obtained results and the relationships between the concentration of heavy metals in the tested river water and sample sediments, canonical correlation analysis (CCA) was utilized. The rivers were grouped into two classes (those having no pollution and those having low pollution) based on the HCA results obtained for river water samples. CCA results found numerous relationships between rivers in Iran's Guilan province and their size-fractionated sediments samples. The heavy metals of sediments with 0.038 to 0.125 mm size in diameter are slightly correlated with those of water samples.

Malaria prevalence metrics in low- and middle-income countries: an assessment of precision in nationally-representative surveys.

PubMed

Alegana, Victor A; Wright, Jim; Bosco, Claudio; Okiro, Emelda A; Atkinson, Peter M; Snow, Robert W; Tatem, Andrew J; Noor, Abdisalan M

2017-11-21

One pillar to monitoring progress towards the Sustainable Development Goals is the investment in high quality data to strengthen the scientific basis for decision-making. At present, nationally-representative surveys are the main source of data for establishing a scientific evidence base, monitoring, and evaluation of health metrics. However, little is known about the optimal precisions of various population-level health and development indicators that remains unquantified in nationally-representative household surveys. Here, a retrospective analysis of the precision of prevalence from these surveys was conducted. Using malaria indicators, data were assembled in nine sub-Saharan African countries with at least two nationally-representative surveys. A Bayesian statistical model was used to estimate between- and within-cluster variability for fever and malaria prevalence, and insecticide-treated bed nets (ITNs) use in children under the age of 5 years. The intra-class correlation coefficient was estimated along with the optimal sample size for each indicator with associated uncertainty. Results suggest that the estimated sample sizes for the current nationally-representative surveys increases with declining malaria prevalence. Comparison between the actual sample size and the modelled estimate showed a requirement to increase the sample size for parasite prevalence by up to 77.7% (95% Bayesian credible intervals 74.7-79.4) for the 2015 Kenya MIS (estimated sample size of children 0-4 years 7218 [7099-7288]), and 54.1% [50.1-56.5] for the 2014-2015 Rwanda DHS (12,220 [11,950-12,410]). This study highlights the importance of defining indicator-relevant sample sizes to achieve the required precision in the current national surveys. While expanding the current surveys would need additional investment, the study highlights the need for improved approaches to cost effective sampling.

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

The effect of age and body composition on body mass estimation of males using the stature/bi-iliac method.

PubMed

Junno, Juho-Antti; Niskanen, Markku; Maijanen, Heli; Holt, Brigitte; Sladek, Vladimir; Niinimäki, Sirpa; Berner, Margit

2018-02-01

The stature/bi-iliac breadth method provides reasonably precise, skeletal frame size (SFS) based body mass (BM) estimations across adults as a whole. In this study, we examine the potential effects of age changes in anthropometric dimensions on the estimation accuracy of SFS-based body mass estimation. We use anthropometric data from the literature and our own skeletal data from two osteological collections to study effects of age on stature, bi-iliac breadth, body mass, and body composition, as they are major components behind body size and body size estimations. We focus on males, as relevant longitudinal data are based on male study samples. As a general rule, lean body mass (LBM) increases through adolescence and early adulthood until people are aged in their 30s or 40s, and starts to decline in the late 40s or early 50s. Fat mass (FM) tends to increase until the mid-50s and declines thereafter, but in more mobile traditional societies it may decline throughout adult life. Because BM is the sum of LBM and FM, it exhibits a curvilinear age-related pattern in all societies. Skeletal frame size is based on stature and bi-iliac breadth, and both of those dimensions are affected by age. Skeletal frame size based body mass estimation tends to increase throughout adult life in both skeletal and anthropometric samples because an age-related increase in bi-iliac breadth more than compensates for an age-related stature decline commencing in the 30s or 40s. Combined with the above-mentioned curvilinear BM change, this results in curvilinear estimation bias. However, for simulations involving low to moderate percent body fat, the stature/bi-iliac method works well in predicting body mass in younger and middle-aged adults. Such conditions are likely to have applied to most human paleontological and archaeological samples. Copyright © 2017 Elsevier Ltd. All rights reserved.

Risk Factors for Addiction and Their Association with Model-Based Behavioral Control.

PubMed

Reiter, Andrea M F; Deserno, Lorenz; Wilbertz, Tilmann; Heinze, Hans-Jochen; Schlagenhauf, Florian

2016-01-01

Addiction shows familial aggregation and previous endophenotype research suggests that healthy relatives of addicted individuals share altered behavioral and cognitive characteristics with individuals suffering from addiction. In this study we asked whether impairments in behavioral control proposed for addiction, namely a shift from goal-directed, model-based toward habitual, model-free control, extends toward an unaffected sample (n = 20) of adult children of alcohol-dependent fathers as compared to a sample without any personal or family history of alcohol addiction (n = 17). Using a sequential decision-making task designed to investigate model-free and model-based control combined with a computational modeling analysis, we did not find any evidence for altered behavioral control in individuals with a positive family history of alcohol addiction. Independent of family history of alcohol dependence, we however observed that the interaction of two different risk factors of addiction, namely impulsivity and cognitive capacities, predicts the balance of model-free and model-based behavioral control. Post-hoc tests showed a positive association of model-based behavior with cognitive capacity in the lower, but not in the higher impulsive group of the original sample. In an independent sample of particularly high- vs. low-impulsive individuals, we confirmed the interaction effect of cognitive capacities and high vs. low impulsivity on model-based control. In the confirmation sample, a positive association of omega with cognitive capacity was observed in highly impulsive individuals, but not in low impulsive individuals. Due to the moderate sample size of the study, further investigation of the association of risk factors for addiction with model-based behavior in larger sample sizes is warranted.

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.

High-Throughput and Label-Free Single Nanoparticle Sizing Based on Time-Resolved On-Chip Microscopy

DTIC Science & Technology

2015-02-17

12,13 soot ,6,14 ice crystals in clouds,15 and engineered nano- materials,16 among others. While there exist various nanoparticle detection and sizing...the sample of interest is placed on an optoelectronic sensor -array with typically less than 0.5 mm gap (z2) between the sample and sensor planes such...that, under unit mag- nification, the entire sensor active area serves as the imaging FOV, easily reaching >2030 mm2 with state-of-the-art CMOS

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.

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.

Tunable separations based on a molecular size effect for biomolecules by poly(ethylene glycol) gel-based capillary electrophoresis.

PubMed

Kubo, Takuya; Nishimura, Naoki; Furuta, Hayato; Kubota, Kei; Naito, Toyohiro; Otsuka, Koji

2017-11-10

We report novel capillary gel electrophoresis (CGE) with poly(ethylene glycol) (PEG)-based hydrogels for the effective separations of biomolecules containing sugars and DNAs based on a molecular size effect. The gel capillaries were prepared in a fused silica capillary modified with 3-(trimethoxysilyl)propylmethacrylate using a variety of the PEG-based hydrogels. After the fundamental evaluations in CGE regarding the separation based on the molecular size effect depending on the crosslinking density, the optimized capillary provided the efficient separation of glucose ladder (G1 to G20). In addition, another capillary showed the successful separation of DNA ladder in the range of 10-1100 base pair, which is superior to an authentic acrylamide-based gel capillary. For both glucose and DNA ladders, the separation ranges against the molecular size were simply controllable by alteration of the concentration and/or units of ethylene oxide in the PEG-based crosslinker. Finally, we demonstrated the separations of real samples, which included sugars carved out from monoclonal antibodies, mAbs, and then the efficient separations based on the molecular size effect were achieved. Copyright © 2017 Elsevier B.V. All rights reserved.

Assessing relative abundance and reproductive success of shrubsteppe raptors

USGS Publications Warehouse

Lehman, Robert N.; Carpenter, L.B.; Steenhof, Karen; Kochert, Michael N.

1998-01-01

From 1991-1994, we quantified relative abundance and reproductive success of the Ferruginous Hawk (Buteo regalis), Northern Harrier (Circus cyaneus), Burrowing Owl (Speotytoc unicularia), and Short-eared Owl (Asio flammeus) on the shrubsteppe plateaus (benchlands) in and near the Snake River Birds of Prey National Conservation Area in southwestern Idaho. To assess relative abundance, we searched randomly selected plots using four sampling methods: point counts, line transects, and quadrats of two sizes. On a persampling-effort basis, transects were slightly more effective than point counts and quadrats for locating raptor nests (3.4 pairs detected/100 h of effort vs. 2.2-3.1 pairs). Random sampling using quadrats failed to detect a Short-eared Owl population increase from 1993 to 1994. To evaluate nesting success, we tried to determine reproductive outcome for all nesting attempts located during random, historical, and incidental nest searches. We compared nesting success estimates based on all nesting attempts, on attempts found during incubation, and the Mayfield model. Most pairs used to evaluate success were pairs found incidentally. Visits to historical nesting areas yielded the highest number of pairs per sampling effort (14.6/100 h), but reoccupancy rates for most species decreased through time. Estimates based on all attempts had the highest sample sizes but probably overestimated success for all species except the Ferruginous Hawk. Estimates of success based on nesting attempts found during incubation had the lowest sample sizes. All three methods yielded biased nesting snccess estimates for the Northern Harrier and Short-eared Owl. The estimate based on pairs found during incubation probably provided the least biased estimate for the Burrowing Owl. Assessments of nesting success were hindered by difficulties in confirming egg laying and nesting success for all species except the Ferruginous hawk.

Combining gas-phase electrophoretic mobility molecular analysis (GEMMA), light scattering, field flow fractionation and cryo electron microscopy in a multidimensional approach to characterize liposomal carrier vesicles

PubMed Central

Gondikas, Andreas; von der Kammer, Frank; Hofmann, Thilo; Marchetti-Deschmann, Martina; Allmaier, Günter; Marko-Varga, György; Andersson, Roland

2017-01-01

For drug delivery, characterization of liposomes regarding size, particle number concentrations, occurrence of low-sized liposome artefacts and drug encapsulation are of importance to understand their pharmacodynamic properties. In our study, we aimed to demonstrate the applicability of nano Electrospray Gas-Phase Electrophoretic Mobility Molecular Analyser (nES GEMMA) as a suitable technique for analyzing these parameters. We measured number-based particle concentrations, identified differences in size between nominally identical liposomal samples, and detected the presence of low-diameter material which yielded bimodal particle size distributions. Subsequently, we compared these findings to dynamic light scattering (DLS) data and results from light scattering experiments coupled to Asymmetric Flow-Field Flow Fractionation (AF4), the latter improving the detectability of smaller particles in polydisperse samples due to a size separation step prior detection. However, the bimodal size distribution could not be detected due to method inherent limitations. In contrast, cryo transmission electron microscopy corroborated nES GEMMA results. Hence, gas-phase electrophoresis proved to be a versatile tool for liposome characterization as it could analyze both vesicle size and size distribution. Finally, a correlation of nES GEMMA results with cell viability experiments was carried out to demonstrate the importance of liposome batch-to-batch control as low-sized sample components possibly impact cell viability. PMID:27639623

Interval estimation and optimal design for the within-subject coefficient of variation for continuous and binary variables

PubMed Central

Shoukri, Mohamed M; Elkum, Nasser; Walter, Stephen D

2006-01-01

Background In this paper we propose the use of the within-subject coefficient of variation as an index of a measurement's reliability. For continuous variables and based on its maximum likelihood estimation we derive a variance-stabilizing transformation and discuss confidence interval construction within the framework of a one-way random effects model. We investigate sample size requirements for the within-subject coefficient of variation for continuous and binary variables. Methods We investigate the validity of the approximate normal confidence interval by Monte Carlo simulations. In designing a reliability study, a crucial issue is the balance between the number of subjects to be recruited and the number of repeated measurements per subject. We discuss efficiency of estimation and cost considerations for the optimal allocation of the sample resources. The approach is illustrated by an example on Magnetic Resonance Imaging (MRI). We also discuss the issue of sample size estimation for dichotomous responses with two examples. Results For the continuous variable we found that the variance stabilizing transformation improves the asymptotic coverage probabilities on the within-subject coefficient of variation for the continuous variable. The maximum like estimation and sample size estimation based on pre-specified width of confidence interval are novel contribution to the literature for the binary variable. Conclusion Using the sample size formulas, we hope to help clinical epidemiologists and practicing statisticians to efficiently design reliability studies using the within-subject coefficient of variation, whether the variable of interest is continuous or binary. PMID:16686943

Stratum variance estimation for sample allocation in crop surveys. [Great Plains Corridor

NASA Technical Reports Server (NTRS)

Perry, C. R., Jr.; Chhikara, R. S. (Principal Investigator)

1980-01-01

The problem of determining stratum variances needed in achieving an optimum sample allocation for crop surveys by remote sensing is investigated by considering an approach based on the concept of stratum variance as a function of the sampling unit size. A methodology using the existing and easily available information of historical crop statistics is developed for obtaining initial estimates of tratum variances. The procedure is applied to estimate stratum variances for wheat in the U.S. Great Plains and is evaluated based on the numerical results thus obtained. It is shown that the proposed technique is viable and performs satisfactorily, with the use of a conservative value for the field size and the crop statistics from the small political subdivision level, when the estimated stratum variances were compared to those obtained using the LANDSAT data.

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.

Microgravity

NASA Image and Video Library

2004-04-15

Comparison of ground-based (left) and Skylab (right) electron beam welds in pure tantalum (Ta) (10X magnification). Residual votices left behind in the ground-based sample after the electron beam passed were frozen into the grain structure. These occurred because of the rapid cooling rate at the high temperature. Although the thermal characteristics and electron beam travel speeds were comparable for the skylab sample, the residual vortices were erased in the grain structure. This may have been due to the fact that final grain size of the solidified material was smaller in the Skylab sample compared to the ground-based sample. The Skylab sample was processed in the M512 Materials Processing Facility (MPF) during Skylab SL-2 Mission. Principal Investigator was Richard Poorman.

Threshold-dependent sample sizes for selenium assessment with stream fish tissue

USGS Publications Warehouse

Hitt, Nathaniel P.; Smith, David R.

2015-01-01

Natural resource managers are developing assessments of selenium (Se) contamination in freshwater ecosystems based on fish tissue concentrations. We evaluated the effects of sample size (i.e., number of fish per site) on the probability of correctly detecting mean whole-body Se values above a range of potential management thresholds. We modeled Se concentrations as gamma distributions with shape and scale parameters fitting an empirical mean-to-variance relationship in data from southwestern West Virginia, USA (63 collections, 382 individuals). We used parametric bootstrapping techniques to calculate statistical power as the probability of detecting true mean concentrations up to 3 mg Se/kg above management thresholds ranging from 4 to 8 mg Se/kg. Sample sizes required to achieve 80% power varied as a function of management thresholds and Type I error tolerance (α). Higher thresholds required more samples than lower thresholds because populations were more heterogeneous at higher mean Se levels. For instance, to assess a management threshold of 4 mg Se/kg, a sample of eight fish could detect an increase of approximately 1 mg Se/kg with 80% power (given α = 0.05), but this sample size would be unable to detect such an increase from a management threshold of 8 mg Se/kg with more than a coin-flip probability. Increasing α decreased sample size requirements to detect above-threshold mean Se concentrations with 80% power. For instance, at an α-level of 0.05, an 8-fish sample could detect an increase of approximately 2 units above a threshold of 8 mg Se/kg with 80% power, but when α was relaxed to 0.2, this sample size was more sensitive to increasing mean Se concentrations, allowing detection of an increase of approximately 1.2 units with equivalent power. Combining individuals into 2- and 4-fish composite samples for laboratory analysis did not decrease power because the reduced number of laboratory samples was compensated for by increased precision of composites for estimating mean conditions. However, low sample sizes (<5 fish) did not achieve 80% power to detect near-threshold values (i.e., <1 mg Se/kg) under any scenario we evaluated. This analysis can assist the sampling design and interpretation of Se assessments from fish tissue by accounting for natural variation in stream fish populations.

Designing a multiple dependent state sampling plan based on the coefficient of variation.

PubMed

Yan, Aijun; Liu, Sanyang; Dong, Xiaojuan

2016-01-01

A multiple dependent state (MDS) sampling plan is developed based on the coefficient of variation of the quality characteristic which follows a normal distribution with unknown mean and variance. The optimal plan parameters of the proposed plan are solved by a nonlinear optimization model, which satisfies the given producer's risk and consumer's risk at the same time and minimizes the sample size required for inspection. The advantages of the proposed MDS sampling plan over the existing single sampling plan are discussed. Finally an example is given to illustrate the proposed plan.

Developing effective sampling designs for monitoring natural resources in Alaskan national parks: an example using simulations and vegetation data

USGS Publications Warehouse

Thompson, William L.; Miller, Amy E.; Mortenson, Dorothy C.; Woodward, Andrea

2011-01-01

Monitoring natural resources in Alaskan national parks is challenging because of their remoteness, limited accessibility, and high sampling costs. We describe an iterative, three-phased process for developing sampling designs based on our efforts to establish a vegetation monitoring program in southwest Alaska. In the first phase, we defined a sampling frame based on land ownership and specific vegetated habitats within the park boundaries and used Path Distance analysis tools to create a GIS layer that delineated portions of each park that could be feasibly accessed for ground sampling. In the second phase, we used simulations based on landcover maps to identify size and configuration of the ground sampling units (single plots or grids of plots) and to refine areas to be potentially sampled. In the third phase, we used a second set of simulations to estimate sample size and sampling frequency required to have a reasonable chance of detecting a minimum trend in vegetation cover for a specified time period and level of statistical confidence. Results of the first set of simulations indicated that a spatially balanced random sample of single plots from the most common landcover types yielded the most efficient sampling scheme. Results of the second set of simulations were compared with field data and indicated that we should be able to detect at least a 25% change in vegetation attributes over 31. years by sampling 8 or more plots per year every five years in focal landcover types. This approach would be especially useful in situations where ground sampling is restricted by access.

Lithologic, natural-gamma, grain-size, and well-construction data for Wright-Patterson Air Force Base, Ohio

USGS Publications Warehouse

Dumouchelle, D.H.; De Roche, Jeffrey T.

1991-01-01

Wright-Patterson Air Force Base, in southwestern Ohio, overlies a buried-valley aquifer. The U.S. Geological Survey installed 35 observation wells at 13 sites on the base from fall 1988 through spring 1990. Fourteen of the wells were completed in bedrock; the remaining wells were completed in unconsolidated sediments. Split-spoon and bedrock cores were collected from all of the bedrock wells. Shelby-tube samples were collected from four wells. The wells were drilled by either the cable-tool or rotary method. Data presented in this report include lithologic and natural-gamma logs, and, for selected sediment samples, grain-size distributions of permeability. Final well-construction details, such as the total depth of well, screened interval, and grouting details, also are presented.

Fossil shrews from Honduras and their significance for late glacial evolution in body size (Mammalia: Soricidae: Cryptotis)

USGS Publications Warehouse

Woodman, N.; Croft, D.A.

2005-01-01

Our study of mammalian remains excavated in the 1940s from McGrew Cave, north of Copan, Honduras, yielded an assemblage of 29 taxa that probably accumulated predominantly as the result of predation by owls. Among the taxa present are three species of small-eared shrews, genus Cryptotis. One species, Cryptotis merriami, is relatively rare among the fossil remains. The other two shrews, Cryptotis goodwini and Cryptotis orophila, are abundant and exhibit morpho metrical variation distinguishing them from modern populations. Fossils of C. goodwini are distinctly and consistently smaller than modern members of the species. To quantify the size differences, we derived common measures of body size for fossil C. goodwini using regression models based on modern samples of shrews in the Cryptotis mexicana-group. Estimated mean length of head and body for the fossil sample is 72-79 mm, and estimated mean mass is 7.6-9.6 g. These numbers indicate that the fossil sample averaged 6-14% smaller in head and body length and 39-52% less in mass than the modern sample and that increases of 6-17% in head and body length and 65-108% in mass occurred to achieve the mean body size of the modern sample. Conservative estimates of fresh (wet) food intake based on mass indicate that such a size increase would require a 37-58% increase in daily food consumption. In contrast to C. goodwini, fossil C. orophila from the cave is not different in mean body size from modern samples. The fossil sample does, however, show slightly greater variation in size than is currently present throughout the modern geographical distribution of the taxon. Moreover, variation in some other dental and mandibular characters is more constrained, exhibiting a more direct relationship to overall size. Our study of these species indicates that North American shrews have not all been static in size through time, as suggested by some previous work with fossil soricids. Lack of stratigraphic control within the site and our failure to obtain reliable radiometric dates on remains restrict our opportunities to place the site in a firm temporal context. However, the morphometrical differences we document for fossil C. orophila and C. goodwini show them to be distinct from modern populations of these shrews. Some other species of fossil mammals from McGrew Cave exhibit distinct size changes of the magnitudes experienced by many northern North American and some Mexican mammals during the transition from late glacial to Holocene environmental conditions, and it is likely that at least some of the remains from the cave are late Pleistocene in age. One curious factor is that, whereas most mainland mammals that exhibit large-scale size shifts during the late glacial/postglacial transition experienced dwarfing, C. goodwini increased in size. The lack of clinal variation in modern C. goodwini supports the hypothesis that size evolution can result from local selection rather than from cline translocation. Models of size change in mammals indicate that increased size, such as that observed for C. goodwini, are a likely consequence of increased availability of resources and, thereby, a relaxation of selection during critical times of the year.

Bed-sediment grain-size and morphologic data from Suisun, Grizzly, and Honker Bays, CA, 1998-2002

USGS Publications Warehouse

Hampton, Margaret A.; Snyder, Noah P.; Chin, John L.; Allison, Dan W.; Rubin, David M.

2003-01-01

The USGS Place Based Studies Program for San Francisco Bay investigates this sensitive estuarine system to aid in resource management. As part of the inter-disciplinary research program, the USGS collected side-scan sonar data and bed-sediment samples from north San Francisco Bay to characterize bed-sediment texture and investigate temporal trends in sedimentation. The study area is located in central California and consists of Suisun Bay, and Grizzly and Honker Bays, sub-embayments of Suisun Bay. During the study (1998-2002), the USGS collected three side-scan sonar data sets and approximately 300 sediment samples. The side-scan data revealed predominantly fine-grained material on the bayfloor. We also mapped five different bottom types from the data set, categorized as featureless, furrows, sand waves, machine-made, and miscellaneous. We performed detailed grain-size and statistical analyses on the sediment samples. Overall, we found that grain size ranged from clay to fine sand, with the coarsest material in the channels and finer material located in the shallow bays. Grain-size analyses revealed high spatial variability in size distributions in the channel areas. In contrast, the shallow regions exhibited low spatial variability and consistent sediment size over time.

Size-segregated compositional analysis of aerosol particles collected in the European Arctic during the ACCACIA campaign

NASA Astrophysics Data System (ADS)

Young, G.; Jones, H. M.; Darbyshire, E.; Baustian, K. J.; McQuaid, J. B.; Bower, K. N.; Connolly, P. J.; Gallagher, M. W.; Choularton, T. W.

2016-03-01

Single-particle compositional analysis of filter samples collected on board the Facility for Airborne Atmospheric Measurements (FAAM) BAe-146 aircraft is presented for six flights during the springtime Aerosol-Cloud Coupling and Climate Interactions in the Arctic (ACCACIA) campaign (March-April 2013). Scanning electron microscopy was utilised to derive size-segregated particle compositions and size distributions, and these were compared to corresponding data from wing-mounted optical particle counters. Reasonable agreement between the calculated number size distributions was found. Significant variability in composition was observed, with differing external and internal mixing identified, between air mass trajectory cases based on HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) analyses. Dominant particle classes were silicate-based dusts and sea salts, with particles notably rich in K and Ca detected in one case. Source regions varied from the Arctic Ocean and Greenland through to northern Russia and the European continent. Good agreement between the back trajectories was mirrored by comparable compositional trends between samples. Silicate dusts were identified in all cases, and the elemental composition of the dust was consistent for all samples except one. It is hypothesised that long-range, high-altitude transport was primarily responsible for this dust, with likely sources including the Asian arid regions.

Estimating population size for Capercaillie (Tetrao urogallus L.) with spatial capture-recapture models based on genotypes from one field sample

USGS Publications Warehouse

Mollet, Pierre; Kery, Marc; Gardner, Beth; Pasinelli, Gilberto; Royle, Andy

2015-01-01

We conducted a survey of an endangered and cryptic forest grouse, the capercaillie Tetrao urogallus, based on droppings collected on two sampling occasions in eight forest fragments in central Switzerland in early spring 2009. We used genetic analyses to sex and individually identify birds. We estimated sex-dependent detection probabilities and population size using a modern spatial capture-recapture (SCR) model for the data from pooled surveys. A total of 127 capercaillie genotypes were identified (77 males, 46 females, and 4 of unknown sex). The SCR model yielded atotal population size estimate (posterior mean) of 137.3 capercaillies (posterior sd 4.2, 95% CRI 130–147). The observed sex ratio was skewed towards males (0.63). The posterior mean of the sex ratio under the SCR model was 0.58 (posterior sd 0.02, 95% CRI 0.54–0.61), suggesting a male-biased sex ratio in our study area. A subsampling simulation study indicated that a reduced sampling effort representing 75% of the actual detections would still yield practically acceptable estimates of total size and sex ratio in our population. Hence, field work and financial effort could be reduced without compromising accuracy when the SCR model is used to estimate key population parameters of cryptic species.

US EPA BASE Study Standard Operating Procedure for Sampling of Particulates

EPA Pesticide Factsheets

The objective of the procedure described is to collect a sample of particles of respirable and inhalable size (approx. 0.1 to 10 microns in diameter) from indoor air and from the outdoor air supplied to the indoor space tested.

Vitamin D receptor gene and osteoporosis - author`s response

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

Looney, J.E.; Yoon, Hyun Koo; Fischer, M.

1996-04-01

We appreciate the comments of Dr. Nguyen et al. about our recent study, but we disagree with their suggestion that the lack of an association between low bone density and the BB VDR genotype, which we reported, is an artifact generated by the small sample size. Furthermore, our results are consistent with similar conclusions reached by a number of other investigators, as recently reported by Peacock. Peacock states {open_quotes}Taken as a whole, the results of studies outlined ... indicate that VDR alleles, cannot account for the major part of the heritable component of bone density as indicated by Morrison etmore » al.{close_quotes}. The majority of the 17 studies cited in this editorial could not confirm an association between the VDR genotype and the bone phenotype. Surely one cannot criticize this combined work as representing an artifact because of a too small sample size. We do not dispute the suggestion by Nguyen et al. that large sample sizes are required to analyze small biological effects. This is evident in both Peacock`s summary and in their own bone density studies. We did not design our study with a larger sample size because, based on the work of Morrison et al., we had hypothesized a large biological effect; large sample sizes are only needed for small biological effects. 4 refs.« less

On the repeated measures designs and sample sizes for randomized controlled trials.

PubMed

Tango, Toshiro

2016-04-01

For the analysis of longitudinal or repeated measures data, generalized linear mixed-effects models provide a flexible and powerful tool to deal with heterogeneity among subject response profiles. However, the typical statistical design adopted in usual randomized controlled trials is an analysis of covariance type analysis using a pre-defined pair of "pre-post" data, in which pre-(baseline) data are used as a covariate for adjustment together with other covariates. Then, the major design issue is to calculate the sample size or the number of subjects allocated to each treatment group. In this paper, we propose a new repeated measures design and sample size calculations combined with generalized linear mixed-effects models that depend not only on the number of subjects but on the number of repeated measures before and after randomization per subject used for the analysis. The main advantages of the proposed design combined with the generalized linear mixed-effects models are (1) it can easily handle missing data by applying the likelihood-based ignorable analyses under the missing at random assumption and (2) it may lead to a reduction in sample size, compared with the simple pre-post design. The proposed designs and the sample size calculations are illustrated with real data arising from randomized controlled trials. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Synthesis, structural, optical and morphological characterization of hematite through the precipitation method: Effect of varying the nature of the base

NASA Astrophysics Data System (ADS)

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

2017-08-01

Iron oxide (α-Fe2O3) nanoparticles were synthesized using the precipitation synthesis method focusing only on (FeCl3, 6H2O), NaOH, KOH and NH4OH as raw materials. The impact of varying the nature of the base on the crystalline phase, size and morphology of α-Fe2O3 products was explored. XRD spectra revealed that samples crystallize in the rhombohedral (hexagonal) system at 800 °C.The Transmission Electron Microscopy (TEM) and Scanning Electron Microscopy (SEM) were used to detect the morphology of synthesized nanoparticles and specify their sizes. However, the Fourier Transform Infra-Red (FT-IR) spectroscopy has permitted the observation of vibration band Fe-O. Raman spectroscopy was used not only to prove that we have synthesized hematite but also to identify their phonon modes. The Thermo Gravimetric Analysis (TGA) findings allow the thermal cycle determination of samples whereas Differential Thermal Analysis (DTA) findings allow the phase transition temperature identification. Besides, the optical investigation revealed that samples have an optical gap of about 2.1 eV. Findings highlight that the nature of the agent precipitant plays a significant role in the morphology of the products and the formation of the crystalline phase. Hematite synthesis with the base NH4OH brought about much stronger, sharper and wider diffraction peaks of α-Fe2O3. The morphology of samples are spherical with a size of about 61 nm while the size of the nanoparticles of hematite which we have synthesized with NaOH and KOH is respectively of the order of 82 and 79 nm.

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.

Particle size distribution of distillers dried grains with solubles (DDGS) and relationships to compositional and color properties.

PubMed

Liu, Keshun

2008-11-01

Eleven distillers dried grains with solubles (DDGS), processed from yellow corn, were collected from different ethanol processing plants in the US Midwest area. Particle size distribution (PSD) by mass of each sample was determined using a series of six selected US standard sieves: Nos. 8, 12, 18, 35, 60, and 100, and a pan. The original sample and sieve sized fractions were measured for surface color and contents of moisture, protein, oil, ash, and starch. Total carbohydrate (CHO) and total non-starch CHO were also calculated. Results show that there was a great variation in composition and color among DDGS from different plants. Surprisingly, a few DDGS samples contained unusually high amounts of residual starch (11.1-17.6%, dry matter basis, vs. about 5% of the rest), presumably resulting from modified processing methods. Particle size of DDGS varied greatly within a sample and PSD varied greatly among samples. The 11 samples had a mean value of 0.660mm for the geometric mean diameter (dgw) of particles and a mean value of 0.440mm for the geometric standard deviation (Sgw) of particle diameters by mass. The majority had a unimodal PSD, with a mode in the size class between 0.5 and 1.0mm. Although PSD and color parameters had little correlation with composition of whole DDGS samples, distribution of nutrients as well as color attributes correlated well with PSD. In sieved fractions, protein content, L and a color values negatively while contents of oil and total CHO positively correlated with particle size. It is highly feasible to fractionate DDGS for compositional enrichment based on particle size, while the extent of PSD can serve as an index for potential of DDGS fractionation. The above information should be a vital addition to quality and baseline data of DDGS.

Random forests ensemble classifier trained with data resampling strategy to improve cardiac arrhythmia diagnosis.

PubMed

Ozçift, Akin

2011-05-01

Supervised classification algorithms are commonly used in the designing of computer-aided diagnosis systems. In this study, we present a resampling strategy based Random Forests (RF) ensemble classifier to improve diagnosis of cardiac arrhythmia. Random forests is an ensemble classifier that consists of many decision trees and outputs the class that is the mode of the class's output by individual trees. In this way, an RF ensemble classifier performs better than a single tree from classification performance point of view. In general, multiclass datasets having unbalanced distribution of sample sizes are difficult to analyze in terms of class discrimination. Cardiac arrhythmia is such a dataset that has multiple classes with small sample sizes and it is therefore adequate to test our resampling based training strategy. The dataset contains 452 samples in fourteen types of arrhythmias and eleven of these classes have sample sizes less than 15. Our diagnosis strategy consists of two parts: (i) a correlation based feature selection algorithm is used to select relevant features from cardiac arrhythmia dataset. (ii) RF machine learning algorithm is used to evaluate the performance of selected features with and without simple random sampling to evaluate the efficiency of proposed training strategy. The resultant accuracy of the classifier is found to be 90.0% and this is a quite high diagnosis performance for cardiac arrhythmia. Furthermore, three case studies, i.e., thyroid, cardiotocography and audiology, are used to benchmark the effectiveness of the proposed method. The results of experiments demonstrated the efficiency of random sampling strategy in training RF ensemble classification algorithm. Copyright © 2011 Elsevier Ltd. All rights reserved.

Can mindfulness-based interventions influence cognitive functioning in older adults? A review and considerations for future research.

PubMed

Berk, Lotte; van Boxtel, Martin; van Os, Jim

2017-11-01

An increased need exists to examine factors that protect against age-related cognitive decline. There is preliminary evidence that meditation can improve cognitive function. However, most studies are cross-sectional and examine a wide variety of meditation techniques. This review focuses on the standard eight-week mindfulness-based interventions (MBIs) such as mindfulness-based stress reduction (MBSR) and mindfulness-based cognitive therapy (MBCT). We searched the PsychINFO, CINAHL, Web of Science, COCHRANE, and PubMed databases to identify original studies investigating the effects of MBI on cognition in older adults. Six reports were included in the review of which three were randomized controlled trials. Studies reported preliminary positive effects on memory, executive function and processing speed. However, most reports had a high risk of bias and sample sizes were small. The only study with low risk of bias, large sample size and active control group reported no significant findings. We conclude that eight-week MBI for older adults are feasible, but results on cognitive improvement are inconclusive due a limited number of studies, small sample sizes, and a high risk of bias. Rather than a narrow focus on cognitive training per se, future research may productively shift to investigate MBI as a tool to alleviate suffering in older adults, and to prevent cognitive problems in later life already in younger target populations.

Atomically precise (catalytic) particles synthesized by a novel cluster deposition instrument

DOE PAGES

Yin, C.; Tyo, E.; Kuchta, K.; ...

2014-05-06

Here, we report a new high vacuum instrument which is dedicated to the preparation of well-defined clusters supported on model and technologically relevant supports for catalytic and materials investigations. The instrument is based on deposition of size selected metallic cluster ions that are produced by a high flux magnetron cluster source. Furthermore, we maximize the throughput of the apparatus by collecting and focusing ions utilizing a conical octupole ion guide and a linear ion guide. The size selection is achieved by a quadrupole mass filter. The new design of the sample holder provides for the preparation of multiple samples onmore » supports of various sizes and shapes in one session. After cluster deposition onto the support of interest, samples will be taken out of the chamber for a variety of testing and characterization.« less

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.

Composition and Morphology of Major Particle Types from Airborne Measurements during ICE-T and PRADACS Field Studies

NASA Astrophysics Data System (ADS)

Venero, I. M.; Mayol-Bracero, O. L.; Anderson, J. R.

2012-12-01

As part of the Puerto Rican African Dust and Cloud Study (PRADACS) and the Ice in Clouds Experiment - Tropical (ICE-T), we sampled giant airborne particles to study their elemental composition, morphology, and size distributions. Samples were collected in July 2011 during field measurements performed by NCAR's C-130 aircraft based on St Croix, U.S Virgin Island. The results presented here correspond to the measurements done during research flight #8 (RF8). Aerosol particles with Dp > 1 um were sampled with the Giant Nuclei Impactor and particles with Dp < 1 um were collected with the Wyoming Inlet. Collected particles were later analyzed using an automated scanning electron microscope (SEM) and manual observation by field emission SEM. We identified the chemical composition and morphology of major particle types in filter samples collected at different altitudes (e.g., 300 ft, 1000 ft, and 4500ft). Results from the flight upwind of Puerto Rico show that particles in the giant nuclei size range are dominated by sea salt. Samples collected at altitudes 300 ft and 1000 ft showed the highest number of sea salt particles and the samples collected at higher altitudes (> 4000 ft) showed the highest concentrations of clay material. HYSPLIT back trajectories for all samples showed that the low altitude samples initiated in the free troposphere in the Atlantic Ocean, which may account for the high sea salt content and that the source of the high altitude samples was closer to the Saharan - Sahel desert region and, therefore, these samples possibly had the influence of African dust. Size distribution results for quartz and unreacted sea-salt aerosols collected on the Giant Nuclei Impactor showed that sample RF08 - 12:05 UTM (300 ft) had the largest size value (mean = 2.936 μm) than all the other samples. Additional information was also obtained from the Wyoming Inlet present at the C - 130 aircraft which showed that size distribution results for all particles were smaller in size. The different mineral components of the dust have different size distributions so that a fractionation process could occur during transport. Also, the presence of supermicron sea salt at altitude is important for cloud processes.

Selecting the optimum plot size for a California design-based stream and wetland mapping program.

PubMed

Lackey, Leila G; Stein, Eric D

2014-04-01

Accurate estimates of the extent and distribution of wetlands and streams are the foundation of wetland monitoring, management, restoration, and regulatory programs. Traditionally, these estimates have relied on comprehensive mapping. However, this approach is prohibitively resource-intensive over large areas, making it both impractical and statistically unreliable. Probabilistic (design-based) approaches to evaluating status and trends provide a more cost-effective alternative because, compared with comprehensive mapping, overall extent is inferred from mapping a statistically representative, randomly selected subset of the target area. In this type of design, the size of sample plots has a significant impact on program costs and on statistical precision and accuracy; however, no consensus exists on the appropriate plot size for remote monitoring of stream and wetland extent. This study utilized simulated sampling to assess the performance of four plot sizes (1, 4, 9, and 16 km(2)) for three geographic regions of California. Simulation results showed smaller plot sizes (1 and 4 km(2)) were most efficient for achieving desired levels of statistical accuracy and precision. However, larger plot sizes were more likely to contain rare and spatially limited wetland subtypes. Balancing these considerations led to selection of 4 km(2) for the California status and trends program.

Strain Amount Dependent Grain Size and Orientation Developments during Hot Compression of a Polycrystalline Nickel Based Superalloy

PubMed Central

He, Guoai; Tan, Liming; Liu, Feng; Huang, Lan; Huang, Zaiwang; Jiang, Liang

2017-01-01

Controlling grain size in polycrystalline nickel base superalloy is vital for obtaining required mechanical properties. Typically, a uniform and fine grain size is required throughout forging process to realize the superplastic deformation. Strain amount occupied a dominant position in manipulating the dynamic recrystallization (DRX) process and regulating the grain size of the alloy during hot forging. In this article, the high-throughput double cone specimen was introduced to yield wide-range strain in a single sample. Continuous variations of effective strain ranging from 0.23 to 1.65 across the whole sample were achieved after reaching a height reduction of 70%. Grain size is measured to be decreased from the edge to the center of specimen with increase of effective strain. Small misorientation tended to generate near the grain boundaries, which was manifested as piled-up dislocation in micromechanics. After the dislocation density reached a critical value, DRX progress would be initiated at higher deformation region, leading to the refinement of grain size. During this process, the transformations from low angle grain boundaries (LAGBs) to high angle grain boundaries (HAGBs) and from subgrains to DRX grains are found to occur. After the accomplishment of DRX progress, the neonatal grains are presented as having similar orientation inside the grain boundary. PMID:28772514

Application of binomial and multinomial probability statistics to the sampling design process of a global grain tracing and recall system

USDA-ARS?s Scientific Manuscript database

Small, coded, pill-sized tracers embedded in grain are proposed as a method for grain traceability. A sampling process for a grain traceability system was designed and investigated by applying probability statistics using a science-based sampling approach to collect an adequate number of tracers fo...

A size-dependent constitutive model of bulk metallic glasses in the supercooled liquid region

PubMed Central

Yao, Di; Deng, Lei; Zhang, Mao; Wang, Xinyun; Tang, Na; Li, Jianjun

2015-01-01

Size effect is of great importance in micro forming processes. In this paper, micro cylinder compression was conducted to investigate the deformation behavior of bulk metallic glasses (BMGs) in supercooled liquid region with different deformation variables including sample size, temperature and strain rate. It was found that the elastic and plastic behaviors of BMGs have a strong dependence on the sample size. The free volume and defect concentration were introduced to explain the size effect. In order to demonstrate the influence of deformation variables on steady stress, elastic modulus and overshoot phenomenon, four size-dependent factors were proposed to construct a size-dependent constitutive model based on the Maxwell-pulse type model previously presented by the authors according to viscosity theory and free volume model. The proposed constitutive model was then adopted in finite element method simulations, and validated by comparing the micro cylinder compression and micro double cup extrusion experimental data with the numerical results. Furthermore, the model provides a new approach to understanding the size-dependent plastic deformation behavior of BMGs. PMID:25626690

A Feedfordward Adaptive Controller to Reduce the Imaging Time of Large-Sized Biological Samples with a SPM-Based Multiprobe Station

PubMed Central

Otero, Jorge; Guerrero, Hector; Gonzalez, Laura; Puig-Vidal, Manel

2012-01-01

The time required to image large samples is an important limiting factor in SPM-based systems. In multiprobe setups, especially when working with biological samples, this drawback can make impossible to conduct certain experiments. In this work, we present a feedfordward controller based on bang-bang and adaptive controls. The controls are based in the difference between the maximum speeds that can be used for imaging depending on the flatness of the sample zone. Topographic images of Escherichia coli bacteria samples were acquired using the implemented controllers. Results show that to go faster in the flat zones, rather than using a constant scanning speed for the whole image, speeds up the imaging process of large samples by up to a 4× factor. PMID:22368491

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%.

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.

Radar volume reflectivity estimation using an array of ground-based rainfall drop size detectors

NASA Astrophysics Data System (ADS)

Lane, John; Merceret, Francis; Kasparis, Takis; Roy, D.; Muller, Brad; Jones, W. Linwood

2000-08-01

Rainfall drop size distribution (DSD) measurements made by single disdrometers at isolated ground sites have traditionally been used to estimate the transformation between weather radar reflectivity Z and rainfall rate R. Despite the immense disparity in sampling geometries, the resulting Z-R relation obtained by these single point measurements has historically been important in the study of applied radar meteorology. Simultaneous DSD measurements made at several ground sites within a microscale area may be used to improve the estimate of radar reflectivity in the air volume surrounding the disdrometer array. By applying the equations of motion for non-interacting hydrometers, a volume estimate of Z is obtained from the array of ground based disdrometers by first calculating a 3D drop size distribution. The 3D-DSD model assumes that only gravity and terminal velocity due to atmospheric drag within the sampling volume influence hydrometer dynamics. The sampling volume is characterized by wind velocities, which are input parameters to the 3D-DSD model, composed of vertical and horizontal components. Reflectivity data from four consecutive WSR-88D volume scans, acquired during a thunderstorm near Melbourne, FL on June 1, 1997, are compared to data processed using the 3D-DSD model and data form three ground based disdrometers of a microscale array.

A review of accuracy assessment for object-based image analysis: From per-pixel to per-polygon approaches

NASA Astrophysics Data System (ADS)

Ye, Su; Pontius, Robert Gilmore; Rakshit, Rahul

2018-07-01

Object-based image analysis (OBIA) has gained widespread popularity for creating maps from remotely sensed data. Researchers routinely claim that OBIA procedures outperform pixel-based procedures; however, it is not immediately obvious how to evaluate the degree to which an OBIA map compares to reference information in a manner that accounts for the fact that the OBIA map consists of objects that vary in size and shape. Our study reviews 209 journal articles concerning OBIA published between 2003 and 2017. We focus on the three stages of accuracy assessment: (1) sampling design, (2) response design and (3) accuracy analysis. First, we report the literature's overall characteristics concerning OBIA accuracy assessment. Simple random sampling was the most used method among probability sampling strategies, slightly more than stratified sampling. Office interpreted remotely sensed data was the dominant reference source. The literature reported accuracies ranging from 42% to 96%, with an average of 85%. A third of the articles failed to give sufficient information concerning accuracy methodology such as sampling scheme and sample size. We found few studies that focused specifically on the accuracy of the segmentation. Second, we identify a recent increase of OBIA articles in using per-polygon approaches compared to per-pixel approaches for accuracy assessment. We clarify the impacts of the per-pixel versus the per-polygon approaches respectively on sampling, response design and accuracy analysis. Our review defines the technical and methodological needs in the current per-polygon approaches, such as polygon-based sampling, analysis of mixed polygons, matching of mapped with reference polygons and assessment of segmentation accuracy. Our review summarizes and discusses the current issues in object-based accuracy assessment to provide guidance for improved accuracy assessments for OBIA.

Application-Specific Graph Sampling for Frequent Subgraph Mining and Community Detection

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

Purohit, Sumit; Choudhury, Sutanay; Holder, Lawrence B.

Graph mining is an important data analysis methodology, but struggles as the input graph size increases. The scalability and usability challenges posed by such large graphs make it imperative to sample the input graph and reduce its size. The critical challenge in sampling is to identify the appropriate algorithm to insure the resulting analysis does not suffer heavily from the data reduction. Predicting the expected performance degradation for a given graph and sampling algorithm is also useful. In this paper, we present different sampling approaches for graph mining applications such as Frequent Subgrpah Mining (FSM), and Community Detection (CD). Wemore » explore graph metrics such as PageRank, Triangles, and Diversity to sample a graph and conclude that for heterogeneous graphs Triangles and Diversity perform better than degree based metrics. We also present two new sampling variations for targeted graph mining applications. We present empirical results to show that knowledge of the target application, along with input graph properties can be used to select the best sampling algorithm. We also conclude that performance degradation is an abrupt, rather than gradual phenomena, as the sample size decreases. We present the empirical results to show that the performance degradation follows a logistic function.« less

Fluorescence-Activated Cell Sorting of Live Versus Dead Bacterial Cells and Spores

NASA Technical Reports Server (NTRS)

Bernardini, James N.; LaDuc, Myron T.; Diamond, Rochelle; Verceles, Josh

2012-01-01

This innovation is a coupled fluorescence-activated cell sorting (FACS) and fluorescent staining technology for purifying (removing cells from sampling matrices), separating (based on size, density, morphology, and live versus dead), and concentrating cells (spores, prokaryotic, eukaryotic) from an environmental sample.

Comparative study of soft thermal printing and lamination of dry thick photoresist films for the uniform fabrication of polymer MOEMS on small-sized samples

NASA Astrophysics Data System (ADS)

Abada, S.; Salvi, L.; Courson, R.; Daran, E.; Reig, B.; Doucet, J. B.; Camps, T.; Bardinal, V.

2017-05-01

A method called ‘soft thermal printing’ (STP) was developed to ensure the optimal transfer of 50 µm-thick dry epoxy resist films (DF-1050) on small-sized samples. The aim was the uniform fabrication of high aspect ratio polymer-based MOEMS (micro-optical-electrical-mechanical system) on small and/or fragile samples, such as GaAs. The printing conditions were optimized, and the resulting thickness uniformity profiles were compared to those obtained via lamination and SU-8 standard spin-coating. Under the best conditions tested, STP and lamination produced similar results, with a maximum deviation to the central thickness of 3% along the sample surface, compared to greater than 40% for SU-8 spin-coating. Both methods were successfully applied to the collective fabrication of DF1050-based MOEMS designed for the dynamic focusing of VCSELs (vertical-cavity surface-emitting lasers). Similar, efficient electro-thermo-mechanical behaviour was obtained in both cases.

Colorimetric detection of trace copper ions based on catalytic leaching of silver-coated gold nanoparticles.

PubMed

Lou, Tingting; Chen, Lingxin; Chen, Zhaopeng; Wang, Yunqing; Chen, Ling; Li, Jinhua

2011-11-01

A colorimetric, label-free, and nonaggregation-based silver coated gold nanoparticles (Ag/Au NPs) probe has been developed for detection of trace Cu(2+) in aqueous solution, based on the fact that Cu(2+) can accelerate the leaching rate of Ag/Au NPs by thiosulfate (S(2)O(3)(2-)). The leaching of Ag/Au NPs would lead to dramatic decrease in the surface plasmon resonance (SPR) absorption as the size of Ag/Au NPs decreased. This colorimetric strategy based on size-dependence of nanoparticles during their leaching process provided a highly sensitive (1.0 nM) and selective detection toward Cu(2+), with a wide linear detection range (5-800 nM) over nearly 3 orders of magnitude. The cost-effective probe allows rapid and sensitive detection of trace Cu(2+) ions in water samples, indicating its potential applicability for the determination of copper in real samples.

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".

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).

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.

Estimating sample size for landscape-scale mark-recapture studies of North American migratory tree bats

USGS Publications Warehouse

Ellison, Laura E.; Lukacs, Paul M.

2014-01-01

Concern for migratory tree-roosting bats in North America has grown because of possible population declines from wind energy development. This concern has driven interest in estimating population-level changes. Mark-recapture methodology is one possible analytical framework for assessing bat population changes, but sample size requirements to produce reliable estimates have not been estimated. To illustrate the sample sizes necessary for a mark-recapture-based monitoring program we conducted power analyses using a statistical model that allows reencounters of live and dead marked individuals. We ran 1,000 simulations for each of five broad sample size categories in a Burnham joint model, and then compared the proportion of simulations in which 95% confidence intervals overlapped between and among years for a 4-year study. Additionally, we conducted sensitivity analyses of sample size to various capture probabilities and recovery probabilities. More than 50,000 individuals per year would need to be captured and released to accurately determine 10% and 15% declines in annual survival. To detect more dramatic declines of 33% or 50% survival over four years, then sample sizes of 25,000 or 10,000 per year, respectively, would be sufficient. Sensitivity analyses reveal that increasing recovery of dead marked individuals may be more valuable than increasing capture probability of marked individuals. Because of the extraordinary effort that would be required, we advise caution should such a mark-recapture effort be initiated because of the difficulty in attaining reliable estimates. We make recommendations for what techniques show the most promise for mark-recapture studies of bats because some techniques violate the assumptions of mark-recapture methodology when used to mark bats.

Statistical considerations in evaluating pharmacogenomics-based clinical effect for confirmatory trials.

PubMed

Wang, Sue-Jane; O'Neill, Robert T; Hung, Hm James

2010-10-01

The current practice for seeking genomically favorable patients in randomized controlled clinical trials using genomic convenience samples. To discuss the extent of imbalance, confounding, bias, design efficiency loss, type I error, and type II error that can occur in the evaluation of the convenience samples, particularly when they are small samples. To articulate statistical considerations for a reasonable sample size to minimize the chance of imbalance, and, to highlight the importance of replicating the subgroup finding in independent studies. Four case examples reflecting recent regulatory experiences are used to underscore the problems with convenience samples. Probability of imbalance for a pre-specified subgroup is provided to elucidate sample size needed to minimize the chance of imbalance. We use an example drug development to highlight the level of scientific rigor needed, with evidence replicated for a pre-specified subgroup claim. The convenience samples evaluated ranged from 18% to 38% of the intent-to-treat samples with sample size ranging from 100 to 5000 patients per arm. The baseline imbalance can occur with probability higher than 25%. Mild to moderate multiple confounders yielding the same directional bias in favor of the treated group can make treatment group incomparable at baseline and result in a false positive conclusion that there is a treatment difference. Conversely, if the same directional bias favors the placebo group or there is loss in design efficiency, the type II error can increase substantially. Pre-specification of a genomic subgroup hypothesis is useful only for some degree of type I error control. Complete ascertainment of genomic samples in a randomized controlled trial should be the first step to explore if a favorable genomic patient subgroup suggests a treatment effect when there is no clear prior knowledge and understanding about how the mechanism of a drug target affects the clinical outcome of interest. When stratified randomization based on genomic biomarker status cannot be implemented in designing a pharmacogenomics confirmatory clinical trial, if there is one genomic biomarker prognostic for clinical response, as a general rule of thumb, a sample size of at least 100 patients may be needed to be considered for the lower prevalence genomic subgroup to minimize the chance of an imbalance of 20% or more difference in the prevalence of the genomic marker. The sample size may need to be at least 150, 350, and 1350, respectively, if an imbalance of 15%, 10% and 5% difference is of concern.

High frequency mesozooplankton monitoring: Can imaging systems and automated sample analysis help us describe and interpret changes in zooplankton community composition and size structure — An example from a coastal site

NASA Astrophysics Data System (ADS)

Romagnan, Jean Baptiste; Aldamman, Lama; Gasparini, Stéphane; Nival, Paul; Aubert, Anaïs; Jamet, Jean Louis; Stemmann, Lars

2016-10-01

The present work aims to show that high throughput imaging systems can be useful to estimate mesozooplankton community size and taxonomic descriptors that can be the base for consistent large scale monitoring of plankton communities. Such monitoring is required by the European Marine Strategy Framework Directive (MSFD) in order to ensure the Good Environmental Status (GES) of European coastal and offshore marine ecosystems. Time and cost-effective, automatic, techniques are of high interest in this context. An imaging-based protocol has been applied to a high frequency time series (every second day between April 2003 to April 2004 on average) of zooplankton obtained in a coastal site of the NW Mediterranean Sea, Villefranche Bay. One hundred eighty four mesozooplankton net collected samples were analysed with a Zooscan and an associated semi-automatic classification technique. The constitution of a learning set designed to maximize copepod identification with more than 10,000 objects enabled the automatic sorting of copepods with an accuracy of 91% (true positives) and a contamination of 14% (false positives). Twenty seven samples were then chosen from the total copepod time series for detailed visual sorting of copepods after automatic identification. This method enabled the description of the dynamics of two well-known copepod species, Centropages typicus and Temora stylifera, and 7 other taxonomically broader copepod groups, in terms of size, biovolume and abundance-size distributions (size spectra). Also, total copepod size spectra underwent significant changes during the sampling period. These changes could be partially related to changes in the copepod assemblage taxonomic composition and size distributions. This study shows that the use of high throughput imaging systems is of great interest to extract relevant coarse (i.e. total abundance, size structure) and detailed (i.e. selected species dynamics) descriptors of zooplankton dynamics. Innovative zooplankton analyses are therefore proposed and open the way for further development of zooplankton community indicators of changes.

Magnetic fingerprint of the sediment load in a meander bend section of the Seine River (France)

NASA Astrophysics Data System (ADS)

Kayvantash, D.; Cojan, I.; Kissel, C.; Franke, C.

2017-06-01

This study aims to evaluate the potential of magnetic methods to determine the composition of the sediment load in a cross section of an unmanaged meander in the upstream stretch of the Seine River (Marnay-sur-Seine). Suspended particulate matter (SPM) was collected based on a regular sampling scheme along a cross section of the river, at two different depth levels: during a low-water stage (May 2014) and a high-water stage (February 2015). Riverbed sediments (RBS) were collected during the low-water stage and supplementary samples were taken from the outer and inner banks. Magnetic properties of the dry bulk SPM and sieved RBS and bank sediments were analysed. After characterizing the main magnetic carrier as magnetite, hysteresis parameters were measured, giving access to the grain size and the concentration of these magnetite particles. The results combined with sedimentary grain size data were compared to the three-dimensional velocity profile of the river flow. In the RBS where the magnetic grain size is rather uniform, the concentration of magnetite is inversely proportional to the mean grain size of the total sediment indicating that magnetite is strongly associated with the fine sedimentary fraction. The same pattern is observed in the samples from the outer and inner banks. During the low-water stage, the uniformly fine SPM grain size distribution characterizes the wash load. The magnetic fraction is also relatively fine (within the pseudo single domain range) with concentration similar to that of the fine RBS fraction. During the high-water stage, SPM samples correspond to mixtures of wash load and resuspended sediment from the bedload and riverbanks. Here, the grain size distribution is heterogeneous across the section showing coarser particles compared to those in the low-water stage and more varying magnetite concentrations while the magnetic grain size is like that of the low-water stage. The magnetite concentration in the high-water SPM can be modelled based on a mixing of the magnetite concentrations of the different grain size fractions, thus quantifying the impact of resuspension in the cross section.

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

ERIC Educational Resources Information Center

Rotondi, Michael A.; Donner, Allan

2009-01-01

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

Web-Based Menus: Font Size and Line Spacing Preferences.

ERIC Educational Resources Information Center

Pacheco, Janice; Day, Barbara Taylor; Cribelli, Susan; Jordan, John; Murry, Brandon; Persichitte, Kay A.

The study investigated the elements of font size and line spacing in World Wide Web menus for both a scrolled and not scrolled condition with a sample of undergraduate university students. Subjects were 185 students enrolled in 13 section of educational technology preservice teacher courses at the University of Northern Colorado. Students were…

Hierarchical Linear Modeling Meta-Analysis of Single-Subject Design Research

ERIC Educational Resources Information Center

Gage, Nicholas A.; Lewis, Timothy J.

2014-01-01

The identification of evidence-based practices continues to provoke issues of disagreement across multiple fields. One area of contention is the role of single-subject design (SSD) research in providing scientific evidence. The debate about SSD's utility centers on three issues: sample size, effect size, and serial dependence. One potential…

Effect of freezing conditions on β-Tricalcium Phosphate /Camphene scaffold with micro sized particles fabricated by freeze casting.

PubMed

Singh, Gurdev; Soundarapandian, S

2018-03-01

The long standing need of the implant manufacturing industries is to fabricate multi-matrix, customized porous scaffold as cost-effectively. In recent years, freeze casting has shown greater opportunity in the fabrication of porous scaffolds (tricalcium phosphate, hydroxyapatite, bioglass, alumina, etc.) such as at ease and good control over pore size, porosity, a range of materials and economic feasibility. In particular, tricalcium phosphate (TCP) has proved as it possesses good biocompatible (osteoinduction, osteoconduction, etc.) and biodegradability hence beta-tricalcium phosphate (β-TCP, particle size of 10µm) was used as base material and camphene was used as a freezing vehicle in this study. Both freezing conditions such as constant freezing temperature (CFT) and constant freezing rate (CFR) were used for six different conditional samples (CFT: 30, 35 and 40vol% solid loading; similarly CFR: 30, 35 and 40vol% solid loading) to study and understand the effect of various properties (pore size, porosity and compressive strength) of the freeze-cast porous scaffold. It was observed that the average size of the pore was varying linearly as from lower to higher when the solid loading was varying higher to lower. With the help of scanning electron micrographs (SEM), it was observed that the average size of pore during CFR (9.7/ 6.5/ 4.9µm) was comparatively higher than the process of CFT (6.0/ 4.8/ 2.6µm) with respect to the same solid loading (30/ 35/ 40vol%) conditions. From the Gas pycnometer analysis, it was found that the porosity in both freezing conditions (CFT, CFR) were almost near values such as 32.8% and 28.5%. Further to be observed that with the increase in solid loading, the total porosity value has decreased due to the reduction in the concentration of the freezing vehicle. Hence, the freezing vehicle was found as responsible for the formation of appropriate size and orientation of pores during freeze casting. The compressive strength (CS) testing was clearly indicated that the CS was majorly depending on the size of pore which was depending on solid loading. The CS of CFT-based samples (smaller pore sizes and higher resistance to the propagation of crack) were higher due to the higher solid content (pore size) in compared with CFR-based samples on the similar solid loading conditions. As evidently, it was noted that the CFT-based sample with 40% solid loading has given the compressive strength which has come in the range of cancellous bone. The positive note was that the ratio of Ca/P has come as 1.68 (natural bone) after sintering and that was the required value recommended by the food and drug administration (FDI) for manufacturing of bone implants. Copyright © 2017 Elsevier Ltd. All rights reserved.

The late Neandertal supraorbital fossils from Vindija Cave, Croatia: a biased sample?

PubMed

Ahern, James C M; Lee, Sang-Hee; Hawks, John D

2002-09-01

The late Neandertal sample from Vindija (Croatia) has been described as transitional between the earlier Central European Neandertals from Krapina (Croatia) and modern humans. However, the morphological differences indicating this transition may rather be the result of different sex and/or age compositions between the samples. This study tests the hypothesis that the metric differences between the Krapina and Vindija supraorbital samples are due to sampling bias. We focus upon the supraorbital region because past studies have posited this region as particularly indicative of the Vindija sample's transitional nature. Furthermore, the supraorbital region varies significantly with both age and sex. We analyzed four chords and two derived indices of supraorbital torus form as defined by Smith & Ranyard (1980, Am. J. phys. Anthrop.93, pp. 589-610). For each variable, we analyzed relative sample bias of the Krapina and Vindija samples using three sampling methods. In order to test the hypothesis that the Vindija sample contains an over-representation of females and/or young while the Krapina sample is normal or also female/young biased, we determined the probability of drawing a sample of the same size as and with a mean equal to or less than Vindija's from a Krapina-based population. In order to test the hypothesis that the Vindija sample is female/young biased while the Krapina sample is male/old biased, we determined the probability of drawing a sample of the same size as and with a mean equal or less than Vindija's from a generated population whose mean is halfway between Krapina's and Vindija's. Finally, in order to test the hypothesis that the Vindija sample is normal while the Krapina sample contains an over-representation of males and/or old, we determined the probability of drawing a sample of the same size as and with a mean equal to or greater than Krapina's from a Vindija-based population. Unless we assume that the Vindija sample is female/young and the Krapina sample is male/old biased, our results falsify the hypothesis that the metric differences between the Krapina and Vindija samples are due to sample bias.

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.

Mapping South San Francisco Bay's seabed diversity for use in wetland restoration planning

USGS Publications Warehouse

Fregoso, Theresa A.; Jaffe, B.; Rathwell, G.; Collins, W.; Rhynas, K.; Tomlin, V.; Sullivan, S.

2006-01-01

Data for an acoustic seabed classification were collected as a part of a California Coastal Conservancy funded bathymetric survey of South Bay in early 2005.  A QTC VIEW seabed classification system recorded echoes from a sungle bean 50 kHz echosounder.  Approximately 450,000 seabed classification records were generated from an are of of about 30 sq. miles.  Ten district acoustic classes were identified through an unsupervised classification system using principle component and cluster analyses.  One hundred and sixty-one grab samples and forty-five benthic community composition data samples collected in the study area shortly before and after the seabed classification survey, further refined the ten classes into groups based on grain size.  A preliminary map of surficial grain size of South Bay was developed from the combination of the seabed classification and the grab and benthic samples.  The initial seabed classification map, the grain size map, and locations of sediment samples will be displayed along with the methods of acousitc seabed classification.

Landsat image and sample design for water reservoirs (Rapel dam Central Chile).

PubMed

Lavanderos, L; Pozo, M E; Pattillo, C; Miranda, H

1990-01-01

Spatial heterogeneity of the Rapel reservoir surface waters is analyzed through Landsat images. The image digital counts are used with the aim or developing an aprioristic quantitative sample design.Natural horizontal stratification of the Rapel Reservoir (Central Chile) is produced mainly by suspended solids. The spatial heterogeneity conditions of the reservoir for the Spring 86-Summer 87 period were determined by qualitative analysis and image processing of the MSS Landsat, bands 1 and 3. The space-time variations of the different observed strata obtained with multitemporal image analysis.A random stratified sample design (r.s.s.d) was developed, based on the digital counts statistical analysis. Strata population size as well as the average, variance and sampling size of the digital counts were obtained by the r.s.s.d method.Stratification determined by analysis of satellite images were later correlated with ground data. Though the stratification of the reservoir is constant over time, the shape and size of the strata varys.

The Power of Low Back Pain Trials: A Systematic Review of Power, Sample Size, and Reporting of Sample Size Calculations Over Time, in Trials Published Between 1980 and 2012.

PubMed

Froud, Robert; Rajendran, Dévan; Patel, Shilpa; Bright, Philip; Bjørkli, Tom; Eldridge, Sandra; Buchbinder, Rachelle; Underwood, Martin

2017-06-01

A systematic review of nonspecific low back pain trials published between 1980 and 2012. To explore what proportion of trials have been powered to detect different bands of effect size; whether there is evidence that sample size in low back pain trials has been increasing; what proportion of trial reports include a sample size calculation; and whether likelihood of reporting sample size calculations has increased. Clinical trials should have a sample size sufficient to detect a minimally important difference for a given power and type I error rate. An underpowered trial is one within which probability of type II error is too high. Meta-analyses do not mitigate underpowered trials. Reviewers independently abstracted data on sample size at point of analysis, whether a sample size calculation was reported, and year of publication. Descriptive analyses were used to explore ability to detect effect sizes, and regression analyses to explore the relationship between sample size, or reporting sample size calculations, and time. We included 383 trials. One-third were powered to detect a standardized mean difference of less than 0.5, and 5% were powered to detect less than 0.3. The average sample size was 153 people, which increased only slightly (∼4 people/yr) from 1980 to 2000, and declined slightly (∼4.5 people/yr) from 2005 to 2011 (P < 0.00005). Sample size calculations were reported in 41% of trials. The odds of reporting a sample size calculation (compared to not reporting one) increased until 2005 and then declined (Equation is included in full-text article.). Sample sizes in back pain trials and the reporting of sample size calculations may need to be increased. It may be justifiable to power a trial to detect only large effects in the case of novel interventions. 3.

Are catchment-wide erosion rates really "Catchment-Wide"? Effects of grain size on erosion rates determined from 10Be

NASA Astrophysics Data System (ADS)

Reitz, M. A.; Seeber, L.; Schaefer, J. M.; Ferguson, E. K.

2012-12-01

Early studies pioneering the method for catchment wide erosion rates by measuring 10Be in alluvial sediment were taken at river mouths and used the sand size grain fraction from the riverbeds in order to average upstream erosion rates and measure erosion patterns. Finer particles (<0.0625 mm) were excluded to reduce the possibility of a wind-blown component of sediment and coarser particles (>2 mm) were excluded to better approximate erosion from the entire upstream catchment area (coarse grains are generally found near the source). Now that the sensitivity of 10Be measurements is rapidly increasing, we can precisely measure erosion rates from rivers eroding active tectonic regions. These active regions create higher energy drainage systems that erode faster and carry coarser sediment. In these settings, does the sand-sized fraction fully capture the average erosion of the upstream drainage area? Or does a different grain size fraction provide a more accurate measure of upstream erosion? During a study of the Neto River in Calabria, southern Italy, we took 8 samples along the length of the river, focusing on collecting samples just below confluences with major tributaries, in order to use the high-resolution erosion rate data to constrain tectonic motion. The samples we measured were sieved to either a 0.125 mm - 0.710 mm fraction or the 0.125 mm - 4 mm fraction (depending on how much of the former was available). After measuring these 8 samples for 10Be and determining erosion rates, we used the approach by Granger et al. [1996] to calculate the subcatchment erosion rates between each sample point. In the subcatchments of the river where we used grain sizes up to 4 mm, we measured very low 10Be concentrations (corresponding to high erosion rates) and calculated nonsensical subcatchment erosion rates (i.e. negative rates). We, therefore, hypothesize that the coarser grain sizes we included are preferentially sampling a smaller upstream area, and not the entire upstream catchment, which is assumed when measurements are based solely on the sand sized fraction. To test this hypothesis, we used samples with a variety of grain sizes from the Shillong Plateau. We sieved 5 samples into three grain size fractions: 0.125 mm - 710 mm, 710 mm - 4 mm, and >4 mm and measured 10Be concentrations in each fraction. Although there is some variation in the grain size fraction that yields the highest erosion rate, generally, the coarser grain size fractions have higher erosion rates. More significant are the results when calculating the subcatchment erosion rates, which suggest that even medium sized grains (710 mm - 4 mm) are sampling an area smaller than the entire upstream area; this finding is consistent with the nonsensical results from the Neto River study. This result has numerous implications for the interpretations of 10Be erosion rates: most importantly, an alluvial sample may not be averaging the entire upstream area, even when using the sand size fraction - resulting erosion rates more pertinent for that sample point rather than the entire catchment.

Variable aperture-based ptychographical iterative engine method.

PubMed

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. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Log-Normal Distribution of Cosmic Voids in Simulations and Mocks

NASA Astrophysics Data System (ADS)

Russell, E.; Pycke, J.-R.

2017-01-01

Following up on previous studies, we complete here a full analysis of the void size distributions of the Cosmic Void Catalog based on three different simulation and mock catalogs: dark matter (DM), haloes, and galaxies. Based on this analysis, we attempt to answer two questions: Is a three-parameter log-normal distribution a good candidate to satisfy the void size distributions obtained from different types of environments? Is there a direct relation between the shape parameters of the void size distribution and the environmental effects? In an attempt to answer these questions, we find here that all void size distributions of these data samples satisfy the three-parameter log-normal distribution whether the environment is dominated by DM, haloes, or galaxies. In addition, the shape parameters of the three-parameter log-normal void size distribution seem highly affected by environment, particularly existing substructures. Therefore, we show two quantitative relations given by linear equations between the skewness and the maximum tree depth, and between the variance of the void size distribution and the maximum tree depth, directly from the simulated data. In addition to this, we find that the percentage of voids with nonzero central density in the data sets has a critical importance. If the number of voids with nonzero central density reaches ≥3.84% in a simulation/mock sample, then a second population is observed in the void size distributions. This second population emerges as a second peak in the log-normal void size distribution at larger radius.

Estimating the Size of the Methamphetamine-Using Population in New York City Using Network Sampling Techniques.

PubMed

Dombrowski, Kirk; Khan, Bilal; Wendel, Travis; McLean, Katherine; Misshula, Evan; Curtis, Ric

2012-12-01

As part of a recent study of the dynamics of the retail market for methamphetamine use in New York City, we used network sampling methods to estimate the size of the total networked population. This process involved sampling from respondents' list of co-use contacts, which in turn became the basis for capture-recapture estimation. Recapture sampling was based on links to other respondents derived from demographic and "telefunken" matching procedures-the latter being an anonymized version of telephone number matching. This paper describes the matching process used to discover the links between the solicited contacts and project respondents, the capture-recapture calculation, the estimation of "false matches", and the development of confidence intervals for the final population estimates. A final population of 12,229 was estimated, with a range of 8235 - 23,750. The techniques described here have the special virtue of deriving an estimate for a hidden population while retaining respondent anonymity and the anonymity of network alters, but likely require larger sample size than the 132 persons interviewed to attain acceptable confidence levels for the estimate.

Calibrations and Comparisons of Aerosol Spectrometers linking Ground and Airborne Measurements

NASA Astrophysics Data System (ADS)

Williamson, C.; Brock, C. A.; Erdesz, F.

2015-12-01

The nucleation-mode aerosol size spectrometer (NMASS), a fast-time response instrument measuring aerosol size distributions between 5 and 60nm, is to sample in the boundary layer and free troposphere on NASA's Atmospheric Tomography mission (ATom), providing contiguous data with global coverage in all four seasons. In preparation for this the NMASS is calibrated for the expected flight conditions and compatibility studies are made with ground-based instrumentation. The NMASS is comprised of 5 parallel condensation particle counters (CPCs) using perfluoro-tributylamine as a working fluid. Understanding the variation of CPC counting efficiencies with respect to the chemical composition of the sample is important for accurate data analysis and can be used to give indirect information about sample chemical composition. This variation is strongly dependent on the working fluid. The absolute responses and associated variations of the NMASS to ammonium sulfate and limonene ozonolysis products, compounds pertinent to the composition of particles nucleated in the free troposphere and boundary later, are compared to those of butanol, diethylene-glycol and water based CPCs, which are more commonly used in ground-based measurements. While fast time-response is key to measuring aerosol size distributions on flights, high size-resolution is often prioritized for ground-based measurements, and so a scanning mobility particle sizer (SMPS) is commonly used. Inter-comparison between NMASS and SMPS data is non-trivial because of the different working principles and resolutions of the instruments and yet it is vital, for example, for understanding the sources of particles observed during flights and the global relevance of phenomena observed from field stations and in chambers. We report compatibility studies on inversions of data from the SMPS and NMASS, evaluating temporal and spatial resolution and sources of uncertainty.

Nickel speciation in several serpentine (ultramafic) topsoils via bulk synchrotron-based techniques

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

Siebecker, Matthew G.; Chaney, Rufus L.; Sparks, Donald L.

2017-07-01

Serpentine soils have elevated concentrations of trace metals including nickel, cobalt, and chromium compared to non-serpentine soils. Identifying the nickel bearing minerals allows for prediction of potential mobility of nickel. Synchrotron-based techniques can identify the solid-phase chemical forms of nickel with minimal sample treatment. Element concentrations are known to vary among soil particle sizes in serpentine soils. Sonication is a useful method to physically disperse sand, silt and clay particles in soils. Synchrotron-based techniques and sonication were employed to identify nickel species in discrete particle size fractions in several serpentine (ultramafic) topsoils to better understand solid-phase nickel geochemistry. Nickel commonlymore » resided in primary serpentine parent material such as layered-phyllosilicate and chain-inosilicate minerals and was associated with iron oxides. In the clay fractions, nickel was associated with iron oxides and primary serpentine minerals, such as lizardite. Linear combination fitting (LCF) was used to characterize nickel species. Total metal concentration did not correlate with nickel speciation and is not an indicator of the major nickel species in the soil. Differences in soil texture were related to different nickel speciation for several particle size fractionated samples. A discussion on LCF illustrates the importance of choosing standards based not only on statistical methods such as Target Transformation but also on sample mineralogy and particle size. Results from the F-test (Hamilton test), which is an underutilized tool in the literature for LCF in soils, highlight its usefulness to determine the appropriate number of standards to for LCF. EXAFS shell fitting illustrates that destructive interference commonly found for light and heavy elements in layered double hydroxides and in phyllosilicates also can occur in inosilicate minerals, causing similar structural features and leading to false positive results in LCF.« less

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.

Combining gas-phase electrophoretic mobility molecular analysis (GEMMA), light scattering, field flow fractionation and cryo electron microscopy in a multidimensional approach to characterize liposomal carrier vesicles.

PubMed

Urey, Carlos; Weiss, Victor U; Gondikas, Andreas; von der Kammer, Frank; Hofmann, Thilo; Marchetti-Deschmann, Martina; Allmaier, Günter; Marko-Varga, György; Andersson, Roland

2016-11-20

For drug delivery, characterization of liposomes regarding size, particle number concentrations, occurrence of low-sized liposome artefacts and drug encapsulation are of importance to understand their pharmacodynamic properties. In our study, we aimed to demonstrate the applicability of nano Electrospray Gas-Phase Electrophoretic Mobility Molecular Analyser (nES GEMMA) as a suitable technique for analyzing these parameters. We measured number-based particle concentrations, identified differences in size between nominally identical liposomal samples, and detected the presence of low-diameter material which yielded bimodal particle size distributions. Subsequently, we compared these findings to dynamic light scattering (DLS) data and results from light scattering experiments coupled to Asymmetric Flow-Field Flow Fractionation (AF4), the latter improving the detectability of smaller particles in polydisperse samples due to a size separation step prior detection. However, the bimodal size distribution could not be detected due to method inherent limitations. In contrast, cryo transmission electron microscopy corroborated nES GEMMA results. Hence, gas-phase electrophoresis proved to be a versatile tool for liposome characterization as it could analyze both vesicle size and size distribution. Finally, a correlation of nES GEMMA results with cell viability experiments was carried out to demonstrate the importance of liposome batch-to-batch control as low-sized sample components possibly impact cell viability. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

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.

Decision and function problems based on boson sampling

NASA Astrophysics Data System (ADS)

Nikolopoulos, Georgios M.; Brougham, Thomas

2016-07-01

Boson sampling is a mathematical problem that is strongly believed to be intractable for classical computers, whereas passive linear interferometers can produce samples efficiently. So far, the problem remains a computational curiosity, and the possible usefulness of boson-sampling devices is mainly limited to the proof of quantum supremacy. The purpose of this work is to investigate whether boson sampling can be used as a resource of decision and function problems that are computationally hard, and may thus have cryptographic applications. After the definition of a rather general theoretical framework for the design of such problems, we discuss their solution by means of a brute-force numerical approach, as well as by means of nonboson samplers. Moreover, we estimate the sample sizes required for their solution by passive linear interferometers, and it is shown that they are independent of the size of the Hilbert space.

Accounting for treatment by center interaction in sample size determinations and the use of surrogate outcomes in the pessary for the prevention of preterm birth trial: a simulation study.

PubMed

Willan, Andrew R

2016-07-05

The Pessary for the Prevention of Preterm Birth Study (PS3) is an international, multicenter, randomized clinical trial designed to examine the effectiveness of the Arabin pessary in preventing preterm birth in pregnant women with a short cervix. During the design of the study two methodological issues regarding power and sample size were raised. Since treatment in the Standard Arm will vary between centers, it is anticipated that so too will the probability of preterm birth in that arm. This will likely result in a treatment by center interaction, and the issue of how this will affect the sample size requirements was raised. The sample size requirements to examine the effect of the pessary on the baby's clinical outcome was prohibitively high, so the second issue is how best to examine the effect on clinical outcome. The approaches taken to address these issues are presented. Simulation and sensitivity analysis were used to address the sample size issue. The probability of preterm birth in the Standard Arm was assumed to vary between centers following a Beta distribution with a mean of 0.3 and a coefficient of variation of 0.3. To address the second issue a Bayesian decision model is proposed that combines the information regarding the between-treatment difference in the probability of preterm birth from PS3 with the data from the Multiple Courses of Antenatal Corticosteroids for Preterm Birth Study that relate preterm birth and perinatal mortality/morbidity. The approach provides a between-treatment comparison with respect to the probability of a bad clinical outcome. The performance of the approach was assessed using simulation and sensitivity analysis. Accounting for a possible treatment by center interaction increased the sample size from 540 to 700 patients per arm for the base case. The sample size requirements increase with the coefficient of variation and decrease with the number of centers. Under the same assumptions used for determining the sample size requirements, the simulated mean probability that pessary reduces the risk of perinatal mortality/morbidity is 0.98. The simulated mean decreased with coefficient of variation and increased with the number of clinical sites. Employing simulation and sensitivity analysis is a useful approach for determining sample size requirements while accounting for the additional uncertainty due to a treatment by center interaction. Using a surrogate outcome in conjunction with a Bayesian decision model is an efficient way to compare important clinical outcomes in a randomized clinical trial in situations where the direct approach requires a prohibitively high sample size.

Characterization of minerals in natural and manufactured sand in Cauvery River belt, Tamilnadu, India

NASA Astrophysics Data System (ADS)

Gnanasaravanan, S.; Rajkumar, P.

2013-05-01

The present study investigates the characterization of minerals in the River Sand (R - Sand) and the Manufactured sand (M-Sand) through FTIR spectroscopic studies. The R - Sand is collected from seven different locations in Cauvery River and M - Sand is collected from eight different manufactures around the Cauvery River belt in Salem, Erode, Tirupur and Namakkal districts of Tamilnadu, India. To extend the effectiveness of the analysis, the samples were subjected to grain size separation to classify the bulk samples into different grain sizes. All the samples were analyzed using FTIR spectrometer. The number of minerals identified with the help of FTIR spectra in overall (bulk) samples of R - Sand is 14 and of M - Sand is 13. The number has been increased while going for grain size separation, i.e., from 14 to 31 for R - Sand and from 13 to 20 for M - Sand. Among all minerals, quartz plays a major role. The relative distribution and the crystallinity nature of quartz have been discussed based on the extinction co-efficient and the crystallinity index values computed. There is no major variation found in M - Sand while going for grain size separation.

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

Dual-window dual-bandwidth spectroscopic optical coherence tomography metric for qualitative scatterer size differentiation in tissues.

PubMed

Tay, Benjamin Chia-Meng; Chow, Tzu-Hao; Ng, Beng-Koon; Loh, Thomas Kwok-Seng

2012-09-01

This study investigates the autocorrelation bandwidths of dual-window (DW) optical coherence tomography (OCT) k-space scattering profile of different-sized microspheres and their correlation to scatterer size. A dual-bandwidth spectroscopic metric defined as the ratio of the 10% to 90% autocorrelation bandwidths is found to change monotonically with microsphere size and gives the best contrast enhancement for scatterer size differentiation in the resulting spectroscopic image. A simulation model supports the experimental results and revealed a tradeoff between the smallest detectable scatterer size and the maximum scatterer size in the linear range of the dual-window dual-bandwidth (DWDB) metric, which depends on the choice of the light source optical bandwidth. Spectroscopic OCT (SOCT) images of microspheres and tonsil tissue samples based on the proposed DWDB metric showed clear differentiation between different-sized scatterers as compared to those derived from conventional short-time Fourier transform metrics. The DWDB metric significantly improves the contrast in SOCT imaging and can aid the visualization and identification of dissimilar scatterer size in a sample. Potential applications include the early detection of cell nuclear changes in tissue carcinogenesis, the monitoring of healing tendons, and cell proliferation in tissue scaffolds.

Studies on Microstructure and Thermoelectric Properties of p-Type Bi-Sb-Te Based Alloys by Gas Atomization and Hot Extrusion Processes

NASA Astrophysics Data System (ADS)

Park, Ki-Chan; Madavali, Babu; Kim, Eun-Bin; Koo, Kyung-Wan; Hong, Soon-Jik

2017-05-01

p-Type Bi2Te3 + 75% Sb2Te3 based thermoelectric materials were fabricated via gas atomization and the hot extrusion process. The gas atomized powder showed a clean surface with a spherical shape, and expanded in a wide particle size distribution (average particle size 50 μm). The phase of the fabricated extruded and R-extruded bars was identified using x-ray diffraction. The relative densities of both the extruded and R-extruded samples were measured by Archimedes principle with ˜98% relative density. The R-extruded bar exhibited finer grain microstructure than that of single extrusion process, which was attributed to a recrystallization mechanism during the fabrication. The R-extruded sample showed improved Vickers hardness compared to the extruded sample due to its fine grain microstructure. The electrical conductivity improved for the extruded sample whereas the Seebeck coefficient decreases due to its high carrier concentration. The peak power factor, ˜4.26 × 10-3 w/mK2 was obtained for the single extrusion sample, which is higher than the R-extrusion sample owing to its high electrical properties.

DIY Tomography sample holder

NASA Astrophysics Data System (ADS)

Lari, L.; Wright, I.; Boyes, E. D.

2015-10-01

A very simple tomography sample holder at minimal cost was developed in-house. The holder is based on a JEOL single tilt fast exchange sample holder where its exchangeable tip was modified to allow high angle degree tilt. The shape of the tip was designed to retain mechanical stability while minimising the lateral size of the tip. The sample can be mounted on as for a standard 3mm Cu grids as well as semi-circular grids from FIB sample preparation. Applications of the holder on different sample systems are shown.

Super-resolution imaging based on the temperature-dependent electron-phonon collision frequency effect of metal thin films

NASA Astrophysics Data System (ADS)

Ding, Chenliang; Wei, Jingsong; Xiao, Mufei

2018-05-01

We herein propose a far-field super-resolution imaging with metal thin films based on the temperature-dependent electron-phonon collision frequency effect. In the proposed method, neither fluorescence labeling nor any special properties are required for the samples. The 100 nm lands and 200 nm grooves on the Blu-ray disk substrates were clearly resolved and imaged through a laser scanning microscope of wavelength 405 nm. The spot size was approximately 0.80 μm , and the imaging resolution of 1/8 of the laser spot size was experimentally obtained. This work can be applied to the far-field super-resolution imaging of samples with neither fluorescence labeling nor any special properties.

Imaging of zymogen granules in fully wet cells: evidence for restricted mechanism of granule growth.

PubMed

Hammel, Ilan; Anaby, Debbie

2007-09-01

The introduction of wet SEM imaging technology permits electron microscopy of wet samples. Samples are placed in sealed specimen capsules and are insulated from the vacuum in the SEM chamber by an impermeable, electron-transparent membrane. The complete insulation of the sample from the vacuum allows direct imaging of fully hydrated, whole-mount tissue. In the current work, we demonstrate direct inspection of thick pancreatic tissue slices (above 400 mum). In the case of scanning of the pancreatic surface, the boundaries of intracellular features are seen directly. Thus no unfolding is required to ascertain the actual particle size distribution based on the sizes of the sections. This method enabled us to investigate the true granule size distribution and confirm early studies of improved conformity to a Poisson-like distribution, suggesting that the homotypic granule growth results from a mechanism, which favors the addition of a single unit granule to mature granules.

Optimum sample size allocation to minimize cost or maximize power for the two-sample trimmed mean test.

PubMed

Guo, Jiin-Huarng; Luh, Wei-Ming

2009-05-01

When planning a study, sample size determination is one of the most important tasks facing the researcher. The size will depend on the purpose of the study, the cost limitations, and the nature of the data. By specifying the standard deviation ratio and/or the sample size ratio, the present study considers the problem of heterogeneous variances and non-normality for Yuen's two-group test and develops sample size formulas to minimize the total cost or maximize the power of the test. For a given power, the sample size allocation ratio can be manipulated so that the proposed formulas can minimize the total cost, the total sample size, or the sum of total sample size and total cost. On the other hand, for a given total cost, the optimum sample size allocation ratio can maximize the statistical power of the test. After the sample size is determined, the present simulation applies Yuen's test to the sample generated, and then the procedure is validated in terms of Type I errors and power. Simulation results show that the proposed formulas can control Type I errors and achieve the desired power under the various conditions specified. Finally, the implications for determining sample sizes in experimental studies and future research are discussed.

Spatial and temporal variation of body size among early Homo.

PubMed

Will, Manuel; Stock, Jay T

2015-05-01

The estimation of body size among the earliest members of the genus Homo (2.4-1.5Myr [millions of years ago]) is central to interpretations of their biology. It is widely accepted that Homo ergaster possessed increased body size compared with Homo habilis and Homo rudolfensis, and that this may have been a factor involved with the dispersal of Homo out of Africa. The study of taxonomic differences in body size, however, is problematic. Postcranial remains are rarely associated with craniodental fossils, and taxonomic attributions frequently rest upon the size of skeletal elements. Previous body size estimates have been based upon well-preserved specimens with a more reliable species assessment. Since these samples are small (n < 5) and disparate in space and time, little is known about geographical and chronological variation in body size within early Homo. We investigate temporal and spatial variation in body size among fossils of early Homo using a 'taxon-free' approach, considering evidence for size variation from isolated and fragmentary postcranial remains (n = 39). To render the size of disparate fossil elements comparable, we derived new regression equations for common parameters of body size from a globally representative sample of hunter-gatherers and applied them to available postcranial measurements from the fossils. The results demonstrate chronological and spatial variation but no simple temporal or geographical trends for the evolution of body size among early Homo. Pronounced body size increases within Africa take place only after hominin populations were established at Dmanisi, suggesting that migrations into Eurasia were not contingent on larger body sizes. The primary evidence for these marked changes among early Homo is based upon material from Koobi Fora after 1.7Myr, indicating regional size variation. The significant body size differences between specimens from Koobi Fora and Olduvai support the cranial evidence for at least two co-existing morphotypes in the Early Pleistocene of eastern Africa. Copyright © 2015 Elsevier Ltd. All rights reserved.

Autonomous microfluidic sample preparation system for protein profile-based detection of aerosolized bacterial cells and spores.

PubMed

Stachowiak, Jeanne C; Shugard, Erin E; Mosier, Bruce P; Renzi, Ronald F; Caton, Pamela F; Ferko, Scott M; Van de Vreugde, James L; Yee, Daniel D; Haroldsen, Brent L; VanderNoot, Victoria A

2007-08-01

For domestic and military security, an autonomous system capable of continuously monitoring for airborne biothreat agents is necessary. At present, no system meets the requirements for size, speed, sensitivity, and selectivity to warn against and lead to the prevention of infection in field settings. We present a fully automated system for the detection of aerosolized bacterial biothreat agents such as Bacillus subtilis (surrogate for Bacillus anthracis) based on protein profiling by chip gel electrophoresis coupled with a microfluidic sample preparation system. Protein profiling has previously been demonstrated to differentiate between bacterial organisms. With the goal of reducing response time, multiple microfluidic component modules, including aerosol collection via a commercially available collector, concentration, thermochemical lysis, size exclusion chromatography, fluorescent labeling, and chip gel electrophoresis were integrated together to create an autonomous collection/sample preparation/analysis system. The cycle time for sample preparation was approximately 5 min, while total cycle time, including chip gel electrophoresis, was approximately 10 min. Sensitivity of the coupled system for the detection of B. subtilis spores was 16 agent-containing particles per liter of air, based on samples that were prepared to simulate those collected by wetted cyclone aerosol collector of approximately 80% efficiency operating for 7 min.

Identification of missing variants by combining multiple analytic pipelines.

PubMed

Ren, Yingxue; Reddy, Joseph S; Pottier, Cyril; Sarangi, Vivekananda; Tian, Shulan; Sinnwell, Jason P; McDonnell, Shannon K; Biernacka, Joanna M; Carrasquillo, Minerva M; Ross, Owen A; Ertekin-Taner, Nilüfer; Rademakers, Rosa; Hudson, Matthew; Mainzer, Liudmila Sergeevna; Asmann, Yan W

2018-04-16

After decades of identifying risk factors using array-based genome-wide association studies (GWAS), genetic research of complex diseases has shifted to sequencing-based rare variants discovery. This requires large sample sizes for statistical power and has brought up questions about whether the current variant calling practices are adequate for large cohorts. It is well-known that there are discrepancies between variants called by different pipelines, and that using a single pipeline always misses true variants exclusively identifiable by other pipelines. Nonetheless, it is common practice today to call variants by one pipeline due to computational cost and assume that false negative calls are a small percent of total. We analyzed 10,000 exomes from the Alzheimer's Disease Sequencing Project (ADSP) using multiple analytic pipelines consisting of different read aligners and variant calling strategies. We compared variants identified by using two aligners in 50,100, 200, 500, 1000, and 1952 samples; and compared variants identified by adding single-sample genotyping to the default multi-sample joint genotyping in 50,100, 500, 2000, 5000 and 10,000 samples. We found that using a single pipeline missed increasing numbers of high-quality variants correlated with sample sizes. By combining two read aligners and two variant calling strategies, we rescued 30% of pass-QC variants at sample size of 2000, and 56% at 10,000 samples. The rescued variants had higher proportions of low frequency (minor allele frequency [MAF] 1-5%) and rare (MAF < 1%) variants, which are the very type of variants of interest. In 660 Alzheimer's disease cases with earlier onset ages of ≤65, 4 out of 13 (31%) previously-published rare pathogenic and protective mutations in APP, PSEN1, and PSEN2 genes were undetected by the default one-pipeline approach but recovered by the multi-pipeline approach. Identification of the complete variant set from sequencing data is the prerequisite of genetic association analyses. The current analytic practice of calling genetic variants from sequencing data using a single bioinformatics pipeline is no longer adequate with the increasingly large projects. The number and percentage of quality variants that passed quality filters but are missed by the one-pipeline approach rapidly increased with sample size.

Thoracic and respirable particle definitions for human health risk assessment.

PubMed

Brown, James S; Gordon, Terry; Price, Owen; Asgharian, Bahman

2013-04-10

Particle size-selective sampling refers to the collection of particles of varying sizes that potentially reach and adversely affect specific regions of the respiratory tract. Thoracic and respirable fractions are defined as the fraction of inhaled particles capable of passing beyond the larynx and ciliated airways, respectively, during inhalation. In an attempt to afford greater protection to exposed individuals, current size-selective sampling criteria overestimate the population means of particle penetration into regions of the lower respiratory tract. The purpose of our analyses was to provide estimates of the thoracic and respirable fractions for adults and children during typical activities with both nasal and oral inhalation, that may be used in the design of experimental studies and interpretation of health effects evidence. We estimated the fraction of inhaled particles (0.5-20 μm aerodynamic diameter) penetrating beyond the larynx (based on experimental data) and ciliated airways (based on a mathematical model) for an adult male, adult female, and a 10 yr old child during typical daily activities and breathing patterns. Our estimates show less penetration of coarse particulate matter into the thoracic and gas exchange regions of the respiratory tract than current size-selective criteria. Of the parameters we evaluated, particle penetration into the lower respiratory tract was most dependent on route of breathing. For typical activity levels and breathing habits, we estimated a 50% cut-size for the thoracic fraction at an aerodynamic diameter of around 3 μm in adults and 5 μm in children, whereas current ambient and occupational criteria suggest a 50% cut-size of 10 μm. By design, current size-selective sample criteria overestimate the mass of particles generally expected to penetrate into the lower respiratory tract to provide protection for individuals who may breathe orally. We provide estimates of thoracic and respirable fractions for a variety of breathing habits and activities that may benefit the design of experimental studies and interpretation of particle size-specific health effects.

Thoracic and respirable particle definitions for human health risk assessment

PubMed Central

2013-01-01

Background Particle size-selective sampling refers to the collection of particles of varying sizes that potentially reach and adversely affect specific regions of the respiratory tract. Thoracic and respirable fractions are defined as the fraction of inhaled particles capable of passing beyond the larynx and ciliated airways, respectively, during inhalation. In an attempt to afford greater protection to exposed individuals, current size-selective sampling criteria overestimate the population means of particle penetration into regions of the lower respiratory tract. The purpose of our analyses was to provide estimates of the thoracic and respirable fractions for adults and children during typical activities with both nasal and oral inhalation, that may be used in the design of experimental studies and interpretation of health effects evidence. Methods We estimated the fraction of inhaled particles (0.5-20 μm aerodynamic diameter) penetrating beyond the larynx (based on experimental data) and ciliated airways (based on a mathematical model) for an adult male, adult female, and a 10 yr old child during typical daily activities and breathing patterns. Results Our estimates show less penetration of coarse particulate matter into the thoracic and gas exchange regions of the respiratory tract than current size-selective criteria. Of the parameters we evaluated, particle penetration into the lower respiratory tract was most dependent on route of breathing. For typical activity levels and breathing habits, we estimated a 50% cut-size for the thoracic fraction at an aerodynamic diameter of around 3 μm in adults and 5 μm in children, whereas current ambient and occupational criteria suggest a 50% cut-size of 10 μm. Conclusions By design, current size-selective sample criteria overestimate the mass of particles generally expected to penetrate into the lower respiratory tract to provide protection for individuals who may breathe orally. We provide estimates of thoracic and respirable fractions for a variety of breathing habits and activities that may benefit the design of experimental studies and interpretation of particle size-specific health effects. PMID:23575443

Comparative fiber evaluation of the mesdan aqualab microwave moisture measurement instrument

USDA-ARS?s Scientific Manuscript database

Moisture is a key cotton fiber parameter, as it can impact the fiber quality and the processing of cotton fiber. The Mesdan Aqualab is a microwave-based fiber moisture measurement instrument for samples with moderate sample size. A program was implemented to determine the capabilities of the Aqual...

Accurate in situ measurement of complex refractive index and particle size in intralipid emulsions

NASA Astrophysics Data System (ADS)

Dong, Miao L.; Goyal, Kashika G.; Worth, Bradley W.; Makkar, Sorab S.; Calhoun, William R.; Bali, Lalit M.; Bali, Samir

2013-08-01

A first accurate measurement of the complex refractive index in an intralipid emulsion is demonstrated, and thereby the average scatterer particle size using standard Mie scattering calculations is extracted. Our method is based on measurement and modeling of the reflectance of a divergent laser beam from the sample surface. In the absence of any definitive reference data for the complex refractive index or particle size in highly turbid intralipid emulsions, we base our claim of accuracy on the fact that our work offers several critically important advantages over previously reported attempts. First, our measurements are in situ in the sense that they do not require any sample dilution, thus eliminating dilution errors. Second, our theoretical model does not employ any fitting parameters other than the two quantities we seek to determine, i.e., the real and imaginary parts of the refractive index, thus eliminating ambiguities arising from multiple extraneous fitting parameters. Third, we fit the entire reflectance-versus-incident-angle data curve instead of focusing on only the critical angle region, which is just a small subset of the data. Finally, despite our use of highly scattering opaque samples, our experiment uniquely satisfies a key assumption behind the Mie scattering formalism, namely, no multiple scattering occurs. Further proof of our method's validity is given by the fact that our measured particle size finds good agreement with the value obtained by dynamic light scattering.

Accurate in situ measurement of complex refractive index and particle size in intralipid emulsions.

PubMed

Dong, Miao L; Goyal, Kashika G; Worth, Bradley W; Makkar, Sorab S; Calhoun, William R; Bali, Lalit M; Bali, Samir

2013-08-01

A first accurate measurement of the complex refractive index in an intralipid emulsion is demonstrated, and thereby the average scatterer particle size using standard Mie scattering calculations is extracted. Our method is based on measurement and modeling of the reflectance of a divergent laser beam from the sample surface. In the absence of any definitive reference data for the complex refractive index or particle size in highly turbid intralipid emulsions, we base our claim of accuracy on the fact that our work offers several critically important advantages over previously reported attempts. First, our measurements are in situ in the sense that they do not require any sample dilution, thus eliminating dilution errors. Second, our theoretical model does not employ any fitting parameters other than the two quantities we seek to determine, i.e., the real and imaginary parts of the refractive index, thus eliminating ambiguities arising from multiple extraneous fitting parameters. Third, we fit the entire reflectance-versus-incident-angle data curve instead of focusing on only the critical angle region, which is just a small subset of the data. Finally, despite our use of highly scattering opaque samples, our experiment uniquely satisfies a key assumption behind the Mie scattering formalism, namely, no multiple scattering occurs. Further proof of our method's validity is given by the fact that our measured particle size finds good agreement with the value obtained by dynamic light scattering.

Operationalizing hippocampal volume as an enrichment biomarker for amnestic MCI trials: effect of algorithm, test-retest variability and cut-point on trial cost, duration and sample size

PubMed Central

Yu, P.; Sun, J.; Wolz, R.; Stephenson, D.; Brewer, J.; Fox, N.C.; Cole, P.E.; Jack, C.R.; Hill, D.L.G.; Schwarz, A.J.

2014-01-01

Objective To evaluate the effect of computational algorithm, measurement variability and cut-point on hippocampal volume (HCV)-based patient selection for clinical trials in mild cognitive impairment (MCI). Methods We used normal control and amnestic MCI subjects from ADNI-1 as normative reference and screening cohorts. We evaluated the enrichment performance of four widely-used hippocampal segmentation algorithms (FreeSurfer, HMAPS, LEAP and NeuroQuant) in terms of two-year changes in MMSE, ADAS-Cog and CDR-SB. We modeled the effect of algorithm, test-retest variability and cut-point on sample size, screen fail rates and trial cost and duration. Results HCV-based patient selection yielded not only reduced sample sizes (by ~40–60%) but also lower trial costs (by ~30–40%) across a wide range of cut-points. Overall, the dependence on the cut-point value was similar for the three clinical instruments considered. Conclusion These results provide a guide to the choice of HCV cut-point for aMCI clinical trials, allowing an informed trade-off between statistical and practical considerations. PMID:24211008

Exploring the variability of aerosol particle composition in the Arctic: a study from the springtime ACCACIA campaign

NASA Astrophysics Data System (ADS)

Young, G.; Jones, H. M.; Darbyshire, E.; Baustian, K. J.; McQuaid, J. B.; Bower, K. N.; Connolly, P. J.; Gallagher, M. W.; Choularton, T. W.

2015-10-01

Single-particle compositional analysis of filter samples collected on-board the FAAM BAe-146 aircraft is presented for six flights during the springtime Aerosol-Cloud Coupling and Climate Interactions in the Arctic (ACCACIA) campaign (March-April 2013). Scanning electron microscopy was utilised to derive size distributions and size-segregated particle compositions. These data were compared to corresponding data from wing-mounted optical particle counters and reasonable agreement between the calculated number size distributions was found. Significant variability in composition was observed, with differing external and internal mixing identified, between air mass trajectory cases based on HYSPLIT analyses. Dominant particle classes were silicate-based dusts and sea salts, with particles notably rich in K and Ca detected in one case. Source regions varied from the Arctic Ocean and Greenland through to northern Russia and the European continent. Good agreement between the back trajectories was mirrored by comparable compositional trends between samples. Silicate dusts were identified in all cases, and the elemental composition of the dust was consistent for all samples except one. It is hypothesised that long-range, high-altitude transport was primarily responsible for this dust, with likely sources including the Asian arid regions.

Portfolio of automated trading systems: complexity and learning set size issues.

PubMed

Raudys, Sarunas

2013-03-01

In this paper, we consider using profit/loss histories of multiple automated trading systems (ATSs) as N input variables in portfolio management. By means of multivariate statistical analysis and simulation studies, we analyze the influences of sample size (L) and input dimensionality on the accuracy of determining the portfolio weights. We find that degradation in portfolio performance due to inexact estimation of N means and N(N - 1)/2 correlations is proportional to N/L; however, estimation of N variances does not worsen the result. To reduce unhelpful sample size/dimensionality effects, we perform a clustering of N time series and split them into a small number of blocks. Each block is composed of mutually correlated ATSs. It generates an expert trading agent based on a nontrainable 1/N portfolio rule. To increase the diversity of the expert agents, we use training sets of different lengths for clustering. In the output of the portfolio management system, the regularized mean-variance framework-based fusion agent is developed in each walk-forward step of an out-of-sample portfolio validation experiment. Experiments with the real financial data (2003-2012) confirm the effectiveness of the suggested approach.

Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining.

PubMed

Hero, Alfred O; Rajaratnam, Bala

2016-01-01

When can reliable inference be drawn in fue "Big Data" context? This paper presents a framework for answering this fundamental question in the context of correlation mining, wifu implications for general large scale inference. In large scale data applications like genomics, connectomics, and eco-informatics fue dataset is often variable-rich but sample-starved: a regime where the number n of acquired samples (statistical replicates) is far fewer than fue number p of observed variables (genes, neurons, voxels, or chemical constituents). Much of recent work has focused on understanding the computational complexity of proposed methods for "Big Data". Sample complexity however has received relatively less attention, especially in the setting when the sample size n is fixed, and the dimension p grows without bound. To address fuis gap, we develop a unified statistical framework that explicitly quantifies the sample complexity of various inferential tasks. Sampling regimes can be divided into several categories: 1) the classical asymptotic regime where fue variable dimension is fixed and fue sample size goes to infinity; 2) the mixed asymptotic regime where both variable dimension and sample size go to infinity at comparable rates; 3) the purely high dimensional asymptotic regime where the variable dimension goes to infinity and the sample size is fixed. Each regime has its niche but only the latter regime applies to exa cale data dimension. We illustrate this high dimensional framework for the problem of correlation mining, where it is the matrix of pairwise and partial correlations among the variables fua t are of interest. Correlation mining arises in numerous applications and subsumes the regression context as a special case. we demonstrate various regimes of correlation mining based on the unifying perspective of high dimensional learning rates and sample complexity for different structured covariance models and different inference tasks.

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

[A comparison of convenience sampling and purposive sampling].

PubMed

Suen, Lee-Jen Wu; Huang, Hui-Man; Lee, Hao-Hsien

2014-06-01

Convenience sampling and purposive sampling are two different sampling methods. This article first explains sampling terms such as target population, accessible population, simple random sampling, intended sample, actual sample, and statistical power analysis. These terms are then used to explain the difference between "convenience sampling" and purposive sampling." Convenience sampling is a non-probabilistic sampling technique applicable to qualitative or quantitative studies, although it is most frequently used in quantitative studies. In convenience samples, subjects more readily accessible to the researcher are more likely to be included. Thus, in quantitative studies, opportunity to participate is not equal for all qualified individuals in the target population and study results are not necessarily generalizable to this population. As in all quantitative studies, increasing the sample size increases the statistical power of the convenience sample. In contrast, purposive sampling is typically used in qualitative studies. Researchers who use this technique carefully select subjects based on study purpose with the expectation that each participant will provide unique and rich information of value to the study. As a result, members of the accessible population are not interchangeable and sample size is determined by data saturation not by statistical power analysis.

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

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.

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.

A new estimator of the discovery probability.

PubMed

Favaro, Stefano; Lijoi, Antonio; Prünster, Igor

2012-12-01

Species sampling problems have a long history in ecological and biological studies and a number of issues, including the evaluation of species richness, the design of sampling experiments, and the estimation of rare species variety, are to be addressed. Such inferential problems have recently emerged also in genomic applications, however, exhibiting some peculiar features that make them more challenging: specifically, one has to deal with very large populations (genomic libraries) containing a huge number of distinct species (genes) and only a small portion of the library has been sampled (sequenced). These aspects motivate the Bayesian nonparametric approach we undertake, since it allows to achieve the degree of flexibility typically needed in this framework. Based on an observed sample of size n, focus will be on prediction of a key aspect of the outcome from an additional sample of size m, namely, the so-called discovery probability. In particular, conditionally on an observed basic sample of size n, we derive a novel estimator of the probability of detecting, at the (n+m+1)th observation, species that have been observed with any given frequency in the enlarged sample of size n+m. Such an estimator admits a closed-form expression that can be exactly evaluated. The result we obtain allows us to quantify both the rate at which rare species are detected and the achieved sample coverage of abundant species, as m increases. Natural applications are represented by the estimation of the probability of discovering rare genes within genomic libraries and the results are illustrated by means of two expressed sequence tags datasets. © 2012, The International Biometric Society.

Got power? A systematic review of sample size adequacy in health professions education research.

PubMed

Cook, David A; Hatala, Rose

2015-03-01

Many education research studies employ small samples, which in turn lowers statistical power. We re-analyzed the results of a meta-analysis of simulation-based education to determine study power across a range of effect sizes, and the smallest effect that could be plausibly excluded. We systematically searched multiple databases through May 2011, and included all studies evaluating simulation-based education for health professionals in comparison with no intervention or another simulation intervention. Reviewers working in duplicate abstracted information to calculate standardized mean differences (SMD's). We included 897 original research studies. Among the 627 no-intervention-comparison studies the median sample size was 25. Only two studies (0.3%) had ≥80% power to detect a small difference (SMD > 0.2 standard deviations) and 136 (22%) had power to detect a large difference (SMD > 0.8). 110 no-intervention-comparison studies failed to find a statistically significant difference, but none excluded a small difference and only 47 (43%) excluded a large difference. Among 297 studies comparing alternate simulation approaches the median sample size was 30. Only one study (0.3%) had ≥80% power to detect a small difference and 79 (27%) had power to detect a large difference. Of the 128 studies that did not detect a statistically significant effect, 4 (3%) excluded a small difference and 91 (71%) excluded a large difference. In conclusion, most education research studies are powered only to detect effects of large magnitude. For most studies that do not reach statistical significance, the possibility of large and important differences still exists.

Firefighter Hand Anthropometry and Structural Glove Sizing: A New Perspective.

PubMed

Hsiao, Hongwei; Whitestone, Jennifer; Kau, Tsui-Ying; Hildreth, Brooke

2015-12-01

We evaluated the current use and fit of structural firefighting gloves and developed an improved sizing scheme that better accommodates the U.S. firefighter population. Among surveys, 24% to 30% of men and 31% to 62% of women reported experiencing problems with the fit or bulkiness of their structural firefighting gloves. An age-, race/ethnicity-, and gender-stratified sample of 863 male and 88 female firefighters across the United States participated in the study. Fourteen hand dimensions relevant to glove design were measured. A cluster analysis of the hand dimensions was performed to explore options for an improved sizing scheme. The current national standard structural firefighting glove-sizing scheme underrepresents firefighter hand size range and shape variation. In addition, mismatch between existing sizing specifications and hand characteristics, such as hand dimensions, user selection of glove size, and the existing glove sizing specifications, is significant. An improved glove-sizing plan based on clusters of overall hand size and hand/finger breadth-to-length contrast has been developed. This study presents the most up-to-date firefighter hand anthropometry and a new perspective on glove accommodation. The new seven-size system contains narrower variations (standard deviations) for almost all dimensions for each glove size than the current sizing practices. The proposed science-based sizing plan for structural firefighting gloves provides a step-forward perspective (i.e., including two women hand model-based sizes and two wide-palm sizes for men) for glove manufacturers to advance firefighter hand protection. © 2015, Human Factors and Ergonomics Society.

Evaluation of single and two-stage adaptive sampling designs for estimation of density and abundance of freshwater mussels in a large river

USGS Publications Warehouse

Smith, D.R.; Rogala, J.T.; Gray, B.R.; Zigler, S.J.; Newton, T.J.

2011-01-01

Reliable estimates of abundance are needed to assess consequences of proposed habitat restoration and enhancement projects on freshwater mussels in the Upper Mississippi River (UMR). Although there is general guidance on sampling techniques for population assessment of freshwater mussels, the actual performance of sampling designs can depend critically on the population density and spatial distribution at the project site. To evaluate various sampling designs, we simulated sampling of populations, which varied in density and degree of spatial clustering. Because of logistics and costs of large river sampling and spatial clustering of freshwater mussels, we focused on adaptive and non-adaptive versions of single and two-stage sampling. The candidate designs performed similarly in terms of precision (CV) and probability of species detection for fixed sample size. Both CV and species detection were determined largely by density, spatial distribution and sample size. However, designs did differ in the rate that occupied quadrats were encountered. Occupied units had a higher probability of selection using adaptive designs than conventional designs. We used two measures of cost: sample size (i.e. number of quadrats) and distance travelled between the quadrats. Adaptive and two-stage designs tended to reduce distance between sampling units, and thus performed better when distance travelled was considered. Based on the comparisons, we provide general recommendations on the sampling designs for the freshwater mussels in the UMR, and presumably other large rivers.

Task-based exposure assessment of nanoparticles in the workplace

NASA Astrophysics Data System (ADS)

Ham, Seunghon; Yoon, Chungsik; Lee, Euiseung; Lee, Kiyoung; Park, Donguk; Chung, Eunkyo; Kim, Pilje; Lee, Byoungcheun

2012-09-01

Although task-based sampling is, theoretically, a plausible approach to the assessment of nanoparticle exposure, few studies using this type of sampling have been published. This study characterized and compared task-based nanoparticle exposure profiles for engineered nanoparticle manufacturing workplaces (ENMW) and workplaces that generated welding fumes containing incidental nanoparticles. Two ENMW and two welding workplaces were selected for exposure assessments. Real-time devices were utilized to characterize the concentration profiles and size distributions of airborne nanoparticles. Filter-based sampling was performed to measure time-weighted average (TWA) concentrations, and off-line analysis was performed using an electron microscope. Workplace tasks were recorded by researchers to determine the concentration profiles associated with particular tasks/events. This study demonstrated that exposure profiles differ greatly in terms of concentrations and size distributions according to the task performed. The size distributions recorded during tasks were different from both those recorded during periods with no activity and from the background. The airborne concentration profiles of the nanoparticles varied according to not only the type of workplace but also the concentration metrics. The concentrations measured by surface area and the number concentrations measured by condensation particle counter, particulate matter 1.0, and TWA mass concentrations all showed a similar pattern, whereas the number concentrations measured by scanning mobility particle sizer indicated that the welding fume concentrations at one of the welding workplaces were unexpectedly higher than were those at workplaces that were engineering nanoparticles. This study suggests that a task-based exposure assessment can provide useful information regarding the exposure profiles of nanoparticles and can therefore be used as an exposure assessment tool.

Sampling designs for contaminant temporal trend analyses using sedentary species exemplified by the snails Bellamya aeruginosa and Viviparus viviparus.

PubMed

Yin, Ge; Danielsson, Sara; Dahlberg, Anna-Karin; Zhou, Yihui; Qiu, Yanling; Nyberg, Elisabeth; Bignert, Anders

2017-10-01

Environmental monitoring typically assumes samples and sampling activities to be representative of the population being studied. Given a limited budget, an appropriate sampling strategy is essential to support detecting temporal trends of contaminants. In the present study, based on real chemical analysis data on polybrominated diphenyl ethers in snails collected from five subsites in Tianmu Lake, computer simulation is performed to evaluate three sampling strategies by the estimation of required sample size, to reach a detection of an annual change of 5% with a statistical power of 80% and 90% with a significant level of 5%. The results showed that sampling from an arbitrarily selected sampling spot is the worst strategy, requiring much more individual analyses to achieve the above mentioned criteria compared with the other two approaches. A fixed sampling site requires the lowest sample size but may not be representative for the intended study object e.g. a lake and is also sensitive to changes of that particular sampling site. In contrast, sampling at multiple sites along the shore each year, and using pooled samples when the cost to collect and prepare individual specimens are much lower than the cost for chemical analysis, would be the most robust and cost efficient strategy in the long run. Using statistical power as criterion, the results demonstrated quantitatively the consequences of various sampling strategies, and could guide users with respect of required sample sizes depending on sampling design for long term monitoring programs. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

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).

Effect of freezing temperature in thermally induced phase separation method in hydroxyapatite/chitosan-based bone scaffold biomaterial

NASA Astrophysics Data System (ADS)

Albab, Muh Fadhil; Yuwono, Akhmad Herman; Sofyan, Nofrijon; Ramahdita, Ghiska

2017-02-01

In the current study, hydroxyapatite (HA)/chitosan-based bone scaffold has been fabricated using Thermally Induced Phase Separation (TIPS) method under freezing temperature variation of -20, -30, -40 and -80 °C. The samples with weight percent ratio of 70% HA and 30% chitosan were homogeneously mixed and subsequently dissolved in 2% acetic acid. The synthesized samples were further characterized using Fourier transform infrared (FTIR), compressive test and scanning electron microscope (SEM). The investigation results showed that low freezing temperature reduced the pore size and increased the compressive strength of the scaffold. In the freezing temperature of -20 °C, the pore size was 133.93 µm with the compressive strength of 5.9 KPa, while for -80 °C, the pore size declined to 60.55 µm with the compressive strength 29.8 KPa. Considering the obtained characteristics, HA/chitosan obtained in this work has potential to be applied as a bone scaffold.

Evaluation of Bias-Variance Trade-Off for Commonly Used Post-Summarizing Normalization Procedures in Large-Scale Gene Expression Studies

PubMed Central

Qiu, Xing; Hu, Rui; Wu, Zhixin

2014-01-01

Normalization procedures are widely used in high-throughput genomic data analyses to remove various technological noise and variations. They are known to have profound impact to the subsequent gene differential expression analysis. Although there has been some research in evaluating different normalization procedures, few attempts have been made to systematically evaluate the gene detection performances of normalization procedures from the bias-variance trade-off point of view, especially with strong gene differentiation effects and large sample size. In this paper, we conduct a thorough study to evaluate the effects of normalization procedures combined with several commonly used statistical tests and MTPs under different configurations of effect size and sample size. We conduct theoretical evaluation based on a random effect model, as well as simulation and biological data analyses to verify the results. Based on our findings, we provide some practical guidance for selecting a suitable normalization procedure under different scenarios. PMID:24941114

Isolation of nanoscale exosomes using viscoelastic effect

NASA Astrophysics Data System (ADS)

Hu, Guoqing; Liu, Chao

2017-11-01

Exosomes, molecular cargos secreted by almost all mammalian cells, are considered as promising biomarkers to identify many diseases including cancers. However, the small size of exosomes (30-200 nm) poses serious challenges on their isolation from the complex media containing a variety of extracellular vesicles (EVs) of different sizes, especially in small sample volumes. Here we develop a viscoelasticity-based microfluidic system to directly separate exosomes from cell culture media or serum in a continuous, size-dependent, and label-free manner. Using a small amount of biocompatible polymer as the additive into the media to control the viscoelastic forces exerted on EVs, we are able to achieve a high separation purity (>90%) and recovery (>80%) of exosomes. The size cutoff in viscoelasticity-based microfluidics can be easily controlled using different PEO concentrations. Based on this size-dependent viscoelastic separation strategy, we envision the handling of diverse nanoscale objects, such as gold nanoparticles, DNA origami structures, and quantum dots. This work was supported financially by National Natural Science Foundation of China (11572334, 91543125).

Plasma asymmetric dimethylarginine, L-arginine and left ventricular structure and function in a community-based sample.

PubMed

Lieb, Wolfgang; Benndorf, Ralf A; Benjamin, Emelia J; Sullivan, Lisa M; Maas, Renke; Xanthakis, Vanessa; Schwedhelm, Edzard; Aragam, Jayashri; Schulze, Friedrich; Böger, Rainer H; Vasan, Ramachandran S

2009-05-01

Increasing evidence indicates that cardiac structure and function are modulated by the nitric oxide (NO) system. Elevated plasma concentrations of asymmetric dimethylarginine (ADMA; a competitive inhibitor of NO synthase) have been reported in patients with end-stage renal disease. It is unclear if circulating ADMA and L-arginine levels are related to cardiac structure and function in the general population. We related plasma ADMA and L-arginine (the amino acid precursor of NO) to echocardiographic left ventricular (LV) mass, left atrial (LA) size and fractional shortening (FS) using multivariable linear regression analyses in 1919 Framingham Offspring Study participants (mean age 57 years, 58% women). Overall, neither ADMA or L-arginine, nor their ratio was associated with LV mass, LA size and FS in multivariable models (p>0.10 for all). However, we observed effect modification by obesity of the relations of ADMA and LA size (p for interaction p=0.04): ADMA was positively related to LA size in obese individuals (adjusted-p=0.0004 for trend across ADMA quartiles) but not in non-obese people. In our large community-based sample, plasma ADMA and l-arginine concentrations were not related to cardiac structure or function. The observation of positive relations of LA size and ADMA in obese individuals warrants confirmation.

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.

Methodological Issues in Curriculum-Based Reading Assessment.

ERIC Educational Resources Information Center

Fuchs, Lynn S.; And Others

1984-01-01

Three studies involving elementary students examined methodological issues in curriculum-based reading assessment. Results indicated that (1) whereas sample duration did not affect concurrent validity, increasing duration reduced performance instability and increased performance slopes and (2) domain size was related inversely to performance slope…

[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.

Sample Size Estimation: The Easy Way

ERIC Educational Resources Information Center

Weller, Susan C.

2015-01-01

This article presents a simple approach to making quick sample size estimates for basic hypothesis tests. Although there are many sources available for estimating sample sizes, methods are not often integrated across statistical tests, levels of measurement of variables, or effect sizes. A few parameters are required to estimate sample sizes and…

Fungal Fragments in Moldy Houses: A Field Study in Homes in New Orleans and Southern Ohio

PubMed Central

Reponen, Tiina; Seo, Sung-Chul; Grimsley, Faye; Lee, Taekhee; Crawford, Carlos; Grinshpun, Sergey A.

2007-01-01

Smaller-sized fungal fragments (<1 μm) may contribute to mold-related health effects. Previous laboratory-based studies have shown that the number concentration of fungal fragments can be up to 500 times higher than that of fungal spores, but this has not yet been confirmed in a field study due to lack of suitable methodology. We have recently developed a field-compatible method for the sampling and analysis of airborne fungal fragments. The new methodology was utilized for characterizing fungal fragment exposures in mold-contaminated homes selected in New Orleans, Louisiana and Southern Ohio. Airborne fungal particles were separated into three distinct size fractions: (i) >2.25 μm (spores); (ii) 1.05–2.25 μm (mixture); and (iii) < 1.0 μm (submicrometer-sized fragments). Samples were collected in five homes in summer and winter and analyzed for (1→3)-β-D-glucan. The total (1→3)-β-D-glucan varied from 0.2 to 16.0 ng m−3. The ratio of (1→3)-β-D-glucan mass in fragment size fraction to that in spore size fraction (F/S) varied from 0.011 to 2.163. The mass ratio was higher in winter (average = 1.017) than in summer (0.227) coinciding with a lower relative humidity in the winter. Assuming a mass-based F/S-ratio=1 and the spore size = 3 μm, the corresponding number-based F/S-ratio (fragment number/spore number) would be 103 and 106, for the fragment sizes of 0.3 and 0.03 μm, respectively. These results indicate that the actual (field) contribution of fungal fragments to the overall exposure may be very high, even much greater than that estimated in our earlier laboratory-based studies. PMID:19050738

Designing image segmentation studies: Statistical power, sample size and reference standard quality.

PubMed

Gibson, Eli; Hu, Yipeng; Huisman, Henkjan J; Barratt, Dean C

2017-12-01

Segmentation algorithms are typically evaluated by comparison to an accepted reference standard. The cost of generating accurate reference standards for medical image segmentation can be substantial. Since the study cost and the likelihood of detecting a clinically meaningful difference in accuracy both depend on the size and on the quality of the study reference standard, balancing these trade-offs supports the efficient use of research resources. In this work, we derive a statistical power calculation that enables researchers to estimate the appropriate sample size to detect clinically meaningful differences in segmentation accuracy (i.e. the proportion of voxels matching the reference standard) between two algorithms. Furthermore, we derive a formula to relate reference standard errors to their effect on the sample sizes of studies using lower-quality (but potentially more affordable and practically available) reference standards. The accuracy of the derived sample size formula was estimated through Monte Carlo simulation, demonstrating, with 95% confidence, a predicted statistical power within 4% of simulated values across a range of model parameters. This corresponds to sample size errors of less than 4 subjects and errors in the detectable accuracy difference less than 0.6%. The applicability of the formula to real-world data was assessed using bootstrap resampling simulations for pairs of algorithms from the PROMISE12 prostate MR segmentation challenge data set. The model predicted the simulated power for the majority of algorithm pairs within 4% for simulated experiments using a high-quality reference standard and within 6% for simulated experiments using a low-quality reference standard. A case study, also based on the PROMISE12 data, illustrates using the formulae to evaluate whether to use a lower-quality reference standard in a prostate segmentation study. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Online clustering algorithms for radar emitter classification.

PubMed

Liu, Jun; Lee, Jim P Y; Senior; Li, Lingjie; Luo, Zhi-Quan; Wong, K Max

2005-08-01

Radar emitter classification is a special application of data clustering for classifying unknown radar emitters from received radar pulse samples. The main challenges of this task are the high dimensionality of radar pulse samples, small sample group size, and closely located radar pulse clusters. In this paper, two new online clustering algorithms are developed for radar emitter classification: One is model-based using the Minimum Description Length (MDL) criterion and the other is based on competitive learning. Computational complexity is analyzed for each algorithm and then compared. Simulation results show the superior performance of the model-based algorithm over competitive learning in terms of better classification accuracy, flexibility, and stability.

Context Matters: Volunteer Bias, Small Sample Size, and the Value of Comparison Groups in the Assessment of Research-Based Undergraduate Introductory Biology Lab Courses

PubMed Central

Brownell, Sara E.; Kloser, Matthew J.; Fukami, Tadashi; Shavelson, Richard J.

2013-01-01

The shift from cookbook to authentic research-based lab courses in undergraduate biology necessitates the need for evaluation and assessment of these novel courses. Although the biology education community has made progress in this area, it is important that we interpret the effectiveness of these courses with caution and remain mindful of inherent limitations to our study designs that may impact internal and external validity. The specific context of a research study can have a dramatic impact on the conclusions. We present a case study of our own three-year investigation of the impact of a research-based introductory lab course, highlighting how volunteer students, a lack of a comparison group, and small sample sizes can be limitations of a study design that can affect the interpretation of the effectiveness of a course. PMID:24358380

Context matters: volunteer bias, small sample size, and the value of comparison groups in the assessment of research-based undergraduate introductory biology lab courses.

PubMed

Brownell, Sara E; Kloser, Matthew J; Fukami, Tadashi; Shavelson, Richard J

2013-01-01

The shift from cookbook to authentic research-based lab courses in undergraduate biology necessitates the need for evaluation and assessment of these novel courses. Although the biology education community has made progress in this area, it is important that we interpret the effectiveness of these courses with caution and remain mindful of inherent limitations to our study designs that may impact internal and external validity. The specific context of a research study can have a dramatic impact on the conclusions. We present a case study of our own three-year investigation of the impact of a research-based introductory lab course, highlighting how volunteer students, a lack of a comparison group, and small sample sizes can be limitations of a study design that can affect the interpretation of the effectiveness of a course.

Mating System and Effective Population Size of the Overexploited Neotropical Tree (Myroxylon peruiferum L.f.) and Their Impact on Seedling Production.

PubMed

Silvestre, Ellida de Aguiar; Schwarcz, Kaiser Dias; Grando, Carolina; de Campos, Jaqueline Bueno; Sujii, Patricia Sanae; Tambarussi, Evandro Vagner; Macrini, Camila Menezes Trindade; Pinheiro, José Baldin; Brancalion, Pedro Henrique Santin; Zucchi, Maria Imaculada

2018-03-16

The reproductive system of a tree species has substantial impact on genetic diversity and structure within and among natural populations. Such information, should be considered when planning tree planting for forest restoration. Here, we describe the mating system and genetic diversity of an overexploited Neotropical tree, Myroxylon peruiferum L.f. (Fabaceae) sampled from a forest remnant (10 seed trees and 200 seeds) and assess whether the effective population size of nursery-grown seedlings (148 seedlings) is sufficient to prevent inbreeding depression in reintroduced populations. Genetic analyses were performed based on 8 microsatellite loci. M. peruiferum presented a mixed mating system with evidence of biparental inbreeding (t^m-t^s = 0.118). We found low levels of genetic diversity for M. peruiferum species (allelic richness: 1.40 to 4.82; expected heterozygosity: 0.29 to 0.52). Based on Ne(v) within progeny, we suggest a sample size of 47 seed trees to achieve an effective population size of 100. The effective population sizes for the nursery-grown seedlings were much smaller Ne = 27.54-34.86) than that recommended for short term Ne ≥ 100) population conservation. Therefore, to obtain a reasonable genetic representation of native tree species and prevent problems associated with inbreeding depression, seedling production for restoration purposes may require a much larger sampling effort than is currently used, a problem that is further complicated by species with a mixed mating system. This study emphasizes the need to integrate species reproductive biology into seedling production programs and connect conservation genetics with ecological restoration.

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

Effects of grain size, mineralogy, and acid-extractable grain coatings on the distribution of the fallout radionuclides 7Be, 10Be, 137Cs, and 210Pb in river sediment

NASA Astrophysics Data System (ADS)

Singleton, Adrian A.; Schmidt, Amanda H.; Bierman, Paul R.; Rood, Dylan H.; Neilson, Thomas B.; Greene, Emily Sophie; Bower, Jennifer A.; Perdrial, Nicolas

2017-01-01

Grain-size dependencies in fallout radionuclide activity have been attributed to either increase in specific surface area in finer grain sizes or differing mineralogical abundances in different grain sizes. Here, we consider a third possibility, that the concentration and composition of grain coatings, where fallout radionuclides reside, controls their activity in fluvial sediment. We evaluated these three possible explanations in two experiments: (1) we examined the effect of sediment grain size, mineralogy, and composition of the acid-extractable materials on the distribution of 7Be, 10Be, 137Cs, and unsupported 210Pb in detrital sediment samples collected from rivers in China and the United States, and (2) we periodically monitored 7Be, 137Cs, and 210Pb retention in samples of known composition exposed to natural fallout in Ohio, USA for 294 days. Acid-extractable materials (made up predominately of Fe, Mn, Al, and Ca from secondary minerals and grain coatings produced during pedogenesis) are positively related to the abundance of fallout radionuclides in our sediment samples. Grain-size dependency of fallout radionuclide concentrations was significant in detrital sediment samples, but not in samples exposed to fallout under controlled conditions. Mineralogy had a large effect on 7Be and 210Pb retention in samples exposed to fallout, suggesting that sieving sediments to a single grain size or using specific surface area-based correction terms may not completely control for preferential distribution of these nuclides. We conclude that time-dependent geochemical, pedogenic, and sedimentary processes together result in the observed differences in nuclide distribution between different grain sizes and substrate compositions. These findings likely explain variability of measured nuclide activities in river networks that exceeds the variability introduced by analytical techniques as well as spatial and temporal differences in erosion rates and processes. In short, we suggest that presence and amount of pedogenic grain coatings is more important than either specific surface area or surface charge in setting the distribution of fallout radionuclides.

The Relationship between Sample Sizes and Effect Sizes in Systematic Reviews in Education

ERIC Educational Resources Information Center

Slavin, Robert; Smith, Dewi

2009-01-01

Research in fields other than education has found that studies with small sample sizes tend to have larger effect sizes than those with large samples. This article examines the relationship between sample size and effect size in education. It analyzes data from 185 studies of elementary and secondary mathematics programs that met the standards of…

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.

Development of a sampling strategy and sample size calculation to estimate the distribution of mammographic breast density in Korean women.

PubMed

Jun, Jae Kwan; Kim, Mi Jin; Choi, Kui Son; Suh, Mina; Jung, Kyu-Won

2012-01-01

Mammographic breast density is a known risk factor for breast cancer. To conduct a survey to estimate the distribution of mammographic breast density in Korean women, appropriate sampling strategies for representative and efficient sampling design were evaluated through simulation. Using the target population from the National Cancer Screening Programme (NCSP) for breast cancer in 2009, we verified the distribution estimate by repeating the simulation 1,000 times using stratified random sampling to investigate the distribution of breast density of 1,340,362 women. According to the simulation results, using a sampling design stratifying the nation into three groups (metropolitan, urban, and rural), with a total sample size of 4,000, we estimated the distribution of breast density in Korean women at a level of 0.01% tolerance. Based on the results of our study, a nationwide survey for estimating the distribution of mammographic breast density among Korean women can be conducted efficiently.

Researchers’ Intuitions About Power in Psychological Research

PubMed Central

Bakker, Marjan; Hartgerink, Chris H. J.; Wicherts, Jelte M.; van der Maas, Han L. J.

2016-01-01

Many psychology studies are statistically underpowered. In part, this may be because many researchers rely on intuition, rules of thumb, and prior practice (along with practical considerations) to determine the number of subjects to test. In Study 1, we surveyed 291 published research psychologists and found large discrepancies between their reports of their preferred amount of power and the actual power of their studies (calculated from their reported typical cell size, typical effect size, and acceptable alpha). Furthermore, in Study 2, 89% of the 214 respondents overestimated the power of specific research designs with a small expected effect size, and 95% underestimated the sample size needed to obtain .80 power for detecting a small effect. Neither researchers’ experience nor their knowledge predicted the bias in their self-reported power intuitions. Because many respondents reported that they based their sample sizes on rules of thumb or common practice in the field, we recommend that researchers conduct and report formal power analyses for their studies. PMID:27354203

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.

Researchers' Intuitions About Power in Psychological Research.

PubMed

Bakker, Marjan; Hartgerink, Chris H J; Wicherts, Jelte M; van der Maas, Han L J

2016-08-01

Many psychology studies are statistically underpowered. In part, this may be because many researchers rely on intuition, rules of thumb, and prior practice (along with practical considerations) to determine the number of subjects to test. In Study 1, we surveyed 291 published research psychologists and found large discrepancies between their reports of their preferred amount of power and the actual power of their studies (calculated from their reported typical cell size, typical effect size, and acceptable alpha). Furthermore, in Study 2, 89% of the 214 respondents overestimated the power of specific research designs with a small expected effect size, and 95% underestimated the sample size needed to obtain .80 power for detecting a small effect. Neither researchers' experience nor their knowledge predicted the bias in their self-reported power intuitions. Because many respondents reported that they based their sample sizes on rules of thumb or common practice in the field, we recommend that researchers conduct and report formal power analyses for their studies. © The Author(s) 2016.

A risk assessment method for multi-site damage

NASA Astrophysics Data System (ADS)

Millwater, Harry Russell, Jr.

This research focused on developing probabilistic methods suitable for computing small probabilities of failure, e.g., 10sp{-6}, of structures subject to multi-site damage (MSD). MSD is defined as the simultaneous development of fatigue cracks at multiple sites in the same structural element such that the fatigue cracks may coalesce to form one large crack. MSD is modeled as an array of collinear cracks with random initial crack lengths with the centers of the initial cracks spaced uniformly apart. The data used was chosen to be representative of aluminum structures. The structure is considered failed whenever any two adjacent cracks link up. A fatigue computer model is developed that can accurately and efficiently grow a collinear array of arbitrary length cracks from initial size until failure. An algorithm is developed to compute the stress intensity factors of all cracks considering all interaction effects. The probability of failure of two to 100 cracks is studied. Lower bounds on the probability of failure are developed based upon the probability of the largest crack exceeding a critical crack size. The critical crack size is based on the initial crack size that will grow across the ligament when the neighboring crack has zero length. The probability is evaluated using extreme value theory. An upper bound is based on the probability of the maximum sum of initial cracks being greater than a critical crack size. A weakest link sampling approach is developed that can accurately and efficiently compute small probabilities of failure. This methodology is based on predicting the weakest link, i.e., the two cracks to link up first, for a realization of initial crack sizes, and computing the cycles-to-failure using these two cracks. Criteria to determine the weakest link are discussed. Probability results using the weakest link sampling method are compared to Monte Carlo-based benchmark results. The results indicate that very small probabilities can be computed accurately in a few minutes using a Hewlett-Packard workstation.

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.

Phylogenetic effective sample size.

PubMed

Bartoszek, Krzysztof

2016-10-21

In this paper I address the question-how large is a phylogenetic sample? I propose a definition of a phylogenetic effective sample size for Brownian motion and Ornstein-Uhlenbeck processes-the regression effective sample size. I discuss how mutual information can be used to define an effective sample size in the non-normal process case and compare these two definitions to an already present concept of effective sample size (the mean effective sample size). Through a simulation study I find that the AICc is robust if one corrects for the number of species or effective number of species. Lastly I discuss how the concept of the phylogenetic effective sample size can be useful for biodiversity quantification, identification of interesting clades and deciding on the importance of phylogenetic correlations. Copyright © 2016 Elsevier Ltd. All rights reserved.

LOG-NORMAL DISTRIBUTION OF COSMIC VOIDS IN SIMULATIONS AND MOCKS

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

Russell, E.; Pycke, J.-R., E-mail: er111@nyu.edu, E-mail: jrp15@nyu.edu

2017-01-20

Following up on previous studies, we complete here a full analysis of the void size distributions of the Cosmic Void Catalog based on three different simulation and mock catalogs: dark matter (DM), haloes, and galaxies. Based on this analysis, we attempt to answer two questions: Is a three-parameter log-normal distribution a good candidate to satisfy the void size distributions obtained from different types of environments? Is there a direct relation between the shape parameters of the void size distribution and the environmental effects? In an attempt to answer these questions, we find here that all void size distributions of thesemore » data samples satisfy the three-parameter log-normal distribution whether the environment is dominated by DM, haloes, or galaxies. In addition, the shape parameters of the three-parameter log-normal void size distribution seem highly affected by environment, particularly existing substructures. Therefore, we show two quantitative relations given by linear equations between the skewness and the maximum tree depth, and between the variance of the void size distribution and the maximum tree depth, directly from the simulated data. In addition to this, we find that the percentage of voids with nonzero central density in the data sets has a critical importance. If the number of voids with nonzero central density reaches ≥3.84% in a simulation/mock sample, then a second population is observed in the void size distributions. This second population emerges as a second peak in the log-normal void size distribution at larger radius.« less

Relative efficiency of unequal versus equal cluster sizes in cluster randomized trials using generalized estimating equation models.

PubMed

Liu, Jingxia; Colditz, Graham A

2018-05-01

There is growing interest in conducting cluster randomized trials (CRTs). For simplicity in sample size calculation, the cluster sizes are assumed to be identical across all clusters. However, equal cluster sizes are not guaranteed in practice. Therefore, the relative efficiency (RE) of unequal versus equal cluster sizes has been investigated when testing the treatment effect. One of the most important approaches to analyze a set of correlated data is the generalized estimating equation (GEE) proposed by Liang and Zeger, in which the "working correlation structure" is introduced and the association pattern depends on a vector of association parameters denoted by ρ. In this paper, we utilize GEE models to test the treatment effect in a two-group comparison for continuous, binary, or count data in CRTs. The variances of the estimator of the treatment effect are derived for the different types of outcome. RE is defined as the ratio of variance of the estimator of the treatment effect for equal to unequal cluster sizes. We discuss a commonly used structure in CRTs-exchangeable, and derive the simpler formula of RE with continuous, binary, and count outcomes. Finally, REs are investigated for several scenarios of cluster size distributions through simulation studies. We propose an adjusted sample size due to efficiency loss. Additionally, we also propose an optimal sample size estimation based on the GEE models under a fixed budget for known and unknown association parameter (ρ) in the working correlation structure within the cluster. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Development and Validation of Pathogen Environmental Monitoring Programs for Small Cheese Processing Facilities.

PubMed

Beno, Sarah M; Stasiewicz, Matthew J; Andrus, Alexis D; Ralyea, Robert D; Kent, David J; Martin, Nicole H; Wiedmann, Martin; Boor, Kathryn J

2016-12-01

Pathogen environmental monitoring programs (EMPs) are essential for food processing facilities of all sizes that produce ready-to-eat food products exposed to the processing environment. We developed, implemented, and evaluated EMPs targeting Listeria spp. and Salmonella in nine small cheese processing facilities, including seven farmstead facilities. Individual EMPs with monthly sample collection protocols were designed specifically for each facility. Salmonella was detected in only one facility, with likely introduction from the adjacent farm indicated by pulsed-field gel electrophoresis data. Listeria spp. were isolated from all nine facilities during routine sampling. The overall Listeria spp. (other than Listeria monocytogenes ) and L. monocytogenes prevalences in the 4,430 environmental samples collected were 6.03 and 1.35%, respectively. Molecular characterization and subtyping data suggested persistence of a given Listeria spp. strain in seven facilities and persistence of L. monocytogenes in four facilities. To assess routine sampling plans, validation sampling for Listeria spp. was performed in seven facilities after at least 6 months of routine sampling. This validation sampling was performed by independent individuals and included collection of 50 to 150 samples per facility, based on statistical sample size calculations. Two of the facilities had a significantly higher frequency of detection of Listeria spp. during the validation sampling than during routine sampling, whereas two other facilities had significantly lower frequencies of detection. This study provides a model for a science- and statistics-based approach to developing and validating pathogen EMPs.

Estimating the breeding population of long-billed curlew in the United States

USGS Publications Warehouse

Stanley, T.R.; Skagen, S.K.

2007-01-01

Determining population size and long-term trends in population size for species of high concern is a priority of international, national, and regional conservation plans. Long-billed curlews (Numenius americanus) are a species of special concern in North America due to apparent declines in their population. Because long-billed curlews are not adequately monitored by existing programs, we undertook a 2-year study with the goals of 1) determining present long-billed curlew distribution and breeding population size in the United States and 2) providing recommendations for a long-term long-billed curlew monitoring protocol. We selected a stratified random sample of survey routes in 16 western states for sampling in 2004 and 2005, and we analyzed count data from these routes to estimate detection probabilities and abundance. In addition, we evaluated habitat along roadsides to determine how well roadsides represented habitat throughout the sampling units. We estimated there were 164,515 (SE = 42,047) breeding long-billed curlews in 2004, and 109,533 (SE = 31,060) breeding individuals in 2005. These estimates far exceed currently accepted estimates based on expert opinion. We found that habitat along roadsides was representative of long-billed curlew habitat in general. We make recommendations for improving sampling methodology, and we present power curves to provide guidance on minimum sample sizes required to detect trends in abundance.

10 CFR Appendix B to Subpart C of... - Sampling Plan for Enforcement Testing of Covered Equipment and Certain Low-Volume Covered Products

Code of Federal Regulations, 2014 CFR

2014-01-01

... percent, one-sided confidence limit and a sample size of n1. (2) For an energy consumption standard (ECS..., where ECS is the energy consumption standard and t is a statistic based on a 97.5 percent, one-sided...

10 CFR Appendix B to Subpart C of... - Sampling Plan for Enforcement Testing of Covered Equipment and Certain Low-Volume Covered Products

Code of Federal Regulations, 2013 CFR

2013-01-01

... percent, one-sided confidence limit and a sample size of n1. (2) For an energy consumption standard (ECS..., where ECS is the energy consumption standard and t is a statistic based on a 97.5 percent, one-sided...

10 CFR Appendix B to Subpart C of... - Sampling Plan for Enforcement Testing of Covered Equipment and Certain Low-Volume Covered Products

Code of Federal Regulations, 2012 CFR

2012-01-01

... percent, one-sided confidence limit and a sample size of n1. (2) For an energy consumption standard (ECS..., where ECS is the energy consumption standard and t is a statistic based on a 97.5 percent, one-sided...

Utility of the Mantel-Haenszel Procedure for Detecting Differential Item Functioning in Small Samples

ERIC Educational Resources Information Center

Fidalgo, Angel M.; Ferreres, Doris; Muniz, Jose

2004-01-01

Sample-size restrictions limit the contingency table approaches based on asymptotic distributions, such as the Mantel-Haenszel (MH) procedure, for detecting differential item functioning (DIF) in many practical applications. Within this framework, the present study investigated the power and Type I error performance of empirical and inferential…

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.

Public Opinion Polls, Chicken Soup and Sample Size

ERIC Educational Resources Information Center

Nguyen, Phung

2005-01-01

Cooking and tasting chicken soup in three different pots of very different size serves to demonstrate that it is the absolute sample size that matters the most in determining the accuracy of the findings of the poll, not the relative sample size, i.e. the size of the sample in relation to its population.

Multi-parameter analysis using photovoltaic cell-based optofluidic cytometer

PubMed Central

Yan, Chien-Shun; Wang, Yao-Nan

2016-01-01

A multi-parameter optofluidic cytometer based on two low-cost commercial photovoltaic cells and an avalanche photodetector is proposed. The optofluidic cytometer is fabricated on a polydimethylsiloxane (PDMS) substrate and is capable of detecting side scattered (SSC), extinction (EXT) and fluorescence (FL) signals simultaneously using a free-space light transmission technique without the need for on-chip optical waveguides. The feasibility of the proposed device is demonstrated by detecting fluorescent-labeled polystyrene beads with sizes of 3 μm, 5 μm and 10 μm, respectively, and label-free beads with a size of 7.26 μm. The detection experiments are performed using both single-bead population samples and mixed-bead population samples. The detection results obtained using the SSC/EXT, EXT/FL and SSC/FL signals are compared with those obtained using a commercial flow cytometer. It is shown that the optofluidic cytometer achieves a high detection accuracy for both single-bead population samples and mixed-bead population samples. Consequently, the proposed device provides a versatile, straightforward and low-cost solution for a wide variety of point-of-care (PoC) cytometry applications. PMID:27699122

Coalescence computations for large samples drawn from populations of time-varying sizes

PubMed Central

Polanski, Andrzej; Szczesna, Agnieszka; Garbulowski, Mateusz; Kimmel, Marek

2017-01-01

We present new results concerning probability distributions of times in the coalescence tree and expected allele frequencies for coalescent with large sample size. The obtained results are based on computational methodologies, which involve combining coalescence time scale changes with techniques of integral transformations and using analytical formulae for infinite products. We show applications of the proposed methodologies for computing probability distributions of times in the coalescence tree and their limits, for evaluation of accuracy of approximate expressions for times in the coalescence tree and expected allele frequencies, and for analysis of large human mitochondrial DNA dataset. PMID:28170404

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.

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.

tscvh R Package: Computational of the two samples test on microarray-sequencing data

NASA Astrophysics Data System (ADS)

Fajriyah, Rohmatul; Rosadi, Dedi

2017-12-01

We present a new R package, a tscvh (two samples cross-variance homogeneity), as we called it. This package is a software of the cross-variance statistical test which has been proposed and introduced by Fajriyah ([3] and [4]), based on the cross-variance concept. The test can be used as an alternative test for the significance difference between two means when sample size is small, the situation which is usually appeared in the bioinformatics research. Based on its statistical distribution, the p-value can be also provided. The package is built under a homogeneity of variance between samples.

Non-parametric estimation of population size changes from the site frequency spectrum.

PubMed

Waltoft, Berit Lindum; Hobolth, Asger

2018-06-11

Changes in population size is a useful quantity for understanding the evolutionary history of a species. Genetic variation within a species can be summarized by the site frequency spectrum (SFS). For a sample of size n, the SFS is a vector of length n - 1 where entry i is the number of sites where the mutant base appears i times and the ancestral base appears n - i times. We present a new method, CubSFS, for estimating the changes in population size of a panmictic population from an observed SFS. First, we provide a straightforward proof for the expression of the expected site frequency spectrum depending only on the population size. Our derivation is based on an eigenvalue decomposition of the instantaneous coalescent rate matrix. Second, we solve the inverse problem of determining the changes in population size from an observed SFS. Our solution is based on a cubic spline for the population size. The cubic spline is determined by minimizing the weighted average of two terms, namely (i) the goodness of fit to the observed SFS, and (ii) a penalty term based on the smoothness of the changes. The weight is determined by cross-validation. The new method is validated on simulated demographic histories and applied on unfolded and folded SFS from 26 different human populations from the 1000 Genomes Project.

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.

Probing defects in chemically synthesized ZnO nanostrucures by positron annihilation and photoluminescence spectroscopy

NASA Astrophysics Data System (ADS)

Chaudhuri, S. K.; Ghosh, Manoranjan; Das, D.; Raychaudhuri, A. K.

2010-09-01

The present article describes the size induced changes in the structural arrangement of intrinsic defects present in chemically synthesized ZnO nanoparticles of various sizes. Routine x-ray diffraction and transmission electron microscopy have been performed to determine the shapes and sizes of the nanocrystalline ZnO samples. Detailed studies using positron annihilation spectroscopy reveals the presence of zinc vacancy. Whereas analysis of photoluminescence results predict the signature of charged oxygen vacancies. The size induced changes in positron parameters as well as the photoluminescence properties, has shown contrasting or nonmonotonous trends as size varies from 4 to 85 nm. Small spherical particles below a critical size (˜23 nm) receive more positive surface charge due to the higher occupancy of the doubly charge oxygen vacancy as compared to the bigger nanostructures where singly charged oxygen vacancy predominates. This electronic alteration has been seen to trigger yet another interesting phenomenon, described as positron confinement inside nanoparticles. Finally, based on all the results, a model of the structural arrangement of the intrinsic defects in the present samples has been reconciled.

The grain size(s) of Black Hills Quartzite deformed in the dislocation creep regime

NASA Astrophysics Data System (ADS)

Heilbronner, Renée; Kilian, Rüdiger

2017-10-01

General shear experiments on Black Hills Quartzite (BHQ) deformed in the dislocation creep regimes 1 to 3 have been previously analyzed using the CIP method (Heilbronner and Tullis, 2002, 2006). They are reexamined using the higher spatial and orientational resolution of EBSD. Criteria for coherent segmentations based on c-axis orientation and on full crystallographic orientations are determined. Texture domains of preferred c-axis orientation (Y and B domains) are extracted and analyzed separately. Subdomains are recognized, and their shape and size are related to the kinematic framework and the original grains in the BHQ. Grain size analysis is carried out for all samples, high- and low-strain samples, and separately for a number of texture domains. When comparing the results to the recrystallized quartz piezometer of Stipp and Tullis (2003), it is found that grain sizes are consistently larger for a given flow stress. It is therefore suggested that the recrystallized grain size also depends on texture, grain-scale deformation intensity, and the kinematic framework (of axial vs. general shear experiments).

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.

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.

Silica dust exposure: Effect of filter size to compliance determination

NASA Astrophysics Data System (ADS)

Amran, Suhaily; Latif, Mohd Talib; Khan, Md Firoz; Leman, Abdul Mutalib; Goh, Eric; Jaafar, Shoffian Amin

2016-11-01

Monitoring of respirable dust was performed using a set of integrated sampling system consisting of sampling pump attached with filter media and separating device such as cyclone or special cassette. Based on selected method, filter sizes are either 25 mm or 37 mm poly vinyl chloride (PVC) filter. The aim of this study was to compare performance of two types of filter during personal respirable dust sampling for silica dust under field condition. The comparison strategy focused on the final compliance judgment based on both dataset. Eight hour parallel sampling of personal respirable dust exposure was performed among 30 crusher operators at six quarries. Each crusher operator was attached with parallel set of integrated sampling train containing either 25 mm or 37 mm PVC filter. Each set consisted of standard flow SKC sampler, attached with SKC GS3 cyclone and 2 pieces cassette loaded with 5.0 µm of PVC filter. Samples were analyzed by gravimetric technique. Personal respirable dust exposure between the two types of filters indicated significant positive correlation (p < 0.05) with moderate relationship (r2 = 0.6431). Personal exposure based on 25 mm PVC filter indicated 0.1% non-compliance to overall data while 37 mm PVC filter indicated similar findings at 0.4 %. Both data showed similar arithmetic mean(AM) and geometric mean(GM). In overall we concluded that personal respirable dust exposure either based on 25mm or 37mm PVC filter will give similar compliance determination. Both filters are reliable to be used in respirable dust monitoring for silica dust related exposure.

Statistical power calculations for mixed pharmacokinetic study designs using a population approach.

PubMed

Kloprogge, Frank; Simpson, Julie A; Day, Nicholas P J; White, Nicholas J; Tarning, Joel

2014-09-01

Simultaneous modelling of dense and sparse pharmacokinetic data is possible with a population approach. To determine the number of individuals required to detect the effect of a covariate, simulation-based power calculation methodologies can be employed. The Monte Carlo Mapped Power method (a simulation-based power calculation methodology using the likelihood ratio test) was extended in the current study to perform sample size calculations for mixed pharmacokinetic studies (i.e. both sparse and dense data collection). A workflow guiding an easy and straightforward pharmacokinetic study design, considering also the cost-effectiveness of alternative study designs, was used in this analysis. Initially, data were simulated for a hypothetical drug and then for the anti-malarial drug, dihydroartemisinin. Two datasets (sampling design A: dense; sampling design B: sparse) were simulated using a pharmacokinetic model that included a binary covariate effect and subsequently re-estimated using (1) the same model and (2) a model not including the covariate effect in NONMEM 7.2. Power calculations were performed for varying numbers of patients with sampling designs A and B. Study designs with statistical power >80% were selected and further evaluated for cost-effectiveness. The simulation studies of the hypothetical drug and the anti-malarial drug dihydroartemisinin demonstrated that the simulation-based power calculation methodology, based on the Monte Carlo Mapped Power method, can be utilised to evaluate and determine the sample size of mixed (part sparsely and part densely sampled) study designs. The developed method can contribute to the design of robust and efficient pharmacokinetic studies.

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…

24-Month-Old Children with Larger Oral Vocabularies Display Greater Academic and Behavioral Functioning at Kindergarten Entry

ERIC Educational Resources Information Center

Morgan, Paul L.; Farkas, George; Hillemeier, Marianne M.; Hammer, Carol Scheffner; Maczuga, Steve

2015-01-01

Data were analyzed from a population-based, longitudinal sample of 8,650 U.S. children to (a) identify factors associated with or predictive of oral vocabulary size at 24 months of age and (b) evaluate whether oral vocabulary size is uniquely predictive of academic and behavioral functioning at kindergarten entry. Children from higher…

Diversity, abundance, and size structure of bivalve assemblages in the Sipsey River, Alabama

Treesearch

Wendell R. Haag; Melvin L. Jr. Warren

2010-01-01

1. Patterns of mussel diversity and assemblage structure in the Sipsey River, Alabama, are described. Qualitative data were used to describe river-wide patterns of diversity. Quantitative data were used to describe the structure of mussel assemblages at several sites based on whole-substrate sampling that ensured all size classes were detected. 2. Major human impacts...

Influence of preservative and mounting media on the size and shape of monogenean sclerites.

PubMed

Fankoua, Severin-Oscar; Bitja Nyom, Arnold R; Bahanak, Dieu Ne Dort; Bilong Bilong, Charles F; Pariselle, Antoine

2017-08-01

Based on Cichlidogyrus sp. (Monogenea, Ancyrocephalidae) specimens from Hemichromis sp. hosts, we tested the influence of different methods to fix/preserve samples/specimens [frozen material, alcohol or formalin preserved, museum process for fish preservation (fixed in formalin and preserved in alcohol)] and different media used to mount the slides [tap water, glycerin ammonium picrate (GAP), Hoyer's one (HM)] on the size/shape of sclerotized parts of monogenean specimens. The results show that the use of HM significantly increases the size of haptoral sclerites [marginal hooks I, II, IV, V, and VI; dorsal bar length, width, distance between auricles and auricle length, ventral bar length and width], and changes their shape [angle opening between shaft and guard (outer and inner roots) in both ventral and dorsal anchors, ventral bar much wider, dorsal one less curved]. This influence seems to be reduced when specimens/samples are fixed in formalin. The systematics of Monogenea being based on the size and shape of their sclerotized parts, to prevent misidentifications or description of invalid new species, we recommend the use of GAP as mounting medium; Hoyer's one should be restricted to monogenean specimens fixed for a long time which are more shrunken.

Analytical template protection performance and maximum key size given a Gaussian-modeled biometric source

NASA Astrophysics Data System (ADS)

Kelkboom, Emile J. C.; Breebaart, Jeroen; Buhan, Ileana; Veldhuis, Raymond N. J.

2010-04-01

Template protection techniques are used within biometric systems in order to protect the stored biometric template against privacy and security threats. A great portion of template protection techniques are based on extracting a key from or binding a key to a biometric sample. The achieved protection depends on the size of the key and its closeness to being random. In the literature it can be observed that there is a large variation on the reported key lengths at similar classification performance of the same template protection system, even when based on the same biometric modality and database. In this work we determine the analytical relationship between the system performance and the theoretical maximum key size given a biometric source modeled by parallel Gaussian channels. We consider the case where the source capacity is evenly distributed across all channels and the channels are independent. We also determine the effect of the parameters such as the source capacity, the number of enrolment and verification samples, and the operating point selection on the maximum key size. We show that a trade-off exists between the privacy protection of the biometric system and its convenience for its users.

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.

Neurocognitive performance in family-based and case-control studies of schizophrenia.

PubMed

Gur, Ruben C; Braff, David L; Calkins, Monica E; Dobie, Dorcas J; Freedman, Robert; Green, Michael F; Greenwood, Tiffany A; Lazzeroni, Laura C; Light, Gregory A; Nuechterlein, Keith H; Olincy, Ann; Radant, Allen D; Seidman, Larry J; Siever, Larry J; Silverman, Jeremy M; Sprock, Joyce; Stone, William S; Sugar, Catherine A; Swerdlow, Neal R; Tsuang, Debby W; Tsuang, Ming T; Turetsky, Bruce I; Gur, Raquel E

2015-04-01

Neurocognitive deficits in schizophrenia (SZ) are established and the Consortium on the Genetics of Schizophrenia (COGS) investigated such measures as endophenotypes in family-based (COGS-1) and case-control (COGS-2) studies. By requiring family participation, family-based sampling may result in samples that vary demographically and perform better on neurocognitive measures. The Penn computerized neurocognitive battery (CNB) evaluates accuracy and speed of performance for several domains and was administered across sites in COGS-1 and COGS-2. Most tests were included in both studies. COGS-1 included 328 patients with SZ and 497 healthy comparison subjects (HCS) and COGS-2 included 1195 patients and 1009 HCS. Demographically, COGS-1 participants were younger, more educated, with more educated parents and higher estimated IQ compared to COGS-2 participants. After controlling for demographics, the two samples produced very similar performance profiles compared to their respective controls. As expected, performance was better and with smaller effect sizes compared to controls in COGS-1 relative to COGS-2. Better performance was most pronounced for spatial processing while emotion identification had large effect sizes for both accuracy and speed in both samples. Performance was positively correlated with functioning and negatively with negative and positive symptoms in both samples, but correlations were attenuated in COGS-2, especially with positive symptoms. Patients ascertained through family-based design have more favorable demographics and better performance on some neurocognitive domains. Thus, studies that use case-control ascertainment may tap into populations with more severe forms of illness that are exposed to less favorable factors compared to those ascertained with family-based designs.

Impact of minimum catch size on the population viability of Strombus gigas (Mesogastropoda: Strombidae) in Quintana Roo, Mexico.

PubMed

Peel, Joanne R; Mandujano, María del Carmen

2014-12-01

The queen conch Strombus gigas represents one of the most important fishery resources of the Caribbean but heavy fishing pressure has led to the depletion of stocks throughout the region, causing the inclusion of this species into CITES Appendix II and IUCN's Red-List. In Mexico, the queen conch is managed through a minimum fishing size of 200 mm shell length and a fishing quota which usually represents 50% of the adult biomass. The objectives of this study were to determine the intrinsic population growth rate of the queen conch population of Xel-Ha, Quintana Roo, Mexico, and to assess the effects of a regulated fishing impact, simulating the extraction of 50% adult biomass on the population density. We used three different minimum size criteria to demonstrate the effects of minimum catch size on the population density and discuss biological implications. Demographic data was obtained through capture-mark-recapture sampling, collecting all animals encountered during three hours, by three divers, at four different sampling sites of the Xel-Ha inlet. The conch population was sampled each month between 2005 and 2006, and bimonthly between 2006 and 2011, tagging a total of 8,292 animals. Shell length and lip thickness were determined for each individual. The average shell length for conch with formed lip in Xel-Ha was 209.39 ± 14.18 mm and the median 210 mm. Half of the sampled conch with lip ranged between 200 mm and 219 mm shell length. Assuming that the presence of the lip is an indicator for sexual maturity, it can be concluded that many animals may form their lip at greater shell lengths than 200 mm and ought to be considered immature. Estimation of relative adult abundance and densities varied greatly depending on the criteria employed for adult classification. When using a minimum fishing size of 200 mm shell length, between 26.2% and up to 54.8% of the population qualified as adults, which represented a simulated fishing impact of almost one third of the population. When conch extraction was simulated using a classification criteria based on lip thickness, it had a much smaller impact on the population density. We concluded that the best management strategy for S. gigas is a minimum fishing size based on a lip thickness, since it has lower impact on the population density, and given that selective fishing pressure based on size may lead to the appearance of small adult individuals with reduced fecundity. Furthermore, based on the reproductive biology and the results of the simulated fishing, we suggest a minimum lip thickness of ≥ 15 mm, which ensures the protection of reproductive stages, reduces the risk of overfishing, leading to non-viable density reduction.

The effect of sample holder material on ion mobility spectrometry reproducibility

NASA Technical Reports Server (NTRS)

Jadamec, J. Richard; Su, Chih-Wu; Rigdon, Stephen; Norwood, Lavan

1995-01-01

When a positive detection of a narcotic occurs during the search of a vessel, a decision has to be made whether further intensive search is warranted. This decision is based in part on the results of a second sample collected from the same area. Therefore, the reproducibility of both sampling and instrumental analysis is critical in terms of justifying an in depth search. As reported at the 2nd Annual IMS Conference in Quebec City, the U.S. Coast Guard has determined that when paper is utilized as the sample desorption medium for the Barringer IONSCAN, the analytical results using standard reference samples are reproducible. A study was conducted utilizing papers of varying pore sizes and comparing their performance as a desorption material relative to the standard Barringer 50 micron Teflon. Nominal pore sizes ranged from 30 microns down to 2 microns. Results indicate that there is some peak instability in the first two to three windows during the analysis. The severity of the instability was observed to increase as the pore size of the paper is decreased. However, the observed peak instability does not create a situation that results in a decreased reliability or reproducibility in the analytical result.

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

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.

Characterization of the particulate emissions from the BP Deepwater Horizon surface oil burns.

PubMed

Gullett, Brian K; Hays, Michael D; Tabor, Dennis; Wal, Randy Vander

2016-06-15

Sampling of the smoke plumes from the BP Deepwater Horizon surface oil burns led to the unintentional collection of soot particles on the sail of an instrument-bearing, tethered aerostat. This first-ever plume sampling from oil burned at an actual spill provided an opportunistic sample from which to characterize the particles' chemical properties for polycyclic aromatic hydrocarbons (PAHs), organic carbon, elemental carbon, metals, and polychlorinated dibenzodioxins/dibenzofurans (PCDDs/PCDFs) and physical properties for size and nanostructure. Thermal-optical analyses indicated that the particulate matter was 93% carbon with 82% being refractory elemental carbon. PAHs accounted for roughly 68μg/g of the PM filter mass and 5mg/kg oil burned, much lower than earlier laboratory based studies. Microscopy indicated that the soot is distinct from more common soot by its aggregate size, primary particle size, and nanostructure. PM-bound metals were largely unremarkable but PCDD/PCDF formation was observed, contrary to other's findings. Levels of lighter PCDD/PCDF and PAH compounds were reduced compared to historical samples, possibly due to volatilization or photo-oxidation. Published by Elsevier Ltd.

EVALUATION OF A NEW MEAN SCALED AND MOMENT ADJUSTED TEST STATISTIC FOR SEM.

PubMed

Tong, Xiaoxiao; Bentler, Peter M

2013-01-01

Recently a new mean scaled and skewness adjusted test statistic was developed for evaluating structural equation models in small samples and with potentially nonnormal data, but this statistic has received only limited evaluation. The performance of this statistic is compared to normal theory maximum likelihood and two well-known robust test statistics. A modification to the Satorra-Bentler scaled statistic is developed for the condition that sample size is smaller than degrees of freedom. The behavior of the four test statistics is evaluated with a Monte Carlo confirmatory factor analysis study that varies seven sample sizes and three distributional conditions obtained using Headrick's fifth-order transformation to nonnormality. The new statistic performs badly in most conditions except under the normal distribution. The goodness-of-fit χ(2) test based on maximum-likelihood estimation performed well under normal distributions as well as under a condition of asymptotic robustness. The Satorra-Bentler scaled test statistic performed best overall, while the mean scaled and variance adjusted test statistic outperformed the others at small and moderate sample sizes under certain distributional conditions.

Prospects and difficulties in TiO₂ nanoparticles analysis in cosmetic and food products using asymmetrical flow field-flow fractionation hyphenated to inductively coupled plasma mass spectrometry.

PubMed

López-Heras, Isabel; Madrid, Yolanda; Cámara, Carmen

2014-06-01

In this work, we proposed an analytical approach based on asymmetrical flow field-flow fractionation combined to an inductively coupled plasma mass spectrometry (AsFlFFF-ICP-MS) for rutile titanium dioxide nanoparticles (TiO2NPs) characterization and quantification in cosmetic and food products. AsFlFFF-ICP-MS separation of TiO2NPs was performed using 0.2% (w/v) SDS, 6% (v/v) methanol at pH 8.7 as the carrier solution. Two problems were addressed during TiO2NPs analysis by AsFlFFF-ICP-MS: size distribution determination and element quantification of the NPs. Two approaches were used for size determination: size calibration using polystyrene latex standards of known sizes and transmission electron microscopy (TEM). A method based on focused sonication for preparing NPs dispersions followed by an on-line external calibration strategy based on AsFlFFF-ICP-MS, using rutile TiO2NPs as standards is presented here for the first time. The developed method suppressed non-specific interactions between NPs and membrane, and overcame possible erroneous results obtained when quantification is performed by using ionic Ti solutions. The applicability of the quantification method was tested on cosmetic products (moisturizing cream). Regarding validation, at the 95% confidence level, no significant differences were detected between titanium concentrations in the moisturizing cream prior sample mineralization (3865±139 mg Ti/kg sample), by FIA-ICP-MS analysis prior NPs extraction (3770±24 mg Ti/kg sample), and after using the optimized on-line calibration approach (3699±145 mg Ti/kg sample). Besides the high Ti content found in the studied food products (sugar glass and coffee cream), TiO2NPs were not detected. Copyright © 2014 Elsevier B.V. All rights reserved.

Assessment of optimum threshold and particle shape parameter for the image analysis of aggregate size distribution of concrete sections

NASA Astrophysics Data System (ADS)

Ozen, Murat; Guler, Murat

2014-02-01

Aggregate gradation is one of the key design parameters affecting the workability and strength properties of concrete mixtures. Estimating aggregate gradation from hardened concrete samples can offer valuable insights into the quality of mixtures in terms of the degree of segregation and the amount of deviation from the specified gradation limits. In this study, a methodology is introduced to determine the particle size distribution of aggregates from 2D cross sectional images of concrete samples. The samples used in the study were fabricated from six mix designs by varying the aggregate gradation, aggregate source and maximum aggregate size with five replicates of each design combination. Each sample was cut into three pieces using a diamond saw and then scanned to obtain the cross sectional images using a desktop flatbed scanner. An algorithm is proposed to determine the optimum threshold for the image analysis of the cross sections. A procedure was also suggested to determine a suitable particle shape parameter to be used in the analysis of aggregate size distribution within each cross section. Results of analyses indicated that the optimum threshold hence the pixel distribution functions may be different even for the cross sections of an identical concrete sample. Besides, the maximum ferret diameter is the most suitable shape parameter to estimate the size distribution of aggregates when computed based on the diagonal sieve opening. The outcome of this study can be of practical value for the practitioners to evaluate concrete in terms of the degree of segregation and the bounds of mixture's gradation achieved during manufacturing.

A novel approach for small sample size family-based association studies: sequential tests.

PubMed

Ilk, Ozlem; Rajabli, Farid; Dungul, Dilay Ciglidag; Ozdag, Hilal; Ilk, Hakki Gokhan

2011-08-01

In this paper, we propose a sequential probability ratio test (SPRT) to overcome the problem of limited samples in studies related to complex genetic diseases. The results of this novel approach are compared with the ones obtained from the traditional transmission disequilibrium test (TDT) on simulated data. Although TDT classifies single-nucleotide polymorphisms (SNPs) to only two groups (SNPs associated with the disease and the others), SPRT has the flexibility of assigning SNPs to a third group, that is, those for which we do not have enough evidence and should keep sampling. It is shown that SPRT results in smaller ratios of false positives and negatives, as well as better accuracy and sensitivity values for classifying SNPs when compared with TDT. By using SPRT, data with small sample size become usable for an accurate association analysis.

Quantitative flaw characterization with scanning laser acoustic microscopy

NASA Technical Reports Server (NTRS)

Generazio, E. R.; Roth, D. J.

1986-01-01

Surface roughness and diffraction are two factors that have been observed to affect the accuracy of flaw characterization with scanning laser acoustic microscopy. In accuracies can arise when the surface of the test sample is acoustically rough. It is shown that, in this case, Snell's law is no longer valid for determining the direction of sound propagation within the sample. The relationship between the direction of sound propagation within the sample, the apparent flaw depth, and the sample's surface roughness is investigated. Diffraction effects can mask the acoustic images of minute flaws and make it difficult to establish their size, depth, and other characteristics. It is shown that for Fraunhofer diffraction conditions the acoustic image of a subsurface defect corresponds to a two-dimensional Fourier transform. Transforms based on simulated flaws are used to infer the size and shape of the actual flaw.

Intra-class correlation estimates for assessment of vitamin A intake in children.

PubMed

Agarwal, Girdhar G; Awasthi, Shally; Walter, Stephen D

2005-03-01

In many community-based surveys, multi-level sampling is inherent in the design. In the design of these studies, especially to calculate the appropriate sample size, investigators need good estimates of intra-class correlation coefficient (ICC), along with the cluster size, to adjust for variation inflation due to clustering at each level. The present study used data on the assessment of clinical vitamin A deficiency and intake of vitamin A-rich food in children in a district in India. For the survey, 16 households were sampled from 200 villages nested within eight randomly-selected blocks of the district. ICCs and components of variances were estimated from a three-level hierarchical random effects analysis of variance model. Estimates of ICCs and variance components were obtained at village and block levels. Between-cluster variation was evident at each level of clustering. In these estimates, ICCs were inversely related to cluster size, but the design effect could be substantial for large clusters. At the block level, most ICC estimates were below 0.07. At the village level, many ICC estimates ranged from 0.014 to 0.45. These estimates may provide useful information for the design of epidemiological studies in which the sampled (or allocated) units range in size from households to large administrative zones.

Bergmann's rule is maintained during a rapid range expansion in a damselfly.

PubMed

Hassall, Christopher; Keat, Simon; Thompson, David J; Watts, Phillip C

2014-02-01

Climate-induced range shifts result in the movement of a sample of genotypes from source populations to new regions. The phenotypic consequences of those shifts depend upon the sample characteristics of the dispersive genotypes, which may act to either constrain or promote phenotypic divergence, and the degree to which plasticity influences the genotype-environment interaction. We sampled populations of the damselfly Erythromma viridulum from northern Europe to quantify the phenotypic (latitude-body size relationship based on seven morphological traits) and genetic (variation at microsatellite loci) patterns that occur during a range expansion itself. We find a weak spatial genetic structure that is indicative of high gene flow during a rapid range expansion. Despite the potentially homogenizing effect of high gene flow, however, there is extensive phenotypic variation among samples along the invasion route that manifests as a strong, positive correlation between latitude and body size consistent with Bergmann's rule. This positive correlation cannot be explained by variation in the length of larval development (voltinism). While the adaptive significance of latitudinal variation in body size remains obscure, geographical patterns in body size in odonates are apparently underpinned by phenotypic plasticity and this permits a response to one or more environmental correlates of latitude during a range expansion. © 2013 John Wiley & Sons Ltd.

Metallographic Characterization of Wrought Depleted Uranium

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

Forsyth, Robert Thomas; Hill, Mary Ann

Metallographic characterization was performed on wrought depleted uranium (DU) samples taken from the longitudinal and transverse orientations from specific locations on two specimens. Characterization of the samples included general microstructure, inclusion analysis, grain size analysis, and microhardness testing. Comparisons of the characterization results were made to determine any differences based on specimen, sample orientation, or sample location. In addition, the characterization results for the wrought DU samples were also compared with data obtained from the metallographic characterization of cast DU samples previously characterized. No differences were observed in microstructure, inclusion size, morphology, and distribution, or grain size in regard tomore » specimen, location, or orientation for the wrought depleted uranium samples. However, a small difference was observed in average hardness with regard to orientation at the same locations within the same specimen. The longitudinal samples were slightly harder than the transverse samples from the same location of the same specimen. This was true for both wrought DU specimens. Comparing the wrought DU sample data with the previously characterized cast DU sample data, distinct differences in microstructure, inclusion size, morphology and distribution, grain size, and microhardness were observed. As expected, the microstructure of the wrought DU samples consisted of small recrystallized grains which were uniform, randomly oriented, and equiaxed with minimal twinning observed in only a few grains. In contrast, the cast DU microstructure consisted of large irregularly shaped grains with extensive twinning observed in most grains. Inclusions in the wrought DU samples were elongated, broken and cracked and light and dark phases were observed in some inclusions. The mean inclusion area percentage for the wrought DU samples ranged from 0.08% to 0.34% and the average density from all wrought DU samples was 1.62E+04/cm 2. Inclusions in the cast DU samples were equiaxed and intact with light and dark phases observed in some inclusions. The mean inclusion area percentage for the cast DU samples ranged from 0.93% to 1.00% and the average density from all wrought DU samples was 2.83E+04/cm 2. The average mean grain area from all wrought DU samples was 141 μm 2 while the average mean grain area from all cast DU samples was 1.7 mm2. The average Knoop microhardness from all wrought DU samples was 215 HK and the average Knoop microhardness from all cast DU samples was 264 HK.« less

Optimizing variable radius plot size and LiDAR resolution to model standing volume in conifer forests

Treesearch

Ram Kumar Deo; Robert E. Froese; Michael J. Falkowski; Andrew T. Hudak

2016-01-01

The conventional approach to LiDAR-based forest inventory modeling depends on field sample data from fixed-radius plots (FRP). Because FRP sampling is cost intensive, combining variable-radius plot (VRP) sampling and LiDAR data has the potential to improve inventory efficiency. The overarching goal of this study was to evaluate the integration of LiDAR and VRP data....

Reporting of sample size calculations in analgesic clinical trials: ACTTION systematic review.

PubMed

McKeown, Andrew; Gewandter, Jennifer S; McDermott, Michael P; Pawlowski, Joseph R; Poli, Joseph J; Rothstein, Daniel; Farrar, John T; Gilron, Ian; Katz, Nathaniel P; Lin, Allison H; Rappaport, Bob A; Rowbotham, Michael C; Turk, Dennis C; Dworkin, Robert H; Smith, Shannon M

2015-03-01

Sample size calculations determine the number of participants required to have sufficiently high power to detect a given treatment effect. In this review, we examined the reporting quality of sample size calculations in 172 publications of double-blind randomized controlled trials of noninvasive pharmacologic or interventional (ie, invasive) pain treatments published in European Journal of Pain, Journal of Pain, and Pain from January 2006 through June 2013. Sixty-five percent of publications reported a sample size calculation but only 38% provided all elements required to replicate the calculated sample size. In publications reporting at least 1 element, 54% provided a justification for the treatment effect used to calculate sample size, and 24% of studies with continuous outcome variables justified the variability estimate. Publications of clinical pain condition trials reported a sample size calculation more frequently than experimental pain model trials (77% vs 33%, P < .001) but did not differ in the frequency of reporting all required elements. No significant differences in reporting of any or all elements were detected between publications of trials with industry and nonindustry sponsorship. Twenty-eight percent included a discrepancy between the reported number of planned and randomized participants. This study suggests that sample size calculation reporting in analgesic trial publications is usually incomplete. Investigators should provide detailed accounts of sample size calculations in publications of clinical trials of pain treatments, which is necessary for reporting transparency and communication of pre-trial design decisions. In this systematic review of analgesic clinical trials, sample size calculations and the required elements (eg, treatment effect to be detected; power level) were incompletely reported. A lack of transparency regarding sample size calculations may raise questions about the appropriateness of the calculated sample size. Copyright © 2015 American Pain Society. All rights reserved.

Polystyrene-Divinylbenzene-Based Adsorbents Reduce Endothelial Activation and Monocyte Adhesion Under Septic Conditions in a Pore Size-Dependent Manner.

PubMed

Eichhorn, Tanja; Rauscher, Sabine; Hammer, Caroline; Gröger, Marion; Fischer, Michael B; Weber, Viktoria

2016-10-01

Endothelial activation with excessive recruitment and adhesion of immune cells plays a central role in the progression of sepsis. We established a microfluidic system to study the activation of human umbilical vein endothelial cells by conditioned medium containing plasma from lipopolysaccharide-stimulated whole blood or from septic blood and to investigate the effect of adsorption of inflammatory mediators on endothelial activation. Treatment of stimulated whole blood with polystyrene-divinylbenzene-based cytokine adsorbents (average pore sizes 15 or 30 nm) prior to passage over the endothelial layer resulted in significantly reduced endothelial cytokine and chemokine release, plasminogen activator inhibitor-1 secretion, adhesion molecule expression, and in diminished monocyte adhesion. Plasma samples from sepsis patients differed substantially in their potential to induce endothelial activation and monocyte adhesion despite their almost identical interleukin-6 and tumor necrosis factor-alpha levels. Pre-incubation of the plasma samples with a polystyrene-divinylbenzene-based adsorbent (30 nm average pore size) reduced endothelial intercellular adhesion molecule-1 expression to baseline levels, resulting in significantly diminished monocyte adhesion. Our data support the potential of porous polystyrene-divinylbenzene-based adsorbents to reduce endothelial activation under septic conditions by depletion of a broad range of inflammatory mediators.

Potential for adult-based epidemiological studies to characterize overall cancer risks associated with a lifetime of CT scans.

PubMed

Shuryak, Igor; Lubin, Jay H; Brenner, David J

2014-06-01

Recent epidemiological studies have suggested that radiation exposure from pediatric CT scanning is associated with small excess cancer risks. However, the majority of CT scans are performed on adults, and most radiation-induced cancers appear during middle or old age, in the same age range as background cancers. Consequently, a logical next step is to investigate the effects of CT scanning in adulthood on lifetime cancer risks by conducting adult-based, appropriately designed epidemiological studies. Here we estimate the sample size required for such studies to detect CT-associated risks. This was achieved by incorporating different age-, sex-, time- and cancer type-dependent models of radiation carcinogenesis into an in silico simulation of a population-based cohort study. This approach simulated individual histories of chest and abdominal CT exposures, deaths and cancer diagnoses. The resultant sample sizes suggest that epidemiological studies of realistically sized cohorts can detect excess lifetime cancer risks from adult CT exposures. For example, retrospective analysis of CT exposure and cancer incidence data from a population-based cohort of 0.4 to 1.3 million (depending on the carcinogenic model) CT-exposed UK adults, aged 25-65 in 1980 and followed until 2015, provides 80% power for detecting cancer risks from chest and abdominal CT scans.

Firefighter Hand Anthropometry and Structural Glove Sizing: A New Perspective

PubMed Central

Hsiao, Hongwei; Whitestone, Jennifer; Kau, Tsui-Ying; Hildreth, Brooke

2015-01-01

Objective We evaluated the current use and fit of structural firefighting gloves and developed an improved sizing scheme that better accommodates the U.S. firefighter population. Background Among surveys, 24% to 30% of men and 31% to 62% of women reported experiencing problems with the fit or bulkiness of their structural firefighting gloves. Method An age-, race/ethnicity-, and gender-stratified sample of 863 male and 88 female firefighters across the United States participated in the study. Fourteen hand dimensions relevant to glove design were measured. A cluster analysis of the hand dimensions was performed to explore options for an improved sizing scheme. Results The current national standard structural firefighting glove-sizing scheme underrepresents firefighter hand size range and shape variation. In addition, mismatch between existing sizing specifications and hand characteristics, such as hand dimensions, user selection of glove size, and the existing glove sizing specifications, is significant. An improved glove-sizing plan based on clusters of overall hand size and hand/finger breadth-to-length contrast has been developed. Conclusion This study presents the most up-to-date firefighter hand anthropometry and a new perspective on glove accommodation. The new seven-size system contains narrower variations (standard deviations) for almost all dimensions for each glove size than the current sizing practices. Application The proposed science-based sizing plan for structural firefighting gloves provides a step-forward perspective (i.e., including two women hand model–based sizes and two wide-palm sizes for men) for glove manufacturers to advance firefighter hand protection. PMID:26169309

Phase-contrast x-ray computed tomography for biological imaging

NASA Astrophysics Data System (ADS)

Momose, Atsushi; Takeda, Tohoru; Itai, Yuji

1997-10-01

We have shown so far that 3D structures in biological sot tissues such as cancer can be revealed by phase-contrast x- ray computed tomography using an x-ray interferometer. As a next step, we aim at applications of this technique to in vivo observation, including radiographic applications. For this purpose, the size of view field is desired to be more than a few centimeters. Therefore, a larger x-ray interferometer should be used with x-rays of higher energy. We have evaluated the optimal x-ray energy from an aspect of does as a function of sample size. Moreover, desired spatial resolution to an image sensor is discussed as functions of x-ray energy and sample size, basing on a requirement in the analysis of interference fringes.

Synthetic Control of Crystallite Size of Silver Vanadium Phosphorous Oxide (Ag 0.50VOPO 4·1.9H 2O): Impact on Electrochemistry

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

Huie, Matthew M.; Marschilok, Amy C.; Takeuchi, Esther S.

Here, this report describes a synthetic approach to control the crystallite size of silver vanadium phosphorous oxide, Ag 0.50VOPO 4·1.9H 2O, and the impact on electrochemistry in lithium based batteries. Ag 0.50VOPO 4·1.9H 2O was synthesized using a stirred hydrothermal method over a range of temperatures. X-ray diffraction (XRD) was used to confirm the crystalline phase and the crystallite size sizes of 11, 22, 38, 40, 49, and 120 nm. Particle shape was plate-like with edges <1 micron to >10 microns. Under galvanostatic reduction the samples with 22 nm crystallites and 880 nm particles produced the highest capacity, ~25% moremore » capacity than the 120 nm sample. Notably, the 11 nm sample resulted in reduced delivered capacity and higher resistance consistent with increased grain boundaries contributing to resistance. Under intermittent pulsing ohmic resistance decreased with increasing crystallite size from 11 nm to 120 nm implying that electrical conduction within a crystal is more facile than between crystallites and across grain boundaries. Finally, this systematic study of material dimension shows that crystallite size impacts deliverable capacity as well as cell resistance where both interparticle and intraparticle transport are important.« less

Synthetic Control of Crystallite Size of Silver Vanadium Phosphorous Oxide (Ag 0.50VOPO 4·1.9H 2O): Impact on Electrochemistry

DOE PAGES

Huie, Matthew M.; Marschilok, Amy C.; Takeuchi, Esther S.; ...

2017-04-12

Here, this report describes a synthetic approach to control the crystallite size of silver vanadium phosphorous oxide, Ag 0.50VOPO 4·1.9H 2O, and the impact on electrochemistry in lithium based batteries. Ag 0.50VOPO 4·1.9H 2O was synthesized using a stirred hydrothermal method over a range of temperatures. X-ray diffraction (XRD) was used to confirm the crystalline phase and the crystallite size sizes of 11, 22, 38, 40, 49, and 120 nm. Particle shape was plate-like with edges <1 micron to >10 microns. Under galvanostatic reduction the samples with 22 nm crystallites and 880 nm particles produced the highest capacity, ~25% moremore » capacity than the 120 nm sample. Notably, the 11 nm sample resulted in reduced delivered capacity and higher resistance consistent with increased grain boundaries contributing to resistance. Under intermittent pulsing ohmic resistance decreased with increasing crystallite size from 11 nm to 120 nm implying that electrical conduction within a crystal is more facile than between crystallites and across grain boundaries. Finally, this systematic study of material dimension shows that crystallite size impacts deliverable capacity as well as cell resistance where both interparticle and intraparticle transport are important.« less

Estimation of the Human Extrathoracic Deposition Fraction of Inhaled Particles Using a Polyurethane Foam Collection Substrate in an IOM Sampler.

PubMed

Sleeth, Darrah K; Balthaser, Susan A; Collingwood, Scott; Larson, Rodney R

2016-03-07

Extrathoracic deposition of inhaled particles (i.e., in the head and throat) is an important exposure route for many hazardous materials. Current best practices for exposure assessment of aerosols in the workplace involve particle size selective sampling methods based on particle penetration into the human respiratory tract (i.e., inhalable or respirable sampling). However, the International Organization for Standardization (ISO) has recently adopted particle deposition sampling conventions (ISO 13138), including conventions for extrathoracic (ET) deposition into the anterior nasal passage (ET₁) and the posterior nasal and oral passages (ET₂). For this study, polyurethane foam was used as a collection substrate inside an inhalable aerosol sampler to provide an estimate of extrathoracic particle deposition. Aerosols of fused aluminum oxide (five sizes, 4.9 µm-44.3 µm) were used as a test dust in a low speed (0.2 m/s) wind tunnel. Samplers were placed on a rotating mannequin inside the wind tunnel to simulate orientation-averaged personal sampling. Collection efficiency data for the foam insert matched well to the extrathoracic deposition convention for the particle sizes tested. The concept of using a foam insert to match a particle deposition sampling convention was explored in this study and shows promise for future use as a sampling device.

Estimation of the Human Extrathoracic Deposition Fraction of Inhaled Particles Using a Polyurethane Foam Collection Substrate in an IOM Sampler

PubMed Central

Sleeth, Darrah K.; Balthaser, Susan A.; Collingwood, Scott; Larson, Rodney R.

2016-01-01

Extrathoracic deposition of inhaled particles (i.e., in the head and throat) is an important exposure route for many hazardous materials. Current best practices for exposure assessment of aerosols in the workplace involve particle size selective sampling methods based on particle penetration into the human respiratory tract (i.e., inhalable or respirable sampling). However, the International Organization for Standardization (ISO) has recently adopted particle deposition sampling conventions (ISO 13138), including conventions for extrathoracic (ET) deposition into the anterior nasal passage (ET1) and the posterior nasal and oral passages (ET2). For this study, polyurethane foam was used as a collection substrate inside an inhalable aerosol sampler to provide an estimate of extrathoracic particle deposition. Aerosols of fused aluminum oxide (five sizes, 4.9 µm–44.3 µm) were used as a test dust in a low speed (0.2 m/s) wind tunnel. Samplers were placed on a rotating mannequin inside the wind tunnel to simulate orientation-averaged personal sampling. Collection efficiency data for the foam insert matched well to the extrathoracic deposition convention for the particle sizes tested. The concept of using a foam insert to match a particle deposition sampling convention was explored in this study and shows promise for future use as a sampling device. PMID:26959046

Summary and Synthesis: How to Present a Research Proposal.

PubMed

Setia, Maninder Singh; Panda, Saumya

2017-01-01

This concluding module attempts to synthesize the key learning points discussed during the course of the previous ten sets of modules on methodology and biostatistics. The objective of this module is to discuss how to present a model research proposal, based on whatever was discussed in the preceding modules. The lynchpin of a research proposal is the protocol, and the key component of a protocol is the study design. However, one must not neglect the other areas, be it the project summary through which one catches the eyes of the reviewer of the proposal, or the background and the literature review, or the aims and objectives of the study. Two critical areas in the "methods" section that cannot be emphasized more are the sampling strategy and a formal estimation of sample size. Without a legitimate sample size, none of the conclusions based on the statistical analysis would be valid. Finally, the ethical parameters of the study should be well understood by the researchers, and that should get reflected in the proposal.

Summary and Synthesis: How to Present a Research Proposal

PubMed Central

Setia, Maninder Singh; Panda, Saumya

2017-01-01

This concluding module attempts to synthesize the key learning points discussed during the course of the previous ten sets of modules on methodology and biostatistics. The objective of this module is to discuss how to present a model research proposal, based on whatever was discussed in the preceding modules. The lynchpin of a research proposal is the protocol, and the key component of a protocol is the study design. However, one must not neglect the other areas, be it the project summary through which one catches the eyes of the reviewer of the proposal, or the background and the literature review, or the aims and objectives of the study. Two critical areas in the “methods” section that cannot be emphasized more are the sampling strategy and a formal estimation of sample size. Without a legitimate sample size, none of the conclusions based on the statistical analysis would be valid. Finally, the ethical parameters of the study should be well understood by the researchers, and that should get reflected in the proposal. PMID:28979004

Mechanisms of Laser-Induced Dissection and Transport of Histologic Specimens

PubMed Central

Vogel, Alfred; Lorenz, Kathrin; Horneffer, Verena; Hüttmann, Gereon; von Smolinski, Dorthe; Gebert, Andreas

2007-01-01

Rapid contact- and contamination-free procurement of histologic material for proteomic and genomic analysis can be achieved by laser microdissection of the sample of interest followed by laser-induced transport (laser pressure catapulting). The dynamics of laser microdissection and laser pressure catapulting of histologic samples of 80 μm diameter was investigated by means of time-resolved photography. The working mechanism of microdissection was found to be plasma-mediated ablation initiated by linear absorption. Catapulting was driven by plasma formation when tightly focused pulses were used, and by photothermal ablation at the bottom of the sample when defocused pulses producing laser spot diameters larger than 35 μm were used. With focused pulses, driving pressures of several hundred MPa accelerated the specimen to initial velocities of 100–300 m/s before they were rapidly slowed down by air friction. When the laser spot was increased to a size comparable to or larger than the sample diameter, both driving pressure and flight velocity decreased considerably. Based on a characterization of the thermal and optical properties of the histologic specimens and supporting materials used, we calculated the evolution of the heat distribution in the sample. Selected catapulted samples were examined by scanning electron microscopy or analyzed by real-time reverse-transcriptase polymerase chain reaction. We found that catapulting of dissected samples results in little collateral damage when the laser pulses are either tightly focused or when the laser spot size is comparable to the specimen size. By contrast, moderate defocusing with spot sizes up to one-third of the specimen diameter may involve significant heat and ultraviolet exposure. Potential side effects are maximal when samples are catapulted directly from a glass slide without a supporting polymer foil. PMID:17766336

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.

Linear models for airborne-laser-scanning-based operational forest inventory with small field sample size and highly correlated LiDAR data

USGS Publications Warehouse

Junttila, Virpi; Kauranne, Tuomo; Finley, Andrew O.; Bradford, John B.

2015-01-01

Modern operational forest inventory often uses remotely sensed data that cover the whole inventory area to produce spatially explicit estimates of forest properties through statistical models. The data obtained by airborne light detection and ranging (LiDAR) correlate well with many forest inventory variables, such as the tree height, the timber volume, and the biomass. To construct an accurate model over thousands of hectares, LiDAR data must be supplemented with several hundred field sample measurements of forest inventory variables. This can be costly and time consuming. Different LiDAR-data-based and spatial-data-based sampling designs can reduce the number of field sample plots needed. However, problems arising from the features of the LiDAR data, such as a large number of predictors compared with the sample size (overfitting) or a strong correlation among predictors (multicollinearity), may decrease the accuracy and precision of the estimates and predictions. To overcome these problems, a Bayesian linear model with the singular value decomposition of predictors, combined with regularization, is proposed. The model performance in predicting different forest inventory variables is verified in ten inventory areas from two continents, where the number of field sample plots is reduced using different sampling designs. The results show that, with an appropriate field plot selection strategy and the proposed linear model, the total relative error of the predicted forest inventory variables is only 5%–15% larger using 50 field sample plots than the error of a linear model estimated with several hundred field sample plots when we sum up the error due to both the model noise variance and the model’s lack of fit.

Determination of the optimal sample size for a clinical trial accounting for the population size.

PubMed

Stallard, Nigel; Miller, Frank; Day, Simon; Hee, Siew Wan; Madan, Jason; Zohar, Sarah; Posch, Martin

2017-07-01

The problem of choosing a sample size for a clinical trial is a very common one. In some settings, such as rare diseases or other small populations, the large sample sizes usually associated with the standard frequentist approach may be infeasible, suggesting that the sample size chosen should reflect the size of the population under consideration. Incorporation of the population size is possible in a decision-theoretic approach either explicitly by assuming that the population size is fixed and known, or implicitly through geometric discounting of the gain from future patients reflecting the expected population size. This paper develops such approaches. Building on previous work, an asymptotic expression is derived for the sample size for single and two-arm clinical trials in the general case of a clinical trial with a primary endpoint with a distribution of one parameter exponential family form that optimizes a utility function that quantifies the cost and gain per patient as a continuous function of this parameter. It is shown that as the size of the population, N, or expected size, N∗ in the case of geometric discounting, becomes large, the optimal trial size is O(N1/2) or O(N∗1/2). The sample size obtained from the asymptotic expression is also compared with the exact optimal sample size in examples with responses with Bernoulli and Poisson distributions, showing that the asymptotic approximations can also be reasonable in relatively small sample sizes. © 2016 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Online versus offline: The Web as a medium for response time data collection.

PubMed

Chetverikov, Andrey; Upravitelev, Philipp

2016-09-01

The Internet provides a convenient environment for data collection in psychology. Modern Web programming languages, such as JavaScript or Flash (ActionScript), facilitate complex experiments without the necessity of experimenter presence. Yet there is always a question of how much noise is added due to the differences between the setups used by participants and whether it is compensated for by increased ecological validity and larger sample sizes. This is especially a problem for experiments that measure response times (RTs), because they are more sensitive (and hence more susceptible to noise) than, for example, choices per se. We used a simple visual search task with different set sizes to compare laboratory performance with Web performance. The results suggest that although the locations (means) of RT distributions are different, other distribution parameters are not. Furthermore, the effect of experiment setting does not depend on set size, suggesting that task difficulty is not important in the choice of a data collection method. We also collected an additional online sample to investigate the effects of hardware and software diversity on the accuracy of RT data. We found that the high diversity of browsers, operating systems, and CPU performance may have a detrimental effect, though it can partly be compensated for by increased sample sizes and trial numbers. In sum, the findings show that Web-based experiments are an acceptable source of RT data, comparable to a common keyboard-based setup in the laboratory.

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.

[Potentials in the regionalization of health indicators using small-area estimation methods : Exemplary results based on the 2009, 2010 and 2012 GEDA studies].

PubMed

Kroll, Lars Eric; Schumann, Maria; Müters, Stephan; Lampert, Thomas

2017-12-01

Nationwide health surveys can be used to estimate regional differences in health. Using traditional estimation techniques, the spatial depth for these estimates is limited due to the constrained sample size. So far - without special refreshment samples - results have only been available for larger populated federal states of Germany. An alternative is regression-based small-area estimation techniques. These models can generate smaller-scale data, but are also subject to greater statistical uncertainties because of the model assumptions. In the present article, exemplary regionalized results based on the studies "Gesundheit in Deutschland aktuell" (GEDA studies) 2009, 2010 and 2012, are compared to the self-rated health status of the respondents. The aim of the article is to analyze the range of regional estimates in order to assess the usefulness of the techniques for health reporting more adequately. The results show that the estimated prevalence is relatively stable when using different samples. Important determinants of the variation of the estimates are the achieved sample size on the district level and the type of the district (cities vs. rural regions). Overall, the present study shows that small-area modeling of prevalence is associated with additional uncertainties compared to conventional estimates, which should be taken into account when interpreting the corresponding findings.

Accounting for parameter uncertainty in the definition of parametric distributions used to describe individual patient variation in health economic models.

PubMed

Degeling, Koen; IJzerman, Maarten J; Koopman, Miriam; Koffijberg, Hendrik

2017-12-15

Parametric distributions based on individual patient data can be used to represent both stochastic and parameter uncertainty. Although general guidance is available on how parameter uncertainty should be accounted for in probabilistic sensitivity analysis, there is no comprehensive guidance on reflecting parameter uncertainty in the (correlated) parameters of distributions used to represent stochastic uncertainty in patient-level models. This study aims to provide this guidance by proposing appropriate methods and illustrating the impact of this uncertainty on modeling outcomes. Two approaches, 1) using non-parametric bootstrapping and 2) using multivariate Normal distributions, were applied in a simulation and case study. The approaches were compared based on point-estimates and distributions of time-to-event and health economic outcomes. To assess sample size impact on the uncertainty in these outcomes, sample size was varied in the simulation study and subgroup analyses were performed for the case-study. Accounting for parameter uncertainty in distributions that reflect stochastic uncertainty substantially increased the uncertainty surrounding health economic outcomes, illustrated by larger confidence ellipses surrounding the cost-effectiveness point-estimates and different cost-effectiveness acceptability curves. Although both approaches performed similar for larger sample sizes (i.e. n = 500), the second approach was more sensitive to extreme values for small sample sizes (i.e. n = 25), yielding infeasible modeling outcomes. Modelers should be aware that parameter uncertainty in distributions used to describe stochastic uncertainty needs to be reflected in probabilistic sensitivity analysis, as it could substantially impact the total amount of uncertainty surrounding health economic outcomes. If feasible, the bootstrap approach is recommended to account for this uncertainty.

Discerning some Tylenol brands using attenuated total reflection Fourier transform infrared data and multivariate analysis techniques.

PubMed

Msimanga, Huggins Z; Ollis, Robert J

2010-06-01

Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were used to classify acetaminophen-containing medicines using their attenuated total reflection Fourier transform infrared (ATR-FT-IR) spectra. Four formulations of Tylenol (Arthritis Pain Relief, Extra Strength Pain Relief, 8 Hour Pain Relief, and Extra Strength Pain Relief Rapid Release) along with 98% pure acetaminophen were selected for this study because of the similarity of their spectral features, with correlation coefficients ranging from 0.9857 to 0.9988. Before acquiring spectra for the predictor matrix, the effects on spectral precision with respect to sample particle size (determined by sieve size opening), force gauge of the ATR accessory, sample reloading, and between-tablet variation were examined. Spectra were baseline corrected and normalized to unity before multivariate analysis. Analysis of variance (ANOVA) was used to study spectral precision. The large particles (35 mesh) showed large variance between spectra, while fine particles (120 mesh) indicated good spectral precision based on the F-test. Force gauge setting did not significantly affect precision. Sample reloading using the fine particle size and a constant force gauge setting of 50 units also did not compromise precision. Based on these observations, data acquisition for the predictor matrix was carried out with the fine particles (sieve size opening of 120 mesh) at a constant force gauge setting of 50 units. After removing outliers, PCA successfully classified the five samples in the first and second components, accounting for 45.0% and 24.5% of the variances, respectively. The four-component PLS-DA model (R(2)=0.925 and Q(2)=0.906) gave good test spectra predictions with an overall average of 0.961 +/- 7.1% RSD versus the expected 1.0 prediction for the 20 test spectra used.

Microgravity

NASA Image and Video Library

2001-01-24

Typical metal sample that was processed by TEMPUS (Tiegelfreies Elektromagnetisches Prozessieren Unter Schwerelosigkeit), an electromagnetic levitation facility developed by German researchers and flown on the IML-2 and MSL-1 and 1R Spacelab missions. Electromagnetic levitation is used commonly in ground-based experiments to melt and then cool metallic melts below their freezing points without solidification occurring. Sample size is limited in ground-based experiments. Research with TEMPUS aboard Spacelab allowed scientists to study the viscosity, surface tension, and other properties of several metals and alloys while undercooled (i.e., cooled below their normal solidification points). The sample is about 1 cm (2/5 inch) in diameter.

The Influence of Mark-Recapture Sampling Effort on Estimates of Rock Lobster Survival

PubMed Central

Kordjazi, Ziya; Frusher, Stewart; Buxton, Colin; Gardner, Caleb; Bird, Tomas

2016-01-01

Five annual capture-mark-recapture surveys on Jasus edwardsii were used to evaluate the effect of sample size and fishing effort on the precision of estimated survival probability. Datasets of different numbers of individual lobsters (ranging from 200 to 1,000 lobsters) were created by random subsampling from each annual survey. This process of random subsampling was also used to create 12 datasets of different levels of effort based on three levels of the number of traps (15, 30 and 50 traps per day) and four levels of the number of sampling-days (2, 4, 6 and 7 days). The most parsimonious Cormack-Jolly-Seber (CJS) model for estimating survival probability shifted from a constant model towards sex-dependent models with increasing sample size and effort. A sample of 500 lobsters or 50 traps used on four consecutive sampling-days was required for obtaining precise survival estimations for males and females, separately. Reduced sampling effort of 30 traps over four sampling days was sufficient if a survival estimate for both sexes combined was sufficient for management of the fishery. PMID:26990561

Sample size calculations for randomized clinical trials published in anesthesiology journals: a comparison of 2010 versus 2016.

PubMed

Chow, Jeffrey T Y; Turkstra, Timothy P; Yim, Edmund; Jones, Philip M

2018-06-01

Although every randomized clinical trial (RCT) needs participants, determining the ideal number of participants that balances limited resources and the ability to detect a real effect is difficult. Focussing on two-arm, parallel group, superiority RCTs published in six general anesthesiology journals, the objective of this study was to compare the quality of sample size calculations for RCTs published in 2010 vs 2016. Each RCT's full text was searched for the presence of a sample size calculation, and the assumptions made by the investigators were compared with the actual values observed in the results. Analyses were only performed for sample size calculations that were amenable to replication, defined as using a clearly identified outcome that was continuous or binary in a standard sample size calculation procedure. The percentage of RCTs reporting all sample size calculation assumptions increased from 51% in 2010 to 84% in 2016. The difference between the values observed in the study and the expected values used for the sample size calculation for most RCTs was usually > 10% of the expected value, with negligible improvement from 2010 to 2016. While the reporting of sample size calculations improved from 2010 to 2016, the expected values in these sample size calculations often assumed effect sizes larger than those actually observed in the study. Since overly optimistic assumptions may systematically lead to underpowered RCTs, improvements in how to calculate and report sample sizes in anesthesiology research are needed.

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.

Valid approximation of spatially distributed grain size distributions - A priori information encoded to a feedforward network

NASA Astrophysics Data System (ADS)

Berthold, T.; Milbradt, P.; Berkhahn, V.

2018-04-01

This paper presents a model for the approximation of multiple, spatially distributed grain size distributions based on a feedforward neural network. Since a classical feedforward network does not guarantee to produce valid cumulative distribution functions, a priori information is incor porated into the model by applying weight and architecture constraints. The model is derived in two steps. First, a model is presented that is able to produce a valid distribution function for a single sediment sample. Although initially developed for sediment samples, the model is not limited in its application; it can also be used to approximate any other multimodal continuous distribution function. In the second part, the network is extended in order to capture the spatial variation of the sediment samples that have been obtained from 48 locations in the investigation area. Results show that the model provides an adequate approximation of grain size distributions, satisfying the requirements of a cumulative distribution function.

Effect of particle size and dopant concentration on photophysical properties of Eu3+-doped rare earth oxysulphide phosphor coatings.

PubMed

Chakradhar, R P S; Basu, Bharathibai J; Lakshmi, R V

2011-02-01

Europium-doped rare-earth oxysulphides (red phosphors) are often used as reference luminophore in pyrene-based pressure sensor coatings for aerodynamic applications. Different red phosphor samples were characterized for their particle size, chemical composition, photoluminescent properties and temperature sensitivity. The red phosphor samples were characterized using energy-dispersive X-ray spectroscopy (EDX) for elemental analysis and scanning electron microscopy (SEM) for morphology and particle size measurement. The particle size was in the range of 1.5-5.7 μm with morphology of hexagonal or spherical shape. It was found that phosphor with higher europium content exhibited higher luminescent emission intensity. The phosphor coatings were prepared by spraying a dispersion of the material in silicone resin. Smooth coatings were obtained by using phosphor samples with smaller particle size. Upon 334 nm excitation, the coatings showed characteristic luminescence 5D0→7FJ (J=0, 1, 2, 3, 4) of the Eu3+ ions. The electronic transition located at 626 nm (5D0→7F2) of Eu3+ ions was stronger than the magnetic dipole transition located at 595 nm (5D0→7F1). Luminescence decay curves obeyed double exponential behaviour. The phosphor samples showed temperature sensitivity of -0.012 to -0.168%/°C in the temperature range of 25-50 °C. Copyright © 2010 Elsevier B.V. All rights reserved.

Operationalizing hippocampal volume as an enrichment biomarker for amnestic mild cognitive impairment trials: effect of algorithm, test-retest variability, and cut point on trial cost, duration, and sample size.

PubMed

Yu, Peng; Sun, Jia; Wolz, Robin; Stephenson, Diane; Brewer, James; Fox, Nick C; Cole, Patricia E; Jack, Clifford R; Hill, Derek L G; Schwarz, Adam J

2014-04-01

The objective of this study was to evaluate the effect of computational algorithm, measurement variability, and cut point on hippocampal volume (HCV)-based patient selection for clinical trials in mild cognitive impairment (MCI). We used normal control and amnestic MCI subjects from the Alzheimer's Disease Neuroimaging Initiative 1 (ADNI-1) as normative reference and screening cohorts. We evaluated the enrichment performance of 4 widely used hippocampal segmentation algorithms (FreeSurfer, Hippocampus Multi-Atlas Propagation and Segmentation (HMAPS), Learning Embeddings Atlas Propagation (LEAP), and NeuroQuant) in terms of 2-year changes in Mini-Mental State Examination (MMSE), Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog), and Clinical Dementia Rating Sum of Boxes (CDR-SB). We modeled the implications for sample size, screen fail rates, and trial cost and duration. HCV based patient selection yielded reduced sample sizes (by ∼40%-60%) and lower trial costs (by ∼30%-40%) across a wide range of cut points. These results provide a guide to the choice of HCV cut point for amnestic MCI clinical trials, allowing an informed tradeoff between statistical and practical considerations. Copyright © 2014 Elsevier Inc. All rights reserved.

Improving the Selection, Classification, and Utilization of Army Enlisted Personnel. Project A: Research Plan

DTIC Science & Technology

1983-05-01

occur. 4) It is also true that during a given time period, at a given base, not all of the people in the sample will actually be available for testing...taken sample sizes into consideration, we currently estimate that with few exceptions, we will have adequate samples to perform the analysis of simple ...aalanced Half Sample Repli- cations (BHSA). His analyses of simple cases have shown that this method is substantially more efficient than the

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...

Local reconstruction in computed tomography of diffraction enhanced imaging

NASA Astrophysics Data System (ADS)

Huang, Zhi-Feng; Zhang, Li; Kang, Ke-Jun; Chen, Zhi-Qiang; Zhu, Pei-Ping; Yuan, Qing-Xi; Huang, Wan-Xia

2007-07-01

Computed tomography of diffraction enhanced imaging (DEI-CT) based on synchrotron radiation source has extremely high sensitivity of weakly absorbing low-Z samples in medical and biological fields. The authors propose a modified backprojection filtration(BPF)-type algorithm based on PI-line segments to reconstruct region of interest from truncated refraction-angle projection data in DEI-CT. The distribution of refractive index decrement in the sample can be directly estimated from its reconstruction images, which has been proved by experiments at the Beijing Synchrotron Radiation Facility. The algorithm paves the way for local reconstruction of large-size samples by the use of DEI-CT with small field of view based on synchrotron radiation source.

Investigating the unification of LOFAR-detected powerful AGN in the Boötes field

NASA Astrophysics Data System (ADS)

Morabito, Leah K.; Williams, W. L.; Duncan, Kenneth J.; Röttgering, H. J. A.; Miley, George; Saxena, Aayush; Barthel, Peter; Best, P. N.; Bruggen, M.; Brunetti, G.; Chyży, K. T.; Engels, D.; Hardcastle, M. J.; Harwood, J. J.; Jarvis, Matt J.; Mahony, E. K.; Prandoni, I.; Shimwell, T. W.; Shulevski, A.; Tasse, C.

2017-08-01

Low radio frequency surveys are important for testing unified models of radio-loud quasars and radio galaxies. Intrinsically similar sources that are randomly oriented on the sky will have different projected linear sizes. Measuring the projected linear sizes of these sources provides an indication of their orientation. Steep-spectrum isotropic radio emission allows for orientation-free sample selection at low radio frequencies. We use a new radio survey of the Boötes field at 150 MHz made with the Low-Frequency Array (LOFAR) to select a sample of radio sources. We identify 60 radio sources with powers P > 1025.5 W Hz-1 at 150 MHz using cross-matched multiwavelength information from the AGN and Galaxy Evolution Survey, which provides spectroscopic redshifts and photometric identification of 16 quasars and 44 radio galaxies. When considering the radio spectral slope only, we find that radio sources with steep spectra have projected linear sizes that are on average 4.4 ± 1.4 larger than those with flat spectra. The projected linear sizes of radio galaxies are on average 3.1 ± 1.0 larger than those of quasars (2.0 ± 0.3 after correcting for redshift evolution). Combining these results with three previous surveys, we find that the projected linear sizes of radio galaxies and quasars depend on redshift but not on power. The projected linear size ratio does not correlate with either parameter. The LOFAR data are consistent within the uncertainties with theoretical predictions of the correlation between the quasar fraction and linear size ratio, based on an orientation-based unification scheme.

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...

The Risk of Adverse Impact in Selections Based on a Test with Known Effect Size

ERIC Educational Resources Information Center

De Corte, Wilfried; Lievens, Filip

2005-01-01

The authors derive the exact sampling distribution function of the adverse impact (AI) ratio for single-stage, top-down selections using tests with known effect sizes. Subsequently, it is shown how this distribution function can be used to determine the risk that a future selection decision on the basis of such tests will result in an outcome that…

Wafer scale formation of monocrystalline silicon-based Mie resonators via silicon-on-insulator dewetting.

PubMed

Abbarchi, Marco; Naffouti, Meher; Vial, Benjamin; Benkouider, Abdelmalek; Lermusiaux, Laurent; Favre, Luc; Ronda, Antoine; Bidault, Sébastien; Berbezier, Isabelle; Bonod, Nicolas

2014-11-25

Subwavelength-sized dielectric Mie resonators have recently emerged as a promising photonic platform, as they combine the advantages of dielectric microstructures and metallic nanoparticles supporting surface plasmon polaritons. Here, we report the capabilities of a dewetting-based process, independent of the sample size, to fabricate Si-based resonators over large scales starting from commercial silicon-on-insulator (SOI) substrates. Spontaneous dewetting is shown to allow the production of monocrystalline Mie-resonators that feature two resonant modes in the visible spectrum, as observed in confocal scattering spectroscopy. Homogeneous scattering responses and improved spatial ordering of the Si-based resonators are observed when dewetting is assisted by electron beam lithography. Finally, exploiting different thermal agglomeration regimes, we highlight the versatility of this technique, which, when assisted by focused ion beam nanopatterning, produces monocrystalline nanocrystals with ad hoc size, position, and organization in complex multimers.

Recent Structural Evolution of Early-Type Galaxies: Size Growth from z = 1 to z = 0

NASA Astrophysics Data System (ADS)

van der Wel, Arjen; Holden, Bradford P.; Zirm, Andrew W.; Franx, Marijn; Rettura, Alessandro; Illingworth, Garth D.; Ford, Holland C.

2008-11-01

Strong size and internal density evolution of early-type galaxies between z ~ 2 and the present has been reported by several authors. Here we analyze samples of nearby and distant (z ~ 1) galaxies with dynamically measured masses in order to confirm the previous, model-dependent results and constrain the uncertainties that may play a role. Velocity dispersion (σ) measurements are taken from the literature for 50 morphologically selected 0.8 < z < 1.2 field and cluster early-type galaxies with typical masses Mdyn = 2 × 1011 M⊙. Sizes (Reff) are determined with Advanced Camera for Surveys imaging. We compare the distant sample with a large sample of nearby (0.04 < z < 0.08) early-type galaxies extracted from the Sloan Digital Sky Survey for which we determine sizes, masses, and densities in a consistent manner, using simulations to quantify systematic differences between the size measurements of nearby and distant galaxies. We find a highly significant difference between the σ - Reff distributions of the nearby and distant samples, regardless of sample selection effects. The implied evolution in Reff at fixed mass between z = 1 and the present is a factor of 1.97 +/- 0.15. This is in qualitative agreement with semianalytic models; however, the observed evolution is much faster than the predicted evolution. Our results reinforce and are quantitatively consistent with previous, photometric studies that found size evolution of up to a factor of 5 since z ~ 2. A combination of structural evolution of individual galaxies through the accretion of companions and the continuous formation of early-type galaxies through increasingly gas-poor mergers is one plausible explanation of the observations. Based on observations with the Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by AURA, Inc., under NASA contract NAS5-26555, and observations made with the Spitzer Space Telescope, which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under NASA contract 1407. Based on observations collected at the European Southern Observatory, Chile (169.A-0458). Some of the data presented herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California and the National Aeronautics and Space Administration. The Observatory was made possible by the generous financial support of the W.M. Keck Foundation.

[Association between productivity, list size, patient and practice characteristics in general practice].

PubMed

Olsen, Kim Rose; Sørensen, Torben Højmark; Gyrd-Hansen, Dorte

2010-04-19

Due to shortage of general practitioners, it may be necessary to improve productivity. We assess the association between productivity, list size and patient- and practice characteristics. A regression approach is used to perform productivity analysis based on national register data and survey data for 1,758 practices. Practices are divided into four groups according to list size and productivity. Statistical tests are used to assess differences in patient- and practice characteristics. There is a significant, positive correlation between list size and productivity (p < 0.01). Nevertheless, 19% of the practices have a list size below and a productivity above mean sample values. These practices have relatively demanding patients (older, low socioeconomic status, high use of pharmaceuticals) and they are frequently located in areas with limited access to specialized care and have a low use of assisting personnel. 13% of the practices have a list size above and a productivity below mean sample values. These practices have relatively less demanding patients, are located in areas with good access to specialized care, and have a high use of assisting personnel. Lists and practice characteristics have substantial influence on both productivity and list size. Adjusting list size to external factors seems to be an effective tool to increase productivity in general practice.

Analysis of methods commonly used in biomedicine for treatment versus control comparison of very small samples.

PubMed

Ristić-Djurović, Jasna L; Ćirković, Saša; Mladenović, Pavle; Romčević, Nebojša; Trbovich, Alexander M

2018-04-01

A rough estimate indicated that use of samples of size not larger than ten is not uncommon in biomedical research and that many of such studies are limited to strong effects due to sample sizes smaller than six. For data collected from biomedical experiments it is also often unknown if mathematical requirements incorporated in the sample comparison methods are satisfied. Computer simulated experiments were used to examine performance of methods for qualitative sample comparison and its dependence on the effectiveness of exposure, effect intensity, distribution of studied parameter values in the population, and sample size. The Type I and Type II errors, their average, as well as the maximal errors were considered. The sample size 9 and the t-test method with p = 5% ensured error smaller than 5% even for weak effects. For sample sizes 6-8 the same method enabled detection of weak effects with errors smaller than 20%. If the sample sizes were 3-5, weak effects could not be detected with an acceptable error; however, the smallest maximal error in the most general case that includes weak effects is granted by the standard error of the mean method. The increase of sample size from 5 to 9 led to seven times more accurate detection of weak effects. Strong effects were detected regardless of the sample size and method used. The minimal recommended sample size for biomedical experiments is 9. Use of smaller sizes and the method of their comparison should be justified by the objective of the experiment. Copyright © 2018 Elsevier B.V. All rights reserved.

Plasma asymmetric dimethylarginine, L-arginine and Left Ventricular Structure and Function in a Community-based Sample

PubMed Central

Lieb, Wolfgang; Benndorf, Ralf A.; Benjamin, Emelia J.; Sullivan, Lisa M.; Maas, Renke; Xanthakis, Vanessa; Schwedhelm, Edzard; Aragam, Jayashri; Schulze, Friedrich; Böger, Rainer H.; Vasan, Ramachandran S.

2009-01-01

Objective Increasing evidence indicates that cardiac structure and function are modulated by the nitric oxide (NO) system. Elevated plasma concentrations of asymmetric dimethylarginine (ADMA; a competitive inhibitor of NO synthase) have been reported in patients with end-stage renal disease. It is unclear if circulating ADMA and L-arginine levels are related to cardiac structure and function in the general population. Methods We related plasma ADMA and L-Arginine (the amino acid precursor of NO) to echocardiographic left ventricular (LV) mass, left atrial (LA) size and fractional shortening (FS) using multivariable linear regression analyses in 1,919 Framingham Offspring Study participants (mean age 57 years, 58 % women). Results Overall, neither ADMA or L-arginine, nor their ratio was associated with LV mass, LA size and FS in multivariable models (p>0.10 for all). However, we observed effect modification by obesity of the relations of ADMA and LA size (p for interaction p=0.04): ADMA was positively related to LA size in obese individuals (adjusted-p=0.0004 for trend across ADMA quartiles) but not in non-obese people. Conclusion In our large community-based sample, plasma ADMA and L-arginine concentrations were not related to cardiac structure or function. The observation of positive relations of LA size and ADMA in obese individuals warrants confirmation. PMID:18829028

Development and experimental study of large size composite plasma immersion ion implantation device

NASA Astrophysics Data System (ADS)

Falun, SONG; Fei, LI; Mingdong, ZHU; Langping, WANG; Beizhen, ZHANG; Haitao, GONG; Yanqing, GAN; Xiao, JIN

2018-01-01

Plasma immersion ion implantation (PIII) overcomes the direct exposure limit of traditional beam-line ion implantation, and is suitable for the treatment of complex work-piece with large size. PIII technology is often used for surface modification of metal, plastics and ceramics. Based on the requirement of surface modification of large size insulating material, a composite full-directional PIII device based on RF plasma source and metal plasma source is developed in this paper. This device can not only realize gas ion implantation, but also can realize metal ion implantation, and can also realize gas ion mixing with metal ions injection. This device has two metal plasma sources and each metal source contains three cathodes. Under the condition of keeping the vacuum unchanged, the cathode can be switched freely. The volume of the vacuum chamber is about 0.94 m3, and maximum vacuum degree is about 5 × 10-4 Pa. The density of RF plasma in homogeneous region is about 109 cm-3, and plasma density in the ion implantation region is about 1010 cm-3. This device can be used for large-size sample material PIII treatment, the maximum size of the sample diameter up to 400 mm. The experimental results show that the plasma discharge in the device is stable and can run for a long time. It is suitable for surface treatment of insulating materials.

Introduction to Permutation and Resampling-Based Hypothesis Tests

ERIC Educational Resources Information Center

LaFleur, Bonnie J.; Greevy, Robert A.

2009-01-01

A resampling-based method of inference--permutation tests--is often used when distributional assumptions are questionable or unmet. Not only are these methods useful for obvious departures from parametric assumptions (e.g., normality) and small sample sizes, but they are also more robust than their parametric counterparts in the presences of…

Key Roles of Size and Crystallinity of Nanosized Iron Hydr(oxides) Stabilized by Humic Substances in Iron Bioavailability to Plants.

PubMed

Kulikova, Natalia A; Polyakov, Alexander Yu; Lebedev, Vasily A; Abroskin, Dmitry P; Volkov, Dmitry S; Pankratov, Denis A; Klein, Olga I; Senik, Svetlana V; Sorkina, Tatiana A; Garshev, Alexey V; Veligzhanin, Alexey A; Garcia Mina, Jose M; Perminova, Irina V

2017-12-27

Availability of Fe in soil to plants is closely related to the presence of humic substances (HS). Still, the systematic data on applicability of iron-based nanomaterials stabilized with HS as a source for plant nutrition are missing. The goal of our study was to establish a connection between properties of iron-based materials stabilized by HS and their bioavailability to plants. We have prepared two samples of leonardite HS-stabilized iron-based materials with substantially different properties using the reported protocols and studied their physical chemical state in relation to iron uptake and other biological effects. We used Mössbauer spectroscopy, XRD, SAXS, and TEM to conclude on iron speciation, size, and crystallinity. One material (Fe-HA) consisted of polynuclear iron(III) (hydr)oxide complexes, so-called ferric polymers, distributed in HS matrix. These complexes are composed of predominantly amorphous small-size components (<5 nm) with inclusions of larger crystalline particles (the mean size of (11 ± 4) nm). The other material was composed of well-crystalline feroxyhyte (δ'-FeOOH) NPs with mean transverse sizes of (35 ± 20) nm stabilized by small amounts of HS. Bioavailability studies were conducted on wheat plants under conditions of iron deficiency. The uptake studies have shown that small and amorphous ferric polymers were readily translocated into the leaves on the level of Fe-EDTA, whereas relatively large and crystalline feroxyhyte NPs were mostly sorbed on the roots. The obtained data are consistent with the size exclusion limits of cell wall pores (5-20 nm). Both samples demonstrated distinct beneficial effects with respect to photosynthetic activity and lipid biosynthesis. The obtained results might be of use for production of iron-based nanomaterials stabilized by HS with the tailored iron availability to plants. They can be applied as the only source for iron nutrition as well as in combination with the other elements, for example, for industrial production of "nanofortified" macrofertilizers (NPK).

Using pilot data to size a two-arm randomized trial to find a nearly optimal personalized treatment strategy.

PubMed

Laber, Eric B; Zhao, Ying-Qi; Regh, Todd; Davidian, Marie; Tsiatis, Anastasios; Stanford, Joseph B; Zeng, Donglin; Song, Rui; Kosorok, Michael R

2016-04-15

A personalized treatment strategy formalizes evidence-based treatment selection by mapping patient information to a recommended treatment. Personalized treatment strategies can produce better patient outcomes while reducing cost and treatment burden. Thus, among clinical and intervention scientists, there is a growing interest in conducting randomized clinical trials when one of the primary aims is estimation of a personalized treatment strategy. However, at present, there are no appropriate sample size formulae to assist in the design of such a trial. Furthermore, because the sampling distribution of the estimated outcome under an estimated optimal treatment strategy can be highly sensitive to small perturbations in the underlying generative model, sample size calculations based on standard (uncorrected) asymptotic approximations or computer simulations may not be reliable. We offer a simple and robust method for powering a single stage, two-armed randomized clinical trial when the primary aim is estimating the optimal single stage personalized treatment strategy. The proposed method is based on inverting a plugin projection confidence interval and is thereby regular and robust to small perturbations of the underlying generative model. The proposed method requires elicitation of two clinically meaningful parameters from clinical scientists and uses data from a small pilot study to estimate nuisance parameters, which are not easily elicited. The method performs well in simulated experiments and is illustrated using data from a pilot study of time to conception and fertility awareness. Copyright © 2015 John Wiley & Sons, Ltd.

Measuring size evolution of distant, faint galaxies in the radio regime

NASA Astrophysics Data System (ADS)

Lindroos, L.; Knudsen, K. K.; Stanley, F.; Muxlow, T. W. B.; Beswick, R. J.; Conway, J.; Radcliffe, J. F.; Wrigley, N.

2018-05-01

We measure the evolution of sizes for star-forming galaxies as seen in 1.4 GHz continuum radio for z = 0-3. The measurements are based on combined VLA+MERLIN data of the Hubble Deep Field, and using a uv-stacking algorithm combined with model fitting to estimate the average sizes of galaxies. A sample of ˜1000 star-forming galaxies is selected from optical and near-infrared catalogues, with stellar masses M⊙ ≈ 1010-1011 M⊙ and photometric redshifts 0-3. The median sizes are parametrized for stellar mass M* = 5 × 1010 M⊙ as R_e = A× {}(H(z)/H(1.5))^{α _z}. We find that the median radio sizes evolve towards larger sizes at later times with αz = -1.1 ± 0.6, and A (the median size at z ≈ 1.5) is found to be 0.26^'' ± 0.07^'' or 2.3±0.6 kpc. The measured radio sizes are typically a factor of 2 smaller than those measure in the optical, and are also smaller than the typical H α sizes in the literature. This indicates that star formation, as traced by the radio continuum, is typically concentrated towards the centre of galaxies, for the sampled redshift range. Furthermore, the discrepancy of measured sizes from different tracers of star formation, indicates the need for models of size evolution to adopt a multiwavelength approach in the measurement of the sizes star-forming regions.

Cancer classification through filtering progressive transductive support vector machine based on gene expression data

NASA Astrophysics Data System (ADS)

Lu, Xinguo; Chen, Dan

2017-08-01

Traditional supervised classifiers neglect a large amount of data which not have sufficient follow-up information, only work with labeled data. Consequently, the small sample size limits the advancement of design appropriate classifier. In this paper, a transductive learning method which combined with the filtering strategy in transductive framework and progressive labeling strategy is addressed. The progressive labeling strategy does not need to consider the distribution of labeled samples to evaluate the distribution of unlabeled samples, can effective solve the problem of evaluate the proportion of positive and negative samples in work set. Our experiment result demonstrate that the proposed technique have great potential in cancer prediction based on gene expression.

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.

Using known populations of pronghorn to evaluate sampling plans and estimators

USGS Publications Warehouse

Kraft, K.M.; Johnson, D.H.; Samuelson, J.M.; Allen, S.H.

1995-01-01

Although sampling plans and estimators of abundance have good theoretical properties, their performance in real situations is rarely assessed because true population sizes are unknown. We evaluated widely used sampling plans and estimators of population size on 3 known clustered distributions of pronghorn (Antilocapra americana). Our criteria were accuracy of the estimate, coverage of 95% confidence intervals, and cost. Sampling plans were combinations of sampling intensities (16, 33, and 50%), sample selection (simple random sampling without replacement, systematic sampling, and probability proportional to size sampling with replacement), and stratification. We paired sampling plans with suitable estimators (simple, ratio, and probability proportional to size). We used area of the sampling unit as the auxiliary variable for the ratio and probability proportional to size estimators. All estimators were nearly unbiased, but precision was generally low (overall mean coefficient of variation [CV] = 29). Coverage of 95% confidence intervals was only 89% because of the highly skewed distribution of the pronghorn counts and small sample sizes, especially with stratification. Stratification combined with accurate estimates of optimal stratum sample sizes increased precision, reducing the mean CV from 33 without stratification to 25 with stratification; costs increased 23%. Precise results (mean CV = 13) but poor confidence interval coverage (83%) were obtained with simple and ratio estimators when the allocation scheme included all sampling units in the stratum containing most pronghorn. Although areas of the sampling units varied, ratio estimators and probability proportional to size sampling did not increase precision, possibly because of the clumped distribution of pronghorn. Managers should be cautious in using sampling plans and estimators to estimate abundance of aggregated populations.

On sample size and different interpretations of snow stability datasets

NASA Astrophysics Data System (ADS)

Schirmer, M.; Mitterer, C.; Schweizer, J.

2009-04-01

Interpretations of snow stability variations need an assessment of the stability itself, independent of the scale investigated in the study. Studies on stability variations at a regional scale have often chosen stability tests such as the Rutschblock test or combinations of various tests in order to detect differences in aspect and elevation. The question arose: ‘how capable are such stability interpretations in drawing conclusions'. There are at least three possible errors sources: (i) the variance of the stability test itself; (ii) the stability variance at an underlying slope scale, and (iii) that the stability interpretation might not be directly related to the probability of skier triggering. Various stability interpretations have been proposed in the past that provide partly different results. We compared a subjective one based on expert knowledge with a more objective one based on a measure derived from comparing skier-triggered slopes vs. slopes that have been skied but not triggered. In this study, the uncertainties are discussed and their effects on regional scale stability variations will be quantified in a pragmatic way. An existing dataset with very large sample sizes was revisited. This dataset contained the variance of stability at a regional scale for several situations. The stability in this dataset was determined using the subjective interpretation scheme based on expert knowledge. The question to be answered was how many measurements were needed to obtain similar results (mainly stability differences in aspect or elevation) as with the complete dataset. The optimal sample size was obtained in several ways: (i) assuming a nominal data scale the sample size was determined with a given test, significance level and power, and by calculating the mean and standard deviation of the complete dataset. With this method it can also be determined if the complete dataset consists of an appropriate sample size. (ii) Smaller subsets were created with similar aspect distributions to the large dataset. We used 100 different subsets for each sample size. Statistical variations obtained in the complete dataset were also tested on the smaller subsets using the Mann-Whitney or the Kruskal-Wallis test. For each subset size, the number of subsets were counted in which the significance level was reached. For these tests no nominal data scale was assumed. (iii) For the same subsets described above, the distribution of the aspect median was determined. A count of how often this distribution was substantially different from the distribution obtained with the complete dataset was made. Since two valid stability interpretations were available (an objective and a subjective interpretation as described above), the effect of the arbitrary choice of the interpretation on spatial variability results was tested. In over one third of the cases the two interpretations came to different results. The effect of these differences were studied in a similar method as described in (iii): the distribution of the aspect median was determined for subsets of the complete dataset using both interpretations, compared against each other as well as to the results of the complete dataset. For the complete dataset the two interpretations showed mainly identical results. Therefore the subset size was determined from the point at which the results of the two interpretations converged. A universal result for the optimal subset size cannot be presented since results differed between different situations contained in the dataset. The optimal subset size is thus dependent on stability variation in a given situation, which is unknown initially. There are indications that for some situations even the complete dataset might be not large enough. At a subset size of approximately 25, the significant differences between aspect groups (as determined using the whole dataset) were only obtained in one out of five situations. In some situations, up to 20% of the subsets showed a substantially different distribution of the aspect median. Thus, in most cases, 25 measurements (which can be achieved by six two-person teams in one day) did not allow to draw reliable conclusions.

Class size as related to the use of technology, educational practices, and outcomes in Web-based nursing courses.

PubMed

Burruss, Nancy M; Billings, Diane M; Brownrigg, Vicki; Skiba, Diane J; Connors, Helen R

2009-01-01

With the expanding numbers of nursing students enrolled in Web-based courses and the shortage of faculty, class sizes are increasing. This exploratory descriptive study examined class size in relation to the use of technology and to particular educational practices and outcomes. The sample consisted of undergraduate (n = 265) and graduate (n = 863) students enrolled in fully Web-based nursing courses. The Evaluating Educational Uses of Web-based Courses in Nursing survey (Billings, D., Connors, H., Skiba, D. (2001). Benchmarking best practices in Web-based nursing courses. Advances in Nursing Science, 23, 41--52) and the Social Presence Scale (Gunawardena, C. N., Zittle, F. J. (1997). Social presence as a predictor of satisfaction within a computer-mediated conferencing environment. The American Journal of Distance Education, 11, 9-26.) were used to gather data about the study variables. Class sizes were defined as very small (1 to 10 students), small (11 to 20 students), medium (21 to 30 students), large (31 to 40 students), and very large (41 students and above). Descriptive and inferential statistics were used to analyze the data. There were significant differences by class size in students' perceptions of active participation in learning, student-faculty interaction, peer interaction, and connectedness. Some differences by class size between undergraduate and graduate students were also found, and these require further study.

In situ synchrotron investigation of grain growth behavior of nano-grained UO 2

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

Miao, Yinbin; Yao, Tiankai; Lian, Jie

Here, we report on the study of grain growth kinetics in nano-grained UO 2 samples. Dense nano-grained UO 2 samples with well-controlled stoichiometry and grain size were fabricated using the spark plasma sintering technique. To determine the grain growth kinetics at elevated temperatures, a synchrotron wide-angle X-ray scattering (WAXS) study was performed in situ to measure the real-time grain size evolution based on the modified Williamson-Hall analysis. The unique grain growth kinetics of nanocrystalline UO 2 at 730 °C and 820 °C were observed and explained by the difference in mobility of various grain boundaries.

In situ synchrotron investigation of grain growth behavior of nano-grained UO 2

DOE PAGES

Miao, Yinbin; Yao, Tiankai; Lian, Jie; ...

2017-01-09

Here, we report on the study of grain growth kinetics in nano-grained UO 2 samples. Dense nano-grained UO 2 samples with well-controlled stoichiometry and grain size were fabricated using the spark plasma sintering technique. To determine the grain growth kinetics at elevated temperatures, a synchrotron wide-angle X-ray scattering (WAXS) study was performed in situ to measure the real-time grain size evolution based on the modified Williamson-Hall analysis. The unique grain growth kinetics of nanocrystalline UO 2 at 730 °C and 820 °C were observed and explained by the difference in mobility of various grain boundaries.

Speckle imaging through turbulent atmosphere based on adaptable pupil segmentation

NASA Astrophysics Data System (ADS)

Loktev, Mikhail; Soloviev, Oleg; Savenko, Svyatoslav; Vdovin, Gleb

2011-07-01

We report on the first results to our knowledge obtained with adaptable multiaperture imaging through turbulence on a horizontal atmospheric path. We show that the resolution can be improved by adaptively matching the size of the subaperture to the characteristic size of the turbulence. Further improvement is achieved by the deconvolution of a number of subimages registered simultaneously through multiple subapertures. Different implementations of multiaperture geometry, including pupil multiplication, pupil image sampling, and a plenoptic telescope, are considered. Resolution improvement has been demonstrated on a ˜550m horizontal turbulent path, using a combination of aperture sampling, speckle image processing, and, optionally, frame selection.

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

Efficient design and inference for multistage randomized trials of individualized treatment policies.

PubMed

Dawson, Ree; Lavori, Philip W

2012-01-01

Clinical demand for individualized "adaptive" treatment policies in diverse fields has spawned development of clinical trial methodology for their experimental evaluation via multistage designs, building upon methods intended for the analysis of naturalistically observed strategies. Because often there is no need to parametrically smooth multistage trial data (in contrast to observational data for adaptive strategies), it is possible to establish direct connections among different methodological approaches. We show by algebraic proof that the maximum likelihood (ML) and optimal semiparametric (SP) estimators of the population mean of the outcome of a treatment policy and its standard error are equal under certain experimental conditions. This result is used to develop a unified and efficient approach to design and inference for multistage trials of policies that adapt treatment according to discrete responses. We derive a sample size formula expressed in terms of a parametric version of the optimal SP population variance. Nonparametric (sample-based) ML estimation performed well in simulation studies, in terms of achieved power, for scenarios most likely to occur in real studies, even though sample sizes were based on the parametric formula. ML outperformed the SP estimator; differences in achieved power predominately reflected differences in their estimates of the population mean (rather than estimated standard errors). Neither methodology could mitigate the potential for overestimated sample sizes when strong nonlinearity was purposely simulated for certain discrete outcomes; however, such departures from linearity may not be an issue for many clinical contexts that make evaluation of competitive treatment policies meaningful.

Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining

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

Hero, Alfred O.; Rajaratnam, Bala

When can reliable inference be drawn in the ‘‘Big Data’’ context? This article presents a framework for answering this fundamental question in the context of correlation mining, with implications for general large-scale inference. In large-scale data applications like genomics, connectomics, and eco-informatics, the data set is often variable rich but sample starved: a regime where the number n of acquired samples (statistical replicates) is far fewer than the number p of observed variables (genes, neurons, voxels, or chemical constituents). Much of recent work has focused on understanding the computational complexity of proposed methods for ‘‘Big Data.’’ Sample complexity, however, hasmore » received relatively less attention, especially in the setting when the sample size n is fixed, and the dimension p grows without bound. To address this gap, we develop a unified statistical framework that explicitly quantifies the sample complexity of various inferential tasks. Sampling regimes can be divided into several categories: 1) the classical asymptotic regime where the variable dimension is fixed and the sample size goes to infinity; 2) the mixed asymptotic regime where both variable dimension and sample size go to infinity at comparable rates; and 3) the purely high-dimensional asymptotic regime where the variable dimension goes to infinity and the sample size is fixed. Each regime has its niche but only the latter regime applies to exa-scale data dimension. We illustrate this high-dimensional framework for the problem of correlation mining, where it is the matrix of pairwise and partial correlations among the variables that are of interest. Correlation mining arises in numerous applications and subsumes the regression context as a special case. We demonstrate various regimes of correlation mining based on the unifying perspective of high-dimensional learning rates and sample complexity for different structured covariance models and different inference tasks.« less

Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining

PubMed Central

Hero, Alfred O.; Rajaratnam, Bala

2015-01-01

When can reliable inference be drawn in fue “Big Data” context? This paper presents a framework for answering this fundamental question in the context of correlation mining, wifu implications for general large scale inference. In large scale data applications like genomics, connectomics, and eco-informatics fue dataset is often variable-rich but sample-starved: a regime where the number n of acquired samples (statistical replicates) is far fewer than fue number p of observed variables (genes, neurons, voxels, or chemical constituents). Much of recent work has focused on understanding the computational complexity of proposed methods for “Big Data”. Sample complexity however has received relatively less attention, especially in the setting when the sample size n is fixed, and the dimension p grows without bound. To address fuis gap, we develop a unified statistical framework that explicitly quantifies the sample complexity of various inferential tasks. Sampling regimes can be divided into several categories: 1) the classical asymptotic regime where fue variable dimension is fixed and fue sample size goes to infinity; 2) the mixed asymptotic regime where both variable dimension and sample size go to infinity at comparable rates; 3) the purely high dimensional asymptotic regime where the variable dimension goes to infinity and the sample size is fixed. Each regime has its niche but only the latter regime applies to exa cale data dimension. We illustrate this high dimensional framework for the problem of correlation mining, where it is the matrix of pairwise and partial correlations among the variables fua t are of interest. Correlation mining arises in numerous applications and subsumes the regression context as a special case. we demonstrate various regimes of correlation mining based on the unifying perspective of high dimensional learning rates and sample complexity for different structured covariance models and different inference tasks. PMID:27087700

Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining

DOE PAGES

Hero, Alfred O.; Rajaratnam, Bala

2015-12-09

When can reliable inference be drawn in the ‘‘Big Data’’ context? This article presents a framework for answering this fundamental question in the context of correlation mining, with implications for general large-scale inference. In large-scale data applications like genomics, connectomics, and eco-informatics, the data set is often variable rich but sample starved: a regime where the number n of acquired samples (statistical replicates) is far fewer than the number p of observed variables (genes, neurons, voxels, or chemical constituents). Much of recent work has focused on understanding the computational complexity of proposed methods for ‘‘Big Data.’’ Sample complexity, however, hasmore » received relatively less attention, especially in the setting when the sample size n is fixed, and the dimension p grows without bound. To address this gap, we develop a unified statistical framework that explicitly quantifies the sample complexity of various inferential tasks. Sampling regimes can be divided into several categories: 1) the classical asymptotic regime where the variable dimension is fixed and the sample size goes to infinity; 2) the mixed asymptotic regime where both variable dimension and sample size go to infinity at comparable rates; and 3) the purely high-dimensional asymptotic regime where the variable dimension goes to infinity and the sample size is fixed. Each regime has its niche but only the latter regime applies to exa-scale data dimension. We illustrate this high-dimensional framework for the problem of correlation mining, where it is the matrix of pairwise and partial correlations among the variables that are of interest. Correlation mining arises in numerous applications and subsumes the regression context as a special case. We demonstrate various regimes of correlation mining based on the unifying perspective of high-dimensional learning rates and sample complexity for different structured covariance models and different inference tasks.« less

Sample Size Calculations for Population Size Estimation Studies Using Multiplier Methods With Respondent-Driven Sampling Surveys.

PubMed

Fearon, Elizabeth; Chabata, Sungai T; Thompson, Jennifer A; Cowan, Frances M; Hargreaves, James R

2017-09-14

While guidance exists for obtaining population size estimates using multiplier methods with respondent-driven sampling surveys, we lack specific guidance for making sample size decisions. To guide the design of multiplier method population size estimation studies using respondent-driven sampling surveys to reduce the random error around the estimate obtained. The population size estimate is obtained by dividing the number of individuals receiving a service or the number of unique objects distributed (M) by the proportion of individuals in a representative survey who report receipt of the service or object (P). We have developed an approach to sample size calculation, interpreting methods to estimate the variance around estimates obtained using multiplier methods in conjunction with research into design effects and respondent-driven sampling. We describe an application to estimate the number of female sex workers in Harare, Zimbabwe. There is high variance in estimates. Random error around the size estimate reflects uncertainty from M and P, particularly when the estimate of P in the respondent-driven sampling survey is low. As expected, sample size requirements are higher when the design effect of the survey is assumed to be greater. We suggest a method for investigating the effects of sample size on the precision of a population size estimate obtained using multipler methods and respondent-driven sampling. Uncertainty in the size estimate is high, particularly when P is small, so balancing against other potential sources of bias, we advise researchers to consider longer service attendance reference periods and to distribute more unique objects, which is likely to result in a higher estimate of P in the respondent-driven sampling survey. ©Elizabeth Fearon, Sungai T Chabata, Jennifer A Thompson, Frances M Cowan, James R Hargreaves. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 14.09.2017.

Interventions targeting substance abuse among women survivors of intimate partner abuse: a meta-analysis.

PubMed

Fowler, Dawnovise N; Faulkner, Monica

2011-12-01

In this article, meta-analytic techniques are used to examine existing intervention studies (n = 11) to determine their effects on substance abuse among female samples of intimate partner abuse (IPA) survivors. This research serves as a starting point for greater attention in research and practice to the implementation of evidence-based, integrated services to address co-occurring substance abuse and IPA victimization among women as major intersecting public health problems. The results show greater effects in three main areas. First, greater effect sizes exist in studies where larger numbers of women experienced current IPA. Second, studies with a lower mean age also showed greater effect sizes than studies with a higher mean age. Lastly, studies with smaller sample sizes have greater effects. This research helps to facilitate cohesion in the knowledge base on this topic, and the findings of this meta-analysis, in particular, contribute needed information to gaps in the literature on the level of promise of existing interventions to impact substance abuse in this underserved population. Published by Elsevier Inc.

Effect of Study Design on Sample Size in Studies Intended to Evaluate Bioequivalence of Inhaled Short‐Acting β‐Agonist Formulations

PubMed Central

Zeng, Yaohui; Singh, Sachinkumar; Wang, Kai

2017-01-01

Abstract Pharmacodynamic studies that use methacholine challenge to assess bioequivalence of generic and innovator albuterol formulations are generally designed per published Food and Drug Administration guidance, with 3 reference doses and 1 test dose (3‐by‐1 design). These studies are challenging and expensive to conduct, typically requiring large sample sizes. We proposed 14 modified study designs as alternatives to the Food and Drug Administration–recommended 3‐by‐1 design, hypothesizing that adding reference and/or test doses would reduce sample size and cost. We used Monte Carlo simulation to estimate sample size. Simulation inputs were selected based on published studies and our own experience with this type of trial. We also estimated effects of these modified study designs on study cost. Most of these altered designs reduced sample size and cost relative to the 3‐by‐1 design, some decreasing cost by more than 40%. The most effective single study dose to add was 180 μg of test formulation, which resulted in an estimated 30% relative cost reduction. Adding a single test dose of 90 μg was less effective, producing only a 13% cost reduction. Adding a lone reference dose of either 180, 270, or 360 μg yielded little benefit (less than 10% cost reduction), whereas adding 720 μg resulted in a 19% cost reduction. Of the 14 study design modifications we evaluated, the most effective was addition of both a 90‐μg test dose and a 720‐μg reference dose (42% cost reduction). Combining a 180‐μg test dose and a 720‐μg reference dose produced an estimated 36% cost reduction. PMID:29281130

A Monte-Carlo simulation analysis for evaluating the severity distribution functions (SDFs) calibration methodology and determining the minimum sample-size requirements.

PubMed

Shirazi, Mohammadali; Reddy Geedipally, Srinivas; Lord, Dominique

2017-01-01

Severity distribution functions (SDFs) are used in highway safety to estimate the severity of crashes and conduct different types of safety evaluations and analyses. Developing a new SDF is a difficult task and demands significant time and resources. To simplify the process, the Highway Safety Manual (HSM) has started to document SDF models for different types of facilities. As such, SDF models have recently been introduced for freeway and ramps in HSM addendum. However, since these functions or models are fitted and validated using data from a few selected number of states, they are required to be calibrated to the local conditions when applied to a new jurisdiction. The HSM provides a methodology to calibrate the models through a scalar calibration factor. However, the proposed methodology to calibrate SDFs was never validated through research. Furthermore, there are no concrete guidelines to select a reliable sample size. Using extensive simulation, this paper documents an analysis that examined the bias between the 'true' and 'estimated' calibration factors. It was indicated that as the value of the true calibration factor deviates further away from '1', more bias is observed between the 'true' and 'estimated' calibration factors. In addition, simulation studies were performed to determine the calibration sample size for various conditions. It was found that, as the average of the coefficient of variation (CV) of the 'KAB' and 'C' crashes increases, the analyst needs to collect a larger sample size to calibrate SDF models. Taking this observation into account, sample-size guidelines are proposed based on the average CV of crash severities that are used for the calibration process. Copyright © 2016 Elsevier Ltd. All rights reserved.

Random-effects linear modeling and sample size tables for two special crossover designs of average bioequivalence studies: the four-period, two-sequence, two-formulation and six-period, three-sequence, three-formulation designs.

PubMed

Diaz, Francisco J; Berg, Michel J; Krebill, Ron; Welty, Timothy; Gidal, Barry E; Alloway, Rita; Privitera, Michael

2013-12-01

Due to concern and debate in the epilepsy medical community and to the current interest of the US Food and Drug Administration (FDA) in revising approaches to the approval of generic drugs, the FDA is currently supporting ongoing bioequivalence studies of antiepileptic drugs, the EQUIGEN studies. During the design of these crossover studies, the researchers could not find commercial or non-commercial statistical software that quickly allowed computation of sample sizes for their designs, particularly software implementing the FDA requirement of using random-effects linear models for the analyses of bioequivalence studies. This article presents tables for sample-size evaluations of average bioequivalence studies based on the two crossover designs used in the EQUIGEN studies: the four-period, two-sequence, two-formulation design, and the six-period, three-sequence, three-formulation design. Sample-size computations assume that random-effects linear models are used in bioequivalence analyses with crossover designs. Random-effects linear models have been traditionally viewed by many pharmacologists and clinical researchers as just mathematical devices to analyze repeated-measures data. In contrast, a modern view of these models attributes an important mathematical role in theoretical formulations in personalized medicine to them, because these models not only have parameters that represent average patients, but also have parameters that represent individual patients. Moreover, the notation and language of random-effects linear models have evolved over the years. Thus, another goal of this article is to provide a presentation of the statistical modeling of data from bioequivalence studies that highlights the modern view of these models, with special emphasis on power analyses and sample-size computations.

Can cloud point-based enrichment, preservation, and detection methods help to bridge gaps in aquatic nanometrology?

PubMed

Duester, Lars; Fabricius, Anne-Lena; Jakobtorweihen, Sven; Philippe, Allan; Weigl, Florian; Wimmer, Andreas; Schuster, Michael; Nazar, Muhammad Faizan

2016-11-01

Coacervate-based techniques are intensively used in environmental analytical chemistry to enrich and extract different kinds of analytes. Most methods focus on the total content or the speciation of inorganic and organic substances. Size fractionation is less commonly addressed. Within coacervate-based techniques, cloud point extraction (CPE) is characterized by a phase separation of non-ionic surfactants dispersed in an aqueous solution when the respective cloud point temperature is exceeded. In this context, the feature article raises the following question: May CPE in future studies serve as a key tool (i) to enrich and extract nanoparticles (NPs) from complex environmental matrices prior to analyses and (ii) to preserve the colloidal status of unstable environmental samples? With respect to engineered NPs, a significant gap between environmental concentrations and size- and element-specific analytical capabilities is still visible. CPE may support efforts to overcome this "concentration gap" via the analyte enrichment. In addition, most environmental colloidal systems are known to be unstable, dynamic, and sensitive to changes of the environmental conditions during sampling and sample preparation. This delivers a so far unsolved "sample preparation dilemma" in the analytical process. The authors are of the opinion that CPE-based methods have the potential to preserve the colloidal status of these instable samples. Focusing on NPs, this feature article aims to support the discussion on the creation of a convention called the "CPE extractable fraction" by connecting current knowledge on CPE mechanisms and on available applications, via the uncertainties visible and modeling approaches available, with potential future benefits from CPE protocols.

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.

Modeling grain size variations of aeolian gypsum deposits at White Sands, New Mexico, using AVIRIS imagery

USGS Publications Warehouse

Ghrefat, H.A.; Goodell, P.C.; Hubbard, B.E.; Langford, R.P.; Aldouri, R.E.

2007-01-01

Visible and Near-Infrared (VNIR) through Short Wavelength Infrared (SWIR) (0.4-2.5????m) AVIRIS data, along with laboratory spectral measurements and analyses of field samples, were used to characterize grain size variations in aeolian gypsum deposits across barchan-transverse, parabolic, and barchan dunes at White Sands, New Mexico, USA. All field samples contained a mineralogy of ?????100% gypsum. In order to document grain size variations at White Sands, surficial gypsum samples were collected along three Transects parallel to the prevailing downwind direction. Grain size analyses were carried out on the samples by sieving them into seven size fractions ranging from 45 to 621????m, which were subjected to spectral measurements. Absorption band depths of the size fractions were determined after applying an automated continuum-removal procedure to each spectrum. Then, the relationship between absorption band depth and gypsum size fraction was established using a linear regression. Three software processing steps were carried out to measure the grain size variations of gypsum in the Dune Area using AVIRIS data. AVIRIS mapping results, field work and laboratory analysis all show that the interdune areas have lower absorption band depth values and consist of finer grained gypsum deposits. In contrast, the dune crest areas have higher absorption band depth values and consist of coarser grained gypsum deposits. Based on laboratory estimates, a representative barchan-transverse dune (Transect 1) has a mean grain size of 1.16 ??{symbol} (449????m). The error bar results show that the error ranges from - 50 to + 50????m. Mean grain size for a representative parabolic dune (Transect 2) is 1.51 ??{symbol} (352????m), and 1.52 ??{symbol} (347????m) for a representative barchan dune (Transect 3). T-test results confirm that there are differences in the grain size distributions between barchan and parabolic dunes and between interdune and dune crest areas. The t-test results also show that there are no significant differences between modeled and laboratory-measured grain size values. Hyperspectral grain size modeling can help to determine dynamic processes shaping the formation of the dunes such as wind directions, and the relative strengths of winds through time. This has implications for studying such processes on other planetary landforms that have mineralogy with unique absorption bands in VNIR-SWIR hyperspectral data. ?? 2006 Elsevier B.V. All rights reserved.

Neurocognitive performance in family-based and case-control studies of schizophrenia

PubMed Central

Gur, Ruben C.; Braff, David L.; Calkins, Monica E.; Dobie, Dorcas J.; Freedman, Robert; Green, Michael F.; Greenwood, Tiffany A.; Lazzeroni, Laura C.; Light, Gregory A.; Nuechterlein, Keith H.; Olincy, Ann; Radant, Allen D.; Seidman, Larry J.; Siever, Larry J.; Silverman, Jeremy M.; Sprock, Joyce; Stone, William S.; Sugar, Catherine A.; Swerdlow, Neal R.; Tsuang, Debby W.; Tsuang, Ming T.; Turetsky, Bruce I.; Gur, Raquel E.

2014-01-01

Background Neurocognitive deficits in schizophrenia (SZ) are established and the Consortium on the Genetics of Schizophrenia (COGS) investigated such measures as endophenotypes in family-based (COGS-1) and case-control (COGS-2) studies. By requiring family participation, family-based sampling may result in samples that vary demographically and perform better on neurocognitive measures. Methods The Penn computerized neurocognitive battery (CNB) evaluates accuracy and speed of performance for several domains and was administered across sites in COGS-1 and COGS-2. Most tests were included in both studies. COGS-1 included 328 patients with SZ and 497 healthy comparison subjects (HCS) and COGS-2 included 1195 patients and 1009 HCS. Results Demographically, COGS-1 participants were younger, more educated, with more educated parents and higher estimated IQ compared to COGS-2 participants. After controlling for demographics, the two samples produced very similar performance profiles compared to their respective controls. As expected, performance was better and with smaller effect sizes compared to controls in COGS-1 relative to COGS-2. Better performance was most pronounced for spatial processing while emotion identification had large effect sizes for both accuracy and speed in both samples. Performance was positively correlated with functioning and negatively with negative and positive symptoms in both samples, but correlations were attenuated in COGS-2, especially with positive symptoms. Conclusions Patients ascertained through family-based design have more favorable demographics and better performance on some neurocognitive domains. Thus, studies that use case-control ascertainment may tap into populations with more severe forms of illness that are exposed to less favorable factors compared to those ascertained with family-based designs. PMID:25432636

Elasto-inertial microfluidics for bacteria separation from whole blood for sepsis diagnostics.

PubMed

Faridi, Muhammad Asim; Ramachandraiah, Harisha; Banerjee, Indradumna; Ardabili, Sahar; Zelenin, Sergey; Russom, Aman

2017-01-04

Bloodstream infections (BSI) remain a major challenge with high mortality rate, with an incidence that is increasing worldwide. Early treatment with appropriate therapy can reduce BSI-related morbidity and mortality. However, despite recent progress in molecular based assays, complex sample preparation steps have become critical roadblock for a greater expansion of molecular assays. Here, we report a size based, label-free, bacteria separation from whole blood using elasto-inertial microfluidics. In elasto-inertial microfluidics, the viscoelastic flow enables size based migration of blood cells into a non-Newtonian solution, while smaller bacteria remain in the streamline of the blood sample entrance and can be separated. We first optimized the flow conditions using particles, and show continuous separation of 5 μm particles from 2 μm at a yield of 95% for 5 µm particle and 93% for 2 µm particles at respective outlets. Next, bacteria were continuously separated at an efficiency of 76% from undiluted whole blood sample. We demonstrate separation of bacteria from undiluted while blood using elasto-inertial microfluidics. The label-free, passive bacteria preparation method has a great potential for downstream phenotypic and molecular analysis of bacteria.

Effect of Layer Thickness and Printing Orientation on Mechanical Properties and Dimensional Accuracy of 3D Printed Porous Samples for Bone Tissue Engineering

PubMed Central

Farzadi, Arghavan; Solati-Hashjin, Mehran; Asadi-Eydivand, Mitra; Abu Osman, Noor Azuan

2014-01-01

Powder-based inkjet 3D printing method is one of the most attractive solid free form techniques. It involves a sequential layering process through which 3D porous scaffolds can be directly produced from computer-generated models. 3D printed products' quality are controlled by the optimal build parameters. In this study, Calcium Sulfate based powders were used for porous scaffolds fabrication. The printed scaffolds of 0.8 mm pore size, with different layer thickness and printing orientation, were subjected to the depowdering step. The effects of four layer thicknesses and printing orientations, (parallel to X, Y and Z), on the physical and mechanical properties of printed scaffolds were investigated. It was observed that the compressive strength, toughness and Young's modulus of samples with 0.1125 and 0.125 mm layer thickness were more than others. Furthermore, the results of SEM and μCT analyses showed that samples with 0.1125 mm layer thickness printed in X direction have more dimensional accuracy and significantly close to CAD software based designs with predefined pore size, porosity and pore interconnectivity. PMID:25233468

Cation solvation with quantum chemical effects modeled by a size-consistent multi-partitioning quantum mechanics/molecular mechanics method.

PubMed

Watanabe, Hiroshi C; Kubillus, Maximilian; Kubař, Tomáš; Stach, Robert; Mizaikoff, Boris; Ishikita, Hiroshi

2017-07-21

In the condensed phase, quantum chemical properties such as many-body effects and intermolecular charge fluctuations are critical determinants of the solvation structure and dynamics. Thus, a quantum mechanical (QM) molecular description is required for both solute and solvent to incorporate these properties. However, it is challenging to conduct molecular dynamics (MD) simulations for condensed systems of sufficient scale when adapting QM potentials. To overcome this problem, we recently developed the size-consistent multi-partitioning (SCMP) quantum mechanics/molecular mechanics (QM/MM) method and realized stable and accurate MD simulations, using the QM potential to a benchmark system. In the present study, as the first application of the SCMP method, we have investigated the structures and dynamics of Na + , K + , and Ca 2+ solutions based on nanosecond-scale sampling, a sampling 100-times longer than that of conventional QM-based samplings. Furthermore, we have evaluated two dynamic properties, the diffusion coefficient and difference spectra, with high statistical certainty. Furthermore the calculation of these properties has not previously been possible within the conventional QM/MM framework. Based on our analysis, we have quantitatively evaluated the quantum chemical solvation effects, which show distinct differences between the cations.

MD-based computational design of new engineered Ni-based nanocatalysts: An in-depth study of the underlying mechanism

NASA Astrophysics Data System (ADS)

Kardani, Arash; Mehrafrooz, Behzad; Montazeri, Abbas

2018-03-01

Porous nickel-based nanocatalysts have attracted great attention thanks to their high surface-to-volume ratio and desired mechanical properties. One of the major challenges associated with their applications is weakening their shear properties due to their contact with the high fluid flow values at elevated service temperatures. On the other hand, their shear behavior is dominantly influenced by the size and distribution of pores available in their structure. In this study, different nickel samples containing periodic distribution surface porosities with 2 nm diameter are examined via molecular dynamics simulation. Moreover, to explore the effects of porosities distribution, the obtained results are compared with those of the samples having concentrated pores at the bigger size of 10nm. Accordingly, shear loading conditions are imposed to capture the dependency of the shear characteristics of the samples on the location and on the geometrical factors of the aforementioned porosities. Surprisingly, it is revealed that the existence of randomly distributed pores can lead to an enhancement of their yield strain compared to that of non-porous counterparts. The underlying mechanism governing this special behavior is thoroughly studied employing several case studies.

Improving the accuracy of hyaluronic acid molecular weight estimation by conventional size exclusion chromatography.

PubMed

Shanmuga Doss, Sreeja; Bhatt, Nirav Pravinbhai; Jayaraman, Guhan

2017-08-15

There is an unreasonably high variation in the literature reports on molecular weight of hyaluronic acid (HA) estimated using conventional size exclusion chromatography (SEC). This variation is most likely due to errors in estimation. Working with commercially available HA molecular weight standards, this work examines the extent of error in molecular weight estimation due to two factors: use of non-HA based calibration and concentration of sample injected into the SEC column. We develop a multivariate regression correlation to correct for concentration effect. Our analysis showed that, SEC calibration based on non-HA standards like polyethylene oxide and pullulan led to approximately 2 and 10 times overestimation, respectively, when compared to HA-based calibration. Further, we found that injected sample concentration has an effect on molecular weight estimation. Even at 1g/l injected sample concentration, HA molecular weight standards of 0.7 and 1.64MDa showed appreciable underestimation of 11-24%. The multivariate correlation developed was found to reduce error in estimations at 1g/l to <4%. The correlation was also successfully applied to accurately estimate the molecular weight of HA produced by a recombinant Lactococcus lactis fermentation. Copyright © 2017 Elsevier B.V. All rights reserved.

R2 effect-size measures for mediation analysis

PubMed Central

Fairchild, Amanda J.; MacKinnon, David P.; Taborga, Marcia P.; Taylor, Aaron B.

2010-01-01

R2 effect-size measures are presented to assess variance accounted for in mediation models. The measures offer a means to evaluate both component paths and the overall mediated effect in mediation models. Statistical simulation results indicate acceptable bias across varying parameter and sample-size combinations. The measures are applied to a real-world example using data from a team-based health promotion program to improve the nutrition and exercise habits of firefighters. SAS and SPSS computer code are also provided for researchers to compute the measures in their own data. PMID:19363189

Influence of specimen dimensions on ductile-to-brittle transition temperature in Charpy impact test

NASA Astrophysics Data System (ADS)

Rzepa, S.; Bucki, T.; Konopík, P.; Džugan, J.; Rund, M.; Procházka, R.

2017-02-01

This paper discusses the correlation between specimen dimensions and transition temperature. Notch toughness properties of Standard Charpy-V specimens are compared to samples with lower width (7.5 mm, 5 mm, 2.5 mm) and sub-size Charpy specimens with cross section 3×4. In this study transition curves are correlated with lateral ductile part of fracture related ones for 5 considered geometries. Based on the results obtained, correlation procedure for transition temperature determination of full size specimens defined by fracture appearance of sub-sized specimens is proposed.

Differential Risk of Injury to Child Occupants by SUV Size

PubMed Central

Kallan, Michael J.; Durbin, Dennis R.; Elliott, Michael R.; Arbogast, Kristy B.; Winston, Flaura K.

2004-01-01

In the United States, the sport utility vehicle (SUV) is the fastest growing segment of the passenger vehicle fleet, yet SUVs vary widely in size and crashworthiness. Using data collected from a population-based sample of crashes in insured vehicles, we quantified the risk of injury to child occupants in SUVs by vehicle weight. There is an increased risk in both Small and Midsize SUVs when compared to Large SUVs. Parents who are purchasing a SUV should strongly consider the size of the vehicle and its crashworthiness. PMID:15319119

R2 effect-size measures for mediation analysis.

PubMed

Fairchild, Amanda J; Mackinnon, David P; Taborga, Marcia P; Taylor, Aaron B

2009-05-01

R(2) effect-size measures are presented to assess variance accounted for in mediation models. The measures offer a means to evaluate both component paths and the overall mediated effect in mediation models. Statistical simulation results indicate acceptable bias across varying parameter and sample-size combinations. The measures are applied to a real-world example using data from a team-based health promotion program to improve the nutrition and exercise habits of firefighters. SAS and SPSS computer code are also provided for researchers to compute the measures in their own data.

Dust generation in powders: Effect of particle size distribution

NASA Astrophysics Data System (ADS)

Chakravarty, Somik; Le Bihan, Olivier; Fischer, Marc; Morgeneyer, Martin

2017-06-01

This study explores the relationship between the bulk and grain-scale properties of powders and dust generation. A vortex shaker dustiness tester was used to evaluate 8 calcium carbonate test powders with median particle sizes ranging from 2μm to 136μm. Respirable aerosols released from the powder samples were characterised by their particle number and mass concentrations. All the powder samples were found to release respirable fractions of dust particles which end up decreasing with time. The variation of powder dustiness as a function of the particle size distribution was analysed for the powders, which were classified into three groups based on the fraction of particles within the respirable range. The trends we observe might be due to the interplay of several mechanisms like de-agglomeration and attrition and their relative importance.

ALCHEMY: a reliable method for automated SNP genotype calling for small batch sizes and highly homozygous populations

PubMed Central

Wright, Mark H.; Tung, Chih-Wei; Zhao, Keyan; Reynolds, Andy; McCouch, Susan R.; Bustamante, Carlos D.

2010-01-01

Motivation: The development of new high-throughput genotyping products requires a significant investment in testing and training samples to evaluate and optimize the product before it can be used reliably on new samples. One reason for this is current methods for automated calling of genotypes are based on clustering approaches which require a large number of samples to be analyzed simultaneously, or an extensive training dataset to seed clusters. In systems where inbred samples are of primary interest, current clustering approaches perform poorly due to the inability to clearly identify a heterozygote cluster. Results: As part of the development of two custom single nucleotide polymorphism genotyping products for Oryza sativa (domestic rice), we have developed a new genotype calling algorithm called ‘ALCHEMY’ based on statistical modeling of the raw intensity data rather than modelless clustering. A novel feature of the model is the ability to estimate and incorporate inbreeding information on a per sample basis allowing accurate genotyping of both inbred and heterozygous samples even when analyzed simultaneously. Since clustering is not used explicitly, ALCHEMY performs well on small sample sizes with accuracy exceeding 99% with as few as 18 samples. Availability: ALCHEMY is available for both commercial and academic use free of charge and distributed under the GNU General Public License at http://alchemy.sourceforge.net/ Contact: mhw6@cornell.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20926420

Concentrations of selected constituents in surface-water and streambed-sediment samples collected from streams in and near an area of oil and natural-gas development, south-central Texas, 2011-13

USGS Publications Warehouse

Opsahl, Stephen P.; Crow, Cassi L.

2014-01-01

During collection of streambed-sediment samples, additional samples from a subset of three sites (the SAR Elmendorf, SAR 72, and SAR McFaddin sites) were processed by using a 63-µm sieve on one aliquot and a 2-mm sieve on a second aliquot for PAH and n-alkane analyses. The purpose of analyzing PAHs and n-alkanes on a sample containing sand, silt, and clay versus a sample containing only silt and clay was to provide data that could be used to determine if these organic constituents had a greater affinity for silt- and clay-sized particles relative to sand-sized particles. The greater concentrations of PAHs in the <63-μm size-fraction samples at all three of these sites are consistent with a greater percentage of binding sites associated with fine-grained (<63 μm) sediment versus coarse-grained (<2 mm) sediment. The larger difference in total PAHs between the <2-mm and <63-μm size-fraction samples at the SAR Elmendorf site might be related to the large percentage of sand in the <2-mm size-fraction sample which was absent in the <63-μm size-fraction sample. In contrast, the <2-mm size-fraction sample collected from the SAR McFaddin site contained very little sand and was similar in particle-size composition to the <63-μm size-fraction sample.

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.